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Sample records for optimizing deposition parameters

  1. Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    Norlina Mohd Sabri

    2016-06-01

    Full Text Available This research is focusing on the radio frequency (RF magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of Particle Swarm Optimization (PSO, Genetic Algorithm (GA, Artificial Immune System (AIS and Ant Colony Optimization (ACO. Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process.

  2. Optimization of operating parameters in polysilicon chemical vapor deposition reactor with response surface methodology

    Science.gov (United States)

    An, Li-sha; Liu, Chun-jiao; Liu, Ying-wen

    2018-05-01

    In the polysilicon chemical vapor deposition reactor, the operating parameters are complex to affect the polysilicon's output. Therefore, it is very important to address the coupling problem of multiple parameters and solve the optimization in a computationally efficient manner. Here, we adopted Response Surface Methodology (RSM) to analyze the complex coupling effects of different operating parameters on silicon deposition rate (R) and further achieve effective optimization of the silicon CVD system. Based on finite numerical experiments, an accurate RSM regression model is obtained and applied to predict the R with different operating parameters, including temperature (T), pressure (P), inlet velocity (V), and inlet mole fraction of H2 (M). The analysis of variance is conducted to describe the rationality of regression model and examine the statistical significance of each factor. Consequently, the optimum combination of operating parameters for the silicon CVD reactor is: T = 1400 K, P = 3.82 atm, V = 3.41 m/s, M = 0.91. The validation tests and optimum solution show that the results are in good agreement with those from CFD model and the deviations of the predicted values are less than 4.19%. This work provides a theoretical guidance to operate the polysilicon CVD process.

  3. System principles and evaluation criteria of reliability for optimization of technological parameters of coal deposits

    Directory of Open Access Journals (Sweden)

    A.О. Khorolskiy

    2017-12-01

    Full Text Available The article deals with solving the scientific problem of select mining equipment for selection longwall faces of mining venture. The main goal of the paper is to study technology of coal extraction of mining venture. The paper proposes a new approach to solve a problem of mining equipment selection for longwall faces of mining venture. The article describes new method for selection of mining equipment based on theory graph. Special attention is given to technological aspects; they are lenght of longwall faces, depth of coal stratum. Predictions obtained for daily production of mining equipment are compared with design outputs. Conclusions regarding the main reason of instability of longwall faces workings are made. It is found that to be able to use standard algorithms find the shortest path between vertices, you must perform matrix description of the constructed graphs that illustrate the structure of the interaction of different types of control equipment. Using classical optimization of method of discrete mathematics and algorithms for finding the shortest path between two vertices of network models obtained from the formalization of graphs with maximum results of specific types of equipment production chains, solved the problem of rational choice cleaning equipment for the new site with the cost parameters of the mining equipment and cost of mining coal. The authors developed effective and appropriate variants for the mine development for different coal deposits of mining venture.

  4. Simulation optimization of filament parameters for uniform depositions of diamond films on surfaces of ultra-large circular holes

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xinchang, E-mail: wangxinchangz@163.com; Shen, Xiaotian; Sun, Fanghong; Shen, Bin

    2016-12-01

    Highlights: • A verified simulation model using a novel filament arrangement is constructed. • Influences of filament parameters are clarified. • A coefficient between simulated and experimental results is proposed. • Orthogonal simulations are adopted to optimize filament parameters. • A general filament arrangement suitable for different conditions is determined. - Abstract: Chemical vapor deposition (CVD) diamond films have been widely applied as protective coatings on varieties of anti-frictional and wear-resistant components, owing to their excellent mechanical and tribological properties close to the natural diamond. In applications of some components, the inner hole surface will serve as the working surface that suffers severe frictional or erosive wear. It is difficult to realize uniform depositions of diamond films on surfaces of inner holes, especially ultra-large inner holes. Adopting a SiC compact die with an aperture of 80 mm as an example, a novel filament arrangement with a certain number of filaments evenly distributed on a circle is designed, and specific effects of filament parameters, including the filament number, arrangement direction, filament temperature, filament diameter, circumradius and the downward translation, on the substrate temperature distribution are studied by computational fluid dynamics (CFD) simulations based on the finite volume method (FVM), adopting a modified computational model well consistent with the actual deposition environment. Corresponding temperature measurement experiments are also conducted to verify the rationality of the computational model. From the aspect of depositing uniform boron-doped micro-crystalline, undoped micro-crystalline and undoped fine-grained composite diamond (BDM-UMC-UFGCD) film on such the inner hole surface, filament parameters as mentioned above are accurately optimized and compensated by orthogonal simulations. Moreover, deposition experiments adopting compensated optimized

  5. Optimization of Process Parameters of Pulsed Electro Deposition Technique for Nanocrystalline Nickel Coating Using Gray Relational Analysis (GRA)

    Science.gov (United States)

    Venkatesh, C.; Sundara Moorthy, N.; Venkatesan, R.; Aswinprasad, V.

    The moving parts of any mechanism and machine parts are always subjected to a significant wear due to the development of friction. It is an utmost important aspect to address the wear problems in present environment. But the complexity goes on increasing to replace the worn out parts if they are very precise. Technology advancement in surface engineering ensures the minimum surface wear with the introduction of polycrystalline nano nickel coating. The enhanced tribological property of the nano nickel coating was achieved by the development of grain size and hardness of the surface. In this study, it has been decided to focus on the optimized parameters of the pulsed electro deposition to develop such a coating. Taguchi’s method coupled gray relational analysis was employed by considering the pulse frequency, average current density and duty cycle as the chief process parameters. The grain size and hardness were considered as responses. Totally, nine experiments were conducted as per L9 design of experiment. Additionally, response graph method has been applied to determine the most significant parameter to influence both the responses. In order to improve the degree of validation, confirmation test and predicted gray grade were carried out with the optimized parameters. It has been observed that there was significant improvement in gray grade for the optimal parameters.

  6. Optimization of the Deposition Parameters of HVOF FeMnCrSi+Ni+B Thermally Sprayed Coatings

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    Gustavo Bavaresco Sucharski

    2015-06-01

    Full Text Available AbstractHVOF thermal spray process produces coatings with low porosity and low oxide content, as well as high substrate adhesion. Small variations on the parameters of the HVOF process can generate coatings with different characteristics and properties, which also is chemical composition depended of the alloy. FeMnCrSi alloy is a cavitation resistant class of material with a great potential for HVOF deposition use. The main goal of this article is to study the influence of some HVOF parameters deposition, as standoff distance, powder feed rate and carrier gas pressure on three different alloys. FeMnCrSi experimental alloys with some variations in nickel and boron content were studied. Taguchi experimental design with L9 orthogonal array was used in this work. Porosity, oxide content, tensile adhesion strength and microhardness of the coatings were evaluated. The results indicated that all factors have significant influence on these properties. Chemical composition of the alloys was the most important factor, followed by the carrier gas pressure, standoff distance and powder feed rate. The addition of Ni, produces coatings with lower levels of oxide content and porosity. An experiment with improved parameters was conducted, and a great improvement on the coating properties was observed.

  7. Application of the Taguchi analytical method for optimization of effective parameters of the chemical vapor deposition process controlling the production of nanotubes/nanobeads.

    Science.gov (United States)

    Sharon, Maheshwar; Apte, P R; Purandare, S C; Zacharia, Renju

    2005-02-01

    Seven variable parameters of the chemical vapor deposition system have been optimized with the help of the Taguchi analytical method for getting a desired product, e.g., carbon nanotubes or carbon nanobeads. It is observed that almost all selected parameters influence the growth of carbon nanotubes. However, among them, the nature of precursor (racemic, R or Technical grade camphor) and the carrier gas (hydrogen, argon and mixture of argon/hydrogen) seem to be more important parameters affecting the growth of carbon nanotubes. Whereas, for the growth of nanobeads, out of seven parameters, only two, i.e., catalyst (powder of iron, cobalt, and nickel) and temperature (1023 K, 1123 K, and 1273 K), are the most influential parameters. Systematic defects or islands on the substrate surface enhance nucleation of novel carbon materials. Quantitative contributions of process parameters as well as optimum factor levels are obtained by performing analysis of variance (ANOVA) and analysis of mean (ANOM), respectively.

  8. Optimization of Processing Parameters in 3D-Printing of Poly(lactic acid by Fused Deposition Modeling Method

    Directory of Open Access Journals (Sweden)

    Maryam Ezoji

    2017-05-01

    Full Text Available Nowadays, making use of additive manufacturing (AM processes such as fused deposition modeling (FDM, in different areas, such as car manufacturing, biomedical and aerospace industries is gaining popularity worldwide because of their capacities in producing functional parts with complex geometries. Therefore, it is very important to identify the significance of FDM processing parameters which would have an impact on the quality of articles produced by the processing system. In this work, poly(lactic acid was used to study the effects of processing parameters such as layer thickness, raster angle and printing plane on the tensile properties and surface roughness of the printed specimens. The results showed that the tensile strength of a specimen increased by reducing its layer thickness. However, the elastic modulus values increased with decreasing the layer thickness to some extent. Moreover, when the layer thickness was kept constant at 0.05 mm and 3D-printing was carried out in XYZ plane, the maximum modulus and tensile strength were obtained for the raster angle of 0˚. Microscopic studies showed that in low layer thickness, the polymeric layers diffused properly into each other and no voids were formed between the layers. However, with a thickness above its critical value, a few voids were formed between the layers which played as a stress concentrator and decreased the tensile strength of the specimens. The results also showed that the surface roughness increased with increasing the layer thickness.

  9. Infrared Drying Parameter Optimization

    Science.gov (United States)

    Jackson, Matthew R.

    In recent years, much research has been done to explore direct printing methods, such as screen and inkjet printing, as alternatives to the traditional lithographic process. The primary motivation is reduction of the material costs associated with producing common electronic devices. Much of this research has focused on developing inkjet or screen paste formulations that can be printed on a variety of substrates, and which have similar conductivity performance to the materials currently used in the manufacturing of circuit boards and other electronic devices. Very little research has been done to develop a process that would use direct printing methods to manufacture electronic devices in high volumes. This study focuses on developing and optimizing a drying process for conductive copper ink in a high volume manufacturing setting. Using an infrared (IR) dryer, it was determined that conductive copper prints could be dried in seconds or minutes as opposed to tens of minutes or hours that it would take with other drying devices, such as a vacuum oven. In addition, this study also identifies significant parameters that can affect the conductivity of IR dried prints. Using designed experiments and statistical analysis; the dryer parameters were optimized to produce the best conductivity performance for a specific ink formulation and substrate combination. It was determined that for an ethylene glycol, butanol, 1-methoxy 2- propanol ink formulation printed on Kapton, the optimal drying parameters consisted of a dryer height of 4 inches, a temperature setting between 190 - 200°C, and a dry time of 50-65 seconds depending on the printed film thickness as determined by the number of print passes. It is important to note that these parameters are optimized specifically for the ink formulation and substrate used in this study. There is still much research that needs to be done into optimizing the IR dryer for different ink substrate combinations, as well as developing a

  10. Buncher system parameter optimization

    International Nuclear Information System (INIS)

    Wadlinger, E.A.

    1981-01-01

    A least-squares algorithm is presented to calculate the RF amplitudes and cavity spacings for a series of buncher cavities each resonating at a frequency that is a multiple of a fundamental frequency of interest. The longitudinal phase-space distribution, obtained by particle tracing through the bunching system, is compared to a desired distribution function of energy and phase. The buncher cavity parameters are adjusted to minimize the difference between these two distributions. Examples are given for zero space charge. The manner in which the method can be extended to include space charge using the 3-D space-charge calculation procedure is indicated

  11. Multivariate optimization of ILC parameters

    International Nuclear Information System (INIS)

    Bazarov, I.V.; Padamsee, H.S.

    2005-01-01

    We present results of multiobjective optimization of the International Linear Collider (ILC) which seeks to maximize luminosity at each given total cost of the linac (capital and operating costs of cryomodules, refrigeration and RF). Evolutionary algorithms allow quick exploration of optimal sets of parameters in a complicated system such as ILC in the presence of realistic constraints as well as investigation of various what-if scenarios in potential performance. Among the parameters we varied there were accelerating gradient and Q of the cavities (in a coupled manner following a realistic Q vs. E curve), the number of particles per bunch, the bunch length, number of bunches in the train, etc. We find an optimum which decreases (relative to TESLA TDR baseline) the total linac cost by 22%, capital cost by 25% at the same luminosity of 3 x 10 38 m -2 s -1 . For this optimum the gradient is 35 MV/m, the final spot size is 3.6 nm, and the beam power is 15.9 MV/m. Changing the luminosity by 10 38 m -2 s -1 results in 10% change in the total linac cost and 4% in the capital cost. We have also explored the optimal fronts of luminosity vs. cost for several other scenarios using the same approach. (orig.)

  12. Optimization of Parameters of Asymptotically Stable Systems

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    Anna Guerman

    2011-01-01

    Full Text Available This work deals with numerical methods of parameter optimization for asymptotically stable systems. We formulate a special mathematical programming problem that allows us to determine optimal parameters of a stabilizer. This problem involves solutions to a differential equation. We show how to chose the mesh in order to obtain discrete problem guaranteeing the necessary accuracy. The developed methodology is illustrated by an example concerning optimization of parameters for a satellite stabilization system.

  13. Evaluation of GCC optimization parameters

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    Rodrigo D. Escobar

    2012-12-01

    Full Text Available Compile-time optimization of code can result in significant performance gains. The amount of these gains varies widely depending upon the code being optimized, the hardware being compiled for, the specific performance increase attempted (e.g. speed, throughput, memory utilization, etc. and the used compiler. We used the latest version of the SPEC CPU 2006 benchmark suite to help gain an understanding of possible performance improvements using GCC (GNU Compiler Collection options focusing mainly on speed gains made possible by tuning the compiler with the standard compiler optimization levels as well as a specific compiler option for the hardware processor. We compared the best standardized tuning options obtained for a core i7 processor, to the same relative options used on a Pentium4 to determine whether the GNU project has improved its performance tuning capabilities for specific hardware over time.

  14. Parameters control in GAs for dynamic optimization

    Directory of Open Access Journals (Sweden)

    Khalid Jebari

    2013-02-01

    Full Text Available The Control of Genetic Algorithms parameters allows to optimize the search process and improves the performance of the algorithm. Moreover it releases the user to dive into a game process of trial and failure to find the optimal parameters.

  15. Optimization of electrospinning parameters for chitosan nanofibres

    CSIR Research Space (South Africa)

    Jacobs, V

    2011-06-01

    Full Text Available Electrospinning of chitosan, a naturally occurring polysaccharide biopolymer, has been investigated. In this paper, the authors report the optimization of electrospinning process and solution parameters using factorial design approach to obtain...

  16. Optimization of Agrobacterium -mediated transformation parameters ...

    African Journals Online (AJOL)

    Agrobacterium-mediated transformation factors for sweet potato embryogenic calli were optimized using -glucuronidase (GUS) as a reporter. The binary vector pTCK303 harboring the modified GUS gene driven by the CaMV 35S promoter was used. Transformation parameters were optimized including bacterial ...

  17. Optimal Laser Phototherapy Parameters for Pain Relief.

    Science.gov (United States)

    Kate, Rohit J; Rubatt, Sarah; Enwemeka, Chukuka S; Huddleston, Wendy E

    2018-03-27

    Studies on laser phototherapy for pain relief have used parameters that vary widely and have reported varying outcomes. The purpose of this study was to determine the optimal parameter ranges of laser phototherapy for pain relief by analyzing data aggregated from existing primary literature. Original studies were gathered from available sources and were screened to meet the pre-established inclusion criteria. The included articles were then subjected to meta-analysis using Cohen's d statistic for determining treatment effect size. From these studies, ranges of the reported parameters that always resulted into large effect sizes were determined. These optimal ranges were evaluated for their accuracy using leave-one-article-out cross-validation procedure. A total of 96 articles met the inclusion criteria for meta-analysis and yielded 232 effect sizes. The average effect size was highly significant: d = +1.36 (confidence interval [95% CI] = 1.04-1.68). Among all the parameters, total energy was found to have the greatest effect on pain relief and had the most prominent optimal ranges of 120-162 and 15.36-20.16 J, which always resulted in large effect sizes. The cross-validation accuracy of the optimal ranges for total energy was 68.57% (95% CI = 53.19-83.97). Fewer and less-prominent optimal ranges were obtained for the energy density and duration parameters. None of the remaining parameters was found to be independently related to pain relief outcomes. The findings of meta-analysis indicate that laser phototherapy is highly effective for pain relief. Based on the analysis of parameters, total energy can be optimized to yield the largest effect on pain relief.

  18. Optimal design criteria - prediction vs. parameter estimation

    Science.gov (United States)

    Waldl, Helmut

    2014-05-01

    G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

  19. Cosmological parameter estimation using Particle Swarm Optimization

    Science.gov (United States)

    Prasad, J.; Souradeep, T.

    2014-03-01

    Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.

  20. Cosmological parameter estimation using Particle Swarm Optimization

    International Nuclear Information System (INIS)

    Prasad, J; Souradeep, T

    2014-01-01

    Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite

  1. Optimal parameters uncoupling vibration modes of oscillators

    Science.gov (United States)

    Le, K. C.; Pieper, A.

    2017-07-01

    This paper proposes a novel optimization concept for an oscillator with two degrees of freedom. By using specially defined motion ratios, we control the action of springs to each degree of freedom of the oscillator. We aim at showing that, if the potential action of the springs in one period of vibration, used as the payoff function for the conservative oscillator, is maximized among all admissible parameters and motions satisfying Lagrange's equations, then the optimal motion ratios uncouple vibration modes. A similar result holds true for the dissipative oscillator having dampers. The application to optimal design of vehicle suspension is discussed.

  2. Mixed integer evolution strategies for parameter optimization.

    Science.gov (United States)

    Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C

    2013-01-01

    Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.

  3. Chickpea seeds germination rational parameters optimization

    Science.gov (United States)

    Safonova, Yu A.; Ivliev, M. N.; Lemeshkin, A. V.

    2018-05-01

    The paper presents the influence of chickpea seeds bioactivation parameters on their enzymatic activity experimental results. Optimal bioactivation process modes were obtained by regression-factor analysis: process temperature - 13.6 °C, process duration - 71.5 h. It was found that in the germination process, the proteolytic, amylolytic and lipolytic enzymes activity increased, and the urease enzyme activity is reduced. The dependences of enzyme activity on chickpea seeds germination conditions were obtained by mathematical processing of experimental data. The calculated data are in good agreement with the experimental ones. This confirms the optimization efficiency based on experiments mathematical planning in order to determine the enzymatic activity of chickpea seeds germination optimal parameters of bioactivated seeds.

  4. Optimization of parameters of heat exchangers vehicles

    Directory of Open Access Journals (Sweden)

    Andrei MELEKHIN

    2014-09-01

    Full Text Available The relevance of the topic due to the decision of problems of the economy of resources in heating systems of vehicles. To solve this problem we have developed an integrated method of research, which allows to solve tasks on optimization of parameters of heat exchangers vehicles. This method decides multicriteria optimization problem with the program nonlinear optimization on the basis of software with the introduction of an array of temperatures obtained using thermography. The authors have developed a mathematical model of process of heat exchange in heat exchange surfaces of apparatuses with the solution of multicriteria optimization problem and check its adequacy to the experimental stand in the visualization of thermal fields, an optimal range of managed parameters influencing the process of heat exchange with minimal metal consumption and the maximum heat output fin heat exchanger, the regularities of heat exchange process with getting generalizing dependencies distribution of temperature on the heat-release surface of the heat exchanger vehicles, defined convergence of the results of research in the calculation on the basis of theoretical dependencies and solving mathematical model.

  5. Parameter optimization for surface flux transport models

    Science.gov (United States)

    Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.

    2017-11-01

    Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.

  6. Cosmological parameter estimation using particle swarm optimization

    Science.gov (United States)

    Prasad, Jayanti; Souradeep, Tarun

    2012-06-01

    Constraining theoretical models, which are represented by a set of parameters, using observational data is an important exercise in cosmology. In Bayesian framework this is done by finding the probability distribution of parameters which best fits to the observational data using sampling based methods like Markov chain Monte Carlo (MCMC). It has been argued that MCMC may not be the best option in certain problems in which the target function (likelihood) poses local maxima or have very high dimensionality. Apart from this, there may be examples in which we are mainly interested to find the point in the parameter space at which the probability distribution has the largest value. In this situation the problem of parameter estimation becomes an optimization problem. In the present work we show that particle swarm optimization (PSO), which is an artificial intelligence inspired population based search procedure, can also be used for cosmological parameter estimation. Using PSO we were able to recover the best-fit Λ cold dark matter (LCDM) model parameters from the WMAP seven year data without using any prior guess value or any other property of the probability distribution of parameters like standard deviation, as is common in MCMC. We also report the results of an exercise in which we consider a binned primordial power spectrum (to increase the dimensionality of problem) and find that a power spectrum with features gives lower chi square than the standard power law. Since PSO does not sample the likelihood surface in a fair way, we follow a fitting procedure to find the spread of likelihood function around the best-fit point.

  7. Optimization of deposition conditions of CdS thin films using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Yücel, Ersin, E-mail: dr.ersinyucel@gmail.com [Department of Physics, Faculty of Arts and Sciences, Mustafa Kemal University, 31034 Hatay (Turkey); Güler, Nuray [Department of Physics, Faculty of Arts and Sciences, Mustafa Kemal University, 31034 Hatay (Turkey); Yücel, Yasin [Department of Chemistry, Faculty of Arts and Sciences, Mustafa Kemal University, 31034 Hatay (Turkey)

    2014-03-15

    Highlights: • Statistical methods used for optimization of CdS deposition parameters. • The morphology of the films was smooth, homogeneous and continuous. • Optimal conditions found as pH 11, stirring speed:361 rpm and deposition time: 55 min. • CdS thin film band gap value was 2.72 eV under the optimum conditions. -- Abstract: Cadmium sulfide (CdS) thin films were prepared on glass substrates by chemical bath deposition (CBD) technique under different pH, stirring speed and deposition time. Response Surface Methodology (RSM) and Central Composite Design (CCD) were used to optimization of deposition parameters of the CdS thin films. RSM and CCD were also used to understand the significance and interaction of the factors affecting the film quality. Variables were determined as pH, stirring speed and deposition time. The band gap was chosen as response in the study. Influences of the variables on the band gap and the film quality were investigated. 5-level-3-factor central composite design was employed to evaluate the effects of the deposition conditions parameters such as pH (10.2–11.8), stirring speed (132–468 rpm) and deposition time (33–67 min) on the band gap of the films. The samples were characterized using X-ray diffraction (XRD), scanning electron microscope (SEM) and ultraviolet–visible spectroscopy (UV–vis) measurements. The optimal conditions for the deposition parameters of the CdS thin films have been found to be: pH 11, 361 of stirring speed and 55 min of deposition time. Under the optimal conditions theoretical (predicted) band gap of CdS (2.66 eV) was calculated using optimal coded values from the model and the theoretical value is good agreement with the value (2.72 eV) obtained by verification experiment.

  8. Optimization of nonlinear wave function parameters

    International Nuclear Information System (INIS)

    Shepard, R.; Minkoff, M.; Chemistry

    2006-01-01

    An energy-based optimization method is presented for our recently developed nonlinear wave function expansion form for electronic wave functions. This expansion form is based on spin eigenfunctions, using the graphical unitary group approach (GUGA). The wave function is expanded in a basis of product functions, allowing application to closed-shell and open-shell systems and to ground and excited electronic states. Each product basis function is itself a multiconfigurational function that depends on a relatively small number of nonlinear parameters called arc factors. The energy-based optimization is formulated in terms of analytic arc factor gradients and orbital-level Hamiltonian matrices that correspond to a specific kind of uncontraction of each of the product basis functions. These orbital-level Hamiltonian matrices give an intuitive representation of the energy in terms of disjoint subsets of the arc factors, they provide for an efficient computation of gradients of the energy with respect to the arc factors, and they allow optimal arc factors to be determined in closed form for subspaces of the full variation problem. Timings for energy and arc factor gradient computations involving expansion spaces of > 10 24 configuration state functions are reported. Preliminary convergence studies and molecular dissociation curves are presented for some small molecules

  9. Optimal construction parameters of electrosprayed trilayer organic photovoltaic devices

    International Nuclear Information System (INIS)

    Shah, S K; Ali, M; Gunnella, R; Abbas, M; Hirsch, L

    2014-01-01

    A detailed investigation of the optimal set of parameters employed in multilayer device fabrication obtained through successive electrospray deposited layers is reported. In this scheme, the donor/acceptor (D/A) bulk heterojunction layer is sandwiched between two thin stacked layers of individual donor and acceptor materials. The stacked layers geometry with optimal thicknesses plays a decisive role in improving operation characteristics. Among the parameters of the multilayer organic photovoltaics device, the D/A concentration ratio, blend thickness and stacking layers thicknesses are optimized. Other parameters, such as thermal annealing and the role of top metal contacts, are also discussed. Internal photon to current efficiency is found to attain a strong response in the 500 nm optical region for the most efficient device architectures. Such an observation indicates a clear interplay between photon harvesting of active layers and transport by ancillary stacking layers, opening up the possibility to engineer both the material fine structure and the device architecture to obtain the best photovoltaic response from a complex organic heterostructure. (paper)

  10. How deposition parameters control growth dynamics of nc-Si deposited by hot-wire chemical vapor deposition

    International Nuclear Information System (INIS)

    Moutinho, H.R.; To, B.; Jiang, C.-S.; Xu, Y.; Nelson, B.P.; Teplin, C.W.; Jones, K.M.; Perkins, J.; Al-Jassim, M.M.

    2006-01-01

    We studied the growth of silicon films deposited by hot-wire chemical vapor deposition under different values of filament current, substrate temperature, and hydrogen dilution ratio. The physical and electrical properties of the films were studied by Raman spectroscopy, x-ray diffraction, atomic force microscopy, conductive-atomic force microscopy, and transmission electron microscopy. There is an interdependence of the growth parameters, and films grown with different parameters can have similar structures. We discuss why this interdependence occurs and how it influences the properties of the deposited films, as well as the deposition rate. In general, the films have a complex structure, with a mixture of amorphous (220)-oriented crystalline and nanocrystalline phases present in most cases. The amount of each phase can be controlled by the variation of one or more of the growth parameters at a time

  11. Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization

    Directory of Open Access Journals (Sweden)

    MadhuSudana Rao Nalluri

    2017-01-01

    Full Text Available With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM and multilayer perceptron (MLP technique. We employ three recent evolutionary algorithms to optimize the parameters of the classifiers above, leading to six alternative hybrid disease diagnosis systems, also referred to as hybrid intelligent systems (HISs. Multiple objectives, namely, prediction accuracy, sensitivity, and specificity, have been considered to assess the efficacy of the proposed hybrid systems with existing ones. The proposed model is evaluated on 11 benchmark datasets, and the obtained results demonstrate that our proposed hybrid diagnosis systems perform better in terms of disease prediction accuracy, sensitivity, and specificity. Pertinent statistical tests were carried out to substantiate the efficacy of the obtained results.

  12. GA based CNC turning center exploitation process parameters optimization

    Directory of Open Access Journals (Sweden)

    Z. Car

    2009-01-01

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

  13. Optimization of rotational arc station parameter optimized radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Dong, P.; Ungun, B. [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Boyd, S. [Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Xing, L., E-mail: lei@stanford.edu [Department of Radiation Oncology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States)

    2016-09-15

    Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was

  14. Optimization of rotational arc station parameter optimized radiation therapy

    International Nuclear Information System (INIS)

    Dong, P.; Ungun, B.; Boyd, S.; Xing, L.

    2016-01-01

    Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was

  15. Optimal parameters for laser tissue soldering

    Science.gov (United States)

    McNally-Heintzelman, Karen M.; Sorg, Brian S.; Chan, Eric K.; Welch, Ashley J.; Dawes, Judith M.; Owen, Earl R.

    1998-07-01

    Variations in laser irradiance, exposure time, solder composition, chromophore type and concentration have led to inconsistencies in published results of laser-solder repair of tissue. To determine optimal parameters for laser tissue soldering, an in vitro study was performed using an 808-nm diode laser in conjunction with an indocyanine green (ICG)- doped albumin protein solder to weld bovine aorta specimens. Liquid and solid protein solders prepared from 25% and 60% bovine serum albumin (BSA), respectively, were compared. The effects of laser irradiance and exposure time on tensile strength of the weld and temperature rise as well as the effect of hydration on bond stability were investigated. Optimum irradiance and exposure times were identified for each solder type. Increasing the BSA concentration from 25% to 60% greatly increased the tensile strength of the weld. A reduction in dye concentration from 2.5 mg/ml to 0.25 mg/ml was also found to result in an increase in tensile strength. The strongest welds were produced with an irradiance of 6.4 W/cm2 for 50 s using a solid protein solder composed of 60% BSA and 0.25 mg/ml ICG. Steady-state solder surface temperatures were observed to reach 85 plus or minus 5 degrees Celsius with a temperature gradient across the solid protein solder strips of between 15 and 20 degrees Celsius. Finally, tensile strength was observed to decrease significantly (20 to 25%) after the first hour of hydration in phosphate-buffered saline. No appreciable change was observed in the strength of the tissue bonds with further hydration.

  16. Bath parameter dependence of chemically deposited Copper Selenide thin film

    International Nuclear Information System (INIS)

    Al-Mamun; Islam, A.B.M.O.

    2004-09-01

    In this article, a low cost chemical bath deposition (CBD) technique has been used for the preparation Of Cu 2-x Se thin films on to glass substrate. Different thin fms (0.2-0.6/μm) were prepared by adjusting the bath parameter like concentration of ammonia, deposition time, temperature of the solution, and the ratios of the mixing composition between copper and selenium in the reaction bath. From these studies, it reveals that at low concentration of ammonia or TEA, the terminal thicknesses of the films are less, which gradually increases with the increase of concentrations and then drop down at still higher concentrations. It has been found that completing the Cu 2+ ions with EA first, and then addition of ammonia yields better results than the reverse process. The film thickness increases with the decrease of value x of Cu 2-x Se. (author)

  17. PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

    Institute of Scientific and Technical Information of China (English)

    HU Jie; PENG Yinghong; XIONG Guangleng

    2006-01-01

    A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

  18. Coating material innovation in conjunction with optimized deposition technologies

    International Nuclear Information System (INIS)

    Stolze, M.; Leitner, K.

    2009-01-01

    Concentrating on physical vapour deposition methods several examples of recently developed coating materials for optical applications were studied for film deposition with optimized coating technologies: mixed evaporation materials for ion assisted deposition with modern plasma ion sources, planar metal and oxide sputter targets for Direct Current (DC) and Mid-Frequency (MF) pulsed sputter deposition and planar and rotatable sputter targets of transparent conductive oxides (TCO) for large-area sputter deposition. Films from specially designed titania based mixed evaporation materials deposited with new plasma ion sources and possible operation with pure oxygen showed extended ranges of the ratio between refractive index and structural film stress, hence there is an increased potential for the reduction of the total coating stress in High-Low alternating stacks and for coating plastics. DC and MF-pulsed sputtering of niobium metal and suboxide targets for optical coatings yielded essential benefits of the suboxide targets in a range of practical coating conditions (for absent in-situ post-oxidation ability): higher refractive index and deposition rate, better reproducibility and easier process control, and the potential for co-deposition of several targets. Technological progress in the manufacture of rotatable indium tin oxide (ITO) targets with regard to higher wall-thickness and density was shown to be reflected in higher material stock and coater up-time, economical deposition rates and stable process behaviour. Both for the rotatable ITO targets and higher-dense aluminum-doped zinc oxide (AZO) planar targets values of film transmittance and resistivity were in the range of the best values industrially achieved for films from the respective planar targets. The results for the rotatable ITO and planar AZO targets point to equally optimized process and film properties for the optimized rotatable AZO targets currently in testing

  19. Optimalization of selected RFID systems Parameters

    Directory of Open Access Journals (Sweden)

    Peter Vestenicky

    2004-01-01

    Full Text Available This paper describes procedure for maximization of RFID transponder read range. This is done by optimalization of magnetics field intensity at transponder place and by optimalization of antenna and transponder coils coupling factor. Results of this paper can be used for RFID with inductive loop, i.e. system working in near electromagnetic field.

  20. Highly doped ZnO films deposited by spray-pyrolysis. Design parameters for optoelectronic applications

    Energy Technology Data Exchange (ETDEWEB)

    Garcés, F.A., E-mail: felipe.garces@santafe-conicet.gov.ar [Instituto de Física del Litoral (UNL-CONICET), Güemes 3450, Santa Fe S3000GLN (Argentina); Budini, N. [Instituto de Física del Litoral (UNL-CONICET), Güemes 3450, Santa Fe S3000GLN (Argentina); Schmidt, J.A.; Arce, R.D. [Instituto de Física del Litoral (UNL-CONICET), Güemes 3450, Santa Fe S3000GLN (Argentina); Facultad de Ingeniería Química, Universidad Nacional del Litoral, Santiago del Estero 2829, Santa Fe S3000AOM (Argentina)

    2016-04-30

    Synthesis and preparation of ZnO films are relevant subjects for obtaining transparent and conducting layers with interesting applications in optoelectronics and photovoltaics. Optimization of parameters such as dopant type and concentration, deposition time and substrate temperature is important for obtaining ZnO layers with optimal properties. In this work we present a study about the induced effects of deposition time on optical and electrical properties of ZnO thin films. These films were deposited by spray pyrolysis of a suitable Zn precursor, obtained through the sol–gel method. The deposition time has direct incidence on internal stress in the crystal structure, generating defects that may affect transparency and electrical transport into the layers. We performed mosaicity measurements, through X-ray diffraction, and used it as a tool to get an insight on structural characteristics and homogeneity of ZnO layers. Also, through this technique, we analyzed thickness and doping effects on crystallinity and carrier transport properties. - Highlights: • Al-doped ZnO films with high conductivity and moderate Hall mobility were obtained. • Mosaicity between crystalline domains increased with film thickness. • Lattice parameters a and c diminished linearly as a function of Al concentration. • First steps for developing porous silicon/doped ZnO heterojunctions were presented.

  1. Highly doped ZnO films deposited by spray-pyrolysis. Design parameters for optoelectronic applications

    International Nuclear Information System (INIS)

    Garcés, F.A.; Budini, N.; Schmidt, J.A.; Arce, R.D.

    2016-01-01

    Synthesis and preparation of ZnO films are relevant subjects for obtaining transparent and conducting layers with interesting applications in optoelectronics and photovoltaics. Optimization of parameters such as dopant type and concentration, deposition time and substrate temperature is important for obtaining ZnO layers with optimal properties. In this work we present a study about the induced effects of deposition time on optical and electrical properties of ZnO thin films. These films were deposited by spray pyrolysis of a suitable Zn precursor, obtained through the sol–gel method. The deposition time has direct incidence on internal stress in the crystal structure, generating defects that may affect transparency and electrical transport into the layers. We performed mosaicity measurements, through X-ray diffraction, and used it as a tool to get an insight on structural characteristics and homogeneity of ZnO layers. Also, through this technique, we analyzed thickness and doping effects on crystallinity and carrier transport properties. - Highlights: • Al-doped ZnO films with high conductivity and moderate Hall mobility were obtained. • Mosaicity between crystalline domains increased with film thickness. • Lattice parameters a and c diminished linearly as a function of Al concentration. • First steps for developing porous silicon/doped ZnO heterojunctions were presented.

  2. GA BASED GLOBAL OPTIMAL DESIGN PARAMETERS FOR ...

    African Journals Online (AJOL)

    Journal of Modeling, Design and Management of Engineering Systems ... DESIGN PARAMETERS FOR CONSECUTIVE REACTIONS IN SERIALLY CONNECTED ... for the process equipments such as chemical reactors used in industries.

  3. Analysis Balance Parameter of Optimal Ramp metering

    Science.gov (United States)

    Li, Y.; Duan, N.; Yang, X.

    2018-05-01

    Ramp metering is a motorway control method to avoid onset congestion through limiting the access of ramp inflows into the main road of the motorway. The optimization model of ramp metering is developed based upon cell transmission model (CTM). With the piecewise linear structure of CTM, the corresponding motorway traffic optimization problem can be formulated as a linear programming (LP) problem. It is known that LP problem can be solved by established solution algorithms such as SIMPLEX or interior-point methods for the global optimal solution. The commercial software (CPLEX) is adopted in this study to solve the LP problem within reasonable computational time. The concept is illustrated through a case study of the United Kingdom M25 Motorway. The optimal solution provides useful insights and guidances on how to manage motorway traffic in order to maximize the corresponding efficiency.

  4. Optimization of regeneration and transformation parameters in ...

    African Journals Online (AJOL)

    PRECIOUS

    transformation and regeneration therefore optimization of these two factors is .... An analysis of variance was conducted using explants types x construct ... and significant differences between means were assessed by the. Tukey's test at 1 and ...

  5. Optimal Design of Shock Tube Experiments for Parameter Inference

    KAUST Repository

    Bisetti, Fabrizio; Knio, Omar

    2014-01-01

    We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation

  6. Optimization of process and solution parameters in electrospinning polyethylene oxide

    CSIR Research Space (South Africa)

    Jacobs, V

    2011-11-01

    Full Text Available This paper reports the optimization of electrospinning process and solution parameters using factorial design approach to obtain uniform polyethylene oxide (PEO) nanofibers. The parameters studied were distance between nozzle and collector screen...

  7. Nanohydroxyapatite synthesis using optimized process parameters ...

    Indian Academy of Sciences (India)

    3Energy Research Group, School of Engineering, Taylor's University, 47500 ... influence of different ultrasonication parameters on the prop- ... to evaluate multiple process parameters and their interaction. ..... dent and dependent variables by a 3-D representation of .... The intensities of O–H functional groups are seen to.

  8. Optimizing growth conditions for electroless deposition of Au films ...

    Indian Academy of Sciences (India)

    Unknown

    Optimizing growth conditions for electroless deposition of Au films on. Si(111) substrates. BHUVANA and G U KULKARNI*. Chemistry and Physics of Materials Unit and DST Unit on Nanoscience, Jawaharlal Nehru Centre for. Advanced Scientific Research, Jakkur PO, Bangalore 560 064, India. MS received 24 March 2006.

  9. Optimizing the fabrication of carbon nanotube electrode for effective capacitive deionization via electrophoretic deposition strategy

    Directory of Open Access Journals (Sweden)

    Simeng Zhang

    2018-04-01

    Full Text Available In order to obtain superior electrode performances in capacitive deionization (CDI, the electrophoretic deposition (EPD was introduced as a novel strategy for the fabrication of carbon nanotube (CNT electrode. Preparation parameters, including the concentration of slurry components, deposition time and electric field intensity, were mainly investigated and optimized in terms of electrochemical characteristic and desalination performance of the deposited CNT electrode. The SEM image shows that the CNT material was deposited homogeneously on the current collector and a non-crack surface of the electrode was obtained. An optimal preparation condition of the deposited CNT electrode was obtained and specified as the Al (NO33 M concentration of 1.3 × 10−2 mol/L, the deposition time of 30 min and the electric field intensity of 15 V/cm. The obtained electrode performs an increasing specific mass capacitance of 33.36 F/g and specific adsorption capacity of 23.93 mg/g, which are 1.62 and 1.85 times those of the coated electrode respectively. The good performance of the deposited CNT electrode indicates the promising application of the EPD methodology in subsequent research and fabrication of the CDI electrodes for CDI process. Keywords: Carbon nanotube, Water treatment, Desalination, Capacitive deionization, Electrode fabrication, Electrophoretic deposition

  10. Future xenon system operational parameter optimization

    International Nuclear Information System (INIS)

    Lowrey, J.D.; Eslinger, P.W.; Miley, H.S.

    2016-01-01

    Any atmospheric monitoring network will have practical limitations in the density of its sampling stations. The classical approach to network optimization has been to have 12 or 24-h integration of air samples at the highest station density possible to improve minimum detectable concentrations. The authors present here considerations on optimizing sampler integration time to make the best use of any network and maximize the likelihood of collecting quality samples at any given location. In particular, this work makes the case that shorter duration sample integration (i.e. <12 h) enhances critical isotopic information and improves the source location capability of a radionuclide network, or even just one station. (author)

  11. Optimization of CVD parameters for long ZnO NWs grown on ITO

    Indian Academy of Sciences (India)

    The optimization of chemical vapour deposition (CVD) parameters for long and vertically aligned (VA) ZnO nanowires (NWs) were investigated. Typical ZnO NWs as a single crystal grown on indium tin oxide (ITO)-coated glass substrate were successfully synthesized. First, the conducted side of ITO–glass substrate was ...

  12. Nanohydroxyapatite synthesis using optimized process parameters

    Indian Academy of Sciences (India)

    Nanohydroxyapatite; ultrasonication; response surface methodology; calcination; ... Three independent process parameters: temperature () (70, 80 and 90°C), ... Bangi, Selangor, Malaysia; Energy Research Group, School of Engineering, ...

  13. Hybrid computer optimization of systems with random parameters

    Science.gov (United States)

    White, R. C., Jr.

    1972-01-01

    A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

  14. Experimental Verification of Statistically Optimized Parameters for Low-Pressure Cold Spray Coating of Titanium

    Directory of Open Access Journals (Sweden)

    Damilola Isaac Adebiyi

    2016-06-01

    Full Text Available The cold spray coating process involves many process parameters which make the process very complex, and highly dependent and sensitive to small changes in these parameters. This results in a small operational window of the parameters. Consequently, mathematical optimization of the process parameters is key, not only to achieving deposition but also improving the coating quality. This study focuses on the mathematical identification and experimental justification of the optimum process parameters for cold spray coating of titanium alloy with silicon carbide (SiC. The continuity, momentum and the energy equations governing the flow through the low-pressure cold spray nozzle were solved by introducing a constitutive equation to close the system. This was used to calculate the critical velocity for the deposition of SiC. In order to determine the input temperature that yields the calculated velocity, the distribution of velocity, temperature, and pressure in the cold spray nozzle were analyzed, and the exit values were predicted using the meshing tool of Solidworks. Coatings fabricated using the optimized parameters and some non-optimized parameters are compared. The coating of the CFD-optimized parameters yielded lower porosity and higher hardness.

  15. Optimization of Milling Parameters Employing Desirability Functions

    Science.gov (United States)

    Ribeiro, J. L. S.; Rubio, J. C. Campos; Abrão, A. M.

    2011-01-01

    The principal aim of this paper is to investigate the influence of tool material (one cermet and two coated carbide grades), cutting speed and feed rate on the machinability of hardened AISI H13 hot work steel, in order to identify the cutting conditions which lead to optimal performance. A multiple response optimization procedure based on tool life, surface roughness, milling forces and the machining time (required to produce a sample cavity) was employed. The results indicated that the TiCN-TiN coated carbide and cermet presented similar results concerning the global optimum values for cutting speed and feed rate per tooth, outperforming the TiN-TiCN-Al2O3 coated carbide tool.

  16. Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

    OpenAIRE

    Zhang, Xiangsheng; Pan, Feng

    2015-01-01

    Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...

  17. Parameters Optimization and Application to Glutamate Fermentation Model Using SVM

    Directory of Open Access Journals (Sweden)

    Xiangsheng Zhang

    2015-01-01

    Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.

  18. Optimization design of energy deposition on single expansion ramp nozzle

    Science.gov (United States)

    Ju, Shengjun; Yan, Chao; Wang, Xiaoyong; Qin, Yupei; Ye, Zhifei

    2017-11-01

    Optimization design has been widely used in the aerodynamic design process of scramjets. The single expansion ramp nozzle is an important component for scramjets to produces most of thrust force. A new concept of increasing the aerodynamics of the scramjet nozzle with energy deposition is presented. The essence of the method is to create a heated region in the inner flow field of the scramjet nozzle. In the current study, the two-dimensional coupled implicit compressible Reynolds Averaged Navier-Stokes and Menter's shear stress transport turbulence model have been applied to numerically simulate the flow fields of the single expansion ramp nozzle with and without energy deposition. The numerical results show that the proposal of energy deposition can be an effective method to increase force characteristics of the scramjet nozzle, the thrust coefficient CT increase by 6.94% and lift coefficient CN decrease by 26.89%. Further, the non-dominated sorting genetic algorithm coupled with the Radial Basis Function neural network surrogate model has been employed to determine optimum location and density of the energy deposition. The thrust coefficient CT and lift coefficient CN are selected as objective functions, and the sampling points are obtained numerically by using a Latin hypercube design method. The optimized thrust coefficient CT further increase by 1.94%, meanwhile, the optimized lift coefficient CN further decrease by 15.02% respectively. At the same time, the optimized performances are in good and reasonable agreement with the numerical predictions. The findings suggest that scramjet nozzle design and performance can benefit from the application of energy deposition.

  19. Computer Simulation of Temperature Parameter for Diamond Formation by Using Hot-Filament Chemical Vapor Deposition

    Directory of Open Access Journals (Sweden)

    Chang Weon Song

    2017-12-01

    Full Text Available To optimize the deposition parameters of diamond films, the temperature, pressure, and distance between the filament and the susceptor need to be considered. However, it is difficult to precisely measure and predict the filament and susceptor temperature in relation to the applied power in a hot filament chemical vapor deposition (HF-CVD system. In this study, the temperature distribution inside the system was numerically calculated for the applied powers of 12, 14, 16, and 18 kW. The applied power needed to achieve the appropriate temperature at a constant pressure and other conditions was deduced, and applied to actual experimental depositions. The numerical simulation was conducted using the commercial computational fluent dynamics software ANSYS-FLUENT. To account for radiative heat-transfer in the HF-CVD reactor, the discrete ordinate (DO model was used. The temperatures of the filament surface and the susceptor at different power levels were predicted to be 2512–2802 K and 1076–1198 K, respectively. Based on the numerical calculations, experiments were performed. The simulated temperatures for the filament surface were in good agreement with the experimental temperatures measured using a two-color pyrometer. The results showed that the highest deposition rate and the lowest deposition of non-diamond was obtained at a power of 16 kW.

  20. Optimizing incomplete sample designs for item response model parameters

    NARCIS (Netherlands)

    van der Linden, Willem J.

    Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with

  1. Optimized plasma-deposited fluorocarbon coating for dry release and passivation of thin SU-8 cantilevers

    DEFF Research Database (Denmark)

    Keller, Stephan Urs; Häfliger, Daniel; Boisen, Anja

    2008-01-01

    during fluorocarbon deposition, the surface free energy of the coating can be tuned to allow for uniform wetting during spin coating of arbitrary thin SU-8 films. Further, they define an optimal pressure regime for the release of thin polymer structures at high yield. They demonstrate the successful......Plasma-deposited fluorocarbon coatings are introduced as a convenient method for the dry release of polymer structures. In this method, the passivation process in a deep reactive ion etch reactor was used to deposit hydrophobic fluorocarbon films. Standard photolithography with the negative epoxy......-based photoresist SU-8 was used to fabricate polymer structures such as cantilevers and membranes on top of the nonadhesive release layer. The authors identify the plasma density as the main parameter determining the surface properties of the deposited fluorocarbon films. They show that by modifying the pressure...

  2. Optimizing a Water Simulation based on Wavefront Parameter Optimization

    OpenAIRE

    Lundgren, Martin

    2017-01-01

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

  3. Influence of processing parameters on lattice parameters in laser deposited tool alloy steel

    Energy Technology Data Exchange (ETDEWEB)

    Sun, G.F., E-mail: gfsun82@gmail.com [Center for Laser-Aided Intelligent Manufacturing, University of Michigan, Ann Arbor, MI, 48109 (United States); School of Mechanical Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013 (China); Bhattacharya, S. [Center for Laser-Aided Intelligent Manufacturing, University of Michigan, Ann Arbor, MI, 48109 (United States); Dinda, G.P.; Dasgupta, A. [Center for Advanced Technologies, Focus: Hope, Detroit, MI, 48238 (United States); Mazumder, J. [Center for Laser-Aided Intelligent Manufacturing, University of Michigan, Ann Arbor, MI, 48109 (United States)

    2011-06-15

    Highlights: {yields} Orientation relationships among phases in the DMD are given. {yields} Martensite lattice parameters increased with laser specific energy. {yields} Austenite lattice parameters decreased with laser specific energy. - Abstract: Laser aided direct metal deposition (DMD) has been used to form AISI 4340 steel coating on the AISI 4140 steel substrate. The microstructural property of the DMD coating was analyzed by means of scanning electron microscopy, transmission electron microscopy and X-ray diffractometry. Microhardness of the DMD was measured with a Vickers microhardness tester. Results indicate that DMD can be used to form dense AISI 4340 steel coatings on AISI 4140 steel substrate. The DMD coating is mainly composed of martensite and retained austenite. Consecutive thermal cycles have a remarkable effect on the microstructure of the plan view of the DMD coating and on the corresponding microhardness distribution. Orientation relationships among austenite, martensite and cementite in the DMD coating followed the ones in conventional heat treated steels. As the laser specific energy decreased, cooling rate increased, and martensite peaks broadened and shifted to a lower Bragg's angle. Also martensite lattice parameters increased and austenite lattice parameters decreased due to the above parameter change.

