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.
NASA Astrophysics Data System (ADS)
Zhang, Tao; Liu, Xuan; Sun, Fanghong; Zhang, Zhiming
2015-09-01
In the present work, microcrystalline diamond powders are deposited by using a bias-enhanced hot filament chemical vapor deposition (HFCVD) apparatus. Mirror-polished silicon wafers are served as substrates, pretreated by the scratching process for 10-15 s. A systematic investigation is under taken into the combined effects of deposition parameters on nucleation and growth characteristics of microcrystalline diamonds, based on the orthogonal collocation method. The results show that the morphology of final microcrystals depend mainly on that of nuclei rather than the deposition parameters, while the quality and grain size of crystals largely depend upon the deposition parameters. A high reactor pressure (3-4.5 kPa) in the nucleation process is a necessary condition for depositing the ideal nuclei with the single-crystal structure and euhedral diamond faces. Then under a set of optimized growth parameters, the final single crystals exhibit the regular-shaped morphology and smooth surfaces. The CVD microcrystals with various grain sizes in the range of 0.3-2 μm can be obtained by regulating the deposition time; moreover, they have a dramatically narrow particle size distribution, meeting the requirements on certain types of commercial powders without the process of sieving grain.
NASA Astrophysics Data System (ADS)
Kuai, Su-Lan; Hu, Xing-Fang; Haché, Alain; Truong, Vo-Van
2004-06-01
High-quality polystyrene colloidal crystals were fabricated from aqueous solutions with a vertical deposition technique. The role of sphere size, volume fraction, relative humidity (RH), evaporation temperature and the final drying conditions on the film quality were investigated. We found that all those parameters must be taken into account in order to achieve highest quality for a given particle size. With particles of 300 nm in diameter, the optimal conditions were found to be a 0.1-0.2% volume fraction, an RH between 80% and 90%, an evaporation temperature near 60°C and a quasi-equilibrium drying process.
Guo, Qing-Lin; Cui, Yong-Liang; Chen, Jian-Hui; Zhang, Jin-Ping; Huai, Su-Fang; Liu, Bao-Ting; Chen, Jin-Zhong
2010-12-01
The plasma emission spectra generated during the deposition process of Si-based thin films by radio frequency (RF) magnetron sputtering using Cu and Al targets in an argon atmosphere were acquired by the plasma analysis system, which consists of a magnetron sputtering apparatus, an Omni-lambda300 series grating spectrometer, a CCD data acquisition system and an optical fiber transmission system. The variation in Cu and Al plasma emission spectra intensity depending on sputtering conditions, such as sputtering time, sputtering power, the target-to-substrate distance and deposition pressure, was studied by using the analysis lines Cu I 324. 754 nm, Cu I 327. 396 nm, Cu I 333. 784 nm, Cu I 353. 039 nm, Al I 394. 403 nm and Al I 396. 153 nm. Compared with the option of experimental parameters of thin films deposited by RF magnetron sputtering, it was shown that emission spectra analysis methods play a guiding role in optimizing the deposition conditions of thin films in RF magnetron sputtering.
Parameter optimization for controlling aluminum loss when laser depositing Ti-6Al-4V
NASA Astrophysics Data System (ADS)
Barclay, Richard Charles
The ability to predict the mechanical properties of engineering materials is crucial to the manufacturing of advanced products. In the aerospace industry, Ti-6Al-4V is commonly used to build structures. Any deviation from the alloy's standard properties can prove detrimental. Thus, the compositional integrity of the material must be controlled. The ability to directly build and repair large, complicated structures directly from CAD files is highly sought after. Laser Metal Deposition (LMD) technology has the potential to deliver that ability. Before this process can gain widespread acceptance, however, a set of process parameters must be established that yield finished parts of consistent chemical composition. This research aims to establish such a set of parameters. Design of Experiments was utilized to maximize the information gained while minimizing the number of experimental trials required. A randomized, two-factor experiment was designed, performed, and replicated. Another set of experiments (nearly identical to the first) was then performed. The first set of experiments was completed in an open environment, while the second set was performed in an argon chamber. Energy Dispersive X-Ray Spectroscopy (EDS) was then used to perform a quantitative microanalysis to determine the aluminum level in each sample. Regression analysis was performed on the results to determine the factors of importance. Finally, fit plots and response surface curves were used to determine an optimal parameter set (process window). The process window was established to allow for consistent chemical composition of laser deposited Ti64 parts.
NASA Astrophysics Data System (ADS)
Wang, Xinchang; Shen, Xiaotian; Sun, Fanghong; Shen, Bin
2016-12-01
Chemical vapor deposition (CVD) diamond films have been widely applied as protective coatings on varieties of anti-frictional and wear-resistant components, owing to their excellent mechanical and tribological properties close to the natural diamond. In applications of some components, the inner hole surface will serve as the working surface that suffers severe frictional or erosive wear. It is difficult to realize uniform depositions of diamond films on surfaces of inner holes, especially ultra-large inner holes. Adopting a SiC compact die with an aperture of V80 mm as an example, a novel filament arrangement with a certain number of filaments evenly distributed on a circle is designed, and specific effects of filament parameters, including the filament number, arrangement direction, filament temperature, filament diameter, circumradius and the downward translation, on the substrate temperature distribution are studied by computational fluid dynamics (CFD) simulations based on the finite volume method (FVM), adopting a modified computational model well consistent with the actual deposition environment. Corresponding temperature measurement experiments are also conducted to verify the rationality of the computational model. From the aspect of depositing uniform boron-doped micro-crystalline, undoped micro-crystalline and undoped fine-grained composite diamond (BDM-UMC-UFGCD) film on such the inner hole surface, filament parameters as mentioned above are accurately optimized and compensated by orthogonal simulations. Moreover, deposition experiments adopting compensated optimized parameters and some typical contrastive parameters are also accomplished for further verifying the rationality of the computational model and the correctness of the compensation coefficient 0.7 defined for the downward translation determined by simulations. More importantly, on the basis of more simulations and verification tests, a general filament arrangement model suitable for V50-120 mm
Optimization of exchange bias in Co/CoO magnetic nanocaps by tuning deposition parameters
NASA Astrophysics Data System (ADS)
Sharma, A.; Tripathi, J.; Ugochukwu, K. C.; Tripathi, S.
2017-03-01
In the present work, we report exchange bias tuning by varying thin film deposition parameters such as synthesis method and underlying layer patterning. The patterned substrates for this study were prepared by self-assembly of polystyrene (PS) latex spheres ( 530 nm) on Si (100) substrate. The desired magnetic nanocaps composed of CoO/Co bilayer film on these patterned substrates were prepared by molecular beam epitaxy technique under ultra-high vacuum conditions. For this, a Co layer of 10 nm thickness was deposited on the substrates and then oxidized in-situ to form CoO/Co/PS in-situ oxidized film or ex-situ in ambiance which also gives CoO/Co/PS naturally oxidized film. Simultaneously, reference thin films of Co ( 10 nm) were also prepared on plane Si substrate and similar oxidation treatments were performed on them respectively. The magnetic properties studied using SQUID technique revealed higher exchange bias ( 1736 Oe) in the in-situ oxidized Co/PS film as compared to that in naturally oxidized Co/PS film ( 1544 Oe) and also compared to the reference film. The observed variations in the magnetic properties are explained in terms of surface patterning induced structural changes of the deposited films and different oxidation methods.
2010-10-01
Experiment (DOE) approach. These parameters were validated through supplemental testing and found to be non-embrittling with improved fatigue and neutral salt...supplemental testing and found to be non-embrittling with improved fatigue and neutral salt fog corrosion performance as compared to hard chromium...plating, and although it requires capital investment, it saves money because it eliminates the need for the Cr6+ scrubber, which costs more than
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
Computer program for parameter optimization
NASA Technical Reports Server (NTRS)
Glatt, C. R.; Hague, D. S.
1968-01-01
Flexible, large scale digital computer program was designed for the solution of a wide range of multivariable parameter optimization problems. The program has the ability to solve constrained optimization problems involving up to one hundred parameters.
The Sequential Parameter Optimization Toolbox
NASA Astrophysics Data System (ADS)
Bartz-Beielstein, Thomas; Lasarczyk, Christian; Preuss, Mike
The sequential parameter optimization toolbox (SPOT) is one possible implementation of the SPO framework introduced in Chap. 2. It has been successfully applied to numerous heuristics for practical and theoretical optimization problems. We describe the mechanics and interfaces employed by SPOT to enable users to plug in their own algorithms. Furthermore, two case studies are presented to demonstrate how SPOT can be applied in practice, followed by a discussion of alternative metamodels to be plugged into it.We conclude with some general guidelines.
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.
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.
Optimization of chemical bath deposited cadmium sulfide thin films
Oladeji, I.O.; Chow, L.
1997-07-01
Cadmium sulfide (CdS) is known to be an excellent heterojunction partner of p-type cadmium telluride (CdTe) or p-type copper indium diselenide (CuInSe{sub 2}) due essentially to its high electron affinity. It is widely used as a window material in high efficiency thin-film solar cells based on CdTe or CuInSe{sub 2} owing to its transparency and photoconductivity among other properties. The authors report the optimization of CdS thin film grown by chemical bath deposition where homogeneous reactions are minimized. The optimum parameters have enabled them to maximize the thickness of the deposited film in a single dip and to grow thicker films by periodically replenishing the concentration of reactants while the substrate remains continuously dipped in the reaction bath. Characterization results reveal the deposited CdS films exhibit improved optical and electrical properties.
Optimal design criteria - prediction vs. parameter estimation
NASA Astrophysics Data System (ADS)
Waldl, Helmut
2014-05-01
G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.
Cosmological parameter estimation using Particle Swarm Optimization
NASA Astrophysics Data System (ADS)
Prasad, J.; Souradeep, T.
2014-03-01
Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.
Optimal parameters uncoupling vibration modes of oscillators
NASA Astrophysics Data System (ADS)
Le, K. C.; Pieper, A.
2017-07-01
This paper proposes a novel optimization concept for an oscillator with two degrees of freedom. By using specially defined motion ratios, we control the action of springs to each degree of freedom of the oscillator. We aim at showing that, if the potential action of the springs in one period of vibration, used as the payoff function for the conservative oscillator, is maximized among all admissible parameters and motions satisfying Lagrange's equations, then the optimal motion ratios uncouple vibration modes. A similar result holds true for the dissipative oscillator having dampers. The application to optimal design of vehicle suspension is discussed.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
Quantum parameter estimation with optimal control
NASA Astrophysics Data System (ADS)
Liu, Jing; Yuan, Haidong
2017-07-01
A pivotal task in quantum metrology, and quantum parameter estimation in general, is to design schemes that achieve the highest precision with the given resources. Standard models of quantum metrology usually assume that the dynamics is fixed and that the highest precision is achieved by preparing the optimal probe states and performing optimal measurements. However, in many practical experimental settings, additional controls are usually available to alter the dynamics. Here we propose to use optimal control methods for further improvement of the precision limit of quantum parameter estimation. We show that, by exploring the additional degree of freedom offered by the controls, a higher-precision limit can be achieved. In particular, we show that the precision limit under the controlled schemes can go beyond the constraints put by the coherent time, which is in contrast with the standard scheme where the precision limit is always bounded by the coherent time.
Effects of Technical Parameters on the Pulsed Laser Deposited Ferroelectric Films
NASA Astrophysics Data System (ADS)
Zhao, Yafan; Chen, Chuanzhong; Song, Mingda; Ma, Jie; Wang, Diangang
Pulsed laser deposition (PLD), which is a novel technique in producing thin films in the recent years, shows unique advantages for the deposition of ferroelectric films. Effects of technical parameters on the pulsed laser deposited ferroelectric films, including substrate temperature, oxygen pressure, post-annealing, buffer layer, target composition, energy density, wavelength, target-to-substrate distance, and laser pulse rate, are systematically reviewed in order to optimize these parameters. Processing-microstructure-property relationships of ferroelectric films by PLD are discussed. The application prospect is pointed as well.
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.
A method for predicting optimized processing parameters for surfacing
Dupont, J.N.; Marder, A.R.
1994-12-31
Welding is used extensively for surfacing applications. To operate a surfacing process efficiently, the variables must be optimized to produce low levels of dilution with the substrate while maintaining high deposition rates. An equation for dilution in terms of the welding variables, thermal efficiency factors, and thermophysical properties of the overlay and substrate was developed by balancing energy and mass terms across the welding arc. To test the validity of the resultant dilution equation, the PAW, GTAW, GMAW, and SAW processes were used to deposit austenitic stainless steel onto carbon steel over a wide range of parameters. Arc efficiency measurements were conducted using a Seebeck arc welding calorimeter. Melting efficiency was determined based on knowledge of the arc efficiency. Dilution was determined for each set of processing parameters using a quantitative image analysis system. The pertinent equations indicate dilution is a function of arc power (corrected for arc efficiency), filler metal feed rate, melting efficiency, and thermophysical properties of the overlay and substrate. With the aid of the dilution equation, the effect of processing parameters on dilution is presented by a new processing diagram. A new method is proposed for determining dilution from welding variables. Dilution is shown to depend on the arc power, filler metal feed rate, arc and melting efficiency, and the thermophysical properties of the overlay and substrate. Calculated dilution levels were compared with measured values over a large range of processing parameters and good agreement was obtained. The results have been applied to generate a processing diagram which can be used to: (1) predict the maximum deposition rate for a given arc power while maintaining adequate fusion with the substrate, and (2) predict the resultant level of dilution with the substrate.
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.
Optimal diabatic states based on solvation parameters
NASA Astrophysics Data System (ADS)
Alguire, Ethan; Subotnik, Joseph E.
2012-11-01
A new method for obtaining diabatic electronic states of a molecular system in a condensed environment is proposed and evaluated. This technique, which we denote as Edmiston-Ruedenberg (ER)-ɛ diabatization, forms diabatic states as a linear combination of adiabatic states by minimizing an approximation to the total coupling between states in a medium with temperature T and with a characteristic Pekar factor C. ER-ɛ diabatization represents an improvement upon previous localized diabatization methods for two reasons: first, it is sensitive to the energy separation between adiabatic states, thus accounting for fluctuations in energy and effectively preventing over-mixing. Second, it responds to the strength of system-solvent interactions via parameters for the dielectric constant and temperature of the medium, which is physically reasonable. Here, we apply the ER-ɛ technique to both intramolecular and intermolecular excitation energy transfer systems. We find that ER-ɛ diabatic states satisfy three important properties: (1) they have small derivative couplings everywhere; (2) they have small diabatic couplings at avoided crossings, and (3) they have negligible diabatic couplings everywhere else. As such, ER-ɛ states are good candidates for so-called "optimal diabatic states."
Optimal linear estimation of binary star parameters
NASA Astrophysics Data System (ADS)
Burke, Daniel; Devaney, Nicholas; Gladysz, Szymon; Barrett, Harrisson H.; Whitaker, Meredith K.; Caucci, Luca
2008-07-01
We propose a new post-processing technique for the detection of faint companions and the estimation of their parameters from adaptive optics (AO) observations. We apply the optimal linear detector, which is the Hotelling observer, to perform detection, astrometry and photometry on real and simulated data. The real data was obtained from the AO system on the 3m Lick telescope1. The Hotelling detector, which is a prewhitening matched filter, calculates the Hotelling test statistic which is then compared to a threshold. If the test statistic is greater than the threshold the algorithm decides that a companion is present. This decision is the main task performed by the Hotelling observer. After a detection is made the location and intensity of the companion which maximise this test statistic are taken as the estimated values. We compare the Hotelling approach with current detection algorithms widely used in astronomy. We discuss the use of the estimation receiver operating characteristic (EROC) curve in quantifying the performance of the algorithm with no prior estimate of the companion's location or intensity. The robustness of this technique to errors in point spread function (PSF) estimation is also investigated.
Optimal parameters for laser tissue soldering
NASA Astrophysics Data System (ADS)
McNally-Heintzelman, Karen M.; Sorg, Brian S.; Chan, Eric K.; Welch, Ashley J.; Dawes, Judith M.; Owen, Earl R.
1998-07-01
Variations in laser irradiance, exposure time, solder composition, chromophore type and concentration have led to inconsistencies in published results of laser-solder repair of tissue. To determine optimal parameters for laser tissue soldering, an in vitro study was performed using an 808-nm diode laser in conjunction with an indocyanine green (ICG)- doped albumin protein solder to weld bovine aorta specimens. Liquid and solid protein solders prepared from 25% and 60% bovine serum albumin (BSA), respectively, were compared. The effects of laser irradiance and exposure time on tensile strength of the weld and temperature rise as well as the effect of hydration on bond stability were investigated. Optimum irradiance and exposure times were identified for each solder type. Increasing the BSA concentration from 25% to 60% greatly increased the tensile strength of the weld. A reduction in dye concentration from 2.5 mg/ml to 0.25 mg/ml was also found to result in an increase in tensile strength. The strongest welds were produced with an irradiance of 6.4 W/cm2 for 50 s using a solid protein solder composed of 60% BSA and 0.25 mg/ml ICG. Steady-state solder surface temperatures were observed to reach 85 plus or minus 5 degrees Celsius with a temperature gradient across the solid protein solder strips of between 15 and 20 degrees Celsius. Finally, tensile strength was observed to decrease significantly (20 to 25%) after the first hour of hydration in phosphate-buffered saline. No appreciable change was observed in the strength of the tissue bonds with further hydration.
Optimal Linking Design for Response Model Parameters
ERIC Educational Resources Information Center
Barrett, Michelle D.; van der Linden, Wim J.
2017-01-01
Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…
Alternative Weights and Invariant Parameters in Optimal Scaling.
ERIC Educational Resources Information Center
McDonald, Roderick P.
1983-01-01
Under conditions commonly met in optimal scaling problems, arbitrary sets of optimal weights can be obtained by choices of generalized universe scores. It is suggested that the invariant parameters of optimal scaling should be interpreted according to latent trait theory, rather than the arbitrary weights. (Author/JKS)
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.
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.
Wang, B. B.; Ostrikov, K.
2009-04-15
Carbon nanotips have been synthesized from a thin carbon film deposited on silicon by bias-enhanced hot filament chemical vapor deposition under different process parameters. The results of scanning electron microscopy indicate that high-quality carbon nanotips can only be obtained under conditions when the ion flux is effectively drawn from the plasma sustained in a CH{sub 4}+NH{sub 3}+H{sub 2} gas mixture. It is shown that the morphology of the carbon nanotips can be controlled by varying the process parameters such as the applied bias, gas pressure, and the NH{sub 3}/H{sub 2} mass flow ratios. The nanotip formation process is examined through a model that accounts for surface diffusion, in addition to sputtering and deposition processes included in the existing models. This model makes it possible to explain the major difference in the morphologies of the carbon nanotips formed without and with the aid of the plasma as well as to interpret the changes of their aspect ratio caused by the variation in the ion/gas fluxes. Viable ways to optimize the plasma-based process parameters to synthesize high-quality carbon nanotips are suggested. The results are relevant to the development of advanced plasma-/ion-assisted methods of nanoscale synthesis and processing.
Machine Self-Teaching Methods for Parameter Optimization.
1986-12-01
A199 285 MACHINE SELF- TEACHING METHODS FOR PARAMETER / OPTIMIZATION(U) NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA R A DILLARD DEC 86 NOSC/TR-1S39...Technical Document 1039 C) ,December 1986 Machine Self- Teaching Methods for Parameter Optimization Robin A. Dillard DTICS ELECTE MAY i01 STAra Approved...ELEMEWt NO PROECi’ No TASK NO ARC Locally FundedI I1 I TE (ewd* Seawmy Cft*Wi., Machine Self- Teaching Methods for Parameter Optimization it PERSONAL
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.
NASA Astrophysics Data System (ADS)
Ghadai, R. K.; Das, P. P.; Shivakoti, I.; Mondal, S. C.; Swain, B. P.
2017-07-01
Diamond-like carbon (DLC) coatings are widely used in medical, manufacturing and aerospace industries due to their excellent mechanical, biological, optical and tribological properties. The selection of optimal process parameters for efficient characteristics of DLC film is always a challenging issue for the materials science researchers. The optimal combination of the process parameters involved in the deposition of DLC films provide a better result, which subsequently help other researchers to choose the process parameters. In the present work Grey Relation Analysis (GRA) and Fuzzy-logic are being used for the optimization of process parameters in DLC film coating by using plasma assist chemical vapour deposition (PACVD) technique. The bias voltage, bias frequency, deposition pressure, gas composition are considered as input process parameters and hardness (GPa), Young's modulus (GPa), ratio between diamond to graphic fraction, (Id/Ig) ratio are considered as response parameters. The input parameters are optimized by grey fuzzy analysis. The contribution of individual input parameter is done by ANOVA. In this analysis found that bias voltage having the least influence and gas composition has highest influence in the PACVD deposited DLC films. The grey fuzzy analysis results indicated that optimum results for bias voltage, bias frequency, deposition pressure, gas composition for the DLC thin films are -50 V, 6 kHz, 4 μbar and 60:40 % respectively.
Quantum Tunneling Parameter in Global Optimization
NASA Astrophysics Data System (ADS)
Itami, Teturo
Quantum tunneling that helps particles escape from local minima has been applied in “quantum annealing” method to global optimization of nonlinear functions. To control size of kinetic energy of quantum particles, we form a “quantum tunneling parameter” QT≡m/HR2, where HR corresponds to a physical constant h, Planck's constant divided by 2π, that determines the lowest eigenvalue of quantum particles with mass m. Assumptions on profiles of the function V(x) around its minimum point x0, harmonic oscillator type and square well type, make us possible to write down analytical formulae of the kinetic energy K in terms of QT. The formulae tell that we can make quantum expectation value of particle coordinates x approximate to the minimum point x0 in QT→∞. For systems where we have almost degenerate eigenvalues, examination working with our QT, that x→x0 in QT→∞, is analytically shown also efficient. Similar results that x→x0 under QT→∞ are also obtained when we utilize random-walk quantum Monte Carlo method to represent tunneling phenomena according to conventional quantum annealing.
Optimization of Uranium Molecular Deposition for Alpha-Counting Sources
Monzo, Ellen; Parsons-Moss, Tashi; Genetti, Victoria; Knight, Kimberly
2016-12-12
Method development for molecular deposition of uranium onto aluminum 1100 plates was conducted with custom plating cells at Lawrence Livermore National Laboratory. The method development focused primarily on variation of electrode type, which was expected to directly influence plated sample homogeneity. Solid disc platinum and mesh platinum anodes were compared and data revealed that solid disc platinum anodes produced more homogenous uranium oxide films. However, the activity distribution also depended on the orientation of the platinum electrode relative to the aluminum cathode, starting current, and material composition of the plating cell. Experiments demonstrated these variables were difficult to control under the conditions available. Variation of plating parameters among a series of ten deposited plates yielded variations up to 30% in deposition efficiency. Teflon particles were observed on samples plated in Teflon cells, which poses a problem for alpha activity measurements of the plates. Preliminary electropolishing and chemical polishing studies were also conducted on the aluminum 1100 cathode plates.
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
Optimization of the cell lattice parameters for the SSC
1986-10-15
This report discusses the following topics on the cell lattices parameters optimization at the SSC: Cell lattices; needed aperture; magnet errors; calculated aperture; the trade off curves; cost model; and additional considerations.
Optimized LOWESS normalization parameter selection for DNA microarray data
Berger, John A; Hautaniemi, Sampsa; Järvinen, Anna-Kaarina; Edgren, Henrik; Mitra, Sanjit K; Astola, Jaakko
2004-01-01
Background Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail. Results and discussion In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies. Conclusions Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical
Optimization of NLC machine parameters for specific physics processes
Thompson, Kathleen A
1999-10-11
We examine the optimization of NLC parameters at 500, 1000, and 1500 GeV c.m. energy for specific classes of physics processes, in particular, top and stop pair production, and W-W scattering processes. Our focus is on optimizing the luminosity spectrum, while maintaining or improving machine operability.
Multimodel parameter optimization with adaptive population importance sampler (APIS)
NASA Astrophysics Data System (ADS)
Mäkelä, Jarmo; Susiluoto, Jouni; Knauer, Jürgen; Aurela, Mika; Mammarella, Ivan; Markkanen, Tiina; Thum, Tea; Zaehle, Sönke; Aalto, Tuula
2017-04-01
We are optimizing key parameters in soil hydrology and forest water and carbon exchange related formulations in ecosystem model JSBACH, which is the land surface component of the Earth System model of Max Planck Institute for Meteorology (MPI-ESM). The model has been modified to use multiple stomatal/canopy conductance formulations which will vary during the optimization process. Our previous results have shown that JSBACH is lacking in its response to drought, which is the motivation to test the different conductance formulations. The optimization is done with the adaptive population importance sampler (APIS) algorithm, that provides a global estimation of the selected JSBACH parameters, using all generated samples. Additionally APIS is able to estimate the model evidence (or partition function), which can be used to determine the optimal submodel (conductance formulation). APIS starts with a set of N randomly generated proposals (standard deviations for the parameters), with location parameters spread in the state space. We draw M samples and calculate the partial IS (importance sampler) estimators for each proposal, after which we update the location parameters and each proposal as well as the global estimator for each JSBACH parameter. This process is then repeated a number of times. The study focuses on boreal coniferous evergreen forests. The optimization is based on site level eddy covariance flux measurements on multiple sites across the Northern Hemisphere, where the parameters are estimated by minimizing the model-data mismatch in evapotranspiration and gross primary production.
Parameter optimization toward optimal microneedle-based dermal vaccination.
van der Maaden, Koen; Varypataki, Eleni Maria; Yu, Huixin; Romeijn, Stefan; Jiskoot, Wim; Bouwstra, Joke
2014-11-20
Microneedle-based vaccination has several advantages over vaccination by using conventional hypodermic needles. Microneedles are used to deliver a drug into the skin in a minimally-invasive and potentially pain free manner. Besides, the skin is a potent immune organ that is highly suitable for vaccination. However, there are several factors that influence the penetration ability of the skin by microneedles and the immune responses upon microneedle-based immunization. In this study we assessed several different microneedle arrays for their ability to penetrate ex vivo human skin by using trypan blue and (fluorescently or radioactively labeled) ovalbumin. Next, these different microneedles and several factors, including the dose of ovalbumin, the effect of using an impact-insertion applicator, skin location of microneedle application, and the area of microneedle application, were tested in vivo in mice. The penetration ability and the dose of ovalbumin that is delivered into the skin were shown to be dependent on the use of an applicator and on the microneedle geometry and size of the array. Besides microneedle penetration, the above described factors influenced the immune responses upon microneedle-based vaccination in vivo. It was shown that the ovalbumin-specific antibody responses upon microneedle-based vaccination could be increased up to 12-fold when an impact-insertion applicator was used, up to 8-fold when microneedles were applied over a larger surface area, and up to 36-fold dependent on the location of microneedle application. Therefore, these influencing factors should be considered to optimize microneedle-based dermal immunization technologies.
Parameter optimization in HN-IMRT for Elekta linacs.
Worthy, Danielle; Wu, Qiuwen
2009-04-28
Planning and delivery in HN-IMRT has been challenging for the Elekta linac because of numerous machine limitations. Direct aperture optimization (DAO) algorithms have had success in simplifying the planning process and improving plan quality. Commercial adaptations of DAO allow for widespread use in many clinics; however clinical validation of these methods is still needed. In this work we evaluated Pinnacle3 commercial software for HN-IMRT on the Elekta linac. The purpose was to find a set of planning parameters that are applicable to most patients and optimal in terms of plan quality, delivery efficiency, and dosimetric accuracy. Four types of plans were created for each of 12 patients: ideal fluence optimization (FO), conventional two-step optimization (TS), segment weight optimization (SW), and direct machine parameter optimization (DMPO). Maximum number of segments (NS) and minimum segment area (MSA) were varied in DMPO. Results showed DMPO plans have the best optimization scores and dosimetric indices, and the most consistent IMRT output among patients. At larger NS (> or = 80), plan quality decreases with increasing MSA as expected, except for MSA<8 cm(2), suggesting presence of local minima in DMPO. Segment area and MUs can vary significantly between optimization methods and parameter settings; however, the quantity 'integral MU' remains constant. Irradiation time is linearly proportional to total plan segments, weakly dependent on MUs and independent of MSA. Dosimetric accuracy is independent of DMPO parameters. The superior quality of DMPO makes it the choice for HN-IMRT on Elekta linacs and its consistency allows development of 'class solutions'. However, planners should be aware of the local minima issue when pushing parameters to the limit such as NS<80 and MSA<8 cm(2). The optimal set of parameters should be chosen to balance plan quality and delivery efficiency based on a systematic evaluation of the planning technique and system constraints.
Optimization of Cold Spray Deposition of High-Density Polyethylene Powders
NASA Astrophysics Data System (ADS)
Bush, Trenton B.; Khalkhali, Zahra; Champagne, Victor; Schmidt, David P.; Rothstein, Jonathan P.
2017-09-01
When a solid, ductile particle impacts a substrate at sufficient velocity, the resulting heat, pressure and plastic deformation can produce bonding between the particle and the substrate. The use of a cool supersonic gas flow to accelerate these solid particles is known as cold spray deposition. The cold spray process has been commercialized for some metallic materials, but further research is required to unlock the exciting potential material properties possible with polymeric particles. In this work, a combined computational and experimental study was employed to study the cold spray deposition of high-density polyethylene powders over a wide range of particle temperatures and impact velocities. Cold spray deposition of polyethylene powders was demonstrated across a range broad range of substrate materials including several different polymer substrates with different moduli, glass and aluminum. A material-dependent window of successful deposition was determined for each substrate as a function of particle temperature and impact velocity. Additionally, a study of deposition efficiency revealed the optimal process parameters for high-density polyethylene powder deposition which yielded a deposition efficiency close to 10% and provided insights into the physical mechanics responsible for bonding while highlighting paths toward future process improvements.
Optimization of Cold Spray Deposition of High-Density Polyethylene Powders
NASA Astrophysics Data System (ADS)
Bush, Trenton B.; Khalkhali, Zahra; Champagne, Victor; Schmidt, David P.; Rothstein, Jonathan P.
2017-10-01
When a solid, ductile particle impacts a substrate at sufficient velocity, the resulting heat, pressure and plastic deformation can produce bonding between the particle and the substrate. The use of a cool supersonic gas flow to accelerate these solid particles is known as cold spray deposition. The cold spray process has been commercialized for some metallic materials, but further research is required to unlock the exciting potential material properties possible with polymeric particles. In this work, a combined computational and experimental study was employed to study the cold spray deposition of high-density polyethylene powders over a wide range of particle temperatures and impact velocities. Cold spray deposition of polyethylene powders was demonstrated across a range broad range of substrate materials including several different polymer substrates with different moduli, glass and aluminum. A material-dependent window of successful deposition was determined for each substrate as a function of particle temperature and impact velocity. Additionally, a study of deposition efficiency revealed the optimal process parameters for high-density polyethylene powder deposition which yielded a deposition efficiency close to 10% and provided insights into the physical mechanics responsible for bonding while highlighting paths toward future process improvements.
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.
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.
Sequential ensemble-based optimal design for parameter estimation
NASA Astrophysics Data System (ADS)
Man, Jun; Zhang, Jiangjiang; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng
2016-10-01
The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.
Parameter extraction of solar cells using particle swarm optimization
NASA Astrophysics Data System (ADS)
Ye, Meiying; Wang, Xiaodong; Xu, Yousheng
2009-05-01
In this article, particle swarm optimization (PSO) was applied to extract the solar cell parameters from illuminated current-voltage characteristics. The performance of the PSO was compared with the genetic algorithms (GAs) for the single and double diode models. Based on synthetic and experimental current-voltage data, it has been confirmed that the proposed method can obtain higher parameter precision with better computational efficiency than the GA method. Compared with conventional gradient-based methods, even without a good initial guess, the PSO method can obtain the parameters of solar cells as close as possible to the practical parameters only based on a broad range specified for each of the parameters.
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.
Optimization of parameters of Smith-Purcell BWO.
Kumar, V.; Kim, K.-J.; Accelerator Systems Division; RRCAT
2006-01-01
We study the dependence of start current in Smith-Purcell backwardwave oscillator (SP-BWO) on grating parameters and electron beam parameters. The attenuation due to finite conductivity of the grating material is taken into account and three-dimensional effects are included in an approximate way in the analysis. We find that the start current can be significantly reduced by optimizing the grating parameters.
In situ growth optimization in focused electron-beam induced deposition
Weirich, Paul M; Winhold, Marcel; Huth, Michael
2013-01-01
Summary We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques. PMID:24367761
In situ growth optimization in focused electron-beam induced deposition.
Weirich, Paul M; Winhold, Marcel; Schwalb, Christian H; Huth, Michael
2013-01-01
We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt-C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques.
Projector Augmented Wave database with automatic parameter optimization
NASA Astrophysics Data System (ADS)
Snow, R. J.; Wright, A. F.; Fong, C. Y.
2009-03-01
Projector Augmented Wave (PAW) parameter sets, similar to pseudopotential parameters, can be constructed in many ways. Due to a non-local expansion of projectors, the PAW method can include parameters for each angular momentum channel separately. While this gives the flexibility to optimize projectors individually, it also creates an unfathomable parameter space for searching for good parameter sets. To automatically search for good PAW sets, logarithmic derivatives were analyzed numerically for matching with AE logarithmic derivatives. Logarithmic derivative matching, total energy convergence, and scf convergence were used as scores for automatic optimization of the accuracy and speed of PAW parameter sets using a genetic algorithm within an optimization code. The Dakota [1] program was used for the parameter optimization, while the atompaw program was used for PAW generation. A new database of PAW functions will be introduced and a number of examples discussed. [1] Sand Report Sand 2001-3514, (2002) [2] N.A.W. Holzwrth, A.R. Tackett, and G.E. Matthews, Computer Physics Communications 135, 329 (2001)
NASA Astrophysics Data System (ADS)
Habibi, Mehran; Ahmadian-Yazdi, Mohammad-Reza; Eslamian, Morteza
2017-04-01
We use facile coating techniques including spray coating and drop casting to fabricate methylammonium lead iodide perovskite solar cells through a two-step sequential deposition approach. In the first step, for the deposition of the lead iodide, spray coating substitutes for the commonly used lab-scale spin coating, while the operating parameters of the former process are optimized to achieve a fully covered and uniform film of lead iodide. In the second step, to deposit methylammonium iodide atop the lead iodide layer to form methylammonium lead iodide perovskite, dip-coating process is replaced by the touch-free drop casting and scalable pulsed-spray coating. It is found that the performance of the perovskite films and devices made by pulsed-spray coating and drop casting is similar to those prepared by dip coating, while the large-scale production capabilities of such methods beside the low material consumptions of drop casting prove their potential to replace dip coating in large-scale manufacturing of perovskite solar cells. The champion devices fabricated by spray-drop and spin-drop techniques demonstrated power conversion efficiencies of 6.92% and 9.48%, respectively. It is expected that device fabrication in a low-humidity environment using the optimized parameters and optimization of other layers will result in higher efficiencies.
Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization
NASA Astrophysics Data System (ADS)
Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin
2017-09-01
Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.
The influence of energy deposition parameters on laser plasma drag reduction
NASA Astrophysics Data System (ADS)
Dou, Zhiguo; Liu, Zhun; Yao, Honglin; Li, Xiuqian
2013-09-01
Laser plasma drag reduction is a new method to reduce the wave drag of hypersonic flight. The research of the laser plasma drag reduction performance is an important work. The purpose of this paper is investigating laser plasma drag reduction by numerical simulation to enhance the understanding of the drag reduction mechanism, get the drag reduction performance in different conditions, and provide references for laser plasma drag reduction experiment in the future. Based on summarizing correlative references systematically, through building the model of energy deposition and comparison the simulated results to the empirical formula and computation results to verify the program correctness, the influence of laser energy parameters to laser plasma drag reduction were simulated numerically for optimize the performance. The follow conclusions were got by numerical simulation: The computation program can well simulate the interacting of LSDW(laser supported detonation wave) to the bow shock in front of the blunt body. Results indicate that the blunt body drag could be decreased by injecting laser energy into the incoming hypersonic flow. The correctness of program was verified by compare result to the experiment and computation results. Blunt body drag will be greatly decreased with injected laser power increased, The bigger laser power is injected, the more drag decreases. There's an energy saturation value for each laser power level, the injecting laser power effectiveness values are never quite high for all laser power level. There is an optimized energy deposition location in upstream flow, this location is right ahead of the blunt body. When the distance from deposition location to the surface of blunt body is 5 times the blunt radius, blunt body drag decreased the most. This paper investigated the parameters which primary influence the performance of drag reduction. The numerical simulation data and obtained results are meaningful for laser plasma drag reduction
Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...
With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th
Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...
With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th
Optimization of Gas Metal Arc Welding Process Parameters
NASA Astrophysics Data System (ADS)
Kumar, Amit; Khurana, M. K.; Yadav, Pradeep K.
2016-09-01
This study presents the application of Taguchi method combined with grey relational analysis to optimize the process parameters of gas metal arc welding (GMAW) of AISI 1020 carbon steels for multiple quality characteristics (bead width, bead height, weld penetration and heat affected zone). An orthogonal array of L9 has been implemented to fabrication of joints. The experiments have been conducted according to the combination of voltage (V), current (A) and welding speed (Ws). The results revealed that the welding speed is most significant process parameter. By analyzing the grey relational grades, optimal parameters are obtained and significant factors are known using ANOVA analysis. The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions.
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.
Finding optimal vaccination strategies under parameter uncertainty using stochastic programming.
Tanner, Matthew W; Sattenspiel, Lisa; Ntaimo, Lewis
2008-10-01
We present a stochastic programming framework for finding the optimal vaccination policy for controlling infectious disease epidemics under parameter uncertainty. Stochastic programming is a popular framework for including the effects of parameter uncertainty in a mathematical optimization model. The problem is initially formulated to find the minimum cost vaccination policy under a chance-constraint. The chance-constraint requires that the probability that R(*)
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
NASA Astrophysics Data System (ADS)
Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal
2017-07-01
Fused Deposition Modeling (FDM) is one of the prominent additive manufacturing technologies for producing polymer products. FDM is a complex additive manufacturing process that can be influenced by many process conditions. The industrial demands required from the FDM process are increasing with higher level product functionality and properties. The functionality and performance of FDM manufactured parts are greatly influenced by the combination of many various FDM process parameters. Designers and researchers always pay attention to study the effects of FDM process parameters on different product functionalities and properties such as mechanical strength, surface quality, dimensional accuracy, build time and material consumption. However, very limited studies have been carried out to investigate and optimize the effect of FDM build parameters on wear performance. This study focuses on the effect of different build parameters on micro-structural and wear performance of FDM specimens using definitive screening design based quadratic model. This would reduce the cost and effort of additive manufacturing engineer to have a systematic approachto make decision among the manufacturing parameters to achieve the desired product quality.
