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
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.
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.
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, 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.
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
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.
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.
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
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.
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.
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.
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
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.
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
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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
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.
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.
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)
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.
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.
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
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.
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.
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.
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
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
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
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.
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.
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
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
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
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.
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
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 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.
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.
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
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
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.
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
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
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)
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.
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.
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.
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
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
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
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 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