  4. Influence of processing parameters on lattice parameters in laser deposited tool alloy steel

    International Nuclear Information System (INIS)

    Sun, G.F.; Bhattacharya, S.; Dinda, G.P.; Dasgupta, A.; Mazumder, J.

    2011-01-01

    Highlights: → Orientation relationships among phases in the DMD are given. → Martensite lattice parameters increased with laser specific energy. → Austenite lattice parameters decreased with laser specific energy. - Abstract: Laser aided direct metal deposition (DMD) has been used to form AISI 4340 steel coating on the AISI 4140 steel substrate. The microstructural property of the DMD coating was analyzed by means of scanning electron microscopy, transmission electron microscopy and X-ray diffractometry. Microhardness of the DMD was measured with a Vickers microhardness tester. Results indicate that DMD can be used to form dense AISI 4340 steel coatings on AISI 4140 steel substrate. The DMD coating is mainly composed of martensite and retained austenite. Consecutive thermal cycles have a remarkable effect on the microstructure of the plan view of the DMD coating and on the corresponding microhardness distribution. Orientation relationships among austenite, martensite and cementite in the DMD coating followed the ones in conventional heat treated steels. As the laser specific energy decreased, cooling rate increased, and martensite peaks broadened and shifted to a lower Bragg's angle. Also martensite lattice parameters increased and austenite lattice parameters decreased due to the above parameter change.

  5. Optimization of surface roughness parameters in dry turning

    OpenAIRE

    R.A. Mahdavinejad; H. Sharifi Bidgoli

    2009-01-01

    Purpose: The precision of machine tools on one hand and the input setup parameters on the other hand, are strongly influenced in main output machining parameters such as stock removal, toll wear ratio and surface roughnes.Design/methodology/approach: There are a lot of input parameters which are effective in the variations of these output parameters. In CNC machines, the optimization of machining process in order to predict surface roughness is very important.Findings: From this point of view...

  6. Grey fuzzy logic approach for the optimization of DLC thin film coating process parameters using PACVD technique

    Science.gov (United States)

    Ghadai, R. K.; Das, P. P.; Shivakoti, I.; Mondal, S. C.; Swain, B. P.

    2017-07-01

    Diamond-like carbon (DLC) coatings are widely used in medical, manufacturing and aerospace industries due to their excellent mechanical, biological, optical and tribological properties. The selection of optimal process parameters for efficient characteristics of DLC film is always a challenging issue for the materials science researchers. The optimal combination of the process parameters involved in the deposition of DLC films provide a better result, which subsequently help other researchers to choose the process parameters. In the present work Grey Relation Analysis (GRA) and Fuzzy-logic are being used for the optimization of process parameters in DLC film coating by using plasma assist chemical vapour deposition (PACVD) technique. The bias voltage, bias frequency, deposition pressure, gas composition are considered as input process parameters and hardness (GPa), Young's modulus (GPa), ratio between diamond to graphic fraction, (Id/Ig) ratio are considered as response parameters. The input parameters are optimized by grey fuzzy analysis. The contribution of individual input parameter is done by ANOVA. In this analysis found that bias voltage having the least influence and gas composition has highest influence in the PACVD deposited DLC films. The grey fuzzy analysis results indicated that optimum results for bias voltage, bias frequency, deposition pressure, gas composition for the DLC thin films are -50 V, 6 kHz, 4 μbar and 60:40 % respectively.

  7. Optimization of Uranium Molecular Deposition for Alpha-Counting Sources

    Energy Technology Data Exchange (ETDEWEB)

    Monzo, Ellen [Univ. of Minnesota, Duluth, MN (United States); Parsons-Moss, Tashi [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Genetti, Victoria [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Knight, Kimberly [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-12-12

    Method development for molecular deposition of uranium onto aluminum 1100 plates was conducted with custom plating cells at Lawrence Livermore National Laboratory. The method development focused primarily on variation of electrode type, which was expected to directly influence plated sample homogeneity. Solid disc platinum and mesh platinum anodes were compared and data revealed that solid disc platinum anodes produced more homogenous uranium oxide films. However, the activity distribution also depended on the orientation of the platinum electrode relative to the aluminum cathode, starting current, and material composition of the plating cell. Experiments demonstrated these variables were difficult to control under the conditions available. Variation of plating parameters among a series of ten deposited plates yielded variations up to 30% in deposition efficiency. Teflon particles were observed on samples plated in Teflon cells, which poses a problem for alpha activity measurements of the plates. Preliminary electropolishing and chemical polishing studies were also conducted on the aluminum 1100 cathode plates.

  8. Optimal parameters of the SVM for temperature prediction

    Directory of Open Access Journals (Sweden)

    X. Shi

    2015-05-01

    Full Text Available This paper established three different optimization models in order to predict the Foping station temperature value. The dimension was reduced to change multivariate climate factors into a few variables by principal component analysis (PCA. And the parameters of support vector machine (SVM were optimized with genetic algorithm (GA, particle swarm optimization (PSO and developed genetic algorithm. The most suitable method was applied for parameter optimization by comparing the results of three different models. The results are as follows: The developed genetic algorithm optimization parameters of the predicted values were closest to the measured value after the analog trend, and it is the most fitting measured value trends, and its homing speed is relatively fast.

  9. 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 ...

  10. Optimization of process parameters for synthesis of silica–Ni ...

    Indian Academy of Sciences (India)

    Optimization of process parameters for synthesis of silica–Ni nanocomposite by design of experiment ... Sol–gel; Ni; design of experiments; nanocomposites. ... Kolkata 700 032, India; Rustech Products Pvt. Ltd., Kolkata 700 045, India ...

  11. Setting of the Optimal Parameters of Melted Glass

    Czech Academy of Sciences Publication Activity Database

    Luptáková, Natália; Matejíčka, L.; Krečmer, N.

    2015-01-01

    Roč. 10, č. 1 (2015), s. 73-79 ISSN 1802-2308 Institutional support: RVO:68081723 Keywords : Striae * Glass * Glass melting * Regression * Optimal parameters Subject RIV: JH - Ceramics, Fire-Resistant Materials and Glass

  12. Search Parameter Optimization for Discrete, Bayesian, and Continuous Search Algorithms

    Science.gov (United States)

    2017-09-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CONTINUOUS SEARCH ALGORITHMS by...to 09-22-2017 4. TITLE AND SUBTITLE SEARCH PARAMETER OPTIMIZATION FOR DISCRETE , BAYESIAN, AND CON- TINUOUS SEARCH ALGORITHMS 5. FUNDING NUMBERS 6...simple search and rescue acts to prosecuting aerial/surface/submersible targets on mission. This research looks at varying the known discrete and

  13. Optimization Design of Multi-Parameters in Rail Launcher System

    OpenAIRE

    Yujiao Zhang; Weinan Qin; Junpeng Liao; Jiangjun Ruan

    2014-01-01

    Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different paramete...

  14. On the role of modeling parameters in IMRT plan optimization

    International Nuclear Information System (INIS)

    Krause, Michael; Scherrer, Alexander; Thieke, Christian

    2008-01-01

    The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way

  15. An optimization method for parameters in reactor nuclear physics

    International Nuclear Information System (INIS)

    Jachic, J.

    1982-01-01

    An optimization method for two basic problems of Reactor Physics was developed. The first is the optimization of a plutonium critical mass and the bruding ratio for fast reactors in function of the radial enrichment distribution of the fuel used as control parameter. The second is the maximization of the generation and the plutonium burnup by an optimization of power temporal distribution. (E.G.) [pt

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

    Science.gov (United States)

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

    2014-11-20

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

  17. An optimized nanoparticle separator enabled by electron beam induced deposition

    International Nuclear Information System (INIS)

    Fowlkes, J D; Rack, P D; Doktycz, M J

    2010-01-01

    Size-based separations technologies will inevitably benefit from advances in nanotechnology. Direct-write nanofabrication provides a useful mechanism for depositing/etching nanoscale elements in environments otherwise inaccessible to conventional nanofabrication techniques. Here, electron beam induced deposition was used to deposit an array of nanoscale features in a 3D environment with minimal material proximity effects outside the beam-interaction region. Specifically, the membrane component of a nanoparticle separator was fabricated by depositing a linear array of sharply tipped nanopillars, with a singular pitch, designed for sub-50 nm nanoparticle permeability. The nanopillar membrane was used in a dual capacity to control the flow of nanoparticles in the transaxial direction of the array while facilitating the sealing of the cellular-sized compartment in the paraxial direction. An optimized growth recipe resulted which (1) maximized the growth efficiency of the membrane (which minimizes proximity effects) and (2) preserved the fidelity of the spacing between nanopillars (which maximizes the size-based gating quality of the membrane) while (3) maintaining sharp nanopillar apexes for impaling an optically transparent polymeric lid critical for device sealing.

  18. An optimized nanoparticle separator enabled by electron beam induced deposition

    Science.gov (United States)

    Fowlkes, J. D.; Doktycz, M. J.; Rack, P. D.

    2010-04-01

    Size-based separations technologies will inevitably benefit from advances in nanotechnology. Direct-write nanofabrication provides a useful mechanism for depositing/etching nanoscale elements in environments otherwise inaccessible to conventional nanofabrication techniques. Here, electron beam induced deposition was used to deposit an array of nanoscale features in a 3D environment with minimal material proximity effects outside the beam-interaction region. Specifically, the membrane component of a nanoparticle separator was fabricated by depositing a linear array of sharply tipped nanopillars, with a singular pitch, designed for sub-50 nm nanoparticle permeability. The nanopillar membrane was used in a dual capacity to control the flow of nanoparticles in the transaxial direction of the array while facilitating the sealing of the cellular-sized compartment in the paraxial direction. An optimized growth recipe resulted which (1) maximized the growth efficiency of the membrane (which minimizes proximity effects) and (2) preserved the fidelity of the spacing between nanopillars (which maximizes the size-based gating quality of the membrane) while (3) maintaining sharp nanopillar apexes for impaling an optically transparent polymeric lid critical for device sealing.

  19. Optimization of hydraulic turbine governor parameters based on WPA

    Science.gov (United States)

    Gao, Chunyang; Yu, Xiangyang; Zhu, Yong; Feng, Baohao

    2018-01-01

    The parameters of hydraulic turbine governor directly affect the dynamic characteristics of the hydraulic unit, thus affecting the regulation capacity and the power quality of power grid. The governor of conventional hydropower unit is mainly PID governor with three adjustable parameters, which are difficult to set up. In order to optimize the hydraulic turbine governor, this paper proposes wolf pack algorithm (WPA) for intelligent tuning since the good global optimization capability of WPA. Compared with the traditional optimization method and PSO algorithm, the results show that the PID controller designed by WPA achieves a dynamic quality of hydraulic system and inhibits overshoot.

  20. Integral Optimization of Systematic Parameters of Flip-Flow Screens

    Institute of Scientific and Technical Information of China (English)

    翟宏新

    2004-01-01

    The synthetic index Ks for evaluating flip-flow screens is proposed and systematically optimized in view of the whole system. A series of optimized values of relevant parameters are found and then compared with those of the current industrial specifications. The results show that the optimized value Ks approaches the one of those famous flip-flow screens in the world. Some new findings on geometric and kinematics parameters are useful for improving the flip-flow screens with a low Ks value, which is helpful in developing clean coal technology.

  1. Investigation and validation of optimal cutting parameters for least ...

    African Journals Online (AJOL)

    The cutting parameters were analyzed and optimized using Box Behnken procedure in the DESIGN EXPERT environment. The effect of process parameters with the output variable were predicted which indicates that the highest cutting speed has significant role in producing least surface roughness followed by feed and ...

  2. Parameter optimization of electrochemical machining process using black hole algorithm

    Science.gov (United States)

    Singh, Dinesh; Shukla, Rajkamal

    2017-12-01

    Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

  3. Multi-parameter optimization design of parabolic trough solar receiver

    International Nuclear Information System (INIS)

    Guo, Jiangfeng; Huai, Xiulan

    2016-01-01

    Highlights: • The optimal condition can be obtained by multi-parameter optimization. • Exergy and thermal efficiencies are employed as objective function. • Exergy efficiency increases at the expense of heat losses. • The heat obtained by working fluid increases as thermal efficiency grows. - Abstract: The design parameters of parabolic trough solar receiver are interrelated and interact with one another, so the optimal performance of solar receiver cannot be obtained by the convectional single-parameter optimization. To overcome the shortcoming of single-parameter optimization, a multi-parameter optimization of parabolic trough solar receiver is employed based on genetic algorithm in the present work. When the thermal efficiency is taken as the objective function, the heat obtained by working fluid increases while the average temperature of working fluid and wall temperatures of solar receiver decrease. The average temperature of working fluid and the wall temperatures of solar receiver increase while the heat obtained by working fluid decreases generally by taking the exergy efficiency as an objective function. Assuming that the solar radiation intensity remains constant, the exergy obtained by working fluid increases by taking exergy efficiency as the objective function, which comes at the expense of heat losses of solar receiver.

  4. Genetic Algorithm Optimizes Q-LAW Control Parameters

    Science.gov (United States)

    Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard

    2008-01-01

    A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.

  5. Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor

    Directory of Open Access Journals (Sweden)

    Lin Ye

    2014-02-01

    Full Text Available Using the finite element method (FEM and particle swarm optimization (PSO, a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters’ effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°.

  6. Multi-objective optimization in quantum parameter estimation

    Science.gov (United States)

    Gong, BeiLi; Cui, Wei

    2018-04-01

    We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

  7. Optimizing chirped laser pulse parameters for electron acceleration in vacuum

    Energy Technology Data Exchange (ETDEWEB)

    Akhyani, Mina; Jahangiri, Fazel; Niknam, Ali Reza; Massudi, Reza, E-mail: r-massudi@sbu.ac.ir [Laser and Plasma Research Institute, Shahid Beheshti University, Tehran 1983969411 (Iran, Islamic Republic of)

    2015-11-14

    Electron dynamics in the field of a chirped linearly polarized laser pulse is investigated. Variations of electron energy gain versus chirp parameter, time duration, and initial phase of laser pulse are studied. Based on maximizing laser pulse asymmetry, a numerical optimization procedure is presented, which leads to the elimination of rapid fluctuations of gain versus the chirp parameter. Instead, a smooth variation is observed that considerably reduces the accuracy required for experimentally adjusting the chirp parameter.

  8. A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

    Science.gov (United States)

    Bhattacharjya, Rajib Kumar

    2018-05-01

    The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

  9. In situ growth optimization in focused electron-beam induced deposition

    Directory of Open Access Journals (Sweden)

    Paul M. Weirich

    2013-12-01

    Full Text Available We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID. It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me3. For W(CO6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques.

  10. Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...

    Science.gov (United States)

    With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th

  11. APPLICATION OF GENETIC ALGORITHMS FOR ROBUST PARAMETER OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    N. Belavendram

    2010-12-01

    Full Text Available Parameter optimization can be achieved by many methods such as Monte-Carlo, full, and fractional factorial designs. Genetic algorithms (GA are fairly recent in this respect but afford a novel method of parameter optimization. In GA, there is an initial pool of individuals each with its own specific phenotypic trait expressed as a ‘genetic chromosome’. Different genes enable individuals with different fitness levels to reproduce according to natural reproductive gene theory. This reproduction is established in terms of selection, crossover and mutation of reproducing genes. The resulting child generation of individuals has a better fitness level akin to natural selection, namely evolution. Populations evolve towards the fittest individuals. Such a mechanism has a parallel application in parameter optimization. Factors in a parameter design can be expressed as a genetic analogue in a pool of sub-optimal random solutions. Allowing this pool of sub-optimal solutions to evolve over several generations produces fitter generations converging to a pre-defined engineering optimum. In this paper, a genetic algorithm is used to study a seven factor non-linear equation for a Wheatstone bridge as the equation to be optimized. A comparison of the full factorial design against a GA method shows that the GA method is about 1200 times faster in finding a comparable solution.

  12. Influence of deposition parameters on morphological properties of biomedical calcium phosphate coatings prepared using electrostatic spray deposition

    International Nuclear Information System (INIS)

    Leeuwenburgh, S.C.G.; Wolke, J.G.C.; Schoonman, J.; Jansen, J.A.

    2005-01-01

    In order to deposit biomedical calcium phosphate (CaP) coatings with a defined surface morphology, the electrostatic spray deposition (ESD) technique was used since this technique offers the possibility to deposit ceramic coatings with a variety of surface morphologies. A scanning electron microscopical study was performed in order to investigate the influence of several deposition parameters on the final morphology of the deposited coatings. The chemical characteristics of the coatings were studied by means of X-ray diffraction and Fourier-transform infrared spectroscopy. Regarding the chemical coating properties, the results showed that the coatings can be described as crystalline carbonate apatite coatings, a crystal phase which is similar to the mineral phase of bone and teeth. The morphology of CaP coatings, deposited using the ESD technique, was strongly dependent on the deposition parameters. By changing the nozzle-to-substrate distance, the precursor liquid flow rate and the deposition temperature, coating morphologies were deposited, which varied from dense to highly porous, reticular morphologies. The formation of various morphologies was the result of an equilibrium between the relative rates of CaP solute precipitation/reaction, solvent evaporation and droplet spreading onto the substrate surface

  13. Estimating cellular parameters through optimization procedures: elementary principles and applications

    Directory of Open Access Journals (Sweden)

    Akatsuki eKimura

    2015-03-01

    Full Text Available Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE in a prediction or to maximize likelihood. A (local maximum of likelihood or (local minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

  14. Effects of build parameters on linear wear loss in plastic part produced by fused deposition modeling

    Science.gov (United States)

    Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

    2017-07-01

    Fused Deposition Modeling (FDM) is one of the prominent additive manufacturing technologies for producing polymer products. FDM is a complex additive manufacturing process that can be influenced by many process conditions. The industrial demands required from the FDM process are increasing with higher level product functionality and properties. The functionality and performance of FDM manufactured parts are greatly influenced by the combination of many various FDM process parameters. Designers and researchers always pay attention to study the effects of FDM process parameters on different product functionalities and properties such as mechanical strength, surface quality, dimensional accuracy, build time and material consumption. However, very limited studies have been carried out to investigate and optimize the effect of FDM build parameters on wear performance. This study focuses on the effect of different build parameters on micro-structural and wear performance of FDM specimens using definitive screening design based quadratic model. This would reduce the cost and effort of additive manufacturing engineer to have a systematic approachto make decision among the manufacturing parameters to achieve the desired product quality.

  15. Parameter optimization in the regularized kernel minimum noise fraction transformation

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2012-01-01

    Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....

  16. An optimal generic model for multi-parameters and big data optimizing: a laboratory experimental study

    Science.gov (United States)

    Utama, D. N.; Ani, N.; Iqbal, M. M.

    2018-03-01

    Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.

  17. Control parameter optimization for AP1000 reactor using Particle Swarm Optimization

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  18. Parameter Optimization and Electrode Improvement of Rotary Stepper Micromotor

    Science.gov (United States)

    Sone, Junji; Mizuma, Toshinari; Mochizuki, Shunsuke; Sarajlic, Edin; Yamahata, Christophe; Fujita, Hiroyuki

    We developed a three-phase electrostatic stepper micromotor and performed a numerical simulation to improve its performance for practical use and to optimize its design. We conducted its circuit simulation by simplifying its structure, and the effect of springback force generated by supported mechanism using flexures was considered. And we considered new improvement method for electrodes. This improvement and other parameter optimizations achieved the low voltage drive of micromotor.

  19. Complicated problem solution techniques in optimal parameter searching

    International Nuclear Information System (INIS)

    Gergel', V.P.; Grishagin, V.A.; Rogatneva, E.A.; Strongin, R.G.; Vysotskaya, I.N.; Kukhtin, V.V.

    1992-01-01

    An algorithm is presented of a global search for numerical solution of multidimentional multiextremal multicriteria optimization problems with complicated constraints. A boundedness of object characteristic changes is assumed at restricted changes of its parameters (Lipschitz condition). The algorithm was realized as a computer code. The algorithm was realized as a computer code. The programme was used to solve in practice the different applied optimization problems. 10 refs.; 3 figs

  20. Optimal Parameter Selection of Power System Stabilizer using Genetic Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Hyeng Hwan; Chung, Dong Il; Chung, Mun Kyu [Dong-AUniversity (Korea); Wang, Yong Peel [Canterbury Univeristy (New Zealand)

    1999-06-01

    In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer (PSS) with robustness in low frequency oscillation for power system using real variable elitism genetic algorithm (RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristics of PSS, the system eigenvalues criterion and the dynamic characteristics were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory. (author). 20 refs., 15 figs., 8 tabs.

  1. Optimization Design of Multi-Parameters in Rail Launcher System

    Directory of Open Access Journals (Sweden)

    Yujiao Zhang

    2014-05-01

    Full Text Available Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different parameters respectively. And the orthogonal test approach is used to guide the simulation for choosing the better parameter combinations, as well reduce the calculation cost. The research shows that the proposed method gives a better result in the energy efficiency of the system. To improve the energy conversion efficiency of electromagnetic rail launchers, the selection of more parameters must be considered in the design stage, such as the width, height and length of rail, the distance between rail pair, and pulse forming inductance. However, the relationship between these parameters and energy conversion efficiency cannot be directly described by one mathematical expression. So optimization methods must be applied to conduct design. In this paper, a rail launcher with five parameters was optimized by using orthogonal test method. According to the arrangement of orthogonal table, the better parameters’ combination can be obtained through less calculation. Under the condition of different parameters’ value, field and circuit simulation analysis were made. The results show that the energy conversion efficiency of the system is increased by 71.9 % after parameters optimization.

  2. Optimal Design of Shock Tube Experiments for Parameter Inference

    KAUST Repository

    Bisetti, Fabrizio

    2014-01-06

    We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation energies in the reaction rate expressions. The control parameters are the initial mixture composition and the temperature. The approach is based on first building a polynomial based surrogate model for the observables relevant to the shock tube experiments. Based on these surrogates, a novel MAP based approach is used to estimate the expected information gain in the proposed experiments, and to select the best experimental set-ups yielding the optimal expected information gains. The validity of the approach is tested using synthetic data generated by sampling the PC surrogate. We finally outline a methodology for validation using actual laboratory experiments, and extending experimental design methodology to the cases where the control parameters are noisy.

  3. Hidden parameters in the plasma deposition of microcrystalline silicon solar cells

    NARCIS (Netherlands)

    van den Donker, M.N.; Rech, B.; Schmitz, R.; Klomfass, J.; Dingemans, G.; Finger, F.; Houben, L.; Kessels, W.M.M.; Sanden, van de M.C.M.

    2007-01-01

    The effect of process parameters on the plasma deposition of µc-Si:H solar cells is reviewed in this article. Several in situ diagnostics are presented, which can be used to study the process stability as an additional parameter in the deposition process. The diagnostics were used to investigate the

  4. Optimal properties for coated titanium implants with the hydroxyapatite layer formed by the pulsed laser deposition technique

    Science.gov (United States)

    Himmlova, Lucia; Dostalova, Tatjana; Jelinek, Miroslav; Bartova, Jirina; Pesakova, V.; Adam, M.

    1999-02-01

    Pulsed laser deposition technique allow to 'tailor' bioceramic coat for metal implants by the change of deposition conditions. Each attribute is influenced by the several deposition parameters and each parameter change several various properties. Problem caused that many parameters has an opposite function and improvement of one property is followed by deterioration of other attribute. This study monitor influence of each single deposition parameter and evaluate its importance form the point of view of coat properties. For deposition KrF excimer laser in stainless-steel deposition chamber was used. Deposition conditions (ambient composition and pressures, metallic substrate temperature, energy density and target-substrate distance) were changed according to the film properties. A non-coated titanium implant was used as a control. Films with promising mechanical quality underwent an in vitro biological tests -- measurement of proliferation activity, observing cell interactions with macrophages, fibroblasts, testing toxicity of percolates, observing a solubility of hydroxyapatite (HA) coat. Deposition conditions corresponding with the optimal mechanical and biochemical properties are: metal temperature 490 degrees Celsius, ambient-mixture of argon and water vapor, energy density 3 Jcm-2, target-substrate distance 7.5 cm.

  5. Concurrently adjusting interrelated control parameters to achieve optimal engine performance

    Science.gov (United States)

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

    2015-12-01

    Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

  6. Quantitative optimization of solid freeform deposition of aqueous hydrogels

    International Nuclear Information System (INIS)

    Kang, K H; Hockaday, L A; Butcher, J T

    2013-01-01

    Many soft tissues exhibit complex anatomical geometry that is challenging to replicate for regenerative medicine applications. Solid freeform fabrication (SFF) has emerged as an attractive approach for creating 3D tissues, but a detailed understanding of how specific fabrication parameters affect accuracy and viability has not been established to date. In this study, we evaluate the effects of printing parameters of the Fab-Home 3D printing system on accuracy using alginate, photocrosslinkable polyethylene-glycol diacrylate (PEG-DA) and gelatin as commonly used model hydrogel materials. Print accuracy and resolution along the length, width and height were determined based on quantitative image analysis. The effects of extrusion parameters on cell viability were assessed using porcine aortic valve interstitial cells (PAVIC) as a model cell type. We observed that pressure, pathheight and pathspace all significantly affected print accuracy and resolution. Printing conditions did not affect PAVIC viability within the ranges applied. We predicted that optimal pressure, pathheight and pathspace values would be increased linearly with increasing nozzle diameter, and we confirmed that the predicted values generate accurate 3D geometries while poorly chosen parameters yield inaccurate, unpredictable geometries. This systematic optimization strategy therefore improves the accuracy of 3D printing platforms for biofabrication and tissue engineering applications. (paper)

  7. Optimization of parameters of special asynchronous electric drives

    Science.gov (United States)

    Karandey, V. Yu; Popov, B. K.; Popova, O. B.; Afanasyev, V. L.

    2018-03-01

    The article considers the solution of the problem of parameters optimization of special asynchronous electric drives. The solution of the problem will allow one to project and create special asynchronous electric drives for various industries. The created types of electric drives will have optimum mass-dimensional and power parameters. It will allow one to realize and fulfill the set characteristics of management of technological processes with optimum level of expenses of electric energy, time of completing the process or other set parameters. The received decision allows one not only to solve a certain optimizing problem, but also to construct dependences between the optimized parameters of special asynchronous electric drives, for example, with the change of power, current in a winding of the stator or rotor, induction in a gap or steel of magnetic conductors and other parameters. On the constructed dependences, it is possible to choose necessary optimum values of parameters of special asynchronous electric drives and their components without carrying out repeated calculations.

  8. Parameters influencing deposit estimation when using water sensitive papers

    Directory of Open Access Journals (Sweden)

    Emanuele Cerruto

    2013-10-01

    Full Text Available The aim of the study was to assess the possibility of using water sensitive papers (WSP to estimate the amount of deposit on the target when varying the spray characteristics. To identify the main quantities influencing the deposit, some simplifying hypotheses were applied to simulate WSP behaviour: log-normal distribution of the diameters of the drops and circular stains randomly placed on the images. A very large number (4704 of images of WSPs were produced by means of simulation. The images were obtained by simulating drops of different arithmetic mean diameter (40-300 μm, different coefficient of variation (0.1-1.5, and different percentage of covered surface (2-100%, not considering overlaps. These images were considered to be effective WSP images and then analysed using image processing software in order to measure the percentage of covered surface, the number of particles, and the area of each particle; the deposit was then calculated. These data were correlated with those used to produce the images, varying the spray characteristics. As far as the drop populations are concerned, a classification based on the volume median diameter only should be avoided, especially in case of high variability. This, in fact, results in classifying sprays with very low arithmetic mean diameter as extremely or ultra coarse. The WSP image analysis shows that the relation between simulated and computed percentage of covered surface is independent of the type of spray, whereas impact density and unitary deposit can be estimated from the computed percentage of covered surface only if the spray characteristics (arithmetic mean and coefficient of variation of the drop diameters are known. These data can be estimated by analysing the particles on the WSP images. The results of a validation test show good agreement between simulated and computed deposits, testified by a high (0.93 coefficient of determination.

  9. Comparisons of criteria in the assessment model parameter optimizations

    International Nuclear Information System (INIS)

    Liu Xinhe; Zhang Yongxing

    1993-01-01

    Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment

  10. Statistical optimization of process parameters for the production of ...

    African Journals Online (AJOL)

    In this study, optimization of process parameters such as moisture content, incubation temperature and initial pH (fixed) for the improvement of citric acid production from oil palm empty fruit bunches through solid state bioconversion was carried out using traditional one-factor-at-a-time (OFAT) method and response surface ...

  11. Optimization of physico-chemical and nutritional parameters for ...

    African Journals Online (AJOL)

    Optimization of physico-chemical and nutritional parameters for pullulan production by a mutant of thermotolerant Aureobasidium pullulans, in fed batch ... minutes, having killing rate of 70% level, produced 6 g l-1 higher pullulan as compared to the wild type without loosing thermotolerant and non-melanin producing ability.

  12. Optimization of machining parameters of hard porcelain on a CNC ...

    African Journals Online (AJOL)

    Optimization of machining parameters of hard porcelain on a CNC machine by Taguchi-and RSM method. ... Journal Home > Vol 10, No 1 (2018) > ... The conduct of experiments was made by employing the Taguchi's L27 Orthogonal array to ...

  13. Optimization of CNC end milling process parameters using PCA ...

    African Journals Online (AJOL)

    Optimization of CNC end milling process parameters using PCA-based Taguchi method. ... International Journal of Engineering, Science and Technology ... To meet the basic assumption of Taguchi method; in the present work, individual response correlations have been eliminated first by means of Principal Component ...

  14. Parameters optimization for magnetic resonance coupling wireless power transmission.

    Science.gov (United States)

    Li, Changsheng; Zhang, He; Jiang, Xiaohua

    2014-01-01

    Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.

  15. Parameter assessment for virtual Stackelberg game in aerodynamic shape optimization

    Science.gov (United States)

    Wang, Jing; Xie, Fangfang; Zheng, Yao; Zhang, Jifa

    2018-05-01

    In this paper, parametric studies of virtual Stackelberg game (VSG) are conducted to assess the impact of critical parameters on aerodynamic shape optimization, including design cycle, split of design variables and role assignment. Typical numerical cases, including the inverse design and drag reduction design of airfoil, have been carried out. The numerical results confirm the effectiveness and efficiency of VSG. Furthermore, the most significant parameters are identified, e.g. the increase of design cycle can improve the optimization results but it will also add computational burden. These studies will maximize the productivity of the effort in aerodynamic optimization for more complicated engineering problems, such as the multi-element airfoil and wing-body configurations.

  16. Automatic Measuring System for Oil Stream Paraffin Deposits Parameters

    Science.gov (United States)

    Kopteva, A. V.; Koptev, V. Yu

    2018-03-01

    This paper describes a new method for monitoring oil pipelines, as well as a highly efficient and automated paraffin deposit monitoring method. When operating oil pipelines, there is an issue of paraffin, resin and salt deposits on the pipeline walls that come with the oil stream. It ultimately results in frequent transportation suspension to clean or even replace pipes and other equipment, thus shortening operation periods between repairs, creating emergency situations and increasing production expenses, badly affecting environment, damaging ecology and spoil underground water, killing animals, birds etc. Oil spills contaminate rivers, lakes, and ground waters. Oil transportation monitoring issues are still subject for further studying. Thus, there is the need to invent a radically new automated process control and management system, together with measurement means intellectualization. The measurement principle is based on the Lambert-Beer law that describes the dependence between the gamma-radiation frequency and the density together with the linear attenuation coefficient for a substance. Using the measuring system with high accuracy (± 0,2%), one can measure the thickness of paraffin deposits with an absolute accuracy of ± 5 mm, which is sufficient to ensure reliable operation of the pipeline system. Safety is a key advantage, when using the proposed control system.

  17. 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

  18. On the effect of response transformations in sequential parameter optimization.

    Science.gov (United States)

    Wagner, Tobias; Wessing, Simon

    2012-01-01

    Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation.

  19. Optimization of synthesis conditions of PbS thin films grown by chemical bath deposition using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Yücel, Ersin, E-mail: dr.ersinyucel@gmail.com [Department of Physics, Faculty of Arts and Sciences, Mustafa Kemal University, 31034 Hatay (Turkey); Yücel, Yasin; Beleli, Buse [Department of Chemistry, Faculty of Arts and Sciences, Mustafa Kemal University, 31034 Hatay (Turkey)

    2015-09-05

    Highlights: • For the first time, RSM and CCD used for optimization of PbS thin film. • Tri-sodium citrate, deposition time and temperature were independent variables. • PbS thin film band gap value was 2.20 eV under the optimum conditions. • Quality of the film was improved after chemometrics optimization. - Abstract: In this study, PbS thin films were synthesized by chemical bath deposition (CBD) under different deposition parameters. Response surface methodology (RSM) was used to optimize synthesis parameters including amount of tri-sodium citrate (0.2–0.8 mL), deposition time (14–34 h) and deposition temperature (26.6–43.4 °C) for deposition of the films. 5-level-3-factor central composite design (CCD) was employed to evaluate effects of the deposition parameters on the response (optical band gap of the films). The significant level of both the main effects and the interaction are investigated by analysis of variance (ANOVA). The film structures were characterized by X-ray diffractometer (XRD). Morphological properties of the films were studied with a scanning electron microscopy (SEM). The optical properties of the films were investigated using a UV–visible spectrophotometer. The optimum amount of tri-sodium citrate, deposition time and deposition temperature were found to be 0.7 mL, 18.07 h and 30 °C respectively. Under these conditions, the experimental band gap of PbS was 2.20 eV, which is quite good correlation with value (1.98 eV) predicted by the model.

  20. Optimization of synthesis conditions of PbS thin films grown by chemical bath deposition using response surface methodology

    International Nuclear Information System (INIS)

    Yücel, Ersin; Yücel, Yasin; Beleli, Buse

    2015-01-01

    Highlights: • For the first time, RSM and CCD used for optimization of PbS thin film. • Tri-sodium citrate, deposition time and temperature were independent variables. • PbS thin film band gap value was 2.20 eV under the optimum conditions. • Quality of the film was improved after chemometrics optimization. - Abstract: In this study, PbS thin films were synthesized by chemical bath deposition (CBD) under different deposition parameters. Response surface methodology (RSM) was used to optimize synthesis parameters including amount of tri-sodium citrate (0.2–0.8 mL), deposition time (14–34 h) and deposition temperature (26.6–43.4 °C) for deposition of the films. 5-level-3-factor central composite design (CCD) was employed to evaluate effects of the deposition parameters on the response (optical band gap of the films). The significant level of both the main effects and the interaction are investigated by analysis of variance (ANOVA). The film structures were characterized by X-ray diffractometer (XRD). Morphological properties of the films were studied with a scanning electron microscopy (SEM). The optical properties of the films were investigated using a UV–visible spectrophotometer. The optimum amount of tri-sodium citrate, deposition time and deposition temperature were found to be 0.7 mL, 18.07 h and 30 °C respectively. Under these conditions, the experimental band gap of PbS was 2.20 eV, which is quite good correlation with value (1.98 eV) predicted by the model

  1. Optimization of virtual source parameters in neutron scattering instrumentation

    International Nuclear Information System (INIS)

    Habicht, K; Skoulatos, M

    2012-01-01

    We report on phase-space optimizations for neutron scattering instruments employing horizontal focussing crystal optics. Defining a figure of merit for a generic virtual source configuration we identify a set of optimum instrumental parameters. In order to assess the quality of the instrumental configuration we combine an evolutionary optimization algorithm with the analytical Popovici description using multidimensional Gaussian distributions. The optimum phase-space element which needs to be delivered to the virtual source by preceding neutron optics may be obtained using the same algorithm which is of general interest in instrument design.

  2. AI-guided parameter optimization in inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-10-01

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

  4. Identification of metabolic system parameters using global optimization methods

    Directory of Open Access Journals (Sweden)

    Gatzke Edward P

    2006-01-01

    Full Text Available Abstract Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA models. The estimation problem is posed as a global optimization task, for which novel techniques can be applied to determine the best set of parameter values given the measured responses of the biological system. The challenge is that this task is nonconvex. Nonetheless, deterministic optimization techniques can be used to find a global solution that best reconciles the model parameters and measurements. Specifically, the paper employs branch-and-bound principles to identify the best set of model parameters from observed time course data and illustrates this method with an existing model of the fermentation pathway in Saccharomyces cerevisiae. This is a relatively simple yet representative system with five dependent states and a total of 19 unknown parameters of which the values are to be determined. Conclusion The efficacy of the branch-and-reduce algorithm is illustrated by the S. cerevisiae example. The method described in this paper is likely to be widely applicable in the dynamic modeling of metabolic networks.

  5. Deterioration of the fuel injection parameters as a result of Common Rail injectors deposit formation

    Directory of Open Access Journals (Sweden)

    Stępień Zbigniew

    2017-01-01

    Full Text Available The article describes external and internal Common Rail injectors deposits formed in dynamometer engine simulation tests. It discussed not only the key reasons and factors influencing injector deposit formation but also the resulting way of fuel preparation and engine test approaches. The effects of external coking deposit as well as internal deposits two most common form types that is carboxylic soaps and organic amides on deterioration of the fuel injection parameters were assessed. The assessments covered both deposits impacts on quantitative and qualitative changes of the injectors diagnostic parameters and as a result on deterioration of the injector performance. Finally the comparisons between characteristic of dosage of one fuel injector before test and characteristics few injectors after engine tests of simulated deposit formation were made.

  6. Optimization of reserve lithium thionyl chloride battery electrochemical design parameters

    Energy Technology Data Exchange (ETDEWEB)

    Doddapaneni, N.; Godshall, N.A.

    1987-01-01

    The performance of Reserve Lithium Thionyl Chloride (RLTC) batteries was optimized by conducting a parametric study of seven electrochemical parameters: electrode compression, carbon thickness, presence of catalyst, temperature, electrode limitation, discharge rate, and electrolyte acidity. Increasing electrode compression (from 0 to 15%) improved battery performance significantly (10% greater carbon capacity density). Although thinner carbon cathodes yielded less absolute capacity than did thicker cathodes, they did so with considerably higher volume efficiencies. The effect of these parameters, and their synergistic interactions, on electrochemical cell peformance is illustrated. 5 refs., 9 figs., 3 tabs.

  7. Optimization of reserve lithium thionyl chloride battery electrochemical design parameters

    Science.gov (United States)

    Doddapaneni, N.; Godshall, N. A.

    The performance of Reserve Lithium Thionyl Chloride (RLTC) batteries was optimized by conducting a parametric study of seven electrochemical parameters: electrode compression, carbon thickness, presence of catalyst, temperature, electrode limitation, discharge rate, and electrolyte acidity. Increasing electrode compression (from 0 to 15 percent) improved battery performance significantly (10 percent greater carbon capacity density). Although thinner carbon cathodes yielded less absolute capacity than did thicker cathodes, they did so with considerably higher volume efficiencies. The effect of these parameters, and their synergistic interactions, on electrochemical cell performance is illustrated.

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

    Directory of Open Access Journals (Sweden)

    Bin He

    2014-01-01

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

  9. PARAMETER ESTIMATION OF VALVE STICTION USING ANT COLONY OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    S. Kalaivani

    2012-07-01

    Full Text Available In this paper, a procedure for quantifying valve stiction in control loops based on ant colony optimization has been proposed. Pneumatic control valves are widely used in the process industry. The control valve contains non-linearities such as stiction, backlash, and deadband that in turn cause oscillations in the process output. Stiction is one of the long-standing problems and it is the most severe problem in the control valves. Thus the measurement data from an oscillating control loop can be used as a possible diagnostic signal to provide an estimate of the stiction magnitude. Quantification of control valve stiction is still a challenging issue. Prior to doing stiction detection and quantification, it is necessary to choose a suitable model structure to describe control-valve stiction. To understand the stiction phenomenon, the Stenman model is used. Ant Colony Optimization (ACO, an intelligent swarm algorithm, proves effective in various fields. The ACO algorithm is inspired from the natural trail following behaviour of ants. The parameters of the Stenman model are estimated using ant colony optimization, from the input-output data by minimizing the error between the actual stiction model output and the simulated stiction model output. Using ant colony optimization, Stenman model with known nonlinear structure and unknown parameters can be estimated.

  10. Standardless quantification by parameter optimization in electron probe microanalysis

    International Nuclear Information System (INIS)

    Limandri, Silvina P.; Bonetto, Rita D.; Josa, Víctor Galván; Carreras, Alejo C.; Trincavelli, Jorge C.

    2012-01-01

    A method for standardless quantification by parameter optimization in electron probe microanalysis is presented. The method consists in minimizing the quadratic differences between an experimental spectrum and an analytical function proposed to describe it, by optimizing the parameters involved in the analytical prediction. This algorithm, implemented in the software POEMA (Parameter Optimization in Electron Probe Microanalysis), allows the determination of the elemental concentrations, along with their uncertainties. The method was tested in a set of 159 elemental constituents corresponding to 36 spectra of standards (mostly minerals) that include trace elements. The results were compared with those obtained with the commercial software GENESIS Spectrum® for standardless quantification. The quantifications performed with the method proposed here are better in the 74% of the cases studied. In addition, the performance of the method proposed is compared with the first principles standardless analysis procedure DTSA for a different data set, which excludes trace elements. The relative deviations with respect to the nominal concentrations are lower than 0.04, 0.08 and 0.35 for the 66% of the cases for POEMA, GENESIS and DTSA, respectively. - Highlights: ► A method for standardless quantification in EPMA is presented. ► It gives better results than the commercial software GENESIS Spectrum. ► It gives better results than the software DTSA. ► It allows the determination of the conductive coating thickness. ► It gives an estimation for the concentration uncertainties.

  11. Optimizing cathodic electrodeposition parameters of ceria coating to enhance the oxidation resistance of a Cr{sub 2}O{sub 3}-forming alloy

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xu, E-mail: xuw388@mail.usask.ca; Fan, Fan; Szpunar, Jerzy A.

    2016-07-29

    Nano-ceria coating was deposited onto a chromium oxide forming alloy through galvanostatic cathodic electro-deposition method in cerium nitrate electrolyte. The electrochemical behavior and influence of main deposition parameters of current density, deposition time, and temperature were studied. It was seen that the crystal size decreased with increasing of current density while micro-cracks were also observed at higher current density. Slightly increasing of crystal size and smoothing of surface morphology were seen with increasing of deposition time. It was reported that the bath temperature has the most significant effect on crystal size and surface morphology of the deposit. Green rust as corrosion product was also observed with deposition temperatures higher than 35 °C. Optimized deposition parameters were used to produce homogeneous, continuous and green rust-free coatings which enhance the oxidation resistance of alloy 230. The electro-deposition process was found to be an accessible and efficient method to prepare nano-crystalline ceria coating. - Highlights: • Electrodeposition was used to make ceria coating on a chromium oxide forming alloy; • Deposition parameters of current density, time and temperature were investigated; • Crystal size and morphology of coating vary with changing of deposition parameters; • Coating prepared with optimized parameters reduced oxidation rate of alloy 230.

  12. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

    Directory of Open Access Journals (Sweden)

    Rupert Faltermeier

    2015-01-01

    Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

  13. Structural parameter optimization design for Halbach permanent maglev rail

    International Nuclear Information System (INIS)

    Guo, F.; Tang, Y.; Ren, L.; Li, J.

    2010-01-01

    Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.

  14. Structural parameter optimization design for Halbach permanent maglev rail

    Energy Technology Data Exchange (ETDEWEB)

    Guo, F., E-mail: guofang19830119@163.co [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China); Tang, Y.; Ren, L.; Li, J. [R and D Center of Applied Superconductivity, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2010-11-01

    Maglev rail is an important part of the magnetic levitation launch system. Reducing the manufacturing cost of magnetic levitation rail is the key problem for the development of magnetic levitation launch system. The Halbach permanent array has an advantage that the fundamental spatial field is cancelled on one side of the array while the field on the other side is enhanced. So this array used in the design of high temperature superconducting permanent maglev rail could improve the surface magnetic field and the levitation force. In order to make the best use of Nd-Fe-B (NdFeB) material and reduce the cost of maglev rail, the effect of the rail's structural parameters on levitation force and the utilization rate of NdFeB material are analyzed. The optimal ranges of these structural parameters are obtained. The mutual impact of these parameters is also discussed. The optimization method of these structure parameters is proposed at the end of this paper.

  15. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

    Science.gov (United States)

    Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

    2015-01-01

    Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

  16. Density-based penalty parameter optimization on C-SVM.

    Science.gov (United States)

    Liu, Yun; Lian, Jie; Bartolacci, Michael R; Zeng, Qing-An

    2014-01-01

    The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.

  17. Optimization of cladding parameters for resisting corrosion on low carbon steels using simulated annealing algorithm

    Science.gov (United States)

    Balan, A. V.; Shivasankaran, N.; Magibalan, S.

    2018-04-01

    Low carbon steels used in chemical industries are frequently affected by corrosion. Cladding is a surfacing process used for depositing a thick layer of filler metal in a highly corrosive materials to achieve corrosion resistance. Flux cored arc welding (FCAW) is preferred in cladding process due to its augmented efficiency and higher deposition rate. In this cladding process, the effect of corrosion can be minimized by controlling the output responses such as minimizing dilution, penetration and maximizing bead width, reinforcement and ferrite number. This paper deals with the multi-objective optimization of flux cored arc welding responses by controlling the process parameters such as wire feed rate, welding speed, Nozzle to plate distance, welding gun angle for super duplex stainless steel material using simulated annealing technique. Regression equation has been developed and validated using ANOVA technique. The multi-objective optimization of weld bead parameters was carried out using simulated annealing to obtain optimum bead geometry for reducing corrosion. The potentiodynamic polarization test reveals the balanced formation of fine particles of ferrite and autenite content with desensitized nature of the microstructure in the optimized clad bead.

  18. Optimization of plasma flow parameters of the magnetoplasma compressor

    International Nuclear Information System (INIS)

    Dojcinovic, I P; Kuraica, M M; Obradovc, B M; Cvetanovic, N; Puric, J

    2007-01-01

    Optimization of the working conditions of the magnetoplasma compressor (MPC) has been performed through analysing discharge and compression plasma flow parameters in hydrogen, nitrogen and argon at different pressures. Energy conversion rate, volt-ampere curve exponent and plasma flow velocities have been studied to optimize the efficiency of energy transfer from the supply source to the plasma. It has been found that the most effective energy transfer from the supply to the plasma is in hydrogen as a working gas at 1000 Pa pressure. It was found that the accelerating regime exists for hydrogen up to 3000 Pa pressures, in nitrogen up to 2000 Pa and in argon up to 1000 Pa pressure. At higher pressures MPC in all the gases works in the decelerating regime. At pressures lower than 200 Pa, high cathode erosion is observed. MPC plasma flow parameter optimization is very important because this plasma accelerating system may be of special interest for solid surface modification and other technology applications

  19. Measurements of dry-deposition parameters for the California acid-deposition monitoring program. Final report

    International Nuclear Information System (INIS)

    Watson, J.G.; Chow, J.C.; Egami, R.T.; Bowen, J.L.; Frazier, C.A.

    1991-06-01

    The State of California monitors the concentrations of acidic gases and particles at 10 sites throughout the state. Seven sites represent urban areas (South Coast Air Basin - three sites, San Francisco Bay Area, Bakersfield, Santa Barbara, and Sacramento) and three represent forested areas (Sequoia National Park, Yosemite National Park, and Gasquet). Several sites are collocated with monitoring instruments for other air quality and forest response networks. Continuous monitors for the dry deposition network collect hourly average values for ozone, wind speed, wind direction, atmospheric stability, temperature, dew point, time of wetness, and solar radiation. A newly-designed gas/particle sampler collects daytime (6 a.m. to 6 p.m.) and nighttime (6 p.m. to 6 a.m.) samples every sixth day for sulfur dioxide, ammonia, nitrogen dioxide, and nitric acid. Particles are collected on the same day/night schedule in PM(10) and PM(2.5) size ranges, and are analyzed for mass, sulfate, nitrate, chloride, ammonium, sodium, magnesium, potassium, and calcium ions. The sampling schedule follows the regulatory schedule adopted by the EPA and ARB for suspended particulate matter. Wet deposition data are collected at or nearby the dry deposition stations. The first year of the monitoring program included installation of the network, training of technicians, acquisition and validation of data, and transfer of the sampling and analysis technology to Air Resources Board operating divisions. Data have been validated and stored for the period May, 1988 through September, 1989

  20. 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

    Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle

  1. Optimization of geometric parameters of heat exchange pipes pin finning

    Science.gov (United States)

    Akulov, K. A.; Golik, V. V.; Voronin, K. S.; Zakirzakov, A. G.