Optimization routine for identification of model parameters in soil plasticity
NASA Astrophysics Data System (ADS)
Mattsson, Hans; Klisinski, Marek; Axelsson, Kennet
2001-04-01
The paper presents an optimization routine especially developed for the identification of model parameters in soil plasticity on the basis of different soil tests. Main focus is put on the mathematical aspects and the experience from application of this optimization routine. Mathematically, for the optimization, an objective function and a search strategy are needed. Some alternative expressions for the objective function are formulated. They capture the overall soil behaviour and can be used in a simultaneous optimization against several laboratory tests. Two different search strategies, Rosenbrock's method and the Simplex method, both belonging to the category of direct search methods, are utilized in the routine. Direct search methods have generally proved to be reliable and their relative simplicity make them quite easy to program into workable codes. The Rosenbrock and simplex methods are modified to make the search strategies as efficient and user-friendly as possible for the type of optimization problem addressed here. Since these search strategies are of a heuristic nature, which makes it difficult (or even impossible) to analyse their performance in a theoretical way, representative optimization examples against both simulated experimental results as well as performed triaxial tests are presented to show the efficiency of the optimization routine. From these examples, it has been concluded that the optimization routine is able to locate a minimum with a good accuracy, fast enough to be a very useful tool for identification of model parameters in soil plasticity.
Concurrent optimization of airframe and engine design parameters
NASA Technical Reports Server (NTRS)
Lavelle, Thomas M.; Plencner, Robert M.; Seidel, Jonathan A.
1991-01-01
An integrated system for the multidisciplinary analysis and optimization of airframe and propulsion design parameters is being developed. This system is known as IPAS, the Integrated Propulsion/Airframe Analysis System. The traditional method of analysis is one in which the propulsion system analysis is loosely coupled to the overall mission performance analysis. This results in a time consuming iterative process. First, the engine is designed and analyzed. Then, the results from this analysis are used in a mission analysis to determine the overall aircraft performance. The results from the mission analysis are used as a guide as the engine is redesigned and the entire process repeated. In IPAS, the propulsion system, airframe, and mission are closely coupled. The propulsion system analysis code is directly integrated into the mission analysis code. This allows the propulsion design parameters to be optimized along with the airframe and mission design parameters, significantly reducing the time required to obtain an optimized solution.
Research on Optimization of GLCM Parameter in Cell Classification
NASA Astrophysics Data System (ADS)
Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua
2016-05-01
Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.
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.
Optimal sensor location for parameter identification in soft clay
NASA Astrophysics Data System (ADS)
Hölter, R.; Mahmoudi, E.; Schanz, T.
2015-10-01
Performing parameter identification for model calibration prior to numerical simulation is an essential task in geotechnical engineering. However, it has to be kept in mind that the accuracy of the obtained parameter is closely related to the chosen experimental set-up, such as the number of sensors as well as their location. A well considered position of sensors can increase the quality of the measurement and reduce the number of monitoring points. This paper illustrates this concept by means of a loading device that is used to identify the stiffness and permeability factor of soft clays. With an initial set-up of the measurement devices the pore water pressure and the vertical displacements are recorded and used to identify the aforementioned parameters. Starting from these identified parameters, the optimal measurement set-up is investigated with a method based on global sensitivity analysis. This method shows an optimal sensor location assuming three sensors for each measured quantity.
NASA Astrophysics Data System (ADS)
Jakšić, Nikola
2015-03-01
The optimality of the procedure of parameter identification is scrutinized in this paper. It was shown, with the relations between the mathematical theory of function approximation, three parameter probability distributions, which can adjust their shape, and the maximum-likelihood method, that the optimal expression of the distance between measured data and model fitting it can be established by using the three parameter probability distributions on the basis of iteration procedure, where the noise contained in the measured signal is extracted as well. The iterative method for optimal system/model parameter identification is presented and tested by the numerical experimentation. Four types of noise added to the simple single-degree-of-freedom system response are considered: Gauss, Cauchy, Laplace and Uniform. The method performs well for the noise types at relatively high noise content in the signal.
Calculation of optimal parameters for 19F MRI
NASA Astrophysics Data System (ADS)
Anisimov, N.; Gulaev, M.; Pavlova, O.; Fomina, D.; Glukhova, V.; Batova, S.; Pirogov, Yu
2017-08-01
This paper presents a method for optimizing the parameters of the scanning pulse sequences for MRI in relation to objects with a wide NMR spectrum. In this case, a broadband excitation of the spin system is difficult because of hardware limitations. It is proposed to apply the selective excitation, the optimum parameters of which are calculated by an algorithm that uses information concerning the NMR spectrum. The method is especially useful for 19F MRI of fluorocarbons.
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.
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.
NASA Astrophysics Data System (ADS)
Cai, Lanlan; Li, Peng; Luo, Qi; Zhai, Pengcheng; Zhang, Qingjie
2017-01-01
As no single thermoelectric material has presented a high figure-of-merit (ZT) over a very wide temperature range, segmented thermoelectric generators (STEGs), where the p- and n-legs are formed of different thermoelectric material segments joined in series, have been developed to improve the performance of thermoelectric generators. A crucial but difficult problem in a STEG design is to determine the optimal values of the geometrical parameters, like the relative lengths of each segment and the cross-sectional area ratio of the n- and p-legs. Herein, a multi-parameter and nonlinear optimization method, based on the Improved Powell Algorithm in conjunction with the discrete numerical model, was implemented to solve the STEG's geometrical optimization problem. The multi-parameter optimal results were validated by comparison with the optimal outcomes obtained from the single-parameter optimization method. Finally, the effect of the hot- and cold-junction temperatures on the geometry optimization was investigated. Results show that the optimal geometry parameters for maximizing the specific output power of a STEG are different from those for maximizing the conversion efficiency. Data also suggest that the optimal geometry parameters and the interfacial temperatures of the adjacent segments optimized for maximum specific output power or conversion efficiency vary with changing hot- and cold-junction temperatures. Through the geometry optimization, the CoSb3/Bi2Te3-based STEG can obtain a maximum specific output power up to 1725.3 W/kg and a maximum efficiency of 13.4% when operating at a hot-junction temperature of 823 K and a cold-junction temperature of 298 K.
NASA Astrophysics Data System (ADS)
Cai, Lanlan; Li, Peng; Luo, Qi; Zhai, Pengcheng; Zhang, Qingjie
2017-03-01
As no single thermoelectric material has presented a high figure-of-merit (ZT) over a very wide temperature range, segmented thermoelectric generators (STEGs), where the p- and n-legs are formed of different thermoelectric material segments joined in series, have been developed to improve the performance of thermoelectric generators. A crucial but difficult problem in a STEG design is to determine the optimal values of the geometrical parameters, like the relative lengths of each segment and the cross-sectional area ratio of the n- and p-legs. Herein, a multi-parameter and nonlinear optimization method, based on the Improved Powell Algorithm in conjunction with the discrete numerical model, was implemented to solve the STEG's geometrical optimization problem. The multi-parameter optimal results were validated by comparison with the optimal outcomes obtained from the single-parameter optimization method. Finally, the effect of the hot- and cold-junction temperatures on the geometry optimization was investigated. Results show that the optimal geometry parameters for maximizing the specific output power of a STEG are different from those for maximizing the conversion efficiency. Data also suggest that the optimal geometry parameters and the interfacial temperatures of the adjacent segments optimized for maximum specific output power or conversion efficiency vary with changing hot- and cold-junction temperatures. Through the geometry optimization, the CoSb3/Bi2Te3-based STEG can obtain a maximum specific output power up to 1725.3 W/kg and a maximum efficiency of 13.4% when operating at a hot-junction temperature of 823 K and a cold-junction temperature of 298 K.
SNR dependence of optimal parameters for apparent diffusion coefficient measurements.
Saritas, Emine U; Lee, Jin H; Nishimura, Dwight G
2011-02-01
Optimizing the diffusion-weighted imaging (DWI) parameters (i.e., the b-value and the number of image averages) to the tissue of interest is essential for producing high-quality apparent diffusion coefficient (ADC) maps. Previous investigation of this optimization was performed assuming Gaussian noise statistics for the ADC map, which is only valid for high signal-to-noise ratio (SNR) imaging. In this work, the true statistics of the noise in ADC maps are derived, followed by an optimization of the DWI parameters as a function of the imaging SNR. Specifically, it is demonstrated that the optimum b-value is a monotonically increasing function of the imaging SNR, which converges to the optimum b-value from previously proposed approaches for high-SNR cases, while exhibiting a significant deviation from this asymptote for low-SNR situations. Incorporating the effects of T(2) weighting further increases the SNR dependence of the optimal parameters. The proposed optimization scheme is particularly important for high-resolution DWI, which intrinsically suffers from low SNR and therefore cannot afford the use of the conventional high b-values. Comparison scans were performed for high-resolution DWI of the spinal cord, demonstrating the improvements in the resulting images and the ADC maps achieved by this method.
Optimizing Parameters for Deep-Space Optical Communication
NASA Technical Reports Server (NTRS)
Moison, Bruce; Hamkins, Jon
2005-01-01
A paper discusses the optimization of the parameters of a high-rate, deep-space optical communication link that utilizes pulse-position modulation (PPM) and an error-correcting code (ECC). The parameters in question include the PPM order (number of pulse time slots in one symbol period), the ECC rate, and the uncoded symbol error rate. In simple terms, the optimization problem is to choose the combination of these parameters that maximizes the throughput data rate at a given bit-error-rate (BER), subject to several constraints, including limits on the average and peak power and possibly a limit on the uncoded symbol error rate. This is a complex, multidimensional optimization problem, the solution of which involves computation of channel capacities for various combinations of the parameters. The paper presents extensive theoretical analyses and numerical predictions that elucidate the many facets of the optimization problem. It shows how a nearly optimum solution can be obtained by choosing the optimum PPM order for the desired number of bits per slot and concatenating the PPM mapping with an error-correction code so that the decoded bits satisfy some BER threshold.
Optimized analysis of geometry parameters for honeycomb sandwich mirror
NASA Astrophysics Data System (ADS)
Chen, Xiao'an; Cheng, Yuntao; Zeng, Qingna; Liu, Hong; Fang, Jingzhong; Rao, Changhui
2014-07-01
The relationship of geometry parameters, specific stiffness, surface figure and natural frequency was investigated based on modified Gibson theory, sandwich theory, Hoff theory and vibration theory. By theoretical analysis and finite element method, we demonstrated the geometric parameters had non-linear influence on dimensionless specific stiffness in different directions with the honeycomb core was equivalent as modified solid material. Approximate expressions of deformation, natural frequency and geometric parameters were obtained. The results showed the optimal solidity ratio and face plate thickness ratio were in the range of 0.03 ~ 0.1 and 0.02 ~0.05, respectively.
Influence of Process Parameters on the Process Efficiency in Laser Metal Deposition Welding
NASA Astrophysics Data System (ADS)
Güpner, Michael; Patschger, Andreas; Bliedtner, Jens
Conventionally manufactured tools are often completely constructed of a high-alloyed, expensive tool steel. An alternative way to manufacture tools is the combination of a cost-efficient, mild steel and a functional coating in the interaction zone of the tool. Thermal processing methods, like laser metal deposition, are always characterized by thermal distortion. The resistance against the thermal distortion decreases with the reduction of the material thickness. As a consequence, there is a necessity of a special process management for the laser based coating of thin parts or tools. The experimental approach in the present paper is to keep the energy and the mass per unit length constant by varying the laser power, the feed rate and the powder mass flow. The typical seam parameters are measured in order to characterize the cladding process, define process limits and evaluate the process efficiency. Ways to optimize dilution, angular distortion and clad height are presented.
Parameters optimization for magnetic resonance coupling wireless power transmission.
Li, Changsheng; Zhang, He; Jiang, Xiaohua
2014-01-01
Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.
Optimal line drop compensation parameters under multi-operating conditions
NASA Astrophysics Data System (ADS)
Wan, Yuan; Li, Hang; Wang, Kai; He, Zhe
2017-01-01
Line Drop Compensation (LDC) is a main function of Reactive Current Compensation (RCC) which is developed to improve voltage stability. While LDC has benefit to voltage, it may deteriorate the small-disturbance rotor angle stability of power system. In present paper, an intelligent algorithm which is combined by Genetic Algorithm (GA) and Backpropagation Neural Network (BPNN) is proposed to optimize parameters of LDC. The objective function proposed in present paper takes consideration of voltage deviation and power system oscillation minimal damping ratio under multi-operating conditions. A simulation based on middle area of Jiangxi province power system is used to demonstrate the intelligent algorithm. The optimization result shows that coordinate optimized parameters can meet the multioperating conditions requirement and improve voltage stability as much as possible while guaranteeing enough damping ratio.
Programmable physical parameter optimization for particle plasma simulations
NASA Astrophysics Data System (ADS)
Ragan-Kelley, Benjamin; Verboncoeur, John; Lin, Ming-Chieh
2012-10-01
We have developed a scheme for interactive and programmable optimization of physical parameters for plasma simulations. The simulation code Object-Oriented Plasma Device 1-D (OOPD1) has been adapted to a Python interface, allowing sophisticated user or program interaction with simulations, and detailed numerical analysis via numpy. Because the analysis/diagnostic interface is the same as the input mechanism (the Python programming language), it is straightforward to optimize simulation parameters based on analysis of previous runs and automate the optimization process using a user-determined scheme and criteria. An example use case of the Child-Langmuir space charge limit in bipolar flow is demonstrated, where the beam current is iterated upon by measuring the relationship of the measured current and the injected current.
Optimization of polyetherimide processing parameters for optical interconnect applications
NASA Astrophysics Data System (ADS)
Zhao, Wei; Johnson, Peter; Wall, Christopher
2015-10-01
ULTEM® polyetherimide (PEI) resins have been used in opto-electronic markets since the optical properties of these materials enable the design of critical components under tight tolerances. PEI resins are the material of choice for injection molded integrated lens applications due to good dimensional stability, near infrared (IR) optical transparency, low moisture uptake and high heat performance. In most applications, parts must be produced consistently with minimal deviations to insure compatibility throughout the lifetime of the part. With the large number of lenses needed for this market, injection molding has been optimized to maximize the production rate. These optimized parameters for high throughput may or may not translate to an optimized optical performance. In this paper, we evaluate and optimize PEI injection molding processes with a focus on optical property performance. A commonly used commercial grade was studied to determine factors and conditions which contribute to optical transparency, color, and birefringence. Melt temperature, mold temperature, injection speed and cycle time were varied to develop optimization trials and evaluate optical properties. These parameters could be optimized to reduce in-plane birefringence from 0.0148 to 0.0006 in this study. In addition, we have studied an optically smooth, sub-10nm roughness mold to re-evaluate material properties with minimal influence from mold quality and further refine resin and process effects for the best optical performance.
NASA Astrophysics Data System (ADS)
Chandrasekaram, Sandeep D.
Development of air travel technology is always increasing and fuel efficiency is one of the most important factors that's being looked into. For a 25% increase in fuel efficiency in the future aeroplanes, reduction in the weight of the engine is one of the factors that should be addressed while increasing the strength and power generated. For this purpose, General Electric Aviation has chosen Silicon Carbide as the material to build the turbine blades of its engines. Silicon carbide works best as it is strong, can withstand high temperature and lightweight. The downside of this material is that it reacts with water vapor at temperatures greater than 2700°F to form volatile Silicon hydroxide from Silicon dioxide, its protective layer; and furthermore it reduces to Silicon monoxide that vaporizes. To counter this problem, scientists at the National Aeronautics & Space Administration (NASA) have found that a rare earth silicate could be used as an environmental barrier coating (EBC) to prevent the exposure of Silicon Carbide to water vapor. The EBC can't be directly coated on the Silicon Carbide surface as it isn't chemically adhesive enough, therefore Silicon was chosen to act as the bond coat between the Silicon Carbide and EBC. The goal of this research is to design a reactor for the composites to be coated with Silicon using the reaction and diffusion kinetics determined at higher temperatures and different partial pressures compared to the standard electronics industry. Chemical Vapor Deposition is the technique that will be used in determining the necessary parameters. The findings from this research can be further used in optimizing the utilization of the reagents and optimizing the process economically.
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.
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.
Leeuwenburgh, S; Wolke, J; Schoonman, J; Jansen, J A
2005-08-01
The electrostatic spray deposition (ESD) technique offers the possibility of depositing calcium phosphate (CaP) coatings onto various substrate materials with defined chemical and morphological properties. The relationship between physical, apparatus-related deposition parameters, and the chemical characteristics of ESD coatings was investigated by means of X-ray diffraction, Fourier transform infrared spectroscopy, and energy dispersive spectroscopy to be able to deposit CaP coatings with tailored chemical properties. The results showed that the chemical characteristics of CaP coatings, deposited with use of the ESD technique, were strongly dependent on the deposition temperature, the nozzle-to-substrate distance, the liquid flow rate, and the geometry of the spraying nozzle. By investigating the influence of the deposition temperature, information could be obtained on the formation mechanism of CaP coatings-and specifically the biologically interesting carbonate apatite phase-using the ESD technique. CaP coatings were not formed merely because of solvent evaporation; a chemical reaction was needed to synthesize the coatings. This reaction involved thermal decomposition of the organic solvent butyl carbitol into carbonate ions via formation of intermediate oxalate ions. The amount of carbonate incorporation, and consequently, the Ca/P ratios of the deposited coatings, was shown 1) to decrease with increasing nozzle-to-substrate distance, 2) to decrease with increasing liquid flow rate, and 3) to decrease by making use of a novel two-component nozzle geometry. (c) 2005 Wiley Periodicals, Inc.
Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback
NASA Astrophysics Data System (ADS)
Bruni, Renato; Celani, Fabio
2016-10-01
The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.
Multiexposure imaging and parameter optimization for intensified star trackers.
Yu, Wenbo; Jiang, Jie; Zhang, Guangjun
2016-12-20
Due to the introduction of the intensified image detector, the dynamic performance of the intensified star tracker is effectively improved. However, its attitude update rate is still seriously restricted by the transmission and processing of pixel data. In order to break through the above limitation, a multiexposure imaging approach for intensified star trackers is proposed in this paper. One star image formed by this approach actually records N different groups of star positions, and then N corresponding groups of attitude information can be acquired. Compared with the existing exposure imaging approach, the proposed approach improves the attitude update rate by N times. Furthermore, for a dim star, the proposed approach can also accumulate the energy of its N positions and then effectively improve its signal-to-noise ratio. Subsequently, in order to obtain the optimal performance of the proposed approach, parameter optimization is carried out. First, the motion model of the star spot in the image plane is established, and then based on it, all the key parameters are optimized. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach and parameter optimization.
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.
NASA Astrophysics Data System (ADS)
Mukhtar, Aiman; Shahzad Khan, Babar; Mehmood, Tahir
2016-12-01
The effect of deposition potential on the crystal structure and composition of Co-Ni alloy nanowires is studied by XRD, FE-SEM and EDX. The alloy nanowires deposited at -3.2 V are metastable fcc phase Co-Ni. The alloy nanowires deposited at -1.8 V are hcp phase Co-Ni. The formation of the metastable fcc alloy nanowires can be attributed to smaller critical clusters formed at the high potential as the smaller critical clusters favor fcc structure because of the significant surface energy effect. The content of Co inside nanowires increases with increasing potential. This can be understood by the polarization curves of depositing Co and Ni nanowires, which show that the current density ratio of Ni to Co at low potential has larger value than that at high potential.
Optimization of gun parameters for a pulsed power electron gun
NASA Astrophysics Data System (ADS)
Srinivasan-Rao, T.; Smedley, J.; Batchelor, K.; Farrell, J. P.; Dudnikova, G.
1999-07-01
Extensive simulation work has been done to identify the optimal parameters for a pulsed power electron gun. PBGUNS, an electrostatic beam optics code, was used to optimize the electrode shape and the beam spatial distribution, including modeling the focusing effect of a curved cathode surface. MAFIA, a particle-in-a-cell code, was used to investigate those aspects that required time dependence, such as longitudinal energy spread. The range of agreement between the two codes was also investigated. The transverse phase space at a comparison plane was found to be very close (within 1% at low currents and 4% for higher currents), even for bunch lengths shorter than the gap transit time.
Optimization of gun parameters for a pulsed power electron gun
Srinivasan-Rao, T.; Smedley, J.; Batchelor, K.; Farrell, J. P.; Dudnikova, G.
1999-07-12
Extensive simulation work has been done to identify the optimal parameters for a pulsed power electron gun. PBGUNS, an electrostatic beam optics code, was used to optimize the electrode shape and the beam spatial distribution, including modeling the focusing effect of a curved cathode surface. MAFIA, a particle-in-a-cell code, was used to investigate those aspects that required time dependence, such as longitudinal energy spread. The range of agreement between the two codes was also investigated. The transverse phase space at a comparison plane was found to be very close (within 1% at low currents and 4% for higher currents), even for bunch lengths shorter than the gap transit time.
Optimization of gun parameters for a pulsed power electron gun
Srvinivasan-Rao, T.; Smedley, J.; Batchelor, K.; Farrell, J.P.; Dudnikova, G.
1998-07-01
Extensive simulation work has been done to identify the optimal parameters for a pulsed power electron gun. PBGUNS, an electrostatic beam optics code, was used to optimize the electrode shape and the beam spatial distribution, including modeling the focusing effect of a curved cathode surface. MAFIA, a particle-in-a-cell code, was used to investigate those aspects that required time dependence, such as longitudinal energy spread. The range of agreement between the two codes was also investigated. The transverse phase space at a comparison plane was found to be very close (within 1% at low currents and 4% for higher currents), even for bunch lengths shorter than the gap transit time.
Identification of optimal parameter combinations for the emergence of bistability.
Májer, Imre; Hajihosseini, Amirhossein; Becskei, Attila
2015-11-24
Bistability underlies cellular memory and maintains alternative differentiation states. Bistability can emerge only if its parameter range is either physically realizable or can be enlarged to become realizable. We derived a general rule and showed that the bistable range of a reaction parameter is maximized by a pair of other parameters in any gene regulatory network provided they satisfy a general condition. The resulting analytical expressions revealed whether or not such reaction pairs are present in prototypical positive feedback loops. They are absent from the feedback loop enclosed by protein dimers but present in both the toggle-switch and the feedback circuit inhibited by sequestration. Sequestration can generate bistability even at narrow feedback expression range at which cooperative binding fails to do so, provided inhibition is set to an optimal value. These results help to design bistable circuits and cellular reprogramming and reveal whether bistability is possible in gene networks in the range of realistic parameter values.
Man, Jun; Zhang, Jiangjiang; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng
2016-10-01
The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.
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.
Analysis and Optimization of Central Processing Unit Process Parameters
NASA Astrophysics Data System (ADS)
Kaja Bantha Navas, R.; Venkata Chaitana Vignan, Budi; Durganadh, Margani; Rama Krishna, Chunduri
2017-05-01
The rapid growth of computer has made processing more data capable, which increase the heat dissipation. Hence the system unit CPU must be cooled against operating temperature. This paper presents a novel approach for the optimization of operating parameters on Central Processing Unit with single response based on response graph method. These methods have a series of steps from of proposed approach which are capable of decreasing uncertainty caused by engineering judgment in the Taguchi method. Orthogonal Array value was taken from ANSYS report. The method shows a good convergence with the experimental and the optimum process parameters.
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.
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.
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.
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
Optimal control for a Formula One car with variable parameters
NASA Astrophysics Data System (ADS)
Perantoni, Giacomo; Limebeer, David J. N.
2014-05-01
The minimum-lap-time optimal control problem for a Formula One race car is solved using direct transcription and nonlinear programming. Features of this work include significantly reduced full-lap solution times and the simultaneous optimisation of the driven line, the driver controls and multiple car set-up parameters. It is shown that significant reductions in the driven lap time can be obtained from track-specific set-up parameter optimisation. Reduced computing times are achieved using a combination of a track description based on curvilinear coordinates, analytical derivatives and model non-dimensionalisation. The curvature of the track centre line is found by solving an auxiliary optimal control problem that negates the difficulties associated with integration drift and trajectory closure.
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.
Optimization of the selective frequency damping parameters using model reduction
NASA Astrophysics Data System (ADS)
Cunha, Guilherme; Passaggia, Pierre-Yves; Lazareff, Marc
2015-09-01
In the present work, an optimization methodology to compute the best control parameters, χ and Δ, for the selective frequency damping method is presented. The optimization does not suppose any a priori knowledge of the flow physics, neither of the underlying numerical methods, and is especially suited for simulations requiring large quantity of grid elements and processors. It allows for obtaining an optimal convergence rate to a steady state of the damped Navier-Stokes system. This is achieved using the Dynamic Mode Decomposition, which is a snapshot-based method, to estimate the eigenvalues associated with global unstable dynamics. Validations test cases are presented for the numerical configurations of a laminar flow past a 2D cylinder, a separated boundary-layer over a shallow bump, and a 3D turbulent stratified-Poiseuille flow.
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.
Optimization of Parameters for Semiempirical Methods 1. Method
1989-01-01
average size."’ In con- the value of the orbital exponent for carbon . sequence, elements were parameterized only A new and completely general optimiza...the type used in MOPAC9 carbon , nitrogen, and oxygen), several other is described here. In this method, use is elements were parameterized rapidly. In...C angle in dimethyl ether. necessary condition for an optimized set of Two reference functions which have no parameters is that the error function, S
H-Infinity-Optimal Control for Distributed Parameter Systems
1991-02-28
F. Callier and C.A. Desoer , "An Algebra of Transfer Functions for Distributed Linear Time-Invariant Systems," IEEE Trans. Circuits Syst., Sept. 1978...neeuey and -f by blog* nu"bM) This report describes progress in the development and application of H-infinity-optimal control theory to distributed...parameter systems. This research is intended to develop both theory and algorithms capable of providing realistic control systems for physical plants which
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.
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.
Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology
Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander
2015-01-01
Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250
Optimal sensor placement for parameter estimation of bridges
NASA Astrophysics Data System (ADS)
Eskew, Edward; Jang, Shinae
2017-04-01
Gathering measurements from a structure can be extremely valuable for tasks such as verifying a numerical model, or structural health monitoring (SHM) to identify changes in the natural frequencies and mode shapes which can be attributed to changes in the system. In most monitoring applications, the number of potential degrees-of-freedom (DOF) for monitoring greatly outnumbers the available sensors. Optimal sensor placement (OSP) is a field of research into different methods for locating the available sensors to gather the optimal measurements. Three common methods of OSP are the effective independence (EI), effective independence driving point residue (EI-DPR), and modal kinetic energy (MKE) methods. However, comparisons of the different OSP methods for SHM applications are limited. In this paper, a comparison of the performance of the three described OSP methods for parameter estimation is performed. Parameter estimation is implemented using modified parameter localization with direct model updating, and added mass quantification utilizing a genetic algorithm (GA). The quantification of the mass addition, using simulated measurements from the sensor networks developed by each OSP method, is compared to provide an evaluation of each OSP methods capability for parameter estimation applications.
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.
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
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
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.
Parameters optimization and control in precision laser scribing
NASA Astrophysics Data System (ADS)
Zhang, Qiu'e.; Li, Yongda; Li, Yongzheng
2005-01-01
The positional precision of laser scribing and laser marking in precision metrological tools, such as scale plate and scale dial, is of the order of μm. The control of scribing must be very accurate. The laser beam parameters, focal length of the lens, and the position of the focal spot must be carefully selected and accurately controlled. The workpiece must also be accurately and repeatedly positioned. Any deviation from the required parameters would seriously affect the product quality. This paper studied an Nd:YAG laser scribing system specially designed for scribing of extremely high precision dial scale used in petroleum drilling machine. The relevant parameters were carefully selected and optimized. CAD, CAM, NC and automatic control technology were employed in the system. The integration of optics, mechanics, electronics and computer ensured high precision laser scribing.
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.
Basin structure of optimization based state and parameter estimation.
Schumann-Bischoff, Jan; Parlitz, Ulrich; Abarbanel, Henry D I; Kostuk, Mark; Rey, Daniel; Eldridge, Michael; Luther, Stefan
2015-05-01
Most data based state and parameter estimation methods require suitable initial values or guesses to achieve convergence to the desired solution, which typically is a global minimum of some cost function. Unfortunately, however, other stable solutions (e.g., local minima) may exist and provide suboptimal or even wrong estimates. Here, we demonstrate for a 9-dimensional Lorenz-96 model how to characterize the basin size of the global minimum when applying some particular optimization based estimation algorithm. We compare three different strategies for generating suitable initial guesses, and we investigate the dependence of the solution on the given trajectory segment (underlying the measured time series). To address the question of how many state variables have to be measured for optimal performance, different types of multivariate time series are considered consisting of 1, 2, or 3 variables. Based on these time series, the local observability of state variables and parameters of the Lorenz-96 model is investigated and confirmed using delay coordinates. This result is in good agreement with the observation that correct state and parameter estimation results are obtained if the optimization algorithm is initialized with initial guesses close to the true solution. In contrast, initialization with other exact solutions of the model equations (different from the true solution used to generate the time series) typically fails, i.e., the optimization procedure ends up in local minima different from the true solution. Initialization using random values in a box around the attractor exhibits success rates depending on the number of observables and the available time series (trajectory segment).
Basin structure of optimization based state and parameter estimation
NASA Astrophysics Data System (ADS)
Schumann-Bischoff, Jan; Parlitz, Ulrich; Abarbanel, Henry D. I.; Kostuk, Mark; Rey, Daniel; Eldridge, Michael; Luther, Stefan
2015-05-01
Most data based state and parameter estimation methods require suitable initial values or guesses to achieve convergence to the desired solution, which typically is a global minimum of some cost function. Unfortunately, however, other stable solutions (e.g., local minima) may exist and provide suboptimal or even wrong estimates. Here, we demonstrate for a 9-dimensional Lorenz-96 model how to characterize the basin size of the global minimum when applying some particular optimization based estimation algorithm. We compare three different strategies for generating suitable initial guesses, and we investigate the dependence of the solution on the given trajectory segment (underlying the measured time series). To address the question of how many state variables have to be measured for optimal performance, different types of multivariate time series are considered consisting of 1, 2, or 3 variables. Based on these time series, the local observability of state variables and parameters of the Lorenz-96 model is investigated and confirmed using delay coordinates. This result is in good agreement with the observation that correct state and parameter estimation results are obtained if the optimization algorithm is initialized with initial guesses close to the true solution. In contrast, initialization with other exact solutions of the model equations (different from the true solution used to generate the time series) typically fails, i.e., the optimization procedure ends up in local minima different from the true solution. Initialization using random values in a box around the attractor exhibits success rates depending on the number of observables and the available time series (trajectory segment).
Hybrid optimization method with general switching strategy for parameter estimation.
Balsa-Canto, Eva; Peifer, Martin; Banga, Julio R; Timmer, Jens; Fleck, Christian
2008-03-24
Modeling and simulation of cellular signaling and metabolic pathways as networks of biochemical reactions yields sets of non-linear ordinary differential equations. These models usually depend on several parameters and initial conditions. If these parameters are unknown, results from simulation studies can be misleading. Such a scenario can be avoided by fitting the model to experimental data before analyzing the system. This involves parameter estimation which is usually performed by minimizing a cost function which quantifies the difference between model predictions and measurements. Mathematically, this is formulated as a non-linear optimization problem which often results to be multi-modal (non-convex), rendering local optimization methods detrimental. In this work we propose a new hybrid global method, based on the combination of an evolutionary search strategy with a local multiple-shooting approach, which offers a reliable and efficient alternative for the solution of large scale parameter estimation problems. The presented new hybrid strategy offers two main advantages over previous approaches: First, it is equipped with a switching strategy which allows the systematic determination of the transition from the local to global search. This avoids computationally expensive tests in advance. Second, using multiple-shooting as the local search procedure reduces the multi-modality of the non-linear optimization problem significantly. Because multiple-shooting avoids possible spurious solutions in the vicinity of the global optimum it often outperforms the frequently used initial value approach (single-shooting). Thereby, the use of multiple-shooting yields an enhanced robustness of the hybrid approach.
Watson, J.G.; Chow, J.C.; Egami, R.T.; Bowen, J.L.; Frazier, C.A.
1991-06-01
The State of California monitors the concentrations of acidic gases and particles at 10 sites throughout the state. Seven sites represent urban areas (South Coast Air Basin - three sites, San Francisco Bay Area, Bakersfield, Santa Barbara, and Sacramento) and three represent forested areas (Sequoia National Park, Yosemite National Park, and Gasquet). Several sites are collocated with monitoring instruments for other air quality and forest response networks. Continuous monitors for the dry deposition network collect hourly average values for ozone, wind speed, wind direction, atmospheric stability, temperature, dew point, time of wetness, and solar radiation. A newly-designed gas/particle sampler collects daytime (6 a.m. to 6 p.m.) and nighttime (6 p.m. to 6 a.m.) samples every sixth day for sulfur dioxide, ammonia, nitrogen dioxide, and nitric acid. Particles are collected on the same day/night schedule in PM(10) and PM(2.5) size ranges, and are analyzed for mass, sulfate, nitrate, chloride, ammonium, sodium, magnesium, potassium, and calcium ions. The sampling schedule follows the regulatory schedule adopted by the EPA and ARB for suspended particulate matter. Wet deposition data are collected at or nearby the dry deposition stations. The first year of the monitoring program included installation of the network, training of technicians, acquisition and validation of data, and transfer of the sampling and analysis technology to Air Resources Board operating divisions. Data have been validated and stored for the period May, 1988 through September, 1989.
Estimation of Saxophone Control Parameters by Convex Optimization
Wang, Cheng-i; Smyth, Tamara; Lipton, Zachary C.
2015-01-01
In this work, an approach to jointly estimating the tone hole configuration (fingering) and reed model parameters of a saxophone is presented. The problem isn't one of merely estimating pitch as one applied fingering can be used to produce several different pitches by bugling or overblowing. Nor can a fingering be estimated solely by the spectral envelope of the produced sound (as it might for estimation of vocal tract shape in speech) since one fingering can produce markedly different spectral envelopes depending on the player's embouchure and control of the reed. The problem is therefore addressed by jointly estimating both the reed (source) parameters and the fingering (filter) of a saxophone model using convex optimization and 1) a bank of filter frequency responses derived from measurement of the saxophone configured with all possible fingerings and 2) sample recordings of notes produced using all possible fingerings, played with different overblowing, dynamics and timbre. The saxophone model couples one of several possible frequency response pairs (corresponding to the applied fingering), and a quasi-static reed model generating input pressure at the mouthpiece, with control parameters being blowing pressure and reed stiffness. Applied fingering and reed parameters are estimated for a given recording by formalizing a minimization problem, where the cost function is the error between the recording and the synthesized sound produced by the model having incremental parameter values for blowing pressure and reed stiffness. The minimization problem is nonlinear and not differentiable and is made solvable using convex optimization. The performance of the fingering identification is evaluated with better accuracy than previous reported value. PMID:27754493
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.
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.
NASA Astrophysics Data System (ADS)
Park, Yunkyu; Lim, Jongmin; Lee, Chongmu
2005-05-01
The reactive sputter deposition of tungsten carbide (WCx) films as an alternative to chromium electroplating was studied. The effects of rf power, pressure, sputtering gas composition, and substrate temperature on the deposition rate of the WCx coatings were investigated. The effects of rf power and sputtering gas composition on the hardness and corrosion resistance of the WCx coatings were also investigated. X-ray diffraction (XRD) and Auger electron spectroscopy (AES) analyses were performed to determine the structures and compositions of the films, respectively. The hardnesses of the films were measured using a nanoindenter. The microstructures of the films were observed by scanning electron microscopy. The corrosion resistances of the films were evaluated using a salt-spray test. The deposition rate of the films was proportional to rf power and inversely proportional to the CH4 content of the sputtering gas. The deposition rate increased linearly with increasing chamber pressure. The hardness of the WCx coatings increased as rf power increased. The highest hardness was obtained at a CH4 concentration of 10 vol.% in the sputtering gas. The hardness of the WCx film deposited under optimal conditions was much higher than that of the electroplated chromium film, although the corrosion resistance of the former was slightly lower than that of the latter.
NASA Astrophysics Data System (ADS)
Baciu, M. A.; Nanu, C.; Sandu, G. I.; Toma, B. F.; Bejinariu, C.; Cazac, A.; Toma, S. L.
2017-06-01
The paper aims to determine the influence of the process parameters, namely: C2H2 gas flow rate and inclination angle of the spraying gun on physico and mechanical properties of the hardalloyed layers of Diamax 10999 Eutalloy, on steel support - obtained by flame thermal spray process. For this purpose, the two technological parameters varied on three levels and in each case were evaluated the deposits properties. Investigations conducted by electronical microscopy SEM, X-ray, micro-hardness and by adherence evaluation and of the deposits porosity allowed the establishment of the performant deposit. Thus it was found that at the decreasing of the spraying distance,the deposit porosity decreases; in layer appear the phenomena of overheating, issue that determine the adherence reducing in average of 22%, and also the modification of chemical composition. The results recorded have afforded the obtaining of an optimum domain of variation of the process parameters.
NASA Astrophysics Data System (ADS)
Afshari Pour, Elnaz; Shafai, Cyrus
2017-02-01
The variation of oxygen concentration in the Indium Tin Oxide (ITO) structure highly impacts its electrical and optical characteristics. In this work, we investigated the effect of oxygen partial flow (O2/O2+Ar) and deposition pressure (p) on the refractive index (n) of reactive sputtered ITO thin films. A statistical study with a Genetic Algorithm (GA) optimization was implemented to find optimal deposition conditions for obtaining particular refractive indices. Several samples of ITO thin films with refractive indices ranging from 1.69 - 2.1 were deposited by DC sputtering technique at various oxygen concentrations and deposition pressures, in order to develop the statistical database. A linear polynomial surface was locally fitted to the data of O2/O2+Ar, p, and n of deposited films. This surface was then used as the fitness function of the GA. By defining the desired n as the objective value of the GA, the optimized deposition conditions can be found. Two cases were experimentally demonstrated, with the GA determining the needed process parameters to deposit ITO with n=2.2 and n=1.6. Measured results were very close to desired values, with n=2.25 and n=1.62, demonstrating the effectiveness of this method for predicting needed reactive sputtering conditions to enable arbitrary refractive indices.
Optimization of gun parameters for a pulsed power electron gun
Srinivasan-Rao, T.; Smedley, J.; Batchelor, K.; Farrell, J.P.; Dudnikova, G.
