NASA Astrophysics Data System (ADS)
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 sputter deposition parameters for magnetostrictive Fe62Co19Ga19/Si(100) films
NASA Astrophysics Data System (ADS)
Jen, S. U.; Tsai, T. L.
2012-04-01
A good magnetostrictive material should have large saturation magnetostriction (λS) and low saturation (or anisotropy) field (HS), such that its magnetostriction susceptibility (SH) can be as large as possible. In this study, we have made Fe62Co19Ga19/Si(100) nano-crystalline films by using the dc magnetron sputtering technique under various deposition conditions: Ar working gas pressure (pAr) was varied from 1 to 15 mTorr; sputtering power (Pw) was from 10 to 120 W; deposition temperature (TS) was from room temperature (RT) to 300 °C, The film thickness (tf) was fixed at 175 nm. Each magnetic domain looked like a long leaf, with a long-axis of about 12-15 μm and a short-axis of about 1.5 μm. The optimal magnetic and electrical properties were found from the Fe62Co19Ga19 film made with the sputter deposition parameters of pAr = 5 mTorr, Pw = 80 W, and TS = RT. Those optimal properties include λS = 80 ppm, HS = 19.8 Oe, SH = 6.1 ppm/Oe, and electrical resistivity ρ = 57.0 μΩ cm. Note that SH for the conventional magnetostrictive Terfenol-D film is, in general, equal to 1.5 ppm/Oe only.
Hamedani, Hoda A.; Dahmen, Klaus-Hermann; Li, Dongsheng; Peydaye-Saheli, Houman; Garmestani, Hamid; Khaleel, Mohammad A.
2008-10-07
Multiple-step ultrasonic spray pyrolysis was developed to produce a gradient porous lanthanum strontium manganite (LSM) cathode on yttria-stabilized zirconia (YSZ) electrolyte for use in intermediate temperature solid oxide fuel cells (IT-SOFCs). The effect of solvent and precursor type on the morphology and compositional homogeneity of the LSM film was first identified. The LSM film prepared from organo-metallic precursor and organic solvent showed a homogeneous crack-free microstructure before and after heat treatment as opposed to aqueous solution. With respect to the effect of processing parameters, increasing the temperature and solution flow rate in the specific range of 520–580 °C leads to change the microstructure from a dense to a highly porous structure. Using a dilute organic solution a nanocrystalline thin layer was first deposited at 520 °C and solution flow rate of 0.73 ml/min on YSZ surface; then, three gradient porous layers were sprayed from concentrated solution at higher temperatures (540–580 °C) and solution flow rates (1.13–1.58 ml/min) to form a gradient porous LSM cathode film with 30 μm thickness. The microstructure, phase crystallinity and compositional homogeneity of the fabricated films were examined by scanning electron microscopy (SEM), X-ray diffraction (XRD) and energy dispersive analysis of X-ray (EDX). Results showed that the spray pyrolized gradient film fabricated in the temperature range of 520–580 °C is composed of highly crystalline LSM phase which can remove the need for subsequent heat treatment.
Infrared Drying Parameter Optimization
NASA Astrophysics Data System (ADS)
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
Optimization of the microcrystalline silicon deposition efficiency
Strahm, B.; Howling, A. A.; Sansonnens, L.; Hollenstein, Ch.
2007-07-15
Cost reduction constraints for microcrystalline silicon thin film photovoltaic solar cells require high deposition rates and high silane gas utilization efficiencies. If the requirements in deposition rate have sometimes been fulfilled, it is generally not the case for the silane utilization. In this work, a reactor-independent methodology has been developed to determine the optimum plasma parameters in terms of deposition rate, silane utilization, and material microstructure. Using this optimization method, a microcrystalline layer has been deposited over a large area at a rate of 10.9 A/s, with a silane utilization efficiency above 80%.
Optimization for minimum sensitivity to uncertain parameters
NASA Technical Reports Server (NTRS)
Pritchard, Jocelyn I.; Adelman, Howard M.; Sobieszczanski-Sobieski, Jaroslaw
1994-01-01
A procedure to design a structure for minimum sensitivity to uncertainties in problem parameters is described. The approach is to minimize directly the sensitivity derivatives of the optimum design with respect to fixed design parameters using a nested optimization procedure. The procedure is demonstrated for the design of a bimetallic beam for minimum weight with insensitivity to uncertainties in structural properties. The beam is modeled with finite elements based on two dimensional beam analysis. A sequential quadratic programming procedure used as the optimizer supplies the Lagrange multipliers that are used to calculate the optimum sensitivity derivatives. The method was perceived to be successful from comparisons of the optimization results with parametric studies.
NASA Astrophysics Data System (ADS)
Coşkun, M. İbrahim; Karahan, İsmail H.; Yücel, Yasin; Golden, Teresa D.
2016-04-01
CoCrMo bio-metallic alloys were coated with a hydroxyapatite (HA) film by electrodeposition using various electrochemical parameters. Response surface methodology and central composite design were used to optimize deposition parameters such as electrolyte pH, deposition potential, and deposition time. The effects of the coating parameters were evaluated within the limits of solution pH (3.66 to 5.34), deposition potential (-1.13 to -1.97 V), and deposition time (6.36 to 73.64 minutes). A 5-level-3-factor experimental plan was used to determine ideal deposition parameters. Optimum conditions for the deposition parameters of the HA coating with high in vitro corrosion performance were determined as electrolyte pH of 5.00, deposition potential of -1.8 V, and deposition time of 20 minutes.
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. PMID:22122384
Optimized Parameters for a Mercury Jet Target
Ding, X.; Kirk, H.
2010-12-01
A study of target parameters for a high-power, liquid mercury jet target system for a neutrino factory or muon collider is presented. Using the MARS code, we simulate particle production initiated by incoming protons with kinetic energies between 2 and 100 GeV. For each proton beam energy, we maximize production by varying the geometric parameters of the target: the mercury jet radius, the incoming proton beam angle, and the crossing angle between the mercury jet and the proton beam. The number of muons surviving through an ionization cooling channel is determined as a function of the proton beam energy. We optimize the mercury jet target parameters: the mercury jet radius, the incoming proton beam angle and the crossing angle between the mercury jet and the proton beam for each proton beam energy. The optimized target radius varies from about 0.4 cm to 0.6 cm as the proton beam energy increases. The optimized beam angle varies from 75 mrad to 120 mrad. The optimized crossing angle is near 20 mrad for energies above 5 GeV. These values differ from earlier choices of 67 mrad for the beam angle and 33 mrad for the crossing angle. These new choices for the beam parameters increase the meson production by about 20% compared to the earlier parameters. Our study demonstrates that the maximum meson production efficiency per unit proton beam power occurs when the proton kinetic energy is in the range of 5-15 GeV. Finally, the dependence on energy of the number of muons at the end of the cooling channel is nearly identical to the dependence on energy of the meson production 50 m from the target. This demonstrates that the target parameters can be optimized without the additional step of running the distribution through a code such as ICOOL that simulates the bunching, phase rotation, and cooling.
Parameter estimation and optimal experimental design.
Banga, Julio R; Balsa-Canto, Eva
2008-01-01
Mathematical models are central in systems biology and provide new ways to understand the function of biological systems, helping in the generation of novel and testable hypotheses, and supporting a rational framework for possible ways of intervention, like in e.g. genetic engineering, drug development or treatment of diseases. Since the amount and quality of experimental 'omics' data continue to increase rapidly, there is great need for methods for proper model building which can handle this complexity. In the present chapter we review two key steps of the model building process, namely parameter estimation (model calibration) and optimal experimental design. Parameter estimation aims to find the unknown parameters of the model which give the best fit to a set of experimental data. Optimal experimental design aims to devise the dynamic experiments which provide the maximum information content for subsequent non-linear model identification, estimation and/or discrimination. We place emphasis on the need for robust global optimization methods for proper solution of these problems, and we present a motivating example considering a cell signalling model. PMID:18793133
Parameter optimization in S-system models
Vilela, Marco; Chou, I-Chun; Vinga, Susana; Vasconcelos, Ana Tereza R; Voit, Eberhard O; Almeida, Jonas S
2008-01-01
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. PMID:18416837
Advanced rotorcraft control using parameter optimization
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1991-01-01
A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.
RTLS entry load relief parameter optimization
NASA Technical Reports Server (NTRS)
Crull, T. J.
1975-01-01
The results are presented of a study of a candidate load relief control law for use during the pullup phase of Return-to-Launch-Site (RTLS) abort entries. The control law parameters and cycle time which optimized performance of the normal load factor limiting phase (load relief phase) of an RTLS entry are examined. A set of control law gains, a smoothing parameter, and a normal force coefficient curve fit are established which resulted in good load relief performance considering the possible aerodynamic coefficient uncertainties defined. Also, the examination of various guidance cycle times revealed improved load relief performance with decreasing cycle time. A .5 second cycle provided smooth and adequate load relief in the presence of all the aerodynamic uncertainties examined.
Automatic parameter optimization in inspection systems
NASA Astrophysics Data System (ADS)
Bhatia, Peeyush
1997-08-01
Automatic inspection systems for IC mark, package and lead inspection are being widely used as in-process controls and check points. Here their primary function is not only to inspect and sort out defective parts but also to provide feedback on how well a process such as marking or trim and form is performing. Inspection results of every part inspected are often accumulated in a statistical process control (SPC) program that can monitor drifts in the process. Not all drifts are caused by problems in the process itself. For example the mark contrast on a package may be reduced not only because of some problem with the marking process but also because of changes in the mold compound of the package or changes in the light intensity of the inspection system. In latter case a statistical tool such as the SPC program may alert the user of a process drift and he will have to retune, recalibrate or change the parameters of the inspection system. Often the change in parameter is done by trail-and-error. A change too much or too little can result in excess overkill or even escapes. Alternatively the statistical data itself can be used to suggest the user what changes should be made to the inspection parameters. This method of automatic parameter optimization is discussed in detail in this paper. A mark inspection system is chosen as a specific example on how to apply this method.
XTC MRI: sensitivity improvement through parameter optimization.
Ruppert, Kai; Mata, Jaime F; Wang, Hsuan-Tsung J; Tobias, William A; Cates, Gordon D; Brookeman, James R; Hagspiel, Klaus D; Mugler, John P
2007-06-01
Xenon polarization Transfer Contrast (XTC) MRI pulse sequences permit the gas exchange of hyperpolarized xenon-129 in the lung to be measured quantitatively. However, the pulse sequence parameter values employed in previously published work were determined empirically without considering the now-known gas exchange rates and the underlying lung physiology. By using a theoretical model for the consumption of magnetization during data acquisition, the noise intensity in the computed gas-phase depolarization maps was minimized as a function of the gas-phase depolarization rate. With such optimization the theoretical model predicted an up to threefold improvement in precision. Experiments in rabbits demonstrated that for typical imaging parameter values the optimized XTC pulse sequence yielded a median noise intensity of only about 3% in the depolarization maps. Consequently, the reliable detection of variations in the average alveolar wall thickness of as little as 300 nm can be expected. This improvement in the precision of the XTC MRI technique should lead to a substantial increase in its sensitivity for detecting pathological changes in lung function. PMID:17534927
CMB Polarization Detector Operating Parameter Optimization
NASA Astrophysics Data System (ADS)
Randle, Kirsten; Chuss, David; Rostem, Karwan; Wollack, Ed
2015-04-01
Examining the polarization of the Cosmic Microwave Background (CMB) provides the only known way to probe the physics of inflation in the early universe. Gravitational waves produced during inflation are posited to produce a telltale pattern of polarization on the CMB and if measured would provide both tangible evidence for inflation along with a measurement of inflation's energy scale. Leading the effort to detect and measure this phenomenon, Goddard Space Flight Center has been developing high-efficiency detectors. In order to optimize signal-to-noise ratios, sources like the atmosphere and the instrumentation must be considered. In this work we examine operating parameters of these detectors such as optical power loading and photon noise. SPS Summer Internship at NASA Goddard Spaceflight Center.
Optimal filtration of the atmospheric parameters profiles
NASA Technical Reports Server (NTRS)
Zuev, V. E.; Glazov, G. N.; Igonin, G. M.
1986-01-01
The idea of optimal Marcovian filtration of fluctuating profiles from lidar signals is developed but as applied to a double-frequency sounding which allows the use of large cross sections of elastic scattering and correct separation of the contributions due to aerosol and Rayleigh scatterings from the total lidar return. The filtration efficiency is shown under different conditions of sounding using a computer model. The accuracy of restituted profiles (temperature, pressure, density) is determined by the elements of a posteriori matrix K. The results obtained allow the determination of the lidar power required for providing the necessary accuracy of restitution of the atmospheric parameter profiles at chosen wavelengths of sounding in the ultraviolet and visible range.
Optimization of laser wakefield accelerator parameters
Pogorelsky, I.V.
1998-02-01
The author reveals the dependencies of the laser wakefield accelerator (LWFA) performance upon such basic parameters as laser wavelength, power, and pulse duration and apply them for optimization of the plasma-channeled standard LWFA operating in a linear regime. The maximum energy gain over the dephasing distance scales proportionally to the laser peak power, while the allowed minimum laser pulse duration is proportional to the square root of the energy gain. Electron beam energy spread, emittance and luminosity tend to improve with the laser wavelength increase. These considerations, supported by quantitative examples for the S GeV LWFA stage, favor picosecond CO{sub 2} laser as the optimum choice for future advanced accelerator projects.
Taguchi Method Applied in Optimization of Shipley SJR 5740 Positive Resist Deposition
NASA Technical Reports Server (NTRS)
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.
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. PMID:23943088
Optimized parameter extraction using fuzzy logic
NASA Astrophysics Data System (ADS)
Picos, Rodrigo; Calvo, Oscar; Iñiguez, Benjamín; García-Moreno, Eugeni; García, Rodolfo; Estrada, Magali
2007-05-01
Precise extraction of transistor model parameters is of much importance for modeling and at the same time a difficult and time consuming task. Methods for parameter extraction can rely on purely mathematical basis, calling for intensive use of computational resources, or in human expertise to interpret results. In this work, we propose a method for parameter extraction based on fuzzy logic that includes a precise knowledge about the function of each parameter in the model to create a set of simple fitting rules that are easy to describe in human language. To simplify the computational effort, the parameter fitting rules work using only data at specific points (e.g. the distance between the calculated curve and the measured one at VDS corresponding to 50% of the maximum current). If necessary, a more accurate implementation can be used without altering the basic underlying philosophy of the method. In this work, the method is applied to extract model parameters required by Level 3 bulk MOS model and by a compact model for TFTs used in the Unified Model and Extraction Method (UMEM), which is based on an integral function. Results obtained show that the method is quite insensitive to the initial conditions and that it is also quite fast. Extension of this method for more complex models requires only the creation of the corresponding rule base, using the appropriate measurements. The method is especially useful for production testing or design.
Optimization of Milling Parameters Employing Desirability Functions
NASA Astrophysics Data System (ADS)
Ribeiro, J. L. S.; Rubio, J. C. Campos; Abrão, A. M.
2011-01-01
The principal aim of this paper is to investigate the influence of tool material (one cermet and two coated carbide grades), cutting speed and feed rate on the machinability of hardened AISI H13 hot work steel, in order to identify the cutting conditions which lead to optimal performance. A multiple response optimization procedure based on tool life, surface roughness, milling forces and the machining time (required to produce a sample cavity) was employed. The results indicated that the TiCN-TiN coated carbide and cermet presented similar results concerning the global optimum values for cutting speed and feed rate per tooth, outperforming the TiN-TiCN-Al2O3 coated carbide tool.
Parameter study of HP/HVOF deposited WC-Co coatings
NASA Astrophysics Data System (ADS)
de Villiers Lovelock, H. L.; Richter, P. W.; Benson, J. M.; Young, P. M.
1998-03-01
The deposition parameters of WC-17% Co coatings produced using the JP-5000 liquid-fuel HP/HVOF system (Eutectic TAFA) were investigated with the initial purpose of parameter improvement and optimization. The coating microstructures, porosities, phase compositions, and abrasion resistance were characterized. Preliminary work using the Taguchi statistical experimental design method aimed at optimizing the spray parameters in terms of the microstructure and phase composition was unsuccessful. The variations in the measured properties were too small to be correlated with the spray parameters. Subsequent experiments showed this was primarily due to the fact that the properties, particularly the abrasion resistance, of the WC-Co coatings were not primarily influenced by variations in the spray parameters, but were more dependent on the powder composition, particle size range, and manufacturing route. Hence, the application of Taguchi techniques would have been more effective over a much wider parameter space than was originally used. This result is valuable because it suggests that this process is robust and can be used for WC-Co coatings without large investments in spray parameter optimization and control once the coating and powder type have been fixed.
Surface parameters modification by multilayer coatings deposition for biomedical applications
NASA Astrophysics Data System (ADS)
Zykova, A.; Safonov, V.; Virva, O.; Luk'yanchenko, V.; Walkowich, J.; Rogowska, R.; Yakovin, S.
2008-05-01
Studies are presented of the surface parameters of various multilayer coatings, namely, TiN, CrN, (Ti, Cr)N, TiN/TiC10N90, TiN/TiC20N80 deposited by means of Arc-PVD on stainless steel (1H18N9), as well as of the same coatings with an additional Al2O3 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/TiC10N90 and oxide coatings.
Parameter optimization of unbaffled circular surface aeration tank.
Kumar, Bimlesh; Rao, Achanta Ramakrishna; Patel, Ajey Kumar
2011-01-01
The efficiency of the surface aeration systems is generally governed by the geometric and dynamic parameters. The geometry is important because successful translation of the laboratory finding can be scaled up to field installations. Experimental optimization of the geometrical parameters (classical approach of one parameter variations at a time) has certain limitations, because it assumes a linear relationship among the various geometric parameters. In the real experimental process, it is not possible to vary all the parameters simultaneously. In such a case, the model of the system is built through computer simulation, assuming that the model will result in adequate determination of the optimum conditions for the real system. In this paper, two approaches have been used to model the phenomena in unbaffled circular surface aerators: i) Multiple regression and ii) Neural network. It has been found that neural network approach is showing better predictability compared to the multiple regression approach. In process of optimization, the pertinent dynamic parameter is divided into a finite number of segments over the entire range of observations. For each segment of the dynamic parameter, the neural network model is optimized for the geometrical parameters spanning over the entire range of observations. Thus each segment of the dynamic parameter has its set of optimal geometrical conditions. Results obtained are having less variation among them and they are very nearer to the experimental optimal conditions. Input parameter significance test of neural network model reveals that blade width of the rotor is the most significant geometric parameter for the aeration process. PMID:22324141
Optimal parameters of leader development in lightning
NASA Technical Reports Server (NTRS)
Petrov, N. I.; Petrova, G. N.
1991-01-01
The dependences between the different parameters of a leader in lightning are obtained theoretically. The physical mechanism of the instability leading to the formation of the streamer zone is proposed. The instability has the wave nature and is caused by the self-influence effects of the space charge. Using a stability condition of the leader propagation, a dependence is obtained between the current across the leader head and its velocity of motion. The dependence of the streamer zone length on the gap length is also obtained. It is shown that the streamer zone length is saturated with the increasing of the gap length. A comparison between the obtained dependences and the experimental data is presented.
Optimizing parameters for magnetorheological finishing supersmooth surface
NASA Astrophysics Data System (ADS)
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.
Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor
Ye, Lin; Yang, Ming; Xu, Liang; Zhuang, Xiaoqi; Dong, Zhaopeng; Li, Shiyang
2014-01-01
Using the finite element method (FEM) and particle swarm optimization (PSO), a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters' effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°. PMID:24590353
Cylindrical cloaking at oblique incidence with optimized finite multilayer parameters.
Zhang, Baile; Wu, Bae-Ian
2010-08-15
We propose multilayer cylindrical invisibility cloaks that are optimized for oblique incidences through a combination of analytic formalism of scattering and genetic optimization. We show that by using only four layers of homogeneous and anisotropic metamaterials without large values of constitutive parameters, the scattering for oblique incidences can be reduced by 2 orders. Although the optimization is done at a single incident angle, the cloak provides reduced scattering over a large range of incident angles. PMID:20717422
Optimization of Nanostructuring Burnishing Technological Parameters by Taguchi Method
NASA Astrophysics Data System (ADS)
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.
Laboratory measurements of parameters affecting wet deposition of methyl iodide
Maeck, W.J.; Honkus, R.J.; Keller, J.H.; Voilleque, P.G.
1984-09-01
The transfer of gaseous methyl iodide (CH/sub 3/I) to raindrops and the initial retention by vegetation of CH/sub 3/I in raindrops have been studied in a laboratory experimental program. The measured air-to-drop transfer parameters and initial retention factors both affect the wet deposition of methyl iodide onto vegetation. No large effects on the air-to-drop transfer due to methyl iodide concentration, temperature, acidity, or rain type were observed. Differences between laboratory measurements and theoretical values of the mass transfer coefficient were found. Pasture grass, lettuce, and alfalfa were used to study the initial retention of methyl iodide by vegetation. Only a small fraction of the incident CH/sub 3/I in raindrops was held by any of the three vegetation types.
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
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.
Helical tomotherapy optimized planning parameters for nasopharyngeal cancer
NASA Astrophysics Data System (ADS)
Yawichai, K.; Chitapanarux, I.; Wanwilairat, S.
2016-03-01
Helical TomoTherapy(HT) planning depends on optimize parameters including field width (FW), pitch factor (PF) and modulation factor (MF). These optimize parameters are effect to quality of plans and treatment time. The aim of this study was to find the optimized parameters which compromise between plan quality and treatment times. Six nasopharyngeal cancer patients were used. For each patient data set, 18 treatment plans consisted of different optimize parameters combination (FW=5.0, 2.5, 1.0 cm; PF=0.43, 0.287, 0.215; MF2.0, 3.0) were created. The identical optimization procedure followed ICRU83 recommendations. The average D50 of both parotid glands and treatment times per fraction were compared for all plans. The study show treatment plan with FW1.0 cm showed the lowest average D50 of both parotid glands. The treatment time increased inversely to FW. The FW1.0 cm the average treatment time was 4 times longer than FW5.0 cm. PF was very little influence on the average D50 of both parotid glands. Finally, MF increased from 2.0 to 3.0 the average D50 of both parotid glands was slightly decreased. However, the average treatment time was increased 22.28%. For routine nasopharyngeal cancer patients with HT, we suggest the planning optimization parameters consist of FW=5.0 cm, PF=0.43 and MF=2.0.
Optimizing chirped laser pulse parameters for electron acceleration in vacuum
Akhyani, Mina; Jahangiri, Fazel; Niknam, Ali Reza; Massudi, Reza
2015-11-14
Electron dynamics in the field of a chirped linearly polarized laser pulse is investigated. Variations of electron energy gain versus chirp parameter, time duration, and initial phase of laser pulse are studied. Based on maximizing laser pulse asymmetry, a numerical optimization procedure is presented, which leads to the elimination of rapid fluctuations of gain versus the chirp parameter. Instead, a smooth variation is observed that considerably reduces the accuracy required for experimentally adjusting the chirp parameter.
Genetic algorithm parameter optimization: applied to sensor coverage
NASA Astrophysics Data System (ADS)
Sahin, Ferat; Abbate, Giuseppe
2004-08-01
Genetic Algorithms are powerful tools, which when set upon a solution space will search for the optimal answer. These algorithms though have some associated problems, which are inherent to the method such as pre-mature convergence and lack of population diversity. These problems can be controlled with changes to certain parameters such as crossover, selection, and mutation. This paper attempts to tackle these problems in GA by having another GA controlling these parameters. The values for crossover parameter are: one point, two point, and uniform. The values for selection parameters are: best, worst, roulette wheel, inside 50%, outside 50%. The values for the mutation parameter are: random and swap. The system will include a control GA whose population will consist of different parameters settings. While this GA is attempting to find the best parameters it will be advancing into the search space of the problem and refining the population. As the population changes due to the search so will the optimal parameters. For every control GA generation each of the individuals in the population will be tested for fitness by being run through the problem GA with the assigned parameters. During these runs the population used in the next control generation is compiled. Thus, both the issue of finding the best parameters and the solution to the problem are attacked at the same time. The goal is to optimize the sensor coverage in a square field. The test case used was a 30 by 30 unit field with 100 sensor nodes. Each sensor node had a coverage area of 3 by 3 units. The algorithm attempts to optimize the sensor coverage in the field by moving the nodes. The results show that the control GA will provide better results when compared to a system with no parameter changes.
Automatic parameter optimizer (APO) for multiple-point statistics
NASA Astrophysics Data System (ADS)
Bani Najar, Ehsanollah; Sharghi, Yousef; Mariethoz, Gregoire
2016-04-01
Multiple Point statistics (MPS) have gained popularity in recent years for generating stochastic realizations of complex natural processes. The main principle is that a training image (TI) is used to represent the spatial patterns to be modeled. One important feature of MPS is that the spatial model of the fields generated is made of 1) the chosen TI and 2) a set of algorithmic parameters that are specific to each MPS algorithm. While the choice of a training image can be guided by expert knowledge (e.g. for geological modeling) or by data acquisition methods (e.g. remote sensing) determining the algorithmic parameters can be more challenging. To date, only specific guidelines have been proposed for some simulation methods, and a general parameters inference methodology is still lacking, in particular for complex modeling settings such as when using multivariate training images. The common practice consists in carrying out an extensive parameters sensitivity analysis which can be cumbersome. An additional complexity is that the algorithmic parameters do influence CPU cost, and therefore finding optimal parameters is not only a modeling question, but also a computational challenge. To overcome these issues, we propose the automatic parameter optimizer (MPS-APO), a generic method based on stochastic optimization to rapidly determine acceptable parameters, in different settings and for any MPS method. The MPS automatic parameter optimizer proceeds in a 2-step approach. In the first step, it considers the set of input parameters of a given MPS algorithm and formulates an objective function that quantifies the reproduction of spatial patterns. The Simultaneous Perturbation Stochastic Approximation (SPSA) optimization method is used to minimize the objective function. SPSA is chosen because it is able to deal with the stochastic nature of the objective function and for its computational efficiency. At each iteration, small gaps are randomly placed in the input image
NASA Astrophysics Data System (ADS)
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.
Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki
2015-01-01
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. PMID:25784880
Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki
2015-01-01
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. PMID:25784880
Controlled nanoporous Pt morphologies by varying deposition parameters
Misra, Amit; Nastasi, Michael A; Baldwin, J Kevin; Goodwin, Peter M; Bhattacharyya, Dhriti; Antoniou, Antonia
2009-01-01
Typically, dealloying of an alloy can result in an open cell nanoporous structure of the least electrochemically active element. Here, we show that a wider range of nanoporous structures is possible by controlling the composition and deposition parameters of the as-synthesized alloy as a way to provide sites for preferential etching. We demonstrate this by synthesizing nanoporous platinum (np-Pt) through electrochemical dealloying in aqueous HF from co-sputtered Pt{sub x}Si{sub 1-x} amorphous films. For increased Pt fraction of the amorphous alloy, silicon dissolution is favored along pre-existing features of the amorphous film (e.g. column boundaries or surface asperities). The resulting np-Pt depends on the manner in which silicon is preferentially removed. In addition to the expected isotropic open cell structure, columnar and Voronoi (radial) np-Pt are observed. A processing-structure map is developed to correlate np-Pt morphology to the initial composition and thickness of the amorphous Pt{sub x}Si{sub 1-x} film and the negative substrate bias used in magnetron sputtering.
Automatic optimization of parameters for seizure detection systems.
Dollfuß, P; Hartmann, M M; Skupch, A; Fürbaß, F; Kluge, T
2013-01-01
A parameter optimization method for an automatic seizure detection algorithm using the Nelder Mead algorithm is presented. A suitable cost function for joint optimization of sensitivity and false alarm rate is proposed. The optimization is done using EEG datasets from 23 patients and validated on datasets from another 23 patients. The resulting sensitivity was 82.3% with a false alarm rate of 0.24 FA/h. This is a reduction of the false alarm rate by 1.58 FA/h with an acceptable loss of sensitivity of 4.3%. PMID:24110103
Aerodynamic optimization by simultaneously updating flow variables and design parameters
NASA Technical Reports Server (NTRS)
Rizk, M. H.
1990-01-01
The application of conventional optimization schemes to aerodynamic design problems leads to inner-outer iterative procedures that are very costly. An alternative approach is presented based on the idea of updating the flow variable iterative solutions and the design parameter iterative solutions simultaneously. Two schemes based on this idea are applied to problems of correcting wind tunnel wall interference and optimizing advanced propeller designs. The first of these schemes is applicable to a limited class of two-design-parameter problems with an equality constraint. It requires the computation of a single flow solution. The second scheme is suitable for application to general aerodynamic problems. It requires the computation of several flow solutions in parallel. In both schemes, the design parameters are updated as the iterative flow solutions evolve. Computations are performed to test the schemes' efficiency, accuracy, and sensitivity to variations in the computational parameters.
Concurrently adjusting interrelated control parameters to achieve optimal engine performance
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2015-12-01
Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.
An optimized nanoparticle separator enabled by electron beam induced deposition.
Fowlkes, J D; Doktycz, M J; Rack, P D
2010-04-23
Size-based separations technologies will inevitably benefit from advances in nanotechnology. Direct-write nanofabrication provides a useful mechanism for depositing/etching nanoscale elements in environments otherwise inaccessible to conventional nanofabrication techniques. Here, electron beam induced deposition was used to deposit an array of nanoscale features in a 3D environment with minimal material proximity effects outside the beam-interaction region. Specifically, the membrane component of a nanoparticle separator was fabricated by depositing a linear array of sharply tipped nanopillars, with a singular pitch, designed for sub-50 nm nanoparticle permeability. The nanopillar membrane was used in a dual capacity to control the flow of nanoparticles in the transaxial direction of the array while facilitating the sealing of the cellular-sized compartment in the paraxial direction. An optimized growth recipe resulted which (1) maximized the growth efficiency of the membrane (which minimizes proximity effects) and (2) preserved the fidelity of the spacing between nanopillars (which maximizes the size-based gating quality of the membrane) while (3) maintaining sharp nanopillar apexes for impaling an optically transparent polymeric lid critical for device sealing. PMID:20351412
An Optimized Nanoparticle Separator Enabled by Electron Beam Induced Deposition
Fowlkes, Jason Davidson; Doktycz, Mitchel John; Rack, P. D.
2010-01-01
Size based separations technologies will inevitably benefit from advances in nanotechnology. Direct write nanofabrication provides a useful mechanism to deposit/etch nanoscale elements in environments otherwise inaccessible to conventional nanofabrication techniques. Here, electron beam induced deposition (EBID) was used to deposit an array of nanoscale features in a 3D environment with minimal material proximity effects outside the beam interaction region (BIR). Specifically, the membrane component of a nanoparticle separator was fabricated by depositing a linear array of sharply tipped nanopillars, with a singular pitch, designed for sub 50nm nanoparticle permeability. The nanopillar membrane was used in a dual capacity to control the flow of nanoparticles in the transaxial direction of the array while facilitating the sealing of the cellular sized compartment in the paraxial direction. An optimized growth recipe resulted which (1) maximized the growth efficiency of the membrane (which minimizes proximity effects), (2) preserved the fidelity of spacing between nanopillars (which maximizes the size based gating quality of the membrane) while (3) maintaining sharp nanopillar apexes for impaling an optically transparent polymeric lid critical for device sealing.
Optimization of polyetherimide processing parameters for optical interconnect applications
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
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.
On the effect of response transformations in sequential parameter optimization.
Wagner, Tobias; Wessing, Simon
2012-01-01
Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation. PMID:22129277
Rajora, Manik; Zou, Pan; Yang, Yao Guang; Fan, Zhi Wen; Chen, Hung Yi; Wu, Wen Chieh; Li, Beizhi; Liang, Steven Y
2016-01-01
It can be observed from the experimental data of different processes that different process parameter combinations can lead to the same performance indicators, but during the optimization of process parameters, using current techniques, only one of these combinations can be found when a given objective function is specified. The combination of process parameters obtained after optimization may not always be applicable in actual production or may lead to undesired experimental conditions. In this paper, a split-optimization approach is proposed for obtaining multiple solutions in a single-objective process parameter optimization problem. This is accomplished by splitting the original search space into smaller sub-search spaces and using GA in each sub-search space to optimize the process parameters. Two different methods, i.e., cluster centers and hill and valley splitting strategy, were used to split the original search space, and their efficiency was measured against a method in which the original search space is split into equal smaller sub-search spaces. The proposed approach was used to obtain multiple optimal process parameter combinations for electrochemical micro-machining. The result obtained from the case study showed that the cluster centers and hill and valley splitting strategies were more efficient in splitting the original search space than the method in which the original search space is divided into smaller equal sub-search spaces. PMID:27625978
An automatic and effective parameter optimization method for model tuning
NASA Astrophysics Data System (ADS)
Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.
2015-11-01
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 determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. 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 parameter tuning during the model development stage.
Identification of optimal parameter combinations for the emergence of bistability
NASA Astrophysics Data System (ADS)
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.
Communication: Optimal parameters for basin-hopping global optimization based on Tsallis statistics
Shang, C. Wales, D. J.
2014-08-21
A fundamental problem associated with global optimization is the large free energy barrier for the corresponding solid-solid phase transitions for systems with multi-funnel energy landscapes. To address this issue we consider the Tsallis weight instead of the Boltzmann weight to define the acceptance ratio for basin-hopping global optimization. Benchmarks for atomic clusters show that using the optimal Tsallis weight can improve the efficiency by roughly a factor of two. We present a theory that connects the optimal parameters for the Tsallis weighting, and demonstrate that the predictions are verified for each of the test cases.
Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations
NASA Technical Reports Server (NTRS)
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.
A Parameter Optimization for a National SASE FEL Facility
Yavas, O.; Yigit, S.
2007-04-23
The parameter optimization for a national SASE FEL facility was studied. Turkish State Planing Organization (DPT) gave financial support as an inter-universities project to begin technical design studies and test facility of National Accelerator Complex starting from 2006. In addition to a particle factory, the complex will contain a linac based free electron laser, positron ring based synchrotron radiation facilities and a proton accelerator. In this paper, we have given some results of main parameters of SASE FEL facility based on 130 MeV linac, application potential in basic and applied research.
Optimization of reserve lithium thionyl chloride battery electrochemical design parameters
NASA Astrophysics Data System (ADS)
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.
Optimization of reserve lithium thionyl chloride battery electrochemical design parameters
Doddapaneni, N.; Godshall, N.A.
1987-01-01
The performance of Reserve Lithium Thionyl Chloride (RLTC) batteries was optimized by conducting a parametric study of seven electrochemical parameters: electrode compression, carbon thickness, presence of catalyst, temperature, electrode limitation, discharge rate, and electrolyte acidity. Increasing electrode compression (from 0 to 15%) improved battery performance significantly (10% greater carbon capacity density). Although thinner carbon cathodes yielded less absolute capacity than did thicker cathodes, they did so with considerably higher volume efficiencies. The effect of these parameters, and their synergistic interactions, on electrochemical cell peformance is illustrated. 5 refs., 9 figs., 3 tabs.
Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning
Brković, Milenko; Simić, Mirjana
2014-01-01
Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443
Using string invariants for prediction searching for optimal parameters
NASA Astrophysics Data System (ADS)
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.
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. PMID:26739144
Parameter Optimization for Laser Polishing of Niobium for SRF Applications
Zhao, Liang; Klopf, John Michael; Reece, Charles E.; Kelley, Michael J.
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.
On optimization of sub-THz gyrotron parameters
Dumbrajs, O.; Nusinovich, G. S.
2012-10-15
The theory is developed describing how the optimization of gyrotron parameters should be done taking into account two effects deteriorating the gyrotron efficiency: the spread in electron velocities and the spread in the guiding center radii. The paper starts from qualitative analysis of the problem. This simplified theory is used for making some estimates for a specific gyrotron design. The same design is then studied by using more accurate numerical methods. Results of the latter treatment agree with former qualitative predictions.
An automatic and effective parameter optimization method for model tuning
NASA Astrophysics Data System (ADS)
Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.
2015-05-01
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.
Optimizing spectral CT parameters for material classification tasks
NASA Astrophysics Data System (ADS)
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.
Damage localization using experimental modal parameters and topology optimization
NASA Astrophysics Data System (ADS)
Niemann, Hanno; Morlier, Joseph; Shahdin, Amir; Gourinat, Yves
2010-04-01
This work focuses on the development of a damage detection and localization tool using the topology optimization feature of MSC.Nastran. This approach is based on the correlation of a local stiffness loss and the change in modal parameters due to damages in structures. The loss in stiffness is accounted by the topology optimization approach for updating undamaged numerical models towards similar models with embedded damages. Hereby, only a mass penalization and the changes in experimentally obtained modal parameters are used as objectives. The theoretical background for the implementation of this method is derived and programmed in a Nastran input file and the general feasibility of the approach is validated numerically, as well as experimentally by updating a model of an experimentally tested composite laminate specimen. The damages have been introduced to the specimen by controlled low energy impacts and high quality vibration tests have been conducted on the specimen for different levels of damage. These supervised experiments allow to test the numerical diagnosis tool by comparing the result with both NDT technics and results of previous works (concerning shifts in modal parameters due to damage). Good results have finally been achieved for the localization of the damages by the topology optimization.
Optimizing spectral CT parameters for material classification tasks.
Rigie, D S; La Rivière, P J
2016-06-21
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. PMID:27227430
Optimization of laser butt welding parameters with multiple performance characteristics
NASA Astrophysics Data System (ADS)
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.
Saoula, N.; Henda, K.; Kesri, R.
2008-09-23
In this study, we present the effect of the plasma deposition parameters on the mechanical properties of Ti/TiN multilayers. The elaboration of our films has been carried out by RF-Magnetron Sputtering (13.56 MHz) under nitrogen and argon reactive plasma at low pressure. The film depositions have been done on steel substrates. The first step of our study was the optimization of the depositions conditions in order to obtain good quality films. The amount of nitrogen in the sputtering gases being fixed at 10%. The total pressure was set between 2mTorr to 10mTorr. The deposited multilayers were characterized by X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), atomic force microscopy (AFM) and micro-indentation.
Efficient global optimization of a limited parameter antenna design
NASA Astrophysics Data System (ADS)
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.
Drift parameters optimization of a TPC polarimeter: a simulation study
NASA Astrophysics Data System (ADS)
Rakhee, K.; Radhakrishna, V.; Koushal, V.; Baishali, G.; Vinodkumar, A. M.
2015-06-01
Time Projection Chamber (TPC) based X-ray polarimeters using Gas Electron Multiplier (GEM) are currently being developed to make sensitive measurement of polarization in 2-10 keV energy range. The emission direction of the photoelectron ejected via photoelectric effect carries the information of the polarization of the incident X-ray photon. Performance of a gas based polarimeter is affected by the operating drift parameters such as gas pressure, drift field and drift-gap. We present simulation studies carried out in order to understand the effect of these operating parameters on the modulation factor of a TPC polarimeter. Models of Garfield are used to study photoelectron interaction in gas and drift of electron cloud towards GEM. Our study is aimed at achieving higher modulation factors by optimizing drift parameters. Study has shown that Ne/DME (50/50) at lower pressure and drift field can lead to desired performance of a TPC polarimeter.
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. PMID:25114978
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. PMID:25114978
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. PMID:21115841
Shen, Meie; Chen, Wei-Neng; Zhang, Jun; Chung, Henry Shu-Hung; Kaynak, Okyay
2013-04-01
The optimal selection of parameters for time-delay embedding is crucial to the analysis and the forecasting of chaotic time series. Although various parameter selection techniques have been developed for conventional uniform embedding methods, the study of parameter selection for nonuniform embedding is progressed at a slow pace. In nonuniform embedding, which enables different dimensions to have different time delays, the selection of time delays for different dimensions presents a difficult optimization problem with combinatorial explosion. To solve this problem efficiently, this paper proposes an ant colony optimization (ACO) approach. Taking advantage of the characteristic of incremental solution construction of the ACO, the proposed ACO for nonuniform embedding (ACO-NE) divides the solution construction procedure into two phases, i.e., selection of embedding dimension and selection of time delays. In this way, both the embedding dimension and the time delays can be optimized, along with the search process of the algorithm. To accelerate search speed, we extract useful information from the original time series to define heuristics to guide the search direction of ants. Three geometry- or model-based criteria are used to test the performance of the algorithm. The optimal embeddings found by the algorithm are also applied in time-series forecasting. Experimental results show that the ACO-NE is able to yield good embedding solutions from both the viewpoints of optimization performance and prediction accuracy. PMID:23144038
Process Parameters Optimization in Single Point Incremental Forming
NASA Astrophysics Data System (ADS)
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.
Dynamic imaging model and parameter optimization for a star tracker.
Yan, Jinyun; Jiang, Jie; Zhang, Guangjun
2016-03-21
Under dynamic conditions, star spots move across the image plane of a star tracker and form a smeared star image. This smearing effect increases errors in star position estimation and degrades attitude accuracy. First, an analytical energy distribution model of a smeared star spot is established based on a line segment spread function because the dynamic imaging process of a star tracker is equivalent to the static imaging process of linear light sources. The proposed model, which has a clear physical meaning, explicitly reflects the key parameters of the imaging process, including incident flux, exposure time, velocity of a star spot in an image plane, and Gaussian radius. Furthermore, an analytical expression of the centroiding error of the smeared star spot is derived using the proposed model. An accurate and comprehensive evaluation of centroiding accuracy is obtained based on the expression. Moreover, analytical solutions of the optimal parameters are derived to achieve the best performance in centroid estimation. Finally, we perform numerical simulations and a night sky experiment to validate the correctness of the dynamic imaging model, the centroiding error expression, and the optimal parameters. PMID:27136791
Optimizing experimental parameters for tracking of diffusing particles
NASA Astrophysics Data System (ADS)
Vestergaard, Christian L.
2016-08-01
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 content in individual frames.
Total energy control system autopilot design with constrained parameter optimization
NASA Technical Reports Server (NTRS)
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.
Optimization and testing of solid thin film lubrication deposition processes
NASA Astrophysics Data System (ADS)
Danyluk, Michael J.
A novel method for testing solid thin films in rolling contact fatigue (RCF) under ultra-high vacuum (UHV) and high rotational speeds (130 Hz) is presented in this thesis. The UHV-RCF platform is used to quantify the adhesion and lubrication aspects of two thin film coatings deposited on ball-bearings using a physical vapor deposition ion plating process. Plasma properties during ion plating were measured using a Langmuir probe and there is a connection between ion flux, film stress, film adhesion, process voltage, pressure, and RCF life. The UHV-RCF platform and vacuum chamber were constructed using off-the-shelf components and 88 RCF tests in high vacuum have been completed. Maximum RCF life was achieved by maintaining an ion flux between 10 13 to 1015 (cm-2 s-1) with a process voltage and pressure near 1.5 kV and 15 mTorr. Two controller schemes were investigated to maintain optimal plasma conditions for maximum RCF life: PID and LQR. Pressure disturbances to the plasma have a detrimental effect on RCF life. Control algorithms that mitigate pressure and voltage disturbances already exist. However, feedback from the plasma to detect disturbances has not been explored related to deposition processes in the thin-film science literature. Manometer based pressure monitoring systems have a 1 to 2 second delay time and are too slow to detect common pressure bursts during the deposition process. Plasma diagnostic feedback is much faster, of the order of 0.1 second. Plasma total-current feedback was used successfully to detect a typical pressure disturbance associated with the ion plating process. Plasma current is related to ion density and process pressure. A real-time control application was used to detect the pressure disturbance by monitoring plasma-total current and converting it to feedback-input to a pressure control system. Pressure overshoot was eliminated using a nominal PID controller with feedback from a plasma-current diagnostic measurement tool.
Space shuttle propulsion parameter estimation using optimal estimation techniques
NASA Technical Reports Server (NTRS)
1983-01-01
The first twelve system state variables are presented with the necessary mathematical developments for incorporating them into the filter/smoother algorithm. Other state variables, i.e., aerodynamic coefficients can be easily incorporated into the estimation algorithm, representing uncertain parameters, but for initial checkout purposes are treated as known quantities. An approach for incorporating the NASA propulsion predictive model results into the optimal estimation algorithm was identified. This approach utilizes numerical derivatives and nominal predictions within the algorithm with global iterations of the algorithm. The iterative process is terminated when the quality of the estimates provided no longer significantly improves.
Parameter optimization for through-focus scanning optical microscopy.
Attota, Ravi Kiran; Kang, Hyeonggon
2016-06-27
It is important to economically and non-destructively analyze three-dimensional (3-D) shapes of nanometer to micrometer scale objects with sub-nanometer measurement resolution for emerging high-volume nanomanufacturing, especially for process control. High-throughput through-focus scanning optical microscopy (TSOM) demonstrates promise for such applications. TSOM uses a conventional optical microscope for 3-D shape metrology by making use of the complete set of through-focus, four-dimensional optical data. However, a systematic study showing the effect of various parameters on the TSOM method is lacking. Here we present the optimization of the basic parameters such as illumination numerical aperture (NA), collection NA, focus step height, digital camera pixel size, illumination polarization, and illumination wavelength to achieve peak performance of the TSOM method. PMID:27410642
Parameter optimization in AQM controller design to support TCP traffic
NASA Astrophysics Data System (ADS)
Yang, Wei; Yang, Oliver W.
2004-09-01
TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.
Optimal VLF Parameters for Pitch Angle Scattering of Trapped Electrons
NASA Astrophysics Data System (ADS)
Albert, J. M.; Inan, U. S.
2001-12-01
VLF waves are known to determine the lifetimes of energetic radiation belt electrons in the inner radiation belt and slot regions. Artificial injection of such waves from ground- or space-based transmitters may thus be used to affect the trapped electron population. In this paper, we seek to determine the optimal parameters (frequency and wave normal angle) of a quasi-monochromatic VLF wave using bounce-averaged quasi-linear theory. We consider the cumulative effects of all harmonic resonances and determine the diffusion rates of particles with selected energies on particular L-shells. We also compare the effects of the VLF wave to diffusion driven by other whistler-mode waves (plasmaspheric hiss, lightning, and VLF transmitters). With appropriate choice of the wave parameters, it may be possible to substantially reduce the lifetime of selected classes of particles.
Power Saving Optimization for Linear Collider Interaction Region Parameters
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.
NASA Astrophysics Data System (ADS)
Ruan, Cong; Sun, Xiao-Min; Song, Yi-Xu
In this paper, we propose a method to optimize etching yield parameters. By means of defining a fitness function between the actual etching profile and the simulation profile, the etching yield parameters solving problem is transformed into an optimization problem. The problem is nonlinear and high dimensional, and each simulation is computationally expensive. To solve this problem, we need to search a better solution in a multidimensional space. Ordinal optimization and tabu search hybrid algorithm is introduced to solve this complex problem. This method ensures getting good enough solution in an acceptable time. The experimental results illustrate that simulation profile obtained by this method is very similar with the actual etching profile in surface topography. It also proves that our proposed method has feasibility and validity.