    2018-05-01

    The work is devoted to optimization of geometric parameters of the pin finning of heat-exchanging pipes. Pin fins were considered from the point of view of mechanics of a deformed solid body as overhang beams with a uniformly distributed load. It was found out under what geometric parameters of the nib (diameter and length); the stresses in it from the influence of the washer fluid will not exceed the yield strength of the material (aluminum). Optimal values of the geometric parameters of nibs were obtained for different velocities of the medium washed by them. As a flow medium, water and air were chosen, and the cross section of the nibs was round and square. Pin finning turned out to be more than 3 times more compact than circumferential finning, so its use makes it possible to increase the number of fins per meter of the heat-exchanging pipe. And it is well-known that this is the main method for increasing the heat transfer of a convective surface, giving them an indisputable advantage.

  2. Optimization of vibratory welding process parameters using response surface methodology

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Pravin Kumar; Kumar, S. Deepak; Patel, D.; Prasad, S. B. [National Institute of Technology Jamshedpur, Jharkhand (India)

    2017-05-15

    The current investigation was carried out to study the effect of vibratory welding technique on mechanical properties of 6 mm thick butt welded mild steel plates. A new concept of vibratory welding technique has been designed and developed which is capable to transfer vibrations, having resonance frequency of 300 Hz, into the molten weld pool before it solidifies during the Shielded metal arc welding (SMAW) process. The important process parameters of vibratory welding technique namely welding current, welding speed and frequency of the vibrations induced in molten weld pool were optimized using Taguchi’s analysis and Response surface methodology (RSM). The effect of process parameters on tensile strength and hardness were evaluated using optimization techniques. Applying RSM, the effect of vibratory welding parameters on tensile strength and hardness were obtained through two separate regression equations. Results showed that, the most influencing factor for the desired tensile strength and hardness is frequency at its resonance value, i.e. 300 Hz. The micro-hardness and microstructures of the vibratory welded joints were studied in detail and compared with those of conventional SMAW joints. Comparatively, uniform and fine grain structure has been found in vibratory welded joints.

  3. Optimization of cutting parameters for machining time in turning process

    Science.gov (United States)

    Mavliutov, A. R.; Zlotnikov, E. G.

    2018-03-01

    This paper describes the most effective methods for nonlinear constraint optimization of cutting parameters in the turning process. Among them are Linearization Programming Method with Dual-Simplex algorithm, Interior Point method, and Augmented Lagrangian Genetic Algorithm (ALGA). Every each of them is tested on an actual example – the minimization of production rate in turning process. The computation was conducted in the MATLAB environment. The comparative results obtained from the application of these methods show: The optimal value of the linearized objective and the original function are the same. ALGA gives sufficiently accurate values, however, when the algorithm uses the Hybrid function with Interior Point algorithm, the resulted values have the maximal accuracy.

  4. Optimal CT scanning parameters for commonly used tumor ablation applicators

    International Nuclear Information System (INIS)

    Eltorai, Adam E.M.; Baird, Grayson L.; Monu, Nicholas; Wolf, Farrah; Seidler, Michael; Collins, Scott; Kim, Jeomsoon; Dupuy, Damian E.

    2017-01-01

    Highlights: • This study aimed to determine optimal scanning parameters for commonly-used tumor ablation applicators. • The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance. • Optimum combinations for each probe are provided. - Abstract: Purpose: CT-beam hardening artifact can make tumor margin visualization and its relationship to the ablation applicator tip challenging. To determine optimal scanning parameters for commonly-used applicators. Materials and methods: Applicators were placed in ex-vivo cow livers with implanted mock tumors, surrounded by bolus gel. Various CT scans were performed at 440 mA with 5 mm thickness changing kVp, scan time, ASiR, scan type, pitch, and reconstruction algorithm. Four radiologists blindly scored the images for image quality and artifact quantitatively. Results: A significant relationship between probe, kVp level, ASiR level, and reconstruction algorithm was observed concerning both image artifact and image quality (both p = <0.0001). Specifically, there are certain combinations of kVp, ASiR, and reconstruction algorithm that yield better images than other combinations. In particular, one probe performed equivalently or better than any competing probe considered here, regardless of kVp, ASiR, and reconstruction algorithm combination. Conclusion: The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance for a certain combinations of kVp, ASiR, reconstruction algorithm and probes at their disposal. Optimum combinations for each probe are provided.

  5. Optimal CT scanning parameters for commonly used tumor ablation applicators

    Energy Technology Data Exchange (ETDEWEB)

    Eltorai, Adam E.M. [Warren Alpert Medical School of Brown University (United States); Baird, Grayson L. [Department of Diagnostic Imaging (United States); Warren Alpert Medical School of Brown University (United States); Lifespan Biostatistics Core (United States); Rhode Island Hospital (United States); Monu, Nicholas; Wolf, Farrah; Seidler, Michael [Department of Diagnostic Imaging (United States); Warren Alpert Medical School of Brown University (United States); Rhode Island Hospital (United States); Collins, Scott [Department of Diagnostic Imaging (United States); Rhode Island Hospital (United States); Kim, Jeomsoon [Department of Medical Physics (United States); Rhode Island Hospital (United States); Dupuy, Damian E., E-mail: ddupuy@comcast.net [Department of Diagnostic Imaging (United States); Warren Alpert Medical School of Brown University (United States); Rhode Island Hospital (United States)

    2017-04-15

    Highlights: • This study aimed to determine optimal scanning parameters for commonly-used tumor ablation applicators. • The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance. • Optimum combinations for each probe are provided. - Abstract: Purpose: CT-beam hardening artifact can make tumor margin visualization and its relationship to the ablation applicator tip challenging. To determine optimal scanning parameters for commonly-used applicators. Materials and methods: Applicators were placed in ex-vivo cow livers with implanted mock tumors, surrounded by bolus gel. Various CT scans were performed at 440 mA with 5 mm thickness changing kVp, scan time, ASiR, scan type, pitch, and reconstruction algorithm. Four radiologists blindly scored the images for image quality and artifact quantitatively. Results: A significant relationship between probe, kVp level, ASiR level, and reconstruction algorithm was observed concerning both image artifact and image quality (both p = <0.0001). Specifically, there are certain combinations of kVp, ASiR, and reconstruction algorithm that yield better images than other combinations. In particular, one probe performed equivalently or better than any competing probe considered here, regardless of kVp, ASiR, and reconstruction algorithm combination. Conclusion: The findings illustrate the overall interaction of the effects of kVp, ASiR, and reconstruction algorithm within and between probes, so that radiologists may easily reference optimal imaging performance for a certain combinations of kVp, ASiR, reconstruction algorithm and probes at their disposal. Optimum combinations for each probe are provided.

  6. Standardless quantification by parameter optimization in electron probe microanalysis

    Energy Technology Data Exchange (ETDEWEB)

    Limandri, Silvina P. [Instituto de Fisica Enrique Gaviola (IFEG), CONICET (Argentina); Facultad de Matematica, Astronomia y Fisica, Universidad Nacional de Cordoba, Medina Allende s/n, (5016) Cordoba (Argentina); Bonetto, Rita D. [Centro de Investigacion y Desarrollo en Ciencias Aplicadas Dr. Jorge Ronco (CINDECA), CONICET, 47 Street 257, (1900) La Plata (Argentina); Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 1 and 47 Streets (1900) La Plata (Argentina); Josa, Victor Galvan; Carreras, Alejo C. [Instituto de Fisica Enrique Gaviola (IFEG), CONICET (Argentina); Facultad de Matematica, Astronomia y Fisica, Universidad Nacional de Cordoba, Medina Allende s/n, (5016) Cordoba (Argentina); Trincavelli, Jorge C., E-mail: trincavelli@famaf.unc.edu.ar [Instituto de Fisica Enrique Gaviola (IFEG), CONICET (Argentina); Facultad de Matematica, Astronomia y Fisica, Universidad Nacional de Cordoba, Medina Allende s/n, (5016) Cordoba (Argentina)

    2012-11-15

    A method for standardless quantification by parameter optimization in electron probe microanalysis is presented. The method consists in minimizing the quadratic differences between an experimental spectrum and an analytical function proposed to describe it, by optimizing the parameters involved in the analytical prediction. This algorithm, implemented in the software POEMA (Parameter Optimization in Electron Probe Microanalysis), allows the determination of the elemental concentrations, along with their uncertainties. The method was tested in a set of 159 elemental constituents corresponding to 36 spectra of standards (mostly minerals) that include trace elements. The results were compared with those obtained with the commercial software GENESIS Spectrum Registered-Sign for standardless quantification. The quantifications performed with the method proposed here are better in the 74% of the cases studied. In addition, the performance of the method proposed is compared with the first principles standardless analysis procedure DTSA for a different data set, which excludes trace elements. The relative deviations with respect to the nominal concentrations are lower than 0.04, 0.08 and 0.35 for the 66% of the cases for POEMA, GENESIS and DTSA, respectively. - Highlights: Black-Right-Pointing-Pointer A method for standardless quantification in EPMA is presented. Black-Right-Pointing-Pointer It gives better results than the commercial software GENESIS Spectrum. Black-Right-Pointing-Pointer It gives better results than the software DTSA. Black-Right-Pointing-Pointer It allows the determination of the conductive coating thickness. Black-Right-Pointing-Pointer It gives an estimation for the concentration uncertainties.

  7. Optimization of some electrochemical etching parameters for cellulose derivatives

    International Nuclear Information System (INIS)

    Chowdhury, Annis; Gammage, R.B.

    1978-01-01

    Electrochemical etching of fast neutron induced recoil particle tracks in cellulose derivatives and other polymers provides an inexpensive and sensitive means of fast neutron personnel dosimetry. A study of the shape, clarity, and size of the tracks in Transilwrap polycarbonate indicated that the optimum normality of the potassium hydroxide etching solution is 9 N. Optimizations have also been attempted for cellulose nitrate, triacetate, and acetobutyrate with respect to such electrochemical etching parameters as frequency, voltage gradient, and concentration of the etching solution. The measurement of differential leakage currents between the undamaged and the neutron damaged foils aided in the selection of optimum frequencies. (author)

  8. Robust Optimization for Household Load Scheduling with Uncertain Parameters

    Directory of Open Access Journals (Sweden)

    Jidong Wang

    2018-04-01

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

  9. Parameters influencing the deposition of methylammonium lead halide iodide in hole conductor free perovskite-based solar cells

    Science.gov (United States)

    Cohen, Bat-El; Gamliel, Shany; Etgar, Lioz

    2014-08-01

    Perovskite is a promising light harvester for use in photovoltaic solar cells. In recent years, the power conversion efficiency of perovskite solar cells has been dramatically increased, making them a competitive source of renewable energy. An important parameter when designing high efficiency perovskite-based solar cells is the perovskite deposition, which must be performed to create complete coverage and optimal film thickness. This paper describes an in-depth study on two-step deposition, separating the perovskite deposition into two precursors. The effects of spin velocity, annealing temperature, dipping time, and methylammonium iodide concentration on the photovoltaic performance are studied. Observations include that current density is affected by changing the spin velocity, while the fill factor changes mainly due to the dipping time and methylammonium iodide concentration. Interestingly, the open circuit voltage is almost unaffected by these parameters. Hole conductor free perovskite solar cells are used in this work, in order to minimize other possible effects. This study provides better understanding and control over the perovskite deposition through highly efficient, low-cost perovskite-based solar cells.

  10. Parameters influencing the deposition of methylammonium lead halide iodide in hole conductor free perovskite-based solar cells

    International Nuclear Information System (INIS)

    Cohen, Bat-El; Gamliel, Shany; Etgar, Lioz

    2014-01-01

    Perovskite is a promising light harvester for use in photovoltaic solar cells. In recent years, the power conversion efficiency of perovskite solar cells has been dramatically increased, making them a competitive source of renewable energy. An important parameter when designing high efficiency perovskite-based solar cells is the perovskite deposition, which must be performed to create complete coverage and optimal film thickness. This paper describes an in-depth study on two-step deposition, separating the perovskite deposition into two precursors. The effects of spin velocity, annealing temperature, dipping time, and methylammonium iodide concentration on the photovoltaic performance are studied. Observations include that current density is affected by changing the spin velocity, while the fill factor changes mainly due to the dipping time and methylammonium iodide concentration. Interestingly, the open circuit voltage is almost unaffected by these parameters. Hole conductor free perovskite solar cells are used in this work, in order to minimize other possible effects. This study provides better understanding and control over the perovskite deposition through highly efficient, low-cost perovskite-based solar cells

  11. Optimal bank portfolio choice under fixed-rate deposit insurance

    OpenAIRE

    Anlong Li

    1991-01-01

    An analysis of the investment decisions of a bank whose deposits are fully insured under fixed-rate insurance, showing how banks dynamically adjust their investment portfolios in response to market information and how this flexibility affects both investment decisions and the fair cost of deposit insurance.

  12. Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves

    Science.gov (United States)

    Tarano, Ana; Mathias, Donovan; Wheeler, Lorien; Close, Sigrid

    2018-01-01

    An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment.

  13. Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO

    Directory of Open Access Journals (Sweden)

    Adel Taieb

    2017-01-01

    Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.

  14. Acoustical characterization and parameter optimization of polymeric noise control materials

    Science.gov (United States)

    Homsi, Emile N.

    2003-10-01

    The sound transmission loss (STL) characteristics of polymer-based materials are considered. Analytical models that predict, characterize and optimize the STL of polymeric materials, with respect to physical parameters that affect performance, are developed for single layer panel configuration and adapted for layered panel construction with homogenous core. An optimum set of material parameters is selected and translated into practical applications for validation. Sound attenuating thermoplastic materials designed to be used as barrier systems in the automotive and consumer industries have certain acoustical characteristics that vary in function of the stiffness and density of the selected material. The validity and applicability of existing theory is explored, and since STL is influenced by factors such as the surface mass density of the panel's material, a method is modified to improve STL performance and optimize load-bearing attributes. An experimentally derived function is applied to the model for better correlation. In-phase and out-of-phase motion of top and bottom layers are considered. It was found that the layered construction of the co-injection type would exhibit fused planes at the interface and move in-phase. The model for the single layer case is adapted to the layered case where it would behave as a single panel. Primary physical parameters that affect STL are identified and manipulated. Theoretical analysis is linked to the resin's matrix attribute. High STL material with representative characteristics is evaluated versus standard resins. It was found that high STL could be achieved by altering materials' matrix and by integrating design solution in the low frequency range. A suggested numerical approach is described for STL evaluation of simple and complex geometries. In practice, validation on actual vehicle systems proved the adequacy of the acoustical characterization process.

  15. Low-pressure chemical vapour deposition of LiCoO2 thin films: a systematic investigation of the deposition parameters

    NARCIS (Netherlands)

    Oudenhoven, J.F.M.; Dongen, van T.; Niessen, R.A.H.; Croon, de M.H.J.M.; Notten, P.H.L.

    2009-01-01

    The feasibility of volatile precursor low-pressure chemical vapor deposition (LPCVD) for the production of LiCoO2 cathodes for all solid-state microbatteries was examined. To test this feasibility, and gain insight into the deposition behavior, the influence of the deposition parameters on the

  16. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

    CERN Document Server

    Patan, Maciej

    2012-01-01

    Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...

  17. Microbial alkaline proteases: Optimization of production parameters and their properties

    Directory of Open Access Journals (Sweden)

    Kanupriya Miglani Sharma

    2017-06-01

    Full Text Available Proteases are hydrolytic enzymes capable of degrading proteins into small peptides and amino acids. They account for nearly 60% of the total industrial enzyme market. Proteases are extensively exploited commercially, in food, pharmaceutical, leather and detergent industry. Given their potential use, there has been renewed interest in the discovery of proteases with novel properties and a constant thrust to optimize the enzyme production. This review summarizes a fraction of the enormous reports available on various aspects of alkaline proteases. Diverse sources for isolation of alkaline protease producing microorganisms are reported. The various nutritional and environmental parameters affecting the production of alkaline proteases in submerged and solid state fermentation are described. The enzymatic and physicochemical properties of alkaline proteases from several microorganisms are discussed which can help to identify enzymes with high activity and stability over extreme pH and temperature, so that they can be developed for industrial applications.

  18. Optimization-based particle filter for state and parameter estimation

    Institute of Scientific and Technical Information of China (English)

    Li Fu; Qi Fei; Shi Guangming; Zhang Li

    2009-01-01

    In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

  19. OPTIMIZATION OF OPERATION PARAMETERS OF 80-KEV ELECTRON GUN

    Directory of Open Access Journals (Sweden)

    JEONG DONG KIM

    2014-06-01

    As a first step, the electron generator of an 80-keV electron gun was manufactured. In order to produce the high beam power from electron linear accelerator, a proper beam current is required form the electron generator. In this study, the beam current was measured by evaluating the performance of the electron generator. The beam current was determined by five parameters: high voltage at the electron gun, cathode voltage, pulse width, pulse amplitude, and bias voltage at the grid. From the experimental results under optimal conditions, the high voltage was determined to be 80 kV, the pulse width was 500 ns, and the cathode voltage was from 4.2 V to 4.6 V. The beam current was measured as 1.9 A at maximum. These results satisfy the beam current required for the operation of an electron linear accelerator.

  20. Investigation of effect of process parameters on multilayer builds by direct metal deposition

    International Nuclear Information System (INIS)

    Amine, Tarak; Newkirk, Joseph W.; Liou, Frank

    2014-01-01

    Multilayer direct laser deposition (DLD) is a fabrication process through which parts are fabricated by creating a molten pool into which metal powder is injected as. During fabrication, complex thermal activity occurs in different regions of the build; for example, newly deposited layers will reheat previously deposited layers. The objective of this study was to provide insight into the thermal activity that occurs during the DLD process. This work focused on the effect of the deposition parameters of deposited layers on the microstructure and mechanical properties of the previously deposited layers. It is important to characterize these effects in order to provide information for proper parameter selection in future DLD fabrication. Varying the parameters was shown to produce different effects on the microstructure morphology and property values, presumably resulting from in-situ quench and tempering of the steels. In general, the microstructure was secondary dendrite arm spacing. Typically, both the travel speed and laser power significantly affect the microstructure and hardness. A commercial ABAQUS/CAE software was used to model this process by developing a thermo-mechanical 3D finite element model. This work presents a 3D heat transfer model that considers the continuous addition of mass in front of a moving laser beam using ABAQUS/CAE software. The model assumes the deposit geometry appropriate to each experimental condition and calculates the temperature distribution, cooling rates and re-melted layer depth, which can affect the final microstructure. Model simulations were qualitatively compared with experimental results acquired in situ using a K-type thermocouple. - Highlights: • Direct laser deposition DLD. • Microstructure of stainless steel 316L. • Thermocouples measurement. • 3D finite element modeling

  1. High Temperature Epoxy Foam: Optimization of Process Parameters

    Directory of Open Access Journals (Sweden)

    Samira El Gazzani

    2016-06-01

    Full Text Available For many years, reduction of fuel consumption has been a major aim in terms of both costs and environmental concerns. One option is to reduce the weight of fuel consumers. For this purpose, the use of a lightweight material based on rigid foams is a relevant choice. This paper deals with a new high temperature epoxy expanded material as substitution of phenolic resin, classified as potentially mutagenic by European directive Reach. The optimization of thermoset foam depends on two major parameters, the reticulation process and the expansion of the foaming agent. Controlling these two phenomena can lead to a fully expanded and cured material. The rheological behavior of epoxy resin is studied and gel time is determined at various temperatures. The expansion of foaming agent is investigated by thermomechanical analysis. Results are correlated and compared with samples foamed in the same temperature conditions. The ideal foaming/gelation temperature is then determined. The second part of this research concerns the optimization of curing cycle of a high temperature trifunctional epoxy resin. A two-step curing cycle was defined by considering the influence of different curing schedules on the glass transition temperature of the material. The final foamed material has a glass transition temperature of 270 °C.

  2. Laser Processing of Multilayered Thermal Spray Coatings: Optimal Processing Parameters

    Science.gov (United States)

    Tewolde, Mahder; Zhang, Tao; Lee, Hwasoo; Sampath, Sanjay; Hwang, David; Longtin, Jon

    2017-12-01

    Laser processing offers an innovative approach for the fabrication and transformation of a wide range of materials. As a rapid, non-contact, and precision material removal technology, lasers are natural tools to process thermal spray coatings. Recently, a thermoelectric generator (TEG) was fabricated using thermal spray and laser processing. The TEG device represents a multilayer, multimaterial functional thermal spray structure, with laser processing serving an essential role in its fabrication. Several unique challenges are presented when processing such multilayer coatings, and the focus of this work is on the selection of laser processing parameters for optimal feature quality and device performance. A parametric study is carried out using three short-pulse lasers, where laser power, repetition rate and processing speed are varied to determine the laser parameters that result in high-quality features. The resulting laser patterns are characterized using optical and scanning electron microscopy, energy-dispersive x-ray spectroscopy, and electrical isolation tests between patterned regions. The underlying laser interaction and material removal mechanisms that affect the feature quality are discussed. Feature quality was found to improve both by using a multiscanning approach and an optional assist gas of air or nitrogen. Electrically isolated regions were also patterned in a cylindrical test specimen.

  3. Optimization of Robotic Spray Painting process Parameters using Taguchi Method

    Science.gov (United States)

    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.

  4. Real parameter optimization by an effective differential evolution algorithm

    Directory of Open Access Journals (Sweden)

    Ali Wagdy Mohamed

    2013-03-01

    Full Text Available This paper introduces an Effective Differential Evolution (EDE algorithm for solving real parameter optimization problems over continuous domain. The proposed algorithm proposes a new mutation rule based on the best and the worst individuals among the entire population of a particular generation. The mutation rule is combined with the basic mutation strategy through a linear decreasing probability rule. The proposed mutation rule is shown to promote local search capability of the basic DE and to make it faster. Furthermore, a random mutation scheme and a modified Breeder Genetic Algorithm (BGA mutation scheme are merged to avoid stagnation and/or premature convergence. Additionally, the scaling factor and crossover of DE are introduced as uniform random numbers to enrich the search behavior and to enhance the diversity of the population. The effectiveness and benefits of the proposed modifications used in EDE has been experimentally investigated. Numerical experiments on a set of bound-constrained problems have shown that the new approach is efficient, effective and robust. The comparison results between the EDE and several classical differential evolution methods and state-of-the-art parameter adaptive differential evolution variants indicate that the proposed EDE algorithm is competitive with , and in some cases superior to, other algorithms in terms of final solution quality, efficiency, convergence rate, and robustness.

  5. OPTIMIZATION OF DYEING PARAMETERS TO DYE COTTON WITH CARROT EXTRACTION

    Directory of Open Access Journals (Sweden)

    MIRALLES Verónica

    2017-05-01

    Full Text Available Natural dyes derived from flora and fauna are believed to be safe because of non-toxic, non-carcinogenic and biodegradable nature. Furthermore, natural dyes do not cause pollution and waste water problems. Natural dyes as well as synthetic dyes need the optimum parameters to get a good dyeing. On some occasions, It is necessary the use of mordants to increase the affinity between cellulose fiber and natural dye, but there are other conditions to optimize in the dyeing process, like time, temperature, auxiliary porducts, etc. In addition, the optimum conditions are different depends on the type of dye and the fiber nature. The aim of this work is the use of carrot extract to dye cotton fabric by exhaustion at diverse dyeing conditions. Diffferent dyeing processes were carried out to study the effect of pH condition and the temperature, using 7, 6 and 4 pH values and 95 ºC and 130ºC for an hour. As a result some images of dyed samples are shown. Moreover, to evaluate the colour of each sample CIELAB parameters are analysed obtained by reflexion spectrophotometre. The results showed that the temperature used has an important influence on the colour of the dyed sample.

  6. Robust fluence map optimization via alternating direction method of multipliers with empirical parameter optimization

    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)

  7. OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS

    Directory of Open Access Journals (Sweden)

    Olga Sergeevna Khalyutina

    2017-01-01

    Full Text Available Traditionally, the problem of autonomous navigation is solved by dead reckoning navigation flight parameters (NFP of the aircraft (AC. With increasing requirements to accuracy of definition NFP improved the sensors of the prima- ry navigation information: gyroscopes and accelerometers. the gyroscopes of a new type, the so-called solid-state wave gyroscopes (SSVG are currently developed and put into practice. The work deals with the problem of increasing the accu- racy of measurements of angular velocity of the hemispherical resonator gyroscope (HRG. The reduction in the accuracy characteristics of HRG is caused by the presence of defects in the distribution of mass in the volume of its design. The syn- thesis of control system for optimal damping of the distortion parameters of the standing wave due to the influence of the mass defect resonator is adapted. The research challenge was: to examine and analytically offset the impact of the standing wave (amplitude and frequency parameters defect. Research was performed by mathematical modeling in the environment of SolidWorks Simulation for the case when the characteristics of the sensitive element of the HRG met the technological drawings of a particular type of resonator. The method of the inverse dynamics was chosen for synthesis. The research re- sults are presented in graphs the amplitude-frequency characteristics (AFC of the resonator output signal. Simulation was performed for the cases: the perfect distribution of weight; the presence of the mass defect; the presence of the mass defects are shown using the synthesized control action. Evaluating the effectiveness of the proposed control algorithm is deter- mined by the results of the resonator output signal simulation provided the perfect constructive and its performance in the presence of a mass defect in it. It is assumed that the excitation signals are standing waves in the two cases are identical in both amplitude and frequency. In this

  8. Choice of optimal parameters for the superconductive quantum magnetometer

    Energy Technology Data Exchange (ETDEWEB)

    Vasiliev, B V; Ivanenko, A I; Trofimov, V N

    1974-12-31

    The problem of choosing the optimal coupling coefficient and optimal working frequency for superconductive quantum magnetometer is considered. The present experimental signalnoise dependence confirms the drawn conclusions. (auth)

  9. Plasma enhanced chemical vapor deposition silicon oxynitride optimized for application in integrated optics

    NARCIS (Netherlands)

    Worhoff, Kerstin; Driessen, A.; Lambeck, Paul; Hilderink, L.T.H.; Linders, Petrus W.C.; Popma, T.J.A.

    1999-01-01

    Silicon Oxynitride layers are grown from SiH4/N2, NH3 and N2O by Plasma Enhanced Chemical Vapor Deposition. The process is optimized with respect to deposition of layers with excellent uniformity in the layer thickness, high homogeneity of the refractive index and good reproducibility of the layer

  10. Effect of Processing Parameters on Performance of Spray-Deposited Organic Thin-Film Transistors

    Directory of Open Access Journals (Sweden)

    Jack W. Owen

    2011-01-01

    Full Text Available The performance of organic thin-film transistors (OTFTs is often strongly dependent on the fabrication procedure. In this study, we fabricate OTFTs of soluble small-molecule organic semiconductors by spray-deposition and explore the effect of processing parameters on film morphology and device mobility. In particular, we report on the effect of the nature of solvent, the pressure of the carrier gas used in deposition, and the spraying distance. We investigate the surface morphology using scanning force microscopy and show that the molecules pack along the π-stacking direction, which is the preferred charge transport direction. Our results demonstrate that we can tune the field-effect mobility of spray-deposited devices two orders of magnitude, from 10−3 cm2/Vs to 10−1 cm2/Vs, by controlling fabrication parameters.

  11. Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

    Science.gov (United States)

    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.

  12. Estimation of Genetic Parameters for Fat Deposition and Carcass Traits in Broilers

    NARCIS (Netherlands)

    Zerehdaran, S.; Vereijken, A.L.J.; Arendonk, van J.A.M.; Waaij, van der E.H.

    2004-01-01

    Abdominal and subcutaneous fat are regarded as the main sources of waste in the slaughterhouse. Fat stored intramuscularly is regarded a favorite trait related to meat quality. The objective of current study was to estimate genetic parameters for fat deposition in the 3 different parts of body and

  13. Deposition and characterization of CuInSe{sub 2} films for solar cells using an optimized chemical route

    Energy Technology Data Exchange (ETDEWEB)

    Berruet, M. [Division Corrosion, INTEMA, CONICET, Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, B7608FDQ Mar del Plata (Argentina); Schreiner, W.H. [Laboratorio de Superficies e Interfases, Departamento de Fisica, Universidade Federal do Parana, 81531-990 Curitiba, PR (Brazil); Cere, S. [Division Corrosion, INTEMA, CONICET, Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, B7608FDQ Mar del Plata (Argentina); Vazquez, M., E-mail: mvazquez@fi.mdp.edu.ar [Division Corrosion, INTEMA, CONICET, Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, B7608FDQ Mar del Plata (Argentina)

    2011-02-10

    Research highlights: > CuInSe{sub 2} has been deposited on glass by optimizing some parameters in the SILAR method. > Renewing the precursors after 40 cycles improves the composition of the deposit. > Photoelectrochemical tests and Mott-Schottky analysis confirm p-type conduction. > The quality of the material shows potential for application in solar cell devices. - Abstract: CuInSe{sub 2} (CISe) thin films have been deposited on glass using successive ionic layer adsorption and reaction (SILAR). The as-deposited films are treated at 400 deg. C in argon atmosphere and etched in KCN solution to remove detrimental secondary phases. The preparation and temperature of the precursor solutions, the duration of the reaction cycles and the duration of the annealing stage have been optimized. The films have been characterized employing grazing incident X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy and energy dispersive scanning spectroscopy. Relevant semiconductor parameters have been calculated. Photoelectrochemical tests confirm p-type conduction. The films are crystalline and the stoichiometry can be improved by renewing the precursor solution after completing half of the cycles, annealing for 90 min and later etching in KCN. The quality of the material seems to be promising for application in solar cell devices.

  14. Deposition and characterization of CuInSe2 films for solar cells using an optimized chemical route

    International Nuclear Information System (INIS)

    Berruet, M.; Schreiner, W.H.; Cere, S.; Vazquez, M.

    2011-01-01

    Research highlights: → CuInSe 2 has been deposited on glass by optimizing some parameters in the SILAR method. → Renewing the precursors after 40 cycles improves the composition of the deposit. → Photoelectrochemical tests and Mott-Schottky analysis confirm p-type conduction. → The quality of the material shows potential for application in solar cell devices. - Abstract: CuInSe 2 (CISe) thin films have been deposited on glass using successive ionic layer adsorption and reaction (SILAR). The as-deposited films are treated at 400 deg. C in argon atmosphere and etched in KCN solution to remove detrimental secondary phases. The preparation and temperature of the precursor solutions, the duration of the reaction cycles and the duration of the annealing stage have been optimized. The films have been characterized employing grazing incident X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy and energy dispersive scanning spectroscopy. Relevant semiconductor parameters have been calculated. Photoelectrochemical tests confirm p-type conduction. The films are crystalline and the stoichiometry can be improved by renewing the precursor solution after completing half of the cycles, annealing for 90 min and later etching in KCN. The quality of the material seems to be promising for application in solar cell devices.

  15. Optimization of exposure parameters in full field digital mammography

    International Nuclear Information System (INIS)

    Williams, Mark B.; Raghunathan, Priya; More, Mitali J.; Seibert, J. Anthony; Kwan, Alexander; Lo, Joseph Y.; Samei, Ehsan; Ranger, Nicole T.; Fajardo, Laurie L.; McGruder, Allen; McGruder, Sandra M.; Maidment, Andrew D. A.; Yaffe, Martin J.; Bloomquist, Aili; Mawdsley, Gordon E.

    2008-01-01

    Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal-to-noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this study is to compare, for each of the major commercially available full field digital mammography (FFDM) systems, the impact of the selection of technique factors on image SNR and radiation dose for a range of breast thickness and tissue types. This phantom study is an update of a previous investigation and includes measurements on recent versions of two of the FFDM systems discussed in that article, as well as on three FFDM systems not available at that time. The five commercial FFDM systems tested, the Senographe 2000D from GE Healthcare, the Mammomat Novation DR from Siemens, the Selenia from Hologic, the Fischer Senoscan, and Fuji's 5000MA used with a Lorad M-IV mammography unit, are located at five different university test sites. Performance was assessed using all available x-ray target and filter combinations and nine different phantom types (three compressed thicknesses and three tissue composition types). Each phantom type was also imaged using the automatic exposure control (AEC) of each system to identify the exposure parameters used under automated image acquisition. The figure of merit (FOM) used to compare technique factors is the ratio of the square of the image SNR to the mean glandular dose. The results show that, for a given target/filter combination, in general FOM is a slowly changing function of kVp, with stronger dependence on the choice of target/filter combination. In all cases the FOM was a decreasing function of kVp at the top of the available range of kVp settings, indicating that higher tube voltages would produce no further performance improvement. For a given phantom type, the exposure parameter set resulting in the highest FOM value was system specific, depending on both the set of available target/filter combinations, and

  16. Spray-deposited CuIn{sub 1-x}Ga{sub x}Se{sub 2} solar cell absorbers: Influence of spray deposition parameters and crystallization promoters

    Energy Technology Data Exchange (ETDEWEB)

    Carrete, Alex; Placidi, Marcel; Shavel, Alexey [Catalonia Institute for Energy Research - IREC, Sant Adria del Besos, Barcelona (Spain); Perez-Rodriguez, Alejandro [Catalonia Institute for Energy Research - IREC, Sant Adria del Besos, Barcelona (Spain); IN2UB, Departament d' Electronica, Universitat de Barcelona (Spain); Cabot, Andreu [Catalonia Institute for Energy Research - IREC, Sant Adria del Besos, Barcelona (Spain); Institucio Catalana de Recerca i Estudis Avancats - ICREA, Barcelona (Spain)

    2015-01-01

    To produce smooth, crack-free, and highly crystalline absorber layers are the main challenges in the fabrication of thin film solar cells using nanoparticle-based solution-processing technologies. In this work, we report on the optimization of the spray deposition parameters to produce highly homogeneous CuIn{sub 1-x}Ga{sub x}S{sub 2} thin films with controlled thickness using nanoparticle-based inks. We further explore the use of inorganic ligand exchange strategies to introduce metal ions able to promote crystallization during the selenization of the layers, removing structural defects and grain boundaries that potentially act as recombination centers. (copyright 2015 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  17. Optimization of chemical displacement deposition of copper on porous silicon.

    Science.gov (United States)

    Bandarenka, Hanna; Redko, Sergey; Nenzi, Paolo; Balucani, Marco; Bondarenko, Vitaly

    2012-11-01

    Copper (II) sulfate was used as a source of copper to achieve uniform distribution of Cu particles deposited on porous silicon. Layers of the porous silicon were formed by electrochemical anodization of Si wafers in a mixture of HF, C3H7OH and deionized water. The well-known chemical displacement technique was modified to grow the copper particles of specific sizes. SEM and XRD analysis revealed that the outer surface of the porous silicon was covered with copper particles of the crystal orientation inherited from the planes of porous silicon skeleton. The copper crystals were found to have the cubic face centering elementary cell. In addition, the traces of Cu2O cubic primitive crystalline phases were identified. The dimensions of Cu particles were determined by the Feret's analysis of the SEM images. The sizes of the particles varied widely from a few to hundreds of nanometers. A phenomenological model of copper deposition was proposed.

  18. Exploration of method determining hydrogeologic parameters of low permeability sandstone uranium deposits

    International Nuclear Information System (INIS)

    Ji Hongbin; Wu Liwu; Cao Zhen

    2012-01-01

    A hypothesis of regarding injecting test as 'anti-pumping' test is presented, and pumping test's 'match line method' is used to process data of injecting test. Accurate hydrogeologic parameters can be obtained by injecting test in the sandstone uranium deposits with low permeability and small pumping volume. Taking injecting test in a uranium deposit of Xinjiang for example, the hydrogeologic parameters of main ore-bearing aquifer were calculated by using the 'anti-pumping' hypothesis. Results calculated by the 'anti-pumping' hypothesis were compared with results calculated by water level recovery method. The results show that it is feasible to use 'anti-pumping' hypothesis to calculate the hydrogeologic parameters of main ore-bearing aquifer. (authors)

  19. Network synthesis and parameter optimization for vehicle suspension with inerter

    Directory of Open Access Journals (Sweden)

    Long Chen

    2016-12-01

    Full Text Available In order to design a comfortable-oriented vehicle suspension structure, the network synthesis method was utilized to transfer the problem into solving a timing robust control problem and determine the structure of “inerter–spring–damper” suspension. Bilinear Matrix Inequality was utilized to obtain the timing transfer function. Then, the transfer function of suspension system can be physically implemented by passive elements such as spring, damper, and inerter. By analyzing the sensitivity and quantum genetic algorithm, the optimized parameters of inerter–spring–damper suspension were determined. A quarter-car model was established. The performance of the inerter–spring–damper suspension was verified under random input. The simulation results manifested that the dynamic performance of the proposed suspension was enhanced in contrast with traditional suspension. The root mean square of vehicle body acceleration decreases by 18.9%. The inerter–spring–damper suspension can inhibit the vertical vibration within the frequency of 1–3 Hz effectively and enhance the performance of ride comfort significantly.

  20. Optimizing gelling parameters of gellan gum for fibrocartilage tissue engineering.

    Science.gov (United States)

    Lee, Haeyeon; Fisher, Stephanie; Kallos, Michael S; Hunter, Christopher J

    2011-08-01

    Gellan gum is an attractive biomaterial for fibrocartilage tissue engineering applications because it is cell compatible, can be injected into a defect, and gels at body temperature. However, the gelling parameters of gellan gum have not yet been fully optimized. The aim of this study was to investigate the mechanics, degradation, gelling temperature, and viscosity of low acyl and low/high acyl gellan gum blends. Dynamic mechanical analysis showed that increased concentrations of low acyl gellan gum resulted in increased stiffness and the addition of high acyl gellan gum resulted in greatly decreased stiffness. Degradation studies showed that low acyl gellan gum was more stable than low/high acyl gellan gum blends. Gelling temperature studies showed that increased concentrations of low acyl gellan gum and CaCl₂ increased gelling temperature and low acyl gellan gum concentrations below 2% (w/v) would be most suitable for cell encapsulation. Gellan gum blends were generally found to have a higher gelling temperature than low acyl gellan gum. Viscosity studies showed that increased concentrations of low acyl gellan gum increased viscosity. Our results suggest that 2% (w/v) low acyl gellan gum would have the most appropriate mechanics, degradation, and gelling temperature for use in fibrocartilage tissue engineering applications. Copyright © 2011 Wiley Periodicals, Inc.

  1. A choice of the parameters of NPP steam generators on the basis of vector optimization

    International Nuclear Information System (INIS)

    Lemeshev, V.U.; Metreveli, D.G.

    1981-01-01

    The optimization problem of the parameters of the designed systems is considered as the problem of multicriterion optimization. It is proposed to choose non-dominant, optimal according to Pareto, parameters. An algorithm is built on the basis of the required and sufficient non-dominant conditions to find non-dominant solutions. This algorithm has been employed to solve the problem on a choice of optimal parameters for the counterflow shell-tube steam generator of NPP of BRGD type [ru

  2. Parameter Optimization of Multi-Element Synthetic Aperture Imaging Systems

    Directory of Open Access Journals (Sweden)

    Vera Behar

    2007-03-01

    Full Text Available In conventional ultrasound imaging systems with phased arrays, the further improvement of lateral resolution requires enlarging of the number of array elements that in turn increases both, the complexity and the cost, of imaging systems. Multi-element synthetic aperture focusing (MSAF systems are a very good alternative to conventional systems with phased arrays. The benefit of the synthetic aperture is in reduction of the system complexity, cost and acquisition time. In a MSAF system considered in the paper, a group of elements transmit and receive signals simultaneously, and the transmit beam is defocused to emulate a single element response. The echo received at each element of a receive sub-aperture is recorded in the computer memory. The process of transmission/reception is repeated for all positions of a transmit sub-aperture. All the data recordings associated with each corresponding pair "transmit-receive sub-aperture" are then focused synthetically producing a low-resolution image. The final high-resolution image is formed by summing of the all low-resolution images associated with transmit/receive sub-apertures. A problem of parameter optimization of a MSAF system is considered in this paper. The quality of imaging (lateral resolution and contrast is expressed in terms of the beam characteristics - beam width and side lobe level. The comparison between the MSAF system described in the paper and an equivalent conventional phased array system shows that the MSAF system acquires images of equivalent quality much faster using only a small part of the power per image.

  3. Mixed-integer evolution strategies for parameter optimization and their applications to medical image analysis

    NARCIS (Netherlands)

    Li, Rui

    2009-01-01

    The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of

  4. Effect of process parameters on formability of laser melting deposited 12CrNi2 alloy steel

    Science.gov (United States)

    Peng, Qian; Dong, Shiyun; Kang, Xueliang; Yan, Shixing; Men, Ping

    2018-03-01

    As a new rapid prototyping technology, the laser melting deposition technology not only has the advantages of fast forming, high efficiency, but also free control in the design and production chain. Therefore, it has drawn extensive attention from community.With the continuous improvement of steel performance requirements, high performance low-carbon alloy steel is gradually integrated into high-tech fields such as aerospace, high-speed train and armored equipment.However, it is necessary to further explore and optimize the difficult process of laser melting deposited alloy steel parts to achieve the performance and shape control.This article took the orthogonal experiment on alloy steel powder by laser melting deposition ,and revealed the influence rule of the laser power, scanning speed, powder gas flow on the quality of the sample than the dilution rate, surface morphology and microstructure analysis were carried out.Finally, under the optimum technological parameters, the Excellent surface quality of the alloy steel forming part with high density, no pore and cracks was obtained.

  5. Adjusting inkjet printhead parameters to deposit drugs into micro-sized reservoirs

    Directory of Open Access Journals (Sweden)

    Mau Robert

    2016-09-01

    Full Text Available Drug delivery systems (DDS ensure that therapeutically effective drug concentrations are delivered locally to the target site. For that reason, it is common to coat implants with a degradable polymer which contains drugs. However, the use of polymers as a drug carrier has been associated with adverse side effects. For that reason, several technologies have been developed to design polymer-free DDS. In literature it has been shown that micro-sized reservoirs can be applied as drug reservoirs. Inkjet techniques are capable of depositing drugs into these reservoirs. In this study, two different geometries of micro-sized reservoirs have been laden with a drug (ASA using a drop-on-demand inkjet printhead. Correlations between the characteristics of the drug solution, the operating parameters of the printhead and the geometric parameters of the reservoir are shown. It is indicated that wettability of the surface play a key role for drug deposition into micro-sized reservoirs.

  6. Optimization of solar cell performance using atmospheric pressure chemical vapour deposition deposited TCOs

    Czech Academy of Sciences Publication Activity Database

    Yates, H.M.; Evans, P.; Sheel, D.W.; Hodgkinson, J.L.; Sheel, P.; Dagkaldiran, U.; Gordijn, A.; Finger, F.; Remeš, Zdeněk; Vaněček, Milan

    2009-01-01

    Roč. 25, č. 8 (2009), s. 789-796 ISSN 1938-5862. [International Chemical Vapor Deposition Symposium (CVD-XVII) /17./. Wien, 04.10.2009-09.10.2009] Grant - others:European Community(XE) Project (STREP) of the 6. FP Institutional research plan: CEZ:AV0Z10100521 Keywords : solar cells * TCO * CVD Subject RIV: BM - Solid Matter Physics ; Magnetism

  7. CANDU fuel deposits and chemistry optimizations. Recent regulatory experience in Canadian Nuclear Power Plants

    International Nuclear Information System (INIS)

    Kameswaran, Ram

    2014-01-01

    Water chemistry of the Primary Heat Transport System (PHT) of CANDU – Pressurised Heavy Water Reactors profoundly influences the transport of corrosion products around the Heat Transport System (HTS), where they can be deposited as crud on steam generators, feeder pipes and on the fuel. Fuel cladding can be covered with deposits which have precipitated from the coolant as a result of temperature changes or non-optimal coolant pH. Precipitation of deposits in-core must be avoided as far as possible, as it leads to fouling of the fuel, loss of heat transfer efficiency, and increased radiation fields. In the recent years a Canadian NPP experienced increased instances of black deposits being observed on fuel bundles discharged from one of the units. The black deposits were initially observed in 2008 during in-bay fuel inspections. Since then it has been determined that all the discharged fuel bundles have black deposits on them and that observed deposits have been increasing in size (thickness and surface area). This negative trend has persisted through to 2012, when one of fuel bundles was observed with significantly larger deposit than previously seen. Initial analysis of the deposit indicated it to be iron oxide (magnetite). Flow Accelerated Corrosion (FAC) of carbon steel feeder pipes is the primary source of iron, which deposits as magnetite on HTS surfaces. The black deposits have predominantly been located immediately downstream of the bearing pads of the fuel bundle. Deposits have also tended to form on the bottom-downstream quadrant of the fuel bundles. The deposits were most prevalent in low power channels, but some deposits have been observed on high power channels. It was reported by the utility that the PHT system chemistry has been maintained in specification for most of the time during normal operation but the chemistry control during outages was inadequate. Due to design constraints, purification circuit was not available during outages and ion

  8. WE-AB-209-09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Dong, P; Xing, L [Stanford University School of Medicine, Stanford, CA (United States); Ungun, B [Stanford University School of Medicine, Stanford, CA (United States); Stanford University School of Engineering, Stanford, CA (United States); Boyd, S [Stanford University School of Engineering, Stanford, CA (United States)

    2016-06-15

    Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. To avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain). Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case. Conclusion: The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.

  9. WE-AB-209-09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy

    International Nuclear Information System (INIS)

    Dong, P; Xing, L; Ungun, B; Boyd, S

    2016-01-01

    Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. To avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain). Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case. Conclusion: The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.

  10. Analysis of process parameters in the laser deposition of YBa{sub 2}Cu{sub 3}O{sub 7} superconducting films by using SVR

    Energy Technology Data Exchange (ETDEWEB)

    Cai, C.Z., E-mail: caiczh@gmail.com [Department of Applied Physics, Chongqing University, Chongqing 401331 (China); Xiao, T.T. [Department of Applied Physics, Chongqing University, Chongqing 401331 (China); Science and Technology on Plasma Physics Laboratory, Research Center of Laser Fusion, CAEP, P.O. Box 919-988, Mianyang 621900 (China); Tang, J.L.; Huang, S.J. [Department of Applied Physics, Chongqing University, Chongqing 401331 (China)

    2013-10-15

    Highlights: • Proposed new ideas and strategies to improve energy storage density for SMES system. • One is to increase the effective current density in the superconducting coils. • Another is to optimize the configuration of the SMES coil. • A new conceive of energy compression is also proposed. -- Abstract: There are several process parameters in the growth of YBa{sub 2}Cu{sub 3}O{sub 7} superconducting films by using pulsed laser deposition (PLD). The relationship between the response and process parameters is highly nonlinear and quite complicated. It is very valuable to quantitatively estimate the response under different deposition parameters. In this study, according to an experimental data set on the superconducting transition temperature (T{sub c}) and relative resistance ratio (r{sub R}) of 17 samples of YBa{sub 2}Cu{sub 3}O{sub 7} films deposited under various parameters, the support vector regression (SVR) combined with particle swarm optimization (PSO), was proposed to predict the T{sub c} and r{sub R} for YBa{sub 2}Cu{sub 3}O{sub 7} films. The prediction performance of SVR was compared with that of multiple regression analysis (MRA) models. The results strongly support that the generalization ability of SVR model consistently surpasses that of MRA via leave-one-out cross validation (LOOCV). The mean absolute percentage errors for T{sub c} and r{sub R} are 0.37% and 1.51% respectively via LOOCV test of SVR. Sensitivity analysis discovered the most sensitive parameters affecting the T{sub c} and r{sub R}. This study suggests that the established SVR model can be used to accurately foresee the T{sub c} and r{sub R}. And it can be used to optimizing the deposition parameters in the development of YBa{sub 2}Cu{sub 3}O{sub 7} films via PLD.

  11. A procedure for multi-objective optimization of tire design parameters

    OpenAIRE

    Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović

    2015-01-01

    The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...