1999-07-01
Extensive simulation work has been done to identify the optimal parameters for a pulsed power electron gun. PBGUNS, an electrostatic beam optics code, was used to optimize the electrode shape and the beam spatial distribution, including modeling the focusing effect of a curved cathode surface. MAFIA, a particle-in-a-cell code, was used to investigate those aspects that required time dependence, such as longitudinal energy spread. The range of agreement between the two codes was also investigated. The transverse phase space at a comparison plane was found to be very close (within 1{percent} at low currents and 4{percent} for higher currents), even for bunch lengths shorter than the gap transit time. {copyright} {ital 1999 American Institute of Physics.}
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.
Adaptive Estimation of Intravascular Shear Rate Based on Parameter Optimization
NASA Astrophysics Data System (ADS)
Nitta, Naotaka; Takeda, Naoto
2008-05-01
The relationships between the intravascular wall shear stress, controlled by flow dynamics, and the progress of arteriosclerosis plaque have been clarified by various studies. Since the shear stress is determined by the viscosity coefficient and shear rate, both factors must be estimated accurately. In this paper, an adaptive method for improving the accuracy of quantitative shear rate estimation was investigated. First, the parameter dependence of the estimated shear rate was investigated in terms of the differential window width and the number of averaged velocity profiles based on simulation and experimental data, and then the shear rate calculation was optimized. The optimized result revealed that the proposed adaptive method of shear rate estimation was effective for improving the accuracy of shear rate calculation.
Optimal segmentation of pupillometric images for estimating pupil shape parameters.
De Santis, A; Iacoviello, D
2006-12-01
The problem of determining the pupil morphological parameters from pupillometric data is considered. These characteristics are of great interest for non-invasive early diagnosis of the central nervous system response to environmental stimuli of different nature, in subjects suffering some typical diseases such as diabetes, Alzheimer disease, schizophrenia, drug and alcohol addiction. Pupil geometrical features such as diameter, area, centroid coordinates, are estimated by a procedure based on an image segmentation algorithm. It exploits the level set formulation of the variational problem related to the segmentation. A discrete set up of this problem that admits a unique optimal solution is proposed: an arbitrary initial curve is evolved towards the optimal segmentation boundary by a difference equation; therefore no numerical approximation schemes are needed, as required in the equivalent continuum formulation usually adopted in the relevant literature.
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.
Sahu, B. B. E-mail: hanjg@skku.edu; Yin, Yongyi; Han, Jeon G. E-mail: hanjg@skku.edu
2016-03-15
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 N{sub 2}/NH{sub 3}/SiH{sub 4} 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.
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.
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.
Vibration evaluation and parameter optimization of hydraulic thruster
NASA Astrophysics Data System (ADS)
Peng, Yong; Zhang, Haokun
2017-01-01
Two difficult problems which are drilling string vibration and drilling pressure control exist in the process of drilling large displacement horizontal well. Using hydraulic thruster can not only improve the mechanical drilling speed and increase the horizontal section of footage displacement but also obtain better drill string dynamic characteristics and reduce vibration of drilling tool and prolong the life of the bottom hole assembly. By using the spring-damping model of drill string, the dynamic response of the different excitation of the drill bit is analyzed, so as to evaluate the effect of vibration reduction of hydraulic thruster. Use the three factors four levels orthogonal test method to optimize the key design parameters of hydraulic thruster. The analysis shows that the different drilling mud density should be used in the hydraulic thruster with different key parameters, in order to display its superiority.
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.
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.
Optimal-control theoretic methods for optimization and regulation of distributed parameter systems
NASA Astrophysics Data System (ADS)
Goss, Jennifer Dawn
Optimal control and optimization of distributed parameter systems are discussed in the context of a common control framework. The adjoint method of optimization and the traditional linear quadratic regulator implementation of optimal control both employ adjoint or costate variables in the determination of control variable progression. As well both theories benefit from a reduced order model approximation in their execution. This research aims to draw clear parallels between optimization and optimal control utilizing these similarities. Several applications are presented showing the use of adjoint/costate variables and reduced order models in optimization and optimal control problems. The adjoint method for shape optimization is derived and implemented for the quasi-one-dimensional duct and two variations of a two-dimensional double ramp inlet. All applications are governed by the Euler equations. The quasi-one-dimensional duct is solved first to test the adjoint method and to verify the results against an analytical solution. The method is then adapted to solve the shape optimization of the double ramp inlet. A finite volume solver is tested on the flow equations and then implemented for the corresponding adjoint equations. The gradient of the cost function with respect to the shape parameters is derived based on the computed adjoint variables. The same inlet shape optimization problem is then solved using a reduced order model. The basis functions in the reduced order model are computed using the method of snapshots form of proper orthogonal decomposition. The corresponding weights are derived using an optimization in the design parameter space to match the reduced order model to the original snapshots. A continuous map of these weights in terms of the design variables is obtained via a response surface approximations and artificial neural networks. This map is then utilized in an optimization problem to determine the optimal inlet shape. As in the adjoint method
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.
Plasma deposition of tetraglyme inside small diameter tubing: optimization and characterization.
Cao, Lan; Ratner, Buddy D; Horbett, Thomas A
2007-04-01
In this study, a glow discharge plasma deposition system previously used for treating flat substrates was successfully modified and optimized to produce a PEO-like coating on the inner surface of 1-3 mm ID polyethylene tubing by deposition of tetra ethylene glycol dimethyl ether (tetraglyme). The plasma treatment conditions were varied in order to find operating values that would produce coatings with the ultralow (< 5 ng/cm(2)) fibrinogen adsorption (Gamma(Fg)) previously shown necessary to significantly reduce platelet adhesion. The flow rate of gaseous tetraglyme monomer, pressure, and plasma generating power were found to be the most important parameters affecting the uniformity and chemical structure of the coating. The coating uniformity and quality were assessed by measuring Gamma(Fg) at positions 1 cm apart along the entire tube and the fraction of C1s carbon that was in an ether bond (ether-carbon ratio) by electron spectroscopy of chemical analysis. Under optimized conditions, tetraglyme plasma-coated tubes of up to 20 cm in length had ultralow Gamma(Fg). The region of the tube that had ultralow Gamma(Fg) also had C1s ether-carbon ratios that are greater than 50%. (c) 2006 Wiley Periodicals, Inc.
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.
Peng, Bin; Gong, Dongdong; Zhang, Wanli; Jiang, Jianying; Shu, Lin; Zhang, Yahui
2016-08-10
AlN thin films were deposited on flexible Hastelloy tapes and Si (100) substrate by middle-frequency magnetron sputtering. A layer of Y₂O₃ films was used as a buffer layer for the Hastelloy tapes. A two-step deposition technique was used to prepare the AlN films. The effects of deposition parameters such as sputtering power, N₂/Ar flow rate and sputtering pressure on the microstructure of the AlN thin films were systematically investigated. The results show that the dependency of the full width at half maximum (FWHM) of AlN/Y₂O₃/Hastelloy on the sputtering parameters is similar to that of AlN/Si (100). The FWHM of the AlN (002) peak of the prepared AlN films decreases with increasing sputtering power. The FWHM decreases with the increase of the N₂/Ar flow rate or sputtering pressure, and increases with the further increase of the N₂/Ar flow rate or sputtering pressure. The FWHM of the AlN/Y₂O₃/Hastelloy prepared under optimized parameters is only 3.7° and its root mean square (RMS) roughness is 5.46 nm. Based on the experimental results, the growth mechanism of AlN thin films prepared by the two-step deposition process was explored. This work would assist us in understanding the AlN film's growth mechanism of the two-step deposition process, preparing highly c-axis-oriented AlN films on flexible metal tapes and developing flexible surface acoustic wave (SAW) sensors from an application perspective.
Peng, Bin; Gong, Dongdong; Zhang, Wanli; Jiang, Jianying; Shu, Lin; Zhang, Yahui
2016-01-01
AlN thin films were deposited on flexible Hastelloy tapes and Si (100) substrate by middle-frequency magnetron sputtering. A layer of Y2O3 films was used as a buffer layer for the Hastelloy tapes. A two-step deposition technique was used to prepare the AlN films. The effects of deposition parameters such as sputtering power, N2/Ar flow rate and sputtering pressure on the microstructure of the AlN thin films were systematically investigated. The results show that the dependency of the full width at half maximum (FWHM) of AlN/Y2O3/Hastelloy on the sputtering parameters is similar to that of AlN/Si (100). The FWHM of the AlN (002) peak of the prepared AlN films decreases with increasing sputtering power. The FWHM decreases with the increase of the N2/Ar flow rate or sputtering pressure, and increases with the further increase of the N2/Ar flow rate or sputtering pressure. The FWHM of the AlN/Y2O3/Hastelloy prepared under optimized parameters is only 3.7° and its root mean square (RMS) roughness is 5.46 nm. Based on the experimental results, the growth mechanism of AlN thin films prepared by the two-step deposition process was explored. This work would assist us in understanding the AlN film’s growth mechanism of the two-step deposition process, preparing highly c-axis–oriented AlN films on flexible metal tapes and developing flexible surface acoustic wave (SAW) sensors from an application perspective. PMID:28773806
Multivariate Parameter Sets for Optimal Synthesis of Compliant Mechanisms
NASA Technical Reports Server (NTRS)
Shibakov, Alex; Hull, Patrick V.; Canfield, Stephen L.; Tinker, Mike
2005-01-01
This paper will propose the use of control maps along with discretized elements or meshes in the design parameter set for optimizing compliant mechanisms. The use of control maps will be demonstrated to encode the motion of groups of nodes or control points within a compliant mechanism design with simple mapping rules. The technique will serve as an alternative to increased mesh size or node wandering techniques that have been proposed to increase the number of alternative design shapes that may be considered. As an alternative approach, the proposed control map parameterization has the significant benefit that it minimizes the number of design parameters necessary (parameters increase linearly with the mesh size) in describing a given design making it computationally efficient. A limited number of tiles can produce a map that has a significant effect on the final shape. If the tiles are chosen appropriately, the problems such as material overlap and non-convex mesh elements are avoided automatically. This paper will describe the implementation of these control maps and provide several examples showing their implementation in the compliant mechanism topology synthesis process.
Optimization of process parameters in stereolithography using genetic algorithm
NASA Astrophysics Data System (ADS)
Chockalingam, K.; Jawahar, N.; Vijaybabu, E. R.
2003-10-01
Stereolithography is the most popular RP process in which intricate models are directly constructed from a CAD package by polymerizing a plastic monomer. The application range is still limited, because dimensional accuracy is still inferior to that of conventional machining process. The ultimate dimensional accuracy of a part built on a layer-by-layer basis depends on shrinkage which depend on many factors such as layer thickness, hatch spacing, hatch style, hatch over cure and fill cure depth. The influence of the above factors on shrinkage in X and Y directions fit to the nonlinear pattern. A particular combination of process variables that would result same shrinkage rate in both directions would enable to predict shrinkage allowance to be provided on a part and hence the CAD model could be constructed including shrinkage allowance. In this concern, the objective of the present work is set as determination of process parameters to have same shrinkage rate in both X and Y directions. A genetic algorithm (GA) is proposed to find optimal process parameters for the above objective. This approach is an analytical approach with experimental sample data and has great potential to predict process parameters for better dimensional accuracy in stereolithography process.
Prasad, Leena Kumari; LaFountaine, Justin S; Keen, Justin M; Williams, Robert O; McGinity, James W
2016-12-30
Electrostatic powder deposition (ESPD) has been developed as a solvent-free method to prepare pharmaceutical films. The aim of this work was to investigate the influence of process parameters during (1) electrostatic powder deposition, (2) curing, and (3) removal of the film from the substrate on the properties of the film. Polyethylene oxide (PEO) was used as the model polymer and stainless steel 316 as the substrate. Deposition efficiency (i.e. deposited weight) was measured with varying charging voltage, gun tip to substrate distance, and environmental humidity. Scanning electron microscopy was utilized to assess film formation, and adhesive and mechanical strength of films were measured with varying cure temperature and time. Adhesive strength was measured for films prepared on substrates of varying surface roughness. When deposition was performed at low humidity conditions, 25%RH, process parameters did not significantly affect deposition behavior. At 40%RH, increasing deposition efficiency with decreasing gun tip to substrate distance and increasing voltage (up to 60kV) was observed. Complete film formation was seen by 30min at 80°C, compared to lower curing temperatures and times. All films were readily removed from the substrates. The results show the ESPD process can be modified to produce films with good mechanical properties (e.g. tensile strength>0.06MPa), suggesting it is a promising dry powder process for preparing pharmaceutical films.
NASA Astrophysics Data System (ADS)
Angelastro, A.; Campanelli, S. L.; Casalino, G.
2017-09-01
This paper presents a study on process parameters and building strategy for the deposition of Colmonoy 227-F powder by CO2 laser with a focal spot diameter of 0.3 mm. Colmonoy 227-F is a nickel alloy especially designed for mold manufacturing. The substrate material is a 10 mm thick plate of AISI 304 steel. A commercial CO2 laser welding machine was equipped with a low-cost powder feeding system. In this work, following another one in which laser power, scanning speed and powder flow rate had been studied, the effects of two important process parameters, i.e. hatch spacing and step height, on the properties of the built parts were analysed. The explored ranges of hatch spacing and step height were respectively 150-300 μm and 100-200 μm, whose dimensions were comparable with that of the laser spot. The roughness, adhesion, microstructure, microhardness and density of the manufactured specimens were studied for multi-layer samples, which were made of 30 layers. The statistical significance of the studied process parameters was assessed by the analysis of the variance. The process parameters used allowed to obtain both first layer-to-substrate and layer-to-layer good adhesions. The microstructure was fine and almost defect-free. The microhardness of the deposited material was about 100 HV higher than that of the starting powder. The density as high as 98% of that of the same bulk alloy was more than satisfactory. Finally, simultaneous optimization of density and roughness was performed using the contour plots.
NASA Astrophysics Data System (ADS)
Spanu, Antonio; Michieli Vitturi, Mattia de'; Barsotti, Sara
2016-09-01
Since the 1970s, multiple reconstruction techniques have been proposed and are currently used, to extrapolate and quantify eruptive parameters from sampled tephra fall deposit datasets. Atmospheric transport and deposition processes strongly control the spatial distribution of tephra deposit; therefore, a large uncertainty affects mass derived estimations especially for fall layer that are not well exposed. This paper has two main aims: the first is to analyse the sensitivity to the deposit sampling strategy of reconstruction techniques. The second is to assess whether there are differences between the modelled values for emitted mass and grainsize, versus values estimated from the deposits. We find significant differences and propose a new correction strategy. A numerical approach is demonstrated by simulating with a dispersal code a mild explosive event occurring at Mt. Etna on 24 November 2006. Eruptive parameters are reconstructed by an inversion information collected after the eruption. A full synthetic deposit is created by integrating the deposited mass computed by the model over the computational domain (i.e., an area of 7.5 × 104 km 2). A statistical analysis based on 2000 sampling tests of 50 sampling points shows a large variability, up to 50 % for all the reconstruction techniques. Moreover, for some test examples Power Law errors are larger than estimated uncertainty. A similar analysis, on simulated grain-size classes, shows how spatial sampling limitations strongly reduce the utility of available information on the total grain size distribution. For example, information on particles coarser than ϕ(-4) is completely lost when sampling at 1.5 km from the vent for all columns with heights less than 2000 m above the vent. To correct for this effect an optimal sampling strategy and a new reconstruction method are presented. A sensitivity study shows that our method can be extended to a wide range of eruptive scenarios including those in which
Optimization of resistance spot welding parameters for microalloyed steel sheets
NASA Astrophysics Data System (ADS)
Viňáš, Ján; Kaščák, Ľuboš; Greš, Miroslav
2016-11-01
The paper presents the results of resistance spot welding of hot-dip galvanized microalloyed steel sheets used in car body production. The spot welds were made with various welding currents and welding time values, but with a constant pressing force of welding electrodes. The welding current and welding time are the dominant characteristics in spot welding that affect the quality of spot welds, as well as their dimensions and load-bearing capacity. The load-bearing capacity of welded joints was evaluated by tensile test according to STN 05 1122 standard and dimensions and inner defects were evaluated by metallographic analysis by light optical microscope. Thewelding parameters of investigated microalloyed steel sheets were optimized for resistance spot welding on the pneumatic welding machine BPK 20.
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.
Parameter identifiability-based optimal observation remedy for biological networks.
Wang, Yulin; Miao, Hongyu
2017-05-04
To systematically understand the interactions between numerous biological components, a variety of biological networks on different levels and scales have been constructed and made available in public databases or knowledge repositories. Graphical models such as structural equation models have long been used to describe biological networks for various quantitative analysis tasks, especially key biological parameter estimation. However, limited by resources or technical capacities, partial observation is a common problem in experimental observations of biological networks, and it thus becomes an important problem how to select unobserved nodes for additional measurements such that all unknown model parameters become identifiable. To the best knowledge of our authors, a solution to this problem does not exist until this study. The identifiability-based observation problem for biological networks is mathematically formulated for the first time based on linear recursive structural equation models, and then a dynamic programming strategy is developed to obtain the optimal observation strategies. The efficiency of the dynamic programming algorithm is achieved by avoiding both symbolic computation and matrix operations as used in other studies. We also provided necessary theoretical justifications to the proposed method. Finally, we verified the algorithm using synthetic network structures and illustrated the application of the proposed method in practice using a real biological network related to influenza A virus infection. The proposed approach is the first solution to the structural identifiability-based optimal observation remedy problem. It is applicable to an arbitrary directed acyclic biological network (recursive SEMs) without bidirectional edges, and it is a computerizable method. Observation remedy is an important issue in experiment design for biological networks, and we believe that this study provides a solid basis for dealing with more challenging design
NASA Astrophysics Data System (ADS)
Barber, Michael N.
1980-03-01
An algorithm for determining the sequence of variational parameters in a variational approximation to a real-space renormalization group is developed. Using this procedure, the Kadanoff one-hypercube approximation for the two-dimensional Ising model is investigated in some detail. We conclude that the apparent success of this method is somewhat fortuitous; a consistent and completely optimized treatment yielding considerably poorer estimates of the specific heat exponents. In addition, the variational parameter is found to be non-analytic at the fixed point. The nature of singularity agrees with the predictions of van Saarloos, van Leeuwen, and Pruisken.
Parameter optimization in differential geometry based solvation models
Wang, Bao; Wei, G. W.
2015-01-01
Differential geometry (DG) based solvation models are a new class of variational implicit solvent approaches that are able to avoid unphysical solvent-solute boundary definitions and associated geometric singularities, and dynamically couple polar and non-polar interactions in a self-consistent framework. Our earlier study indicates that DG based non-polar solvation model outperforms other methods in non-polar solvation energy predictions. However, the DG based full solvation model has not shown its superiority in solvation analysis, due to its difficulty in parametrization, which must ensure the stability of the solution of strongly coupled nonlinear Laplace-Beltrami and Poisson-Boltzmann equations. In this work, we introduce new parameter learning algorithms based on perturbation and convex optimization theories to stabilize the numerical solution and thus achieve an optimal parametrization of the DG based solvation models. An interesting feature of the present DG based solvation model is that it provides accurate solvation free energy predictions for both polar and non-polar molecules in a unified formulation. Extensive numerical experiment demonstrates that the present DG based solvation model delivers some of the most accurate predictions of the solvation free energies for a large number of molecules. PMID:26450304
Robust integrated autopilot/autothrottle design using constrained parameter optimization
NASA Technical Reports Server (NTRS)
Ly, Uy-Loi; Voth, Christopher; Sanjay, Swamy
1990-01-01
A multivariable control design method based on constrained parameter optimization was applied to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the following: (1) direct synthesis of a multivariable 'inner-loop' feedback control system based on total energy control principles; (2) synthesis of speed/altitude-hold designs as 'outer-loop' feedback/feedforward control systems around the above inner loop; and (3) direct synthesis of a combined 'inner-loop' and 'outer-loop' multivariable control system. The design procedure offers a direct and structured approach for the determination of a set of controller gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The presented approach may be applied to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by this method following careful problem formulation of the design objectives and constraints. Performance characteristics of the optimization design were improved over the current autopilot design on the B737-100 Transport Research Vehicle (TSRV) at the landing approach and cruise flight conditions; particularly in the areas of closed-loop damping, command responses, and control activity in the presence of turbulence.
Optimal z-axis scanning parameters for gynecologic cytology specimens
Donnelly, Amber D.; Mukherjee, Maheswari S.; Lyden, Elizabeth R.; Bridge, Julia A.; Lele, Subodh M.; Wright, Najia; McGaughey, Mary F.; Culberson, Alicia M.; Horn, Adam J.; Wedel, Whitney R.; Radio, Stanley J.
2013-01-01
Background: The use of virtual microscopy (VM) in clinical cytology has been limited due to the inability to focus through three dimensional (3D) cell clusters with a single focal plane (2D images). Limited information exists regarding the optimal scanning parameters for 3D scanning. Aims: The purpose of this study was to determine the optimal number of the focal plane levels and the optimal scanning interval to digitize gynecological (GYN) specimens prepared on SurePath™ glass slides while maintaining a manageable file size. Subjects and Methods: The iScanCoreo Au scanner (Ventana, AZ, USA) was used to digitize 192 SurePath™ glass slides at three focal plane levels at 1 μ interval. The digitized virtual images (VI) were annotated using BioImagene's Image Viewer. Five participants interpreted the VI and recorded the focal plane level at which they felt confident and later interpreted the corresponding glass slide specimens using light microscopy (LM). The participants completed a survey about their experiences. Inter-rater agreement and concordance between the VI and the glass slide specimens were evaluated. Results: This study determined an overall high intra-rater diagnostic concordance between glass and VI (89-97%), however, the inter-rater agreement for all cases was higher for LM (94%) compared with VM (82%). Survey results indicate participants found low grade dysplasia and koilocytes easy to diagnose using three focal plane levels, the image enhancement tool was useful and focusing through the cells helped with interpretation; however, the participants found VI with hyperchromatic crowded groups challenging to interpret. Participants reported they prefer using LM over VM. This study supports using three focal plane levels and 1 μ interval to expand the use of VM in GYN cytology. Conclusion: Future improvements in technology and appropriate training should make this format a more preferable and practical option in clinical cytology. PMID:24524004
Optimization of system parameters for a complete multispectral polarimeter
Hollstein, Andre; Ruhtz, Thomas; Fischer, Juergen; Preusker, Rene
2009-08-20
We optimize a general class of complete multispectral polarimeters with respect to signal-to-noise ratio, stability against alignment errors, and the minimization of errors regarding a given set of polarization states. The class of polarimeters that are dealt with consists of at least four polarization optics each with a multispectral detector. A polarization optic is made of an azimuthal oriented wave plate and a polarizing filter. A general, but not unique, analytic solution that minimizes signal-to-noise ratio is introduced for a polarimeter that incorporates four simultaneous measurements with four independent optics. The optics consist of four sufficient wave plates, where at least one is a quarter-wave plate. The solution is stable with respect to the retardance of the quarter-wave plate; therefore, it can be applied to real-world cases where the retardance deviates from {lambda}/4. The solution is a set of seven rotational parameters that depends on the given retardances of the wave plates. It can be applied to a broad range of real world cases. A numerical method for the optimization of arbitrary polarimeters of the type discussed is also presented and applied for two cases. First, the class of polarimeters that were analytically dealt with are further optimized with respect to stability and error performance with respect to linear polarized states. Then a multispectral case for a polarimeter that consists of four optics with real achromatic wave plates is presented. This case was used as the theoretical background for the development of the Airborne Multi-Spectral Sunphoto- and Polarimeter (AMSSP), which is an instrument for the German research aircraft HALO.
Optimization of system parameters for a complete multispectral polarimeter.
Hollstein, André; Ruhtz, Thomas; Fischer, Jürgen; Preusker, René
2009-08-20
We optimize a general class of complete multispectral polarimeters with respect to signal-to-noise ratio, stability against alignment errors, and the minimization of errors regarding a given set of polarization states. The class of polarimeters that are dealt with consists of at least four polarization optics each with a multispectral detector. A polarization optic is made of an azimuthal oriented wave plate and a polarizing filter. A general, but not unique, analytic solution that minimizes signal-to-noise ratio is introduced for a polarimeter that incorporates four simultaneous measurements with four independent optics. The optics consist of four sufficient wave plates, where at least one is a quarter-wave plate. The solution is stable with respect to the retardance of the quarter-wave plate; therefore, it can be applied to real-world cases where the retardance deviates from lambda/4. The solution is a set of seven rotational parameters that depends on the given retardances of the wave plates. It can be applied to a broad range of real world cases. A numerical method for the optimization of arbitrary polarimeters of the type discussed is also presented and applied for two cases. First, the class of polarimeters that were analytically dealt with are further optimized with respect to stability and error performance with respect to linear polarized states. Then a multispectral case for a polarimeter that consists of four optics with real achromatic wave plates is presented. This case was used as the theoretical background for the development of the Airborne Multi-Spectral Sunphoto- and Polarimeter (AMSSP), which is an instrument for the German research aircraft HALO.
Optimal vibration control of curved beams using distributed parameter models
NASA Astrophysics Data System (ADS)
Liu, Fushou; Jin, Dongping; Wen, Hao
2016-12-01
The design of linear quadratic optimal controller using spectral factorization method is studied for vibration suppression of curved beam structures modeled as distributed parameter models. The equations of motion for active control of the in-plane vibration of a curved beam are developed firstly considering its shear deformation and rotary inertia, and then the state space model of the curved beam is established directly using the partial differential equations of motion. The functional gains for the distributed parameter model of curved beam are calculated by extending the spectral factorization method. Moreover, the response of the closed-loop control system is derived explicitly in frequency domain. Finally, the suppression of the vibration at the free end of a cantilevered curved beam by point control moment is studied through numerical case studies, in which the benefit of the presented method is shown by comparison with a constant gain velocity feedback control law, and the performance of the presented method on avoidance of control spillover is demonstrated.
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.
Optimized interaction parameters for metal-doped endohedral fullerene
NASA Astrophysics Data System (ADS)
Dhiman, Shobhna; Kumar, Ranjan; Dharamvir, Keya
2017-06-01
Interaction between various atoms doped inside C60 can be modeled using interaction potentials and, thus, cohesive energy and other physical constants may be calculated. In case of metal-doped fullerene total energy may be written in terms of three different types of interactions, namely carbon-carbon interaction, metal-metal interaction and carbon-metal interaction. Brenner potential, Gupta potential, and Lennard-Jones potentials have been used to model these interactions respectively. Generally, parameters used in these model potentials are not readily available and need to be fine-tuned for different dopants. In this paper, we have deduced/optimized these interaction parameters for Cu, Ag, Al and Ga doped C60 comparing with our Density Functional Theory (DFT) results and hence predicting the stability of various metal-doped fullerenes. Total energy calculations reveal that a maximum of nine copper atoms can be doped inside the fullerene cage and form stable complex without distorting the cage significantly. As we add more number of Cu atoms in the fullerene molecule, cage structure breaks down. In the same way, we have done calculations for Ag, Al and Ga atoms doped inside the fullerene molecule and found that the maximum of eight, nine, nine atoms can form stable complexes.
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)
Kadyrmetov, A. M.; Sharifullin, S. N.
2016-11-01
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.
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.
Deng, Zhang; He, Wenjie; Duan, Chenlong; Chen, Rong; Shan, Bin
2016-01-15
Spatial atomic layer deposition (SALD) is a promising technology with the aim of combining the advantages of excellent uniformity and conformity of temporal atomic layer deposition (ALD), and an industrial scalable and continuous process. In this manuscript, an experimental and numerical combined model of atmospheric SALD system is presented. To establish the connection between the process parameters and the growth efficiency, a quantitative model on reactant isolation, throughput, and precursor utilization is performed based on the separation gas flow rate, carrier gas flow rate, and precursor mass fraction. The simulation results based on this model show an inverse relation between the precursor usage and the carrier gas flow rate. With the constant carrier gas flow, the relationship of precursor usage and precursor mass fraction follows monotonic function. The precursor concentration, regardless of gas velocity, is the determinant factor of the minimal residual time. The narrow gap between precursor injecting heads and the substrate surface in general SALD system leads to a low Péclet number. In this situation, the gas diffusion act as a leading role in the precursor transport in the small gap rather than the convection. Fluid kinetics from the numerical model is independent of the specific structure, which is instructive for the SALD geometry design as well as its process optimization.
Sachot, Nadège; Castano, Oscar; Planell, Josep A; Engel, Elisabeth
2015-08-01
Electrospinning is a method that can be used to efficiently produce scaffolds that mimic the fibrous structure of natural tissue, such as muscle structures or the extracellular matrix of bone. The technique is often used as a way of depositing composites (organic/inorganic materials) to obtain bioactive nanofibers which have the requisite mechanical properties for use in tissue engineering. However, many factors can influence the formation and collection of fibers, including experimental variables such as the parameters of the solution of the electrospun slurry. In this study, we assessed the influence of the polymer concentration, glass content and glass hydrolysis level on the morphology and thickness of fibers produced by electrospinning for a PCL-(Si-Ca-P2 ) bioactive ormoglass-organically modified glass-blend. Based on previous assays, this combination of materials shows good angiogenic and osteogenic properties, which gives it great potential for use in tissue engineering. The results of our study showed that blend preparation directly affected the features of the resulting fibers, and when the parameters of the blend are precisely controlled, fibers with a regular diameter could be produced fairly easily when 2,2,2-trifluoroethanol was used as a solvent instead of tetrahydrofuran. The diameter of the homogeneous fibers ranged from 360 to 620 nm depending on the experimental conditions used. This demonstrates that experimental optimization of the electrospinning process is crucial in order to obtain a deposit of hybrid nanofibers with a regular shape.
Optimization of chemical displacement deposition of copper on porous silicon.
Bandarenka, Hanna; Redko, Sergey; Nenzi, Paolo; Balucani, Marco; Bondarenko, Vitaly
2012-11-01
Copper (II) sulfate was used as a source of copper to achieve uniform distribution of Cu particles deposited on porous silicon. Layers of the porous silicon were formed by electrochemical anodization of Si wafers in a mixture of HF, C3H7OH and deionized water. The well-known chemical displacement technique was modified to grow the copper particles of specific sizes. SEM and XRD analysis revealed that the outer surface of the porous silicon was covered with copper particles of the crystal orientation inherited from the planes of porous silicon skeleton. The copper crystals were found to have the cubic face centering elementary cell. In addition, the traces of Cu2O cubic primitive crystalline phases were identified. The dimensions of Cu particles were determined by the Feret's analysis of the SEM images. The sizes of the particles varied widely from a few to hundreds of nanometers. A phenomenological model of copper deposition was proposed.
Multivariable norm optimal and parameter optimal iterative learning control: a unified formulation
NASA Astrophysics Data System (ADS)
Owens, D. H.
2012-08-01
This article investigates the two paradigms of norm optimal iterative learning control (NOILC) and parameter optimal iterative learning control (POILC) for multivariable (MIMO) ℓ-input, m-output linear discrete-time systems. The main result is a proof that, despite their algebraic and conceptual differences, they can be unified using linear quadratic multi-parameter optimisation techniques. In particular, whilst POILC has been naturally regarded as an approximation to NOILC, it is shown that the NOILC control law can be generated from a suitable choice of control law parameterisation and objective function in a multi-parameter MIMO POILC problem. The form of this equivalence is used to propose a new general approach to the construction of POILC problems for MIMO systems that approximates the solution of a given NOILC problem. An infinite number of such approximations exist. This great diversity is illustrated by the derivation of new convergent algorithms based on time interval and gradient partition that extend previously published work.
Analytically optimal parameters of dynamic vibration absorber with negative stiffness
NASA Astrophysics Data System (ADS)
Shen, Yongjun; Peng, Haibo; Li, Xianghong; Yang, Shaopu
2017-02-01
In this paper the optimal parameters of a dynamic vibration absorber (DVA) with negative stiffness is analytically studied. The analytical solution is obtained by Laplace transform method when the primary system is subjected to harmonic excitation. The research shows there are still two fixed points independent of the absorber damping in the amplitude-frequency curve of the primary system when the system contains negative stiffness. Then the optimum frequency ratio and optimum damping ratio are respectively obtained based on the fixed-point theory. A new strategy is proposed to obtain the optimum negative stiffness ratio and make the system remain stable at the same time. At last the control performance of the presented DVA is compared with those of three existing typical DVAs, which were presented by Den Hartog, Ren and Sims respectively. The comparison results in harmonic and random excitation show that the presented DVA in this paper could not only reduce the peak value of the amplitude-frequency curve of the primary system significantly, but also broaden the efficient frequency range of vibration mitigation.
Optimal parameters of monolithic high-index contrast grating VCSELs
NASA Astrophysics Data System (ADS)
Marciniak, Magdalena; Gebski, Marcin; Dems, Maciej; Czyszanowski, Tomasz
2016-04-01
Monolithic High refractive index Contrast Grating (MHCG) allows several-fold size reduction of epitaxial structure of VCSEL and facilitates VCSEL fabrication in all photonic material systems. MHCGs can be fabricated of material which refractive index is higher than 1.75 without the need of the combination of low and high refractive index materials. MHCGs have a great application potential in optoelectronic devices, especially in phosphide- and nitride-based VCSELs, which suffer from the lack of efficient monolithically integrated DBR mirrors. MHCGs can simplify the construction of VCSELs, reducing their epitaxial design to monolithic wafer with carrier confinement and active region inside and etched stripes on both surfaces in post processing. In this paper we present results of numerical analysis of MHCGs as a high reflective mirrors for broad range of refractive indices that corresponds to plethora of materials typically used in optoelectronics. Our calculations base on a three-dimensional, fully vectorial optical model. We investigate the reflectance of the MHCG mirrors of different design as the function of the refractive index and we show the optimal geometrical parameters of MHCG enabling nearly 100% reflectance and broad reflection stop-band. We show that MHCG can be designed based on most of semiconductors materials and for any incident light wavelength from optical spectrum.
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 EBSD parameters for ultra-fast characterization.
Chen, Y; Hjelen, J; Gireesh, S S; Roven, H J
2012-02-01
Ultra-fast pattern acquisition of electron backscatter diffraction and offline indexing could become a dominant technique over online electron backscatter diffraction to investigate the microstructures of a wide range of materials, especially for in situ experiments or very large scans. However, less attention has been paid to optimize the parameters related to ultra-fast electron backscatter diffraction. The present results show that contamination on a clean and unmounted specimen is not a problem even at step sizes as small as 1 nm at a vacuum degree of 6.1 × 10(-5) Pa. There exists an optimum step size at about 50 data acquisition board units. A new and easy method to calculate the effective spatial resolution is proposed. Effective spatial resolution tends to increase slightly as the probe current increases from 10 to 100 nA. The fraction of indexed points decreases slightly as the frame rate increases from 128 patterns per second (pps) to 835 pps by compensating the probe current at the same ratio. The value 96 × 96 is found to be the optimum pattern resolution to obtain optimum speed and image quality. For a fixed position of electron backscatter diffraction detector, the fraction of indexed points as a function of working distance has a maximum value and drops sharply by shortening the working distance and it decreases slowly with increasing the working distance. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.
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.
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 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)
Stephens, J.; Fierro, A.; Trienekens, D.; Dickens, J.; Neuber, A.
2015-02-01
Utilizing nanosecond high voltage pulses to drive microdischarges (MDs) at repetition rates in the vicinity of 1 MHz previously enabled increased time-averaged power deposition, peak vacuum ultraviolet (VUV) power yield, as well as time-averaged VUV power yield. Here, various pulse widths (30-250 ns), and pulse repetition rates (100 kHz-5 MHz) are utilized, and the resulting VUV yield is reported. It was observed that the use of a 50 ns pulse width, at a repetition rate of 100 kHz, provided 62 W peak VUV power and 310 mW time-averaged VUV power, with a time-averaged VUV generation efficiency of ˜1.1%. Optimization of the driving parameters resulted in 1-2 orders of magnitude increase in peak and time-averaged power when compared to low power, dc-driven MDs.
Optimization of an ionized metal physical vapor deposition reactor
Lu, J.; Kushner, M.J.
1998-12-31
Conventional sputtering for microelectronic fabrication produces poorly collimated neutral atom fluxes. Ion fluxes, however, can be accelerated and collimated by using a conventional dc or rf substrate bias. Hence, magnetron ionized metal physical vapor deposition (IMPVD) can produce highly ionized metal fluxes that can be used to fill high-aspect-ratio vias and trenches in microelectronic devices. Hopwood and Qian have examined design issues in IMPVD systems. In this study, a Design of Experiment (DOE) has been numerically performed for an IMPVD reactor using an inductively coupled plasma and a capacitively biased substrate. Gas pressure, reactor geometry, ICP power, and number of inductive coils are the design variables. Uniformity, magnitude, and ionization fraction of the depositing fluxes are the response variables. The influence of the design variables on the response variables is examined, with the goals of obtaining high uniformity, high magnitude, and high ionization fraction of the depositing metal fluxes. The computational tool used in this study is the two-dimensional Hybrid Plasma Equipment Model (HPEM). The aspect ratio of the reactor (height/radius) ranges from 0.5 to 1.0, the gas pressure ranges from 10 to 40 mTorr, the ICP power ranges from 0.5 to 2.0 kW, and the number of ICP coils ranges from 2 to 6. It was found that: (a) uniformity maximizes at high aspect ratio, low power, and high pressure; (b) flux magnitude maximizes at low aspect ratio, high power, and low pressure; (c) ionization fraction maximizes at high aspect ratio, high power, and high pressure.
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.
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.
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)
Pronin, V. P.; Dolgintsev, D. M.; Pronin, I. P.; Senkevich, S. V.; Kaptelov, E. Yu; Sergienko, A. Yu
2017-07-01
The article presents the effect of technological parameters of RF magnetron sputtering on the concentration of components of thin-film ferroelectric structures based on lead zirconate titanate PZT in the region of the morphotropic phase boundary. It is shown that by changing the distance from the target to the substrate and the pressure of the working gas mixture Ar + O2, it is possible to vary the composition of the deposited thin layers.
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.
Determination of the optimal mesh parameters for Iguassu centrifuge flow and separation calculations
NASA Astrophysics Data System (ADS)
Romanihin, S. M.; Tronin, I. V.
2016-09-01
We present the method and the results of the determination for optimal computational mesh parameters for axisymmetric modeling of flow and separation in the Iguasu gas centrifuge. The aim of this work was to determine the mesh parameters which provide relatively low computational cost whithout loss of accuracy. We use direct search optimization algorithm to calculate optimal mesh parameters. Obtained parameters were tested by the calculation of the optimal working regime of the Iguasu GC. Separative power calculated using the optimal mesh parameters differs less than 0.5% from the result obtained on the detailed mesh. Presented method can be used to determine optimal mesh parameters of the Iguasu GC with different rotor speeds.