Simunek, J.; Nimmo, J.R.
2005-01-01
A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time-variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field. Copyright 2005 by the American Geophysical Union.
Biohydrogen Production from Simple Carbohydrates with Optimization of Operating Parameters.
Muri, Petra; Osojnik-Črnivec, Ilja Gasan; Djinovič, Petar; Pintar, Albin
2016-01-01
Hydrogen could be alternative energy carrier in the future as well as source for chemical and fuel synthesis due to its high energy content, environmentally friendly technology and zero carbon emissions. In particular, conversion of organic substrates to hydrogen via dark fermentation process is of great interest. The aim of this study was fermentative hydrogen production using anaerobic mixed culture using different carbon sources (mono and disaccharides) and further optimization by varying a number of operating parameters (pH value, temperature, organic loading, mixing intensity). Among all tested mono- and disaccharides, glucose was shown as the preferred carbon source exhibiting hydrogen yield of 1.44 mol H(2)/mol glucose. Further evaluation of selected operating parameters showed that the highest hydrogen yield (1.55 mol H(2)/mol glucose) was obtained at the initial pH value of 6.4, T=37 °C and organic loading of 5 g/L. The obtained results demonstrate that lower hydrogen yield at all other conditions was associated with redirection of metabolic pathways from butyric and acetic (accompanied by H(2) production) to lactic (simultaneous H(2) production is not mandatory) acid production. These results therefore represent an important foundation for the optimization and industrial-scale production of hydrogen from organic substrates. PMID:26970800
Ebrahimiasl, Saeideh; Zakaria, Azmi
2014-01-01
A nanocrystalline SnO2 thin film was synthesized by a chemical bath method. The parameters affecting the energy band gap and surface morphology of the deposited SnO2 thin film were optimized using a semi-empirical method. Four parameters, including deposition time, pH, bath temperature and tin chloride (SnCl2·2H2O) concentration were optimized by a factorial method. The factorial used a Taguchi OA (TOA) design method to estimate certain interactions and obtain the actual responses. Statistical evidences in analysis of variance including high F-value (4,112.2 and 20.27), very low P-value (<0.012 and 0.0478), non-significant lack of fit, the determination coefficient (R2 equal to 0.978 and 0.977) and the adequate precision (170.96 and 12.57) validated the suggested model. The optima of the suggested model were verified in the laboratory and results were quite close to the predicted values, indicating that the model successfully simulated the optimum conditions of SnO2 thin film synthesis. PMID:24509767
On choosing ?optimal? shape parameters for RBF approximation
NASA Astrophysics Data System (ADS)
Fasshauer, Gregory; Zhang, Jack
2007-08-01
Many radial basis function (RBF) methods contain a free shape parameter that plays an important role for the accuracy of the method. In most papers the authors end up choosing this shape parameter by trial and error or some other ad hoc means. The method of cross validation has long been used in the statistics literature, and the special case of leave-one-out cross validation forms the basis of the algorithm for choosing an optimal value of the shape parameter proposed by Rippa in the setting of scattered data interpolation with RBFs. We discuss extensions of this approach that can be applied in the setting of iterated approximate moving least squares approximation of function value data and for RBF pseudo-spectral methods for the solution of partial differential equations. The former method can be viewed as an efficient alternative to ridge regression or smoothing spline approximation, while the latter forms an extension of the classical polynomial pseudo-spectral approach. Numerical experiments illustrating the use of our algorithms are included.
Ablation Plasma Ion Implantation Optimization and Deposition of Compound Coatings
NASA Astrophysics Data System (ADS)
Jones, M. C.; Qi, B.; Gilgenbach, R. M.; Johnston, M. D.; Lau, Y. Y.; Doll, G. L.; Lazarides, A.
2002-10-01
Ablation Plasma Ion Implantation (APII) utilizes KrF laser ablation plasma plumes to implant ions into pulsed, negatively-biased substrates [1]. Ablation targets are Ti foils and TiN disks. Substrates are Si wafers and Al, biased from 0 to -10 kV. Optimization experiments address: 1) configurations that reduce arcing, 2) reduction of particulate, and 3) deposition/implantation of compounds (e.g. TiN). Arcing is suppressed by positioning the target perpendicular (previously parallel) to the substrate. Thus, bias voltage can be applied at the same time as the KrF laser, resulting in higher ion current. This geometry also yields lower particulate. APII with TiN has the goal of hardened coatings with excellent adhesion. SEM, AFM, XPS, TEM, and scratch tests characterize properties of the thin films. Ti APII films at - 4kV are smoother with lower friction. 1. B. Qi, R.M. Gilgenbach, Y.Y. Lau, M.D. Johnston, J. Lian, L.M. Wang, G. L. Doll and A. Lazarides, APL, 78, 3785 (2001) * Research funded by NSF
Selection of optimal composition-control parameters for friable materials
Pak, Yu.N.; Vdovkin, A.V.
1988-05-01
A method for composition analysis of coal and minerals is proposed which uses scattered gamma radiation and does away with preliminary sample preparation to ensure homogeneous particle density, surface area, and size. Reduction of the error induced by material heterogeneity has previously been achieved by rotation of the control object during analysis. A further refinement is proposed which addresses the necessity that the contribution of the radiation scattered from each individual surface to the total intensity be the same. This is achieved by providing a constant linear rate of travel for the irradiated spot through back-and-forth motion of the sensor. An analytical expression is given for the laws of motion for the sensor and test tube which provides for uniform irradiated area movement along a path analogous to the Archimedes spiral. The relationships obtained permit optimization of measurement parameters in analyzing friable materials which are not uniform in grain size.
Design of Life Extending Controls Using Nonlinear Parameter Optimization
NASA Technical Reports Server (NTRS)
Lorenzo, Carl F.; Holmes, Michael S.; Ray, Asok
1998-01-01
This report presents the conceptual development of a life extending control system where the objective is to achieve high performance and structural durability of the plant. A life extending controller is designed for a reusable rocket engine via damage mitigation in both the fuel and oxidizer turbines while achieving high performance for transient responses of the combustion chamber pressure and the O2/H2 mixture ratio. This design approach makes use of a combination of linear and nonlinear controller synthesis techniques and also allows adaptation of the life extending controller module to augment a conventional performance controller of a rocket engine. The nonlinear aspect of the design is achieved using nonlinear parameter optimization of a prescribed control structure.
Rochelle, B.P.; Liff, C.I.; Campbell, W.G.; Cassell, D.L.; Church, M.R.
1989-01-01
The authors determined geomorphic and hydrologic parameters for 144 forested, lake watersheds in the Northeast (NE) of the United States based primarily on measurements from topographic maps. These parameters were used to test for relationships with selected surface water chemistry relevant to acidic deposition. Analyses were conducted on regional and subregional scales delineated based on soils, land use, physiography, total sulfur deposition and statistical clustering of selected geomorphic/hydrologic parameters. Significant relationships were found among the geomorphic/hydrologic parameters and the surface water chemistry for the NE. Elevation had the most significant relationship with surface water chemistry, particularly in the mountainous areas of the NE. Other factors occurring consistently as significant predictors of surface water chemistry were maximum relief, relief ratio, runoff, and estimates of basin elongation. Results suggest that elevational parameters might be surrogates for other watershed characteristics, such as soils or spatial deposition patterns.
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. PMID:26450304
Robust integrated autopilot/autothrottle design using constrained parameter optimization
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
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.
Parallel axes gear set optimization in two-parameter space
NASA Astrophysics Data System (ADS)
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.
NASA Technical Reports Server (NTRS)
Armand, J. P.
1972-01-01
An extension of classical methods of optimal control theory for systems described by ordinary differential equations to distributed-parameter systems described by partial differential equations is presented. An application is given involving the minimum-mass design of a simply-supported shear plate with a fixed fundamental frequency of vibration. An optimal plate thickness distribution in analytical form is found. The case of a minimum-mass design of an elastic sandwich plate whose fundamental frequency of free vibration is fixed. Under the most general conditions, the optimization problem reduces to the solution of two simultaneous partial differential equations involving the optimal thickness distribution and the modal displacement. One equation is the uniform energy distribution expression which was found by Ashley and McIntosh for the optimal design of one-dimensional structures with frequency constraints, and by Prager and Taylor for various design criteria in one and two dimensions. The second equation requires dynamic equilibrium at the preassigned vibration frequency.
NASA Astrophysics Data System (ADS)
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.
Cohen, Bat-El; Gamliel, Shany; Etgar, Lioz
2014-08-01
Perovskite is a promising light harvester for use in photovoltaic solar cells. In recent years, the power conversion efficiency of perovskite solar cells has been dramatically increased, making them a competitive source of renewable energy. An important parameter when designing high efficiency perovskite-based solar cells is the perovskite deposition, which must be performed to create complete coverage and optimal film thickness. This paper describes an in-depth study on two-step deposition, separating the perovskite deposition into two precursors. The effects of spin velocity, annealing temperature, dipping time, and methylammonium iodide concentration on the photovoltaic performance are studied. Observations include that current density is affected by changing the spin velocity, while the fill factor changes mainly due to the dipping time and methylammonium iodide concentration. Interestingly, the open circuit voltage is almost unaffected by these parameters. Hole conductor free perovskite solar cells are used in this work, in order to minimize other possible effects. This study provides better understanding and control over the perovskite deposition through highly efficient, low-cost perovskite-based solar cells.
Optimization of exposure parameters in full field digital mammography
Williams, Mark B.; Raghunathan, Priya; More, Mitali J.; Seibert, J. Anthony; Kwan, Alexander; Lo, Joseph Y.; Samei, Ehsan; Ranger, Nicole T.; Fajardo, Laurie L.; McGruder, Allen; McGruder, Sandra M.; Maidment, Andrew D. A.; Yaffe, Martin J.; Bloomquist, Aili; Mawdsley, Gordon E.
2008-06-15
Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal-to-noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this study is to compare, for each of the major commercially available full field digital mammography (FFDM) systems, the impact of the selection of technique factors on image SNR and radiation dose for a range of breast thickness and tissue types. This phantom study is an update of a previous investigation and includes measurements on recent versions of two of the FFDM systems discussed in that article, as well as on three FFDM systems not available at that time. The five commercial FFDM systems tested, the Senographe 2000D from GE Healthcare, the Mammomat Novation DR from Siemens, the Selenia from Hologic, the Fischer Senoscan, and Fuji's 5000MA used with a Lorad M-IV mammography unit, are located at five different university test sites. Performance was assessed using all available x-ray target and filter combinations and nine different phantom types (three compressed thicknesses and three tissue composition types). Each phantom type was also imaged using the automatic exposure control (AEC) of each system to identify the exposure parameters used under automated image acquisition. The figure of merit (FOM) used to compare technique factors is the ratio of the square of the image SNR to the mean glandular dose. The results show that, for a given target/filter combination, in general FOM is a slowly changing function of kVp, with stronger dependence on the choice of target/filter combination. In all cases the FOM was a decreasing function of kVp at the top of the available range of kVp settings, indicating that higher tube voltages would produce no further performance improvement. For a given phantom type, the exposure parameter set resulting in the highest FOM value was system specific, depending on both the set of available target/filter combinations, and
NASA Astrophysics Data System (ADS)
Chateigner, D.; Brunet, F.; Deneuville, A.; Germi, P.; Pernet, M.; Gheeraert, E.; Gonon, P.
1995-02-01
Incorporation of boron in polycrystalline diamond films deposited on Si is shown to decrease or increase the lattice parameter below and above about 10 19 B cm -3, respectively. At lower values of doping, the lattice parameter is lower than that of the undoped films, while their <111> texture is maintained. At higher values, the lattice parameter increases rapidly above that of the undoped films, while the <111> texture is progressively lost until it becomes untextured at 6 × 10 20 B cm -3. A coherent interpretation of these results is proposed, based on a decrease and an increase of the defect concentration with B incorporation below and above 10 19 B cm -3, with the hypothesis that the defects increase the diamond lattice parameter.
Impact of sputter deposition parameters on molybdenum nitride thin film properties
NASA Astrophysics Data System (ADS)
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.
Inversion of generalized relaxation time distributions with optimized damping parameter
NASA Astrophysics Data System (ADS)
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.
Optimization of HPM device parameters for maximum air transmission
Roussel-Dupre, R.; Tunnell, T.
1993-02-01
The propagation of high-power microwave (HPM) pulses through the atmosphere is a subject that has received renewed attention in the last decade. For sufficiently high-power pulses it is possible for air breakdown to be initiated by the front end of the pulse and for ohmic dissipation of the tail end to proceed as the tail propagates through the newly created plasma. Generally, this nonlinear process termed tail erosion is modeled with time-dependent fluid or kinetic codes that require a fine mesh of range and time points. The computational time to run these codes, however, precludes their use in determining theoptimum pulse characteristics and propagation paths for transmission of a desired fluence. In this paper a new frequency scaling law that greatly reduces computational requirements and at the same time incorporates the nonlinear effects inherent to HPM propagation is discussed. Results of a comparison between predictions of air breakdown thresholds made using the frequency scaling law and experimental data taken at various frequencies are presented. The scaling law is implemented in an existing HPM propagation code and has been used recently to develop a new predictive capability that calculates the optimum energy, power, and antenna requirements necessary to transmit a desired fluence. These capabilities provide both the accuracy and rapid computational turnaround necessary for system studies that assess the effects of HPM propagation for particular HPM devices and that attempt to open device parameters for maximum air transmission. Samples of both forward propagation, predictive calculations and inverse, optimization calculations are presented.
Optimization of HPM device parameters for maximum air transmission
Roussel-Dupre, R. ); Tunnell, T. )
1993-01-01
The propagation of high-power microwave (HPM) pulses through the atmosphere is a subject that has received renewed attention in the last decade. For sufficiently high-power pulses it is possible for air breakdown to be initiated by the front end of the pulse and for ohmic dissipation of the tail end to proceed as the tail propagates through the newly created plasma. Generally, this nonlinear process termed tail erosion is modeled with time-dependent fluid or kinetic codes that require a fine mesh of range and time points. The computational time to run these codes, however, precludes their use in determining theoptimum pulse characteristics and propagation paths for transmission of a desired fluence. In this paper a new frequency scaling law that greatly reduces computational requirements and at the same time incorporates the nonlinear effects inherent to HPM propagation is discussed. Results of a comparison between predictions of air breakdown thresholds made using the frequency scaling law and experimental data taken at various frequencies are presented. The scaling law is implemented in an existing HPM propagation code and has been used recently to develop a new predictive capability that calculates the optimum energy, power, and antenna requirements necessary to transmit a desired fluence. These capabilities provide both the accuracy and rapid computational turnaround necessary for system studies that assess the effects of HPM propagation for particular HPM devices and that attempt to open device parameters for maximum air transmission. Samples of both forward propagation, predictive calculations and inverse, optimization calculations are presented.
He, C.N.; Zhao, N.Q.; Shi, C.S.; Song, S.Z.
2010-09-15
In order to optimize the chemical vapor deposition process for fabrication of carbon nanotube/Al composite powders, the effect of different reaction conditions (such as reaction temperature, reaction time, and reaction gas ratio) on the morphological and structural development of the powder and dispersion of CNTs in Al powder was investigated using transmission electron microscope. The results showed that low temperatures (500-550 {sup o}C) give rise to herringbone-type carbon nanofibers and high temperatures (600-630 {sup o}C) lead to multi-walled CNTs. Long reaction times broaden the CNT size distribution and increase the CNT yield. Appropriate nitrogen flow is preferred for CNT growth, but high and low nitrogen flow result in carbon nanospheres and CNTs with coarse surfaces, respectively. Above results show that appropriate parameters are effective in dispersing the nanotubes in the Al powder which simultaneously protects the nanotubes from damage.
NASA Astrophysics Data System (ADS)
Klein, Stefan; Finger, Friedhelm; Carius, Reinhard; Stutzmann, Martin
2005-07-01
Microcrystalline silicon (μc-Si:H) of superior quality can be prepared using the hot-wire chemical-vapor deposition method (HWCVD). At a low substrate temperature (TS) of 185 °C excellent material properties and solar cell performance were obtained with spin densities of 6×1015cm-3 and solar cell efficiencies up to 9.4%, respectively. In this study we have systematically investigated the influence of various deposition parameters on the deposition rate and the material properties. For this purpose, thin films and solar cells were prepared at specific substrate and filament temperatures and deposition pressures (pD), covering the complete range from amorphous to highly crystalline material by adjusting the silane concentration. The influence of these deposition parameters on the chemical reactions at the filament and in the gas phase qualitatively explains the behavior of the structural composition and the formation of defects. In particular, we propose that the deposition rate is determined by the production of reactive species at the filament and a particular atomic-hydrogen-to-silicon ratio is found at the microcrystalline/amorphous transition. The structural, optical, and electronic properties were studied using Raman and infrared spectroscopies, optical-absorption measurements, electron-spin resonance, and dark and photoconductivities. These experiments show that higher TS and pD lead to a deterioration of the material quality, i.e., much higher defect densities, oxygen contaminations, and SiH absorption at 2100cm-1. Similar to plasma enhanced chemical-vapor deposition material, μc-Si:H solar cells prepared with HW i layers show increasing open circuit voltages (Voc) with increasing silane concentration and best performance is achieved near the transition to amorphous growth. Such solar cells prepared at low TS exhibit very high Voc up to 600 mV and fill factors above 70% with i layers prepared by HWCVD.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Vahedein, Yashar Seyed
Template-based chemical vapor deposition (TB-CVD) is a versatile technique for manufacturing carbon nanotubes (CNTs) or CNT-based devices for various applications. In this process, carbon is deposited by thermal decomposition of a carbon-based precursor gas inside the nanoscopic cylindrical pores of anodized aluminum oxide (AAO) templates to form CNTs. Experimental results show CNT formation in templates is controlled by TB-CVD process parameters, such as time, temperature and flow rate. Optimization of this process is done empirically, requiring tremendous time and effort. Moreover, there is a need for a more comprehensive and low cost way to characterize the flow in the furnace in order to understand how process parameters may affect CNT formation. In this report, we describe the development of four, three-dimensional numerical models, each varying in complexity, to elucidate the thermo-fluid behavior inside the TB-CVD process. Using computational fluid dynamic (CFD) commercial codes, the four models were compared to determine how the presence of the template and boat, composition of the precursor gas, and consumption of species at the template surface affect the temperature profiles and velocity fields in the system. The most accurate model will be used to conduct particle injection/tracking near the templates and to characterize the particle residence time as a function of time and consumption rate. The developments in this work build the groundwork for explaining how flow characteristics affect carbon deposition on templates in any CVD reactor.
DEPOSITION PATTERNS OF AEROSOLIZED DRUGS WITHIN HUMAN LUNGS: EFFECTS OF VENTILATORY PARAMETERS
An analytical model is used to study the effects of ventilatory parameters on particle deposition patterns within the human lung. ased upon fluid dynamics considerations (Reynolds numbers), an original method of partitioning the lung is presented. he model is validated by compari...
Effect of processing parameters on surface finish for fused deposition machinable wax patterns
NASA Technical Reports Server (NTRS)
Roberts, F. E., III
1995-01-01
This report presents a study on the effect of material processing parameters used in layer-by-layer material construction on the surface finish of a model to be used as an investment casting pattern. The data presented relate specifically to fused deposition modeling using a machinable wax.
Mathematical modeling of plasma deposition and hardening of coatings-switched electrical parameters
NASA Astrophysics Data System (ADS)
Kadyrmetov, A. M.; Sharifullin, S. N.; Pustovalov, AS
2016-01-01
This paper presents the results of simulation of plasma deposition and hardening of coatings in modulating the electrical parameters. Mathematical models are based on physical models of gas-dynamic mechanisms more dynamic and thermal processes of the plasma jet. As an example the modeling of dynamic processes of heterogeneous plasma jet, modulated current pulses indirect arc plasma torch.
An effective approach to optimizing the parameters of complex thermal power plants
NASA Astrophysics Data System (ADS)
Kler, A. M.; Zharkov, P. V.; Epishkin, N. O.
2016-03-01
A new approach has been developed to solve the optimization problems of continuous parameters of thermal power plants. It is based on such organization of optimization, in which the solution of the system of equations describing thermal power plant, is achieved only at the endpoint of the optimization process. By the example of optimizing the parameters of a coal power unit for ultra-supercritical steam parameters, the efficiency of the proposed approach is demonstrated and compared with the previously used one, in which the system of equations was solved at each iteration of the optimization process.
Direct Multiple Shooting Optimization with Variable Problem Parameters
NASA Technical Reports Server (NTRS)
Whitley, Ryan J.; Ocampo, Cesar A.
2009-01-01
Taking advantage of a novel approach to the design of the orbital transfer optimization problem and advanced non-linear programming algorithms, several optimal transfer trajectories are found for problems with and without known analytic solutions. This method treats the fixed known gravitational constants as optimization variables in order to reduce the need for an advanced initial guess. Complex periodic orbits are targeted with very simple guesses and the ability to find optimal transfers in spite of these bad guesses is successfully demonstrated. Impulsive transfers are considered for orbits in both the 2-body frame as well as the circular restricted three-body problem (CRTBP). The results with this new approach demonstrate the potential for increasing robustness for all types of orbit transfer problems.
Adaptive neuro-fuzzy estimation of optimal lens system parameters
NASA Astrophysics Data System (ADS)
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.
Saikia, Partha; Kakati, Bharat
2013-11-15
In this study, the effect of working pressure and input power on the physical properties and sputtering efficiencies of argon–nitrogen (Ar/N{sub 2}) plasma in direct current magnetron discharge is investigated. The discharge in Ar/N{sub 2} is used to deposit TiN films on high speed steel substrate. The physical plasma parameters are determined by using Langmuir probe and optical emission spectroscopy. On the basis of the different reactions in the gas phase, the variation of plasma parameters and sputtering rate are explained. A prominent change of electron temperature, electron density, ion density, and degree of ionization of Ar is found as a function of working pressure and input power. The results also show that increasing working pressure exerts a negative effect on film deposition rate while increasing input power has a positive impact on the same. To confirm the observed physical properties and evaluate the texture growth as a function of deposition parameters, x-ray diffraction study of deposited TiN films is also done.
Optimizing Soil Hydraulic Parameters in RZWQM2 Under Fallow Conditions
Technology Transfer Automated Retrieval System (TEKTRAN)
Effective estimation of soil hydraulic parameters is essential for predicting soil water dynamics and related biochemical processes in agricultural systems. However, high uncertainties in estimated parameter values limit a model’s skill for prediction and application. In this study, a global search ...
Parameter optimization method for the water quality dynamic model based on data-driven theory.
Liang, Shuxiu; Han, Songlin; Sun, Zhaochen
2015-09-15
Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). PMID:26277602
NASA Technical Reports Server (NTRS)
Natarajan, V.; Lamb, J. D.; Woollam, J. A.; Liu, D. C.; Gulino, D. A.
1985-01-01
An RF plasma deposition system was used to prepare amorphous 'diamondlike' carbon films. The source gases for the RF system include methane, ethylene, propane, and propylene, and the parameters varied were power, dc substrate bias, and postdeposition anneal temperature. Films were deposited on various substrates. The main diagnostics were optical absorption in the visible and in the infrared, admittance as a function of frequency, hardness, and Auger and ESCA spectroscopy. Band gap is found to depend strongly on RF power level and band gaps up to 2.7 eV and hardness up to 7 Mohs were found. There appears to be an inverse relationship between hardness and optical band gap.
NASA Astrophysics Data System (ADS)
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.
Funke, Stefanie; Matilainen, Julia; Nalenz, Heiko; Bechtold-Peters, Karoline; Mahler, Hanns-Christian; Friess, Wolfgang
2016-07-01
Biopharmaceutical products are increasingly commercialized as drug/device combinations to enable self-administration. Siliconization of the inner syringe/cartridge glass barrel for adequate functionality is either performed at the supplier or drug product manufacturing site. Yet, siliconization processes are often insufficiently investigated. In this study, an optimized bake-on siliconization process for cartridges using a pilot-scale siliconization unit was developed. The following process parameters were investigated: spray quantity, nozzle position, spray pressure, time for pump dosing and the silicone emulsion concentration. A spray quantity of 4mg emulsion showed best, immediate atomization into a fine spray. 16 and 29mg of emulsion, hence 4-7-times the spray volume, first generated an emulsion jet before atomization was achieved. Poor atomization of higher quantities correlated with an increased spray loss and inhomogeneous silicone distribution, e.g., due to runlets forming build-ups at the cartridge lower edge and depositing on the star wheel. A prolonged time for pump dosing of 175ms led to a more intensive, long-lasting spray compared to 60ms as anticipated from a higher air-to-liquid ratio. A higher spray pressure of 2.5bar did not improve atomization but led to an increased spray loss. At a 20mm nozzle-to-flange distance the spray cone exactly reached the cartridge flange, which was optimal for thicker silicone layers at the flange to ease piston break-loose. Initially, 10μg silicone was sufficient for adequate extrusion in filled cartridges. However, both maximum break-loose and gliding forces in filled cartridges gradually increased from 5-8N to 21-22N upon 80weeks storage at room temperature. The increase for a 30μg silicone level from 3-6N to 10-12N was moderate. Overall, the study provides a comprehensive insight into critical process parameters during the initial spray-on process and the impact of these parameters on the characteristics of the
Comparisons of Solar Wind Coupling Parameters with Auroral Energy Deposition Rates
NASA Technical Reports Server (NTRS)
Elsen, R.; Brittnacher, M. J.; Fillingim, M. O.; Parks, G. K.; Germany G. A.; Spann, J. F., Jr.
1997-01-01
Measurement of the global rate of energy deposition in the ionosphere via auroral particle precipitation is one of the primary goals of the Polar UVI program and is an important component of the ISTP program. The instantaneous rate of energy deposition for the entire month of January 1997 has been calculated by applying models to the UVI images and is presented by Fillingim et al. In this session. A number of parameters that predict the rate of coupling of solar wind energy into the magnetosphere have been proposed in the last few decades. Some of these parameters, such as the epsilon parameter of Perrault and Akasofu, depend on the instantaneous values in the solar wind. Other parameters depend on the integrated values of solar wind parameters, especially IMF Bz, e.g. applied flux which predicts the net transfer of magnetic flux to the tail. While these parameters have often been used successfully with substorm studies, their validity in terms of global energy input has not yet been ascertained, largely because data such as that supplied by the ISTP program was lacking. We have calculated these and other energy coupling parameters for January 1997 using solar wind data provided by WIND and other solar wind monitors. The rates of energy input predicted by these parameters are compared to those measured through UVI data and correlations are sought. Whether these parameters are better at providing an instantaneous rate of energy input or an average input over some time period is addressed. We also study if either type of parameter may provide better correlations if a time delay is introduced; if so, this time delay may provide a characteristic time for energy transport in the coupled solar wind-magnetosphere-ionosphere system.
Multi-objective parameter optimization of common land model using adaptive surrogate modelling
NASA Astrophysics Data System (ADS)
Gong, W.; Duan, Q.; Li, J.; Wang, C.; Di, Z.; Dai, Y.; Ye, A.; Miao, C.
2014-06-01
Parameter specification usually has significant influence on the performance of land surface models (LSMs). However, estimating the parameters properly is a challenging task due to the following reasons: (1) LSMs usually have too many adjustable parameters (20-100 or even more), leading to the curse of dimensionality in the parameter input space; (2) LSMs usually have many output variables involving water/energy/carbon cycles, so that calibrating LSMs is actually a multi-objective optimization problem; (3) regional LSMs are expensive to run, while conventional multi-objective optimization methods needs a huge number of model runs (typically 105~106). It makes parameter optimization computationally prohibitive. An uncertainty qualification framework was developed to meet the aforementioned challenges: (1) use parameter screening to reduce the number of adjustable parameters; (2) use surrogate models to emulate the response of dynamic models to the variation of adjustable parameters; (3) use an adaptive strategy to promote the efficiency of surrogate modeling based optimization; (4) use a weighting function to transfer multi-objective optimization to single objective optimization. In this study, we demonstrate the uncertainty quantification framework on a single column case study of a land surface model - Common Land Model (CoLM) and evaluate the effectiveness and efficiency of the proposed framework. The result indicated that this framework can achieve optimal parameter set using totally 411 model runs, and worth to be extended to other large complex dynamic models, such as regional land surface models, atmospheric models and climate models.
Properties of electrodeposited Co-Mn films: Influence of deposition parameters
NASA Astrophysics Data System (ADS)
Karpuz, Ali; Kockar, Hakan; Alper, Mursel
2015-12-01
Co-Mn films were produced with electrodeposition considering the deposition parameters of electrolyte pH value, Mn concentration of the electrolyte and film thickness. The effect of each parameter on the structural, magnetic and magnetoresistance properties of the films was studied, separately. X-ray diffraction measurement showed that the films have hexagonal close packed structure. For the films deposited at different pH values, the surface morphologies with different-sized globular granules were observed whereas the morphology covered by uniformly distributed nanoscale grains was detected for the surfaces of all films produced from electrolytes with different Mn concentrations. Also, the ribbed surfaces for 6 μm and 4 μm, and the nano-sized acicular surface morphologies for 2 μm were observed. To the results of magnetic measurements, the saturation magnetization was found to be ∼1230 emu/cm3 for all films deposited at different electrolyte pHs. The highest remanent magnetization value was obtained to be 882 emu/cm3 for the film produced from the electrolyte containing 0.06 M Mn concentration. The coercivity, Hc, values decreased from 147 Oe to 43 Oe when the electrolyte pH decreased from 4.7 to 2.6. And, the Hc continued to decrease from 45 Oe to 31 Oe when the Mn concentration increased from 0.02 M to 0.06 M, and from 27 Oe to 22 Oe when the film thickness decreased from 6 μm to 2 μm. It is seen that the Hc was immensely affected by the deposition parameters applied during the film production. The Co-Mn films with low Hc were achieved using relatively low electrolyte pH, high Mn concentration of electrolyte and low film thickness, respectively. Also, influence of the deposition parameters affect Hc is in order of the electrolyte pH, the Mn concentration in the electrolyte and the film thickness (from high to low influence). As it is observed that the magnetic properties are sensible to the deposition parameters and the Co-Mn films may have the potential
Application of optimal input synthesis to aircraft parameter identification
NASA Technical Reports Server (NTRS)
Gupta, N. K.; Hall, W. E., Jr.; Mehra, R. K.
1976-01-01
The Frequency Domain Input Synthesis procedure is used in identifying the stability and control derivatives of an aircraft. By using a frequency-domain approach, one can handle criteria that are not easily handled by the time-domain approaches. Numerical results are presented for optimal elevator deflections to estimate the longitudinal stability and control derivatives subject to root-mean square constraints on the input. The applicability of the steady state optimal inputs to finite duration flight testing is investigated. The steady state approximation of frequency-domain synthesis is good for data lengths greater than two time cycles for the short period mode of the aircraft longitudinal motions. Phase relationships between different frequency components become important for shorter data lengths. The frequency domain inputs are shown to be much better than the conventional doublet inputs.
Mechanical surface treatment of steel-Optimization parameters of regime
NASA Astrophysics Data System (ADS)
Laouar, L.; Hamadache, H.; Saad, S.; Bouchelaghem, A.; Mekhilef, S.
2009-11-01
Mechanical treatment process by superficial plastic deformation is employed for finished mechanical part surface. It introduces structural modifications that offer to basic material new properties witch give a high quality of physical and geometrical on superficial layers. This study focuses on the application of burnishing treatment (ball burnishing) on XC48 steel and parameters optimisation of treatment regime. Three important parameters were considered: burnishing force ' Py', burnishing feed 'f' and ball radius 'r'. An empirical model has been developed to illustrate the relationship between these parameters and superficial layer characteristics defined by surface roughness ' Ra' and superficial hardness ' Hv'. A program was developed in order to determine the optimum treatment regimes for each characteristic.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
NASA Technical Reports Server (NTRS)
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.
NASA Technical Reports Server (NTRS)
Rees, M. H.; Lummerzheim, D.; Roble, R. G.; Winningham, J. D.; Craven, J. D.
1988-01-01
Auroral images obtained by the Spin Scan Auroral Imager (SAI) aboard the DE-1 satellite were used to derive auroral energy deposition rate, characteristic electron energy, and ionospheric parameters. The principles involved in the imaging technique and the physical mechanisms that underlie the relationship between the spectral images and the geophysical parameters are discussed together with the methodology for implementing such analyses. It is shown that images obtained with the SAI provide global parameters at 12-min temporal resolution; the spatial resolution is limited by the field of view of a pixel. The analysis of the 12-min images presented yielded a representation of ionospheric parameters that was better than can be obtained using empirical models based on local measurements averaged over long periods of time.
Calculation and optimization of parameters in low-flow pumps
NASA Astrophysics Data System (ADS)
Kraeva, E. M.; Masich, I. S.
2016-04-01
The materials on balance tests of high-speed centrifugal pumps with low flow rate are presented. On the bases of analysis and research synthesis, we demonstrate the rational use of impellers of semi-open and open types providing high values for energy parameters of feed system of low-flow pumps.
NASA Astrophysics Data System (ADS)
Xia, Youlong; Yang, Zong-Liang; Stoffa, Paul L.; Sen, Mrinal K.
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.
NASA Astrophysics Data System (ADS)
Radhakrishnan, J. K.; Pandian, P. S.; Padaki, V. C.; Bhusan, H.; Rao, K. U. B.; Xie, J.; Abraham, J. K.; Varadan, V. K.
2009-04-01
Multiwalled carbon nanotube (CNT) arrays were grown by catalytic thermal decomposition of acetylene, over Fe-catalyst deposited on Si-wafer in the temperature range 700-750 °C. The growth parameters were optimized to obtain dense arrays of multiwalled CNTs of uniform diameter. The vertical cross-section of the grown nanotube arrays reveals a quasi-vertical alignment of the nanotubes. The effect of varying the thickness of the catalyst layer and the effect of increasing the growth duration on the morphology and distribution of the grown nanotubes were studied. A scotch-tape test to check the strength of adhesion of the grown CNTs to the Si-substrate surface reveals a strong adhesion between the grown nanotubes and the substrate surface. Transmission electron microscopy analysis of the grown CNTs shows that the grown CNTs are multiwalled nanotubes with a bamboo structure, and follow the base-growth mechanism.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
NASA Technical Reports Server (NTRS)
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. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail 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 the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.
NASA Astrophysics Data System (ADS)
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.
Method for Predicting and Optimizing System Parameters for Electrospinning System
NASA Technical Reports Server (NTRS)
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.
Optimal parameters of monolithic high-contrast grating mirrors.
Marciniak, Magdalena; Gębski, Marcin; Dems, Maciej; Haglund, Erik; Larsson, Anders; Riaziat, Majid; Lott, James A; Czyszanowski, Tomasz
2016-08-01
In this Letter a fully vectorial numerical model is used to search for the construction parameters of monolithic high-contrast grating (MHCG) mirrors providing maximal power reflectance. We determine the design parameters of highly reflecting MHCG mirrors where the etching depth of the stripes is less than two wavelengths in free space. We analyze MHCGs in a broad range of real refractive index values corresponding to most of the common optoelectronic materials in use today. Our results comprise a complete image of possible highly reflecting MHCG mirror constructions for potential use in optoelectronic devices and systems. We support the numerical analysis by experimental verification of the high reflectance via a GaAs MHCG designed for a wavelength of 980 nm. PMID:27472602
An all-at-once factorial method to optimize dip-pen deposition of liquid protein inks
NASA Astrophysics Data System (ADS)
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.
On optimal detection and estimation of the FCN parameters
NASA Astrophysics Data System (ADS)
Yatskiv, Y.
2009-09-01
Statistical approach for detection and estimation of parameters of short-term quasi- periodic processes was used in order to investigate the Free Core Nutation (FCN) signal in the Celestial Pole Offset (CPO). The results show that this signal is very unstable and that it disappeared in year 2000. The amplitude of oscillation with period of about 435 days is larger for dX as compared with that for dY .
GEANT4 for breast dosimetry: parameters optimization study
NASA Astrophysics Data System (ADS)
Fedon, C.; Longo, F.; Mettivier, G.; Longo, R.
2015-08-01
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 ({{r}2}>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.
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. PMID:26267405
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%. PMID:24966425
Design and parameter optimization of flip-chip bonder
NASA Astrophysics Data System (ADS)
Shim, Hyoungsub; Kang, Heuiseok; Jeong, Hoon; Cho, Youngjune; Kim, Wansoo; Kang, Shinill
2005-12-01
Bare-chip packaging becomes more popular along with the miniaturization of IT components. In this paper, we have studied flip-chip process, and developed automated bonding system. Among the several bonding method, NCP bonding is chosen and batch-type equipment is manufactured. The dual optics and vision system aligns the chip with the substrate. The bonding head equipped with temperature and force controllers bonds the chip. The system can be easily modified for other bonding methods such as ACF. In bonding process, the bonding force and temperature are known as the most dominant bonding parameters. A parametric study is performed for these two parameters. For the test sample, we used standard flip-chip test kit which consists of FR4 boards and dummy flip-chips. The bonding temperatures are chosen between 25°C to 300°C. The bonding forces are chosen between 5N and 300N. To test the bonding strength, a bonding strength tester was designed and constructed. After the bonding strength test, the samples are examined by microscope to determine the failure mode. The relations between the bonding strength and the bonding parameters are analyzed and compared with bonding models. Finally, the most suitable bonding condition is suggested in terms of temperature and force.
NASA Astrophysics Data System (ADS)
Mrabet, Elyes; Guedri, Mohamed; Ichchou, Mohamed; Ghanmi, Samir
2015-10-01
This work deals with control of vibrating structures using tuned mass damper (TMD) in presence of uncertain bounded structural parameters. The adopted optimization strategy of the TMD parameters is the reliability based optimization (RBO) where the failure probability, approximated with the classical Rice's formula, is related to the primary structure displacement. In presence of uncertain bounded structural parameters it is convenient to describe them using intervals. Consequently, the optimized failure probability is also defined over an interval. In this paper a continuous-optimization nested loop method (CONLM) is presented to provide the exact range of the optimum TMD parameters and their corresponding failure probabilities. The CONLM is time consuming; in this context an approximation method using the monotonicity-based extension method (MBEM) with box splitting is also proposed. Therefore, the initial non-deterministic optimization problem can be transformed into two independent deterministic sub-problems involving discrete-optimization nested loop rather than the continuous-optimization nested loop used in the CONLM. The effectiveness and robustness of the presented optimum bounds of the TMD parameters are investigated and a performance index is introduced. The numerical results obtained with a one degree of freedom and a multi-degree of freedom systems subject to different seismic motions have shown the efficiency of the proposed methods, even with high level of uncertainties. Besides, the good robustness of the TMD device when it is exactly tuned on the optimum TMD parameters corresponding to the deterministic structural parameters has been proven.
NASA Astrophysics Data System (ADS)
Ngo, Viet V.; Gerke, Horst H.; Badorreck, Annika
2014-05-01
The estimability analysis has been proposed to improve the quality of parameter optimization. For field data, wetting and drying processes may complicate optimization of soil hydraulic parameters. The objectives of this study were to apply estimability analysis for improving optimization of soil hydraulic parameters and compare models with and without considering hysteresis. Soil water pressure head data of a field irrigation experiment were used. The one-dimensional vertical water movement in variably-saturated soil was described with the Richards equation using the HYDRUS-1D code. Estimability of the unimodal van Genuchten - Mualem hydraulic model parameters as well as of the hysteretic parameter model of Parker and Lenhard was classified according to a sensitivity coefficient matrix. The matrix was obtained by sequentially calculating effects of initial parameter variations on changes in the simulated pressure head values. Optimization was carried out by means of the Levenberg-Marquardt method as implemented in the HYDRUS-1D code. The parameters α, Ks, θs, and n in the nonhysteretic model were found sensitive and parameter θs and n strongly correlated with parameter n in the nonhysteretic model. When assuming hysteresis, the estimability was highest for αw and decreased with soil depth for Ks and αd, and increased for θs and n. The hysteretic model could approximate the pressure heads in the soil by considering parameters from wetting and drying periods separately as initial estimates. The inverse optimization could be carried out more efficiently with most estimable parameters. Despite the weaknesses of the local optimization algorithm and the inflexibility of the unimodal van Genuchten model, the results suggested that estimability analysis could be considered as a guidance to better define the optimization scenarios and then improved the determination of soil hydraulic parameters.
NASA Astrophysics Data System (ADS)
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.
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan
Liao, Hung-Chang; Chen, Meng-Hao; Wang, Ya-huei
2014-01-01
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. PMID:25250397
NASA Astrophysics Data System (ADS)
Zhang, Xiao-Ming; Ding, Han
2008-11-01
The concept of uncertainty plays an important role in the design of practical mechanical system. The most common methods for solving uncertainty problems are to model the parameters as a random vector. A natural way to handle the randomness is to admit that a given probability density function represents the uncertainty distribution. However, the drawback of this approach is that the probability distribution is difficult to obtain. In this paper, we use the non-probabilistic convex model to deal with the uncertain parameters in which there is no need for probability density functions. Using the convex model theory, a new method to optimize the dynamic response of mechanical system with uncertain parameters is derived. Because the uncertain parameters can be selected as the optimization parameters, the present method can provide more information about the optimization results than those obtained by the deterministic optimization. The present method is implemented for a torsional vibration system. The numerical results show that the method is effective.
NASA Astrophysics Data System (ADS)
Ocylok, Sörn; Alexeev, Eugen; Mann, Stefan; Weisheit, Andreas; Wissenbach, Konrad; Kelbassa, Ingomar
One major demand of today's laser metal deposition (LMD) processes is to achieve a fail-save build-up regarding changing conditions like heat accumulations. Especially for the repair of thin parts like turbine blades is the knowledge about the correlations between melt pool behavior and process parameters like laser power, feed rate and powder mass stream indispensable. The paper will show the process layout with the camera based coaxial monitoring system and the quantitative influence of the process parameters on the melt pool geometry. Therefore the diameter, length and area of the melt pool are measured by a video analytic system at various parameters and compared with the track wide in cross-sections and the laser spot diameter. The influence of changing process conditions on the melt pool is also investigated. On the base of these results an enhanced process of the build-up of a multilayer one track fillet geometry will be presented.
Lee, Chong Bum; Kim, Jeong, Sik; Kim, Yong Goog; Cho, Chang Rae; Byun, D.W.
1996-12-31
The dry deposition of pollutants can be calculated from the concentration of pollutants in the atmosphere and deposition velocity. To calculate deposition velocity, turbulence parameters such as friction velocity and Monin-Obukhov length are used. However, due to the difficulties in observation of turbulence parameters, usually mean values of wind speed and temperature observed using conventional meteorological instruments are used to estimate the dry deposition. The dry deposition velocity is the function of aerodynamic resistance (R{sub a}), sublayer resistance (R{sub b}), surface resistance (R{sub c}). R{sub a} and R{sub b} are calculated from turbulence parameters and R{sub c} is related to surface characteristics. The purpose of the present study is to compare the dry deposition obtained using the data sets of mean values and turbulence parameters measured by sonic anemometer-thermometer. The field observation was performed for 30 days from October 27 to November 25, 1995. The turbulence parameters were measured by 3 dimensional sonic anemometer-thermometer and mean meteorological variables are obtained at two heights, 2.5 m and 10 m. The results show that the dry deposition velocity is large, in daytime and small in nighttime. The major factor of diurnal variation is Ra. In the daytime the dry deposition velocity calculated using mean meteorological data show relatively similar to the dry deposition velocity calculated using the turbulence data, however there are big differences at night.
Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method
NASA Astrophysics Data System (ADS)
Sun, Jun; Zhao, Ji; Wu, Xiaojun; Fang, Wei; Cai, Yujie; Xu, Wenbo
2010-06-01
Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics.
Simultaneous optimization of diesel engine parameters for low emissions using Taguchi methods
Hunter, C.E.; Gardner, T.P.; Zakrajsek, C.E.
1990-01-01
This paper describes a study which was conducted to simultaneously optimize several diesel engine design and operating parameters for low exhaust emissions using the Taguchi method. A single cylinder, research, diesel engine equipped with a high pressure, cam-driven, electronic unit injector was used in this optimization experiment. The major effects of key engine design parameters on exhaust emissions were quantified and optimum parameter settings were determined. Measurement of exhaust emissions using the optimum parameter settings showed that particulates and NO{sub x} emissions were significantly lower than those obtained for the baseline engine. The Taguchi method was found to be a useful technique for the simultaneous optimization of several engine parameters and for predicting the effect of various design parameters on diesel exhaust emissions.
Optimizing composting parameters for nitrogen conservation in composting.
Bueno, P; Tapias, R; López, F; Díaz, M J
2008-07-01
A central composite experimental design was used to investigate the influence of environmental composting parameters (moisture, aeration, particle size and time) for legume trimming residues, used on soil restoration, on the properties of products obtained (organic matter, Kjeldahl-N, C/N ratio and nitrogen losses (N-losses)) in order to determine the best composting conditions. A second-order polynomial model consisting of four independent process variables was found to accurately describe (the differences between the experimental values and those estimated by using the equations never exceeded 10% of the former) the composting process. Results of the experiment showed that compost with acceptably chemical properties (OM, 85%; Kjeldahl-N, 3.2%), high degradation and minimum N-losses entails operating at high operation time (78 days), low particle size (1cm), medium moisture content (40%) and medium to low aeration level (0.2-0.4 l air/min kg). PMID:18023339
Parameter and cost optimizations for a modular stellarator reactor
NASA Astrophysics Data System (ADS)
Hitchon, W. N. G.; Johnson, P. C.; Watson, C. J. H.
1983-02-01
The physical scaling and cost scaling of a modular stellarator reactor are described. It is shown that configurations based on l=2 are best able to support adequate beta, and physical relationships are derived which enable the geometry and parameters of an l=2 modular stellarator to be defined. A cost scaling for the components of the nuclear island is developed using Starfire (tokamak reactor study) engineering as a basis. It is shown that for minimum cost the stellarator should be of small aspect ratio. For a 4000 MWth plant, as Starfire, the optimum configuration is a 15 coil, 3 field period, l=2 device with a major radius of 16 m and a plasma minor radius of 2 m; and with a conservative wall loading of 2 MW/m2 and an average beta of 3.9%; the estimated cost per kilowatt (electrical) is marginally (7%) greater than Starfire.