  12. Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect

    OpenAIRE

    Yue Hu; Xilu Zhao; Takao Yamaguchi; Manabu Sasajima; Yoshio Koike; Akira Hara

    2016-01-01

    This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. Th...

  13. Growth of different phases and morphological features of MnS thin films by chemical bath deposition: Effect of deposition parameters and annealing

    Energy Technology Data Exchange (ETDEWEB)

    Hannachi, Amira, E-mail: amira.hannachi88@gmail.com; Maghraoui-Meherzi, Hager

    2017-03-15

    Manganese sulfide thin films have been deposited on glass slides by chemical bath deposition (CBD) method. The effects of preparative parameters such as deposition time, bath temperature, concentration of precursors, multi-layer deposition, different source of manganese, different complexing agent and thermal annealing on structural and morphological film properties have been investigated. The prepared thin films have been characterized using the X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). It exhibit the metastable forms of MnS, the hexagonal γ-MnS wurtzite phase with preferential orientation in the (002) plane or the cubic β-MnS zinc blende with preferential orientation in the (200) plane. Microstructural studies revealed the formation of MnS crystals with different morphologies, such as hexagons, spheres, cubes or flowers like. - Graphical Abstract: We report the preparation of different phases of manganese sulfide thin films (γ, β and α-MnS) by chemical bath deposition method. The effects of deposition parameters such as deposition time and temperature, concentrations of precursors and multi-layer deposition on MnS thin films structure and morphology were investigated. The influence of thermal annealing under nitrogen atmosphere at different temperature on MnS properties was also studied. Different manganese precursors as well as different complexing agent were also used. - Highlights: • γ and β-MnS films were deposited on substrate using the chemical bath deposition. • The effect of deposition parameters on MnS film properties has been investigated. • Multi-layer deposition was also studied to increase film thickness. • The effect of annealing under N{sub 2} at different temperature was investigated.

  14. Optimization of machining parameters of hard porcelain on a CNC ...

    African Journals Online (AJOL)

    s (2010) focus was to calculate drilled composite's surface roughness with the application of ... instance, objective function as well as restrictions on rotor enactment. ..... to aerodynamic optimization design of helicopter rotor blade, International.

  15. Optimization of silicon oxynitrides by plasma-enhanced chemical vapor deposition for an interferometric biosensor

    Science.gov (United States)

    Choo, Sung Joong; Lee, Byung-Chul; Lee, Sang-Myung; Park, Jung Ho; Shin, Hyun-Joon

    2009-09-01

    In this paper, silicon oxynitride layers deposited with different plasma-enhanced chemical vapor deposition (PECVD) conditions were fabricated and optimized, in order to make an interferometric sensor for detecting biochemical reactions. For the optimization of PECVD silicon oxynitride layers, the influence of the N2O/SiH4 gas flow ratio was investigated. RF power in the PEVCD process was also adjusted under the optimized N2O/SiH4 gas flow ratio. The optimized silicon oxynitride layer was deposited with 15 W in chamber under 25/150 sccm of N2O/SiH4 gas flow rates. The clad layer was deposited with 20 W in chamber under 400/150 sccm of N2O/SiH4 gas flow condition. An integrated Mach-Zehnder interferometric biosensor based on optical waveguide technology was fabricated under the optimized PECVD conditions. The adsorption reaction between bovine serum albumin (BSA) and the silicon oxynitride surface was performed and verified with this device.

  16. FCC-hh final-focus for flat-beams: parameters and energy deposition studies

    CERN Document Server

    AUTHOR|(CDS)2081283; Cruz Alaniz, Emilia; Seryi, Andrei; Van Riesen-Haupt, Leon; Besana, Maria Ilaria

    2017-01-01

    The international Future Circular Collider (FCC) study comprises the study of a new scientific structure in a tunnel of 100 km. This will allow the installation of two accelerators, a 45.6–175 GeV lepton collider and a 100-TeV hadron collider. An optimized design of a final-focus system for the hadron collider is presented here. The new design is more compact and enables unequal ${\\beta}$$^{∗}$ in both planes, whose choice is justified here. This is followed by energy deposition studies, where the total dose in the magnets as a consequence of the collision debris is evaluated.

  17. An Optimal Investment Strategy and Multiperiod Deposit Insurance Pricing Model for Commercial Banks

    Directory of Open Access Journals (Sweden)

    Grant E. Muller

    2018-01-01

    Full Text Available We employ the method of stochastic optimal control to derive the optimal investment strategy for maximizing an expected exponential utility of a commercial bank’s capital at some future date T>0. In addition, we derive a multiperiod deposit insurance (DI pricing model that incorporates the explicit solution of the optimal control problem and an asset value reset rule comparable to the typical practice of insolvency resolution by insuring agencies. By way of numerical simulations, we study the effects of changes in the DI coverage horizon, the risk associated with the asset portfolio of the bank, and the bank’s initial leverage level (deposit-to-asset ratio on the DI premium while the optimal investment strategy is followed.

  18. An automatic and effective parameter optimization method for model tuning

    Directory of Open Access Journals (Sweden)

    T. Zhang

    2015-11-01

    simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

  19. Optimal parameters for the FFA-Beddoes dynamic stall model

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

    1999-03-01

    Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)

  20. Optimizing best management practices to control anthropogenic sources of atmospheric phosphorus deposition to inland lakes.

    Science.gov (United States)

    Weiss, Lee; Thé, Jesse; Winter, Jennifer; Gharabaghi, Bahram

    2018-04-18

    Excessive phosphorus loading to inland freshwater lakes around the globe has resulted in nuisance plant growth along the waterfronts, degraded habitat for cold water fisheries, and impaired beaches, marinas and waterfront property. The direct atmospheric deposition of phosphorus can be a significant contributing source to inland lakes. The atmospheric deposition monitoring program for Lake Simcoe, Ontario indicates roughly 20% of the annual total phosphorus load (2010-2014 period) is due to direct atmospheric deposition (both wet and dry deposition) on the lake. This novel study presents a first-time application of the Genetic Algorithm (GA) methodology to optimize the application of best management practices (BMPs) related to agriculture and mobile sources to achieve atmospheric phosphorus reduction targets and restore the ecological health of the lake. The novel methodology takes into account the spatial distribution of the emission sources in the airshed, the complex atmospheric long-range transport and deposition processes, cost and efficiency of the popular management practices and social constraints related to the adoption of BMPs. The optimization scenarios suggest that the optimal overall capital investment of approximately $2M, $4M, and $10M annually can achieve roughly 3, 4 and 5 tonnes reduction in atmospheric P load to the lake, respectively. The exponential trend indicates diminishing returns for the investment beyond roughly $3M per year and that focussing much of this investment in the upwind, nearshore area will significantly impact deposition to the lake. The optimization is based on a combination of the lowest-cost, most-beneficial and socially-acceptable management practices that develops a science-informed promotion of implementation/BMP adoption strategy. The geospatial aspect to the optimization (i.e. proximity and location with respect to the lake) will help land managers to encourage the use of these targeted best practices in areas that

  1. Study of the effect of the deposition parameters on the structural, electric and optical characteristics of polymorphous silicon films prepared by low frequency PECVD

    Energy Technology Data Exchange (ETDEWEB)

    Moreno, M., E-mail: mmoreno@inaoep.mx [Instituto Nacional de Astrofisica, Optica y Electronica, INAOE, Puebla (Mexico); Torres, A. [Instituto Nacional de Astrofisica, Optica y Electronica, INAOE, Puebla (Mexico); Ambrosio, R. [Universidad Autonoma de Ciudad Juarez, Electrical Deparment, Chihuahua (Mexico); Zuniga, C.; Torres-Rios, A.; Monfil, K.; Rosales, P.; Itzmoyotl, A. [Instituto Nacional de Astrofisica, Optica y Electronica, INAOE, Puebla (Mexico)

    2011-10-25

    In this work we present our results on the deposition and characterization of polymorphous silicon (pm-Si:H) films prepared by low frequency plasma enhanced chemical vapor deposition (LF-PECVD). We have studied the effect of the plasma deposition parameters (as the chamber pressure and gas flow rates of SiH{sub 4} and H{sub 2}) on the structural, electric, and optical characteristics of the films. The temperature dependence of conductivity ({sigma}(T)), activation energy (E{sub a}), optical band gap (E{sub g}) and deposition rate (V{sub d}) were extracted for pm-Si:H films deposited at different pressure values and different gas flow rates. We observed that the chamber pressure is an important parameter that has a significant effect on the electric characteristics, and as well on the morphology of the pm-Si:H films (deduced from atomic force microscopy). It was found an optimal pressure range, in order to produce pm-Si:H films with high E{sub a} and room temperature conductivity, {sigma}{sub RT}, which are key parameters for thermal detection applications.

  2. Study of the effect of the deposition parameters on the structural, electric and optical characteristics of polymorphous silicon films prepared by low frequency PECVD

    International Nuclear Information System (INIS)

    Moreno, M.; Torres, A.; Ambrosio, R.; Zuniga, C.; Torres-Rios, A.; Monfil, K.; Rosales, P.; Itzmoyotl, A.

    2011-01-01

    In this work we present our results on the deposition and characterization of polymorphous silicon (pm-Si:H) films prepared by low frequency plasma enhanced chemical vapor deposition (LF-PECVD). We have studied the effect of the plasma deposition parameters (as the chamber pressure and gas flow rates of SiH 4 and H 2 ) on the structural, electric, and optical characteristics of the films. The temperature dependence of conductivity (σ(T)), activation energy (E a ), optical band gap (E g ) and deposition rate (V d ) were extracted for pm-Si:H films deposited at different pressure values and different gas flow rates. We observed that the chamber pressure is an important parameter that has a significant effect on the electric characteristics, and as well on the morphology of the pm-Si:H films (deduced from atomic force microscopy). It was found an optimal pressure range, in order to produce pm-Si:H films with high E a and room temperature conductivity, σ RT , which are key parameters for thermal detection applications.

  3. Optimizing design parameter for light isotopes separation by distillation method

    International Nuclear Information System (INIS)

    Ahmadi, M.

    1999-01-01

    More than methods are suggested in the world for producing heavy water, where between them chemical isotopic methods, distillation and electro lys are used widely in industrial scale. To select suitable method for heavy water production in Iran, taking into consideration, domestic technology an facilities, combination of hydrogen sulphide-water dual temperature process (Gs) and distillation (D W) may be proposed. Natural water, is firstly enriched up to 15 a% by G S process and then by distillation unit is enriched up to the grade necessary for Candu type reactors (99.8 a%). The aim of present thesis, is to achieve know-how, optimization of design parameters, and executing basic design for water isotopes separation using distillation process in a plant having minimum scale possible. In distillation, vapour phase resulted from liquid phase heating, is evidently composed of the same constituents as liquid phase. In isotopic distillation, the difference in composition of constituents is not considerable. In fact alteration of constituents composition is so small that makes the separation process impossible, however, direct separation and production of pure products without further processing which becomes possible by distillation, makes this process as one of the most important separation processes. Profiting distillation process to produce heavy water is based on difference existing between boiling point of heavy and light water. The trends of boiling points differences (heavy and light water) is adversely dependant with pressure. As the whole system pressure decreases, difference in boiling points increases. On the other hand according to the definition, separation factor is equal to the ratio of pure light water vapour pressure to that of heavy water, or we can say that the trend of whole system pressure decrease results in separation factor increase, which accordingly separation factor equation to pressure variable should be computed firstly. According to the

  4. Optimization of multilayer neural network parameters for speaker recognition

    Science.gov (United States)

    Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

    2016-05-01

    This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

  5. Optimization of Key Parameters of Energy Management Strategy for Hybrid Electric Vehicle Using DIRECT Algorithm

    Directory of Open Access Journals (Sweden)

    Jingxian Hao

    2016-11-01

    Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.

  6. Planar structured perovskite solar cells by hybrid physical chemical vapor deposition with optimized perovskite film thickness

    Science.gov (United States)

    Wei, Xiangyang; Peng, Yanke; Jing, Gaoshan; Cui, Tianhong

    2018-05-01

    The thickness of perovskite absorber layer is a critical parameter to determine a planar structured perovskite solar cell’s performance. By modifying the spin coating speed and PbI2/N,N-dimethylformamide (DMF) solution concentration, the thickness of perovskite absorber layer was optimized to obtain high-performance solar cells. Using a PbI2/DMF solution of 1.3 mol/L, maximum power conversion efficiency (PCE) of a perovskite solar cell is 15.5% with a perovskite film of 413 nm at 5000 rpm, and PCE of 14.3% was also obtained for a solar cell with a perovskite film of 182 nm thick. It is derived that higher concentration of PbI2/DMF will result in better perovskite solar cells. Additionally, these perovskite solar cells are highly uniform. In 14 sets of solar cells, standard deviations of 11 sets of solar cells were less than 0.50% and the smallest standard deviation was 0.25%, which demonstrates the reliability and effectiveness of hybrid physical chemical vapor deposition (HPCVD) method.

  7. Mobility Optimization in LaxBa1-xSnO3 Thin Films Deposited via High Pressure Oxygen Sputtering

    Science.gov (United States)

    Postiglione, William Michael

    BaSnO3 (BSO) is one of the most promising semiconducting oxides currently being explored for use in future electronic applications. BSO possesses a unique combination of high room temperature mobility (even at very high carrier concentrations, > 1019 cm-3), wide band gap, and high temperature stability, making it a potentially useful material for myriad applications. Significant challenges remain however in optimizing the properties and processing of epitaxial BSO, a critical step towards industrial applications. In this study we investigate the viability of using high pressure oxygen sputtering to produce high mobility La-doped BSO thin films. In the first part of our investigation we synthesized, using solid state reaction, phase-pure stoichiometric polycrystalline 2% La-doped BaSnO 3 for use as a target material in our sputtering system. We verified the experimental bulk lattice constant, 4.117 A, to be in good agreement with literature values. Next, we set out to optimize the growth conditions for DC sputtering of La doped BaSnO3. We found that mobility for all our films increased monotonically with deposition temperature, suggesting the optimum temperature for deposition is > 900 °C and implicating a likely improvement in transport properties with post-growth thermal anneal. We then preformed systematic studies aimed at probing the effects of varying thickness and deposition rate to optimize the structural and electronic transport properties in unbuffered BSO films. In this report we demonstrate the ability to grow 2% La BSO thin films with an effective dopant activation of essentially 100%. Our films showed fully relaxed (bulk), out-of-plane lattice parameter values when deposited on LaAlO3, MgO, and (LaAlO3)0.3(Sr2 TaAlO6)0.7 substrates, and slightly expanded out-of-plane lattice parameters for films deposited on SrTiO3, GdScO3, and PrScO3 substrates. The surface roughness's of our films were measured via AFM, and determined to be on the nm scale or better

  8. A Particle Swarm Optimization Algorithm for Optimal Operating Parameters of VMI Systems in a Two-Echelon Supply Chain

    Science.gov (United States)

    Sue-Ann, Goh; Ponnambalam, S. G.

    This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.

  9. Deposition parameters to improve the fouling-release properties of thin siloxane coatings prepared by PACVD

    International Nuclear Information System (INIS)

    Akesso, Laurent; Navabpour, Parnia; Teer, Dennis; Pettitt, Michala E.; Callow, Maureen E.; Liu Chen; Su Xueju; Wang Su; Zhao Qi; Donik, Crtomir; Kocijan, Aleksandra; Jenko, Monika; Callow, James A.

    2009-01-01

    A range of SiO x -like coatings was deposited on glass slides from a hexamethylsiloxane precursor by plasma-assisted CVD. The effect of varying deposition parameters, specifically ion cleaning time and HMDSO/O 2 ratios, on the coating properties and antifouling performance was investigated. At low HMDSO/O 2 ratios, the resulting coatings were close to SiO 2 . Carbon content in the bulk of the coatings increased with increasing HMDSO/O 2 ratio. Coatings deposited at high HMDSO/O 2 ratios and with the longest cleaning time (30 min), elevated the relative carbon content to 25 atomic %. Surface energies (22-43 mJ/m) were correlated with the degree of surface oxidation and hydrocarbon content. With the exception of the most polar coatings the apolar component of the surface energy (γ LW ) was the dominant component. In the most hydrophilic coatings, the Lewis base component of the surface energy (γ - ) was dominant. Significantly improved antifouling performance was detected with the most reduced coatings deposited using the extended ion cleaning times. For both, the removal of sporelings of the marine green alga, Ulvalinza and the initial adhesion of the freshwater bacterium, Pseudomonas fluorescens, there was a strong, positive correlation between strength of attachment and ion cleaning time. Increased ion cleaning time will elevate the deposition temperature, increasing decomposition rates and thus the crosslinking of the polymer. Increased cross-linking may render these coatings less permeable to penetration and mechanical interlocking by the adhesive polymers used by these organisms, thus reducing their adhesion. Films with improved biological performance have potential for use as coatings in the control of biofouling in applications such as heat exchangers, where thin films are important for effective thermal transfer, or optical windows where transparency is important.

  10. Dependence of the surface roughness of MAPLE-deposited films on the solvent parameters

    Science.gov (United States)

    Caricato, A. P.; Leggieri, G.; Martino, M.; Vantaggiato, A.; Valerini, D.; Cretì, A.; Lomascolo, M.; Manera, M. G.; Rella, R.; Anni, M.

    2010-12-01

    Matrix-assisted pulsed laser evaporation (MAPLE) was used to deposit layers of poly(9,9-dioctylfluorene) (PFO) to study the relation between the solvent properties (laser light absorption, boiling temperature and solubility parameters) and the morphology of the deposited films. To this end, the polymer was diluted (0.5 wt%) in tetrahydrofuran—THF, toluene and toluene/hexane mixtures. The thickness of the films was equal to 70±20 nm. The morphology and uniformity of the films was investigated by Atomic Force Microscopy and by the photoluminescence emission properties of the polymer films, respectively. It is shown that, although the solubility parameters of the solvents are important in controlling the film roughness and morphology, the optical absorption properties and boiling temperature play a very important role, too. In fact, for matrices characterized by the same total solubility parameter, lower roughness values are obtained for films prepared using solvents with lower penetration depth of the laser radiation and higher boiling temperatures.

  11. Optimization of turning process parameters by using grey-Taguchi

    African Journals Online (AJOL)

    DR OKE

    ... India continue to choose the operating conditions solely on the basis of handbook values .... Surface Roughness Measuring instrument ... process control parameters like spindle speed, feed and depth of cut. ..... and Industrial Engineering.

  12. Optimization of processing parameters on the controlled growth of c-axis oriented ZnO nanorod arrays

    Energy Technology Data Exchange (ETDEWEB)

    Malek, M. F., E-mail: mfmalek07@gmail.com; Rusop, M., E-mail: rusop@salam.uitm.my [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); NANO-SciTech Centre (NST), Institute of Science (IOS), Universiti Teknologi MARA - UiTM, 40450 Shah Alam, Selangor (Malaysia); Mamat, M. H., E-mail: hafiz-030@yahoo.com [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); Musa, M. Z., E-mail: musa948@gmail.com [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Pulau Pinang, Jalan Permatang Pauh, 13500 Permatang Pauh, Pulau Pinang (Malaysia); Saurdi, I., E-mail: saurdy788@gmail.com; Ishak, A., E-mail: ishak@sarawak.uitm.edu.my [NANO-ElecTronic Centre (NET), Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM), 40450 Shah Alam, Selangor (Malaysia); Faculty of Electrical Engineering, Universiti Teknologi MARA (UiTM) Sarawak, Kampus Kota Samarahan, Jalan Meranek, 94300 Kota Samarahan, Sarawak (Malaysia); Alrokayan, Salman A. H., E-mail: dr.salman@alrokayan.com; Khan, Haseeb A., E-mail: khan-haseeb@yahoo.com [Chair of Targeting and Treatment of Cancer Using Nanoparticles, Deanship of Scientific Research, King Saud University (KSU), Riyadh 11451 (Saudi Arabia)

    2016-07-06

    Optimization of the growth time parameter was conducted to synthesize high-quality c-axis ZnO nanorod arrays. The effects of the parameter on the crystal growth and properties were systematically investigated. Our studies confirmed that the growth time influence the properties of ZnO nanorods where the crystallite size of the structures was increased at higher deposition time. Field emission scanning electron microsope analysis confirmed the morphologies structure of the ZnO nanorods. The ZnO nanostructures prepared under the optimized growth conditions showed an intense XRD peak which reveal a higher c-axis oriented ZnO nanorod arrays thus demonstrating the formation of defect free structure.

  13. Determination and optimization of the ζ potential in boron electrophoretic deposition on aluminium substrates

    International Nuclear Information System (INIS)

    Oliveira Sampa, M.H. de; Vinhas, L.A.; Pino, E.S.

    1991-05-01

    In this work we present an introduction of the electrophoretic process followed by a detailed experimental treatment of the technique used in the determination and optimization of the ζ-potential, mainly as a function of the electrolyte concentration, in a high purity boron electrophoretics deposition on aluminium substrates used as electrodes in neutron detectors. (author)

  14. Optimization of injection moulding process parameters in the ...

    African Journals Online (AJOL)

    In this study, optimal injection moulding conditions for minimum shrinkage during moulding of High Density Polyethylene (HDPE) were obtained by Taguchi method. The result showed that melting temperature of 190OC, injection pressure of 55 MPa, refilling pressure of 85 MPa and cooling time of 11 seconds gave ...

  15. Air Compressor Driving with Synchronous Motors at Optimal Parameters

    Directory of Open Access Journals (Sweden)

    Iuliu Petrica

    2010-10-01

    Full Text Available In this paper a method of optimal compensation of the reactive load by the synchronous motors, driving the air compressors, used in mining enterprises is presented, taking into account that in this case, the great majority of the equipment (compressors, pumps are generally working a constant load.

  16. Optimizing Acquisition Parameters for MASW in Shallow Water

    NARCIS (Netherlands)

    Diaferia, G.; Kruiver, P.P.; Drijkoningen, G.G.

    2013-01-01

    Analogous to the use of Rayleigh waves in MASW on land, Scholte waves can be used to derive shear wave velocity profiles for the subsurface under water. These profiles are useful for dredging operations, offshore wind farms, oil rigs and pipelines. We have determined the optimal acquisition set up

  17. Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

    Science.gov (United States)

    Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

    2017-11-20

    A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

  18. Optimal Selection of the Sampling Interval for Estimation of Modal Parameters by an ARMA- Model

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning

    1993-01-01

    Optimal selection of the sampling interval for estimation of the modal parameters by an ARMA-model for a white noise loaded structure modelled as a single degree of- freedom linear mechanical system is considered. An analytical solution for an optimal uniform sampling interval, which is optimal...

  19. Effect of Target Composition and Sputtering Deposition Parameters on the Functional Properties of Nitrogenized Ag-Permalloy Flexible Thin Films Deposited on Polymer Substrates

    Directory of Open Access Journals (Sweden)

    Waheed Khan

    2018-03-01

    Full Text Available We report the first results of functional properties of nitrogenized silver-permalloy thin films deposited on polyethylene terephthalic ester {PETE (C10H8O4n} flexible substrates by magnetron sputtering. These new soft magnetic thin films have magnetization that is comparable to pure Ni81Fe19 permalloy films. Two target compositions (Ni76Fe19Ag5 and Ni72Fe18Ag10 were used to study the effect of compositional variation and sputtering parameters, including nitrogen flow rate on the phase evolution and surface properties. Aggregate flow rate and total pressure of Ar+N2 mixture was 60 sccm and 0.55 Pa, respectively. The distance between target and the substrate was kept at 100 mm, while using sputtering power from 100–130 W. Average film deposition rate was confirmed at around 2.05 nm/min for argon atmosphere and was reduced to 1.8 nm/min in reactive nitrogen atmosphere. X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, vibrating sample magnetometer, and contact angle measurements were used to characterize the functional properties. Nano sized character of films was confirmed by XRD and SEM. It is found that the grain size was reduced by the formation of nitride phase, which in turns enhanced the magnetization and lowers the coercivity. Magnetic field coupling efficiency limit was determined from 1.6–2 GHz frequency limit. The results of comparable magnetic performance, lowest magnetic loss, and highest surface free energy, confirming that 15 sccm nitrogen flow rate at 115 W is optimal for producing Ag-doped permalloy flexible thin films having excellent magnetic field coupling efficiency.

  20. Optimization of control parameters for petroleum waste composting

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as theactivity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5-59.5, 7.0-8.5 and 55%-60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.

  1. Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network

    OpenAIRE

    Jing Wang; Yourui Huang

    2013-01-01

    In order to solve problems such as initial weights are difficult to be determined, training results are easy to trap in local minima in optimization process of PID neural network parameters by traditional BP algorithm, this paper proposed a new method based on improved artificial fish algorithm for parameters optimization of PID neural network. This improved artificial fish algorithm uses a composite adaptive artificial fish algorithm based on optimal artificial fish and nearest artificial fi...

  2. Optimization of MIS/IL solar cells parameters using genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, K.A.; Mohamed, E.A.; Alaa, S.H. [Faculty of Engineering, Alexandria Univ. (Egypt); Motaz, M.S. [Institute of Graduate Studies and Research, Alexandria Univ. (Egypt)

    2004-07-01

    This paper presents a genetic algorithm optimization for MIS/IL solar cell parameters including doping concentration NA, metal work function {phi}m, oxide thickness d{sub ox}, mobile charge density N{sub m}, fixed oxide charge density N{sub ox} and the external back bias applied to the inversion grid V. The optimization results are compared with theoretical optimization and shows that the genetic algorithm can be used for determining the optimum parameters of the cell. (orig.)

  3. Characterization and Optimization of Ni-WC Composite Weld Matrix Deposited by Plasma-Transferred Arc Process

    Science.gov (United States)

    Tahaei, Ali; Horley, Paul; Merlin, Mattia; Torres-Torres, David; Garagnani, Gian Luca; Praga, Rolando; Vázquez, Felipe J. García; Arizmendi-Morquecho, Ana

    2017-03-01

    This work is dedicated to optimization of carbide particle system in a weld bead deposited by PTAW technique over D2 tool steel with high chromium content. The paper reports partial melting of the original carbide grains of the Ni-based filling powder, and growing of the secondary carbide phase (Cr, Ni)_3W_3C in the form of dendrites with wide branches that enhanced mechanical properties of the weld. The optimization of bead parameters was made with design of experiment methodology complemented by a complex sample characterization including SEM, EDXS, XRD, and nanoindentation measurements. It was shown that the preheat of the substrate to a moderate temperature 523 K (250° C) establishes linear pattern of metal flow in the weld pool, resulting in the most homogeneous distribution of the primary carbides in the microstructure of weld bead.

  4. Data Mining and Optimization Tools for Developing Engine Parameters Tools

    Science.gov (United States)

    Dhawan, Atam P.

    1998-01-01

    This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  6. Optimization of Surface Roughness Parameters of Al-6351 Alloy in EDC Process: A Taguchi Coupled Fuzzy Logic Approach

    Science.gov (United States)

    Kar, Siddhartha; Chakraborty, Sujoy; Dey, Vidyut; Ghosh, Subrata Kumar

    2017-10-01

    This paper investigates the application of Taguchi method with fuzzy logic for multi objective optimization of roughness parameters in electro discharge coating process of Al-6351 alloy with powder metallurgical compacted SiC/Cu tool. A Taguchi L16 orthogonal array was employed to investigate the roughness parameters by varying tool parameters like composition and compaction load and electro discharge machining parameters like pulse-on time and peak current. Crucial roughness parameters like Centre line average roughness, Average maximum height of the profile and Mean spacing of local peaks of the profile were measured on the coated specimen. The signal to noise ratios were fuzzified to optimize the roughness parameters through a single comprehensive output measure (COM). Best COM obtained with lower values of compaction load, pulse-on time and current and 30:70 (SiC:Cu) composition of tool. Analysis of variance is carried out and a significant COM model is observed with peak current yielding highest contribution followed by pulse-on time, compaction load and composition. The deposited layer is characterised by X-Ray Diffraction analysis which confirmed the presence of tool materials on the work piece surface.

  7. Optimization of Storage Parameters of Selected Fruits in Passive ...

    African Journals Online (AJOL)

    This study was carried out to determine the optimum storage parameters of selected fruit using three sets of four types of passive evaporative cooling structures made of two different materials clay and aluminium. One set consisted of four separate cooling chambers. Two cooling chambers were made with aluminium ...

  8. Optimal Two Parameter Bounds for the Seiffert Mean

    Directory of Open Access Journals (Sweden)

    Hui Sun

    2013-01-01

    Full Text Available We obtain sharp bounds for the Seiffert mean in terms of a two parameter family of means. Our results generalize and extend the recent bounds presented in the Journal of Inequalities and Applications (2012 and Abstract and Applied Analysis (2012.

  9. Investigation and validation of optimal cutting parameters for least ...

    African Journals Online (AJOL)

    user

    Turning is carried on lathe that provides the power to turn the work piece at a given rotational speed and ... The cutting parameters influencing the surface finish in EN24 is to be studied ...... Design from Anna University, Chennai, India in 2004.

  10. Optimization of physico-chemical and nutritional parameters for ...

    African Journals Online (AJOL)

    hope&shola

    2010-10-25

    Oct 25, 2010 ... industrial production in order to reduce the cost of production. ... is of great economic importance with increased appli- ... industries (Seviour et al., 1992; Leathers, 2003). .... The various process parameters influencing pullulan production ..... formation by Aureobasidium pullulans in stirred tanks. Enzyme.

  11. Optimization and Analysis of Cutting Tool Geometrical Parameters ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Bassett et al.,(2012);. Kountanya et al., (2016) studied the effect of tool edge geometry and cutting conditions on the chip morphology in orthogonal hard turning of 100Cr6 steel. Their study shows that the edge radius does not influence the geometrical parameters of the chip. Moreover cutting forces decreases as the cutting.

  12. Optimization of cathodic arc deposition and pulsed plasma melting techniques for growing smooth superconducting Pb photoemissive films for SRF injectors

    Science.gov (United States)

    Nietubyć, Robert; Lorkiewicz, Jerzy; Sekutowicz, Jacek; Smedley, John; Kosińska, Anna

    2018-05-01

    Superconducting photoinjectors have a potential to be the optimal solution for moderate and high current cw operating free electron lasers. For this application, a superconducting lead (Pb) cathode has been proposed to simplify the cathode integration into a 1.3 GHz, TESLA-type, 1.6-cell long purely superconducting gun cavity. In the proposed design, a lead film several micrometres thick is deposited onto a niobium plug attached to the cavity back wall. Traditional lead deposition techniques usually produce very non-uniform emission surfaces and often result in a poor adhesion of the layer. A pulsed plasma melting procedure reducing the non-uniformity of the lead photocathodes is presented. In order to determine the parameters optimal for this procedure, heat transfer from plasma to the film was first modelled to evaluate melting front penetration range and liquid state duration. The obtained results were verified by surface inspection of witness samples. The optimal procedure was used to prepare a photocathode plug, which was then tested in an electron gun. The quantum efficiency and the value of cavity quality factor have been found to satisfy the requirements for an injector of the European-XFEL facility.

  13. Effect of angle of deposition on micro-roughness parameters and optical properties of HfO{sub 2} thin films deposited by reactive electron beam evaporation

    Energy Technology Data Exchange (ETDEWEB)

    Tokas, R.B., E-mail: tokasstar@gmail.com; Jena, S.; Thakur, S.; Sahoo, N.K.

    2016-06-30

    Oblique angle deposited oxide thin films, in which refractive index profiles can be tailored across depth by tuning their microstructure using varying angle of deposition, have opened up new dimensions in fabrication of optical interference devices. Since surface morphology plays an important role for the qualification of these thin film devices for optical or other applications, it is important to investigate morphological properties of obliquely deposited thin films. In the present work, a set of HfO{sub 2} thin films have been deposited at several oblique angles. Morphological parameters of such thin films viz., correlation length, intrinsic roughness, fractal spectral strength, etc., have been determined through suitable modelling of extended power spectral density measured by atomic force microscopy. It has been found that intrinsic roughness and fractal spectral strength show an interesting behaviour with deposition angle and the same has been discussed in the light of atomic shadowing and re-emission and diffusion of ad-atoms. Further refractive index and thickness of such thin films have been estimated from optical transmission spectra through suitable modelling. Refractive index of such thin film varies from 1.93 to 1.37 as the deposition angle varies from normal to glancing angle (80°). Further, refractive index and grain size depict an opposite trend with deposition angle. This variation has been explained in terms of varying film porosity and column slanting with angle of deposition. - Highlights: • HfO{sub 2} thin films deposited at several oblique angles • Film deposited at 80° exhibits the highest grain size and intrinsic roughness (σ). • Fractal strength and σ depict an interesting trend with angle of deposition. • Refractive index and grain size depict an opposite trend with angle of deposition.

  14. Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

    Science.gov (United States)

    Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

    2014-01-01

    Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

  15. Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

    Science.gov (United States)

    Neverov, V. V.; Kozhukhov, Y. V.; Yablokov, A. M.; Lebedev, A. A.

    2017-08-01

    Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.

  16. Intelligent Mechatronics Systems for Transport Climate Parameters Optimization Using Fuzzy Logic Control

    OpenAIRE

    Beinarts, I; Ļevčenkovs, A; Kuņicina, N

    2007-01-01

    In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...

  17. Air conditioning with methane: Efficiency and economics optimization parameters

    International Nuclear Information System (INIS)

    Mastrullo, R.; Sasso, M.; Sibilio, S.; Vanoli, R.

    1992-01-01

    This paper presents an efficiency and economics evaluation method for methane fired cooling systems. Focus is on direct flame two staged absorption systems and alternative engine driven compressor sets. Comparisons are made with conventional vapour compression plants powered by electricity supplied by the national grid. A first and second law based thermodynamics analysis is made in which fuel use coefficients and exergy yields are determined. The economics analysis establishes annual energy savings, unit cooling energy production costs, payback periods and economics/efficiency optimization curves useful for preliminary feasibility studies

  18. Parameter selection for the SSC trade-offs and optimization

    International Nuclear Information System (INIS)

    Edwards, D.A.; Syphers, M.J.

    1991-01-01

    In November of 1988, a site was selected in the state of Texas for the SSC. In January of 1989, the SSC Laboratory was established in Texas to adapt the design of the collider to the site and to manage the construction of the project. This paper describes the evolution of the SSC design since site selection, notes the increased concentration on the injector system, and addresses the rationale for choice of parameters

  19. Diagnostics and tolerance optimization of nuclear facilities parameters

    International Nuclear Information System (INIS)

    Novak, M.; Otcenasek, P.

    1988-01-01

    The possibilities are discussed of applying the theory of tolerances for assessing the service life of systems in nuclear power. The approach proceeds from the postulate that the nuclear power plant is on the one hand an extremely sophisticated technical system and on the other a system with well defined demands on the state and properties of components and of the whole system, with rationally defined limits, conditions of permissible states and limit values. It is stated that the basic ideas of the theory of the hot channel may be extended and generalized. The theory was initially limited to the study of relations between deviations in nucleaer and non-nuclear parameters in the fuel assembly, and the temperature field; it can be generalized to the analysis of permissible parameter tolerances of the whole system. The foundations are outlined of the theory of tolerances of general technical system parameters. Brief attention is also paid to the general possibilities of the use of life curves for designing the system such as would extend its service life. (Z.M.). 10 figs., 5 refs

  20. Optimization of process parameters through GRA, TOPSIS and RSA models

    Directory of Open Access Journals (Sweden)

    Suresh Nipanikar

    2018-01-01

    Full Text Available This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min, feed (0.08, 0.15, 0.2 mm/rev and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oi

  1. Relationships among various parameters for decision tree optimization

    KAUST Repository

    Hussain, Shahid

    2014-01-14

    In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

  2. Relationships among various parameters for decision tree optimization

    KAUST Repository

    Hussain, Shahid

    2014-01-01

    In this chapter, we study, in detail, the relationships between various pairs of cost functions and between uncertainty measure and cost functions, for decision tree optimization. We provide new tools (algorithms) to compute relationship functions, as well as provide experimental results on decision tables acquired from UCI ML Repository. The algorithms presented in this paper have already been implemented and are now a part of Dagger, which is a software system for construction/optimization of decision trees and decision rules. The main results presented in this chapter deal with two types of algorithms for computing relationships; first, we discuss the case where we construct approximate decision trees and are interested in relationships between certain cost function, such as depth or number of nodes of a decision trees, and an uncertainty measure, such as misclassification error (accuracy) of decision tree. Secondly, relationships between two different cost functions are discussed, for example, the number of misclassification of a decision tree versus number of nodes in a decision trees. The results of experiments, presented in the chapter, provide further insight. © 2014 Springer International Publishing Switzerland.

  3. Optimizing the Use of Resources of Technogenic Deposits Taking into Account Uncertainties

    Directory of Open Access Journals (Sweden)

    Ivan Mikhaylovich Potravny

    2017-12-01

    Full Text Available The article discusses the problem of resource deterioration and the exhaustion of natural resources as well as the involvement in economic circulation of waste production, resources of technogenic deposits in order to maintain natural capital and support “green” economic growth. This necessitates the development of the mechanism for the environmental management optimization. This mechanism aims at using technogenic deposits in the economy to decrease of both the nature intensity of production and the cost of production. Furthermore, the environmental management optimization should reduce the negative impact of production on the environment. The authors propose to construct a model of economic relevance for the use of waste based on the theory of sustainable development and the theory of substitution of primary natural resources. Under substitutes, we consider useful products, resources from technogenic deposits, resulting from past economic activities. The article considers the problem of accumulation of municipal solid waste and industrial wastes in the regions of Russia in terms of forming and operating the ever-growing technogenic deposits. The authors propose a set of models for the optimum exploitation of technogenic deposits taking into account various factors of the external and internal environment as well as the time factor. The proposed models allow to substantiate and choose the best technologies for the processing of accumulated waste in terms of the reduction of pollution and “green” revenues from the exploitation of technogenic deposits. To account the probabilistic assessments of the geological structure of the technogenic deposits, we propose to use a combination of Monte-Carlo method and of developed optimization models. The authors describe the calculation results and the prospects for the development of a comprehensive model using regional technogenic deposits. The results of the research allow forming an optimal set

  4. A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision

    Directory of Open Access Journals (Sweden)

    loubna benchikhi

    2017-10-01

    Full Text Available Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO, reinforcement learning (RL and ant colony optimization (ACO show the efficiency of this novel method.

  5. Sediment transport modeling in deposited bed sewers: unified form of May's equations using the particle swarm optimization algorithm.

    Science.gov (United States)

    Safari, Mir Jafar Sadegh; Shirzad, Akbar; Mohammadi, Mirali

    2017-08-01

    May proposed two dimensionless parameters of transport (η) and mobility (F s ) for self-cleansing design of sewers with deposited bed condition. The relationships between those two parameters were introduced in conditional form for specific ranges of F s , which makes it difficult to use as a practical tool for sewer design. In this study, using the same experimental data used by May and employing the particle swarm optimization algorithm, a unified equation is recommended based on η and F s . The developed model is compared with original May relationships as well as corresponding models available in the literature. A large amount of data taken from the literature is used for the models' evaluation. The results demonstrate that the developed model in this study is superior to May and other existing models in the literature. Due to the fact that in May's dimensionless parameters more effective variables in the sediment transport process in sewers with deposited bed condition are considered, it is concluded that the revised May equation proposed in this study is a reliable model for sewer design.

  6. Optimization of sampling parameters for standardized exhaled breath sampling.

    Science.gov (United States)

    Doran, Sophie; Romano, Andrea; Hanna, George B

    2017-09-05

    The lack of standardization of breath sampling is a major contributing factor to the poor repeatability of results and hence represents a barrier to the adoption of breath tests in clinical practice. On-line and bag breath sampling have advantages but do not suit multicentre clinical studies whereas storage and robust transport are essential for the conduct of wide-scale studies. Several devices have been developed to control sampling parameters and to concentrate volatile organic compounds (VOCs) onto thermal desorption (TD) tubes and subsequently transport those tubes for laboratory analysis. We conducted three experiments to investigate (i) the fraction of breath sampled (whole vs. lower expiratory exhaled breath); (ii) breath sample volume (125, 250, 500 and 1000ml) and (iii) breath sample flow rate (400, 200, 100 and 50 ml/min). The target VOCs were acetone and potential volatile biomarkers for oesophago-gastric cancer belonging to the aldehyde, fatty acids and phenol chemical classes. We also examined the collection execution time and the impact of environmental contamination. The experiments showed that the use of exhaled breath-sampling devices requires the selection of optimum sampling parameters. The increase in sample volume has improved the levels of VOCs detected. However, the influence of the fraction of exhaled breath and the flow rate depends on the target VOCs measured. The concentration of potential volatile biomarkers for oesophago-gastric cancer was not significantly different between the whole and lower airway exhaled breath. While the recovery of phenols and acetone from TD tubes was lower when breath sampling was performed at a higher flow rate, other VOCs were not affected. A dedicated 'clean air supply' overcomes the contamination from ambient air, but the breath collection device itself can be a source of contaminants. In clinical studies using VOCs to diagnose gastro-oesophageal cancer, the optimum parameters are 500mls sample volume

  7. Parameter extraction using global particle swarm optimization approach and the influence of polymer processing temperature on the solar cell parameters

    Science.gov (United States)

    Kumar, S.; Singh, A.; Dhar, A.

    2017-08-01

    The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.

  8. Influence of the growth parameters on TiO2 thin films deposited using the MOCVD method

    Directory of Open Access Journals (Sweden)

    Bernardi M. I. B.

    2002-01-01

    Full Text Available In this work we report the synthesis of TiO2 thin films by the Organometallic Chemical Vapor Deposition (MOCVD method. The influence of deposition parameters used during the growth in the obtained structural characteristics was studied. Different temperatures of the organometallic bath, deposition time, temperature and type of the substrate were combined. Using Scanning Electron Microscopy associated to Electron Dispersive X-Ray Spectroscopy, Atomic Force Microscopy and X-ray Diffraction, the strong influence of these parameters in the thin films final microstructure was verified.

  9. Optimization of dissolution process parameters for uranium ore concentrate powders

    Energy Technology Data Exchange (ETDEWEB)

    Misra, M.; Reddy, D.M.; Reddy, A.L.V.; Tiwari, S.K.; Venkataswamy, J.; Setty, D.S.; Sheela, S.; Saibaba, N. [Nuclear Fuel Complex, Hyderabad (India)

    2013-07-01

    Nuclear fuel complex processes Uranium Ore Concentrate (UOC) for producing uranium dioxide powder required for the fabrication of fuel assemblies for Pressurized Heavy Water Reactor (PHWR)s in India. UOC is dissolved in nitric acid and further purified by solvent extraction process for producing nuclear grade UO{sub 2} powder. Dissolution of UOC in nitric acid involves complex nitric oxide based reactions, since it is in the form of Uranium octa oxide (U{sub 3}O{sub 8}) or Uranium Dioxide (UO{sub 2}). The process kinetics of UOC dissolution is largely influenced by parameters like concentration and flow rate of nitric acid, temperature and air flow rate and found to have effect on recovery of nitric oxide as nitric acid. The plant scale dissolution of 2 MT batch in a single reactor is studied and observed excellent recovery of oxides of nitrogen (NO{sub x}) as nitric acid. The dissolution process is automated by PLC based Supervisory Control and Data Acquisition (SCADA) system for accurate control of process parameters and successfully dissolved around 200 Metric Tons of UOC. The paper covers complex chemistry involved in UOC dissolution process and also SCADA system. The solid and liquid reactions were studied along with multiple stoichiometry of nitrous oxide generated. (author)

  10. Optimization of Experimental Model Parameter Identification for Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Rosario Morello

    2013-09-01

    Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.

  11. Parameters and design optimization of the ring piezoelectric ceramic transformer

    Directory of Open Access Journals (Sweden)

    Jiří Erhart

    2015-09-01

    Full Text Available Main aim of the presented paper is the theoretical analysis and experimental verification of the transformation parameters for the new type of nonhomogeneously poled ring transformer. The input part is poled in the thickness direction and output part in the radial direction. Two transformer geometries are studied — the input part is at inner ring segment, or it is at the outer ring segment. The optimum electrode size aspect ratios have been found experimentally as d1∕D≈0.60−0.65 for the ring with aspect ratio d∕D=0.2. The fundamental as well as higher overtone resonances were studied for the transformation ratio, the optimum resistive load, efficiency and no-load transformation ratio. Higher overtones have better transformation parameters compared to the fundamental resonance. The new type ring transformer exhibits very high transformation ratios up to 200 under no-load and up to 13.4 under a high efficiency of 97% at the optimum load conditions of 10 kΩ. Strong electric field gradient at the output circuit is applicable for the electrical discharge generation.

  12. Composition and structure variation for magnetron sputtered tantalum oxynitride thin films, as function of deposition parameters

    Energy Technology Data Exchange (ETDEWEB)

    Cristea, D.; Pătru, M.; Crisan, A.; Munteanu, D. [Department of Materials Science, Transilvania University, 500036 Brasov (Romania); Crăciun, D. [Laser Department, National Institute for Laser, Plasma, and Radiation Physics, Magurele (Romania); Barradas, N.P. [Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, E.N. 10 ao km 139,7, 2695-066 Bobadela LRS (Portugal); Alves, E. [Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, E.N. 10 ao km 139,7, 2695-066 Bobadela LRS (Portugal); Apreutesei, M. [Université de Lyon, Institut des Nanotechnologies de Lyon INL-UMR 5270, CNRS, Ecole Centrale de Lyon, Ecully F-69134 (France); MATEIS Laboratory-INSA de Lyon, Bât. B. Pascal, 7 Avenue Jean Capelle, 69621 Villeurbanne Cedex (France); Moura, C. [Center of Physics, University of Minho, Campus de Gualtar, 4710-057 Braga (Portugal); Cunha, L., E-mail: lcunha@fisica.uminho.pt [Center of Physics, University of Minho, Campus de Gualtar, 4710-057 Braga (Portugal)

    2015-12-15

    Highlights: • Structural evolution from β-Ta, to fcc-Ta(O,N), to amorphous Ta{sub 2}O{sub 5} with increasing P(N{sub 2} + O{sub 2}). • The substrate bias influences the N content, but does not influence the O content of the films. • The structural features of the films appear at lower P(N{sub 2} + O{sub 2}) when produced with grounded substrate. - Abstract: Tantalum oxynitride thin films were produced by magnetron sputtering. The films were deposited using a pure Ta target and a working atmosphere with a constant N{sub 2}/O{sub 2} ratio. The choice of this constant ratio limits the study concerning the influence of each reactive gas, but allows a deeper understanding of the aspects related to the affinity of Ta to the non-metallic elements and it is economically advantageous. This work begins by analysing the data obtained directly from the film deposition stage, followed by the analysis of the morphology, composition and structure. For a better understanding regarding the influence of the deposition parameters, the analyses are presented by using the following criterion: the films were divided into two sets, one of them produced with grounded substrate holder and the other with a polarization of −50 V. Each one of these sets was produced with different partial pressure of the reactive gases P(N{sub 2} + O{sub 2}). All the films exhibited a O/N ratio higher than the N/O ratio in the deposition chamber atmosphere. In the case of the films produced with grounded substrate holder, a strong increase of the O content is observed, associated to the strong decrease of the N content, when P(N{sub 2} + O{sub 2}) is higher than 0.13 Pa. The higher Ta affinity for O strongly influences the structural evolution of the films. Grazing incidence X-ray diffraction showed that the lower partial pressure films were crystalline, while X-ray reflectivity studies found out that the density of the films depended on the deposition conditions: the higher the gas pressure, the

  13. Joint optimization of collimator and reconstruction parameters in SPECT imaging for lesion quantification

    International Nuclear Information System (INIS)

    McQuaid, Sarah J; Southekal, Sudeepti; Kijewski, Marie Foley; Moore, Stephen C

    2011-01-01

    Obtaining the best possible task performance using reconstructed SPECT images requires optimization of both the collimator and reconstruction parameters. The goal of this study is to determine how to perform this optimization, namely whether the collimator parameters can be optimized solely from projection data, or whether reconstruction parameters should also be considered. In order to answer this question, and to determine the optimal collimation, a digital phantom representing a human torso with 16 mm diameter hot lesions (activity ratio 8:1) was generated and used to simulate clinical SPECT studies with parallel-hole collimation. Two approaches to optimizing the SPECT system were then compared in a lesion quantification task: sequential optimization, where collimation was optimized on projection data using the Cramer–Rao bound, and joint optimization, which simultaneously optimized collimator and reconstruction parameters. For every condition, quantification performance in reconstructed images was evaluated using the root-mean-squared-error of 400 estimates of lesion activity. Compared to the joint-optimization approach, the sequential-optimization approach favoured a poorer resolution collimator, which, under some conditions, resulted in sub-optimal estimation performance. This implies that inclusion of the reconstruction parameters in the optimization procedure is important in obtaining the best possible task performance; in this study, this was achieved with a collimator resolution similar to that of a general-purpose (LEGP) collimator. This collimator was found to outperform the more commonly used high-resolution (LEHR) collimator, in agreement with other task-based studies, using both quantification and detection tasks.