Baudet, E; Sergent, M; Němec, P; Cardinaud, C; Rinnert, E; Michel, K; Jouany, L; Bureau, B; Nazabal, V
2017-06-14
The development of the optical bio-chemical sensing technology is an extremely important scientific and technological issue for diagnosis and monitoring of diseases, control of industrial processes, environmental detection of air and water pollutants. Owing to their distinctive features, chalcogenide amorphous thin films represent a keystone in the manufacture of middle infrared integrated optical devices for a sensitive detection of biological or environmental variations. Since the chalcogenide thin films characteristics, i.e. stoichiometric conformity, structure, roughness or optical properties can be affected by the growth process, the choice and control of the deposition method is crucial. An approach based on the experimental design is undoubtedly a way to be explored allowing fast optimization of chalcogenide film deposition by means of radio frequency sputtering process. Argon (Ar) pressure, working power and deposition time were selected as potentially the most influential factors among all possible. The experimental design analysis confirms the great influence of the Ar pressure on studied responses: chemical composition, refractive index in near-IR (1.55 µm) and middle infrared (6.3 and 7.7 µm), band-gap energy, deposition rate and surface roughness. Depending on the intended application and therefore desired thin film characteristics, mappings of the experimental design meaningfully help to select suitable deposition parameters.
NASA Astrophysics Data System (ADS)
Gelfenbaum, G. R.; La Selle, S.; Sugawara, D.; Jaffe, B. E.
2016-12-01
A challenge in assessing tsunami hazard from sandy coastal deposits is inferring the relative magnitude of past tsunamis from characteristics of the deposits. Empirical data from a laboratory flume experiment and field data from the 2011 Tohoku-oki earthquake and tsunami reveal a high correlation between the volume of onshore sandy tsunami deposits and tsunami magnitude and seafloor deformation. We use Delft3D, a hydrodynamic and sediment transport model, to test how well we can replicate the relationships between onshore tsunami deposit volume and offshore slip from the 2011 Tohoku-oki earthquake and tsunami. An initial water-level condition was obtained from a published tsunami source model based on waveform inversion method (Satake et al., 2013) and was used to derive the hydrodynamic boundary conditions for the sediment transport simulations. The model uses sediment transport formulations and coefficients from van Rijn (2007) and a two-dimensional vertical grid in order to include the affect of suspended-sediment induced density stratification on the vertical turbulent mixing. This test explores how variation in offshore slip affects tsunami deposit volume for a wide range of sediment sources, offshore and onshore slopes, and boundary roughness conditions. Model results show a strong correlation between onshore tsunami deposit volume and adjacent offshore coseismic slip, so long as ample sediment is available in the model to be eroded and transported. These results are consistent with data from the 2011 Tohoku tsunami at sites with sufficiently wide beaches and without shoreline armoring. We will continue to test the model to evaluate sensitivity to parameters that may not be well known for paleotsunamis such as width of fault rupture and roughness of inundated terrain.
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.
NASA Astrophysics Data System (ADS)
Choo, Sung Joong; Lee, Byung-Chul; Lee, Sang-Myung; Park, Jung Ho; Shin, Hyun-Joon
2009-09-01
In this paper, silicon oxynitride layers deposited with different plasma-enhanced chemical vapor deposition (PECVD) conditions were fabricated and optimized, in order to make an interferometric sensor for detecting biochemical reactions. For the optimization of PECVD silicon oxynitride layers, the influence of the N2O/SiH4 gas flow ratio was investigated. RF power in the PEVCD process was also adjusted under the optimized N2O/SiH4 gas flow ratio. The optimized silicon oxynitride layer was deposited with 15 W in chamber under 25/150 sccm of N2O/SiH4 gas flow rates. The clad layer was deposited with 20 W in chamber under 400/150 sccm of N2O/SiH4 gas flow condition. An integrated Mach-Zehnder interferometric biosensor based on optical waveguide technology was fabricated under the optimized PECVD conditions. The adsorption reaction between bovine serum albumin (BSA) and the silicon oxynitride surface was performed and verified with this device.
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.
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.
NASA Astrophysics Data System (ADS)
Zhang, Tao; Wang, Xinchang; Shen, Bin; Sun, Fanghong; Zhang, Zhiming
2013-06-01
The micron well-faceted diamond powders have attracted an increasing attention in the polishing filed, owing to improve the surface finish of components using the powders. In the present work, the hot filament chemical vapor deposition (HFCVD) technique is employed for synthesizing such diamond powders. A great many of micron diamonds are grown simultaneously but independently onto a large-area substrate. First, a novel seeding method, spraying the diamond seeds suspension toward the substrate using a spin coater machine, is proposed, with which the seeds with a controlled density are distributed evenly onto the substrate. Also, the method is more suitable for the fabrication of the micron isolated diamonds, compared with other nucleation initiation methods, such as the scratching pre-treatment and electrical biasing on substrates. Afterwards, a systematic investigation is under taken into the effects of deposition parameters on the basic growth characteristics of CVD micron diamonds, and on the inhibition of films growth. Furthermore, the reactive pressure, substrate temperature, carbon concentration, and growth duration are determined to be 4500 Pa, 850 °C, 1.3-1.4%, 60-90 min, respectively. Eventually, under the preferred deposition conditions, approximately 15 million cube-octahedral crystals with the mean size of 2-3 μm are deposited simultaneously on the 1000 mm2 substrate.
The effects of process parameters on spatter deposition in laser percussion drilling
NASA Astrophysics Data System (ADS)
Low, D. K. Y.; Li, L.; Byrd, P. J.
2000-07-01
This paper reports on the characterisation and analysis of spatter deposition during laser drilling in Nimonic 263 alloy for various laser processing parameters using a fibre-optic delivered 400 W Nd:YAG laser. The principal findings are a large proportion of the spatter (approx. > 70%) was deposited due to the initial laser pulses (before beam breakthrough) required to drill a through-hole. Short pulse widths, low peak powers and high pulse frequencies generated smaller spatter deposition areas. At high pulse frequencies, the spatter distribution/thickness can be altered as a result of laser-ejected material interaction. Focal plane positions between -0.5 and +1.5 mm produced relatively similar spatter areas of about 14 mm2. As a result of the reduction in the material removed per pulse, a longer focal length of 160 mm generated smaller areas of spatter deposition in comparison to a shorter focal length of 120 mm. In addition, a generic relationship between the spatter area and dentrance/ dexit with increasing total laser energy has been established.
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
Parameter optimization for photonic nanojet of dielectric microsphere
NASA Astrophysics Data System (ADS)
Ku, Yu-long; Kuang, Cui-fang; Hao, Xiang; Li, Hai-feng; Liu, Xu
2013-03-01
The characteristics of photonic nanojets are analyzed by changing the parameters, such as the wavelength, refractive index of the surroundings, diameter and refractive index of the microsphere, in this paper. Quadratic functions are used to describe the relation between the above parameters and photonic nanojets' characteristics. Several techniques are proposed to control the photonic nanojets.
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)
Sue-Ann, Goh; Ponnambalam, S. G.
This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.
Bath Parameter Dependence of Chemically-Deposited Copper Selenide Thin Film
NASA Astrophysics Data System (ADS)
Al-Mamun; Islam, A. B. M. O.
In this article, a low cost chemical bath deposition (CBD) technique has been used for the preparation of Cu2-xSe thin films on to glass substrate. Different thin films (0.2-0.6 μm) were prepared by adjusting the bath parameter like concentration of ammonia, deposition time, temperature of the solution, and the ratios of the mixing composition between copper and selenium in the reaction bath. From these studies, it reveals that at low concentration of ammonia or TEA, the terminal thicknesses of the films are less, which gradually increases with the increase of concentrations and then drop down at still higher concentrations. It has been found that complexing the Cu2+ ions with TEA first, and then addition of ammonia yields better results than the reverse process. The film thickness increases with the decrease of value x of Cu2-xSe.
Growth process optimization of ZnO thin film using atomic layer deposition
NASA Astrophysics Data System (ADS)
Weng, Binbin; Wang, Jingyu; Larson, Preston; Liu, Yingtao
2016-12-01
The work reports experimental studies of ZnO thin films grown on Si(100) wafers using a customized thermal atomic layer deposition. The impact of growth parameters including H2O/DiethylZinc (DEZn) dose ratio, background pressure, and temperature are investigated. The imaging results of scanning electron microscopy and atomic force microscopy reveal that the dose ratio is critical to the surface morphology. To achieve high uniformity, the H2O dose amount needs to be at least twice that of DEZn per each cycle. If the background pressure drops below 400 mTorr, a large amount of nanoflower-like ZnO grains would emerge and increase surface roughness significantly. In addition, the growth temperature range between 200 °C and 250 °C is found to be the optimal growth window. And the crystal structures and orientations are also strongly correlated to the temperature as proved by electron back-scattering diffraction and x-ray diffraction results.
Optimization of the Automated Spray Layer-by-Layer Technique for Thin Film Deposition
2010-06-01
SUPPLEMENTARY NOTES 14. ABSTRACT The operational parameters of the automated Spray- LbL technique for thin film deposition have been investigated in...order to-identify their effects on film thickness and roughness. We use the automated Spray- LbL system developed at MIT by the Hammond lab to build...This interdiffusion is investigated using both the conventional dipped LbL and Spray- LbL deposition techniques. Interdiffusion is shown to be dependent
NASA Astrophysics Data System (ADS)
Goyal, Tarun; Sidhu, T. S.; Walia, R. S.
2014-01-01
Most of the existing multi-response optimization approaches focus on the subjective and practical know-how of the process. As a result, some confusion and uncertainty are introduced in the overall decision-making process. In this work, an approach based on a Utility theory and Taguchi quality loss function has been applied to the process parameters for low-pressure cold spray process deposition of copper coatings, for simultaneous optimization of more than one response characteristics. In the present paper, two potential response parameters, i.e., coating thickness and coating density, have been selected. Utility values based on these response parameters have been analyzed for optimization using the Taguchi approach. The selected input parameters of powder feeding arrangement, substrate material, air stagnation pressure, air stagnation temperature, and stand-off distance significantly improve the Utility function (raw data) comprising quality characteristics (coating thickness and coating density). The percentage contribution of the parameters to achieve a higher value of Utility function is substrate material (50.03%), stand-off distance (28.87%), air stagnation pressure (6.41%), powder feeding arrangement (4.68%), and air stagnation temperature (2.64%).
Optimization of multilayer neural network parameters for speaker recognition
NASA Astrophysics Data System (ADS)
Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka
2016-05-01
This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.
Optimization of processing parameters on the controlled growth of c-axis oriented ZnO nanorod arrays
Malek, M. F. Rusop, M.; Mamat, M. H.; Musa, M. Z.; Saurdi, I. Ishak, A.; Alrokayan, Salman A. H. Khan, Haseeb A.
2016-07-06
Optimization of the growth time parameter was conducted to synthesize high-quality c-axis ZnO nanorod arrays. The effects of the parameter on the crystal growth and properties were systematically investigated. Our studies confirmed that the growth time influence the properties of ZnO nanorods where the crystallite size of the structures was increased at higher deposition time. Field emission scanning electron microsope analysis confirmed the morphologies structure of the ZnO nanorods. The ZnO nanostructures prepared under the optimized growth conditions showed an intense XRD peak which reveal a higher c-axis oriented ZnO nanorod arrays thus demonstrating the formation of defect free structure.
Development of customer assistance software for alignment parameter optimization
NASA Astrophysics Data System (ADS)
Kanaya, Yuho; Nakajima, Shinichi
2004-04-01
Wafer alignment plays a significant role in the advancement of microlithography and has been constantly improved to meet various situations. As a result, its configuration is very dynamic and it sometimes requires considerable cost for process optimization. Software has been developed which evaluates the alignment performance in a variety of conditions from the minimal data set. It allows the user to perform off-line optimization, essentially reducing the amount of interruption toward production. This article illustrates the simulation method implemented in the software, OverLay EValuation program (OLEV).
Stability and optimal parameters for continuous feedback chaos control.
Kouomou, Y Chembo; Woafo, P
2002-09-01
We investigate the conditions under which an optimal continuous feedback control can be achieved. Chaotic oscillations in the single-well Duffing model, with either a positive or a negative nonlinear stiffness term, are tuned to their related Ritz approximation. The Floquet theory enables the stability analysis of the control. Critical values of the feedback control coefficient fulfilling the optimization criteria are derived. The influence of the chosen target orbit, of the feedback coefficient, and of the onset time of control on its duration is discussed. The analytic approach is confirmed by numerical simulations.
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.
NASA Technical Reports Server (NTRS)
Rafol, S. B.; Gunapala, S. D.; Bandara, S.; Liu, J. K.; Mumolo, J.; Trinh, J.; Jhabvala, M.
2003-01-01
This paper will report on the characterization of spatially separated four-color QWIP FPA and LWIR QWIP camera. Optimization of operating parameters for each color and the best optimized operating parameters for all four-color operating simultaneously will be discussed.
Determination of dispersion parameters of thermally deposited CdTe thin film
Dhimmar, J. M. Desai, H. N.; Modi, B. P.
2016-05-23
Cadmium Telluride (CdTe) thin film was deposited onto glass substrates under a vacuum of 5 × 10{sup −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.
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
Parameter estimation for chaotic systems based on improved boundary chicken swarm optimization
NASA Astrophysics Data System (ADS)
Chen, Shaolong; Yan, Renhuan
2016-10-01
Estimating unknown parameters for chaotic system is a key problem in the field of chaos control and synchronization. Through constructing an appropriate fitness function, parameter estimation of chaotic system could be converted to a multidimensional parameter optimization problem. In this paper, a new method base on improved boundary chicken swarm optimization (IBCSO) algorithm is proposed for solving the problem of parameter estimation in chaotic system. However, to the best of our knowledge, there is no published research work on chicken swarm optimization for parameters estimation of chaotic system. Computer simulation based on Lorenz system and comparisons with chicken swarm optimization, particle swarm optimization, and genetic algorithm shows the effectiveness and feasibility of the proposed method.
NASA Astrophysics Data System (ADS)
Tahaei, Ali; Horley, Paul; Merlin, Mattia; Torres-Torres, David; Garagnani, Gian Luca; Praga, Rolando; Vázquez, Felipe J. García; Arizmendi-Morquecho, Ana
2017-03-01
This work is dedicated to optimization of carbide particle system in a weld bead deposited by PTAW technique over D2 tool steel with high chromium content. The paper reports partial melting of the original carbide grains of the Ni-based filling powder, and growing of the secondary carbide phase (Cr, Ni)_3W_3C in the form of dendrites with wide branches that enhanced mechanical properties of the weld. The optimization of bead parameters was made with design of experiment methodology complemented by a complex sample characterization including SEM, EDXS, XRD, and nanoindentation measurements. It was shown that the preheat of the substrate to a moderate temperature 523 K (250° C) establishes linear pattern of metal flow in the weld pool, resulting in the most homogeneous distribution of the primary carbides in the microstructure of weld bead.
NASA Astrophysics Data System (ADS)
Tahaei, Ali; Horley, Paul; Merlin, Mattia; Torres-Torres, David; Garagnani, Gian Luca; Praga, Rolando; Vázquez, Felipe J. García; Arizmendi-Morquecho, Ana
2017-01-01
This work is dedicated to optimization of carbide particle system in a weld bead deposited by PTAW technique over D2 tool steel with high chromium content. The paper reports partial melting of the original carbide grains of the Ni-based filling powder, and growing of the secondary carbide phase (Cr, Ni)_3 W_3 C in the form of dendrites with wide branches that enhanced mechanical properties of the weld. The optimization of bead parameters was made with design of experiment methodology complemented by a complex sample characterization including SEM, EDXS, XRD, and nanoindentation measurements. It was shown that the preheat of the substrate to a moderate temperature 523 K (250° C) establishes linear pattern of metal flow in the weld pool, resulting in the most homogeneous distribution of the primary carbides in the microstructure of weld bead.
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.
NASA Astrophysics Data System (ADS)
Kar, Siddhartha; Chakraborty, Sujoy; Dey, Vidyut; Ghosh, Subrata Kumar
2017-10-01
This paper investigates the application of Taguchi method with fuzzy logic for multi objective optimization of roughness parameters in electro discharge coating process of Al-6351 alloy with powder metallurgical compacted SiC/Cu tool. A Taguchi L16 orthogonal array was employed to investigate the roughness parameters by varying tool parameters like composition and compaction load and electro discharge machining parameters like pulse-on time and peak current. Crucial roughness parameters like Centre line average roughness, Average maximum height of the profile and Mean spacing of local peaks of the profile were measured on the coated specimen. The signal to noise ratios were fuzzified to optimize the roughness parameters through a single comprehensive output measure (COM). Best COM obtained with lower values of compaction load, pulse-on time and current and 30:70 (SiC:Cu) composition of tool. Analysis of variance is carried out and a significant COM model is observed with peak current yielding highest contribution followed by pulse-on time, compaction load and composition. The deposited layer is characterised by X-Ray Diffraction analysis which confirmed the presence of tool materials on the work piece surface.
Optimization of Electrical Stimulation Parameters for Cardiac Tissue Engineering
Tandon, Nina; Marsano, Anna; Maidhof, Robert; Wan, Leo; Park, Hyoungshin; Vunjak-Novakovic, Gordana
2010-01-01
In vitro application of pulsatile electrical stimulation to neonatal rat cardiomyocytes cultured on polymer scaffolds has been shown to improve the functional assembly of cells into contractile cardiac tissue constrcuts. However, to date, the conditions of electrical stimulation have not been optimized. We have systematically varied the electrode material, amplitude and frequency of stimulation, to determine the conditions that are optimal for cardiac tissue engineering. Carbon electrodes, exhibiting the highest charge-injection capacity and producing cardiac tissues with the best structural and contractile properties, and were thus used in tissue engineering studies. Cardiac tissues stimulated at 3V/cm amplitude and 3Hz frequency had the highest tissue density, the highest concentrations of cardiac troponin-I and connexin-43, and the best developed contractile behavior. These findings contribute to defining bioreactor design specifications and electrical stimulation regime for cardiac tissue engineering. PMID:21604379
Optimization of electrical stimulation parameters for cardiac tissue engineering.
Tandon, Nina; Marsano, Anna; Maidhof, Robert; Wan, Leo; Park, Hyoungshin; Vunjak-Novakovic, Gordana
2011-06-01
In vitro application of pulsatile electrical stimulation to neonatal rat cardiomyocytes cultured on polymer scaffolds has been shown to improve the functional assembly of cells into contractile engineered cardiac tissues. However, to date, the conditions of electrical stimulation have not been optimized. We have systematically varied the electrode material, amplitude and frequency of stimulation to determine the conditions that are optimal for cardiac tissue engineering. Carbon electrodes, exhibiting the highest charge-injection capacity and producing cardiac tissues with the best structural and contractile properties, were thus used in tissue engineering studies. Engineered cardiac tissues stimulated at 3 V/cm amplitude and 3 Hz frequency had the highest tissue density, the highest concentrations of cardiac troponin-I and connexin-43 and the best-developed contractile behaviour. These findings contribute to defining bioreactor design specifications and electrical stimulation regime for cardiac tissue engineering.
Optimal parameters of gyrotrons with weak electron-wave interaction
NASA Astrophysics Data System (ADS)
Glyavin, M. Yu.; Oparina, Yu. S.; Savilov, A. V.; Sedov, A. S.
2016-09-01
In low-power gyrotrons with weak electron-wave interaction, there is a problem of determining the optimal length of the operating cavity, which is found as a result of a tradeoff between the enhancement of the electron efficiency and the increase in the Ohmic loss share with increasing cavity length. In fact, this is the problem of an optimal ratio between the diffraction and Ohmic Q-factors of the operating gyrotron mode, which determines the share of the radiated rf power lost in the cavity wall. In this paper, this problem is studied on the basis of a universal set of equations, which are appropriate for a wide class of electron oscillators with low efficiencies of the electron-wave interaction.
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.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
NASA Technical Reports Server (NTRS)
Dhawan, Atam P.
1998-01-01
This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.
NASA 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.
Parameter Space of Atomic Layer Deposition of Ultrathin Oxides on Graphene
2016-01-01
Atomic layer deposition (ALD) of ultrathin aluminum oxide (AlOx) films was systematically studied on supported chemical vapor deposition (CVD) graphene. We show that by extending the precursor residence time, using either a multiple-pulse sequence or a soaking period, ultrathin continuous AlOx films can be achieved directly on graphene using standard H2O and trimethylaluminum (TMA) precursors even at a high deposition temperature of 200 °C, without the use of surfactants or other additional graphene surface modifications. To obtain conformal nucleation, a precursor residence time of >2s is needed, which is not prohibitively long but sufficient to account for the slow adsorption kinetics of the graphene surface. In contrast, a shorter residence time results in heterogeneous nucleation that is preferential to defect/selective sites on the graphene. These findings demonstrate that careful control of the ALD parameter space is imperative in governing the nucleation behavior of AlOx on CVD graphene. We consider our results to have model system character for rational two-dimensional (2D)/non-2D material process integration, relevant also to the interfacing and device integration of the many other emerging 2D materials. PMID:27723305
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.
Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende
2014-01-01
Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.
Optimization of mean-shift scale parameters on the EGEE grid.
Li, Ting; Camarasu-Pop, Sorina; Glatard, Tristan; Grenier, Thomas; Benoit-Cattin, Hugues
2010-01-01
This paper studies the optimization of Mean-Shift (MS) image filtering scale parameters. A parameter sweep experiment representing 164 days of CPU is performed on the EGEE grid. The mathematical foundations of Mean-Shift and the grid environment used for the deployment are described in details. The experiments and results are then discussed highlighting the efficiency of gradient ascent algorithm for MS parameters optimization and a number of grid observations related to data transfers, reliability, task scheduling, CPU time and usability.
Structural studies of ZnO nanostructures by varying the deposition parameters
NASA Astrophysics Data System (ADS)
Yunus, S. H. A.; Sahdan, M. Z.; Ichimura, M.; Supee, A.; Rahim, S.
2017-01-01
The effect of Zinc Oxide (ZnO) thin film on the growth of ZnO nanorods (NRs) was investigated. The structures of ZnO NRs were synthesized by chemical bath deposition (CBD) method in aqueous solution of N2O6Zn.6H2O and C6H12N4 at 90°C of deposition temperature. One of the ZnO NRs samples was deposited on a ZnO seed layer coated on a glass substrate to investigate the properties of ZnO NRs without receiving effect of other materials. Next, for diode application, the ZnO NRs was deposited on tin monosulfide (SnS) coated on indium-tin-oxide (ITO) coated glass substrate (SnS/ITO). The next, the ZnO structural properties were studied from surface morphology, X-ray diffractometer (XRD) spectra, and chemical composition by using field emission scanning electron microscope (FESEM), XRD and energy dispersive X-ray Spectroscopy (EDX). The growth of ZnO NRs on ZnO seed layer was investigated by ZnO seed layer condition while the growth of ZnO NRs on SnS/ITO was investigated by deposition time and deposition temperature parameters. From FESEM images, aligned ZnO NRs were obtained, and the diameters of ZnO NRs were 0.024-3.94 µm. The SnS thin film was affected by the diameter of ZnO NRs which are the ZnO NRs grow on SnS thin films has a larger diameter compared to ZnO NRs grow on ZnO seed layer. Besides that, all of ZnO peaks observed from XRD corresponding to the wurzite structure and preferentially oriented along the c-axis. In addition, EDX shows a high composition of zinc (Zn) and oxygen (O) signals, which indicated that the NRs are indeed made up of Zn and O.
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.
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.
Wilbrandt, Steffen; Stenzel, Olaf; Kaiser, Norbert
2010-09-13
A new all-oxide design for broadband antireflection coatings with significantly reduced impact of deposition errors to the final reflectance is presented. Computational manufacturing including re-optimization during deposition has been used in the design work to account for maximum insensibility of the design with respect to deposition errors typical for plasma ion assisted deposition PIAD. Repeated deposition runs with the deducted monitoring and re-optimization strategy verify the validity of the simulations and the stability of the derived design solution.
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.
Process parameters optimization in ion exchange 238Pu aqueous processing
NASA Astrophysics Data System (ADS)
Pansoy-Hjelvik, M. E.; Nixon, J.; Laurinat, J.; Brock, J.; Silver, G.; Reimus, M.; Ramsey, K. B.
2000-07-01
This paper describes bench-scale efforts (5-7 grams of 238Pu) to optimize the ion exchange process for 234U separation with minimal 238Pu losses to the effluent and wash liquids. The bench-scale experiments also determine the methodology to be used for the full-scale process: 5 kg238Pu annual throughput. Heat transfer calculations used to determine the thermal gradients expected during ion exchange processing are also described. The calculations were performed in collaboration with Westinghouse Savannah River Technology Center (WSRTC) and provide information for the design of the full-scale ion exchange equipment.
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.
Optimizing the Yb:YAG thin disc laser design parameters
NASA Astrophysics Data System (ADS)
Javadi-Dashcasan, M.; Hajiesmaeilbaigi, F.; Razzaghi, H.; Mahdizadeh, M.; Moghadam, M.
2008-09-01
Based on quasi-three-level system, a numerical model of continuous wave thin disc laser is proposed. The fluorescence concentration quenching (FCQ), refractive index depending concentration effects and temperature distribution in the gain medium have been taken into account in the model. The first and second phenomena are not included in previously models. The model is used to determine optimum design parameters and to calculate the influence of various parameters like temperature, number of pump beam passes, active ions concentration and the crystal thickness on the operational efficiency of the laser. This model shows that for higher doping concentrations (>15%) the optical efficiency is decreased due to fluorescence concentration quenching. Our results are excellently in agreement with experimental results.
Optimal estimation of parameters of an entangled quantum state
NASA Astrophysics Data System (ADS)
Virzì, S.; Avella, A.; Piacentini, F.; Gramegna, M.; Brida, G.; Degiovanni, I. P.; Genovese, M.
2017-05-01
Two-photon entangled quantum states are a fundamental tool for quantum information and quantum cryptography. A complete description of a generic quantum state is provided by its density matrix: the technique allowing experimental reconstruction of the density matrix is called quantum state tomography. Entangled states density matrix reconstruction requires a large number of measurements on many identical copies of the quantum state. An alternative way of certifying the amount of entanglement in two-photon states is represented by the estimation of specific parameters, e.g., negativity and concurrence. If we have a priori partial knowledge of our state, it’s possible to develop several estimators for these parameters that require lower amount of measurements with respect to full density matrix reconstruction. The aim of this work is to introduce and test different estimators for negativity and concurrence for a specific class of two-photon states.
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.
Optimal Regulation of Structural Systems with Uncertain Parameters.
1981-02-02
been addressed, in part, by Statistical Energy Analysis . Moti- vated by a concern with high frequency vibration and acoustical- structural...Parameter Systems," AFOSR-TR-79-0753 (May, 1979). 25. R. H. Lyon, Statistical Energy Analysis of Dynamical Systems: Theory and Applications, (M.I.T...Press, Cambridge, Mass., 1975). 26. E. E. Ungar, " Statistical Energy Analysis of Vibrating Systems," Trans. ASME, J. Eng. Ind. 89, 626 (1967). 139 27
Towards optimal cosmological parameter recovery from compressed bispectrum statistics
NASA Astrophysics Data System (ADS)
Byun, Joyce; Eggemeier, Alexander; Regan, Donough; Seery, David; Smith, Robert E.
2017-10-01
Over the next decade, improvements in cosmological parameter constraints will be driven by surveys of a large-scale structure in the Universe. The information they contain can be measured by suitably chosen correlation functions, and the non-linearity of structure formation implies that significant information will be carried by the 3-point function or higher correlators. Extracting this information is extremely challenging, requiring accurate modelling and significant computational resources to estimate the covariance matrix describing correlation between different Fourier configurations. We investigate whether it is possible to reduce this matrix without significant loss of information by using a proxy that aggregates the bispectrum over a subset of configurations. Specifically, we study constraints on ΛCDM parameters from a future galaxy survey combining the power spectrum with (a) the integrated bispectrum, (b) the line correlation function and (c) the modal decomposition of the bispectrum. We include a simple estimate for the degradation of the bispectrum with shot noise. Our results demonstrate that the modal bispectrum has comparable performance to the Fourier bispectrum, even using considerably fewer modes than Fourier configurations. The line correlation function has good performance, but is less effective. The integrated bispectrum is comparatively insensitive to the background cosmology. Addition of bispectrum data can improve constraints on bias parameters and σ8 by a factor between 3 and 5 compared to power spectrum measurements alone. For other parameters, improvements of up to ∼20 per cent are possible. Finally, we use a range of theoretical models to explore the sophistication required to produce realistic predictions for each proxy.
Optimizing Hyperspectral Imagery Anomaly Detection through Robust Parameter Design
2011-10-01
THROUGH ROBUST PARAMETER DESIGN DISSERTATION Presented to the Faculty Graduate School of Engineering and Management Air Force Institute of Technology...Air University Air Education and Training Command in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Francis M. Mindrup...Graduate School of Engineering and Management For my loving wife, daughter and sons iv AFIT/DS/ENS/11-04 Abstract Advances in sensor technology
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.
Optimization of technological parameters for preparation of lycopene microcapsules.
Guo, Hui; Huang, Ying; Qian, Jun-Qing; Gong, Qiu-Yi; Tang, Ying
2014-07-01
Lycopene belongs to the carotenoid family with high degree of unsaturation and all-trans form. Lycopene is easy to isomerize and auto oxide by heat, light, oxygen and different food matrices. With an increasing understanding of the health benefit of lycopene, to enhance stability and bioavailability of lycopene, ultrasonic emulsification was used to prepare lycopene microcapsules in this article. The results optimized by response surface methodology (RSM) for microcapsules consisted of four major steps: (1) 0.54 g glycerin monostearate was fully dissolved in 5 mL ethyl acetate and then added 0.02 g lycopene to form an organic phase, 100.7 mL distilled water which dissolved 0.61 g synperonic pe(R)/F68 as the aqueous phase; (2) the organic phase was pulled into the aqueous phase under stirring at 60 °C water bath for 5 min; (3) the mixture was then ultrasonic homogenized at 380 W for 20 min to form a homogenous emulsion; (4) the resulting emulsion was rotary evaporated at 50 °C water bath for 10 min under a pressure of 20 MPa. Encapsulation efficiency (EE) of lycopene microcapsules under the optimized conditions approached to 64.4%.
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan
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)
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Optimization of sampling parameters for standardized exhaled breath sampling.
Doran, Sophie; Romano, Andrea; Hanna, George B
2017-09-05
The lack of standardization of breath sampling is a major contributing factor to the poor repeatability of results and hence represents a barrier to the adoption of breath tests in clinical practice. On-line and bag breath sampling have advantages but do not suit multicentre clinical studies whereas storage and robust transport are essential for the conduct of wide-scale studies. Several devices have been developed to control sampling parameters and to concentrate volatile organic compounds (VOCs) onto thermal desorption (TD) tubes and subsequently transport those tubes for laboratory analysis. We conducted three experiments to investigate (i) the fraction of breath sampled (whole vs. lower expiratory exhaled breath); (ii) breath sample volume (125, 250, 500 and 1000ml) and (iii) breath sample flow rate (400, 200, 100 and 50 ml/min). The target VOCs were acetone and potential volatile biomarkers for oesophago-gastric cancer belonging to the aldehyde, fatty acids and phenol chemical classes. We also examined the collection execution time and the impact of environmental contamination. The experiments showed that the use of exhaled breath-sampling devices requires the selection of optimum sampling parameters. The increase in sample volume has improved the levels of VOCs detected. However, the influence of the fraction of exhaled breath and the flow rate depends on the target VOCs measured. The concentration of potential volatile biomarkers for oesophago-gastric cancer was not significantly different between the whole and lower airway exhaled breath. While the recovery of phenols and acetone from TD tubes was lower when breath sampling was performed at a higher flow rate, other VOCs were not affected. A dedicated 'clean air supply' overcomes the contamination from ambient air, but the breath collection device itself can be a source of contaminants. In clinical studies using VOCs to diagnose gastro-oesophageal cancer, the optimum parameters are 500mls sample
Optimization of design parameters of low-energy buildings
NASA Astrophysics Data System (ADS)
Vala, Jiří; Jarošová, Petra
2017-07-01
Evaluation of temperature development and related consumption of energy required for heating, air-conditioning, etc. in low-energy buildings requires the proper physical analysis, covering heat conduction, convection and radiation, including beam and diffusive components of solar radiation, on all building parts and interfaces. The system approach and the Fourier multiplicative decomposition together with the finite element technique offers the possibility of inexpensive and robust numerical and computational analysis of corresponding direct problems, as well as of the optimization ones with several design variables, using the Nelder-Mead simplex method. The practical example demonstrates the correlation between such numerical simulations and the time series of measurements of energy consumption on a small family house in Ostrov u Macochy (35 km northern from Brno).
NASA Astrophysics Data System (ADS)
Kumar, S.; Singh, A.; Dhar, A.
2017-08-01
The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.
Local E-optimality Conditions for Trajectory Design to Estimate Parameters in Nonlinear Systems
Wilson, Andrew D.; Murphey, Todd D.
2014-01-01
This paper develops an optimization method to synthesize trajectories for use in the identification of system parameters. Using widely studied techniques to compute Fisher information based on observations of nonlinear dynamical systems, an infinite-dimensional, projection-based optimization algorithm is formulated to optimize the system trajectory using eigenvalues of the Fisher information matrix as the cost metric. An example of a cart-pendulum simulation demonstrates a significant increase in the Fisher information using the optimized trajectory with decreased parameter variances shown through Monte-Carlo tests and computation of the Cramer-Rao lower bound. PMID:25346569
Key parameter optimization and analysis of stochastic seismic inversion
NASA Astrophysics Data System (ADS)
Huang, Zhe-Yuan; Gan, Li-Deng; Dai, Xiao-Feng; Li, Ling-Gao; Wang, Jun
2012-03-01
Stochastic seismic inversion is the combination of geostatistics and seismic inversion technology which integrates information from seismic records, well logs, and geostatistics into a posterior probability density function (PDF) of subsurface models. The Markov chain Monte Carlo (MCMC) method is used to sample the posterior PDF and the subsurface model characteristics can be inferred by analyzing a set of the posterior PDF samples. In this paper, we first introduce the stochastic seismic inversion theory, discuss and analyze the four key parameters: seismic data signal-to-noise ratio (S/N), variogram, the posterior PDF sample number, and well density, and propose the optimum selection of these parameters. The analysis results show that seismic data S/N adjusts the compromise between the influence of the seismic data and geostatistics on the inversion results, the variogram controls the smoothness of the inversion results, the posterior PDF sample number determines the reliability of the statistical characteristics derived from the samples, and well density influences the inversion uncertainty. Finally, the comparison between the stochastic seismic inversion and the deterministic model based seismic inversion indicates that the stochastic seismic inversion can provide more reliable information of the subsurface character.
Optimization of process parameters in explosive cladding of mild steel and aluminum
NASA Astrophysics Data System (ADS)
Raghukandan, K.; Hokamoto, K.; Manikandan, P.
2004-04-01
Explosive cladding is best known for its capability to join a wide variety of both similar and dissimilar combinations of metals that cannot be joined by other conventional metal joining techniques. An attempt has been made to optimize, the tensile and shear strengths of an explosive clad interface using fuzzy logic and genetic algorithm. The parameters considered for this study include flyer plate thickness, loading ratio, angle of inclination, and stand off distance. The experimental data was trained and simulated using fuzzy logic and the optimization of process parameters was performed using genetic algorithm. The optimized process parameters were validated using experimental results.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.
2017-03-01
Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.
Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis
NASA Astrophysics Data System (ADS)
Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo
2017-08-01
This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.
Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis
NASA Astrophysics Data System (ADS)
Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo
2016-11-01
This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.
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
Optimization of radar imaging system parameters for geological analysis
NASA Technical Reports Server (NTRS)
Waite, W. P.; Macdonald, H. C.; Kaupp, V. H.
1981-01-01
The use of radar image simulation to model terrain variation and determine optimum sensor parameters for geological analysis is described. Optimum incidence angle is determined by the simulation, which evaluates separately the discrimination of surface features possible due to terrain geometry and that due to terrain scattering. Depending on the relative relief, slope, and scattering cross section, optimum incidence angle may vary from 20 to 80 degrees. Large incident angle imagery (more than 60 deg) is best for the widest range of geological applications, but in many cases these large angles cannot be achieved by satellite systems. Low relief regions require low incidence angles (less than 30 deg), so a satellite system serving a broad range of applications should have at least two selectable angles of incidence.
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).
NASA Astrophysics Data System (ADS)
Slawig, Thomas; Rückelt, Johannes; Sauerland, Volkmar; Srivastav, Anand; Ward, Ben
2010-05-01
Methods and results for parameter optimization and uncertainty analysis for a one dimensional marine biogeochemical model of NPZD type developed by Schartau and Oschlies are presented. The model simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean data. For the optimization, we use two strategies: At first, a genetic algorithm combined with a local search method. Secondly, a gradient-based quasi-newton SQP method to identify parameters and fit them to given observational data. For the SQP method, we use gradients generated by a source transformation tool for Automatic/Algorithmic Differentiation (AD). The algorithm is designed in a flexible way: The local method is a freely available code that can be replaced by other methods offering the same features, e.g. treatment of box constarints. Both optimization methods are parallized and can be viewed as instances of a hybrid, mixed evolutionary and deterministic optimization algorithm. We compare the performance of both approaches. Moreover, we present an uncertainty analysis of the optimized parameters with respect to Gaussian perturbed observations. Here, an ensemble of perturbed observations is taken as target or desired state for the optimization. After the optimization is applied, the distribution of the optimal parameters shows the dependenc of the parameters with respect to uncertainty in the observations.
McCloy, John S.; Wolf, Walter; Wimmer, Erich; Zelinski, Brian
2013-01-09
The lattice parameter of cubic chemical vapor deposited (CVD) ZnS with measured oxygen concentrations < 0.6 at.% and hydrogen impurities of < 0.015 at.% have been measured and found to vary between -0.10% and +0.09% relative to the reference lattice parameter (5.4093 Å) of oxygen-free cubic ZnS as reported in the literature. Defects other than substitutional O must be invoked to explain these observed volume changes. The structure and thermodynamic stability of a wide range of native and impurity induced defects in ZnS have been determined by Ab initio calculations. Lattice contraction is caused by S-vacancies, substitutional O on S sites, Zn vacancies, H in S vacancies, peroxy defects, and dissociated water in S-vacancies. The lattice is expanded by interstitial H, H in Zn vacancies, dihydroxy defects, interstitial oxygen, Zn and [ZnHn] complexes (n=1,…,4), interstitial Zn, and S2 dumbbells. Oxygen, though present, likely forms substitutional defects for sulfur resulting in lattice contraction rather than as interstitial oxygen resulting in lattice expansion. It is concluded based on measurement and calculations that excess zinc atoms either at anti-sites (i.e. Zn atoms on S-sites) or possibly as interstitial Zn are responsible for the relative increase of the lattice parameter of commercially produced CVD ZnS.