Enhancing parameter precision of optimal quantum estimation by quantum screening
NASA Astrophysics Data System (ADS)
Jiang, Huang; You-Neng, Guo; Qin, Xie
2016-02-01
We propose a scheme of quantum screening to enhance the parameter-estimation precision in open quantum systems by means of the dynamics of quantum Fisher information. The principle of quantum screening is based on an auxiliary system to inhibit the decoherence processes and erase the excited state to the ground state. By comparing the case without quantum screening, the results show that the dynamics of quantum Fisher information with quantum screening has a larger value during the evolution processes. Project supported by the National Natural Science Foundation of China (Grant No. 11374096), the Natural Science Foundation of Guangdong Province, China (Grants No. 2015A030310354), and the Project of Enhancing School with Innovation of Guangdong Ocean University (Grants Nos. GDOU2014050251 and GDOU2014050252).
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. PMID:27149415
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. PMID:27149415
Parameter Optimization for the Gaussian Model of Folded Proteins
NASA Astrophysics Data System (ADS)
Erman, Burak; Erkip, Albert
2000-03-01
Recently, we proposed an analytical model of protein folding (B. Erman, K. A. Dill, J. Chem. Phys, 112, 000, 2000) and showed that this model successfully approximates the known minimum energy configurations of two dimensional HP chains. All attractions (covalent and non-covalent) as well as repulsions were treated as if the monomer units interacted with each other through linear spring forces. Since the governing potential of the linear springs are derived from a Gaussian potential, the model is called the ''Gaussian Model''. The predicted conformations from the model for the hexamer and various 9mer sequences all lie on the square lattice, although the model does not contain information about the lattice structure. Results of predictions for chains with 20 or more monomers also agreed well with corresponding known minimum energy lattice structures. However, these predicted conformations did not lie exactly on the square lattice. In the present work, we treat the specific problem of optimizing the potentials (the strengths of the spring constants) so that the predictions are in better agreement with the known minimum energy structures.
Influence of ion beam assisted deposition parameters on the growth of MgO and CoFeB
Ferreira, Ricardo; Freitas, Paulo P.; Petrova, Rumyana; McVitie, Stephen
2012-04-01
The effect of the kinetic parameters of an assistance ion beam on the crystallization of ion beam deposited MgO was investigated. It is shown that the crystallization of MgO in the as-deposited state is strongly dependent on the assistance beam parameters. Furthermore, two deposition regimes corresponding to different ranges of the assistance beam energy are found. XRD and TEM studies of CoFeB/MgO/CoFeB with MgO deposited in the two regimes show that CoFeB crystallization is favored when low energy assist beams are used, despite no differences being found in the MgO.
NASA Astrophysics Data System (ADS)
Davis, Stacy
Development of a reliable and inexpensive method for producing hydrogen permeable membranes is of intense interest to ongoing fuel cell research. This study investigated electroless plating of palladium onto stainless steel substrates in hydrazine solution as a possible means of membrane production. Following initial research to establish the optimum infiltrant particle size, sensitization time, and activation time, electroless plating experiments were performed to determine the effects of varying hydrazine concentration, agitation, and residence time on the palladium deposit quality and morphology. SEM examination of the experimental products elucidated relationships between specific plating bath parameters or combinations of parameters, the governing deposition mechanisms, and the deposit morphologies. The results indicate that it is possible to produce application-specific deposit layer morphologies by modifying the plating bath parameters at critical stages of the plating cycle.
NASA Astrophysics Data System (ADS)
Srivastava, Prashant K.; O'Neill, Peggy; Han, Dawei; Rico-Ramirez, Miguel A.; Petropoulos, George P.; Islam, Tanvir; Gupta, Manika
2015-04-01
Roughness parameterization is necessary for nearly all soil moisture retrieval algorithms such as single or dual channel algorithms, L-band Microwave Emission of Biosphere (LMEB), Land Parameter Retrieval Model (LPRM), etc. At present, roughness parameters can be obtained either by field experiments, although obtaining field measurements all over the globe is nearly impossible, or by using a land cover-based look up table, which is not always accurate everywhere for individual fields. From a catalogue of models available in the technical literature domain, the LPRM model was used here because of its robust nature and applicability to a wide range of frequencies. LPRM needs several parameters for soil moisture retrieval -- in particular, roughness parameters (h and Q) are important for calculating reflectivity. In this study, the h and Q parameters are optimized using the soil moisture deficit (SMD) estimated from the probability distributed model (PDM) and Soil Moisture and Ocean Salinity (SMOS) brightness temperatures following the Levenberg-Marquardt (LM) algorithm over the Brue catchment, Southwest of England, U.K.. The catchment is predominantly a pasture land with moderate topography. The PDM-based SMD is used as it is calibrated and validated using locally available ground-based information, suitable for large scale areas such as catchments. The optimal h and Q parameters are determined by maximizing the correlation between SMD and LPRM retrieved soil moisture. After optimization the values of h and Q have been found to be 0.32 and 0.15, respectively. For testing the usefulness of the estimated roughness parameters, a separate set of SMOS datasets are taken into account for soil moisture retrieval using the LPRM model and optimized roughness parameters. The overall analysis indicates a satisfactory result when compared against the SMD information. This work provides quantitative values of roughness parameters suitable for large scale applications. The
Simulation optimization of the cathode deposit growth in a coaxial electrolyzer-refiner
NASA Astrophysics Data System (ADS)
Smirnov, G. B.; Fokin, A. A.; Markina, S. E.; Vakhitov, A. I.
2015-08-01
The results of simulation of the cathode deposit growth in a coaxial electrolyzer-refiner are presented. The sizes of the initial cathode matrix are optimized. The data obtained by simulation and full-scale tests of the precipitation of platinum from a salt melt are compared.
Rethinking design parameters in the search for optimal dynamic seating.
Pynt, Jennifer
2015-04-01
Dynamic seating design purports to lessen damage incurred during sedentary occupations by increasing sitter movement while modifying muscle activity. Dynamic sitting is currently defined by O'Sullivan et al. ( 2013a) as relating to 'the increased motion in sitting which is facilitated by the use of specific chairs or equipment' (p. 628). Yet the evidence is conflicting that dynamic seating creates variation in the sitter's lumbar posture or muscle activity with the overall consensus being that current dynamic seating design fails to fulfill its goals. Research is needed to determine if a new generation of chairs requiring active sitter involvement fulfills the goals of dynamic seating and aids cardio/metabolic health. This paper summarises the pursuit of knowledge regarding optimal seated spinal posture and seating design. Four new forms of dynamic seating encouraging active sitting are discussed. These are 1) The Core-flex with a split seatpan to facilitate a walking action while seated 2) the Duo balans requiring body action to create rocking 3) the Back App and 4) Locus pedestal stools both using the sitter's legs to drive movement. Unsubstantiated claims made by the designers of these new forms of dynamic seating are outlined. Avenues of research are suggested to validate designer claims and investigate whether these designs fulfill the goals of dynamic seating and assist cardio/metabolic health. Should these claims be efficacious then a new definition of dynamic sitting is suggested; 'Sitting in which the action is provided by the sitter, while the dynamic mechanism of the chair accommodates that action'. PMID:25892386
Evaluation of fluid bed heat exchanger optimization parameters. Final report
Not Available
1980-03-01
Uncertainty in the relationship of specific bed material properties to gas-side heat transfer in fluidized beds has inhibited the search for optimum bed materials and has led to over-conservative assumptions in the design of fluid bed heat exchangers. An experimental program was carried out to isolate the effects of particle density, thermal conductivity, and heat capacitance upon fluid bed heat transfer. A total of 31 tests were run with 18 different bed material loads on 12 material types; particle size variations were tested on several material types. The conceptual design of a fluidized bed evaporator unit was completed for a diesel exhaust heat recovery system. The evaporator heat transfer surface area was substantially reduced while the physical dimensions of the unit increased. Despite the overall increase in unit size, the overall cost was reduced. A study of relative economics associated with bed material selection was conducted. For the fluidized bed evaporator, it was found that zircon sand was the best choice among materials tested in this program, and that the selection of bed material substantially influences the overall system costs. The optimized fluid bed heat exchanger has an estimated cost 19% below a fin augmented tubular heat exchanger; 31% below a commercial design fluid bed heat exchanger; and 50% below a conventional plain tube heat exchanger. The comparisons being made for a 9.6 x 10/sup 6/ Btu/h waste heat boiler. The fluidized bed approach potentially has other advantages such as resistance to fouling. It is recommended that a study be conducted to develop a systematic selection of bed materials for fluidized bed heat exchanger applications, based upon findings of the study reported herein.
NASA Technical Reports Server (NTRS)
Rizk, Magdi H.
1988-01-01
This user's manual is presented for an aerodynamic optimization program that updates flow variables and design parameters simultaneously. The program was developed for solving constrained optimization problems in which the objective function and the constraint function are dependent on the solution of the nonlinear flow equations. The program was tested by applying it to the problem of optimizing propeller designs. Some reference to this particular application is therefore made in the manual. However, the optimization scheme is suitable for application to general aerodynamic design problems. A description of the approach used in the optimization scheme is first presented, followed by a description of the use of the program.
Figueredo-Sobrinho, Francisco A A; Santos, Luis P M; Leite, Davi S; Craveiro, Diego C; Santos, Samir H; Eguiluz, Katlin I B; Salazar-Banda, Giancarlo R; Maciel, Cleiton D; Coutinho-Neto, Maurício D; Homem-de-Mello, Paula; de Lima-Neto, Pedro; Correia, Adriana N
2016-03-14
The low toxicity and environmentally compatible ionic liquids (ILs) are alternatives to the toxic and harmful cyanide-based baths used in industrial silver electrodeposition. Here, we report the successful galvanostatic electrodeposition of silver films using the air and water stable ILs 1-ethyl-3-methylimidazolium trifluoromethylsulfonate ([EMIM]TfO) and 1-H-3-methylimidazolium hydrogen sulphate ([HMIM(+)][HSO4(-)]) as solvents and AgTfO as the source of silver. The electrochemical deposition parameters were thoughtfully studied by cyclic voltammetry before deposition. The electrodeposits were characterized by scanning electron microscopy coupled with X-ray energy dispersive spectroscopy and X-ray diffraction. Molecular dynamics (MD) simulations were used to investigate the structural dynamic and energetic properties of AgTfO in both ILs. Cyclic voltammetry experiments revealed that the reduction of silver is a diffusion-controlled process. The morphology of the silver coatings obtained in [EMIM]TfO is independent of the applied current density, resulting in nodular electrodeposits grouped as crystalline clusters. However, the current density significantly influences the morphology of silver electrodeposits obtained in [HMIM(+)][HSO4(-)], thus evolving from dendrites at 15 mA cm(-2) to the coexistence of dendrites and columnar shapes at 30 mA cm(-2). These differences are probably due to the greater interaction of Ag(+) with [HSO4(-)] than with TfO(-), as indicated by the MD simulations. The morphology of Ag deposits is independent of the electrodeposition temperature for both ILs, but higher values of temperature promoted increased cluster sizes. Pure face-centred cubic polycrystalline Ag was deposited on the films with crystallite sizes on the nanometre scale. The morphological dependence of Ag electrodeposits obtained in the [HMIM(+)][HSO4(-)] IL on the current density applied opens up the opportunity to produce different and predetermined Ag deposits. PMID
NASA Astrophysics Data System (ADS)
Akesso, Laurent; Navabpour, Parnia; Teer, Dennis; Pettitt, Michala E.; Callow, Maureen E.; Liu, Chen; Su, Xueju; Wang, Su; Zhao, Qi; Donik, Crtomir; Kocijan, Aleksandra; Jenko, Monika; Callow, James A.
2009-04-01
A range of SiO x-like coatings was deposited on glass slides from a hexamethylsiloxane precursor by plasma-assisted CVD. The effect of varying deposition parameters, specifically ion cleaning time and HMDSO/O 2 ratios, on the coating properties and antifouling performance was investigated. At low HMDSO/O 2 ratios, the resulting coatings were close to SiO 2. Carbon content in the bulk of the coatings increased with increasing HMDSO/O 2 ratio. Coatings deposited at high HMDSO/O 2 ratios and with the longest cleaning time (30 min), elevated the relative carbon content to 25 atomic %. Surface energies (22-43 mJ/m) were correlated with the degree of surface oxidation and hydrocarbon content. With the exception of the most polar coatings the apolar component of the surface energy ( γLW) was the dominant component. In the most hydrophilic coatings, the Lewis base component of the surface energy ( γ-) was dominant. Significantly improved antifouling performance was detected with the most reduced coatings deposited using the extended ion cleaning times. For both, the removal of sporelings of the marine green alga, Ulvalinza and the initial adhesion of the freshwater bacterium, Pseudomonas fluorescens, there was a strong, positive correlation between strength of attachment and ion cleaning time. Increased ion cleaning time will elevate the deposition temperature, increasing decomposition rates and thus the crosslinking of the polymer. Increased cross-linking may render these coatings less permeable to penetration and mechanical interlocking by the adhesive polymers used by these organisms, thus reducing their adhesion. Films with improved biological performance have potential for use as coatings in the control of biofouling in applications such as heat exchangers, where thin films are important for effective thermal transfer, or optical windows where transparency is important.
Wafer-scale process and materials optimization in cross-flow atomic layer deposition
NASA Astrophysics Data System (ADS)
Lecordier, Laurent Christophe
The exceptional thickness control (atomic scale) and conformality (uniformity over nanoscale 3D features) of atomic layer deposition (ALD) has made it the process of choice for numerous applications from microelectronics to nanotechnology, and for a wide variety of ALD processes and resulting materials. While its benefits derive from self-terminated chemisorbed reactions of alternatively supplied gas precursors, identifying a suitable process window in which ALD's benefits are realized can be a challenge, even in favorable cases. In this work, a strategy exploiting in-situ gas phase sensing in conjunction with ex-situ measurements of the film properties at the wafer scale is employed to explore and optimize the prototypical Al2O3 ALD process. Downstream mass-spectrometry is first used to rapidly identify across the [H2O x Al(CH3)3] process space the exposure conditions leading to surface saturation. The impact of precursor doses outside as well as inside the parameter space outlined by mass-spectrometry is then investigated by characterizing film properties across 100 mm wafer using spectroscopic ellipsometry, CV and IV electrical characterization, XPS and SIMS. Under ideal dose conditions, excellent thickness uniformity was achieved (1sigma/mean<1%) in conjunction with a deposition rate and electrical properties in good agreement with best literature data. As expected, under-dosing of precursor results in depletion of film growth in the flow direction across the wafer surface. Since adsorbed species are reactive with respect to subsequent dose of the complementary precursor, such depletion magnifies non-uniformities as seen in the cross-flow reactor, thereby decorating deviations from a suitable ALD process recipe. Degradation of the permittivity and leakage current density across the wafer was observed though the film composition remained unchanged. Upon higher water dose in the over-exposure regime, deposition rates increased by up to 40% while the uniformity
CH4 parameter estimation in CLM4.5bgc using surrogate global optimization
NASA Astrophysics Data System (ADS)
Müller, J.; Paudel, R.; Shoemaker, C. A.; Woodbury, J.; Wang, Y.; Mahowald, N.
2015-10-01
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 methane emission predictions of the CLM using the optimized parameters agree better with the observed methane emission data in northern and tropical latitudes. With the optimized parameters, the methane emission predictions are higher in northern latitudes than when the default parameters are
NASA Astrophysics Data System (ADS)
Reimer, J.; Schürch, M.; Slawig, T.
2014-09-01
The weighted least squares estimator for model parameters was presented together with its asymptotic properties. A popular approach to optimize experimental designs called local optimal experimental designs was described together with a lesser known approach which takes into account a potential nonlinearity of the model parameters. These two approaches were combined with two different methods to solve their underlying discrete optimization problem. All presented methods were implemented in an open source MATLAB toolbox called the Optimal Experimental Design Toolbox whose structure and handling was described. In numerical experiments, the model parameters and experimental design were optimized using this toolbox. Two models for sediment concentration in seawater of different complexity served as application example. The advantages and disadvantages of the different approaches were compared, and an evaluation of the approaches was performed.
Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S
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
Optimizing the sequence parameters for double-quantum CRAZED imaging.
Marques, J P; Bowtell, R
2004-01-01
The evolution of magnetization during repeated application of the double-quantum-(DQ)-CRAZED sequence is analyzed, with the aim of identifying sequence parameters that maximize sensitivity to signal produced by the distant dipole field (DDF). Phase cycling schemes that allow cancellation of signals following undesired coherence pathways are also described. Simulations and imaging experiments carried out at 3 T on phantoms and the human head were used to verify the analysis. The results indicate that in the absence of phase cycling, the DDF-related signal-to-noise ratio (SNR) per unit time is maximized using TR=2.05 T1, along with values of the RF flip angles (alpha approximately 90 degrees and beta approximately 60 degrees ), and echo time (TE=T2) that have previously been shown to maximize the DDF-related signal at long TR. However, with TR=2.05 T1 there can also be a significant signal contribution due to stimulated echo effects (up to 40% of the signal for water at 3 T and TE=70 ms). Using a two-step phase cycle, the stimulated echo signal is eliminated and the maximum SNR per unit time occurs for TR=2.76 T1. It is also demonstrated that sensitivity to signal changes caused by small variations in T2 is maximized by setting TE=2T2. PMID:14705055
Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method
Parida, Arun Kumar; Routara, Bharat Chandra
2014-01-01
Taguchi's design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (v), feed (f), and depth of cut (d), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (Ra). The machining is conducted with Taguchi L9 orthogonal array, and based on the S/N analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, v3-f2-d3. Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, v1-f1-d3. Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach. PMID:27437503
Structure and electronic parameters of a-Si:H deposited by DC-MASD
Golikova, O.A.; Kuznetsov, A.N.; Kudoyarova, V.K.; Kazanin, M.M.; Adriaenssens, G.J.; Herremans, H.
1997-07-01
A systematic study of structure and electronic parameters of a-Si:H deposited by dc-magnetron assisted SiH{sub 4} decomposition (MASD) depending on substrate temperature, gas pressure, gas flow and grid mounting has been carried out. Correlation between the film microstructure, dangling bond density and electron mobility-life time product were established. The photoconductivity changes under light soaking were shown to be minimal when the films contained hydrogen in the (SiH{sub 2}){sub n} chains.
Determination of dispersion parameters of thermally deposited CdTe thin film
NASA Astrophysics Data System (ADS)
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.
Optimization of parameters for coverage of low molecular weight proteins
Müller, Stephan A.; Kohajda, Tibor; Findeiß, Sven; Stadler, Peter F.; Washietl, Stefan; Kellis, Manolis; von Bergen, Martin
2010-01-01
Proteins with molecular weights of <25 kDa are involved in major biological processes such as ribosome formation, stress adaption (e.g., temperature reduction) and cell cycle control. Despite their importance, the coverage of smaller proteins in standard proteome studies is rather sparse. Here we investigated biochemical and mass spectrometric parameters that influence coverage and validity of identification. The underrepresentation of low molecular weight (LMW) proteins may be attributed to the low numbers of proteolytic peptides formed by tryptic digestion as well as their tendency to be lost in protein separation and concentration/desalting procedures. In a systematic investigation of the LMW proteome of Escherichia coli, a total of 455 LMW proteins (27% of the 1672 listed in the SwissProt protein database) were identified, corresponding to a coverage of 62% of the known cytosolic LMW proteins. Of these proteins, 93 had not yet been functionally classified, and five had not previously been confirmed at the protein level. In this study, the influences of protein extraction (either urea or TFA), proteolytic digestion (solely, and the combined usage of trypsin and AspN as endoproteases) and protein separation (gel- or non-gel-based) were investigated. Compared to the standard procedure based solely on the use of urea lysis buffer, in-gel separation and tryptic digestion, the complementary use of TFA for extraction or endoprotease AspN for proteolysis permits the identification of an extra 72 (32%) and 51 proteins (23%), respectively. Regarding mass spectrometry analysis with an LTQ Orbitrap mass spectrometer, collision-induced fragmentation (CID and HCD) and electron transfer dissociation using the linear ion trap (IT) or the Orbitrap as the analyzer were compared. IT-CID was found to yield the best identification rate, whereas IT-ETD provided almost comparable results in terms of LMW proteome coverage. The high overlap between the proteins identified with IT
Multi-objective parameter optimization of common land model using adaptive surrogate modeling
NASA Astrophysics Data System (ADS)
Gong, W.; Duan, Q.; Li, J.; Wang, C.; Di, Z.; Dai, Y.; Ye, A.; Miao, C.
2015-05-01
Parameter specification usually has significant influence on the performance of land surface models (LSMs). However, estimating the parameters properly is a challenging task due to the following reasons: (1) LSMs usually have too many adjustable parameters (20 to 100 or even more), leading to the curse of dimensionality in the parameter input space; (2) LSMs usually have many output variables involving water/energy/carbon cycles, so that calibrating LSMs is actually a multi-objective optimization problem; (3) Regional LSMs are expensive to run, while conventional multi-objective optimization methods need a large number of model runs (typically ~105-106). It makes parameter optimization computationally prohibitive. An uncertainty quantification framework was developed to meet the aforementioned challenges, which include the following steps: (1) using parameter screening to reduce the number of adjustable parameters, (2) using surrogate models to emulate the responses of dynamic models to the variation of adjustable parameters, (3) using an adaptive strategy to improve the efficiency of surrogate modeling-based optimization; (4) using a weighting function to transfer multi-objective optimization to single-objective optimization. In this study, we demonstrate the uncertainty quantification framework on a single column application of a LSM - the Common Land Model (CoLM), and evaluate the effectiveness and efficiency of the proposed framework. The result indicate that this framework can efficiently achieve optimal parameters in a more effective way. Moreover, this result implies the possibility of calibrating other large complex dynamic models, such as regional-scale LSMs, atmospheric models and climate models.
NASA Astrophysics Data System (ADS)
Hu, Li-Yun; Liao, Zeyang; Ma, Shengli; Zubairy, M. Suhail
2016-03-01
We introduce three tunable parameters to optimize the fidelity of quantum teleportation with continuous variables in a nonideal scheme. By using the characteristic-function formalism, we present the condition that the teleportation fidelity is independent of the amplitude of input coherent states for any entangled resource. Then we investigate the effects of tunable parameters on the fidelity with or without the presence of the environment and imperfect measurements by analytically deriving the expression of fidelity for three different input coherent-state distributions. It is shown that, for the linear distribution, the optimization with three tunable parameters is the best one with respect to single- and two-parameter optimization. Our results reveal the usefulness of tunable parameters for improving the fidelity of teleportation and the ability against decoherence.
NASA Astrophysics Data System (ADS)
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.
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, is now a
NASA Astrophysics Data System (ADS)
Rao, R. V.; Savsani, V. J.; Balic, J.
2012-12-01
An efficient optimization algorithm called teaching-learning-based optimization (TLBO) is proposed in this article to solve continuous unconstrained and constrained optimization problems. The proposed method is based on the effect of the influence of a teacher on the output of learners in a class. The basic philosophy of the method is explained in detail. The algorithm is tested on 25 different unconstrained benchmark functions and 35 constrained benchmark functions with different characteristics. For the constrained benchmark functions, TLBO is tested with different constraint handling techniques such as superiority of feasible solutions, self-adaptive penalty, ɛ-constraint, stochastic ranking and ensemble of constraints. The performance of the TLBO algorithm is compared with that of other optimization algorithms and the results show the better performance of the proposed algorithm.
NASA Astrophysics Data System (ADS)
Tomov, R.; Tsaneva, V.; Tsanev, V.; Ouzounov, D.
1996-12-01
Cumulative laser irradiation during high-Tc superconducting thin film pulsed laser deposition (PLD) may have a detrimental effect on film characteristics. Initial decrease of deposition rate and gradual shift of the center of the deposited material spot towards the incoming laser beam were registered on cold glass substrates. Their absorbance was used for evaluation of the film thickness distribution over the substrate area. At the initial stage, two components of the spot could be distinguished along its short axis: central (˜cosn θ, n≫1) and peripherial (˜cos θ), while with cumulative irradiation the thickness followed an overall cosm θ (m
NASA Astrophysics Data System (ADS)
Coon, Joshua
Magnetic Resonance guided High Intensity Focused Ultrasound (MRgHIFU) treatments are a promising modality for cancer treatments in which a focused beam of ultrasound energy is used to kill tumor tissue. However, obstacles still exist to its widespread clinical implementation, including long treatment times. This research demonstrates reductions in treatment times through intelligent selection of the user-controllable parameters, including: the focal zone treatment path, focal zone size, focal zone spacing, and whether to treat one or several focal zone locations at any given time. Several treatments using various combinations of these parameters were simulated using a finite difference method to solve the Pennes bio-heat transfer equation for an ultrasonically heated tissue region with a wide range of acoustic, thermal, geometric, and tumor properties. The total treatment time was iteratively optimized using either a heuristic method or routines included in the Matlab software package, with constraints imposed for patient safety and treatment efficacy. The results demonstrate that large reductions in treatment time are possible through the intelligent selection of user-controllable treatment parameters. For the treatment path, treatment times are reduced by as much as an order of magnitude if the focal zones are arranged into stacks along the axial direction and a middle-front-back ordering is followed. For situations where normal tissue heating constraints are less stringent, these focal zones should have high levels of adjacency to further decrease treatment times; however, adjacency should be reduced in some cases where normal tissue constraints are more stringent. Also, the use of smaller, more concentrated focal zones produces shorter treatment times than larger, more diluted focal zones, a result verified in an agar phantom model. Further, focal zones should be packed using only a small amount of overlap in the axial direction and with a small gap in the
NASA Astrophysics Data System (ADS)
Pradhan, Ajaya Kumar; Das, Siddhartha
2014-11-01
Cu-SiC nanocomposite coatings have been deposited from an aqueous sulfate electrolyte using the technique of pulse reverse electrodeposition both in the absence and presence of three different types of surfactants, anionic, cationic, or nonionic. The effects of different electrodeposition parameters on some properties of the coatings have been studied. In all cases, it has been observed that the surface roughness, hardness, and resistivity increase with the increase in cathodic current density. However, they have been observed to decrease with the increase in anodic current density and the anodic current time. The variation in the amount of incorporated reinforcement with different deposition parameters has been observed to be dependent on the nature of the surfactant used. In the presence of cationic and nonionic surfactant, a noticeable increase in the amount of incorporated reinforcement and hardness has been observed. Samples prepared under higher anodic current density have been observed to possess lower stress, but intense texture. An increase in cathodic current density has been observed to decrease the extent of texturing.
Influence of the oxygen plasma parameters on the atomic layer deposition of titanium dioxide.
Ratzsch, Stephan; Kley, Ernst-Bernhard; Tünnermann, Andreas; Szeghalmi, Adriana
2015-01-16
The influence of the oxygen plasma parameters on the morphology and optical properties of TiO2 thin films has been extensively analyzed in plasma enhanced atomic layer deposition (PEALD) processes. Crystalline aggregates with the anatase phase have been identified on the film surface at a low deposition temperature (down to 70 °C) under specific plasma conditions. Up to 70% surface coverage by anatase crystallites is obtained at low oxygen gas flow rates and high plasma power. The hillocks abundance is correlated with high ion flux and electron density and with the resulting enhanced ion bombardment of the surface. Altering the plasma conditions is an important parameter besides temperature to control the morphology of the titania film for specific applications such as photocatalysis or functional optical coatings. Specifically, photocatalytic titania coatings on polymer substrates could benefit of such low temperature PEALD processes with abundant anatase crystallites; whereas optical coatings require smooth, high refractive index titania as obtained with low plasma power and high oxygen flow rate. PMID:25525676
Derivative-free optimization for parameter estimation in computational nuclear physics
NASA Astrophysics Data System (ADS)
Wild, Stefan M.; Sarich, Jason; Schunck, Nicolas
2015-03-01
We consider optimization problems that arise when estimating a set of unknown parameters from experimental data, particularly in the context of nuclear density functional theory. We examine the cost of not having derivatives of these functionals with respect to the parameters. We show that the POUNDERS code for local derivative-free optimization obtains consistent solutions on a variety of computationally expensive energy density functional calibration problems. We also provide a primer on the operation of the POUNDERS software in the Toolkit for advanced optimization.
Zhang, Xing-Yi; Chen, Da-Wei; Jin, Jie; Lu, Wei
2009-10-01
Artificial neural network (ANN) is a multi-objective optimization method that needs mathematic and statistic knowledge which restricts its application in the pharmaceutical research area. An artificial neural network parameters optimization software (ANNPOS) programmed by the Visual Basic language was developed to overcome this shortcoming. In the design of a sustained release formulation, the suitable parameters of ANN were estimated by the ANNPOS. And then the Matlab 5.0 Neural Network Toolbox was used to determine the optimal formulation. It showed that the ANNPOS reduced the complexity and difficulty in the ANN's application. PMID:20055142
Study of deposition parameters for the fabrication of ZnO thin films using femtosecond laser
NASA Astrophysics Data System (ADS)
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.
Iyer, Shilesh; Carranza, Dafnis; Kolodney, Michael; Macgregor, David; Chipps, Lisa; Soriano, Teresa
2007-06-01
Several lasers and light sources have been reported to induce dermal collagen remodeling without damaging the epidermis. The intense pulsed light (IPL) system, which emits polychromatic light of wavelengths between 560 and 1200 nm belongs to this group of increasingly popular non-ablative skin rejuvenation devices. Various IPL treatment parameters can be adjusted to achieve optimal dermal remodeling and clinical improvement. The aim of this study was to evaluate variations in IPL treatment parameters and the effect on procollagen I deposition. Marked areas of a live Yorkshire pig's flank skin were irradiated with a single or double pass of an IPL source using a fluence of 30 or 40 J/cm2 and a cut-off wavelength filter of 590 nm. Skin biopsies were performed on postoperative days 1, 7, 14, 21, and 42. A statistically significant increase in procollagen I in treated versus untreated sites was found on postoperative days 21 and 42, but not earlier. There was a uniformly significant increase in procollagen I on day 42 using the 590 nm filter at both 30 and 40 J/cm2 with either a single or double pass. The increase in procollagen was greater with a fluence of 40 J/cm2 compared with 30 J/cm2. PMID:17558756
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. PMID:26943630
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. PMID:26943630
NASA Astrophysics Data System (ADS)
Bera, Mahua; Banerjee, Jayeta; Ray, Mina
2014-02-01
Metallic film thickness optimization in mono- and bimetallic plasmonic structures has been carried out in order to determine the correct device parameters. Different resonance parameters, such as reflectivity, phase, field enhancement, and the complex amplitude reflectance Argand diagram (CARAD), have been investigated for the proposed optimization procedure. Comparison of mono- and bimetallic plasmonic structures has been carried out in the context of these resonance parameters with simultaneous angular and spectral interrogation. Differential phase analysis has also been performed and its application to sensing has been discussed along with a proposed interferometric set-up.
Optimization of parameters for the inline-injection system at Brookhaven Accelerator Test Facility
Parsa, Z.; Ko, S.K.
1995-10-01
We present some of our parameter optimization results utilizing code PARMLEA, for the ATF Inline-Injection System. The new solenoid-Gun-Solenoid -- Drift-Linac Scheme would improve the beam quality needed for FEL and other experiments at ATF as compared to the beam quality of the original design injection system. To optimize the gain in the beam quality we have considered various parameters including the accelerating field gradient on the photoathode, the Solenoid field strengths, separation between the gun and entrance to the linac as well as the (type size) initial charge distributions. The effect of the changes in the parameters on the beam emittance is also given.
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
Yousefi, Amin Termeh; Mahmood, Mohamad Rusop; Ikeda, Shoichiro
2016-07-01
According to the unique properties of Carbon nanotubes (CNTs), they have been under scientific investigation for more than fifteen years in different applications. Here we reported the effect of temperature on camphor in a wide range of 500-1150 ˚C. The results indicate that camphor did not decompose below 500 ˚C but very short-length tubes emerged from the silicon substrate at 550 ˚C which is suggesting that the catalyst activity. According to the results, the CNT growth rate was abruptly increased at 600 ˚C. This process was done on the same condition by optimizing the temperature up to 900 ˚C. FESEM images indicate the highest catalyst activity at 850 ˚C which direct the experiment to grow purified CNT up to 3 µm in the length. This result suggests that, at low temperatures, the catalyst-support interaction is strong enough not to let the metal particles to involve in deposition process, but at 850 ˚C MWCNTs and SWCNTs can be selectively grown as a function of CVD temperature. The optimum deposition time was found in 30 minutes, which based on the Raman shift results the growth CNTs has shown high purity and crystallinity as well as high aspect ratio.
Oyster Creek cycle 10 nodal model parameter optimization study using PSMS
Dougher, J.D.
1987-01-01
The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed.
NASA Astrophysics Data System (ADS)
Cristea, D.; Pătru, M.; Crisan, A.; Munteanu, D.; Crăciun, D.; Barradas, N. P.; Alves, E.; Apreutesei, M.; Moura, C.; Cunha, L.
2015-12-01
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 N2/O2 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(N2 + O2). 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(N2 + O2) 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 lower the density. Firstly, a dominant β-Ta structure is observed, for low P(N2 + O2); secondly a fcc-Ta(N,O) structure, for intermediate P(N2 + O2); thirdly, the films are amorphous for the highest partial pressures. The comparison of the characteristics of both sets of produced TaNxOy films are explained, with detail, in the text.
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.
NASA Astrophysics Data System (ADS)
Chiu, Y.; Nishikawa, T.
2013-12-01
With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.
Parametric optimal bounded feedback control for smart parameter-controllable composite structures
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Chen, Y.; Li, J.; Xu, H.
2015-10-01
Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be
Optimization of hydrological parameters of a distributed runoff model based on multiple flood events
NASA Astrophysics Data System (ADS)
Miyamoto, Mamoru; Matsumoto, Kazuhiro; Tsuda, Morimasa; Yamakage, Yuzuru; Iwami, Yoichi; Anai, Hirokazu
2015-04-01
The error sources of flood forecasting by a runoff model commonly include input data, model structures, and parameter settings. This study focused on a calibration procedure to minimize errors due to parameter settings. Although many studies have been done on hydrological parameter optimization, they are mostly about individual optimization cases applying a specific optimization technique to a specific flood. Consequently, it is difficult to determine the most appropriate parameter set to make forecasts on future floods, because optimized parameter sets vary by flood type. Thus, this study aimed to develop a comprehensive method for optimizing hydrological parameters of a distributed runoff model for future flood forecasting. A distributed runoff model, PWRI-DHM, was applied to the Gokase River basin of 1,820km2 in Japan in this study. The model with gridded two-layer tanks for the entire target river basin includes hydrological parameters, such as hydraulic conductivity, surface roughness and runoff coefficient, which are set according to land-use and soil-type distributions. Global data sets, e.g., Global Map and DSMW (Digital Soil Map of the World), were employed as input data such as elevation, land use and soil type. Thirteen optimization algorithms such as GA, PSO and DEA were carefully selected from seventy-four open-source algorithms available for public use. These algorithms were used with three error assessment functions to calibrate the parameters of the model to each of fifteen past floods in the predetermined search range. Fifteen optimized parameter sets corresponding to the fifteen past floods were determined by selecting the best sets from the calibration results in terms of reproducible accuracy. This process helped eliminate bias due to type of optimization algorithms. Although the calibration results of each parameter were widely distributed in the search range, statistical significance was found in comparisons between the optimized parameters
"Body-In-The-Loop": Optimizing Device Parameters Using Measures of Instantaneous Energetic Cost
Felt, Wyatt; Selinger, Jessica C.; Donelan, J. Maxwell; Remy, C. David
2015-01-01
This paper demonstrates methods for the online optimization of assistive robotic devices such as powered prostheses, orthoses and exoskeletons. Our algorithms estimate the value of a physiological objective in real-time (with a body “in-the-loop”) and use this information to identify optimal device parameters. To handle sensor data that are noisy and dynamically delayed, we rely on a combination of dynamic estimation and response surface identification. We evaluated three algorithms (Steady-State Cost Mapping, Instantaneous Cost Mapping, and Instantaneous Cost Gradient Search) with eight healthy human subjects. Steady-State Cost Mapping is an established technique that fits a cubic polynomial to averages of steady-state measures at different parameter settings. The optimal parameter value is determined from the polynomial fit. Using a continuous sweep over a range of parameters and taking into account measurement dynamics, Instantaneous Cost Mapping identifies a cubic polynomial more quickly. Instantaneous Cost Gradient Search uses a similar technique to iteratively approach the optimal parameter value using estimates of the local gradient. To evaluate these methods in a simple and repeatable way, we prescribed step frequency via a metronome and optimized this frequency to minimize metabolic energetic cost. This use of step frequency allows a comparison of our results to established techniques and enables others to replicate our methods. Our results show that all three methods achieve similar accuracy in estimating optimal step frequency. For all methods, the average error between the predicted minima and the subjects’ preferred step frequencies was less than 1% with a standard deviation between 4% and 5%. Using Instantaneous Cost Mapping, we were able to reduce subject walking-time from over an hour to less than 10 minutes. While, for a single parameter, the Instantaneous Cost Gradient Search is not much faster than Steady-State Cost Mapping, the
NASA Technical Reports Server (NTRS)
Foote, M. C.; Jones, B. B.; Hunt, B. D.; Barner, J. B.; Vasquez, R. P.; Bajuk, L. J.
1992-01-01
The composition of pulsed-ultraviolet-laser-deposited Y-Ba-Cu-O films was examined as a function of position across the substrate, laser fluence, laser spot size, substrate temperature, target conditioning, oxygen pressure and target-substrate distance. Laser fluence, laser spot size, and substrate temperature were found to have little effect on composition within the range investigated. Ablation from a fresh target surface results in films enriched in copper and barium, both of which decrease in concentration until a steady state condition is achieved. Oxygen pressure and target-substrate distance have a significant effect on film composition. In vacuum, copper and barium are slightly concentrated at the center of deposition. With the introduction of an oxygen background pressure, scattering results in copper and barium depletion in the deposition center, an effect which increases with increasing target-substrate distance. A balancing of these two effects results in stoichiometric deposition.
Landmark-driven parameter optimization for non-linear image registration
NASA Astrophysics Data System (ADS)
Schmidt-Richberg, Alexander; Werner, René; Ehrhardt, Jan; Wolf, Jan-Christoph; Handels, Heinz
2011-03-01
Image registration is one of the most common research areas in medical image processing. It is required for example for image fusion, motion estimation, patient positioning, or generation of medical atlases. In most intensity-based registration approaches, parameters have to be determined, most commonly a parameter indicating to which extend the transformation is required to be smooth. Its optimal value depends on multiple factors like the application and the occurrence of noise in the images, and may therefore vary from case to case. Moreover, multi-scale approaches are commonly applied on registration problems and demand for further adjustment of the parameters. In this paper, we present a landmark-based approach for automatic parameter optimization in non-linear intensity-based image registration. In a first step, corresponding landmarks are automatically detected in the images to match. The landmark-based target registration error (TRE), which is shown to be a valid metric for quantifying registration accuracy, is then used to optimize the parameter choice during the registration process. The approach is evaluated for the registration of lungs based on 22 thoracic 4D CT data sets. Experiments show that the TRE can be reduced on average by 0.07 mm using automatic parameter optimization.
Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei
2016-01-01
Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762
Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei
2016-01-01
Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762
Optimization of Ta_{2}O_{5} 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 Ta_{2}O_{5} 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. PMID:27409310
NASA Astrophysics Data System (ADS)
Chen, Y.; Li, J.; Xu, H.
2016-01-01
Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show
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. PMID:25603158
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. PMID:25603158
NASA Astrophysics Data System (ADS)
Belwanshi, Vinod; Topkar, Anita
2016-05-01
Finite element analysis study has been carried out to optimize the design parameters for bulk micro-machined silicon membranes for piezoresistive pressure sensing applications. The design is targeted for measurement of pressure up to 200 bar for nuclear reactor applications. The mechanical behavior of bulk micro-machined silicon membranes in terms of deflection and stress generation has been simulated. Based on the simulation results, optimization of the membrane design parameters in terms of length, width and thickness has been carried out. Subsequent to optimization of membrane geometrical parameters, the dimensions and location of the high stress concentration region for implantation of piezoresistors have been obtained for sensing of pressure using piezoresistive sensing technique.
Li, Pengsong; Huang, Jinyang; Luo, Liang; Kuang, Yun; Sun, Xiaoming
2016-09-01
Density gradient ultracentrifugation (DGUC) has recently emerged as an effective nanoseparation method to sort polydispersed colloidal NPs mainly according to their size differences to reach monodispersed fractions (NPs), but its separation modeling is still lack and the separation parameters' optimization mainly based on experience of operators. In this paper, we gave mathematical descriptions on the DGUC separation, which suggested the best separation parameters for a given system. The separation parameters, including media density, centrifuge speed and time, which affected the separation efficiency, were discussed in details. Further mathematical optimization model was established to calculate and yield the "best" (optimized) linear gradient for a colloidal system with given size and density. The practical experiment results matched well with theoretical prediction, demonstrating the DGUC method, an efficient, practical, and predictable separation technique with universal utilization for colloid sorting. PMID:27457445
Plasma parameters of pulsed-dc discharges in methane used to deposit diamondlike carbon films
NASA Astrophysics Data System (ADS)
Corbella, C.; Rubio-Roy, M.; Bertran, E.; Andújar, J. L.
2009-08-01
Here we approximate the plasma kinetics responsible for diamondlike carbon (DLC) depositions that result from pulsed-dc discharges. The DLC films were deposited at room temperature by plasma-enhanced chemical vapor deposition (PECVD) in a methane (CH4) atmosphere at 10 Pa. We compared the plasma characteristics of asymmetric bipolar pulsed-dc discharges at 100 kHz to those produced by a radio frequency (rf) source. The electrical discharges were monitored by a computer-controlled Langmuir probe operating in time-resolved mode. The acquisition system provided the intensity-voltage (I-V) characteristics with a time resolution of 1 μs. This facilitated the discussion of the variation in plasma parameters within a pulse cycle as a function of the pulse waveform and the peak voltage. The electron distribution was clearly divided into high- and low-energy Maxwellian populations of electrons (a bi-Maxwellian population) at the beginning of the negative voltage region of the pulse. We ascribe this to intense stochastic heating due to the rapid advancing of the sheath edge. The hot population had an electron temperature Tehot of over 10 eV and an initial low density nehot which decreased to zero. Cold electrons of temperature Tecold˜1 eV represented the majority of each discharge. The density of cold electrons necold showed a monotonic increase over time within the negative pulse, peaking at almost 7×1010 cm-3, corresponding to the cooling of the hot electrons. The plasma potential Vp of ˜30 V underwent a smooth increase during the pulse and fell at the end of the negative region. Different rates of CH4 conversion were calculated from the DLC deposition rate. These were explained in terms of the specific activation energy Ea and the conversion factor xdep associated with the plasma processes. The work deepens our understanding of the advantages of using pulsed power supplies for the PECVD of hard metallic and protective coatings for industrial applications (optics
NASA Astrophysics Data System (ADS)
Huang, Zhipeng; Gao, Lihong; Wang, Yangwei; Wang, Fuchi
2016-06-01
The Johnson-Cook (J-C) constitutive model is widely used in the finite element simulation, as this model shows the relationship between stress and strain in a simple way. In this paper, a cluster global optimization algorithm is proposed to determine the J-C constitutive model parameters of materials. A set of assumed parameters is used for the accuracy verification of the procedure. The parameters of two materials (401 steel and 823 steel) are determined. Results show that the procedure is reliable and effective. The relative error between the optimized and assumed parameters is no more than 4.02%, and the relative error between the optimized and assumed stress is 0.2% × 10-5. The J-C constitutive parameters can be determined more precisely and quickly than the traditional manual procedure. Furthermore, all the parameters can be simultaneously determined using several curves under different experimental conditions. A strategy is also proposed to accurately determine the constitutive parameters.
Zarepisheh, Masoud; Uribe-Sanchez, Andres F.; Li, Nan; Jia, Xun; Jiang, Steve B.
2014-04-15
Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for a set of the objective functions associated to the organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the impact of using different objective functions on plan qualities and Pareto surfaces. The main discoveries are threefold: (1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly
Optimization of the parameters of a virtual-cathode oscillator with an inhomogeneous magnetic field
NASA Astrophysics Data System (ADS)
Kurkin, S. A.; Koronovskii, A. A.; Khramov, A. E.; Kuraev, A. A.; Kolosov, S. V.
2013-10-01
A two-dimensional numerical model is used to study the generation of powerful microwave radiation in a vircator with an inhomogeneous magnetic field applied to focus a beam. The characteristics of the external inhomogeneous magnetic field are found to strongly affect the vircator generation characteristics. Mathematical optimization is used to search for the optimum parameters of the magnetic periodic focusing system of the oscillator in order to achieve the maximum power of the output microwave radiation. The dependences of the output vircator power on the characteristics of the external inhomogeneous magnetic field are studied near the optimum control parameters. The physical processes that occur in optimized virtual cathode oscillators are investigated.
NASA Technical Reports Server (NTRS)
Brown, Aaron J.
2011-01-01
Orbit maintenance is the series of burns performed during a mission to ensure the orbit satisfies mission constraints. Low-altitude missions often require non-trivial orbit maintenance Delta V due to sizable orbital perturbations and minimum altitude thresholds. A strategy is presented for minimizing this Delta V using impulsive burn parameter optimization. An initial estimate for the burn parameters is generated by considering a feasible solution to the orbit maintenance problem. An low-lunar orbit example demonstrates the Delta V savings from the feasible solution to the optimal solution. The strategy s extensibility to more complex missions is discussed, as well as the limitations of its use.
CH4 parameter estimation in CLM4.5bgc using surrogate global optimization
NASA Astrophysics Data System (ADS)
Müller, J.; Paudel, R.; Shoemaker, C. A.; Woodbury, J.; Wang, Y.; Mahowald, N.
2015-01-01
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 tropics.
Factorization and the synthesis of optimal feedback gains for distributed parameter systems
NASA Technical Reports Server (NTRS)
Milman, Mark H.; Scheid, Robert E.
1990-01-01
An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.
Optimization of 15 parameters influencing the long-term survival of bacteria in aquatic systems
NASA Technical Reports Server (NTRS)
Obenhuber, D. C.
1993-01-01
NASA is presently engaged in the design and development of a water reclamation system for the future space station. A major concern in processing water is the control of microbial contamination. As a means of developing an optimal microbial control strategy, studies were undertaken to determine the type and amount of contamination which could be expected in these systems under a variety of changing environmental conditions. A laboratory-based Taguchi optimization experiment was conducted to determine the ideal settings for 15 parameters which influence the survival of six bacterial species in aquatic systems. The experiment demonstrated that the bacterial survival period could be decreased significantly by optimizing environmental conditions.