  14. Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

    Science.gov (United States)

    Yu, Tao; Kang, Chao; Zhao, Pan

    2018-01-01

    The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

  15. Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method

    International Nuclear Information System (INIS)

    Sun Jun; Zhao Ji; Wu Xiaojun; Fang Wei; Cai Yujie; Xu Wenbo

    2010-01-01

    Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics.

  16. Thermal expansion and lattice parameters of shaped metal deposited Ti-6Al-4V

    Energy Technology Data Exchange (ETDEWEB)

    Swarnakar, Akhilesh Kumar; Van der Biest, Omer [Katholieke Universiteit Leuven, MTM, Kasteelpark Arenberg 44, 3001 Leuven (Belgium); Baufeld, Bernd, E-mail: b.baufeld@sheffield.ac.uk [Katholieke Universiteit Leuven, MTM, Kasteelpark Arenberg 44, 3001 Leuven (Belgium)

    2011-02-10

    Research highlights: > Measurement of thermal expansion and of the lattice parameters of Ti-6Al-4V fabricated by shaped metal deposition up to 1100 {sup o}C. > The observation of alpha to beta transformation not reflected in the expansion but in the contraction curve is explained by non-equilibrium alpha phase of the SMD material. > Denuding of the {alpha} phase and enrichment of the {beta} phase of Vanadium due to high temperature experiments. > The unit cell volumes derived from lattice parameters measured by X-ray diffraction are at room temperature larger for the {alpha} than for the {beta} phase. With increasing temperature the unit cell volume of the {beta} phase increases stronger than the one of the {alpha} phase resulting in a similar unit cell volume at the {beta} transus temperature. - Abstract: Thermal expansion and lattice parameters are investigated up to 1100 deg. C for Ti-6Al-4V components, fabricated by shaped metal deposition. This is a novel additive layer manufacturing technique where near net-shape components are built by tungsten inert gas welding. The as-fabricated SMD Ti-6Al-4V components exhibit a constant coefficient of thermal expansion of 1.17 x 10{sup -5} K{sup -1} during heating up to 1100 {sup o}C, not reflecting the {alpha} to {beta} phase transformation. During cooling a stalling of the contraction is observed starting at the {beta} transus temperature. These high temperature experiments denude the {alpha} phase of V and enrich the {beta} phase. The development of the lattice parameters in dependence on temperature are observed with high temperature X-ray diffraction. The unit cell volumes derived from these parameters are at room temperature larger for the {alpha} than for the {beta} phase. With increasing temperature the unit cell volume of the {beta} phase increases stronger than the one of the {alpha} phase resulting in a similar unit cell volume at the {beta} transus temperature. These observations are interpreted as an

  17. Metallic Fuel Casting Development and Parameter Optimization Simulations

    International Nuclear Information System (INIS)

    Fielding, Randall S.; Kennedy, J.R.; Crapps, J.; Unal, C.

    2013-01-01

    Conclusions: • Gravity casting is a feasible process for casting of metallic fuels: – May not be as robust as CGIC, more parameter dependent to find right “sweet spot” for high quality castings; – Fluid flow is very important and is affected by mold design, vent size, super heat, etc.; – Pressure differential assist was found to be detrimental. • Simulation found that vent location was important to allow adequate filling of mold; • Surface tension plays an important role in determining casting quality; • Casting and simulations high light the need for better characterized fluid physical and thermal properties; • Results from simulations will be incorporated in GACS design such as vent location and physical property characterization

  18. Beyond bixels: Generalizing the optimization parameters for intensity modulated radiation therapy

    International Nuclear Information System (INIS)

    Markman, Jerry; Low, Daniel A.; Beavis, Andrew W.; Deasy, Joseph O.

    2002-01-01

    Intensity modulated radiation therapy (IMRT) treatment planning systems optimize fluence distributions by subdividing the fluence distribution into rectangular bixels. The algorithms typically optimize the fluence intensity directly, often leading to fluence distributions with sharp discontinuities. These discontinuities may yield difficulties in delivery of the fluence distribution, leading to inaccurate dose delivery. We have developed a method for decoupling the bixel intensities from the optimization parameters; either by introducing optimization control points from which the bixel intensities are interpolated or by parametrizing the fluence distribution using basis functions. In either case, the number of optimization search parameters is reduced from the direct bixel optimization method. To illustrate the concept, the technique is applied to two-dimensional idealized head and neck treatment plans. The interpolation algorithms investigated were nearest-neighbor, linear and cubic spline, and radial basis functions serve as the basis function test. The interpolation and basis function optimization techniques were compared against the direct bixel calculation. The number of optimization parameters were significantly reduced relative to the bixel optimization, and this was evident in the reduction of computation time of as much as 58% from the full bixel optimization. The dose distributions obtained using the reduced optimization parameter sets were very similar to the full bixel optimization when examined by dose distributions, statistics, and dose-volume histograms. To evaluate the sensitivity of the fluence calculations to spatial misalignment caused either by delivery errors or patient motion, the doses were recomputed with a 1 mm shift in each beam and compared to the unshifted distributions. Except for the nearest-neighbor algorithm, the reduced optimization parameter dose distributions were generally less sensitive to spatial shifts than the bixel

  19. PARAMETERS OPTIMIZATION OF METAL-DIELECTRIC NANOSTRUCTURES FOR SENSOR APPLICATIONS

    Directory of Open Access Journals (Sweden)

    V. I. Egorov

    2014-07-01

    Full Text Available We present calculation results of optical properties of silver nanoparticles with dielectric shell in relation to their applications in chemical and biosensors. Absorption cross-section calculation for spherical silver nanoparticles was performed by quasi static dipole approximation. It is shown that dielectric shell thickness equal to 2-3 nm and its refraction index equal to 1,5-1,75 are optimal. Calculation results were compared to experimental data. Experimental investigation of metal-dielectric nanostructures sensitivity to external refraction index was performed. Synthesis of silver nanoparticles with dielectric shell on glass surface was performed by nanosecond laser ablation method in near-surface glass layer at 1,06 μm wavelength (Solar LQ129. Synthesis of silver nanoparticles without a shell on the glass surface with silver ions was performed using thermal treatment in wet atmosphere. Spectrophotometer Cary 500 (Varyan was used for spectral measurements. In case of laser ablation method application, external refraction index changes from 1 (the air to 1,33 (water and plasmon resonance band shift for 6 nm occurs. In case of another method application at the same conditions the registered shift was equal to 13 nm. However, in the latter case the particles can be easily removed from the substrate surface. Obtained results will be useful for developing chemical and biological sensors based on plasmon resonance band shift.

  20. Steam condenser optimization using Real-parameter Genetic Algorithm for Prototype Fast Breeder Reactor

    International Nuclear Information System (INIS)

    Jayalal, M.L.; Kumar, L. Satish; Jehadeesan, R.; Rajeswari, S.; Satya Murty, S.A.V.; Balasubramaniyan, V.; Chetal, S.C.

    2011-01-01

    Highlights: → We model design optimization of a vital reactor component using Genetic Algorithm. → Real-parameter Genetic Algorithm is used for steam condenser optimization study. → Comparison analysis done with various Genetic Algorithm related mechanisms. → The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.

  1. Optimization of process parameters in drilling of fibre hybrid composite using Taguchi and grey relational analysis

    Science.gov (United States)

    Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.

    2017-03-01

    Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.

  2. Steam condenser optimization using Real-parameter Genetic Algorithm for Prototype Fast Breeder Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jayalal, M.L., E-mail: jayalal@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Kumar, L. Satish, E-mail: satish@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Jehadeesan, R., E-mail: jeha@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Rajeswari, S., E-mail: raj@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Satya Murty, S.A.V., E-mail: satya@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Balasubramaniyan, V.; Chetal, S.C. [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India)

    2011-10-15

    Highlights: > We model design optimization of a vital reactor component using Genetic Algorithm. > Real-parameter Genetic Algorithm is used for steam condenser optimization study. > Comparison analysis done with various Genetic Algorithm related mechanisms. > The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.

  3. Parameters for modelling the interception and retention of deposits from atmosphere by grain and leafy vegetables

    International Nuclear Information System (INIS)

    Simmonds, J.R.; Linsley, G.S.

    1982-01-01

    The Normalised Specific Activity (NSA), a quantity which relates the concentration of a contaminant per unit mass of vegetation to its daily rate of ground deposition, has been used as the basis for determining interception factors and retention half-lives for radioactive contaminants deposited on grain and leafy vegetables. The values are for use in assessing contamination levels on crops at harvest during condition of continuous deposition. The approach implicitly takes account of other processes which influence foliar contamination, namely, translocation and dilution due to plant growth. The respective NSA values for grain and prepared leafy vegetables determined from several separate experimental studies are fairly constant and are of about the same level for fall-out strontium and caesium. There is evidence from previous studies on herbage to suggest that similar NSA values might be expected for other contaminants on grain and leafy vegetables. Plutonium is an exception in that NSA values for grain and prepared leafy vegetables are lower than those for the fission products by factors of between 5 and 10 depending upon the source of the contaminant. Consideration has been given to determining the most appropriate value of the fraction of activity transferred from grain to flour during refining. This is an element dependent parameter and the values estimated for strontium, caesium and plutonium are respectively 0.15, 0.5 and 0.1. The study has indicated the need for data in several areas in order to improve the capability to model interception and retention on field crops in continuous and acute release conditions. (author)

  4. Biomimetic Cationic Nanoparticles Based on Silica: Optimizing Bilayer Deposition from Lipid Films

    Directory of Open Access Journals (Sweden)

    Rodrigo T. Ribeiro

    2017-10-01

    Full Text Available The optimization of bilayer coverage on particles is important for a variety of biomedical applications, such as drug, vaccine, and genetic material delivery. This work aims at optimizing the deposition of cationic bilayers on silica over a range of experimental conditions for the intervening medium and two different assemblies for the cationic lipid, namely, lipid films or pre-formed lipid bilayer fragments. The lipid adsorption on silica in situ over a range of added lipid concentrations was determined from elemental analysis of carbon, hydrogen, and nitrogen and related to the colloidal stability, sizing, zeta potential, and polydispersity of the silica/lipid nanoparticles. Superior bilayer deposition took place from lipid films, whereas adsorption from pre-formed bilayer fragments yielded limiting adsorption below the levels expected for bilayer adsorption.

  5. Optimization of Performance Parameters for Large Area Silicon Photomultipliers

    Science.gov (United States)

    Janzen, Kathryn

    2008-10-01

    The goal of the GlueX experiment is to search for exotic hybrid mesons as evidence of gluonic excitations in an effort to better understand confinement. A key component of the GlueX detector is the electromagnetic barrel calorimeter (BCAL) located immediately inside a superconducting solenoid of approximately 2.5T. Because of this arrangement, traditional vacuum photomultiplier tubes (PMTs) which are affected significantly by magnetic fields cannot be used on the BCAL. The use of Silicon photomultipliers (SiPMs) as front-end detectors has been proposed. While the largest SiPMs that have been previously employed by other experiments are 1x1 mm^2, GlueX proposes to use large area SiPMs each composed of 16 - 3x3 mm^2 cells in a 4x4 array. This puts the GlueX collaboration in the unique position of driving the technology for larger area sensors. In this talk I will discuss tests done in Regina regarding performance parameters of prototype SiPM arrays delivered by SensL, a photonics research and development company based in Ireland, as well as sample 1x1 mm^2 and 3x3 mm^2 SiPMs.

  6. SU-E-T-295: Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT)

    Energy Technology Data Exchange (ETDEWEB)

    Zarepisheh, M; Li, R; Xing, L [Stanford UniversitySchool of Medicine, Stanford, CA (United States); Ye, Y [Stanford Univ, Management Science and Engineering, Stanford, Ca (United States); Boyd, S [Stanford University, Electrical Engineering, Stanford, CA (United States)

    2014-06-01

    Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves

  7. SU-E-T-295: Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT)

    International Nuclear Information System (INIS)

    Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S

    2014-01-01

    Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves

  8. THE PARAMETER OPTIMIZATION MODEL OF INVESTMENT AND CONSTRUCTION PROJECTS AND MANAGERIAL FEASIBILITY OF THEIR BEHAVIOR

    Directory of Open Access Journals (Sweden)

    P. Ye. Uvarov

    2009-09-01

    Full Text Available In the article the basic problem of substantiation of parameters of optimization model of organizationaltechnological solutions for investment-building projects in the system of project management is considered.

  9. Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

    Directory of Open Access Journals (Sweden)

    Omar Ahmed Mohamed

    2016-11-01

    Full Text Available Fused deposition modeling (FDM additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM and multilayer feed-forward neural networks (MFNNs. The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM. Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

  10. Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

    Science.gov (United States)

    Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

    2016-01-01

    Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019

  11. A Parameter Estimation Method for Nonlinear Systems Based on Improved Boundary Chicken Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Shaolong Chen

    2016-01-01

    Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.

  12. Adjoint Parameter Sensitivity Analysis for the Hydrodynamic Lattice Boltzmann Method with Applications to Design Optimization

    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...

  13. Real-time parameter optimization based on neural network for smart injection molding

    Science.gov (United States)

    Lee, H.; Liau, Y.; Ryu, K.

    2018-03-01

    The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. Injection molding process has a short cycle time and high productivity. This features have been making it suitable for mass production. In addition, this process is used to produce precise parts in various industry fields such as automobiles, optics and medical devices. Injection molding process has a mixture of discrete and continuous variables. In order to optimized the quality, variables that is generated in the injection molding process must be considered. Furthermore, Optimal parameter setting is time-consuming work to predict the optimum quality of the product. Since the process parameter cannot be easily corrected during the process execution. In this research, we propose a neural network based real-time process parameter optimization methodology that sets optimal process parameters by using mold data, molding machine data, and response data. This paper is expected to have academic contribution as a novel study of parameter optimization during production compare with pre - production parameter optimization in typical studies.

  14. Optimization of pulsed DC PACVD parameters: Toward reducing wear rate of the DLC films

    Science.gov (United States)

    Ebrahimi, Mansoureh; Mahboubi, Farzad; Naimi-Jamal, M. Reza

    2016-12-01

    The effect of pulsed direct current (DC) plasma-assisted chemical vapor deposition (PACVD) parameters such as temperature, duty cycle, hydrogen flow, and argon/CH4 flow ratio on the wear behavior and wear durability of the diamond-like carbon (DLC) films was studied by using response surface methodology (RSM). DLC films were deposited on nitrocarburized AISI 4140 steel. Wear rate and wear durability of the DLC films were examined with the pin-on-disk method. Field emission scanning electron microscopy, Raman spectroscopy, and nanoindentation techniques were used for studying wear mechanisms, chemical structure, and hardness of the DLC films. RSM results show that duty cycle is one of the important parameters that affect the wear rate of the DLC samples. The wear rate of the samples deposited with a duty cycle of >75% decreases with an increase in the argon/CH4 ratio. In contrast, for a duty cycle of <65%, the wear rate increases with an increase in the argon/CH4 ratio. The wear durability of the DLC samples increases with an increase in the duty cycle, hydrogen flow, and argon/CH4 flow ratio at the deposition temperature between 85 °C and 110 °C. Oxidation, fatigue, abrasive wear, and graphitization are the wear mechanisms observed on the wear scar of the DLC samples deposited with the optimum deposition conditions.

  15. On the deposition parameters of indium oxide (IO) and tin oxide (TO) by reactive evaporation technique

    International Nuclear Information System (INIS)

    Hassan, F.; Abdullah, A.H.; Salam, R.

    1990-01-01

    Thin films of tin oxide (TO) and indium oxide (IO) are prepared by the reactive evaporation technique, where indium or tin sources are evaporated and made to react with oxygen gas injected close to the substrate. In both depositions a substrate temperature of 380 0 C and a chamber pressure of 2x10 -5 mbar are utilized, but however different oxygen flow rates has been maintained. For TO, the deposition rate is found to be constant up to about 55 minutes of deposition time with a deposition rate of about 0.10 A/s, but for longer deposition time the deposition rate increases rapidly up to about 0.30 A/s. The IO displays a higher deposition rate of about 0.80 A/s over a deposition time 30 minutes, beyond which the deposition rate increases gradually

  16. Network optimization including gas lift and network parameters under subsurface uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Schulze-Riegert, R.; Baffoe, J.; Pajonk, O. [SPT Group GmbH, Hamburg (Germany); Badalov, H.; Huseynov, S. [Technische Univ. Clausthal, Clausthal-Zellerfeld (Germany). ITE; Trick, M. [SPT Group, Calgary, AB (Canada)

    2013-08-01

    Optimization of oil and gas field production systems poses a great challenge to field development due to complex and multiple interactions between various operational design parameters and subsurface uncertainties. Conventional analytical methods are capable of finding local optima based on single deterministic models. They are less applicable for efficiently generating alternative design scenarios in a multi-objective context. Practical implementations of robust optimization workflows integrate the evaluation of alternative design scenarios and multiple realizations of subsurface uncertainty descriptions. Production or economic performance indicators such as NPV (Net Present Value) are linked to a risk-weighted objective function definition to guide the optimization processes. This work focuses on an integrated workflow using a reservoir-network simulator coupled to an optimization framework. The work will investigate the impact of design parameters while considering the physics of the reservoir, wells, and surface facilities. Subsurface uncertainties are described by well parameters such as inflow performance. Experimental design methods are used to investigate parameter sensitivities and interactions. Optimization methods are used to find optimal design parameter combinations which improve key performance indicators of the production network system. The proposed workflow will be applied to a representative oil reservoir coupled to a network which is modelled by an integrated reservoir-network simulator. Gas-lift will be included as an explicit measure to improve production. An objective function will be formulated for the net present value of the integrated system including production revenue and facility costs. Facility and gas lift design parameters are tuned to maximize NPV. Well inflow performance uncertainties are introduced with an impact on gas lift performance. Resulting variances on NPV are identified as a risk measure for the optimized system design. A

  17. Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jing Li

    2017-01-01

    Full Text Available The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS model and improved particle swarm optimization (PSO algorithm. A method to optimize air conditioning parameters and installation distance is proposed. The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities. A laboratory model is established, and simulated flow field information is obtained with the CFD software. Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output “metamodels” for the subsequent optimization. With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized. The functions comprise PMV, PPD, and mean age of air. The optimal installation distance is determined with the hemisphere model. Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device. The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.

  18. Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters.

    Science.gov (United States)

    Stewart, James J P

    2013-01-01

    Modern semiempirical methods are of sufficient accuracy when used in the modeling of molecules of the same type as used as reference data in the parameterization. Outside that subset, however, there is an abundance of evidence that these methods are of very limited utility. In an attempt to expand the range of applicability, a new method called PM7 has been developed. PM7 was parameterized using experimental and high-level ab initio reference data, augmented by a new type of reference data intended to better define the structure of parameter space. The resulting method was tested by modeling crystal structures and heats of formation of solids. Two changes were made to the set of approximations: a modification was made to improve the description of noncovalent interactions, and two minor errors in the NDDO formalism were rectified. Average unsigned errors (AUEs) in geometry and ΔHf for PM7 were reduced relative to PM6; for simple gas-phase organic systems, the AUE in bond lengths decreased by about 5% and the AUE in ΔHf decreased by about 10%; for organic solids, the AUE in ΔHf dropped by 60% and the reduction was 33.3% for geometries. A two-step process (PM7-TS) for calculating the heights of activation barriers has been developed. Using PM7-TS, the AUE in the barrier heights for simple organic reactions was decreased from values of 12.6 kcal/mol(-1) in PM6 and 10.8 kcal/mol(-1) in PM7 to 3.8 kcal/mol(-1). The origins of the errors in NDDO methods have been examined, and were found to be attributable to inadequate and inaccurate reference data. This conclusion provides insight into how these methods can be improved.

  19. Sensitivity of the optimal parameter settings for a LTE packet scheduler

    NARCIS (Netherlands)

    Fernandez-Diaz, I.; Litjens, R.; van den Berg, C.A.; Dimitrova, D.C.; Spaey, K.

    Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to various

  20. The primary ion source for construction and optimization of operation parameters

    International Nuclear Information System (INIS)

    Synowiecki, A.; Gazda, E.

    1986-01-01

    The construction of primary ion source for SIMS has been presented. The influence of individual operation parameters on the properties of ion source has been investigated. Optimization of these parameters has allowed to appreciate usefulness of the ion source for SIMS study. 14 refs., 8 figs., 2 tabs. (author)

  1. Study on feed forward neural network convex optimization for LiFePO4 battery parameters

    Science.gov (United States)

    Liu, Xuepeng; Zhao, Dongmei

    2017-08-01

    Based on the modern facility agriculture automatic walking equipment LiFePO4 Battery, the parameter identification of LiFePO4 Battery is analyzed. An improved method for the process model of li battery is proposed, and the on-line estimation algorithm is presented. The parameters of the battery are identified using feed forward network neural convex optimization algorithm.

  2. Optimization of exploring well laying place from parameter of regional ecological protection point of view

    International Nuclear Information System (INIS)

    Khairov, G.B.

    1997-01-01

    In this article an influence of petroleum industry and especially discovery of hydrocarbon deposits with high content of hydrogen sulfide to ecological safety and environment is shown. New criteria for zoning and geological estimation are presented. For the first time a parameter of territory ecological protection is offered. (author)

  3. Optimization of the Electrodeposition Parameters to Improve the Stoichiometry of In2S3 Films for Solar Applications Using the Taguchi Method

    Directory of Open Access Journals (Sweden)

    Maqsood Ali Mughal

    2014-01-01

    Full Text Available Properties of electrodeposited semiconductor thin films are dependent upon the electrolyte composition, plating time, and temperature as well as the current density and the nature of the substrate. In this study, the influence of the electrodeposition parameters such as deposition voltage, deposition time, composition of solution, and deposition temperature upon the properties of In2S3 films was analyzed by the Taguchi Method. According to Taguchi analysis, the interaction between deposition voltage and deposition time was significant. Deposition voltage had the largest impact upon the stoichiometry of In2S3 films and deposition temperature had the least impact. The stoichiometric ratios between sulfur and indium (S/In: 3/2 obtained from experiments performed with optimized electrodeposition parameters were in agreement with predicted values from the Taguchi Method. The experiments were carried out according to Taguchi orthogonal array L27 (3^4 design of experiments (DOE. Approximately 600 nm thick In2S3 films were electrodeposited from an organic bath (ethylene glycol-based containing indium chloride (InCl3, sodium chloride (NaCl, and sodium thiosulfate (Na2S2O3·5H2O, the latter used as an additional sulfur source along with elemental sulfur (S. An X-ray diffractometer (XRD, energy dispersive X-ray spectroscopy (EDS unit, and scanning electron microscope (SEM were, respectively, used to analyze the phases, elemental composition, and morphology of the electrodeposited In2S3 films.

  4. Intermolecular Force Field Parameters Optimization for Computer Simulations of CH4 in ZIF-8

    Directory of Open Access Journals (Sweden)

    Phannika Kanthima

    2016-01-01

    Full Text Available The differential evolution (DE algorithm is applied for obtaining the optimized intermolecular interaction parameters between CH4 and 2-methylimidazolate ([C4N2H5]− using quantum binding energies of CH4-[C4N2H5]− complexes. The initial parameters and their upper/lower bounds are obtained from the general AMBER force field. The DE optimized and the AMBER parameters are then used in the molecular dynamics (MD simulations of CH4 molecules in the frameworks of ZIF-8. The results show that the DE parameters are better for representing the quantum interaction energies than the AMBER parameters. The dynamical and structural behaviors obtained from MD simulations with both sets of parameters are also of notable differences.

  5. 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.

  6. Optimization of machining parameters of turning operations based on multi performance criteria

    Directory of Open Access Journals (Sweden)

    N.K.Mandal

    2013-01-01

    Full Text Available The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA. Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.

  7. Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Bambang Wahono

    2015-07-01

    Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.

  8. Optimization of parameters for the inline-injection system at Brookhaven Accelerator Test Facility

    International Nuclear Information System (INIS)

    Parsa, Z.; Ko, S.K.

    1995-01-01

    We present some of our parameter optimization results utilizing code PARMLEA, for the ATF Inline-Injection System. The new solenoid-Gun-Solenoid -- Drift-Linac Scheme would improve the beam quality needed for FEL and other experiments at ATF as compared to the beam quality of the original design injection system. To optimize the gain in the beam quality we have considered various parameters including the accelerating field gradient on the photoathode, the Solenoid field strengths, separation between the gun and entrance to the linac as well as the (type size) initial charge distributions. The effect of the changes in the parameters on the beam emittance is also given

  9. Warpage improvement on wheel caster by optimizing the process parameters using genetic algorithm (GA)

    Science.gov (United States)

    Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

    2017-09-01

    In injection moulding process, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively.

  10. Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

    International Nuclear Information System (INIS)

    Xu Ruirui; Chen Tianlun; Gao Chengfeng

    2006-01-01

    Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

  11. A procedure for multi-objective optimization of tire design parameters

    Directory of Open Access Journals (Sweden)

    Nikola Korunović

    2015-04-01

    Full Text Available The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.

  12. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

    Directory of Open Access Journals (Sweden)

    Huanqing Cui

    2017-03-01

    Full Text Available Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  13. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

    Science.gov (United States)

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-03-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  14. Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

    Science.gov (United States)

    Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

    2018-03-01

    Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

  15. Optimization of spray deposition and Tetranychus urticae control with air assisted and electrostatic sprayer

    Directory of Open Access Journals (Sweden)

    Denise Tourino Rezende de Cerqueira

    Full Text Available ABSTRACT: Improved spray deposition can be attained by electrostatically charging spray droplets, which increases the attraction of droplets to plants and decreases operator exposure to pesticide and losses to the environment. However, this technique alone is not sufficient to achieve desirable penetration of the spray solution into the crop canopy; thus, air assistance can be added to the electrostatic spraying to further improve spray deposition. This study was conducted to compare different spraying technologies on spray deposition and two-spotted spider mite control in cut chrysanthemum. Treatments included in the study were: conventional TJ 8003 double flat fan nozzles, conventional TXVK-3 hollow cone nozzles, semi-stationary motorized jet launched spray with electrostatic spray system (ESS and air assistance (AA, and semi-stationary motorized jet launched spray with AA only (no ESS. To evaluate the effect of these spraying technologies on the control of two-spotted spider mite, a control treatment was included that did not receive an acaricide application. The AA spraying technology, with or without ESS, optimized spray deposition and provided satisfactory two-spotted spider mite control up to 4 days after application.

  16. Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

    International Nuclear Information System (INIS)

    Dougher, J.D.

    1987-01-01

    The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed

  17. Self-optimized metal coatings for fiber plasmonics by electroless deposition.

    Science.gov (United States)

    Bialiayeu, A; Caucheteur, C; Ahamad, N; Ianoul, A; Albert, J

    2011-09-26

    We present a novel method to prepare optimized metal coatings for infrared Surface Plasmon Resonance (SPR) sensors by electroless plating. We show that Tilted Fiber Bragg grating sensors can be used to monitor in real-time the growth of gold nano-films up to 70 nm in thickness and to stop the deposition of the gold at a thickness that maximizes the SPR (near 55 nm for sensors operating in the near infrared at wavelengths around 1550 nm). The deposited films are highly uniform around the fiber circumference and in spite of some nanoscale roughness (RMS surface roughness of 5.17 nm) the underlying gratings show high quality SPR responses in water. © 2011 Optical Society of America

  18. Optimization studies of HgSe thin film deposition by electrochemical atomic layer epitaxy (EC-ALE)

    CSIR Research Space (South Africa)

    Venkatasamy, V

    2006-06-01

    Full Text Available Studies of the optimization of HgSe thin film deposition using electrochemical atomic layer epitaxy (EC-ALE) are reported. Cyclic voltammetry was used to obtain approximate deposition potentials for each element. These potentials were then coupled...

  19. Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

    Energy Technology Data Exchange (ETDEWEB)

    Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A

    2009-02-26

    The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.

  20. Effects of processing parameters on the properties of tantalum nitride thin films deposited by reactive sputtering

    Energy Technology Data Exchange (ETDEWEB)

    Nazon, J.; Sarradin, J.; Flaud, V.; Tedenac, J.C. [Institut Charles Gerhardt, UMR 5253 CNRS-UM2-ENSCM-UM1, cc 1504, Place E. Bataillon, 34095 Montpellier Cedex 5 (France); Frety, N. [Institut Charles Gerhardt, UMR 5253 CNRS-UM2-ENSCM-UM1, cc 1504, Place E. Bataillon, 34095 Montpellier Cedex 5 (France)], E-mail: Nicole.Frety@univ-montp2.fr

    2008-09-22

    The effects of processing parameters on the properties of tantalum nitride thin films deposited by radio frequency reactive sputtering have been investigated. The influence of the N{sub 2} partial and (Ar + N{sub 2}) total gas pressures as well as the sputtering power on the microstructure and electrical properties is reported. Rising the N{sub 2} partial pressure, from 2 to 10.7%, induces a change in the composition of the {delta}-TaN phase, from TaN to TaN{sub 1.13}. This composition change is associated with a drastic increase of the electrical resistivity over a 7.3% N{sub 2} partial pressure. The total gas pressure is revealed to strongly affect the film microstructure since a variation in both composition and grain size is observed when the gas pressure rises from 6.8 to 24.6 Pa. When the sputtering power varied between 50 and 110 W, an increase of the grain size related to a decrease of the electrical resistivity is observed.

  1. Use of multilevel modeling for determining optimal parameters of heat supply systems

    Science.gov (United States)

    Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.

    2017-07-01

    The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in

  2. Parameter identification using optimization techniques in the continuous simulation programs FORSIM and MACKSIM

    International Nuclear Information System (INIS)

    Carver, M.B.; Austin, C.F.; Ross, N.E.

    1980-02-01

    This report discusses the mechanics of automated parameter identification in simulation packages, and reviews available integration and optimization algorithms and their interaction within the recently developed optimization options in the FORSIM and MACKSIM simulation packages. In the MACKSIM mass-action chemical kinetics simulation package, the form and structure of the ordinary differential equations involved is known, so the implementation of an optimizing option is relatively straightforward. FORSIM, however, is designed to integrate ordinary and partial differential equations of abritrary definition. As the form of the equations is not known in advance, the design of the optimizing option is more intricate, but the philosophy could be applied to most simulation packages. In either case, however, the invocation of the optimizing interface is simple and user-oriented. Full details for the use of the optimizing mode for each program are given; specific applications are used as examples. (O.T.)

  3. Chaotic invasive weed optimization algorithm with application to parameter estimation of chaotic systems

    International Nuclear Information System (INIS)

    Ahmadi, Mohamadreza; Mojallali, Hamed

    2012-01-01

    Highlights: ► A new meta-heuristic optimization algorithm. ► Integration of invasive weed optimization and chaotic search methods. ► A novel parameter identification scheme for chaotic systems. - Abstract: This paper introduces a novel hybrid optimization algorithm by taking advantage of the stochastic properties of chaotic search and the invasive weed optimization (IWO) method. In order to deal with the weaknesses associated with the conventional method, the proposed chaotic invasive weed optimization (CIWO) algorithm is presented which incorporates the capabilities of chaotic search methods. The functionality of the proposed optimization algorithm is investigated through several benchmark multi-dimensional functions. Furthermore, an identification technique for chaotic systems based on the CIWO algorithm is outlined and validated by several examples. The results established upon the proposed scheme are also supplemented which demonstrate superior performance with respect to other conventional methods.

  4. A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process

    Science.gov (United States)

    Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa

    2017-06-01

    High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio ( S/ N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.

  5. Selection of Near Optimal Laser Cutting Parameters in CO2 Laser Cutting by the Taguchi Method

    Directory of Open Access Journals (Sweden)

    Miloš MADIĆ

    2013-12-01

    Full Text Available Identification of laser cutting conditions that are insensitive to parameter variations and noise is of great importance. This paper demonstrates the application of Taguchi method for optimization of surface roughness in CO2 laser cutting of stainless steel. The laser cutting experiment was planned and conducted according to the Taguchi’s experimental design using the L27 orthogonal array. Four laser cutting parameters such as laser power, cutting speed, assist gas pressure, and focus position were considered in the experiment. Using the analysis of means and analysis of variance, the significant laser cutting parameters were identified, and subsequently the optimal combination of laser cutting parameter levels was determined. The results showed that the cutting speed is the most significant parameter affecting the surface roughness whereas the influence of the assist gas pressure can be neglected. It was observed, however, that interaction effects have predominant influence over the main effects on the surface roughness.

  6. Application of Factorial Design for Gas Parameter Optimization in CO2 Laser Welding

    DEFF Research Database (Denmark)

    Gong, Hui; Dragsted, Birgitte; Olsen, Flemming Ove

    1997-01-01

    The effect of different gas process parameters involved in CO2 laser welding has been studied by applying two-set of three-level complete factorial designs. In this work 5 gas parameters, gas type, gas flow rate, gas blowing angle, gas nozzle diameter, gas blowing point-offset, are optimized...... to be a very useful tool for parameter optimi-zation in laser welding process. Keywords: CO2 laser welding, gas parameters, factorial design, Analysis of Variance........ The bead-on-plate welding specimens are evaluated by a number of quality char-acteristics, such as the penetration depth and the seam width. The significance of the gas pa-rameters and their interactions are based on the data found by the Analysis of Variance-ANOVA. This statistic methodology is proven...

  7. Error propagation of partial least squares for parameters optimization in NIR modeling.

    Science.gov (United States)

    Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

    2018-03-05

    A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

  8. Error propagation of partial least squares for parameters optimization in NIR modeling

    Science.gov (United States)

    Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

    2018-03-01

    A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

  9. Grinding Parameter Optimization of Ultrasound-Aided Electrolytic in Process Dressing for Finishing Nanocomposite Ceramics

    Directory of Open Access Journals (Sweden)

    Fan Chen

    2016-01-01

    Full Text Available In order to achieve the precision and efficient processing of nanocomposite ceramics, the ultrasound-aided electrolytic in process dressing method was proposed. But how to realize grinding parameter optimization, that is, the maximum processing efficiency, on the premise of the assurance of best workpiece quality is a problem that needs to be solved urgently. Firstly, this research investigated the influence of grinding parameters on material removal rate and critical ductile depth, and their mathematic models based on the existing models were developed to simulate the material removal process. Then, on the basis of parameter sensitivity analysis based on partial derivative, the sensitivity models of material removal rates on grinding parameter were established and computed quantitatively by MATLAB, and the key grinding parameter for optimal grinding process was found. Finally, the theoretical analyses were verified by experiments: the material removal rate increases with the increase of grinding parameters, including grinding depth (ap, axial feeding speed (fa, workpiece speed (Vw, and wheel speed (Vs; the parameter sensitivity of material removal rate was in a descending order as ap>fa>Vw>Vs; the most sensitive parameter (ap was optimized and it was found that the better machining result has been obtained when ap was about 3.73 μm.

  10. Fault detection of feed water treatment process using PCA-WD with parameter optimization.

    Science.gov (United States)

    Zhang, Shirong; Tang, Qian; Lin, Yu; Tang, Yuling

    2017-05-01

    Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T 2 and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA-WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T 2 and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an automatic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Development and Application of a Tool for Optimizing Composite Matrix Viscoplastic Material Parameters

    Science.gov (United States)

    Murthy, Pappu L. N.; Naghipour Ghezeljeh, Paria; Bednarcyk, Brett A.

    2018-01-01

    This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is

  12. Evaluation and optimization of footwear comfort parameters using finite element analysis and a discrete optimization algorithm

    Science.gov (United States)

    Papagiannis, P.; Azariadis, P.; Papanikos, P.

    2017-10-01

    Footwear is subject to bending and torsion deformations that affect comfort perception. Following review of Finite Element Analysis studies of sole rigidity and comfort, a three-dimensional, linear multi-material finite element sole model for quasi-static bending and torsion simulation, overcoming boundary and optimisation limitations, is described. Common footwear materials properties and boundary conditions from gait biomechanics are used. The use of normalised strain energy for product benchmarking is demonstrated along with comfort level determination through strain energy density stratification. Sensitivity of strain energy against material thickness is greater for bending than for torsion, with results of both deformations showing positive correlation. Optimization for a targeted performance level and given layer thickness is demonstrated with bending simulations sufficing for overall comfort assessment. An algorithm for comfort optimization w.r.t. bending is presented, based on a discrete approach with thickness values set in line with practical manufacturing accuracy. This work illustrates the potential of the developed finite element analysis applications to offer viable and proven aids to modern footwear sole design assessment and optimization.

  13. An automated analysis workflow for optimization of force-field parameters using neutron scattering data

    Energy Technology Data Exchange (ETDEWEB)

    Lynch, Vickie E.; Borreguero, Jose M. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Bhowmik, Debsindhu [Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Ganesh, Panchapakesan; Sumpter, Bobby G. [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Proffen, Thomas E. [Neutron Data Analysis & Visualization Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Goswami, Monojoy, E-mail: goswamim@ornl.gov [Center for Nanophase Material Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States); Computational Sciences & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831 (United States)

    2017-07-01

    Graphical abstract: - Highlights: • An automated workflow to optimize force-field parameters. • Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA. • The mechanism relies on molecular dynamics simulation and neutron scattering experimental data. • The workflow can be generalized to any other experimental and simulation techniques. - Abstract: Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D{sub 2}O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.

  14. Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

    Science.gov (United States)

    Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

    2016-01-01

    Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

  15. Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model

    Energy Technology Data Exchange (ETDEWEB)

    Rengers, Francis; Lunacek, Monte; Tucker, Gregory

    2016-06-01

    Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-05-15

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

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

    International Nuclear Information System (INIS)

    Rao, R. Venkata; Rai, Dhiraj P.

    2017-01-01

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

  18. Themoeconomic optimization of triple pressure heat recovery steam generator operating parameters for combined cycle plants

    Directory of Open Access Journals (Sweden)

    Mohammd Mohammed S.

    2015-01-01

    Full Text Available The aim of this work is to develop a method for optimization of operating parameters of a triple pressure heat recovery steam generator. Two types of optimization: (a thermodynamic and (b thermoeconomic were preformed. The purpose of the thermodynamic optimization is to maximize the efficiency of the plant. The selected objective for this purpose is minimization of the exergy destruction in the heat recovery steam generator (HRSG. The purpose of the thermoeconomic optimization is to decrease the production cost of electricity. Here, the total annual cost of HRSG, defined as a sum of annual values of the capital costs and the cost of the exergy destruction, is selected as the objective function. The optimal values of the most influencing variables are obtained by minimizing the objective function while satisfying a group of constraints. The optimization algorithm is developed and tested on a case of CCGT plant with complex configuration. Six operating parameters were subject of optimization: pressures and pinch point temperatures of every three (high, intermediate and low pressure steam stream in the HRSG. The influence of these variables on the objective function and production cost are investigated in detail. The differences between results of thermodynamic and the thermoeconomic optimization are discussed.

  19. GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

    International Nuclear Information System (INIS)

    Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

    2015-01-01

    Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

  20. Optimization of process parameters in welding of dissimilar steels using robot TIG welding

    Science.gov (United States)

    Navaneeswar Reddy, G.; VenkataRamana, M.

    2018-03-01

    Robot TIG welding is a modern technique used for joining two work pieces with high precision. Design of Experiments is used to conduct experiments by varying weld parameters like current, wire feed and travelling speed. The welding parameters play important role in joining of dissimilar stainless steel SS 304L and SS430. In this work, influences of welding parameter on Robot TIG Welded specimens are investigated using Response Surface Methodology. The Micro Vickers hardness tests of the weldments are measured. The process parameters are optimized to maximize the hardness of the weldments.

  1. Comparative study for different statistical models to optimize cutting parameters of CNC end milling machines

    International Nuclear Information System (INIS)

    El-Berry, A.; El-Berry, A.; Al-Bossly, A.

    2010-01-01

    In machining operation, the quality of surface finish is an important requirement for many work pieces. Thus, that is very important to optimize cutting parameters for controlling the required manufacturing quality. Surface roughness parameter (Ra) in mechanical parts depends on turning parameters during the turning process. In the development of predictive models, cutting parameters of feed, cutting speed, depth of cut, are considered as model variables. For this purpose, this study focuses on comparing various machining experiments which using CNC vertical machining center, work pieces was aluminum 6061. Multiple regression models are used to predict the surface roughness at different experiments.

  2. Mechanical Properties Optimization of Poly-Ether-Ether-Ketone via Fused Deposition Modeling

    Directory of Open Access Journals (Sweden)

    Xiaohu Deng

    2018-01-01

    Full Text Available Compared to the common selective laser sintering (SLS manufacturing method, fused deposition modeling (FDM seems to be an economical and efficient three-dimensional (3D printing method for high temperature polymer materials in medical applications. In this work, a customized FDM system was developed for polyether-ether-ketone (PEEK materials printing. The effects of printing speed, layer thickness, printing temperature and filling ratio on tensile properties were analyzed by the orthogonal test of four factors and three levels. Optimal tensile properties of the PEEK specimens were observed at a printing speed of 60 mm/s, layer thickness of 0.2 mm, temperature of 370 °C and filling ratio of 40%. Furthermore, the impact and bending tests were conducted under optimized conditions and the results demonstrated that the printed PEEK specimens have appropriate mechanical properties.

  3. Mechanical Properties Optimization of Poly-Ether-Ether-Ketone via Fused Deposition Modeling.

    Science.gov (United States)

    Deng, Xiaohu; Zeng, Zhi; Peng, Bei; Yan, Shuo; Ke, Wenchao

    2018-01-30

    Compared to the common selective laser sintering (SLS) manufacturing method, fused deposition modeling (FDM) seems to be an economical and efficient three-dimensional (3D) printing method for high temperature polymer materials in medical applications. In this work, a customized FDM system was developed for polyether-ether-ketone (PEEK) materials printing. The effects of printing speed, layer thickness, printing temperature and filling ratio on tensile properties were analyzed by the orthogonal test of four factors and three levels. Optimal tensile properties of the PEEK specimens were observed at a printing speed of 60 mm/s, layer thickness of 0.2 mm, temperature of 370 °C and filling ratio of 40%. Furthermore, the impact and bending tests were conducted under optimized conditions and the results demonstrated that the printed PEEK specimens have appropriate mechanical properties.

  4. Laser Welding Process Parameters Optimization Using Variable-Fidelity Metamodel and NSGA-II

    Directory of Open Access Journals (Sweden)

    Wang Chaochao

    2017-01-01

    Full Text Available An optimization methodology based on variable-fidelity (VF metamodels and nondominated sorting genetic algorithm II (NSGA-II for laser bead-on-plate welding of stainless steel 316L is presented. The relationships between input process parameters (laser power, welding speed and laser focal position and output responses (weld width and weld depth are constructed by VF metamodels. In VF metamodels, the information from two levels fidelity models are integrated, in which the low-fidelity model (LF is finite element simulation model that is used to capture the general trend of the metamodels, and high-fidelity (HF model which from physical experiments is used to ensure the accuracy of metamodels. The accuracy of the VF metamodel is verified by actual experiments. To slove the optimization problem, NSGA-II is used to search for multi-objective Pareto optimal solutions. The results of verification experiments show that the obtained optimal parameters are effective and reliable.

  5. Parameter estimation of fractional-order chaotic systems by using quantum parallel particle swarm optimization algorithm.

    Directory of Open Access Journals (Sweden)

    Yu Huang

    Full Text Available Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.

  6. Optimization of design parameters for bulk micromachined silicon membranes for piezoresistive pressure sensing application

    International Nuclear Information System (INIS)

    Belwanshi, Vinod; Topkar, Anita

    2016-01-01

    Finite element analysis study has been carried out to optimize the design parameters for bulk micro-machined silicon membranes for piezoresistive pressure sensing applications. The design is targeted for measurement of pressure up to 200 bar for nuclear reactor applications. The mechanical behavior of bulk micro-machined silicon membranes in terms of deflection and stress generation has been simulated. Based on the simulation results, optimization of the membrane design parameters in terms of length, width and thickness has been carried out. Subsequent to optimization of membrane geometrical parameters, the dimensions and location of the high stress concentration region for implantation of piezoresistors have been obtained for sensing of pressure using piezoresistive sensing technique.

  7. Optimization of TRPO process parameters for americium extraction from high level waste

    International Nuclear Information System (INIS)

    Chen Jing; Wang Jianchen; Song Chongli

    2001-01-01

    The numerical calculations for Am multistage fractional extraction by trialkyl phosphine oxide (TRPO) were verified by a hot test. 1750L/t-U high level waste (HLW) was used as the feed to the TRPO process. The analysis used the simple objective function to minimize the total waste content in the TRPO process streams. Some process parameters were optimized after other parameters were selected. The optimal process parameters for Am extraction by TRPO are: 10 stages for extraction and 2 stages for scrubbing; a flow rate ratio of 0.931 for extraction and 4.42 for scrubbing; nitric acid concentration of 1.35 mol/L for the feed and 0.5 mol/L for the scrubbing solution. Finally, the nitric acid and Am concentration profiles in the optimal TRPO extraction process are given

  8. Thermo-mechanical simulation and parameters optimization for beam blank continuous casting

    International Nuclear Information System (INIS)

    Chen, W.; Zhang, Y.Z.; Zhang, C.J.; Zhu, L.G.; Lu, W.G.; Wang, B.X.; Ma, J.H.

    2009-01-01

    The objective of this work is to optimize the process parameters of beam blank continuous casting in order to ensure high quality and productivity. A transient thermo-mechanical finite element model is developed to compute the temperature and stress profile in beam blank continuous casting. By comparing the calculated data with the metallurgical constraints, the key factors causing defects of beam blank can be found out. Then based on the subproblem approximation method, an optimization program is developed to search out the optimum cooling parameters. Those optimum parameters can make it possible to run the caster at its maximum productivity, minimum cost and to reduce the defects. Now, online verifying of this optimization project has been put in practice, which can prove that it is very useful to control the actual production

  9. Optimization of design parameters for bulk micromachined silicon membranes for piezoresistive pressure sensing application

    Science.gov (United States)

    Belwanshi, Vinod; Topkar, Anita

    2016-05-01

    Finite element analysis study has been carried out to optimize the design parameters for bulk micro-machined silicon membranes for piezoresistive pressure sensing applications. The design is targeted for measurement of pressure up to 200 bar for nuclear reactor applications. The mechanical behavior of bulk micro-machined silicon membranes in terms of deflection and stress generation has been simulated. Based on the simulation results, optimization of the membrane design parameters in terms of length, width and thickness has been carried out. Subsequent to optimization of membrane geometrical parameters, the dimensions and location of the high stress concentration region for implantation of piezoresistors have been obtained for sensing of pressure using piezoresistive sensing technique.

  10. Experimental Study of Direct Laser Deposition of Ti-6Al-4V and Inconel 718 by Using Pulsed Parameters

    Directory of Open Access Journals (Sweden)

    Kamran Shah

    2014-01-01

    Full Text Available Laser direct metal deposition (LDMD has developed from a prototyping to a single metal manufacturing tool. Its potential for creating multimaterial and functionally graded structures is now beginning to be explored. This work is a first part of a study in which a single layer of Inconel 718 is deposited on Ti-6Al-4V substrate. Single layer tracks were built at a range of powder mass flow rates using a coaxial nozzle and 1.5 kW diode laser operating in both continuous and pulsed beam modes. This part of the study focused on the experimental findings during the deposition of Inconel 718 powder on Ti-6Al-4V substrate. Scanning electron microscopy (SEM and X-ray diffraction analysis were performed for characterization and phase identification. Residual stress measurement had been carried out to ascertain the effects of laser pulse parameters on the crack development during the deposition process.