Parameter spaces and design optimization of thermoacoustic refrigerators
Wetzel, M.; Herman, C.
1996-12-31
In the last two decades thermoacoustic refrigerators were developed in research laboratories with the goal to understand the basic physics and thermodynamics of thermoacoustic heat pumping. These research efforts led to a good understanding of this new environmentally safe refrigeration technology that employs acoustic power to pump heat. Consequently the next step is to improve and optimize the performance of thermoacoustic refrigerators and seek commercial applications. For this purpose, the need for fast and simple engineering estimates arises. By implementing the simplified linear model of thermoacoustic refrigerators--the short stack boundary layer approximation--such design estimates were derived and presented in this paper in the form of a design algorithm. Calculations obtained with this algorithm predict values for the Coefficient Of Performance (COP) of the order of 5 to 6. These values cannot be achieved at this time because of loss mechanisms in key parts of the thermoacoustic refrigerator, which are not quite understood yet. Nevertheless, these values are encouraging and gaining a better understanding of these loss mechanisms will be a big step towards the commercial market for this new environmentally safe refrigeration technology.
Optimal Parameter Determination for Tritiated Water Storage in Polyacrylic Networks
Postolache, C.; Matei, Lidia; Georgescu, Rodica; Ionita, Gh.
2005-07-15
Due to the remarkable capacity of water retaining, croslinked polyacrylic acids (PAA) represent an interesting alternative for tritiated water trapping. The study was developed on radiolytical processes in PAA:HTO systems derivated from irradiation of polymeric network by disintegration of tritium atoms from HTO. The aim of these studies is the identification of polymeric structures and optimal storage conditions.Sol and gel fractions were determinated by radiometrical methods using PAA labeled with 14-C at carboxylic groups and T at main chains of the polymer. Simulation of radiolytical processes was realized using {gamma} radiation field emitted by a irradiation source of 60-Co which ensures a maximum of absorbed dose rate of 3 kGy/h. Self-radiolytical effects were investigated using labeled PAA in HTO with great radioactive concentration (37-185 GBq/mL). The experiment suggests as optimum for HTO storage as tritium liquid wastes a 1:30 PAA:HTO swelling degree at 18.5-37 MBqL. HTO radioactive concentration.RES studies of radiolytical processes were also realized on dry polyacrylic acid (PAA) and polyacrylic based hydrogels irradiated and determined at 77 K. In the study we observed the effect of swelling capacity of hydrogel o the formation of free radicals.
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.
To denoise or deblur: parameter optimization for imaging systems
NASA Astrophysics Data System (ADS)
Mitra, Kaushik; Cossairt, Oliver; Veeraraghavan, Ashok
2014-03-01
In recent years smartphone cameras have improved a lot but they still produce very noisy images in low light conditions. This is mainly because of their small sensor size. Image quality can be improved by increasing the aperture size and/or exposure time however this make them susceptible to defocus and/or motion blurs. In this paper, we analyze the trade-off between denoising and deblurring as a function of the illumination level. For this purpose we utilize a recently introduced framework for analysis of computational imaging systems that takes into account the effect of (1) optical multiplexing, (2) noise characteristics of the sensor, and (3) the reconstruction algorithm, which typically uses image priors. Following this framework, we model the image prior using Gaussian Mixture Model (GMM), which allows us to analytically compute the Minimum Mean Squared Error (MMSE). We analyze the specific problem of motion and defocus deblurring, showing how to find the optimal exposure time and aperture setting as a function of illumination level. This framework gives us the machinery to answer an open question in computational imaging: To deblur or denoise?.
Oliver, J.B.; Talbot, D.
2003-05-06
Multilayer coatings on large substrates with increasingly complex spectral requirements are essential for a number of optical systems, placing stringent requirements on the error tolerances of individual layers. Each layer must be deposited quite uniformly over the entire substrate surface since any nonuniformity will add to the layer-thickness error level achieved. A deposition system containing a planetary rotation system with stationary uniformity masking is modeled, with refinements of the planetary gearing, source placement, and uniformity mask shape being utilized to achieve an optimal configuration. The impact of improper planetary gearing is demonstrated theoretically, as well as experimentally, providing more comprehensive requirements than simply avoiding repetition of previous paths through the vapor plume, until all possible combinations of gear teeth have been used. Deposition efficiency and the impact on the uniformity achieved are used to validate improved source placement.
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
NASA Astrophysics Data System (ADS)
Li, Sui-xian; Chen, Haiyang; Sun, Min; Cheng, Zaijun
2009-11-01
Aimed at improving the calculation accuracy when calculating the energy deposition of electrons traveling in solids, a method we call optimal subdivision number searching algorithm is proposed. When treating the energy deposition of electrons traveling in solids, large calculation errors are found, we are conscious of that it is the result of dividing and summing when calculating the integral. Based on the results of former research, we propose a further subdividing and summing method. For β particles with the energy in the entire spectrum span, the energy data is set only to be the integral multiple of keV, and the subdivision number is set to be from 1 to 30, then the energy deposition calculation error collections are obtained. Searching for the minimum error in the collections, we can obtain the corresponding energy and subdivision number pairs, as well as the optimal subdivision number. The method is carried out in four kinds of solid materials, Al, Si, Ni and Au to calculate energy deposition. The result shows that the calculation error is reduced by one order with the improved algorithm.
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'.
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 Astrophysics Data System (ADS)
Jackson, E.; Aga, R.; Steigerwald, A.; Ueda, A.; Pan, Z.; Collins, W. E.; Mu, R.
2008-03-01
Telluride (CdTe) is a front-runner photovoltaic (PV) material because it has already attained efficiencies above 16%. The fabrication of CdTe nanoparticles has aroused considerable interest because of their potential application as active layer in organic/inorganic hybrid solar cells. They can also be used for sensitisation of wide band gap semiconductors. In this work, we explore pulsed electron beam deposition (PED) technique to fabricate CdTe nanoparticles. Two ablation parameters, namely background gas pressure and electron energy were varied to investigate their effects on the nanoparticle formation. AFM and optical transmission measurements indicate that we have fabricated CdTe nanocrystalline films exhibiting quantum confinement effect. These films contain scattered nanoparticles with diameters varying from 40 nm to 500 nm, which contribute to the optical absorption near the bulk bandgap energy. However, increasing the background pressure to 19 mTorr improves the nanocrystalline film uniformity.
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.
Parameter Optimization for Mould and Die Recovering Using Laser Cladding
NASA Astrophysics Data System (ADS)
Tabernero, I.; Lamikiz, A.; Ukar, E.; Arregi, B.; Figueras, J.; Soriano, C.
2009-11-01
In the last years the laser cladding has become an important technology that has been studied by several industries as automotive or aeronautical. Therefore, although this technology was used initially for coatings, actually it is being used for repairing or even direct manufacturing of high added value parts. In this paper, the application of laser cladding for repairing a GGG70L stamping die is presented. The first step is to present the methodology used to obtain the optimum conditions for AISI 316L stainless steel clads on structural steel (DIN C45). The next section shows a deeper study about the capacity of the process to fill standard geometries on DIN C45 and DIN 1.2379. Finally, a nodular cast iron GGG70L stamping die is repaired using laser cladding process. The parameters and strategy used for the repairing have been obtained on previous sections. Furthermore, in the final section a powder concentration model is presented as the first step to create a complete model that simulate the three stages of laser cladding: interaction between powder and laser beam, creation of melt pool and generation of clad geometry.
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
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 (R a ). 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, v 3-f 2-d 3. 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, v 1-f 1-d 3. 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.
NASA Astrophysics Data System (ADS)
Hannachi, Amira; Maghraoui-Meherzi, Hager
2017-03-01
Manganese sulfide thin films have been deposited on glass slides by chemical bath deposition (CBD) method. The effects of preparative parameters such as deposition time, bath temperature, concentration of precursors, multi-layer deposition, different source of manganese, different complexing agent and thermal annealing on structural and morphological film properties have been investigated. The prepared thin films have been characterized using the X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). It exhibit the metastable forms of MnS, the hexagonal γ-MnS wurtzite phase with preferential orientation in the (002) plane or the cubic β-MnS zinc blende with preferential orientation in the (200) plane. Microstructural studies revealed the formation of MnS crystals with different morphologies, such as hexagons, spheres, cubes or flowers like.
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
Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal
2016-01-01
Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019
Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal
2016-11-04
Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.
Plasma parameters of pulsed-dc discharges in methane used to deposit diamondlike carbon films
Corbella, C.; Rubio-Roy, M.; Bertran, E.; Andujar, 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 (CH{sub 4}) 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 mus. 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 T{sub e}{sup hot} of over 10 eV and an initial low density n{sub e}{sup hot} which decreased to zero. Cold electrons of temperature T{sub e}{sup cold}approx1 eV represented the majority of each discharge. The density of cold electrons n{sub e}{sup cold} showed a monotonic increase over time within the negative pulse, peaking at almost 7x10{sup 10} cm{sup -3}, corresponding to the cooling of the hot electrons. The plasma potential V{sub p} of approx30 V underwent a smooth increase during the pulse and fell at the end of the negative region. Different rates of CH{sub 4} conversion were calculated from the DLC deposition rate. These were explained in terms of the specific activation energy E{sub a} and the conversion factor x{sub dep} associated with the plasma processes. The work deepens our understanding of the advantages of using pulsed power supplies
Ha, Kil-Chan; Kye, Seung-Hyeok
2011-08-15
In a recent paper [D. Chruscinski and F. A. Wudarski, Open Sys. Information Dyn. (unpublished)], it was conjectured that the entanglement witnesses arising from some generalized Choi maps are optimal. We show that this conjecture is true. Furthermore, we show that they provide a one-parameter family of indecomposable optimal entanglement witnesses.
A combinatorial optimization scheme for parameter structure identification in ground water modeling.
Tsai, Frank T C; Sun, Ne-Zheng; Yeh, William W G
2003-01-01
This research develops a methodology for parameter structure identification in ground water modeling. For a given set of observations, parameter structure identification seeks to identify the parameter dimension, its corresponding parameter pattern and values. Voronoi tessellation is used to parameterize the unknown distributed parameter into a number of zones. Accordingly, the parameter structure identification problem is equivalent to finding the number and locations as well as the values of the basis points associated with the Voronoi tessellation. A genetic algorithm (GA) is allied with a grid search method and a quasi-Newton algorithm to solve the inverse problem. GA is first used to search for the near-optimal parameter pattern and values. Next, a grid search method and a quasi-Newton algorithm iteratively improve the GA's estimates. Sensitivities of state variables to parameters are calculated by the sensitivity-equation method. MODFLOW and MT3DMS are employed to solve the coupled flow and transport model as well as the derived sensitivity equations. The optimal parameter dimension is determined using criteria based on parameter uncertainty and parameter structure discrimination. Numerical experiments are conducted to demonstrate the proposed methodology, in which the true transmissivity field is characterized by either a continuous distribution or a distribution that can be characterized by zones. We conclude that the optimized transmissivity zones capture the trend and distribution of the true transmissivity field.
Kurzke, J.
1999-01-01
In gas turbine performance simulations often the following question arises: what is the best thermodynamic cycle design point? This is an optimization task which can be attacked in two ways. One can do a series of parameter variations and pick from the resulting graphs the best solution or one can employ numerical optimization algorithms that produce a single cycle that fulfills all constraints. The conventional parameter study builds strongly on the engineering judgment and gives useful information over a range of parameter selections. However, when values for more than a few variables have to be determined while several constraints are existing, then numerical optimization routines can help to find the mathematical optimum faster and more accurately. Sometimes even an outstanding solution is found which was overlooked while doing a preliminary parameter study. For any simulation task a sophisticated graphical user interface is of great benefit. This is especially true for automated numerical optimizations. It is quite helpful to see on the screen of a PC how the variables are changing and which constraints are limiting the design. A quick and clear graphical representation of trade studies is also of great advantage. The paper describes how numerical optimization and parameter studies are implemented in a Windows-based PC program. As an example, the cycle selection of a derivative turbofan engine with a given core shows the merits of numerical optimization. The parameter variation is best suited for presenting the sensitivity of the result in the neighborhood of the optimum cycle design point.
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.
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
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; Kalkhof, Stefan
2010-12-01
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)
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
Nakatsui, Masahiko; Horimoto, Katsuhisa; Okamoto, Masahiro; Tokumoto, Yasuhito; Miyake, Jun
2010-09-13
The investigation of network dynamics is a major issue in systems and synthetic biology. One of the essential steps in a dynamics investigation is the parameter estimation in the model that expresses biological phenomena. Indeed, various techniques for parameter optimization have been devised and implemented in both free and commercial software. While the computational time for parameter estimation has been greatly reduced, due to improvements in calculation algorithms and the advent of high performance computers, the accuracy of parameter estimation has not been addressed. We propose a new approach for parameter optimization by using differential elimination, to estimate kinetic parameter values with a high degree of accuracy. First, we utilize differential elimination, which is an algebraic approach for rewriting a system of differential equations into another equivalent system, to derive the constraints between kinetic parameters from differential equations. Second, we estimate the kinetic parameters introducing these constraints into an objective function, in addition to the error function of the square difference between the measured and estimated data, in the standard parameter optimization method. To evaluate the ability of our method, we performed a simulation study by using the objective function with and without the newly developed constraints: the parameters in two models of linear and non-linear equations, under the assumption that only one molecule in each model can be measured, were estimated by using a genetic algorithm (GA) and particle swarm optimization (PSO). As a result, the introduction of new constraints was dramatically effective: the GA and PSO with new constraints could successfully estimate the kinetic parameters in the simulated models, with a high degree of accuracy, while the conventional GA and PSO methods without them frequently failed. The introduction of new constraints in an objective function by using differential elimination
2010-01-01
Background The investigation of network dynamics is a major issue in systems and synthetic biology. One of the essential steps in a dynamics investigation is the parameter estimation in the model that expresses biological phenomena. Indeed, various techniques for parameter optimization have been devised and implemented in both free and commercial software. While the computational time for parameter estimation has been greatly reduced, due to improvements in calculation algorithms and the advent of high performance computers, the accuracy of parameter estimation has not been addressed. Results We propose a new approach for parameter optimization by using differential elimination, to estimate kinetic parameter values with a high degree of accuracy. First, we utilize differential elimination, which is an algebraic approach for rewriting a system of differential equations into another equivalent system, to derive the constraints between kinetic parameters from differential equations. Second, we estimate the kinetic parameters introducing these constraints into an objective function, in addition to the error function of the square difference between the measured and estimated data, in the standard parameter optimization method. To evaluate the ability of our method, we performed a simulation study by using the objective function with and without the newly developed constraints: the parameters in two models of linear and non-linear equations, under the assumption that only one molecule in each model can be measured, were estimated by using a genetic algorithm (GA) and particle swarm optimization (PSO). As a result, the introduction of new constraints was dramatically effective: the GA and PSO with new constraints could successfully estimate the kinetic parameters in the simulated models, with a high degree of accuracy, while the conventional GA and PSO methods without them frequently failed. Conclusions The introduction of new constraints in an objective function by
NASA Astrophysics Data System (ADS)
Lü, Hui; Yu, Dejie
2014-12-01
An uncertain optimization method for brake squeal reduction of vehicle disc brake system with interval parameters is presented in this paper. In the proposed method, the parameters of frictional coefficient, material properties and the thicknesses of wearing components are treated as uncertain parameters, which are described as interval variables. Attention is focused on the stability analysis of a brake system in squeal, and the stability of brake system is investigated via the complex eigenvalue analysis (CEA) method. The dominant unstable mode is extracted by performing CEA based on a linear finite element (FE) model, and the negative damping ratio corresponding to the dominant unstable mode is selected as the indicator of instability. The response surface method (RSM) is applied to approximate the implicit relationship between the unstable mode and the system parameters. A reliability-based optimization model for improving the stability of the vehicle disc brake system with interval parameters is constructed based on RSM, interval analysis and reliability analysis. The Genetic Algorithm is used to get the optimal values of design parameters from the optimization model. The stability analysis and optimization of a disc brake system are carried out, and the results show that brake squeal propensity can be reduced by using stiffer back plates. The proposed approach can be used to improve the stability of the vehicle disc brake system with uncertain parameters effectively.
Optical Parameters of Spray-Deposited CdS1- y Te y Thin Films
NASA Astrophysics Data System (ADS)
Ikhmayies, Shadia J.
2017-02-01
CdS x Te1- x and CdS1- y Te y solid solutions are usually formed in the interfacial region in CdS/CdTe solar cells during the deposition of the CdTe layer and/or the processing steps of the device. In this work, indium-doped CdS1- y Te y thin films were prepared by first producing CdS:In thin films by the spray pyrolysis technique on glass substrates, then annealing the films in nitrogen atmosphere in the presence of elemental tellurium. The films were characterized by scanning electron microscopy, energy dispersive x-ray spectroscopy, and transmittance measurements. The transmittance was used to deduce the reflectance from which the optical parameters were computed. The extinction coefficient, refractive index, the real and imaginary parts of the dielectric constant, optical conductivity, and energy loss were computed, and their dependence on the composition was investigated. In addition, the dispersion of the refractive index was analyzed by the single oscillator model, and dispersion parameters were investigated.
Optimization of pulsed DC PACVD parameters: Toward reducing wear rate of the DLC films
NASA Astrophysics Data System (ADS)
Ebrahimi, Mansoureh; Mahboubi, Farzad; Naimi-Jamal, M. Reza
2016-12-01
The effect of pulsed direct current (DC) plasma-assisted chemical vapor deposition (PACVD) parameters such as temperature, duty cycle, hydrogen flow, and argon/CH4 flow ratio on the wear behavior and wear durability of the diamond-like carbon (DLC) films was studied by using response surface methodology (RSM). DLC films were deposited on nitrocarburized AISI 4140 steel. Wear rate and wear durability of the DLC films were examined with the pin-on-disk method. Field emission scanning electron microscopy, Raman spectroscopy, and nanoindentation techniques were used for studying wear mechanisms, chemical structure, and hardness of the DLC films. RSM results show that duty cycle is one of the important parameters that affect the wear rate of the DLC samples. The wear rate of the samples deposited with a duty cycle of >75% decreases with an increase in the argon/CH4 ratio. In contrast, for a duty cycle of <65%, the wear rate increases with an increase in the argon/CH4 ratio. The wear durability of the DLC samples increases with an increase in the duty cycle, hydrogen flow, and argon/CH4 flow ratio at the deposition temperature between 85 °C and 110 °C. Oxidation, fatigue, abrasive wear, and graphitization are the wear mechanisms observed on the wear scar of the DLC samples deposited with the optimum deposition conditions.
Learning optimal spatially-dependent regularization parameters in total variation image denoising
NASA Astrophysics Data System (ADS)
Van Chung, Cao; De los Reyes, J. C.; Schönlieb, C. B.
2017-07-01
We consider a bilevel optimization approach in function space for the choice of spatially dependent regularization parameters in TV image denoising models. First- and second-order optimality conditions for the bilevel problem are studied when the spatially-dependent parameter belongs to the Sobolev space {{H}1}≤ft(Ω \\right) . A combined Schwarz domain decomposition-semismooth Newton method is proposed for the solution of the full optimality system and local superlinear convergence of the semismooth Newton method is verified. Exhaustive numerical computations are finally carried out to show the suitability of the approach.
NASA Astrophysics Data System (ADS)
Basavaraj, C. K.; Vishwas, M.
2016-09-01
This paper discusses the process parameters for fused deposition modelling (FDM). Layer thickness, Orientation angle and shell thickness are the process variables considered for studies. Ultimate tensile strength, dimensional accuracy and manufacturing time are the response parameters. For number of experimental runs the taguchi's L9 orthogonal array is used. Taguchis S/N ratio was used to identify a set of process parameters which give good results for respective response characteristics. Effectiveness of each parameter is investigated by using analysis of variance. The material used for the studies of process parameter is Nylon.
NASA Astrophysics Data System (ADS)
Bulbul, Ferhat
2011-02-01
Electroless Ni-B coatings were deposited on AISI 304 stainless steels by electroless deposition method, which was performed for nine different test conditions at various levels of temperature, concentration of NaBH4, concentration of NiCl2, and time, using the Taguchi L9(34) experimental method. The effects of deposition parameters on the crystallographic orientation of electroless Ni-B coatings were investigated using SEM and XRD equipment. SEM analysis revealed that the Ni-B coatings developed six types (pea-like, maize-like, primary nodular, blackberry-like or grapes-like, broccoli-like, and cauliflower-like) of morphological structures depending on the deposition parameters. XRD results also showed that these structures exhibited different levels of amorphous character. The concentration of NaBH4 had the most dominant effect on the morphological and crystallographic development of electroless Ni-B coatings.
Study on feed forward neural network convex optimization for LiFePO4 battery parameters
NASA Astrophysics Data System (ADS)
Liu, Xuepeng; Zhao, Dongmei
2017-08-01
Based on the modern facility agriculture automatic walking equipment LiFePO4 Battery, the parameter identification of LiFePO4 Battery is analyzed. An improved method for the process model of li battery is proposed, and the on-line estimation algorithm is presented. The parameters of the battery are identified using feed forward network neural convex optimization algorithm.
Regmi, Murari; Chisholm, Matthew F; Eres, Gyula
2012-01-01
We present a comprehensive study of the parameter space for single layer graphene growth by chemical vapor deposition on Cu. The temperature is the most widely recognized parameter in single layer graphene growth. We show that the methane-to-hydrogen ratio and the growth pressure also are critical parameters that affect the structural perfection and the cleanliness of graphene. The optimal conditions for suppressing double and multilayer graphene growth occur near 1000 C, 1:20 methane-to-hydrogen ratio, and a total pressure in the range from 0.5 to 1 Torr. Raman mapping of a 40x30 m2 area shows single layer domains with 5-10 m linear dimensions. Atomic resolution imaging of suspended graphene by aberration corrected scanning transmission electron microscopy shows that the cleanest single layer graphene consists of areas of 10-15 nm linear dimensions and smaller patches of residual contamination that was undetected by other characterization methods.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning
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
Optimal Design of Material and Process Parameters in Powder Injection Molding
NASA Astrophysics Data System (ADS)
Ayad, G.; Barriere, T.; Gelin, J. C.; Song, J.; Liu, B.
2007-04-01
The paper is concerned with optimization and parametric identification for the different stages in Powder Injection Molding process that consists first in injection of powder mixture with polymer binder and then to the sintering of the resulting powders part by solid state diffusion. In the first part, one describes an original methodology to optimize the process and geometry parameters in injection stage based on the combination of design of experiments and an adaptive Response Surface Modeling. Then the second part of the paper describes the identification strategy that one proposes for the sintering stage, using the identification of sintering parameters from dilatometeric curves followed by the optimization of the sintering process. The proposed approaches are applied to the optimization of material and process parameters for manufacturing a ceramic femoral implant. One demonstrates that the proposed approach give satisfactory results.
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.
Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong
2017-03-01
Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.
Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong
2017-01-01
Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060
Global optimization of parameters in the reactive force field ReaxFF for SiOH.
Larsson, Henrik R; van Duin, Adri C T; Hartke, Bernd
2013-09-30
We have used unbiased global optimization to fit a reactive force field to a given set of reference data. Specifically, we have employed genetic algorithms (GA) to fit ReaxFF to SiOH data, using an in-house GA code that is parallelized across reference data items via the message-passing interface (MPI). Details of GA tuning turn-ed out to be far less important for global optimization efficiency than using suitable ranges within which the parameters are varied. To establish these ranges, either prior knowledge can be used or successive stages of GA optimizations, each building upon the best parameter vectors and ranges found in the previous stage. We have finally arrive-ed at optimized force fields with smaller error measures than those published previously. Hence, this optimization approach will contribute to converting force-field fitting from a specialist task to an everyday commodity, even for the more difficult case of reactive force fields.
Laikhtman, A; Rapoport, L; Perfilyev, V; Moshkovich, A; Akhvlediani, R; Hoffman, A
2011-09-01
In the present work we perform optimization of mechanical and crystalline properties of CVD microcrystalline diamond films grown on steel substrates. A chromium-nitride (Cr-N) interlayer had been previously proposed to serve as a buffer for carbon and iron inter-diffusion and as a matching layer for the widely differing expansion coefficients of diamond and steel. However, adhesion and wear as well as crystalline perfection of diamond films are strongly affected by conditions of both Cr-N interlayer preparation and CVD diamond deposition. In this work we assess the effects of two parameters. The first one is the temperature of the Cr-N interlayer preparation: temperatures in the range of 500 degrees C-800 degrees C were used. The second one is diamond film thickness in the 0.5 microm-2 microm range monitored through variation of the deposition time from approximately 30 min to 2 hours. The mechanical properties of so deposited diamond films were investigated. For this purpose, scratch tests were performed at different indentation loads. The friction coefficient and wear loss were assessed. The mechanical and tribological properties were related to structure, composition, and crystalline perfection of diamond films which were extensively analyzed using different microscopic and spectroscopic techniques. It was found that relatively thick diamond film deposited on the Cr-N interlayer prepared at the temperature similar to that of the CVD process has the best mechanical and adhesion strength. This film was stable without visible cracks around the wear track during all scratch tests with different indentation loads. In other cases, cracking and delamination of the films took place at low to moderate indentation loads.
Optimization of periodic column growth in glancing angle deposition for photonic crystal fabrication
NASA Astrophysics Data System (ADS)
Summers, M. A.; Brett, M. J.
2008-10-01
We investigate the growth of periodically aligned silicon microstructures for the fabrication of square spiral photonic crystals using the glancing angle deposition phi-sweep process. We report the optimization of the phi-sweep offset angle for fabrication of microstructures with more precise geometry. The effects of varying the sweep offset angle of the phi-sweep process are studied for films deposited onto a square lattice array of growth seeds. To represent one growth segment of the phi-sweep process, we fabricate 15 nm silicon thin films using several azimuthal substrate offsets from 0° to 45° at a vapor incidence angle of 85°. We also deposit silicon square spirals on square lattice arrays with the phi-sweep method, using various sweep offset angles from γ = 0° to 45°. We find that using an offset angle of γ = 26.5° optimizes the shadowing geometry, which minimizes anisotropic broadening, producing greater quality photonic crystal structures. From normal incidence reflection spectroscopy, a maximum full width at half-maximum of 273 ± 3 nm and a relative peak width (Δλ/λ) of 16.1 ± 0.1% were found for a sweep offset angle of γ = 26.5°.
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.
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.
Use of multilevel modeling for determining optimal parameters of heat supply systems
NASA Astrophysics Data System (ADS)
Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.
2017-07-01
The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in
A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process
NASA Astrophysics Data System (ADS)
Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa
2016-12-01
High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio (S/N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.
Global Parameter Optimization of CLM4.5 Using Sparse-Grid Based Surrogates
NASA Astrophysics Data System (ADS)
Lu, D.; Ricciuto, D. M.; Gu, L.
2016-12-01
Calibration of the Community Land Model (CLM) is challenging because of its model complexity, large parameter sets, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time. The goal of this study is to calibrate some of the CLM parameters in order to improve model projection of carbon fluxes. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the actual CLM model, and then we calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated with sufficiently large number of times in the optimization, which facilitates the global search. We calibrate five parameters against 12 months of GPP, NEP, and TLAI data from the U.S. Missouri Ozark (US-MOz) tower. The results indicate that an accurate surrogate model can be created for the CLM4.5 with a relatively small number of SG points (i.e., CLM4.5 simulations), and the application of the optimized parameters leads to a higher predictive capacity than the default parameter values in the CLM4.5 for the US-MOz site.
Parameter optimization in milling of glass fiber reinforced plastic (GFRP) using DOE-Taguchi method.
Ghalme, Sachin; Mankar, Ankush; Bhalerao, Y J
2016-01-01
Optimization of machining parameters is essential for improving expected outcome of any machining operation. The aim of this work is to find out optimum values of machining parameters to achieve minimal surface roughness during milling operation of GFRP. In this machining operation speed, depth of cut and feed rate are considered as parameters affecting surface roughness and Design of Experiment (DOE)-Taguchi method tool is used to plan experiments and analyse results. Analysis of experimental results presents optimum values of these three parameters to achieve minimal surface roughness with speed as a major contributing factor. Speed-200 rpm, depth of cut-1.2 mm and feed-40 mm/min are an optimal combination of machining parameter to produce minimal surface roughness during milling of GFRP.
Multi-parameter Optimization of a Thermoelectric Power Generator and Its Working Conditions
NASA Astrophysics Data System (ADS)
Zhang, T.
2017-01-01
The global optimal working conditions and optimal couple design for thermoelectric (TE) generators with realistic thermal coupling between the heat reservoirs and the TE couple were studied in the current work. The heat fluxes enforced by the heat reservoirs at the hot and the cold junctions of the TE couple were used in combination with parameter normalization to obtain a single cubic algebraic equation relating the temperature differences between the TE couple junctions and between the heat reservoirs, through the electric load resistance ratio, the reservoir thermal conductance ratio, the reservoir thermal conductance to the TE couple thermal conductance ratio, the Thomson to Seebeck coefficient ratio, and the figure of merit ( Z) of the material based on the linear TE transport equations and their solutions. A broad reservoir thermal conductance ranging between 0.01 W/K and 100 W/K and TE element length ranging from 10-7 m to 10-3 m were explored to find the global optimal systems. The global optimal parameters related to the working conditions, i.e., reservoir thermal conductance ratio and electric load resistance ratio, and the optimal design parameter related to the TE couple were determined for a given TE material. These results demonstrated that the internal and external electric resistance, the thermal resistance between the reservoirs, the thermal resistance between the reservoir and the TE couple, and the optimal thermoelement length have to be well coordinated to obtain optimal power production.
Fault detection of feed water treatment process using PCA-WD with parameter optimization.
Zhang, Shirong; Tang, Qian; Lin, Yu; Tang, Yuling
2017-04-03
Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T(2) and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA-WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T(2) and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an automatic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results.
When the optimal is not the best: parameter estimation in complex biological models.
Fernández Slezak, Diego; Suárez, Cecilia; Cecchi, Guillermo A; Marshall, Guillermo; Stolovitzky, Gustavo
2010-10-25
The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system and point to the need of a theory that addresses this problem more generally.
Development of a framework of automated water quality parameter optimization and its application
NASA Astrophysics Data System (ADS)
Kim, Kyung-Sub; Je, Chung-Hwan
2006-01-01
This paper presents a methodology and framework for the development of an automated least-squares optimization tool for calibrating water quality parameters in QUAL2E. The method has been applied to estimate the optimal water quality parameters in simulation of stream water quality for the Anyang stream in Korea. The Monte Carlo analysis is used to assess the relative importance of model parameters for water quality constituents. It is found that μmax and ρ are the most influential parameters for Chlorophyll-a modeling and K 1 and K 3 are critical parameters for variation of DO and BOD in the Anyang stream. A computer program for automated parameter calibration has been developed using a nonlinear GRG optimization algorithm. The application framework provides an intuitive and easy-to-use interface and allows visual evaluation of results. According to the simulation results, the automated approach is computationally efficient for evaluation of model parameters and converges on a best fit more rapidly and reliably than a trial and error method. The methodology proposed herein can be extended to other models to obtain the best possible parameter values.
Influence of deposition parameters on the microstructure of ion-plated films
NASA Astrophysics Data System (ADS)
Broitman, Esteban; Zimmerman, Rosa
1996-07-01
Ion plating is essentially vapor deposition onto a substrate which is the cathode of a glow discharge. The most important characteristic of the technique is that the growing film is subjected to a flux of high energy particles (neutrals and ions). In this study we report information about the effect of ion plating parameters on grain diameter and crystallite size distribution. At a constant potential grain size remains constant with the increase of ion density. On the other hand, at a constant ion density the grain size decreases with the substrate potential increment. Ion bombardment also has an effect on the crystallite size distribution. The ion plated films show a higher degree of uniformity in grain size than vacuum evaporated films. In contrast with vacuum evaporated films, where the grain size is proportional to the thickness, no variation of grain size with film thickness has been observed for the ion-plated films. Electron diffraction patterns have shown that the orientation remains near random over the entire J and V range studied.
Influence of deposition parameters on the structure and optical property of Zn(S,O) films
NASA Astrophysics Data System (ADS)
Tsai, Du-Cheng; Kuo, Bing-Hau; Chang, Zue-Chin; Chen, Erh-Chiang; Shieu, Fuh-Sheng
2017-01-01
This paper presents the influence of process parameters, including sputtering power, oxygen partial pressure ( R O), and substrate temperature on the optical property of Zn(S,O) thin films fabricated by radio frequency magnetron sputtering technology and deposited on glass substrates. The chemical composition, structural and optical properties of the samples were investigated by electron spectroscopy for chemical analysis, X-ray diffraction, and spectrophotometer. All the films mainly exhibited β-ZnS phase with (111) preferred orientation. [S]/([S]+[O]) ratio increased at high sputtering power, low RO, and low substrate temperature. Moderate ranges in sputtering power and substrate temperature and low RO resulted in large grain size. Adatoms are expected to exhibit increased mobility under these conditions. Average transmittance exceeded 75% in the visible wavelength region. Bandgap under these conditions was dominated strongly by the change in grain size and [S]/([S]+[O]) ratio. Optical properties of Zn(S,O) thin films could be modified, which is promising for optoelectronic applications.
Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model.
Quilot-Turion, Bénédicte; Génard, Michel; Valsesia, Pierre; Memmah, Mohamed-Mahmoud
2016-01-01
Process-based models are effective tools to predict the phenotype of an individual in different growing conditions. Combined with a quantitative trait locus (QTL) mapping approach, it is then possible to predict the behavior of individuals with any combinations of alleles. However the number of simulations to explore the realm of possibilities may become infinite. Therefore, the use of an efficient optimization algorithm to intelligently explore the search space becomes imperative. The optimization algorithm has to solve a multi-objective problem, since the phenotypes of interest are usually a complex of traits, to identify the individuals with best tradeoffs between those traits. In this study we proposed to unroll such a combined approach in the case of peach fruit quality described through three targeted traits, using a process-based model with seven parameters controlled by QTL. We compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimization of the alleles controlling the parameters. The optimization algorithm has been adapted to deal with both continuous and combinatorial problems. We compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces. The use of a genetic model enabled the restriction of the dimension of the parameter space toward more feasible combinations of parameter values, reproducing relationships between parameters as observed in a real progeny. The results of this study demonstrated the potential of such an approach to refine the solutions toward more realistic ideotypes. Perspectives of improvement are discussed.
Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model
Quilot-Turion, Bénédicte; Génard, Michel; Valsesia, Pierre; Memmah, Mohamed-Mahmoud
2016-01-01
Process-based models are effective tools to predict the phenotype of an individual in different growing conditions. Combined with a quantitative trait locus (QTL) mapping approach, it is then possible to predict the behavior of individuals with any combinations of alleles. However the number of simulations to explore the realm of possibilities may become infinite. Therefore, the use of an efficient optimization algorithm to intelligently explore the search space becomes imperative. The optimization algorithm has to solve a multi-objective problem, since the phenotypes of interest are usually a complex of traits, to identify the individuals with best tradeoffs between those traits. In this study we proposed to unroll such a combined approach in the case of peach fruit quality described through three targeted traits, using a process-based model with seven parameters controlled by QTL. We compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimization of the alleles controlling the parameters. The optimization algorithm has been adapted to deal with both continuous and combinatorial problems. We compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces. The use of a genetic model enabled the restriction of the dimension of the parameter space toward more feasible combinations of parameter values, reproducing relationships between parameters as observed in a real progeny. The results of this study demonstrated the potential of such an approach to refine the solutions toward more realistic ideotypes. Perspectives of improvement are discussed. PMID:28066450
"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
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.
Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model
Rengers, Francis; Lunacek, Monte; Tucker, Gregory
2016-06-01
Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.
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
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.
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)
Olivares, Irene; Angelova, Todora I.; Pinilla-Cienfuegos, Elena; Sanchis, Pablo
2016-05-01
The electro-optic Pockels effect may be generated in silicon photonics structures by breaking the crystal symmetry by means of a highly stressing cladding layer (typically silicon nitride, SiN) deposited on top of the silicon waveguide. In this work, the influence of the waveguide parameters on the strain distribution and its overlap with the optical mode to enhance the Pockels effect has been analyzed. The optimum waveguide structure have been designed based on the definition and quantification of a figure of merit. The fabrication of highly stressing SiN layers by PECVD has also been optimized to characterize the designed structures. The residual stress has been controlled during the growth process by analyzing the influence of the main deposition parameters. Therefore, two identical samples with low and high stress conditions were fabricated and electro-optically characterized to test the induced Pockels effect and the influence of carrier effects. Electro-optical modulation was only measured in the sample with the high stressing SiN layer that could be attributed to the Pockels effect. Nevertheless, the influence of carriers were also observed thus making necessary additional experiments to decouple both effects.
An Integrated Framework for Parameter-based Optimization of Scientific Workflows
Kumar, Vijay S.; Sadayappan, P.; Mehta, Gaurang; Vahi, Karan; Deelman, Ewa; Ratnakar, Varun; Kim, Jihie; Gil, Yolanda; Hall, Mary; Kurc, Tahsin; Saltz, Joel
2011-01-01
Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as grouping of workflow components and their mapping to machines do not a ect the accuracy of the output, others may dictate trading the output quality of individual components (and of the whole workflow) for performance. This paper describes an integrated framework which is capable of supporting performance optimizations along multiple dimensions of the parameter space. Using two real-world applications in the spatial data analysis domain, we present an experimental evaluation of the proposed framework. PMID:22068617
NASA Astrophysics Data System (ADS)
Hou, Zhi-chao; Lao, Yao-xin; Lu, Qiu-hai
2008-11-01
Tensioner is a critical mechanism to ensure a constant tension level within a serpentine belt drive that is widely used in modern passenger vehicles. For a belt drive with n pulleys, generic and explicit formulae about sensitivities of both frequency and steady harmonic responses are established in terms of system matrices with respect to any design parameter of the system. Deductions from the formulae results in frequency and steady response sensitivities relative to key tensioner parameters and the belt speed. Based on sensitivity analysis, optimizations are conducted on tensioner so as to suppress dynamic responses of the system by frequency detuning. A new approach for searching optimal parameters is put forward by incorporating sensitivity information into a classical coordinate alternating procedure. Examples are given to validate the analytical formulae of the frequency sensitivity and to demonstrate the effect of optimization.
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.