Stability of the genetic code and optimal parameters of amino acids.
Chechetkin, V R; Lobzin, V V
2011-01-21
The standard genetic code is known to be much more efficient in minimizing adverse effects of misreading errors and one-point mutations in comparison with a random code having the same structure, i.e. the same number of codons coding for each particular amino acid. We study the inverse problem, how the code structure affects the optimal physico-chemical parameters of amino acids ensuring the highest stability of the genetic code. It is shown that the choice of two or more amino acids with given properties determines unambiguously all the others. In this sense the code structure determines strictly the optimal parameters of amino acids or the corresponding scales may be derived directly from the genetic code. In the code with the structure of the standard genetic code the resulting values for hydrophobicity obtained in the scheme "leave one out" and in the scheme with fixed maximum and minimum parameters correlate significantly with the natural scale. The comparison of the optimal and natural parameters allows assessing relative impact of physico-chemical and error-minimization factors during evolution of the genetic code. As the resulting optimal scale depends on the choice of amino acids with given parameters, the technique can also be applied to testing various scenarios of the code evolution with increasing number of codified amino acids. Our results indicate the co-evolution of the genetic code and physico-chemical properties of recruited amino acids. PMID:20955716
NASA Astrophysics Data System (ADS)
Agarwal, Reema; Köhl, Armin; Stammer, Detlef
2013-04-01
We present an application of a multivariate parameter optimization technique to a global primitive equation Atmospheric GCM. The technique is based upon the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm, in which gradients of the objective function are approximated. This technique has some advantages over other optimization procedures (such as Green's function or the Adjoint methods) like robustness to noise in the objective function and ability to find the actual minimum in case of multiple minima. Another useful feature of the technique is its simplicity and cost effectiveness. The atmospheric GCM used is the coarse resolution PLAnet SIMulator (PLASIM). In order to identify the parameters to be used in the optimization procedure, a series of sensitivity experiments with 12 different parameters was performed and subsequently 5 parameters related to cloud radiation parameterization to which the GCM was highly sensitive were finally selected. The optimization technique is applied and the selected parameters were simultaneously tuned and tested for a period of 1-year GCM integrations. The performance of the technique is judged by the behavior of model's cost function, which includes temperature, precipitation, humidity and flux contributions. The method is found to be useful for reducing the model's cost function against both identical twin data as well as ECMWF ERA-40 reanalysis data.
Parameter identification of a distributed runoff model by the optimization software Colleo
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
Ashassi-Sorkhabi, H.; Dolati, H.; Parvini-Ahmadi, N.; Manzoori, J.
2002-01-01
Cupronickel alloys are known for their excellent corrosion resistance, especially in marine atmosphere. The development of an appropriate electroless bath involves the use of a reducing agent, complexing and stabilizing compounds and metallic salts. In this work, autocatalytic deposition of Ni-Cu-P alloys (28-95 wt.% Ni, 66-0 wt.% Cu, 7.5-3 wt.% P) has been carried out on 302 b steel sheets from bath containing: NiCl 2·6H 2O, CuCl 2·2H 2O, NaH 2PO 2, Na citrate, sulphosalicilic acid and triethanolamine. The effects of pH, temperature, and bath composition on the hardness and the composition of deposits have been studied. In addition, the deposition rates of alloy, nickel, copper and phosphorus were investigated and optimum conditions were obtained. The average rate of alloy deposition was 9 mg cm -2 h -1 and the optimum pH and temperature were 8.5 and 80 °C, respectively. The chemical stability of bath was desirable, and no spontaneous decomposition occurred. The changes in the structure of deposit by heat treatment were studied by the X-ray diffraction (XRD) method. The XRD patterns indicate that the copper content affects the structure changes. With increasing copper content, the phosphorus content decreased and the crystallinity of the deposits grew. After heat treatment of alloys with lower copper content at 400 °C for 1 h, the crystallization to Ni 3P was observed.
Optimal Estimation of Phenological Crop Model Parameters for Rice (Oryza sativa)
NASA Astrophysics Data System (ADS)
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 < 2.2). Both optimization approaches in both models resulted in only small 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.
NASA Technical Reports Server (NTRS)
Rizk, Magdi H.
1988-01-01
A scheme is developed for solving constrained optimization problems in which the objective function and the constraint function are dependent on the solution of the nonlinear flow equations. The scheme updates the design parameter iterative solutions and the flow variable iterative solutions simultaneously. It is applied to an advanced propeller design problem with the Euler equations used as the flow governing equations. The scheme's accuracy, efficiency and sensitivity to the computational parameters are tested.
NASA Technical Reports Server (NTRS)
Rizk, Magdi H.
1988-01-01
A scheme is developed for solving constrained optimization problems in which the objective function and the constraint function are dependent on the solution of the nonlinear flow equations. The scheme updates the design parameter iterative solutions and the flow variable iterative solutions simultaneously. It is applied to an advanced propeller design problem with the Euler equations used as the flow governing equations. The scheme's accuracy, efficiency and sensitivity to the computational parameters are tested.
A novel optimization method of camera parameters used for vision measurement
NASA Astrophysics Data System (ADS)
Zhou, Fuqiang; Cui, Yi; Peng, Bin; Wang, Yexin
2012-09-01
Camera calibration plays an important role in the field of machine vision applications. During the process of camera calibration, nonlinear optimization technique is crucial to obtain the best performance of camera parameters. Currently, the existing optimization method aims at minimizing the distance error between the detected image point and the calculated back-projected image point, based on 2D image pixels coordinate. However, the vision measurement process is conducted in 3D space while the optimization method generally adopted is carried out in 2D image plane. Moreover, the error criterion with respect to optimization and measurement is different. In other words, the equal pixel distance error in 2D image plane leads to diverse 3D metric distance error at different position before the camera. All the reasons mentioned above will cause accuracy decrease for 3D vision measurement. To solve the problem, a novel optimization method of camera parameters used for vision measurement is proposed. The presented method is devoted to minimizing the metric distance error between the calculated point and the real point in 3D measurement coordinate system. Comparatively, the initial camera parameters acquired through linear calibration are optimized through two different methods: one is the conventional method and the other is the novel method presented by this paper. Also, the calibration accuracy and measurement accuracy of the parameters obtained by the two methods are thoroughly analyzed and the choice of a suitable accuracy evaluation method is discussed. Simulative and real experiments to estimate the performance of the proposed method on test data are reported, and the results show that the proposed 3D optimization method is quite efficient to improve measurement accuracy compared with traditional method. It can meet the practical requirement of high precision in 3D vision metrology engineering.
Optimization of deposition rate in HiPIMS by controlling the peak target current
NASA Astrophysics Data System (ADS)
Tiron, V.; Velicu, I.-L.; Vasilovici, O.; Popa, G.
2015-12-01
High power impulse magnetron sputtering (HiPIMS) is a very attractive ionized physical vapour deposition technique which has been of great interest over the last decade. Thanks to the high ionization degree of the sputtered material (typically >50%), this technique is used mainly for enhancing and tailoring coating properties. However, the lower deposition rate compared to the conventional direct-current (dc) magnetron sputtering process still represents a major drawback of HiPIMS. In this contribution, a study of the ability to control the peak target current in HiPIMS discharge through certain experimental parameters and, thus, to overcome the deposition rate limitation is presented. The HiPIMS was operated with ultra-short pulse durations (<20 μs) and two different operation modes have been used: single-pulse mode and multi-pulse mode, respectively. The peak target current was controlled by changing the target voltage, pulse duration, magnetic field, and target erosion depth. For a certain favorable combination of experimental parameters, it was found that the deposition rate value can be increased by a factor of up to 3.5, reaching values only 20% lower than those found in dc.
NASA Astrophysics Data System (ADS)
Chiu, Yung-Chia
2014-12-01
Parameter structure identification is formulated in terms of solving an inverse problem, which allows for a determination of an appropriate level of parameter structure complexity, and the identification of its pattern and the associated parameter values. With the increasing complexity of parameter structure identification in groundwater modeling, demand for robust, fast, and accurate optimizers is on the rise among researchers from groundwater hydrology fields. A novel global optimizer, differential evolution (DE), has been proposed to solve the parameter-structure-identification problem. The Voronoi tessellation is adopted for the automatic parameterization. The stepwise regression method and the error covariance matrix are used to determine the optimal structure complexity. Numerical experiments with a continuous hydraulic conductivity distribution are conducted to demonstrate the proposed methodology. The results indicate that the DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters and mutation schemes implemented in the DE is employed to examine their influence on the objective function. The comparison between DE and genetic algorithm shows the advantage of DE in terms of robustness and efficiency. The proposed methodology is also applied to a real groundwater system, Pingtung Plain in Taiwan, and the properties of aquifers are successfully identified.
NASA Astrophysics Data System (ADS)
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.
Generation of pareto optimal ensembles of calibrated parameter sets for climate models.
Dalbey, Keith R.; Levy, Michael Nathan
2010-12-01
Climate models have a large number of inputs and outputs. In addition, diverse parameters sets can match observations similarly well. These factors make calibrating the models difficult. But as the Earth enters a new climate regime, parameters sets may cease to match observations. History matching is necessary but not sufficient for good predictions. We seek a 'Pareto optimal' ensemble of calibrated parameter sets for the CCSM climate model, in which no individual criteria can be improved without worsening another. One Multi Objective Genetic Algorithm (MOGA) optimization typically requires thousands of simulations but produces an ensemble of Pareto optimal solutions. Our simulation budget of 500-1000 runs allows us to perform the MOGA optimization once, but with far fewer evaluations than normal. We devised an analytic test problem to aid in the selection MOGA settings. The test problem's Pareto set is the surface of a 6 dimensional hypersphere with radius 1 centered at the origin, or rather the portion of it in the [0,1] octant. We also explore starting MOGA from a space-filling Latin Hypercube sample design, specifically Binning Optimal Symmetric Latin Hypercube Sampling (BOSLHS), instead of Monte Carlo (MC). We compare the Pareto sets based on: their number of points, N, larger is better; their RMS distance, d, to the ensemble's center, 0.5553 is optimal; their average radius, {mu}(r), 1 is optimal; their radius standard deviation, {sigma}(r), 0 is optimal. The estimated distributions for these metrics when starting from MC and BOSLHS are shown in Figs. 1 and 2.
NASA Astrophysics Data System (ADS)
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
Lambrakos, S.G.; Milewski, J.O.
1998-12-01
An analysis of weld morphology which typically occurs in deep penetration welding processes using electron or laser beams is presented. The method of analysis is based on geometric constraints with formal mathematical foundation within the theory of constrained parameter optimization. The analysis presented in this report serves as an example of the application of the geometric-constraints method to the analysis of weld fusion boundary morphology where there can be fragmented and incomplete information concerning material properties and only approximate information concerning the character of energy deposition, thus making a direct first principals approach difficult. A significant aspect of the geometric-constraints method is that it permits the implicit representation of information concerning temperature dependence of material properties and of coupling between heat transfer and fluid convection occurring in the weld meltpool.
NASA Astrophysics Data System (ADS)
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
2015-04-01
A multi-scale parameter-estimation method, as presented by Samaniego et al. (2010), is implemented and extended for the conceptual hydrological model COSERO. COSERO is a HBV-type model that is specialized for alpine-environments, but has been applied over a wide range of basins all over the world (see: Kling et al., 2014 for an overview). Within the methodology available small-scale information (DEM, soil texture, land cover, etc.) is used to estimate the coarse-scale model parameters by applying a set of transfer-functions (TFs) and subsequent averaging methods, whereby only TF hyper-parameters are optimized against available observations (e.g. runoff data). The parameter regionalisation approach was extended in order to allow for a more meta-heuristical handling of the transfer-functions. The two main novelties are: 1. An explicit introduction of constrains into parameter estimation scheme: The constraint scheme replaces invalid parts of the transfer-function-solution space with valid solutions. It is inspired by applications in evolutionary algorithms and related to the combination of learning and evolution. This allows the consideration of physical and numerical constraints as well as the incorporation of a priori modeller-experience into the parameter estimation. 2. Spline-based transfer-functions: Spline-based functions enable arbitrary forms of transfer-functions: This is of importance since in many cases the general relationship between sub-grid information and parameters are known, but not the form of the transfer-function itself. The contribution presents the results and experiences with the adopted method and the introduced extensions. Simulation are performed for the pre-alpine/alpine Traisen catchment in Lower Austria. References: Samaniego, L., Kumar, R., Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., doi: 10.1029/2008WR007327 Kling, H., Stanzel, P., Fuchs, M., and
Heidari, M.; Ranjithan, S.R.
1998-01-01
In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is
Optimization of injection molding parameters for poly(styrene-isobutylene-styrene) block copolymer
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Hutter, Frank; Bartz-Beielstein, Thomas; Hoos, Holger H.; Leyton-Brown, Kevin; Murphy, Kevin P.
This work experimentally investigates model-based approaches for optimizing the performance of parameterized randomized algorithms. Such approaches build a response surface model and use this model for finding good parameter settings of the given algorithm. We evaluated two methods from the literature that are based on Gaussian process models: sequential parameter optimization (SPO) (Bartz-Beielstein et al. 2005) and sequential Kriging optimization (SKO) (Huang et al. 2006). SPO performed better "out-of-the-box," whereas SKO was competitive when response values were log transformed. We then investigated key design decisions within the SPO paradigm, characterizing the performance consequences of each. Based on these findings, we propose a new version of SPO, dubbed SPO+, which extends SPO with a novel intensification procedure and a log-transformed objective function. In a domain for which performance results for other (modelfree) parameter optimization approaches are available, we demonstrate that SPO+ achieves state-of-the-art performance. Finally, we compare this automated parameter tuning approach to an interactive, manual process that makes use of classical
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Gao, P.; Shetty, S.; Momm, H. G.
2014-11-01
Evolutionary computation is used for improved information extraction from high-resolution satellite imagery. The utilization of evolutionary computation is based on stochastic selection of input parameters often defined in a trial-and-error approach. However, exploration of optimal input parameters can yield improved candidate solutions while requiring reduced computation resources. In this study, the design and implementation of a system that investigates the optimal input parameters was researched in the problem of feature extraction from remotely sensed imagery. The two primary assessment criteria were the highest fitness value and the overall computational time. The parameters explored include the population size and the percentage and order of mutation and crossover. The proposed system has two major subsystems; (i) data preparation: the generation of random candidate solutions; and (ii) data processing: evolutionary process based on genetic programming, which is used to spectrally distinguish the features of interest from the remaining image background of remote sensed imagery. The results demonstrate that the optimal generation number is around 1500, the optimal percentage of mutation and crossover ranges from 35% to 40% and 5% to 0%, respectively. Based on our findings the sequence that yielded better results was mutation over crossover. These findings are conducive to improving the efficacy of utilizing genetic programming for feature extraction from remotely sensed imagery.
Properties of sputtered TiO2 thin films as a function of deposition and annealing parameters
NASA Astrophysics Data System (ADS)
Pjević, Dejan; Obradović, Marko; Marinković, Tijana; Grce, Ana; Milosavljević, Momir; Grieseler, Rolf; Kups, Thomas; Wilke, Marcus; Schaaf, Peter
2015-04-01
The influence of sputtering parameters and annealing on the structure and optical properties of TiO2 thin films deposited by RF magnetron sputtering is reported. A pure TiO2 target was used to deposit the films on Si(100) and glass substrates, and Ar/O2 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/O2 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 O2. 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 O2 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 TiO2 thin films with defined structure and properties.
Automated optimization of water-water interaction parameters for a coarse-grained model.
Fogarty, Joseph C; Chiu, See-Wing; Kirby, Peter; Jakobsson, Eric; Pandit, Sagar A
2014-02-13
We have developed an automated parameter optimization software framework (ParOpt) that implements the Nelder-Mead simplex algorithm and applied it to a coarse-grained polarizable water model. The model employs a tabulated, modified Morse potential with decoupled short- and long-range interactions incorporating four water molecules per interaction site. Polarizability is introduced by the addition of a harmonic angle term defined among three charged points within each bead. The target function for parameter optimization was based on the experimental density, surface tension, electric field permittivity, and diffusion coefficient. The model was validated by comparison of statistical quantities with experimental observation. We found very good performance of the optimization procedure and good agreement of the model with experiment. PMID:24460506
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. PMID:27570139
Automated Optimization of Water–Water Interaction Parameters for a Coarse-Grained Model
2015-01-01
We have developed an automated parameter optimization software framework (ParOpt) that implements the Nelder–Mead simplex algorithm and applied it to a coarse-grained polarizable water model. The model employs a tabulated, modified Morse potential with decoupled short- and long-range interactions incorporating four water molecules per interaction site. Polarizability is introduced by the addition of a harmonic angle term defined among three charged points within each bead. The target function for parameter optimization was based on the experimental density, surface tension, electric field permittivity, and diffusion coefficient. The model was validated by comparison of statistical quantities with experimental observation. We found very good performance of the optimization procedure and good agreement of the model with experiment. PMID:24460506
NASA Astrophysics Data System (ADS)
Xu, Dexiang
This dissertation presents a novel method of designing finite word length Finite Impulse Response (FIR) digital filters using a Real Parameter Parallel Genetic Algorithm (RPPGA). This algorithm is derived from basic Genetic Algorithms which are inspired by natural genetics principles. Both experimental results and theoretical studies in this work reveal that the RPPGA is a suitable method for determining the optimal or near optimal discrete coefficients of finite word length FIR digital filters. Performance of RPPGA is evaluated by comparing specifications of filters designed by other methods with filters designed by RPPGA. The parallel and spatial structures of the algorithm result in faster and more robust optimization than basic genetic algorithms. A filter designed by RPPGA is implemented in hardware to attenuate high frequency noise in a data acquisition system for collecting seismic signals. These studies may lead to more applications of the Real Parameter Parallel Genetic Algorithms in Electrical Engineering.
Improving flash flood forecasting with distributed hydrological model by parameter optimization
NASA Astrophysics Data System (ADS)
Chen, Yangbo
2016-04-01
In China, flash food is usually regarded as flood occured in small and medium sized watersheds with drainage area less than 200 km2, and is mainly induced by heavy rains, and occurs in where hydrological observation is lacked. Flash flood is widely observed in China, and is the flood causing the most casualties nowadays in China. Due to hydrological data scarcity, lumped hydrological model is difficult to be employed for flash flood forecasting which requires lots of observed hydrological data to calibrate model parameters. Physically based distributed hydrological model discrete the terrain of the whole watershed into a number of grid cells at fine resolution, assimilate different terrain data and precipitation to different cells, and derive model parameteris from the terrain properties, thus having the potential to be used in flash flood forecasting and improving flash flood prediction capability. In this study, the Liuxihe Model, a physically based distributed hydrological model mainly proposed for watershed flood forecasting is employed to simulate flash floods in the Ganzhou area in southeast China, and models have been set up in 5 watersheds. Model parameters have been derived from the terrain properties including the DEM, the soil type and land use type, but the result shows that the flood simulation uncertainty is high, which may be caused by parameter uncertainty, and some kind of uncertainty control is needed before the model could be used in real-time flash flood forecastin. Considering currently many Chinese small and medium sized watersheds has set up hydrological observation network, and a few flood events could be collected, it may be used for model parameter optimization. For this reason, an automatic model parameter optimization algorithm using Particle Swam Optimization(PSO) is developed to optimize the model parameters, and it has been found that model parameters optimized even only with one observed flood events could largely reduce the flood
NASA Technical Reports Server (NTRS)
Starlinger, Alois; Duffy, Stephen F.; Palko, Joseph L.
1993-01-01
New methods are presented that utilize the optimization of goodness-of-fit statistics in order to estimate Weibull parameters from failure data. It is assumed that the underlying population is characterized by a three-parameter Weibull distribution. Goodness-of-fit tests are based on the empirical distribution function (EDF). The EDF is a step function, calculated using failure data, and represents an approximation of the cumulative distribution function for the underlying population. Statistics (such as the Kolmogorov-Smirnov statistic and the Anderson-Darling statistic) measure the discrepancy between the EDF and the cumulative distribution function (CDF). These statistics are minimized with respect to the three Weibull parameters. Due to nonlinearities encountered in the minimization process, Powell's numerical optimization procedure is applied to obtain the optimum value of the EDF. Numerical examples show the applicability of these new estimation methods. The results are compared to the estimates obtained with Cooper's nonlinear regression algorithm.
Parameter optimization of nanosecond laser for microdrilling on PVC by Taguchi method
NASA Astrophysics Data System (ADS)
Canel, Timur; Kaya, A. Uğur; Çelik, Bekir
2012-11-01
Formation of cavities having maximum aspect ratio (depth-to-width (D/W) ratio) on PVC during laser drilling has several undesirable outcomes with regard to cavity quality. Hence it is essential to select optimum drilling process parameters to maximize aspect ratio and minimize Heat Affected Zone (HAZ) and circularity. This paper presents application of the Taguchi optimization method to obtain cavities possessing maximum aspect ratio influenced by drilling conditions such as wavelength, fluence and frequency. In the present work, the effects of laser processing parameters, including laser fluence, laser frequency and wavelength were investigated in relation to the aspect ratio, HAZ and circularity. Then the optimal values of wavelength, fluence and frequency were determined. According to the result of the confirmation experiment using optimum parameters, it was observed that experimental results were compatible with Taguchi method with 93% rate. The details of experimentation analysis and analysis of variance are presented in this paper.
Big Bang-Big Crunch optimization for parameter estimation in structural systems
NASA Astrophysics Data System (ADS)
Tang, Hesheng; Zhou, Jin; Xue, Songtao; Xie, Liyu
2010-11-01
A new approach to parameter estimation of structural systems using the recently developed Big Bang-Big Crunch (BB-BC) optimization is proposed, in which the parameter estimation is formulated as a multi-modal optimization problem with high dimension. The BB-BC method is inspired by one of the theories of the evolution of universe. The potentialities of BB-BC are its inherent numerical simplicity, high convergence speed, and easy implementation. The performances of the proposed method are investigated with simulation results for identifying the parameters of structural systems under conditions including limited output data, noise-polluted signals, and no priori knowledge of mass, damping, or stiffness. It is observed that BB-BC gives comparatively better results than existing methods. Moreover the method is computationally simpler.
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. PMID:26880874
Theoretic aspects of the identification of the parameters in the optimal control model
NASA Technical Reports Server (NTRS)
Vanwijk, R. A.; Kok, J. J.
1977-01-01
The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.
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. PMID:26880874
NASA Astrophysics Data System (ADS)
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.
NASA Technical Reports Server (NTRS)
Stahara, S. S.
1984-01-01
An investigation was carried out to complete the preliminary development of a combined perturbation/optimization procedure and associated computational code for designing optimized blade-to-blade profiles of turbomachinery blades. The overall purpose of the procedures developed is to provide demonstration of a rapid nonlinear perturbation method for minimizing the computational requirements associated with parametric design studies of turbomachinery flows. The method combines the multiple parameter nonlinear perturbation method, successfully developed in previous phases of this study, with the NASA TSONIC blade-to-blade turbomachinery flow solver, and the COPES-CONMIN optimization procedure into a user's code for designing optimized blade-to-blade surface profiles of turbomachinery blades. Results of several design applications and a documented version of the code together with a user's manual are provided.
An improved swarm optimization for parameter estimation and biological model selection.
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This
An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
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.
Modeling Network Intrusion Detection System Using Feature Selection and Parameters Optimization
NASA Astrophysics Data System (ADS)
Kim, Dong Seong; Park, Jong Sou
Previous approaches for modeling Intrusion Detection System (IDS) have been on twofold: improving detection model(s) in terms of (i) feature selection of audit data through wrapper and filter methods and (ii) parameters optimization of detection model design, based on classification, clustering algorithms, etc. In this paper, we present three approaches to model IDS in the context of feature selection and parameters optimization: First, we present Fusion of Genetic Algorithm (GA) and Support Vector Machines (SVM) (FuGAS), which employs combinations of GA and SVM through genetic operation and it is capable of building an optimal detection model with only selected important features and optimal parameters value. Second, we present Correlation-based Hybrid Feature Selection (CoHyFS), which utilizes a filter method in conjunction of GA for feature selection in order to reduce long training time. Third, we present Simultaneous Intrinsic Model Identification (SIMI), which adopts Random Forest (RF) and shows better intrusion detection rates and feature selection results, along with no additional computational overheads. We show the experimental results and analysis of three approaches on KDD 1999 intrusion detection datasets.
NASA Astrophysics Data System (ADS)
Mohanty, Sankhya; Hattel, Jesper H.
2015-03-01
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 method based uncertainty and reliability analysis. The reliability of the scanning paths are established using cumulative probability distribution functions for process output criteria such as sample density, thermal homogeneity, etc. A customized genetic algorithm is used along with the simulation model 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.
NASA Technical Reports Server (NTRS)
Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian
1992-01-01
A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.
NASA Astrophysics Data System (ADS)
Rahman, Md Ashiqur; Anwar, Sohel; Izadian, Afshin
2016-03-01
In this paper, a gradient-free optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized to identify specific parameters of the electrochemical model of a Lithium-Ion battery with LiCoO2 cathode chemistry. Battery electrochemical model parameters are subject to change under severe or abusive operating conditions resulting in, for example, over-discharged battery, over-charged battery, etc. It is important for a battery management system to have these parameter changes fully captured in a bank of battery models that can be used to monitor battery conditions in real time. Here the PSO methodology has been successfully applied to identify four electrochemical model parameters that exhibit significant variations under severe operating conditions: solid phase diffusion coefficient at the positive electrode (cathode), solid phase diffusion coefficient at the negative electrode (anode), intercalation/de-intercalation reaction rate at the cathode, and intercalation/de-intercalation reaction rate at the anode. The identified model parameters were used to generate the respective battery models for both healthy and degraded batteries. These models were then validated by comparing the model output voltage with the experimental output voltage for the stated operating conditions. The identified Li-Ion battery electrochemical model parameters are within reasonable accuracy as evidenced by the experimental validation results.
2011-01-01
Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These
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. PMID:21905841
NASA Astrophysics Data System (ADS)
Weber, Christian-Toralf; Gabbert, Ulrich; Enzmann, Marc R.
1998-07-01
The design of adaptive mechanical structures is divided into three parts: the structural design, the controller design and the placement of actuators and sensors. The objective of the design is to create a mechanical structure, which corresponds with the physical and technical requirements. The controller design includes the definition of the optimal controller law and the parameters required to create an actuator adjustment from the perceptible signals of the structural answer. The placement of the actuators and of the sensors give an answer to the question about the optimal distribution of the actuators and sensors in the structure. The sensor placement determines which signals are available to the automatic controller. The position of the actuators in the mechanical structure determines at which points control forces may act to influence the structural behavior in a suitable manner. The determination of the optimal position of the actuators require information about the controller design, the sensor position and the layout and the behavior of the structure. Based on the ideas of the shape optimization and topology optimization, a procedure will be presented, to handle simultaneously the discrete positions of the actuators and the continuous parameters of the controller. The method is based on an augmented Lagrangian function to include additional conditions and the discontinuity of the discrete variables into the objective function. The method will be demonstrated by an test example.
Deka, Deepmoni; Das, Saprativ P.; Sahoo, Naresh; Das, Debasish; Jawed, Mohammad; Goyal, Dinesh
2013-01-01
Effect of physical parameters such as initial pH, agitation (rpm), and temperature (°C) for cellulase production from Bacillus subtilis AS3 was investigated. Central composite design of experiments followed by multiple desirability function was applied for the optimization of cellulase activity and cell growth. The effect of the temperature and agitation was found to be significant among the three independent variables. The optimum levels of initial pH, temperature, and agitation for alkaline carboxymethylcellulase (CMCase) production predicted by the model were 7.2, 39°C, and 121 rpm, respectively. The CMCase activity with unoptimized physical parameters and previously optimized medium composition was 0.43 U/mL. The maximum activity (0.56 U/mL) and cell growth (2.01 mg/mL) predicted by the model were in consensus with values (0.57 U/mL, 2.1 mg/mL) obtained using optimized medium and optimal values of physical parameters. After optimization, 33% enhancement in CMCase activity (0.57 U/mL) was recorded. On scale-up of cellulase production process in bioreactor with all the optimized conditions, an activity of 0.75 U/mL was achieved. Consequently, the bacterial cellulase employed for bioethanol production expending (5%, w/v) NaOH-pretreated wild grass with Zymomonas mobilis yielded an utmost ethanol titre of 7.56 g/L and 11.65 g/L at shake flask and bioreactor level, respectively. PMID:25937985
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Chrzanowski, J.; Meng-Burany, S.; Xing, W. B.; Curzon, A. E.; Heinrich, B.; Irwin, J. C.; Cragg, R. A.; Zhou, H.; Habib, F.; Angus, V.
1995-04-01
Two series of Y1Ba2Cu3O(z) thin films deposited on (001) LaAl03 single crystals by excimer laser ablation under two different protocols have been investigated. The research has yielded well defined deposition conditions in terms of oxygen partial pressure p(O2) and substrate temperature of the deposition process Th, for the growth of high quality epitaxial films of YBCO. The films grown under conditions close to optimal for both j(sub c) and T(sub c) exhibited T(sub c) greater than or equal to 91 K and j(sub c) greater than or equal to 4 x 106 A/sq cm, at 77 K. Close correlations between the structural quality of the film, the growth parameters (p(O2), T(sub h)) and j(sub c) and T(sub c) have been found.
NASA Technical Reports Server (NTRS)
Chrzanowski, J.; Meng-Burany, S.; Xing, W. B.; Curzon, A. E.; Heinrich, B.; Irwin, J. C.; Cragg, R. A.; Zhou, H.; Habib, F.; Angus, V.
1995-01-01
Two series of Y1Ba2Cu3O(z) thin films deposited on (001) LaAl03 single crystals by excimer laser ablation under two different protocols have been investigated. The research has yielded well defined deposition conditions in terms of oxygen partial pressure p(O2) and substrate temperature of the deposition process Th, for the growth of high quality epitaxial films of YBCO. The films grown under conditions close to optimal for both j(sub c) and T(sub c) exhibited T(sub c) greater than or equal to 91 K and j(sub c) greater than or equal to 4 x 106 A/sq cm, at 77 K. Close correlations between the structural quality of the film, the growth parameters (p(O2), T(sub h)) and j(sub c) and T(sub c) have been found.
Effect of experimental parameters on optimal reflection of light from opaque media
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Cardiff, M. A.; Kitanidis, P. K.
2005-12-01
In this presentation we revisit the problem of semivariogram estimation and present a modular, reusable, and encapsulated set of MATLAB programs that use a hybrid Ant Colony Optimization (ACO) heuristic to solve the "optimal fit" problem. Though the ACO heuristic involves a stochastic component, advantages of the heuristic over traditional gradient-search methods, like the Gauss-Newton method, include the ability to estimate model semivariogram parameters accurately without initial guesses input by the user. The ACO heuristic is also superiorly suited for strongly nonlinear optimization over spaces that may contain several local minima. The presentation will focus on the application of ACO to existing weighted least squares and restricted maximum likelihood estimation methods with a comparison of results. The presentation will also discuss parameter uncertainty, particularly in the context of restricted maximum likelihood and Bayesian methods. We compare the local linearized parameter estimates (or Cramer-Rao lower bounds) with modern Monte Carlo methods, such as acceptance-rejection. Finally, we present ensemble kriging in which conditional realizations are generated in a way that uncertainty in semi-variogram parameters is fully accounted for. Results for a variety of sample problems will be presented along with a discussion of solution accuracy and computational efficiency.
Parameter extraction from experimental PEFC data using an evolutionary optimization algorithm
NASA Astrophysics Data System (ADS)
Zaglio, M.; Schuler, G.; Wokaun, A.; Mantzaras, J.; Büchi, F. N.
2011-05-01
The accurate characterization of the parameters related to the charge and water transport in the ionomer membrane of polymer electrolyte fuel cells (PEFC) is highly important for the understanding and interpretation of the overall cell behavior. Despite the big efforts to experimentally determine these parameters, a large scatter of data is reported in the literature, due to the inherent experimental difficulties. Likewise, the porosity and tortuosity of the gas diffusion layers affect the membrane water content and the local cell performance, but the published data are usually measured ex-situ, not accounting for the effect of clamping pressure. Using a quasi two-dimensional model and experimental current density data from a linear cell of technical size, a multiparameter optimization procedure based on an evolutionary algorithm has been applied to determine eight material properties highly influencing the cell performance. The optimization procedure converges towards a well defined solution and the resulting parameter values are compared to those available in the literature. The quality of the set of parameters extracted by the optimization procedure is assessed by a sensitivity analysis.
Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1993-01-01
The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.
An Approach to Optimize Size Parameters of Forging by Combining Hot-Processing Map and FEM
NASA Astrophysics Data System (ADS)
Hu, H. E.; Wang, X. Y.; Deng, L.
2014-11-01
The size parameters of 6061 aluminum alloy rib-web forging were optimized by using hot-processing map and finite element method (FEM) based on high-temperature compression data. The results show that the stress level of the alloy can be represented by a Zener-Holloman parameter in a hyperbolic sine-type equation with the hot deformation activation energy of 343.7 kJ/mol. Dynamic recovery and dynamic recrystallization concurrently preceded during high-temperature deformation of the alloy. Optimal hot-processing parameters for the alloy corresponding to the peak value of 0.42 are 753 K and 0.001 s-1. The instability domain occurs at deformation temperature lower than 653 K. FEM is an available method to validate hot-processing map in actual manufacture by analyzing the effect of corner radius, rib width, and web thickness on workability of rib-web forging of the alloy. Size parameters of die forgings can be optimized conveniently by combining hot-processing map and FEM.
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Optimal input design for aircraft parameter estimation using dynamic programming principles
NASA Technical Reports Server (NTRS)
Klein, Vladislav; Morelli, Eugene A.
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.
Algorithms of D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
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
Sankaran, Sethuraman; Humphrey, Jay D.; Marsden, Alison L.
2013-01-01
Computational models for vascular growth and remodeling (G&R) are used to predict the long-term response of vessels to changes in pressure, flow, and other mechanical loading conditions. Accurate predictions of these responses are essential for understanding numerous disease processes. Such models require reliable inputs of numerous parameters, including material properties and growth rates, which are often experimentally derived, and inherently uncertain. While earlier methods have used a brute force approach, systematic uncertainty quantification in G&R models promises to provide much better information. In this work, we introduce an efficient framework for uncertainty quantification and optimal parameter selection, and illustrate it via several examples. First, an adaptive sparse grid stochastic collocation scheme is implemented in an established G&R solver to quantify parameter sensitivities, and near-linear scaling with the number of parameters is demonstrated. This non-intrusive and parallelizable algorithm is compared with standard sampling algorithms such as Monte-Carlo. Second, we determine optimal arterial wall material properties by applying robust optimization. We couple the G&R simulator with an adaptive sparse grid collocation approach and a derivative-free optimization algorithm. We show that an artery can achieve optimal homeostatic conditions over a range of alterations in pressure and flow; robustness of the solution is enforced by including uncertainty in loading conditions in the objective function. We then show that homeostatic intramural and wall shear stress is maintained for a wide range of material properties, though the time it takes to achieve this state varies. We also show that the intramural stress is robust and lies within 5% of its mean value for realistic variability of the material parameters. We observe that prestretch of elastin and collagen are most critical to maintaining homeostasis, while values of the material properties are
Shah, Kamran; Haq, Izhar Ul; Shah, Shaukat Ali; Khan, Farid Ullah; 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. PMID:24592190
Gholami-Boroujeny, Shiva; Bolic, Miodrag
2016-04-01
Fitting the measured bioimpedance spectroscopy (BIS) data to the Cole model and then extracting the Cole parameters is a common practice in BIS applications. The extracted Cole parameters then can be analysed as descriptors of tissue electrical properties. To have a better evaluation of physiological or pathological properties of biological tissue, accurate extraction of Cole parameters is of great importance. This paper proposes an improved Cole parameter extraction based on bacterial foraging optimization (BFO) algorithm. We employed simulated datasets to test the performance of the BFO fitting method regarding parameter extraction accuracy and noise sensitivity, and we compared the results with those of a least squares (LS) fitting method. The BFO method showed better robustness to the noise and higher accuracy in terms of extracted parameters. In addition, we applied our method to experimental data where bioimpedance measurements were obtained from forearm in three different positions of the arm. The goal of the experiment was to explore how robust Cole parameters are in classifying position of the arm for different people, and measured at different times. The extracted Cole parameters obtained by LS and BFO methods were applied to different classifiers. Two other evolutionary algorithms, GA and PSO were also used for comparison purpose. We showed that when the classifiers are fed with the extracted feature sets by BFO fitting method, higher accuracy is obtained both when applying on training data and test data. PMID:26215520
Hussain, Majid; Renate, Winker-Heil; Werner, Hofmann
2011-01-01
Objective The structure of extrathoracic passages, variability of tracheobronchial (TB) airways and alveolar dimensions and individual variations of breathing pattern exhibit significant intersubject variations, which affect extrathoracic deposition and, in further consequence, the fraction of inhaled particles actually reaching the thoracic region. The present study was conducted to quantify the intersubject variability of lung deposition fractions caused by the fluctuations in these three major sources of intersubject variability. Methods To quantify intersubject variability of extrathoracic, thoracic and total deposition fractions (TDF), different combinations of the three sources of variability were simulated to identify the most important factors. Deposition fractions of inhaled particles were computed by the stochastic airway generation model IDEAL. The dimensions of the respiratory airways were scaled in proportion to age and height of the subject to calculate TDFs. Results The variability of deposition fractions increased with the stepwise addition of influencing factors and the resulting standard deviations ranged up to 30%. While some combinations enhanced the effects of individual factors on deposition by up to 40%, others seemed to compensate each other with only a minor effect on deposition. Conclusion The present study attempts to quantify experimentally observed intersubject variability of regional deposition fractions caused by individual variations of nasal and oral geometry, lung airway dimensions and breathing patterns in healthy lungs, serving as a baseline for subsequent calculations for diseased lungs, e.g. asthma, COPD, and emphysema, which may further increase intersubject variabilities of medically relevant depositions. PMID:22263083
Chang, Liang-Cheng; Chu, Hone-Jay; Lin, Yu-Pin; Chen, Yu-Wen
2010-10-01
This research develops an optimum design model of groundwater network using genetic algorithm (GA) and modified Newton approach, based on the experimental design conception. The goal of experiment design is to minimize parameter uncertainty, represented by the covariance matrix determinant of estimated parameters. The design problem is constrained by a specified cost and solved by GA and a parameter identification model. The latter estimates optimum parameter value and its associated sensitivity matrices. The general problem is simplified into two classes of network design problems: an observation network design problem and a pumping network design problem. Results explore the relationship between the experimental design and the physical processes. The proposed model provides an alternative to solve optimization problems for groundwater experimental design. PMID:19757116
Parameter estimation of copula functions using an optimization-based method
NASA Astrophysics Data System (ADS)
Abdi, Amin; Hassanzadeh, Yousef; Talatahari, Siamak; Fakheri-Fard, Ahmad; Mirabbasi, Rasoul
2016-02-01
Application of the copulas can be useful for the accurate multivariate frequency analysis of hydrological phenomena. There are many copula functions and some methods were proposed for estimating the copula parameters. Since the copula functions are mathematically complicated, estimating of the copula parameter is an effortful work. In the present study, an optimization-based method (OBM) is proposed to obtain the parameters of copulas. The usefulness of the proposed method is illustrated on drought events. For this purpose, three commonly used copulas of Archimedean family, namely, Clayton, Frank, and Gumbel copulas are used to construct the joint probability distribution of drought characteristics of 60 gauging sites located in East-Azarbaijan province, Iran. The performance of OBM was compared with two conventional methods, namely, method of moments and inference function for margins. The results illustrate the supremacy of the OBM to estimate the copula parameters compared to the other considered methods.
Decision support system for optimal reservoir operation modeling within sediment deposition control.
Hadihardaja, Iwan K
2009-01-01
Suspended sediment deals with surface runoff moving toward watershed affects reservoir sustainability due to the reduction of storage capacity. The purpose of this study is to introduce a reservoir operation model aimed at minimizing sediment deposition and maximizing energy production expected to obtain optimal decision policy for both objectives. The reservoir sediment-control operation model is formulated by using Non-Linear Programming with an iterative procedure based on a multi-objective measurement in order to achieve optimal decision policy that is established in association with the development of a relationship between stream inflow and sediment rate by utilizing the Artificial Neural Network. Trade off evaluation is introduced to generate a strategy for controlling sediment deposition at same level of target ratio while producing hydroelectric energy. The case study is carried out at the Sanmenxia Reservoir in China where redesign and reconstruction have been accomplished. However, this model deals only with the original design and focuses on a wet year operation. This study will also observe a five-year operation period to show the accumulation of sediment due to the impact of reservoir storage capacity. PMID:19214002
NASA Astrophysics Data System (ADS)
Kadaksham, Arun J.; Teki, Ranganath; Godwin, Milton; House, Matt; Goodwin, Frank
2013-04-01
With the insertion of extreme ultraviolet lithography (EUVL) for high volume manufacturing (HVM) expected in the next few years, it is necessary to examine the performance of low thermal expansion materials (LTEMs) and assess industry readiness of EUV substrates. Owing to the high cost of LTEM, most of the development work so far has been done on fused silica substrates. Especially in developing cleaning technology prior to multilayer deposition, fused silica substrates have been used extensively, and defect trends and champion blank data have been reported using multilayer deposition data on fused silica substrates. In this paper, the response of LTEMs to cleaning processes prior to multilayer deposition is discussed. Cleaning processes discussed in this paper are developed using fused silica substrates and applied on LTEM substrates. The defectivity and properties of LTEM to fused silica are compared. Using the dense scan feature of the substrate inspection tool capable of detecting defects down to 35 nm SiO2 equivalent size and appropriate defect decoration techniques to decorate small defects on substrates to make them detectable, cleaning technologies that have the potential to meet high demands on LTEM for EUVL are developed and optimized.
Stock optimizing in choice when a token deposit is the operant.
Widholm, J J; Silberberg, A; Hursh, S R; Imam, A A; Warren-Boulton, F R
2001-01-01
Each of 2 monkeys typically earned their daily food ration by depositing tokens in one of two slots. Tokens deposited in one slot dropped into a bin where they were kept (token kept). Deposits to a second slot dropped into a bin where they could be obtained again (token returned). In Experiment 1, a fixed-ratio (FR) 5 schedule that provided two food pellets was associated with each slot. Both monkeys preferred the token-returned slot. In Experiment 2, both subjects chose between unequal FR schedules with the token-returned slot always associated with the leaner schedule. When the FRs were 2 versus 3 and 2 versus 6, preferences were maintained for the token-returned slot; however, when the ratios were 2 versus 12, preference shifted to the token-kept slot. In Experiment 3, both monkeys chose between equal-valued concurrent variable-interval variable-interval schedules. Both monkeys preferred the slot that returned tokens. In Experiment 4, both monkeys chose between FRs that typically differed in size by a factor of 10. Both monkeys preferred the FR schedule that provided more food per trial. These data show that monkeys will choose so as to increase the number of reinforcers earned (stock optimizing) even when this preference reduces the rate of reinforcement (all reinforcers divided by session time). PMID:11768710
Optimization procedures for the estimation of phase portrait parameters of orientation fields
NASA Astrophysics Data System (ADS)
Ayres, Fábio J.; Rangayyan, Rangaraj M.
2006-02-01
Oriented patterns in an image often convey important information regarding the scene or the objects contained. Given an image presenting oriented texture, the orientation field of the image is a map that depicts the orientation angle of the texture at each pixel. Rao and Jain developed a method to describe oriented patterns in an image based on the association between the orientation field of a textured image and the phase portrait generated by a pair of linear first-order differential equations. The estimation of the model parameters is a nonlinear, nonconvex optimization problem, and practical experience shows that irrelevant local minima can lead to convergence to inappropriate results. We investigated the performance of four optimization algorithms for the estimation of the optimal phase portrait parameters for a given orientation field. The investigated algorithms are: nonlinear least-squares, linear least-squares, iterative linear least-squares, and simulated annealing. The algorithms are evaluated and compared in terms of the error between the estimated parameters and the parameters known by design, in the presence of noise in the orientation field and imprecision in the initialization of the parameters. The computational effort required by each algorithm is also assessed. Individually, the simulated annealing procedure yielded low fixed-point and parameter errors over the entire range of noise tested, whereas the performance of the other methods deteriorated with higher levels of noise. The use of the result of simulated annealing for the initialization of the nonlinear least-squares method led to further improvement upon the simulated annealing results.
Correlation between Deposition Parameters and Hydrogen Production in CuO Nanostructured Thin Films.
Artioli, Gianluca A; Mancini, Alessandro; Barbieri, Victoria Raissa; Quattrini, Matteo C; Quartarone, Eliana; Mozzati, Maria Cristina; Drera, Giovanni; Sangaletti, Luigi; Gombac, Valentina; Fornasiero, Paolo; Malavasi, Lorenzo
2016-02-16
In this article, we report a systematic investigation of the role of (i) substrate temperature, (ii) oxygen partial pressure, and (iii) radio frequency (rf) power on the crystal structure and morphology of CuO nanostructured thin films prepared by means of rf-magnetron sputtering starting from a Cu metal target. On selected films, photocatalytic tests have been carried out in order to correlate the structural and morphological properties of the thin films prepared under different conditions with the photocatalytic properties and to find out the key parameters to optimize the CuO nanostructured films. All of the synthesized films were single-phase CuO nanorods of variable diameter between 80 and 200 nm. Better-aligned rods were obtained at relatively low substrate temperatures and from low to intermediate oxygen partial pressures, resulting in more efficient photocatalytic activities. Our investigation suggests a relevant role of the crystallographic orientation of the CuO tenorite film on the photocatalytic activity, as demonstrated by the significant improvement in H2 evolution for highly oriented films. PMID:26788810
NASA Astrophysics Data System (ADS)
Agabekov, Vladimir E.; Gudimenko, Yurii I.; Ignasheva, Olga E.
1992-08-01
The phisico-chemical properties of the benzo [a] phenoxazone-5 derivatives and their vacuum-deposited thin films (optical absorption, phase and chemical compositions, free surface energies of the films, and their supermolecular structures) have been studied. Changes in the vapor phase ratio of the dye derivatives have been investigated dependent on the boat- evaporator temperature, and chemical structures of the transformation products have been established. The films of different structure phase states have been obtained dependent on the formation conditions. Thin films of 9-diethylamino-3-methacryloyloxy-5H-benzo [a] phenoxaz-5-dicyanmethylene display good light-sensitive and masking properties and are suitable for submicron patterning under UV-exposure with (lambda) equals 266 nm.
NASA Astrophysics Data System (ADS)
Gelfenbaum, G. R.; La Selle, S.; Witter, R. C.; Sugawara, D.; Jaffe, B. E.