  11. Optimization of laser energy deposition for single-shot high aspect-ratio microstructuring of thick BK7 glass

    Energy Technology Data Exchange (ETDEWEB)

    Garzillo, Valerio; Grigutis, Robertas [Dipartimento di Scienza e Alta Tecnologia, University of Insubria, Via Valleggio 11, I-22100 Como (Italy); Jukna, Vytautas [Centre de Physique Theorique, CNRS, Ecole Polytechnique, Université Paris-Saclay, F-91128 Palaiseau (France); LOA, ENSTA-ParisTech, CNRS, Ecole Polytechnique, Université Paris Saclay, F-91762 Palaiseau (France); Couairon, Arnaud [Centre de Physique Theorique, CNRS, Ecole Polytechnique, Université Paris-Saclay, F-91128 Palaiseau (France); Di Trapani, Paolo [Dipartimento di Scienza e Alta Tecnologia, University of Insubria and CNISM UdR Como, Via Valleggio 11, I-22100 Como (Italy); Jedrkiewicz, Ottavia, E-mail: ottavia.jedrkiewicz@ifn.cnr.it [Istituto di Fotonica e Nanotecnologie, CNR and CNISM UdR Como, Via Valleggio 11, I-22100 Como (Italy)

    2016-07-07

    We investigate the generation of high aspect ratio microstructures across 0.7 mm thick glass by means of single shot Bessel beam laser direct writing. We study the effect on the photoinscription of the cone angle, as well as of the energy and duration of the ultrashort laser pulse. The aim of the study is to optimize the parameters for the writing of a regular microstructure due to index modification along the whole sample thickness. By using a spectrally resolved single pulse transmission diagnostics at the output surface of the glass, we correlate the single shot material modification with observations of the absorption in different portions of the retrieved spectra, and with the absence or presence of spectral modulation. Numerical simulations of the evolution of the Bessel pulse intensity and of the energy deposition inside the sample help us interpret the experimental results that suggest to use picosecond pulses for an efficient and more regular energy deposition. Picosecond pulses take advantage of nonlinear plasma absorption and avoid temporal dynamics effects which can compromise the stationarity of the Bessel beam propagation.

  12. PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization

    Directory of Open Access Journals (Sweden)

    S. Chebli

    2016-09-01

    Full Text Available In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI based congestion controller in active queue management (AQM router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters.

  13. Optimization of growth parameters of hydrogenated amorphous silicon-sulphur alloys

    International Nuclear Information System (INIS)

    Al-Dallal, S.; Aljishi, S.; Arekat, S.; Al-alawi, S.M.; Hammam, H.

    1995-01-01

    Hydrogenated amorphous silicon sulphur thin films were grown by capacitively coupled radio frequency glow discharge decomposition of SiH/sub 4/ + He) and H/sub 2/S + He) gas mixtures. In this work we report on a study undertaken to instigative the effect of deposition conditions on the optoelectronic properties of a-Si,S:H films. Three series of deposition conditions on the optoelectronic properties of a-Si,S:H films. Three series of films were prepared using a constant flow rate of the gaseous mixture while varying one of the other deposition parameters: substrate temperature, RF powder and process pressure. The films are characterized via IR measurements, optical transmission, photothermal deflection spectroscopy, photoluminescence, the constant photocurrent methods and conductivity measurements. Results indicate that a relatively high power level and a high substrate temperature are necessary to obtain the best films. (author) 8 figs

  14. A multicriteria framework with voxel-dependent parameters for radiotherapy treatment plan optimization

    International Nuclear Information System (INIS)

    Zarepisheh, Masoud; Uribe-Sanchez, Andres F.; Li, Nan; Jia, Xun; Jiang, Steve B.

    2014-01-01

    Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for a set of the objective functions associated to the organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the impact of using different objective functions on plan qualities and Pareto surfaces. The main discoveries are threefold: (1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly

  15. VISUALIZATION SOFTWARE DEVELOPMENT FOR PROCEDURE OF MULTI-DIMENSIONAL OPTIMIZATION OF TECHNOLOGICAL PROCESS FUNCTIONAL PARAMETERS

    Directory of Open Access Journals (Sweden)

    E. N. Ishakova

    2016-05-01

    Full Text Available A method for multi-criteria optimization of the design parameters for technological object is described. The existing optimization methods are overviewed, and works in the field of basic research and applied problems are analyzed. The problem is formulated, based on the process requirements, making it possible to choose the geometrical dimensions of machine tips and the flow rate of the process, so that the resulting technical and economical parameters were optimal. In the problem formulation application of the performance method adapted to a particular domain is described. Task implementation is shown; the method of characteristics creation for the studied object in view of some restrictions for parameters in both analytical and graphical representation. On the basis of theoretical research the software system is developed that gives the possibility to automate the discovery of optimal solutions for specific problems. Using available information sources, that characterize the object of study, it is possible to establish identifiers, add restrictions from the one side, and in the interval as well. Obtained result is a visual depiction of dependence of the main study parameters on the others, which may have an impact on both the flow of the process, and the quality of products. The resulting optimal area shows the use of different design options for technological object in an acceptable kinematic range that makes it possible for the researcher to choose the best design solution.

  16. Study of dose calculation and beam parameters optimization with genetic algorithm in IMRT

    International Nuclear Information System (INIS)

    Chen Chaomin; Tang Mutao; Zhou Linghong; Lv Qingwen; Wang Zhuoyu; Chen Guangjie

    2006-01-01

    Objective: To study the construction of dose calculation model and the method of automatic beam parameters selection in IMRT. Methods: The three-dimension convolution dose calculation model of photon was constructed with the methods of Fast Fourier Transform. The objective function based on dose constrain was used to evaluate the fitness of individuals. The beam weights were optimized with genetic algorithm. Results: After 100 iterative analyses, the treatment planning system produced highly conformal and homogeneous dose distributions. Conclusion: the throe-dimension convolution dose calculation model of photon gave more accurate results than the conventional models; genetic algorithm is valid and efficient in IMRT beam parameters optimization. (authors)

  17. Iterative choice of the optimal regularization parameter in TV image deconvolution

    International Nuclear Information System (INIS)

    Sixou, B; Toma, A; Peyrin, F; Denis, L

    2013-01-01

    We present an iterative method for choosing the optimal regularization parameter for the linear inverse problem of Total Variation image deconvolution. This approach is based on the Morozov discrepancy principle and on an exponential model function for the data term. The Total Variation image deconvolution is performed with the Alternating Direction Method of Multipliers (ADMM). With a smoothed l 2 norm, the differentiability of the value of the Lagrangian at the saddle point can be shown and an approximate model function obtained. The choice of the optimal parameter can be refined with a Newton method. The efficiency of the method is demonstrated on a blurred and noisy bone CT cross section

  18. Error reduction and parameter optimization of the TAPIR method for fast T1 mapping.

    Science.gov (United States)

    Zaitsev, M; Steinhoff, S; Shah, N J

    2003-06-01

    A methodology is presented for the reduction of both systematic and random errors in T(1) determination using TAPIR, a Look-Locker-based fast T(1) mapping technique. The relations between various sequence parameters were carefully investigated in order to develop recipes for choosing optimal sequence parameters. Theoretical predictions for the optimal flip angle were verified experimentally. Inversion pulse imperfections were identified as the main source of systematic errors in T(1) determination with TAPIR. An effective remedy is demonstrated which includes extension of the measurement protocol to include a special sequence for mapping the inversion efficiency itself. Copyright 2003 Wiley-Liss, Inc.

  19. Optimization of Cutting Parameters of the Haynes 718 Nickel Alloy With Gas CO2 Laser

    Directory of Open Access Journals (Sweden)

    Jana PETRŮ

    2011-06-01

    Full Text Available This article deals with the application of laser technology and the optimization of parameters in the area of nickel alloy laser cutting intended for application in the aircraft industry. The main goal is to outline possibilities of use of the laser technology, primarily its application in the area of 3D material cutting. This experiment is focused on the optimization of cutting parameters of the Haynes 718 alloy with a gas CO2 laser. Originating cuts are evaluated primarily from the point of view of cut quality and accompanying undesirable phenomena occurring in the process of cutting. In conclusion the results achieved in the metallographic laboratory are described and analyzed.

  20. Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

    The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...

  1. Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

    Energy Technology Data Exchange (ETDEWEB)

    Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

  2. Optimizing the dermal accumulation of a tazarotene microemulsion using skin deposition modeling.

    Science.gov (United States)

    Nasr, Maha; Abdel-Hamid, Sameh

    2016-01-01

    It is well known that microemulsions are mainly utilized for their transdermal rather than their dermal drug delivery potential due to their low viscosity, and the presence of penetration enhancing surfactants and co-surfactants. Applying quality by design (QbD) principles, a tazarotene microemulsion formulation for local skin delivery was optimized by creating a control space. Critical formulation factors (CFF) were oil, surfactant/co-surfactant (SAA/CoS), and water percentages. Critical quality attributes (CQA) were globular size, microemulsion viscosity, tazarotene skin deposition, permeation, and local accumulation efficiency index. Increasing oil percentage increased globular size, while the opposite occurred regarding SAA/CoS, (p = 0.001). Microemulsion viscosity was reduced by increasing oil and water percentages (p microemulsion viscosity, and drug deposition. A combination of 40% oil and 45% SAA/CoS showed the maximum drug deposition of 75.1%. Clinical skin irritation study showed that the aforementioned formula was safe for topical use. This article suggests that applying QbD tools such as experimental design is an efficient tool for drug product design.

  3. Cathodic deposition of CdSe films from dimethyl formamide solution at optimized temperature

    Energy Technology Data Exchange (ETDEWEB)

    Datta, J. [Department of Chemistry, Bengal Engineering and Science University, Shibpur, Howrah 711 103, West Bengal (India)]. E-mail: jayati_datta@rediffmail.com; Bhattacharya, C. [Department of Chemistry, Bengal Engineering and Science University, Shibpur, Howrah 711 103, West Bengal (India); Visiting Research Associate, School of Materials Science and Engineering, UNSW (Australia); Bandyopadhyay, S. [School of Materials Science and Engineering, UNSW, Sydney 2052 (Australia)

    2006-12-15

    In the present paper, thin film CdSe compound semiconductors have been electroplated on transparent conducting oxide coated glass substrates from nonaqueous dimethyl formamide bath containing CdCl{sub 2}, KI and Se under controlled temperature ranging from 100 to 140 deg. C. Thickness of the deposited films as obtained through focussed ion beam technique as well as their microstructural and photoelectrochemical properties have been found to depend on temperature. The film growth was therefore optimized at a bath temperature {approx}125 deg. C. The formation of crystallites in the range of 100-150 nm size has been ascertained through atomic force microscopy and scanning electron microscopy. Energy dispersive analysis of X-rays for the as deposited film confirmed the 1:1 composition of CdSe compound in the matrix exhibiting band-gap energy of 1.74 eV. Microstructural properties of the deposited films have been determined through X-ray diffraction studies, high-resolution transmission electron microscopy and electron diffraction pattern analysis. Electrochemical impedance spectroscopy and current-potential measurements have been performed to characterize the electrochemical behavior of the semiconductor-electrolyte interface. The photo-activity of the films have been recorded in polysulphide solution under illumination and solar conversion efficiency {>=}1% was achieved.

  4. Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

    Science.gov (United States)

    Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

    2018-03-01

    Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF

  5. A Particle Swarm Optimization of Natural Ventilation Parameters in a Greenhouse with Continuous Roof Vents

    Directory of Open Access Journals (Sweden)

    Abdelhafid HASNI

    2009-03-01

    Full Text Available Although natural ventilation plays an important role in the affecting greenhouse climate, as defined by temperature, humidity and CO2 concentration, particularly in Mediterranean countries, little information and data are presently available on full-scale greenhouse ventilation mechanisms. In this paper, we present a new method for selecting the parameters based on a particle swarm optimization (PSO algorithm which optimize the choice of parameters by minimizing a cost function. The simulator was based on a published model with some minor modifications as we were interested in the parameter of ventilation. The function is defined by a reduced model that could be used to simulate and predict the greenhouse environment, as well as the tuning methods to compute their parameters. This study focuses on the dynamic behavior of the inside air temperature and humidity during ventilation. Our approach is validated by comparison with some experimental results. Various experimental techniques were used to make full-scale measurements of the air exchange rate in a 400 m2 plastic greenhouse. The model which we propose based on natural ventilation parameters optimized by a particle swarm optimization was compared with the measurements results.

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

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2016-01-01

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

  7. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

    Science.gov (United States)

    Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

    2017-09-21

    In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  8. Factorization and the synthesis of optimal feedback gains for distributed parameter systems

    Science.gov (United States)

    Milman, Mark H.; Scheid, Robert E.

    1990-01-01

    An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.

  9. Optimization of basic parameters of cyclic operation of underground gas storages

    Directory of Open Access Journals (Sweden)

    Віктор Олександрович Заєць

    2015-04-01

    Full Text Available The problem of optimization of process parameters of cyclic operation of underground gas storages in gas mode is determined in the article. The target function is defined, expressing necessary capacity of compressor station for gas injection in the storage. Its minimization will find the necessary technological parameters, such as flow and reservoir pressure change over time. Limitations and target function are reduced to a linear form. Solution of problems is made by the simplex method

  10. A parameter estimation for DC servo motor by using optimization process

    International Nuclear Information System (INIS)

    Arjoni Amir

    2010-01-01

    Modeling and simulation parameters of DC servo motor using Matlab Simulink software have been done. The objective to define the DC servo motor parameter estimation is to get DC servo motor parameter values (B, La, Ra, Km, J) which are significant value that can be used for actuation process of control systems. In the analysis of control systems DC the servo motor expressed by transfer function equation to make faster to be analyzed as a component of the actuator. To obtain the data model parameters and initial conditions of the DC servo motors is then carried out the processor modeling and simulation in which the DC servo motor combined with other components. To obtain preliminary data of the DC servo motor parameters as estimated venue, it is obtained from the data factory of the DC servo motor. The initial data parameters of the DC servo motor are applied for the optimization process by using nonlinear least square algorithm and minimize the cost function value so that the DC servo motors parameter values are obtained significantly. The result of the optimization process of the DC servo motor parameter values are B = 0.039881, J= 1.2608e-007, Km = 0.069648, La = 2.3242e-006 and Ra = 1.8837. (author)

  11. Revision of deposition and weathering parameters for the ingestion dose module (ECOSYS) of the ARGOS and RODOS decision support systems

    DEFF Research Database (Denmark)

    Andersson, Kasper Grann; Nielsen, Sven Poul; Thørring, Håvard

    2011-01-01

    The ECOSYS model is the ingestion dose model integrated in the ARGOS and RODOS decision support systems for nuclear emergency management. The parameters used in this model have however not been updated in recent years, where the level of knowledge on various environmental processes has increased...... considerably. A Nordic work group has carried out a series of evaluations of the general validity of current ECOSYS default parameters. This paper specifically discusses the parameter revisions required with respect to the modelling of deposition and natural weathering of contaminants on agricultural crops......, to enable the trustworthy prognostic modelling that is essential to ensure justification and optimisation of countermeasure strategies. New modelling approaches are outlined, since it was found that current ECOSYS approaches for deposition and natural weathering could lead to large prognostic errors....

  12. Influence of deposition parameters and annealing on Cu2ZnSnS4 thin films grown by SILAR

    International Nuclear Information System (INIS)

    Patel, Kinjal; Shah, Dimple V.; Kheraj, Vipul

    2015-01-01

    Highlights: • Optimisation of Cu 2 ZnSnS 4 (CZTS) thin film deposition using SILAR method. • Study on effects of annealing at different temperature under two different ambients, viz. sulphur and tin sulphide. • Formation of CZTS thin films with good crystalline quality confirmed by XRD and Raman spectra. - Abstract: Cu 2 ZnSnS 4 (CZTS) thin films were deposited on glass substrates using Successive Ionic Layer Adsorption and Reaction (SILAR) technique at the room-temperature. The deposition parameters such as concentration of precursors and number of cycles were optimised for the deposition of uniform CZTS thin films. Effects of annealing at different temperature under two different ambient, viz. sulphur and tin sulphide have also been investigated. The structural and optical properties of the films were studied using X-ray diffraction, scanning electron microscopy, Raman spectroscopy and UV-visible spectra in light with the deposition parameters and annealing conditions. It is observed that a good quality CZTS film can be obtained by SILAR at room temperature followed by annealing at 500 °C in presence of sulphur

  13. Optimization of the dressing parameters in cylindrical grinding based on a generalized utility function

    Science.gov (United States)

    Aleksandrova, Irina

    2016-01-01

    The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on the experience of the qualified staff or using data from reference books. The optimal dressing parameters, which are only valid for the particular methods and dressing and grinding conditions, are also used. The paper presents a methodology for optimization of the dressing parameters in cylindrical grinding. The generalized utility function has been chosen as an optimization parameter. It is a complex indicator determining the economic, dynamic and manufacturing characteristics of the grinding process. The developed methodology is implemented for the dressing of aluminium oxide grinding wheels by using experimental diamond roller dressers with different grit sizes made of medium- and high-strength synthetic diamonds type ??32 and ??80. To solve the optimization problem, a model of the generalized utility function is created which reflects the complex impact of dressing parameters. The model is built based on the results from the conducted complex study and modeling of the grinding wheel lifetime, cutting ability, production rate and cutting forces during grinding. They are closely related to the dressing conditions (dressing speed ratio, radial in-feed of the diamond roller dresser and dress-out time), the diamond roller dresser grit size/grinding wheel grit size ratio, the type of synthetic diamonds and the direction of dressing. Some dressing parameters are determined for which the generalized utility function has a maximum and which guarantee an optimum combination of the following: the lifetime and cutting ability of the abrasive wheels, the tangential cutting force magnitude and the production rate of the grinding process. The results obtained prove the possibility of control and optimization of grinding by selecting particular dressing

  14. A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers

    Science.gov (United States)

    Heidari, M.; Ranjithan, S.R.

    1998-01-01

    In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is

  15. Parameter optimization method for longitudinal vibration absorber of ship shaft system

    Directory of Open Access Journals (Sweden)

    LIU Jinlin

    2017-05-01

    Full Text Available The longitudinal vibration of the ship shaft system is the one of the most important factors of hull stern vibration, and it can be effectively minimized by installing a longitudinal vibration absorber. In this way, the vibration and noise of ships can be brought under control. However, the parameters of longitudinal vibration absorbers have a great influence on the vibration characteristics of the shaft system. As such, a certain shafting testing platform was studied as the object on which a finite model was built, and the relationship between longitudinal stiffness and longitudinal vibration in the shaft system was analyzed in a straight alignment state. Furthermore, a longitudinal damping model of the shaft system was built in which the parameters of the vibration absorber were non-dimensionalized, the weight of the vibration absorber was set as a constant, and an optimizing algorithm was used to calculate the optimized stiffness and damping coefficient of the vibration absorber. Finally, the longitudinal vibration frequency response of the shafting testing platform before and after optimizing the parameters of the longitudinal vibration absorber were compared, and the results indicated that the longitudinal vibration of the shafting testing platform was decreased effectively, which suggests that it could provide a theoretical foundation for the parameter optimization of longitudinal vibration absorbers.

  16. High-resolution MRI of the labyrinth. Optimization of scan parameters with 3D-FSE

    International Nuclear Information System (INIS)

    Sakata, Motomichi; Harada, Kuniaki; Shirase, Ryuji; Kumagai, Akiko; Ogasawara, Masashi

    2005-01-01

    The aim of our study was to optimize the parameters of high-resolution MRI of the labyrinth with a 3D fast spin-echo (3D-FSE) sequence. We investigated repetition time (TR), echo time (TE), Matrix, field of view (FOV), and coil selection in terms of CNR (contrast-to-noise ratio) and SNR (signal-to-noise ratio) by comparing axial images and/or three-dimensional images. The optimal 3D-FSE sequence parameters were as follows: 1.5 Tesla MR unit (Signa LX, GE Medical Systems), 3D-FSE sequence, dual 3-inch surface coil, acquisition time=12.08 min, TR=5000 msec, TE=300 msec, 3 number of excitations (NEX), FOV=12 cm, matrix=256 x 256, slice thickness=0.5 mm/0.0 sp, echo train=64, bandwidth=±31.5 kHz. High-resolution MRI of the labyrinth using the optimized 3D-FSE sequence parameters permits visualization of important anatomic details (such as scala tympani and scala vestibuli), making it possible to determine inner ear anomalies and the patency of cochlear turns. To obtain excellent heavily T2-weighted axial and three-dimensional images in the labyrinth, high CNR, SNR, and spatial resolution are significant factors at the present time. Furthermore, it is important not only to optimize the scan parameters of 3D-FSE but also to select an appropriate coil for high-resolution MRI of the labyrinth. (author)

  17. Optimization of Temperature Schedule Parameters on Heat Supply in Power-and-Heat Supply Systems

    Directory of Open Access Journals (Sweden)

    V. A. Sednin

    2009-01-01

    Full Text Available The paper considers problems concerning optimization of a temperature schedule in the district heating systems with steam-turbine thermal power stations having average initial steam parameters. It has been shown in the paper that upkeeping of an optimum network water temperature permits to increase an energy efficiency of heat supply due to additional systematic saving of fuel. 

  18. Fast reactor parameter optimization taking into account changes in fuel charge type during reactor operation time

    International Nuclear Information System (INIS)

    Afrin, B.A.; Rechnov, A.V.; Usynin, G.B.

    1987-01-01

    The formulation and solution of optimization problem for parameters determining the layout of the central part of sodium cooled power reactor taking into account possible changes in fuel charge type during reactor operation time are performed. The losses under change of fuel composition type for two reactor modifications providing for minimum doubling time for oxide and carbide fuels respectively, are estimated

  19. Is transverse feedback necessary for the SSC emittance preservation? (Vibration noise analysis and feedback parameters optimization)

    International Nuclear Information System (INIS)

    Parkhomchuk, V.V.; Shiltsev, V.D.

    1993-06-01

    The paper considers the Superconducting Super Collider (SSC) site ground motion measurements as well as data from accelerators worldwide about noises that worsen beam performance. Unacceptably fast emittance growth due to these noises is predicted for the SSC. A transverse feedback system was found to be the only satisfactory alternative to prevent emittance decay. Optimization of the primary feedback parameters was done

  20. Bounds on Entanglement Dimensions and Quantum Graph Parameters via Noncommutative Polynomial Optimization

    NARCIS (Netherlands)

    Gribling, Sander; de Laat, David; Laurent, Monique

    2017-01-01

    In this paper we study bipartite quantum correlations using techniques from tracial polynomial optimization. We construct a hierarchy of semidefinite programming lower bounds on the minimal entanglement dimension of a bipartite correlation. This hierarchy converges to a new parameter: the minimal

  1. Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

    Energy Technology Data Exchange (ETDEWEB)

    Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Zanela, A. [Rome Univ. `La Sapienza` (Italy). Dipt. di Fisica

    1997-03-01

    An optimization method for some of the CNN`s (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN`s literature.

  2. Optimization of WEDM process parameters using deep cryo-treated Inconel 718 as work material

    Directory of Open Access Journals (Sweden)

    Bijaya Bijeta Nayak

    2016-03-01

    Full Text Available The present work proposes an experimental investigation and optimization of various process parameters during taper cutting of deep cryo-treated Inconel 718 in wire electrical discharge machining process. Taguchi's design of experiment is used to gather information regarding the process with less number of experimental runs considering six input parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension. Since traditional Taguchi method fails to optimize multiple performance characteristics, maximum deviation theory is applied to convert multiple performance characteristics into an equivalent single performance characteristic. Due to the complexity and non-linearity involved in this process, good functional relationship with reasonable accuracy between performance characteristics and process parameters is difficult to obtain. To address this issue, the present study proposes artificial neural network (ANN model to determine the relationship between input parameters and performance characteristics. Finally, the process model is optimized to obtain a best parametric combination by a new meta-heuristic approach known as bat algorithm. The results of the proposed algorithm show that the proposed method is an effective tool for simultaneous optimization of performance characteristics during taper cutting in WEDM process.

  3. An analysis to optimize the process parameters of friction stir welded ...

    African Journals Online (AJOL)

    The friction stir welding (FSW) of steel is a challenging task. Experiments are conducted here, with a tool having a conical pin of 0.4mm clearance. The process parameters are optimized by using the Taguchi technique based on Taguchi's L9 orthogonal array. Experiments have been conducted based on three process ...

  4. Cellular Neural Networks: A genetic algorithm for parameters optimization in artificial vision applications

    International Nuclear Information System (INIS)

    Taraglio, S.; Zanela, A.

    1997-03-01

    An optimization method for some of the CNN's (Cellular Neural Network) parameters, based on evolutionary strategies, is proposed. The new class of feedback template found is more effective in extracting features from the images that an autonomous vehicle acquires, than in the previous CNN's literature

  5. Multi Objective Optimization of Weld Parameters of Boiler Steel Using Fuzzy Based Desirability Function

    Directory of Open Access Journals (Sweden)

    M. Satheesh

    2014-01-01

    Full Text Available The high pressure differential across the wall of pressure vessels is potentially dangerous and has caused many fatal accidents in the history of their development and operation. For this reason the structural integrity of weldments is critical to the performance of pressure vessels. In recent years much research has been conducted to the study of variations in welding parameters and consumables on the mechanical properties of pressure vessel steel weldments to optimize weld integrity and ensure pressure vessels are safe. The quality of weld is a very important working aspect for the manufacturing and construction industries. Because of high quality and reliability, Submerged Arc Welding (SAW is one of the chief metal joining processes employed in industry. This paper addresses the application of desirability function approach combined with fuzzy logic analysis to optimize the multiple quality characteristics (bead reinforcement, bead width, bead penetration and dilution of submerged arc welding process parameters of SA 516 Grade 70 steels(boiler steel. Experiments were conducted using Taguchi’s L27 orthogonal array with varying the weld parameters of welding current, arc voltage, welding speed and electrode stickout. By analyzing the response table and response graph of the fuzzy reasoning grade, optimal parameters were obtained. Solutions from this method can be useful for pressure vessel manufacturers and operators to search an optimal solution of welding condition.

  6. Parameter Optimization for Quantitative Signal-Concentration Mapping Using Spoiled Gradient Echo MRI

    Directory of Open Access Journals (Sweden)

    Gasser Hathout

    2012-01-01

    Full Text Available Rationale and Objectives. Accurate signal to tracer concentration maps are critical to quantitative MRI. The purpose of this study was to evaluate and optimize spoiled gradient echo (SPGR MR sequences for the use of gadolinium (Gd-DTPA as a kinetic tracer. Methods. Water-gadolinium phantoms were constructed for a physiologic range of gadolinium concentrations. Observed and calculated SPGR signal to concentration curves were generated. Using a percentage error determination, optimal pulse parameters for signal to concentration mapping were obtained. Results. The accuracy of the SPGR equation is a function of the chosen MR pulse parameters, particularly the time to repetition (TR and the flip angle (FA. At all experimental values of TR, increasing FA decreases the ratio between observed and calculated signals. Conversely, for a constant FA, increasing TR increases this ratio. Using optimized pulse parameter sets, it is possible to achieve excellent accuracy (approximately 5% over a physiologic range of concentration tracer concentrations. Conclusion. Optimal pulse parameter sets exist and their use is essential for deriving accurate signal to concentration curves in quantitative MRI.

  7. A New Method for Determining Optimal Regularization Parameter in Near-Field Acoustic Holography

    Directory of Open Access Journals (Sweden)

    Yue Xiao

    2018-01-01

    Full Text Available Tikhonov regularization method is effective in stabilizing reconstruction process of the near-field acoustic holography (NAH based on the equivalent source method (ESM, and the selection of the optimal regularization parameter is a key problem that determines the regularization effect. In this work, a new method for determining the optimal regularization parameter is proposed. The transfer matrix relating the source strengths of the equivalent sources to the measured pressures on the hologram surface is augmented by adding a fictitious point source with zero strength. The minimization of the norm of this fictitious point source strength is as the criterion for choosing the optimal regularization parameter since the reconstructed value should tend to zero. The original inverse problem in calculating the source strengths is converted into a univariate optimization problem which is solved by a one-dimensional search technique. Two numerical simulations with a point driven simply supported plate and a pulsating sphere are investigated to validate the performance of the proposed method by comparison with the L-curve method. The results demonstrate that the proposed method can determine the regularization parameter correctly and effectively for the reconstruction in NAH.

  8. Optimization of control parameters of a hot cold controller by means of Simplex type methods

    Science.gov (United States)

    Porte, C.; Caron-Poussin, M.; Carot, S.; Couriol, C.; Moreno, M. Martin; Delacroix, A.

    1997-01-01

    This paper describes a hot/cold controller for regulating crystallization operations. The system was identified with a common method (the Broida method) and the parameters were obtained by the Ziegler-Nichols method. The paper shows that this empirical method will only allow a qualitative approach to regulation and that, in some instances, the parameters obtained are unreliable and therefore cannot be used to cancel variations between the set point and the actual values. Optimization methods were used to determine the regulation parameters and solve this identcation problem. It was found that the weighted centroid method was the best one. PMID:18924791

  9. Process parameter optimization based on principal components analysis during machining of hardened steel

    Directory of Open Access Journals (Sweden)

    Suryakant B. Chandgude

    2015-09-01

    Full Text Available The optimum selection of process parameters has played an important role for improving the surface finish, minimizing tool wear, increasing material removal rate and reducing machining time of any machining process. In this paper, optimum parameters while machining AISI D2 hardened steel using solid carbide TiAlN coated end mill has been investigated. For optimization of process parameters along with multiple quality characteristics, principal components analysis method has been adopted in this work. The confirmation experiments have revealed that to improve performance of cutting; principal components analysis method would be a useful tool.

  10. Parameter optimization for reproducible cardiac 1 H-MR spectroscopy at 3 Tesla.

    Science.gov (United States)

    de Heer, Paul; Bizino, Maurice B; Lamb, Hildo J; Webb, Andrew G

    2016-11-01

    To optimize data acquisition parameters in cardiac proton MR spectroscopy, and to evaluate the intra- and intersession variability in myocardial triglyceride content. Data acquisition parameters at 3 Tesla (T) were optimized and reproducibility measured using, in total, 49 healthy subjects. The signal-to-noise-ratio (SNR) and the variance in metabolite amplitude between averages were measured for: (i) global versus local power optimization; (ii) static magnetic field (B 0 ) shimming performed during free-breathing or within breathholds; (iii) post R-wave peak measurement times between 50 and 900 ms; (iv) without respiratory compensation, with breathholds and with navigator triggering; and (v) frequency selective excitation, Chemical Shift Selective (CHESS) and Multiply Optimized Insensitive Suppression Train (MOIST) water suppression techniques. Using the optimized parameters intra- and intersession myocardial triglyceride content reproducibility was measured. Two cardiac proton spectra were acquired with the same parameters and compared (intrasession reproducibility) after which the subject was removed from the scanner and placed back in the scanner and a third spectrum was acquired which was compared with the first measurement (intersession reproducibility). Local power optimization increased SNR on average by 22% compared with global power optimization (P = 0.0002). The average linewidth was not significantly different for pencil beam B 0 shimming using free-breathing or breathholds (19.1 Hz versus 17.5 Hz; P = 0.15). The highest signal stability occurred at a cardiac trigger delay around 240 ms. The mean amplitude variation was significantly lower for breathholds versus free-breathing (P = 0.03) and for navigator triggering versus free-breathing (P = 0.03) as well as for navigator triggering versus breathhold (P = 0.02). The mean residual water signal using CHESS (1.1%, P = 0.01) or MOIST (0.7%, P = 0.01) water suppression was significantly lower than using

  11. Combination of Compensations and Multi-Parameter Coil for Efficiency Optimization of Inductive Power Transfer System

    Directory of Open Access Journals (Sweden)

    Guozhen Hu

    2017-12-01

    Full Text Available A loosely coupled inductive power transfer (IPT system for industrial track applications has been researched in this paper. The IPT converter using primary Inductor-Capacitor-Inductor (LCL network and secondary parallel-compensations is analyzed combined coil design for optimal operating efficiency. Accurate mathematical analytical model and expressions of self-inductance and mutual inductance are proposed to achieve coil parameters. Furthermore, the optimization process is performed combined with the proposed resonant compensations and coil parameters. The results are evaluated and discussed using finite element analysis (FEA. Finally, an experimental prototype is constructed to verify the proposed approach and the experimental results show that the optimization can be better applied to industrial track distributed IPT system.

  12. Q-Learning Multi-Objective Sequential Optimal Sensor Parameter Weights

    Directory of Open Access Journals (Sweden)

    Raquel Cohen

    2016-04-01

    Full Text Available The goal of our solution is to deliver trustworthy decision making analysis tools which evaluate situations and potential impacts of such decisions through acquired information and add efficiency for continuing mission operations and analyst information.We discuss the use of cooperation in modeling and simulation and show quantitative results for design choices to resource allocation. The key contribution of our paper is to combine remote sensing decision making with Nash Equilibrium for sensor parameter weighting optimization. By calculating all Nash Equilibrium possibilities per period, optimization of sensor allocation is achieved for overall higher system efficiency. Our tool provides insight into what are the most important or optimal weights for sensor parameters and can be used to efficiently tune those weights.

  13. Optimal selection of LQR parameter using AIS for LFC in a multi-area power system

    Directory of Open Access Journals (Sweden)

    Muhammad Abdillah

    2016-12-01

    Full Text Available This paper proposes a method to optimize the parameter of the linear quadratic regulator (LQR using artificial immune system (AIS via clonal selection. The parameters of LQR utilized in this paper are the weighting matrices Q and R. The optimal LQR control for load frequency control (LFC is installed on each area as a decentralized control scheme. The aim of this control design is to improve the dynamic performance of LFC automatically when unexpected load change occurred on power system network. The change of load demands 0.01 p.u used as a disturbance is applied to LFC in Area 1. The proposed method guarantees the stability of the overall closed-loop system. The simulation result shows that the proposed method can reduce the overshoot of the system and compress the time response to steady-state which is better compared to trial error method (TEM and without optimal LQR control.

  14. Parameter optimization of differential evolution algorithm for automatic playlist generation problem

    Science.gov (United States)

    Alamag, Kaye Melina Natividad B.; Addawe, Joel M.

    2017-11-01

    With the digitalization of music, the number of collection of music increased largely and there is a need to create lists of music that filter the collection according to user preferences, thus giving rise to the Automatic Playlist Generation Problem (APGP). Previous attempts to solve this problem include the use of search and optimization algorithms. If a music database is very large, the algorithm to be used must be able to search the lists thoroughly taking into account the quality of the playlist given a set of user constraints. In this paper we perform an evolutionary meta-heuristic optimization algorithm, Differential Evolution (DE) using different combination of parameter values and select the best performing set when used to solve four standard test functions. Performance of the proposed algorithm is then compared with normal Genetic Algorithm (GA) and a hybrid GA with Tabu Search. Numerical simulations are carried out to show better results from Differential Evolution approach with the optimized parameter values.

  15. Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine

    Science.gov (United States)

    Zhang, L.; Zhuge, W. L.; Peng, J.; Liu, S. J.; Zhang, Y. J.

    2013-12-01

    In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (WR and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β6, the exit tip radius R6t and hub radius R6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency ηts, and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency ηts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the value

  16. Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine

    International Nuclear Information System (INIS)

    Zhang, L; Zhuge, W L; Liu, S J; Zhang, Y J; Peng, J

    2013-01-01

    In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (W R and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β 6 , the exit tip radius R 6t and hub radius R 6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency η ts , and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency η ts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the

  17. Optimization of process parameters for a quasi-continuous tablet coating system using design of experiments.

    Science.gov (United States)

    Cahyadi, Christine; Heng, Paul Wan Sia; Chan, Lai Wah

    2011-03-01

    The aim of this study was to identify and optimize the critical process parameters of the newly developed Supercell quasi-continuous coater for optimal tablet coat quality. Design of experiments, aided by multivariate analysis techniques, was used to quantify the effects of various coating process conditions and their interactions on the quality of film-coated tablets. The process parameters varied included batch size, inlet temperature, atomizing pressure, plenum pressure, spray rate and coating level. An initial screening stage was carried out using a 2(6-1(IV)) fractional factorial design. Following these preliminary experiments, optimization study was carried out using the Box-Behnken design. Main response variables measured included drug-loading efficiency, coat thickness variation, and the extent of tablet damage. Apparent optimum conditions were determined by using response surface plots. The process parameters exerted various effects on the different response variables. Hence, trade-offs between individual optima were necessary to obtain the best compromised set of conditions. The adequacy of the optimized process conditions in meeting the combined goals for all responses was indicated by the composite desirability value. By using response surface methodology and optimization, coating conditions which produced coated tablets of high drug-loading efficiency, low incidences of tablet damage and low coat thickness variation were defined. Optimal conditions were found to vary over a large spectrum when different responses were considered. Changes in processing parameters across the design space did not result in drastic changes to coat quality, thereby demonstrating robustness in the Supercell coating process. © 2010 American Association of Pharmaceutical Scientists

  18. Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

    Science.gov (United States)

    Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

    2017-12-01

    Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

  19. Multi-parameter geometrical scaledown study for energy optimization of MTJ and related spintronics nanodevices

    Science.gov (United States)

    Farhat, I. A. H.; Alpha, C.; Gale, E.; Atia, D. Y.; Stein, A.; Isakovic, A. F.

    The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tfree, lateral size of the MTJ, w, and the anisotropy parameter of the MTJ. At the same time, we point out which values of the saturation magnetization, Ms, and anisotropy field, Hk, can lead to lowering the switching current and overall decrease of the energy needed to operate an MTJ. It is demonstrated that scaledown via decreasing the lateral size of the MTJ, while allowing some other parameters to be unconstrained, can improve energy performance by a measurable factor, shown to be the function of both geometric and physical parameters above. Given the complex interdependencies among both families of parameters, we developed a particle swarm optimization (PSO) algorithm that can simultaneously lower energy of operation and the switching current density. Results we obtained in scaledown study and via PSO optimization are compared to experimental results. Support by Mubadala-SRC 2012-VJ-2335 is acknowledged, as are staff at Cornell-CNF and BNL-CFN.

  20. Optimization of injection molding process parameters for a plastic cell phone housing component

    Science.gov (United States)

    Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya

    2016-11-01

    To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.

  1. Sensitivity of Calibrated Parameters and Water Resource Estimates on Different Objective Functions and Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Delaram Houshmand Kouchi

    2017-05-01

    Full Text Available The successful application of hydrological models relies on careful calibration and uncertainty analysis. However, there are many different calibration/uncertainty analysis algorithms, and each could be run with different objective functions. In this paper, we highlight the fact that each combination of optimization algorithm-objective functions may lead to a different set of optimum parameters, while having the same performance; this makes the interpretation of dominant hydrological processes in a watershed highly uncertain. We used three different optimization algorithms (SUFI-2, GLUE, and PSO, and eight different objective functions (R2, bR2, NSE, MNS, RSR, SSQR, KGE, and PBIAS in a SWAT model to calibrate the monthly discharges in two watersheds in Iran. The results show that all three algorithms, using the same objective function, produced acceptable calibration results; however, with significantly different parameter ranges. Similarly, an algorithm using different objective functions also produced acceptable calibration results, but with different parameter ranges. The different calibrated parameter ranges consequently resulted in significantly different water resource estimates. Hence, the parameters and the outputs that they produce in a calibrated model are “conditioned” on the choices of the optimization algorithm and objective function. This adds another level of non-negligible uncertainty to watershed models, calling for more attention and investigation in this area.

  2. Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

    Directory of Open Access Journals (Sweden)

    Zhiqiang GENG

    2014-01-01

    Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.

  3. Dependence of silicon carbide coating properties on deposition parameters: preliminary report

    International Nuclear Information System (INIS)

    Lauf, R.J.; Braski, D.N.

    1980-05-01

    Fuel particles for the High-Temperature Gas-Cooled Reactor (HTGR) contain a layer of pyrolytic silicon carbide, which acts as a pressure vessel and provides containment of metallic fission products. The silicon carbide (SiC) is deposited by the thermal decomposition of methyltrichlorosilane (CH 3 SiCl 3 or MTS) in an excess of hydrogen. The purpose of the current study is to determine how the deposition variables affect the structure and properties of the SiC layer

  4. Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm

    International Nuclear Information System (INIS)

    Oliva, Diego; Abd El Aziz, Mohamed; Ella Hassanien, Aboul

    2017-01-01

    Highlights: •We modify the whale algorithm using chaotic maps. •We apply a chaotic algorithm to estimate parameter of photovoltaic cells. •We perform a study of chaos in whale algorithm. •Several comparisons and metrics support the experimental results. •We test the method with data from real solar cells. -- Abstract: The using of solar energy has been increased since it is a clean source of energy. In this way, the design of photovoltaic cells has attracted the attention of researchers over the world. There are two main problems in this field: having a useful model to characterize the solar cells and the absence of data about photovoltaic cells. This situation even affects the performance of the photovoltaic modules (panels). The characteristics of the current vs. voltage are used to describe the behavior of solar cells. Considering such values, the design problem involves the solution of the complex non-linear and multi-modal objective functions. Different algorithms have been proposed to identify the parameters of the photovoltaic cells and panels. Most of them commonly fail in finding the optimal solutions. This paper proposes the Chaotic Whale Optimization Algorithm (CWOA) for the parameters estimation of solar cells. The main advantage of the proposed approach is using the chaotic maps to compute and automatically adapt the internal parameters of the optimization algorithm. This situation is beneficial in complex problems, because along the iterative process, the proposed algorithm improves their capabilities to search for the best solution. The modified method is able to optimize complex and multimodal objective functions. For example, the function for the estimation of parameters of solar cells. To illustrate the capabilities of the proposed algorithm in the solar cell design, it is compared with other optimization methods over different datasets. Moreover, the experimental results support the improved performance of the proposed approach

  5. Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Heide, J; Zhang, Qi; Fitzek, F H P

    2013-01-01

    This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...... reduction in the number of transmitted packets can be achieved. However, NC introduces additional computations and potentially a non-negligible transmission overhead, both of which depend on the chosen coding parameters. Therefore it is necessary to consider the trade-off that these coding parameters...... present in order to obtain the lowest energy consumption per transmitted bit. This problem is analyzed and suitable coding parameters are determined for the popular Tmote Sky platform. Compared to the use of traditional RLNC, these parameters enable a reduction in the energy spent per bit which grows...

  6. Development of a parameter optimization technique for the design of automatic control systems

    Science.gov (United States)

    Whitaker, P. H.

    1977-01-01

    Parameter optimization techniques for the design of linear automatic control systems that are applicable to both continuous and digital systems are described. The model performance index is used as the optimization criterion because of the physical insight that can be attached to it. The design emphasis is to start with the simplest system configuration that experience indicates would be practical. Design parameters are specified, and a digital computer program is used to select that set of parameter values which minimizes the performance index. The resulting design is examined, and complexity, through the use of more complex information processing or more feedback paths, is added only if performance fails to meet operational specifications. System performance specifications are assumed to be such that the desired step function time response of the system can be inferred.

  7. Efficiency Optimization Control of IPM Synchronous Motor Drives with Online Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Sadegh Vaez-Zadeh

    2011-04-01

    Full Text Available This paper describes an efficiency optimization control method for high performance interior permanent magnet synchronous motor drives with online estimation of motor parameters. The control system is based on an input-output feedback linearization method which provides high performance control and simultaneously ensures the minimization of the motor losses. The controllable electrical loss can be minimized by the optimal control of the armature current vector. It is shown that parameter variations except at near the nominal conditions have undesirable effect on the controller performance. Therefore, a parameter estimation method based on the second method of Lyapunov is presented which guarantees the stability and convergence of the estimation. The extensive simulation results show the feasibility of the proposed controller and observer and their desirable performances.

  8. Optimization of process parameter for graft copolymerization of glycidyl methacrylate onto delignified banana fibers

    International Nuclear Information System (INIS)

    Selambakkannu, S.; Nor Azillah Fatimah Othman; Siti Fatahiyah Mohamad

    2016-01-01

    This paper focused on pre-treated banana fibers as a trunk polymer for optimization of radiation-induced graft copolymerization process parameters. Pre-treated banana fiber was grafted with glycidyl methacrylate (GMA) via electron beam irradiation. Optimization of grafting parameters in term of grafting yield was analyzed at numerous radiation dose, monomer concentration and reaction time. Grafting yield had been calculated gravimetrically against all the process parameters. The grafting yield at 40 kGy had increases from 14 % to 22.5 % at 1 h and 24 h of reaction time respectively. Grafting yield at 1 % of GMA was about 58 % and it increases to 187 % at 3 % GMA. The grafting of GMA onto pre-treated banana fibers confirmed with the characterization using FTIR, SEM and TGA. Grafting of GMA onto pre-treated fibers was successfully carried out and it was confirmed by the results obtained via the characterization. (author)

  9. Optimization of cryogenic cooled EDM process parameters using grey relational analysis

    International Nuclear Information System (INIS)

    Kumar, S Vinoth; Kumar, M Pradeep

    2014-01-01

    This paper presents an experimental investigation on cryogenic cooling of liquid nitrogen (LN 2 ) copper electrode in the electrical discharge machining (EDM) process. The optimization of the EDM process parameters, such as the electrode environment (conventional electrode and cryogenically cooled electrode in EDM), discharge current, pulse on time, gap voltage on material removal rate, electrode wear, and surface roughness on machining of AlSiCp metal matrix composite using multiple performance characteristics on grey relational analysis was investigated. The L 18 orthogonal array was utilized to examine the process parameters, and the optimal levels of the process parameters were identified through grey relational analysis. Experimental data were analyzed through analysis of variance. Scanning electron microscopy analysis was conducted to study the characteristics of the machined surface.

  10. Effect of PECVD deposition parameters on structural and optoelectronics properties of hydrogenated polymorphous silicon thin films deposited by dichlorosilane for implementation in solar cells

    International Nuclear Information System (INIS)

    Álvarez-Macías, C.; Hernández González, Oscar Daniel; Barrera Calva, Enrique; Gómez González, L.; Santana, G.

    2015-01-01

    Hydrogenated polymorphous silicon (pm-Si: H) thin films were deposited at room temperature by plasma enhanced chemical vapor deposition (PECVD) using SiH2Cl2 as precursor gas. We examine the effect of deposition pressure (250 y 500 mTorr) and H2 dilution (flow rates 25, 50, 75 y 100 sccm) on the structural and optoelectronics properties. The nano-structural properties was confirmed by Raman spectroscopy studies in terms of the changes in crystallite sizes and their volume fractions. On the other hand, by FTIR analysis we notice bond configurations associated to photostability of the nanostructures, which was confirmed by Light soaking experiments during 250h. We found a tunable band gap and important behaviors on the electronic transport properties measurements for samples with high and low incorporation of oxygen whose compositions were determined by XPS measurements. Understanding structural and chemical properties of pm- Si: H thin films is key towards optimizing their electrical and optical properties for applications in solar cells. (full text)

  11. Optimal allocation of sensors for state estimation of distributed parameter systems

    International Nuclear Information System (INIS)

    Sunahara, Yoshifumi; Ohsumi, Akira; Mogami, Yoshio.

    1978-01-01

    The purpose of this paper is to present a method for finding the optimal allocation of sensors for state estimation of linear distributed parameter systems. This method is based on the criterion that the error covariance associated with the state estimate becomes minimal with respect to the allocation of the sensors. A theorem is established, giving the sufficient condition for optimizing the allocation of sensors to make minimal the error covariance approximated by a modal expansion. The remainder of this paper is devoted to illustrate important phases of the general theory of the optimal measurement allocation problem. To do this, several examples are demonstrated, including extensive discussions on the mutual relation between the optimal allocation and the dynamics of sensors. (author)

  12. OPTIMIZATION OF TRANSESTERIFICATION PARAMETERS FOR OPTIMAL BIODIESEL YIELD FROM CRUDE JATROPHA OIL USING A NEWLY SYNTHESIZED SEASHELL CATALYST

    Directory of Open Access Journals (Sweden)

    A. N. R. REDDY

    2017-10-01

    Full Text Available Heterogeneous catalysts are promising catalysts for optimal biodiesel yield from transesterification of vegetable oils. In this work calcium oxide (CaO heterogeneous catalyst was synthesized from Polymedosa erosa seashell. Calcination was carried out at 900ºC for 2h and characterized using Fourier transform infrared spectroscopy. Catalytic efficiency of CaO was testified in transesterification of crude Jatropha oil (CJO. A response surface methodology (RSM based on five-level-two-factor central composite design (CCD was employed to optimize two critical transesterification parameters catalyst concentration to pretreated CJO (0.01-0.03 w/w % and the reaction time (90 min - 150 min. A JB yield of 96.48% was estimated at 0.023 w/w% catalyst and 125.76 min reaction using response optimizer. The legitimacy of the predicted model was verified through the experiments. The validation experiments conformed a yield of JB 96.4%±0.01% as optimal at 0.023 w/w% catalyst to pretreated oil ratio and 126 min reaction time.

