Mahamood, Rasheedat M.; Akinlabi, Esther T.
2016-03-01
Ti6Al4V is an important Titanium alloy that is mostly used in many applications such as: aerospace, petrochemical and medicine. The excellent corrosion resistance property, the high strength to weight ratio and the retention of properties at high temperature makes them to be favoured in most applications. The high cost of Titanium and its alloys makes their use to be prohibitive in some applications. Ti6Al4V can be cladded on a less expensive material such as steel, thereby reducing cost and providing excellent properties. Laser Metal Deposition (LMD) process, an additive manufacturing process is capable of producing complex part directly from the 3-D CAD model of the part and it also has the capability of handling multiple materials. Processing parameters play an important role in LMD process and in order to achieve desired results at a minimum cost, then the processing parameters need to be properly controlled. This paper investigates the role of processing parameters: laser power, scanning speed, powder flow rate and gas flow rate, on the material utilization efficiency in laser metal deposited Ti6Al4V. A two-level full factorial design of experiment was used in this investigation, to be able to understand the processing parameters that are most significant as well as the interactions among these processing parameters. Four process parameters were used, each with upper and lower settings which results in a combination of sixteen experiments. The laser power settings used was 1.8 and 3 kW, the scanning speed was 0.05 and 0.1 m/s, the powder flow rate was 2 and 4 g/min and the gas flow rate was 2 and 4 l/min. The experiments were designed and analyzed using Design Expert 8 software. The software was used to generate the optimized process parameters which were found to be laser power of 3.2 kW, scanning speed of 0.06 m/s, powder flow rate of 2 g/min and gas flow rate of 3 l/min.
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.
Wang, Xinchang; Shen, Xiaotian; Sun, Fanghong; Shen, Bin
2016-12-01
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 V80 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 parameters and some typical contrastive parameters are also accomplished for further verifying the rationality of the computational model and the correctness of the compensation coefficient 0.7 defined for the downward translation determined by simulations. More importantly, on the basis of more simulations and verification tests, a general filament arrangement model suitable for V50-120 mm
Optimization of exchange bias in Co/CoO magnetic nanocaps by tuning deposition parameters
Sharma, A.; Tripathi, J.; Ugochukwu, K. C.; Tripathi, S.
2017-03-01
In the present work, we report exchange bias tuning by varying thin film deposition parameters such as synthesis method and underlying layer patterning. The patterned substrates for this study were prepared by self-assembly of polystyrene (PS) latex spheres ( 530 nm) on Si (100) substrate. The desired magnetic nanocaps composed of CoO/Co bilayer film on these patterned substrates were prepared by molecular beam epitaxy technique under ultra-high vacuum conditions. For this, a Co layer of 10 nm thickness was deposited on the substrates and then oxidized in-situ to form CoO/Co/PS in-situ oxidized film or ex-situ in ambiance which also gives CoO/Co/PS naturally oxidized film. Simultaneously, reference thin films of Co ( 10 nm) were also prepared on plane Si substrate and similar oxidation treatments were performed on them respectively. The magnetic properties studied using SQUID technique revealed higher exchange bias ( 1736 Oe) in the in-situ oxidized Co/PS film as compared to that in naturally oxidized Co/PS film ( 1544 Oe) and also compared to the reference film. The observed variations in the magnetic properties are explained in terms of surface patterning induced structural changes of the deposited films and different oxidation methods.
Indian Academy of Sciences (India)
Dipika Barbadikar; Rashmi Gautam; Sanjay Sahare; Rajendra Patrikar; Jatin Bhatt
2013-06-01
Si quantum dots-based structures are studied recently for performance enhancement in electronic devices. This paper presents an attempt to get high density quantum dots (QDs) by low pressure chemical vapour deposition (LPCVD) on SiO2 substrate. Surface treatment, annealing and rapid thermal processing (RTP) are performed to study their effect on size and density of QDs. The samples are also studied using Fourier transformation infrared spectroscopy (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM) and photoluminescence study (PL). The influence of Si–OH bonds formed due to surface treatment on the density of QDs is discussed. Present study also discusses the influence of surface treatment and annealing on QD formation.
Dasgupta, K; Sen, D; Mazumder, S; Basak, C B; Joshi, J B; Banerjee, S
2010-06-01
The process parameters (viz. temperature of synthesis, type of catalyst, concentration of catalyst and type of catalyst-support material) for controlling purity of carbon nanotubes synthesized by catalytic chemical vapour deposition of acetylene have been optimized by analyzing the experimental results using Taguchi method. It has been observed that the catalyst-support material has the maximum (59.4%) and the temperature of synthesis has the minimum effect (2.1%) on purity of the nanotubes. At optimum condition (15% ferrocene supported on carbon black at the synthesis temperature of 700 degrees C) the purity of nanotubes was found out to be 96.2% with yield of 1900%. Thermogravimetry has been used to assess purity of nanotubes. These nantubes have been further characterized by scanning electron microscopy, transmission electron microscopy and Raman Spectroscopy. Small angle neutron scattering has been used to find out their average inner and outer diameter using an appropriate model. The nanotubes are well crystallized but with wide range of diameter varying between 20-150 nm.
Infrared Drying Parameter Optimization
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
Optimized the Parameters in Process of PECVD Deposition Silicon Nitride Film%PECVD氮化硅薄膜工艺参数研究
Institute of Scientific and Technical Information of China (English)
张树明; 廖华; 何京鸿; 尹云坤; 胡俊涛; 罗群
2011-01-01
According to the structure of solar modules and the performance of encapsulating material, the best antireflection film thickness and refractive index have been designed for silicon solar cell, and the technical parameters have been optimized with TAYLOR formula. Through the experiments, the good deposition parameters have been obtained for CETC-48th tube PECVD equipment.%根据太阳电池组件的结构和封装材料特性,设计出硅太阳电池片减反射薄膜的最佳厚度和折射率,利用泰勒公式进行优化PECVD制备氮化硅薄膜的工艺参数.通过实验,找出适合中电48所工业生产用管式PECVD制备氮化硅薄膜的工艺参数.
Institute of Scientific and Technical Information of China (English)
王颖; 康敏; 陈超; 杨勇; 傅秀清
2013-01-01
The cylinder is an extremely important easily wearing part of a tractor engine, whose service life and production cost are directly affected by the wear resistance of the component. With excellent wear resistance, corrosion resistance, and greater hardness, a Ni-P alloy deposited layer can significantly enhance the service life and reliability of the cylinder, and the capability and quality of the tractor engine can be improved. The lower limiting current density of the traditional electrodeposited Ni-P alloy method leads to a lower depositing rate and lower production efficiency. Jet electrodeposition has been developed in recent years, which can significant increase the depositing rate because the jet electrolyte can accelerate the transfer process of the electrodeposition material and augment limiting current density. So jet electrodeposition is a type of high-velocity, selective electrodeposition technique with high deposition current density and high velocity. Furthermore, optimization of the process parameters of jet electrodeposition is the way to further increase the depositing rate. In this paper, technological experimentation is investigated by using a custom design of JMP to optimize process parameters of jet electrodeposition. The JMP software is Six Sigma statistical software developed by SAS, which is a professional statistical analysis tool. The JMP software can be used for processing data and designing of experiments. To the best of our knowledge, there is currently no report about applications of JMP in electrochemical use domestically. Voltage, electrolyte temperature, dipolar space, flow velocity of electrolyte, and dipolar relative velocity are the influence factors, and the depositing rate of deposited layers is the experimental index, and the relationships between the experimental index and the influence factors are analyzed through the response surface analysis method and sub-stepping method. The quadratic regression mathematical models that
Optimization of submerged vane parameters
Indian Academy of Sciences (India)
H SHARMA; B JAIN; Z AHMAD
2016-03-01
Submerged vanes are airfoils which are in general placed at certain angle with respect to the flow direction in a channel to induce artificial circulations downstream. By virtue of these artificially generated circulations, submerged vanes were utilized to protect banks of rivers against erosion, to control shifting of rivers, to avoid blocking of lateral intake with sediment deposition, etc. Odgaard and his associates have experimentally obtained the optimum vane sizes and recommended that it can be used for vane design. Thispaper is an attempt to review and validate the findings of Odgaard and his associates by utilizing computational fluid dynamics and experiments as a tool in which the vane generated vorticity in the downstream was maximized in order to obtain optimum vane parameters for single and multiple vane arrays.
Energy Technology Data Exchange (ETDEWEB)
Pflueger, A.; Mukherjee, C.; Schroeder, B. [Department of Physics, Center of Materials Science, University of Kaiserslautern, P.O. Box 3049, D-67653 Kaiserslautern (Germany)
2002-07-01
Scale-up of a-Si:H-based thin film applications such as solar cells, entirely or partly prepared by hot-wire chemical vapor deposition (HWCVD), requires research on the deposition process in a large-area HWCVD system. The influence of gas supply and filament geometry on thickness uniformity has already been reported, but their influence on material quality is systematically studied for the first time. The optimization of deposition parameters for obtaining best material quality in our large-area HWCVD system resulted in an optimum filament temperature, T{sub fil}{approx}1600C, pressure, p=8mTorr and silane flow, F(SiH{sub 4})=100sccm, keeping the substrate temperature at T{sub S}=200C. A special gas supply (gas shower with tiny holes of uniform size) and a filament grid, consisting of six filaments with an interfilament distance, d{sub fil}=4cm were used. The optimum filament-to-substrate distance was found to be d{sub fil-S}=8.4cm. While studying the influence of different d{sub fil} and gas supply configurations on the material quality, the above-mentioned setup and parameters yield best results for both uniformity and material quality. With the setup mentioned, we could achieve device quality a-Si:H films with a thickness uniformity of {+-}2.5% on a circular area of 20cm in diameter. The material, grown at a deposition rate of r{sub d}{approx}4A/s, was characterized on nine positions of the 30cmx30cm substrate area, and revealed reasonable uniformity of the opto-electronic properties, e.g photosensitivity, {sigma}{sub Ph}/{sigma}{sub D}=(2.46{+-}0.7)x10{sup 5}, microstructure factor, R=0.17{+-}0.05, defect densities, N{sub d(PDS)}=(2.06{+-}0.6)x10{sup 17}cm{sup -3} and N{sub d(CPM)}=(2.05{+-}0.5)x10{sup 16}cm{sup -3} (film properties are given as mean values and standard deviations). Finally, we fabricated pin solar cells, with the i-layer deposited on small-area p-substrates distributed over an area of 20cmx20cm in this large-area deposition system, and
Optimization of Parameters of Asymptotically Stable Systems
Directory of Open Access Journals (Sweden)
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.
Novel system for modulated lidar parameter optimization
Institute of Scientific and Technical Information of China (English)
Bo Zhou; Yong Ma; Kun Liang; Zhiqiang Tu; Hongyuan Wang
2011-01-01
We present a novel system for parameter design and optimization of modulated lidar. The system is realized by combining software simulation with hardware circuit. This method is more reliable and flexible for lidar parameter optimization compared with theoretical computation or fiber-simulated system. Experiments confirm that the system is capable of optimizing parameters for modulated lidar. Key parameters are analyzed as well. The optimal filter bandwidth is 200 MHz and the optimal modulation depth is 0.5 under typical application environment.%@@ We present a novel system for parameter design and optimization of modulated lidar.The system is realized by combining software simulation with hardware circuit.This method is more reliable and flexible for lidar parameter optimization compared with theoretical computation or fiber-simulated system.Experiments confirm that the system is capable of optimizing parameters for modulated lidar.Key parameters are analyzed as well.The optimal filter bandwidth is 200 MHz and the optimal modulation depth is 0.5 under typical application environment.
Evaluation of GCC optimization parameters
Directory of Open Access Journals (Sweden)
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.
Parameters Optimization of Synergetic Recognition Approach
Institute of Scientific and Technical Information of China (English)
GAOJun; DONGHuoming; SHAOJing; ZHAOJing
2005-01-01
Synergetic pattern recognition is a novel and effective pattern recognition method, and has some advantages in image recognition. Researches have shown that attention parameters λ and parameters B， C directly influence on the recognition results, but there is no general research theory to control these parameters in the recognition process. We abstractly analyze these parameters in this paper, and purpose a novel parameters optimization method based on simulated annealing algorithm. SA algorithm has good optimization performance and is used to search the global optimized solution of these parameters. Theoretic analysis and experimental results both show that the proposed parameters optimization method is effective, which can fully improve the performance of synergetic recognition approach, and the algorithm realization is simple and fast.
QUADRATIC OPTIMIZATION METHOD AND ITS APPLICATION ON OPTIMIZING MECHANISM PARAMETER
Institute of Scientific and Technical Information of China (English)
ZHAO Yun; CHEN Jianneng; YU Yaxin; YU Gaohong; ZHU Jianping
2006-01-01
In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal dynamic behavior and the constraint equations are from the results of the kinematic optimization. This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.
Optimal Parameters Multicomponent Mixtures Extruding
Directory of Open Access Journals (Sweden)
Ramil F. Sagitov
2013-01-01
Full Text Available Experimental research of multicomponent mixtures extruding from production wastes are carried out, unit for production of composites from different types of waste is presented. Having analyzed dependence of multicomponent mixtures extruding energy requirements on die length and components content at three values of angular rate of screw rotation, we received the values of energy requirements at optimal length of the die, angular speed and percent of binding additives.
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...
Weigh in Motion Based on Parameters Optimization
Institute of Scientific and Technical Information of China (English)
ZHOU Zhi-feng; CAI Ping; CHEN Ri-xing
2009-01-01
Dynamic tire forces are the main factor affecting the measurement accuracy of the axle weight of moving vehicle. This paper presents a novel method to reduce the influence of the dynamic tire forces on the weighing accuracy. On the basis of analyzing the characteristic of the dynamic tire forces, the objective optimization equation is constructed. The optimization algorithm is presented to get the optimal estimations of the objective parameters. According to the estimations of the parameters, the dynamic tire forces are separated from the axle weigh signal. The results of simulation and field experiments prove the effectiveness of the proposed method.
Optimal choice of parameters for particle swarm optimization
Institute of Scientific and Technical Information of China (English)
ZHANG Li-ping; YU Huan-jun; HU Shang-xu
2005-01-01
The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically investigated based on some benchmark functions. The constriction factor, velocity constraint, and population size all have significant impact on the performance of CFM for PSO. The constriction factor and velocity constraint have optimal values in practical application, and improper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. The characteristics of CFM parameters are described and guidelines for determining parameter values are given in this paper.
Optimal design criteria - prediction vs. parameter estimation
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.
Cosmological parameter estimation using Particle Swarm Optimization
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.
Optimal parameters uncoupling vibration modes of oscillators
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.
Mixed integer evolution strategies for parameter optimization.
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.
An Optimization Model of Tunnel Support Parameters
Directory of Open Access Journals (Sweden)
Su Lijuan
2015-05-01
Full Text Available An optimization model was developed to obtain the ideal values of the primary support parameters of tunnels, which are wide-ranging in high-speed railway design codes when the surrounding rocks are at the III, IV, and V levels. First, several sets of experiments were designed and simulated using the FLAC3D software under an orthogonal experimental design. Six factors, namely, level of surrounding rock, buried depth of tunnel, lateral pressure coefficient, anchor spacing, anchor length, and shotcrete thickness, were considered. Second, a regression equation was generated by conducting a multiple linear regression analysis following the analysis of the simulation results. Finally, the optimization model of support parameters was obtained by solving the regression equation using the least squares method. In practical projects, the optimized values of support parameters could be obtained by integrating known parameters into the proposed model. In this work, the proposed model was verified on the basis of the Liuyang River Tunnel Project. Results show that the optimization model significantly reduces related costs. The proposed model can also be used as a reliable reference for other high-speed railway tunnels.
Institute of Scientific and Technical Information of China (English)
Aiying WANG; Kwangryeol Lee; Chao SUN; Lishi WEN
2006-01-01
During the growth of the hot filament chemical vapor deposition(HFCVD)diamond films, numerical simulations in a 2-D mathematical model were employed to investigate the influence of various deposition parameters on the gas physical parameters, including the temperature, velocity and volume density of gas. It was found that, even in the case of optimized deposition parameters, the space distributions of gas parameters were heterogeneous due primarily to the thermal blockage come from the hot filaments and cryogenic pump effect arisen from the cold reactor wall. The distribution of volume density agreed well with the thermal round-flow phenomenon, one of the key obstacles to obtaining high growth rate in HFCVD process. In virtue of isothermal boundary with high temperature or adiabatic boundary condition of reactor wall, however, the thermal roundflow was profoundly reduced and as a consequence, the uniformity of gas physical parameters was considerably improved, as identified by the experimental films growth.
Parameter optimization in S-system models
Directory of Open Access Journals (Sweden)
Vasconcelos Ana
2008-04-01
Full Text Available Abstract Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well.
Optimization of audio - ultrasonic plasma system parameters
Haleem, N. A.; Abdelrahman, M. M.; Ragheb, M. S.
2016-10-01
The present plasma is a special glow plasma type generated by an audio ultrasonic discharge voltage. A definite discharge frequency using a gas at a narrow band pressure creates and stabilizes this plasma type. The plasma cell is a self-extracted ion beam; it is featured with its high output intensity and its small size. The influence of the plasma column length on the output beam due to the variation of both the audio discharge frequency and the power applied to the plasma electrodes is investigated. In consequence, the aim of the present work is to put in evidence the parameters that influence the self-extracted collected ion beam and to optimize the conditions that enhance the collected ion beam. The experimental parameters studied are the nitrogen gas, the applied frequency from 10 to 100 kHz, the plasma length that varies from 8 to 14 cm, at a gas pressure of ≈ 0.25 Torr and finally the discharge power from 50 to 500 Watt. A sheet of polyethylene of 5 micrometer covers the collector electrode in order to confirm how much ions from the beam can go through the polymer and reach the collector. To diagnose the occurring events of the beam on the collector, the polymer used is analyzed by means of the FTIR and the XRF techniques. Optimization of the plasma cell parameters succeeded to enhance and to identify the parameters that influence the output ion beam and proved that its particles attaining the collector are multi-energetic.
Optimal construction parameters of electrosprayed trilayer organic photovoltaic devices
Shah, S. K.; Abbas, M.; Ali, M.; Hirsch, L.; Gunnella, R.
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.
Taguchi Method Applied in Optimization of Shipley SJR 5740 Positive Resist Deposition
Hui, A.; Blosiu, J. O.; Wiberg, D. V.
1998-01-01
Taguchi Methods of Robust Design presents a way to optimize output process performance through an organized set of experiments by using orthogonal arrays. Analysis of variance and signal-to-noise ratio is used to evaluate the contribution of each of the process controllable parameters in the realization of the process optimization. In the photoresist deposition process, there are numerous controllable parameters that can affect the surface quality and thickness of the final photoresist layer.
Improving hardness of electroless Ni-B coatings using optimized deposition conditions and annealing
Energy Technology Data Exchange (ETDEWEB)
Oraon, B. [Department of Mechanical Engineering, Jadavpur University, Kolkata 700 032 (India)], E-mail: b_oraon_65@yahoo.co.in; Majumdar, G. [Department of Mechanical Engineering, Jadavpur University, Kolkata 700 032 (India); Ghosh, B. [Advanced Materials and Solar Photovoltaic Division, School of Energy Studies, Jadavpur University, Kolkata 700 032 (India)
2008-07-01
The alkaline borohydride-reduced bath has been used to deposit electroless nickel-boron (Ni-B) coatings on a pure (99.99%) copper substrate. The hardness of the Ni-B coatings has been improved using optimized deposition conditions and thereafter by annealing. The electroless Ni-B deposition per unit area has been considered as the response variable and response surface method (RSM) has been used to optimize the process parameters and the deposition per unit area. The electroless Ni-B coatings have again been formed at the optimized deposition conditions and the as-deposited coating hardness has been evaluated using an empirical model and regression analysis. It has been observed that there is a significant improvement in as-deposited coating hardness. The Ni-B coated specimens formed at optimized deposition conditions have also been annealed at different temperatures ranging from 100 deg. C to 500 deg. C. The hardness of the annealed specimens has been estimated for different annealing temperatures and has been observed that the coating hardness increases with annealing temperature and then further increase in annealing temperature reduces the coating hardness. The coating hardness becomes the highest for annealing temperature of about 300 deg. C. Both the as-deposited and annealed coating hardness have been observed to be significantly higher than that reported by many researchers for electroless Ni-B coatings.
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.
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.
Parameter optimization model in electrical discharge machining process
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper,artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.
Directory of Open Access Journals (Sweden)
R. Venkata Rao
2016-03-01
Full Text Available The performance of rapid prototyping (RP processes is often measured in terms of build time, product quality, dimensional accuracy, cost of production, mechanical and tribological properties of the models and energy consumed in the process. The success of any RP process in terms of these performance measures entails selection of the optimum combination of the influential process parameters. Thus, in this work the single-objective and multi-objective optimization problems of a widely used RP process, namely, fused deposition modeling (FDM, are formulated, and the same are solved using the teaching-learning-based optimization (TLBO algorithm and non-dominated Sorting TLBO (NSTLBO algorithm, respectively. The results of the TLBO algorithm are compared with those obtained using genetic algorithm (GA, and quantum behaved particle swarm optimization (QPSO algorithm. The TLBO algorithm showed better performance as compared to GA and QPSO algorithms. The NSTLBO algorithm proposed to solve the multi-objective optimization problems of the FDM process in this work is a posteriori version of the TLBO algorithm. The NSTLBO algorithm is incorporated with non-dominated sorting concept and crowding distance assignment mechanism to obtain a dense set of Pareto optimal solutions in a single simulation run. The results of the NSTLBO algorithm are compared with those obtained using non-dominated sorting genetic algorithm (NSGA-II and the desirability function approach. The Pareto-optimal set of solutions for each problem is obtained and reported. These Pareto-optimal set of solutions will help the decision maker in volatile scenarios and are useful for the FDM process.
Optimization of Ta2O5 optical thin film deposited by radio frequency magnetron sputtering.
Shakoury, R; Willey, Ronald R
2016-07-10
Radio frequency magnetron sputtering has been used here to find the parameters at which to deposit Ta2O5 optical thin films with negligible absorption in the visible spectrum. The design of experiment methodology was employed to minimize the number of experiments needed to find the optimal results. Two independent approaches were used to determine the index of refraction n and k values.
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.
Surface parameters modification by multilayer coatings deposition for biomedical applications
Energy Technology Data Exchange (ETDEWEB)
Zykova, A [Institute of Surface Engineering, 4 Zalutinskaya Str., Kharkov (Ukraine); Safonov, V [National Science Center, Kharkov Institute of Physics and Technology, 1 Akademicheskaja Str., 61108 Kharkov (Ukraine); Virva, O; Luk' yanchenko, V [Institute of Spine and Joint Pathologies, 80 Pushkinskaya Str., 61024 Kharkov (Ukraine); Walkowich, J; Rogowska, R [Institute for Sustainable Technologies, National Research Institute, 6/10 K. Pulaskiego Str., Radom (Poland); Yakovin, S [Department of Physical Technologies, Kharkov National University, 31 Kurchatov Ave., Kharkov (Ukraine)], E-mail: zykov@bi.com.ua
2008-05-01
Studies are presented of the surface parameters of various multilayer coatings, namely, TiN, CrN, (Ti, Cr)N, TiN/TiC{sub 10}N{sub 90}, TiN/TiC{sub 20}N{sub 80} deposited by means of Arc-PVD on stainless steel (1H18N9), as well as of the same coatings with an additional Al{sub 2}O{sub 3} film deposited by reactive magnetron sputtering (RMS). The surface thickness, roughness and topography are estimated. Other parameters, such as the surface free energy (SFE) and fractional polarity are determined by means of the Wu and the Owens-Wendt-Rabel-Kaelble methods. Experiments are carried out on the in vitro cell/material interaction (in a fibroblasts culture) in order to determine the materials biomedical response. The results show some correlation between the surface properties and cell adhesion. The best biological response parameters (cell number, proliferation function, morphology) are obtained in the case of coatings with the highest values of the polar part component of the SFE and the fractional polarity, such as TiN, TiN/TiC{sub 10}N{sub 90} and oxide coatings.
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.
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.
Optimal parameters uncoupling vibration modes of oscillators
Le, Khanh Chau
2016-01-01
A novel optimization concept for an oscillator with two degrees of freedom is proposed. By using specially defined motion ratios, we control the action of springs and dampers to each degree of freedom of the oscillator. If the potential action of the springs in one period of vibration, used as the payoff function for the conservative oscillator, is maximized, then the optimal motion ratios uncouple vibration modes. The same result holds true for the dissipative oscillator. The application to optimal design of vehicle suspension is discussed.
A New Approach for Parameter Optimization in Land Surface Model
Institute of Scientific and Technical Information of China (English)
LI Hongqi; GUO Weidong; SUN Guodong; ZHANG Yaocun; FU Congbin
2011-01-01
In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyn station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple- and six-parameter optinizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.
Optimization parameters system maintenance transport aircraft
Directory of Open Access Journals (Sweden)
І.І. Ліннік
2006-01-01
Full Text Available The algorithm of unconditional and conditional optimization Markov models of maintenance systems of transport airplanes of their programs of technical operation used at improvement is considered.
Parameter Optimization Based on GA and HFSS
Institute of Scientific and Technical Information of China (English)
SUN Shu-hui; WANG Bing-zhong
2005-01-01
A new project based on genetic algorithm (GA) and high frequency simulation software (HFSS) is proposed to optimize microwave passive devices effectively. This project is realized with a general program named as optimization program. The program is compiled by Matlab and the macro language of HFSS which is a fast and effective way to accomplish tasks. In the paper, two examples are used to show the project's feasibility.
Optimal control of nonsmooth distributed parameter systems
Tiba, Dan
1990-01-01
The book is devoted to the study of distributed control problems governed by various nonsmooth state systems. The main questions investigated include: existence of optimal pairs, first order optimality conditions, state-constrained systems, approximation and discretization, bang-bang and regularity properties for optimal control. In order to give the reader a better overview of the domain, several sections deal with topics that do not enter directly into the announced subject: boundary control, delay differential equations. In a subject still actively developing, the methods can be more important than the results and these include: adapted penalization techniques, the singular control systems approach, the variational inequality method, the Ekeland variational principle. Some prerequisites relating to convex analysis, nonlinear operators and partial differential equations are collected in the first chapter or are supplied appropriately in the text. The monograph is intended for graduate students and for resea...
Simultaneous optimal experimental design for in vitro binding parameter estimation.
Ernest, C Steven; Karlsson, Mats O; Hooker, Andrew C
2013-10-01
Simultaneous optimization of in vitro ligand binding studies using an optimal design software package that can incorporate multiple design variables through non-linear mixed effect models and provide a general optimized design regardless of the binding site capacity and relative binding rates for a two binding system. Experimental design optimization was employed with D- and ED-optimality using PopED 2.8 including commonly encountered factors during experimentation (residual error, between experiment variability and non-specific binding) for in vitro ligand binding experiments: association, dissociation, equilibrium and non-specific binding experiments. Moreover, a method for optimizing several design parameters (ligand concentrations, measurement times and total number of samples) was examined. With changes in relative binding site density and relative binding rates, different measurement times and ligand concentrations were needed to provide precise estimation of binding parameters. However, using optimized design variables, significant reductions in number of samples provided as good or better precision of the parameter estimates compared to the original extensive sampling design. Employing ED-optimality led to a general experimental design regardless of the relative binding site density and relative binding rates. Precision of the parameter estimates were as good as the extensive sampling design for most parameters and better for the poorly estimated parameters. Optimized designs for in vitro ligand binding studies provided robust parameter estimation while allowing more efficient and cost effective experimentation by reducing the measurement times and separate ligand concentrations required and in some cases, the total number of samples.
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.
Machine Self-Teaching Methods for Parameter Optimization.
1986-12-01
A199 285 MACHINE SELF- TEACHING METHODS FOR PARAMETER / OPTIMIZATION(U) NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA R A DILLARD DEC 86 NOSC/TR-1S39...Technical Document 1039 C) ,December 1986 Machine Self- Teaching Methods for Parameter Optimization Robin A. Dillard DTICS ELECTE MAY i01 STAra Approved...ELEMEWt NO PROECi’ No TASK NO ARC Locally FundedI I1 I TE (ewd* Seawmy Cft*Wi., Machine Self- Teaching Methods for Parameter Optimization it PERSONAL
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.
Temporal Parameter Optimization in Four-Dimensional Flash Trajectory Imaging
Institute of Scientific and Technical Information of China (English)
WANG Xin-Wei; ZHOU Yan; FAN Song-Tao; LIU Yu-Liang
2011-01-01
In four-dimensional fiash trajectory imaging, temporal parameters include time delay, laser pulse width, gate time, pulse pair repetition frequency and the frame rate of CCD, which directly impact on the acquisition of target trajectories over time. We propose a method of optimizing the temporal parameters of flash trajectory imaging. All the temporal parameters can be estimated by the spatial parameters of the volumes of interest, target scale and velocity, and target sample number. The formulae for optimizing temporal parameters are derived, and the method is demonstrated in an experiment with a ball oscillating as a pendulum.%In four-dimensional flash trajectory imaging,temporal parameters include time delay,laser pulse width,gate time,pulse pair repetition frequency and the frame rate of CCD,which directly impact on the acquisition of target trajectories over time.We propose a method of optimizing the temporal parameters of flash trajectory imaging.All the temporal parameters can be estimated by the spatial parameters of the volumes of interest,target scale and velocity,and target sample number.The formulae for optimizing temporal parameters are derived,and the method is demonstrated in an experiment with a ball oscillating as a pendulum.Four-dimensional flash trajectory imaging (FTI)based on time-delay-modulated range-gated viewing can directly image the trajectories of moving objects with backgrounds filtered and deduce target 3D positions over time,[1] which has potentials in astronomy,remote sensing and biomedical applications.[2 4] Temporal parameters are crucial for FTI.An unreasonable setting of temporal parameters will lead to failure in obtaining target trajectories.However,in the previous work,[1] the optimization of temporal parameters has not been discussed in detail.Therefore,in this Letter we give a method of estimating the temporal parameters of FTI.
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.
Structural Parameter Optimization of Multilayer Conductors in HTS Cable
Institute of Scientific and Technical Information of China (English)
Yan Mao; Jie Qiu; Xin-Ying Liu; Zhi-Xuan Wang; Shu-Hong Wang; Jian-Guo Zhu; You-Guang Guo; Zhi-Wei Lin; Jian-Xun Jin
2008-01-01
In this paper, the design optimization of the structural parameters of multilayer conductors in high temperature superconducting (HTS) cable is reviewed. Various optimization methods, such as the particle swarm optimization (PSO), the genetic algorithm (GA), and a robust optimization method based on design for six sigma (DFSS), have been applied to realize uniform current distribution among the multi- layer HTS conductors. The continuous and discrete variables, such as the winding angle, radius, and winding direction of each layer, are chosen as the design parameters. Under the constraints of the mechanical properties and critical current, PSO is proven to be a more powerful tool than GA for structural parameter optimization, and DFSS can not only achieve a uniform current distribution, but also improve significantly the reliability and robustness of the HTS cable quality.
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.
Optimizing parameters for magnetorheological finishing supersmooth surface
Cheng, Haobo; Feng, Zhijing; Wang, Yingwei
2005-02-01
This paper presents a reasonable approach to this issue, i.e., computer controlled magnetorheological finishing (MRF). In MRF, magnetically stiffened magnetorheological (MR) abrasive fluid flows through a preset converging gap that is formed by a workpiece surface and a moving rigid wall, to create precise material removal and polishing. Tsinghua University recently completed a project with MRF technology, in which a 66 mm diameter, f/5 parabolic mirror was polished to the shape accuracy of λ/17 RMS (λ=632.8nm) and the surface roughness of 1.22 nm Ra. This was done on a home made novel aspheric computer controlled manufacturing system. It is a three-axis, self-rotating wheel machine, the polishing tool is driven with one motor through a belt. This paper presents the manufacturing and testing processes, including establish the mathematics model of MRF optics on the basis of Preston equation, profiler test and relative coefficients, i.e., pressure between workpiece and tool, velocity of MR fluid in polishing spot, tolerance control of geometrical parameters such as radius of curvature and conic constant also been analyzed in the paper. Experiments were carried out on the features of MRF. The results indicated that the required convergent speed, surface roughness could be achieved with high efficiency.
OPTIMIZATION OF PARAMETERS OF ELEMENTS COMPUTER SYSTEM
Directory of Open Access Journals (Sweden)
Nesterov G. D.
2016-03-01
Full Text Available The work is devoted to the topical issue of increasing the productivity of computers. It has an experimental character. Therefore, the description of a number of the carried-out tests and the analysis of their results is offered. Previously basic characteristics of modules of the computer for the regular mode of functioning are provided in the article. Further the technique of regulating their parameters in the course of experiment is described. Thus the special attention is paid to observing the necessary thermal mode in order to avoid an undesirable overheat of the central processor. Also, operability of system in the conditions of the increased energy consumption is checked. The most responsible moment thus is regulating the central processor. As a result of the test its optimum tension, frequency and delays of data reading from memory are found. The analysis of stability of characteristics of the RAM, in particular, a condition of its tires in the course of experiment is made. As the executed tests took place within the standard range of characteristics of modules, and, therefore, the margin of safety put in the computer and capacity of system wasn't used, further experiments were made at extreme dispersal in the conditions of air cooling. The received results are also given in the offered article
Optimization of underwater wet welding process parameters using neural network
National Research Council Canada - National Science Library
Omajene, Joshua Emuejevoke; Martikainen, Jukka; Wu, Huapeng; Kah, Paul
2014-01-01
.... The soundness of a weld can be predicted from the weld bead geometry.This paper illustrates the application of artificial neural network approach in the optimization of the welding process parameter and the influence of the water environment...
CADLIVE optimizer: web-based parameter estimation for dynamic models
Directory of Open Access Journals (Sweden)
Inoue Kentaro
2012-08-01
Full Text Available Abstract Computer simulation has been an important technique to capture the dynamics of biochemical networks. In most networks, however, few kinetic parameters have been measured in vivo because of experimental complexity. We develop a kinetic parameter estimation system, named the CADLIVE Optimizer, which comprises genetic algorithms-based solvers with a graphical user interface. This optimizer is integrated into the CADLIVE Dynamic Simulator to attain efficient simulation for dynamic models.
Optimization of Nanostructuring Burnishing Technological Parameters by Taguchi Method
Kuznetsov, V. P.; Dmitriev, A. I.; Anisimova, G. S.; Semenova, Yu V.
2016-04-01
On the basis of application of Taguchi optimization method, an approach for researching influence of nanostructuring burnishing technological parameters, considering the surface layer microhardness criterion, is developed. Optimal values of burnishing force, feed and number of tool passes for hardened steel AISI 420 hardening treatment are defined.
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.
Optimization of Cold Spray Deposition of High-Density Polyethylene Powders
Bush, Trenton B.; Khalkhali, Zahra; Champagne, Victor; Schmidt, David P.; Rothstein, Jonathan P.
2017-09-01
When a solid, ductile particle impacts a substrate at sufficient velocity, the resulting heat, pressure and plastic deformation can produce bonding between the particle and the substrate. The use of a cool supersonic gas flow to accelerate these solid particles is known as cold spray deposition. The cold spray process has been commercialized for some metallic materials, but further research is required to unlock the exciting potential material properties possible with polymeric particles. In this work, a combined computational and experimental study was employed to study the cold spray deposition of high-density polyethylene powders over a wide range of particle temperatures and impact velocities. Cold spray deposition of polyethylene powders was demonstrated across a range broad range of substrate materials including several different polymer substrates with different moduli, glass and aluminum. A material-dependent window of successful deposition was determined for each substrate as a function of particle temperature and impact velocity. Additionally, a study of deposition efficiency revealed the optimal process parameters for high-density polyethylene powder deposition which yielded a deposition efficiency close to 10% and provided insights into the physical mechanics responsible for bonding while highlighting paths toward future process improvements.
Nayar, Priyanka; Zhu, Xue-Yi; Yang, Fuyi; Lu, Minghui; Lakshminarayana, G.; Liu, Xiao Ping; Chen, Yan-Feng; Kityk, I. V.
2016-10-01
Erbium doped amorphous alumina thin films were fabricated using Co-sputtering technique in various depositions runs with varying parameters for optimizing the deposition parameters to obtain the films with best optical performance. The main subject of investigation includes the effects of change in various deposition parameters such as substrate heating, radio frequency (RF) power and oxygen pressure inside the chamber while deposition. High quality as-deposited films with various Er concentrations and low carbon content have been confirmed by XPS. Substrate heating ∼500 °C was found to be very effective in getting highly dense films with high refractive index of 1.70 at 1530-1570 nm emission band. The Er3+-doped films showed very intense near-infrared luminescence peak at 1550 nm even without any post-deposition annealing treatment.
Expected optimal feedback with Time-Varying Parameters
Tucci, M.P.; Kendrick, D.A.; Amman, H.M.
2011-01-01
In this paper we derive the closed loop form of the Expected Optimal Feedback rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (1981,2002, Chapter 6) where parameters are assumed to vary randomly around a known
Automated Optimization of Walking Parameters for the Nao Humanoid Robot
Girardi, N.; Kooijman, C.; Wiggers, A.J.; Visser, A.