2015-12-01
Inferring the relative magnitude of tsunamis generated during earthquakes based on the characteristics of sandy coastal deposits is a challenging problem. Using a hydrodynamic and sediment transport model, we explore whether the volume of sandy tsunami deposits can be used to infer tsunami magnitude and seafloor deformation. For large subduction zone earthquakes specifically, we are testing the hypothesis that onshore tsunami deposit volume is correlated with nearshore tsunami wave height and coseismic slip. First, we test this hypothesis using onshore tsunami deposit volume data and offshore slip for the 2011 Tohoku earthquake and tsunami. This test considers tsunami deposit volume and offshore slip as they vary alongshore across a wide range of sediment sources, offshore and onshore slopes, and boundary roughness conditions. Preliminary analysis suggests that a strong correlation exists between onshore tsunami deposit volume and adjacent offshore coseismic slip, so long as ample sediment were available along the coast to be eroded. Second, we apply a Delft3D tsunami inundation and sediment transport model to Stardust Bay in the U.S. Aleutian Islands, where 6 tsunamis in the last ~1700 years deposited marine sand across a coastal plain as much as 800 m inland and up to ~15 m above mean sea level. The youngest sand sheet, probably deposited by a tsunami generated during the 1957 Andreanof Islands earthquake (Mw 8.6), has the smallest sediment volume. Several older deposits have larger volumes. Models show that ≥10 m of slip on the Aleutian subduction megathrust offshore of Stardust Bay could produce the onshore sediment volume measured for the 1957 deposit. Older tsunami deposits of greater volume require up to 14 m of megathrust slip. Model sensitivity studies show that onshore sediment volume is most sensitive to megathrust slip and less sensitive to other unknowns such as width of fault rupture and roughness of inundated terrain
NASA Astrophysics Data System (ADS)
Wang, Dong; Tsui, Kwok-Leung; Zhou, Qiang
2016-05-01
Rolling element bearings are commonly used in machines to provide support for rotating shafts. Bearing failures may cause unexpected machine breakdowns and increase economic cost. To prevent machine breakdowns and reduce unnecessary economic loss, bearing faults should be detected as early as possible. Because wavelet transform can be used to highlight impulses caused by localized bearing faults, wavelet transform has been widely investigated and proven to be one of the most effective and efficient methods for bearing fault diagnosis. In this paper, a new Gauss-Hermite integration based Bayesian inference method is proposed to estimate the posterior distribution of wavelet parameters. The innovations of this paper are illustrated as follows. Firstly, a non-linear state space model of wavelet parameters is constructed to describe the relationship between wavelet parameters and hypothetical measurements. Secondly, the joint posterior probability density function of wavelet parameters and hypothetical measurements is assumed to follow a joint Gaussian distribution so as to generate Gaussian perturbations for the state space model. Thirdly, Gauss-Hermite integration is introduced to analytically predict and update moments of the joint Gaussian distribution, from which optimal wavelet parameters are derived. At last, an optimal wavelet filtering is conducted to extract bearing fault features and thus identify localized bearing faults. Two instances are investigated to illustrate how the proposed method works. Two comparisons with the fast kurtogram are used to demonstrate that the proposed method can achieve better visual inspection performances than the fast kurtogram.
Optimizing parameters of a technical system using quality function deployment method
NASA Astrophysics Data System (ADS)
Baczkowicz, M.; Gwiazda, A.
2015-11-01
The article shows the practical use of Quality Function Deployment (QFD) on the example of a mechanized mining support. Firstly it gives a short description of this method and shows how the designing process, from the constructor point of view, looks like. The proposed method allows optimizing construction parameters and comparing them as well as adapting to customer requirements. QFD helps to determine the full set of crucial construction parameters and then their importance and difficulty of their execution. Secondly it shows chosen technical system and presents its construction with figures of the existing and future optimized model. The construction parameters were selected from the designer point of view. The method helps to specify a complete set of construction parameters, from the point of view, of the designed technical system and customer requirements. The QFD matrix can be adjusted depending on designing needs and not every part of it has to be considered. Designers can choose which parts are the most important. Due to this QFD can be a very flexible tool. The most important is to define relationships occurring between parameters and that part cannot be eliminated from the analysis.
Data set of optimal parameters for colorimetric red assay of epoxide hydrolase activity.
de Oliveira, Gabriel Stephani; Adriani, Patricia Pereira; Borges, Flavia Garcia; Lopes, Adriana Rios; Campana, Patricia T; Chambergo, Felipe S
2016-09-01
The data presented in this article are related to the research article entitled "Epoxide hydrolase of Trichoderma reesei: Biochemical properties and conformational characterization" [1]. Epoxide hydrolases (EHs) are enzymes that catalyze the hydrolysis of epoxides to the corresponding vicinal diols. This article describes the optimal parameters for the colorimetric red assay to determine the enzymatic activity, with an emphasis on the characterization of the kinetic parameters, pH optimum and thermal stability of this enzyme. The effects of reagents that are not resistant to oxidation by sodium periodate on the reactions can generate false positives and interfere with the final results of the red assay. PMID:27366781
Factorization and reduction methods for optimal control of distributed parameter systems
NASA Technical Reports Server (NTRS)
Burns, J. A.; Powers, R. K.
1985-01-01
A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.
Parameter Identification of Chaotic Systems by a Novel Dual Particle Swarm Optimization
NASA Astrophysics Data System (ADS)
Jiang, Yunxiang; Lau, Francis C. M.; Wang, Shiyuan; Tse, Chi K.
In this paper, we propose a dual particle swarm optimization (PSO) algorithm for parameter identification of chaotic systems. We also consider altering the search range of individual particles adaptively according to their objective function value. We consider both noiseless and noisy channels between the original system and the estimation system. Finally, we verify the effectiveness of the proposed dual PSO method by estimating the parameters of the Lorenz system using two different data acquisition schemes. Simulation results show that the proposed method always outperforms the traditional PSO algorithm.
Hasan, Khader M.
2007-01-01
In this Communication, a theoretical framework for quality control and parameter optimization in diffusion tensor imaging (DTI) is presented and validated. The approach is based on the analytical error propagation of the mean diffusivity (Dav) obtained directly from the diffusion-weighted data (DW) acquired using rotationally-invariant and uniformly distributed icosahedral encoding schemes. The error propagation of a recently described and validated cylindrical tensor model is further extrapolated to the spherical tensor case (diffusion anisotropy ~ 0) to relate analytically the precision error in fractional tensor anisotropy (FA) with the mean diffusion signal-to-noise ratio (DNR). The approach provided simple analytical and empirical quality control measures for optimization of diffusion parameter space in an isotropic medium that can be tested using widely available water phantoms. PMID:17442523
Behnajady, Mohammad A; Modirshahla, Nasser; Mirzamohammady, Maryam; Vahid, Behrouz; Behnajady, Bahram
2008-12-30
In the present work the optimization of heat attachment method for increasing photoactivity of immobilized TiO2 on glass plate was investigated. Results show that sonication time, TiO2 suspension dosage, immobilization temperature, solvent type and immobilization replications are very effective on the photoactivity of immobilized TiO2 on glass plate on the removal of C.I. Acid Red 88 (AR88) and optimizing these parameters increases the photoactivity of immobilized catalyst. In other step, the effect of operational parameters such as light intensity and initial concentration of AR88 on the removal of AR88 was investigated with four times immobilized TiO2 on glass plate. Results show that removal rate decreases with increasing initial concentration of AR88 but increases with increasing UV-light intensity. PMID:18440135
NASA Astrophysics Data System (ADS)
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.
Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2006-01-01
This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.
Ng, Sook Kien; Zygmanski, Piotr; Jeung, Andrew; Mostafavi, Hassan; Hesser, Juergen; Bellon, Jennifer R; Wong, Julia S; Lyatskaya, Yulia
2012-01-01
Digital tomosynthesis (DTS) was evaluated as an alternative to cone-beam computed tomography (CBCT) for patient setup. DTS is preferable when there are constraints with setup time, gantry-couch clearance, and imaging dose using CBCT. This study characterizes DTS data acquisition and registration parameters for the setup of breast cancer patients using nonclinical Varian DTS software. DTS images were reconstructed from CBCT projections acquired on phantoms and patients with surgical clips in the target volume. A shift-and-add algorithm was used for DTS volume reconstructions, while automated cross-correlation matches were performed within Varian DTS software. Triangulation on two short DTS arcs separated by various angular spread was done to improve 3D registration accuracy. Software performance was evaluated on two phantoms and ten breast cancer patients using the registration result as an accuracy measure; investigated parameters included arc lengths, arc orientations, angular separation between two arcs, reconstruction slice spacing, and number of arcs. The shifts determined from DTS-to-CT registration were compared to the shifts based on CBCT-to-CT registration. The difference between these shifts was used to evaluate the software accuracy. After findings were quantified, optimal parameters for the clinical use of DTS technique were determined. It was determined that at least two arcs were necessary for accurate 3D registration for patient setup. Registration accuracy of 2 mm was achieved when the reconstruction arc length was > 5° for clips with HU ≥ 1000; larger arc length (≥ 8°) was required for very low HU clips. An optimal arc separation was found to be ≥ 20° and optimal arc length was 10°. Registration accuracy did not depend on DTS slice spacing. DTS image reconstruction took 10-30 seconds and registration took less than 20 seconds. The performance of Varian DTS software was found suitable for the accurate setup of breast cancer patients
NASA Astrophysics Data System (ADS)
Jiang, Hai Ming; Xie, Kang; Wang, Ya Fei
2011-11-01
In this work, a novel metaheuristic named artificial fish school algorithm is introduced into the optimization of pump parameters for the design of gain flattened Raman fiber amplifiers for the first time. Artificial fish school algorithm emulates three simple social behaviors of a fish in a school, namely, preying, swarming and following, to optimize a target function. In this algorithm the pump wavelengths and power levels are mapped respectively to the state of a fish in a school, and the gain of a Raman fiber amplifier is mapped to the concentration of a food source for the fish school to search. Application of this algorithm to the design of a C-band gain flattened Raman fiber amplifier leads to an optimized amplifier that produces a flat gain spectrum with 0.63 dB in band ripple for given conditions. This result demonstrates that the artificial fish school algorithm is efficient for the optimization of pump parameters of gain flattened Raman fiber amplifiers.
NASA Astrophysics Data System (ADS)
Agarwal, R.; Koehl, A.; Stammer, D.
2013-12-01
We present an application of a multivariate data assimilation technique for the optimization of parameters of a global primitive equation Atmospheric General Circulation Model (AGCM), the Planet Simulator (PlaSim). The technique is a gradient descent method, the Simultaneous Perturbation Stochastic Approximation algorithm, which utilizes approximations of gradients from cost function evaluations. Assimilated data includes contributions of temperature, precipitation and heat flux. The optimization technique is applied for tuning of 15 control parameters by assimilation of annual mean data. The method is effective in reducing the model-data differences measured by a cost function in an identical twin experiment and also shown to work with realistic data from ERA-Interim. Results are evaluated against ERA-Interim observations. The RMSD of temperature and net heat flux in the optimized simulations is reduced by 15-20 % while the errors in precipitation are reduced by 6%. Regionally, there is a marked improvement in surface temperature and net flux simulations, especially in the North West Pacific and North Atlantic Ocean. As compared to other optimization procedures, the main advantage of SPSA is that it is simple to implement, less time consuming and robust to noise in the cost function which makes it applicable for the assimilation of statistical information into chaotic models.
Xie, Dongming; Liu, Dehua; Zhu, Haoli; Zhang, Jianan
2002-05-01
To optimize the fed-batch processes of glycerol fermentation in different reactor states, typical bioreactors including 500-mL shaking flask, 600-mL and 15-L airlift loop reactor, and 5-L stirred vessel were investigated. It was found that by reestimating the values of only two variable kinetic parameters associated with physical transport phenomena in a reactor, the macrokinetic model of glycerol fermentation proposed in previous work could describe well the batch processes in different reactor states. This variable kinetic parameter (VKP) approach was further applied to model-based optimization of discrete-pulse feed (DPF) strategies of both glucose and corn steep slurry for glycerol fed-batch fermentation. The experimental results showed that, compared with the feed strategies determined just by limited experimental optimization in previous work, the DPF strategies with VKPs adjusted could improve glycerol productivity at least by 27% in the scale-down and scale-up reactor states. The approach proposed appeared promising for further modeling and optimization of glycerol fermentation or the similar bioprocesses in larger scales. PMID:12049203
Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System
Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei
2015-01-01
Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm. PMID:26121614
Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization.
Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri
2013-09-01
Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors. PMID:24065871
Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization
Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri
2013-01-01
Abstract Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors. PMID:24065871
Variational optimization of sub-grid scale convection parameters. Final report
Zivkovic-Rothman, M.
1997-11-25
Under the DOE CHAMMP/CLIMATE Program, a convective scheme was developed for use in climate models. The purpose of the present study was to develop an adjoint model of its tangent-linear model. the convective scheme was integrated within a single column model which provides radiative-convective equilibrium solutions applicable to climate models. The main goal of this part of the project was to develop an adjoint of the scheme to facilitate the optimization of its convective parameters. For that purpose, adjoint sensitivities were calculated with the adjoint code. Parameter optimization was based on TOGA COARE data which were also used in this study to obtain integrations of the nonlinear and tangent-linear models as well as the integrations of the adjoint model. Some inadequacies of the inner IFA data array were found, and did not permit a single numerical integration during the entire 4 months of data. However, reliable monthly radiative-convective equilibrium solutions and associated adjoint sensitivities were obtained and used to bring about the parameter optimization.
Jussen, Daniel; Soltner, Helmut; Stute, Birgit; Wiechert, Wolfgang; von Lieres, Eric; Pohl, Martina
2016-08-10
Enzymatic parameter determination is an essential step in biocatalytic process development. Therefore higher throughput in miniaturized devices is urgently needed. An ideal microfluidic device should combine easy immobilization and retention of a minimal amount of biocatalyst with a well-mixed reaction volume. Together, all criteria are hardly met by current tools. Here we describe a microfluidic reactor (μMORE) which employs magnetic particles for both enzyme immobilization and efficient mixing using two permanent magnets placed in rotating cylinders next to the a glass chip reactor. The chip geometry and agitation speed was optimized by investigation of the mixing and retention characteristics using simulation and dye distribution analysis. Subsequently, the μMORE was successfully applied to determine critical biocatalytic process parameters in a parallelized manner for the carboligation of benzaldehyde and acetaldehyde to (S)-2-hydroxy-1-phenylpropan-1-one with less than 5μg of benzoylformate decarboxylase from Pseudomonas putida immobilized on magnetic beads. Here, one run of the device in six parallelized glass reactors took only 2-3h for an immobilized enzyme with very low activity (∼2U/mg). The optimized parameter set was finally tested in a 10mL enzyme membrane reactor, demonstrating that the μMORE provides a solid data base for biocatalytic process optimization. PMID:27288595
Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.
Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei
2015-01-01
Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm. PMID:26121614
Parameters optimization of laser brazing in crimping butt using Taguchi and BPNN-GA
NASA Astrophysics Data System (ADS)
Rong, Youmin; Zhang, Zhen; Zhang, Guojun; Yue, Chen; Gu, Yafei; Huang, Yu; Wang, Chunming; Shao, Xinyu
2015-04-01
The laser brazing (LB) is widely used in the automotive industry due to the advantages of high speed, small heat affected zone, high quality of welding seam, and low heat input. Welding parameters play a significant role in determining the bead geometry and hence quality of the weld joint. This paper addresses the optimization of the seam shape in LB process with welding crimping butt of 0.8 mm thickness using back propagation neural network (BPNN) and genetic algorithm (GA). A 3-factor, 5-level welding experiment is conducted by Taguchi L25 orthogonal array through the statistical design method. Then, the input parameters are considered here including welding speed, wire speed rate, and gap with 5 levels. The output results are efficient connection length of left side and right side, top width (WT) and bottom width (WB) of the weld bead. The experiment results are embed into the BPNN network to establish relationship between the input and output variables. The predicted results of the BPNN are fed to GA algorithm that optimizes the process parameters subjected to the objectives. Then, the effects of welding speed (WS), wire feed rate (WF), and gap (GAP) on the sum values of bead geometry is discussed. Eventually, the confirmation experiments are carried out to demonstrate the optimal values were effective and reliable. On the whole, the proposed hybrid method, BPNN-GA, can be used to guide the actual work and improve the efficiency and stability of LB process.
Optimization of parameter settings in cine-MR imaging for diagnosis of swallowing.
Ohkubo, Mai; Higaki, Takuo; Nishikawa, Keiichi; Otonari-Yamamoto, Mika; Sugiyama, Tetsuya; Ishida, Ryo; Wako, Mamoru; Sano, Tsukasa
2014-01-01
Videofluorography is frequently used to evaluate swallowing and is considered the "gold standard" among imaging modalities. This modality, however, has several disadvantages, including radiation exposure and limitations in the detection of soft tissues. Conversely, magnetic resonance imaging (MRI) offers excellent contrast resolution in soft tissue without radiation exposure. A major drawback of MRI in evaluating swallowing, however, is that temporal resolution is poor. The aim of this study was to investigate a new cine-MRI modality. Imaging parameters were optimized and the efficacy of this new technique is discussed. Three techniques for speeding up MRI were combined: true fast imaging with steady state precession, generalized auto-calibrating partially parallel acquisition, and key-hole imaging. The effects of the receiver coils used, receiving bandwidth, slice thickness, and flip angle on each image were determined. The optimal imaging parameters obtained comprised a reduction factor of 2, receiving bandwidth of 1,000 Hz/pixel (repetition time of 151.7 milliseconds and echo time of 1.4 milliseconds), flip angle of 50°, and slice thickness of 6 mm. Neck and spine coils were used. Under these conditions, the new cine-MR imaging technique investigated showed a temporal resolution of 0.1 sec/slice (10 frames/sec). Even with optimized parameter settings, this technique did not allow a true temporal resolution of 30 frames/sec by a large margin. Motion artifacts persisted. Further study is needed on how to speed up this technique. PMID:25212558
NASA Astrophysics Data System (ADS)
Basak, Amrita; Acharya, Ranadip; Das, Suman
2016-06-01
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.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Portnoy, David; Feuerbach, Robert; Heimberg, Jennifer
2011-10-01
Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the "threat" set of spectra
Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin
2016-01-01
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974
Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin
2016-01-01
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974
Modenese, Luca; Ceseracciu, Elena; Reggiani, Monica; Lloyd, David G
2016-01-25
A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par. PMID:26776930
NASA Astrophysics Data System (ADS)
Toker, C.; Gokdag, Y. E.; Arikan, F.; Arikan, O.
2012-04-01
Ionosphere is a very important part of Space Weather. Modeling and monitoring of ionospheric variability is a major part of satellite communication, navigation and positioning systems. Total Electron Content (TEC), which is defined as the line integral of the electron density along a ray path, is one of the parameters to investigate the ionospheric variability. Dual-frequency GPS receivers, with their world wide availability and efficiency in TEC estimation, have become a major source of global and regional TEC modeling. When Global Ionospheric Maps (GIM) of International GPS Service (IGS) centers (http://iono.jpl.nasa.gov/gim.html) are investigated, it can be observed that regional ionosphere along the midlatitude regions can be modeled as a constant, linear or a quadratic surface. Globally, especially around the magnetic equator, the TEC surfaces resemble twisted and dispersed single centered or double centered Gaussian functions. Particle Swarm Optimization (PSO) proved itself as a fast converging and an effective optimization tool in various diverse fields. Yet, in order to apply this optimization technique into TEC modeling, the method has to be modified for higher efficiency and accuracy in extraction of geophysical parameters such as model parameters of TEC surfaces. In this study, a modified PSO (mPSO) method is applied to regional and global synthetic TEC surfaces. The synthetic surfaces that represent the trend and small scale variability of various ionospheric states are necessary to compare the performance of mPSO over number of iterations, accuracy in parameter estimation and overall surface reconstruction. The Cramer-Rao bounds for each surface type and model are also investigated and performance of mPSO are tested with respect to these bounds. For global models, the sample points that are used in optimization are obtained using IGS receiver network. For regional TEC models, regional networks such as Turkish National Permanent GPS Network (TNPGN
NASA Astrophysics Data System (ADS)
Campbell, Michelle E.; Porritt, Lucy; Russell, J. K.
2016-02-01
The 2360 BP eruption of Mount Meager, Canada featured an explosive subplinian onset resulting in dacitic fallout tephra and associated pumiceous pyroclastic flow deposits, followed by the effusion of dacite lava and the deposition of a thick sequence of block and ash flow deposits. Fall deposits are distributed to the NE of the vent onto a rugged, deeply incised landscape. The central axis of deposition is ~ 063° Az; the lateral margins of the fall deposit are massive to unbedded whereas deposits underlying the plume axis feature complex bedding relationships. We present componentry and granulometry data for eight outcroppings of the fall deposit (four on plume axis and four off plume axis). Vertical cross-sections, based on surface outcrops and drill core logs from local commercial drilling programs, are used to relate the accessory lithics to their source depth in the underlying subvolcanic basement. These combined datasets inform on the dynamics of this explosive phase of the eruption including variations in column height, eruption intensity, atmospheric conditions, and depth to fragmentation front. The lateral variations within the fall strata reflect the effects of the prevailing atmospheric conditions on the form and dispersal pattern of the subplinian plume. Vertical variations in granulometry and componentry of the fall deposits are used to track temporal changes in eruption intensity and column height and the transient influence of the jetstream on the dispersal pattern of the plume. Lastly, vertical variations in lithic componentry, combined with our knowledge of the subsurface geology, are used to quantitatively track the deepening of the fragmentation front. Our computed results show that the fragmentation front migrated from ~ 640 m to ~ 1160 m below the vent over the course of the 2360 BP Mount Meager eruption.
NASA Astrophysics Data System (ADS)
Reimer, J.; Schuerch, M.; Slawig, T.
2015-03-01
The geosciences are a highly suitable field of application for optimizing model parameters and experimental designs especially because many data are collected. In this paper, the weighted least squares estimator for optimizing model parameters is presented together with its asymptotic properties. A popular approach to optimize experimental designs called local optimal experimental designs is described together with a lesser known approach which takes into account the potential nonlinearity of the model parameters. These two approaches have been combined with two methods to solve their underlying discrete optimization problem. All presented methods were implemented in an open-source MATLAB toolbox called the Optimal Experimental Design Toolbox whose structure and application is described. In numerical experiments, the model parameters and experimental design were optimized using this toolbox. Two existing models for sediment concentration in seawater and sediment accretion on salt marshes of different complexity served as an application example. The advantages and disadvantages of these approaches were compared based on these models. Thanks to optimized experimental designs, the parameters of these models could be determined very accurately with significantly fewer measurements compared to unoptimized experimental designs. The chosen optimization approach played a minor role for the accuracy; therefore, the approach with the least computational effort is recommended.
Fast and Efficient Black Box Optimization Using the Parameter-less Population Pyramid.
Goldman, B W; Punch, W F
2015-01-01
The parameter-less population pyramid (P3) is a recently introduced method for performing evolutionary optimization without requiring any user-specified parameters. P3's primary innovation is to replace the generational model with a pyramid of multiple populations that are iteratively created and expanded. In combination with local search and advanced crossover, P3 scales to problem difficulty, exploiting previously learned information before adding more diversity. Across seven problems, each tested using on average 18 problem sizes, P3 outperformed all five advanced comparison algorithms. This improvement includes requiring fewer evaluations to find the global optimum and better fitness when using the same number of evaluations. Using both algorithm analysis and comparison, we find P3's effectiveness is due to its ability to properly maintain, add, and exploit diversity. Unlike the best comparison algorithms, P3 was able to achieve this quality without any problem-specific tuning. Thus, unlike previous parameter-less methods, P3 does not sacrifice quality for applicability. Therefore we conclude that P3 is an efficient, general, parameter-less approach to black box optimization which is more effective than existing state-of-the-art techniques. PMID:25781724
Temporal artifact minimization in sonoelastography through optimal selection of imaging parameters.
Torres, Gabriela; Chau, Gustavo R; Parker, Kevin J; Castaneda, Benjamin; Lavarello, Roberto J
2016-07-01
Sonoelastography is an ultrasonic technique that uses Kasai's autocorrelation algorithms to generate qualitative images of tissue elasticity using external mechanical vibrations. In the absence of synchronization between the mechanical vibration device and the ultrasound system, the random initial phase and finite ensemble length of the data packets result in temporal artifacts in the sonoelastography frames and, consequently, in degraded image quality. In this work, the analytic derivation of an optimal selection of acquisition parameters (i.e., pulse repetition frequency, vibration frequency, and ensemble length) is developed in order to minimize these artifacts, thereby eliminating the need for complex device synchronization. The proposed rule was verified through experiments with heterogeneous phantoms, where the use of optimally selected parameters increased the average contrast-to-noise ratio (CNR) by more than 200% and reduced the CNR standard deviation by 400% when compared to the use of arbitrarily selected imaging parameters. Therefore, the results suggest that the rule for specific selection of acquisition parameters becomes an important tool for producing high quality sonoelastography images. PMID:27475192
Parameter-space correlations of the optimal statistic for continuous gravitational-wave detection
Pletsch, Holger J.
2008-11-15
The phase parameters of matched-filtering searches for continuous gravitational-wave signals are sky position, frequency, and frequency time-derivatives. The space of these parameters features strong global correlations in the optimal detection statistic. For observation times smaller than 1 yr, the orbital motion of the Earth leads to a family of global-correlation equations which describes the 'global maximum structure' of the detection statistic. The solution to each of these equations is a different hypersurface in parameter space. The expected detection statistic is maximal at the intersection of these hypersurfaces. The global maximum structure of the detection statistic from stationary instrumental-noise artifacts is also described by the global-correlation equations. This permits the construction of a veto method which excludes false candidate events.
Chen, Tao; Kirkby, Norman F; Jena, Raj
2012-12-01
Model predictive control (MPC), originally developed in the community of industrial process control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis of MPC is usually a state-space model (a system of ordinary differential equations), whereby existing studies usually assume that the entire states can be directly measured. This paper aims to demonstrate that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment. This aim is achieved through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the system states and parameters. The effectiveness of the MPC-MHE scheme is illustrated through scheduling the dose of tamoxifen for simulated tumour-bearing patients, and the impact of estimation horizon and magnitude of parameter discrepancy is also investigated. PMID:22739208
Multiobjective optimization in structural design with uncertain parameters and stochastic processes
NASA Technical Reports Server (NTRS)
Rao, S. S.
1984-01-01
The application of multiobjective optimization techniques to structural design problems involving uncertain parameters and random processes is studied. The design of a cantilever beam with a tip mass subjected to a stochastic base excitation is considered for illustration. Several of the problem parameters are assumed to be random variables and the structural mass, fatigue damage, and negative of natural frequency of vibration are considered for minimization. The solution of this three-criteria design problem is found by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It is observed that the game theory approach is superior in finding a better optimum solution, assuming the proper balance of the various objective functions. The procedures used in the present investigation are expected to be useful in the design of general dynamic systems involving uncertain parameters, stochastic process, and multiple objectives.
Hui, Ben B B; Dokos, Socrates; Lovell, Nigel H
2007-01-01
Published models of excitable cells can be used to fit to a range of action potential experimental data. CellML is a well-defined standard for publishing and exchanging such models, but currently there is a lack of software that utilizes CellML for parameter analysis. In this paper, we introduce a Java-based utility capable of performing model simulation, identifiability analysis, and parameter optimization of ionic cardiac cell models written in CellML. Identifiability analysis was performed in seven CellML models. Parameter identifiability was consistently improved by using the compensatory membrane current as opposed to the membrane voltage as the residual. as well as through the introduction of an additional stimulus set used in the fitting process. PMID:18003205
Paramfit: automated optimization of force field parameters for molecular dynamics simulations.
Betz, Robin M; Walker, Ross C
2015-01-15
The generation of bond, angle, and torsion parameters for classical molecular dynamics force fields typically requires fitting parameters such that classical properties such as energies and gradients match precalculated quantum data for structures that scan the value of interest. We present a program, Paramfit, distributed as part of the AmberTools software package that automates and extends this fitting process, allowing for simplified parameter generation for applications ranging from single molecules to entire force fields. Paramfit implements a novel combination of a genetic and simplex algorithm to find the optimal set of parameters that replicate either quantum energy or force data. The program allows for the derivation of multiple parameters simultaneously using significantly fewer quantum calculations than previous methods, and can also fit parameters across multiple molecules with applications to force field development. Paramfit has been applied successfully to systems with a sparse number of structures, and has already proven crucial in the development of the Assisted Model Building with Energy Refinement Lipid14 force field. PMID:25413259
Optimization of image process parameters through factorial experiments using a flat panel detector
NASA Astrophysics Data System (ADS)
Norrman, Eva; Geijer, Håkan; Persliden, Jan
2007-09-01
In the optimization process of lumbar spine examinations, factorial experiments were performed addressing the question of whether the effective dose can be reduced and the image quality maintained by adjusting the image processing parameters. A 2k-factorial design was used which is a systematic and effective method of investigating the influence of many parameters on a result variable. Radiographic images of a Contrast Detail phantom were exposed using the default settings of the process parameters for lumbar spine examinations. The image was processed using different settings of the process parameters. The parameters studied were ROI density, gamma, detail contrast enhancement (DCE), noise compensation, unsharp masking and unsharp masking kernel (UMK). The images were computer analysed and an image quality figure (IQF) was calculated and used as a measurement of the image quality. The parameters with the largest influence on image quality were noise compensation, unsharp masking, unsharp masking kernel and detail contrast enhancement. There was an interaction between unsharp masking and kernel indicating that increasing the unsharp masking improved the image quality when combined with a large kernel size. Combined with a small kernel size however the unsharp masking had a deteriorating effect. Performing a factorial experiment gave an overview of how the image quality was influenced by image processing. By adjusting the level of noise compensation, unsharp masking and kernel, the IQF was improved to a 30% lower effective dose.
Analysis and optimization of process parameters in Al-SiCp laser cladding
NASA Astrophysics Data System (ADS)
Riquelme, Ainhoa; Rodrigo, Pilar; Escalera-Rodríguez, María Dolores; Rams, Joaquín
2016-03-01
The laser cladding process parameters have great effect on the clad geometry and on dilution in the single and multi-pass aluminum matrix composite reinforced with SiC particles (Al/SiCp) coatings on ZE41 magnesium alloys deposited using a high-power diode laser (HPLD). The influence of the laser power (500-700 W), scan speed (3-17 mm/s) and laser beam focal position (focus, positive and negative defocus) on the shape factor, cladding-bead geometry, cladding-bead microstructure (including the presence of pores and cracks), and hardness has been evaluated. The correlation of these process parameters and their influence on the properties and ultimately, on the feasibility of the cladding process, is demonstrated. The importance of focal position is demonstrated. The different energy distribution of the laser beam cross section in focus plane or in positive and negative defocus plane affect on the cladding-bead properties.
Leong, Wai Fun; Che Man, Yaakob B; Lai, Oi Ming; Long, Kamariah; Misran, Misni; Tan, Chin Ping
2009-09-23
The purpose of this study was to optimize the parameters involved in the production of water-soluble phytosterol microemulsions for use in the food industry. In this study, response surface methodology (RSM) was employed to model and optimize four of the processing parameters, namely, the number of cycles of high-pressure homogenization (1-9 cycles), the pressure used for high-pressure homogenization (100-500 bar), the evaporation temperature (30-70 degrees C), and the concentration ratio of microemulsions (1-5). All responses-particle size (PS), polydispersity index (PDI), and percent ethanol residual (%ER)-were well fit by a reduced cubic model obtained by multiple regression after manual elimination. The coefficient of determination (R(2)) and absolute average deviation (AAD) value for PS, PDI, and %ER were 0.9628 and 0.5398%, 0.9953 and 0.7077%, and 0.9989 and 1.0457%, respectively. The optimized processing parameters were 4.88 (approximately 5) homogenization cycles, homogenization pressure of 400 bar, evaporation temperature of 44.5 degrees C, and concentration ratio of microemulsions of 2.34 cycles (approximately 2 cycles) of high-pressure homogenization. The corresponding responses for the optimized preparation condition were a minimal particle size of 328 nm, minimal polydispersity index of 0.159, and <0.1% of ethanol residual. The chi-square test verified the model, whereby the experimental values of PS, PDI, and %ER agreed with the predicted values at a 0.05 level of significance. PMID:19694442
NASA Astrophysics Data System (ADS)
Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas
2016-04-01
Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.
NASA Astrophysics Data System (ADS)
Sahoo, G. B.
2007-12-01
In recent years, artificial neural networks (ANNs) appear to be viable alternative to models that use phenomenological hypotheses (i.e. knowledge based models) for cases (1) the available data are not detailed and sufficient for using a process based model and (2) the detailed complex physics of the system is partially understood. ANNs have been widely used in many fields such as chemical and environmental engineering, hydrology, and water resources applications for optimum prediction of system parameters and variables. However, in most cases, parameters and system variables were forecasted employing suboptimal ANNs. The geometry and modeling parameters of an artificial neural network (ANN) and the training dataset have significant effects on its predictive performance efficiency. The combination of ANN modeling parameter and geometry arranged in the modeling domain (i.e. lower and upper bounds of each modeling parameter and geometry) is large enough (i.e. greater than 100000) that it is difficult to examine all cases using trial and error approach for the selection of an optimum set. Thus, one could easily end up with finding a set of suboptimal values. This study presents the use of genetic algorithms (GAs) to search for the optimal geometry and values of modeling parameters of a multilayer feedforward backpropagation neural network (BPNN) and a radial basis function network (RBFN). The predictive performance efficiency of the GA and ANN combination is examined using two datasets derived from the same population for training. It is illustrated that (1) the GA optimized ANN outperforms to the ANN using a trial and error approach, and (2) ANN predictive performance and geometry depend on the number of samples and the characteristics of samples included in the training dataset.
Optimizing galvanic pulse plating parameters to improve indium bump to bump bonding
NASA Astrophysics Data System (ADS)
Coleman, Jonathan J.; Rowen, Adam; Mani, Seethambal S.; Yelton, W. Graham; Arrington, Christian; Gillen, Rusty; Hollowell, Andrew E.; Okerlund, Daniel; Ionescu, Adrian
2010-02-01
The plating characteristics of a commercially available indium plating solution are examined and optimized to help meet the increasing performance demands of integrated circuits requiring substantial numbers of electrical interconnections over large areas. Current fabrication techniques rely on evaporation of soft metals, such as indium, into lift-off resist profiles. This becomes increasingly difficult to accomplish as pitches decrease and aspect ratios increase. To minimize pixel dimensions and maximize the number of pixels per unit area, lithography and electrochemical deposition (ECD) of indium has been investigated. Pulse ECD offers the capability of improving large area uniformity ideal for large area device hybridization. Electrochemical experimentation into lithographically patterned molds allow for large areas of bumps to be fabricated for low temperature indium to indium bonds. The galvanic pulse profile, in conjunction with the bath configuration, determines the uniformity of the plated array. This pulse is manipulated to produce optimal properties for hybridizing arrays of aligned and bonded indium bumps. The physical properties of the indium bump arrays are examined using a white light interferometer, a SEM and tensile pull testing. This paper provides details from the electroplating processes as well as conclusions leading to optimized plating conditions.
NASA Astrophysics Data System (ADS)
Fei, Chenxi; Liu, Hongxia; Wang, Xing; Fan, Xiaojiao
2015-04-01
The influence of processing parameters of aluminum oxide (Al2O3) and lanthanum oxide (La2O3) gate dielectric is investigated. Trimethylaluminum (TMA) and tris(isopropylcyclopentadienyl) lanthanum [La(iPrCp)3] were used as precursors separately, and H2O was used as oxidant. The ultra-thin La1 - x Al x O3 gate dielectric films are deposited on p-type silicon substrates by atom layer deposition (ALD) for different pulse ratios of precursors. Effects of different La/Al precursor pulse ratios on the physical properties and electrical characteristics of La1 - x Al x O3 films are studied. The preliminary testing results indicate that the increase of La precursor pulse can improve the characteristics of film, which has significant effects on the dielectric constant, equivalent oxide thickness (EOT), electrical properties, and stability of film.
Fei, Chenxi; Liu, Hongxia; Wang, Xing; Fan, Xiaojiao
2015-01-01
The influence of processing parameters of aluminum oxide (Al2O3) and lanthanum oxide (La2O3) gate dielectric is investigated. Trimethylaluminum (TMA) and tris(isopropylcyclopentadienyl) lanthanum [La(iPrCp)3] were used as precursors separately, and H2O was used as oxidant. The ultra-thin La1 - x Al x O3 gate dielectric films are deposited on p-type silicon substrates by atom layer deposition (ALD) for different pulse ratios of precursors. Effects of different La/Al precursor pulse ratios on the physical properties and electrical characteristics of La1 - x Al x O3 films are studied. The preliminary testing results indicate that the increase of La precursor pulse can improve the characteristics of film, which has significant effects on the dielectric constant, equivalent oxide thickness (EOT), electrical properties, and stability of film. PMID:25983672
Brevet, Romain; Richter, Daniel; Graeff, Christian; Durante, Marco; Bert, Christoph
2015-01-01
Scanned ion beam therapy of lung tumors is severely limited in its clinical applicability by intrafractional organ motion, interference effects between beam and tumor motion (interplay), as well as interfractional anatomic changes. To compensate for dose deterioration caused by intrafractional motion, motion mitigation techniques, such as gating, have been developed. However, optimization of the treatment parameters is needed to further improve target dose coverage and normal tissue sparing. The aim of this study was to determine treatment-planning parameters that permit to recover good target coverage for each fraction of lung tumor treatments. For 9 lung tumor patients from MD Anderson Cancer Center (Houston, Texas), a total of 70 weekly time-resolved computed tomography (4DCT) datasets, which depict the evolution of the patient anatomy over the several fractions of the treatment, were available. Using the GSI in-house treatment planning system TRiP4D, 4D simulations were performed on each weekly 4DCT for each patient using gating and optimization of a single treatment plan based on a planning CT acquired prior to treatment. The impact on target dose coverage (V 95%,CTV) of variations in focus size and length of the gating window, as well as different additional margins and the number of fields was analyzed. It appeared that interfractional variability could potentially have a larger impact on V 95%,CTV than intrafractional motion. However, among the investigated parameters, the use of a large beam spot size, a short gating window, additional margins, and multiple fields permitted to obtain an average V 95%,CTV of 96.5%. In the presented study, it was shown that optimized treatment parameters have an important impact on target dose coverage in the treatment of moving tumors. Indeed, intrafractional motion occurring during the treatment of lung tumors and interfractional variability were best mitigated using a large focus, a short gating window, additional margins
Brevet, Romain; Richter, Daniel; Graeff, Christian; Durante, Marco; Bert, Christoph
2015-01-01
Scanned ion beam therapy of lung tumors is severely limited in its clinical applicability by intrafractional organ motion, interference effects between beam and tumor motion (interplay), as well as interfractional anatomic changes. To compensate for dose deterioration caused by intrafractional motion, motion mitigation techniques, such as gating, have been developed. However, optimization of the treatment parameters is needed to further improve target dose coverage and normal tissue sparing. The aim of this study was to determine treatment-planning parameters that permit to recover good target coverage for each fraction of lung tumor treatments. For 9 lung tumor patients from MD Anderson Cancer Center (Houston, Texas), a total of 70 weekly time-resolved computed tomography (4DCT) datasets, which depict the evolution of the patient anatomy over the several fractions of the treatment, were available. Using the GSI in-house treatment planning system TRiP4D, 4D simulations were performed on each weekly 4DCT for each patient using gating and optimization of a single treatment plan based on a planning CT acquired prior to treatment. The impact on target dose coverage (V 95%,CTV) of variations in focus size and length of the gating window, as well as different additional margins and the number of fields was analyzed. It appeared that interfractional variability could potentially have a larger impact on V 95%,CTV than intrafractional motion. However, among the investigated parameters, the use of a large beam spot size, a short gating window, additional margins, and multiple fields permitted to obtain an average V 95%,CTV of 96.5%. In the presented study, it was shown that optimized treatment parameters have an important impact on target dose coverage in the treatment of moving tumors. Indeed, intrafractional motion occurring during the treatment of lung tumors and interfractional variability were best mitigated using a large focus, a short gating window, additional margins
NASA Astrophysics Data System (ADS)
Rosolem, R.; Shuttleworth, W. J.; Gupta, H. V.; Goncalves, L.; Zeng, X.; Restrepo-Coupe, N.
2010-12-01
About eight years of data (1999-2006) collected from a variety of sites located in the Amazon basin under the Large-scale Biosphere-Atmosphere experiment in Amazonia (LBA) are now being used to compare a large number of land surface parameterization (LSP) schemes as part of the LBA Data-Model Intercomparison Project (LBA-DMIP). We use continuous hourly meteorological data obtained from the LBA-DMIP to drive the third generation of the Simple Biosphere model (SiB3), and to conduct a comprehensive parameter estimation study in the region. The validation data comprise of sensible and latent heat flux densities (i.e., H and LE, respectively) and Net Ecosystem Exchange of CO2 (i.e., NEE). Given the large number of parameters found in current LSP schemes (such as SiB3), manual calibration can be intractable and, consequently, automatic calibration techniques have become the preferred alternative. Parameter sensitivity analysis contributes to the understanding of potential structural characteristics of a model, and also reduces the dimension of the optimization problem by fixing insensitive parameters to their nominal values. In this study, we use the variance-based Sobol sensitivity analysis approach which determines the sensitivity of each parameter based on its percent contribution to the total output variance in the model. We then conduct the optimization of the most significant parameters in SiB3 using the so called “A Multi-Algorithm, Genetically Adaptive Multiobjective” (AMALGAM) which combines two highly desired concepts in evolutionary algorithms: (1) simultaneous multimethod search, and (2) self-adaptive offspring creation. The ultimate goal of this study is to identify key parameters related to individual LBA sites that need to be properly analyzed and calibrated in order to improve simulated land surface processes in the region. We anticipate that this will also help how measurements of these parameters are obtained in situ. The performance of SiB3 prior
Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling
Hamrick, Todd
2011-01-01
Efficiency in drilling is measured by Mechanical Specific Energy (MSE). MSE is the measure of the amount of energy input required to remove a unit volume of rock, expressed in units of energy input divided by volume removed. It can be expressed mathematically in terms of controllable parameters; Weight on Bit, Torque, Rate of Penetration, and RPM. It is well documented that minimizing MSE by optimizing controllable factors results in maximum Rate of Penetration. Current methods for computing MSE make it possible to minimize MSE in the field only through a trial-and-error process. This work makes it possible to compute the optimum drilling parameters that result in minimum MSE. The parameters that have been traditionally used to compute MSE are interdependent. Mathematical relationships between the parameters were established, and the conventional MSE equation was rewritten in terms of a single parameter, Weight on Bit, establishing a form that can be minimized mathematically. Once the optimum Weight on Bit was determined, the interdependent relationship that Weight on Bit has with Torque and Penetration per Revolution was used to determine optimum values for those parameters for a given drilling situation. The improved method was validated through laboratory experimentation and analysis of published data. Two rock types were subjected to four treatments each, and drilled in a controlled laboratory environment. The method was applied in each case, and the optimum parameters for minimum MSE were computed. The method demonstrated an accurate means to determine optimum drilling parameters of Weight on Bit, Torque, and Penetration per Revolution. A unique application of micro-cracking is also presented, which demonstrates that rock failure ahead of the bit is related to axial force more than to rotation speed.
Jevtić, Aleksandar; Gutiérrez, Álvaro
2011-01-01
Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677
Optimization of process parameters for the rapid biosynthesis of hematite nanoparticles.
Rajendran, Kumar; Sen, Shampa
2016-06-01
Hematite (α-Fe2O3) nanoparticles are widely used in various applications including gas sensors, pigments owing to its low cost, environmental friendliness, non-toxicity and high resistance to corrosion. These nanoparticles were generally synthesized by different chemical methods. In the present study, nanoparticles were synthesized rapidly without heat treatment by biosynthesis approach using culture supernatant of Bacillus cereus SVK1. The physiochemical parameters for rapid synthesis were optimized by using UV-visible spectroscopy. The time taken for hematite nanoparticle synthesis was found to increase with the increasing concentration of the precursor. This might be due to the inadequate proportion of quantity of biomolecules present in the culture supernatant to the precursor which led to delayed bioreduction. Greater quantities of culture supernatant with respect to precursor lead to rapid synthesis of hematite nanoparticles. The nucleation of the hematite nucleus happens more easily when the solution pH was less than 10. The optimum parameters identified for the rapid biosynthesis of hematite nanoparticles were pH9, 37°C (temperature) and 1mM ferric chloride as precursor. The particles were well crystallized hexagonal structured hematite nanoparticles and are predominantly (110)-oriented. The synthesized nanoparticles were found to contain predominantly iron (73.47%) and oxygen (22.58%) as evidenced by Energy Dispersive X-ray analysis. Hematite nanoparticles of 15-40nm diameters were biosynthesized in 48h under optimized conditions, compared to 21days before optimization. PMID:27045277
NASA Astrophysics Data System (ADS)
Chang, Kwo-Ping; Wang, Zhi-Wei; Shiau, An-Cheng
2014-02-01
Monte Carlo (MC) method is a well known calculation algorithm which can accurately assess the dose distribution for radiotherapy. The present study investigated all the possible regions of the depth-dose or lateral profiles which may affect the fitting of the initial parameters (mean energy and the radial intensity (full width at half maximum, FWHM) of the incident electron). EGSnrc-based BEAMnrc codes were used to generate the phase space files (SSD=100 cm, FS=40×40 cm2) for the linac (linear accelerator, Varian 21EX, 6 MV photon mode) and EGSnrc-based DOSXYZnrc code was used to calculate the dose in the region of interest. Interpolation of depth dose curves of pre-set energies was proposed as a preliminary step for optimal energy fit. A good approach for determination of the optimal mean energy is the difference comparison of the PDD curves excluding buildup region, and using D(10) as a normalization method. For FWHM fitting, due to electron disequilibrium and the larger statistical uncertainty, using horn or/and penumbra regions will give inconsistent outcomes at various depths. Difference comparisons should be performed in the flat regions of the off-axis dose profiles at various depths to optimize the FWHM parameter.
Jevtić, Aleksandar; Gutiérrez, Alvaro
2011-01-01
Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the distributed bees algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA's control parameters by means of a genetic algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots' distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677
Optimization of kinetic parameters for the degradation of plasmid DNA in rat plasma
NASA Astrophysics Data System (ADS)
Chaudhry, Q. A.