Belwanshi, Vinod; Topkar, Anita
2016-05-23
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.
Case study: Optimizing fault model input parameters using bio-inspired algorithms
NASA Astrophysics Data System (ADS)
Plucar, Jan; Grunt, Onřej; Zelinka, Ivan
2017-07-01
We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.
NASA Technical Reports Server (NTRS)
Chrzanowski, J.; Meng-Burany, S.; Xing, W. B.; Curzon, A. E.; Heinrich, B.; Irwin, J. C.; Cragg, R. A.; Zhou, H.; Habib, F.; Angus, V.
1995-01-01
Two series of Y1Ba2Cu3O(z) thin films deposited on (001) LaAl03 single crystals by excimer laser ablation under two different protocols have been investigated. The research has yielded well defined deposition conditions in terms of oxygen partial pressure p(O2) and substrate temperature of the deposition process Th, for the growth of high quality epitaxial films of YBCO. The films grown under conditions close to optimal for both j(sub c) and T(sub c) exhibited T(sub c) greater than or equal to 91 K and j(sub c) greater than or equal to 4 x 106 A/sq cm, at 77 K. Close correlations between the structural quality of the film, the growth parameters (p(O2), T(sub h)) and j(sub c) and T(sub c) have been found.
Garzillo, Valerio; Grigutis, Robertas; Jukna, Vytautas; Couairon, Arnaud; Di Trapani, Paolo; Jedrkiewicz, Ottavia
2016-07-07
We investigate the generation of high aspect ratio microstructures across 0.7 mm thick glass by means of single shot Bessel beam laser direct writing. We study the effect on the photoinscription of the cone angle, as well as of the energy and duration of the ultrashort laser pulse. The aim of the study is to optimize the parameters for the writing of a regular microstructure due to index modification along the whole sample thickness. By using a spectrally resolved single pulse transmission diagnostics at the output surface of the glass, we correlate the single shot material modification with observations of the absorption in different portions of the retrieved spectra, and with the absence or presence of spectral modulation. Numerical simulations of the evolution of the Bessel pulse intensity and of the energy deposition inside the sample help us interpret the experimental results that suggest to use picosecond pulses for an efficient and more regular energy deposition. Picosecond pulses take advantage of nonlinear plasma absorption and avoid temporal dynamics effects which can compromise the stationarity of the Bessel beam propagation.
NASA Astrophysics Data System (ADS)
Ghulam Saber, Md; Arif Shahriar, Kh; Ahmed, Ashik; Hasan Sagor, Rakibul
2016-10-01
Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square (RMS) deviation is determined and compared.
Real-time Optimization Method for Optical Parameters of Ion Implanters
Ogata, Seiji; Nishihashi, Tsutomu; Tonari, Kazuhiko; Yokoo, Hidekazu; Suzuki, Hideo; Hisamune, Takeshi; Araki, Masasumi
2006-11-13
Real-time optimization for optical parameters, such as applied voltage to the electrostatic quadrupole lens, has been realized by using newly developed high-speed computation algorithm for charged particle beams. The virtual optimization code has been incorporated in the control system of SOPHI-200, which is the ULVAC'S new medium current ion implanter. Automatic setup within 5minutes is achieved for any recipe of implantation.
NASA Astrophysics Data System (ADS)
Huang, Zhipeng; Gao, Lihong; Wang, Yangwei; Wang, Fuchi
2016-09-01
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.
Shah, Kamran; Haq, Izhar Ul; Shah, Shaukat Ali; Khan, Farid Ullah; Khan, Sikander
2014-01-01
Laser direct metal deposition (LDMD) has developed from a prototyping to a single metal manufacturing tool. Its potential for creating multimaterial and functionally graded structures is now beginning to be explored. This work is a first part of a study in which a single layer of Inconel 718 is deposited on Ti-6Al-4V substrate. Single layer tracks were built at a range of powder mass flow rates using a coaxial nozzle and 1.5 kW diode laser operating in both continuous and pulsed beam modes. This part of the study focused on the experimental findings during the deposition of Inconel 718 powder on Ti-6Al-4V substrate. Scanning electron microscopy (SEM) and X-ray diffraction analysis were performed for characterization and phase identification. Residual stress measurement had been carried out to ascertain the effects of laser pulse parameters on the crack development during the deposition process. PMID:24592190
Shah, Kamran; Izhar Ul Haq; Shah, Shaukat Ali; Khan, Farid Ullah; Khan, Muhammad Tahir; Khan, Sikander
2014-01-01
Laser direct metal deposition (LDMD) has developed from a prototyping to a single metal manufacturing tool. Its potential for creating multimaterial and functionally graded structures is now beginning to be explored. This work is a first part of a study in which a single layer of Inconel 718 is deposited on Ti-6Al-4V substrate. Single layer tracks were built at a range of powder mass flow rates using a coaxial nozzle and 1.5 kW diode laser operating in both continuous and pulsed beam modes. This part of the study focused on the experimental findings during the deposition of Inconel 718 powder on Ti-6Al-4V substrate. Scanning electron microscopy (SEM) and X-ray diffraction analysis were performed for characterization and phase identification. Residual stress measurement had been carried out to ascertain the effects of laser pulse parameters on the crack development during the deposition process.
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 scanning parameters for MR elastography at 3.0 T clinical unit: volunteer study.
Shinagawa, Yoshinobu; Mitsufuji, Toshimichi; Morimoto, Shoichi; Nakamuta, Ryuji; Urakawa, Hiroshi; Morita, Ayako; Fujimitsu, Ritsuko; Takano, Koichi; Yoshimitsu, Kengo
2014-07-01
We sought to optimize scanning parameters for MR elastography at 3.0 T clinical unit. 10 volunteers were scanned with various magnetization encoding gradient (MEG) frequencies from 60 to 120 Hz at every 10 Hz, with otherwise fixed parameters (external driver frequency/amplitude = 60 Hz/50 %, 10 mm slice thickness, etc.). Images were qualitatively assessed for the degree of image defects, and also quantitatively for the areas without cross-hatching. After determining optimal MEG frequency, external driver amplitudes of 70 % (vs 50 %) and slice thickness of 8 mm (vs 10 mm) were also tested. With the optimized parameters, scans were repeated 1 week after the initial scan, and the repeatability of the liver stiffness measurement was validated. 80 or 90 Hz was shown to be the best MEG frequency. There were no significant differences in the qualitative and quantitative assessment between the two amplitudes and two slice thicknesses; however, 70 % amplitude resulted in discomfort at the chest wall beneath the external acoustic driver. Thus, MEG 80 (or 90) Hz, amplitude 50 %, and thickness 10 (or 8) mm were considered optimal. Repeatability of the liver stiffness measurement was ±10 % (95 % confidence interval). With the optimized parameters, repeatability of ±10 % in liver stiffness measurement was obtained.
NASA Astrophysics Data System (ADS)
Potters, M. G.; Mansoori, M.; Bombois, X.; Jansen, J. D.; Van den Hof, P. M. J.
2016-03-01
This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using either inlet pressure/outlet pressure measurements (Heller et al., 2002) or actuator position/outlet pressure measurements, where the latter is a novel approach. The solution to the optimization problem reveals that for both measurement methods an optimal excitation frequency, an optimal inlet volume, and an optimal outlet volume exist. We find that under the same parameter variance bounds and actuator constraints, actuator position/outlet pressure measurements result in required experiment times that are a factor fourteen smaller compared to inlet pressure/outlet pressure measurements. This result is analysed in detail and we find that the dominant effect driving this difference originates from an identifiability problem when using inlet-outlet pressure measurements for joint estimation of permeability and porosity. We illustrate our results with numerical simulations, and show excellent agreement with theoretical expectations.
Iterative optimization algorithm with parameter estimation for the ambulance location problem.
Kim, Sun Hoon; Lee, Young Hoon
2016-12-01
The emergency vehicle location problem to determine the number of ambulance vehicles and their locations satisfying a required reliability level is investigated in this study. This is a complex nonlinear issue involving critical decision making that has inherent stochastic characteristics. This paper studies an iterative optimization algorithm with parameter estimation to solve the emergency vehicle location problem. In the suggested algorithm, a linear model determines the locations of ambulances, while a hypercube simulation is used to estimate and provide parameters regarding ambulance locations. First, we suggest an iterative hypercube optimization algorithm in which interaction parameters and rules for the hypercube and optimization are identified. The interaction rules employed in this study enable our algorithm to always find the locations of ambulances satisfying the reliability requirement. We also propose an iterative simulation optimization algorithm in which the hypercube method is replaced by a simulation, to achieve computational efficiency. The computational experiments show that the iterative simulation optimization algorithm performs equivalently to the iterative hypercube optimization. The suggested algorithms are found to outperform existing algorithms suggested in the literature.
Error reduction and parameter optimization of the TAPIR method for fast T1 mapping.
Zaitsev, M; Steinhoff, S; Shah, N J
2003-06-01
A methodology is presented for the reduction of both systematic and random errors in T(1) determination using TAPIR, a Look-Locker-based fast T(1) mapping technique. The relations between various sequence parameters were carefully investigated in order to develop recipes for choosing optimal sequence parameters. Theoretical predictions for the optimal flip angle were verified experimentally. Inversion pulse imperfections were identified as the main source of systematic errors in T(1) determination with TAPIR. An effective remedy is demonstrated which includes extension of the measurement protocol to include a special sequence for mapping the inversion efficiency itself.
Xue, Dingyü; Li, Tingxue
2017-04-27
The parameter optimization method for multivariable systems is extended to the controller design problems for multiple input multiple output (MIMO) square fractional-order plants. The algorithm can be applied to search for the optimal parameters of integer-order controllers for fractional-order plants with or without time delays. Two examples are given to present the controller design procedures for MIMO fractional-order systems. Simulation studies show that the integer-order controllers designed are robust to plant gain variations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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.
NASA Astrophysics Data System (ADS)
Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei
2017-05-01
Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF
Vackel, Andrew; Sampath, Sanjay
2017-02-27
Thermal spray deposited WC-CoCr coatings are extensively used for surface protection of wear prone components in a variety of applications. Although the primary purpose of the coating is wear and corrosion protection, many of the coated components are structural systems (aero landing gear, hydraulic cylinders, drive shafts etc.) and as such experience cyclic loading during service and are potentially prone to fatigue failure. It is of interest to ensure that the coating and the application process does not deleteriously affect the fatigue strength of the parent structural metal. It has long been appreciated that the relative fatigue life of amore » thermal sprayed component can be affected by the residual stresses arising from coating deposition. The magnitude of these stresses can be managed by torch processing parameters and can also be influenced by deposition effects, particularly the deposition temperature. In this study, the effect of both torch operating parameters (particle states) and deposition conditions (notably substrate temperature) were investigated through rotating bending fatigue studies. The results indicate a strong influence of process parameters on relative fatigue life, including credit or debit to the substrate's fatigue life measured via rotating bend beam studies. Damage progression within the substrate was further explored by stripping the coating off part way through fatigue testing, revealing a delay in the onset of substrate damage with more fatigue resistant coatings but no benefit with coatings with inadequate properties. Finally, the results indicate that compressive residual stress and adequate load bearing capability of the coating (both controlled by torch and deposition parameters) delay onset of substrate damage, enabling fatigue credit of the coated component.« less
Zheng, Xiaoming
2017-08-18
The purpose of this work was to examine the effects of relationship functions between diagnostic image quality and radiation dose on the governing equations for image acquisition parameter variations in X-ray imaging. Various equations were derived for the optimal selection of peak kilovoltage (kVp) and exposure parameter (milliAmpere second, mAs) in computed tomography (CT), computed radiography (CR), and direct digital radiography. Logistic, logarithmic, and linear functions were employed to establish the relationship between radiation dose and diagnostic image quality. The radiation dose to the patient, as a function of image acquisition parameters (kVp, mAs) and patient size (d), was used in radiation dose and image quality optimization. Both logistic and logarithmic functions resulted in the same governing equation for optimal selection of image acquisition parameters using a dose efficiency index. For image quality as a linear function of radiation dose, the same governing equation was derived from the linear relationship. The general equations should be used in guiding clinical X-ray imaging through optimal selection of image acquisition parameters. The radiation dose to the patient could be reduced from current levels in medical X-ray imaging.
Lynch, Vickie E.; Borreguero, Jose M.; Bhowmik, Debsindhu; ...
2017-03-27
Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. In order to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. Here, we describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in amore » deuterated water (D2O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. In order to compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.« less
NASA Astrophysics Data System (ADS)
Lynch, Vickie E.; Borreguero, Jose M.; Bhowmik, Debsindhu; Ganesh, Panchapakesan; Sumpter, Bobby G.; Proffen, Thomas E.; Goswami, Monojoy
2017-07-01
Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D2O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.
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.
Parameter estimation of a pulp digester model with derivative-free optimization strategies
NASA Astrophysics Data System (ADS)
Seiça, João C.; Romanenko, Andrey; Fernandes, Florbela P.; Santos, Lino O.; Fernandes, Natércia C. P.
2017-07-01
The work concerns the parameter estimation in the context of the mechanistic modelling of a pulp digester. The problem is cast as a box bounded nonlinear global optimization problem in order to minimize the mismatch between the model outputs with the experimental data observed at a real pulp and paper plant. MCSFilter and Simulated Annealing global optimization methods were used to solve the optimization problem. While the former took longer to converge to the global minimum, the latter terminated faster at a significantly higher value of the objective function and, thus, failed to find the global solution.
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.
Lerondel, S; Le Pape, A; Sené, C; Faure, L; Bernard, S; Diot, P; Nicolis, E; Mehtali, M; Lusky, M; Cabrini, G; Pavirani, A
2001-01-01
Cystic fibrosis is a common, heriditary disease resulting from mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Airway transfer of the CFTR gene is a potential strategy to treat or prevent the lung pathology that is the main cause of morbidity and mortality. Among the vectors used for gene therapy, adenoviruses have shown their ability to transfer the CFTR gene to respiratory epithelial cells, using either instillation or nebulization. Our objective was to characterize the lung deposition of aerosolized adenovirus by quantitative radioisotopic imaging, the only noninvasive technique allowing in vivo quantitation of inhaled drugs. We first labeled an adenovirus expressing human CFTR with the gamma-emitting radioisotope, technetium 99m (99mTc), and determined the best labeling conditions to allow preservation of virus bioactivity. We then administered the radioaerosol to baboons, determined lung regional deposition of 99mTc-labeled adenovirus, and compared the expression of CFTR transcripts 3 and 21 days after inhalation. The expression of vector-encoded mRNA ranged from 4 to 22% with respect to the endogenous CFTR mRNA depending on the lung segments. Moreover, we have developed a model using 99mTc-DTPA (diethylenetriamine pentaacetic acid), which can be used, as an alternative to adenovirus, to determine the profile of lung deposition of the vector. This study demonstrates that scintigraphy is a useful technique to achieve optimization of gene administration to the airways.
Stock optimizing in choice when a token deposit is the operant.
Widholm, J J; Silberberg, A; Hursh, S R; Imam, A A; Warren-Boulton, F R
2001-01-01
Each of 2 monkeys typically earned their daily food ration by depositing tokens in one of two slots. Tokens deposited in one slot dropped into a bin where they were kept (token kept). Deposits to a second slot dropped into a bin where they could be obtained again (token returned). In Experiment 1, a fixed-ratio (FR) 5 schedule that provided two food pellets was associated with each slot. Both monkeys preferred the token-returned slot. In Experiment 2, both subjects chose between unequal FR schedules with the token-returned slot always associated with the leaner schedule. When the FRs were 2 versus 3 and 2 versus 6, preferences were maintained for the token-returned slot; however, when the ratios were 2 versus 12, preference shifted to the token-kept slot. In Experiment 3, both monkeys chose between equal-valued concurrent variable-interval variable-interval schedules. Both monkeys preferred the slot that returned tokens. In Experiment 4, both monkeys chose between FRs that typically differed in size by a factor of 10. Both monkeys preferred the FR schedule that provided more food per trial. These data show that monkeys will choose so as to increase the number of reinforcers earned (stock optimizing) even when this preference reduces the rate of reinforcement (all reinforcers divided by session time). PMID:11768710
Stock optimizing in choice when a token deposit is the operant.
Widholm, J J; Silberberg, A; Hursh, S R; Imam, A A; Warren-Boulton, F R
2001-11-01
Each of 2 monkeys typically earned their daily food ration by depositing tokens in one of two slots. Tokens deposited in one slot dropped into a bin where they were kept (token kept). Deposits to a second slot dropped into a bin where they could be obtained again (token returned). In Experiment 1, a fixed-ratio (FR) 5 schedule that provided two food pellets was associated with each slot. Both monkeys preferred the token-returned slot. In Experiment 2, both subjects chose between unequal FR schedules with the token-returned slot always associated with the leaner schedule. When the FRs were 2 versus 3 and 2 versus 6, preferences were maintained for the token-returned slot; however, when the ratios were 2 versus 12, preference shifted to the token-kept slot. In Experiment 3, both monkeys chose between equal-valued concurrent variable-interval variable-interval schedules. Both monkeys preferred the slot that returned tokens. In Experiment 4, both monkeys chose between FRs that typically differed in size by a factor of 10. Both monkeys preferred the FR schedule that provided more food per trial. These data show that monkeys will choose so as to increase the number of reinforcers earned (stock optimizing) even when this preference reduces the rate of reinforcement (all reinforcers divided by session time).
Evaluation of a new parallel numerical parameter optimization algorithm for a dynamical system
NASA Astrophysics Data System (ADS)
Duran, Ahmet; Tuncel, Mehmet
2016-10-01
It is important to have a scalable parallel numerical parameter optimization algorithm for a dynamical system used in financial applications where time limitation is crucial. We use Message Passing Interface parallel programming and present such a new parallel algorithm for parameter estimation. For example, we apply the algorithm to the asset flow differential equations that have been developed and analyzed since 1989 (see [3-6] and references contained therein). We achieved speed-up for some time series to run up to 512 cores (see [10]). Unlike [10], we consider more extensive financial market situations, for example, in presence of low volatility, high volatility and stock market price at a discount/premium to its net asset value with varying magnitude, in this work. Moreover, we evaluated the convergence of the model parameter vector, the nonlinear least squares error and maximum improvement factor to quantify the success of the optimization process depending on the number of initial parameter vectors.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.
Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei
2017-09-21
In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.
Sequential deposition: optimization of solvent swelling for high-performance polymer solar cells.
Liu, Yao; Liu, Feng; Wang, Hsin-Wei; Nordlund, Dennis; Sun, Zhiwei; Ferdous, Sunzida; Russell, Thomas P
2015-01-14
Organic solar cells based on a typical DPP polymer were systematically optimized by a solvent swelling assisted sequential deposition process. We investigated the influence of solvent swelling on the morphology and structure order of the swollen film and the resultant device performance. Morphological and structural characterization confirmed the realization of ideal bulk heterojunctions using a suitable swelling solvent. A trilayered morphology was also found with the conjugated polymer concentrated bottom layer, PC71BM concentrated top layer, and interpenetrated networks of donor and acceptor in the middle by solvent swelling instead of thermal annealing in the sequential solution processing method. We proposed a simple strategy to optimize the sequential deposition fabricated devices by tuning the concentration of the PC71BM solution instead of thermal annealing. The best device showed a PCE of 7.59% with a Voc of 0.61 V, Jsc of 17.95 mA/cm(2), and FF of 69.6%, which is the highest reported efficiency for devices fabricated by a sequential processing method and among the best results for DPP polymers.
Variable ingestion rate and its role in optimal foraging behavior of marine deposit feeders
Taghon, G.L.; Jumars, P.A.
1984-04-01
Tests of optimal foraging theory have focused generally on food item selection by mobile, high-trophic-level predators. Deposit-feeding invertebrates are aquatic organisms with limited mobility and hence limited ability to forage actively for food-rich patches. In addition, there is little evidence for a major role of behaviorally mediated food item choice in these animals, and growing evidence of mechanical limitations in food particle choice. Given such limited food-selection ability, varying ingestion rate in response to changes in food value is likely to be an important animal response affecting feeding energetics. A previously developed optimal foraging model predicted that ingestion rate and food value should covary positively in order to maximize net time rate of energy gain. To test this general prediction, the authors fed three species of deposit-feeding polychaetes artifical sediments which varied only in protein content (food value); other physical and chemical properties which might affect ingestion rate were kept constant. In support of the model, ingestion rates increased as protein levels increased.
Parameter optimization capability in the trajectory code PMAST (Point-Mass Simulation Tool)
Outka, D.E.
1987-01-28
Trajectory optimization capability has been added to PMAST through addition of the Recursive Quadratic Programming code VF02AD. The scope of trajectory optimization problems the resulting code can solve is very broad, as it takes advantage of the versatility of the original PMAST code. Most three-degree-of-freedom flight-vehicle problems can be simulated with PMAST, and up to 25 parameters specifying initial conditions, weights, control histories and other problem-deck inputs can be used to meet trajectory constraints in some optimal manner. This report outlines the mathematical formulation of the optimization technique, describes the input requirements and suggests guidelines for problem formulation. An example problem is presented to demonstrate the use and features of the optimization portions of the code.
NASA Astrophysics Data System (ADS)
Gelfenbaum, G. R.; La Selle, S.; Witter, R. C.; Sugawara, D.; Jaffe, B. E.
2015-12-01
Inferring the relative magnitude of tsunamis generated during earthquakes based on the characteristics of sandy coastal deposits is a challenging problem. Using a hydrodynamic and sediment transport model, we explore whether the volume of sandy tsunami deposits can be used to infer tsunami magnitude and seafloor deformation. For large subduction zone earthquakes specifically, we are testing the hypothesis that onshore tsunami deposit volume is correlated with nearshore tsunami wave height and coseismic slip. First, we test this hypothesis using onshore tsunami deposit volume data and offshore slip for the 2011 Tohoku earthquake and tsunami. This test considers tsunami deposit volume and offshore slip as they vary alongshore across a wide range of sediment sources, offshore and onshore slopes, and boundary roughness conditions. Preliminary analysis suggests that a strong correlation exists between onshore tsunami deposit volume and adjacent offshore coseismic slip, so long as ample sediment were available along the coast to be eroded. Second, we apply a Delft3D tsunami inundation and sediment transport model to Stardust Bay in the U.S. Aleutian Islands, where 6 tsunamis in the last ~1700 years deposited marine sand across a coastal plain as much as 800 m inland and up to ~15 m above mean sea level. The youngest sand sheet, probably deposited by a tsunami generated during the 1957 Andreanof Islands earthquake (Mw 8.6), has the smallest sediment volume. Several older deposits have larger volumes. Models show that ≥10 m of slip on the Aleutian subduction megathrust offshore of Stardust Bay could produce the onshore sediment volume measured for the 1957 deposit. Older tsunami deposits of greater volume require up to 14 m of megathrust slip. Model sensitivity studies show that onshore sediment volume is most sensitive to megathrust slip and less sensitive to other unknowns such as width of fault rupture and roughness of inundated terrain
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 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.
2007-04-01
of felt blankets, ceramic blankets, ceramic tiles, carbon - carbon leading edges, as well as metallic TPS. Metallic TPS has obvious advantages and...optimization6 that contains dynamic characteristics. In this paper, the modified static control parameter using von Mises stress is newly formulated to...volume reduction. In the next section, control parameters for static and dynamic analysis based on von Mises stress are formulated. Section III
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.
Abe, Tomomi; Hashimoto, Shuji; Matsumoto, Mitsuharu
2010-02-01
epsilon-filter can reduce most kinds of noise from a single-channel noisy signal while preserving signals that vary drastically such as speech signals. It can reduce not only stationary noise but also nonstationary noise. However, it has some parameters whose values are set empirically. So far, there have been few studies to evaluate the appropriateness of the parameter settings for epsilon-filter. This paper employs the correlation coefficient of the filter output and the difference between the filter input and output as the evaluation function of the parameter setting. This paper also describes the algorithm to set the optimal parameter value of epsilon-filter automatically. To evaluate the adequateness of the obtained parameter, the mean absolute error is calculated. The experimental results show that the adequate parameter in epsilon-filter can be obtained automatically by using the proposed method.
Fourier-based reconstruction for fully 3-D PET: optimization of interpolation parameters.
Matej, Samuel; Kazantsev, Ivan G
2006-07-01
Fourier-based approaches for three-dimensional (3-D) reconstruction are based on the relationship between the 3-D Fourier transform (FT) of the volume and the two-dimensional (2-D) FT of a parallel-ray projection of the volume. The critical step in the Fourier-based methods is the estimation of the samples of the 3-D transform of the image from the samples of the 2-D transforms of the projections on the planes through the origin of Fourier space, and vice versa for forward-projection (reprojection). The Fourier-based approaches have the potential for very fast reconstruction, but their straightforward implementation might lead to unsatisfactory results if careful attention is not paid to interpolation and weighting functions. In our previous work, we have investigated optimal interpolation parameters for the Fourier-based forward and back-projectors for iterative image reconstruction. The optimized interpolation kernels were shown to provide excellent quality comparable to the ideal sinc interpolator. This work presents an optimization of interpolation parameters of the 3-D direct Fourier method with Fourier reprojection (3D-FRP) for fully 3-D positron emission tomography (PET) data with incomplete oblique projections. The reprojection step is needed for the estimation (from an initial image) of the missing portions of the oblique data. In the 3D-FRP implementation, we use the gridding interpolation strategy, combined with proper weighting approaches in the transform and image domains. We have found that while the 3-D reprojection step requires similar optimal interpolation parameters as found in our previous studies on Fourier-based iterative approaches, the optimal interpolation parameters for the main 3D-FRP reconstruction stage are quite different. Our experimental results confirm that for the optimal interpolation parameters a very good image accuracy can be achieved even without any extra spectral oversampling, which is a common practice to decrease errors
2013-01-01
Background Recovering the network topology and associated kinetic parameter values from time-series data are central topics in systems biology. Nevertheless, methods that simultaneously do both are few and lack generality. Results Here, we present a rigorous approach for simultaneously estimating the parameters and regulatory topology of biochemical networks from time-series data. The parameter estimation task is formulated as a mixed-integer dynamic optimization problem with: (i) binary variables, used to model the existence of regulatory interactions and kinetic effects of metabolites in the network processes; and (ii) continuous variables, denoting metabolites concentrations and kinetic parameters values. The approach simultaneously optimizes the Akaike criterion, which captures the trade-off between complexity (measured by the number of parameters), and accuracy of the fitting. This simultaneous optimization mitigates a possible overfitting that could result from addition of spurious regulatory interactions. Conclusion The capabilities of our approach were tested in one benchmark problem. Our algorithm is able to identify a set of plausible network topologies with their associated parameters. PMID:24176044
PALS — The optimal laser for determining optimal ablative laser propulsion parameters?
NASA Astrophysics Data System (ADS)
Boody, Frederick P.
2005-04-01
Ablative laser propulsion (ALP) could revolutionize space travel by reducing the 30:1 propellant/payload ratio needed for near-earth orbit 50-fold. To date, experiments have demonstrated the necessary efficiency, coupling coefficient, and specific impulse for application, but were performed at pulse energies and spot sizes much smaller than required and at wavelengths not usable in the atmosphere. Also, most experiments have not simultaneously measured the properties of the ions produced or of the ablated surface, properties that would allow full understanding of the propulsion properties in terms of ion characteristics. Realistic measurement of laser propulsion parameters is proposed using PALS (Prague Asterix Laser System), whose parameters, except for pulse rate and wavelength — pulse energy (˜1kJ), pulse length (400ps), beam diameter (˜29cm), and flat beam profile — equal those required for application. PALS wavelength is a little short (1.3μm vs. >1.5μm) but is closer than any other laser available and, due to PALS 2ω / 3ω capability, wavelength dependence can be studied and results extrapolated to application values. PALS' proven infrastructure for measuring laser-driven ion properties means that only an instrument for measuring momentum transfer, such as a ballistic pendulum, will have to be added.
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
Effects of AV-delay optimization on hemodynamic parameters in patients with VDD pacemakers.
Krychtiuk, Konstantin A; Nürnberg, Michael; Volker, Romana; Pachinger, Linda; Jarai, Rudolf; Freynhofer, Matthias K; Wojta, Johann; Huber, Kurt; Weiss, Thomas W
2014-05-01
Atrioventricular (AV) delay optimization improves hemodynamics and clinical parameters in patients treated with cardiac resynchronization therapy and dual-chamber-pacemakers (PM). However, data on optimizing AV delay in patients treated with VDD-PMs are scarce. We, therefore, investigated the acute and chronic effects of AV delay optimization on hemodynamics in patients treated with VDD-PMs due to AV-conduction disturbances. In this prospective, single-center interventional trial, we included 64 patients (38 men, 26 women, median age: 77 (70-82) years) with implanted VDD-PM. AV-delay optimization was performed using a formula based on the surface electrocardiogram (ECG). Hemodynamic parameters (stroke volume (SV), cardiac output (CO), heart rate (HR), and blood pressure (BP)) were measured at baseline and follow-up after 3 months using impedance cardiography. Using an ECG formula for AV-delay optimization, the AV interval was decreased from 180 (180-180) to 75 (75-100) ms. At baseline, AV-delay optimization led to a significant increase of both SV (71.3 ± 15.8 vs. 55.3 ± 12.7 ml, p < 0.001, for optimized AV delay vs. nominal AV interval, respectively) and CO (5.1 ± 1.4 vs. 3.9 ± 1.0 l/min, p < 0.001), while HR and BP remained unchanged. At follow-up, the improvement in CO remained stable (4.9 ± 1.3 l/min, p = 0.09), while SV slightly, but significantly, decreased (to 65.1 ± 17.6, p < 0.01). AV-delay optimization in patients treated with VDD-PMs exhibits immediate beneficial effects on hemodynamic parameters that are sustained for 3 months.
Andersson, Kasper G; Nielsen, Sven P; Thørring, Håvard; Hansen, Hanne S; Joensen, Hans Pauli; Isaksson, Mats; Kostiainen, Eila; Suolanen, Vesa; Pálsson, Sigurdur Emil
2011-11-01
The ECOSYS model is the ingestion dose model integrated in the ARGOS and RODOS decision support systems for nuclear emergency management. The parameters used in this model have however not been updated in recent years, where the level of knowledge on various environmental processes has increased considerably. A Nordic work group has carried out a series of evaluations of the general validity of current ECOSYS default parameters. This paper specifically discusses the parameter revisions required with respect to the modelling of deposition and natural weathering of contaminants on agricultural crops, to enable the trustworthy prognostic modelling that is essential to ensure justification and optimisation of countermeasure strategies. New modelling approaches are outlined, since it was found that current ECOSYS approaches for deposition and natural weathering could lead to large prognostic errors.
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
He, Meng-Xuan; Li, Hong-Yuan; Mo, Xun-Qiang; Meng, Wei-Qing; Yang, Jia-Nan
2014-08-01
The thickness of surface soil, the covering thickness and the number of adding arbor seeds are all important factors to be considered in the application of soil seed bank (SSB) for vegetation recovery. To determine the optimal conditions, the Box-Behnken central composite design with three parameters and three levels was conducted and Design-Expert was used for response surface optimization. Finally, the optimal model and optimal level of each parameter were selected. The quadratic model was more suitable for response surface optimization (P < 0.0001), indicating the model had good statistical significance which could express ideal relations between all the independent variable and dependent variable. For the optimum condition, the thickness of surface soil was 4.3 cm, the covering thickness was 2 cm, and the number of adding arbor seeds was 224 ind x m(-2), under which the number of germinated seedlings could be reached up to 6222 plants x m(-2). During the process of seed germination, significant interactions between the thickness of surface soil and the covering thickness, as well as the thickness of surface soil and the number of adding arbor seeds were found, but the relationship between the covering thickness and the number of adding arbor seeds was relatively unremarkable. Among all the parameters, the thickness of surface soil was the most important one, which had the steepest curve and the largest standardized coefficient.
Parameters Optimization for Operational Storm Surge/Tide Forecast Model using a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Lee, W.; You, S.; Ryoo, S.; Global Environment System Research Laboratory
2010-12-01
Typhoons generated in northwestern Pacific Ocean annually affect the Korean Peninsula and storm surges generated by strong low pressure and sea winds often cause serious damage to property in the coastal region. To predict storm surges, a lot of researches have been conducted by using numerical models for many years. Various parameters used for calculation of physics process are used in numerical models based on laws of physics, but they are not accurate values. Because those parameters affect to the model performance, these uncertain values can sensitively operate results of the model. Therefore, optimization of these parameters used in numerical model is essential for accurate storm surge predictions. A genetic algorithm (GA) is recently used to estimate optimized values of these parameters. The GA is a stochastic exploration modeling natural phenomenon named genetic heritance and competition for survival. To realize breeding of species and selection, the groups which may be harmed are kept and use genetic operators such as inheritance, mutation, selection and crossover. In this study, we have improved operational storm surge/tide forecast model(STORM) of NIMR/KMA (National Institute of Meteorological Research/Korea Meteorological Administration) that covers 115E - 150E, 20N - 52N based on POM (Princeton Ocean Model) with 8km horizontal resolutions using the GA. Optimized values have been estimated about main 4 parameters which are bottom drag coefficient, background horizontal diffusivity coefficient, Smagoranski’s horizontal viscosity coefficient and sea level pressure scaling coefficient within STORM. These optimized parameters were estimated on typhoon MAEMI in 2003 and 9 typhoons which have affected to Korea peninsula from 2005 to 2007. The 4 estimated parameters were also used to compare one-month predictions in February and August 2008. During the 48h forecast time, the mean and median model accuracies improved by 25 and 51%, respectively.
Parkhomchuk, V.V.; Shiltsev, V.D.
1993-06-01
The paper considers the Superconducting Super Collider (SSC) site ground motion measurements as well as data from accelerators worldwide about noises that worsen beam performance. Unacceptably fast emittance growth due to these noises is predicted for the SSC. A transverse feedback system was found to be the only satisfactory alternative to prevent emittance decay. Optimization of the primary feedback parameters was done.
NASA Astrophysics Data System (ADS)
Evstigneev, Vladislav P.; Pashkova, Irina S.; Kostjukov, Viktor V.; Hernandez Santiago, Adrian A.; Evstigneev, Maxim P.
2016-11-01
The principal condition for optimal experiment design, required for getting reasonable error for equilibrium aggregation constant, K, determination is obtained. This condition states that the selected concentration range for performing titration experiment should be inversely proportional to the expected value of K. As a consequence, the choice of physico-chemical methods for determination of aggregation parameters must obey this condition.
Optimization of electro-optical parameters of LCD for advertising systems
NASA Astrophysics Data System (ADS)
Olifierczuk, Marek; Zielinski, Jerzy; Klosowicz, Stanislaw J.
1998-02-01
The analysis of the optimization of negative image twisted nematic LCD is presented. Theoretical considerations are confirmed by experimental results. The effect of material parameters and technology on the contrast ratio and display dynamics is given. The effect in TN display with black dye is presented.
An analysis of the accuracy of a parameter optimization. M.S. Thesis
NASA Technical Reports Server (NTRS)
Baram, Y.
1974-01-01
The numerical operations involved in a currently used optimization technique are discussed and analyzed with special attention to the numerical accuracy. Alternative methods for deriving linear system transfer functions, finding the relationships between the transfer function coefficients and the design parameters, and solving a matrix equation are presented for more accurate and cost effective solutions.
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.
A Systematic Comparison between Classical Optimal Scaling and the Two-Parameter IRT Model
ERIC Educational Resources Information Center
Warrens, Matthijs J.; de Gruijter, Dato N. M.; Heiser, Willem J.
2007-01-01
In this article, the relationship between two alternative methods for the analysis of multivariate categorical data is systematically explored. It is shown that the person score of the first dimension of classical optimal scaling correlates strongly with the latent variable for the two-parameter item response theory (IRT) model. Next, under the…
Optimization of operating parameters of endothermic generators with electric heating of retort
NASA Astrophysics Data System (ADS)
Dubinin, A. M.; Fink, A. V.; Kagarmanov, G. R.
2009-07-01
Equations of heat and gas balance of endothermic generator at air conversion of methane are used for optimizing the parameters with respect to maximum yield of hydrogen and carbon oxide at minimum consumption of electric energy for heating the retort with catalyst.
NASA Astrophysics Data System (ADS)
Campbell, Michelle E.; Porritt, Lucy; Russell, J. K.
2016-02-01
The 2360 BP eruption of Mount Meager, Canada featured an explosive subplinian onset resulting in dacitic fallout tephra and associated pumiceous pyroclastic flow deposits, followed by the effusion of dacite lava and the deposition of a thick sequence of block and ash flow deposits. Fall deposits are distributed to the NE of the vent onto a rugged, deeply incised landscape. The central axis of deposition is ~ 063° Az; the lateral margins of the fall deposit are massive to unbedded whereas deposits underlying the plume axis feature complex bedding relationships. We present componentry and granulometry data for eight outcroppings of the fall deposit (four on plume axis and four off plume axis). Vertical cross-sections, based on surface outcrops and drill core logs from local commercial drilling programs, are used to relate the accessory lithics to their source depth in the underlying subvolcanic basement. These combined datasets inform on the dynamics of this explosive phase of the eruption including variations in column height, eruption intensity, atmospheric conditions, and depth to fragmentation front. The lateral variations within the fall strata reflect the effects of the prevailing atmospheric conditions on the form and dispersal pattern of the subplinian plume. Vertical variations in granulometry and componentry of the fall deposits are used to track temporal changes in eruption intensity and column height and the transient influence of the jetstream on the dispersal pattern of the plume. Lastly, vertical variations in lithic componentry, combined with our knowledge of the subsurface geology, are used to quantitatively track the deepening of the fragmentation front. Our computed results show that the fragmentation front migrated from ~ 640 m to ~ 1160 m below the vent over the course of the 2360 BP Mount Meager eruption.
Issues in optimal parameter estimation for the nonlinear Muskingum flood routing model
NASA Astrophysics Data System (ADS)
Geem, Zong Woo
2014-03-01
This study answers two questions raised in the parameter estimation optimization for the nonlinear Muskingum flood routing model. The first question is whether a new global optimum was still found after the existing global optimum had already been found. In order to fairly verify this question, a standard routing procedure for the nonlinear Muskingum model, which has not been clearly described previously, is proposed. Because the routing procedure was coded in a spreadsheet, any researcher can easily test it after downloading it. The second question is the reason why various approaches, such as Lagrange multiplier, Broyden-Fletcher-Goldfarb-Shanno (BFGS), genetic algorithm, harmony search and particle swarm optimization, have tackled only Wilson's data set as the parameter estimation optimization for the nonlinear Muskingum model, because Wilson's data have a unique structure which is differentiated from other data sets. This study also provides various data sets to compare.