2013-01-01
This paper describes a framework for optimizing walking parameters for a Nao humanoid robot. In this case an omnidirectional walk is learned. The parameters are learned in simulation with an evolutionary approach. The best performance was obtained for a combination of a low mutation rate and a high
Genetic Algorithm Optimizes Q-LAW Control Parameters
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.
Application of Improved Genetic Algorithm in PID Controller Parameters Optimization
Directory of Open Access Journals (Sweden)
Ying Chen
2013-01-01
Full Text Available Ying Chen, Yong-jie Ma, Wen-xia Yun College of Physics and Electronic Engineering, Northwest Normal University, Anning Road no.967 ,Lanzhou,China,0931-7971503 e-mail:chenying1386685@126.com Abstract The setting and optimization of Proportion Integration Differentiation(PID parameters have been always the important study topics in the automatic control field. The current optimization design methods are often difficult to consider the system requirements for quickness ,reliability and robustness .So a method of PID controller parameters optimization based on Improved Genetic Algorithm(IGA is presented .Simulations with Matlab have proved that the control performance index based on IGA is better than that of the GA method and Z-N method, and is a method which has good practical value of the PID parameter setting and optimization .
A FUZZY CLOPE ALGORITHM AND ITS OPTIMAL PARAMETER CHOICE
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Among the available clustering algorithms in data mining, the CLOPE algorithm attracts much more attention with its high speed and good performance. However, the proper choice of some parameters in the CLOPE algorithm directly affects the validity of the clustering results, which is still an open issue. For this purpose, this paper proposes a fuzzy CLOPE algorithm, and presents a method for the optimal parameter choice by defining a modified partition fuzzy degree as a clustering validity function. The experimental results with real data set illustrate the effectiveness of the proposed fuzzy CLOPE algorithm and optimal parameter choice method based on the modified partition fuzzy degree.
The Horizontal Well Drilling Parameter Optimization Design Research
Directory of Open Access Journals (Sweden)
Wang Yan
2013-07-01
Full Text Available Extended-reach drilling technology has rapidly developed during the past three decades. It requires improved new models and technology. This study has created a rapid optimum method to design the horizontal well drilling parameters. Genetic Algorithm is applied in this method to optimize the parameters such WOB, RPM. According to practical situation, the suitable fitness function and value of operators of GA are given and reasonable convergence delay-independent conditions are set. Based on the intelligence and global quick search of GA and the convergence of GA, the design parameters can be globally optimized quickly and accurately. An example is taken to prove that the application of GA in the field of drilling parameters is successful. This optimization method based on GA can provide guide for field design.
Waddell, Ewan; Gibson, Des; Lin, Li; Fu, Xiuhua
2011-09-01
This paper describes a method for modelling film thickness variation across the deposition area within plasma enhanced chemical vapour deposition (PECVD) processes. The model enables identification and optimization of film thickness uniformity sensitivities to electrode configuration, temperature, deposition system design and gas flow distribution. PECVD deposition utilizes a co-planar 300mm diameter electrodes with separate RF power matching to each electrode. The system has capability to adjust electrode separation and electrode temperature as parameters to optimize uniformity. Vacuum is achieved using dry pumping with real time control of butterfly valve position for active pressure control. Comparison between theory and experiment is provided for PECVD of diamond-like-carbon (DLC) deposition onto flat and curved substrate geometries. The process utilizes butane reactive feedstock with an argon carrier gas. Radiofrequency plasma is used. Deposited film thickness sensitivities to electrode geometry, plasma power density, pressure and gas flow distribution are demonstrated. Use of modelling to optimise film thickness uniformity is demonstrated. Results show DLC uniformity of 0.30% over a 200 mm flat zone diameter within overall electrode diameter of 300mm. Thickness uniformity of 0.75% is demonstrated over a 200mm diameter for a non-conformal substrate geometry. Use of the modelling method for PECVD using metal-organic chemical vapour deposition (MOCVD) feedstock is demonstrated, specifically for deposition of silica films using metal-organic tetraethoxy-silane. Excellent agreement between experimental and theory is demonstrated for conformal and non-conformal geometries. The model is used to explore scalability of PECVD processes and trade-off against film thickness uniformity. Application to MEMS, optical coatings and thin film photovoltaics is discussed.
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.
Directory of Open Access Journals (Sweden)
W. H. Kao
2015-02-01
Full Text Available The Taguchi design method is used to optimize the adhesion, hardness, and wear resistance properties of a-C:H coatings deposited on AISI M2 steel substrates using the ion beam assisted physical vapor deposition method. The adhesion strength of the coatings is evaluated by means of scratch tests, while the hardness is measured using a nanoindentation tester. Finally, the wear resistance is evaluated by performing cyclic ball-on-disc wear tests. The Taguchi experimental results show that the optimal deposition parameters are as follows: a substrate bias voltage of 90 V, an ion beam voltage of 1 kV, an acetylene flow rate of 21 sccm, and a working distance of 7 cm. Given these optimal processing conditions, the a-C:H coating has a critical load of 99.8 N, a hardness of 25.5 GPa, and a wear rate of 0.4 × 10−6 mm3/Nm.
Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...
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
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.
Optimization of Gas Metal Arc Welding Process Parameters
Kumar, Amit; Khurana, M. K.; Yadav, Pradeep K.
2016-09-01
This study presents the application of Taguchi method combined with grey relational analysis to optimize the process parameters of gas metal arc welding (GMAW) of AISI 1020 carbon steels for multiple quality characteristics (bead width, bead height, weld penetration and heat affected zone). An orthogonal array of L9 has been implemented to fabrication of joints. The experiments have been conducted according to the combination of voltage (V), current (A) and welding speed (Ws). The results revealed that the welding speed is most significant process parameter. By analyzing the grey relational grades, optimal parameters are obtained and significant factors are known using ANOVA analysis. The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions.
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.
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.
Optimization routine for identification of model parameters in soil plasticity
Mattsson, Hans; Klisinski, Marek; Axelsson, Kennet
2001-04-01
The paper presents an optimization routine especially developed for the identification of model parameters in soil plasticity on the basis of different soil tests. Main focus is put on the mathematical aspects and the experience from application of this optimization routine. Mathematically, for the optimization, an objective function and a search strategy are needed. Some alternative expressions for the objective function are formulated. They capture the overall soil behaviour and can be used in a simultaneous optimization against several laboratory tests. Two different search strategies, Rosenbrock's method and the Simplex method, both belonging to the category of direct search methods, are utilized in the routine. Direct search methods have generally proved to be reliable and their relative simplicity make them quite easy to program into workable codes. The Rosenbrock and simplex methods are modified to make the search strategies as efficient and user-friendly as possible for the type of optimization problem addressed here. Since these search strategies are of a heuristic nature, which makes it difficult (or even impossible) to analyse their performance in a theoretical way, representative optimization examples against both simulated experimental results as well as performed triaxial tests are presented to show the efficiency of the optimization routine. From these examples, it has been concluded that the optimization routine is able to locate a minimum with a good accuracy, fast enough to be a very useful tool for identification of model parameters in soil plasticity.
Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm
Directory of Open Access Journals (Sweden)
P. Sabarinath
2015-01-01
Full Text Available The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.
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....
Extended Range Guided Munition Parameter Optimization Based on Genetic Algorithms
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Many factors influencing range of extended range guided munition (ERGM) are analyzed. The definition domain of the most important three parameters are ascertained by preparatory mathematical simulation, the optimized mathematical model of ERGM maximum range with boundary conditions is created, and parameter optimization based on genetic algorithm (GA) is adopted. In the GA design, three-point crossover is used and the best chromosome is kept so that the convergence speed becomes rapid. Simulation result shows that GA is feasible, the result is good and it can be easy to attain global optimization solution, especially when the objective function is not the convex one for independent variables and it is a multi-parameter problem.
Research on Optimization of GLCM Parameter in Cell Classification
Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua
2016-05-01
Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.
Optimal Design of Shock Tube Experiments for Parameter Inference
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.
Parameter optimization for tandemregenerative system based on critical path
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
For a tandem queue system, the regenerative path is constructed. In an inter-regeneration cycle, the sensitivity value of performance measure with respect to the adjustable parameter θ can be acquired based on a fixed length of observation. Furthermore, a new algorithm of parameter optimization for the tandem queue system is given,which requires less simulation and no analysis for the perturbation transmission and makes a better estimation for the sen sitivity.
Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.
2016-07-01
In the RF magnetron sputtering process, the desirable layer properties are largely influenced by the process parameters and conditions. If the quality of the thin film has not reached up to its intended level, the experiments have to be repeated until the desirable quality has been met. This research is proposing Gravitational Search Algorithm (GSA) as the optimization model to reduce the time and cost to be spent in the thin film fabrication. The optimization model's engine has been developed using Java. The model is developed based on GSA concept, which is inspired by the Newtonian laws of gravity and motion. In this research, the model is expected to optimize four deposition parameters which are RF power, deposition time, oxygen flow rate and substrate temperature. The results have turned out to be promising and it could be concluded that the performance of the model is satisfying in this parameter optimization problem. Future work could compare GSA with other nature based algorithms and test them with various set of data.
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.
Cai, Lanlan; Li, Peng; Luo, Qi; Zhai, Pengcheng; Zhang, Qingjie
2017-03-01
As no single thermoelectric material has presented a high figure-of-merit (ZT) over a very wide temperature range, segmented thermoelectric generators (STEGs), where the p- and n-legs are formed of different thermoelectric material segments joined in series, have been developed to improve the performance of thermoelectric generators. A crucial but difficult problem in a STEG design is to determine the optimal values of the geometrical parameters, like the relative lengths of each segment and the cross-sectional area ratio of the n- and p-legs. Herein, a multi-parameter and nonlinear optimization method, based on the Improved Powell Algorithm in conjunction with the discrete numerical model, was implemented to solve the STEG's geometrical optimization problem. The multi-parameter optimal results were validated by comparison with the optimal outcomes obtained from the single-parameter optimization method. Finally, the effect of the hot- and cold-junction temperatures on the geometry optimization was investigated. Results show that the optimal geometry parameters for maximizing the specific output power of a STEG are different from those for maximizing the conversion efficiency. Data also suggest that the optimal geometry parameters and the interfacial temperatures of the adjacent segments optimized for maximum specific output power or conversion efficiency vary with changing hot- and cold-junction temperatures. Through the geometry optimization, the CoSb3/Bi2Te3-based STEG can obtain a maximum specific output power up to 1725.3 W/kg and a maximum efficiency of 13.4% when operating at a hot-junction temperature of 823 K and a cold-junction temperature of 298 K.
SNR dependence of optimal parameters for apparent diffusion coefficient measurements.
Saritas, Emine U; Lee, Jin H; Nishimura, Dwight G
2011-02-01
Optimizing the diffusion-weighted imaging (DWI) parameters (i.e., the b-value and the number of image averages) to the tissue of interest is essential for producing high-quality apparent diffusion coefficient (ADC) maps. Previous investigation of this optimization was performed assuming Gaussian noise statistics for the ADC map, which is only valid for high signal-to-noise ratio (SNR) imaging. In this work, the true statistics of the noise in ADC maps are derived, followed by an optimization of the DWI parameters as a function of the imaging SNR. Specifically, it is demonstrated that the optimum b-value is a monotonically increasing function of the imaging SNR, which converges to the optimum b-value from previously proposed approaches for high-SNR cases, while exhibiting a significant deviation from this asymptote for low-SNR situations. Incorporating the effects of T(2) weighting further increases the SNR dependence of the optimal parameters. The proposed optimization scheme is particularly important for high-resolution DWI, which intrinsically suffers from low SNR and therefore cannot afford the use of the conventional high b-values. Comparison scans were performed for high-resolution DWI of the spinal cord, demonstrating the improvements in the resulting images and the ADC maps achieved by this method.
Wrapped Progressive Sampling Search for Optimizing Learning Algorithm Parameters
Bosch, Antal van den
2005-01-01
We present a heuristic meta-learning search method for finding a set of optimized algorithmic parameters for a range of machine learning algo- rithms. The method, wrapped progressive sampling, is a combination of classifier wrapping and progressive sampling of training data. A series of experiments
Wrapped Progressive Sampling Search for Optimizing Learning Algorithm Parameters
Bosch, Antal van den
2005-01-01
We present a heuristic meta-learning search method for finding a set of optimized algorithmic parameters for a range of machine learning algo- rithms. The method, wrapped progressive sampling, is a combination of classifier wrapping and progressive sampling of training data. A series of experiments
Parameters optimization for magnetic resonance coupling wireless power transmission.
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.
Programmable physical parameter optimization for particle plasma simulations
Ragan-Kelley, Benjamin; Verboncoeur, John; Lin, Ming-Chieh
2012-10-01
We have developed a scheme for interactive and programmable optimization of physical parameters for plasma simulations. The simulation code Object-Oriented Plasma Device 1-D (OOPD1) has been adapted to a Python interface, allowing sophisticated user or program interaction with simulations, and detailed numerical analysis via numpy. Because the analysis/diagnostic interface is the same as the input mechanism (the Python programming language), it is straightforward to optimize simulation parameters based on analysis of previous runs and automate the optimization process using a user-determined scheme and criteria. An example use case of the Child-Langmuir space charge limit in bipolar flow is demonstrated, where the beam current is iterated upon by measuring the relationship of the measured current and the injected current.
Optimal line drop compensation parameters under multi-operating conditions
Wan, Yuan; Li, Hang; Wang, Kai; He, Zhe
2017-01-01
Line Drop Compensation (LDC) is a main function of Reactive Current Compensation (RCC) which is developed to improve voltage stability. While LDC has benefit to voltage, it may deteriorate the small-disturbance rotor angle stability of power system. In present paper, an intelligent algorithm which is combined by Genetic Algorithm (GA) and Backpropagation Neural Network (BPNN) is proposed to optimize parameters of LDC. The objective function proposed in present paper takes consideration of voltage deviation and power system oscillation minimal damping ratio under multi-operating conditions. A simulation based on middle area of Jiangxi province power system is used to demonstrate the intelligent algorithm. The optimization result shows that coordinate optimized parameters can meet the multioperating conditions requirement and improve voltage stability as much as possible while guaranteeing enough damping ratio.
Parameters Optimization for Magnetic Resonance Coupling Wireless Power Transmission
Directory of Open Access Journals (Sweden)
Changsheng Li
2014-01-01
Full Text Available 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.
Optimization of polyetherimide processing parameters for optical interconnect applications
Zhao, Wei; Johnson, Peter; Wall, Christopher
2015-10-01
ULTEM® polyetherimide (PEI) resins have been used in opto-electronic markets since the optical properties of these materials enable the design of critical components under tight tolerances. PEI resins are the material of choice for injection molded integrated lens applications due to good dimensional stability, near infrared (IR) optical transparency, low moisture uptake and high heat performance. In most applications, parts must be produced consistently with minimal deviations to insure compatibility throughout the lifetime of the part. With the large number of lenses needed for this market, injection molding has been optimized to maximize the production rate. These optimized parameters for high throughput may or may not translate to an optimized optical performance. In this paper, we evaluate and optimize PEI injection molding processes with a focus on optical property performance. A commonly used commercial grade was studied to determine factors and conditions which contribute to optical transparency, color, and birefringence. Melt temperature, mold temperature, injection speed and cycle time were varied to develop optimization trials and evaluate optical properties. These parameters could be optimized to reduce in-plane birefringence from 0.0148 to 0.0006 in this study. In addition, we have studied an optically smooth, sub-10nm roughness mold to re-evaluate material properties with minimal influence from mold quality and further refine resin and process effects for the best optical performance.
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.
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
Directory of Open Access Journals (Sweden)
Godfrey C. Onwubolu
2014-01-01
Full Text Available While fused deposition modelling (FDM is one of the most used additive manufacturing (AM techniques today due to its ability to manufacture very complex geometries, the major research issues have been to balance ability to produce aesthetically appealing looking products with functionality. In this study, five important process parameters such as layer thickness, part orientation, raster angle, raster width, and air gap have been considered to study their effects on tensile strength of test specimen, using design of experiment (DOE. Using group method of data handling (GMDH, mathematical models relating the response with the process parameters have been developed. Using differential evolution (DE, optimal process parameters have been found to achieve good strength simultaneously for the response. The optimization of the mathematical model realized results in maximized tensile strength. Consequently, the additive manufacturing part produced is improved by optimizing the process parameters. The predicted models obtained show good correlation with the measured values and can be used to generalize prediction for process conditions outside the current study. Results obtained are very promising and hence the approach presented in this paper has practical applications for design and manufacture of parts using additive manufacturing technologies.
Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback
Bruni, Renato; Celani, Fabio
2016-10-01
The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.
Multiexposure imaging and parameter optimization for intensified star trackers.
Yu, Wenbo; Jiang, Jie; Zhang, Guangjun
2016-12-20
Due to the introduction of the intensified image detector, the dynamic performance of the intensified star tracker is effectively improved. However, its attitude update rate is still seriously restricted by the transmission and processing of pixel data. In order to break through the above limitation, a multiexposure imaging approach for intensified star trackers is proposed in this paper. One star image formed by this approach actually records N different groups of star positions, and then N corresponding groups of attitude information can be acquired. Compared with the existing exposure imaging approach, the proposed approach improves the attitude update rate by N times. Furthermore, for a dim star, the proposed approach can also accumulate the energy of its N positions and then effectively improve its signal-to-noise ratio. Subsequently, in order to obtain the optimal performance of the proposed approach, parameter optimization is carried out. First, the motion model of the star spot in the image plane is established, and then based on it, all the key parameters are optimized. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach and parameter optimization.
Parameter variations in prediction skill optimization at ECMWF
Ollinaho, P.; Bechtold, P.; Leutbecher, M.; Laine, M.; Solonen, A.; Haario, H.; Järvinen, H.
2013-11-01
Algorithmic numerical weather prediction (NWP) skill optimization has been tested using the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). We report the results of initial experimentation using importance sampling based on model parameter estimation methodology targeted for ensemble prediction systems, called the ensemble prediction and parameter estimation system (EPPES). The same methodology was earlier proven to be a viable concept in low-order ordinary differential equation systems, and in large-scale atmospheric general circulation models (ECHAM5). Here we show that prediction skill optimization is possible even in the context of a system that is (i) of very high dimensionality, and (ii) carefully tuned to very high skill. We concentrate on four closure parameters related to the parameterizations of sub-grid scale physical processes of convection and formation of convective precipitation. We launch standard ensembles of medium-range predictions such that each member uses different values of the four parameters, and make sequential statistical inferences about the parameter values. Our target criterion is the squared forecast error of the 500 hPa geopotential height at day three and day ten. The EPPES methodology is able to converge towards closure parameter values that optimize the target criterion. Therefore, we conclude that estimation and cost function-based tuning of low-dimensional static model parameters is possible despite the very high dimensional state space, as well as the presence of stochastic noise due to initial state and physical tendency perturbations. The remaining question before EPPES can be considered as a generally applicable tool in model development is the correct formulation of the target criterion. The one used here is, in our view, very selective. Considering the multi-faceted question of improving forecast model performance, a more general target criterion should be developed
Parameters Optimization of Low Carbon Low Alloy Steel Annealing Process
Institute of Scientific and Technical Information of China (English)
Maoyu ZHAO; Qianwang CHEN
2013-01-01
A suitable match of annealing process parameters is critical for obtaining the fine microstructure of material.Low carbon low alloy steel (20CrMnTi) was heated for various durations near Ac temperature to obtain fine pearlite and ferrite grains.Annealing temperature and time were used as independent variables,and material property data were acquired by orthogonal experiment design under intercritical process followed by subcritical annealing process (IPSAP).The weights of plasticity (hardness,yield strength,section shrinkage and elongation) of annealed material were calculated by analytic hierarchy process,and then the process parameters were optimized by the grey theory system.The results observed by SEM images show that microstructure of optimization annealing material are consisted of smaller lamellar pearlites (ferrite-cementite)and refining ferrites which distribute uniformly.Morphologies on tension fracture surface of optimized annealing material indicate that the numbers of dimple fracture show more finer toughness obviously comparing with other annealing materials.Moreover,the yield strength value of optimization annealing material decreases apparently by tensile test.Thus,the new optimized strategy is accurate and feasible.
Dynamic Experiments for Bioprocess Parameter Optimization with Extreme Halophilic Archaea
Directory of Open Access Journals (Sweden)
Bettina Lorantfy
2013-11-01
Full Text Available The to-date studies on extreme halophiles were focused on shake flask cultivations. Bioreactor technology with quantitative approaches can offer a wide variety of biotechnological applications to exploit the special biochemical features of halophiles. Enabling industrial use of Haloferax mediterranei, finding the optima of cultivation parameters is of high interest. In general, process parameter optimizations were mainly carried out with laborious and time-consuming chemostat cultures. This work offers a faster alternative for process parameter optimization by applying temperature ramps and pH shifts on a halophilic continuous bioreactor culture. Although the hydraulic equilibrium in continuous culture is not reached along the ramps, the main effects on the activity from the dynamic studies can still be concluded. The results revealed that the optimal temperature range may be limited at the lower end by the activity of the primary metabolism pathways. At the higher end, the mass transfer of oxygen between the gaseous and the liquid phase can be limiting for microbial growth. pH was also shown to be a key parameter for avoiding overflow metabolism. The obtained experimental data were evaluated by clustering with multivariate data analyses. Showing the feasibility on a halophilic example, the presented dynamic methodology offers a tool for accelerating bioprocess development.
Mukhtar, Aiman; Shahzad Khan, Babar; Mehmood, Tahir
2016-12-01
The effect of deposition potential on the crystal structure and composition of Co-Ni alloy nanowires is studied by XRD, FE-SEM and EDX. The alloy nanowires deposited at -3.2 V are metastable fcc phase Co-Ni. The alloy nanowires deposited at -1.8 V are hcp phase Co-Ni. The formation of the metastable fcc alloy nanowires can be attributed to smaller critical clusters formed at the high potential as the smaller critical clusters favor fcc structure because of the significant surface energy effect. The content of Co inside nanowires increases with increasing potential. This can be understood by the polarization curves of depositing Co and Ni nanowires, which show that the current density ratio of Ni to Co at low potential has larger value than that at high potential.
Optimizing dictionary learning parameters for solving Audio Inpainting problem
Directory of Open Access Journals (Sweden)
Václav Mach
2013-01-01
Full Text Available Recovering missing or distorted audio signal sam-ples has been recently improved by solving an Audio Inpaintingproblem. This paper aims to connect this problem with K-SVD dictionary learning to improve reconstruction error formissing signal insertion problem. Our aim is to adapt an initialdictionary to the reliable signal to be more accurate in missingsamples estimation. This approach is based on sparse signalsreconstruction and optimization problem. In the paper two staplealgorithms, connection between them and emerging problemsare described. We tried to find optimal parameters for efficientdictionary learning.
Novel Approach to Nonlinear PID Parameter Optimization Using Ant Colony Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
Duan Hai-bin; Wang Dao-bo; Yu Xiu-fen
2006-01-01
This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm,an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response.
Identification of optimal parameter combinations for the emergence of bistability.
Májer, Imre; Hajihosseini, Amirhossein; Becskei, Attila
2015-11-24
Bistability underlies cellular memory and maintains alternative differentiation states. Bistability can emerge only if its parameter range is either physically realizable or can be enlarged to become realizable. We derived a general rule and showed that the bistable range of a reaction parameter is maximized by a pair of other parameters in any gene regulatory network provided they satisfy a general condition. The resulting analytical expressions revealed whether or not such reaction pairs are present in prototypical positive feedback loops. They are absent from the feedback loop enclosed by protein dimers but present in both the toggle-switch and the feedback circuit inhibited by sequestration. Sequestration can generate bistability even at narrow feedback expression range at which cooperative binding fails to do so, provided inhibition is set to an optimal value. These results help to design bistable circuits and cellular reprogramming and reveal whether bistability is possible in gene networks in the range of realistic parameter values.
Cosmological parameter estimation using Particle Swarm Optimization (PSO)
Prasad, Jayanti
2011-01-01
Obtaining the set of cosmological parameters consistent with observational data is an important exercise in current cosmological research. It involves finding the global maximum of the likelihood function in the multi-dimensional parameter space. Currently sampling based methods, which are in general stochastic in nature, like Markov-Chain Monte Carlo(MCMC), are being commonly used for parameter estimation. The beauty of stochastic methods is that the computational cost grows, at the most, linearly in place of exponentially (as in grid based approaches) with the dimensionality of the search space. MCMC methods sample the full joint probability distribution (posterior) from which one and two dimensional probability distributions, best fit (average) values of parameters and then error bars can be computed. In the present work we demonstrate the application of another stochastic method, named Particle Swarm Optimization (PSO), that is widely used in the field of engineering and artificial intelligence, for cosmo...
Identification of optimal parameter combinations for the emergence of bistability
Májer, Imre; Hajihosseini, Amirhossein; Becskei, Attila
2015-12-01
Bistability underlies cellular memory and maintains alternative differentiation states. Bistability can emerge only if its parameter range is either physically realizable or can be enlarged to become realizable. We derived a general rule and showed that the bistable range of a reaction parameter is maximized by a pair of other parameters in any gene regulatory network provided they satisfy a general condition. The resulting analytical expressions revealed whether or not such reaction pairs are present in prototypical positive feedback loops. They are absent from the feedback loop enclosed by protein dimers but present in both the toggle-switch and the feedback circuit inhibited by sequestration. Sequestration can generate bistability even at narrow feedback expression range at which cooperative binding fails to do so, provided inhibition is set to an optimal value. These results help to design bistable circuits and cellular reprogramming and reveal whether bistability is possible in gene networks in the range of realistic parameter values.
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.
NWP model forecast skill optimization via closure parameter variations
Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.
2012-04-01
We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.
Optimization of Neutrino Oscillation Parameters using Differential Evolution
Mustafa, Ghulam; Masud, Bilal
2011-01-01
We combine Differential Evolution, a new technique, with the traditional grid based method for optimization of solar neutrino oscillation parameters $\\Delta m^2$ and $\\tan^{2}\\theta$ for the case of two neutrinos. The Differential Evolution is a population based stochastic algorithm for optimization of real valued non-linear non-differentiable objective functions that has become very popular during the last decade. We calculate well known chi-square ($\\chi^2$) function for neutrino oscillations for a grid of the parameters using total event rates of chlorine (Homestake), Gallax+GNO, SAGE, Superkamiokande and SNO detectors and theoretically calculated event rates. We find minimum $\\chi^2$ values in different regions of the parameter space. We explore regions around these minima using Differential Evolution for the fine tuning of the parameters allowing even those values of the parameters which do not lie on any grid. We note as much as 4 times decrease in $\\chi^2$ value in the SMA region and even better goodne...
Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations
Hanson, Andrea; Reed, Erik; Cavanagh, Peter
2011-01-01
Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.
Optimization of reserve lithium thionyl chloride battery electrochemical design parameters
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.
Analysis and Optimization of Central Processing Unit Process Parameters
Kaja Bantha Navas, R.; Venkata Chaitana Vignan, Budi; Durganadh, Margani; Rama Krishna, Chunduri
2017-05-01
The rapid growth of computer has made processing more data capable, which increase the heat dissipation. Hence the system unit CPU must be cooled against operating temperature. This paper presents a novel approach for the optimization of operating parameters on Central Processing Unit with single response based on response graph method. These methods have a series of steps from of proposed approach which are capable of decreasing uncertainty caused by engineering judgment in the Taguchi method. Orthogonal Array value was taken from ANSYS report. The method shows a good convergence with the experimental and the optimum process parameters.
The optimization of operating parameters on microalgae upscaling process planning.
Ma, Yu-An; Huang, Hsin-Fu; Yu, Chung-Chyi
2016-03-01
The upscaling process planning developed in this study primarily involved optimizing operating parameters, i.e., dilution ratios, during process designs. Minimal variable cost was used as an indicator for selecting the optimal combination of dilution ratios. The upper and lower mean confidence intervals obtained from the actual cultured cell density data were used as the final cell density stability indicator after the operating parameters or dilution ratios were selected. The process planning method and results were demonstrated through three case studies of batch culture simulation. They are (1) final objective cell densities were adjusted, (2) high and low light intensities were used for intermediate-scale cultures, and (3) the number of culture days was expressed as integers for the intermediate-scale culture.
Using string invariants for prediction searching for optimal parameters
Bundzel, Marek; Kasanický, Tomáš; Pinčák, Richard
2016-02-01
We have developed a novel prediction method based on string invariants. The method does not require learning but a small set of parameters must be set to achieve optimal performance. We have implemented an evolutionary algorithm for the parametric optimization. We have tested the performance of the method on artificial and real world data and compared the performance to statistical methods and to a number of artificial intelligence methods. We have used data and the results of a prediction competition as a benchmark. The results show that the method performs well in single step prediction but the method's performance for multiple step prediction needs to be improved. The method works well for a wide range of parameters.
Optimizing bowtie structure parameters for specific incident light
Institute of Scientific and Technical Information of China (English)
Wang Qiao; WU Shi-Fa; Li Xu-Feng; Wang Xiao-Gang
2010-01-01
We investigate optical properties of a bowtie-shaped aperture using the finite difference time domain method to optimize its geometric parameters for specific incident lights. The influence of the parameters on local field enhancement and resonant wavelength in the visible frequency range is numerically analysed. It is found that the major resonance of the spectrum is exponentially depended on the bowtie angle but independent of the whole aperture size. The simulation also demonstrates that increasing the aperture size raises the local field intensity on the exit plane due to an enlarged interaction area between the light and the metal medium. And the near-field spot size is closely related to the gap.Based on these results, the design rules of the bowtie structure can be optimized for specific wavelengths excited.
Optimal designs for dose response curves with common parameters
Feller, Chrystel; Schorning, Kirsten; Dette, Holger; Bermann, Georgina; Bornkamp, Björn
2016-01-01
A common problem in Phase II clinical trials is the comparison of dose response curves corresponding to different treatment groups. If the effect of the dose level is described by parametric regression models and the treatments differ in the administration frequency (but not in the sort of drug) a reasonable assumption is that the regression models for the different treatments share common parameters. This paper develops optimal design theory for the comparison of different regression models ...
Parameter Optimization for Laser Polishing of Niobium for SRF Applications
Energy Technology Data Exchange (ETDEWEB)
Zhao, Liang [Thomas Jefferson National Accelerator Facility, Newport News, VA (United States) and William and Mary College, Williamsburg, VA (United States); Klopf, John Michael [Thomas Jefferson National Accelerator Facility, Newport News, VA (United States); Reece, Charles E. [Thomas Jefferson National Accelerator Facility, Newport News, VA (United States); Kelley, Michael J. [Thomas Jefferson National Accelerator Facility, Newport News, VA (United States) and William and Mary College, Williamsburg, VA (United States)
2013-06-01
Surface smoothness is critical to the performance of SRF cavities. As laser technology has been widely applied to metal machining and surface treatment, we are encouraged to use it on niobium as an alternative to the traditional wet polishing process where aggressive chemicals are involved. In this study, we describe progress toward smoothing by optimizing laser parameters on BCP treated niobium surfaces. Results shows that microsmoothing of the surface without ablation is achievable.
Limiting Behaviour in Parameter Optimal Iterative Learning Control
Institute of Scientific and Technical Information of China (English)
David H. Owens; Maria Tomas-Rodriguez; Jari J. Hat(o)nen
2006-01-01
This paper analyses the concept of a Limit Set in Parameter Optimal Iterative Learning Control (ILC). We investigate the existence of stable and unstable parts of Limit Set and demonstrates that they will often exist in practice.This is illustrated via a 2-dimensional example where the convergence of the learning algorithm is analyzed from the error's dynamic behaviour. These ideas are extended to the N-dimensional cases by analogy and example.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-05-01
Full Text Available Physical parameterizations in General Circulation Models (GCMs, having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM 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 parameters tuning during the model development stage.
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.
Optimization of laser butt welding parameters with multiple performance characteristics
Sathiya, P.; Abdul Jaleel, M. Y.; Katherasan, D.; Shanmugarajan, B.
2011-04-01
This paper presents a study carried out on 3.5 kW cooled slab laser welding of 904 L super austenitic stainless steel. The joints have butts welded with different shielding gases, namely argon, helium and nitrogen, at a constant flow rate. Super austenitic stainless steel (SASS) normally contains high amount of Mo, Cr, Ni, N and Mn. The mechanical properties are controlled to obtain good welded joints. The quality of the joint is evaluated by studying the features of weld bead geometry, such as bead width (BW) and depth of penetration (DOP). In this paper, the tensile strength and bead profiles (BW and DOP) of laser welded butt joints made of AISI 904 L SASS are investigated. The Taguchi approach is used as a statistical design of experiment (DOE) technique for optimizing the selected welding parameters. Grey relational analysis and the desirability approach are applied to optimize the input parameters by considering multiple output variables simultaneously. Confirmation experiments have also been conducted for both of the analyses to validate the optimized parameters.
Optimizing spectral CT parameters for material classification tasks
Rigie, D. S.; La Rivière, P. J.
2016-06-01
In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.
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.
Efficient global optimization of a limited parameter antenna design
O'Donnell, Teresa H.; Southall, Hugh L.; Kaanta, Bryan
2008-04-01
Efficient Global Optimization (EGO) is a competent evolutionary algorithm suited for problems with limited design parameters and expensive cost functions. Many electromagnetics problems, including some antenna designs, fall into this class, as complex electromagnetics simulations can take substantial computational effort. This makes simple evolutionary algorithms such as genetic algorithms or particle swarms very time-consuming for design optimization, as many iterations of large populations are usually required. When physical experiments are necessary to perform tradeoffs or determine effects which may not be simulated, use of these algorithms is simply not practical at all due to the large numbers of measurements required. In this paper we first present a brief introduction to the EGO algorithm. We then present the parasitic superdirective two-element array design problem and results obtained by applying EGO to obtain the optimal element separation and operating frequency to maximize the array directivity. We compare these results to both the optimal solution and results obtained by performing a similar optimization using the Nelder-Mead downhill simplex method. Our results indicate that, unlike the Nelder-Mead algorithm, the EGO algorithm did not become stuck in local minima but rather found the area of the correct global minimum. However, our implementation did not always drill down into the precise minimum and the addition of a local search technique seems to be indicated.
A Combined Method in Parameters Optimization of Hydrocyclone
Directory of Open Access Journals (Sweden)
Jing-an Feng
2016-01-01
Full Text Available To achieve efficient separation of calcium hydroxide and impurities in carbide slag by using hydrocyclone, the physical granularity property of carbide slag, hydrocyclone operation parameters for slurry concentration, and the slurry velocity inlet are designed to be optimized. The optimization methods are combined with the Design of Experiment (DOE method and the Computational Fluid Dynamics (CFD method. Based on Design Expert software, the central composite design (CCD with three factors and five levels amounting to five groups of 20 test responses was constructed, and the experiments were performed by numerical simulation software FLUENT. Through the analysis of variance deduced from numerical simulation experiment results, the regression equations of pressure drop, overflow concentration, purity, and separation efficiencies of two solid phases were, respectively, obtained. The influences of factors were analyzed by the responses, respectively. Finally, optimized results were obtained by the multiobjective optimization method through the Design Expert software. Based on the optimized conditions, the validation test by numerical simulation and separation experiment were separately proceeded. The results proved that the combined method could be efficiently used in studying the hydrocyclone and it has a good performance in application engineering.
Optimization of Neutrino Oscillation Parameters Using Differential Evolution
Institute of Scientific and Technical Information of China (English)
Ghulam Mustafa; Faisal Akram; Bilal Masud
2013-01-01
We show how the traditional grid based method for finding neutrino oscillation parameters △m2 and tan2θ can be combined with an optimization technique,Differential Evolution (DE),to get a significant decrease in computer processing time required to obtain minimal chi-square (x2) in four different regions of the parameter space.We demonstrate efficiency for the two-neutrinos case.For this,the x2 function for neutrino oscillations is evaluated for grids with different density of points in standard allowed regions of the parameter space of △m2 and tan2 θ using experimental and theoretical total event rates of chlorine (Homestake),Gallex+GNO,SAGE,Superkamiokande,and SNO detectors.We find that using DE in combination with the grid based method with small density of points can produce the results comparable with the one obtained using high density grid,in much lesser computation time.
Density-based penalty parameter optimization on C-SVM.
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.
Mathematical Modelling and Parameter Optimization of Pulsating Heat Pipes
Yang, Xin-She; Luan, Tao; Koziel, Slawomir
2014-01-01
Proper heat transfer management is important to key electronic components in microelectronic applications. Pulsating heat pipes (PHP) can be an efficient solution to such heat transfer problems. However, mathematical modelling of a PHP system is still very challenging, due to the complexity and multiphysics nature of the system. In this work, we present a simplified, two-phase heat transfer model, and our analysis shows that it can make good predictions about startup characteristics. Furthermore, by considering parameter estimation as a nonlinear constrained optimization problem, we have used the firefly algorithm to find parameter estimates efficiently. We have also demonstrated that it is possible to obtain good estimates of key parameters using very limited experimental data.
Considerations for parameter optimization and sensitivity in climate models.
Neelin, J David; Bracco, Annalisa; Luo, Hao; McWilliams, James C; Meyerson, Joyce E
2010-12-14
Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention--here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models.