2014-12-01
Biotechnology is a rapidly growing area of research work in the field of pharmaceutical sciences. The study of pharmacokinetics of plasmid DNA (pDNA) is an important area of research work. It has been observed that the process of gene delivery faces many troubles on the transport of pDNA towards their target sites. The topoforms of pDNA has been termed as super coiled (S-C), open circular (O-C) and linear (L), the kinetic model of which will be presented in this paper. The kinetic model gives rise to system of ordinary differential equations (ODEs), the exact solution of which has been found. The kinetic parameters, which are responsible for the degradation of super coiled, and the formation of open circular and linear topoforms have a great significance not only in vitro but for modeling of further processes as well, therefore need to be addressed in great detail. For this purpose, global optimization techniques have been adopted, thus finding the optimal results for the said model. The results of the model, while using the optimal parameters, were compared against the measured data, which gives a nice agreement.
Optimizing gravitational-wave searches for a population of coalescing binaries: Intrinsic parameters
NASA Astrophysics Data System (ADS)
Dent, T.; Veitch, J.
2014-03-01
We revisit the problem of searching for gravitational waves from inspiralling compact binaries in Gaussian colored noise. If the intrinsic parameters of a quasicircular, nonprecessing binary are known, then the optimal statistic for detecting the dominant mode signal in a single interferometer is given by the well-known two-phase matched filter. However, the matched filter signal-to-noise ratio (SNR) is not in general an optimal statistic for an astrophysical population of signals, since their distribution over the intrinsic parameters will almost certainly not mirror that of noise events, which is determined by the (Fisher) information metric. Instead, the optimal statistic for a given astrophysical distribution will be the Bayes factor, which we approximate using the output of a standard template matched filter search. We then quantify the improvement in number of signals detected for various populations of nonspinning binaries: for a distribution of signals uniformly distributed in volume and with component masses distributed uniformly over the range 1≤m1,2/M⊙≤24, (m1+m2)/M⊙≤25 at fixed expected SNR, we find ≳20% more signals at a false alarm threshold of 10-6 Hz in a single detector. The method may easily be generalized to binaries with nonprecessing spins.
NASA Astrophysics Data System (ADS)
Gong, Wei; Duan, Qingyun; Li, Jianduo; Wang, Chen; Di, Zhenhua; Ye, Aizhong; Miao, Chiyuan; Dai, Yongjiu
2016-03-01
Parameter specification is an important source of uncertainty in large, complex geophysical models. These models generally have multiple model outputs that require multiobjective optimization algorithms. Although such algorithms have long been available, they usually require a large number of model runs and are therefore computationally expensive for large, complex dynamic models. In this paper, a multiobjective adaptive surrogate modeling-based optimization (MO-ASMO) algorithm is introduced that aims to reduce computational cost while maintaining optimization effectiveness. Geophysical dynamic models usually have a prior parameterization scheme derived from the physical processes involved, and our goal is to improve all of the objectives by parameter calibration. In this study, we developed a method for directing the search processes toward the region that can improve all of the objectives simultaneously. We tested the MO-ASMO algorithm against NSGA-II and SUMO with 13 test functions and a land surface model - the Common Land Model (CoLM). The results demonstrated the effectiveness and efficiency of MO-ASMO.
Optimal likelihood-based matching of volcanic sources and deposits in the Auckland Volcanic Field
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Caglar, Yasemin; Gorgun, Kamuran; Aksoy, Seval
2015-03-01
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.
NASA Astrophysics Data System (ADS)
Kler, A. M.; Zakharov, Yu. B.; Potanina, Yu. M.
2014-06-01
In the present paper, we evaluate the effectiveness of the coordinated solution to the optimization problem for the parameters of cycles in gas turbine and combined cycle power plants and to the optimization problem for the gas-turbine flow path parameters within an integral complex problem. We report comparative data for optimizations of the combined cycle power plant at coordinated and separate optimizations, when, first, the gas turbine and, then, the steam part of a combined cycle plant is optimized. The comparative data are presented in terms of economic indicators, energy-effectiveness characteristics, and specific costs. Models that were used in the present study for calculating the flow path enable taking into account, as a factor influencing the economic and energy effectiveness of the power plant, the heat stability of alloys from which the nozzle and rotor blades of gas-turbine stages are made.
Madgulkar, A.; Kadam, S.; Pokharkar, V.
2009-01-01
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. PMID:20490296
Raj, A. Moses Ezhil; Ravidhas, C.; Ravishankar, R.; Kumar, A. Rathish; Selvan, G.; Jayachandran, M.; Sanjeeviraja, C.
2009-05-06
Transparent conducting magnesium indium oxide films (MgIn{sub 2}O{sub 4}) were deposited on to quartz substrates without a buffer layer at an optimized deposition temperature of 450 deg. C to achieve high transmittance in the visible spectral range and electrical conductivity in the low temperature region. Magnesium ions are distributed over the tetrahedral and octahedral sites of the inverted spinel structure with preferential orientation along (3 1 1) Miller plane. The possible mechanism that promotes conductivity in this system is the charge transfer between the resident divalent (Mg{sup 2+}) and trivalent (In{sup 3+}) cations in addition to the available oxygen vacancies in the lattice. A room temperature electrical conductivity of 1.5 x 10{sup -5} S cm{sup -1} and an average transmittance >75% have been achieved. Hall measurements showed n-type conductivity with electron mobility value 0.95 x 10{sup -2} cm{sup 2} V{sup -1} s{sup -1} and carrier concentration 2.7 x 10{sup 19} cm{sup -3}. Smoothness of the film surface observed through atomic force microscope measurements favors this material for gas sensing and opto-electronic device development.
Madgulkar, A; Kadam, S; Pokharkar, V
2009-05-01
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. PMID:20490296
Optimization of ion-atomic beam source for deposition of GaN ultrathin films
Mach, Jindřich Kolíbal, Miroslav; Zlámal, Jakub; Voborny, Stanislav; Bartošík, Miroslav; Šikola, Tomáš; Šamořil, Tomáš
2014-08-15
We describe the optimization and application of an ion-atomic beam source for ion-beam-assisted deposition of ultrathin films in ultrahigh vacuum. The device combines an effusion cell and electron-impact ion beam source to produce ultra-low energy (20–200 eV) ion beams and thermal atomic beams simultaneously. The source was equipped with a focusing system of electrostatic electrodes increasing the maximum nitrogen ion current density in the beam of a diameter of ≈15 mm by one order of magnitude (j ≈ 1000 nA/cm{sup 2}). Hence, a successful growth of GaN ultrathin films on Si(111) 7 × 7 substrate surfaces at reasonable times and temperatures significantly lower (RT, 300 °C) than in conventional metalorganic chemical vapor deposition technologies (≈1000 °C) was achieved. The chemical composition of these films was characterized in situ by X-ray Photoelectron Spectroscopy and morphology ex situ using Scanning Electron Microscopy. It has been shown that the morphology of GaN layers strongly depends on the relative Ga-N bond concentration in the layers.
NASA Astrophysics Data System (ADS)
Robertson Cleveland, Erin Darcy
Conformal coatings are becoming increasingly important as technology heads towards the nanoscale. The exceptional thickness control (atomic scale) and conformality (uniformity over nanoscale 3D features) of atomic layer deposition (ALD) has made it the process of choice for numerous applications found in microelectronics and nanotechnology with a wide variety of ALD processes and resulting materials. While its benefits derive from self-limited saturating surface reactions of alternating gas precursors, process optimization for ALD conformality is often difficult as process parameters, such as dosage, purge, temperature and pressure are often interdependent with one another, especially within the confines of an ultra-high aspect ratio nanopore. Therefore, processes must be optimized to achieve self-limiting saturated surfaces and avoid parasitic CVD-like reactions in order to maintain thickness control and achieve uniformity and conformality at the atomic level while preserving the desired materials' properties (electrical, optical, compositional, etc.). This work investigates novel approaches to optimize ALD conformality when transitioning from a 2D planar system to a 3D ultra-high aspect ratio nanopore in the context of a cross-flow wafer-scale reactor used to highlight deviations from ideal ALD behavior. Porous anodic alumina (PAA) is used as a versatile platform to analyze TiO2 ALD profiles via ex-situ SEM, EDS and TEM. Results of TiO2 ALD illustrate enhanced growth rates that can occur when the precursors titanium tetraisopropoxide and ozone were used at minimal saturation doses for ALD and for considerably higher doses. The results also demonstrate that ALD process recipes that achieve excellent across-wafer uniformity across full 100 mm wafers do not produce conformal films in ultra-high aspect ratio nanopores. The results further demonstrate that conformality is determined by precursor dose, surface residence time, and purge time, creating large depletion
NASA Astrophysics Data System (ADS)
Sif Gylfadóttir, Sigríður; Kim, Jihwan; Kristinn Helgason, Jón; Brynjólfsson, Sveinn; Höskuldsson, Ármann; Jóhannesson, Tómas; Bonnevie Harbitz, Carl; Løvholt, Finn
2016-04-01
The Askja central volcano is located in the Northern Volcanic Zone of Iceland. Within the main caldera an inner caldera was formed in an eruption in 1875 and over the next 40 years it gradually subsided and filled up with water, forming Lake Askja. A large rockslide was released from the Southeast margin of the inner caldera into Lake Askja on 21 July 2014. The release zone was located from 150 m to 350 m above the water level and measured 800 m across. The volume of the rockslide is estimated to have been 15-30 million m3, of which 10.5 million m3 was deposited in the lake, raising the water level by almost a meter. The rockslide caused a large tsunami that traveled across the lake, and inundated the shores around the entire lake after 1-2 minutes. The vertical run-up varied typically between 10-40 m, but in some locations close to the impact area it ranged up to 70 m. Lake Askja is a popular destination visited by tens of thousands of tourists every year but as luck would have it, the event occurred near midnight when no one was in the area. Field surveys conducted in the months following the event resulted in an extensive dataset. The dataset contains e.g. maximum inundation, high-resolution digital elevation model of the entire inner caldera, as well as a high resolution bathymetry of the lake displaying the landslide deposits. Using these data, a numerical model of the Lake Askja landslide and tsunami was developed using GeoClaw, a software package for numerical analysis of geophysical flow problems. Both the shallow water version and an extension of GeoClaw that includes dispersion, was employed to simulate the wave generation, propagation, and run-up due to the rockslide plunging into the lake. The rockslide was modeled as a block that was allowed to stretch during run-out after entering the lake. An optimization approach was adopted to constrain the landslide parameters through inverse modeling by comparing the calculated inundation with the observed run
NASA Astrophysics Data System (ADS)
Spooner, Greg J. R.; Marre, Gabrielle; Miller, Doug L.; Williams, A. R.
2000-06-01
Laser induced optical breakdown (LIOB) in fluids produces a localized plasma, an expanding radial shock wave front, heat transfer from the plasma to the fluid, and the formation of cavitation bubbles. Collectively these phenomena are referred to as photodisruption. Subjecting photodisruptively produced cavitation bubble nuclei to an ultrasonic field can result in strong cavitation and local cellular destruction. The ability of ultrafast lasers to produce spatially localized photodisruptions with microJoule pulse energies in combination with the possibility of larger scale tissue destruction using ultrasound presents an attractive and novel technique for selective and non-invasive tissue modification, referred to as photodisruptively nucleated ultrasonic cavitation (PNUC). Optimization of PNUC parameters in a confocal laser and ultrasound geometry is presented. The cavitation signal as measured with an ultrasound receiver was maximized to determine optimal laser and ultrasound spatial overlap in water. A flow chamber was used to evaluate the effect of the laser and ultrasound parameters on the lysis of whole canine red blood cells in saline. Parameters evaluated included laser pulse energy and ultrasound pressure amplitude.
Bauri, Ranjit; Yadav, Devinder; Shyam Kumar, C N; Janaki Ram, G D
2015-12-01
Metal matrix composites (MMCs) exhibit improved strength but suffer from low ductility. Metal particles reinforcement can be an alternative to retain the ductility in MMCs (Bauri and Yadav, 2010; Thakur and Gupta, 2007) [1,2]. However, processing such composites by conventional routes is difficult. The data presented here relates to friction stir processing (FSP) that was used to process metal particles reinforced aluminum matrix composites. The data is the processing parameters, rotation and traverse speeds, which were optimized to incorporate Ni particles. A wide range of parameters covering tool rotation speeds from 1000 rpm to 1800 rpm and a range of traverse speeds from 6 mm/min to 24 mm/min were explored in order to get a defect free stir zone and uniform distribution of particles. The right combination of rotation and traverse speed was found from these experiments. Both as-received coarse particles (70 μm) and ball-milled finer particles (10 μm) were incorporated in the Al matrix using the optimized parameters. PMID:26566541
NASA Astrophysics Data System (ADS)
Garland, Joshua; James, Ryan G.; Bradley, Elizabeth
2016-02-01
Delay-coordinate reconstruction is a proven modeling strategy for building effective forecasts of nonlinear time series. The first step in this process is the estimation of good values for two parameters, the time delay and the embedding dimension. Many heuristics and strategies have been proposed in the literature for estimating these values. Few, if any, of these methods were developed with forecasting in mind, however, and their results are not optimal for that purpose. Even so, these heuristics—intended for other applications—are routinely used when building delay coordinate reconstruction-based forecast models. In this paper, we propose an alternate strategy for choosing optimal parameter values for forecast methods that are based on delay-coordinate reconstructions. The basic calculation involves maximizing the shared information between each delay vector and the future state of the system. We illustrate the effectiveness of this method on several synthetic and experimental systems, showing that this metric can be calculated quickly and reliably from a relatively short time series, and that it provides a direct indication of how well a near-neighbor based forecasting method will work on a given delay reconstruction of that time series. This allows a practitioner to choose reconstruction parameters that avoid any pathologies, regardless of the underlying mechanism, and maximize the predictive information contained in the reconstruction.
Bauri, Ranjit; Yadav, Devinder; Shyam Kumar, C.N.; Janaki Ram, G.D.
2015-01-01
Metal matrix composites (MMCs) exhibit improved strength but suffer from low ductility. Metal particles reinforcement can be an alternative to retain the ductility in MMCs (Bauri and Yadav, 2010; Thakur and Gupta, 2007) [1,2]. However, processing such composites by conventional routes is difficult. The data presented here relates to friction stir processing (FSP) that was used to process metal particles reinforced aluminum matrix composites. The data is the processing parameters, rotation and traverse speeds, which were optimized to incorporate Ni particles. A wide range of parameters covering tool rotation speeds from 1000 rpm to 1800 rpm and a range of traverse speeds from 6 mm/min to 24 mm/min were explored in order to get a defect free stir zone and uniform distribution of particles. The right combination of rotation and traverse speed was found from these experiments. Both as-received coarse particles (70 μm) and ball-milled finer particles (10 μm) were incorporated in the Al matrix using the optimized parameters. PMID:26566541
Inverse Thermal Analysis of Welds Using Multiple Constraints and Relaxed Parameter Optimization
NASA Astrophysics Data System (ADS)
Lambrakos, S. G.
2015-08-01
Aspects of a methodology for inverse thermal analysis of welds are examined that provide for relaxed model-parameter optimization. These aspects are associated with the inherent insensitivity of temperature fields, obtained by inverse analysis, to local shape variations of constrained boundaries within these fields. The inverse analysis methodology is in terms of numerical-analytical basis functions for construction parametric temperature histories, which can be adopted as input data to computational procedures for further analysis. In addition, these parametric temperature histories can be used for inverse thermal analysis of welds corresponding to other process parameters or welding processes whose process conditions are within similar regimes. The inverse thermal analysis procedure provides for the inclusion of volumetric constraint conditions whose two-dimensional projections are mappings onto transverse cross sections of experimentally measured boundary conditions, such as solidification and transformation boundaries, and isothermal surfaces associated with thermocouple measurements. Issues concerning relaxed parameter optimization are discussed with respect to inverse thermal analysis of Ti-6Al-4V pulsed-mode laser welds using multiple constraint conditions.
Optimization of intermolecular potential parameters for the CO2/H2O mixture.
Orozco, Gustavo A; Economou, Ioannis G; Panagiotopoulos, Athanassios Z
2014-10-01
Monte Carlo simulations in the Gibbs ensemble were used to obtain optimized intermolecular potential parameters to describe the phase behavior of the mixture CO2/H2O, over a range of temperatures and pressures relevant for carbon capture and sequestration processes. Commonly used fixed-point-charge force fields that include Lennard-Jones 12-6 (LJ) or exponential-6 (Exp-6) terms were used to describe CO2 and H2O intermolecular interactions. For force fields based on the LJ functional form, changes of the unlike interactions produced higher variations in the H2O-rich phase than in the CO2-rich phase. A major finding of the present study is that for these potentials, no combination of unlike interaction parameters is able to adequately represent properties of both phases. Changes to the partial charges of H2O were found to produce significant variations in both phases and are able to fit experimental data in both phases, at the cost of inaccuracies for the pure H2O properties. By contrast, for the Exp-6 case, optimization of a single parameter, the oxygen-oxygen unlike-pair interaction, was found sufficient to give accurate predictions of the solubilities in both phases while preserving accuracy in the pure component properties. These models are thus recommended for future molecular simulation studies of CO2/H2O mixtures. PMID:25198539
Garland, Joshua; James, Ryan G; Bradley, Elizabeth
2016-02-01
Delay-coordinate reconstruction is a proven modeling strategy for building effective forecasts of nonlinear time series. The first step in this process is the estimation of good values for two parameters, the time delay and the embedding dimension. Many heuristics and strategies have been proposed in the literature for estimating these values. Few, if any, of these methods were developed with forecasting in mind, however, and their results are not optimal for that purpose. Even so, these heuristics-intended for other applications-are routinely used when building delay coordinate reconstruction-based forecast models. In this paper, we propose an alternate strategy for choosing optimal parameter values for forecast methods that are based on delay-coordinate reconstructions. The basic calculation involves maximizing the shared information between each delay vector and the future state of the system. We illustrate the effectiveness of this method on several synthetic and experimental systems, showing that this metric can be calculated quickly and reliably from a relatively short time series, and that it provides a direct indication of how well a near-neighbor based forecasting method will work on a given delay reconstruction of that time series. This allows a practitioner to choose reconstruction parameters that avoid any pathologies, regardless of the underlying mechanism, and maximize the predictive information contained in the reconstruction. PMID:26986345
A self-adaptive parameter optimization algorithm in a real-time parallel image processing system.
Li, Ge; Zhang, Xuehe; Zhao, Jie; Zhang, Hongli; Ye, Jianwei; Zhang, Weizhe
2013-01-01
Aiming at the stalemate that precision, speed, robustness, and other parameters constrain each other in the parallel processed vision servo system, this paper proposed an adaptive load capacity balance strategy on the servo parameters optimization algorithm (ALBPO) to improve the computing precision and to achieve high detection ratio while not reducing the servo circle. We use load capacity functions (LC) to estimate the load for each processor and then make continuous self-adaptation towards a balanced status based on the fluctuated LC results; meanwhile, we pick up a proper set of target detection and location parameters according to the results of LC. Compared with current load balance algorithm, the algorithm proposed in this paper is proceeded under an unknown informed status about the maximum load and the current load of the processors, which means it has great extensibility. Simulation results showed that the ALBPO algorithm has great merits on load balance performance, realizing the optimization of QoS for each processor, fulfilling the balance requirements of servo circle, precision, and robustness of the parallel processed vision servo system. PMID:24174920
NASA Astrophysics Data System (ADS)
Maheshwari, Arpit; Dumitrescu, Mihaela Aneta; Destro, Matteo; Santarelli, Massimo
2016-03-01
Battery models are riddled with incongruous values of parameters considered for validation. In this work, thermally coupled electrochemical model of the pouch is developed and discharge tests on a LiFePO4 pouch cell at different discharge rates are used to optimize the LiFePO4 battery model by determining parameters for which there is no consensus in literature. A discussion on parameter determination, selection and comparison with literature values has been made. The electrochemical model is a P2D model, while the thermal model considers heat transfer in 3D. It is seen that even with no phase change considered for LiFePO4 electrode, the model is able to simulate the discharge curves over a wide range of discharge rates with a single set of parameters provided a dependency of the radius of the LiFePO4 electrode on discharge rate. The approach of using a current dependent radius is shown to be equivalent to using a current dependent diffusion coefficient. Both these modelling approaches are a representation of the particle size distribution in the electrode. Additionally, the model has been thermally validated, which increases the confidence level in the selection of values of parameters.
Celik, Azim
2016-01-01
PURPOSE We aimed to investigate the effect of key imaging parameters on the accuracy of apparent diffusion coefficient (ADC) maps using a phantom model combined with ADC calculation simulation and propose strategies to improve the accuracy of ADC quantification. METHODS Diffusion-weighted imaging (DWI) sequences were acquired on a phantom model using single-shot echo-planar imaging DWI at 1.5 T scanner by varying key imaging parameters including number of averages (NEX), repetition time (TR), echo time (TE), and diffusion preparation pulses. DWI signal simulations were performed for varying TR and TE. RESULTS Magnetic resonance diffusion signal and ADC maps were dependent on TR and TE imaging parameters as well as number of diffusion preparation pulses, but not on the NEX. However, the choice of a long TR and short TE could be used to minimize their effects on the resulting DWI sequences and ADC maps. CONCLUSION This study shows that TR and TE imaging parameters affect the diffusion images and ADC maps, but their effect can be minimized by utilizing diffusion preparation pulses. Another key imaging parameter, NEX, is less relevant to DWI and ADC quantification as long as DWI signal-to-noise ratio is above a certain level. Based on the phantom results and data simulations, DWI acquisition protocol can be optimized to obtain accurate ADC maps in routine clinical application for whole body imaging. PMID:26573977
Alshetaili, Abdullah S; Almutairy, Bjad K; Alshahrani, Saad M; Ashour, Eman A; Tiwari, Roshan V; Alshehri, Sultan M; Feng, Xin; Alsulays, Bader B; Majumdar, Soumyajit; Langley, Nigel; Kolter, Karl; Gryczke, Andreas; Martin, Scott T; Repka, Michael A
2016-11-01
The aim of this study was to formulate face-cut, melt-extruded pellets, and to optimize hot melt process parameters to obtain maximized sphericity and hardness by utilizing Soluplus(®) as a polymeric carrier and carbamazepine (CBZ) as a model drug. Thermal gravimetric analysis (TGA) was used to detect thermal stability of CBZ. The Box-Behnken design for response surface methodology was developed using three factors, processing temperature ( °C), feeding rate (%), and screw speed (rpm), which resulted in 17 experimental runs. The influence of these factors on pellet sphericity and mechanical characteristics was assessed and evaluated for each experimental run. Pellets with optimal sphericity and mechanical properties were chosen for further characterization. This included differential scanning calorimetry, drug release, hardness friability index (HFI), flowability, bulk density, tapped density, Carr's index, and fourier transform infrared radiation (FTIR) spectroscopy. TGA data showed no drug degradation upon heating to 190 °C. Hot melt extrusion processing conditions were found to have a significant effect on the pellet shape and hardness profile. Pellets with maximum sphericity and hardness exhibited no crystalline peak after extrusion. The rate of drug release was affected mainly by pellet size, where smaller pellets released the drug faster. All optimized formulations were found to be of superior hardness and not friable. The flow properties of optimized pellets were excellent with high bulk and tapped density. PMID:27080252
NASA Astrophysics Data System (ADS)
Andronico, Daniele; Scollo, Simona; Cristaldi, Antonio; Lo Castro, Maria Deborah
2014-10-01
The Southeast Crater (SEC) of Mt. Etna, Italy, is renowned for its high activity, mainly long-lived eruptions consisting of sequences of individual paroxysmal episodes which have produced more than 150 eruptive events since 1998. Each episode typically forms eruption columns followed by tephra fallout over distances of up to about 100 km from the vent. One of the last sequences consisted of 25 lava fountaining events, which took place between January 2011 and April 2012 from a pit-vent on the eastern flank of the SEC and built a new scoria cone renamed New Southeast Crater. The first episode on 12-13 January 2011 produced tephra fallout which was unusually dispersed toward to the South extending out over the Mediterranean Sea. The southerly deposition of tephra permitted an extensive survey at distances between ~1 and ~100 km, providing an excellent characterization of the tephra deposit. Here, we document the stratigraphy of the 12-13 January fallout deposit, draw its dispersal, and reconstruct its isopleth map. These data are then used to estimate the main eruption source parameters. The total erupted mass (TEM) was calculated by using four different methodologies which give a mean value of 1.5 ± 0.4 × 108 kg. The mass eruption rate (MER) is 2.5 ± 0.7 × 104 kg/s using eruption duration of 100 min. The total grain-size (TGS) distribution, peaked at -3 phi, ranges between -5 and 5 phi and has a median value of -1.4 phi. Further, for the eruption column height, we obtained respective values of 6.8-13.8 km by using the method of Carey and Sparks (1986) and 3.4 ± 0.3 km by using the methods of Wilson and Walker 1987), Mastin et al. (2009), and Pistolesi et al. (2011) and considering the mean value of MER from the deposit. We also evaluated the uncertainty and reliability of TEM and TGS for scenarios where the proximal and distal samples are not obtainable. This is achieved by only using a sector spanning the downwind distances between 6 and 23 km. This scenario
Using support vector machine and dynamic parameter encoding to enhance global optimization
NASA Astrophysics Data System (ADS)
Zheng, Z.; Chen, X.; Liu, C.; Huang, K.
2016-05-01
This study presents an approach which combines support vector machine (SVM) and dynamic parameter encoding (DPE) to enhance the run-time performance of global optimization with time-consuming fitness function evaluations. SVMs are used as surrogate models to partly substitute for fitness evaluations. To reduce the computation time and guarantee correct convergence, this work proposes a novel strategy to adaptively adjust the number of fitness evaluations needed according to the approximate error of the surrogate model. Meanwhile, DPE is employed to compress the solution space, so that it not only accelerates the convergence but also decreases the approximate error. Numerical results of optimizing a few benchmark functions and an antenna in a practical application are presented, which verify the feasibility, efficiency and robustness of the proposed approach.
Optimizing treatment parameters for the vascular malformations using 1064-nm Nd:YAG laser
NASA Astrophysics Data System (ADS)
Gong, Wei; Lin, He; Xie, Shusen
2010-02-01
Near infrared Nd:YAG pulsed laser treatment had been proved to be an efficient method to treat large-sized vascular malformations like leg telangiectasia for deep penetrating depth into skin and uniform light distribution in vessel. However, optimal clinical outcome was achieved by various laser irradiation parameters and the key factor governing the treatment efficacy was still unclear. A mathematical model in combination with Monte Carlo algorithm and finite difference method was developed to estimate the light distribution, temperature profile and thermal damage in epidermis, dermis and vessel during and after 1064 nm pulsed Nd:YAG laser irradiation. Simulation results showed that epidermal protection could be achieved during 1064 nm Nd:YAG pulsed laser irradiation in conjunction with cryogen spray cooling. However, optimal vessel closure and blood coagulation depend on a compromise between laser spot size and pulse duration.
NASA Astrophysics Data System (ADS)
Tinne, N.; Kaune, B.; Bleeker, S.; Lubatschowski, H.; Krüger, A.; Ripken, T.
2014-02-01
The immediate pulse-to-pulse interaction becomes more and more important for future-generation high-repetition rate ophthalmic laser systems. Therefore, we investigated the interaction of two laser pulses with different spatial and temporal separation by time-resolved photography. There are various different characteristic interaction mechanisms which are divided into 11 interaction scenarios. Furthermore, the parameter range has been constricted regarding the medical application; here, the efficiency was optimized to a maximum jet velocity along the scanning axis with minimum applied pulse energy as well as unwanted side effects at the same time. In conclusion, these results are of great interest for the prospective optimization of the ophthalmic surgical process with future-generation fs-lasers.
NASA Technical Reports Server (NTRS)
Seidel, R. C.; Lehtinen, B.
1974-01-01
A technique is described for designing feedback control systems using frequency domain models, a quadratic cost function, and a parameter optimization computer program. FORTRAN listings for the computer program are included. The approach is applied to the design of shock position controllers for a supersonic inlet. Deterministic or random system disturbances, and the presence of random measurement noise are considered. The cost function minimization is formulated in the time domain, but the problem solution is obtained using a frequency domain system description. A scaled and constrained conjugate gradient algorithm is used for the minimization. The approach to a supersonic inlet included the calculations of the optimal proportional-plus integral (PI) and proportional-plus-integral-plus-derivative controllers. A single-loop PI controller was the most desirable of the designs considered.
NASA Technical Reports Server (NTRS)
Bernstein, Dennis S.; Rosen, I. G.
1988-01-01
In controlling distributed parameter systems it is often desirable to obtain low-order, finite-dimensional controllers in order to minimize real-time computational requirements. Standard approaches to this problem employ model/controller reduction techniques in conjunction with LQG theory. In this paper we consider the finite-dimensional approximation of the infinite-dimensional Bernstein/Hyland optimal projection theory. This approach yields fixed-finite-order controllers which are optimal with respect to high-order, approximating, finite-dimensional plant models. The technique is illustrated by computing a sequence of first-order controllers for one-dimensional, single-input/single-output, parabolic (heat/diffusion) and hereditary systems using spline-based, Ritz-Galerkin, finite element approximation. Numerical studies indicate convergence of the feedback gains with less than 2 percent performance degradation over full-order LQG controllers for the parabolic system and 10 percent degradation for the hereditary system.
Jain, S C; Miller, J R
1976-04-01
A method, using an optimization scheme, has been developed for the interpretation of spectral albedo (or spectral reflectance) curves obtained from remotely sensed water color data. This method used a two-flow model of the radiation flow and solves for the albedo. Optimization fitting of predicted to observed reflectance data is performed by a quadratic interpolation method for the variables chlorophyll concentration and scattering coefficient. The technique is applied to airborne water color data obtained from Kawartha Lakes, Sargasso Sea, and Nova Scotia coast. The modeled spectral albedo curves are compared to those obtained experimentally, and the computed optimum water parameters are compared to ground truth values. It is shown that the backscattered spectral signal contains information that can be interpreted to give quantitative estimates of the chlorophyll concentration and turbidity in the waters studied. PMID:20165093
Yang, Jie; Yang, Xiaodan; Ye, Xiuyun; Lin, Juan
2016-06-01
The data presented in this article are related to the research article entitled "Destaining of Coomassie Brilliant Blue R-250-stained polyacrylamide gels with fungal laccase" [1]. Laccase is a class of multicopper oxidases that can catalyze oxidation of recalcitrant dyestuffs. This article describes optimal parameters for destaining of polyacrylamide gels, stained with Coomassie Brilliant Blue R-250, with laccase from basidiomycete Cerrena sp. strain HYB07. Effects of laccase activity, mediator type and concentration, temperature and time on destaining of polyacrylamide gels were evaluated with respect to gel background intensity and protein band signals, and the optimal destaining effects were obtained with 15 U mL(-1) laccase and 2 μM ABTS at 37 °C after 2 h. PMID:26955647
Studies of Discharge Parameters Influence on the IPD Plasma Deposition Process
NASA Astrophysics Data System (ADS)
Rabiński, Marek; Zdunek, Krzysztof
2006-01-01
The paper presents recent studies of a current sheet dynamics influence on the surface engineering process of impulse plasma deposition (IPD). During the IPD process plasma is generated in the working gas due to a high-voltage high-current oscillating pulse discharge, ignited within an interelectrode region of a coaxial accelerator. The changes of plasma dynamics and generation mechanisms, e.g. the electric arc instead of the plasma sheet formation during the consecutive half-periods of discharge, cause the different deposition efficiency for accelerator with the outer electrode system composed of stainless steel rods instead of standard tubular one. The coating efficiency and deposited layer quality have been examined for the titanium nitride as the model material for surface engineering.
NASA Technical Reports Server (NTRS)
Sager, B.; Benson, P.; Jahoda, K.; Jacobs, J. R.; Bloch, J. J.
1986-01-01
Multilayer W-C diffraction gratings with nominal d spacings of 35 A have been fabricated by magnetron sputter deposition. The peak and integrated reflectivities of these films have been measured with Al K-alpha X-rays and compared to theoretical values. The rms surface roughness has been evaluated. The influence of several sputtering-system process parameters on the reflectivities has been investigated.
NASA Technical Reports Server (NTRS)
Pindera, Marek-Jerzy; Salzar, Robert S.
1996-01-01
The objective of this work was the development of efficient, user-friendly computer codes for optimizing fabrication-induced residual stresses in metal matrix composites through the use of homogeneous and heterogeneous interfacial layer architectures and processing parameter variation. To satisfy this objective, three major computer codes have been developed and delivered to the NASA-Lewis Research Center, namely MCCM, OPTCOMP, and OPTCOMP2. MCCM is a general research-oriented code for investigating the effects of microstructural details, such as layered morphology of SCS-6 SiC fibers and multiple homogeneous interfacial layers, on the inelastic response of unidirectional metal matrix composites under axisymmetric thermomechanical loading. OPTCOMP and OPTCOMP2 combine the major analysis module resident in MCCM with a commercially-available optimization algorithm and are driven by user-friendly interfaces which facilitate input data construction and program execution. OPTCOMP enables the user to identify those dimensions, geometric arrangements and thermoelastoplastic properties of homogeneous interfacial layers that minimize thermal residual stresses for the specified set of constraints. OPTCOMP2 provides additional flexibility in the residual stress optimization through variation of the processing parameters (time, temperature, external pressure and axial load) as well as the microstructure of the interfacial region which is treated as a heterogeneous two-phase composite. Overviews of the capabilities of these codes are provided together with a summary of results that addresses the effects of various microstructural details of the fiber, interfacial layers and matrix region on the optimization of fabrication-induced residual stresses in metal matrix composites.
Ju, Jonghyun; Han, Yun-ah; Kim, Seok-min
2013-01-01
The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC) label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV), full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1) the PWV can be measured by the reflection peak measurement instruments, (2) the grating pitch and duty can be manufactured using conventional lithography systems, and (3) the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU-1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm. PMID:23470487
Torres‐Acosta, Mario A.; Aguilar‐Yañez, Jose M.; Rito‐Palomares, Marco
2015-01-01
Royalactin is a protein with several different potential uses in humans. Research, in insects and in mammalian cells, has shown that it can accelerate cell division and prevent apoptosis. The method of action is through the use of the epidermal growth factor receptor, which is present in humans. Potential use in humans could be to lower cholesterolemic levels in blood, and to elicit similar effects to those seen in bees, e.g., increased lifespan. Mass production of Royalactin has not been accomplished, though a recent article presented a Pichia pastoris fermentation and recovery by aqueous two‐phase systems at laboratory scale as a possible basis for production. Economic modelling is a useful tool with which compare possible outcomes for the production of such a molecule and in particular, to locate areas where additional research is needed and optimization may be required. This study uses the BioSolve software to perform an economic analysis on the scale‐up of the putative process for Royalactin. The key parameters affecting the cost of production were located via a sensitivity analysis and then evaluated by Monte Carlo analysis. Results show that if titer is not optimized the strategy to maintain a low cost of goods is process oriented. After optimization of this parameter the strategy changes to a product‐oriented and the target output becomes the critical parameter determining the cost of goods. This study serves to provide a framework for the evaluation of strategies for future production of Royalactin, by analyzing the factors that influence its cost of manufacture. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:744–749, 2015 PMID:25737309
NASA Astrophysics Data System (ADS)
Cheng, Lishui; Hobbs, Robert F.; Segars, Paul W.; Sgouros, George; Frey, Eric C.
2013-06-01
smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.
Cheng, Lishui; Hobbs, Robert F; Segars, Paul W; Sgouros, George; Frey, Eric C
2013-06-01
smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms. PMID:23648371
The impact of different dose response parameters on biologically optimized IMRT in breast cancer
NASA Astrophysics Data System (ADS)
Costa Ferreira, Brigida; Mavroidis, Panayiotis; Adamus-Górka, Magdalena; Svensson, Roger; Lind, Bengt K.
2008-05-01
The full potential of biologically optimized radiation therapy can only be maximized with the prediction of individual patient radiosensitivity prior to treatment. Unfortunately, the available biological parameters, derived from clinical trials, reflect an average radiosensitivity of the examined populations. In the present study, a breast cancer patient of stage I II with positive lymph nodes was chosen in order to analyse the effect of the variation of individual radiosensitivity on the optimal dose distribution. Thus, deviations from the average biological parameters, describing tumour, heart and lung response, were introduced covering the range of patient radiosensitivity reported in the literature. Two treatment configurations of three and seven biologically optimized intensity-modulated beams were employed. The different dose distributions were analysed using biological and physical parameters such as the complication-free tumour control probability (P+), the biologically effective uniform dose (\\bar{\\bar{D}} ), dose volume histograms, mean doses, standard deviations, maximum and minimum doses. In the three-beam plan, the difference in P+ between the optimal dose distribution (when the individual patient radiosensitivity is known) and the reference dose distribution, which is optimal for the average patient biology, ranges up to 13.9% when varying the radiosensitivity of the target volume, up to 0.9% when varying the radiosensitivity of the heart and up to 1.3% when varying the radiosensitivity of the lung. Similarly, in the seven-beam plan, the differences in P+ are up to 13.1% for the target, up to 1.6% for the heart and up to 0.9% for the left lung. When the radiosensitivity of the most important tissues in breast cancer radiation therapy was simultaneously changed, the maximum gain in outcome was as high as 7.7%. The impact of the dose response uncertainties on the treatment outcome was clinically insignificant for the majority of the simulated patients
NASA Astrophysics Data System (ADS)
Mehedi, H.-A.; Baudrillart, B.; Alloyeau, D.; Mouhoub, O.; Ricolleau, C.; Pham, V. D.; Chacon, C.; Gicquel, A.; Lagoute, J.; Farhat, S.
2016-08-01
This article describes the significant roles of process parameters in the deposition of graphene films via cobalt-catalyzed decomposition of methane diluted in hydrogen using plasma-enhanced chemical vapor deposition (PECVD). The influence of growth temperature (700-850 °C), molar concentration of methane (2%-20%), growth time (30-90 s), and microwave power (300-400 W) on graphene thickness and defect density is investigated using Taguchi method which enables reaching the optimal parameter settings by performing reduced number of experiments. Growth temperature is found to be the most influential parameter in minimizing the number of graphene layers, whereas microwave power has the second largest effect on crystalline quality and minor role on thickness of graphene films. The structural properties of PECVD graphene obtained with optimized synthesis conditions are investigated with Raman spectroscopy and corroborated with atomic-scale characterization performed by high-resolution transmission electron microscopy and scanning tunneling microscopy, which reveals formation of continuous film consisting of 2-7 high quality graphene layers.
Near minimum-time maneuvers of large space structures using parameter optimization
NASA Technical Reports Server (NTRS)
Carter, M. T.; Vadali, S. R.; Singh, T.
1993-01-01
Near minimum-time attitude maneuvers for large, inherently-flexible space structures with finite fuel supplies are investigated. The open loop maneuver is determined with the Sequential Quadratic Programming (SQP) algorithm, which optimizes a bang-off-bang control parameter set for the given maneuver. Torque smoothing is used to prevent discontinuities in the control which would excite the flexible structure. Additional system dynamics such as thruster inefficiency, spring forces and pressure leaks are identified from preliminary experiments on the ASTREX test article.
ZAP and its application to the optimization of synchrotron light source parameters
Zisman, M.S.
1987-03-01
The design of electron storage rings for the production of synchrotron radiation has become increasingly sophisticated in recent years. To assist in the optimization of such storage rings, a new, user-friendly code to treat the relevant collective phenomena, called ZAP, has been written at LBL. The code is designed primarily to carry out parameter studies of electron storage rings, although options for protons or heavy ions are included where appropriate. In this paper, we first describe the contents of the code itself, and then illustrate, via selected examples, how the collective effects treated by ZAP manifest themselves in the new generation of synchrotron light sources.
OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE
Xie, Xianchao; Kou, S. C.; Brown, Lawrence
2015-01-01
This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results. PMID:27041778
YANG, C.; JIANG, W.; CHEN, D. -H.; ADIGA, U.; NG, E. G.; CHIU, W.
2009-01-01
Summary The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes. PMID:19250460
Fine tuning of phase qubit parameters for optimization of fast single-pulse readout
Revin, Leonid S.; Pankratov, Andrey L.
2011-04-18
We analyze a two-level quantum system, describing the phase qubit, during a single-pulse readout process by a numerical solution of the time-dependent Schroedinger equation. It has been demonstrated that the readout error has a minimum for certain values of the system's basic parameters. In particular, the optimization of the qubit capacitance and the readout pulse shape leads to significant reduction in the readout error. It is shown that in an ideal case the fidelity can be increased to almost 97% for 2 ns pulse duration and to 96% for 1 ns pulse duration.
Optimization of sinter/HIP parameters of multiphase silicon nitride/silicon carbide ceramics
Perera, D.S.; Moricca, S.; Drennan, J.; Fan, Q.S.; Gu, P.Z.
1996-12-31
Multiphase silicon carbide reinforced silicon nitride materials were sintered using 3 techniques, (1) pressureless sintering, (2) post-sinter HIPing and (3) sintering and HIPing in the same cycle (sinter/HIP). The materials have been characterized with respect to their microstructure, phase relationships and mechanical properties. The materials reached almost the theoretical density using the 3 sintering methods, but this was achieved at a lower temperature with sinter/HIPing. A balance should be sought between the high pressure required for high density and the prevention of excessive nitrogen (pressurizing gas) dissolution in the glassy grain boundary phases. The optimization of sinter/HIP parameters are discussed with respect to sintering mechanisms.
Yang, Chao; Jiang, Wen; Chen, Dong-Hua; Adiga, Umesh; Ng, Esmond G.; Chiu, Wah
2008-07-28
The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes.
NASA Astrophysics Data System (ADS)
Gao, Zhongmei; Shao, Xinyu; Jiang, Ping; Cao, Longchao; Zhou, Qi; Yue, Chen; Liu, Yang; Wang, Chunming
2016-09-01
It is of great significance to select appropriate welding process parameters for obtaining optimal weld geometry in hybrid laser-arc welding. An integrated optimization approach by combining Kriging model and GA is proposed to optimize process parameters. A four-factor, five-level experiment using Taguchi L25 is conducted considering laser power (P), welding current (A), distance between laser and arc (D) and traveling speed (V). Kriging model is adopted to approximate the relationship between process parameters and weld geometry, namely depth of penetration (DP), bead width (BW) and bead reinforcement (BR). The constructed Kriging model was used for parameters optimization by GA to maximize DP, minimize BW and ensure BR at a desired value. The effects of process parameters on weld geometry are analyzed. Microstructure and micro-hardness are also discussed. Verification experiments demonstrate that the obtained optimum values are in good agreement with experimental results.
NASA Astrophysics Data System (ADS)
Ramimoghadam, Donya; Bagheri, Samira; Yousefi, Amin Termeh; Abd Hamid, Sharifah Bee
2015-11-01
In this study, nanomagnetite particles have been successfully prepared via the coprecipitation method. The effect of the key explanatory variables on the saturation magnetization of synthetic nanomagnetite particles was investigated using the response surface methodology (RSM). The correlation of the involved parameters with the growth process was examined by employing the central composite design method through designating set up experiments that will determine the interaction of the variables. The vibrating sample magnetometer (VSM) was used to confirm the statistical analysis. Furthermore, the regression analysis monitors the priority of the variables' influence on the saturation magnetization of nanomagnetite particles by developing the statistical model of the saturation magnetization. According to the investigated model, the highest interaction of variable belongs to the pH and temperature with the optimized condition of 9-11, and 75-85 °C, respectively. The response obtained by VSM suggests that the saturation magnetization of nanomagnetite particles can be controlled by restricting the effective parameters.
NASA Astrophysics Data System (ADS)
Dhanapal, P.; Mohamed Nazirudeen, S. S.; Chandrasekar, A.
2012-04-01
Carbide 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 and characterizing the proper material composition through the melting route done. In an effort to arrive the optimal production parameters of multi responses, Taguchi method and Grey relational analysis have been applied. To analyze the effect of production parameters on the mechanical properties signal-to-noise ratio and Grey relational grade have been calculated based on the design of experiments. An analysis of variance was calculated to find the amount of contribution of factors on mechanical properties and their significance. The analytical results of Taguchi method were compared with the experimental values, and it shows that both are identical.
Mandal, Subhamoy; Nasonova, Elena; Deán-Ben, Xosé Luís; Razansky, Daniel
2014-01-01
In tomographic optoacoustic imaging, multiple parameters related to both light and ultrasound propagation characteristics of the medium need to be adequately selected in order to accurately recover maps of local optical absorbance. Speed of sound in the imaged object and surrounding medium is a key parameter conventionally assumed to be uniform. Mismatch between the actual and predicted speed of sound values may lead to image distortions but can be mitigated by manual or automatic optimization based on metrics of image sharpness. Although some simple approaches based on metrics of image sharpness may readily mitigate distortions in the presence of highly contrasting and sharp image features, they may not provide an adequate performance for smooth signal variations as commonly present in realistic whole-body optoacoustic images from small animals. Thus, three new hybrid methods are suggested in this work, which are shown to outperform well-established autofocusing algorithms in mouse experiments in vivo. PMID:25431756
NASA Astrophysics Data System (ADS)
Wu, Z.; Gao, Y.; Gong, H.; Li, L.
2016-04-01
Lacking of efficient methods, industry currently uses one only parameter—fuel flow rate—to evaluate the nozzle quality, which is far from satisfying the current emission regulations worldwide. By utilizing synchrotron radiation high energy X-ray in Shanghai Synchrotron Radiation Facility (SSRF), together with the imaging techniques, the 3D models of two nozzles with the same design dimensions were established, and the influence of parameters fluctuation in the azimuthal direction were analyzed in detail. Results indicate that, due to the orifice misalignment, even with the same design dimension, the inlet rounding radius of orifices differs greatly, and its fluctuation in azimuthal direction is also large. This difference will cause variation in the flow characteristics at orifice outlet and then further affect the spray characteristics. The study also indicates that, more precise investigation and insight into the evaluation and optimization of diesel nozzle structural parameter are needed.