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
Optimization of jet parameters to control the flow on a ramp
NASA Astrophysics Data System (ADS)
Guilmineau, Emmanuel; Duvigneau, Régis; Labroquère, Jérémie
2014-06-01
This study deals with the use of optimization algorithms to determine efficient parameters of flow control devices. To improve the performance of systems characterized by detached flows and vortex shedding, the use of flow control devices such as oscillatory jets are intensively studied. However, the determination of efficient control parameters is still a bottleneck for industrial problems. Therefore, we propose to couple a global optimization algorithm with an unsteady flow simulation to derive efficient flow control rules. We consider as a test case a backward-facing step with a slope of 25°, including a synthetic jet actuator. The aim is to reduce the time-averaged recirculation length behind the step by optimizing the jet blowing/suction amplitude and frequency.
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.
Parameter optimization of a dual-comb ranging system by using a numerical simulation method.
Wu, Guanhao; Xiong, Shilin; Ni, Kai; Zhu, Zebin; Zhou, Qian
2015-12-14
Dual-comb system parameters have significant impacts on the ranging accuracy. We present a theoretical model and a numerical simulation method for the parameter optimization of a dual-comb ranging system. With this method we investigate the impacts of repetition rate difference, repetition rate, and carrier-envelope-offset frequency on the ranging accuracy. Firstly, the simulation results suggest a series of discrete zones of repetition rate difference in an optimal range, which are consistent with the experimental results. Secondly, the simulation results of the repetition rate indicate that a higher repetition rate is very favorable to improve the ranging accuracy. Finally, the simulation results suggest a series of discrete optimal ranges of the carrier-envelope-offset frequency for the dual-comb system. The simulated results were verified by our experiments.
Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine
NASA Astrophysics Data System (ADS)
Zhang, L.; Zhuge, W. L.; Peng, J.; Liu, S. J.; Zhang, Y. J.
2013-12-01
In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (WR and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β6, the exit tip radius R6t and hub radius R6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency ηts, and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency ηts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the value
Human-in-the-loop Bayesian optimization of wearable device parameters
Malcolm, Philippe; Speeckaert, Jozefien; Siviy, Christoper J.; Walsh, Conor J.; Kuindersma, Scott
2017-01-01
The increasing capabilities of exoskeletons and powered prosthetics for walking assistance have paved the way for more sophisticated and individualized control strategies. In response to this opportunity, recent work on human-in-the-loop optimization has considered the problem of automatically tuning control parameters based on realtime physiological measurements. However, the common use of metabolic cost as a performance metric creates significant experimental challenges due to its long measurement times and low signal-to-noise ratio. We evaluate the use of Bayesian optimization—a family of sample-efficient, noise-tolerant, and global optimization methods—for quickly identifying near-optimal control parameters. To manage experimental complexity and provide comparisons against related work, we consider the task of minimizing metabolic cost by optimizing walking step frequencies in unaided human subjects. Compared to an existing approach based on gradient descent, Bayesian optimization identified a near-optimal step frequency with a faster time to convergence (12 minutes, p < 0.01), smaller inter-subject variability in convergence time (± 2 minutes, p < 0.01), and lower overall energy expenditure (p < 0.01). PMID:28926613
NASA Astrophysics Data System (ADS)
Fei, Chenxi; Liu, Hongxia; Wang, Xing; Fan, Xiaojiao
2015-04-01
The influence of processing parameters of aluminum oxide (Al2O3) and lanthanum oxide (La2O3) gate dielectric is investigated. Trimethylaluminum (TMA) and tris(isopropylcyclopentadienyl) lanthanum [La(iPrCp)3] were used as precursors separately, and H2O was used as oxidant. The ultra-thin La1 - x Al x O3 gate dielectric films are deposited on p-type silicon substrates by atom layer deposition (ALD) for different pulse ratios of precursors. Effects of different La/Al precursor pulse ratios on the physical properties and electrical characteristics of La1 - x Al x O3 films are studied. The preliminary testing results indicate that the increase of La precursor pulse can improve the characteristics of film, which has significant effects on the dielectric constant, equivalent oxide thickness (EOT), electrical properties, and stability of film.
Parameter uncertainties in the design and optimization of cantilever piezoelectric energy harvesters
NASA Astrophysics Data System (ADS)
Franco, V. R.; Varoto, P. S.
2017-09-01
A crucial issue in piezoelectric energy harvesting is the efficiency of the mechanical to electrical conversion process. Several techniques have been investigated in order to obtain a set of optimum design parameters that will lead to the best performance of the harvester in terms of electrical power generation. Once an optimum design is reached it is also important to consider uncertainties in the selected parameters that in turn can lead to loss of performance in the energy conversion process. The main goal of this paper is to perform a comprehensive discussion of the effects of multi-parameter aleatory uncertainties on the performance and design optimization of a given energy harvesting system. For that, a typical energy harvester consisting of a cantilever beam carrying a tip mass and partially covered by piezoelectric layers on top and bottom surfaces is considered. A distributed parameter electromechanical modal of the harvesting system is formulated and validated through experimental tests. First, the SQP (Sequential Quadratic Planning) optimization is employed to obtain an optimum set of parameters that will lead to best performance of the harvester. Second, once the optimum harvester configuration is found random perturbations are introduced in the key parameters and Monte Carlo simulations are performed to investigate how these uncertainties propagate and affect the performance of the device studied. Numerically simulated results indicate that small variations in some design parameters can cause a significant variation in the output electrical power, what strongly suggests that uncertainties must be accounted for in the design of beam energy harvesting systems.
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
Optimization of injection molding process parameters for a plastic cell phone housing component
NASA Astrophysics Data System (ADS)
Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya
2016-11-01
To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.
Parameter optimization for the visco-hyperelastic constitutive model of tendon using FEM.
Tang, C Y; Ng, G Y F; Wang, Z W; Tsui, C P; Zhang, G
2011-01-01
Numerous constitutive models describing the mechanical properties of tendons have been proposed during the past few decades. However, few were widely used owing to the lack of implementation in the general finite element (FE) software, and very few systematic studies have been done on selecting the most appropriate parameters for these constitutive laws. In this work, the visco-hyperelastic constitutive model of the tendon implemented through the use of three-parameter Mooney-Rivlin form and sixty-four-parameter Prony series were firstly analyzed using ANSYS FE software. Afterwards, an integrated optimization scheme was developed by coupling two optimization toolboxes (OPTs) of ANSYS and MATLAB for estimating these unknown constitutive parameters of the tendon. Finally, a group of Sprague-Dawley rat tendons was used to execute experimental and numerical simulation investigation. The simulated results showed good agreement with the experimental data. An important finding revealed that too many Maxwell elements was not necessary for assuring accuracy of the model, which is often neglected in most open literatures. Thus, all these proved that the constitutive parameter optimization scheme was reliable and highly efficient. Furthermore, the approach can be extended to study other tendons or ligaments, as well as any visco-hyperelastic solid materials.
Land cover classification using random forest with genetic algorithm-based parameter optimization
NASA Astrophysics Data System (ADS)
Ming, Dongping; Zhou, Tianning; Wang, Min; Tan, Tian
2016-07-01
Land cover classification based on remote sensing imagery is an important means to monitor, evaluate, and manage land resources. However, it requires robust classification methods that allow accurate mapping of complex land cover categories. Random forest (RF) is a powerful machine-learning classifier that can be used in land remote sensing. However, two important parameters of RF classification, namely, the number of trees and the number of variables tried at each split, affect classification accuracy. Thus, optimal parameter selection is an inevitable problem in RF-based image classification. This study uses the genetic algorithm (GA) to optimize the two parameters of RF to produce optimal land cover classification accuracy. HJ-1B CCD2 image data are used to classify six different land cover categories in Changping, Beijing, China. Experimental results show that GA-RF can avoid arbitrariness in the selection of parameters. The experiments also compare land cover classification results by using GA-RF method, traditional RF method (with default parameters), and support vector machine method. When the GA-RF method is used, classification accuracies, respectively, improved by 1.02% and 6.64%. The comparison results show that GA-RF is a feasible solution for land cover classification without compromising accuracy or incurring excessive time.
NASA Astrophysics Data System (ADS)
von Wilpert, Jason
2013-01-01
Iron pyrite (FeS2) is a promising material to act as the light absorbing layer in a thin film solar cell. This thesis focuses on the design and optimization of a chemical vapor deposition (CVD) chamber capable of depositing iron pyrite thin films by the reaction of iron acetylacetoneate and tert-butyl disulphide in argon at 300 °C at a base pressure ranging from 10 mTorr to 760 Torr. A custom, as-built 5" CVD system is first characterized by performing experiments attempting to deposit thin films of iron pyrite at a base pressure of 10 mTorr. After initial efforts are unsuccessful, a series of modifications are made to the system, and experiments at both low and atmospheric pressure are pursued. It is found that an external chamber for the iron acetylacetoneate precursor is necessary for better control over its vapor pressure, and that the growth rate must be slow to deposit homogeneous films. Optimal results at atmospheric pressure are achieved when the flow lines of the TBDS vapor, iron acetylacetoneate vapor, and argon carrier gas are combined prior to the deposition chamber.
NASA Astrophysics Data System (ADS)
Zhang, Chuan-Xin; Yuan, Yuan; Zhang, Hao-Wei; Shuai, Yong; Tan, He-Ping
2016-09-01
Considering features of stellar spectral radiation and sky surveys, we established a computational model for stellar effective temperatures, detected angular parameters and gray rates. Using known stellar flux data in some bands, we estimated stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization (SPSO). We first verified the reliability of SPSO, and then determined reasonable parameters that produced highly accurate estimates under certain gray deviation levels. Finally, we calculated 177 860 stellar effective temperatures and detected angular parameters using data from the Midcourse Space Experiment (MSX) catalog. These derived stellar effective temperatures were accurate when we compared them to known values from literatures. This research makes full use of catalog data and presents an original technique for studying stellar characteristics. It proposes a novel method for calculating stellar effective temperatures and detecting angular parameters, and provides theoretical and practical data for finding information about radiation in any band.
Effect of ablation parameters on infrared pulsed laser deposition of poly(ethylene glycol) films
NASA Astrophysics Data System (ADS)
Bubb, Daniel M.; Papantonakis, M. R.; Toftmann, B.; Horwitz, J. S.; McGill, R. A.; Chrisey, D. B.; Haglund, R. F., Jr.
2002-06-01
Polymer thin films were deposited by laser ablation using infrared radiation both resonant (2.90, 3.40, 3.45, and 8.96 mum) and nonresonant (3.30, 3.92, and 4.17 mum) with vibrational modes in the starting material, polyethylene glycol. The chemical structure of the films was characterized by Fourier transform infrared spectroscopy, while the molecular weight distribution was investigated using gel permeation chromatography. The films deposited by resonant irradiation are superior to those deposited with nonresonant radiation with respect to both the chemical structure and the molecular weight distribution of the films. However, the molecular-weight distributions of films deposited at nonresonant infrared wavelengths show marked polymer fragmentation. Fluence and wavelength dependence studies show that the effects may be related to the degree of thermal confinement, and hence to the relative absorption strengths of the targeted vibrational modes.
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.
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.
Theoretic aspects of the identification of the parameters in the optimal control model
NASA Technical Reports Server (NTRS)
Vanwijk, R. A.; Kok, J. J.
1977-01-01
The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.
Wang, Jun; Zhou, Bihua; Zhou, Shudao
2016-01-01
This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior. PMID:26880874
Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.
Yuan, Haidong; Fung, Chi-Hang Fred
2015-09-11
Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.
Development of a parameter optimization technique for the design of automatic control systems
NASA Technical Reports Server (NTRS)
Whitaker, P. H.
1977-01-01
Parameter optimization techniques for the design of linear automatic control systems that are applicable to both continuous and digital systems are described. The model performance index is used as the optimization criterion because of the physical insight that can be attached to it. The design emphasis is to start with the simplest system configuration that experience indicates would be practical. Design parameters are specified, and a digital computer program is used to select that set of parameter values which minimizes the performance index. The resulting design is examined, and complexity, through the use of more complex information processing or more feedback paths, is added only if performance fails to meet operational specifications. System performance specifications are assumed to be such that the desired step function time response of the system can be inferred.
NASA Astrophysics Data System (ADS)
Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.
2016-09-01
The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.
Optimal Feedback Scheme and Universal Time Scaling for Hamiltonian Parameter Estimation
NASA Astrophysics Data System (ADS)
Yuan, Haidong; Fung, Chi-Hang Fred
2015-09-01
Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.
NASA Technical Reports Server (NTRS)
Stahara, S. S.
1984-01-01
An investigation was carried out to complete the preliminary development of a combined perturbation/optimization procedure and associated computational code for designing optimized blade-to-blade profiles of turbomachinery blades. The overall purpose of the procedures developed is to provide demonstration of a rapid nonlinear perturbation method for minimizing the computational requirements associated with parametric design studies of turbomachinery flows. The method combines the multiple parameter nonlinear perturbation method, successfully developed in previous phases of this study, with the NASA TSONIC blade-to-blade turbomachinery flow solver, and the COPES-CONMIN optimization procedure into a user's code for designing optimized blade-to-blade surface profiles of turbomachinery blades. Results of several design applications and a documented version of the code together with a user's manual are provided.
Optimization of marine biogeochemial parameters against climatologies of nutrients and oxygen
NASA Astrophysics Data System (ADS)
Kriest, Iris; Khatiwala, Samar; Sauerland, Volkmar; Oschlies, Andreas
2017-04-01
Global biogeochemical ocean models usually contain a variety of different biogeochemical components, which are described by many parameters. The values of many of these parameters are empirically difficult to constrain, due to the fact that in the models they represent processes for different groups of organisms. Therefore, these models are subject to a high level of parametric uncertainty. This may be of consequence for their skill with respect to accurately describing the relevant features of the present ocean, as well as their sensitivity to possible environmental changes. We here present a framework for the optimization of global biogeochemical ocean models on short and long time scales. The framework combines an offline approach for transport of biogeochemical tracers with an Estimation of Distribution Algorithm, a type of evolutionary algorithm in which the probability distribution is parameterized. We explore the performance and capability of this framework by optimizations of different biogeochemical parameters against different data sets. Optimization of six parameters, mostly tied to the surface biogeochemical processes, against a climatology of observations of annual mean dissolved nutrients and oxygen, reveals that parameters, that act on large spatial and temporal scales are determined earliest, and with the least spread. Parameters more closely tied to surface biology, which act on shorter time scales, are more difficult to determine. Encouragingly, optimized models show a better fit to estimates of global mean biogeochemical fluxes such as production, export, and grazing, although these fluxes did not enter the misfit function. We finally investigate if, and to what extent, we can achieve an equally good fit to observed tracer fields with a model of strongly reduced biogeochemical complexity.
An improved swarm optimization for parameter estimation and biological model selection.
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This
An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This
NASA Astrophysics Data System (ADS)
Janardhanan, S.; Datta, B.
2011-12-01
Surrogate models are widely used to develop computationally efficient simulation-optimization models to solve complex groundwater management problems. Artificial intelligence based models are most often used for this purpose where they are trained using predictor-predictand data obtained from a numerical simulation model. Most often this is implemented with the assumption that the parameters and boundary conditions used in the numerical simulation model are perfectly known. However, in most practical situations these values are uncertain. Under these circumstances the application of such approximation surrogates becomes limited. In our study we develop a surrogate model based coupled simulation optimization methodology for determining optimal pumping strategies for coastal aquifers considering parameter uncertainty. An ensemble surrogate modeling approach is used along with multiple realization optimization. The methodology is used to solve a multi-objective coastal aquifer management problem considering two conflicting objectives. Hydraulic conductivity and the aquifer recharge are considered as uncertain values. Three dimensional coupled flow and transport simulation model FEMWATER is used to simulate the aquifer responses for a number of scenarios corresponding to Latin hypercube samples of pumping and uncertain parameters to generate input-output patterns for training the surrogate models. Non-parametric bootstrap sampling of this original data set is used to generate multiple data sets which belong to different regions in the multi-dimensional decision and parameter space. These data sets are used to train and test multiple surrogate models based on genetic programming. The ensemble of surrogate models is then linked to a multi-objective genetic algorithm to solve the pumping optimization problem. Two conflicting objectives, viz, maximizing total pumping from beneficial wells and minimizing the total pumping from barrier wells for hydraulic control of
NASA Astrophysics Data System (ADS)
Rogers, Adam
2012-01-01
Strong gravitational lensing produces multiple distorted images of a background source when it is closely aligned with a mass distribution along the line of sight. The lensed images provide constraints on the parameters of a model of the lens, and the images themselves can be inverted providing a model of the source. Both of these aspects of lensing are extremely valuable, as lensing depends on the total matter distribution, both luminous and dark. Furthermore, lensed sources are commonly located at cosmological distances and are magnified by the lensing effect. This provides a chance to image sources that would be unobservable when viewed with conventional optics. The semilinear method expresses the source modeling step as a least-squares problem for a given set of lens model parameters. The blurring effect due to the point spread function of the instrument used to observe the lensed images is also taken into account. In general, regularization is needed to solve the source deconvolution problem. We use Krylov subspace methods to solve for the pixelated sources. These optimization techniques, such as the Conjugate Gradient method, provide natural regularizing effects from simple truncated iteration. Using these routines, we are able to avoid the explicit construction of the lens and blurring matrices and solve the least squares source optimization problem iteratively. We explore several regularization parameter selection methods commonly used in standard image deconvolution problems, which lead to previously derived expressions for the number of source degrees of freedom. The parameters that describe the lens density distribution are found by global optimization methods including genetic algorithms and particle swarm optimizers. In general, global optimizers are useful in non-linear optimization problems such as lens modeling due to their parameter space mapping capabilities. However, these optimization methods require many function evaluations and iterative
Cho, Ming-Yuan; Hoang, Thi Thom
2017-01-01
Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.
2017-01-01
Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method. PMID:28781591
Caglar, Yasemin; Gorgun, Kamuran; Aksoy, Seval
2015-03-05
ZnO nanopowders were synthesized via microwave-assisted hydrothermal method at different deposition (microwave irradiation) times and pH values. The effects of pH and deposition (microwave irradiation) time on the crystalline structure and orientation of the ZnO nanopowders have been investigated by X-ray diffraction (XRD) study. XRD observations showed that the crystalline quality of ZnO nanopowders increased with increasing pH value. The crystallite size and texture coefficient values of ZnO nanopowders were calculated. The structural quality of ZnO nanopowder was improved by deposition parameters. Field emission scanning electron microscope (FESEM) was used to analyze the surface morphology of the ZnO nanopowders. Microwave irradiation time and pH value showed a significant effect on the surface morphology.
NASA Astrophysics Data System (ADS)
Caglar, Yasemin; Gorgun, Kamuran; Aksoy, Seval
2015-03-01
ZnO nanopowders were synthesized via microwave-assisted hydrothermal method at different deposition (microwave irradiation) times and pH values. The effects of pH and deposition (microwave irradiation) time on the crystalline structure and orientation of the ZnO nanopowders have been investigated by X-ray diffraction (XRD) study. XRD observations showed that the crystalline quality of ZnO nanopowders increased with increasing pH value. The crystallite size and texture coefficient values of ZnO nanopowders were calculated. The structural quality of ZnO nanopowder was improved by deposition parameters. Field emission scanning electron microscope (FESEM) was used to analyze the surface morphology of the ZnO nanopowders. Microwave irradiation time and pH value showed a significant effect on the surface morphology.
NASA Astrophysics Data System (ADS)
Andronico, Daniele; Scollo, Simona; Cristaldi, Antonio; Lo Castro, Maria Deborah
2014-10-01
The Southeast Crater (SEC) of Mt. Etna, Italy, is renowned for its high activity, mainly long-lived eruptions consisting of sequences of individual paroxysmal episodes which have produced more than 150 eruptive events since 1998. Each episode typically forms eruption columns followed by tephra fallout over distances of up to about 100 km from the vent. One of the last sequences consisted of 25 lava fountaining events, which took place between January 2011 and April 2012 from a pit-vent on the eastern flank of the SEC and built a new scoria cone renamed New Southeast Crater. The first episode on 12-13 January 2011 produced tephra fallout which was unusually dispersed toward to the South extending out over the Mediterranean Sea. The southerly deposition of tephra permitted an extensive survey at distances between ~1 and ~100 km, providing an excellent characterization of the tephra deposit. Here, we document the stratigraphy of the 12-13 January fallout deposit, draw its dispersal, and reconstruct its isopleth map. These data are then used to estimate the main eruption source parameters. The total erupted mass (TEM) was calculated by using four different methodologies which give a mean value of 1.5 ± 0.4 × 108 kg. The mass eruption rate (MER) is 2.5 ± 0.7 × 104 kg/s using eruption duration of 100 min. The total grain-size (TGS) distribution, peaked at -3 phi, ranges between -5 and 5 phi and has a median value of -1.4 phi. Further, for the eruption column height, we obtained respective values of 6.8-13.8 km by using the method of Carey and Sparks (1986) and 3.4 ± 0.3 km by using the methods of Wilson and Walker 1987), Mastin et al. (2009), and Pistolesi et al. (2011) and considering the mean value of MER from the deposit. We also evaluated the uncertainty and reliability of TEM and TGS for scenarios where the proximal and distal samples are not obtainable. This is achieved by only using a sector spanning the downwind distances between 6 and 23 km. This scenario
Fiedler, Anna; Raeth, Sebastian; Theis, Fabian J; Hausser, Angelika; Hasenauer, Jan
2016-08-22
Ordinary differential equation (ODE) models are widely used to describe (bio-)chemical and biological processes. To enhance the predictive power of these models, their unknown parameters are estimated from experimental data. These experimental data are mostly collected in perturbation experiments, in which the processes are pushed out of steady state by applying a stimulus. The information that the initial condition is a steady state of the unperturbed process provides valuable information, as it restricts the dynamics of the process and thereby the parameters. However, implementing steady-state constraints in the optimization often results in convergence problems. In this manuscript, we propose two new methods for solving optimization problems with steady-state constraints. The first method exploits ideas from optimization algorithms on manifolds and introduces a retraction operator, essentially reducing the dimension of the optimization problem. The second method is based on the continuous analogue of the optimization problem. This continuous analogue is an ODE whose equilibrium points are the optima of the constrained optimization problem. This equivalence enables the use of adaptive numerical methods for solving optimization problems with steady-state constraints. Both methods are tailored to the problem structure and exploit the local geometry of the steady-state manifold and its stability properties. A parameterization of the steady-state manifold is not required. The efficiency and reliability of the proposed methods is evaluated using one toy example and two applications. The first application example uses published data while the second uses a novel dataset for Raf/MEK/ERK signaling. The proposed methods demonstrated better convergence properties than state-of-the-art methods employed in systems and computational biology. Furthermore, the average computation time per converged start is significantly lower. In addition to the theoretical results, the
NASA Astrophysics Data System (ADS)
Rahman, Md Ashiqur; Anwar, Sohel; Izadian, Afshin
2016-03-01
In this paper, a gradient-free optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized to identify specific parameters of the electrochemical model of a Lithium-Ion battery with LiCoO2 cathode chemistry. Battery electrochemical model parameters are subject to change under severe or abusive operating conditions resulting in, for example, over-discharged battery, over-charged battery, etc. It is important for a battery management system to have these parameter changes fully captured in a bank of battery models that can be used to monitor battery conditions in real time. Here the PSO methodology has been successfully applied to identify four electrochemical model parameters that exhibit significant variations under severe operating conditions: solid phase diffusion coefficient at the positive electrode (cathode), solid phase diffusion coefficient at the negative electrode (anode), intercalation/de-intercalation reaction rate at the cathode, and intercalation/de-intercalation reaction rate at the anode. The identified model parameters were used to generate the respective battery models for both healthy and degraded batteries. These models were then validated by comparing the model output voltage with the experimental output voltage for the stated operating conditions. The identified Li-Ion battery electrochemical model parameters are within reasonable accuracy as evidenced by the experimental validation results.
Optimization of bone drilling parameters using Taguchi method based on finite element analysis
NASA Astrophysics Data System (ADS)
Rosidi, Ayip; Lenggo Ginta, Turnad; Rani, Ahmad Majdi Bin Abdul
2017-05-01
Thermal necrosis results fracture problems and implant failure if temperature exceeds 47 °C for one minute during bone drilling. To solve this problem, this work studied a new thermal model by using three drilling parameters: drill diameter, feed rate and spindle speed. Effects of those parameters to heat generation were studied. The drill diameters were 4 mm, 6 mm and 6 mm; the feed rates were 80 mm/min, 100 mm/min and 120 mm/min whereas the spindle speeds were 400 rpm, 500 rpm and 600 rpm then an optimization was done by Taguchi method to which combination parameter can be used to prevent thermal necrosis during bone drilling. The results showed that all the combination of parameters produce confidence results which were below 47 °C and finite element analysis combined with Taguchi method can be used for predicting temperature generation and optimizing bone drilling parameters prior to clinical bone drilling. All of the combination parameters can be used for surgeon to achieve sustainable orthopaedic surgery.
Estimation of optimal dispersion model source parameters using satellite detections of volcanic ash
NASA Astrophysics Data System (ADS)
Zidikheri, Meelis J.; Lucas, Christopher; Potts, Rodney J.
2017-08-01
In this paper we demonstrate how parameters describing the geometry of the volcanic ash source for a particular volcanic ash dispersion model (Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT)) may be inferred by the use of satellite data and multiple trial simulations. The areas of space likely to be contaminated by ash are identified with the aid of various remote sensing techniques, and polygons are drawn around these areas as they would be in an operational setting. Dispersion model simulations are initialized by either a cylindrical source or a specified ash distribution depending on the context. Parameters of interest such as the base and top height, diameter, and optimal release time of the cylindrical source or the height of the specified ash distribution are inferred by forming a parameter grid and running multiple simulations for each parameter grid point value. Optimal values of the parameter values are identified by calculating spatial correlations between the model simulations and observations. We demonstrate that the methodology can be used to correctly infer various model parameters and improve volcanic ash forecasts in various eruption case studies.
NASA Astrophysics Data System (ADS)
Schmidt, S.; Hänninen, T.; Wissting, J.; Hultman, L.; Goebbels, N.; Santana, A.; Tobler, M.; Högberg, H.
2017-05-01
The residual coating stress and its control is of key importance for the performance and reliability of silicon nitride (SiNx) coatings for biomedical applications. This study explores the most important deposition process parameters to tailor the residual coating stress and hence improve the adhesion of SiNx coatings deposited by reactive high power impulse magnetron sputtering (rHiPIMS). Reactive sputter deposition and plasma characterization were conducted in an industrial deposition chamber equipped with pure Si targets in N2/Ar ambient. Reactive HiPIMS processes using N2-to-Ar flow ratios of 0 and 0.28-0.3 were studied with time averaged positive ion mass spectrometry. The coatings were deposited to thicknesses of 2 μm on Si(001) and to 5 μm on polished CoCrMo disks. The residual stress of the X-ray amorphous coatings was determined from the curvature of the Si substrates as obtained by X-ray diffraction. The coatings were further characterized by X-ray photoelectron spectroscopy, scanning electron microscopy, and nanoindentation in order to study their elemental composition, morphology, and hardness, respectively. The adhesion of the 5 μm thick coatings deposited on CoCrMo disks was assessed using the Rockwell C test. The deposition of SiNx coatings by rHiPIMS using N2-to-Ar flow ratios of 0.28 yield dense and hard SiNx coatings with Si/N ratios <1. The compressive residual stress of up to 2.1 GPa can be reduced to 0.2 GPa using a comparatively high deposition pressure of 600 mPa, substrate temperatures below 200 °C, low pulse energies of <2.5 Ws, and moderate negative bias voltages of up to 100 V. These process parameters resulted in excellent coating adhesion (ISO 0, HF1) and a low surface roughness of 14 nm for coatings deposited on CoCrMo.
Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng
2012-12-01
This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.
Modeling Network Intrusion Detection System Using Feature Selection and Parameters Optimization
NASA Astrophysics Data System (ADS)
Kim, Dong Seong; Park, Jong Sou
Previous approaches for modeling Intrusion Detection System (IDS) have been on twofold: improving detection model(s) in terms of (i) feature selection of audit data through wrapper and filter methods and (ii) parameters optimization of detection model design, based on classification, clustering algorithms, etc. In this paper, we present three approaches to model IDS in the context of feature selection and parameters optimization: First, we present Fusion of Genetic Algorithm (GA) and Support Vector Machines (SVM) (FuGAS), which employs combinations of GA and SVM through genetic operation and it is capable of building an optimal detection model with only selected important features and optimal parameters value. Second, we present Correlation-based Hybrid Feature Selection (CoHyFS), which utilizes a filter method in conjunction of GA for feature selection in order to reduce long training time. Third, we present Simultaneous Intrinsic Model Identification (SIMI), which adopts Random Forest (RF) and shows better intrusion detection rates and feature selection results, along with no additional computational overheads. We show the experimental results and analysis of three approaches on KDD 1999 intrusion detection datasets.
Zeng, Rongping; Badano, Aldo; Myers, Kyle J
2017-04-07
We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hotelling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre-Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.
NASA Astrophysics Data System (ADS)
Zeng, Rongping; Badano, Aldo; Myers, Kyle J.
2017-04-01
We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hotelling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre-Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.
NASA Technical Reports Server (NTRS)
Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian
1992-01-01
A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.
NASA Technical Reports Server (NTRS)
Schmidt, Phillip H.; Garg, Sanjay; Holowecky, Brian R.
1993-01-01
A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.
Mohmad Kahar, Mohd Nizam; Noraziah, A.
2017-01-01
In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system’s gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics. PMID:28441390
Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo
2011-10-11
We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and
2011-01-01
Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These
Optimal likelihood-based matching of volcanic sources and deposits in the Auckland Volcanic Field
NASA Astrophysics Data System (ADS)
Kawabata, Emily; Bebbington, Mark S.; Cronin, Shane J.; Wang, Ting
2016-09-01
In monogenetic volcanic fields, where each eruption forms a new volcano, focusing and migration of activity over time is a very real possibility. In order for hazard estimates to reflect future, rather than past, behavior, it is vital to assemble as much reliable age data as possible on past eruptions. Multiple swamp/lake records have been extracted from the Auckland Volcanic Field, underlying the 1.4 million-population city of Auckland. We examine here the problem of matching these dated deposits to the volcanoes that produced them. The simplest issue is separation in time, which is handled by simulating prior volcano age sequences from direct dates where known, thinned via ordering constraints between the volcanoes. The subproblem of varying deposition thicknesses (which may be zero) at five locations of known distance and azimuth is quantified using a statistical attenuation model for the volcanic ash thickness. These elements are combined with other constraints, from widespread fingerprinted ash layers that separate eruptions and time-censoring of the records, into a likelihood that was optimized via linear programming. A second linear program was used to optimize over the Monte-Carlo simulated set of prior age profiles to determine the best overall match and consequent volcano age assignments. Considering all 20 matches, and the multiple factors of age, direction, and size/distance simultaneously, results in some non-intuitive assignments which would not be produced by single factor analyses. Compared with earlier work, the results provide better age control on a number of smaller centers such as Little Rangitoto, Otuataua, Taylors Hill, Wiri Mountain, Green Hill, Otara Hill, Hampton Park and Mt Cambria. Spatio-temporal hazard estimates are updated on the basis of the new ordering, which suggest that the scale of the 'flare-up' around 30 ka, while still highly significant, was less than previously thought.
Raj, A. Moses Ezhil; Ravidhas, C.; Ravishankar, R.; Kumar, A. Rathish; Selvan, G.; Jayachandran, M.; Sanjeeviraja, C.
2009-05-06
Transparent conducting magnesium indium oxide films (MgIn{sub 2}O{sub 4}) were deposited on to quartz substrates without a buffer layer at an optimized deposition temperature of 450 deg. C to achieve high transmittance in the visible spectral range and electrical conductivity in the low temperature region. Magnesium ions are distributed over the tetrahedral and octahedral sites of the inverted spinel structure with preferential orientation along (3 1 1) Miller plane. The possible mechanism that promotes conductivity in this system is the charge transfer between the resident divalent (Mg{sup 2+}) and trivalent (In{sup 3+}) cations in addition to the available oxygen vacancies in the lattice. A room temperature electrical conductivity of 1.5 x 10{sup -5} S cm{sup -1} and an average transmittance >75% have been achieved. Hall measurements showed n-type conductivity with electron mobility value 0.95 x 10{sup -2} cm{sup 2} V{sup -1} s{sup -1} and carrier concentration 2.7 x 10{sup 19} cm{sup -3}. Smoothness of the film surface observed through atomic force microscope measurements favors this material for gas sensing and opto-electronic device development.
Matheny, Michael E.; Resnic, Frederic S.; Arora, Nipun; Ohno-Machado, Lucila
2007-01-01
Support Vector Machines (SVM) have become popular among machine learning researchers, but their applications in biomedicine have been somewhat limited. A number of methods, such as grid search and evolutionary algorithms, have been utilized to optimize model parameters of SVMs. The sensitivity of the results to changes in optimization methods has not been investigated in the context of medical applications. In this study, radial-basis kernel SVM and polynomial kernel SVM mortality prediction models for percutaneous coronary interventions were optimized using (a) Mean Squared Error, (b) Mean Cross-Entropy Error, (c) the Area Under the Receiver Operating Characteristic, and (d) the Hosmer-Lemeshow goodness-of-fit test (HL χ2). A 3-fold cross-validation inner and outer loop method was used to select the best models using the training data, and evaluations were based on previously unseen test data. The results were compared to those produced by logistic regression models optimized using the same indices. The choice of optimization parameters had a significant impact on performance in both SVM kernel types. PMID:17600771
Matheny, Michael E; Resnic, Frederic S; Arora, Nipun; Ohno-Machado, Lucila
2007-12-01
Support vector machines (SVM) have become popular among machine learning researchers, but their applications in biomedicine have been somewhat limited. A number of methods, such as grid search and evolutionary algorithms, have been utilized to optimize model parameters of SVMs. The sensitivity of the results to changes in optimization methods has not been investigated in the context of medical applications. In this study, radial-basis kernel SVM and polynomial kernel SVM mortality prediction models for percutaneous coronary interventions were optimized using (a) mean-squared error, (b) mean cross-entropy error, (c) the area under the receiver operating characteristic, and (d) the Hosmer-Lemeshow goodness-of-fit test (HL chi(2)). A threefold cross-validation inner and outer loop method was used to select the best models using the training data, and evaluations were based on previously unseen test data. The results were compared to those produced by logistic regression models optimized using the same indices. The choice of optimization parameters had a significant impact on performance in both SVM kernel types.
Sun, Jun; Fang, Wei; Wu, Xiaojun; Palade, Vasile; Xu, Wenbo
2012-01-01
Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little analysis on how it works in detail. This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms of probability measure. Since the particle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of the theoretical analysis is to find out the upper bound of the CE coefficient, within which the value of the CE coefficient selected can guarantee the convergence or boundedness of the particle's position. In the experimental analysis, the theoretical results are first validated by stochastic simulations for the particle's behavior. Then, based on the derived upper bound of the CE coefficient, we perform empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient, in order to obtain generally good algorithmic performance in real world applications. Finally, a further performance comparison between QPSO and other variants of PSO on the benchmarks is made to show the efficiency of the QPSO algorithm with the proposed parameter control and selection methods.
Mishra, Gayatri; Joshi, Dinesh C; Mohapatra, Debabandya
2015-12-01
Sorghum is a popular healthy snack food. Popped sorghum was prepared in a domestic microwave oven. A 3 factor 3 level Box and Behneken design was used to optimize the pretreatment conditions. Grains were preconditioned to 12-20 % moisture content by the addition of 0-2 % salt solutions. Oil was applied (0-10 % w/w) to the preconditioned grains. Optimization of the pretreatments was based on popping yield, volume expansion ratio, and sensory score. The optimized condition was found at 16.62 % (wb), 0.55 % salt and 10 % oil with popping yield of 82.228 %, volume expansion ratio of 14.564 and overall acceptability of 8.495. Further, the microwave process parameters were optimized using a 2 factor 3 level design having microwave power density ranging from 9 to 18 W/g and residence time ranging from 100 to 180 s. For the production of superior quality pop sorghum, the optimized microwave process parameters were microwave power density of 18 Wg(-1) and residence time of 140 s.
Determination of full piezoelectric complex parameters using gradient-based optimization algorithm
NASA Astrophysics Data System (ADS)
Kiyono, C. Y.; Pérez, N.; Silva, E. C. N.
2016-02-01
At present, numerical techniques allow the precise simulation of mechanical structures, but the results are limited by the knowledge of the material properties. In the case of piezoelectric ceramics, the full model determination in the linear range involves five elastic, three piezoelectric, and two dielectric complex parameters. A successful solution to obtaining piezoceramic properties consists of comparing the experimental measurement of the impedance curve and the results of a numerical model by using the finite element method (FEM). In the present work, a new systematic optimization method is proposed to adjust the full piezoelectric complex parameters in the FEM model. Once implemented, the method only requires the experimental data (impedance modulus and phase data acquired by an impedometer), material density, geometry, and initial values for the properties. This method combines a FEM routine implemented using an 8-noded axisymmetric element with a gradient-based optimization routine based on the method of moving asymptotes (MMA). The main objective of the optimization procedure is minimizing the quadratic difference between the experimental and numerical electrical conductance and resistance curves (to consider resonance and antiresonance frequencies). To assure the convergence of the optimization procedure, this work proposes restarting the optimization loop whenever the procedure ends in an undesired or an unfeasible solution. Two experimental examples using PZ27 and APC850 samples are presented to test the precision of the method and to check the dependency of the frequency range used, respectively.
NASA Astrophysics Data System (ADS)
Basak, Amrita; Acharya, Ranadip; Das, Suman
2016-08-01
This paper focuses on additive manufacturing (AM) of single-crystal (SX) nickel-based superalloy CMSX-4 through scanning laser epitaxy (SLE). SLE, a powder bed fusion-based AM process was explored for the purpose of producing crack-free, dense deposits of CMSX-4 on top of similar chemistry investment-cast substrates. Optical microscopy and scanning electron microscopy (SEM) investigations revealed the presence of dendritic microstructures that consisted of fine γ' precipitates within the γ matrix in the deposit region. Computational fluid dynamics (CFD)-based process modeling, statistical design of experiments (DoE), and microstructural characterization techniques were combined to produce metallurgically bonded single-crystal deposits of more than 500 μm height in a single pass along the entire length of the substrate. A customized quantitative metallography based image analysis technique was employed for automatic extraction of various deposit quality metrics from the digital cross-sectional micrographs. The processing parameters were varied, and optimal processing windows were identified to obtain good quality deposits. The results reported here represent one of the few successes obtained in producing single-crystal epitaxial deposits through a powder bed fusion-based metal AM process and thus demonstrate the potential of SLE to repair and manufacture single-crystal hot section components of gas turbine systems from nickel-based superalloy powders.