Directory of Open Access Journals (Sweden)
Vivienne Denise Falcão
2006-03-01
Full Text Available CdTe thin films are used as absorber layer in CdS/CdTe solar cells. The microstructure of this absorber layer plays a fundamental role in photovoltaic conversion and can be controlled by the deposition parameters used during the film growth. In this work, CdTe thin films were deposited by the CSS method onto glass substrates previously covered with In2O3:Sn. The effects of pressure, source temperature and substrate temperature on the microstructural properties of the films were studied. The properties were mainly influenced by the pressure, the presence of oxygen in the reaction chamber, and the substrate temperature. For films deposited under an argon atmosphere, an increase in grain size and a reduction of the texture were observed as the pressure and substrate temperature were increased. The introduction of oxygen in the atmosphere led to a decrease in the deposition rate and affected the microstructure and composition of the film. Films deposited under an argon-oxygen atmosphere have smaller grains than those deposited under argon and are richer in Te. The addition of oxygen to the atmosphere apparently did not result in the formation of oxides.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Tungsten carbide deposit was made directly from tungsten metal powder through the reaction with methane in radio frequency induction plasma. Effect of major process parameters on the induction plasma reactive deposition of tungsten carbide was studied by optical microscopy, scanning electron microscopy, X-ray diffraction analysis, water displacement method, and microhardness test. The results show that methane flow rate, powder feed rate, particle size, reaction chamber pressure and deposition distance have significant influences on the phase composition, density, and microhardness of the deposit. Extra carbon is necessary to ensure the complete conversion of tungsten metal into the carbide.
Falcão Vivienne Denise; Pinheiro Wagner Anacleto; Ferreira Carlos Luiz; Cruz Leila Rosa de Oliveira
2006-01-01
CdTe thin films are used as absorber layer in CdS/CdTe solar cells. The microstructure of this absorber layer plays a fundamental role in photovoltaic conversion and can be controlled by the deposition parameters used during the film growth. In this work, CdTe thin films were deposited by the CSS method onto glass substrates previously covered with In2O3:Sn. The effects of pressure, source temperature and substrate temperature on the microstructural properties of the films were studied. The p...
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.
Process Parameters Optimization in Single Point Incremental Forming
Gulati, Vishal; Aryal, Ashmin; Katyal, Puneet; Goswami, Amitesh
2016-04-01
This work aims to optimize the formability and surface roughness of parts formed by the single-point incremental forming process for an Aluminium-6063 alloy. The tests are based on Taguchi's L18 orthogonal array selected on the basis of DOF. The tests have been carried out on vertical machining center (DMC70V); using CAD/CAM software (SolidWorks V5/MasterCAM). Two levels of tool radius, three levels of sheet thickness, step size, tool rotational speed, feed rate and lubrication have been considered as the input process parameters. Wall angle and surface roughness have been considered process responses. The influential process parameters for the formability and surface roughness have been identified with the help of statistical tool (response table, main effect plot and ANOVA). The parameter that has the utmost influence on formability and surface roughness is lubrication. In the case of formability, lubrication followed by the tool rotational speed, feed rate, sheet thickness, step size and tool radius have the influence in descending order. Whereas in surface roughness, lubrication followed by feed rate, step size, tool radius, sheet thickness and tool rotational speed have the influence in descending order. The predicted optimal values for the wall angle and surface roughness are found to be 88.29° and 1.03225 µm. The confirmation experiments were conducted thrice and the value of wall angle and surface roughness were found to be 85.76° and 1.15 µm respectively.
DOE Based Robust Optimization Considering Tolerance Bands of Design Parameters
Lee, Jongsoo; Ahn, Byongchul
The paper describes a robust optimization method to account for the tolerance of design variable and the variation in problem parameter. The proposed post-optimization effort is initiated from the deterministic optimum as a baseline. The successive process to find search directions and step sizes toward the robust optimum is conducted by determining the worst design that has the highest level in constraint violation. During the selection of the worst design, an orthogonal array table in the context of design of experiemtns (DOE) is used to reduce the constraint function evaluations especially for higher dimensionality problem. The analysis of means (ANOM) is adopted in a case where the variation in problem parameter is considered. The measurement criterion to select the worst design is based on the degree of cumulative constraint violation. A mathematical function problem is first conducted to examine the tolerance of design variable. A cantilever beam problem described by four design variables and a bracket problem with seven design variables are subsequently explored by considering both tolerance of design variable and variation in problem parameter.
Afshari Pour, Elnaz; Shafai, Cyrus
2017-02-01
The variation of oxygen concentration in the Indium Tin Oxide (ITO) structure highly impacts its electrical and optical characteristics. In this work, we investigated the effect of oxygen partial flow (O2/O2+Ar) and deposition pressure (p) on the refractive index (n) of reactive sputtered ITO thin films. A statistical study with a Genetic Algorithm (GA) optimization was implemented to find optimal deposition conditions for obtaining particular refractive indices. Several samples of ITO thin films with refractive indices ranging from 1.69 - 2.1 were deposited by DC sputtering technique at various oxygen concentrations and deposition pressures, in order to develop the statistical database. A linear polynomial surface was locally fitted to the data of O2/O2+Ar, p, and n of deposited films. This surface was then used as the fitness function of the GA. By defining the desired n as the objective value of the GA, the optimized deposition conditions can be found. Two cases were experimentally demonstrated, with the GA determining the needed process parameters to deposit ITO with n=2.2 and n=1.6. Measured results were very close to desired values, with n=2.25 and n=1.62, demonstrating the effectiveness of this method for predicting needed reactive sputtering conditions to enable arbitrary refractive indices.
Optimal segmentation of pupillometric images for estimating pupil shape parameters.
De Santis, A; Iacoviello, D
2006-12-01
The problem of determining the pupil morphological parameters from pupillometric data is considered. These characteristics are of great interest for non-invasive early diagnosis of the central nervous system response to environmental stimuli of different nature, in subjects suffering some typical diseases such as diabetes, Alzheimer disease, schizophrenia, drug and alcohol addiction. Pupil geometrical features such as diameter, area, centroid coordinates, are estimated by a procedure based on an image segmentation algorithm. It exploits the level set formulation of the variational problem related to the segmentation. A discrete set up of this problem that admits a unique optimal solution is proposed: an arbitrary initial curve is evolved towards the optimal segmentation boundary by a difference equation; therefore no numerical approximation schemes are needed, as required in the equivalent continuum formulation usually adopted in the relevant literature.
Adaptive Estimation of Intravascular Shear Rate Based on Parameter Optimization
Nitta, Naotaka; Takeda, Naoto
2008-05-01
The relationships between the intravascular wall shear stress, controlled by flow dynamics, and the progress of arteriosclerosis plaque have been clarified by various studies. Since the shear stress is determined by the viscosity coefficient and shear rate, both factors must be estimated accurately. In this paper, an adaptive method for improving the accuracy of quantitative shear rate estimation was investigated. First, the parameter dependence of the estimated shear rate was investigated in terms of the differential window width and the number of averaged velocity profiles based on simulation and experimental data, and then the shear rate calculation was optimized. The optimized result revealed that the proposed adaptive method of shear rate estimation was effective for improving the accuracy of shear rate calculation.
Input Parameters Optimization in Swarm DS-CDMA Multiuser Detectors
Abrão, Taufik; Angelico, Bruno A; Jeszensky, Paul Jean E
2010-01-01
In this paper, the uplink direct sequence code division multiple access (DS-CDMA) multiuser detection problem (MuD) is studied into heuristic perspective, named particle swarm optimization (PSO). Regarding different system improvements for future technologies, such as high-order modulation and diversity exploitation, a complete parameter optimization procedure for the PSO applied to MuD problem is provided, which represents the major contribution of this paper. Furthermore, the performance of the PSO-MuD is briefly analyzed via Monte-Carlo simulations. Simulation results show that, after convergence, the performance reached by the PSO-MuD is much better than the conventional detector, and somewhat close to the single user bound (SuB). Rayleigh flat channel is initially considered, but the results are further extend to diversity (time and spatial) channels.
Optimizing experimental parameters for tracking of diffusing particles
DEFF Research Database (Denmark)
Vestergaard, Christian L.
2016-01-01
We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion coefficient. The precision of estimators for the diffusion coefficient is affected by motion blur, limited photon...... statistics, and the length of recorded time series. We demonstrate for a particle undergoing free diffusion that precision is negligibly affected by motion blur in typical experiments, while optimizing photon counts and the number of recorded frames is the key to precision. Building on these results, we...... describe for a wide range of experimental scenarios how to choose experimental parameters in order to optimize the precision. Generally, one should choose quantity over quality: experiments should be designed to maximize the number of frames recorded in a time series, even if this means lower information...
Total energy control system autopilot design with constrained parameter optimization
Ly, Uy-Loi; Voth, Christopher
1990-01-01
A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.
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.
Sahu, B. B.; Yin, Yongyi; Han, Jeon G.
2016-03-01
This work investigates the deposition of hydrogenated amorphous silicon nitride films using various low-temperature plasmas. Utilizing radio-frequency (RF, 13.56 MHz) and ultra-high frequency (UHF, 320 MHz) powers, different plasma enhanced chemical vapor deposition processes are conducted in the mixture of reactive N2/NH3/SiH4 gases. The processes are extensively characterized using different plasma diagnostic tools to study their plasma and radical generation capabilities. A typical transition of the electron energy distribution function from single- to bi-Maxwellian type is achieved by combining RF and ultra-high powers. Data analysis revealed that the RF/UHF dual frequency power enhances the plasma surface heating and produces hot electron population with relatively low electron temperature and high plasma density. Using various film analysis methods, we have investigated the role of plasma parameters on the compositional, structural, and optical properties of the deposited films to optimize the process conditions. The presented results show that the dual frequency power is effective for enhancing dissociation and ionization of neutrals, which in turn helps in enabling high deposition rate and improving film properties.
Power Saving Optimization for Linear Collider Interaction Region Parameters
Energy Technology Data Exchange (ETDEWEB)
Seryi, Andrei; /SLAC
2009-10-30
Optimization of Interaction Region parameters of a TeV energy scale linear collider has to take into account constraints defined by phenomena such as beam-beam focusing forces, beamstrahlung radiation, and hour-glass effect. With those constraints, achieving a desired luminosity of about 2E34 would require use of e{sup +}e{sup -} beams with about 10 MW average power. Application of the 'travelling focus' regime may allow the required beam power to be reduced by at least a factor of two, helping reduce the cost of the collider, while keeping the beamstrahlung energy loss reasonably low. The technique is illustrated for the 500 GeV CM parameters of the International Linear Collider. This technique may also in principle allow recycling the e{sup +}e{sup -} beams and/or recuperation of their energy.
PARAMETER OPTIMIZATION OF CARBIDIC AUSTEMPERED DUCTILE IRON USING TAGUCHI METHOD
Directory of Open Access Journals (Sweden)
P.DHANAPAL
2010-08-01
Full Text Available Carbidic austempered ductile iron [CADI] is the family of ductile iron containing wear resistance alloy carbides in the ausferrite matrix. This CADI is manufactured by selecting proper material composition through the melting route.In an effort to obtain the optimal production parameters, Taguchi method is applied. To analyse the effect of production parameters on the machanical properties, signal-to-noise (S/N ratio is calculated based on the design ofexperiments and the linear graph. The analysis of varience is calculated to find the amount of contribution of factors on individual mechanical properties and its significancy. The analytical results of taguchi method are compared with the experimental values, and it shows both are identical.
Directory of Open Access Journals (Sweden)
Bat-El Cohen
2014-08-01
Full Text Available 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.
Energy Technology Data Exchange (ETDEWEB)
Cohen, Bat-El; Gamliel, Shany; Etgar, Lioz, E-mail: lioz.etgar@mail.huji.ac.il [Institute of Chemistry, Casali Center for Applied Chemistry, The Hebrew University of Jerusalem, Jerusalem 90400 (Israel)
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.
Process parameter optimization for fly ash brick by Taguchi method
Energy Technology Data Exchange (ETDEWEB)
Prabir Kumar Chaulia; Reeta Das [Central Mechanical Engineering Research Institute, Durgapur (India)
2008-04-15
This paper presents the results of an experimental investigation carried out to optimize the mix proportions of the fly ash brick by Taguchi method of parameter design. The experiments have been designed using an L9 orthogonal array with four factors and three levels each. Small quantity of cement has been mixed as binding materials. Both cement and the fly ash used are indicated as binding material and water binder ratio has been considered as one of the control factors. So the effects of water/binder ratio, fly ash, coarse sand, and stone dust on the performance characteristic are analyzed using signal-to-noise ratios and mean response data. According to the results, water/binder ratio and stone dust play the significant role on the compressive strength of the brick. Furthermore, the estimated optimum values of the process parameters are corresponding to water/binder ratio of 0.4, fly ash of 39%, coarse sand of 24% and stone dust of 30%. The mean value of optimal strength is predicted as 166.22 kg.cm{sup -2} with a tolerance of 10.97 kg.cm{sup -2}. The confirmatory experimental result obtained for the optimum conditions is 160.17 kg.cm{sup -2}. 13 refs., 3 figs., 7 tabs.
Optimizing the Pulsed Current Gas Tungsten Arc Welding Parameters
Institute of Scientific and Technical Information of China (English)
M. Balasubramanian; V. Jayabalan; V. Balasubramanian
2006-01-01
The selection of process parameter in the gas tungsten arc (GTA) welding of titanium alloy was presented for obtaining optimum grain size and hardness. Titanium alloy (Ti-6Al-4V) is one of the most important non-ferrous metals which offers great potential application in aerospace, biomedical and chemical industries,because of its low density (4.5 g/cm3), excellent corrosion resistance, high strength, attractive fracture behaviour and high melting point (1678℃). The preferred welding process for titanium alloy is frequent GTA welding due to its comparatively easier applicability and better economy. In the case of single pass (GTA)welding of thinner section of this alloy, the pulsed current has been found beneficial due to its advantages over the conventional continuous current process. Many considerations come into the picture and one needs to carefully balance various pulse current parameters to reach an optimum combination. Four factors, five level, central composite, rotatable design matrix were used to optimize the required number of experimental conditions. Mathematical models were developed to predict the fusion zone grain size using analysis of variance (ANOVA) and regression analysis. The developed models were optimized using the traditional Hooke and Jeeve's algorithm. Experimental results were provided to illustrate the proposed approach.
Optimal bank portfolio choice under fixed-rate deposit insurance
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.
Impact of sputter deposition parameters on molybdenum nitride thin film properties
Stöber, L.; Konrath, J. P.; Krivec, S.; Patocka, F.; Schwarz, S.; Bittner, A.; Schneider, M.; Schmid, U.
2015-07-01
Molybdenum and molybdenum nitride thin films are presented, which are deposited by reactive dc magnetron sputtering. The influence of deposition parameters, especially the amount of nitrogen during film synthesization, to mechanical and electrical properties is investigated. The crystallographic phase and lattice constants are determined by x-ray diffraction analyses. Further information on the microstructure as well as on the biaxial film stress are gained from techniques such as transmission electron microscopy, scanning electron microscopy and the wafer bow. Furthermore, the film resistivity and the temperature coefficient of resistance are measured by the van der Pauw technique starting from room temperature up to 300 °C. Independent of the investigated physical quantity, a dominant dependence on the sputtering gas nitrogen content is observed compared to other deposition parameters such as the plasma power or the sputtering gas pressure in the deposition chamber.
Parameter Estimation of Induction Motors Using Water Cycle Optimization
Directory of Open Access Journals (Sweden)
M. Yazdani-Asrami
2013-12-01
Full Text Available This paper presents the application of recently introduced water cycle algorithm (WCA to optimize the parameters of exact and approximate induction motor from the nameplate data. Considering that induction motors are widely used in industrial applications, these parameters have a significant effect on the accuracy and efficiency of the motors and, ultimately, the overall system performance. Therefore, it is essential to develop algorithms for the parameter estimation of the induction motor. The fundamental concepts and ideas which underlie the proposed method is inspired from nature and based on the observation of water cycle process and how rivers and streams ﬂow to the sea in the real world. The objective function is defined as the minimization of the real values of the relative error between the measured and estimated torques of the machine in different slip points. The proposed WCA approach has been applied on two different sample motors. Results of the proposed method have been compared with other previously applied Meta heuristic methods on the problem, which show the feasibility and the fast convergence of the proposed approach.
Prasad, Leena Kumari; LaFountaine, Justin S; Keen, Justin M; Williams, Robert O; McGinity, James W
2016-12-30
Electrostatic powder deposition (ESPD) has been developed as a solvent-free method to prepare pharmaceutical films. The aim of this work was to investigate the influence of process parameters during (1) electrostatic powder deposition, (2) curing, and (3) removal of the film from the substrate on the properties of the film. Polyethylene oxide (PEO) was used as the model polymer and stainless steel 316 as the substrate. Deposition efficiency (i.e. deposited weight) was measured with varying charging voltage, gun tip to substrate distance, and environmental humidity. Scanning electron microscopy was utilized to assess film formation, and adhesive and mechanical strength of films were measured with varying cure temperature and time. Adhesive strength was measured for films prepared on substrates of varying surface roughness. When deposition was performed at low humidity conditions, 25%RH, process parameters did not significantly affect deposition behavior. At 40%RH, increasing deposition efficiency with decreasing gun tip to substrate distance and increasing voltage (up to 60kV) was observed. Complete film formation was seen by 30min at 80°C, compared to lower curing temperatures and times. All films were readily removed from the substrates. The results show the ESPD process can be modified to produce films with good mechanical properties (e.g. tensile strength>0.06MPa), suggesting it is a promising dry powder process for preparing pharmaceutical films.
Angelastro, A.; Campanelli, S. L.; Casalino, G.
2017-09-01
This paper presents a study on process parameters and building strategy for the deposition of Colmonoy 227-F powder by CO2 laser with a focal spot diameter of 0.3 mm. Colmonoy 227-F is a nickel alloy especially designed for mold manufacturing. The substrate material is a 10 mm thick plate of AISI 304 steel. A commercial CO2 laser welding machine was equipped with a low-cost powder feeding system. In this work, following another one in which laser power, scanning speed and powder flow rate had been studied, the effects of two important process parameters, i.e. hatch spacing and step height, on the properties of the built parts were analysed. The explored ranges of hatch spacing and step height were respectively 150-300 μm and 100-200 μm, whose dimensions were comparable with that of the laser spot. The roughness, adhesion, microstructure, microhardness and density of the manufactured specimens were studied for multi-layer samples, which were made of 30 layers. The statistical significance of the studied process parameters was assessed by the analysis of the variance. The process parameters used allowed to obtain both first layer-to-substrate and layer-to-layer good adhesions. The microstructure was fine and almost defect-free. The microhardness of the deposited material was about 100 HV higher than that of the starting powder. The density as high as 98% of that of the same bulk alloy was more than satisfactory. Finally, simultaneous optimization of density and roughness was performed using the contour plots.
Spanu, Antonio; Michieli Vitturi, Mattia de'; Barsotti, Sara
2016-09-01
Since the 1970s, multiple reconstruction techniques have been proposed and are currently used, to extrapolate and quantify eruptive parameters from sampled tephra fall deposit datasets. Atmospheric transport and deposition processes strongly control the spatial distribution of tephra deposit; therefore, a large uncertainty affects mass derived estimations especially for fall layer that are not well exposed. This paper has two main aims: the first is to analyse the sensitivity to the deposit sampling strategy of reconstruction techniques. The second is to assess whether there are differences between the modelled values for emitted mass and grainsize, versus values estimated from the deposits. We find significant differences and propose a new correction strategy. A numerical approach is demonstrated by simulating with a dispersal code a mild explosive event occurring at Mt. Etna on 24 November 2006. Eruptive parameters are reconstructed by an inversion information collected after the eruption. A full synthetic deposit is created by integrating the deposited mass computed by the model over the computational domain (i.e., an area of 7.5 × 104 km 2). A statistical analysis based on 2000 sampling tests of 50 sampling points shows a large variability, up to 50 % for all the reconstruction techniques. Moreover, for some test examples Power Law errors are larger than estimated uncertainty. A similar analysis, on simulated grain-size classes, shows how spatial sampling limitations strongly reduce the utility of available information on the total grain size distribution. For example, information on particles coarser than ϕ(-4) is completely lost when sampling at 1.5 km from the vent for all columns with heights less than 2000 m above the vent. To correct for this effect an optimal sampling strategy and a new reconstruction method are presented. A sensitivity study shows that our method can be extended to a wide range of eruptive scenarios including those in which
Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems
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...
Optimal Bayesian experimental design for contaminant transport parameter estimation
Tsilifis, Panagiotis; Hajali, Paris
2015-01-01
Experimental design is crucial for inference where limitations in the data collection procedure are present due to cost or other restrictions. Optimal experimental designs determine parameters that in some appropriate sense make the data the most informative possible. In a Bayesian setting this is translated to updating to the best possible posterior. Information theoretic arguments have led to the formation of the expected information gain as a design criterion. This can be evaluated mainly by Monte Carlo sampling and maximized by using stochastic approximation methods, both known for being computationally expensive tasks. We propose an alternative framework where a lower bound of the expected information gain is used as the design criterion. In addition to alleviating the computational burden, this also addresses issues concerning estimation bias. The problem of permeability inference in a large contaminated area is used to demonstrate the validity of our approach where we employ the massively parallel vers...
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.
Parameter identifiability-based optimal observation remedy for biological networks.
Wang, Yulin; Miao, Hongyu
2017-05-04
To systematically understand the interactions between numerous biological components, a variety of biological networks on different levels and scales have been constructed and made available in public databases or knowledge repositories. Graphical models such as structural equation models have long been used to describe biological networks for various quantitative analysis tasks, especially key biological parameter estimation. However, limited by resources or technical capacities, partial observation is a common problem in experimental observations of biological networks, and it thus becomes an important problem how to select unobserved nodes for additional measurements such that all unknown model parameters become identifiable. To the best knowledge of our authors, a solution to this problem does not exist until this study. The identifiability-based observation problem for biological networks is mathematically formulated for the first time based on linear recursive structural equation models, and then a dynamic programming strategy is developed to obtain the optimal observation strategies. The efficiency of the dynamic programming algorithm is achieved by avoiding both symbolic computation and matrix operations as used in other studies. We also provided necessary theoretical justifications to the proposed method. Finally, we verified the algorithm using synthetic network structures and illustrated the application of the proposed method in practice using a real biological network related to influenza A virus infection. The proposed approach is the first solution to the structural identifiability-based optimal observation remedy problem. It is applicable to an arbitrary directed acyclic biological network (recursive SEMs) without bidirectional edges, and it is a computerizable method. Observation remedy is an important issue in experiment design for biological networks, and we believe that this study provides a solid basis for dealing with more challenging design
Barber, Michael N.
1980-03-01
An algorithm for determining the sequence of variational parameters in a variational approximation to a real-space renormalization group is developed. Using this procedure, the Kadanoff one-hypercube approximation for the two-dimensional Ising model is investigated in some detail. We conclude that the apparent success of this method is somewhat fortuitous; a consistent and completely optimized treatment yielding considerably poorer estimates of the specific heat exponents. In addition, the variational parameter is found to be non-analytic at the fixed point. The nature of singularity agrees with the predictions of van Saarloos, van Leeuwen, and Pruisken.
Institute of Scientific and Technical Information of China (English)
QU Quan-yan; QIU Wan-qi; ZENG De-chang; LIU Zhong-wu; DAI Ming-jiang; ZHOU Ke-song
2009-01-01
The uniform diamond films with 60 mm in diameter were deposited by improved DC arc plasma jet chemical vapor deposition technique. The structure of the film was characterized by scanning electronic microcopy(SEM) and laser Raman spectrometry. The thermal conductivity was measured by a photo thermal deflection technique. The effects of main deposition parameters on microstructure and thermal conductivity of the films were investigated. The results show that high thermal conductivity, 10.0 W/(K-cm), can be obtained at a CH4 concentration of 1.5% (volume fraction) and the substrate temperatures of 880-920 ℃ due to the high density and high purity of the film. A low pressure difference between nozzle and vacuum chamber is also beneficial to the high thermal conductivity.
Parameter optimization in differential geometry based solvation models.
Wang, Bao; Wei, G W
2015-10-01
Differential geometry (DG) based solvation models are a new class of variational implicit solvent approaches that are able to avoid unphysical solvent-solute boundary definitions and associated geometric singularities, and dynamically couple polar and non-polar interactions in a self-consistent framework. Our earlier study indicates that DG based non-polar solvation model outperforms other methods in non-polar solvation energy predictions. However, the DG based full solvation model has not shown its superiority in solvation analysis, due to its difficulty in parametrization, which must ensure the stability of the solution of strongly coupled nonlinear Laplace-Beltrami and Poisson-Boltzmann equations. In this work, we introduce new parameter learning algorithms based on perturbation and convex optimization theories to stabilize the numerical solution and thus achieve an optimal parametrization of the DG based solvation models. An interesting feature of the present DG based solvation model is that it provides accurate solvation free energy predictions for both polar and non-polar molecules in a unified formulation. Extensive numerical experiment demonstrates that the present DG based solvation model delivers some of the most accurate predictions of the solvation free energies for a large number of molecules.
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.
Robust integrated autopilot/autothrottle design using constrained parameter optimization
Ly, Uy-Loi; Voth, Christopher; Sanjay, Swamy
1990-01-01
A multivariable control design method based on constrained parameter optimization was applied to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the following: (1) direct synthesis of a multivariable 'inner-loop' feedback control system based on total energy control principles; (2) synthesis of speed/altitude-hold designs as 'outer-loop' feedback/feedforward control systems around the above inner loop; and (3) direct synthesis of a combined 'inner-loop' and 'outer-loop' multivariable control system. The design procedure offers a direct and structured approach for the determination of a set of controller gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The presented approach may be applied to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by this method following careful problem formulation of the design objectives and constraints. Performance characteristics of the optimization design were improved over the current autopilot design on the B737-100 Transport Research Vehicle (TSRV) at the landing approach and cruise flight conditions; particularly in the areas of closed-loop damping, command responses, and control activity in the presence of turbulence.
Capdevielle, Aurélie; Sýkorová, Eva; Biscans, Béatrice; Béline, Fabrice; Daumer, Marie-Line
2013-01-01
International audience; A sustainable way to recover phosphorus (P) in swine wastewater involves a preliminary step of P dissolution followed by the separation of particulate organic matter. The next two steps are firstly the precipitation of struvite crystals done by adding a crystallization reagent (magnesia) and secondly the filtration of the crystals. A design of experiments with five process parameters was set up to optimize the size of the struvite crystals in a synthetic swine wastewat...
Gao, Hao
2016-04-01
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.
Optimal vibration control of curved beams using distributed parameter models
Liu, Fushou; Jin, Dongping; Wen, Hao
2016-12-01
The design of linear quadratic optimal controller using spectral factorization method is studied for vibration suppression of curved beam structures modeled as distributed parameter models. The equations of motion for active control of the in-plane vibration of a curved beam are developed firstly considering its shear deformation and rotary inertia, and then the state space model of the curved beam is established directly using the partial differential equations of motion. The functional gains for the distributed parameter model of curved beam are calculated by extending the spectral factorization method. Moreover, the response of the closed-loop control system is derived explicitly in frequency domain. Finally, the suppression of the vibration at the free end of a cantilevered curved beam by point control moment is studied through numerical case studies, in which the benefit of the presented method is shown by comparison with a constant gain velocity feedback control law, and the performance of the presented method on avoidance of control spillover is demonstrated.
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.
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.
Parallel axes gear set optimization in two-parameter space
Theberge, Y.; Cardou, A.; Cloutier, L.
1991-05-01
This paper presents a method for optimal spur and helical gear transmission design that may be used in a computer aided design (CAD) approach. The design objective is generally taken as obtaining the most compact set for a given power input and gear ratio. A mixed design procedure is employed which relies both on heuristic considerations and computer capabilities. Strength and kinematic constraints are considered in order to define the domain of feasible designs. Constraints allowed include: pinion tooth bending strength, gear tooth bending strength, surface stress (resistance to pitting), scoring resistance, pinion involute interference, gear involute interference, minimum pinion tooth thickness, minimum gear tooth thickness, and profile or transverse contact ratio. A computer program was developed which allows the user to input the problem parameters, to select the calculation procedure, to see constraint curves in graphic display, to have an objective function level curve drawn through the design space, to point at a feasible design point and to have constraint values calculated at that point. The user can also modify some of the parameters during the design process.
Optimized drying parameters of water hyacinths (Eichhornia crassipes. L
Directory of Open Access Journals (Sweden)
Edgardo V. Casas
2012-12-01
Full Text Available The study investigated the optimum drying conditions of water hyacinth to contribute in the improvement of present drying processes. The effects of independent parameters (drying temperature, airflow rate, and number of passes on the responses were determined using the Response Surface Methodology. The response parameters were composed of (1 final moisture content, (2 moisture ratio, (3 drying rate,(4 tensile strength, and (5 browning index. Box and Behnken experimental design represented the design of experiments that resulted in 15 drying runs. Statistical analysis evaluated the treatment effects. Drying temperature significantly affected the drying rate, moisture ratio, and browning index. Airflow rate had a significant effect only on the drying rate, while the number of passes significantly affected both the drying rate and browning index. The optimized conditions for drying the water hyacinth were at drying temperature of 90C, airflow rate of 0.044m3/s, and number of passes equivalent to five. The best modelthat characterizes the drying of water hyacinth is a rational function expressed as:
Optimization of CVD parameters for long ZnO NWs grown on ITO/glass substrate
Indian Academy of Sciences (India)
ABDULQADER D FAISAL
2016-12-01
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 coated with zinc acetate dihydrate to form seed layer of ZnO nanocrystals. Double zone tube furnace connected to vacuum pump was used for ZnO growth process. Zn metal powder was positioned at the first zone at temperature 900$^{\\circ}$C. The ITO–glass substrate with pre-coated seed layer was then located in the second zone of tube furnace at growth temperature of 550$^{\\circ}$C. The growth of ZnO NWs was controlled under constant concentration of seed layer, while other parameters such as argon and oxygen flow rates, substrate position, time and oxygen flow rate were varied.The VA ZnO NWs were finally characterized by scanning electron microscopy, X-ray diffractometer and high-resolution transmission electron microscope equipped with energy-dispersive X-ray spectroscopy. The results showthat long and VA ZnO NWs were single crystalline with hexagonal wurtzite structure. The ultimate length and average diameter of ZnO NWs were 10 $\\mu$m and 50–100 nm, respectively. These were achieved under optimized CVD growth parameters. The mechanism of vertical growth model of ZnO NWs is also discussed.
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.
Spanu, A; Barsotti, S
2015-01-01
Since the seventies, several reconstruction techniques have been proposed, and are currently used, to extrapolate and quantify eruptive parameters from sampled deposit datasets. Discrete numbers of tephra ground loadings or stratigraphic records are usually processed to estimate source eruptive values. Reconstruction techniques like Pyle, Power law and Weibull are adopted as standard to quantify the erupted mass (or volume) whereas Voronoi for reconstructing the granulometry. Reconstructed values can be affected by large uncertainty due to complexities occurring within the atmospheric dispersion and deposition of volcanic particles. Here we want to quantify the sensitivity of reconstruction techniques, and to quantify how much estimated values of mass and grain size differ from emitted and deposited ones. We adopted a numerical approach simulating with a dispersal code a mild explosive event occurring at Mt. Etna, with eruptive parameters similar to those estimated for eruptions occurred in the last decade. T...
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.
Estimation of Genetic Parameters for Fat Deposition and Carcass Traits in Broilers
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
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)
Energy Technology Data Exchange (ETDEWEB)
Deng, Zhang; He, Wenjie; Duan, Chenlong [State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Chen, Rong, E-mail: rongchen@mail.hust.edu.cn [State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Shan, Bin [State Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China)
2016-01-15
Spatial atomic layer deposition (SALD) is a promising technology with the aim of combining the advantages of excellent uniformity and conformity of temporal atomic layer deposition (ALD), and an industrial scalable and continuous process. In this manuscript, an experimental and numerical combined model of atmospheric SALD system is presented. To establish the connection between the process parameters and the growth efficiency, a quantitative model on reactant isolation, throughput, and precursor utilization is performed based on the separation gas flow rate, carrier gas flow rate, and precursor mass fraction. The simulation results based on this model show an inverse relation between the precursor usage and the carrier gas flow rate. With the constant carrier gas flow, the relationship of precursor usage and precursor mass fraction follows monotonic function. The precursor concentration, regardless of gas velocity, is the determinant factor of the minimal residual time. The narrow gap between precursor injecting heads and the substrate surface in general SALD system leads to a low Péclet number. In this situation, the gas diffusion act as a leading role in the precursor transport in the small gap rather than the convection. Fluid kinetics from the numerical model is independent of the specific structure, which is instructive for the SALD geometry design as well as its process optimization.
Bolch, W E; Farfán, E B; Huh, C; Huston, T E; Bolch, W E
2001-10-01
Risk assessment associated with the inhalation of radioactive aerosols requires as an initial step the determination of particle deposition within the various anatomic regions of the respiratory tract. The model outlined in ICRP Publication 66 represents to date one of the most complete overall descriptions of not only particle deposition, but of particle clearance and local radiation dosimetry of lung tissues. In this study, a systematic review of the deposition component within the ICRP 66 respiratory tract model was conducted in which probability density functions were assigned to all input parameters. These distributions were subsequently incorporated within a computer code LUDUC (LUng Dose Uncertainty Code) in which Latin hypercube sampling techniques are used to generate multiple (e.g., 1,000) sets of input vectors (i.e., trials) for all of the model parameters needed to assess particle deposition within the extrathoracic (anterior and posterior), bronchial, bronchiolar, and alveolar-interstitial regions of the ICRP 66 respiratory tract model. Particle deposition values for the various trial simulations were shown to be well described by lognormal probability distributions. Geometric mean deposition fractions from LUDUC were found to be within approximately +/- 10% of the single-value estimates from the LUDEP computer code for each anatomic region and for particle diameters ranging from 0.001 to 50 microm. In all regions of the respiratory tract, LUDUC simulations for an adult male at light exertion show that uncertainties in particle deposition fractions are distributed only over a range of about a factor of approximately 2-4 for particle sizes between 0.005 to 0.2 microm. Below 0.005 microm, uncertainties increase only for deposition within the alveolar region. At particle sizes exceeding 1 microm, uncertainties in the deposition fraction within the extrathoracic regions are relatively small, but approach a factor of 20 for deposition in the bronchial
Taguchi Method Applied in Optimization of Shipley 5740 Positive Resist Deposition
Hui, Allan; Wiberg, Dean V.; Blosiu, Julian
1997-01-01
Taguchi Methods of Robust Design Presents a way to optimize output process performance through organized experiments, by using orthogonal arrays for the evaluation of the process controlleable parameters.
Directory of Open Access Journals (Sweden)
Filip Górski
2013-09-01
Full Text Available The paper presents the results of experimental study – part of research of additive technology using thermoplastics as a build material, namely Fused Deposition Modelling (FDM. Aim of the study was to identify the relation between basic parameter of the FDM process – model orientation during manufacturing – and a dimensional accuracy and repeatability of obtained products. A set of samples was prepared – they were manufactured with variable process parameters and they were measured using 3D scanner. Significant differences in accuracy of products of the same geometry, but manufactured with different set of process parameters were observed.
Sachot, Nadège; Castano, Oscar; Planell, Josep A; Engel, Elisabeth
2015-08-01
Electrospinning is a method that can be used to efficiently produce scaffolds that mimic the fibrous structure of natural tissue, such as muscle structures or the extracellular matrix of bone. The technique is often used as a way of depositing composites (organic/inorganic materials) to obtain bioactive nanofibers which have the requisite mechanical properties for use in tissue engineering. However, many factors can influence the formation and collection of fibers, including experimental variables such as the parameters of the solution of the electrospun slurry. In this study, we assessed the influence of the polymer concentration, glass content and glass hydrolysis level on the morphology and thickness of fibers produced by electrospinning for a PCL-(Si-Ca-P2 ) bioactive ormoglass-organically modified glass-blend. Based on previous assays, this combination of materials shows good angiogenic and osteogenic properties, which gives it great potential for use in tissue engineering. The results of our study showed that blend preparation directly affected the features of the resulting fibers, and when the parameters of the blend are precisely controlled, fibers with a regular diameter could be produced fairly easily when 2,2,2-trifluoroethanol was used as a solvent instead of tetrahydrofuran. The diameter of the homogeneous fibers ranged from 360 to 620 nm depending on the experimental conditions used. This demonstrates that experimental optimization of the electrospinning process is crucial in order to obtain a deposit of hybrid nanofibers with a regular shape.
Multivariable norm optimal and parameter optimal iterative learning control: a unified formulation
Owens, D. H.
2012-08-01
This article investigates the two paradigms of norm optimal iterative learning control (NOILC) and parameter optimal iterative learning control (POILC) for multivariable (MIMO) ℓ-input, m-output linear discrete-time systems. The main result is a proof that, despite their algebraic and conceptual differences, they can be unified using linear quadratic multi-parameter optimisation techniques. In particular, whilst POILC has been naturally regarded as an approximation to NOILC, it is shown that the NOILC control law can be generated from a suitable choice of control law parameterisation and objective function in a multi-parameter MIMO POILC problem. The form of this equivalence is used to propose a new general approach to the construction of POILC problems for MIMO systems that approximates the solution of a given NOILC problem. An infinite number of such approximations exist. This great diversity is illustrated by the derivation of new convergent algorithms based on time interval and gradient partition that extend previously published work.
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.