Strategies to optimize shock wave lithotripsy outcome: Patient selection and treatment parameters
Semins, Michelle Jo; Matlaga, Brian R
2015-01-01
Shock wave lithotripsy (SWL) was introduced in 1980, modernizing the treatment of upper urinary tract stones, and quickly became the most commonly utilized technique to treat kidney stones. Over the past 5-10 years, however, use of SWL has been declining because it is not as reliably effective as more modern technology. SWL success rates vary considerably and there is abundant literature predicting outcome based on patient- and stone-specific parameters. Herein we discuss the ways to optimize SWL outcomes by reviewing proper patient selection utilizing stone characteristics and patient features. Stone size, number, location, density, composition, and patient body habitus and renal anatomy are all discussed. We also review the technical parameters during SWL that can be controlled to improve results further, including type of anesthesia, coupling, shock wave rate, focal zones, pressures, and active monitoring. Following these basic principles and selection criteria will help maximize success rate. PMID:25949936
Optimizing Aqua Splicer Parameters for Lycra-Cotton Core Spun Yarn Using Taguchi Method
NASA Astrophysics Data System (ADS)
Midha, Vinay Kumar; Hiremath, ShivKumar; Gupta, Vaibhav
2015-10-01
In this paper, optimization of the aqua splicer parameters viz opening time, splicing time, feed arm code (i.e. splice length) and duration of water joining was carried out for 37 tex lycra-cotton core spun yarn for better retained splice strength (RSS%), splice abrasion resistance (RYAR%) and splice appearance (RYA%) using Taguchi experimental design. It is observed that as opening time, splicing time and duration of water joining increase, the RSS% and RYAR% increases, whereas increase in feed arm code leads to decrease in both. The opening time and feed arm code do not have significant effect on RYA%. The optimum RSS% of 92.02 % was obtained at splicing parameters of 350 ms opening time, 180 ms splicing time, 65 feed arm code and 600 ms duration of water joining.
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. PMID:24778944
Yazdani, Nuri; Chawla, Vipin; Edwards, Eve; Wood, Vanessa
2014-01-01
Summary 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. PMID:24778944
Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)
NASA Astrophysics Data System (ADS)
Xing, Lei; Li, Ruijiang
2014-03-01
The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.
Loewe, Axel; Wilhelms, Mathias; Schmid, Jochen; Krause, Mathias J.; Fischer, Fathima; Thomas, Dierk; Scholz, Eberhard P.; Dössel, Olaf; Seemann, Gunnar
2016-01-01
Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non
Parameter Optimization and Field Validation of the Functional–Structural Model GREENLAB for Maize
GUO, YAN; MA, YUNTAO; ZHAN, ZHIGANG; LI, BAOGUO; DINGKUHN, MICHAEL; LUQUET, DELPHINE; DE REFFYE, PHILIPPE
2006-01-01
• Background and Aims There are three reasons for the increasing demand for crop models that build the plant on the basis of architectural principles and organogenetic processes: (1) realistic concepts for developing new crops need to be guided by such models; (2) there is an increasing interest in crop phenotypic plasticity, based on variable architecture and morphology; and (3) engineering of mechanized cropping systems requires information on crop architecture. The functional–structural model GREENLAB was recently presented that simulates resource-dependent plasticity of plant architecture. This study introduces a new methodology for crop parameter optimization against measured data called multi-fitting, validates the calibrated model for maize with independent field data, and describes a technique for 3D visualization of outputs. • Methods Maize was grown near Beijing during the 2000, 2001 and 2003 (two sowing dates) summer seasons in a block design with four to five replications. Detailed morphological and topological observations were made on the plant architecture throughout the development of the four crops. Data obtained in 2000 was used to establish target files for parameter optimization using the generalized least square method, and parameter accuracy was evaluated by coefficient of variance. In situ plant digitization was used to establish 3D symbol files for organs that were then used to translate model outputs directly into 3D representations for each time step of model execution. •Key Results and Conclusions Multi-fitting against several target files obtained at different growth stages gave better parameter accuracy than single fitting at maturity only, and permitted extracting generic organ expansion kinetics from the static observations. The 2000 model gave excellent predictions of plant architecture and vegetative growth for the other three seasons having different temperature regimes, but predictions of inter-seasonal variability of
Ryumin, Pavel; Brown, Jeffery; Morris, Michael; Cramer, Rainer
2016-07-15
Liquid matrix-assisted laser desorption/ionization (MALDI) allows the generation of predominantly multiply charged ions in atmospheric pressure (AP) MALDI ion sources for mass spectrometry (MS) analysis. The charge state distribution of the generated ions and the efficiency of the ion source in generating such ions crucially depend on the desolvation regime of the MALDI plume after desorption in the AP-to-vacuum inlet. Both high temperature and a flow regime with increased residence time of the desorbed plume in the desolvation region promote the generation of multiply charged ions. Without such measures the application of an electric ion extraction field significantly increases the ion signal intensity of singly charged species while the detection of multiply charged species is less dependent on the extraction field. In general, optimization of high temperature application facilitates the predominant formation and detection of multiply charged compared to singly charged ion species. In this study an experimental set-up and optimization strategy is described for liquid AP-MALDI MS which improves the ionization efficiency of selected ion species up to 14 times. In combination with ion mobility separation, the method allows the detection of multiply charged peptide and protein ions for analyte solution concentrations as low as 2fmol/μL (0.5μL, i.e. 1fmol, deposited on the target) with very low sample consumption in the low nL-range. PMID:26827934
OPTIMIZATION-BASED CONSTITUTIVE PARAMETER IDENTIFICATION FROM SPARSE TAYLOR CYLINDER DATA
J.M. Lacy
2010-10-01
The classic Taylor impact test imparts temporally and spatially varying fields of strain, strain rate, and temperature through the specimen. It is possible to exploit this complexity to directly identify constitutive model parameters from the deformed shape of the specimen. Where prior investigators have employed various mathematical fitting methods to identify or improve strength model parameters from Taylor cylinder profiles, we extend the method to employ a multi-objective genetic optimization algorithm to minimize the cylinder profile errors simultaneously on three cylinders impacted at different velocities. No experimental data other than the three Taylor cylinders is employed in developing the constitutive model parameter set, and generic starting coefficients are employed. To validate the accuracy of the resulting coefficients, both split Hopkinson pressure bar and axisymmetric expanding ring tests were conducted and compared to the resultant Johnson-Cook strength model. The derived strength model agreed well with experimental data available to date. Further work is necessary to evaluate the range of rates and temperatures over which parameters derived by this method may be applied.
NASA Astrophysics Data System (ADS)
Wu, Xinrong; Han, Guijun; Zhang, Shaoqing; Liu, Zhengyu
2016-02-01
Model error is a major obstacle for enhancing the forecast skill of El Niño-Southern Oscillation (ENSO). Among three kinds of model error sources—dynamical core misfitting, physical scheme approximation and model parameter errors, the model parameter errors are treatable by observations. Based on the Zebiak-Cane model, an ensemble coupled data assimilation system is established to study the impact of parameter optimization (PO) on ENSO predictions within a biased twin experiment framework. "Observations" of sea surface temperature anomalies drawn from the "truth" model are assimilated into a biased prediction model in which model parameters are erroneously set from the "truth" values. The degree by which the assimilation and prediction with or without PO recover the "truth" is a measure of the impact of PO. Results show that PO improves ENSO predictability—enhancing the seasonal-interannual forecast skill by about 18 %, extending the valid lead time up to 33 % and ameliorating the spring predictability barrier. Although derived from idealized twin experiments, results here provide some insights when a coupled general circulation model is initialized from the observing system.
Optimization principle of operating parameters of heat exchanger by using CFD simulation
NASA Astrophysics Data System (ADS)
Mičieta, Jozef; Jiří, Vondál; Jandačka, Jozef; Lenhard, Richard
2016-03-01
Design of effective heat transfer devices and minimizing costs are desired sections in industry and they are important for both engineers and users due to the wide-scale use of heat exchangers. Traditional approach to design is based on iterative process in which is gradually changed design parameters, until a satisfactory solution is achieved. The design process of the heat exchanger is very dependent on the experience of the engineer, thereby the use of computational software is a major advantage in view of time. Determination of operating parameters of the heat exchanger and the subsequent estimation of operating costs have a major impact on the expected profitability of the device. There are on the one hand the material and production costs, which are immediately reflected in the cost of device. But on the other hand, there are somewhat hidden costs in view of economic operation of the heat exchanger. The economic balance of operation significantly affects the technical solution and accompanies the design of the heat exchanger since its inception. Therefore, there is important not underestimate the choice of operating parameters. The article describes an optimization procedure for choice of cost-effective operational parameters for a simple double pipe heat exchanger by using CFD software and the subsequent proposal to modify its design for more economical operation.
Kang, Mingon; Gao, Jean; Tang, Liping
2011-01-01
Developing vigorous mathematical equations and estimating accurate parameters within feasible computational time are two indispensable parts to build reliable system models for representing biological properties of the system and for producing reliable simulation. For a complex biological system with limited observations, one of the daunting tasks is the large number of unknown parameters in the mathematical modeling whose values directly determine the performance of computational modeling. To tackle this problem, we have developed a data-driven global optimization method, nonlinear RANSAC, based on RANdom SAmple Consensus (a.k.a. RANSAC) method for parameter estimation of nonlinear system models. Conventional RANSAC method is sound and simple, but it is oriented for linear system models. We not only adopt the strengths of RANSAC, but also extend the method to nonlinear systems with outstanding performance. As a specific application example, we have targeted understanding phagocyte transmigration which is involved in the fibrosis process for biomedical device implantation. With well-defined mathematical nonlinear equations of the system, nonlinear RANSAC is performed for the parameter estimation. In order to evaluate the general performance of the method, we also applied the method to signalling pathways with ordinary differential equations as a general format. PMID:23227455
NASA Astrophysics Data System (ADS)
Lafrenière-Bérubé, Charles; Chouteau, Michel; Shamsipour, Pejman; Olivo, Gema R.
2016-04-01
Spectral induced polarization (SIP) parameters can be extracted from field or laboratory complex resistivity measurements, and even airborne or ground frequency domain electromagnetic data. With the growing interest in application of complex resistivity measurements to environmental and mineral exploration problems, there is a need for accurate and easy-to-use inversion tools to estimate SIP parameters. These parameters, which often include chargeability and relaxation time may then be studied and related to other rock attributes such as porosity or metallic grain content, in the case of mineral exploration. We present an open source program, available both as a standalone application or Python module, to estimate SIP parameters using Markov-chain Monte Carlo (MCMC) sampling. The Python language is a high level, open source language that is now widely used in scientific computing. Our program allows the user to choose between the more common Cole-Cole (Pelton), Dias, or Debye decomposition models. Simple circuits composed of resistances and constant phase elements may also be used to represent SIP data. Initial guesses are required when using more classic inversion techniques such as the least-squares formulation, and wrong estimates are often the cause of bad curve fitting. In stochastic optimization using MCMC, the effect of the starting values disappears as the simulation proceeds. Our program is then optimized to do batch inversion over large data sets with as little user-interaction as possible. Additionally, the Bayesian formulation allows the user to do quality control by fully propagating the measurement errors in the inversion process, providing an estimation of the SIP parameters uncertainty. This information is valuable when trying to relate chargeability or relaxation time to other physical properties. We test the inversion program on complex resistivity measurements of 12 core samples from the world-class gold deposit of Canadian Malartic. Results show
Optimal choice of the parameters for ventilation and methane drainage in a longwall face with caving
Dziurzynski, W.; Nawrat, S.
1995-12-31
An increasing concentration of coal production, especially in the circumstances of intensive methane inflow makes the coal mine managing staff apply new techniques of safe mining. It paves also the way for scientists to develop new directions of investigations and implementation of state-of-the-art technical solutions. Simultaneously, it could be noticed that the funds assigned for expansive {open_quote}in situ{close_quotes} investigation are continuously decreasing. Better and better results are reached when applying computer technique in calculations of the parameters of ventilation process. Recent theoretical and experimental investigations of air and gas (methane) flow in longwall areas with caving, combined with the implementation of methane drainage system allowed to create, a mathematical model and consequently to elaborate a computer supported numerical simulation of discussed phenomena. The mathematical model has been modified and the simulation program was prepared in such a way that the software is convenient for a user looking for an optimal solution. The paper presented the methodology of optimal choice of following parameters: (1) ventilation system; and (2) rate of flow through the wall. The procedure takes into consideration keeping a safe level of concentration methane in air flowing through the longwall as well as the criterion of maximum methane concentration within the methane drainage pipe line. Results of variant computer simulation regarding the longwall with caving are shown in graphs and tables.
Heidari, Ali; Forouzan, Mohammad R.
2012-01-01
Chatter has been recognized as major restriction for the increase in productivity of cold rolling processes, limiting the rolling speed for thin steel strips. It is shown that chatter has close relation with rolling conditions. So the main aim of this paper is to attain the optimum set points of rolling to achieve maximum rolling speed, preventing chatter to occur. Two combination methods were used for optimization. First method is done in four steps: providing a simulation program for chatter analysis, preparing data from simulation program based on central composite design of experiment, developing a statistical model to relate system tendency to chatter and rolling parameters by response surface methodology, and finally optimizing the process by genetic algorithm. Second method has analogous stages. But central composite design of experiment is replaced by Taguchi method and response surface methodology is replaced by neural network method. Also a study on the influence of the rolling parameters on system stability has been carried out. By using these combination methods, new set points were determined and significant improvement achieved in rolling speed. PMID:25685398
2007-01-01
Several modifications that have been made to the NDDO core-core interaction term and to the method of parameter optimization are described. These changes have resulted in a more complete parameter optimization, called PM6, which has, in turn, allowed 70 elements to be parameterized. The average unsigned error (AUE) between calculated and reference heats of formation for 4,492 species was 8.0 kcal mol−1. For the subset of 1,373 compounds involving only the elements H, C, N, O, F, P, S, Cl, and Br, the PM6 AUE was 4.4 kcal mol−1. The equivalent AUE for other methods were: RM1: 5.0, B3LYP 6–31G*: 5.2, PM5: 5.7, PM3: 6.3, HF 6–31G*: 7.4, and AM1: 10.0 kcal mol−1. Several long-standing faults in AM1 and PM3 have been corrected and significant improvements have been made in the prediction of geometries. Figure Calculated structure of the complex ion [Ta6Cl12]2+ (footnote): Reference value in parenthesis Electronic supplementary material The online version of this article (doi:10.1007/s00894-007-0233-4) contains supplementary material, which is available to authorized users. PMID:17828561
NASA Astrophysics Data System (ADS)
Toghi Eshghi, Amin; Lee, Soobum; Lee, Hanmin; Kim, Young-Cheol
2016-04-01
In this paper, we perform design parameter study and design optimization for a piezoelectric energy harvester considering vehicle speed variation. Initially, a FEM model using ANSYS is developed to appraise the performance of a piezoelectric harvester in a rotating tire. The energy harvester proposed here uses the vertical deformation at contact patch area from the car weight and centrifugal acceleration. This harvester is composed of a beam which is clamped at both ends and a piezoelectric material is attached on the top of that. The piezoelectric material possesses the 31 mode of transduction in which the direction of applied field is perpendicular to that of the electric field. To optimize the harvester performance, we would change the geometrical parameters of the harvester to obtain the maximum power. One of the main challenges in the design process is obtaining the required power while considering the constraints for harvester weight and volume. These two concerns are addressed in this paper. Since the final goal of this study is the development of an energy harvester with a wireless sensor system installed in a real car, the real time data for varied velocity of a vehicle are taken into account for power measurements. This study concludes that the proposed design is applicable to wireless tire sensor systems.
Huang, X N; Ren, H P
2016-01-01
Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043
Heidari, Ali; Forouzan, Mohammad R
2013-01-01
Chatter has been recognized as major restriction for the increase in productivity of cold rolling processes, limiting the rolling speed for thin steel strips. It is shown that chatter has close relation with rolling conditions. So the main aim of this paper is to attain the optimum set points of rolling to achieve maximum rolling speed, preventing chatter to occur. Two combination methods were used for optimization. First method is done in four steps: providing a simulation program for chatter analysis, preparing data from simulation program based on central composite design of experiment, developing a statistical model to relate system tendency to chatter and rolling parameters by response surface methodology, and finally optimizing the process by genetic algorithm. Second method has analogous stages. But central composite design of experiment is replaced by Taguchi method and response surface methodology is replaced by neural network method. Also a study on the influence of the rolling parameters on system stability has been carried out. By using these combination methods, new set points were determined and significant improvement achieved in rolling speed. PMID:25685398
SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier
Huang, Mei-Ling; Hung, Yung-Hsiang; Lee, W. M.; Li, R. K.; Jiang, Bo-Ru
2014-01-01
Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. Dermatology dataset contains 33 feature variables, 1 class variable, and 366 testing instances; and the Zoo dataset contains 16 feature variables, 1 class variable, and 101 testing instances. The feature variables in the two datasets were sorted in descending order by explanatory power, and different feature sets were selected by SVM-RFE to explore classification accuracy. Meanwhile, Taguchi method was jointly combined with SVM classifier in order to optimize parameters C and γ to increase classification accuracy for multiclass classification. The experimental results show that the classification accuracy can be more than 95% after SVM-RFE feature selection and Taguchi parameter optimization for Dermatology and Zoo databases. PMID:25295306
Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit
Elwasif, Wael R; Bernholdt, David E; Pannala, Sreekanth; Allu, Srikanth; Foley, Samantha S
2012-01-01
The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from many simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion
The effect of deposition parameters on the phase of TiO2 films grown by RF magnetron sputtering
NASA Astrophysics Data System (ADS)
Lim, Ji Chon; Song, Kyu Jeong; Park, Chan
2014-12-01
TiO2 thin films were deposited on Si substrates by using conventional radio-frequency (RF) magnetron sputtering with either metallic Ti or TiO2 targets, and the effect of the deposition parameters (substrate temperature ( T s ), RF sputtering power, gas flow ratio of O2/(Ar+O2) and deposition time) on the phase of the film was investigated. X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to obtain information on the phase of the films and on the surface image/thickness of films, respectively. TiO2 films deposited at a T s higher than 300 °C by using a metallic Ti target showed the dominant presence of the rutile phase. For films grown at a constant T s of 300 °C with different gas flow ratios of O2/(Ar+O2), the amount of the rutile phase gradually decreased as the oxygen gas flow was decreased. The anatase phase, however, was formed when the O2/(Ar+O2) was 0.2. On the other hand, for TiO2 films deposited at T s 's between 50 °C and 200 °C with an O2/(Ar+O2) of 0.1 by using a TiO2 target, both the anatase and the rutile phases gradually decreased as the T s was increased. For TiO2 films deposited with various gas flow ratios of O2/(Ar+O2) between 0 and 0.4 at a constant T s of 200 °C by using a TiO2 target, the anatase phase gradually decreased, but the rutile phase gradually increased, as the gas flow ratio was increased.
Parameters optimization for the energy management system of hybrid electric vehicle
NASA Astrophysics Data System (ADS)
Tseng, Chyuan-Yow; Hung, Yi-Hsuan; Tsai, Chien-Hsiung; Huang, Yu-Jen
2007-12-01
Hybrid electric vehicle (HEV) has been widely studied recently due to its high potential in reduction of fuel consumption, exhaust emission, and lower noise. Because of comprised of two power sources, the HEV requires an energy management system (EMS) to distribute optimally the power sources for various driving conditions. The ITRI in Taiwan has developed a HEV consisted of a 2.2L internal combustion engine (ICE), a 18KW motor/generator (M/G), a 288V battery pack, and a continuous variable transmission (CVT). The task of the present study is to design an energy management strategy of the EMS for the HEV. Due to the nonlinear nature and the fact of unknown system model of the system, a kind of simplex method based energy management strategy is proposed for the HEV system. The simplex method is a kind of optimization strategy which is generally used to find out the optimal parameters for un-modeled systems. The way to apply the simplex method for the design of the EMS is presented. The feasibility of the proposed method was verified by perform numerical simulation on the FTP75 drive cycles.
Li, Xingyuan; He, Zhili; Zhou, Jizhong
2005-01-01
The oligonucleotide specificity for microarray hybridization can be predicted by its sequence identity to non-targets, continuous stretch to non-targets, and/or binding free energy to non-targets. Most currently available programs only use one or two of these criteria, which may choose ‘false’ specific oligonucleotides or miss ‘true’ optimal probes in a considerable proportion. We have developed a software tool, called CommOligo using new algorithms and all three criteria for selection of optimal oligonucleotide probes. A series of filters, including sequence identity, free energy, continuous stretch, GC content, self-annealing, distance to the 3′-untranslated region (3′-UTR) and melting temperature (Tm), are used to check each possible oligonucleotide. A sequence identity is calculated based on gapped global alignments. A traversal algorithm is used to generate alignments for free energy calculation. The optimal Tm interval is determined based on probe candidates that have passed all other filters. Final probes are picked using a combination of user-configurable piece-wise linear functions and an iterative process. The thresholds for identity, stretch and free energy filters are automatically determined from experimental data by an accessory software tool, CommOligo_PE (CommOligo Parameter Estimator). The program was used to design probes for both whole-genome and highly homologous sequence data. CommOligo and CommOligo_PE are freely available to academic users upon request. PMID:16246912
Comparison of global optimization approaches for robust calibration of hydrologic model parameters
NASA Astrophysics Data System (ADS)
Jung, I. W.
2015-12-01
Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.
Impact of deposition parameters on the performance of ceria based resistive switching memories
NASA Astrophysics Data System (ADS)
Zhang, Lepeng; Younis, Adnan; Chu, Dewei; Li, Sean
2016-07-01
Resistive-switching memories stacked in a metal–insulator–metal (MIM) like structure have shown great potential for next generation non-volatile memories. In this study, ceria based resistive memory stacks are fabricated by implementing different sputter conditions (temperatures and powers). The films deposited at low temperatures were found to have random grain orientations, less porosity and dense structure. The effect of deposition conditions on resistive switching characteristics of as-prepared films were also investigated. Improved and reliable resistive switching behaviors were achieved for the memory devices occupying less porosity and densely packed structures prepared at low temperatures. Finally, the underlying switching mechanism was also explained on the basis of quantitative analysis.
NASA Astrophysics Data System (ADS)
Murphy, Neil R.; Sun, Lirong; Grant, John T.; Jones, John G.; Jakubiak, Rachel
2015-10-01
Molybdenum oxide films were deposited using modulated pulse power magnetron sputtering (MPPMS) from a molybdenum target in a reactive environment where the flow rate of oxygen was varied from 0 sccm to 2.00 sccm. By varying the amount of reactive oxygen available during deposition, the composition of the films ranged from metallic Mo to fully stoichiometric MoO3, when the molybdenum target became poisoned, due to the formation of a dielectric surface oxide coating. Film compositions were verified using high energy resolution x-ray photoelectron spectroscopy. Target poisoning occurred at an oxygen flow rate of 1.25 sccm and reversed when the flow rate decreased to about 1.00 sccm. MoO3 films deposited via MPPMS had densities of 3.8 g cm-3, 81% of the density of crystalline α-MoO3 as determined by x-ray reflectivity (XRR). In addition, XRR and atomic force microscopy data showed sub-nanometer surface roughness values. From spectroscopic ellipsometry, the measured refractive index of the MoO3 films at 589 nm was 1.97 with extinction coefficient values <0.02 at wavelengths above the measured absorption edge of 506 nm (2.45 eV).
NASA Astrophysics Data System (ADS)
Zidikheri, Meelis J.; Potts, Rodney J.
2015-09-01
A simple inversion scheme for optimizing volcanic emission dispersion model parameters with respect to satellite detections is presented in this paper. In this scheme, multiple dispersion model simulations, obtained by varying relevant model parameters, are created and compared against satellite detections using pattern correlation as a measure of model agreement with observations. It is shown that the scheme is successful in inferring emission source parameters such as those describing the vertical extent of the nascent sulfur dioxide emissions in the November 2010 Mount Merapi eruption in Java, Indonesia. These optimal parameter values then become a basis for improved forecasts of the transport of volcanic emissions.
NASA Astrophysics Data System (ADS)
Shamsipour, Majid; Pahlevani, Zahra; Shabani, Mohsen Ostad; Mazahery, Ali
2016-04-01
Understanding of the electromagnetic stirrer (EMS) process parameters-wear relation in nanocomposite is required for further creation of tailored modifications of process in accordance with the demands for various applications. This study depicts the performance of hybrid algorithm for optimization of the parameters in EMS compocasting of nano-TiC-reinforced Al-Si alloys. Adaptive neuro-fuzzy inference system (ANFIS) coupled with particle swarm optimization (PSO) was applied to find the optimum combination of the inputs including mold temperature, mix time, impeller speed, powder temperature, cast temperature and average particle size. The optimized condition was obtained in minimization of objective function. The objective function is calculated by ANFIS and then minimized by PSO. The optimized parameters were used to produce semisolid cast aluminum matrix composites reinforced with nano-TiC particles. The optimized nanocomposites were then studied for their tribological properties.
Taniguchi, Yoichi; Aoki, Akira; Mizutani, Koji; Takeuchi, Yasuo; Ichinose, Shizuko; Takasaki, Aristeo Atsushi; Schwarz, Frank; Izumi, Yuichi
2013-07-01
Er:YAG laser (ErL) irradiation has been reported to be effective for treating peri-implant disease. The present study seeks to evaluate morphological and elemental changes induced on microstructured surfaces of dental endosseous implants by high-pulse-repetition-rate ErL irradiation and to determine the optimal irradiation conditions for debriding contaminated microstructured surfaces. In experiment 1, dual acid-etched microstructured implants were irradiated by ErL (pulse energy, 30-50 mJ/pulse; repetition rate, 30 Hz) with and without water spray and for used and unused contact tips. Experiment 2 compared the ErL treatment with conventional mechanical treatments (metal/plastic curettes and ultrasonic scalers). In experiment 3, five commercially available microstructures were irradiated by ErL light (pulse energy, 30-50 mJ/pulse; pulse repetition rate, 30 Hz) while spraying water. In experiment 4, contaminated microstructured surfaces of three failed implants were debrided by ErL irradiation. After the experiments, all treated surfaces were assessed by stereomicroscopy, scanning electron microscopy (SEM), and/or energy-dispersive X-ray spectroscopy (EDS). The stereomicroscopy, SEM, and EDS results demonstrate that, unlike mechanical treatments, ErL irradiation at 30 mJ/pulse and 30 Hz with water spray induced no color or morphological changes to the microstructures except for the anodized implant surface, which was easily damaged. The optimized irradiation parameters effectively removed calcified deposits from contaminated titanium microstructures without causing substantial thermal damage. ErL irradiation at pulse energies below 30 mJ/pulse (10.6 J/cm(2)/pulse) and 30 Hz with water spray in near-contact mode seems to cause no damage and to be effective for debriding microstructured surfaces (except for anodized microstructures). PMID:22886137
NASA Astrophysics Data System (ADS)
Salas, Y.; Vera, E.; Moreno, M.; Pineda, Y.
2016-02-01
Parameters required for the preparation of coatings of aluminium oxide deposited on AISI 1020 steels were determined according to their thickness and type of flame to differentiate their behaviour against corrosion. Commercial powders were used by the method of thermal spraying deposition. The coatings were analysed by OM (optical microscopy), the thickness was measured by means of a coating thickness gauge and electrochemical techniques variables measured was the Linear Polarization Resistance (LPR) and approximation Tafel potentiodynamic curves. The corrosion current for steel 1020 with Na2SO4 electrolyte of 3.5% is of the order of hundreds of A/cm2 and coated steel given in the order of A/cm2, which leads to think that the projection produces coatings uniform low closed porosity, although techniques DC indicate a significant porosity as is observable current response to the potentiodynamic curve. The observed thicknesses fall into the hundreds of microns and little uniformity was noted in this coatings. The coatings deposited by oxidizing flame was better performance in corrosion than the coating deposited by neutral flame.
Optimizing Parameters of Process-Based Terrestrial Ecosystem Model with Particle Filter
NASA Astrophysics Data System (ADS)
Ito, A.
2014-12-01
Present terrestrial ecosystem models still contain substantial uncertainties, as model intercomparison studies have shown, because of poor model constraint by observational data. So, development of advanced methodology of data-model fusion, or data-assimilation, is an important task to reduce the uncertainties and improve model predictability. In this study, I apply the Particle filter (or Sequential Monte Carlo filer) to optimize parameters of a process-based terrestrial ecosystem model (VISIT). The Particle filter is one of the data-assimilation methods, in which probability distribution of model state is approximated by many samples of parameter set (i.e., particle). This is a computationally intensive method and applicable to nonlinear systems; this is an advantage of the method in comparison with other techniques like Ensemble Kalman filter and variational method. At several sites, I used flux measurement data of atmosphere-ecosystem CO2 exchange in sequential and non-sequential manners. In the sequential data assimilation, a time-series data at 30-min or daily steps were used to optimize gas-exchange-related parameters; this method would be also effective to assimilate satellite observational data. On the other hand, in the non-sequential case, annual or long-term mean budget was adjusted to observations; this method would be also effective to assimilate carbon stock data. Although there remain technical issues (e.g., appropriate number of particles and likelihood function), I demonstrate that the Partile filter is an effective method of data-assimilation for process-based models, enhancing collaboration between field and model researchers.
Huang, Yang; Liu, Guang-Jian; Liao, Bing; Huang, Guang-Liang; Liang, Jin-Yu; Zhou, Lu-Yao; Wang, Fen; Li, Wei; Xie, Xiao-Yan; Wang, Wei; Lu, Ming-De
2015-09-01
The aims of the present study are to assess the impact factors on acoustic structure quantification (ASQ) ultrasound and find the optimal parameter for the assessment of liver fibrosis. Twenty healthy volunteers underwent ASQ examinations to evaluate impact factors in ASQ image acquisition and analysis. An additional 113 patients with liver diseases underwent standardized ASQ examinations, and the results were compared with histologic staging of liver fibrosis. We found that the right liver displayed lower values of ASQ parameters than the left (p = 0.000-0.021). Receive gain experienced no significant impact except gain 70 (p = 0.193-1.000). With regard to different diameter of involved vessels in regions of interest, the group ≤2.0 mm differed significantly with the group 2.1-5.0 mm (p = 0.000-0.033) and the group >5.0 mm (p = 0.000-0.062). However, the region of interest size (p = 0.438-1.000) and depth (p = 0.072-0.764) had no statistical impact. Good intra- and inter-operator reproducibilities were found in both image acquisitions and offline image analyses. In the liver fibrosis study, the focal disturbance ratio had the highest correlation with histologic fibrosis stage (r = 0.67, p < 0.001). In conclusion, the testing position, receive gain and involved vessels were the main factors in ASQ examinations and focal disturbance ratio was the optimal parameter in the assessment of liver fibrosis. PMID:26055966
Methodology for Determining Optimal Exposure Parameters of a Hyperspectral Scanning Sensor
NASA Astrophysics Data System (ADS)
Walczykowski, P.; Siok, K.; Jenerowicz, A.
2016-06-01
The purpose of the presented research was to establish a methodology that would allow the registration of hyperspectral images with a defined spatial resolution on a horizontal plane. The results obtained within this research could then be used to establish the optimum sensor and flight parameters for collecting aerial imagery data using an UAV or other aerial system. The methodology is based on an user-selected optimal camera exposure parameters (i.e. time, gain value) and flight parameters (i.e. altitude, velocity). A push-broom hyperspectral imager- the Headwall MicroHyperspec A-series VNIR was used to conduct this research. The measurement station consisted of the following equipment: a hyperspectral camera MicroHyperspec A-series VNIR, a personal computer with HyperSpec III software, a slider system which guaranteed the stable motion of the sensor system, a white reference panel and a Siemens star, which was used to evaluate the spatial resolution. Hyperspectral images were recorded at different distances between the sensor and the target- from 5m to 100m. During the registration process of each acquired image, many exposure parameters were changed, such as: the aperture value, exposure time and speed of the camera's movement on the slider. Based on all of the registered hyperspectral images, some dependencies between chosen parameters had been developed: - the Ground Sampling Distance - GSD and the distance between the sensor and the target, - the speed of the camera and the distance between the sensor and the target, - the exposure time and the gain value, - the Density Number and the gain value. The developed methodology allowed us to determine the speed and the altitude of an unmanned aerial vehicle on which the sensor would be mounted, ensuring that the registered hyperspectral images have the required spatial resolution.
Zhang, Yu-xin; Cheng, Zhi-feng; Xu, Zheng-ping; Bai, Jing
2015-01-01
In order to solve the problems such as complex operation, consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis (DGA), this paper proposes a new method which is detecting 5 types of characteristic gas content in transformer oil such as CH4, C2H2, C2H4, C2H6 and H2 based on photoacoustic Spectroscopy and C2H2/C2H4, CH4/H2, C2H4/C2H6 three-ratios data are calculated. The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g, which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed. Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization. The simulation result shows that SVM model composed of C-SVC, RBF kernel functions and genetic algorithm obtain 97. 5% accuracy in test sample set and 98. 333 3% accuracy in train sample set, and genetic algorithm was about two times faster than particles swarm optimization in computing speed. The methods described in this paper has many advantages such as simple operation, non-contact measurement, no consumption for the carrier gas, long test period, high stability and sensitivity, the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis. PMID:25993810
Optimization of accelerator parameters using normal form methods on high-order transfer maps
Snopok, Pavel; /Michigan State U.
2007-05-01
in a way that is easy to understand, such important characteristics as the strengths of the resonances and the tune shifts with amplitude and various parameters of the system are calculated. Each major section is supplied with the results of applying various numerical optimization methods to the problems stated. The emphasis is made on the efficiency comparison of various approaches and methods. The main simulation tool is the arbitrary order code COSY INFINITY written by M. Berz, K. Makino, et al. at Michigan State University. Also, the code MAD is utilized to design the 750 x 750 GeV Muon Collider storage ring baseline lattice.
NASA Astrophysics Data System (ADS)
Salavati, S.; Coyle, T. W.; Mostaghimi, J.
2015-10-01
Open pore metallic foam core sandwich panels prepared by thermal spraying of a coating on the foam structures can be used as high-efficiency heat transfer devices due to their high surface area to volume ratio. The structural, mechanical, and physical properties of thermally sprayed skins play a significant role in the performance of the related devices. These properties are mainly controlled by the porosity content, oxide content, adhesion strength, and stiffness of the deposited coating. In this study, the effects of grit-blasting process parameters on the characteristics of the temporary surface created on the metallic foam substrate and on the twin-wire arc-sprayed alloy 625 coating subsequently deposited on the foam were investigated through response surface methodology. Characterization of the prepared surface and sprayed coating was conducted by scanning electron microscopy, roughness measurements, and adhesion testing. Using statistical design of experiments, response surface method, a model was developed to predict the effect of grit-blasting parameters on the surface roughness of the prepared foam and also the porosity content of the sprayed coating. The coating porosity and adhesion strength were found to be determined by the substrate surface roughness, which could be controlled by grit-blasting parameters. Optimization of the grit-blasting parameters was conducted using the fitted model to minimize the porosity content of the coating while maintaining a high adhesion strength.
NASA Astrophysics Data System (ADS)
Wu, Li-Li; Zhou, Qihou H.; Chen, Tie-Jun; Liang, J. J.; Wu, Xin
2015-09-01
Simultaneous derivation of multiple ionospheric parameters from the incoherent scatter power spectra in the F1 region is difficult because the spectra have only subtle differences for different combinations of parameters. In this study, we apply a particle swarm optimizer (PSO) to incoherent scatter power spectrum fitting and compare it to the commonly used least squares fitting (LSF) technique. The PSO method is found to outperform the LSF method in practically all scenarios using simulated data. The PSO method offers the advantages of not being sensitive to initial assumptions and allowing physical constraints to be easily built into the model. When simultaneously fitting for molecular ion fraction (fm), ion temperature (Ti), and ratio of ion to electron temperature (γT), γT is largely stable. The uncertainty between fm and Ti can be described as a quadratic relationship. The significance of this result is that Ti can be retroactively corrected for data archived many years ago where the assumption of fm may not be accurate, and the original power spectra are unavailable. In our discussion, we emphasize the fitting for fm, which is a difficult parameter to obtain. PSO method is often successful in obtaining fm, whereas LSF fails. We apply both PSO and LSF to actual observations made by the Arecibo incoherent scatter radar. The results show that PSO method is a viable method to simultaneously determine ion and electron temperatures and molecular ion fraction when the last is greater than 0.3.
Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization
Yu, Jing; Li, Yaan
2016-01-01
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target’s velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms. PMID:27376294
Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization.
Yu, Jing; Li, Yaan
2016-01-01
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target's velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms. PMID:27376294
NASA Astrophysics Data System (ADS)
Miyauchi, T.; Machimura, T.
2013-12-01
In the simulation using an ecosystem process model, the adjustment of parameters is indispensable for improving the accuracy of prediction. This procedure, however, requires much time and effort for approaching the simulation results to the measurements on models consisting of various ecosystem processes. In this study, we tried to apply a general purpose optimization tool in the parameter optimization of an ecosystem model, and examined its validity by comparing the simulated and measured biomass growth of a woody plantation. A biometric survey of tree biomass growth was performed in 2009 in an 11-year old Eucommia ulmoides plantation in Henan Province, China. Climate of the site was dry temperate. Leaf, above- and below-ground woody biomass were measured from three cut trees and converted into carbon mass per area by measured carbon contents and stem density. Yearly woody biomass growth of the plantation was calculated according to allometric relationships determined by tree ring analysis of seven cut trees. We used Biome-BGC (Thornton, 2002) to reproduce biomass growth of the plantation. Air temperature and humidity from 1981 to 2010 was used as input climate condition. The plant functional type was deciduous broadleaf, and non-optimizing parameters were left default. 11-year long normal simulations were performed following a spin-up run. In order to select optimizing parameters, we analyzed the sensitivity of leaf, above- and below-ground woody biomass to eco-physiological parameters. Following the selection, optimization of parameters was performed by using the Dakota optimizer. Dakota is an optimizer developed by Sandia National Laboratories for providing a systematic and rapid means to obtain optimal designs using simulation based models. As the object function, we calculated the sum of relative errors between simulated and measured leaf, above- and below-ground woody carbon at each of eleven years. In an alternative run, errors at the last year (at the
Dizon, José M.; Quinn, T. Alexander; Cabreriza, Santos E.; Wang, Daniel; Spotnitz, Henry M.; Hickey, Kathleen; Garan, Hasan
2010-01-01
Aims We investigated the utility of real-time stroke volume (SV) monitoring via the arterial pulse power technique to optimize cardiac resynchronization therapy (CRT) parameters at implant and prospectively evaluated the clinical and echocardiographic results. Methods and results Fifteen patients with ischaemic or non-ischaemic dilated cardiomyopathy, sinus rhythm, Class III congestive heart failure, and QRS >150 ms underwent baseline 2D echocardiogram (echo), 6 min walk distance, and quality of life (QOL) questionnaire within 1 week of implant. Following implant, 0.3 mmol lithium chloride was injected to calibrate SV via dilution curve. Atrioventricular (AV) delay (90, 120, 200 ms, baseline: atrial pacing only) and V-V delay (−80 to 80 ms in 20 ms increments) were varied every 60 s. The radial artery pulse power autocorrelation method (PulseCO algorithm, LiDCO, Ltd.) was used to monitor SV on a beat-to-beat basis (LiDCO, Ltd.). Optimal parameters were programmed and echo, 6 min walk, and QOL were repeated at 6–8 weeks post-implant. Nine patients had >5% increase in SV after optimization (Group A). Six patients had <5% improvement in SV (Group B). Compared with Group B, Group A had significant improvements in left ventricular ejection fraction (LVEF) (11.0 ± 8.5 vs. 0.8 ± 2.0%) and decrease in left ventricular end-diastolic dimension (LVEDD) (−0.6 ± 0.4 vs. −0.2 ± 0.2 cm) and 6 min walk (346 ± 226 vs. 32 ±271 ft, P ≤ 0.05). Group A patients also tended to have greater improvement in the septal-to-posterior wall motion delay on M-mode echo (P = 0.07). Conclusion Real-time SV measurements can be used to optimize CRT at the time of implant. Improvement in SV correlates with improvement in LVEF, LVEDD, and 6 min walk, and improvement in echocardiographic dyssynchrony. PMID:20525728
Kafizas, Andreas; Parkin, Ivan P
2011-12-21
We demonstrate how combinatorial atmospheric pressure chemical vapor deposition (cAPCVD) can be used as a synthetic tool for rapidly optimizing the functional properties of thin-films, by analyzing the self-cleaning properties of tungsten doped anatase as an example. By introducing reagents at separate points inside the reactor, a tungsten/titanium compositional gradient was formed and a diverse range of film growth conditions were obtained. By partially mixing the metal sources, a combinatorial film with a compositional profile that varied primarily in the lateral plane was synthesized. A combinatorial thin-film of anatase TiO(2) doped with an array of tungsten levels as a solid solution ranging from 0.38-13.8 W/Ti atom % was formed on a single glass substrate. The compositional-functional relationships were understood through comprehensively analyzing combinatorial phase space, with 200 positions investigated by high-throughput methods in this study. Physical and functional properties, and their compositional dependencies, were intercorrelated. It was found that increases in photocatalytic activity and conductivity were most highly dependent on film crystallinity within the 0.38-13.8 atom % W/Ti doping regime. However, enhancements in photoinduced surface wetting were primarily dependent on increases in preferred growth in the (211) crystal plane. PMID:22050427
NASA Astrophysics Data System (ADS)
Shahi Ferdows, Mohammad; Ramazi, Hamidreza
2015-12-01
The selection of a suitable membership function and its parameters plays a critical role in the integration of layer information by the fuzzy method. In this paper, parameters of membership function for induced polarization (IP) and resistivity (RS) data (in the Hamyj copper deposit) have been determined by the threshold parameter of IP and resistivity data, already determined by expert opinion or drilling data. The Hamyj deposit is located about 80 km west of Birjand city, South Khorasan province, Iran. In this area, resistivity and induced polarization data have been surveyed by dipole-dipole array. In this paper, outlier-induced polarization data have been corrected by the Doerffel method and then IP and resistivity data have been inversed by the Newton and Gauss-Newton methods. The threshold of the IP data is recognized by statistical (gap statistic) and fractal (concentration-area) methods. The determined threshold by the fractal method is higher than the gap statistic. These two thresholds have been used to determine the S-shape function for the IP data. The thresholds of the RS data are recognized by the fractal method. These two thresholds have been used to determine the Z-shape function for the RS data. The integration of geoelectrical layer information has been carried out by the Gama method. Finally, the best drilling points were proposed based on fuzzy modelling for the area. The results show that the optimum exploration borehole is located at a depth of 25 m.
Lilja, Mirjam; Welch, Ken; Astrand, Maria; Engqvist, Håkan; Strømme, Maria
2012-05-01
This article evaluates the influence of the main parameters in a cathodic arc deposition process on the microstructure of titanium dioxide thin coatings and correlates these to the photocatalytic activity (PCA) and in vitro bioactivity of the coatings. Bioactivity of all as deposited coatings was confirmed by the growth of uniform layers of hydroxyapatite (HA) after 7 days in phosphate buffered saline at 37°C. Comparison of the HA growth after 24 h indicated enhanced HA formation on coatings with small titanium dioxide grains of rutile and anatase phase. The results from the PCA studies showed that coatings containing a mixed microstructure of both anatase and rutile phases, with small grain sizes in the range of 26-30 nm and with a coating thickness of about 250 nm, exhibited enhanced activity as compared with other microstructures and higher coating thickness. The results of this study should be valuable for the development of new bioactive implant coatings with photocatalytically induced on-demand antibacterial properties. PMID:22447517
Relevance of thermodynamic and kinetic parameters of chemical vapor deposition precursors.
Selvakumar, J; Nagaraja, K S; Sathiyamoorthy, D
2011-09-01
We have studied various metallorganic and organometallic compounds by simultaneous nonisothermal thermogravimetric and differential thermogravimetric analyses to confirm their volatility and thermal stability. The equilibrium vapor pressures of the metallorganic and organometallic compounds were determined by horizontal dual arm single furnace thermoanalyzer as transpiration apparatus. Antoine coefficients were calculated from the temperature dependence equilibrium vapor pressure data. The model-fitting solid-state kinetic analyses of Al(acac)3, (acac = acetylacetonato), Cr(CO)6, Fe(Cp)2, (Cp-cyclopentadienyl), Ga(acac)3, Mn(tmhd)3, and Y(tmhd)3 (tmhd = 2,2,6,6,-tetramethyl-3,5-heptanedionato) revealed that the processes follow diffusion controlled, contracting area and zero order model sublimation or evaporation kinetics. The activation energy for the sublimation/evaporation processes were calculated by model-free kinetic methods. Thin films of nickel and lanthanum-strontium-manganite (LSM) are grown on silicon substrate at 573 K using selected metallorganic complexes of Ni[(acac)2en], La(tmhd)3, Sr(tmhd)2 and Mn(tmhd)3 as precursors by plasma assisted liquid injection chemical vapor deposition (PA-LICVD). The deposited films were characterized by scanning electron microscopy and energy dispersive X-ray analysis for their composition and morphology. PMID:22097553
NASA Astrophysics Data System (ADS)
Espinoza, Néstor; Jordán, Andrés
2016-04-01
Very precise measurements of exoplanet transit light curves both from ground- and space-based observatories make it now possible to fit the limb-darkening coefficients in the transit-fitting procedure rather than fix them to theoretical values. This strategy has been shown to give better results, as fixing the coefficients to theoretical values can give rise to important systematic errors which directly impact the physical properties of the system derived from such light curves such as the planetary radius. However, studies of the effect of limb-darkening assumptions on the retrieved parameters have mostly focused on the widely used quadratic limb-darkening law, leaving out other proposed laws that are either simpler or better descriptions of model intensity profiles. In this work, we show that laws such as the logarithmic, square-root and three-parameter law do a better job that the quadratic and linear laws when deriving parameters from transit light curves, both in terms of bias and precision, for a wide range of situations. We therefore recommend to study which law to use on a case-by-case basis. We provide code to guide the decision of when to use each of these laws and select the optimal one in a mean-square error sense, which we note has a dependence on both stellar and transit parameters. Finally, we demonstrate that the so-called exponential law is non-physical as it typically produces negative intensities close to the limb and should therefore not be used.
Cotter, Meghan M.; Whyms, Brian J.; Kelly, Michael P.; Doherty, Benjamin M.; Gentry, Lindell R.; Bersu, Edward T.; Vorperian, Houri K.