NASA Astrophysics Data System (ADS)
Oby, Emily R.; Perel, Sagi; Sadtler, Patrick T.; Ruff, Douglas A.; Mischel, Jessica L.; Montez, David F.; Cohen, Marlene R.; Batista, Aaron P.; Chase, Steven M.
2016-06-01
Objective. A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach. We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent
Deka, Deepmoni; Das, Saprativ P.; Sahoo, Naresh; Das, Debasish; Jawed, Mohammad; Goyal, Dinesh
2013-01-01
Effect of physical parameters such as initial pH, agitation (rpm), and temperature (°C) for cellulase production from Bacillus subtilis AS3 was investigated. Central composite design of experiments followed by multiple desirability function was applied for the optimization of cellulase activity and cell growth. The effect of the temperature and agitation was found to be significant among the three independent variables. The optimum levels of initial pH, temperature, and agitation for alkaline carboxymethylcellulase (CMCase) production predicted by the model were 7.2, 39°C, and 121 rpm, respectively. The CMCase activity with unoptimized physical parameters and previously optimized medium composition was 0.43 U/mL. The maximum activity (0.56 U/mL) and cell growth (2.01 mg/mL) predicted by the model were in consensus with values (0.57 U/mL, 2.1 mg/mL) obtained using optimized medium and optimal values of physical parameters. After optimization, 33% enhancement in CMCase activity (0.57 U/mL) was recorded. On scale-up of cellulase production process in bioreactor with all the optimized conditions, an activity of 0.75 U/mL was achieved. Consequently, the bacterial cellulase employed for bioethanol production expending (5%, w/v) NaOH-pretreated wild grass with Zymomonas mobilis yielded an utmost ethanol titre of 7.56 g/L and 11.65 g/L at shake flask and bioreactor level, respectively. PMID:25937985
An Approach to Optimize Size Parameters of Forging by Combining Hot-Processing Map and FEM
NASA Astrophysics Data System (ADS)
Hu, H. E.; Wang, X. Y.; Deng, L.
2014-11-01
The size parameters of 6061 aluminum alloy rib-web forging were optimized by using hot-processing map and finite element method (FEM) based on high-temperature compression data. The results show that the stress level of the alloy can be represented by a Zener-Holloman parameter in a hyperbolic sine-type equation with the hot deformation activation energy of 343.7 kJ/mol. Dynamic recovery and dynamic recrystallization concurrently preceded during high-temperature deformation of the alloy. Optimal hot-processing parameters for the alloy corresponding to the peak value of 0.42 are 753 K and 0.001 s-1. The instability domain occurs at deformation temperature lower than 653 K. FEM is an available method to validate hot-processing map in actual manufacture by analyzing the effect of corner radius, rib width, and web thickness on workability of rib-web forging of the alloy. Size parameters of die forgings can be optimized conveniently by combining hot-processing map and FEM.
Yang, Anxiong; Stingl, Michael; Berry, David A.; Lohscheller, Jörg; Voigt, Daniel; Eysholdt, Ulrich; Döllinger, Michael
2011-01-01
With the use of an endoscopic, high-speed camera, vocal fold dynamics may be observed clinically during phonation. However, observation and subjective judgment alone may be insufficient for clinical diagnosis and documentation of improved vocal function, especially when the laryngeal disease lacks any clear morphological presentation. In this study, biomechanical parameters of the vocal folds are computed by adjusting the corresponding parameters of a three-dimensional model until the dynamics of both systems are similar. First, a mathematical optimization method is presented. Next, model parameters (such as pressure, tension and masses) are adjusted to reproduce vocal fold dynamics, and the deduced parameters are physiologically interpreted. Various combinations of global and local optimization techniques are attempted. Evaluation of the optimization procedure is performed using 50 synthetically generated data sets. The results show sufficient reliability, including 0.07 normalized error, 96% correlation, and 91% accuracy. The technique is also demonstrated on data from human hemilarynx experiments, in which a low normalized error (0.16) and high correlation (84%) values were achieved. In the future, this technique may be applied to clinical high-speed images, yielding objective measures with which to document improved vocal function of patients with voice disorders. PMID:21877808
Optimizing physical parameters in 1-D particle-in-cell simulations with Python
NASA Astrophysics Data System (ADS)
Ragan-Kelley, Benjamin; Verboncoeur, John P.; Lin, Ming-Chieh
2014-10-01
A particle-in-cell (PIC) simulation tool, OOPD1, is wrapped in the Python programming language, enabling automated algorithmic optimization of physical and numerical parameters. The Python-based environment exposes internal variables, enabling modification of simulation parameters, as well as run-time generation of new diagnostics based on calculations with internal data. For problems requiring an iterative optimization approach, this enables a programmable interactive feedback loop style simulation model, where the input to one simulation is a programmable function of the output of the previous one. This approach is applied to field-emission of electrons in a diode, in order to explore space charge effects in bipolar flow. We find an analytical solution for maximizing the space-charge limited current through a diode with an upstream ion current, and confirm the result with simulations, demonstrating the efficacy of the feedback scheme. We also demonstrate and analyze a modeling approach for scaling the ion mass, which can shorten simulation time without changing the ultimate result. The methods presented can be generalized to handle other applications where it is desirable to evolve simulation parameters based on algorithmic results from the simulation, including models in which physical or numerical parameter tuning is used to converge or optimize a system in one or more variables.
NASA Astrophysics Data System (ADS)
Cardiff, M. A.; Kitanidis, P. K.
2005-12-01
In this presentation we revisit the problem of semivariogram estimation and present a modular, reusable, and encapsulated set of MATLAB programs that use a hybrid Ant Colony Optimization (ACO) heuristic to solve the "optimal fit" problem. Though the ACO heuristic involves a stochastic component, advantages of the heuristic over traditional gradient-search methods, like the Gauss-Newton method, include the ability to estimate model semivariogram parameters accurately without initial guesses input by the user. The ACO heuristic is also superiorly suited for strongly nonlinear optimization over spaces that may contain several local minima. The presentation will focus on the application of ACO to existing weighted least squares and restricted maximum likelihood estimation methods with a comparison of results. The presentation will also discuss parameter uncertainty, particularly in the context of restricted maximum likelihood and Bayesian methods. We compare the local linearized parameter estimates (or Cramer-Rao lower bounds) with modern Monte Carlo methods, such as acceptance-rejection. Finally, we present ensemble kriging in which conditional realizations are generated in a way that uncertainty in semi-variogram parameters is fully accounted for. Results for a variety of sample problems will be presented along with a discussion of solution accuracy and computational efficiency.
Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1993-01-01
The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.
Kane, David B; Asgharian, Bahman; Price, Owen T; Rostami, Ali; Oldham, Michael J
2010-02-01
It is known that puffing conditions such as puff volume, duration, and frequency vary substantially among individual smokers. This study investigates how these parameters affect the particle size distribution and concentration of fresh mainstream cigarette smoke (MCS) and how these changes affect the predicted deposition of MCS particles in a model human respiratory tract. Measurements of the particle size distribution made with an electrical low pressure impactor for a variety of puffing conditions are presented. The average flow rate of the puff is found to be the major factor effecting the measured particle size distribution of the MCS. The results of these measurements were then used as input to a deterministic dosimetry model (MPPD) to estimate the changes in the respiratory tract deposition fraction of smoke particles. The MPPD dosimetry model was modified by incorporating mechanisms involved in respiratory tract deposition of MCS: hygroscopic growth, coagulation, evaporation of semivolatiles, and mixing of the smoke with inhaled dilution air. The addition of these mechanisms to MPPD resulted in reasonable agreement between predicted airway deposition and human smoke retention measurements. The modified MPPD model predicts a modest 10% drop in the total deposition efficiency in a model human respiratory tract as the puff flow rate is increased from 1050 to 3100 ml/min, for a 2-s puff.
Algorithms of D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters
NASA Astrophysics Data System (ADS)
Widiharih, Tatik; Haryatmi, Sri; Gunardi, Wilandari, Yuciana
2016-02-01
Morgan Mercer Flodin (MMF) model is used in many areas including biological growth studies, animal and husbandry, chemistry, finance, pharmacokinetics and pharmacodynamics. Locally D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters are investigated. We used the Generalized Equivalence Theorem of Kiefer and Wolvowitz to determine D-optimality criteria. Number of roots for standardized variance are determined using Tchebysheff system concept and it is used to decide that the design is minimally supported design. In these models, designs are minimally supported designs with uniform weight on its support, and the upper bound of the design region is a support point.
Optimal input design for aircraft parameter estimation using dynamic programming principles
NASA Technical Reports Server (NTRS)
Klein, Vladislav; Morelli, Eugene A.
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Optimal input design for aircraft parameter estimation using dynamic programming principles
NASA Technical Reports Server (NTRS)
Klein, Vladislav; Morelli, Eugene A.
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Sankaran, Sethuraman; Humphrey, Jay D.; Marsden, Alison L.
2013-01-01
Computational models for vascular growth and remodeling (G&R) are used to predict the long-term response of vessels to changes in pressure, flow, and other mechanical loading conditions. Accurate predictions of these responses are essential for understanding numerous disease processes. Such models require reliable inputs of numerous parameters, including material properties and growth rates, which are often experimentally derived, and inherently uncertain. While earlier methods have used a brute force approach, systematic uncertainty quantification in G&R models promises to provide much better information. In this work, we introduce an efficient framework for uncertainty quantification and optimal parameter selection, and illustrate it via several examples. First, an adaptive sparse grid stochastic collocation scheme is implemented in an established G&R solver to quantify parameter sensitivities, and near-linear scaling with the number of parameters is demonstrated. This non-intrusive and parallelizable algorithm is compared with standard sampling algorithms such as Monte-Carlo. Second, we determine optimal arterial wall material properties by applying robust optimization. We couple the G&R simulator with an adaptive sparse grid collocation approach and a derivative-free optimization algorithm. We show that an artery can achieve optimal homeostatic conditions over a range of alterations in pressure and flow; robustness of the solution is enforced by including uncertainty in loading conditions in the objective function. We then show that homeostatic intramural and wall shear stress is maintained for a wide range of material properties, though the time it takes to achieve this state varies. We also show that the intramural stress is robust and lies within 5% of its mean value for realistic variability of the material parameters. We observe that prestretch of elastin and collagen are most critical to maintaining homeostasis, while values of the material properties are
NASA Astrophysics Data System (ADS)
Reimer, Joscha; Piwonski, Jaroslaw; Slawig, Thomas
2016-04-01
The statistical significance of any model-data comparison strongly depends on the quality of the used data and the criterion used to measure the model-to-data misfit. The statistical properties (such as mean values, variances and covariances) of the data should be taken into account by choosing a criterion as, e.g., ordinary, weighted or generalized least squares. Moreover, the criterion can be restricted onto regions or model quantities which are of special interest. This choice influences the quality of the model output (also for not measured quantities) and the results of a parameter estimation or optimization process. We have estimated the parameters of a three-dimensional and time-dependent marine biogeochemical model describing the phosphorus cycle in the ocean. For this purpose, we have developed a statistical model for measurements of phosphate and dissolved organic phosphorus. This statistical model includes variances and correlations varying with time and location of the measurements. We compared the obtained estimations of model output and parameters for different criteria. Another question is if (and which) further measurements would increase the model's quality at all. Using experimental design criteria, the information content of measurements can be quantified. This may refer to the uncertainty in unknown model parameters as well as the uncertainty regarding which model is closer to reality. By (another) optimization, optimal measurement properties such as locations, time instants and quantities to be measured can be identified. We have optimized such properties for additional measurement for the parameter estimation of the marine biogeochemical model. For this purpose, we have quantified the uncertainty in the optimal model parameters and the model output itself regarding the uncertainty in the measurement data using the (Fisher) information matrix. Furthermore, we have calculated the uncertainty reduction by additional measurements depending on time
Sager, B.; Benson, P.; Jahoda, K.; Jacobs, J.R.; Bloch, J.J.; Sanders, W.T.; Lagally, M.G.
1986-05-01
Multilayer W--C diffraction gratings with nominal d spacings of 35 A have been fabricated by magnetron sputter deposition. The peak and integrated reflectivities of these films have been measured with AlK/sub ..cap alpha../ x rays and compared to theoretical values. The rms surface roughness has been evaluated. The influence of several sputtering-system process parameters on the reflectivities has been investigated.
Studies of Discharge Parameters Influence on the IPD Plasma Deposition Process
Rabinski, Marek; Zdunek, Krzysztof
2006-01-15
The paper presents recent studies of a current sheet dynamics influence on the surface engineering process of impulse plasma deposition (IPD). During the IPD process plasma is generated in the working gas due to a high-voltage high-current oscillating pulse discharge, ignited within an interelectrode region of a coaxial accelerator. The changes of plasma dynamics and generation mechanisms, e.g. the electric arc instead of the plasma sheet formation during the consecutive half-periods of discharge, cause the different deposition efficiency for accelerator with the outer electrode system composed of stainless steel rods instead of standard tubular one. The coating efficiency and deposited layer quality have been examined for the titanium nitride as the model material for surface engineering.
Gholami-Boroujeny, Shiva; Bolic, Miodrag
2016-04-01
Fitting the measured bioimpedance spectroscopy (BIS) data to the Cole model and then extracting the Cole parameters is a common practice in BIS applications. The extracted Cole parameters then can be analysed as descriptors of tissue electrical properties. To have a better evaluation of physiological or pathological properties of biological tissue, accurate extraction of Cole parameters is of great importance. This paper proposes an improved Cole parameter extraction based on bacterial foraging optimization (BFO) algorithm. We employed simulated datasets to test the performance of the BFO fitting method regarding parameter extraction accuracy and noise sensitivity, and we compared the results with those of a least squares (LS) fitting method. The BFO method showed better robustness to the noise and higher accuracy in terms of extracted parameters. In addition, we applied our method to experimental data where bioimpedance measurements were obtained from forearm in three different positions of the arm. The goal of the experiment was to explore how robust Cole parameters are in classifying position of the arm for different people, and measured at different times. The extracted Cole parameters obtained by LS and BFO methods were applied to different classifiers. Two other evolutionary algorithms, GA and PSO were also used for comparison purpose. We showed that when the classifiers are fed with the extracted feature sets by BFO fitting method, higher accuracy is obtained both when applying on training data and test data.
Research on the optimal selection method of image complexity assessment model index parameter
NASA Astrophysics Data System (ADS)
Zhu, Yong; Duan, Jin; Qian, Xiaofei; Xiao, Bo
2015-10-01
Target recognition is widely used in national economy, space technology and national defense and other fields. There is great difference between the difficulty of the target recognition and target extraction. The image complexity is evaluating the difficulty level of extracting the target from background. It can be used as a prior evaluation index of the target recognition algorithm's effectiveness. The paper, from the perspective of the target and background characteristics measurement, describe image complexity metrics parameters using quantitative, accurate mathematical relationship. For the collinear problems between each measurement parameters, image complexity metrics parameters are clustered with gray correlation method. It can realize the metrics parameters of extraction and selection, improve the reliability and validity of image complexity description and representation, and optimize the image the complexity assessment calculation model. Experiment results demonstrate that when gray system theory is applied to the image complexity analysis, target characteristics image complexity can be measured more accurately and effectively.
Parameter estimation of copula functions using an optimization-based method
NASA Astrophysics Data System (ADS)
Abdi, Amin; Hassanzadeh, Yousef; Talatahari, Siamak; Fakheri-Fard, Ahmad; Mirabbasi, Rasoul
2016-02-01
Application of the copulas can be useful for the accurate multivariate frequency analysis of hydrological phenomena. There are many copula functions and some methods were proposed for estimating the copula parameters. Since the copula functions are mathematically complicated, estimating of the copula parameter is an effortful work. In the present study, an optimization-based method (OBM) is proposed to obtain the parameters of copulas. The usefulness of the proposed method is illustrated on drought events. For this purpose, three commonly used copulas of Archimedean family, namely, Clayton, Frank, and Gumbel copulas are used to construct the joint probability distribution of drought characteristics of 60 gauging sites located in East-Azarbaijan province, Iran. The performance of OBM was compared with two conventional methods, namely, method of moments and inference function for margins. The results illustrate the supremacy of the OBM to estimate the copula parameters compared to the other considered methods.
NASA Astrophysics Data System (ADS)
Priya, I. Infanta Mary; Vinayagam, B. K.
2017-05-01
The aim of this work is to optimize the parameters namely load, elongation and thickness in tensile test of glass fibre reinforced polymer(GFRP) composites. In the present work, experiments were carried out as per the Taguchi experimental design and an L9 orthogonal array was used to study the influence of various combinations of parameters on stress and strain factors of the composite using MINITAB 17. Analysis of variance (ANOVA) test was conducted to determine the significance of each parameter on stress and strain value of the composite. The results indicate thatload is the most significant factor influencing the stress, and also it is the most significant factor inducing the strain of the composite. This work is useful in selecting the optimum values of various parameters that would, not only maximize the stress in the composite but also reduces the strain to a minimum level and improve the strength of the composite by acquiring a higher load bearing capacity.
Parameter estimation of copula functions using an optimization-based method
NASA Astrophysics Data System (ADS)
Abdi, Amin; Hassanzadeh, Yousef; Talatahari, Siamak; Fakheri-Fard, Ahmad; Mirabbasi, Rasoul
2017-07-01
Application of the copulas can be useful for the accurate multivariate frequency analysis of hydrological phenomena. There are many copula functions and some methods were proposed for estimating the copula parameters. Since the copula functions are mathematically complicated, estimating of the copula parameter is an effortful work. In the present study, an optimization-based method (OBM) is proposed to obtain the parameters of copulas. The usefulness of the proposed method is illustrated on drought events. For this purpose, three commonly used copulas of Archimedean family, namely, Clayton, Frank, and Gumbel copulas are used to construct the joint probability distribution of drought characteristics of 60 gauging sites located in East-Azarbaijan province, Iran. The performance of OBM was compared with two conventional methods, namely, method of moments and inference function for margins. The results illustrate the supremacy of the OBM to estimate the copula parameters compared to the other considered methods.
Parameter optimization of flux-aided backing-submerged arc welding by using Taguchi method
NASA Astrophysics Data System (ADS)
Pu, Juan; Yu, Shengfu; Li, Yuanyuan
2017-07-01
Flux-aided backing-submerged arc welding has been conducted on D36 steel with thickness of 20 mm. The effects of processing parameters such as welding current, voltage, welding speed and groove angle on welding quality were investigated by Taguchi method. The optimal welding parameters were predicted and the individual importance of each parameter on welding quality was evaluated by examining the signal-to-noise ratio and analysis of variance (ANOVA) results. The importance order of the welding parameters for the welding quality of weld bead was: welding current > welding speed > groove angle > welding voltage. The welding quality of weld bead increased gradually with increasing welding current and welding speed and decreasing groove angle. The optimum values of the welding current, welding speed, groove angle and welding voltage were found to be 1050 A, 27 cm/min, 40∘ and 34 V, respectively.
Parameter Identification of a Chaotic Circuit with a Hidden Attractor Using Krill Herd Optimization
NASA Astrophysics Data System (ADS)
Panahi, Shirin; Jafari, Sajad; Pham, Viet-Thanh; Kingni, Sifeu Takougang; Zahedi, Abdulhamid; Sedighy, Seyed Hassan
2016-12-01
Parameter estimation plays an important role in modeling and system identification. However, parameter estimation of chaotic systems has some basic differences with other dynamical systems due to butterfly effect. In this paper, we apply a new cost function for parameter estimation in a very interesting chaotic system, a system with a plane of equilibrium which belongs to a newly introduced category of dynamical systems: systems with hidden attractor. The nonlinear dynamics of this system is described in terms of equilibria and its stability, phase portraits, bifurcation diagram and Lyapunov exponents. In order to minimize the proposed cost function and obtain the correct parameters, we use a new efficient optimization method, Krill Herd algorithm. The results show the success of proposed procedures.
Capdevielle, Aurélie; Sýkorová, Eva; Biscans, Béatrice; Béline, Fabrice; Daumer, Marie-Line
2013-01-15
A sustainable way to recover phosphorus (P) in swine wastewater involves a preliminary step of P dissolution followed by the separation of particulate organic matter. The next two steps are firstly the precipitation of struvite crystals done by adding a crystallization reagent (magnesia) and secondly the filtration of the crystals. A design of experiments with five process parameters was set up to optimize the size of the struvite crystals in a synthetic swine wastewater. More than 90% of P was recovered as large crystals of struvite in optimal conditions which were: low Mg:Ca ratio (2.25:1), the leading parameter, high N:P ratio (3:1), moderate stirring rate (between 45 and 90 rpm) and low temperature (below 20 °C).These results were obtained despite the presence of a large amount of calcium and using a cheap reactant (MgO). The composition of the precipitates was identified by Raman analysis and solid dissolution. Results showed that amorphous calcium phosphate (ACP) co-precipitated with struvite and that carbonates were incorporated with solid fractions. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Wang, Dong; Tsui, Kwok-Leung; Zhou, Qiang
2016-05-01
Rolling element bearings are commonly used in machines to provide support for rotating shafts. Bearing failures may cause unexpected machine breakdowns and increase economic cost. To prevent machine breakdowns and reduce unnecessary economic loss, bearing faults should be detected as early as possible. Because wavelet transform can be used to highlight impulses caused by localized bearing faults, wavelet transform has been widely investigated and proven to be one of the most effective and efficient methods for bearing fault diagnosis. In this paper, a new Gauss-Hermite integration based Bayesian inference method is proposed to estimate the posterior distribution of wavelet parameters. The innovations of this paper are illustrated as follows. Firstly, a non-linear state space model of wavelet parameters is constructed to describe the relationship between wavelet parameters and hypothetical measurements. Secondly, the joint posterior probability density function of wavelet parameters and hypothetical measurements is assumed to follow a joint Gaussian distribution so as to generate Gaussian perturbations for the state space model. Thirdly, Gauss-Hermite integration is introduced to analytically predict and update moments of the joint Gaussian distribution, from which optimal wavelet parameters are derived. At last, an optimal wavelet filtering is conducted to extract bearing fault features and thus identify localized bearing faults. Two instances are investigated to illustrate how the proposed method works. Two comparisons with the fast kurtogram are used to demonstrate that the proposed method can achieve better visual inspection performances than the fast kurtogram.
Optimizing parameters of a technical system using quality function deployment method
NASA Astrophysics Data System (ADS)
Baczkowicz, M.; Gwiazda, A.
2015-11-01
The article shows the practical use of Quality Function Deployment (QFD) on the example of a mechanized mining support. Firstly it gives a short description of this method and shows how the designing process, from the constructor point of view, looks like. The proposed method allows optimizing construction parameters and comparing them as well as adapting to customer requirements. QFD helps to determine the full set of crucial construction parameters and then their importance and difficulty of their execution. Secondly it shows chosen technical system and presents its construction with figures of the existing and future optimized model. The construction parameters were selected from the designer point of view. The method helps to specify a complete set of construction parameters, from the point of view, of the designed technical system and customer requirements. The QFD matrix can be adjusted depending on designing needs and not every part of it has to be considered. Designers can choose which parts are the most important. Due to this QFD can be a very flexible tool. The most important is to define relationships occurring between parameters and that part cannot be eliminated from the analysis.
Data set of optimal parameters for colorimetric red assay of epoxide hydrolase activity.
de Oliveira, Gabriel Stephani; Adriani, Patricia Pereira; Borges, Flavia Garcia; Lopes, Adriana Rios; Campana, Patricia T; Chambergo, Felipe S
2016-09-01
The data presented in this article are related to the research article entitled "Epoxide hydrolase of Trichoderma reesei: Biochemical properties and conformational characterization" [1]. Epoxide hydrolases (EHs) are enzymes that catalyze the hydrolysis of epoxides to the corresponding vicinal diols. This article describes the optimal parameters for the colorimetric red assay to determine the enzymatic activity, with an emphasis on the characterization of the kinetic parameters, pH optimum and thermal stability of this enzyme. The effects of reagents that are not resistant to oxidation by sodium periodate on the reactions can generate false positives and interfere with the final results of the red assay.
Factorization and reduction methods for optimal control of distributed parameter systems
NASA Technical Reports Server (NTRS)
Burns, J. A.; Powers, R. K.
1985-01-01
A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.
Optimal Parameters of High Energy Ion Microprobe Systems Comprised of Lafayette Lenses
NASA Astrophysics Data System (ADS)
Dymnikov, Alexander D.; Glass, Gary A.; Rout, Bibhudutta; Dias, Johnny F.
2009-03-01
High energy optimal ion microprobes comprised of new compact magnetic quadrupole lenses (Lafayette Quadrupole Lens) are numerically investigated. The smallest beam spot size and appropriate radii of object and divergence slits are presented for different emittances and compared with the corresponding parameters of the Oxford triplet for the same total length. The parameters of the calculated microprobes include demagnification, the magnetic field in the lenses and the coefficients of spherical and chromatic aberrations for several quadrupole system configurations including the doublet, the Lafayette symmetric triplet, the Russian magnetic quadruplets and sextuplets.
NASA Astrophysics Data System (ADS)
Ghosal, Arindam; Patil, Pravin
2017-06-01
This experimental work presents the study of machining parameters of Ytterbium fiber laser during machining of 5 mm thick Aluminium/5wt%Alumina-MMC (Metal Matrix Composite). Response surface methodology (RSM) is used to achieve the optimization i.e. minimize hole tapering and maximize Material Removal Rate (MRR). A mathematical model has been developed and ANOVA has been done for correlating the interactive and higher-order influences of Ytterbium fiber laser machining parameters (laser power, modulation frequency, gas pressure, wait time, pulse width) on Material Removal Rate (MRR) and hole tapering during machining process.
Yazdani, Nuri; Chawla, Vipin; Edwards, Eve; Wood, Vanessa; Park, Hyung Gyu; Utke, Ivo
2014-01-01
Many energy conversion and storage devices exploit structured ceramics with large interfacial surface areas. Vertically aligned carbon nanotube (VACNT) arrays have emerged as possible scaffolds to support large surface area ceramic layers. However, obtaining conformal and uniform coatings of ceramics on structures with high aspect ratio morphologies is non-trivial, even with atomic layer deposition (ALD). Here we implement a diffusion model to investigate the effect of the ALD parameters on coating kinetics and use it to develop a guideline for achieving conformal and uniform thickness coatings throughout the depth of ultra-high aspect ratio structures. We validate the model predictions with experimental data from ALD coatings of VACNT arrays. However, the approach can be applied to predict film conformality as a function of depth for any porous topology, including nanopores and nanowire arrays.
Yazdani, Nuri; Chawla, Vipin; Edwards, Eve; Wood, Vanessa
2014-01-01
Summary Many energy conversion and storage devices exploit structured ceramics with large interfacial surface areas. Vertically aligned carbon nanotube (VACNT) arrays have emerged as possible scaffolds to support large surface area ceramic layers. However, obtaining conformal and uniform coatings of ceramics on structures with high aspect ratio morphologies is non-trivial, even with atomic layer deposition (ALD). Here we implement a diffusion model to investigate the effect of the ALD parameters on coating kinetics and use it to develop a guideline for achieving conformal and uniform thickness coatings throughout the depth of ultra-high aspect ratio structures. We validate the model predictions with experimental data from ALD coatings of VACNT arrays. However, the approach can be applied to predict film conformality as a function of depth for any porous topology, including nanopores and nanowire arrays. PMID:24778944
Gu, Qiang; Sivanandam, Thamil Mani
2014-06-01
Microarray experiments are a centerpiece of postgenomics life sciences and the current efforts to develop systems diagnostics for personalized medicine. The majority of antibody microarray experiments are fluorescence-based, which utilizes a scanner to convert target signals into image files for subsequent quantification. Certain scan parameters such as the laser power and photomultiplier tube gain (PMT) can influence the readout of fluorescent intensities and thus may affect data quantitation. To date, however, there is no consensus of how to determine the optimal settings of microarray scanners. Here we show that different settings of the laser power and PMT not only affect the signal intensities but also the accuracy of antibody microarray experiments. More importantly, we demonstrate an experimental approach using two fluorescent dyes to determine optimal settings of scan parameters for microarray experiments. These measures provide added quality control of microarray experiments, and thus help to improve the accuracy of quantitative outcome in microarray experiments in the above contexts.
NASA Astrophysics Data System (ADS)
Dong, Xiaoyu; Yuan, Yulian; Tang, Qian; Dou, Shaohua; Di, Lanbo; Zhang, Xiuling
2014-01-01
In this study, Saccharomyces cerevisiae (S. cerevisiae) was exposed to dielectric barrier discharge plasma (DBD) to improve its ethanol production capacity during fermentation. Response surface methodology (RSM) was used to optimize the discharge-associated parameters of DBD for the purpose of maximizing the ethanol yield achieved by DBD-treated S. cerevisiae. According to single factor experiments, a mathematical model was established using Box-Behnken central composite experiment design, with plasma exposure time, power supply voltage, and exposed-sample volume as impact factors and ethanol yield as the response. This was followed by response surface analysis. Optimal experimental parameters for plasma discharge-induced enhancement in ethanol yield were plasma exposure time of 1 min, power voltage of 26 V, and an exposed sample volume of 9 mL. Under these conditions, the resulting yield of ethanol was 0.48 g/g, representing an increase of 33% over control.
Parameter optimization for transitions between memory states in small arrays of Josephson junctions
NASA Astrophysics Data System (ADS)
Rezac, J. D.; Imam, N.; Braiman, Y.
2017-05-01
Coupled arrays of Josephson junctions possess multiple stable zero voltage states. Such states can store information and consequently can be utilized for cryogenic memory applications. Basic memory operations can be implemented by sending a pulse to one of the junctions and studying transitions between the states. In order to be suitable for memory operations, such transitions between the states have to be fast and energy efficient. In this paper we employed simulated annealing, a stochastic optimization algorithm, to study parameter optimization of array parameters which minimizes times and energies of transitions between specifically chosen states that can be utilized for memory operations (Read, Write, and Reset). Simulation results show that such transitions occur with access times on the order of 10-100 ps and access energies on the order of 10-19-5×10-18 J. Numerical simulations are validated with approximate analytical results.
NASA Astrophysics Data System (ADS)
Xue, Wei; Zhu, Jichao; Rong, Xia; Huang, Yujin; Yang, Yue; Yu, Yunyun
2017-05-01
Ground penetrating radar (GPR) is widely used for subsurface detection due to the nondestructive characteristics. GPR signal is non-stationary because of complex medium environment, and time-frequency analysis is the powerful tool for the research of GPR signal. In this paper, a new generalized S transform with parameters optimization is proposed to analyze the GPR signal. In the proposed scheme, first a flexible window function replaces the fixed window function of S transform, then the criterion of time-frequency concentration is used to optimize the parameters of the window function, the aim is to improve the time-frequency resolution and applicability of S transform. The experimental results for synthetic data and practical GPR data show the proposed scheme can enhance the energy concentration in time-frequency domain effectively and provide better layer recognition and target detection performance.
Compton, Philip D; Strukl, Joseph V; Bai, Dina L; Shabanowitz, Jeffrey; Hunt, Donald F
2012-02-07
Electron transfer dissociation (ETD) has improved the mass spectrometric analysis of proteins and peptides with labile post-translational modifications and larger intact masses. Here, the parameters governing the reaction rate of ETD are examined experimentally. Currently, due to reagent injection and isolation events as well as longer reaction times, ETD spectra require significantly more time to acquire than collision-induced dissociation (CID) spectra (>100 ms), resulting in a trade-off in the dynamic range of tandem MS analyses when ETD-based methods are compared to CID-based methods. Through fine adjustment of reaction parameters and the selection of reagents with optimal characteristics, we demonstrate a drastic reduction in the time taken per ETD event. In fact, ETD can be performed with optimal efficiency in nearly the same time as CID at low precursor charge state (z = +3) and becomes faster at higher charge state (z > +3).
Multi-criteria optimization of chassis parameters of Nissan 200 SX for drifting competitions
NASA Astrophysics Data System (ADS)
Maniowski, M.
2016-09-01
The work objective is to increase performance of Nissan 200sx S13 prepared for a quasi-static state of drifting on a circular path with given constant radius (R=15 m) and tyre-road friction coefficient (μ = 0.9). First, a high fidelity “miMA” multibody model of the vehicle is formulated. Then, a multicriteria optimization problem is solved with one of the goals to maximize a stable drift angle (β) of the vehicle. The decision variables contain 11 parameters of the vehicle chassis (describing the wheel suspension stiffness and geometry) and 2 parameters responsible for a driver steering and accelerator actions, that control this extreme closed-loop manoeuvre. The optimized chassis setup results in the drift angle increase by 14% from 35 to 40 deg.
Liu, Jianguo; Yang, Bo; Chen, Changzhen
2013-02-01
The optimization of operating parameters for the isolation of peroxidase from horseradish (Armoracia rusticana) roots with ultrafiltration (UF) technology was systemically studied. The effects of UF operating conditions on the transmission of proteins were quantified using the parameter scanning UF. These conditions included solution pH, ionic strength, stirring speed and permeate flux. Under optimized conditions, the purity of horseradish peroxidase (HRP) obtained was greater than 84 % after a two-stage UF process and the recovery of HRP from the feedstock was close to 90 %. The resulting peroxidase product was then analysed by isoelectric focusing, SDS-PAGE and circular dichroism, to confirm its isoelectric point, molecular weight and molecular secondary structure. The effects of calcium ion on HRP specific activities were also experimentally determined.
Improvement of properties of aluminosilicate pastes based on optimization of curing parameters
NASA Astrophysics Data System (ADS)
Kočí, Václav; Rovnaníková, Pavla; Černý, Robert
2017-07-01
Alkali-activated binders represent a low-energy alternative to traditional binders based on lime or cement. In this paper, a new binder of this type is designed and the influence of curing parameters on its mechanical properties, namely 7-days compressive strength, is investigated. The curing parameters include the curing temperature and the period of exposure. To maximize the compressive strength of the binder, simplex optimization procedure is applied in order to demonstrate its applicability for this research. The preliminary results indicate that the procedure is able to reach positive results as the compressive strength is found to increase by ˜11 %. As this improvement is achieved already after the first optimization step, it can be concluded that this approach has a potential to be more effective than traditional empirical design which is common in building materials engineering.
Barz, Tilman; Löffler, Verena; Arellano-Garcia, Harvey; Wozny, Günter
2010-06-25
In this work, parameters of the steric mass-formalism SMA are optimally ascertained for a reliable determination of the adsorption isotherms of beta-lactoglobulin A and B under non-isocratic conditions. For this purpose, static batch experiments are used in contrast to the protocols based on different experimental steps, which use a chromatographic column. It is shown that parameters can already be determined for a small number of experiments by using a systematic procedure based on optimal model-based experimental design and an efficient NLP-solver. The in different works observed anti-Langmuir shape of the isotherm for small concentrations of beta-lactoglobulin A was corroborated. Moreover, we also found indications for a porosity variation with changing protein concentrations.
Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2006-01-01
This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.
Michieli, Niccolò; Kalinic, Boris; Scian, Carlo; Cesca, Tiziana; Mattei, Giovanni
2015-03-15
Plasmonic sensors based on ordered arrays of nanoprisms are optimized in terms of their geometric parameters like size, height, aspect ratio for Au, Ag or Au0.5-Ag0.5 alloy to be used in the visible or near IR spectral range. The two figures of merit used for the optimization are the bulk and the surface sensitivity: the first is important for optimizing the sensing to large volume analytes whereas the latter is more important when dealing with small bio-molecules immobilized in close proximity to the nanoparticle surface. A comparison is made between experimentally obtained nanoprisms arrays and simulated ones by using Finite Elements Methods (FEM) techniques. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Mu, Wen-Ying; Cui, Bao-Tong; Lou, Xu-Yang; Li, Wen
2014-07-01
This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.
Numerical simulation and parameter optimization of automobile reinforced inner plate forming process
NASA Astrophysics Data System (ADS)
Su, Yanhong; Ma, Yaxin; Men, Zhengxing; Tang, Yue; Wang, Menghan
2017-08-01
Automotive reinforced inner plate is a typical sheet metal stamping parts, which is characterized by complex shape, the need for multi-channel process to complete. If the parts can be based on the needs and possibilities of a reasonable combination of some processes, not only can improve the quality of the workpiece, but also can save mold costs and improve production efficiency. The finite element analysis software Dy naform is used to develop the finite element model, and the forming process of the automotive reinforced inner plate was simulated and analyzed. The process parameters influencing the forming quality were optimized, and the shape and size of the blank were optimized to obtain the ideal billet state. In the wrinkled surface on the local optimization, a good control of the product forming quality. Finally, the simulation results are compared with those of the actual production. The correctness of the numerical simulation is verified.
Ng, Sook Kien; Zygmanski, Piotr; Jeung, Andrew; Mostafavi, Hassan; Hesser, Juergen; Bellon, Jennifer R; Wong, Julia S; Lyatskaya, Yulia
2012-05-10
Digital tomosynthesis (DTS) was evaluated as an alternative to cone-beam computed tomography (CBCT) for patient setup. DTS is preferable when there are constraints with setup time, gantry-couch clearance, and imaging dose using CBCT. This study characterizes DTS data acquisition and registration parameters for the setup of breast cancer patients using nonclinical Varian DTS software. DTS images were reconstructed from CBCT projections acquired on phantoms and patients with surgical clips in the target volume. A shift-and-add algorithm was used for DTS volume reconstructions, while automated cross-correlation matches were performed within Varian DTS software. Triangulation on two short DTS arcs separated by various angular spread was done to improve 3D registration accuracy. Software performance was evaluated on two phantoms and ten breast cancer patients using the registration result as an accuracy measure; investigated parameters included arc lengths, arc orientations, angular separation between two arcs, reconstruction slice spacing, and number of arcs. The shifts determined from DTS-to-CT registration were compared to the shifts based on CBCT-to-CT registration. The difference between these shifts was used to evaluate the software accuracy. After findings were quantified, optimal parameters for the clinical use of DTS technique were determined. It was determined that at least two arcs were necessary for accurate 3D registration for patient setup. Registration accuracy of 2 mm was achieved when the reconstruction arc length was > 5° for clips with HU ≥ 1000; larger arc length (≥ 8°) was required for very low HU clips. An optimal arc separation was found to be ≥ 20° and optimal arc length was 10°. Registration accuracy did not depend on DTS slice spacing. DTS image reconstruction took 10-30 seconds and registration took less than 20 seconds. The performance of Varian DTS software was found suitable for the accurate setup of breast cancer patients
Bi- and Poly- Optimal Confidence Limits for a Location and Parameter.
1983-11-