Inversion of generalized relaxation time distributions with optimized damping parameter
Florsch, Nicolas; Revil, André; Camerlynck, Christian
2014-10-01
Retrieving the Relaxation Time Distribution (RDT), the Grains Size Distribution (GSD) or the Pore Size Distribution (PSD) from low-frequency impedance spectra is a major goal in geophysics. The “Generalized RTD” generalizes parametric models like Cole-Cole and many others, but remains tricky to invert since this inverse problem is ill-posed. We propose to use generalized relaxation basis function (for instance by decomposing the spectra on basis of generalized Cole-Cole relaxation elements instead of the classical Debye basis) and to use the L-curve approach to optimize the damping parameter required to get smooth and realistic inverse solutions. We apply our algorithm to three examples, one synthetic and two real data sets, and the program includes the possibility of converting the RTD into GSD or PSD by choosing the value of the constant connecting the relaxation time to the characteristic polarization size of interest. A high frequencies (typically above 1 kHz), a dielectric term in taken into account in the model. The code is provided as an open Matlab source as a supplementary file associated with this paper.
Optimal parameters of monolithic high-index contrast grating VCSELs
Marciniak, Magdalena; Gebski, Marcin; Dems, Maciej; Czyszanowski, Tomasz
2016-04-01
Monolithic High refractive index Contrast Grating (MHCG) allows several-fold size reduction of epitaxial structure of VCSEL and facilitates VCSEL fabrication in all photonic material systems. MHCGs can be fabricated of material which refractive index is higher than 1.75 without the need of the combination of low and high refractive index materials. MHCGs have a great application potential in optoelectronic devices, especially in phosphide- and nitride-based VCSELs, which suffer from the lack of efficient monolithically integrated DBR mirrors. MHCGs can simplify the construction of VCSELs, reducing their epitaxial design to monolithic wafer with carrier confinement and active region inside and etched stripes on both surfaces in post processing. In this paper we present results of numerical analysis of MHCGs as a high reflective mirrors for broad range of refractive indices that corresponds to plethora of materials typically used in optoelectronics. Our calculations base on a three-dimensional, fully vectorial optical model. We investigate the reflectance of the MHCG mirrors of different design as the function of the refractive index and we show the optimal geometrical parameters of MHCG enabling nearly 100% reflectance and broad reflection stop-band. We show that MHCG can be designed based on most of semiconductors materials and for any incident light wavelength from optical spectrum.
Analytically optimal parameters of dynamic vibration absorber with negative stiffness
Shen, Yongjun; Peng, Haibo; Li, Xianghong; Yang, Shaopu
2017-02-01
In this paper the optimal parameters of a dynamic vibration absorber (DVA) with negative stiffness is analytically studied. The analytical solution is obtained by Laplace transform method when the primary system is subjected to harmonic excitation. The research shows there are still two fixed points independent of the absorber damping in the amplitude-frequency curve of the primary system when the system contains negative stiffness. Then the optimum frequency ratio and optimum damping ratio are respectively obtained based on the fixed-point theory. A new strategy is proposed to obtain the optimum negative stiffness ratio and make the system remain stable at the same time. At last the control performance of the presented DVA is compared with those of three existing typical DVAs, which were presented by Den Hartog, Ren and Sims respectively. The comparison results in harmonic and random excitation show that the presented DVA in this paper could not only reduce the peak value of the amplitude-frequency curve of the primary system significantly, but also broaden the efficient frequency range of vibration mitigation.
Application of RBF Neural Network in OptimizingMachining Parameters
Institute of Scientific and Technical Information of China (English)
朱喜林; 吴博达; 武星星
2004-01-01
In machining processes, errors of rough in dimension, shape and location lead to changes in processing quantity, and the material of a workpiece may not be uniform. For these reasons, cutting force changes in machining, making the machining system deformable. Consequently errors in workpieces may occur. This is called the error reflection phenomenon. Generally, such errors can be reduced through repeated processing while using appropriate processing quantity in each processing based on operator's experience.According to the theory of error reflection, the error reflection coefficient indicates the extent to which errors of rough influence errors of workpieces. It is related to several factors such as machining condition, hardness of the workpiece, etc. This non-linear relation cannot be worked out using any formula. RBF neural network can approximate a non-linear function within any precision and be trained fast. In this paper, non-linear mapping ability of a fuzzy-neural network is utilized to approximate the non-linear relation. After training of the network with swatch collection obtained in experiments, an appropriate output can be obtained when an input is given. In this way, one can get the required number of processing and the processing quantity each time from the machining condition. Angular rigidity of a machining system,hardness of workpiece, etc., can be input in a form of fuzzy values. Feasibility in solving error reflection and optimizing machining parameters with a RBF neural network is verified by a simulation test with MATLAB.
Parameters optimization for biological molecules patterning using 248-nm ultrafast lasers
Dinca, V.; Ranella, A.; Popescu, A.; Dinescu, M.; Farsari, M.; Fotakis, C.
2007-12-01
Laser-induced forward transfer has been used for the deposition of photoactive biotin in micron-scale patterns. The process uses a 500 fs pulsed KrF laser beam to transfer small amounts of a liquid solution target as micron-size droplets to a substrate placed parallel and in close proximity to it. The biomolecules remain active after the transfer; this is demonstrated through fluorescence assays. In addition to the laser parameters, those regarding the target composition and the receiving surface for the miniaturization of the transferred patterns have been studied and optimized. Droplets as small as 5 μm have been obtained by reducing the target thickness and transfer energy; by increasing the percentage of glycerol added in the biomolecules solution and by using hydrophobic surfaces as receiving substrates. The influence of the glycerol addition and the hydrophobicity of the receiving surfaces on the activity of the transferred biomolecules have also been studied.
Stephens, J.; Fierro, A.; Trienekens, D.; Dickens, J.; Neuber, A.
2015-02-01
Utilizing nanosecond high voltage pulses to drive microdischarges (MDs) at repetition rates in the vicinity of 1 MHz previously enabled increased time-averaged power deposition, peak vacuum ultraviolet (VUV) power yield, as well as time-averaged VUV power yield. Here, various pulse widths (30-250 ns), and pulse repetition rates (100 kHz-5 MHz) are utilized, and the resulting VUV yield is reported. It was observed that the use of a 50 ns pulse width, at a repetition rate of 100 kHz, provided 62 W peak VUV power and 310 mW time-averaged VUV power, with a time-averaged VUV generation efficiency of ˜1.1%. Optimization of the driving parameters resulted in 1-2 orders of magnitude increase in peak and time-averaged power when compared to low power, dc-driven MDs.
Optimization of an ionized metal physical vapor deposition reactor
Energy Technology Data Exchange (ETDEWEB)
Lu, J.; Kushner, M.J. [Univ. of Illinois, Urbana, IL (United States)
1998-12-31
Conventional sputtering for microelectronic fabrication produces poorly collimated neutral atom fluxes. Ion fluxes, however, can be accelerated and collimated by using a conventional dc or rf substrate bias. Hence, magnetron ionized metal physical vapor deposition (IMPVD) can produce highly ionized metal fluxes that can be used to fill high-aspect-ratio vias and trenches in microelectronic devices. Hopwood and Qian have examined design issues in IMPVD systems. In this study, a Design of Experiment (DOE) has been numerically performed for an IMPVD reactor using an inductively coupled plasma and a capacitively biased substrate. Gas pressure, reactor geometry, ICP power, and number of inductive coils are the design variables. Uniformity, magnitude, and ionization fraction of the depositing fluxes are the response variables. The influence of the design variables on the response variables is examined, with the goals of obtaining high uniformity, high magnitude, and high ionization fraction of the depositing metal fluxes. The computational tool used in this study is the two-dimensional Hybrid Plasma Equipment Model (HPEM). The aspect ratio of the reactor (height/radius) ranges from 0.5 to 1.0, the gas pressure ranges from 10 to 40 mTorr, the ICP power ranges from 0.5 to 2.0 kW, and the number of ICP coils ranges from 2 to 6. It was found that: (a) uniformity maximizes at high aspect ratio, low power, and high pressure; (b) flux magnitude maximizes at low aspect ratio, high power, and low pressure; (c) ionization fraction maximizes at high aspect ratio, high power, and high pressure.
Directory of Open Access Journals (Sweden)
Harald Hetzner
2014-12-01
Full Text Available Tungsten-modified hydrogenated amorphous carbon coatings (a-C:H:W were deposited on high speed steel by reactive magnetron sputtering of a tungsten carbide target in an argon-ethine atmosphere. The deposition parameters, sputtering power, bias voltage, argon and ethine flow rate, were varied according to a central composite design comprising 25 different parameter combinations. For comparison, a tungsten carbide coating was deposited, as well. During coating deposition, the process variables, total pressure, sputtering voltage and bias current, were measured as process characteristics. The thickness of the deposited coatings was determined using the crater grinding method, and the deposition rate was calculated. Young’s modulus E and indentation hardness HIT were characterized by means of nanoindentation. With E = 80
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.
Tsutsui, Shigeyosi
This paper proposes an aggregation pheromone system (APS) for solving real-parameter optimization problems using the collective behavior of individuals which communicate using aggregation pheromones. APS was tested on several test functions used in evolutionary computation. The results showed APS could solve real-parameter optimization problems fairly well. The sensitivity analysis of control parameters of APS is also studied.
Energy Technology Data Exchange (ETDEWEB)
Fricke, Katja, E-mail: k.fricke@inp-greifswald.de [Leibniz Institute for Plasma Science and Technology e.V. (INP Greifswald), Felix-Hausdorff-Str. 2, 17489 Greifswald (Germany); Girard-Lauriault, Pierre-Luc [Plasma Processing Laboratory, Department of Chemical Engineering, McGill University, 3610 rue University, Montreal, QC H3A 0C5 (Canada); Weltmann, Klaus-Dieter [Leibniz Institute for Plasma Science and Technology e.V. (INP Greifswald), Felix-Hausdorff-Str. 2, 17489 Greifswald (Germany); Wertheimer, Michael R. [Department of Engineering Physics, École Polytechnique de Montréal, Box 6079, Station Centre-Ville, Montreal, QC H3C 3A7 (Canada)
2016-03-31
We present results on the deposition of plasma polymer (PP) films in a dielectric barrier discharge system fed with mixtures of argon or nitrogen carrier gas plus different hydrocarbon precursors, where the latter possess different carbon-to-hydrogen ratios: CH{sub 4} < C{sub 2}H{sub 6} < C{sub 2}H{sub 4} = C{sub 3}H{sub 6} < C{sub 2}H{sub 2}. The influence of precursor gas mixture and flow rate, excitation frequency, and absorbed power on PP film compositions and properties has been investigated. The discharge was characterized by electrical measurements, while the chemical compositions and structures of coatings were analysed by X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, total combustion, and elastic recoil detection analyses, the latter two for determining carbon-to-hydrogen ratios. Scanning electron microscopy was used to study the coatings' morphology, and profilometry for evaluating deposition rates. - Highlights: • Atmospheric pressure DBD is used to deposit organic hydrocarbon films. • High deposition rates can be achieved by varying the power and/or gas mixture ratio. • Process parameters affect the films' surface chemical composition and morphology. • Deposited films are not soluble in aqueous environment. • No delamination of coatings produced from argon plasma.
Influence of deposition parameters on the microstructure of ion-plated films
Broitman, Esteban; Zimmerman, Rosa
1996-01-01
Ion plating is essentially vapor deposition onto a substrate which is the cathode of a glow discharge. The most important characteristic of the technique is that the growing film is subjected to a flux of high energy particles (neutrals and ions). In this study we report information about the effect of ion plating parameters on grain diameter and crystallite size distribution. At a constant potential grain size remains constant with the increase of ion density. On the other hand, at a constan...
Kaneko, Satoru; Ito, Takeshi; Hirabayashi, Yasuo; Ozawa, Takeshi; Okuda, Tetsuya; Motoizumi, Yu; Hirai, Kiyohito; Naganuma, Yasuhiro; Soga, Masayasu; Yoshimoto, Mamoru; Suzuki, Koji
2011-04-15
Metal oxide nanoparticles prepared by pulsed laser deposition (PLD) were applied to nonenzymatic glucose detection. NiO nanoparticles with size of 3 nm were deposited on glassy carbon (GC) and silicon substrates at room temperature in an oxygen atmosphere. Transmission electron microscope (TEM) image showed nanoparticles with the size of 3 nm uniformly scattered on the Si(001) substrate. Unlike co-sputtering nanoparticle and carbon simultaneously, the PLD method can easily control the surface coverage of nanoparticles on the surface of substrate by deposition time. Cyclic voltammetry was performed on the samples deposited on the GC substrates for electrochemical detection of glucose. The differences between peak currents with and without glucose was used to optimize the coverage of nanoparticles on carbon electrode. The results indicated that optimal coverage of nanoparticles on carbon electrode.
Optimization of Laser Beam Transformation Hardening by One Single Parameter
Meijer, J.; Sprang, van I.
1991-01-01
The process of laser beam transformation hardening is principally controlled by two independent parameters, the absorbed laser power on a given area and the interaction time. These parameters can be transformed into two functional parameters: the maximum surface temperature and the hardening depth.
Optimization of operational aircraft parameters Reducing Noise Emission
Abdallah, Lina; Khardi, Salah
2008-01-01
The objective of this paper is to develop a model and a minimization method to provide flight path optimums reducing aircraft noise in the vicinity of airports. Optimization algorithm has solved a complex optimal control problem, and generates flight paths minimizing aircraft noise levels. Operational and safety constraints have been considered and their limits satisfied. Results are here presented and discussed.
Institute of Scientific and Technical Information of China (English)
ZHANG Xu-ping; YU Yue-qing
2005-01-01
Optimization of structural parameters aimed at improving the load carrying capacity of spatial flexible redundant manipulators is presented in this paper. In order to increase the ratio of load to mass of robots, the cross-sectional parameters and constructional parameters are optimized respectively. The cross-sectional and configurational parameters are optimized simultaneously. The numerical simulation of a 4R spatial manipulator is performed. The results show that the load capacity of robots has been greatly improved through the optimization strategies proposed in this paper.
An all-at-once factorial method to optimize dip-pen deposition of liquid protein inks
Henning, A. K.; Rozhok, S.; Fragala, J.; Shile, R.; Ouyang, K.
2013-03-01
An all-at-once factorial method is presented, which optimizes protein ink deposition using microfabricated pens by identifying the pen design which writes the greatest number of uniform-size spots or droplets without re-inking. Pen features associated with capillary ink transport are varied according to statistical design-of-experiment (SDOE) principles, and evaluated using a special 1D pen array of twelve pens. Variable parameter pens are bracketed by control pens. Each pen array element embodies one component of the SDOE matrix. All parameters are evaluated simultaneously with a single droplet writing pass. Results can also be evaluated simultaneously, leading to rapid choice of those pen parameters which deliver the greatest number of printed features having the smallest coefficient of variation.
A Filled Function with Adjustable Parameters for Unconstrained Global Optimization
Institute of Scientific and Technical Information of China (English)
SHANGYou-lin; LIXiao-yan
2004-01-01
A filled function with adjustable parameters is suggested in this paper for finding a global minimum point of a general class of nonlinear programming problems with a bounded and closed domain. This function has two adjustable parameters. We will discuss the properties of the proposed filled function. Conditions on this function and on the values of parameters are given so that the constructed function has the desired properties of traditional filled function.
FCC-hh final-focus for flat-beams: parameters and energy deposition studies
Abelleira, Jose; 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.
Adaptive neuro-fuzzy estimation of optimal lens system parameters
Petković, Dalibor; Pavlović, Nenad T.; Shamshirband, Shahaboddin; Mat Kiah, Miss Laiha; Badrul Anuar, Nor; Idna Idris, Mohd Yamani
2014-04-01
Due to the popularization of digital technology, the demand for high-quality digital products has become critical. The quantitative assessment of image quality is an important consideration in any type of imaging system. Therefore, developing a design that combines the requirements of good image quality is desirable. Lens system design represents a crucial factor for good image quality. Optimization procedure is the main part of the lens system design methodology. Lens system optimization is a complex non-linear optimization task, often with intricate physical constraints, for which there is no analytical solutions. Therefore lens system design provides ideal problems for intelligent optimization algorithms. There are many tools which can be used to measure optical performance. One very useful tool is the spot diagram. The spot diagram gives an indication of the image of a point object. In this paper, one optimization criterion for lens system, the spot size radius, is considered. This paper presents new lens optimization methods based on adaptive neuro-fuzzy inference strategy (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.
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.
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.
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)
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.
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.
Bath Parameter Dependence of Chemically-Deposited Copper Selenide Thin Film
Al-Mamun; Islam, A. B. M. O.
In this article, a low cost chemical bath deposition (CBD) technique has been used for the preparation of Cu2-xSe thin films on to glass substrate. Different thin films (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 complexing the Cu2+ ions with TEA first, and then addition of ammonia yields better results than the reverse process. The film thickness increases with the decrease of value x of Cu2-xSe.
Growth process optimization of ZnO thin film using atomic layer deposition
Weng, Binbin; Wang, Jingyu; Larson, Preston; Liu, Yingtao
2016-12-01
The work reports experimental studies of ZnO thin films grown on Si(100) wafers using a customized thermal atomic layer deposition. The impact of growth parameters including H2O/DiethylZinc (DEZn) dose ratio, background pressure, and temperature are investigated. The imaging results of scanning electron microscopy and atomic force microscopy reveal that the dose ratio is critical to the surface morphology. To achieve high uniformity, the H2O dose amount needs to be at least twice that of DEZn per each cycle. If the background pressure drops below 400 mTorr, a large amount of nanoflower-like ZnO grains would emerge and increase surface roughness significantly. In addition, the growth temperature range between 200 °C and 250 °C is found to be the optimal growth window. And the crystal structures and orientations are also strongly correlated to the temperature as proved by electron back-scattering diffraction and x-ray diffraction results.
Optimization of multilayer neural network parameters for speaker recognition
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.
Stability and optimal parameters for continuous feedback chaos control.
Kouomou, Y Chembo; Woafo, P
2002-09-01
We investigate the conditions under which an optimal continuous feedback control can be achieved. Chaotic oscillations in the single-well Duffing model, with either a positive or a negative nonlinear stiffness term, are tuned to their related Ritz approximation. The Floquet theory enables the stability analysis of the control. Critical values of the feedback control coefficient fulfilling the optimization criteria are derived. The influence of the chosen target orbit, of the feedback coefficient, and of the onset time of control on its duration is discussed. The analytic approach is confirmed by numerical simulations.
DEFF Research Database (Denmark)
Keller, Stephan Urs; Häfliger, Daniel; Boisen, Anja
2008-01-01
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...
Multi responses optimization of wire EDM process parameters using ...
African Journals Online (AJOL)
International Journal of Engineering, Science and Technology .... considering input parameters peak current, pulse on time, pulse off time & wire tension for En31 tool steel ..... International Journal of Multidisciplinary and Current Research Vol.
Optimization of process and solution parameters in electrospinning polyethylene oxide
CSIR Research Space (South Africa)
Jacobs, V
2011-11-01
Full Text Available , applied voltage and polyallylamine hydrochloride (PAH) concentration in the spinning solution and its influence on nanofiber diameter. The selected parameters were varied at three levels using Box and Behnken factorial design. The interaction effect...
Key safety parameters in the optimization of fuel management
Energy Technology Data Exchange (ETDEWEB)
Kollmar, W.; Boehm, R.; Dernedde, I.; Haase, H.; Kiehlmann, H.D.; Neufert, A.
1988-08-01
Nuclear design related key safety parameters and admissible parameter ranges are defined for reload cycles which are so similar in safety terms as to allow these to be covered by generic reload safety analyses in advance. The conceptual frame of such safety analyses together with the resulting economic benefits are illustrated by four concrete applications demonstrating reduction of excessive safety margins, increase in discharge burnup, streamlining of steam break analysis, and increase in operational flexibility of first cores.
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.
Certain optimal parameters of high-velocity Venturi ejection tubes
Stark, S. B.; Reznichenko, I. G.; Pavlenko, Y. P.
1984-11-01
The influence of the geometrical characteristics of centrifugal nozzles in high velocity Venturi ejection tubes for atomizing liquid in gas cleaning plant is analyzed. An optimal value of the nozzle geometrical characteristic, which is a function of the degree of filling of the nozzle outlet opening by the liquid, is given, at which the throat length is independent of water pressure before the nozzle.
Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
LI Jimin; SHANG Chaoxuan; ZOU Minghu
2007-01-01
The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.
Optimization parameter design of a circular e+e-Higgs factory
Institute of Scientific and Technical Information of China (English)
WANG Dou; GAO Jie; XIAO Ming; GENG Hui-Ping; GUO Yuan-Yuan; XU Shou-Yan; WANG Na
2013-01-01
In this paper we will show a general method of how to make an optimized parameter design of a circular e+e-Higgs factory by using analytical expression of maximum beam-beam parameter and beamstrahlung beam lifetime starting from a given design goal and technical limitations.A parameter space has been explored.Based on beam parameters scan and RF parameters scan,a set of optimized parameter designs for 50 km Circular Higgs Factory (CHF) with different RF frequency was proposed.
Determination of dispersion parameters of thermally deposited CdTe thin film
Dhimmar, J. M.; Desai, H. N.; Modi, B. P.
2016-05-01
Cadmium Telluride (CdTe) thin film was deposited onto glass substrates under a vacuum of 5 × 10-6 torr by using thermal evaporation technique. The prepared film was characterized for dispersion analysis from reflectance spectra within the wavelength range of 300 nm - 1100 nm which was recorded by using UV-Visible spectrophotometer. The dispersion parameters (oscillator strength, oscillator wavelength, high frequency dielectric constant, long wavelength refractive index, lattice dielectric constant and plasma resonance frequency) of CdTe thin film were investigated using single sellimeir oscillator model.
AN IMPROVED GENETIC ALGORITHM FOR SEARCHING OPTIMAL PARAMETERS IN n—DIMENSIONAL SPACE
Institute of Scientific and Technical Information of China (English)
TangBin; HuGuangrui
2002-01-01
An improved genetic algorithm for searching optimal parameters in n-dimensional space is presented,which encodes movement direction and distance and searches from coarse to precise.The algorithm can realize global optimization and improve the search efficiency,and can be applied effectively in industrial optimization ,data mining and pattern recognition.
AN IMPROVED GENETIC ALGORITHM FOR SEARCHING OPTIMAL PARAMETERS IN n-DIMENSIONAL SPACE
Institute of Scientific and Technical Information of China (English)
Tang Bin; Hu Guangrui
2002-01-01
An improved genetic algorithm for searching optimal parameters in n-dimensional space is presented, which encodes movement direction and distance and searches from coarse to precise. The algorithm can realize global optimization and improve the search efficiency, and can be applied effectively in industrial optimization, data mining and pattern recognition.
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...
Parameter selection of support vector machine for function approximation based on chaos optimization
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The support vector machine (SVM) is a novel machine learning method,which has the ability to approximate nonlinear functions with arbitrary accuracy.Setting parameters well is very crucial for SVM learning results and generalization ability,and now there is no systematic,general method for parameter selection.In this article,the SVM parameter selection for function approximation is regarded as a compound optimization problem and a mutative scale chaos optimization algorithm is employed to search for optimal parameter values.The chaos optimization algorithm is an effective way for global optimal and the mutative scale chaos algorithm could improve the search efficiency and accuracy.Several simulation examples show the sensitivity of the SVM parameters and demonstrate the superiority of this proposed method for nonlinear function approximation.
Parameter estimation for chaotic systems based on improved boundary chicken swarm optimization
Chen, Shaolong; Yan, Renhuan
2016-10-01
Estimating unknown parameters for chaotic system is a key problem in the field of chaos control and synchronization. Through constructing an appropriate fitness function, parameter estimation of chaotic system could be converted to a multidimensional parameter optimization problem. In this paper, a new method base on improved boundary chicken swarm optimization (IBCSO) algorithm is proposed for solving the problem of parameter estimation in chaotic system. However, to the best of our knowledge, there is no published research work on chicken swarm optimization for parameters estimation of chaotic system. Computer simulation based on Lorenz system and comparisons with chicken swarm optimization, particle swarm optimization, and genetic algorithm shows the effectiveness and feasibility of the proposed method.
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.
Tahaei, Ali; Horley, Paul; Merlin, Mattia; Torres-Torres, David; Garagnani, Gian Luca; Praga, Rolando; Vázquez, Felipe J. García; Arizmendi-Morquecho, Ana
2017-01-01
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)_3 W_3 C 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.
Optimization design of resistance spot welding parameters of magnesium alloy
Institute of Scientific and Technical Information of China (English)
Lang Bo; Sun Daqian; Wu Qiong; Xuan Zhaozhi
2008-01-01
By means of the quadratic regression combination design process, the regression equations of nugget diameter and tensile shear load of spot welded joint were established. Effects of welding parameters on the nugget diameter and the tensile shear load were investigated. The results show that effect of welding current on nugget diameter is the most evident. And higher welding current will result in bigger nugget diameter. Besides, interaction effect of electrode force and welding current on tensile shear load is the most evident compared with others. The optimum welding parameters corresponding to the maximum of tensile shear load have been obtained by programming using Matlab software, which is 4.7kN electrode force, 28kA welding current and 4 cycle welding time. Under the condition of the optimum welding parameters, the joint having no visible defects can be obtained, nugget diameter and tensile shear load being 6.8mm and 3 256N, respectively.
Kar, Siddhartha; Chakraborty, Sujoy; Dey, Vidyut; Ghosh, Subrata Kumar
2016-06-01
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.
Parameter optimization of temperature field in RF-capacitive hyperthermia
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
To realize a certain target temperature distribution in tumor tissues and avoid over-heating in normal tissues in radio frequency (RF)-capacitive hyperthermia, an objective function and some weight coefficients are introduced. Then using the 2-D finite element method, the electromagnetic and bio-heat transfer equations are solved, and using the genetic algorithm the heating configurations are recursively modified to minimize the objective function. Finally an optimum solution of the expected heating field distribution in hyperthermia is achieved. And with a human heterogeneous tissue model extracted from X-ray CT images, satisfactory optimization results are obtained in the simulations on a biplate RF-capacitive hyperthermia device. This optimization technique for controlling the body temperature field has shown scientific importance and practical values in the research of hyperthermia.
Optimization of electrical stimulation parameters for cardiac tissue engineering.
Tandon, Nina; Marsano, Anna; Maidhof, Robert; Wan, Leo; Park, Hyoungshin; Vunjak-Novakovic, Gordana
2011-06-01
In vitro application of pulsatile electrical stimulation to neonatal rat cardiomyocytes cultured on polymer scaffolds has been shown to improve the functional assembly of cells into contractile engineered cardiac tissues. However, to date, the conditions of electrical stimulation have not been optimized. We have systematically varied the electrode material, amplitude and frequency of stimulation to determine the conditions that are optimal for cardiac tissue engineering. Carbon electrodes, exhibiting the highest charge-injection capacity and producing cardiac tissues with the best structural and contractile properties, were thus used in tissue engineering studies. Engineered cardiac tissues stimulated at 3 V/cm amplitude and 3 Hz frequency had the highest tissue density, the highest concentrations of cardiac troponin-I and connexin-43 and the best-developed contractile behaviour. These findings contribute to defining bioreactor design specifications and electrical stimulation regime for cardiac tissue engineering.
Optimization of control parameters for petroleum waste composting
Institute of Scientific and Technical Information of China (English)
无
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.
Design of Digital Imaging System for Optimization of Control Parameters
Institute of Scientific and Technical Information of China (English)
SONG Yong; HAO Qun; YANG Guang; SUN Hong-wei
2007-01-01
The design of experimental system of digital imaging system for control parameter is discussed in detail. Signal processing of digital CCD imaging system is first analyzed. Then the real time control of CCD driver and digital processing circuit and man-machine interaction are achieved by the design of digital CCD imaging module and control module. Experimental results indicate that the image quality of CCD experimental system makes a good response to the change of control parameters. The system gives an important base for improving image quality and the applicability of micro imaging system in complex environment.
Directory of Open Access Journals (Sweden)
Sukanta Nama
2016-04-01
Full Text Available Differential evolution (DE is an effective and powerful approach and it has been widely used in different environments. However, the performance of DE is sensitive to the choice of control parameters. Thus, to obtain optimal performance, time-consuming parameter tuning is necessary. Backtracking Search Optimization Algorithm (BSA is a new evolutionary algorithm (EA for solving real-valued numerical optimization problems. An ensemble algorithm called E-BSADE is proposed which incorporates concepts from DE and BSA. The performance of E-BSADE is evaluated on several benchmark functions and is compared with basic DE, BSA and conventional DE mutation strategy.
Optimization of technological parameters for preparation of lycopene microcapsules
Guo, Hui; Huang, Ying; Qian, Jun-qing; Gong, Qiu-yi; Tang, Ying
2012-01-01
Lycopene belongs to the carotenoid family with high degree of unsaturation and all-trans form. Lycopene is easy to isomerize and auto oxide by heat, light, oxygen and different food matrices. With an increasing understanding of the health benefit of lycopene, to enhance stability and bioavailability of lycopene, ultrasonic emulsification was used to prepare lycopene microcapsules in this article. The results optimized by response surface methodology (RSM) for microcapsules consisted of four m...
Design optimization on the front wheel orientation parameters of a vehicle
Institute of Scientific and Technical Information of China (English)
CHU Zhigang; DENG Zhaoxiang; HU Yumei; ZHU Ming
2003-01-01
A uniform optimization object function for front wheel orientation parameters of a vehicle is reported, which includes the tolerances of practical values and set values of front wheel orientation parameters under full load, and the changing value of each parameter with front wheel fluctuation to build a front suspension model for optimization analysis based on the multi-body dynamic (MD) theory. The original suspension is optimized with this model, and the variation law of each parameter with front wheel fluctuation is obtained. The results of a case study demonstrate that the front wheel orientation parameters of the optimized vehicle are reasonable under typical conditions and the variation of each parameter is in an ideal range with the wheel fluctuating within ±40 mm. In addition, the driving performance is improved greatly in the road test and practical use.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
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.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
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.
The Influence of Process Parameters on Properties of Conversion Coatings Deposited on Titanium Alloy
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Karaś M.
2016-03-01
Full Text Available The effect of process parameters of conversion coatings on the corrosion resistance was investigated. To produce anodic coatings, the solutions of H2SO4 of 0.5 and 1 M concentrations and current densities of 0.5 and 1 A/dm2 were applied. The coatings were deposited by galvanostatic technique on titanium Grade 1. The result of the study was comparison of the corrosion resistance of coatings produced under varying parameters such as: the anodic current density, the electrolyte concentration, and the speed of reaching the preset voltage. Corrosion tests performed by potentiodynamic polarization test have shown that even nanometric anodic films of amorphous structure improve the corrosion resistance of titanium alloy. The lowest corrosion current and the corrosion potential of the most cathodic nature were observed in the sample with anodic coating produced at J = 1 A/dm2 in a 0.5 M H2SO4 electrolyte concentration.
Roller, Justin M.; Maric, Radenka
2015-12-01
Catalytic materials are complex systems in which achieving the desired properties (i.e., activity, selectivity and stability) depends on exploiting the many degrees of freedom in surface and bulk composition, geometry, and defects. Flame aerosol synthesis is a process for producing nanoparticles with ample processing parameter space to tune the desired properties. Flame dynamics inside the reactor are determined by the input process variables such as solubility of precursor in the fuel; solvent boiling point; reactant flow rate and concentration; flow rates of air, fuel and the carrier gas; and the burner geometry. In this study, the processing parameters for reactive spray deposition technology, a flame-based synthesis method, are systematically evaluated to understand the residence times, reactant mixing, and temperature profiles of flames used in the synthesis of Pt nanoparticles. This provides a framework for further study and modeling. The flame temperature and length are also studied as a function of O2 and fuel flow rates.
Ion beam sputter deposition of Ge films: Influence of process parameters on film properties
Energy Technology Data Exchange (ETDEWEB)
Bundesmann, C., E-mail: carsten.bundesmann@iom-leipzig.de [Leibniz-Institut für Oberflächenmodifizierung e.V., Permoserstrasse 15, 04318 Leipzig (Germany); Feder, R. [Leibniz-Institut für Oberflächenmodifizierung e.V., Permoserstrasse 15, 04318 Leipzig (Germany); Wunderlich, R.; Teschner, U.; Grundmann, M. [Universität Leipzig, Fakultät für Physik und Geowissenschaften, Institut für Experimentelle Physik II, Linnéstrasse 5, 04103 Leipzig (Germany); Neumann, H. [Leibniz-Institut für Oberflächenmodifizierung e.V., Permoserstrasse 15, 04318 Leipzig (Germany)
2015-08-31
Several sets of Ge films were grown by ion beam sputter deposition under systematic variation of ion beam parameters (ion species and ion energy) and geometrical parameters (ion incidence angle and polar emission angle). The films were characterized concerning thickness, growth rate, mass density, structural properties and composition. The film thicknesses show a cosine-like angular distribution, and the growth rates were found to increase with increasing ion incidence angle and ion energy. All films are amorphous and the average mass density was found to be (4.3 ± 0.2) g/cm{sup 3}, without a systematic relation to ion energy and geometrical parameters. Slightly higher mass densities were found for Ge films grown by sputtering with Xe than for sputtering with Ar. The Ge films contain a fraction of inert gas atoms from backscattered primary particles. This fraction is found to be higher for sputtering with Ar than for sputtering with Xe. The fraction of inert gas atoms increases with increasing polar emission angle and increasing ion incidence angle. Raman scattering experiments revealed also systematic shifts of the characteristic Raman mode. The shifts are tentatively assigned to the change of the Ge particle densities caused by the incorporation of inert gas particles. There seem to be also slight changes in short range ordering. The experimental data are discussed with respect to the known energy and angular distributions of the sputtered and backscattered particles. - Highlights: • Ion beam sputter deposition under systematic variation of process parameters • Thickness, growth rate, mass density, composition, structure, phonon properties • All germanium films are amorphous with small variations in mass density. • Incorporation of considerable amount of inert process gas • Vibrational properties correlate with composition.
Automatic Optimization of Alignment Parameters for Tomography Datasets
Bleichrodt, F.; Batenburg, K.J.; Kämäräinen, J.-K.; Koskela, M.
2013-01-01
As tomographic imaging is being performed at increasingly smaller scales, the stability of the scanning hardware is of great importance to the quality of the reconstructed image. Instabilities lead to perturbations in the geometrical parameters used in the acquisition of the projections. In partic
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.
PLAN’S PARAMETERS OF ELEMENTS OPTIMIZATION IN CLASSIFICATION TRACKS
Directory of Open Access Journals (Sweden)
V. I. Bobrovskyi
2010-12-01
Full Text Available The method of determination of optimum parameters of connecting curves on marshalling tracks, which insure the minimum distance from the first bunch switch to the seating of park car retarders is developed. This method can be applied in designing the plan of marshalling tracks.
Institute of Scientific and Technical Information of China (English)
Youlong XIA; Zong-Liang YANG; Paul L. STOFFA; Mrinal K. SEN
2005-01-01
Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI)to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.
A.Thillaivanan,; P. Asokan,; K.N.Srinivasan,; Saravanan, R.
2010-01-01
In this paper the complexity of electrical discharge machining process which is very difficult to determine optimal cutting parameters for improving cutting performance has been reported. Optimization of operating parameters is an important step in machining, particularly for operating unconventional machiningprocedure like EDM. A suitable selection of machining parameters for the electrical discharge machining process relies heavily on the operators’ technologies and experience because of th...
Optimization of mean-shift scale parameters on the EGEE grid.
Li, Ting; Camarasu-Pop, Sorina; Glatard, Tristan; Grenier, Thomas; Benoit-Cattin, Hugues
2010-01-01
This paper studies the optimization of Mean-Shift (MS) image filtering scale parameters. A parameter sweep experiment representing 164 days of CPU is performed on the EGEE grid. The mathematical foundations of Mean-Shift and the grid environment used for the deployment are described in details. The experiments and results are then discussed highlighting the efficiency of gradient ascent algorithm for MS parameters optimization and a number of grid observations related to data transfers, reliability, task scheduling, CPU time and usability.
Structural studies of ZnO nanostructures by varying the deposition parameters
Yunus, S. H. A.; Sahdan, M. Z.; Ichimura, M.; Supee, A.; Rahim, S.
2017-01-01
The effect of Zinc Oxide (ZnO) thin film on the growth of ZnO nanorods (NRs) was investigated. The structures of ZnO NRs were synthesized by chemical bath deposition (CBD) method in aqueous solution of N2O6Zn.6H2O and C6H12N4 at 90°C of deposition temperature. One of the ZnO NRs samples was deposited on a ZnO seed layer coated on a glass substrate to investigate the properties of ZnO NRs without receiving effect of other materials. Next, for diode application, the ZnO NRs was deposited on tin monosulfide (SnS) coated on indium-tin-oxide (ITO) coated glass substrate (SnS/ITO). The next, the ZnO structural properties were studied from surface morphology, X-ray diffractometer (XRD) spectra, and chemical composition by using field emission scanning electron microscope (FESEM), XRD and energy dispersive X-ray Spectroscopy (EDX). The growth of ZnO NRs on ZnO seed layer was investigated by ZnO seed layer condition while the growth of ZnO NRs on SnS/ITO was investigated by deposition time and deposition temperature parameters. From FESEM images, aligned ZnO NRs were obtained, and the diameters of ZnO NRs were 0.024-3.94 µm. The SnS thin film was affected by the diameter of ZnO NRs which are the ZnO NRs grow on SnS thin films has a larger diameter compared to ZnO NRs grow on ZnO seed layer. Besides that, all of ZnO peaks observed from XRD corresponding to the wurzite structure and preferentially oriented along the c-axis. In addition, EDX shows a high composition of zinc (Zn) and oxygen (O) signals, which indicated that the NRs are indeed made up of Zn and O.