  13. Optimization of pulsed DC PACVD parameters: Toward reducing wear rate of the DLC films

    International Nuclear Information System (INIS)

    Ebrahimi, Mansoureh; Mahboubi, Farzad; Naimi-Jamal, M. Reza

    2016-01-01

    Highlights: • Effect of pulsed DC PACVD deposition temperature, duty cycle, hydrogen flow and argon/CH4 flow ratio on the wear rate and durability of DLC films was studied. • Results show that wear rate of the DLC films, reduced from 14×E-4 mm3/Nm to 1×E-6 mm3/Nm with increasing the duty cycle from 50% to 80%. • In low duty cycle (around 50%), wear rate increases with increasing in Argon/CH4 flow ratio. • Oxidation, fatigue, abrasion and graphitization are main wear mechanisms in the DLC film. - Abstract: The effect of pulsed direct current (DC) plasma-assisted chemical vapor deposition (PACVD) parameters such as temperature, duty cycle, hydrogen flow, and argon/CH_4 flow ratio on the wear behavior and wear durability of the diamond-like carbon (DLC) films was studied by using response surface methodology (RSM). DLC films were deposited on nitrocarburized AISI 4140 steel. Wear rate and wear durability of the DLC films were examined with the pin-on-disk method. Field emission scanning electron microscopy, Raman spectroscopy, and nanoindentation techniques were used for studying wear mechanisms, chemical structure, and hardness of the DLC films. RSM results show that duty cycle is one of the important parameters that affect the wear rate of the DLC samples. The wear rate of the samples deposited with a duty cycle of >75% decreases with an increase in the argon/CH4 ratio. In contrast, for a duty cycle of <65%, the wear rate increases with an increase in the argon/CH_4 ratio. The wear durability of the DLC samples increases with an increase in the duty cycle, hydrogen flow, and argon/CH_4 flow ratio at the deposition temperature between 85 °C and 110 °C. Oxidation, fatigue, abrasive wear, and graphitization are the wear mechanisms observed on the wear scar of the DLC samples deposited with the optimum deposition conditions.

  14. Optimization of pulsed DC PACVD parameters: Toward reducing wear rate of the DLC films

    Energy Technology Data Exchange (ETDEWEB)

    Ebrahimi, Mansoureh [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, P.O. Box 1875-4413, Tehran (Iran, Islamic Republic of); Mahboubi, Farzad, E-mail: mahboubi@aut.ac.ir [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, P.O. Box 1875-4413, Tehran (Iran, Islamic Republic of); Naimi-Jamal, M. Reza [Research Laboratory of Green Organic Synthesis and Polymers, Department of Chemistry, Iran University of Science and Technology, P.O. Box 16846, Tehran (Iran, Islamic Republic of)

    2016-12-15

    Highlights: • Effect of pulsed DC PACVD deposition temperature, duty cycle, hydrogen flow and argon/CH4 flow ratio on the wear rate and durability of DLC films was studied. • Results show that wear rate of the DLC films, reduced from 14×E-4 mm3/Nm to 1×E-6 mm3/Nm with increasing the duty cycle from 50% to 80%. • In low duty cycle (around 50%), wear rate increases with increasing in Argon/CH4 flow ratio. • Oxidation, fatigue, abrasion and graphitization are main wear mechanisms in the DLC film. - Abstract: The effect of pulsed direct current (DC) plasma-assisted chemical vapor deposition (PACVD) parameters such as temperature, duty cycle, hydrogen flow, and argon/CH{sub 4} flow ratio on the wear behavior and wear durability of the diamond-like carbon (DLC) films was studied by using response surface methodology (RSM). DLC films were deposited on nitrocarburized AISI 4140 steel. Wear rate and wear durability of the DLC films were examined with the pin-on-disk method. Field emission scanning electron microscopy, Raman spectroscopy, and nanoindentation techniques were used for studying wear mechanisms, chemical structure, and hardness of the DLC films. RSM results show that duty cycle is one of the important parameters that affect the wear rate of the DLC samples. The wear rate of the samples deposited with a duty cycle of >75% decreases with an increase in the argon/CH4 ratio. In contrast, for a duty cycle of <65%, the wear rate increases with an increase in the argon/CH{sub 4} ratio. The wear durability of the DLC samples increases with an increase in the duty cycle, hydrogen flow, and argon/CH{sub 4} flow ratio at the deposition temperature between 85 °C and 110 °C. Oxidation, fatigue, abrasive wear, and graphitization are the wear mechanisms observed on the wear scar of the DLC samples deposited with the optimum deposition conditions.

  15. Coastal aquifer management under parameter uncertainty: Ensemble surrogate modeling based simulation-optimization

    Science.gov (United States)

    Janardhanan, S.; Datta, B.

    2011-12-01

    Surrogate models are widely used to develop computationally efficient simulation-optimization models to solve complex groundwater management problems. Artificial intelligence based models are most often used for this purpose where they are trained using predictor-predictand data obtained from a numerical simulation model. Most often this is implemented with the assumption that the parameters and boundary conditions used in the numerical simulation model are perfectly known. However, in most practical situations these values are uncertain. Under these circumstances the application of such approximation surrogates becomes limited. In our study we develop a surrogate model based coupled simulation optimization methodology for determining optimal pumping strategies for coastal aquifers considering parameter uncertainty. An ensemble surrogate modeling approach is used along with multiple realization optimization. The methodology is used to solve a multi-objective coastal aquifer management problem considering two conflicting objectives. Hydraulic conductivity and the aquifer recharge are considered as uncertain values. Three dimensional coupled flow and transport simulation model FEMWATER is used to simulate the aquifer responses for a number of scenarios corresponding to Latin hypercube samples of pumping and uncertain parameters to generate input-output patterns for training the surrogate models. Non-parametric bootstrap sampling of this original data set is used to generate multiple data sets which belong to different regions in the multi-dimensional decision and parameter space. These data sets are used to train and test multiple surrogate models based on genetic programming. The ensemble of surrogate models is then linked to a multi-objective genetic algorithm to solve the pumping optimization problem. Two conflicting objectives, viz, maximizing total pumping from beneficial wells and minimizing the total pumping from barrier wells for hydraulic control of

  16. Evaluation of the Cerro Solo nuclear ore, province of Chubut. On the economic parameters of the deposit. Pt. 3

    International Nuclear Information System (INIS)

    Navarra, P.R.; Sardin, P.G.; Urquiza, L.; Bernal, G.J.; Guzman Lobos, D.

    1993-01-01

    Preliminary results of the resources estimation carried out in the Cerro Solo uranium ore deposit, located in the Chubut Province, 1900 km SW from Buenos Aires and 380 Km W from Trelew, presented in tonnes of uranium recoverable at costs up to U$S 80/kgU, are as follows: a) Reasonable assured resources (indicated): 800 tU; b) Estimates Additional Resources (inferred): 2200 tU. Economic evaluation at the order-of-magnitude level, performed using the grade-tonnage model of the deposit, resulted a useful tool in the different stages of the project to identify the influence of technical parameters on the potential profitability. Research about feasibility of in-situ leaching method of exploitation for this deposit introduces an interesting alternative for future uranium production in the country. (Author)

  17. Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems.

    Science.gov (United States)

    Cho, Ming-Yuan; Hoang, Thi Thom

    2017-01-01

    Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

  18. Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems

    Directory of Open Access Journals (Sweden)

    Ming-Yuan Cho

    2017-01-01

    Full Text Available Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO based support vector machine (SVM classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR method with a pseudorandom binary sequence (PRBS stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

  19. Comparison of direct machine parameter optimization versus fluence optimization with sequential sequencing in IMRT of hypopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Dobler, Barbara; Pohl, Fabian; Bogner, Ludwig; Koelbl, Oliver

    2007-01-01

    To evaluate the effects of direct machine parameter optimization in the treatment planning of intensity-modulated radiation therapy (IMRT) for hypopharyngeal cancer as compared to subsequent leaf sequencing in Oncentra Masterplan v1.5. For 10 hypopharyngeal cancer patients IMRT plans were generated in Oncentra Masterplan v1.5 (Nucletron BV, Veenendal, the Netherlands) for a Siemens Primus linear accelerator. For optimization the dose volume objectives (DVO) for the planning target volume (PTV) were set to 53 Gy minimum dose and 59 Gy maximum dose, in order to reach a dose of 56 Gy to the average of the PTV. For the parotids a median dose of 22 Gy was allowed and for the spinal cord a maximum dose of 35 Gy. The maximum DVO to the external contour of the patient was set to 59 Gy. The treatment plans were optimized with the direct machine parameter optimization ('Direct Step & Shoot', DSS, Raysearch Laboratories, Sweden) newly implemented in Masterplan v1.5 and the fluence modulation technique ('Intensity Modulation', IM) which was available in previous versions of Masterplan already. The two techniques were compared with regard to compliance to the DVO, plan quality, and number of monitor units (MU) required per fraction dose. The plans optimized with the DSS technique met the DVO for the PTV significantly better than the plans optimized with IM (p = 0.007 for the min DVO and p < 0.0005 for the max DVO). No significant difference could be observed for compliance to the DVO for the organs at risk (OAR) (p > 0.05). Plan quality, target coverage and dose homogeneity inside the PTV were superior for the plans optimized with DSS for similar dose to the spinal cord and lower dose to the normal tissue. The mean dose to the parotids was lower for the plans optimized with IM. Treatment plan efficiency was higher for the DSS plans with (901 ± 160) MU compared to (1151 ± 157) MU for IM (p-value < 0.05). Renormalization of the IM plans to the mean of the

  20. An Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models

    Directory of Open Access Journals (Sweden)

    Daniel Santana-Cedrés

    2016-12-01

    Full Text Available We present a method for the automatic estimation of two-parameter radial distortion models, considering polynomial as well as division models. The method first detects the longest distorted lines within the image by applying the Hough transform enriched with a radial distortion parameter. From these lines, the first distortion parameter is estimated, then we initialize the second distortion parameter to zero and the two-parameter model is embedded into an iterative nonlinear optimization process to improve the estimation. This optimization aims at reducing the distance from the edge points to the lines, adjusting two distortion parameters as well as the coordinates of the center of distortion. Furthermore, this allows detecting more points belonging to the distorted lines, so that the Hough transform is iteratively repeated to extract a better set of lines until no improvement is achieved. We present some experiments on real images with significant distortion to show the ability of the proposed approach to automatically correct this type of distortion as well as a comparison between the polynomial and division models.

  1. Dynamic optimization of a biped model: Energetic walking gaits with different mechanical and gait parameters

    Directory of Open Access Journals (Sweden)

    Kang An

    2015-05-01

    Full Text Available Energy consumption is one of the problems for bipedal robots walking. For the purpose of studying the parameter effects on the design of energetic walking bipeds with strong adaptability, we use a dynamic optimization method on our new walking model to first investigate the effects of the mechanical parameters, including mass and length distribution, on the walking efficiency. Then, we study the energetic walking gait features with the combinations of walking speed and step length. Our walking model is designed upon Srinivasan’s model. Dynamic optimization is used for a free search with minimal constraints. The results show that the cost of transport of a certain gait increases with the increase in the mass and length distribution parameters, except for that the cost of transport decreases with big length distribution parameter and long step length. We can also find a corresponding range of walking speed and step length, in which the variation in one of the two parameters has no obvious effect on the cost of transport. With fixed mechanical parameters, the cost of transport increases with the increase in the walking speed. There is a speed–step length relationship for walking with minimal cost of transport. The hip torque output strategy is adjusted in two situations to meet the walking requirements.

  2. Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints.

    Science.gov (United States)

    Fiedler, Anna; Raeth, Sebastian; Theis, Fabian J; Hausser, Angelika; Hasenauer, Jan

    2016-08-22

    Ordinary differential equation (ODE) models are widely used to describe (bio-)chemical and biological processes. To enhance the predictive power of these models, their unknown parameters are estimated from experimental data. These experimental data are mostly collected in perturbation experiments, in which the processes are pushed out of steady state by applying a stimulus. The information that the initial condition is a steady state of the unperturbed process provides valuable information, as it restricts the dynamics of the process and thereby the parameters. However, implementing steady-state constraints in the optimization often results in convergence problems. In this manuscript, we propose two new methods for solving optimization problems with steady-state constraints. The first method exploits ideas from optimization algorithms on manifolds and introduces a retraction operator, essentially reducing the dimension of the optimization problem. The second method is based on the continuous analogue of the optimization problem. This continuous analogue is an ODE whose equilibrium points are the optima of the constrained optimization problem. This equivalence enables the use of adaptive numerical methods for solving optimization problems with steady-state constraints. Both methods are tailored to the problem structure and exploit the local geometry of the steady-state manifold and its stability properties. A parameterization of the steady-state manifold is not required. The efficiency and reliability of the proposed methods is evaluated using one toy example and two applications. The first application example uses published data while the second uses a novel dataset for Raf/MEK/ERK signaling. The proposed methods demonstrated better convergence properties than state-of-the-art methods employed in systems and computational biology. Furthermore, the average computation time per converged start is significantly lower. In addition to the theoretical results, the

  3. Low-pressure chemical vapor deposition as a tool for deposition of thin film battery materials

    NARCIS (Netherlands)

    Oudenhoven, J.F.M.; Dongen, van T.; Niessen, R.A.H.; Croon, de M.H.J.M.; Notten, P.H.L.

    2009-01-01

    Low Pressure Chemical Vapor Deposition was utilized for the deposition of LiCoO2 cathode materials for all-solid-state thin-film micro-batteries. To obtain insight in the deposition process, the most important process parameters were optimized for the deposition of crystalline electrode films on

  4. Optimal likelihood-based matching of volcanic sources and deposits in the Auckland Volcanic Field

    Science.gov (United States)

    Kawabata, Emily; Bebbington, Mark S.; Cronin, Shane J.; Wang, Ting

    2016-09-01

    In monogenetic volcanic fields, where each eruption forms a new volcano, focusing and migration of activity over time is a very real possibility. In order for hazard estimates to reflect future, rather than past, behavior, it is vital to assemble as much reliable age data as possible on past eruptions. Multiple swamp/lake records have been extracted from the Auckland Volcanic Field, underlying the 1.4 million-population city of Auckland. We examine here the problem of matching these dated deposits to the volcanoes that produced them. The simplest issue is separation in time, which is handled by simulating prior volcano age sequences from direct dates where known, thinned via ordering constraints between the volcanoes. The subproblem of varying deposition thicknesses (which may be zero) at five locations of known distance and azimuth is quantified using a statistical attenuation model for the volcanic ash thickness. These elements are combined with other constraints, from widespread fingerprinted ash layers that separate eruptions and time-censoring of the records, into a likelihood that was optimized via linear programming. A second linear program was used to optimize over the Monte-Carlo simulated set of prior age profiles to determine the best overall match and consequent volcano age assignments. Considering all 20 matches, and the multiple factors of age, direction, and size/distance simultaneously, results in some non-intuitive assignments which would not be produced by single factor analyses. Compared with earlier work, the results provide better age control on a number of smaller centers such as Little Rangitoto, Otuataua, Taylors Hill, Wiri Mountain, Green Hill, Otara Hill, Hampton Park and Mt Cambria. Spatio-temporal hazard estimates are updated on the basis of the new ordering, which suggest that the scale of the 'flare-up' around 30 ka, while still highly significant, was less than previously thought.

  5. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

    Directory of Open Access Journals (Sweden)

    Tashkova Katerina

    2011-10-01

    Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of

  6. Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

    Science.gov (United States)

    Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

    2011-10-11

    We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and

  7. Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization

    Science.gov (United States)

    Mohmad Kahar, Mohd Nizam; Noraziah, A.

    2017-01-01

    In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system’s gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics. PMID:28441390

  8. Fractional Order Controller Designing with Firefly Algorithm and Parameter Optimization for Hydroturbine Governing System

    Directory of Open Access Journals (Sweden)

    Li Junyi

    2015-01-01

    Full Text Available A fractional order PID (FOPID controller, which is suitable for control system designing for being insensitive to the variation in system parameter, is proposed for hydroturbine governing system in the paper. The simultaneous optimization for several parameters of controller, that is, Ki, Kd, Kp, λ, and μ, is done by a recently developed metaheuristic nature-inspired algorithm, namely, the firefly algorithm (FA, for the first time, where the selecting, moving, attractiveness behavior between fireflies and updating of brightness, and decision range are studied in detail to simulate the optimization process. Investigation clearly reveals the advantages of the FOPID controller over the integer controllers in terms of reduced oscillations and settling time. The present work also explores the superiority of FA based optimization technique in finding optimal parameters of the controller. Further, convergence characteristics of the FA are compared with optimum integer order PID (IOPID controller to justify its efficiency. What is more, analysis confirms the robustness of FOPID controller under isolated load operation conditions.

  9. [Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

    Science.gov (United States)

    Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

    2012-12-01

    This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

  10. Three-dimensional optimization and sensitivity analysis of dental implant thread parameters using finite element analysis.

    Science.gov (United States)

    Geramizadeh, Maryam; Katoozian, Hamidreza; Amid, Reza; Kadkhodazadeh, Mahdi

    2018-04-01

    This study aimed to optimize the thread depth and pitch of a recently designed dental implant to provide uniform stress distribution by means of a response surface optimization method available in finite element (FE) software. The sensitivity of simulation to different mechanical parameters was also evaluated. A three-dimensional model of a tapered dental implant with micro-threads in the upper area and V-shaped threads in the rest of the body was modeled and analyzed using finite element analysis (FEA). An axial load of 100 N was applied to the top of the implants. The model was optimized for thread depth and pitch to determine the optimal stress distribution. In this analysis, micro-threads had 0.25 to 0.3 mm depth and 0.27 to 0.33 mm pitch, and V-shaped threads had 0.405 to 0.495 mm depth and 0.66 to 0.8 mm pitch. The optimized depth and pitch were 0.307 and 0.286 mm for micro-threads and 0.405 and 0.808 mm for V-shaped threads, respectively. In this design, the most effective parameters on stress distribution were the depth and pitch of the micro-threads based on sensitivity analysis results. Based on the results of this study, the optimal implant design has micro-threads with 0.307 and 0.286 mm depth and pitch, respectively, in the upper area and V-shaped threads with 0.405 and 0.808 mm depth and pitch in the rest of the body. These results indicate that micro-thread parameters have a greater effect on stress and strain values.

  11. Determination of radial profile of ICF hot spot's state by multi-objective parameters optimization

    International Nuclear Information System (INIS)

    Dong Jianjun; Deng Bo; Cao Zhurong; Ding Yongkun; Jiang Shaoen

    2014-01-01

    A method using multi-objective parameters optimization is presented to determine the radial profile of hot spot temperature and density. And a parameter space which contain five variables: the temperatures at center and the interface of fuel and remain ablator, the maximum model density of remain ablator, the mass ratio of remain ablator to initial ablator and the position of interface between fuel and the remain ablator, is used to described the hot spot radial temperature and density. Two objective functions are set as the variances of normalized intensity profile from experiment X-ray images and the theory calculation. Another objective function is set as the variance of experiment average temperature of hot spot and the average temperature calculated by theoretical model. The optimized parameters are obtained by multi-objective genetic algorithm searching for the five dimension parameter space, thereby the optimized radial temperature and density profiles can be determined. The radial temperature and density profiles of hot spot by experiment data measured by KB microscope cooperating with X-ray film are presented. It is observed that the temperature profile is strongly correlated to the objective functions. (authors)

  12. Optimization of design and operating parameters in a pilot scale Jameson cell for slime coal cleaning

    Energy Technology Data Exchange (ETDEWEB)

    Hacifazlioglu, Hasan; Toroglu, Ihsan [Department of Mining Engineering, University of Karaelmas, 67100 (Turkey)

    2007-07-15

    The Jameson flotation cell has been commonly used to treat a variety of ores (lead, zinc, copper etc.), coal and industrial minerals at commercial scale since 1989. It is especially known to be highly efficient at fine and ultrafine coal recovery. However, although the Jameson cell has quite a simple structure, it may be largely inefficient if the design and operating parameters chosen are not appropriate. In this study, the design and operating parameters of a pilot scale Jameson cell were optimized to obtain a desired metallurgical performance in the slime coal flotation. The optimized design parameters are the nozzle type, the height of the nozzle above the pulp level, the downcomer diameter and the immersion depth of the downcomer. Among the operating parameters optimized are the collector dosage, the frother dosage, the percentage of solids and the froth height. In the optimum conditions, a clean coal with an ash content of 14.90% was obtained from the sample slime having 45.30% ash with a combustible recovery of 74.20%. In addition, a new type nozzle was developed for the Jameson cell, which led to an increase of about 9% in the combustible recovery value.

  13. Prediction and optimization of friction welding parameters for super duplex stainless steel (UNS S32760) joints

    International Nuclear Information System (INIS)

    Udayakumar, T.; Raja, K.; Afsal Husain, T.M.; Sathiya, P.

    2014-01-01

    Highlights: • Corrosion resistance and impact strength – predicted by response surface methodology. • Burn off length has highest significance on corrosion resistance. • Friction force is a strong determinant in changing impact strength. • Pareto front points generated by genetic algorithm aid to fix input control variable. • Pareto front will be a trade-off between corrosion resistance and impact strength. - Abstract: Friction welding finds widespread industrial use as a mass production process for joining materials. Friction welding process allows welding of several materials that are extremely difficult to fusion weld. Friction welding process parameters play a significant role in making good quality joints. To produce a good quality joint it is important to set up proper welding process parameters. This can be done by employing optimization techniques. This paper presents a multi objective optimization method for optimizing the process parameters during friction welding process. The proposed method combines the response surface methodology (RSM) with an intelligent optimization algorithm, i.e. genetic algorithm (GA). Corrosion resistance and impact strength of friction welded super duplex stainless steel (SDSS) (UNS S32760) joints were investigated considering three process parameters: friction force (F), upset force (U) and burn off length (B). Mathematical models were developed and the responses were adequately predicted. Direct and interaction effects of process parameters on responses were studied by plotting graphs. Burn off length has high significance on corrosion current followed by upset force and friction force. In the case of impact strength, friction force has high significance followed by upset force and burn off length. Multi objective optimization for maximizing the impact strength and minimizing the corrosion current (maximizing corrosion resistance) was carried out using GA with the RSM model. The optimization procedure resulted in

  14. An intelligent approach to optimize the EDM process parameters using utility concept and QPSO algorithm

    Directory of Open Access Journals (Sweden)

    Chinmaya P. Mohanty

    2017-04-01

    Full Text Available Although significant research has gone into the field of electrical discharge machining (EDM, analysis related to the machining efficiency of the process with different electrodes has not been adequately made. Copper and brass are frequently used as electrode materials but graphite can be used as a potential electrode material due to its high melting point temperature and good electrical conductivity. In view of this, the present work attempts to compare the machinability of copper, graphite and brass electrodes while machining Inconel 718 super alloy. Taguchi’s L27 orthogonal array has been employed to collect data for the study and analyze effect of machining parameters on performance measures. The important performance measures selected for this study are material removal rate, tool wear rate, surface roughness and radial overcut. Machining parameters considered for analysis are open circuit voltage, discharge current, pulse-on-time, duty factor, flushing pressure and electrode material. From the experimental analysis, it is observed that electrode material, discharge current and pulse-on-time are the important parameters for all the performance measures. Utility concept has been implemented to transform a multiple performance characteristics into an equivalent performance characteristic. Non-linear regression analysis is carried out to develop a model relating process parameters and overall utility index. Finally, the quantum behaved particle swarm optimization (QPSO and particle swarm optimization (PSO algorithms have been used to compare the optimal level of cutting parameters. Results demonstrate the elegance of QPSO in terms of convergence and computational effort. The optimal parametric setting obtained through both the approaches is validated by conducting confirmation experiments.

  15. Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

    Science.gov (United States)

    Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

    2017-10-01

    Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations

  16. A Hybrid Least Square Support Vector Machine Model with Parameters Optimization for Stock Forecasting

    Directory of Open Access Journals (Sweden)

    Jian Chai

    2015-01-01

    Full Text Available This paper proposes an EMD-LSSVM (empirical mode decomposition least squares support vector machine model to analyze the CSI 300 index. A WD-LSSVM (wavelet denoising least squares support machine is also proposed as a benchmark to compare with the performance of EMD-LSSVM. Since parameters selection is vital to the performance of the model, different optimization methods are used, including simplex, GS (grid search, PSO (particle swarm optimization, and GA (genetic algorithm. Experimental results show that the EMD-LSSVM model with GS algorithm outperforms other methods in predicting stock market movement direction.

  17. Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

    Science.gov (United States)

    Morelli, Eugene A.; Klein, Vladislav

    1990-01-01

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

  18. Multi-parameter optimization of a nanomagnetic system for spintronic applications

    Energy Technology Data Exchange (ETDEWEB)

    Morales Meza, Mishel [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Zubieta Rico, Pablo F. [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV) Querétaro, Libramiento Norponiente 2000, Fracc. Real de Juriquilla, 76230 Querétaro (Mexico); Horley, Paul P., E-mail: paul.horley@cimav.edu.mx [Centro de Investigación en Materiales Avanzados, S.C. (CIMAV), Chihuahua/Monterrey, 120 Avenida Miguel de Cervantes, 31109 Chihuahua (Mexico); Sukhov, Alexander [Institut für Physik, Martin-Luther Universität Halle-Wittenberg, 06120 Halle (Saale) (Germany); Vieira, Vítor R. [Centro de Física das Interacções Fundamentais (CFIF), Instituto Superior Técnico, Universidade Técnica de Lisboa, Avenida Rovisco Pais, 1049-001 Lisbon (Portugal)

    2014-11-15

    Magnetic properties of nano-particles feature many interesting physical phenomena that are essentially important for the creation of a new generation of spin-electronic devices. The magnetic stability of the nano-particles can be improved by formation of ordered particle arrays, which should be optimized over several parameters. Here we report successful optimization regarding inter-particle distance and applied field frequency allowing to obtain about three-times reduction of coercivity of a particle array compared to that of a single particle, which opens new perspectives for development of new spintronic devices.

  19. Multi-parameter optimization of a nanomagnetic system for spintronic applications

    International Nuclear Information System (INIS)

    Morales Meza, Mishel; Zubieta Rico, Pablo F.; Horley, Paul P.; Sukhov, Alexander; Vieira, Vítor R.

    2014-01-01

    Magnetic properties of nano-particles feature many interesting physical phenomena that are essentially important for the creation of a new generation of spin-electronic devices. The magnetic stability of the nano-particles can be improved by formation of ordered particle arrays, which should be optimized over several parameters. Here we report successful optimization regarding inter-particle distance and applied field frequency allowing to obtain about three-times reduction of coercivity of a particle array compared to that of a single particle, which opens new perspectives for development of new spintronic devices

  20. The optimization of the nonlinear parameters in the transcorrelated method: the hydrogen molecule

    International Nuclear Information System (INIS)

    Huggett, J.P.; Armour, E.A.G.

    1976-01-01

    The nonlinear parameters in a transcorrelated calculation of the groundstate energy and wavefunction of the hydrogen molecule are optimized using the method of Boys and Handy (Proc. R. Soc. A.; 309:195 and 209, 310:43 and 63, 311:309 (1969)). The method gives quite accurate results in all cases and in some cases the results are highly accurate. This is the first time the method has been applied to the optimization of a term in the correlation function which depends linearly on the interelectronic distance. (author)

  1. The same number of optimized parameters scheme for determining intermolecular interaction energies

    DEFF Research Database (Denmark)

    Kristensen, Kasper; Ettenhuber, Patrick; Eriksen, Janus Juul

    2015-01-01

    We propose the Same Number Of Optimized Parameters (SNOOP) scheme as an alternative to the counterpoise method for treating basis set superposition errors in calculations of intermolecular interaction energies. The key point of the SNOOP scheme is to enforce that the number of optimized wave...... as numerically. Numerical results for second-order Møller-Plesset perturbation theory (MP2) and coupled-cluster with single, double, and approximate triple excitations (CCSD(T)) show that the SNOOP scheme in general outperforms the uncorrected and counterpoise approaches. Furthermore, we show that SNOOP...

  2. Optimization of the Process Parameters for Controlling Residual Stress and Distortion in Friction Stir Welding

    DEFF Research Database (Denmark)

    Tutum, Cem Celal; Schmidt, Henrik Nikolaj Blicher; Hattel, Jesper Henri

    2008-01-01

    In the present paper, numerical optimization of the process parameters, i.e. tool rotation speed and traverse speed, aiming minimization of the two conflicting objectives, i.e. the residual stresses and welding time, subjected to process-specific thermal constraints in friction stir welding......, is investigated. The welding process is simulated in 2-dimensions with a sequentially coupled transient thermo-mechanical model using ANSYS. The numerical optimization problem is implemented in modeFRONTIER and solved using the Multi-Objective Genetic Algorithm (MOGA-II). An engineering-wise evaluation or ranking...

  3. Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

    The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...

  4. Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

    1993-01-01

    The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...

  5. Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

    1991-01-01

    The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...

  6. Effect of pretreatment and deposition parameters on diamond nucleation in CVD

    International Nuclear Information System (INIS)

    Nazim, E.; Izman, S.; Ourdjini, A.; Shaharoun, A.M.

    2007-01-01

    Chemical vapour deposition (CVD) of diamond films on cemented carbide (WC) has aroused great interest in recent years. The combination of toughness from the WC and the high hardness of diamond results in outstanding wear resistance. This will increase the lifetime and better technical performance of the components made of diamond coated carbide. One of the important steps in the growth of diamond film is the nucleation of diamond as its density strongly influences the diamond growth process, film quality and morphology. In this paper the various effects of surface pretreatment and diamond deposition conditions on the diamond nucleation density are reviewed. (author)

  7. Analysis and optimization of machining parameters of laser cutting for polypropylene composite

    Science.gov (United States)

    Deepa, A.; Padmanabhan, K.; Kuppan, P.

    2017-11-01

    Present works explains about machining of self-reinforced Polypropylene composite fabricated using hot compaction method. The objective of the experiment is to find optimum machining parameters for Polypropylene (PP). Laser power and Machining speed were the parameters considered in response to tensile test and Flexure test. Taguchi method is used for experimentation. Grey Relational Analysis (GRA) is used for multiple process parameter optimization. ANOVA (Analysis of Variance) is used to find impact for process parameter. Polypropylene has got the great application in various fields like, it is used in the form of foam in model aircraft and other radio-controlled vehicles, thin sheets (∼2-20μm) used as a dielectric, PP is also used in piping system, it is also been used in hernia and pelvic organ repair or protect new herrnis in the same location.

  8. Parameter Identification of Static Friction Based on An Optimal Exciting Trajectory

    Science.gov (United States)

    Tu, X.; Zhao, P.; Zhou, Y. F.

    2017-12-01

    In this paper, we focus on how to improve the identification efficiency of friction parameters in a robot joint. First, the static friction model that has only linear dependencies with respect to their parameters is adopted so that the servomotor dynamics can be linearized. In this case, the traditional exciting trajectory based on Fourier series is modified by replacing the constant term with quintic polynomial to ensure the boundary continuity of speed and acceleration. Then, the Fourier-related parameters are optimized by genetic algorithm(GA) in which the condition number of regression matrix is set as the fitness function. At last, compared with the constant-velocity tracking experiment, the friction parameters from the exciting trajectory experiment has the similar result with the advantage of time reduction.

  9. Application of Powell's optimization method to surge arrester circuit models' parameters

    Energy Technology Data Exchange (ETDEWEB)

    Christodoulou, C.A.; Stathopulos, I.A. [National Technical University of Athens, School of Electrical and Computer Engineering, 9 Iroon Politechniou St., Zografou Campus, 157 80 Athens (Greece); Vita, V.; Ekonomou, L.; Chatzarakis, G.E. [A.S.PE.T.E. - School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece)

    2010-08-15

    Powell's optimization method has been used for the evaluation of the surge arrester models parameters. The proper modelling of metal-oxide surge arresters and the right selection of equivalent circuit parameters are very significant issues, since quality and reliability of lightning performance studies can be improved with the more efficient representation of the arresters' dynamic behavior. The proposed approach selects optimum arrester model equivalent circuit parameter values, minimizing the error between the simulated peak residual voltage value and this given by the manufacturer. Application of the method in performed on a 120 kV metal oxide arrester. The use of the obtained optimum parameter values reduces significantly the relative error between the simulated and manufacturer's peak residual voltage value, presenting the effectiveness of the method. (author)

  10. Identification of constitutive theory parameters using a tensile machine for deposited filaments of microcrystalline ink by the direct-write method

    International Nuclear Information System (INIS)

    Lourdel, N; Therriault, D; Lévesque, M

    2009-01-01

    A custom-designed tensile machine is developed to characterize the mechanical properties of ink micro-filaments deposited by the direct-write method. The direct-write method has been used for the fabrication of a wide variety of micro-systems such as microvascular networks, chaotic mixers and laboratory on chips. The tensile machine was used to measure the induced force in ink filaments during tensile and tension-relaxation tests as a function of the applied strain rate, the ink composition and the filament diameter. Experimental data were fitted by a linearly viscoelastic model using a data reduction procedure in order to identify the constitutive theory parameters of the deposited ink filaments. The model predictions based on the linearly viscoelastic model and the defined constitutive theory parameters give a close approximation of all experimental data generated in this study. Such models will be useful for the development and optimization of future 3D complex structures made by the direct-write method

  11. Understanding the reaction kinetics to optimize graphene growth on Cu by chemical vapor deposition

    Energy Technology Data Exchange (ETDEWEB)

    Kraus, Juergen; Boebel, Lena; Zwaschka, Gregor; Guenther, Sebastian [Technische Universitaet Muenchen, Zentralinstitut fuer Katalyseforschung, Chemie Department, Physikalische Chemie mit Schwerpunkt Katalyse, Garching (Germany)

    2017-11-15

    Understanding and controlling the growth kinetics of graphene is a prerequisite to synthesize this highly wanted material by chemical vapor deposition on Cu, e.g. for the construction of ultra-stable electron transparent membranes. It is reviewed that Cu foils contain a considerable amount of carbon in the bulk which significantly exceeds the expected amount of thermally equilibrated dissolved carbon in Cu and that this carbon must be removed before any high quality graphene may be grown. Starting with such conditioned Cu foils, systematic studies of the graphene growth kinetics in a reactive CH{sub 4}/H{sub 2} atmosphere allow to extract the following meaningful data: prediction of the equilibrium constant of the graphene formation reaction within a precision of a factor of two, the confirmation that the graphene growth proceeds from a C(ad)-phase on Cu which is in thermal equilibrium with the reactive gas phase, its apparent activation barrier and finally the prediction of the achievable growth velocity of the growing graphene flakes during chemical vapor deposition. As a result of the performed study, growth parameters are identified for the synthesis of high quality monolayer graphene with single crystalline domains of 100-1000 μm in diameter within a reasonable growth time. (copyright 2017 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  12. A novel optimization approach to estimating kinetic parameters of the enzymatic hydrolysis of corn stover

    Directory of Open Access Journals (Sweden)

    Fenglei Qi

    2016-01-01

    Full Text Available Enzymatic hydrolysis is an integral step in the conversion of lignocellulosic biomass to ethanol. The conversion of cellulose to fermentable sugars in the presence of inhibitors is a complex kinetic problem. In this study, we describe a novel approach to estimating the kinetic parameters underlying this process. This study employs experimental data measuring substrate and enzyme loadings, sugar and acid inhibitions for the production of glucose. Multiple objectives to minimize the difference between model predictions and experimental observations are developed and optimized by adopting multi-objective particle swarm optimization method. Model reliability is assessed by exploring likelihood profile in each parameter space. Compared to previous studies, this approach improved the prediction of sugar yields by reducing the mean squared errors by 34% for glucose and 2.7% for cellobiose, suggesting improved agreement between model predictions and the experimental data. Furthermore, kinetic parameters such as K2IG2, K1IG, K2IG, K1IA, and K3IA are identified as contributors to the model non-identifiability and wide parameter confidence intervals. Model reliability analysis indicates possible ways to reduce model non-identifiability and tighten parameter confidence intervals. These results could help improve the design of lignocellulosic biorefineries by providing higher fidelity predictions of fermentable sugars under inhibitory conditions.

  13. Optimization of process parameters in precipitation for consistent quality UO{sub 2} powder production

    Energy Technology Data Exchange (ETDEWEB)

    Tiwari, S.K.; Reddy, A.L.V.; Venkataswamy, J.; Misra, M.; Setty, D.S.; Sheela, S.; Saibaba, N., E-mail: misra@nfc.gov.in [Nuclear Fuel Complex, Hyderabad (India)

    2013-07-01

    Nuclear reactor grade natural uranium dioxide powder is being produced through precipitation route, which is further processed before converting into sintered pellets used in the fabrication of PHWR fuel assemblies of 220 and 540 MWe type reactors. The process of precipitating Uranyl Nitrate Pure Solution (UNPS) is an important step in the UO{sub 2} powder production line, where in soluble uranium is transformed into solid form of Ammonium Uranate (AU), which in turn reflects and decides the powder characteristics. Precipitation of UNPS with vapour ammonia is being carried out in semi batch process and process parameters like ammonia flow rate, temperature, concentration of UNPS and free acidity of UNPS are very critical and decides the UO{sub 2} powder quality. Variation in these critical parameters influences powder characteristics, which in turn influences the sinterability of UO{sub 2} powder. In order to get consistent powder quality and sinterability the critical parameter like ammonia flow rate during precipitation is studied, optimized and validated. The critical process parameters are controlled through PLC based automated on-line data acquisition systems for achieving consistent powder quality with increased recovery and production. The present paper covers optimization of process parameters and powder characteristics. (author)

  14. Optimization of process parameters in precipitation for consistent quality UO2 powder production

    International Nuclear Information System (INIS)

    Tiwari, S.K.; Reddy, A.L.V.; Venkataswamy, J.; Misra, M.; Setty, D.S.; Sheela, S.; Saibaba, N.

    2013-01-01

    Nuclear reactor grade natural uranium dioxide powder is being produced through precipitation route, which is further processed before converting into sintered pellets used in the fabrication of PHWR fuel assemblies of 220 and 540 MWe type reactors. The process of precipitating Uranyl Nitrate Pure Solution (UNPS) is an important step in the UO 2 powder production line, where in soluble uranium is transformed into solid form of Ammonium Uranate (AU), which in turn reflects and decides the powder characteristics. Precipitation of UNPS with vapour ammonia is being carried out in semi batch process and process parameters like ammonia flow rate, temperature, concentration of UNPS and free acidity of UNPS are very critical and decides the UO 2 powder quality. Variation in these critical parameters influences powder characteristics, which in turn influences the sinterability of UO 2 powder. In order to get consistent powder quality and sinterability the critical parameter like ammonia flow rate during precipitation is studied, optimized and validated. The critical process parameters are controlled through PLC based automated on-line data acquisition systems for achieving consistent powder quality with increased recovery and production. The present paper covers optimization of process parameters and powder characteristics. (author)

  15. Optimizing parameters of a technical system using quality function deployment method

    Science.gov (United States)

    Baczkowicz, M.; Gwiazda, A.

    2015-11-01

    The article shows the practical use of Quality Function Deployment (QFD) on the example of a mechanized mining support. Firstly it gives a short description of this method and shows how the designing process, from the constructor point of view, looks like. The proposed method allows optimizing construction parameters and comparing them as well as adapting to customer requirements. QFD helps to determine the full set of crucial construction parameters and then their importance and difficulty of their execution. Secondly it shows chosen technical system and presents its construction with figures of the existing and future optimized model. The construction parameters were selected from the designer point of view. The method helps to specify a complete set of construction parameters, from the point of view, of the designed technical system and customer requirements. The QFD matrix can be adjusted depending on designing needs and not every part of it has to be considered. Designers can choose which parts are the most important. Due to this QFD can be a very flexible tool. The most important is to define relationships occurring between parameters and that part cannot be eliminated from the analysis.

  16. Parameters nanodimensional zinc films deposited by the laser method in vacuum

    International Nuclear Information System (INIS)

    Goncharov, V.K.; Gusakov, G.A.; Puzyrev, M.V.

    2013-01-01

    The investigation of the thickness and structure of a zinc films surface produced by the laser-plasma deposition has been carried out. The dependence of a film thickness and surface structure from laser radiation intensity has been determined. Threshold intensity has been determined when an evaporation of a target material begins. (authors)

  17. Parameters of nanodimensional aluminium films deposited by the laser method in vacuum

    International Nuclear Information System (INIS)

    Gusakov, G.A.; Ismailov, D.R.; Puzyrev, M.V.

    2011-01-01

    The investigation of the thickness and structure of a aluminium films surface produced by the laser-plasma deposition has been carried out. The dependence of a film thickness from laser radiation intensity has been determined. Threshold intensity has been determined when an evaporation of a target material begins. (authors)

  18. Modeling and optimization of atomic layer deposition processes on vertically aligned carbon nanotubes

    Directory of Open Access Journals (Sweden)

    Nuri Yazdani

    2014-03-01

    Full Text Available Many energy conversion and storage devices exploit structured ceramics with large interfacial surface areas. Vertically aligned carbon nanotube (VACNT arrays have emerged as possible scaffolds to support large surface area ceramic layers. However, obtaining conformal and uniform coatings of ceramics on structures with high aspect ratio morphologies is non-trivial, even with atomic layer deposition (ALD. Here we implement a diffusion model to investigate the effect of the ALD parameters on coating kinetics and use it to develop a guideline for achieving conformal and uniform thickness coatings throughout the depth of ultra-high aspect ratio structures. We validate the model predictions with experimental data from ALD coatings of VACNT arrays. However, the approach can be applied to predict film conformality as a function of depth for any porous topology, including nanopores and nanowire arrays.

  19. Modeling and optimization of atomic layer deposition processes on vertically aligned carbon nanotubes.

    Science.gov (United States)

    Yazdani, Nuri; Chawla, Vipin; Edwards, Eve; Wood, Vanessa; Park, Hyung Gyu; Utke, Ivo

    2014-01-01

    Many energy conversion and storage devices exploit structured ceramics with large interfacial surface areas. Vertically aligned carbon nanotube (VACNT) arrays have emerged as possible scaffolds to support large surface area ceramic layers. However, obtaining conformal and uniform coatings of ceramics on structures with high aspect ratio morphologies is non-trivial, even with atomic layer deposition (ALD). Here we implement a diffusion model to investigate the effect of the ALD parameters on coating kinetics and use it to develop a guideline for achieving conformal and uniform thickness coatings throughout the depth of ultra-high aspect ratio structures. We validate the model predictions with experimental data from ALD coatings of VACNT arrays. However, the approach can be applied to predict film conformality as a function of depth for any porous topology, including nanopores and nanowire arrays.

  20. Optimization of Squeeze Casting Parameters for 2017 A Wrought Al Alloy Using Taguchi Method

    Directory of Open Access Journals (Sweden)

    Najib Souissi

    2014-04-01

    Full Text Available This study applies the Taguchi method to investigate the relationship between the ultimate tensile strength, hardness and process variables in a squeeze casting 2017 A wrought aluminium alloy. The effects of various casting parameters including squeeze pressure, melt temperature and die temperature were studied. Therefore, the objectives of the Taguchi method for the squeeze casting process are to establish the optimal combination of process parameters and to reduce the variation in quality between only a few experiments. The experimental results show that the squeeze pressure significantly affects the microstructure and the mechanical properties of 2017 A Al alloy.

  1. Stepwise optimization and global chaos of nonlinear parameters in exact calculations of few-particle systems

    International Nuclear Information System (INIS)

    Frolov, A.M.

    1986-01-01

    The problem of exact variational calculations of few-particle systems in the exponential basis of the relative coordinates using nonlinear parameters is studied. The techniques of stepwise optimization and global chaos of nonlinear parameters are used to calculate the S and P states of homonuclear muonic molecules with an error of no more than +0.001 eV. The global-chaos technique also has proved to be successful in the case of the nuclear systems 3 H and 3 He

  2. Optimization of Cutting Parameters on Delamination of Drilling Glass-Polyester Composites

    Directory of Open Access Journals (Sweden)

    Majid Habeeb Faidh-Allah

    2018-02-01

    Full Text Available This paper attempted to study the effect of cutting parameters (spindle speed and feed rate on delamination phenomena during the drilling glass-polyester composites. Drilling process was done by CNC machine with 10 mm diameter of high-speed steel (HSS drill bit. Taguchi technique with L16 orthogonal layout was used to analyze the effective parameters on delamination factor. The optimal experiment was no. 13 with spindle speed 1273 rpm and feed 0.05 mm/rev with minimum delamination factor 1.28.

  3. Saturne II synchroton injector parameters operation and control: computerization and optimization

    International Nuclear Information System (INIS)

    Lagniel, J.M.

    1983-01-01

    The injector control system has been studied, aiming at the beam quality improvement, the increasing of the versatility, and a better machine availability. It has been choosen to realize the three following functions: - acquisition of the principal parameters of the process, so as to control them quickly and to be warned if one of them is wrong (monitoring); - the control of those parameters, one by one or by families (starting, operating point); - the research of an optimal control (on a model or on the process itself) [fr

  4. Optimization of structural and growth parameters of metamorphic InGaAs photovoltaic converters grown by MOCVD

    Energy Technology Data Exchange (ETDEWEB)

    Rybalchenko, D. V.; Mintairov, S. A.; Salii, R. A.; Shvarts, M. Z.; Timoshina, N. Kh.; Kalyuzhnyy, N. A., E-mail: nickk@mail.ioffe.ru [Russian Academy of Sciences, Ioffe Physical–Technical Institute (Russian Federation)

    2017-01-15

    Metamorphic Ga{sub 0.76}In{sub 0.24}As heterostructures for photovoltaic converters are grown by the MOCVD (metal–organic chemical vapor deposition) technique. It is found that, due to the valence-band offset at the p-In{sub 0.24}Al{sub 0.76}As/p-In{sub 0.24}Ga{sub 0.76}As (wide-gap window/emitter) heterointerface, a potential barrier for holes arises as a result of a low carrier concentration in the wide-gap material. The use of an InAlGaAs solid solution with an Al content lower than 40% makes it possible to raise the hole concentration in the widegap window up ~9 × 10{sup 18} cm{sup –3} and completely remove the potential barrier, thereby reducing the series resistance of the device. The parameters of an GaInAs metamorphic buffer layer with a stepwise In content profile are calculated and its epitaxial growth conditions are optimized, which improves carrier collection from the n-GaInAs base region and provides a quantum efficiency of 83% at a wavelength of 1064 nm. Optimization of the metamorphic heterostructure of the photovoltaic converter results in that its conversion efficiency for laser light with a wavelength of 1064 nm is 38.5%.

  5. An optimal autonomous microgrid cluster based on distributed generation droop parameter optimization and renewable energy sources using an improved grey wolf optimizer

    Science.gov (United States)

    Moazami Goodarzi, Hamed; Kazemi, Mohammad Hosein

    2018-05-01

    Microgrid (MG) clustering is regarded as an important driver in improving the robustness of MGs. However, little research has been conducted on providing appropriate MG clustering. This article addresses this shortfall. It proposes a novel multi-objective optimization approach for finding optimal clustering of autonomous MGs by focusing on variables such as distributed generation (DG) droop parameters, the location and capacity of DG units, renewable energy sources, capacitors and powerline transmission. Power losses are minimized and voltage stability is improved while virtual cut-set lines with minimum power transmission for clustering MGs are obtained. A novel chaotic grey wolf optimizer (CGWO) algorithm is applied to solve the proposed multi-objective problem. The performance of the approach is evaluated by utilizing a 69-bus MG in several scenarios.

  6. Optimal relations of the parameters ensuring safety during reactor start-up

    International Nuclear Information System (INIS)

    Yurkevich, G.P.