2015-01-01
The hyoid bone anchors and supports the vocal tract. Its complex shape is best studied in three dimensions, but it is difficult to capture on computed tomography (CT) images and three-dimensional volume renderings. The goal of this study was to determine the optimal CT scanning and rendering parameters to accurately measure the growth and developmental anatomy of the hyoid and to determine whether it is feasible and necessary to use these parameters in the measurement of hyoids from in vivo CT scans. Direct linear and volumetric measurements of skeletonized hyoid bone specimens were compared to corresponding CT images to determine the most accurate scanning parameters and three-dimensional rendering techniques. A pilot study was undertaken using in vivo scans from a retrospective CT database to determine feasibility of quantifying hyoid growth. Scanning parameters and rendering technique affected accuracy of measurements. Most linear CT measurements were within 10% of direct measurements; however, volume was overestimated when CT scans were acquired with a slice thickness greater than 1.25 mm. Slice-by-slice thresholding of hyoid images decreased volume overestimation. The pilot study revealed that the linear measurements tested correlate with age. A fine-tuned rendering approach applied to small slice thickness CT scans produces the most accurate measurements of hyoid bones. However, linear measurements can be accurately assessed from in vivo CT scans at a larger slice thickness. Such findings imply that investigation into the growth and development of the hyoid bone, and the vocal tract as a whole, can now be performed using these techniques. PMID:25810349
NASA Astrophysics Data System (ADS)
Krenn, Julia; Mergili, Martin
2016-04-01
r.randomwalk is a GIS-based, multi-functional conceptual tool for mass movement routing. Starting from one to many release points or release areas, mass points are routed down through the digital elevation model until a defined break criterion is reached. Break criteria are defined by the user and may consist in an angle of reach or a related parameter (empirical-statistical relationships), in the drop of the flow velocity to zero (two-parameter friction model), or in the exceedance of a maximum runup height. Multiple break criteria may be combined. A constrained random walk approach is applied for the routing procedure, where the slope and the perpetuation of the flow direction determine the probability of the flow to move in a certain direction. r.randomwalk is implemented as a raster module of the GRASS GIS software and, as such, is open source. It can be obtained from http://www.mergili.at/randomwalk.html. Besides other innovative functionalities, r.randomwalk serves with built-in functionalities for the derivation of an impact indicator index (III) map with values in the range 0-1. III is derived from multiple model runs with different combinations of input parameters varied in a random or controlled way. It represents the fraction of model runs predicting an impact at a given pixel and is evaluated against the observed impact area through an ROC Plot. The related tool r.ranger facilitates the automated generation and evaluation of many III maps from a variety of sets of parameter combinations. We employ r.randomwalk and r.ranger for parameter optimization and sensitivity analysis. Thereby we do not focus on parameter values, but - accounting for the uncertainty inherent in all parameters - on parameter ranges. In this sense, we demonstrate two strategies for parameter sensitivity analysis and optimization. We avoid to (i) use one-at-a-time parameter testing which would fail to account for interdependencies of the parameters, and (ii) to explore all possible
Bendall; Skinner
1998-10-01
To provide the most efficient conditions for spin decoupling with least RF power, master calibration curves are provided for the maximum centerband amplitude, and the minimum amplitude for the largest cycling sideband, resulting from STUD+ adiabatic decoupling applied during a single free induction decay. The principal curve is defined as a function of the four most critical experimental input parameters: the maximum amplitude of the RF field, RFmax, the length of the sech/tanh pulse, Tp, the extent of the frequency sweep, bwdth, and the coupling constant, Jo. Less critical parameters, the effective (or actual) decoupled bandwidth, bweff, and the sech/tanh truncation factor, beta, which become more important as bwdth is decreased, are calibrated in separate curves. The relative importance of nine additional factors in determining optimal decoupling performance in a single transient are considered. Specific parameters for efficient adiabatic decoupling can be determined via a set of four equations which will be most useful for 13C decoupling, covering the range of one-bond 13C1H coupling constants from 125 to 225 Hz, and decoupled bandwidths of 7 to 100 kHz, with a bandwidth of 100 kHz being the requirement for a 2 GHz spectrometer. The four equations are derived from a recent vector model of adiabatic decoupling, and experiment, supported by computer simulations. The vector model predicts an inverse linear relation between the centerband and maximum sideband amplitudes, and it predicts a simple parabolic relationship between maximum sideband amplitude and the product JoTp. The ratio bwdth/(RFmax)2 can be viewed as a characteristic time scale, tauc, affecting sideband levels, with tauc approximately Tp giving the most efficient STUD+ decoupling, as suggested by the adiabatic condition. Functional relationships between bwdth and less critical parameters, bweff and beta, for efficient decoupling can be derived from Bloch-equation calculations of the inversion profile
Panigrahi, Swapnesh; Fade, Julien; Ramachandran, Hema; Alouini, Mehdi
2016-07-11
The efficiency of using intensity modulated light for the estimation of scattering properties of a turbid medium and for ballistic photon discrimination is theoretically quantified in this article. Using the diffusion model for modulated photon transport and considering a noisy quadrature demodulation scheme, the minimum-variance bounds on estimation of parameters of interest are analytically derived and analyzed. The existence of a variance-minimizing optimal modulation frequency is shown and its evolution with the properties of the intervening medium is derived and studied. Furthermore, a metric is defined to quantify the efficiency of ballistic photon filtering which may be sought when imaging through turbid media. The analytical derivation of this metric shows that the minimum modulation frequency required to attain significant ballistic discrimination depends only on the reduced scattering coefficient of the medium in a linear fashion for a highly scattering medium. PMID:27410875
Estimation and Optimization of the Parameters Preserving the Lustre of the Fabrics
NASA Astrophysics Data System (ADS)
Prodanova, Krasimira
2009-11-01
The paper discusses the optimization of the continuance of the Damp-Heating Process of a steaming iron press machine, and the preserving of the lustre of the fabrics. In order to be obtained high qualitative damp-heating processing, it is necessary to monitor parameters such as temperature, damp, and pressure during the process. The purpose of the present paper is a mathematical model to be constructed that adequately describes the technological process using multivariate data analysis. It was established that the full factorial design of type 23 is not adequate. The research has proceeded with central rotatable design of experiment. The obtained model adequately describes the technological process of damp-heating treatment in the defined factor space. The present investigation is helpful to the technological improvement and modernization in sewing companies.
[Numerical simulation and optimization research of needle parameters in vial washing machine].
Zhang, Haowei; Li, Zhen; Liu, Ying; Liu, Haigang; Peng, Delian; Wei, Guoqin
2014-10-01
According to the working principle of vertical ultrasonic vial washing machine, receiving respective force of small water droplets on the inside wall of vials and the minimum air velocity of blowing off water droplets can be obtained based on the analysis of water-droplet-related parameters. The inside wall model of 7 mL vial created by GAMBIT was divided into fine grids. Then the Realizable k-epsilon Two Equation Turbulence Model was adopted and the flow field of vial by FLUENT software was simulated when air was flushing inside the wall. In that case, the optimal position, inner diameter and the corresponding minimum air velocity of needle can be acquired to meet the needs of vial washing machine applied to 7 mL vial. PMID:25764721
2014-01-01
Background In the recent study, optimum operational conditions of cathode compartment of microbial fuel cell were determined by using Response Surface Methodology (RSM) with a central composite design to maximize power density and COD removal. Methods The interactive effects of parameters such as, pH, buffer concentration and ionic strength on power density and COD removal were evaluated in two-chamber microbial batch-mode fuel cell. Results Power density and COD removal for optimal conditions (pH of 6.75, buffer concentration of 0.177 M and ionic strength of cathode chamber of 4.69 mM) improve by 17 and 5%, respectively, in comparison with normal conditions (pH of 7, buffer concentration of 0.1 M and ionic strength of 2.5 mM). Conclusions In conclusion, results verify that response surface methodology could successfully determine cathode chamber optimum operational conditions. PMID:24423039
Elements of an algorithm for optimizing a parameter-structural neural network
NASA Astrophysics Data System (ADS)
Mrówczyńska, Maria
2016-06-01
The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH), which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.
Optimization of ultrasound parameters for microbubble-nanoliposome complex-mediated delivery
Yoon, Young Il; Yoon, Tae-Jong; Lee, Hak Jong
2015-01-01
Purpose: The aim of this study was to identify the optimal ultrasound (US) parameters for gene and drug delivery. Methods: In order to target SkBr3, which is a breast cancer cell overexpressing the Her2 receptor, trastuzumab (Herceptin) was used. Micobubble-nanoliposome complex (MLC) was mixed with trastuzumab and stored overnight. Finally, MLC was combined with Her2Ab. A US device equipped with a 1-MHz probe was used for delivery to the cell. Several parameters, including intensity (w/cm2), time (minutes), and duty cycle (%), were varied within a range from 1 w/cm2, 1 minute, and 20% to 2 w/cm2, 2 minutes, and 60%, respectively. A confocal laser scanning microscope (CLSM) was used to confirm the delivery of MLC to the cells after US treatment. Results: MLC with fluorescent dyes and trastuzumab was synthesized successfully. By delivering MLC with Her2Ab to cells, the targeting effect of trastuzumab with MLC was confirmed by CLSM. The cell membranes showed green (fluorescein isothiocyanate) and red (Texas red) fluorescence but treatments with MLC without Her2Ab did not show any fluorescence. Optimal conditions for US-mediated delivery were 1 or 2 w/cm2, 2 minutes, and 60% (uptake ratio, 95.9% for 1 w/cm2 and 95.7% for 2 w/cm2) for hydrophobic materials and 2 w/cm2, 2 minutes, and 60% (uptake ratio, 95.0%) for hydrophilic materials. Conclusion: The greater the strength, duty cycle, and period of US application within the tested range, the more efficiently the fluorescent contents were conveyed. PMID:26044281
Singh, G; Kumar, A; Kumbhar, B K; Dar, B N
2015-02-01
Increasing demand of low calorie and high fibre containing products give impetus to dairy industry for development of a well palatable low calorie dairy products like paneer. The objective of the present study was to develop low-fat fibre-supplemented paneer. The ingredients were chosen for low-fat fibre- supplemented paneer to reduce the cost and calorie content besides providing the functional benefits. Optimization of ingredients was carried out in terms of independent variables viz wheat bran (0.4-0.8 %), maltodextrin (1-5 %), coagulation temperature (60-80 °C) and amount of citric acid solution (150-210 ml). Response Surface Methodology (RSM) was used to design the experiments and to select the optimum levels of ingredients. Paneer was made by using different levels of ingredients by coagulating hot milk using citric acid solution followed by pressing and dipping in chilled water for texturization. These parameters were evaluated in terms of physico-chemical parameters viz water activity, pH and acidity. Instrumental texture profile analysis (TPA) of paneer during optimization trials was done using TAXT 2i Texture Analyzer. The textural responses namely hardness, adhesiveness, springiness, cohesiveness, gumminess and chewiness were measured via Texture Analyzer. The sensory properties namely flavor, appearance, body and texture, mouth feel and overall acceptability of paneer samples were evaluated by a semi-trained panel of judges using 9-point hedonic scale. Full second order polynomial was developed to predict each response. All the textural and sensory responses were statistically analysed. PMID:25694679
Lathwal, Priyanka; Nehra, Kiran; Singh, Manpreet; Jamdagni, Pragati; Rana, Jogender S
2015-01-01
The enormous applications of conventional non-biodegradable plastics have led towards their increased usage and accumulation in the environment. This has become one of the major causes of global environmental concern in the present century. Polyhydroxybutyrate (PHB), a biodegradable plastic is known to have properties similar to conventional plastics, thus exhibiting a potential for replacing conventional non-degradable plastics. In the present study, a total of 303 different bacterial isolates were obtained from soil samples collected from the rhizospheric area of three crops, viz., wheat, mustard and sugarcane. All the isolates were screened for PHB (Poly-3-hydroxy butyric acid) production using Sudan Black staining method, and 194 isolates were found to be PHB positive. Based upon the amount of PHB produced, the isolates were divided into three categories: high, medium and low producers. Representative isolates from each category were selected for biochemical characterization; and for optimization of various culture parameters (carbon source, nitrogen source, C/N ratio, different pH, temperature and incubation time periods) for maximizing PHB accumulation. The highest PHB yield was obtained when the culture medium was supplemented with glucose as the carbon source, ammonium sulphate at a concentration of 1.0 g/l as the nitrogen source, and by maintaining the C/N ratio of the medium as 20:1. The physical growth parameters which supported maximum PHB accumulation included a pH of 7.0, and an incubation temperature of 30 degrees C for a period of 48 h. A few isolates exhibited high PHB accumulation under optimized conditions, thus showing a potential for their industrial exploitation. PMID:26638531
NASA Astrophysics Data System (ADS)
Choi, Seungyeon; Choi, Sunghoon; Kim, Ye-seul; Lee, Haenghwa; Lee, Donghoon; Jeon, Pil-Hyun; Jang, Dong-Hyuk; Kim, Hee-Joung
2016-03-01
Digital tomosynthesis system (DTS), which scans an object in a limited angle, has been considered as an innovative imaging modality which can present lower patient dose than computed tomography and solve the problem of poor depth resolution in conventional digital radiography. Although it has many powerful advantages, only breast tomosynthesis system has been adopted in many hospitals. In order to reduce the patient dose while maintaining image quality, the acquisition conditions need to be studied. In this study, we analyzed effective dose and image qualities of chest phantom using commercialized universal chest digital tomosynthesis (CDT) R/F system to study the optimized exposure parameters. We set 10 different acquisition conditions including the default acquisition condition by user manual of Shimadzu (100 kVp with 0.5 mAs). The effective dose was calculated from PCXMC software version 1.5.1 by utilizing the total X-ray exposure measured by ion chamber. The image quality was evaluated by signal difference to noise ratio (SDNR) in the regions of interest (ROIs) pulmonary arteries at different axial in-plane. We analyzed a figure of merit (FOM) which considers both the effective dose and the SDNR in order to determine the optimal acquisition condition. The results indicated that the most suitable acquisition parameters among 10 conditions were condition 7 and 8 (120 kVp with 0.04 mAs and 0.1 mAs, respectively), which indicated lower effective dose while maintaining reasonable SDNRs and FOMs for three specified regions. Further studies are needed to be conducted for detailed outcomes in CDT acquisition conditions.
NASA Astrophysics Data System (ADS)
Wang, Xin; Zhang, Lei; Fan, Juanjuan; Li, Yufang; Gong, Yao; Dong, Lei; Ma, Weiguang; Yin, Wangbao; Jia, Suotang
2015-11-01
Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy (LIBS) technique, which is expected to be capable of precise and accurate quantitative analysis. It was found that there was great potential to improve the signal quality and repeatability by reducing the laser beam divergence angle using a suitable beam expander (BE). In the present work, the influences of several experimental parameters for the case with BE are studied in order to optimize the analytical performances: the signal to noise ratio (SNR) and the relative standard deviation (RSD). We demonstrate that by selecting the optimal experimental parameters, the BE-included LIBS setup can give higher SNR and lower RSD values of the line intensity normalized by the whole spectrum area. For validation purposes, support vector machine (SVM) regression combined with principal component analysis (PCA) was used to establish a calibration model to realize the quantitative analysis of the ash content. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The measurement accuracy presented here for ash content analysis is estimated to be 0.31%, while the average relative error is 2.36%. supported by the 973 Program of China (No. 2012CB921603), National Natural Science Foundation of China (Nos. 61475093, 61127017, 61178009, 61108030, 61378047, 61275213, 61475093, and 61205216), the National Key Technology R&D Program of China (No. 2013BAC14B01), the Shanxi Natural Science Foundation (Nos. 2013021004-1 and 2012021022-1), the Shanxi Scholarship Council of China (Nos. 2013-011 and 2013-01), and the Program for the Outstanding Innovative Teams of Higher Learning Institutions of Shanxi, China
Adam, Asrul; Shapiai, Mohd Ibrahim; Tumari, Mohd Zaidi Mohd; Mohamad, Mohd Saberi; Mubin, Marizan
2014-01-01
Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236
Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi
2014-01-01
Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236
Automatic Parameter Tuning for the Morpheus Vehicle Using Particle Swarm Optimization
NASA Technical Reports Server (NTRS)
Birge, B.
2013-01-01
A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.
NASA Astrophysics Data System (ADS)
Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen
2015-12-01
Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.
Singh, Gurmeet; Jain, Vivek; Gupta, Dheeraj; Ghai, Aman
2016-09-01
Orthopaedic surgery involves drilling of bones to get them fixed at their original position. The drilling process used in orthopaedic surgery is most likely to the mechanical drilling process and there is all likelihood that it may harm the already damaged bone, the surrounding bone tissue and nerves, and the peril is not limited at that. It is very much feared that the recovery of that part may be impeded so that it may not be able to sustain life long. To achieve sustainable orthopaedic surgery, a surgeon must try to control the drilling damage at the time of bone drilling. The area around the holes decides the life of bone joint and so, the contiguous area of drilled hole must be intact and retain its properties even after drilling. This study mainly focuses on optimization of drilling parameters like rotational speed, feed rate and the type of tool at three levels each used by Taguchi optimization for surface roughness and material removal rate. The confirmation experiments were also carried out and results found with the confidence interval. Scanning electrode microscopy (SEM) images assisted in getting the micro level information of bone damage. PMID:27254280
NASA Astrophysics Data System (ADS)
Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen
2016-07-01
Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.
Optimization of microstructural parameters for hard-soft nanocomposite permanent magnets
NASA Astrophysics Data System (ADS)
Wysocki, Aleksander; Janicka, Karolina; Antropov, Vladimir
2015-03-01
We use finite temperature micromagnetic simulations to investigate hysteretic properties of hard/soft nanocomposite permanent magnets. Several generic geometries are considered including bilayers, superlatices, and different core-shell structures. We perform multiparameter optimization of the permanent magnet properties with respect to grain sizes, texture, and soft phase volume content. In addition, the effects of thermal fluctuations and the variation of the micromagnetic parameters at the hard/soft interface are studied. In particular, we find that the properties show typically only a small dependence on the interface exchange unless it becomes order of magnitude smaller than exchange in common 3d magnets in which case energy products and optimal soft phase content decrease dramatically. This behavior is, however, different for bilayer system with perpendicular anisotropy. Here we demonstrate that the competition between dipolar interactions and the interlayer exchange leads to significant dependence on the latter even for moderate exchange coupling strengths. Our results are compared with existing experimental data for Nd2Fe14B/Fe, SmCo5/Co, and MnBi/FeCo nanocomposites. This work was supported by the project: ``Solid State Processing of Fully Dense Anisotropic Nanocomposite Magnets,'' ARPA-E Control Number 0670-4987. Ames Laboratory is operated by Iowa State University under Contract DE-AC02-07CH11358.
NASA Astrophysics Data System (ADS)
Mozdgir, A.; Mahdavi, Iraj; Seyyedi, I.; Shiraqei, M. E.
2011-06-01
An assembly line is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The assembly line balancing problem arises and has to be solved when an assembly line has to be configured or redesigned. The so-called simple assembly line balancing problem (SALBP), a basic version of the general problem, has attracted attention of researchers and practitioners of operations research for almost half a century. There are four types of objective functions which are considered to this kind of problem. The versions of SALBP may be complemented by a secondary objective which consists of smoothing station loads. Many heuristics have been proposed for the assembly line balancing problem due to its computational complexity and difficulty in identifying an optimal solution and so many heuristic solutions are supposed to solve this problem. In this paper a differential evolution algorithm is developed to minimize workload smoothness index in SALBP-2 and the algorithm parameters are optimized using Taguchi method.
On the optimal use of fictitious time in variation of parameters methods with application to BG14
NASA Technical Reports Server (NTRS)
Gottlieb, Robert G.
1991-01-01
The optimal way to use fictitious time in variation of parameter methods is presented. Setting fictitious time to zero at the end of each step is shown to cure the instability associated with some types of problems. Only some parameters are reinitialized, thereby retaining redundant information.
Influence of deposition parameters on residual stress of YbF3 thin film
NASA Astrophysics Data System (ADS)
Zhang, Yao-ping; Fan, Jun-qi; Long, Guo-yun
2016-01-01
YbF3 was proposed as a substitute for ThF4 in anti-reflection or reflection coatings for the infrared range, and the residual stress of YbF3 thin film using APS plasma ion assisted deposition(PIAD) was studied. From the results, we found the anode voltage of PIAD has a large effect on the residual stress of YbF3 thin film, and the refractive index of YbF3 produced with PIAD was higher than without it, with a possible reason close to packing density. Finally, we produced multi-layer reflection coating on a 260mm diameter mono-crystalline silicon substrate. Its surface contour was approximately 0.240λ (λ＝632.8nm), and the absorption was lower than 200ppm, which can satisfy the practical requirement.
Shapiro, C.S.
1984-08-01
The GLODEP2 computer code was utilized to determine biological impact to humans on a global scale using up-to-date estimates of biological risk. These risk factors use varied biological damage models for assessing effects. All the doses reported are the unsheltered, unweathered, smooth terrain, external gamma dose. We assume the unperturbed atmosphere in determining injection and deposition. Effects due to ''nuclear winter'' may invalidate this assumption. The calculations also include scenarios that attempt to assess the impact of the changing nature of the nuclear stockpile. In particular, the shift from larger to smaller yield nuclear devices significantly changes the injection pattern into the atmosphere, and hence significantly affects the radiation doses that ensue. We have also looked at injections into the equatorial atmosphere. In total, we report here the results for 8 scenarios. 10 refs., 6 figs., 11 tabs.
Stieler, Florian; Yan, Hui; Lohr, Frank; Wenz, Frederik; Yin, Fang-Fang
2009-01-01
Background Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI) guided system was developed and examined. Methods The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS). Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be "translated" to a set of "if-then rules" for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS), was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints). The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules. Results Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02%) and membership functions (3.9%), thus suggesting that the "behavior" of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%. Conclusion The study demonstrated a
Optimization of Machining Process Parameters for Surface Roughness of Al-Composites
NASA Astrophysics Data System (ADS)
Sharma, S.
2013-10-01
Metal matrix composites (MMCs) have become a leading material among the various types of composite materials for different applications due to their excellent engineering properties. Among the various types of composites materials, aluminum MMCs have received considerable attention in automobile and aerospace applications. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like silicon carbide particles. In the present investigation Al-SiC composite was produced by stir casting process. The Brinell hardness of the alloy after SiC addition had increased from 74 ± 2 to 95 ± 5 respectively. The composite was machined using CNC turning center under different machining parameters such as cutting speed (S), feed rate (F), depth of cut (D) and nose radius (R). The effect of machining parameters on surface roughness (Ra) was studied using response surface methodology. Face centered composite design with three levels of each factor was used for surface roughness study of the developed composite. A response surface model for surface roughness was developed in terms of main factors (S, F, D and R) and their significant interactions (SD, SR, FD and FR). The developed model was validated by conducting experiments under different conditions. Further the model was optimized for minimum surface roughness. An error of 3-7 % was observed in the modeled and experimental results. Further, it was fond that the surface roughness of Al-alloy at optimum conditions is lower than that of Al-SiC composite.
Sensitivity study and parameter optimization of OCD tool for 14nm finFET process
NASA Astrophysics Data System (ADS)
Zhang, Zhensheng; Chen, Huiping; Cheng, Shiqiu; Zhan, Yunkun; Huang, Kun; Shi, Yaoming; Xu, Yiping
2016-03-01
Optical critical dimension (OCD) measurement has been widely demonstrated as an essential metrology method for monitoring advanced IC process in the technology node of 90 nm and beyond. However, the rapidly shrunk critical dimensions of the semiconductor devices and the increasing complexity of the manufacturing process bring more challenges to OCD. The measurement precision of OCD technology highly relies on the optical hardware configuration, spectral types, and inherently interactions between the incidence of light and various materials with various topological structures, therefore sensitivity analysis and parameter optimization are very critical in the OCD applications. This paper presents a method for seeking the optimum sensitive measurement configuration to enhance the metrology precision and reduce the noise impact to the greatest extent. In this work, the sensitivity of different types of spectra with a series of hardware configurations of incidence angles and azimuth angles were investigated. The optimum hardware measurement configuration and spectrum parameter can be identified. The FinFET structures in the technology node of 14 nm were constructed to validate the algorithm. This method provides guidance to estimate the measurement precision before measuring actual device features and will be beneficial for OCD hardware configuration.
Evaluation and optimization of handle design parameters of a grass trimming machine.
Mallick, Zulquernain
2008-01-01
The grass trimming machine is a widely used agricultural machine for cutting grass by the roadside and in other areas in Malaysia. Hand-arm vibration (HAV) syndrome is very common among workers operating power tools and performing similar work for extended periods. Grass trimming involves the use of a motorized cutter spinning at high speed, resulting in high levels of HAV among its operators. The existing D-shape handle causes HAV-related stress and operational load in operators. This research proposes a new design of a handle of the grass trimming machine. When this new design was compared with the old one, it was found that the new handle resulted in 18% lower HAV. To find the lowest HAV, 3 critical parameters of the new handle (length, angle and material of the cap of the handle) were optimized using the Taguchi quality tool. Appropriately selected parameters of the new handle significantly reduced the occurrence of HAV among grass trimmers. PMID:18954544
Application of GA-SVM method with parameter optimization for landslide development prediction
NASA Astrophysics Data System (ADS)
Li, X. Z.; Kong, J. M.
2014-03-01
Prediction of the landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. The support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of the SVM model. In this study, we present an application of genetic algorithm and support vector machine (GA-SVM) method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in a hydro-electrical engineering area of southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models, and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest root mean square error (RMSE) of 0.0009 and the highest relation index (RI) of 0.9992.
Application of GA-SVM method with parameter optimization for landslide development prediction
NASA Astrophysics Data System (ADS)
Li, X. Z.; Kong, J. M.
2013-10-01
Prediction of landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. Support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of SVM model. In this study, we presented an application of GA-SVM method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in some hydro - electrical engineering area of Southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that, the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest RSME of 0.0009 and the biggest RI of 0.9992.
Determining System Parameters for Optimal Performance of Hybrid DS/FFH Spread-Spectrum
Ma, Xiao; Olama, Mohammed M; Kuruganti, Phani Teja; Smith, Stephen Fulton; Djouadi, Seddik M
2012-01-01
In recent years there has been great interest in using hybrid spread-spectrum (HSS) techniques for commercial applications, particularly in the Smart Grid, in addition to their use in military communications because they accommodate high data rates with high link integrity, even in the presence of significant multipath effects and interfering signals. A highly useful form of this transmission technique for many types of command, control, and sensing applications is the specific code-related combination of standard direct sequence (DS) modulation with "fast" frequency hopping (FFH), denoted hybrid DS/FFH, wherein multiple frequency hops occur within a single data-bit time. In this paper, an optimization problem is formulated that maximizes the DS/FFH communication system performance in terms of probability of bit error and solves for the system design parameters. The objective function is non-convex and can be solved by applying the Karush-Kuhn-Tucker conditions. System design parameters of interest are the length of the DS code sequence, number of frequency hopping channels, number of channels corrupted by wide-band jamming, and number of hops per bit. The proposed formulation takes into account the effects from wide-band and partial-band jamming, multi-user interference and/or varying degrees of Rayleigh and Rician multipath fading. Numerical results are presented to demonstrate the method s viability.
Parameters optimization in a fission-fusion system with a mirror machine based neutron source
NASA Astrophysics Data System (ADS)
Yurov, D. V.; Anikeev, A. V.; Bagryansky, P. A.; Brednikhin, S. A.; Frolov, S. A.; Lezhnin, S. I.; Prikhodko, V. V.
2012-06-01
Long-lived fission products utilization is a problem of high importance for the modern nuclear reactor technology. BINP jointly with NSI RAS develops a conceptual design of a hybrid sub-critical minor actinides burner with a neutron source based on the gas dynamic mirror machine (GDT) to resolve the stated task. A number of modelling tools was created to calculate the main parameters of the device. First of the codes, GENESYS, is a zero-dimensional code, designed for plasma dynamics numerical investigation in a GDT-based neutron source. The code contains a Monte-Carlo module for the determination of linear neutron emission intensity along the machine axis. Fuel blanket characteristics calculation was implemented by means of a static Monte-Carlo code NMC. Subcritical core, which has been previously analyzed by OECD-NEA, was used as a template for the fuel blanket of the modelled device. This article represents the codes used and recent results of the described system parameters optimization. Particularly, optimum emission zone length of the source and core multiplicity dependence on buffer zone thickness were defined.
NASA Astrophysics Data System (ADS)
Haghmoradi, Navid; Dehghanian, Changiz; Yari, Saeed
2016-07-01
The present work explores how deposition parameters affect structural and morphological characteristics of ZnNi/nano-SiC composites in order to engineer an environmentally benign corrosion-resistant coating. In this regard, ZnNi and ZnNi coatings containing SiC nanoparticles were electrodeposited from chloride bath by direct current method, and the effects of SiC concentration, deposition current density and two types of surfactant (sodium dodecyl sulfate, SDS, and hexadecyltrimethyl ammonium bromide, HTAB) were investigated. Increasing SiC nanoparticles concentration in the electrolyte enhances the SiC content of the coating and can affect the coating composition, structure and morphology. Elevation of deposition current density may reduce SiC content of the coating, yet this decline can be compensated by the addition of HTAB. Application of 11 g/L SiC nanoparticles produced a coating with a more even surface and less porosity that had the highest corrosion resistance. The presence of nanoparticles seemingly reduces the available surface for electrochemical reactions and decelerates corrosion.
NASA Astrophysics Data System (ADS)
Siddiqui, Jamil; Hussain, Tousif; Ahmad, Riaz; Khalid, Nida
2015-06-01
Effects of deposition angle and axial distance on the structural and mechanical properties of niobium nitride synthesized by a dense plasma focus (DPF) system are studied. The x-ray diffraction (XRD) confirms that the deposition parameters affect the growth of multi-phase niobium nitride. Scanning electron microscopy (SEM) shows the granular surface morphology with strong thermally assisted coagulation effects observed at the 5-cm axial distance. The non-porous granular morphology observed at the 9-cm distance along the anode axis is different from those observed at deposition angles of 10° and 20°. Energy dispersive x-ray (EDX) spectroscopy reveals the maximum nitrogen content at the shortest (5 cm) axial position. Atomic force microscopy (AFM) exhibits that the roughness of coated films varies for coatings synthesized at different axial and angular positions, and the Vickers micro-hardness test shows that a maximum hardness value is (08.44 ± 0.01) GPa for niobium nitride synthesized at 5-cm axial distance, which is about 500% more than that of a virgin sample. Project supported by the HEC, Pakistan.
Aljimaee, Yazeed HM; El-Helw, Abdel-Rahim M; Ahmed, Osama AA; El-Say, Khalid M
2015-01-01
Background Carvedilol (CVD) is used for the treatment of essential hypertension, heart failure, and systolic dysfunction after myocardial infarction. Due to its lower aqueous solubility and extensive first-pass metabolism, the absolute bioavailability of CVD does not exceed 30%. To overcome these drawbacks, the objective of this work was to improve the solubility and onset of action of CVD through complexation with hydroxypropyl-β-cyclodextrin and formulation of the prepared complex as orodispersible tablets (ODTs). Methods Compatibility among CVD and all tablet excipients using differential scanning calorimetry and Fourier transform infrared spectroscopy, complexation of CVD with different polymers, and determination of the solubility of CVD in the prepared complexes were first determined. A Box-Behnken design (BBD) was used to study the effect of tablet formulation variables on the characteristics of the prepared tablets and to optimize preparation conditions. According to BBD design, 15 formulations of CVD-ODTs were prepared by direct compression and then evaluated for their quality attributes. The relative pharmacokinetic parameters of the optimized CVD-ODTs were compared with those of the marketed CVD tablet. A single dose, equivalent to 2.5 mg/kg CVD, was administered orally to New Zealand white rabbits using a double-blind, randomized, crossover design. Results The solubility of CVD was improved from 7.32 to 22.92 mg/mL after complexation with hydroxypropyl-β-cyclodextrin at a molar ratio of 1:2 (CVD to cyclodextrin). The formulated CVD-ODTs showed satisfactory results concerning tablet hardness (5.35 kg/cm2), disintegration time (18 seconds), and maximum amount of CVD released (99.72%). The pharmacokinetic data for the optimized CVD-ODT showed a significant (P<0.05) increase in maximum plasma concentration from 363.667 to 496.4 ng/mL, and a shortening of the time taken to reach maximum plasma concentration to 2 hours in comparison with the marketed tablet
NASA Astrophysics Data System (ADS)
nabili, sara; shahbazi majd, nafiseh
2013-04-01
Liquefaction has been a source of major damages during severe earthquakes. To evaluate this phenomenon there are several stress, strain and energy based approaches. Use of the energy method has been more focused by researchers due to its advantages with respect to other approaches. The use of the energy concept to define the liquefaction potential is validated through laboratory element and centrifuge tests as well as field studies. This approach is based on the hypothesis that pore pressure buildup is directly related to the dissipated energy in sands which is the accumulated areas between the stress-strain loops. Numerous investigations were performed to find a relationship which correlates the dissipated energy to the soil parameters, but there are not sufficient studies to relate this dissipated energy, known as demand energy, concurrently, to the seismological and the soil parameters. The aim of this paper is to investigate the dependency of the demand energy in sands to seismological and the soil parameters. To perform this task, an effective stress analysis has been executed using FLAC finite difference program. Finn model, which is a built-in constitutive model implemented in FLAC program, was utilized. Since an important stage to predict the liquefaction is the prediction of excess pore water pressure at a given point, a simple numerical framework is presented to assess its generation during a cyclic loading in a given centrifuge test. According to the results, predicted excess pore water pressures did not closely match to the measured excess pore water pressure values in the centrifuge test but they can be used in the numerical assessment of excess pore water pressure with an acceptable degree of preciseness. Subsequently, the centrifuge model was reanalyzed using several real earthquake acceleration records with different seismological parameters such as earthquake magnitude and Hypocentral distance. The accumulated energies (demand energy) dissipated in
Study of Optimal Cavity Parameter in Optically Pumped D2O Gas Terahertz Laser
NASA Astrophysics Data System (ADS)
He, Zhihong; Zhang, Yuping; Zhang, Huiyun; Zhang, Qingmao; Liao, Jianhong; Zhou, Yongheng; Liu, Songhao; Luo, Xizhang
2010-05-01
Heavy water gas (D2O gas) which owns special structure property, can generate terahertz radiation by optically pumping technology, and its 385 μm wavelength radiation can be widely used. In this research, on the base of semi-classical density matrix theory, we set up a three-level energy system as its theoretical model, a TEA-CO2 laser 9R (22) output line (λ = 9.26 μm) acted as pumping source, D2O gas molecules were operating medium, the expressions of pumping absorption coefficient G p and Terahertz signal gain coefficient G s were deduced. It was shown that the gain of Terahertz signal was related with the energy-level parameters of operating molecules and some operating parameters of the Terahertz laser cavity, mainly including cavity length. By means of iteration method, the output power density of Terahertz pulse signal was calculated numerically. Changing the parameter of cavity length and keeping others steady, the relationship curve between the output power intensity (Is) of Terahertz pulse laser and the operating cavity length (L) was obtained. The curve showed that the power intensity (Is) increased with cavity length (L) in a certain range, but decreased when the length (L) exceeded some value because of the absorption effect, and there was an optimal cavity length for the highest output power. We used a grating tuned TEA-CO2 laser as pumping power and a sample tube of variable length in 70-160 cm as terahertz laser operating cavity to experiment. The results of theoretical calculation and experiment matched with each other, and it is helpful for miniaturizing terahertz laser volume to make it practical.
NASA Astrophysics Data System (ADS)
Venkatesan, K.; Ramanujam, R.; Kuppan, P.
2016-04-01
This paper presents a parametric effect, microstructure, micro-hardness and optimization of laser scanning parameters (LSP) on heating experiments during laser assisted machining of Inconel 718 alloy. The laser source used for experiments is a continuous wave Nd:YAG laser with maximum power of 2 kW. The experimental parameters in the present study are cutting speed in the range of 50-100 m/min, feed rate of 0.05-0.1 mm/rev, laser power of 1.25-1.75 kW and approach angle of 60-90°of laser beam axis to tool. The plan of experiments are based on central composite rotatable design L31 (43) orthogonal array. The surface temperature is measured via on-line measurement using infrared pyrometer. Parametric significance on surface temperature is analysed using response surface methodology (RSM), analysis of variance (ANOVA) and 3D surface graphs. The structural change of the material surface is observed using optical microscope and quantitative measurement of heat affected depth that are analysed by Vicker's hardness test. The results indicate that the laser power and approach angle are the most significant parameters to affect the surface temperature. The optimum ranges of laser power and approach angle was identified as 1.25-1.5 kW and 60-65° using overlaid contour plot. The developed second order regression model is found to be in good agreement with experimental values with R2 values of 0.96 and 0.94 respectively for surface temperature and heat affected depth.
NASA Astrophysics Data System (ADS)
Naumova, Valeriya; Peter, Steffen
2014-12-01
Inspired by several recent developments in regularization theory, optimization, and signal processing, we present and analyze a numerical approach to multi-penalty regularization in spaces of sparsely represented functions. The sparsity prior is motivated by the largely expected geometrical/structured features of high-dimensional data, which may not be well-represented in the framework of typically more isotropic Hilbert spaces. In this paper, we are particularly interested in regularizers which are able to correctly model and separate the multiple components of additively mixed signals. This situation is rather common as pure signals may be corrupted by additive noise. To this end, we consider a regularization functional composed by a data-fidelity term, where signal and noise are additively mixed, a non-smooth and non-convex sparsity promoting term, and a penalty term to model the noise. We propose and analyze the convergence of an iterative alternating algorithm based on simple iterative thresholding steps to perform the minimization of the functional. By means of this algorithm, we explore the effect of choosing different regularization parameters and penalization norms in terms of the quality of recovering the pure signal and separating it from additive noise. For a given fixed noise level numerical experiments confirm a significant improvement in performance compared to standard one-parameter regularization methods. By using high-dimensional data analysis methods such as principal component analysis, we are able to show the correct geometrical clustering of regularized solutions around the expected solution. Eventually, for the compressive sensing problems considered in our experiments we provide a guideline for a choice of regularization norms and parameters.
Photoacoustic design parameter optimization for deep tissue imaging by numerical simulation
NASA Astrophysics Data System (ADS)
Wang, Zhaohui; Ha, Seunghan; Kim, Kang
2012-02-01
A new design of light illumination scheme for deep tissue photoacoustic (PA) imaging, a light catcher, is proposed and evaluated by in silico simulation. Finite element (FE)-based numerical simulation model was developed for photoacoustic (PA) imaging in soft tissues. In this in silico simulation using a commercially available FE simulation package (COMSOL MultiphysicsTM, COMSOL Inc., USA), a short-pulsed laser point source (pulse length of 5 ns) was placed in water on the tissue surface. Overall, four sets of simulation models were integrated together to describe the physical principles of PA imaging. Light energy transmission through background tissues from the laser source to the target tissue or contrast agent was described by diffusion equation. The absorption of light energy and its conversion to heat by target tissue or contrast agent was modeled using bio-heat equation. The heat then causes the stress and strain change, and the resulting displacement of the target surface produces acoustic pressure. The created wide-band acoustic pressure will propagate through background tissues to the ultrasound detector, which is governed by acoustic wave equation. Both optical and acoustical parameters in soft tissues such as scattering, absorption, and attenuation are incorporated in tissue models. PA imaging performance with different design parameters of the laser source and energy delivery scheme was investigated. The laser light illumination into the deep tissues can be significantly improved by up to 134.8% increase of fluence rate by introducing a designed compact light catcher with highly reflecting inner surface surrounding the light source. The optimized parameters through this simulation will guide the design of PA system for deep tissue imaging, and help to form the base protocols of experimental evaluations in vitro and in vivo.
NASA Astrophysics Data System (ADS)
Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li
2015-05-01
In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.
NASA Astrophysics Data System (ADS)
Alston, Robert; Iyer, Shanthi; Bradley, Tanina; Lewis, Jay; Cunningham, Garry; Forsythe, Eric
2014-02-01
Low temperature gallium tin zinc oxide (GSZO) based thin film transistors fabricated on silicon has been investigated as a potential indium free transparent amorphous oxide semiconductor thin film transistor (TAOS TFT) with potential device applications on plastic substrates. A comprehensive and detailed study on the performance of GSZO TFTs has been carried out by studying the effects of processing parameters such as deposition temperature and annealing temperature/duration, as well as the channel thickness with all temperatures held below 150 °C. Variety of characterization techniques, namely Rutherford backscattering (RBS), x-ray photoelectron spectroscopy (XPS) and x-ray reflectivity (XRR) in addition to I-V and C-V measurements were employed to determine the effects of the above parameters on the composition and quality of the channel. Optimized TFT characteristics of ID=3×10-7 A, ION/OFF =2×106, VON ~ -2 V, SS ~ 1 V/dec and μFE = 0.14 cm2/V· s with a ΔVON of 3.3 V under 3 hours electrical stress were produced.
NASA Technical Reports Server (NTRS)
Noffke, Nora; Knoll, Andrew H.
2001-01-01
Shallow-marine, siliciclastic depositional systems are governed by physical sedimentary processes. Mineral precipitation or penecontemporaneous cementation play minor roles. Today, coastal siliciclastic environments may be colonized by a variety of epibenthic, mat-forming cyanobacteria. Studies on microbial mats showed that they are not randomly distributed in modern tidal environments. Distribution and abundancy is mainly function of a particular sedimentary facies. Fine-grained sands composed of "clear" (translucent) quartz particles constitute preferred substrates for cyanobacteria. Mat-builders also favor sites characterized by moderate hydrodynamic flow regimes, which permit biomass enrichment and construction of mat fabrics without lethal burial of mat populations by fine sediments. A comparable facies relationship can be observed in ancient siliciclastic shelf successions from the terminal Neoproterozoic Nama Group, Namibia. Wrinkle structures that record microbial mats are present but sparsely distributed in mid- to inner shelf sandstones of the Nudaus Formation. The sporadic distribution of these structures reflects both the narrow ecological window that governs mat development and the distinctive taphonomic conditions needed to preserve the structures. These observations caution that statements about changing mat abundance across the Proterozoic-Cambrian boundary must be firmly rooted in paleoenvironmental and taphonomic analysis. Understanding the factors that influence the formation and preservation of microbial structures in siliciclastic regimes can facilitate exploration for biological signatures in Earth's oldest rocks. Moreover, insofar as these structures can be preserved on bedding surfaces and are not easily mimicked by physical processes, they constitute a set of biological markers that can be searched for on Mars by remotely controlled rovers.
NASA Technical Reports Server (NTRS)
Stahara, S. S.; Elliott, J. P.; Spreiter, J. R.
1983-01-01
An investigation was conducted to continue the development of perturbation procedures and associated computational codes for rapidly determining approximations to nonlinear flow solutions, with the purpose of establishing a method for minimizing computational requirements associated with parametric design studies of transonic flows in turbomachines. The results reported here concern the extension of the previously developed successful method for single parameter perturbations to simultaneous multiple-parameter perturbations, and the preliminary application of the multiple-parameter procedure in combination with an optimization method to blade design/optimization problem. In order to provide as severe a test as possible of the method, attention is focused in particular on transonic flows which are highly supercritical. Flows past both isolated blades and compressor cascades, involving simultaneous changes in both flow and geometric parameters, are considered. Comparisons with the corresponding exact nonlinear solutions display remarkable accuracy and range of validity, in direct correspondence with previous results for single-parameter perturbations.
Sathiyamoorthy, V.; Sekar, T.; Elango, N.
2015-01-01
Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm3/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm3/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models. PMID:26167538
Sathiyamoorthy, V; Sekar, T; Elango, N
2015-01-01
Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm(3)/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm(3)/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models. PMID:26167538
Optimization of exposure parameters for pediatric chest x-ray imaging
NASA Astrophysics Data System (ADS)
Park, Hye-Suk; Kim, Ye-Seul; Kim, Hee-Joung
2012-03-01
The pediatric patients are more susceptible to the effects of ionizing radiation than adults. Pediatric patients are smaller, more radiosensitive than adult patients and many cannot stand unassisted. Their characteristics affect the method of imaging projection and how dose is optimized. The purpose of this study was to investigate the effect of various technical parameters for the dose optimization in pediatric chest radiological examinations by evaluating effective dose and effective detective quantum efficiency (eDQE) including the scatter radiation from the object, the blur caused by the focal spot, geometric magnification and detector characteristics. For the tube voltages ranging from 40 to 90 kV in 10 kV increments at the focus-to-detector distance of 100, 110, 120, 150, 180 cm, the eDQE was evaluated at same effective dose. The results showed that the eDQE was largest at 60 kVp without and with an anti-scatter grid. Especially, the eDQE was considerably higher without the use of an anti-scatter grid on equivalent effective dose. This indicates that the reducing the scatter radiation did not compensate for the loss of absorbed effective photons in the grid. When the grid is not used the eDQE increased with increasing focus-to-detector distance because of the greater effective modulation transfer function (eMTF) with the lower focal spot blurring. In conclusion, for pediatric patients, the amount of scattered radiation is less, and the amount of grid attenuation increased unnecessary radiation dose.
Si-based thin film coating on Y-TZP: Influence of deposition parameters on adhesion of resin cement
NASA Astrophysics Data System (ADS)
Queiroz, José Renato Cavalcanti; Nogueira Junior, Lafayette; Massi, Marcos; Silva, Alecssandro de Moura; Bottino, Marco Antonio; Sobrinho, Argemiro Soares da Silva; Özcan, Mutlu
2013-10-01
This study evaluated the influence of deposition parameters for Si-based thin films using magnetron sputtering for coating zirconia and subsequent adhesion of resin cement. Zirconia ceramic blocks were randomly divided into 8 groups and specimens were either ground finished and polished or conditioned using air-abrasion with alumina particles coated with silica. In the remaining groups, the polished specimens were coated with Si-based film coating with argon/oxygen magnetron discharge at 8:1 or 20:1 flux. In one group, Si-based film coating was performed on air-abraded surfaces. After application of bonding agent, resin cement was bonded. Profilometry, goniometry, Energy Dispersive X-ray Spectroscopy and Rutherford Backscattering Spectroscopy analysis were performed on the conditioned zirconia surfaces. Adhesion of resin cement to zirconia was tested using shear bond test and debonded surfaces were examined using Scanning Electron Microscopy. Si-based film coating applied on air-abraded rough zirconia surfaces increased the adhesion of the resin cement (22.78 ± 5.2 MPa) compared to those of other methods (0-14.62 MPa) (p = 0.05). Mixed type of failures were more frequent in Si film coated groups on either polished or air-abraded groups. Si-based thin films increased wettability compared to the control group but did not change the roughness, considering the parameters evaluated. Deposition parameters of Si-based thin film and after application of air-abrasion influenced the initial adhesion of resin cement to zirconia.
NASA Astrophysics Data System (ADS)
Qian, Y.; Yang, B.; Lin, G.; Leung, L.; Zhang, Y.
2011-12-01
Uncertainty Quantification (UQ) of a model's tunable parameters is often treated as an optimization procedure to minimize the difference between model results and observations at different time and spatial scales. In current tuning process in global climate model, however, we might be generating a set of tunable parameters that approximate the observed climate but via an unrealistic balance of physical processes and/or compensating errors over different regions in the globe. In this study, we run the Weather Research and Forecasting (WRF) regional model constrained by the reanalysis data over the South