Study of deposition parameters for the fabrication of ZnO thin films using femtosecond laser
Hashmi, Jaweria Zartaj; Siraj, Khurram; Latif, Anwar; Murray, Mathew; Jose, Gin
2016-08-01
Femtosecond (fs) pulsed laser deposition (fs-PLD) of ZnO thin film on borosilicate glass substrates is reported in this work. The effect of important fs-PLD parameters such as target-substrate distance, laser pulse energy and substrate temperature on structure, morphology, optical transparency and luminescence of as-deposited films is discussed. XRD analysis reveals that all the films grown using the laser energy range 120-230 μJ are polycrystalline when they are deposited at room temperature in a ~10-5 Torr vacuum. Introducing 0.7 mTorr oxygen pressure, the films show preferred c-axis growth and transform into a single-crystal-like film when the substrate temperature is increased to 100 °C. The scanning electron micrographs show the presence of small nano-size grains at 25 °C, which grow in size to the regular hexagonal shape particles at 100 °C. Optical transmission of the ZnO film is found to increase with an increase in crystal quality. Maximum transmittance of 95 % in the wavelength range 400-1400 nm is achieved for films deposited at 100 °C employing a laser pulse energy of 180 μJ. The luminescence spectra show a strong UV emission band peaked at 377 nm close to the ZnO band gap. The shallow donor defects increase at higher pulse energies and higher substrate temperatures, which give rise to violet-blue luminescence. The results indicate that nano-crystalline ZnO thin films with high crystalline quality and optical transparency can be fabricated by using pulses from fs lasers.
Optimal Parameter Tuning in a Predictive Nonlinear Control Method for a Mobile Robot
Directory of Open Access Journals (Sweden)
D. Hazry
2006-01-01
Full Text Available This study contributes to a new optimal parameter tuning in a predictive nonlinear control method for stable trajectory straight line tracking with a non-holonomic mobile robot. In this method, the focus lies in finding the optimal parameter estimation and to predict the path that the mobile robot will follow for stable trajectory straight line tracking system. The stability control contains three parameters: 1 deflection parameter for the traveling direction of the mobile robot 2 deflection parameter for the distance across traveling direction of the mobile robot and 3 deflection parameter for the steering angle of the mobile robot . Two hundred and seventy three experimental were performed and the results have been analyzed and described herewith. It is found that by using a new optimal parameter tuning in a predictive nonlinear control method derived from the extension of kinematics model, the movement of the mobile robot is stabilized and adhered to the reference posture
Optimization of Process Parameters of Tool Wear in Turning Operation
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Manik Barman
2015-04-01
Full Text Available Tool Wear is of great apprehension in machining industries since itaffects the surface quality, dimensional accuracy and production cost of the materials / components. In the present study twenty seven experiments were conducted as per 3 parameter 3 level full factorial design for turning operation of a mild steel specimen with high speed steel (HSS cutting tool. An experimental investigation on cutting tool wear and a mathematical model for tool wear estimation is reported in this paper where the model was simulated by computer programming and it has been found that this model is capable of estimating the wear rate of cutting tool and it provides an optimum set of process parameters for minimum tool wear.
Method for Predicting and Optimizing System Parameters for Electrospinning System
Wincheski, Russell A. (Inventor)
2011-01-01
An electrospinning system using a spinneret and a counter electrode is first operated for a fixed amount of time at known system and operational parameters to generate a fiber mat having a measured fiber mat width associated therewith. Next, acceleration of the fiberizable material at the spinneret is modeled to determine values of mass, drag, and surface tension associated with the fiberizable material at the spinneret output. The model is then applied in an inversion process to generate predicted values of an electric charge at the spinneret output and an electric field between the spinneret and electrode required to fabricate a selected fiber mat design. The electric charge and electric field are indicative of design values for system and operational parameters needed to fabricate the selected fiber mat design.
Optimizing the Yb:YAG thin disc laser design parameters
Javadi-Dashcasan, M.; Hajiesmaeilbaigi, F.; Razzaghi, H.; Mahdizadeh, M.; Moghadam, M.
2008-09-01
Based on quasi-three-level system, a numerical model of continuous wave thin disc laser is proposed. The fluorescence concentration quenching (FCQ), refractive index depending concentration effects and temperature distribution in the gain medium have been taken into account in the model. The first and second phenomena are not included in previously models. The model is used to determine optimum design parameters and to calculate the influence of various parameters like temperature, number of pump beam passes, active ions concentration and the crystal thickness on the operational efficiency of the laser. This model shows that for higher doping concentrations (>15%) the optical efficiency is decreased due to fluorescence concentration quenching. Our results are excellently in agreement with experimental results.
GEANT4 for breast dosimetry: parameters optimization study.
Fedon, C; Longo, F; Mettivier, G; Longo, R
2015-08-21
Mean glandular dose (MGD) is the main dosimetric quantity in mammography. MGD evaluation is obtained by multiplying the entrance skin air kerma (ESAK) by normalized glandular dose (DgN) coefficients. While ESAK is an empirical quantity, DgN coefficients can only be estimated with Monte Carlo (MC) methods. Thus, a MC parameters benchmark is needed for effectively evaluating DgN coefficients. GEANT4 is a MC toolkit suitable for medical purposes that offers to the users several computational choices. In this work we investigate the GEANT4 performances testing the main PhysicsLists for medical applications. Four electromagnetic PhysicsLists were implemented: the linear attenuation coefficients were calculated for breast glandularity 0%, 50%, 100% in the energetic range 8-50 keV and DgN coefficients were evaluated. The results were compared with published data. Fit equations for the estimation of the G-factor parameter, introduced by the literature for converting the dose delivered in the heterogeneous medium to that in the glandular tissue, are proposed and the application of this parameter interaction-by-interaction or retrospectively is discussed. G4EmLivermorePhysicsList shows the best agreement for the linear attenuation coefficients both with theoretical values and published data. Moreover, excellent correlation factor (r2>0.99) is found for the DgN coefficients with the literature. The final goal of this study is to identify, for the first time, a benchmark of parameters that could be useful for future breast dosimetry studies with GEANT4.
Towards optimal cosmological parameter recovery from compressed bispectrum statistics
Byun, Joyce; Eggemeier, Alexander; Regan, Donough; Seery, David; Smith, Robert E.
2017-10-01
Over the next decade, improvements in cosmological parameter constraints will be driven by surveys of a large-scale structure in the Universe. The information they contain can be measured by suitably chosen correlation functions, and the non-linearity of structure formation implies that significant information will be carried by the 3-point function or higher correlators. Extracting this information is extremely challenging, requiring accurate modelling and significant computational resources to estimate the covariance matrix describing correlation between different Fourier configurations. We investigate whether it is possible to reduce this matrix without significant loss of information by using a proxy that aggregates the bispectrum over a subset of configurations. Specifically, we study constraints on ΛCDM parameters from a future galaxy survey combining the power spectrum with (a) the integrated bispectrum, (b) the line correlation function and (c) the modal decomposition of the bispectrum. We include a simple estimate for the degradation of the bispectrum with shot noise. Our results demonstrate that the modal bispectrum has comparable performance to the Fourier bispectrum, even using considerably fewer modes than Fourier configurations. The line correlation function has good performance, but is less effective. The integrated bispectrum is comparatively insensitive to the background cosmology. Addition of bispectrum data can improve constraints on bias parameters and σ8 by a factor between 3 and 5 compared to power spectrum measurements alone. For other parameters, improvements of up to ∼20 per cent are possible. Finally, we use a range of theoretical models to explore the sophistication required to produce realistic predictions for each proxy.
Relationships among various parameters for decision tree optimization
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.
Optimization of technological parameters for preparation of lycopene microcapsules.
Guo, Hui; Huang, Ying; Qian, Jun-Qing; Gong, Qiu-Yi; Tang, Ying
2014-07-01
Lycopene belongs to the carotenoid family with high degree of unsaturation and all-trans form. Lycopene is easy to isomerize and auto oxide by heat, light, oxygen and different food matrices. With an increasing understanding of the health benefit of lycopene, to enhance stability and bioavailability of lycopene, ultrasonic emulsification was used to prepare lycopene microcapsules in this article. The results optimized by response surface methodology (RSM) for microcapsules consisted of four major steps: (1) 0.54 g glycerin monostearate was fully dissolved in 5 mL ethyl acetate and then added 0.02 g lycopene to form an organic phase, 100.7 mL distilled water which dissolved 0.61 g synperonic pe(R)/F68 as the aqueous phase; (2) the organic phase was pulled into the aqueous phase under stirring at 60 °C water bath for 5 min; (3) the mixture was then ultrasonic homogenized at 380 W for 20 min to form a homogenous emulsion; (4) the resulting emulsion was rotary evaporated at 50 °C water bath for 10 min under a pressure of 20 MPa. Encapsulation efficiency (EE) of lycopene microcapsules under the optimized conditions approached to 64.4%.
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan
Directory of Open Access Journals (Sweden)
Hung-Chang Liao
2014-01-01
Full Text Available This study proposed the optimal parameter settings for the hospital supply chain system (HSCS when either the total system cost (TSC or patient safety level (PSL (or both simultaneously was considered as the measure of the HSCS’s performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM was used to construct the regression model, and a genetic algorithm (GA was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers.
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Optimization of design parameters of low-energy buildings
Vala, Jiří; Jarošová, Petra
2017-07-01
Evaluation of temperature development and related consumption of energy required for heating, air-conditioning, etc. in low-energy buildings requires the proper physical analysis, covering heat conduction, convection and radiation, including beam and diffusive components of solar radiation, on all building parts and interfaces. The system approach and the Fourier multiplicative decomposition together with the finite element technique offers the possibility of inexpensive and robust numerical and computational analysis of corresponding direct problems, as well as of the optimization ones with several design variables, using the Nelder-Mead simplex method. The practical example demonstrates the correlation between such numerical simulations and the time series of measurements of energy consumption on a small family house in Ostrov u Macochy (35 km northern from Brno).
Directory of Open Access Journals (Sweden)
Dorin Sendrescu
2013-01-01
Full Text Available This paper deals with the offline parameters identification for a class of wastewater treatment bioprocesses using particle swarm optimization (PSO techniques. Particle swarm optimization is a relatively new heuristic method that has produced promising results for solving complex optimization problems. In this paper one uses some variants of the PSO algorithm for parameter estimation of an anaerobic wastewater treatment process that is a complex biotechnological system. The identification scheme is based on a multimodal numerical optimization problem with high dimension. The performances of the method are analyzed by numerical simulations.
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.
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
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.
Measuring Digital PCR Quality: Performance Parameters and Their Optimization.
Lievens, A; Jacchia, S; Kagkli, D; Savini, C; Querci, M
2016-01-01
Digital PCR is rapidly being adopted in the field of DNA-based food analysis. The direct, absolute quantification it offers makes it an attractive technology for routine analysis of food and feed samples for their composition, possible GMO content, and compliance with labelling requirements. However, assessing the performance of dPCR assays is not yet well established. This article introduces three straightforward parameters based on statistical principles that allow users to evaluate if their assays are robust. In addition, we present post-run evaluation criteria to check if quantification was accurate. Finally, we evaluate the usefulness of Poisson confidence intervals and present an alternative strategy to better capture the variability in the analytical chain.
Measuring Digital PCR Quality: Performance Parameters and Their Optimization.
Directory of Open Access Journals (Sweden)
A Lievens
Full Text Available Digital PCR is rapidly being adopted in the field of DNA-based food analysis. The direct, absolute quantification it offers makes it an attractive technology for routine analysis of food and feed samples for their composition, possible GMO content, and compliance with labelling requirements. However, assessing the performance of dPCR assays is not yet well established. This article introduces three straightforward parameters based on statistical principles that allow users to evaluate if their assays are robust. In addition, we present post-run evaluation criteria to check if quantification was accurate. Finally, we evaluate the usefulness of Poisson confidence intervals and present an alternative strategy to better capture the variability in the analytical chain.
Optimal FES parameters based on mechanomyographic efficiency index.
Krueger-Beck, Eddy; Scheeren, Eduardo M; Nogueira-Neto, Guilherme N; Button, Vera Lucia S N; Nohama, Percy
2010-01-01
Functional electrical stimulation (FES) can artificially elicit movements in spinal cord injured (SCI) subjects. FES control strategies involve monitoring muscle features and setting FES profiles so as to postpone the installation of muscle fatigue or nerve cell adaptation. Mechanomyography (MMG) sensors register the lateral oscillations of contracting muscles. This paper presents an MMG efficiency index (EI) that may indicate most efficient FES electrical parameters to control functional movements. Ten healthy and three SCI volunteers participated in the study. Four FES profiles with two FES sessions were applied with in-between 15min rest interval. MMG RMS and median frequency were inserted into the EI equation. EI increased along the test. FES profile set to 1kHz pulse frequency, 200εs active pulse duration and burst frequency of 50Hz was the most efficient.
1000 MW ultra-supercritical turbine steam parameter optimization
Institute of Scientific and Technical Information of China (English)
2008-01-01
The 2 ×1000 MW ultra-supercritical steam turbine of Shanghai Waigaoqiao Phase Ⅲ project,which uses grid frequency regulation and overload control through an overload valve,is manufactured by Shanghai Turbine Company using Siemens technology.Through optimization,the steam pressure is regarded as the criterion between constant pressure and sliding pressure operation.At high circulating water temperature,the turbine overload valve is kept closed when the unit load is lower than 1000 MW while at other circulating water temperatures the turbine can run in sliding pressure operation when the unit load is higher than 1000 MW and the pressure is lower than 27 MPa This increases the unit operation efficiency.The 3D bending technology in the critical piping helps to reduce the project investment and minimize the reheat system pressure drop which improves the unit operation efficiency and safety.By choosing lower circulating water design temperature and by setting the individual Boiler Feedwater Turbine condenser to reduce the exhaust steam flow and the heat load to the main condenser,the unit average back pressure and the terminal temperature difference are minimized.Therefore,the unit heat efficiency is increased.
To denoise or deblur: parameter optimization for imaging systems
Mitra, Kaushik; Cossairt, Oliver; Veeraraghavan, Ashok
2014-03-01
In recent years smartphone cameras have improved a lot but they still produce very noisy images in low light conditions. This is mainly because of their small sensor size. Image quality can be improved by increasing the aperture size and/or exposure time however this make them susceptible to defocus and/or motion blurs. In this paper, we analyze the trade-off between denoising and deblurring as a function of the illumination level. For this purpose we utilize a recently introduced framework for analysis of computational imaging systems that takes into account the effect of (1) optical multiplexing, (2) noise characteristics of the sensor, and (3) the reconstruction algorithm, which typically uses image priors. Following this framework, we model the image prior using Gaussian Mixture Model (GMM), which allows us to analytically compute the Minimum Mean Squared Error (MMSE). We analyze the specific problem of motion and defocus deblurring, showing how to find the optimal exposure time and aperture setting as a function of illumination level. This framework gives us the machinery to answer an open question in computational imaging: To deblur or denoise?.
Critical parameters for optimal biomass refineries: the case of biohydrogen
Energy Technology Data Exchange (ETDEWEB)
Koukios, Emmanuel; Koullas, Dimitrios; Koukios, Irene Daouti; Avgerinos, Emmanouil [National Technical University of Athens, Bioresource Technology Unit, School of Chemical Engineering, Athens (Greece)
2010-04-15
The object of this paper is to identify and assess the elements taken from agro-industries and fossil hydrocarbon refineries, especially with respect to biomass logistics, fractionation kinetics, and process energetics. Such critical information will be of immediate use by policy and decision makers, especially in the early phase of planning and designing the first generation of biorefineries. Concerning feedstock logistics, biorefineries have a lot to learn from food and wood supply chains. This learning could lead to the deployment of complex, decentralised, stage-wise biorefining systems, consisting of local agro-refineries, regional biorefineries, where the primary plant fractions are processed and upgraded to useful intermediates, and central bioconversion units for the generation of market-grade biofuels, such as biohydrogen and other high value-added vectors. The kinetic aspects of biorefineries are related to the physico-chemical nature of the macromolecules. Finally, to solve the problem of the non-optimal energy transformations a tailored-up bioenergy plan is proposed for each biorefinery. The example of a wheat bran-based biorefinery, aiming at the production of biohydrogen will be used to illustrate the way ahead. (orig.)
Energy Technology Data Exchange (ETDEWEB)
MoberlyChan, W J; Schalek, R
2007-11-08
Ion beams of sufficient energy to erode a surface can lead to surface modulations that depend on the ion beam, the material surface it impinges, and extrinsic parameters such as temperature and geometric boundary conditions. Focused Ion Beam technology both enables site-specific placement of these modulations and expedites research through fast, high dose and small efficient use of material. The DualBeam (FIB/SEM) enables in situ metrology, with movies observing ripple formation, wave motion, and the influence of line defects. Nanostructures (ripples of >400nm wavelength to dots spaced <40nm) naturally grow from atomically flat surfaces during erosion, however, a steady state size may or may not be achieved as a consequence of numerous controlled parameters: temperature, angle, energy, crystallography. Geometric factors, which can be easily invoked using a FIB, enable a controlled component of deposition (and/or redeposition) to occur during erosion, and conversely allow a component of etching to be incurred during (ion-beam assisted) deposition. High angles of ion beam inclination commonly lead to 'rougher' surfaces, however, the extreme case of 90.0{sup o} etching enables deposition of organized structures 1000 times smaller than the aforementioned, video-recorded nanostructures. Orientation and position of these picostructures (naturally quantized by their atomic spacings) may be controlled by the same parameters as for nanostructures (e.g. ion inclination and imposed boundary conditions, which are flexibly regulated by FIB). Judicious control of angles during FIB-CVD growth stimulates erosion with directionality that produces surface modulations akin to those observed for sputtering. Just as a diamond surface roughens from 1-D ripples to 2-D steps with increasing angle of ion sputtering, so do ripples and steps appear on carbon-grown surfaces with increase in angle of FIB-CVD. Ion beam processing has been a stalwart of the microelectronics industry
Directory of Open Access Journals (Sweden)
KOTSUR, M.
2015-05-01
Full Text Available We give a solution of optimal control problem for distributed parameter systems described by nonlinear partial differential equations with nonstandard boundary conditions. The variational method is used to obtain the general form of the necessary conditions of optimality. A suitable algorithm based on the numerical method of successive approximations has been constructed for computing the optimal control functions. The results are applied for optimization of transient thermoelectric cooling process. Optimal dependences of current on time have been calculated for thermoelectric cooler power supply with the purpose of minimizing the cooling temperature within a preset time interval.
Institute of Scientific and Technical Information of China (English)
Bian Yushu; Gao Zhihui
2013-01-01
Parameter optimization of the controllable local degree of freedom is studied for reducing vibration of the flexible manipulator at the lowest possible cost.The controllable local degrees of freedom are suggested and introduced to the topological structure of the flexible manipulator,and used as an effective way to alleviate vibration through dynamic coupling.Parameters introduced by the controllable local degrees of freedom are analyzed and their influences on vibration reduction are investigated.A strategy to optimize these parameters is put forward and the corresponding optimization method is suggested based on Particle Swarm Optimization (PSO).Simulations are conducted and results of case studies confirm that the proposed optimization method is effective in reducing vibration of the flexible manipulator at the lowest possible cost.
Zang, Xizhe; Liu, Xinyu; Zhu, Yanhe; Zhao, Jie
2016-04-29
The study of human walking patterns mainly focuses on how control affects walking because control schemes are considered to be dominant in human walking. This study proposes that not only fine control schemes but also optimized body segment parameters are responsible for humans' low-energy walking. A passive dynamic walker provides the possibility of analyzing the effect of parameters on walking efficiency because of its ability to walk without any control. Thus, a passive dynamic walking model with a relatively human-like structure was built, and a parameter optimization process based on the gait sensitivity norm was implemented to determine the optimal mechanical parameters by numerical simulation. The results were close to human body parameters, thus indicating that humans can walk under a passive pattern based on their body segment parameters. A quasi-passive walking prototype was built on the basis of the optimization results. Experiments showed that a passive robot with optimized parameters could walk on level ground with only a simple hip actuation. This result implies that humans can walk under a passive pattern based on their body segment parameters with only simple control strategy implying that humans can opt to walk instinctively under a passive pattern.
MULTI-OBJECTIVE OPTIMIZATION OF EDM PARAMETERS USING GREY RELATION ANALYSIS
Directory of Open Access Journals (Sweden)
N. RADHIKA
2015-01-01
Full Text Available This paper involves the multi-objective optimization of process parameters of AlSi10Mg/9 wt% alumina/3 wt% graphite in Electrical Discharge Machining for obtaining minimum surface roughness, minimum tool wear rate and maximum material removal rate. The important machining parameters were selected as peak current, flushing pressure and pulse-on time. Experiments were conducted by selecting different operating levels for the three parameters according to Taguchi’s Design of Experiments. The multi-objective optimization was performed using Grey Relation Analysis to determine the optimal solution. The Grey Relation Grade values were then analysed using Analysis of Variance to determine the most contributing input parameter. On analysis it was found that peak current, flushing pressure and pulse-on time had an influence of 61.36%, 17.81% and 8.09% respectively on the optimal solution.
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.
Optimization of parameters on material removal rate in micro-WEDG ...
African Journals Online (AJOL)
International Journal of Engineering, Science and Technology ... Optimization of parameters on material removal rate in micro-WEDG process ... nonconventional machining method for manufacturing accurate and complex three dimensional ...
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
Rao, K. Gowrish; Ashith, V. K.
2015-02-01
Polycrystalline CdS films were obtained by a micro-controlled SILAR deposition technique, using aqueous solutions of cadmium acetate and thiourea as precursors. The structural and optical properties of the films were found to be influenced by various deposition parameters such as number of immersion cycles, concentration of the precursors and temperature of the solutions. Contrary to the observations made by some researchers, we found that the thickness of the films increased continuously with number of immersion cycles and also with concentration of the precursor solutions. We also found that the films covered the substrates uniformly, without any voids, unlike the films obtained by others. Effect of deposition parameters on thickness, substrate coverage, grain size, chemical composition, optical band gap and other properties of the films is discussed in detail.
Institute of Scientific and Technical Information of China (English)
WANG Bo; HUO Zhenhua
2013-01-01
An extension of the conditional nonlinear optimal parameter perturbation (CNOP-P) method is applied to the parameter optimization of the Common Land Model (CoLM) for the North China Plain with the differential evolution (DE) method.Using National Meteorological Center (NMC) Reanalysis 6-hourly surface flux data and National Center for Environmental Prediction/Department of Energy (NCEP/DOE)Atmospheric Model Intercomparison Project II (AMIP-II) 6-hourly Reanalysis Gaussian Grid data,two experiments (I and II) were designed to investigate the impact of the percentages of sand and clay in the shallow soil in CoLM on its ability to simulate shallow soil moisture.A third experiment (III) was designed to study the shallow soil moisture and latent heat flux simultaneously.In all the three experiments,after the optimization stage,the percentages of sand and clay of the shallow soil were used to predict the shallow soil moisture in the following month.The results show that the optimal parameters can enable CoLM to better simulate shallow soil moisture,with the simulation results of CoLM after the double-parameter optimal experiment being better than the single-parameter optimal experiment in the optimization slot.Furthermore,the optimal parameters were able to significantly improve the prediction results of CoLM at the prediction stage.In addition,whether or not the atmospheric forcing and observational data are accurate can seriously affect the results of optimization,and the more accurate the data are,the more significant the results of optimization may be.
An adaptive image denoising method based on local parameters optimization
Indian Academy of Sciences (India)
Hari Om; Mantosh Biswas
2014-08-01
In image denoising algorithms, the noise is handled by either modifying term-by-term, i.e., individual pixels or block-by-block, i.e., group of pixels, using suitable shrinkage factor and threshold function. The shrinkage factor is generally a function of threshold and some other characteristics of the neighbouring pixels of the pixel to be thresholded (denoised). The threshold is determined in terms of the noise variance present in the image and its size. The VisuShrink, SureShrink, and NeighShrink methods are important denoising methods that provide good results. The first two, i.e., VisuShrink and SureShrink methods follow term-by-term approach, i.e., modify the individual pixel and the third one, i.e., NeighShrink and its variants: ModiNeighShrink, IIDMWD, and IAWDMBMC, follow block-by-block approach, i.e., modify the pixels in groups, in order to remove the noise. The VisuShrink, SureShrink, and NeighShrink methods however do not give very good visual quality because they remove too many coefficients due to their high threshold values. In this paper, we propose an image denoising method that uses the local parameters of the neighbouring coefficients of the pixel to be denoised in the noisy image. In our method, we propose two new shrinkage factors and the threshold at each decomposition level, which lead to better visual quality. We also establish the relationship between both the shrinkage factors. We compare the performance of our method with that of the VisuShrink and NeighShrink including various variants. Simulation results show that our proposed method has high peak signal-to-noise ratio and good visual quality of the image as compared to the traditional methods:Weiner filter, VisuShrink, SureShrink, NeighBlock, NeighShrink, ModiNeighShrink, LAWML, IIDMWT, and IAWDMBNC methods.
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.
Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal
2016-11-04
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.
ZnO films deposited by optimized PLD technique with bias voltages
Energy Technology Data Exchange (ETDEWEB)
Yamaguchi, Hiroyuki; Shitara, Tamae; Komiyama, Takao; Chonan, Yasunori; Aoyama, Takashi [Department of Electronics and Information Systems, Akita Prefectural University, 84-4 Tsuchiya Ebinokuchi, 015-0055 Yuri-Honjo (Japan)
2010-02-15
The pulsed laser deposition (PLD) technique with bias voltage application for formation of high quality ZnO films was investigated. Oxygen ambient in the PLD chamber significantly decreased the photoluminescence (PL) intensity of near band edge (NBE) emission. Then, instead of using oxygen ambient, the PLD technique with bias voltage application was optimized to attain the stoichiometric composition of the ZnO films. As the deposition temperature was increased, the X-ray spectrum width diffracted from the (0002) planes was decreased and it showed a minimum value at 700 C. The PL intensity of the NBE emission also had its maximum value for the film deposited at 700 C. For the ZnO films deposited at 700 C, the X-ray spectrum width showed the minimum value under a bias voltage of -50 V. The PL intensity of the NBE emission also had a maximum value under the same bias voltage. Thus, ZnO films deposited under a bias voltage of -50 V at 700 C had strong NBE emission intensities. These results could be explained not only by attaining the stoichiometric composition of the ZnO film but also by decreasing the number of high energy O{sup 2-} ions which caused non-radiative recombination centers in the film. (copyright 2010 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
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...
Multi-parameter optimization of a neutron backscattering landmine detection system.
Metwally, Walid A
2015-11-01
A study was performed to enhance the neutron moderation and investigate the response of a landmine detection system based on measuring backscattered neutrons with a (3)He detector. Parameters affecting the system's response were simultaneously optimized to improve the sensitivity of the detection system. The optimized sensitivity of the detection system was analyzed for different horizontal and lateral positions of a landmine.
Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.
2013-07-01
Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (μGA) as an example of a stochastic approach. The optimizations were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations were conducted that differ in the model formulation ("smoothed code" versus standard code) with respect to the FD method and in the population size and number of possibilities with respect to the μGA method. The FD method fails to estimate optimal parameters due to the ill-shaped nature of the cost function caused by the strong non-linearity of the system, whereas the genetic algorithms can effectively estimate near optimal parameters. The results of the study indicate that the sophisticated stochastic approach (μGA) is of practical use for parameter optimization of a coupled ocean-sea ice model with a medium-sized horizontal resolution of 50 km × 50 km as used in this study.
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...
Determination of the optimal relaxation parameter in a numerical procedure for solitons propagation
Cirilo, Eliandro Rodrigues; Romeiro, Neyva Maria Lopes; Natti, Erica Regina Takano
2010-01-01
In this work, considering a numerical procedure developed to solve a system of coupled nonlinear complex differential equations, which describes the solitons propagation in dielectric optical fibers, we optimize the numerical processing time, in relation to the relaxation parameter of the procedure, for relevant groups of values of the dielectric variables of the optic fiber. Key-words: optical soliton, processing time, 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.
Lü, Hui; Yu, Dejie
2014-12-01
An uncertain optimization method for brake squeal reduction of vehicle disc brake system with interval parameters is presented in this paper. In the proposed method, the parameters of frictional coefficient, material properties and the thicknesses of wearing components are treated as uncertain parameters, which are described as interval variables. Attention is focused on the stability analysis of a brake system in squeal, and the stability of brake system is investigated via the complex eigenvalue analysis (CEA) method. The dominant unstable mode is extracted by performing CEA based on a linear finite element (FE) model, and the negative damping ratio corresponding to the dominant unstable mode is selected as the indicator of instability. The response surface method (RSM) is applied to approximate the implicit relationship between the unstable mode and the system parameters. A reliability-based optimization model for improving the stability of the vehicle disc brake system with interval parameters is constructed based on RSM, interval analysis and reliability analysis. The Genetic Algorithm is used to get the optimal values of design parameters from the optimization model. The stability analysis and optimization of a disc brake system are carried out, and the results show that brake squeal propensity can be reduced by using stiffer back plates. The proposed approach can be used to improve the stability of the vehicle disc brake system with uncertain parameters effectively.
Optical Parameters of Spray-Deposited CdS1- y Te y Thin Films
Ikhmayies, Shadia J.
2017-02-01
CdS x Te1- x and CdS1- y Te y solid solutions are usually formed in the interfacial region in CdS/CdTe solar cells during the deposition of the CdTe layer and/or the processing steps of the device. In this work, indium-doped CdS1- y Te y thin films were prepared by first producing CdS:In thin films by the spray pyrolysis technique on glass substrates, then annealing the films in nitrogen atmosphere in the presence of elemental tellurium. The films were characterized by scanning electron microscopy, energy dispersive x-ray spectroscopy, and transmittance measurements. The transmittance was used to deduce the reflectance from which the optical parameters were computed. The extinction coefficient, refractive index, the real and imaginary parts of the dielectric constant, optical conductivity, and energy loss were computed, and their dependence on the composition was investigated. In addition, the dispersion of the refractive index was analyzed by the single oscillator model, and dispersion parameters were investigated.
Optical Parameters of Spray-Deposited CdS1-y Te y Thin Films
Ikhmayies, Shadia J.
2016-11-01
CdS x Te1-x and CdS1-y Te y solid solutions are usually formed in the interfacial region in CdS/CdTe solar cells during the deposition of the CdTe layer and/or the processing steps of the device. In this work, indium-doped CdS1-y Te y thin films were prepared by first producing CdS:In thin films by the spray pyrolysis technique on glass substrates, then annealing the films in nitrogen atmosphere in the presence of elemental tellurium. The films were characterized by scanning electron microscopy, energy dispersive x-ray spectroscopy, and transmittance measurements. The transmittance was used to deduce the reflectance from which the optical parameters were computed. The extinction coefficient, refractive index, the real and imaginary parts of the dielectric constant, optical conductivity, and energy loss were computed, and their dependence on the composition was investigated. In addition, the dispersion of the refractive index was analyzed by the single oscillator model, and dispersion parameters were investigated.
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
Optimization of pulsed DC PACVD parameters: Toward reducing wear rate of the DLC films
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.
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.
Multi-Objective Optimization of Vehicle Suspension Parameters Considering Various Road Classes
Directory of Open Access Journals (Sweden)
Havelka Ferdinand
2014-12-01
Full Text Available Vehicle suspension optimization for various road classes travelled at different velocities is performed. Road excitation is modeled using a first order shaping filter. A half-car model is adopted to simulate the vehicle’s vertical dynamics. The excitation time delay between the rear and the front tire is modeled using Pade approximation. Suspension parameters are optimized using a random search method with respect to “comfort” and “sporty driving” considering the design constraints of the suspension and road holding and maximum suspension travel constraints. Optimal suspension parameters suitable for various road classes and vehicle velocities have been chosen.
Learning optimal spatially-dependent regularization parameters in total variation image denoising
Van Chung, Cao; De los Reyes, J. C.; Schönlieb, C. B.
2017-07-01
We consider a bilevel optimization approach in function space for the choice of spatially dependent regularization parameters in TV image denoising models. First- and second-order optimality conditions for the bilevel problem are studied when the spatially-dependent parameter belongs to the Sobolev space {{H}1}≤ft(Ω \\right) . A combined Schwarz domain decomposition-semismooth Newton method is proposed for the solution of the full optimality system and local superlinear convergence of the semismooth Newton method is verified. Exhaustive numerical computations are finally carried out to show the suitability of the approach.
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 an...... in a simply supported plane, vibrating beam model. Results show optimal number of sensors and their locations....... 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...
Basavaraj, C. K.; Vishwas, M.
2016-09-01
This paper discusses the process parameters for fused deposition modelling (FDM). Layer thickness, Orientation angle and shell thickness are the process variables considered for studies. Ultimate tensile strength, dimensional accuracy and manufacturing time are the response parameters. For number of experimental runs the taguchi's L9 orthogonal array is used. Taguchis S/N ratio was used to identify a set of process parameters which give good results for respective response characteristics. Effectiveness of each parameter is investigated by using analysis of variance. The material used for the studies of process parameter is Nylon.
Sensitivity Analysis of the Optimal Parameter Settings of an LTE Packet Scheduler
Fernandez Diaz, I.; Litjens, R.; Berg, J.L. van den; Dimitrova, D.C.; Spaey, K.
2010-01-01
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 traff
Optimization of the Automated Spray Layer-by-Layer Technique for Thin Film Deposition
2010-06-01
she was extremely busy running our household of five, homeschooling our son and volunteering. She amazes me every single day. I know that her... benefit to using solutions in excess of 80 mmol of PAA. However, at concentrations less than 80 mmol for the other standard parameter values it is...maximum film thickness. These results demonstrate that faster film deposition time is not the only benefit of Spray-LbL’s shorter polyelectrolyte to
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.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Directory of Open Access Journals (Sweden)
Kai Yit Kok
Full Text Available The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
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.
Optimal selection of regularization parameter for l1-based image restoration based on SURE
Xue, Feng; Liu, Xin; Liu, Hongyan; Liu, Jiaqi
2016-10-01
To exploit the sparsity in transform domain (e.g. wavelets), the image deconvolution can be typically formulated as a l1-penalized minimization problem, which, however, generally requires proper selection of regularization parameter for desired reconstruction quality. The key contribution of this paper is to develop a novel data-driven scheme to optimize regularization parameter, such that the resultant restored image achieves minimum prediction error (p-error). First, we develop Stein's unbiased risk estimate (SURE), an unbiased estimate of p-error, for image degradation model. Then, we propose a recursive evaluation of SURE for the basic iterative shrinkage/thresholding (IST), which enables us to find the optimal value of regularization parameter by exhaustive search. The numerical experiments show that the proposed SURE-based optimization leads to nearly optimal deconvolution performance in terms of peak signal-to-noise ratio (PSNR).
Institute of Scientific and Technical Information of China (English)
MA Wei; WANG Zheng-Ou
2003-01-01
Since there were few chaotic neural networks applicable to the global optimization, in this paper, we proposea new neural network model - chaotic parameters disturbance annealing (CPDA) network, which is superior to otherexisting neural networks, genetic algorithms, and simulated annealing algorithms in global optimization. In the presentCPDA network, we add some chaotic parameters in the energy function, which make the Hopfield neural network escapefrom the attraction of a local minimal solution and with the parameter p1 annealing, our model will converge to theglobal optimal solutions quickly and steadily. The converge ability and other characters are also analyzed in this paper.The benchmark examples show the present CPDA neuralnetwork's merits in nonlinear global optimization.
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.
Hotchkiss, G. B.; Burmeister, L. C.; Bishop, K. A.
1980-01-01
A discrete-gradient optimization algorithm is used to identify the parameters in a one-node and a two-node capacitance model of a flat-plate collector. Collector parameters are first obtained by a linear-least-squares fit to steady state data. These parameters, together with the collector heat capacitances, are then determined from unsteady data by use of the discrete-gradient optimization algorithm with less than 10 percent deviation from the steady state determination. All data were obtained in the indoor solar simulator at the NASA Lewis Research Center.
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.
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.
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.
Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong
2017-01-01
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. PMID:28257060
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Nonlinear time series prediction is studied by using an improved least squares support vector machine (LSSVM) 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.
Process Parameter Optimization of the Pulsed Current Argon Tungsten Arc Welding of Titanium Alloy
Institute of Scientific and Technical Information of China (English)
M.Balasubramanian; V.Jayabalan; V.Balasubramanian
2008-01-01
The selection of process parameters for obtaining optimal tensile properties in the pulsed current gas tungsten arc welding is presented. The tensile properties include ultimate tensile strength, yield strength and notch tensile strength. All these characteristics are considered together in the selection of process parameters by modified taguchi method to analyse the effect of each welding process parameter on tensile properties. Experimental results are furnished to illustrate the approach.
Posture parameters optimization of a structured light 3D angle measuring system
2015-01-01
To improve the measurement precision of the structured light target angle, this paper studies the relation between the structured light system parameters and measurement accuracy of the angle. Firstly, the main system structure parameters influencing the angle measurement precision are analyzed based on the structured light measurement principle; secondly, simulation research on the laws of how the structured parameters influence the angle measurement precision are conducted, and the optimize...