    2004-01-01

    Procedure and equations for the determination of optimal ratio between parameters allowing safe removal of reactor in critical state are suggested. Initial pulse frequency of pulsed start-up channel and power of neutron source are decreased by reduced rate of changing reactivity during automatic start-up, disposition of pulsed neutron detector in the range with neutron flux density to 5·10 12 s -1 cm -2 at standard power, separate signal of period for the use in chains of automatic start-up and emergency protection, reduction of pulses frequency of the start-up channel (the frequency is equal to 4000 c -1 ). Procedure and equations for the determination of optimal parameters are effected with the account of statistic character of pulsed detector frequency and false outlet signal [ru

  7. Parameter optimization for transitions between memory states in small arrays of Josephson junctions

    Energy Technology Data Exchange (ETDEWEB)

    Rezac, Jacob D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computing and Computational Sciences Directorate; Univ. of Delaware, Newark, DE (United States). Dept. of Mathematical Sciences; Imam, Neena [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computing and Computational Sciences Directorate; Braiman, Yehuda [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computing and Computational Sciences Directorate; ; Univ. of Tennessee, Knoxville, TN (United States). Dept. of Mechanical, Aerospace, and Biomedical Engineering

    2017-01-11

    Coupled arrays of Josephson junctions possess multiple stable zero voltage states. Such states can store information and consequently can be utilized for cryogenic memory applications. Basic memory operations can be implemented by sending a pulse to one of the junctions and studying transitions between the states. In order to be suitable for memory operations, such transitions between the states have to be fast and energy efficient. Here in this article we employed simulated annealing, a stochastic optimization algorithm, to study parameter optimization of array parameters which minimizes times and energies of transitions between specifically chosen states that can be utilized for memory operations (Read, Write, and Reset). Simulation results show that such transitions occur with access times on the order of 10–100 ps and access energies on the order of 10-19–5×10-18 J. Numerical simulations are validated with approximate analytical results.

  8. Physiochemical parameters optimization for enhanced nisin production by Lactococcus lactis (MTCC 440

    Directory of Open Access Journals (Sweden)

    Puspadhwaja Mall

    2010-02-01

    Full Text Available The influence of various physiochemical parameters on the growth of Lactococcus lactis sub sp. lactis MTCC 440 was studied at shake flask level for 20 h. Media optimization (MRS broth was studied to achieve enhanced growth of the organism and also nisin production. Bioassay of nisin was done with agar diffusion method using Streptococcus agalactae NCIM 2401 as indicator strain. MRS broth (6%, w/v with 0.15μg/ml of nisin supplemented with 0.5% (v/v skimmed milk was found to be the best for nisin production as well as for growth of L lactis. The production of nisin was strongly influenced by the presence of skimmed milk and nisin in MRS broth. The production of nisin was affected by the physical parameters and maximum nisin production was at 30(0C while the optimal temperature for biomass production was 37(0C.

  9. Multi-criteria optimization of chassis parameters of Nissan 200 SX for drifting competitions

    Science.gov (United States)

    Maniowski, M.

    2016-09-01

    The work objective is to increase performance of Nissan 200sx S13 prepared for a quasi-static state of drifting on a circular path with given constant radius (R=15 m) and tyre-road friction coefficient (μ = 0.9). First, a high fidelity “miMA” multibody model of the vehicle is formulated. Then, a multicriteria optimization problem is solved with one of the goals to maximize a stable drift angle (β) of the vehicle. The decision variables contain 11 parameters of the vehicle chassis (describing the wheel suspension stiffness and geometry) and 2 parameters responsible for a driver steering and accelerator actions, that control this extreme closed-loop manoeuvre. The optimized chassis setup results in the drift angle increase by 14% from 35 to 40 deg.

  10. A novel membrane-based process to isolate peroxidase from horseradish roots: optimization of operating parameters.

    Science.gov (United States)

    Liu, Jianguo; Yang, Bo; Chen, Changzhen

    2013-02-01

    The optimization of operating parameters for the isolation of peroxidase from horseradish (Armoracia rusticana) roots with ultrafiltration (UF) technology was systemically studied. The effects of UF operating conditions on the transmission of proteins were quantified using the parameter scanning UF. These conditions included solution pH, ionic strength, stirring speed and permeate flux. Under optimized conditions, the purity of horseradish peroxidase (HRP) obtained was greater than 84 % after a two-stage UF process and the recovery of HRP from the feedstock was close to 90 %. The resulting peroxidase product was then analysed by isoelectric focusing, SDS-PAGE and circular dichroism, to confirm its isoelectric point, molecular weight and molecular secondary structure. The effects of calcium ion on HRP specific activities were also experimentally determined.

  11. Parameter Optimization for Enhancement of Ethanol Yield by Atmospheric Pressure DBD-Treated Saccharomyces cerevisiae

    International Nuclear Information System (INIS)

    Dong Xiaoyu; Yuan Yulian; Tang Qian; Dou Shaohua; Di Lanbo; Zhang Xiuling

    2014-01-01

    In this study, Saccharomyces cerevisiae (S. cerevisiae) was exposed to dielectric barrier discharge plasma (DBD) to improve its ethanol production capacity during fermentation. Response surface methodology (RSM) was used to optimize the discharge-associated parameters of DBD for the purpose of maximizing the ethanol yield achieved by DBD-treated S. cerevisiae. According to single factor experiments, a mathematical model was established using Box-Behnken central composite experiment design, with plasma exposure time, power supply voltage, and exposed-sample volume as impact factors and ethanol yield as the response. This was followed by response surface analysis. Optimal experimental parameters for plasma discharge-induced enhancement in ethanol yield were plasma exposure time of 1 min, power voltage of 26 V, and an exposed sample volume of 9 mL. Under these conditions, the resulting yield of ethanol was 0.48 g/g, representing an increase of 33% over control. (plasma technology)

  12. Optimization of the parameters of power sources excited by β-radiation

    Energy Technology Data Exchange (ETDEWEB)

    Bulyarskiy, S. V., E-mail: bulyar2954@mail.ru; Lakalin, A. V. [Russian Academy of Sciences, Institute of Nanotechnology of Microelectronics (Russian Federation); Abanin, I. E.; Amelichev, V. V. [Technological Center (Russian Federation); Svetuhin, V. V. [Ulyanovsk State University (Russian Federation)

    2017-01-15

    The experimental results and calculations of the efficiency of the energy conversion of Ni-63 β-radiation sources to electricity using silicon p–i–n diodes are presented. All calculations are performed taking into account the energy distribution of β-electrons. An expression for the converter open-circuit voltage is derived taking into account the distribution of high-energy electrons in the space-charge region of the p–i–n diode. Ways of optimizing the converter parameters by improving the technology of diodes and optimizing the emitter active layer and i-region thicknesses of the semiconductor converter are shown. The distribution of the conversion losses to the source and radiation detector and the losses to high-energy electron entry into the semiconductor is calculated. Experimental values of the conversion efficiency of 0.4–0.7% are in good agreement with the calculated parameters.

  13. Parameters estimation online for Lorenz system by a novel quantum-behaved particle swarm optimization

    International Nuclear Information System (INIS)

    Gao Fei; Tong Hengqing; Li Zhuoqiu

    2008-01-01

    This paper proposes a novel quantum-behaved particle swarm optimization (NQPSO) for the estimation of chaos' unknown parameters by transforming them into nonlinear functions' optimization. By means of the techniques in the following three aspects: contracting the searching space self-adaptively; boundaries restriction strategy; substituting the particles' convex combination for their centre of mass, this paper achieves a quite effective search mechanism with fine equilibrium between exploitation and exploration. Details of applying the proposed method and other methods into Lorenz systems are given, and experiments done show that NQPSO has better adaptability, dependability and robustness. It is a successful approach in unknown parameter estimation online especially in the cases with white noises

  14. Performance Evaluation and Parameter Optimization of SoftCast Wireless Video Broadcast

    Directory of Open Access Journals (Sweden)

    Dongxue Yang

    2015-08-01

    Full Text Available Wireless video broadcast plays an imp ortant role in multimedia communication with the emergence of mobile video applications. However, conventional video broadcast designs suffer from a cliff effect due to separated source and channel encoding. The newly prop osed SoftCast scheme employs a cross-layer design, whose reconstructed video quality is prop ortional to the channel condition. In this pap er, we provide the p erformance evaluation and the parameter optimization of the SoftCast system. Optimization principles on parameter selection are suggested to obtain a b etter video quality, o ccupy less bandwidth and/or utilize lower complexity. In addition, we compare SoftCast with H.264 in the LTE EPA scenario. The simulation results show that SoftCast provides a b etter p erformance in the scalability to channel conditions and the robustness to packet losses.

  15. Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems

    Directory of Open Access Journals (Sweden)

    Erdem Demircioglu

    2015-01-01

    Full Text Available This paper discusses bandwidth enhancement for multiband microstrip patch antennas (MMPAs using symmetrical rectangular/square slots etched on the patch and the substrate properties. The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN. To achieve the best ANN performance, Particle Swarm Optimization (PSO and Differential Evolution (DE are applied with ANN’s conventional training algorithm in optimization of the modeling performance. In this study, the slot parameters are assumed as slot distance to the radiating patch edge, slot width, and length. Bandwidth enhancement is applied to a formerly designed MMPA fed by a microstrip transmission line attached to the center pin of 50 ohm SMA connecter. The simulated antennas are fabricated and measured. Measurement results are utilized for training the artificial intelligence models. The ANN provides 98% model accuracy for rectangular slots and 97% for square slots; however, ANFIS offer 90% accuracy with lack of resonance frequency tracking.

  16. Production of sintered alumina from powder; optimization of the sinterized parameters for the maximum mechanical resistence

    International Nuclear Information System (INIS)

    Rocha, J.C. da.

    1981-02-01

    Pure, sinterized alumina and the optimization of the parameters of sinterization in order to obtain the highest mechanical resistence are discussed. Test materials are sinterized from a fine powder of pure alumina (Al 2 O 3 ), α phase, at different temperatures and times, in air. The microstructures are analysed concerning porosity and grain size. Depending on the temperature or the time of sinterization, there is a maximum for the mechanical resistence. (A.R.H.) [pt

  17. Accuracy Analysis and Parameters Optimization in Urban Flood Simulation by PEST Model

    Science.gov (United States)

    Keum, H.; Han, K.; Kim, H.; Ha, C.

    2017-12-01

    The risk of urban flooding has been increasing due to heavy rainfall, flash flooding and rapid urbanization. Rainwater pumping stations, underground reservoirs are used to actively take measures against flooding, however, flood damage from lowlands continues to occur. Inundation in urban areas has resulted in overflow of sewer. Therefore, it is important to implement a network system that is intricately entangled within a city, similar to the actual physical situation and accurate terrain due to the effects on buildings and roads for accurate two-dimensional flood analysis. The purpose of this study is to propose an optimal scenario construction procedure watershed partitioning and parameterization for urban runoff analysis and pipe network analysis, and to increase the accuracy of flooded area prediction through coupled model. The establishment of optimal scenario procedure was verified by applying it to actual drainage in Seoul. In this study, optimization was performed by using four parameters such as Manning's roughness coefficient for conduits, watershed width, Manning's roughness coefficient for impervious area, Manning's roughness coefficient for pervious area. The calibration range of the parameters was determined using the SWMM manual and the ranges used in the previous studies, and the parameters were estimated using the automatic calibration method PEST. The correlation coefficient showed a high correlation coefficient for the scenarios using PEST. The RPE and RMSE also showed high accuracy for the scenarios using PEST. In the case of RPE, error was in the range of 13.9-28.9% in the no-parameter estimation scenarios, but in the scenario using the PEST, the error range was reduced to 6.8-25.7%. Based on the results of this study, it can be concluded that more accurate flood analysis is possible when the optimum scenario is selected by determining the appropriate reference conduit for future urban flooding analysis and if the results is applied to various

  18. Characterization of PV panel and global optimization of its model parameters using genetic algorithm

    International Nuclear Information System (INIS)

    Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.

    2013-01-01

    Highlights: • Genetic Algorithm optimization ability had been utilized to extract parameters of PV panel model. • Effect of solar radiation and temperature variations was taken into account in fitness function evaluation. • We used Matlab-Simulink to simulate operation of the PV-panel to validate results. • Different cases were analyzed to ascertain which of them gives more accurate results. • Accuracy and applicability of this approach to be used as a valuable tool for PV modeling were clearly validated. - Abstract: This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer’s Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab–Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules

  19. SVM classification model in depression recognition based on mutation PSO parameter optimization

    Directory of Open Access Journals (Sweden)

    Zhang Ming

    2017-01-01

    Full Text Available At present, the clinical diagnosis of depression is mainly through structured interviews by psychiatrists, which is lack of objective diagnostic methods, so it causes the higher rate of misdiagnosis. In this paper, a method of depression recognition based on SVM and particle swarm optimization algorithm mutation is proposed. To address on the problem that particle swarm optimization (PSO algorithm easily trap in local optima, we propose a feedback mutation PSO algorithm (FBPSO to balance the local search and global exploration ability, so that the parameters of the classification model is optimal. We compared different PSO mutation algorithms about classification accuracy for depression, and found the classification accuracy of support vector machine (SVM classifier based on feedback mutation PSO algorithm is the highest. Our study promotes important reference value for establishing auxiliary diagnostic used in depression recognition of clinical diagnosis.

  20. Multi-objective optimization problems concepts and self-adaptive parameters with mathematical and engineering applications

    CERN Document Server

    Lobato, Fran Sérgio

    2017-01-01

    This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.

  1. Optimization of pump parameters for gain flattened Raman fiber amplifiers based on artificial fish school algorithm

    Science.gov (United States)

    Jiang, Hai Ming; Xie, Kang; Wang, Ya Fei

    2011-11-01

    In this work, a novel metaheuristic named artificial fish school algorithm is introduced into the optimization of pump parameters for the design of gain flattened Raman fiber amplifiers for the first time. Artificial fish school algorithm emulates three simple social behaviors of a fish in a school, namely, preying, swarming and following, to optimize a target function. In this algorithm the pump wavelengths and power levels are mapped respectively to the state of a fish in a school, and the gain of a Raman fiber amplifier is mapped to the concentration of a food source for the fish school to search. Application of this algorithm to the design of a C-band gain flattened Raman fiber amplifier leads to an optimized amplifier that produces a flat gain spectrum with 0.63 dB in band ripple for given conditions. This result demonstrates that the artificial fish school algorithm is efficient for the optimization of pump parameters of gain flattened Raman fiber amplifiers.

  2. Study on Parameter Optimization Design of Drum Brake Based on Hybrid Cellular Multiobjective Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2012-01-01

    Full Text Available In consideration of the significant role the brake plays in ensuring the fast and safe running of vehicles, and since the present parameter optimization design models of brake are far from the practical application, this paper proposes a multiobjective optimization model of drum brake, aiming at maximizing the braking efficiency and minimizing the volume and temperature rise of drum brake. As the commonly used optimization algorithms are of some deficiency, we present a differential evolution cellular multiobjective genetic algorithm (DECell by introducing differential evolution strategy into the canonical cellular genetic algorithm for tackling this problem. For DECell, the gained Pareto front could be as close as possible to the exact Pareto front, and also the diversity of nondominated individuals could be better maintained. The experiments on the test functions reveal that DECell is of good performance in solving high-dimension nonlinear multiobjective problems. And the results of optimizing the new brake model indicate that DECell obviously outperforms the compared popular algorithm NSGA-II concerning the number of obtained brake design parameter sets, the speed, and stability for finding them.

  3. Optimization of Silicon MZM Fabrication Parameters for High Speed Short Reach Interconnects at 1310 nm

    Directory of Open Access Journals (Sweden)

    Alexis Abraham

    2016-11-01

    Full Text Available Optical modulators are key components to realize photonic circuits, and Mach-Zehnder modulators (MZM are often used for high speed short reach interconnects. In order to maximize the tolerable path loss of a transmission link at a given bitrate, the MZM needs to be optimized. However, the optimization can be complex since the overall link performance depends on various parameters, and, for the MZM in particular, implies several trade-offs between efficiency, losses, and bandwidth. In this work, we propose a general and rigorous method to optimize silicon MZM. We first describe the optical link, and the numerical method used for this study. Then we present the results associated to the active region for 1310 nm applications. An analytical model is generated, and allows us to quickly optimize the p-n junction depending of the targeted performances for the MZM. Taking into account the required optical link parameters, the maximum tolerable path losses for different length of MZM is determined. By applying this method, simulations show that the optimum MZM length for 25 Gbps applications is 4 mm with an efficiency of 1.87 V·cm, 0.52 dB/mm of losses. A tolerable path loss of more than 25 dB is obtained.

  4. Optimizing Parameters of Axial Pressure-Compounded Ultra-Low Power Impulse Turbines at Preliminary Design

    Science.gov (United States)

    Kalabukhov, D. S.; Radko, V. M.; Grigoriev, V. A.

    2018-01-01

    Ultra-low power turbine drives are used as energy sources in auxiliary power systems, energy units, terrestrial, marine, air and space transport within the confines of shaft power N td = 0.01…10 kW. In this paper we propose a new approach to the development of surrogate models for evaluating the integrated efficiency of multistage ultra-low power impulse turbine with pressure stages. This method is based on the use of existing mathematical models of ultra-low power turbine stage efficiency and mass. It has been used in a method for selecting the rational parameters of two-stage axial ultra-low power turbine. The article describes the basic features of an algorithm for two-stage turbine parameters optimization and for efficiency criteria evaluating. Pledged mathematical models are intended for use at the preliminary design of turbine drive. The optimization method was tested at preliminary design of an air starter turbine. Validation was carried out by comparing the results of optimization calculations and numerical gas-dynamic simulation in the Ansys CFX package. The results indicate a sufficient accuracy of used surrogate models for axial two-stage turbine parameters selection

  5. Application of HGSO to security based optimal placement and parameter setting of UPFC

    International Nuclear Information System (INIS)

    Tarafdar Hagh, Mehrdad; Alipour, Manijeh; Teimourzadeh, Saeed

    2014-01-01

    Highlights: • A new method for solving the security based UPFC placement and parameter setting problem is proposed. • The proposed method is a global method for all mixed-integer problems. • The proposed method has the ability of the parallel search in binary and continues space. • By using the proposed method, most of the problems due to line contingencies are solved. • Comparison studies are done to compare the performance of the proposed method. - Abstract: This paper presents a novel method to solve security based optimal placement and parameter setting of unified power flow controller (UPFC) problem based on hybrid group search optimization (HGSO) technique. Firstly, HGSO is introduced in order to solve mix-integer type problems. Afterwards, the proposed method is applied to the security based optimal placement and parameter setting of UPFC problem. The focus of the paper is to enhance the power system security through eliminating or minimizing the over loaded lines and the bus voltage limit violations under single line contingencies. Simulation studies are carried out on the IEEE 6-bus, IEEE 14-bus and IEEE 30-bus systems in order to verify the accuracy and robustness of the proposed method. The results indicate that by using the proposed method, the power system remains secure under single line contingencies

  6. Optimization of processing parameters of amaranth grits before grinding into flour

    Science.gov (United States)

    Zharkova, I. M.; Safonova, Yu A.; Slepokurova, Yu I.

    2018-05-01

    There are the results of experimental studies about the influence of infrared treatment (IR processing) parameters of the amaranth grits before their grinding into flour on the composition and properties of the received product. Using the method called as regressionfactor analysis, the optimal conditions of the thermal processing to the amaranth grits were obtained: the belt speed of the conveyor – 0.049 m/s; temperature of amaranth grits in the tempering silo – 65.4 °C the thickness of the layer of amaranth grits on the belt is 3 - 5 mm and the lamp power is 69.2 kW/m2. The conducted researches confirmed that thermal effect to the amaranth grains in the IR setting allows getting flour with a smaller size of starch grains, with the increased water-holding ability, and with a changed value of its glycemic index. Mathematical processing of experimental data allowed establishing the dependence of the structural and technological characteristics of the amaranth flour on the IR processing parameters of amaranth grits. The obtained results are quite consistent with the experimental ones that proves the effectiveness of optimization based on mathematical planning of the experiment to determine the influence of heat treatment optimal parameters of the amaranth grits on the functional and technological properties of the flour received from it.

  7. Optimization of the fiber laser parameters for local high-temperature impact on metal

    Science.gov (United States)

    Yatsko, Dmitrii S.; Polonik, Marina V.; Dudko, Olga V.

    2016-11-01

    This paper presents the local laser heating process of surface layer of the metal sample. The aim is to create the molten pool with the required depth by laser thermal treatment. During the heating the metal temperature at any point of the molten zone should not reach the boiling point of the main material. The laser power, exposure time and the spot size of a laser beam are selected as the variable parameters. The mathematical model for heat transfer in a semi-infinite body, applicable to finite slab, is used for preliminary theoretical estimation of acceptable parameters values of the laser thermal treatment. The optimization problem is solved by using an algorithm based on the scanning method of the search space (the zero-order method of conditional optimization). The calculated values of the parameters (the optimal set of "laser radiation power - exposure time - spot radius") are used to conduct a series of natural experiments to obtain a molten pool with the required depth. A two-stage experiment consists of: a local laser treatment of metal plate (steel) and then the examination of the microsection of the laser irradiated region. According to the experimental results, we can judge the adequacy of the ongoing calculations within the selected models.

  8. Reduced order modeling and parameter identification of a building energy system model through an optimization routine

    International Nuclear Information System (INIS)

    Harish, V.S.K.V.; Kumar, Arun

    2016-01-01

    Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.

  9. Critical parameters in the sputter-deposition of NdBa{sub 2}Cu{sub 3}O{sub 7-{delta}} thin films

    Energy Technology Data Exchange (ETDEWEB)

    Hakuraku, Y.; Yokoyama, N.; Doi, T.; Inoue, T. [Faculty of Engineering, Kagoshima University, Koorimoto, Kagoshima 890, (Japan); Mori, Z.; Koba, S. [Yatsushiro National College of Technology, Yatsushiro 866 (Japan)

    1999-08-01

    A superconducting thin film of NdBa{sub 2}Cu{sub 3}O{sub 7-{delta}} (NBCO) was prepared on an MgO(100) substrate by dc magnetron sputtering. Superconducting properties as well as features such as resistivity at room temperature and surface morphology were improved by optimizing the composition of sputtering target and critical parameters such as substrate temperature and oxidation gas pressure. A highly c-axis oriented thin film with T{sub c} (zero resistance temperature) = 95.2 K was obtained reproducibly with NdBa{sub 2}Cu{sub 3.2}O{sub 7-{delta}} off-stoichiometric target sputtering. T{sub c} = 95.2 K was 8 K higher than that deposited by stoichiometric target sputtering. Critical current density was 1x10{sup 6} A cm{sup -2} at 77 K, and surface roughness was 35 nm. (author)

  10. Global parameter optimization for maximizing radioisotope detection probabilities at fixed false alarm rates

    Energy Technology Data Exchange (ETDEWEB)

    Portnoy, David, E-mail: david.portnoy@jhuapl.edu [Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723 (United States); Feuerbach, Robert; Heimberg, Jennifer [Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723 (United States)

    2011-10-01

    Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the 'threat' set of

  11. Global parameter optimization for maximizing radioisotope detection probabilities at fixed false alarm rates

    International Nuclear Information System (INIS)

    Portnoy, David; Feuerbach, Robert; Heimberg, Jennifer

    2011-01-01

    Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the 'threat' set of spectra

  12. Global parameter optimization for maximizing radioisotope detection probabilities at fixed false alarm rates

    Science.gov (United States)

    Portnoy, David; Feuerbach, Robert; Heimberg, Jennifer

    2011-10-01

    Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the "threat" set of spectra

  13. Optimization method to determine mass transfer variables in a PWR crud deposition risk assessment tool

    International Nuclear Information System (INIS)

    Do, Chuong; Hussey, Dennis; Wells, Daniel M.; Epperson, Kenny

    2016-01-01

    Optimization numerical method was implemented to determine several mass transfer coefficients in a crud-induced power shift risk assessment code. The approach was to utilize a multilevel strategy that targets different model parameters that first changes the major order variables, mass transfer inputs, then calibrates the minor order variables, crud source terms, according to available plant data. In this manner, the mass transfer inputs are effectively simplified as 'dependent' on the crud source terms. Two optimization studies were performed using DAKOTA, a design and analysis toolkit, with the difference between the runs, being the number of model runs using BOA, allowed for adjusting the crud source terms, therefore, reducing the uncertainty with calibration. The result of the first case showed that the current best estimated values for the mass transfer coefficients, which were derived from first principle analysis, can be considered an optimized set. When the run limit of BOA was increased for the second case, an improvement in the prediction was obtained with the results deviating slightly from the best estimated values. (author)

  14. Growth parameter enhancement for MoS{sub 2} thin films synthesized by pulsed laser deposition

    Energy Technology Data Exchange (ETDEWEB)

    Serna, Martha I.; Higgins, Marissa; Quevedo-Lopez, Manuel A. [Materials Science and Engineering Department, The University of Texas at Dallas, 800 W Campbell Road RL 10, Richardson TX 75080 (United States); Moreno, Salvador [Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080 (United States); Choi, Hyunjoo [Department of Advanced Materials Engineering, Kookmin University, Jeongneung-dong Seongbuk-gu, Seoul 136-702 (Korea, Republic of); Minary-Jolandan, Majid [Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080 (United States); Alan MacDiarmid Nanotech Institute, The University of Texas at Dallas, 800 W Campbell Road RL 10, Richardson TX 75080 (United States)

    2016-12-15

    Two-dimensional materials such as graphene and MoS{sub 2} have been the main focus of intense research efforts over the past few years. The most common method of exfoliating these materials, although efficient for lab-scale experiments, is not acceptable for large area and practical applications. Here, we report the deposition of MoS{sub 2} layered films on amorphous (SiO{sub 2}) and crystalline substrates (sapphire) using a pulsed laser deposition (PLD) method. Increased substrate temperature (∝700 C) and laser energy density (>530 mJ /cm{sup 2}) promotes crystalline MoS{sub 2} films < 20 nm, as demonstrated by fast Fourier transform (FFT) and transmission electron microscopy (TEM). The method reported here opens the possibility for large area layered MoS{sub 2} films by using a laser ablation processes. (copyright 2016 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  15. Coal characteristics from 'Priskupshtina' deposit and technological parameters for briquetting (Macedonia)

    International Nuclear Information System (INIS)

    Damjanovski, Dragan

    1998-01-01

    The use of small class coal as well as the lack of formed fuel needed for the industry and for the consumer goods has been a long lasting problem, and a challenge for the researchers of the Republic of Macedonia. For that purpose, all-inclusive analysis of the quality of the coals in Macedonia, their reserves and technical characteristics, as well as analysis of the petrographic structure were made. Classification of the deposits and the research for the possibility of making briquettes was done, too. Laboratory investigations in the coal deposit 'Priskupshtina' were carried out. The analysis of the coal briquetting show that the expected results in coordination with the required standards were not obtained. Spatially the results from the coal calorific value, its hardness and atmospheric resistance. Standard methods were used for the researches without connective means and the achieved results were mutually correlated. Technical-economic verification is necessary in the further process. (Author)

  16. Sensitive parameters' optimization of the permanent magnet supporting mechanism

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yongguang; Gao, Xiaohui; Wang, Yixuan; Yang, Xiaowei [Beihang University, Beijing (China)

    2014-07-15

    The fast development of the ultra-high speed vertical rotor promotes the study and exploration for the supporting mechanism. It has become the focus of research that how to improve the speed and overcome the vibration when the rotors pass through the low-order critical frequencies. This paper introduces a kind of permanent magnet (PM) supporting mechanism and describes an optimization method of its sensitive parameters, which can make the vertical rotor system reach 80000 r/min smoothly. Firstly we find the sensitive parameters through analyzing the rotor's features in the process of achieving high-speed, then, study these sensitive parameters and summarize the regularities with the method of combining the experiment and the finite element method (FEM), at last, achieve the optimization method of these parameters. That will not only get a stable effect of raising speed and shorten the debugging time greatly, but also promote the extensive application of the PM supporting mechanism in the ultra-high speed vertical rotors.

  17. Homogeneous Gaussian Profile P+-Type Emitters: Updated Parameters and Metal-Grid Optimization

    Directory of Open Access Journals (Sweden)

    M. Cid

    2002-10-01

    Full Text Available P+-type emitters were optimized keeping the base parameters constant. Updated internal parameters were considered. The surface recombination velocity was considered variable with the surface doping level. Passivated homogeneous emitters were found to have low emitter recombination density and high collection efficiency. A complete structure p+nn+ was analyzed, taking into account optimized shadowing and metal-contacted factors for laboratory cells as function of the surface doping level and the emitter thickness. The base parameters were kept constant to make the emitter characteristics evident. The most efficient P+-type passivated homogeneous emitters, provide efficiencies around 21% for a wide range of emitter sheet resistivity (50 -- 500 omega/ with the surface doping levels Ns=1×10(19 cm-3 and 5×10(19 cm-3. The output electrical parameters were evaluated considering the recently proposed value n i=9.65×10(9 (cm-3. A non-significant increase of 0.1% in the efficiency was obtained, validating all the conclusions obtained in this work, considering n i=1×10(10 cm-3.

  18. Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

    Science.gov (United States)

    Pozzobon, Victor; Perre, Patrick

    2018-01-21

    This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Multiobjective Optimization of Turning Cutting Parameters for J-Steel Material

    Directory of Open Access Journals (Sweden)

    Adel T. Abbas

    2016-01-01

    Full Text Available This paper presents a multiobjective optimization study of cutting parameters in turning operation for a heat-treated alloy steel material (J-Steel with Vickers hardness in the range of HV 365–395 using uncoated, unlubricated Tungsten-Carbide tools. The primary aim is to identify proper settings of the cutting parameters (cutting speed, feed rate, and depth of cut that lead to reasonable compromises between good surface quality and high material removal rate. Thorough exploration of the range of cutting parameters was conducted via a five-level full-factorial experimental matrix of samples and the Pareto trade-off frontier is identified. The trade-off among the objectives was observed to have a “knee” shape, in which certain settings for the cutting parameters can achieve both good surface quality and high material removal rate within certain limits. However, improving one of the objectives beyond these limits can only happen at the expense of a large compromise in the other objective. An alternative approach for identifying the trade-off frontier was also tested via multiobjective implementation of the Efficient Global Optimization (m-EGO algorithm. The m-EGO algorithm was successful in identifying two points within the good range of the trade-off frontier with 36% fewer experimental samples.

  20. Statistical analysis of the effect of deposition parameters on the preferred orientation of sputtered AlN thin films

    International Nuclear Information System (INIS)

    Pantojas, V.M.; Otano-Rivera, W.; Caraballo, Jose N.

    2005-01-01

    A response surface statistical method was used to study the effects of deposition pressure, power and substrate temperature on the degree of preferred orientation of aluminum nitride films grown on Si (111) by dc magnetron sputtering. The AlN films were deposited at gas pressures ranging from 0.66 to 1.33 Pa, substrate temperature from 300 to 400 deg. C and power from 100 to 200 W. The degree of preferred orientation was evaluated and quantified using two-dimensional X-ray diffraction, which provides information on the out of plane (002) crystal alignment. The statistical method yielded a surface response curve in the parameter space and a correlation equation between the deposition parameters was obtained. Substrate temperature showed no significant effect upon texture quality for the temperature range studied. A surface response graph as a function of pressure and power was obtained. The main factor affecting texture quality was found to be a pressure-power interaction. The possible mechanisms that contribute to such correlation are discussed. Our best films yielded a rocking curve with full width at half maximum of 6.3 deg

  1. Improvement of the fringe analysis algorithm for wavelength scanning interferometry based on filter parameter optimization.

    Science.gov (United States)

    Zhang, Tao; Gao, Feng; Muhamedsalih, Hussam; Lou, Shan; Martin, Haydn; Jiang, Xiangqian

    2018-03-20

    The phase slope method which estimates height through fringe pattern frequency and the algorithm which estimates height through the fringe phase are the fringe analysis algorithms widely used in interferometry. Generally they both extract the phase information by filtering the signal in frequency domain after Fourier transform. Among the numerous papers in the literature about these algorithms, it is found that the design of the filter, which plays an important role, has never been discussed in detail. This paper focuses on the filter design in these algorithms for wavelength scanning interferometry (WSI), trying to optimize the parameters to acquire the optimal results. The spectral characteristics of the interference signal are analyzed first. The effective signal is found to be narrow-band (near single frequency), and the central frequency is calculated theoretically. Therefore, the position of the filter pass-band is determined. The width of the filter window is optimized with the simulation to balance the elimination of the noise and the ringing of the filter. Experimental validation of the approach is provided, and the results agree very well with the simulation. The experiment shows that accuracy can be improved by optimizing the filter design, especially when the signal quality, i.e., the signal noise ratio (SNR), is low. The proposed method also shows the potential of improving the immunity to the environmental noise by adapting the signal to acquire the optimal results through designing an adaptive filter once the signal SNR can be estimated accurately.

  2. Effects of upper body parameters on biped walking efficiency studied by dynamic optimization

    Directory of Open Access Journals (Sweden)

    Kang An

    2016-12-01

    Full Text Available Walking efficiency is one of the considerations for designing biped robots. This article uses the dynamic optimization method to study the effects of upper body parameters, including upper body length and mass, on walking efficiency. Two minimal actuations, hip joint torque and push-off impulse, are used in the walking model, and minimal constraints are set in a free search using the dynamic optimization. Results show that there is an optimal solution of upper body length for the efficient walking within a range of walking speed and step length. For short step length, walking with a lighter upper body mass is found to be more efficient and vice versa. It is also found that for higher speed locomotion, the increase of the upper body length and mass can make the walking gait optimal rather than other kind of gaits. In addition, the typical strategy of an optimal walking gait is that just actuating the swing leg at the beginning of the step.

  3. Optimal Machining Parameters for Achieving the Desired Surface Roughness in Turning of Steel

    Directory of Open Access Journals (Sweden)

    LB Abhang

    2012-06-01

    Full Text Available Due to the widespread use of highly automated machine tools in the metal cutting industry, manufacturing requires highly reliable models and methods for the prediction of output performance in the machining process. The prediction of optimal manufacturing conditions for good surface finish and dimensional accuracy plays a very important role in process planning. In the steel turning process the tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. In the present work, experimental investigations have been conducted to determine the effect of the tool geometry (effective tool nose radius and metal cutting conditions (cutting speed, feed rate and depth of cut on surface finish during the turning of EN-31 steel. First and second order mathematical models are developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using LINGO solver programs. LINGO is a mathematical modeling language which is used in linear and nonlinear optimization to formulate large problems concisely, solve them, and analyze the solution in engineering sciences, operation research etc. The LINGO solver program is global optimization software. It gives minimum values of surface roughness and their respective optimal conditions.

  4. Design optimization of structural parameters in double gate MOSFETs for RF applications

    International Nuclear Information System (INIS)

    Liang Jiale; Xiao Han; Huang Ru; Wang Pengfei; Wang Yangyuan

    2008-01-01

    Double gate (DG) MOSFETs have recently attracted much attention for both logic and analog/RF applications. In this paper we focus on the design consideration of DG devices for RF applications. The different influences of key structural parameters on RF characteristics are comprehensively studied and optimized, including body thickness, spacer length and source/drain raised height. The impact of the fluctuation of geometrical parameters of DG devices on RF figures-of-merit are estimated. In addition, different dominance of structural parameters for RF applications is studied in DG devices with different channel lengths. The dependence of RF performance on the gate length downscaling of DG devices is also discussed. The obtained results give the design guidelines for DG devices for RF applications

  5. Energetical optimization and parameters selection for a fixed faceted mirror concentrator

    International Nuclear Information System (INIS)

    Nicolas, R.O.; Duran, J.C.; Dawidowski, L.E.

    1990-01-01

    A method which allows to select the parameters of a cylindrical solar collector by means of an energetical optimization is presented. In particular, the energy collected by the operating fluid and the collection efficiency of a Fixed Faceted Mirror Concentrator (FFMC) are obtained and compared for different sets of parameters. To this end, the two-dimensional optical analysis for non-perfect cylindrical concentrators presented previously is used. Some graphs analyzing the variations of the yearly efficiency of the FFMC as a function of those parameters are given. Finally, the possibility of using a second concentrator in the receiver plane of the FFMC in order to improve the whole efficiency of the prototype is also analyzed. (Author)

  6. State and parameter estimation in nonlinear systems as an optimal tracking problem

    International Nuclear Information System (INIS)

    Creveling, Daniel R.; Gill, Philip E.; Abarbanel, Henry D.I.

    2008-01-01

    In verifying and validating models of nonlinear processes it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, we present a framework for connecting a data signal with a model in a way that minimizes the required coupling yet allows the estimation of unknown parameters in the model. The need to evaluate unknown parameters in models of nonlinear physical, biophysical, and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. Our approach builds on existing work that uses synchronization as a tool for parameter estimation. We address some of the critical issues in that work and provide a practical framework for finding an accurate solution. In particular, we show the equivalence of this problem to that of tracking within an optimal control framework. This equivalence allows the application of powerful numerical methods that provide robust practical tools for model development and validation

  7. Optimization of a Cu CMP process modeling parameters of nanometer integrated circuits

    International Nuclear Information System (INIS)

    Ruan Wenbiao; Chen Lan; Ma Tianyu; Fang Jingjing; Zhang He; Ye Tianchun

    2012-01-01

    A copper chemical mechanical polishing (Cu CMP) process is reviewed and analyzed from the view of chemical physics. Three steps Cu CMP process modeling is set up based on the actual process of manufacturing and pattern-density-step-height (PDSH) modeling from MIT. To catch the pattern dependency, a 65 nm testing chip is designed and processed in the foundry. Following the model parameter extraction procedure, the model parameters are extracted and verified by testing data from the 65 nm testing chip. A comparison of results between the model predictions and test data show that the former has the same trend as the latter and the largest deviation is less than 5 nm. Third party testing data gives further evidence to support the great performance of model parameter optimization. Since precise CMP process modeling is used for the design of manufacturability (DFM) checks, critical hotspots are displayed and eliminated, which will assure good yield and production capacity of IC. (semiconductor technology)

  8. Optimization of process parameters of ECM by RSM on AISI 202 steel

    Directory of Open Access Journals (Sweden)

    P. Alex John Britto

    2015-12-01

    Full Text Available The machining of complex shaped designs was difficult earlier, but with the advent of the newer machining processes incorporating in it electrical, chemical & mechanical processes, manufacturing has redefined itself. Especially, the Electrochemical Machining (ECM process is used to machine the hard to cut materials without producing heat and friction. Hence, in this work, the ECM process has been chosen to machine SS AISI 202 steel. This study establishes the effect of process parameters such as voltage, current and concentration of electrolyte on the responses on material removal rate (MRR. In this work, second-order quadratic models were developed for MRR, considering the electrolyte concentration, voltage and current as the machining parameters, using central composite design. The developed models were used for Response Surface Methodology (RSM optimization by desirability function approach to determine the optimum machining parameters.

  9. Optimized Deposition Parameters & Coating Properties of Cobalt Phosphorus Alloy Electroplating for Technology Insertion Risk Reduction

    Science.gov (United States)

    2010-10-01

    of tensile yield strength (Fty) and the runout load (107 cycles), with no more than four points per load. Load and cycles to failure were used to...were coated with 0.002” nCo-P at Integran Technologies Inc. or 0.002” at FRC-SE. Testing was conducted using CS-17 wheels at FRC-SE. 3.2 RESULTS...Abrasive wear tests shall be conducted using the Taber wear test apparatus in accordance with ASTM D4060 using a CS-17 wheel . The wear rate of

  10. Parameters optimization, microstructure and micro-hardness of silicon carbide laser deposited on titanium alloy

    CSIR Research Space (South Africa)

    Adebiyia, DI

    2016-06-01

    Full Text Available Silicon carbide (SiC), has excellent mechanical properties such as high hardness and good wear resistance, and would have been a suitable laser-coating material for titanium alloy to enhance the poor surface hardness of the alloy. However, SiC has...

  11. Towards an Automatic Parameter-Tuning Framework for Cost Optimization on Video Encoding Cloud

    Directory of Open Access Journals (Sweden)

    Xiaowei Li

    2012-01-01

    Full Text Available The emergence of cloud encoding services facilitates many content owners, such as the online video vendors, to transcode their digital videos without infrastructure setup. Such service provider charges the customers only based on their resource consumption. For both the service provider and customers, lowering the resource consumption while maintaining the quality is valuable and desirable. Thus, to choose a cost-effective encoding parameter, configuration is essential and challenging due to the tradeoff between bitrate, encoding speed, and resulting quality. In this paper, we explore the feasibility of an automatic parameter-tuning framework, based on which the above objective can be achieved. We introduce a simple service model, which combines the bitrate and encoding speed into a single value: encoding cost. Then, we conduct an empirical study to examine the relationship between the encoding cost and various parameter settings. Our experiment is based on the one-pass Constant Rate Factor method in x264, which can achieve relatively stable perceptive quality, and we vary each parameter we choose to observe how the encoding cost changes. The experiment results show that the tested parameters can be independently tuned to minimize the encoding cost, which makes the automatic parameter-tuning framework feasible and promising for optimizing the cost on video encoding cloud.

  12. Optimization Of Blasting Design Parameters On Open Pit Bench A Case Study Of Nchanga Open Pits

    Directory of Open Access Journals (Sweden)

    Victor Mwango Bowa

    2015-08-01

    Full Text Available Abstract In hard rock mining blasting is the most productive excavation technique applied to fragment insitu rock to the required size for efficient loading and crushing. In order to blast the insitu rock to the desired fragment size blast design parameter such as bench height hole diameter spacing burden hole length bottom charge specific charge and rock factor are considered. The research was carried out as a practical method on Nchanga Open Pits NOP ore Bench to optimize the blasting design parameters that can yield the required fragmentation size thereby reducing the shovel loading times and maximizing efficiency of the subsequent mining unit operations such as hauling and crushing. Fragmentation characteristics such as the mean fragment size were measured by means of a digital measuring tape and predicated using the Kuznetsov equation and rock factor value of ore bench was calculated using Lilly 1986 equations by means of rock characteristics. Traditional blasting design parameters were acquired for NOP and modified using Langerfors and Sharma P.A approaches. Several blast operations were conducted using both traditional and modified blasting design parameters on the same ore bench with the same geological conditions. Loading times of the shovel and fragment sizes were obtained after the blasts from ore bench where both the traditional and modified blasting design parameters were applied. Results show that mean fragment size and loading times were reduced from 51cm and 12minutes to 22cm and 3minutes where traditional and modified blasting design parameters were applied respectively.

  13. Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

    Science.gov (United States)

    Majumder, Himadri; Maity, Kalipada

    2018-03-01

    Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

  14. Experiments for practical education in process parameter optimization for selective laser sintering to increase workpiece quality

    Science.gov (United States)

    Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas

    2016-04-01

    Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.

  15. Maximising municipal solid waste--legume trimming residue mixture degradation in composting by control parameters optimization.

    Science.gov (United States)

    Cabeza, I O; López, R; Ruiz-Montoya, M; Díaz, M J

    2013-10-15

    Composting is one of the most successful biological processes for the treatment of the residues enriched in putrescible materials. The optimization of parameters which have an influence on the stability of the products is necessary in order to maximize recycling and recovery of waste components. The influence of the composting process parameters (aeration, moisture, C/N ratio, and time) on the stability parameters (organic matter, N-losses, chemical oxygen demand, nitrate, biodegradability coefficient) of the compost was studied. The composting experiment was carried out using Municipal Solid Waste (MSW) and Legume Trimming Residues (LTR) in 200 L isolated acrylic barrels following a Box-Behnken central composite experimental design. Second-order polynomial models were found for each of the studied compost stability parameter, which accurately described the relationship between the parameters. The differences among the experimental values and those estimated by using the equations never exceeded 10% of the former. Results of the modelling showed that excluding the time, the C/N ratio is the strongest variable influencing almost all the stability parameters studied in this case, with the exception of N-losses which is strongly dependent on moisture. Moreover, an optimized ratio MSW/LTR of 1/1 (w/w), moisture content in the range of 40-55% and moderate to low aeration rate (0.05-0.175 Lair kg(-)(1) min(-1)) is recommended to maximise degradation and to obtain a stable product during co-composting of MSW and LTR. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. The 2014 Lake Askja rockslide tsunami - optimization of landslide parameters comparing numerical simulations with observed run-up

    Science.gov (United States)

    Sif Gylfadóttir, Sigríður; Kim, Jihwan; Kristinn Helgason, Jón; Brynjólfsson, Sveinn; Höskuldsson, Ármann; Jóhannesson, Tómas; Bonnevie Harbitz, Carl; Løvholt, Finn

    2016-04-01

    The Askja central volcano is located in the Northern Volcanic Zone of Iceland. Within the main caldera an inner caldera was formed in an eruption in 1875 and over the next 40 years it gradually subsided and filled up with water, forming Lake Askja. A large rockslide was released from the Southeast margin of the inner caldera into Lake Askja on 21 July 2014. The release zone was located from 150 m to 350 m above the water level and measured 800 m across. The volume of the rockslide is estimated to have been 15-30 million m3, of which 10.5 million m3 was deposited in the lake, raising the water level by almost a meter. The rockslide caused a large tsunami that traveled across the lake, and inundated the shores around the entire lake after 1-2 minutes. The vertical run-up varied typically between 10-40 m, but in some locations close to the impact area it ranged up to 70 m. Lake Askja is a popular destination visited by tens of thousands of tourists every year but as luck would have it, the event occurred near midnight when no one was in the area. Field surveys conducted in the months following the event resulted in an extensive dataset. The dataset contains e.g. maximum inundation, high-resolution digital elevation model of the entire inner caldera, as well as a high resolution bathymetry of the lake displaying the landslide deposits. Using these data, a numerical model of the Lake Askja landslide and tsunami was developed using GeoClaw, a software package for numerical analysis of geophysical flow problems. Both the shallow water version and an extension of GeoClaw that includes dispersion, was employed to simulate the wave generation, propagation, and run-up due to the rockslide plunging into the lake. The rockslide was modeled as a block that was allowed to stretch during run-out after entering the lake. An optimization approach was adopted to constrain the landslide parameters through inverse modeling by comparing the calculated inundation with the observed run

  17. A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design--part I. Model development.

    Science.gov (United States)

    He, L; Huang, G H; Lu, H W

    2010-04-15

    Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the "true" ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes. 2009 Elsevier B.V. All rights reserved.

  18. A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design-Part I. Model development

    Energy Technology Data Exchange (ETDEWEB)

    He, L., E-mail: li.he@ryerson.ca [Department of Civil Engineering, Faculty of Engineering, Architecture and Science, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3 (Canada); Huang, G.H. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); College of Urban Environmental Sciences, Peking University, Beijing 100871 (China); Lu, H.W. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada)

    2010-04-15

    Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the 'true' ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes.

  19. Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling

    Energy Technology Data Exchange (ETDEWEB)

    Hamrick, Todd [West Virginia Univ., Morgantown, WV (United States)

    2011-01-01

    Efficiency in drilling is measured by Mechanical Specific Energy (MSE). MSE is the measure of the amount of energy input required to remove a unit volume of rock, expressed in units of energy input divided by volume removed. It can be expressed mathematically in terms of controllable parameters; Weight on Bit, Torque, Rate of Penetration, and RPM. It is well documented that minimizing MSE by optimizing controllable factors results in maximum Rate of Penetration. Current methods for computing MSE make it possible to minimize MSE in the field only through a trial-and-error process. This work makes it possible to compute the optimum drilling parameters that result in minimum MSE. The parameters that have been traditionally used to compute MSE are interdependent. Mathematical relationships between the parameters were established, and the conventional MSE equation was rewritten in terms of a single parameter, Weight on Bit, establishing a form that can be minimized mathematically. Once the optimum Weight on Bit was determined, the interdependent relationship that Weight on Bit has with Torque and Penetration per Revolution was used to determine optimum values for those parameters for a given drilling situation. The improved method was validated through laboratory experimentation and analysis of published data. Two rock types were subjected to four treatments each, and drilled in a controlled laboratory environment. The method was applied in each case, and the optimum parameters for minimum MSE were computed. The method demonstrated an accurate means to determine optimum drilling parameters of Weight on Bit, Torque, and Penetration per Revolution. A unique application of micro-cracking is also presented, which demonstrates that rock failure ahead of the bit is related to axial force more than to rotation speed.

  20. Parameter optimization for Ag-coated TiO2 nanotube arrays as recyclable SERS substrates

    Science.gov (United States)

    Sun, Yuyang; Yang, Lulu; Liao, Fan; Dang, Qian; Shao, Mingwang

    2018-06-01

    The Ag-coated titanium dioxide nanotube arrays (Ag-coated TNTs) are obtained via the deposition of Ag nanoparticles on the two-step anodized TNTs. The wall thickness of TNTs is modulated via finite difference time domain simulation to get the favorable electromagnetic field for surface enhanced Raman scattering (SERS). Ag-coated TNTs with optimal wall thickness of 20 nm were employed as the SERS substrates to detect 2-mercaptobenzoxazole, which show superior detection sensitivity and uniformity. In addition, due to the photocatalysis of TNTs, the SERS substrates could clean themselves and be repeatedly used by photo-degradation of target molecules under the ultra-violet irradiation. The Ag-coated TNTs are a kind of bifunctional SERS substrates which can produce high-quality SERS signals and reuse to reduce the cost.