Global optimization of parameters in the reactive force field ReaxFF for SiOH.
Larsson, Henrik R; van Duin, Adri C T; Hartke, Bernd
2013-09-30
We have used unbiased global optimization to fit a reactive force field to a given set of reference data. Specifically, we have employed genetic algorithms (GA) to fit ReaxFF to SiOH data, using an in-house GA code that is parallelized across reference data items via the message-passing interface (MPI). Details of GA tuning turn-ed out to be far less important for global optimization efficiency than using suitable ranges within which the parameters are varied. To establish these ranges, either prior knowledge can be used or successive stages of GA optimizations, each building upon the best parameter vectors and ranges found in the previous stage. We have finally arrive-ed at optimized force fields with smaller error measures than those published previously. Hence, this optimization approach will contribute to converting force-field fitting from a specialist task to an everyday commodity, even for the more difficult case of reactive force fields.
Zarepisheh, Masoud; Li, Nan; Jia, Xun; Jiang, Steve B
2012-01-01
In a 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 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. To answer questions related to this problem, we establish in this work a new mathematical framework equipped with two theorems. 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 different effects of adjusting weighting factors versus reference doses in the optimization process. 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 sin...
Institute of Scientific and Technical Information of China (English)
P M AJITH; T MAFSAL HUSAIN; P SATHIYA; S ARAVINDAN
2015-01-01
The optimum friction welding (FW) parameters of duplex stainless steel (DSS) UNS S32205 joint was determined. The experiment was carried out as the central composite array of 30 experiments. The selected input parameters were friction pressure (F), upset pressure (U), speed (S) and burn-off length (B), and responses were hardness and ultimate tensile strength. To achieve the quality of the welded joint, the ultimate tensile strength and hardness were maximized, and response surface methodology (RSM) was applied to create separate regression equations of tensile strength and hardness. Intelligent optimization technique such as genetic algorithm was used to predict the Pareto optimal solutions. Depending upon the application, preferred suitable welding parameters were selected. It was inferred that the changing hardness and tensile strength of the friction welded joint inlfuenced the upset pressure, friction pressure and speed of rotation.
Properties of sputtered TiO{sub 2} thin films as a function of deposition and annealing parameters
Energy Technology Data Exchange (ETDEWEB)
Pjević, Dejan, E-mail: dejanp@vinca.rs [VINČA Institute of Nuclear Sciences, University of Belgrade, PO Box 522, Belgrade (Serbia); Obradović, Marko; Marinković, Tijana; Grce, Ana; Milosavljević, Momir [VINČA Institute of Nuclear Sciences, University of Belgrade, PO Box 522, Belgrade (Serbia); Grieseler, Rolf; Kups, Thomas; Wilke, Marcus; Schaaf, Peter [Institute of Materials Engineering and Institute of Micro- and Nanotechnologies MacroNano, Ilmenau University of Technology, Gustav-Kirchhoff-Strasse 5, 98693 Ilmenau (Germany)
2015-04-15
The influence of sputtering parameters and annealing on the structure and optical properties of TiO{sub 2} thin films deposited by RF magnetron sputtering is reported. A pure TiO{sub 2} target was used to deposit the films on Si(100) and glass substrates, and Ar/O{sub 2} gas mixture was used for sputtering. It was found that both the structure and the optical properties of the films depend on deposition parameters and annealing. In all cases the as-deposited films were oxygen deficient, which could be compensated by post-deposition annealing. Changes in the Ar/O{sub 2} mass flow rate affected the films from an amorphous-like structure for samples deposited without oxygen to a structure where nano-crystalline rutile phase is detected in those deposited with O{sub 2}. Annealing of the samples yielded growth of both, rutile and anatase phases, the ratio depending on the added oxygen content. Increasing mass flow rate of O{sub 2} and annealing are responsible for lowering of the energy band gap values and the increase in refractive index of the films. The results can be interesting towards the development of TiO{sub 2} thin films with defined structure and properties.
Particle Swarm Optimization with Time Varying Parameters for Scheduling in Cloud Computing
Directory of Open Access Journals (Sweden)
Shuang Zhao
2015-01-01
Full Text Available Task resource management is important in cloud computing system. It's necessary to find the efficient way to optimize scheduling in cloud computing. In this paper, an optimized particle swarm optimization (PSO algorithms with adaptive change of parameter (viz., inertial weight and acceleration coefficients according to the evolution state evaluation is presented. This adaptation helps to avoid premature convergence and explore the search space more efficiently. Simulations are carried out to test proposed algorithm, test reveal that the algorithm can achieving significant optimization of makespan.
Optimizing reliability, maintainability and testability parameters of equipment based on GSPN
Institute of Scientific and Technical Information of China (English)
Yongcheng Xu
2015-01-01
Reliability, maintainability and testability (RMT) are important properties of equipment, since they have important influ-ence on operational availability and life cycle costs (LCC). There-fore, weighting and optimizing the three properties are of great significance. A new approach for optimization of RMT parameters is proposed. First of al , the model for the equipment operation pro-cess is established based on the generalized stochastic Petri nets (GSPN) theory. Then, by solving the GSPN model, the quantitative relationship between operational availability and RMT parameters is obtained. Afterwards, taking history data of similar equipment and operation process into consideration, a cost model of design, manufacture and maintenance is developed. Based on operational availability, the cost model and parameters ranges, an optimization model of RMT parameters is built. Final y, the effectiveness and practicability of this approach are validated through an example.
Directory of Open Access Journals (Sweden)
Sunil Kumar Sharma
2014-03-01
Full Text Available The aim of this research is to investigate the optimization of cutting parameters (cutting speed, feed rate and depth of cut for surface roughness and metal removal rate in turning of AISI 8620 steel using coated carbide insert. Experiments have been carried out based on Taguchi L9 standard orthogonal array design with three process parameters namely cutting speed, feed rate and depth of cut for surface roughness and metal removal rate. The objective function has been chosen in relation to surface roughness and metal removal rate for quality target. Optimal parameters contribution of the CNC turning operation was obtained via grey relational analysis. The analysis of variance is applied to identify the most significant factor. Experiment with the optimized parameter setting, which has been obtained from the analysis, are giving to validate the results.
Effect of experimental parameters on optimal reflection of light from opaque media
Anderson, Benjamin R; Eilers, Hergen
2016-01-01
Previously we considered the effect of experimental parameters on optimized transmission through opaque media using spatial light modulator (SLM)-based wavefront shaping. In this study we consider the opposite geometry, in which we optimize reflection from an opaque surface such that the backscattered light is focused onto a spot on an imaging detector. By systematically varying different experimental parameters (genetic algorithm iterations, bin size, SLM active area, target area, spot size, and sample angle with respect to the optical axis) and optimizing the reflected light we determine how each parameter affects the intensity enhancement. We find that the effects of the experimental parameters on the enhancement are similar to those measured for a transmissive geometry, but with the exact functional forms changed due to the different geometry and the use of a genetic algorithm instead of an iterative algorithm. Additionally, we find preliminary evidence of greater enhancements than predicted by random mat...
Load Reconstruction Technique Using D-Optimal Design and Markov Parameters
Directory of Open Access Journals (Sweden)
Deepak K. Gupta
2015-01-01
Full Text Available This paper develops a technique for identifying dynamic loads acting on a structure based on impulse response of the structure, also referred to as the system Markov parameters, and structure response measured at optimally placed sensors on the structure. Inverse Markov parameters are computed from the forward Markov parameters using a linear prediction algorithm and have the roles of input and output reversed. The applied loads are then reconstructed by convolving the inverse Markov parameters with the system response to the loads measured at optimal locations on the structure. The structure essentially acts as its own load transducer. It has been noted that the computation of inverse Markov parameters, like most other inverse problems, is ill-conditioned which causes their convolution with the measured response to become quite sensitive to errors in system modeling and response measurements. The computation of inverse Markov parameters (and thereby the quality of load estimates depends on the locations of sensors on the structure. To ensure that the computation of inverse Markov parameters is well-conditioned, a solution approach, based on the construction of D-optimal designs, is presented to determine the optimal sensor locations such that precise load estimates are obtained.
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.
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.
Analysis of Process Parameters for Optimization of Plastic Extrusion in Pipe Manufacturing
Directory of Open Access Journals (Sweden)
Mr. Sandip S. Gadekar
2015-05-01
Full Text Available The objective of this paper is to study the defects in the plastic pipe, to optimize the plastic pipe manufacturing process. It is very essential to learn the process parameter and the defect in the plastic pipe manufacturing process to optimize it. For the optimization Taguchi techniques is used in this paper. For the research work Shivraj HY-Tech Drip Irrigation pipe manufacturing, Company was selected. This paper is specifically design for the optimization in the current process. The experiment was analyzed using commercial Minitab16 software, interpretation has made, and optimized factor settings were chosen. After prediction of result the quality loss is calculated and it is compare with before implementation of DOE. The research works has improves the Production, quality and optimizes the process.
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...... in a Fisherian sense, is given. The solution is investigated by a simulation study. It is shown that if the experimental length T1 is fixed it may be useful to sample the record at a high sampling rate, since more measurements from the system are then collected. No optimal sampling interval exists....... But if the total number of sample points N is fixed an optimal sampling interval exists. Then it is far worse to use a too large sampling interval than a too small one since the information losses increase rapidly when the sampling interval increases from the optimal value....
Use of multilevel modeling for determining optimal parameters of heat supply systems
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
A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process
Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa
2016-12-01
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.
Multi-response optimization of Micro-EDM process parameters on AISI304 steel using TOPSIS
Energy Technology Data Exchange (ETDEWEB)
Manivannan, R.; Kumar, M. Pradeep [CEG, Anna University, Chennai (India)
2016-01-15
The Technique for order preference by similarity to ideal solution (TOPSIS) method of optimization is used to analyze the process parameters of the micro-Electrical discharge machining (micro-EDM) of an AISI 304 steel with multi-performance characteristics. The Taguchi method of experimental design L27 is performed to obtain the optimal parameters for inputs, including feed rate, current, pulse on time, and gap voltage. Several output responses, such as the material removal rate, electrode wear rate, overcut, taper angle, and circularity at entry and exit points, are analyzed for the optimal conditions. Among all the investigated parameters, feed rate exerts a greater influence on the hole quality. ANOVA is employed to identify the contribution of each experiment. The optimal level of parameter setting is maintained at a feed rate of 4 μm/s, a current of 10 A, a pulse on time of 10 μs, and a gap voltage of 10 V. Scanning electron microscope analysis is conducted to examine the hole quality. The experimental results indicate that the optimal level of the process parameter setting over the overall performance of the micro-EDM is improved through TOPSIS.
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...
Directory of Open Access Journals (Sweden)
Muthu Kumar V
2010-06-01
Full Text Available The present work demonstrates optimization of Wire Electrical Discharge Machining process parameters of Incoloy800 super alloy with multiple performance characteristics such as Material Removal Rate (MRR, surface roughness and Kerf based on the Grey–Taguchi Method. The process parameters considered in this research work are Gap Voltage, Pulse On-time, Pulse Off-time and Wire Feed. Taguchi’s L9 Orthogonal Array was used to conduct experiments. Optimal levels of process parameters were identified using Grey Relational Analysis and the relatively significant parameters were determined by Analysis of Variance. The variation of output responses with process parameters were mathematically modelled by using non-linear regression analysismethod and the models were checked for their adequacy. Result of confirmation experiments shows that the established mathematical models can predict the output responses with reasonable accuracy.
Posture parameters optimization of a structured light 3D angle measuring system
Directory of Open Access Journals (Sweden)
Xun DING
2015-10-01
Full Text Available To improve the measurement precision of the structured light target angle, this paper studies the relation between the structured light system parameters and measurement accuracy of the angle. Firstly, the main system structure parameters influencing the angle measurement precision are analyzed based on the structured light measurement principle; secondly, simulation research on the laws of how the structured parameters influence the angle measurement precision are conducted, and the optimized range of values of the structured parameters is proposed; finally, the experimental studies show that, the optimized parameters can improve the angle measurement precision effectively, which lays the design foundation for later improvement schemes of the structured light 3D four-wheel alignment instrument.
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.
Parametric optimal bounded feedback control for smart parameter-controllable composite structures
Ying, Z. G.; Ni, Y. Q.; Duan, Y. F.
2015-03-01
Deterministic and stochastic parametric optimal bounded control problems are presented for smart composite structures such as magneto-rheological visco-elastomer based sandwich beam with controllable bounded parameters subjected to initial disturbances and stochastic excitations. The parametric controls by actively adjusting system parameters differ from the conventional additive controls by systemic external inputs. The dynamical programming equations for the optimal parametric controls are derived based on the deterministic and stochastic dynamical programming principles. The optimal bounded functions of controls are firstly obtained from the equations with the bounded control constraints based on the bang-bang control strategy. Then the optimal bounded parametric control laws are obtained by the inversion of the nonlinear functions. The stability of the optimally controlled systems is proved according to the Lyapunov method. Finally, the proposed optimal bounded parametric feedback control strategy is applied to single-degree-of-freedom and two-degree-of-freedom dynamic systems with nonlinear parametric bounded control terms under initial disturbances and earthquake excitations and then to a magneto-rheological visco-elastomer based sandwich beam system with nonlinear parametric bounded control terms under stochastic excitations. The effective vibration suppression is illustrated with numerical results. The proposed optimal parametric control strategy is applicable to other smart composite structures with nonlinear controllable parameters.
Multi-parameter Optimization of a Thermoelectric Power Generator and Its Working Conditions
Zhang, T.
2016-09-01
The global optimal working conditions and optimal couple design for thermoelectric (TE) generators with realistic thermal coupling between the heat reservoirs and the TE couple were studied in the current work. The heat fluxes enforced by the heat reservoirs at the hot and the cold junctions of the TE couple were used in combination with parameter normalization to obtain a single cubic algebraic equation relating the temperature differences between the TE couple junctions and between the heat reservoirs, through the electric load resistance ratio, the reservoir thermal conductance ratio, the reservoir thermal conductance to the TE couple thermal conductance ratio, the Thomson to Seebeck coefficient ratio, and the figure of merit (Z) of the material based on the linear TE transport equations and their solutions. A broad reservoir thermal conductance ranging between 0.01 W/K and 100 W/K and TE element length ranging from 10-7 m to 10-3 m were explored to find the global optimal systems. The global optimal parameters related to the working conditions, i.e., reservoir thermal conductance ratio and electric load resistance ratio, and the optimal design parameter related to the TE couple were determined for a given TE material. These results demonstrated that the internal and external electric resistance, the thermal resistance between the reservoirs, the thermal resistance between the reservoir and the TE couple, and the optimal thermoelement length have to be well coordinated to obtain optimal power production.
When the optimal is not the best: parameter estimation in complex biological models.
Directory of Open Access Journals (Sweden)
Diego Fernández Slezak
Full Text Available BACKGROUND: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. RESULTS: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. CONCLUSIONS: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system and point to the need of a theory that addresses this problem more generally.
Influence of deposition parameters on the microstructure of ion-plated films
Broitman, Esteban; Zimmerman, Rosa
1996-07-01
Ion plating is essentially vapor deposition onto a substrate which is the cathode of a glow discharge. The most important characteristic of the technique is that the growing film is subjected to a flux of high energy particles (neutrals and ions). In this study we report information about the effect of ion plating parameters on grain diameter and crystallite size distribution. At a constant potential grain size remains constant with the increase of ion density. On the other hand, at a constant ion density the grain size decreases with the substrate potential increment. Ion bombardment also has an effect on the crystallite size distribution. The ion plated films show a higher degree of uniformity in grain size than vacuum evaporated films. In contrast with vacuum evaporated films, where the grain size is proportional to the thickness, no variation of grain size with film thickness has been observed for the ion-plated films. Electron diffraction patterns have shown that the orientation remains near random over the entire J and V range studied.
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.
Optimal parameters for the Green-Ampt infiltration model under rainfall conditions
Directory of Open Access Journals (Sweden)
Chen Li
2015-06-01
Full Text Available The Green-Ampt (GA model is widely used in hydrologic studies as a simple, physically-based method to estimate infiltration processes. The accuracy of the model for applications under rainfall conditions (as opposed to initially ponded situations has not been studied extensively. We compared calculated rainfall infiltration results for various soils obtained using existing GA parameterizations with those obtained by solving the Richards equation for variably saturated flow. Results provided an overview of GA model performance evaluated by means of a root-meansquare- error-based objective function across a large region in GA parameter space as compared to the Richards equation, which showed a need for seeking optimal GA parameters. Subsequent analysis enabled the identification of optimal GA parameters that provided a close fit with the Richards equation. The optimal parameters were found to substantially outperform the standard theoretical parameters, thus improving the utility and accuracy of the GA model for infiltration simulations under rainfall conditions. A sensitivity analyses indicated that the optimal parameters may change for some rainfall scenarios, but are relatively stable for high-intensity rainfall events.
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.
Directory of Open Access Journals (Sweden)
Hongchun Zhu
Full Text Available 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.
Yücel, Ersin; Yücel, Yasin; Beleli, Buse
2015-07-01
In this study, lead sulfide (PbS) thin films were synthesized by a successive ionic layer adsorption and reaction (SILAR) method with different pH, dipping time and dipping cycles. Response surface methodology (RSM) and central composite design (CCD) were successfully used to optimize the PbS films deposition parameters and understand the significance and interaction of the factors affecting the film quality. 5-level-3-factor central composite design was employed to evaluate the effects of the deposition parameters (pH, dipping time and dipping cycles) on the response (the optical band gap of the films). Data obtained from RSM were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation. The optimal conditions for the PbS films deposition have been found to be: pH of 9.1, dipping time of 10 s and dipping cycles of 10 cycles. The predicted band gap of PbS film was 2.13 eV under the optimal conditions. Verification experiment (2.24 eV) confirmed the validity of the predicted model. 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.
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).
Improving hot region prediction by parameter optimization of density clustering in PPI.
Hu, Jing; Zhang, Xiaolong
2016-11-01
This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius.
Huang, Yu; Guo, Feng; Li, Yongling; Liu, Yufeng
2015-01-01
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.
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.
D-optimal Bayesian Interrogation for Parameter and Noise Identification of Recurrent Neural Networks
Poczos, Barnabas
2008-01-01
We introduce a novel online Bayesian method for the identification of a family of noisy recurrent neural networks (RNNs). We develop Bayesian active learning technique in order to optimize the interrogating stimuli given past experiences. In particular, we consider the unknown parameters as stochastic variables and use the D-optimality principle, also known as `\\emph{infomax method}', to choose optimal stimuli. We apply a greedy technique to maximize the information gain concerning network parameters at each time step. We also derive the D-optimal estimation of the additive noise that perturbs the dynamical system of the RNN. Our analytical results are approximation-free. The analytic derivation gives rise to attractive quadratic update rules.
Olivares, Irene; Angelova, Todora I.; Pinilla-Cienfuegos, Elena; Sanchis, Pablo
2016-05-01
The electro-optic Pockels effect may be generated in silicon photonics structures by breaking the crystal symmetry by means of a highly stressing cladding layer (typically silicon nitride, SiN) deposited on top of the silicon waveguide. In this work, the influence of the waveguide parameters on the strain distribution and its overlap with the optical mode to enhance the Pockels effect has been analyzed. The optimum waveguide structure have been designed based on the definition and quantification of a figure of merit. The fabrication of highly stressing SiN layers by PECVD has also been optimized to characterize the designed structures. The residual stress has been controlled during the growth process by analyzing the influence of the main deposition parameters. Therefore, two identical samples with low and high stress conditions were fabricated and electro-optically characterized to test the induced Pockels effect and the influence of carrier effects. Electro-optical modulation was only measured in the sample with the high stressing SiN layer that could be attributed to the Pockels effect. Nevertheless, the influence of carriers were also observed thus making necessary additional experiments to decouple both effects.
Fittschen, Ursula E A; Havrilla, George J
2010-01-01
In this study, we introduce a Hewlett-Packard prototype picoliter pipette, the "thermal inkjet picofluidic system" (TIPS), for analytical purposes. In contrast to the use of actual inkjet printers, this instrument allows for control of all energy and time settings. We are able to show that in contrast to techniques delivering microliter and nanoliter volumes, evaporation has a major influence on the deposition of picoliter volumes and has to be treated seriously when picoliter depositions are applied in the laboratory for calibration purposes. We developed a strategy to reduce evaporation by varying different parameters, thereby achieving a precision of less than 10% for elemental depositions ranging from 1 to 300 picoliters and 1 to 2000 pg elemental deposits. Additionally, we determined the performance of the micro X-ray fluorescence (MXRF) instruments in terms of limit of detection (LODs), focal spot size, sensitivity, and precision and evaluated the TIPS deposits as reference materials for MXRF using single and multielement solutions. A linear response was observed with correlation coefficients from 0.991 to 0.999 for elemental deposits on AP1 film, and there was a standard deviation from 1 to 40%, depending on the element and the mass deposited. LOD's for Ni deposits on AP1 films were found to range from low picogram levels to subpicogram levels. The dried deposits were characterized for size and shape using light microscopy and atomic force microscopy (AFM) to estimate matrix effects and the area covered with sample material for the MXRF analysis. Diameters from 14 to 39 microm and thicknesses from 200 nm to 2 microm were measured. The accuracy of the dried spot approach was demonstrated by comparing multielement deposits from the TIPS with the NIST SRMs 1833 and 1832 thin film standards for MXRF analysis. The deviation from the SRMs was found to be better than 10%.
Optimization of TRPO Process Parameters for Americium Extraction from High Level Waste
Institute of Scientific and Technical Information of China (English)
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.1750 L/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.
Hou, Zhi-chao; Lao, Yao-xin; Lu, Qiu-hai
2008-11-01
Tensioner is a critical mechanism to ensure a constant tension level within a serpentine belt drive that is widely used in modern passenger vehicles. For a belt drive with n pulleys, generic and explicit formulae about sensitivities of both frequency and steady harmonic responses are established in terms of system matrices with respect to any design parameter of the system. Deductions from the formulae results in frequency and steady response sensitivities relative to key tensioner parameters and the belt speed. Based on sensitivity analysis, optimizations are conducted on tensioner so as to suppress dynamic responses of the system by frequency detuning. A new approach for searching optimal parameters is put forward by incorporating sensitivity information into a classical coordinate alternating procedure. Examples are given to validate the analytical formulae of the frequency sensitivity and to demonstrate the effect of optimization.
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.
Garzillo, Valerio; Jukna, Vytautas; Couairon, Arnaud; Grigutis, Robertas; Di Trapani, Paolo; Jedrkiewicz, Ottavia
2016-07-01
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.
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.
Ghulam Saber, Md; Arif Shahriar, Kh; Ahmed, Ashik; Hasan Sagor, Rakibul
2016-10-01
Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square (RMS) deviation is determined and compared.
Multi-objective optimization of cutting parameters in turning using grey relational analysis
2013-01-01
This study presents optimization of performance characteristics in unidirectional glass fiber reinforced plastic composites using Taguchi method and Grey relational analysis. Performance characteristics such as surface roughness and material removal rate are optimized during rough cutting operation. Process parameters including tool nose radius, tool rake angle, feed rate, cutting speed, cutting environment and depth of cut are investigated using mixed L18 orthogonal array. Grey relation anal...
Directory of Open Access Journals (Sweden)
A.Thillaivanan,
2010-12-01
Full Text Available In this paper the complexity of electrical discharge machining process which is very difficult to determine optimal cutting parameters for improving cutting performance has been reported. Optimization of operating parameters is an important step in machining, particularly for operating unconventional machiningprocedure like EDM. A suitable selection of machining parameters for the electrical discharge machining process relies heavily on the operators’ technologies and experience because of their numerous and diverse range. Machining parameters tables provided by the machine tool builder can not meet the operators’ requirements, since for anarbitrary desired machining time for a particular job, they do not provide the optimal machining conditions. An approach to determine parameters setting is proposed. Based on the Taguchi parameter design method and the analysis of variance, the significant factors affecting the machining performance such as total machining time, oversize and taper for a hole machined by EDM process, are determined.Artificial neural networks are highly flexible modeling tools with an ability to learn the mapping between input variables and output feature spaces. The superiority of using artificial neural networks inmodeling machining processes make easier to model the EDM process with dimensional input and output spaces. On the basis of the developed neural network model, for a required total machining time, oversize and taper the corresponding process parameters to be set in EDM by using the developed and trained ANN are determined.
Shah, Kamran; Izhar Ul Haq; Shah, Shaukat Ali; Khan, Farid Ullah; Khan, Muhammad Tahir; Khan, Sikander
2014-01-01
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.
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.
Iterative optimization algorithm with parameter estimation for the ambulance location problem.
Kim, Sun Hoon; Lee, Young Hoon
2016-12-01
The emergency vehicle location problem to determine the number of ambulance vehicles and their locations satisfying a required reliability level is investigated in this study. This is a complex nonlinear issue involving critical decision making that has inherent stochastic characteristics. This paper studies an iterative optimization algorithm with parameter estimation to solve the emergency vehicle location problem. In the suggested algorithm, a linear model determines the locations of ambulances, while a hypercube simulation is used to estimate and provide parameters regarding ambulance locations. First, we suggest an iterative hypercube optimization algorithm in which interaction parameters and rules for the hypercube and optimization are identified. The interaction rules employed in this study enable our algorithm to always find the locations of ambulances satisfying the reliability requirement. We also propose an iterative simulation optimization algorithm in which the hypercube method is replaced by a simulation, to achieve computational efficiency. The computational experiments show that the iterative simulation optimization algorithm performs equivalently to the iterative hypercube optimization. The suggested algorithms are found to outperform existing algorithms suggested in the literature.
Institute of Scientific and Technical Information of China (English)
Yang Haiwei; Zhan Yongqi; Qiao Junwei; Shi Guanglin
2003-01-01
The dynamic working process of 52SFZ-140-207B type of hydraulic bumper is analyzed. The modeling method using architecture-based neural networks is introduced. Using this modeling method, the dynamic model of the hydraulic bumper is established; Based on this model the structural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result shows that the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamic performance of the hydraulic bumper is improved through parameter optimization.
Identification of Dynamic Parameters Based on Pseudo-Parallel Ant Colony Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
ZHAO Feng-yao; MA Zhen-yue; ZHANG Yun-liang
2007-01-01
For the parameter identification of dynamic problems, a pseudo-parallel ant colony optimization (PPACO) algorithm based on graph-based ant system (AS) was introduced. On the platform of ANSYS dynamic analysis, the PPACO algorithm was applied to the identification of dynamic parameters successfully. Using simulated data of forces and displacements, elastic modulus E and damping ratio ξ was identified for a designed 3D finite element model, and the detailed identification step was given. Mathematical example and simulation example show that the proposed method has higher precision, faster convergence speed and stronger antinoise ability compared with the standard genetic algorithm and the ant colony optimization (ACO) algorithms.
Parameter Optimization of Single-Diode Model of Photovoltaic Cell Using Memetic Algorithm
Directory of Open Access Journals (Sweden)
Yourim Yoon
2015-01-01
Full Text Available This study proposes a memetic approach for optimally determining the parameter values of single-diode-equivalent solar cell model. The memetic algorithm, which combines metaheuristic and gradient-based techniques, has the merit of good performance in both global and local searches. First, 10 single algorithms were considered including genetic algorithm, simulated annealing, particle swarm optimization, harmony search, differential evolution, cuckoo search, least squares method, and pattern search; then their final solutions were used as initial vectors for generalized reduced gradient technique. From this memetic approach, we could further improve the accuracy of the estimated solar cell parameters when compared with single algorithm approaches.
CH4 parameter estimation in CLM4.5bgc using surrogate global optimization
Directory of Open Access Journals (Sweden)
J. Müller
2015-01-01
Full Text Available Over the anthropocene methane has increased dramatically. Wetlands are one of the major sources of methane to the atmosphere, but the role of changes in wetland emissions is not well understood. The Community Land Model (CLM of the Community Earth System Models contains a module to estimate methane emissions from natural wetlands and rice paddies. Our comparison of CH4 emission observations at 16 sites around the planet reveals, however, that there are large discrepancies between the CLM predictions and the observations. The goal of our study is to adjust the model parameters in order to minimize the root mean squared error (RMSE between model predictions and observations. These parameters have been selected based on a sensitivity analysis. Because of the cost associated with running the CLM simulation (15 to 30 min on the Yellowstone Supercomputing Facility, only relatively few simulations can be allowed in order to find a near optimal solution within an acceptable time. Our results indicate that the parameter estimation problem has multiple local minima. Hence, we use a computationally efficient global optimization algorithm that uses a radial basis function (RBF surrogate model to approximate the objective function. We use the information from the RBF to select parameter values that are most promising with respect to improving the objective function value. We show with pseudo data that our optimization algorithm is able to make excellent progress with respect to decreasing the RMSE. Using the true CH4 emission observations for optimizing the parameters, we are able to significantly reduce the overall RMSE between observations and model predictions by about 50%. The CLM predictions with the optimized parameters agree for northern and tropical latitudes more with the observed data than when using the default parameters and the emission predictions are higher than with default settings in northern latitudes and lower than default settings in the
Directory of Open Access Journals (Sweden)
K.RAMESH KUMAR
2011-02-01
Full Text Available Optimization of cutting parameters is one of the most important elements in any process planning of metal parts. Economy of machining operation plays a key role in competitiveness in the market. All CNCmachines produce finished components from cylindrical bar. Finished profiles consist of straight turning, facing, taper and circular machining. Finished profile from a cylindrical bar is done in two stages, rough machining and finish machining. Numbers of passes are required for rough machining and single pass is required for the finished pass. The machining parameters in multipass turning are depth of cut, cutting speed and feed. The machining performance is measured by the minimum production time. In this paper the optimal machining parameters for continuous profile machining are determinedwith respect to the minimum production time, subject to a set of practical constraints, cutting force, power and dimensional accuracy and surface finish. Due to complexity of this machining optimizationproblem, a genetic algorithm (GA and Particle Swarm Optimization (PSO are applied to resolve the problem and the results obtained from GA and PSO are compared.
DEFF Research Database (Denmark)
Mohanty, Sankhya; Hattel, Jesper Henri
2015-01-01
to generate optimized cellular scanning strategies and processing parameters, with an objective of reducing thermal asymmetries and mechanical deformations. The optimized scanning strategies are used for selective laser melting of the standard samples, and experimental and numerical results are compared....... gradients that occur during the process. While process monitoring and control of selective laser melting is an active area of research, establishing the reliability and robustness of the process still remains a challenge.In this paper, a methodology for generating reliable, optimized scanning paths...
Design Optimization of RFI Parameters by Manufacturing T-shaped Composite Panel
Institute of Scientific and Technical Information of China (English)
ZHANG Guo-li; HUANG Gu
2005-01-01
The aim of this project is to develop a novel approach for optimizing design resin film infusion (RFI) processing parameters by manufacturing T-shaped composite panel. The dimensional accuracy was selected as the objective function. By investigating the rheological properties of resin film, the compaction behavior of fiber preform and characteristics of RFI process, an optimal mathematical model was established, it was found that the numerical results obtained from the RFICOMP program package have good consistency with the experimental results, and this optimization procedure can be applied to other composites manufacture processes.
Evaluation of a new parallel numerical parameter optimization algorithm for a dynamical system
Duran, Ahmet; Tuncel, Mehmet
2016-10-01
It is important to have a scalable parallel numerical parameter optimization algorithm for a dynamical system used in financial applications where time limitation is crucial. We use Message Passing Interface parallel programming and present such a new parallel algorithm for parameter estimation. For example, we apply the algorithm to the asset flow differential equations that have been developed and analyzed since 1989 (see [3-6] and references contained therein). We achieved speed-up for some time series to run up to 512 cores (see [10]). Unlike [10], we consider more extensive financial market situations, for example, in presence of low volatility, high volatility and stock market price at a discount/premium to its net asset value with varying magnitude, in this work. Moreover, we evaluated the convergence of the model parameter vector, the nonlinear least squares error and maximum improvement factor to quantify the success of the optimization process depending on the number of initial parameter vectors.
Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection
Directory of Open Access Journals (Sweden)
Haris Ahmad Khan
2016-03-01
Full Text Available Automated systems for road crack detection are extremely important in road maintenance for vehicle safety and traveler’s comfort. Emerging cracks in roads need to be detected and accordingly repaired as early as possible to avoid further damage thus reducing rehabilitation cost. In this paper, a robust method for Gabor filter parameters optimization for automatic road crack detection is discussed. Gabor filter has been used in previous literature for similar applications. However, there is a need for automatic selection of optimized Gabor filter parameters due to variation in texture of roads and cracks. The problem of change of background, which in fact is road texture, is addressed through a learning process by using synthetic road crack generation for Gabor filter parameter tuning. Tuned parameters are then tested on real cracks and a thorough quantitative analysis is performed for performance evaluation.
An adjoint data assimilation method for optimizing frictional parameters on the afterslip area
Kano, Masayuki; Miyazaki, Shin'ichi; Ito, Kosuke; Hirahara, Kazuro
2013-12-01
Afterslip sometimes triggers subsequent earthquakes within a timescale of days to several years. Thus, it may be possible to predict the occurrence of such a triggered earthquake by simulating the spatio-temporal evolution of afterslip with estimated frictional parameters. To demonstrate the feasibility of this idea, we consider a plate interface model where afterslip propagates between two asperities following a rate-and-state friction law, and we adopt an adjoint data assimilation method to optimize frictional parameters. Synthetic observation data are sampled as the slip velocities on the plate interface during 20 days. It is found that: (1) all frictional parameters are optimized if the data sets consists not only of the early phase of afterslip or acceleration, but also of the decaying phase or deceleration; and (2) the prediction of the timing of the triggered earthquake is improved by using adjusted frictional parameters.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors
Directory of Open Access Journals (Sweden)
Jilin Zhang
2017-09-01
Full Text Available 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.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.
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.
Sequential deposition: optimization of solvent swelling for high-performance polymer solar cells.
Liu, Yao; Liu, Feng; Wang, Hsin-Wei; Nordlund, Dennis; Sun, Zhiwei; Ferdous, Sunzida; Russell, Thomas P
2015-01-14
Organic solar cells based on a typical DPP polymer were systematically optimized by a solvent swelling assisted sequential deposition process. We investigated the influence of solvent swelling on the morphology and structure order of the swollen film and the resultant device performance. Morphological and structural characterization confirmed the realization of ideal bulk heterojunctions using a suitable swelling solvent. A trilayered morphology was also found with the conjugated polymer concentrated bottom layer, PC71BM concentrated top layer, and interpenetrated networks of donor and acceptor in the middle by solvent swelling instead of thermal annealing in the sequential solution processing method. We proposed a simple strategy to optimize the sequential deposition fabricated devices by tuning the concentration of the PC71BM solution instead of thermal annealing. The best device showed a PCE of 7.59% with a Voc of 0.61 V, Jsc of 17.95 mA/cm(2), and FF of 69.6%, which is the highest reported efficiency for devices fabricated by a sequential processing method and among the best results for DPP polymers.
Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models
Vesselinov, Velimir V
2011-01-01
A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particl...
Parameter identification of a distributed runoff model by the optimization software Colleo
Matsumoto, Kazuhiro; Miyamoto, Mamoru; Yamakage, Yuzuru; Tsuda, Morimasa; Anai, Hirokazu; Iwami, Yoichi
2015-04-01
The introduction of Colleo (Collection of Optimization software) is presented and case studies of parameter identification for a distributed runoff model are illustrated. In order to calculate discharge of rivers accurately, a distributed runoff model becomes widely used to take into account various land usage, soil-type and rainfall distribution. Feasibility study of parameter optimization is desired to be done in two steps. The first step is to survey which optimization algorithms are suitable for the problems of interests. The second step is to investigate the performance of the specific optimization algorithm. Most of the previous studies seem to focus on the second step. This study will focus on the first step and complement the previous studies. Many optimization algorithms have been proposed in the computational science field and a large number of optimization software have been developed and opened to the public with practically applicable performance and quality. It is well known that it is important to use suitable algorithms for the problems to obtain good optimization results efficiently. In order to achieve algorithm comparison readily, optimization software is needed with which performance of many algorithms can be compared and can be connected to various simulation software. Colleo is developed to satisfy such needs. Colleo provides a unified user interface to several optimization software such as pyOpt, NLopt, inspyred and R and helps investigate the suitability of optimization algorithms. 74 different implementations of optimization algorithms, Nelder-Mead, Particle Swarm Optimization and Genetic Algorithm, are available with Colleo. The effectiveness of Colleo was demonstrated with the cases of flood events of the Gokase River basin in Japan (1820km2). From 2002 to 2010, there were 15 flood events, in which the discharge exceeded 1000m3/s. The discharge was calculated with the PWRI distributed hydrological model developed by ICHARM. The target
Levenberg – Marquardt’s Algorithm used for PID Controller Parameters Optimization
Ahmed S. Abd El-Hamid; Ahmed H. Eissa; Aly M. Radwan
2015-01-01
The determination of parameters of controllers is an important problem in automatic control systems. In this paper, the Levenberg Marquardt (LM) Algorithm is used to effectively solve this problem with reasonable computational effort. The Levenberg Marquardt (LM) Algorithm for optimization of three term (PID) controller parameters with dynamic model of pH neutralization process is presented. The main goal is to show the merits of Levenberg Marquardt algorithm optimizat...
Diagnosis parameters of mold filling pattern for optimization of a casting system
2012-01-01
For optimal design of a gating system, the setting of diagnosis parameters is very important. In this study, the permanent mold casting process was selected because most of the other casting processes have more complicated factors that influence the mold filling pattern compared to the permanent mold casting process, such as the surface roughness of mold, gas generation from the mold wash and binder of sand mold, and the gas permeability through a sand mold, etc. Two diagnosis parameters (fl...
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
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In particle sizing by light extinction method, the regularization parameter plays an important role in applying regularization to find the solution to ill-posed inverse problems. We combine the generalized cross-validation (GCV) and L-curve criteria with the Twomey-NNLS algorithm in parameter optimization. Numerical simulation and experimental validation show that the resistance of the newly developed algorithms to measurement errors can be improved leading to stable inversion results for unimodal particle size distribution.
Abe, Tomomi; Hashimoto, Shuji; Matsumoto, Mitsuharu
2010-02-01
epsilon-filter can reduce most kinds of noise from a single-channel noisy signal while preserving signals that vary drastically such as speech signals. It can reduce not only stationary noise but also nonstationary noise. However, it has some parameters whose values are set empirically. So far, there have been few studies to evaluate the appropriateness of the parameter settings for epsilon-filter. This paper employs the correlation coefficient of the filter output and the difference between the filter input and output as the evaluation function of the parameter setting. This paper also describes the algorithm to set the optimal parameter value of epsilon-filter automatically. To evaluate the adequateness of the obtained parameter, the mean absolute error is calculated. The experimental results show that the adequate parameter in epsilon-filter can be obtained automatically by using the proposed method.
Leeuwen, van H.P.; Town, R.M.
2003-01-01
Stripping chronopotentiometry at scanned deposition potential (SSCP) generates curves that are fundamentally different in form from classical polarographic waves. Still, despite their steeper slope and non-linear log plot, the shift in the SSCP half-wave deposition potential can be interpreted in a
Effect of thermophoresis and other parameters on the particle deposition on a tilted surface
Energy Technology Data Exchange (ETDEWEB)
Abdolzadeh, M., E-mail: abdolzadeh@iauk.ac.ir [Department of Mechanical Engineering, Shahid Bahonar University of Kerman (Iran, Islamic Republic of); Mehrabian, M.A.; Zahedi, G. [Department of Mechanical Engineering, Shahid Bahonar University of Kerman (Iran, Islamic Republic of); Soltani Goharrizi, A. [Department of Chemical Engineering, Shahid Bahonar University of Kerman (Iran, Islamic Republic of)
2011-06-15
In this study a modified version of v2-f turbulence model ({phi}-{alpha}), is applied to simulate a non-isothermal air-flow. The {phi}-{alpha} model and a two-phase Eulerian approach complement each other to predict the rate of particle deposition on a tilted surface. The {phi}-{alpha} model can accurately calculate the normal fluctuations, which mainly represent the non-isotropic nature of turbulence regime near the wall. The Eulerian model was modified considering the most important mechanism in the particle deposition rate when compared to the experimental data. The model performance is examined by comparing the rate of particle deposition on a vertical surface with the experimental data in a turbulent channel flow available in the literature. The effects of lift force, turbophoretic force, thermophoreric force, electrostatic force, gravitational force and Brownian/turbulent diffusion were examined on the particle deposition rate. The results show that, using the {phi}-{alpha} model predicts the rate of deposition with reasonable accuracy. The results of modified particle model are in good agreement with the experimental data. This study highlights the paramount effect of thermophoretic force on the particle deposition rate and clearly shows that when the temperature difference exceeds a certain limit, the electrostatic force has insignificant effect on the particle deposition rate. Furthermore, it is indicated that even at small temperature differences, the effect of tilt angle on the particle deposition rate for intermediate-size particles is negligible.
Parameter identification theory of a complex model based on global optimization method
Institute of Scientific and Technical Information of China (English)
2008-01-01
With the development of computer technology and numerical simulation technol- ogy, computer aided engineering (CAE) technology has been widely applied to many fields. One of the main obstacles, which hinder the further application of CAE technology, is how to successfully identify the parameters of the selected model. An elementary framework for parameter identification of a complex model is pro-vided in this paper. The framework includes the construction of objective function, the design of the optimization method and the evaluation of the identified results, etc. The parameter identification process is described in this framework, taking the parameter identification of the superplastic constitutive model considering grain growth for Ti-6Al-4V at 927℃ as an example. The objective function is the weighted quadratic sums of the difference between the experimental and computational data for the stress-strain relationship and the grain growth relationship; the designed optimization method is a hybrid global optimization method, which is based on the feature of the objective function and incorporates the strengths of genetic algo-rithm (GA), the Levenberg-Marquardt algorithm and the augmented Gauss-Newton algorithm. The reliability evaluation of parameter identification result is made through the comparison between the calculated and experimental results and be-tween the theoretical values of the parameters and the identified ones.
Qi, Wei; Zhang, Chi; Fu, Guangtao; Zhou, Huicheng
2016-02-01
It is widely recognized that optimization algorithm parameters have significant impacts on algorithm performance, but quantifying the influence is very complex and difficult due to high computational demands and dynamic nature of search parameters. The overall aim of this paper is to develop a global sensitivity analysis based framework to dynamically quantify the individual and interactive influence of algorithm parameters on algorithm performance. A variance decomposition sensitivity analysis method, Analysis of Variance (ANOVA), is used for sensitivity quantification, because it is capable of handling small samples and more computationally efficient compared with other approaches. The Shuffled Complex Evolution method developed at the University of Arizona algorithm (SCE-UA) is selected as an optimization algorithm for investigation, and two criteria, i.e., convergence speed and success rate, are used to measure the performance of SCE-UA. Results show the proposed framework can effectively reveal the dynamic sensitivity of algorithm parameters in the search processes, including individual influences of parameters and their interactive impacts. Interactions between algorithm parameters have significant impacts on SCE-UA performance, which has not been reported in previous research. The proposed framework provides a means to understand the dynamics of algorithm parameter influence, and highlights the significance of considering interactive parameter influence to improve algorithm performance in the search processes.
PALS — The optimal laser for determining optimal ablative laser propulsion parameters?
Boody, Frederick P.
2005-04-01
Ablative laser propulsion (ALP) could revolutionize space travel by reducing the 30:1 propellant/payload ratio needed for near-earth orbit 50-fold. To date, experiments have demonstrated the necessary efficiency, coupling coefficient, and specific impulse for application, but were performed at pulse energies and spot sizes much smaller than required and at wavelengths not usable in the atmosphere. Also, most experiments have not simultaneously measured the properties of the ions produced or of the ablated surface, properties that would allow full understanding of the propulsion properties in terms of ion characteristics. Realistic measurement of laser propulsion parameters is proposed using PALS (Prague Asterix Laser System), whose parameters, except for pulse rate and wavelength — pulse energy (˜1kJ), pulse length (400ps), beam diameter (˜29cm), and flat beam profile — equal those required for application. PALS wavelength is a little short (1.3μm vs. >1.5μm) but is closer than any other laser available and, due to PALS 2ω / 3ω capability, wavelength dependence can be studied and results extrapolated to application values. PALS' proven infrastructure for measuring laser-driven ion properties means that only an instrument for measuring momentum transfer, such as a ballistic pendulum, will have to be added.
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
Institute of Scientific and Technical Information of China (English)
R Paventhan; P R Lakshminarayanan; V Balasubramanian
2012-01-01
Friction weIding is a solid state joining process used extensively currently owing to its advantages such as low heat input, high production efficiency, ease of manufacture, and environment friendliness. Materials difficult to be welded by fusion welding processes can be successfully welded by friction welding. An attempt was made to develop an empirical relationship to predict the tensile strength of friction welded AISI 1040 grade medium carbon steel and AISI 304 austenitic stainless steel, incorporating the process parameters such as friction pressure, forging pressure, friction time and forging time, which have great influence on strength of the joints. Response surface methodology was applied to optimize the friction welding process parameters to attain maximum tensile strength of the joint. The maximum tensile strength of 543 MPa could be obtained for the joints fabricated under the welding conditions of friction pressure of 90 MPa, forging pressure of 90 MPa, friction time of 6 s and forging time of 6 s.
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...
An optimization analysis on electroless deposition of Al{sub 2}O{sub 3}/Cu core-shell nanostructures
Energy Technology Data Exchange (ETDEWEB)
Beygi, H., E-mail: hossein.beygi@stu-mail.um.ac.ir [Department of Materials Science and Metallurgical Engineering, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad (Iran, Islamic Republic of); Sajjadi, S.A.; Zebarjad, S.M. [Department of Materials Science and Metallurgical Engineering, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad (Iran, Islamic Republic of)
2012-11-15
Highlights: Black-Right-Pointing-Pointer Al{sub 2}O{sub 3}/Cu core-shell nanostructure fabricated by electroless copper plating on Al{sub 2}O{sub 3} particles. Black-Right-Pointing-Pointer Optimization on bath composition and electroless parameters performed by Taguchi method. Black-Right-Pointing-Pointer Using minimum chemicals usage, maximum plating rate of copper obtained. Black-Right-Pointing-Pointer Uniform copper shells with 10 nm thicknesses were fabricated on the Al{sub 2}O{sub 3} nanoparticles. - Abstract: In this study, Al{sub 2}O{sub 3}/Cu core-shell nanostructure was fabricated by electroless plating of copper on Al{sub 2}O{sub 3} particles. In order to reach to the maximum efficiency of electroless deposition, the influence of main effective parameters such as type of pretreatment process, HCHO/CuSO{sub 4}{center_dot}5H{sub 2}O molar ratio, C{sub 4}H{sub 4}O{sub 6}KNa{center_dot}4H{sub 2}O/CuSO{sub 4}{center_dot}5H{sub 2}O molar ratio, pH, pouring rate, concentration of Al{sub 2}O{sub 3} particles, bath temperature, plating time, stirring speed and Al{sub 2}O{sub 3} particle size were investigated. The morphology, uniformity, and chemical composition of the activated and Cu coated Al{sub 2}O{sub 3} particles were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD). The results show that, by optimization on the electroless bath composition and the process parameters, using minimum chemicals usage maximum copper plating rate of 19.51% on the surface of Al{sub 2}O{sub 3} particles is obtained. As result of copper deposition on the surface of Al{sub 2}O{sub 3} nanoparticles, uniform shells with about 10 nm thicknesses was fabricated on the Al{sub 2}O{sub 3} nanoparticles.
Directory of Open Access Journals (Sweden)
Michala Jakubcová
2015-01-01
Full Text Available The presented paper provides the analysis of selected versions of the particle swarm optimization (PSO algorithm. The tested versions of the PSO were combined with the shuffling mechanism, which splits the model population into complexes and performs distributed PSO optimization. One of them is a new proposed PSO modification, APartW, which enhances the global exploration and local exploitation in the parametric space during the optimization process through the new updating mechanism applied on the PSO inertia weight. The performances of four selected PSO methods were tested on 11 benchmark optimization problems, which were prepared for the special session on single-objective real-parameter optimization CEC 2005. The results confirm that the tested new APartW PSO variant is comparable with other existing distributed PSO versions, AdaptW and LinTimeVarW. The distributed PSO versions were developed for finding the solution of inverse problems related to the estimation of parameters of hydrological model Bilan. The results of the case study, made on the selected set of 30 catchments obtained from MOPEX database, show that tested distributed PSO versions provide suitable estimates of Bilan model parameters and thus can be used for solving related inverse problems during the calibration process of studied water balance hydrological model.
Optimization of injection molding parameters for poly(styrene-isobutylene-styrene) block copolymer
Fittipaldi, Mauro; Garcia, Carla; Rodriguez, Luis A.; Grace, Landon R.
2016-03-01
Poly(styrene-isobutylene-styrene) (SIBS) is a widely used thermoplastic elastomer in bioimplantable devices due to its inherent stability in vivo. However, the properties of the material are highly dependent on the fabrication conditions, molecular weight, and styrene content. An optimization method for injection molding is herein proposed which can be applied to varying SIBS formulations in order to maximize ultimate tensile strength, which is critical to certain load-bearing implantable applications. The number of injection molded samples required to ascertain the optimum conditions for maximum ultimate tensile strength is limited in order to minimize experimental time and effort. Injection molding parameters including nozzle temperature (three levels: 218, 246, and 274 °C), mold temperature (three levels: 50, 85, and 120 °C), injection speed (three levels: slow, medium and fast) and holding pressure time (three levels: 2, 6, and 10 seconds) were varied to fabricate dumbbell specimens for tensile testing. A three-level L9 Taguchi method utilizing orthogonal arrays was used in order to rank the importance of the different injection molding parameters and to find an optimal parameter setting to maximize the ultimate tensile strength of the thermoplastic elastomer. Based on the Taguchi design results, a Response Surface Methodology (RSM) was applied in order to build a model to predict the tensile strength of the material at different injection parameters. Finally, the model was optimized to find the injection molding parameters providing maximum ultimate tensile strength. Subsequently, the theoretically-optimum injection molding parameters were used to fabricate additional dumbbell specimens. The experimentally-determined ultimate tensile strength of these samples was found to be in close agreement (1.2%) with the theoretical results, successfully demonstrating the suitability of the Taguchi Method and RSM for optimizing injection molding parameters of SIBS.
On Optimization Control Parameters in an Adaptive Error-Control Scheme in Satellite Networks
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Ranko Vojinović
2011-09-01
Full Text Available This paper presents a method for optimization of control parameters of an adaptive GBN scheme in error-prone satellite channel. Method is based on the channel model with three state, where channel have the variable noise level.
Optimization of WEDM process parameters using deep cryo-treated Inconel 718 as work material
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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.
Zhang, Liqiang; Li, Luoxing; Wang, Shiuping; Zhu, Biwu
2012-04-01
In this article, the low-pressure die-cast (LPDC) process parameters of aluminum alloy thin-walled component with permanent mold are optimized using a combining artificial neural network and genetic algorithm (ANN/GA) method. In this method, an ANN model combining learning vector quantization (LVQ) and back-propagation (BP) algorithm is proposed to map the complex relationship between process conditions and quality indexes of LPDC. The genetic algorithm is employed to optimize the process parameters with the fitness function based on the trained ANN model. Then, by applying the optimized parameters, a thin-walled component with 300 mm in length, 100 mm in width, and 1.5 mm in thickness is successfully prepared and no obvious defects such as shrinkage, gas porosity, distortion, and crack were found in the component. The results indicate that the combining ANN/GA method is an effective tool for the process optimization of LPDC, and they also provide valuable reference on choosing the right process parameters for LPDC thin-walled aluminum alloy casting.
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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.
Jet Drilling and Optimizing Parameter Drilling Technology in Shengli Oil Fields
Institute of Scientific and Technical Information of China (English)
Chen Yue; Peng Junsheng
1996-01-01
@@ In Shengli oilfield, remarkable achievements have been obtained in research and tests on the technologies of jet drilling and optimizing parameter drilling, extensive applications of the technologies have greatly improved drilling speed and sharply decreased drilling time and costs, thus achieving excellent social and economic benefits.
Remondo Bueno, D.; Srinivasan, R.; Nicola, V.F.; van Etten, Wim; Tattje, H.E.P.
2000-01-01
We present new adaptive importance sampling techniques based on stochastic Newton recursions. Their applicability to the performance evaluation of communication systems is studied. Besides bit-error rate (BER) estimation, the techniques are used for system parameter optimization. Two system models
Optimization of Polishing Parameters with Taguchi Method for LBO Crystal in CMP
Institute of Scientific and Technical Information of China (English)
Jun Li; Yongwei Zhu; Dunwen Zuo; Yong Zhu; Chuangtian Chen
2009-01-01
Chemical mechanical polishing (CMP) was used to polish Lithium triborate (UB_3O_5 or LBO) crystal. Taguchi method was applied for optimization of the polishing parameters. Material removal rate (MRR) and surface roughness are considered as criteria for the optimization. The polishing pressure, the abrasive concentration and the table velocity are important parameters which influence MRR and surface roughness in CMP of LBO crystal. Experiment results indicate that for MRR the polishing pressure is the most significant polishing parameter followed by table velocity; while for the surface roughness, the abrasive concentration is the most important one. For high MRR in CMP of LBO crystal the optimal conditions are: pressure 620 g/cm~2, concentration 5.0 wt pct, and velocity 60 r/min, respectively. For the best surface roughness the optimal conditions are: pressure 416 g/cm~2, concentration 5.0 wt pct, and velocity 40 r/min, respectively. The contributions of individual parameters for MRR and surface roughness were obtained.
Gul, Turan; Bischoff, Rainer; Permentier, Hjalmar
2015-01-01
Identification of potentially toxic oxidative drug metabolites is a crucial step in the development of new drugs. Electrochemical methods are useful to study oxidative drug metabolism, but are not widely used to synthesize metabolites for follow-up studies. Careful optimization of reaction parameter
Directory of Open Access Journals (Sweden)
J. Laxman, Dr. K. Guru Raj
2014-05-01
Full Text Available Electrical discharge machining (EDM is a unconventional machining process for the machining of complex shapes and hard materials that are difficult of machining by conventional machining process. In this paper deals with the optimization of EDM process parameters using the grey relational analysis (GRA based on an orthogonal array for the multi response process. The experiments are conducted on Titanium super alloys with copper electrode based on the Taguchi design of experiments L27 orthogonal array by choosing various parameters such as peak current, pulse on time, pulse off time and tool lift time for EDM process to obtain multiple process responses namely Metal removal rate (MRR and Tool Wear Rate (TWR. The combination of Taguchi method with GRA enables to determine the optimal parameters for multiple response process. Gray relational analysis is used to obtain a performance index called gray relational grade to optimize the EDM process with higher MRR and lower TWR and it is clearly found that the performance of the EDM has greatly increased by optimizing the responses the influence of individual machining parameters also investigated by using analysis of variance for the grey relational grade.
Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks
DEFF Research Database (Denmark)
Heide, Janus; Zhang, Qi; Fitzek, Frank
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...
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 calculati...
Directory of Open Access Journals (Sweden)
Zhang Xishun
2013-03-01
Full Text Available Aiming at the drawbacks of the optimization and design methods and the practical production goal of least energy consumption, a new theory is raised that the gas of the layer released energy in the lifting process including two parts: dissolved-gas expansion energy and free-gas expansion energy. The motor’s input power of rod pumping system is divided into hydraulic horse power, gas expansion power, surface mechanical loss power, subsurface loss power. Using the theory of energy-conservation, the simulation model of free-gas expansion power has been established, the simulating models of the motor’s input power which are based on the energy method have been improved and the simulation precision of system efficiency has been enhanced. The entire optimization design models have been set up in which the single-well output is taken as the optimum design variable, the planed production of all oil wells in an overall oilfield as the restraint condition and the least input power of the overall oilfield as the object. Synthesizing the optimization design results of the single well and the entire oilfield, the optimal output and the optimal swabbing parameters of all wells can be got. The actual optimizing examples show that the total power consumption designed by the entire optimization method is less 12.95% than that by the single optimization method.
Optimization of Cutting Parameters for Face Milling Titanium Alloy Using MQL
Institute of Scientific and Technical Information of China (English)
AHMED Hassan; YAO Zhen-qiang
2005-01-01
When using MQL as a cooling technique, many parameters have to be adjusted. The Taguchi method was used in this study to investigate the cutting characteristics of face milling of titanium alloys using PVD-coated inserts. To find the optimal volume removed and surface roughness, an orthogonal array, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) were employed. The optimum cutting parameters was obtained. Throughout this study, it was found that the feed rate is the most influencing cutting parameter in the face milling of titanium alloys.
Joint state and parameter estimation in particle filtering and stochastic optimization
Institute of Scientific and Technical Information of China (English)
Xiaojun YANG; Keyi XING; Kunlin SHI; Quan PAN
2008-01-01
In this paper,an adaptive estimation algorithm is proposed for non-linear dynamic systems with unknown static parameters based on combination of particle filtering and Simultaneous Perturbation Stochastic Approximation(SPSA)technique.The estimations of parameters are obtained by maximum-likelihood estimation and sampling within particle filtering framework,and the SPSA is used for stochastic optimization and to approximate the gradient of the cost function.The proposed algorithm achieves combined estimation of dynamic state and static parameters of nonlinear systerns.Simulation result demonstrates the feasibility and efficiency of the proposed algorithm.
Optimal Estimation of Phenological Crop Model Parameters for Rice (Oryza sativa)
Sharifi, H.; Hijmans, R. J.; Espe, M.; Hill, J. E.; Linquist, B.
2015-12-01
Crop phenology models are important components of crop growth models. In the case of phenology models, generally only a few parameters are calibrated and default cardinal temperatures are used which can lead to a temperature-dependent systematic phenology prediction error. Our objective was to evaluate different optimization approaches in the Oryza2000 and CERES-Rice phenology sub-models to assess the importance of optimizing cardinal temperatures on model performance and systematic error. We used two optimization approaches: the typical single-stage (planting to heading) and three-stage model optimization (for planting to panicle initiation (PI), PI to heading (HD), and HD to physiological maturity (MT)) to simultaneously optimize all model parameters. Data for this study was collected over three years and six locations on seven California rice cultivars. A temperature-dependent systematic error was found for all cultivars and stages, however it was generally small (systematic error changes in cardinal temperature relative to the default values and thus optimization of cardinal temperatures did not affect systematic error or model performance. Compared to single stage optimization, three-stage optimization had little effect on determining time to PI or HD but significantly improved the precision in determining the time from HD to MT: the RMSE reduced from an average of 6 to 3.3 in Oryza2000 and from 6.6 to 3.8 in CERES-Rice. With regards to systematic error, we found a trade-off between RMSE and systematic error when optimization objective set to minimize RMSE or systematic error. Therefore, it is important to find the limits within which the trade-offs between RMSE and systematic error are acceptable, especially in climate change studies where this can prevent erroneous conclusions.
On the optimal experimental design for heat and moisture parameter estimation
Berger, Julien; Mendes, Nathan
2016-01-01
In the context of estimating material properties of porous walls based on in-site measurements and identification method, this paper presents the concept of Optimal Experiment Design (OED). It aims at searching the best experimental conditions in terms of quantity and position of sensors and boundary conditions imposed to the material. These optimal conditions ensure to provide the maximum accuracy of the identification method and thus the estimated parameters. The search of the OED is done by using the Fisher information matrix and a priori knowledge of the parameters. The methodology is applied for two case studies. The first one deals with purely conductive heat transfer. The concept of optimal experiment design is detailed and verified with 100 inverse problems for different experiment designs. The second case study combines a strong coupling between heat and moisture transfer through a porous building material. The methodology presented is based on a scientific formalism for efficient planning of experim...
Using multi-objective optimization to design parameters in electro-discharge machining by wire
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Carlos Alberto OCHOA
2015-03-01
Full Text Available The following paper describes the main objective to follow the methodology used and proposed to obtain the optimal values of WEDM process operation on the machine Robofil 310 by robust parameter design (RPD of Dr. G. Taguichi [TAGUCHI, G. 1993], through controllable factors which result in more inferences regarding the problem to noise signal (S / N, which for this study is the variability of the hardness of samples from 6061, also studied the behaviour of the output parameters as the material removal rate (MRR and surface roughness (Ra, subsequently took the RPD orthogonal array and characterized the individuals in the population, each optimal value is a gene and each possible solution is a chromosome, used multi-objective optimization using Non-dominated Sorting Genetic Algorithm to cross and mutate this population to generate better results MRR and Ra.
Khan, M A; Ngo, H H; Guo, W S; Liu, Y; Nghiem, L D; Hai, F I; Deng, L J; Wang, J; Wu, Y
2016-11-01
The anaerobic digestion process has been primarily utilized for methane containing biogas production over the past few years. However, the digestion process could also be optimized for producing volatile fatty acids (VFAs) and biohydrogen. This is the first review article that combines the optimization approaches for all three possible products from the anaerobic digestion. In this review study, the types and configurations of the bioreactor are discussed for each type of product. This is followed by a review on optimization of common process parameters (e.g. temperature, pH, retention time and organic loading rate) separately for the production of VFA, biohydrogen and methane. This review also includes additional parameters, treatment methods or special additives that wield a significant and positive effect on production rate and these products' yield.
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 calculat...... for estimating the modal damping parameters in a simply supported plane, vibrating beam model. Results show optimal number of sensors and their locations....... 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...
Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine
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
Parameter uncertainties in the design and optimization of cantilever piezoelectric energy harvesters
Franco, V. R.; Varoto, P. S.
2017-09-01
A crucial issue in piezoelectric energy harvesting is the efficiency of the mechanical to electrical conversion process. Several techniques have been investigated in order to obtain a set of optimum design parameters that will lead to the best performance of the harvester in terms of electrical power generation. Once an optimum design is reached it is also important to consider uncertainties in the selected parameters that in turn can lead to loss of performance in the energy conversion process. The main goal of this paper is to perform a comprehensive discussion of the effects of multi-parameter aleatory uncertainties on the performance and design optimization of a given energy harvesting system. For that, a typical energy harvester consisting of a cantilever beam carrying a tip mass and partially covered by piezoelectric layers on top and bottom surfaces is considered. A distributed parameter electromechanical modal of the harvesting system is formulated and validated through experimental tests. First, the SQP (Sequential Quadratic Planning) optimization is employed to obtain an optimum set of parameters that will lead to best performance of the harvester. Second, once the optimum harvester configuration is found random perturbations are introduced in the key parameters and Monte Carlo simulations are performed to investigate how these uncertainties propagate and affect the performance of the device studied. Numerically simulated results indicate that small variations in some design parameters can cause a significant variation in the output electrical power, what strongly suggests that uncertainties must be accounted for in the design of beam energy harvesting systems.
Directory of Open Access Journals (Sweden)
Gang Zhang
2017-07-01
Full Text Available The Sacramento model is widely utilized in hydrological forecast, of which the accuracy and performance are primarily determined by the model parameters, indicating the key role of parameter estimation. This paper presents a multi-step parameter estimation method, which divides the parameter estimation of Sacramento model into three steps and realizes optimization step by step. We firstly use the immune clonal selection algorithm (ICSA to solve the non-liner objective function of parameter estimation, and compare the parameter calibration result of ideal artificial data with Shuffled Complex Evolution (SCE-UA, Parallel Genetic Algorithm (PGA, and Serial Master-slaver Swarms Shuffling Evolution Algorithm Based on Particle Swarms Optimization (SMSE-PSO. The comparison result shows that ICSA has the best convergence, efficiency and precision. Then we apply ICSA to the parameter estimation of single-step and multi-step Sacramento model and simulate 32 floods based on application examples of Dongyang and Tantou river basins for validation. It is clearly shown that the results of multi-step method based on ICSA show higher accuracy and 100% qualified rate, indicating its higher precision and reliability, which has great potential to improve Sacramento model and hydrological forecast.
Optimization of injection molding process parameters for a plastic cell phone housing component
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.
Land cover classification using random forest with genetic algorithm-based parameter optimization
Ming, Dongping; Zhou, Tianning; Wang, Min; Tan, Tian
2016-07-01
Land cover classification based on remote sensing imagery is an important means to monitor, evaluate, and manage land resources. However, it requires robust classification methods that allow accurate mapping of complex land cover categories. Random forest (RF) is a powerful machine-learning classifier that can be used in land remote sensing. However, two important parameters of RF classification, namely, the number of trees and the number of variables tried at each split, affect classification accuracy. Thus, optimal parameter selection is an inevitable problem in RF-based image classification. This study uses the genetic algorithm (GA) to optimize the two parameters of RF to produce optimal land cover classification accuracy. HJ-1B CCD2 image data are used to classify six different land cover categories in Changping, Beijing, China. Experimental results show that GA-RF can avoid arbitrariness in the selection of parameters. The experiments also compare land cover classification results by using GA-RF method, traditional RF method (with default parameters), and support vector machine method. When the GA-RF method is used, classification accuracies, respectively, improved by 1.02% and 6.64%. The comparison results show that GA-RF is a feasible solution for land cover classification without compromising accuracy or incurring excessive time.
Energy Technology Data Exchange (ETDEWEB)
Zhu, D.L., E-mail: dlzhu@szu.edu.cn [College of Materials Science and Engineering, Shenzhen University, Shenzhen 518060 (China); Shenzhen Key Laboratory of Special Functional Materials, Shenzhen University, Shenzhen 518060 (China); Wang, Q.; Han, S.; Cao, P.J.; Liu, W.J.; Jia, F.; Zeng, Y.X.; Ma, X.C. [College of Materials Science and Engineering, Shenzhen University, Shenzhen 518060 (China); Shenzhen Key Laboratory of Special Functional Materials, Shenzhen University, Shenzhen 518060 (China); Lu, Y.M., E-mail: ymlu@szu.edu.cn [College of Materials Science and Engineering, Shenzhen University, Shenzhen 518060 (China); Shenzhen Key Laboratory of Special Functional Materials, Shenzhen University, Shenzhen 518060 (China)
2014-04-01
Highlights: • ρ in GZO films significantly reduces after optimization of parameters by Taguchi method. • ANOVA shows that vacuum annealing is the most significant influencing parameter on ρ. • XPS and PL results show that ρ decrease after annealing is due to the variation of oxygen. • The content of absorbed oxygen and O{sub i} as acceptors will decrease after annealing. - Abstract: Ga-doped ZnO (GZO) transparent conductive thin films have been deposited on quartz substrates by r.f. magnetron sputtering. The optimization of four process parameters (i.e., vacuum annealing temperature, r.f. power, sputtering pressure, and Ar flow rate) based on Taguchi method has been systematically studied in order to obtain the minimum resistivity. Compared to the optimal parameter set selected from orthogonal array by Taguchi method, the optimal prediction design can receive an improvement of 22.3% in electrical resistivity, and the corresponding resistivity is 8.08 × 10{sup −4} Ω cm. The analysis of variance shows that vacuum annealing temperature is the most significant influencing parameter on the electrical properties in GZO films. X-ray photoelectron spectroscopy and photoluminescence results exhibit that the enhancement in electrical conductivity after vacuum annealing is ascribed to the variation of the chemical states of oxygen in GZO films. With the increase in annealing temperature, the content of absorbed oxygen and interstitial oxygen as acceptors will decrease.
Effects of AV-delay optimization on hemodynamic parameters in patients with VDD pacemakers.
Krychtiuk, Konstantin A; Nürnberg, Michael; Volker, Romana; Pachinger, Linda; Jarai, Rudolf; Freynhofer, Matthias K; Wojta, Johann; Huber, Kurt; Weiss, Thomas W
2014-05-01
Atrioventricular (AV) delay optimization improves hemodynamics and clinical parameters in patients treated with cardiac resynchronization therapy and dual-chamber-pacemakers (PM). However, data on optimizing AV delay in patients treated with VDD-PMs are scarce. We, therefore, investigated the acute and chronic effects of AV delay optimization on hemodynamics in patients treated with VDD-PMs due to AV-conduction disturbances. In this prospective, single-center interventional trial, we included 64 patients (38 men, 26 women, median age: 77 (70-82) years) with implanted VDD-PM. AV-delay optimization was performed using a formula based on the surface electrocardiogram (ECG). Hemodynamic parameters (stroke volume (SV), cardiac output (CO), heart rate (HR), and blood pressure (BP)) were measured at baseline and follow-up after 3 months using impedance cardiography. Using an ECG formula for AV-delay optimization, the AV interval was decreased from 180 (180-180) to 75 (75-100) ms. At baseline, AV-delay optimization led to a significant increase of both SV (71.3 ± 15.8 vs. 55.3 ± 12.7 ml, p AV delay vs. nominal AV interval, respectively) and CO (5.1 ± 1.4 vs. 3.9 ± 1.0 l/min, p AV-delay optimization in patients treated with VDD-PMs exhibits immediate beneficial effects on hemodynamic parameters that are sustained for 3 months.
Zhang, Chuan-Xin; Zhang, Hao-Wei; Shuai, Yong; Tan, He-Ping
2016-01-01
Considering features of stellar spectral radiation and survey explorers, we established a computational model for stellar effective temperatures, detected angular parameters, and gray rates. Using known stellar flux data in some band, we estimated stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization (SPSO). We first verified the reliability of SPSO, and then determined reasonable parameters that produced highly accurate estimates under certain gray deviation levels. Finally, we calculated 177,860 stellar effective temperatures and detected angular parameters using the Midcourse Space Experiment (MSX) catalog data. These derived stellar effective temperatures were accurate when we compared them to known values from literatures. This research made full use of catalog data and presented an original technique for studying stellar characteristics. It proposed a novel method for calculating stellar effective temperatures and detected angular parameters, and pro...
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ANIL CHOUBEY
2012-07-01
Full Text Available In this paper Taguchi method is applied to find optimum process parameters for end milling while machining of mild steel. A L9 orthogonal array, taguchi method and analysis of variance (ANOVA are used to formulate the experimental layout, to analyses the effect of each parameter on the machining characteristics and to predict the optimal choice for each end milling parameter such as spindle speed, feed rate, depth of cut and width of cut, and analysed the effect of these parameter on the material removal rate (MRR and surfaceroughness (SR. Results obtained by taguchi method match with ANOVA and cutting speed are highly influencing parameter. The analysis of the taguchi method reveals that, in general the spindle speedsignificantly affects the SR, while, the feed mainly affects the MRR. Experimental results are provided to verify this approach.
Zhang, Chuan-Xin; Yuan, Yuan; Zhang, Hao-Wei; Shuai, Yong; Tan, He-Ping
2016-09-01
Considering features of stellar spectral radiation and sky surveys, we established a computational model for stellar effective temperatures, detected angular parameters and gray rates. Using known stellar flux data in some bands, we estimated stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization (SPSO). We first verified the reliability of SPSO, and then determined reasonable parameters that produced highly accurate estimates under certain gray deviation levels. Finally, we calculated 177 860 stellar effective temperatures and detected angular parameters using data from the Midcourse Space Experiment (MSX) catalog. These derived stellar effective temperatures were accurate when we compared them to known values from literatures. This research makes full use of catalog data and presents an original technique for studying stellar characteristics. It proposes a novel method for calculating stellar effective temperatures and detecting angular parameters, and provides theoretical and practical data for finding information about radiation in any band.
Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.
Yuan, Haidong; Fung, Chi-Hang Fred
2015-09-11
Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.
Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.
2016-09-01
The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.
Optimizing Friction Stir Welding via Statistical Design of Tool Geometry and Process Parameters
Blignault, C.; Hattingh, D. G.; James, M. N.
2012-06-01
This article considers optimization procedures for friction stir welding (FSW) in 5083-H321 aluminum alloy, via control of weld process parameters and tool design modifications. It demonstrates the potential utility of the "force footprint" (FF) diagram in providing a real-time graphical user interface (GUI) for process optimization of FSW. Multiple force, torque, and temperature responses were recorded during FS welding using 24 different tool pin geometries, and these data were statistically analyzed to determine the relative influence of a number of combinations of important process and tool geometry parameters on tensile strength. Desirability profile charts are presented, which show the influence of seven key combinations of weld process variables on tensile strength. The model developed in this study allows the weld tensile strength to be predicted for other combinations of tool geometry and process parameters to fall within an average error of 13%. General guidelines for tool profile selection and the likelihood of influencing weld tensile strength are also provided.
Directory of Open Access Journals (Sweden)
ATUL KUMAR
2012-06-01
Full Text Available Wire electrical discharge machining (WEDM is widely used in machining of conductive materials when precision is of primary significance. Wire-cut electric discharge machining of Skd 61alloy has been considered in the present work. Experimentation has been completed by using Taguchi’s L18 (21x37 orthogonal array under different conditions of parameters. Optimal combinations of parameters were obtained by this technique. The study shows that with the minimum number of experiments the complete problem can be solvedwhen compared to full factorial design. Experimental results make obvious that the machining model is proper and the Taguchi’s method satisfies the practical conditions. The results obtained are analyzed for the selection of an optimal combination of WEDM parameters for proper machining of Skd 61 alloy to achieve better surface finish. Different analysis was made on the data obtained from the experiments.
Directory of Open Access Journals (Sweden)
Jun Wang
2016-01-01
Full Text Available This paper proposes an improved cuckoo search (ICS algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior.
Development of a parameter optimization technique for the design of automatic control systems
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.
Wang, Jun; Zhou, Bihua; Zhou, Shudao
2016-01-01
This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior.
Institute of Scientific and Technical Information of China (English)
A.K.LAKSHMINARAYANAN; V.BALASUBRAMANIAN
2008-01-01
Taguchi approach was applied to determine the most influential control factors which will yield better tensile strength of the joints of friction stir welded RDE-40 aluminium alloy. In order to evaluate the effect of process parameters such as tool rotational speed, traverse speed and axial force on tensile strength of friction stir welded RDE-40 aluminium alloy, Taguchi parametric design and optimization approach was used. Through the Taguchi parametric design approach, the optimum levels of process parameters were determined. The results indicate that the rotational speed, welding speed and axial force are the significant parameters in deciding the tensile strength of the joint. The predicted optimal value of tensile strength of friction stir welded RDE-40 aluminium alloy is 303 MPa. The results were confirmed by further experiments.
DEFF Research Database (Denmark)
Luo, Yangjun; Wu, Xiaoxiang; Zhou, Mingdong
2015-01-01
on a probability-interval mixed reliability model, the imprecision of design parameters is modeled as interval uncertainties fluctuating within allowable tolerance bounds. The optimization model is defined as to minimize the total manufacturing cost under mixed reliability index constraints, which are further...... transformed into their equivalent formulations by using the performance measure approach. The optimization problem is then solved with the sequential approximate programming. Meanwhile, a numerically stable algorithm based on the trust region method is proposed to efficiently update the target performance......Both structural sizes and dimensional tolerances strongly influence the manufacturing cost and the functional performance of a practical product. This paper presents an optimization method to simultaneously find the optimal combination of structural sizes and dimensional tolerances. Based...
Connecting parameters optimization on unsymmetrical twin-tower structure linked by sky-bridge
Institute of Scientific and Technical Information of China (English)
孙黄胜; 刘默涵; 朱宏平
2014-01-01
Based on a simplified 3-DOF model of twin-tower structure linked by a sky-bridge, the frequency response functions, the displacement power spectral density (PSD) functions, and the time-averaged total vibration energy were derived, by assuming the white noise as the earthquake excitation. The effects of connecting parameters, such as linking stiffness ratio and linking damping ratio, on the structural vibration responses were then studied, and the optimal connecting parameters were obtained to minimize the vibration energy of either the independent monomer tower or the integral structure. The influences of sky-bridge elevation position on the optimal connecting parameters were also discussed. Finally, the distribution characteristics of the top displacement PSD and the structural responses, excited by El Centro, Taft and artificial waves, were compared in both frequency and time domain. It is found that the connecting parameters at either end of connection interactively affect the responses of the towers. The optimal connecting parameters can greatly improve the damping connections on their seismic reduction effectiveness, but are unable to reduce the seismic responses of the towers to the best extent simultaneously. It is also indicated that the optimal connecting parameters derived from the simplified 3-DOF model are applicable for two multi-story structures linked by a sky-bridge with dampers. The seismic reduction effectiveness obtained varies from 0.3 to 1.0 with different sky-bridge mass ratio. The displacement responses of the example structures are reduced by approximately 22% with sky-bridge connections.
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
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.
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.
Caglar, Yasemin; Gorgun, Kamuran; Aksoy, Seval
2015-03-05
ZnO nanopowders were synthesized via microwave-assisted hydrothermal method at different deposition (microwave irradiation) times and pH values. The effects of pH and deposition (microwave irradiation) time on the crystalline structure and orientation of the ZnO nanopowders have been investigated by X-ray diffraction (XRD) study. XRD observations showed that the crystalline quality of ZnO nanopowders increased with increasing pH value. The crystallite size and texture coefficient values of ZnO nanopowders were calculated. The structural quality of ZnO nanopowder was improved by deposition parameters. Field emission scanning electron microscope (FESEM) was used to analyze the surface morphology of the ZnO nanopowders. Microwave irradiation time and pH value showed a significant effect on the surface morphology.
Directory of Open Access Journals (Sweden)
Bogner Ludwig
2007-09-01
Full Text Available Abstract Background 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. Methods 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. Results 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 0.05. 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 Renormalization of the IM plans to the mean of the dose to 95% of the PTV (D95 of the DSS plans, resulted in similar target coverage and dose to the parotids for both
Process Parameter Optimization for Wobbling Laser Spot Welding of Ti6Al4V Alloy
Vakili-Farahani, F.; Lungershausen, J.; Wasmer, K.
Laser beam welding (LBW) coupled with "wobble effect" (fast oscillation of the laser beam) is very promising for high precision micro-joining industry. For this process, similarly to the conventional LBW, the laser welding process parameters play a very significant role in determining the quality of a weld joint. Consequently, four process parameters (laser power, wobble frequency, number of rotations within a single laser pulse and focused position) and 5 responses (penetration, width, heat affected zone (HAZ), area of the fusion zone, area of HAZ and hardness) were investigated for spot welding of Ti6Al4V alloy (grade 5) using a design of experiments (DoE) approach. This paper presents experimental results showing the effects of variating the considered most important process parameters on the spot weld quality of Ti6Al4V alloy. Semi-empirical mathematical models were developed to correlate laser welding parameters to each of the measured weld responses. Adequacies of the models were then examined by various methods such as ANOVA. These models not only allows a better understanding of the wobble laser welding process and predict the process performance but also determines optimal process parameters. Therefore, optimal combination of process parameters was determined considering certain quality criteria set.
Schmidt, S.; Hänninen, T.; Wissting, J.; Hultman, L.; Goebbels, N.; Santana, A.; Tobler, M.; Högberg, H.
2017-05-01
The residual coating stress and its control is of key importance for the performance and reliability of silicon nitride (SiNx) coatings for biomedical applications. This study explores the most important deposition process parameters to tailor the residual coating stress and hence improve the adhesion of SiNx coatings deposited by reactive high power impulse magnetron sputtering (rHiPIMS). Reactive sputter deposition and plasma characterization were conducted in an industrial deposition chamber equipped with pure Si targets in N2/Ar ambient. Reactive HiPIMS processes using N2-to-Ar flow ratios of 0 and 0.28-0.3 were studied with time averaged positive ion mass spectrometry. The coatings were deposited to thicknesses of 2 μm on Si(001) and to 5 μm on polished CoCrMo disks. The residual stress of the X-ray amorphous coatings was determined from the curvature of the Si substrates as obtained by X-ray diffraction. The coatings were further characterized by X-ray photoelectron spectroscopy, scanning electron microscopy, and nanoindentation in order to study their elemental composition, morphology, and hardness, respectively. The adhesion of the 5 μm thick coatings deposited on CoCrMo disks was assessed using the Rockwell C test. The deposition of SiNx coatings by rHiPIMS using N2-to-Ar flow ratios of 0.28 yield dense and hard SiNx coatings with Si/N ratios <1. The compressive residual stress of up to 2.1 GPa can be reduced to 0.2 GPa using a comparatively high deposition pressure of 600 mPa, substrate temperatures below 200 °C, low pulse energies of <2.5 Ws, and moderate negative bias voltages of up to 100 V. These process parameters resulted in excellent coating adhesion (ISO 0, HF1) and a low surface roughness of 14 nm for coatings deposited on CoCrMo.
Daneshvar, N; Khataee, A R; Rasoulifard, M H; Pourhassan, M
2007-05-08
In this paper, optimization of biological decolorization of synthetic dye solution containing Malachite Green was investigated. The effect of temperature, initial pH of the solution, type of algae, dye concentration and time of the reaction was studied and optimized using Taguchi method. Sixteen experiments were required to study the effect of parameters on biodegradation of the dye. Each of experiments was repeated three times to calculate signal/noise (S/N). Our results showed that initial pH of the solution was the most effective parameter in comparison with others and the basic pH was favorable. In this study, we also optimized the experimental parameters and chose the best condition by determination effective factors. Based on the S/N ratio, the optimized conditions for dye removal were temperature 25 degrees C, initial pH 10, dye concentration 5 ppm, algae type Chlorella and time 2.5h. The stability and efficiency of Chlorella sp. in long-term repetitive operations were also examined.
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.
Zeng, Rongping; Badano, Aldo; Myers, Kyle J.
2017-04-01
We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hotelling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre-Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.
Optimal likelihood-based matching of volcanic sources and deposits in the Auckland Volcanic Field
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.
Simonov, V. A.; Kovyazin, S. V.; Terenya, E. O.; Maslennikov, V. V.; Zaykov, V. V.; Maslennikova, S. P.
2006-10-01
Melt and fluid inclusions in minerals have been studied and physicochemical parameters of magmatic processes and hydrothermal systems estimated at the Yaman-Kasy copper massive sulfide deposit in the southern Urals. It was established that relatively low-temperature (910-945°C) rhyodacitic melts belonging to the tholeiitic series and containing 2.7-5.2 wt % water participated in the formation of the igneous complexes that host the Yaman-Kasy deposit. As follows from ion microprobe results, these silicic magmas had a primitive character. In the distribution of trace elements, including REE, the rhyodacites are closer to basaltic rather than silicic volcanic rocks, and they are distinguished in this respect from the igneous rocks from other massive sulfide deposits of the Urals and the Rudny Altai. Two types of solutions actively took part in the formation of hydrothermal systems: (1) solutions with a moderate salinity (5-10 wt % dissolved salts) and (2) solutions with a low salinity (a value close to that of seawater or even lower). Concentrated fluids with more than 11.5 wt % dissolved salts were much less abundant. Hydrothermal solutions heated to 130-160, 160-270, or occasionally 280-310°C predominated in ore formation. The sequence of mineral-forming processes at the Yaman-Kasy deposit is demonstrated. Mineral assemblages were formed with an inversion of the parameters characterizing ore-forming solutions. An increase in the temperature and salinity of solutions at the early stages was followed by a decrease at the final stages. The evolution of the hydrothermal system at the Yaman-Kasy deposit has much in common with the parameters of black smokers in the present-day Pacific backarc basins.
Directory of Open Access Journals (Sweden)
Madgulkar A
2009-01-01
Full Text Available The purpose of the present work was to prepare buccal adhesive tablets of miconazole nitrate. The simplex centroid experimental design was used to arrive at optimum ratio of carbopol 934P, hydroxypropylmethylcellulose K4M and polyvinylpyrollidone, which will provide desired drug release and mucoadhesion. Swelling index, mucoadhesive strength and in vitro drug release of the prepared tablet was determined. The drug release and bioadhesion was dependent on type and relative amounts of the polymers. The optimized combination was subjected to in vitro antifungal activity, transmucosal permeation, drug deposition in mucosa, residence time and bioadhesion studies. IR spectroscopy was used to investigate any interaction between drug and excipients. Dissolution of miconazole from tablets was sustained for 6 h. based on the results obtained, it can be concluded that the prepared slow release buccoadhesive tablets of miconazole would markedly prolong the duration of antifungal activity. Comparison of in vitro antifungal activity of tablet with marketed gel showed that drug concentrations above the minimum inhibitory concentration were achieved immediately from both formulations but release from tablet was sustained up to 6 h, while the gel showed initially fast drug release, which did not sustain later. Drug permeation across buccal mucosa was minimum from the tablet as well as marketed gel; the deposition of drug in mucosa was higher in case of tablet. In vitro residence time and bioadhesive strength of tablet was higher than gel. Thus the buccoadhesive tablet of miconazole nitrate may offer better control of antifungal activity as compared to the gel formulation.
Sun, Jun; Fang, Wei; Wu, Xiaojun; Palade, Vasile; Xu, Wenbo
2012-01-01
Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little analysis on how it works in detail. This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms of probability measure. Since the particle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of the theoretical analysis is to find out the upper bound of the CE coefficient, within which the value of the CE coefficient selected can guarantee the convergence or boundedness of the particle's position. In the experimental analysis, the theoretical results are first validated by stochastic simulations for the particle's behavior. Then, based on the derived upper bound of the CE coefficient, we perform empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient, in order to obtain generally good algorithmic performance in real world applications. Finally, a further performance comparison between QPSO and other variants of PSO on the benchmarks is made to show the efficiency of the QPSO algorithm with the proposed parameter control and selection methods.
Mechanism Analysis and Parameter Optimization of Mega-Sub-Isolation System
Directory of Open Access Journals (Sweden)
Xiangxiu Li
2016-01-01
Full Text Available The equation of motion of mega-sub-isolation system is established. The working mechanism of the mega-sub-isolation system is obtained by systematically investigating its dynamic characteristics corresponding to various structural parameters. Considering the number and location of the isolated substructures, a procedure to optimally design the isolator parameters of the mega-sub-isolation system is put forward based on the genetic algorithm with base shear as the optimization objective. The influence of the number and locations of isolated substructures on the control performance of mega-sub-isolation system has also been investigated from the perspective of energy. Results show that, with increase in substructure mass, the working mechanism of the mega-sub-isolation system is changed from tuned vibration absorber and energy dissipation to seismic isolation. The locations of the isolated substructures have little influence on the optimal frequency ratio but have great influence on the optimal damping ratio, while the number of isolated substructures shows great impact on both the optimal frequency ratio and damping ratio. When the number of the isolated substructures is determined, the higher the isolated substructures, the more the energy that will be consumed by the isolation devices, and with the increase of the number of isolated substructures, the better control performance can be achieved.
Mishra, Gayatri; Joshi, Dinesh C; Mohapatra, Debabandya
2015-12-01
Sorghum is a popular healthy snack food. Popped sorghum was prepared in a domestic microwave oven. A 3 factor 3 level Box and Behneken design was used to optimize the pretreatment conditions. Grains were preconditioned to 12-20 % moisture content by the addition of 0-2 % salt solutions. Oil was applied (0-10 % w/w) to the preconditioned grains. Optimization of the pretreatments was based on popping yield, volume expansion ratio, and sensory score. The optimized condition was found at 16.62 % (wb), 0.55 % salt and 10 % oil with popping yield of 82.228 %, volume expansion ratio of 14.564 and overall acceptability of 8.495. Further, the microwave process parameters were optimized using a 2 factor 3 level design having microwave power density ranging from 9 to 18 W/g and residence time ranging from 100 to 180 s. For the production of superior quality pop sorghum, the optimized microwave process parameters were microwave power density of 18 Wg(-1) and residence time of 140 s.
Institute of Scientific and Technical Information of China (English)
Yu-xiang LI; Yin-liang ZHAO‡; Bin LIU; Shuo JI
2015-01-01
Thread partition plays an important role in speculative multithreading (SpMT) for automatic parallelization of ir-regular programs. Using unified values of partition parameters to partition different applications leads to the fact that every ap-plication cannot own its optimal partition scheme. In this paper, five parameters affecting thread partition are extracted from heuristic rules. They are the dependence threshold (DT), lower limit of thread size (TSL), upper limit of thread size (TSU), lower limit of spawning distance (SDL), and upper limit of spawning distance (SDU). Their ranges are determined in accordance with heuristic rules, and their step-sizes are set empirically. Under the condition of setting speedup as an objective function, all com-binations of five threshold values form the solution space, and our aim is to search for the best combination to obtain the best thread granularity, thread dependence, and spawning distance, so that every application has its best partition scheme. The issue can be attributed to a single objective optimization problem. We use the artificial immune algorithm (AIA) to search for the optimal solution. On Prophet, which is a generic SpMT processor to evaluate the performance of multithreaded programs, Olden bench-marks are used to implement the process. Experiments show that we can obtain the optimal parameter values for every benchmark, and Olden benchmarks partitioned with the optimized parameter values deliver a performance improvement of 3.00%on a 4-core platform compared with a machine learning based approach, and 8.92%compared with a heuristics-based approach.
Basak, Amrita; Acharya, Ranadip; Das, Suman
2016-08-01
This paper focuses on additive manufacturing (AM) of single-crystal (SX) nickel-based superalloy CMSX-4 through scanning laser epitaxy (SLE). SLE, a powder bed fusion-based AM process was explored for the purpose of producing crack-free, dense deposits of CMSX-4 on top of similar chemistry investment-cast substrates. Optical microscopy and scanning electron microscopy (SEM) investigations revealed the presence of dendritic microstructures that consisted of fine γ' precipitates within the γ matrix in the deposit region. Computational fluid dynamics (CFD)-based process modeling, statistical design of experiments (DoE), and microstructural characterization techniques were combined to produce metallurgically bonded single-crystal deposits of more than 500 μm height in a single pass along the entire length of the substrate. A customized quantitative metallography based image analysis technique was employed for automatic extraction of various deposit quality metrics from the digital cross-sectional micrographs. The processing parameters were varied, and optimal processing windows were identified to obtain good quality deposits. The results reported here represent one of the few successes obtained in producing single-crystal epitaxial deposits through a powder bed fusion-based metal AM process and thus demonstrate the potential of SLE to repair and manufacture single-crystal hot section components of gas turbine systems from nickel-based superalloy powders.
Oby, Emily R.; Perel, Sagi; Sadtler, Patrick T.; Ruff, Douglas A.; Mischel, Jessica L.; Montez, David F.; Cohen, Marlene R.; Batista, Aaron P.; Chase, Steven M.
2016-06-01
Objective. A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach. We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent
Inflatable Wing Design Parameter Optimization Using Orthogonal Testing and Support Vector Machines
Institute of Scientific and Technical Information of China (English)
WANG Zhifei; WANG Hua
2012-01-01
The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels.To overcome some of the defects of the inflatable wing parameter design method,this paper proposes an optimization design scheme based on orthogonal testing and support vector machines (SVMs).Orthogonal testing design is used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iterations and improve the identification accuracy and efficiency.Orthogonal tests consisting of three factors and three levels are designed to analyze the parameters of pressure,uniform applied load and the number of chambers that affect the bending response of inflatable wings.An SVM intelligent model is established and limited orthogonal test swatches are studied.Thus,the precise relationships between each parameter and product quality features,as well the signal-to-noise ratio (SNR),can be obtained.This can guide general technological design optimization.
Effect of experimental parameters on optimal reflection of light from opaque media
Anderson, Benjamin R.; Gunawidjaja, Ray; Eilers, Hergen
2016-01-01
Previously we considered the effect of experimental parameters on optimized transmission through opaque media using spatial light modulator (SLM)-based wavefront shaping. In this study we consider the opposite geometry, in which we optimize reflection from an opaque surface such that the backscattered light is focused onto a spot on an imaging detector. By systematically varying different experimental parameters (genetic algorithm iterations, bin size, SLM active area, target area, spot size, and sample angle with respect to the optical axis) and optimizing the reflected light we determine how each parameter affects the intensity enhancement. We find that the effects of the experimental parameters on the enhancement are similar to those measured for a transmissive geometry, but with the exact functional forms changed due to the different geometry and the use of a genetic algorithm instead of an iterative algorithm. Additionally, we find preliminary evidence of greater enhancements than predicted by random matrix theory, suggesting a possibly new physical mechanism to be investigated in future work.
Optimization of {sup 210}Po estimation in environmental samples using an improved deposition unit
Energy Technology Data Exchange (ETDEWEB)
Dubey, Jay Singh; Sahoo, Sunil Kumar; Mohapatra, Swagatika; Lenka, Pradyumna; Patra, Aditi Chakravarty; Thakur, Virender Kumar; Ravi, Pazhayath Mana; Tripathi, Raj Mangal [Bhabha Atomic Research Centre, Trombay, Mumbai (India). Health Physics Div.
2015-06-01
Measurement of {sup 210}Po in environmental matrices is important due to its very high specific activity, present in every compartment of the environment due to a daughter product of uranium ({sup 238}U), accumulative and highly toxic in nature. Conventional method for {sup 210}Po estimation is by auto-deposition onto both sides of a silver disc followed by alpha spectrometry of both the sides. A new deposition unit having the facility to hold the silver disc and magnetic stirring bar has designed and fabricated for {sup 210}Po estimation in which only one side is counted. In the conventional method, the total activity is distributed to the both sides of the silver disc and more counting time is required whereas in the improved deposition unit, only one side contain all the activity so that one time counting is required with better statistical significance. The same has been observed in spike recovery and water sample assessment. The tracer recovery in the conventional method was 72%-88% and 70%-85% whereas for the new deposition the recovery is 87%-99% and 78%-94% for spike recovery study and environmental samples, respectively. Certified tracers were analysed for the assurance of the reliability of the method and the results were in good agreement with the recommended value with a relative error <20%. The MDA of the method is 1.5 mBq for the estimation of {sup 210}Po at 3σ confidence level, 86400 s. counting time and 100 ml of water sample, taking the detector efficiency and chemical yield into consideration. The results obtained from both the methods were compared statistically. χ{sup 2} test, repeatability parameters, relative bias measurement and linearity test was performed for both the methods. The % difference between the two methods in terms of linearity is 0.2%. From the χ{sup 2} test it can be concluded that the measured data by two methods falls within 99% confidence interval. The modified deposition unit enhance the statistical significance, reduce
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.
Directory of Open Access Journals (Sweden)
G.G. Bhatt
2011-01-01
Full Text Available We have optimized and automated the experimental in-situ reflectivity measurement system for the laser diode (LD facet coating. We have also developed a reflectivity-simulator program that gives the reflectivity data as a function of the thickness of the film (single or multi-layer for a given wavelength, which aids in optimizing the above parameters while monitoring the coating of the films in-situ. We report the results for the in-situ reflectivity of a single layer MgF2 and a quarter-wave optical thick three bi-layer pairs of MgF2 and silicon on GaAs as a substrate for both the cases. We have achieved up to 83 % experimental reflectivity for the latter case.
Algorithms of D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters
Widiharih, Tatik; Haryatmi, Sri; Gunardi, Wilandari, Yuciana
2016-02-01
Morgan Mercer Flodin (MMF) model is used in many areas including biological growth studies, animal and husbandry, chemistry, finance, pharmacokinetics and pharmacodynamics. Locally D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters are investigated. We used the Generalized Equivalence Theorem of Kiefer and Wolvowitz to determine D-optimality criteria. Number of roots for standardized variance are determined using Tchebysheff system concept and it is used to decide that the design is minimally supported design. In these models, designs are minimally supported designs with uniform weight on its support, and the upper bound of the design region is a support point.
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
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.
DEFF Research Database (Denmark)
Tutum, Cem Celal; Schmidt, Henrik Nikolaj Blicher; Hattel, Jesper Henri
2008-01-01
, 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......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...
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.
Reimer, Joscha; Piwonski, Jaroslaw; Slawig, Thomas
2016-04-01
The statistical significance of any model-data comparison strongly depends on the quality of the used data and the criterion used to measure the model-to-data misfit. The statistical properties (such as mean values, variances and covariances) of the data should be taken into account by choosing a criterion as, e.g., ordinary, weighted or generalized least squares. Moreover, the criterion can be restricted onto regions or model quantities which are of special interest. This choice influences the quality of the model output (also for not measured quantities) and the results of a parameter estimation or optimization process. We have estimated the parameters of a three-dimensional and time-dependent marine biogeochemical model describing the phosphorus cycle in the ocean. For this purpose, we have developed a statistical model for measurements of phosphate and dissolved organic phosphorus. This statistical model includes variances and correlations varying with time and location of the measurements. We compared the obtained estimations of model output and parameters for different criteria. Another question is if (and which) further measurements would increase the model's quality at all. Using experimental design criteria, the information content of measurements can be quantified. This may refer to the uncertainty in unknown model parameters as well as the uncertainty regarding which model is closer to reality. By (another) optimization, optimal measurement properties such as locations, time instants and quantities to be measured can be identified. We have optimized such properties for additional measurement for the parameter estimation of the marine biogeochemical model. For this purpose, we have quantified the uncertainty in the optimal model parameters and the model output itself regarding the uncertainty in the measurement data using the (Fisher) information matrix. Furthermore, we have calculated the uncertainty reduction by additional measurements depending on time
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)
DEFF Research Database (Denmark)
Pauwels, Valentijn; Balenzano, Anna; Satalino, Giuseppe
2009-01-01
It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has...... been focused on the retrieval of land and biogeophysical parameters (e.g., soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such its, for example, hydraulic conductivity, values, through remote sensing. This is due to the fact...... that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through...
Directory of Open Access Journals (Sweden)
Filimonova Ekaterina Aleksandrovna
2012-10-01
The author suggests splitting the aforementioned parameters into the two groups, namely, natural parameters and value-related parameters that are introduced to assess the costs of development, transportation, construction and operation of a structure, as well as the costs of its potential failure. The author proposes a new improved methodology for the identification of the above parameters that ensures optimal solutions to non-linear objective functions accompanied by non-linear restrictions that are critical to the design of reinforced concrete structures. Any structural failure may be interpreted as the bounce of a random process associated with the surplus bearing capacity into the negative domain. Monte Carlo numerical methods make it possible to assess these bounces into the unacc eptable domain.
Directory of Open Access Journals (Sweden)
R. SUDHAKARAN
2012-04-01
Full Text Available This paper presents a study on optimization of process parameters using particle swarm optimization to minimize angular distortion in 202 grade stainless steel gas tungsten arc welded plates. Angular distortion is a major problem and most pronounced among different types of distortion in butt welded plates. The process control parameters chosen for the study are welding gun angle, welding speed, plate length, welding current and gas flow rate. The experiments were conducted using design of experiments technique with five factor five level central composite rotatable design with full replication technique. A mathematical model was developed correlating the process parameters with angular distortion. A source code was developed in MATLAB 7.6 to do the optimization. The optimal process parameters gave a value of 0.0305° for angular distortion which demonstrates the accuracy of the model developed. The results indicate that the optimized values for the process parameters are capable of producing weld with minimum distortion.
Rank evaluation of the Neyveli lignite deposit on the basis of reflectance parameter
Energy Technology Data Exchange (ETDEWEB)
Singh, A.; Singh, B.D. (Birbal Sahni Institute of Paleobotany, Lucknow (India))
1994-10-01
The Neyveli field is well known for Tertiary lignite deposits in India. The reflectance of organic constituents (huminite macerals) has been measured to find out organic maturation level (rank) of the main lignite seam lying either at same time level or at different time levels in space. The deposits are of sub-bituminous C stage (ASTM) with the mean reflectance (R[sub o,max.] in oil) range from 0.34 to 0.42% (average 0.39%). Evidence from rank study indicates that the quality of lignite deteriorates towards southern part of the field
Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.
2012-11-01
Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model, and applicability and efficiency of the respective methods were examined. One is a finite difference method based on a traditional gradient descent approach, while the other adopts genetic algorithms as an example of stochastic approaches. Several series of parameter optimization experiments were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. The finite difference method fails to estimate optimal parameters due to an ill-shaped nature of the cost function, whereas the genetic algorithms can effectively estimate near optimal parameters with a practical number of iterations. The results of the study indicate that a sophisticated stochastic approach is of practical use to a parameter optimization of a coupled ocean-sea ice model.
Tian, Zhen; Jia, Xun; Jiang, Steve B
2013-01-01
In the treatment plan optimization for intensity modulated radiation therapy (IMRT), dose-deposition coefficient (DDC) matrix is often pre-computed to parameterize the dose contribution to each voxel in the volume of interest from each beamlet of unit intensity. However, due to the limitation of computer memory and the requirement on computational efficiency, in practice matrix elements of small values are usually truncated, which inevitably compromises the quality of the resulting plan. A fixed-point iteration scheme has been applied in IMRT optimization to solve this problem, which has been reported to be effective and efficient based on the observations of the numerical experiments. In this paper, we aim to point out the mathematics behind this scheme and to answer the following three questions: 1) whether the fixed-point iteration algorithm converges or not? 2) when it converges, whether the fixed point solution is same as the original solution obtained with the complete DDC matrix? 3) if not the same, wh...
Capdevielle, Aurélie; Sýkorová, Eva; Biscans, Béatrice; Béline, Fabrice; Daumer, Marie-Line
2013-01-15
A sustainable way to recover phosphorus (P) in swine wastewater involves a preliminary step of P dissolution followed by the separation of particulate organic matter. The next two steps are firstly the precipitation of struvite crystals done by adding a crystallization reagent (magnesia) and secondly the filtration of the crystals. A design of experiments with five process parameters was set up to optimize the size of the struvite crystals in a synthetic swine wastewater. More than 90% of P was recovered as large crystals of struvite in optimal conditions which were: low Mg:Ca ratio (2.25:1), the leading parameter, high N:P ratio (3:1), moderate stirring rate (between 45 and 90 rpm) and low temperature (below 20 °C).These results were obtained despite the presence of a large amount of calcium and using a cheap reactant (MgO). The composition of the precipitates was identified by Raman analysis and solid dissolution. Results showed that amorphous calcium phosphate (ACP) co-precipitated with struvite and that carbonates were incorporated with solid fractions.
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.
Directory of Open Access Journals (Sweden)
Suleyman Neseli
2014-10-01
Full Text Available This research outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in drilling of AISI 1040 steel. The drilling parameters evaluated are cutting speed, feed rate, and helix angle. Series of experiments are conducted to relate the cutting parameters on the thrust force and torque. L27(313 orthogonal array, signal-to-noise ratio is employed to analyze the influence of these parameters on thrust force and torque during drilling. Analysis of variance (ANOVA is used to study the effect of process parameters on machining process. The study shows that the Taguchi method is suitable to solve the stated problem with the minimum number of trials. The main objective is to find the important factors and combination of factors that influence the machining process to achieve low thrust force and torque. The analysis of the Taguchi method indicates that the feed rate is the most significant factor affecting the thrust force, while the cutting speed contributes the most to the torque.
Directory of Open Access Journals (Sweden)
Wei Wang
2015-01-01
Full Text Available This paper presented a parameter estimation method based on a coupled hydromechanical model of dynamic compaction and the Pareto multiobjective optimization technique. The hydromechanical model of dynamic compaction is established in the FEM program LS-DYNA. The multiobjective optimization algorithm, Nondominated Sorted Genetic Algorithm (NSGA-IIa, is integrated with the numerical model to identify soil parameters using multiple sources of field data. A field case study is used to demonstrate the capability of the proposed method. The observed pore water pressure and crater depth at early blow of dynamic compaction are simultaneously used to estimate the soil parameters. Robustness of the back estimated parameters is further illustrated by a forward prediction. Results show that the back-analyzed soil parameters can reasonably predict lateral displacements and give generally acceptable predictions of dynamic compaction for an adjacent location. In addition, for prediction of ground response of the dynamic compaction at continuous blows, the prediction based on the second blow is more accurate than the first blow due to the occurrence of the hardening and strengthening of soil during continuous compaction.
Selection of the Optimal Cooling Parameters to the Multi-Cavity Die
Institute of Scientific and Technical Information of China (English)
Chiaming; Yen; Jui-Cheng; Lin; Wujeng; Li
2002-01-01
This study is subject to the finite element and abd uc tive network method application in the multi-cavity die. In order to select the optimal cooling system parameters to minimize the warp of a die-casting die, t he Taguchi's method and the abductive network are used. These methods are appli ed to create an efficient model with functional nodes for the considered problem . Once the cooling system parameters are developed, this network can be used to predict the warp for the die-casting die accurately. A ...
Optimization of constitutive parameters of foundation soils k-means clustering analysis
Institute of Scientific and Technical Information of China (English)
Muge Elif Orakoglu; Cevdet Emin Ekinci
2013-01-01
The goal of this study was to optimize the constitutive parameters of foundation soils using a k-means algorithm with clustering analysis. A database was collected from unconfined compression tests, Proctor tests and grain distribution tests of soils taken from three different types of foundation pits:raft foundations, partial raft foundations and strip foundations. k-means algorithm with clustering analysis was applied to determine the most appropriate foundation type given the un-confined compression strengths and other parameters of the different soils.
Parameter Optimization of a 9 × 9 Polymer Arrayed Waveguide Grating Multiplexer
Institute of Scientific and Technical Information of China (English)
郭文滨; 马春生; 陈维友; 张大明; 陈开鑫; 崔战臣; 赵禹; 刘式墉
2002-01-01
Some important parameters are optimized for a 9 × 9 polymer arrayed waveguide grating multiplexer around the central wavelength of 1.55μm with the wavelength spacing of 1.6nm. These parameters include the thickness and width of the guide core, diffraction order, pitch of adjacent waveguides, path length difference of adjacent arrayed waveguides, focal length of slab waveguides, free spectral range, the number of input/output channels and the number of arrayed waveguides. Finally, a schematic waveguide layout of this device is presented, which contains 2 slabs, 9 input and 9 output channels, and 91 arrayed waveguides.
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.
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.
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.
Galvan, D.; Pei, Y. T.; De Hosson, J. Th. M.
2006-01-01
Nanocomposite coatings based on TiC nanoparticles embedded in an amorphous hydrocarbon (a-C:H) matrix are deposited via reactive closed field unbalanced magnetron sputtering, employing Ti targets and acetylene gas as material precursors. The composition of the coatings is varied by changing the acet
The effect of key parameters on the design of an optimized caes power plant
Directory of Open Access Journals (Sweden)
Assadi M. Khalaji
2016-01-01
Full Text Available Due to the significant variations in electricity generation and its demand, the power plant owners are encountered with challenges of economic operation. Among all, Compressed air energy storage (CAES technology has proposed itself as a reliable and efficient solution to match the two sides. This paper deals with a modeled compressed air energy storage power plant which has been optimized thermodynamically through an efficient genetic algorithm code. The results of this optimized model, considered as the base case, show that the power plant is technically and financially justifiable. In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. This approach will help the designers to analyze the quality of their designs in different situations.
Multi-objective process parameter optimization for energy saving in injection molding process
Institute of Scientific and Technical Information of China (English)
Ning-yun LU; Gui-xia GONG; Yi YANG; Jian-hua LU
2012-01-01
This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance (ANOVA),a process modeling algorithm by artificial neural network (ANN),and a multi-objective parameter optimization algorithm by genetic algorithm (GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.
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.
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.
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.
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.
Institute of Scientific and Technical Information of China (English)
Gao Fei; Li Zhuo-Qiu; Tong Heng-Qing
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 axe 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.
Directory of Open Access Journals (Sweden)
Jui-Chang Lin
2015-01-01
Full Text Available The three-dimensional tube (or pipe is manufactured by CNC tube bending machine. The key techniques are determined by tube diameter, wall thickness, material, and bending radius. The obtained technique through experience and the trial and error method is unreliable. Finite element method (FEM simulation for the tube bending process before production can avoid wasting manpower and raw materials. The computer-aided engineering (CAE software ABAQUS 6.12 is applied to simulate bending characteristics and to explore the maximum stress and strain conditions. The Taguchi method is used to find the optimal parameters of bending. The confirmation experiment is performed according to optimal parameters. Results indicate that the strain error between CAE simulation and bending experiments is within 6.39%.
Experimental and numerical analysis for optimal design parameters of a falling film evaporator
Indian Academy of Sciences (India)
RAJNEESH KAUSHAL; RAJ KUMAR; GAURAV VATS
2016-06-01
Present study exhibits an experimental examination of mass transfer coefficient and evaporative effectiveness of a falling film evaporator. Further, a statistical replica is extended in order to have optimal controlling parameters viz. non-dimensional enthalpy potential, film Reynolds number of cooling water, Reynolds number of air and relative humidity of up-streaming air. The models not only give an optimal solution but also help in establishing a correlation among controlling parameters. In this context, response surface methodology is employed by aid of design of experiment approach. Later, the response surface curves are studied using ANOVA. Finally, the relations established are confirmed experimentally to validate the models. The relations thus established are beneficent in furtherance of designing evaporators. Additionally, the presentstudy is among the first attempts to reveal the effect of humidity on the performance of falling film evaporator.
Multi-criteria optimization of chassis parameters of Nissan 200 SX for drifting competitions
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.
Optimization of Cylindrical Grinding Process Parameters on C40E Steel Using Taguchi Technique
Directory of Open Access Journals (Sweden)
Naresh Kumar
2015-01-01
Full Text Available Surface finish and dimensional accuracy play a vital role in the today’s engineering industry. There are several methods used to achieve good surface finish like burnishing, honing and lapping, and grinding. Grinding is one of these ways that improves the surface finish and dimensional accuracy simultaneously. C40E steel has good industrial application in manufacturing of shafts, axles, spindles, studs, etc. In the present work the cylindrical grinding of C40E steel is done for the optimization of grinding process parameters. During this experimental work input process parameters i.e. speed, feed, depth of cut is optimized using Taguchi L9 orthogonal array. Analysis of variance (ANOVA concluded that surface roughness is minimum at the 210 rpm, 0.11mm/rev feed, and 0.04mm depth of penetration.
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.
Directory of Open Access Journals (Sweden)
N. Dammak
2010-01-01
Full Text Available Problem statement: The objective of this study was to optimize the geometrical parameters of a bubble pump integrated in a solar flat plate collector. Approach: This solar bubble pump was part of an ammonia/water/helium (NH3/H2O/He absorption-diffusion cooling system. Results: An empirical model was developed on the basis of momentum, mass, material equations and energy balances. The mathematical model was solved using the simulation tool Engineering Equation Solver (EES. Conclusion/Recommendations: Using metrological data from Gabes (Tunisia various parameters were geometrically optimized for maximum bubble pump efficiency which was best for a bubble pump tube diameter of 6 mm, a tube length of 1.5 m, an inclination to the horizontal between 30 and 50° of the solar flat plate collector and a submergence ratio between 0.2 and 0.3.
DEFF Research Database (Denmark)
Mohanty, Sankhya; Hattel, Jesper Henri
2015-01-01
Selective laser melting is yet to become a standardized industrial manufacturing technique. The process continues to suffer from defects such as distortions, residual stresses, localized deformations and warpage caused primarily due to the localized heating, rapid cooling and high temperature...... gradients that occur during the process. While process monitoring and control of selective laser melting is an active area of research, establishing the reliability and robustness of the process still remains a challenge.In this paper, a methodology for generating reliable, optimized scanning paths...... and process parameters for selective laser melting of a standard sample is introduced. The processing of the sample is simulated by sequentially coupling a calibrated 3D pseudo-analytical thermal model with a 3D finite element mechanical model.The optimized processing parameters are subjected to a Monte Carlo...
Directory of Open Access Journals (Sweden)
Aijia Ouyang
2015-01-01
Full Text Available Nonlinear Muskingum models are important tools in hydrological forecasting. In this paper, we have come up with a class of new discretization schemes including a parameter θ to approximate the nonlinear Muskingum model based on general trapezoid formulas. The accuracy of these schemes is second order, if θ≠1/3, but interestingly when θ=1/3, the accuracy of the presented scheme gets improved to third order. Then, the present schemes are transformed into an unconstrained optimization problem which can be solved by a hybrid invasive weed optimization (HIWO algorithm. Finally, a numerical example is provided to illustrate the effectiveness of the present methods. The numerical results substantiate the fact that the presented methods have better precision in estimating the parameters of nonlinear Muskingum models.
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.