NASA Astrophysics Data System (ADS)
Mahamood, Rasheedat M.; Akinlabi, Esther T.
2016-03-01
Ti6Al4V is an important Titanium alloy that is mostly used in many applications such as: aerospace, petrochemical and medicine. The excellent corrosion resistance property, the high strength to weight ratio and the retention of properties at high temperature makes them to be favoured in most applications. The high cost of Titanium and its alloys makes their use to be prohibitive in some applications. Ti6Al4V can be cladded on a less expensive material such as steel, thereby reducing cost and providing excellent properties. Laser Metal Deposition (LMD) process, an additive manufacturing process is capable of producing complex part directly from the 3-D CAD model of the part and it also has the capability of handling multiple materials. Processing parameters play an important role in LMD process and in order to achieve desired results at a minimum cost, then the processing parameters need to be properly controlled. This paper investigates the role of processing parameters: laser power, scanning speed, powder flow rate and gas flow rate, on the material utilization efficiency in laser metal deposited Ti6Al4V. A two-level full factorial design of experiment was used in this investigation, to be able to understand the processing parameters that are most significant as well as the interactions among these processing parameters. Four process parameters were used, each with upper and lower settings which results in a combination of sixteen experiments. The laser power settings used was 1.8 and 3 kW, the scanning speed was 0.05 and 0.1 m/s, the powder flow rate was 2 and 4 g/min and the gas flow rate was 2 and 4 l/min. The experiments were designed and analyzed using Design Expert 8 software. The software was used to generate the optimized process parameters which were found to be laser power of 3.2 kW, scanning speed of 0.06 m/s, powder flow rate of 2 g/min and gas flow rate of 3 l/min.
Optimization of sputter deposition parameters for magnetostrictive Fe62Co19Ga19/Si(100) films
NASA Astrophysics Data System (ADS)
Jen, S. U.; Tsai, T. L.
2012-04-01
A good magnetostrictive material should have large saturation magnetostriction (λS) and low saturation (or anisotropy) field (HS), such that its magnetostriction susceptibility (SH) can be as large as possible. In this study, we have made Fe62Co19Ga19/Si(100) nano-crystalline films by using the dc magnetron sputtering technique under various deposition conditions: Ar working gas pressure (pAr) was varied from 1 to 15 mTorr; sputtering power (Pw) was from 10 to 120 W; deposition temperature (TS) was from room temperature (RT) to 300 °C, The film thickness (tf) was fixed at 175 nm. Each magnetic domain looked like a long leaf, with a long-axis of about 12-15 μm and a short-axis of about 1.5 μm. The optimal magnetic and electrical properties were found from the Fe62Co19Ga19 film made with the sputter deposition parameters of pAr = 5 mTorr, Pw = 80 W, and TS = RT. Those optimal properties include λS = 80 ppm, HS = 19.8 Oe, SH = 6.1 ppm/Oe, and electrical resistivity ρ = 57.0 μΩ cm. Note that SH for the conventional magnetostrictive Terfenol-D film is, in general, equal to 1.5 ppm/Oe only.
Sharon, Maheshwar; Apte, P R; Purandare, S C; Zacharia, Renju
2005-02-01
Seven variable parameters of the chemical vapor deposition system have been optimized with the help of the Taguchi analytical method for getting a desired product, e.g., carbon nanotubes or carbon nanobeads. It is observed that almost all selected parameters influence the growth of carbon nanotubes. However, among them, the nature of precursor (racemic, R or Technical grade camphor) and the carrier gas (hydrogen, argon and mixture of argon/hydrogen) seem to be more important parameters affecting the growth of carbon nanotubes. Whereas, for the growth of nanobeads, out of seven parameters, only two, i.e., catalyst (powder of iron, cobalt, and nickel) and temperature (1023 K, 1123 K, and 1273 K), are the most influential parameters. Systematic defects or islands on the substrate surface enhance nucleation of novel carbon materials. Quantitative contributions of process parameters as well as optimum factor levels are obtained by performing analysis of variance (ANOVA) and analysis of mean (ANOM), respectively. PMID:15853150
Optimization of the microcrystalline silicon deposition efficiency
Strahm, B.; Howling, A. A.; Sansonnens, L.; Hollenstein, Ch.
2007-07-15
Cost reduction constraints for microcrystalline silicon thin film photovoltaic solar cells require high deposition rates and high silane gas utilization efficiencies. If the requirements in deposition rate have sometimes been fulfilled, it is generally not the case for the silane utilization. In this work, a reactor-independent methodology has been developed to determine the optimum plasma parameters in terms of deposition rate, silane utilization, and material microstructure. Using this optimization method, a microcrystalline layer has been deposited over a large area at a rate of 10.9 A/s, with a silane utilization efficiency above 80%.
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.
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.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems. PMID:22122384
Parameter optimization in S-system models
Vilela, Marco; Chou, I-Chun; Vinga, Susana; Vasconcelos, Ana Tereza R; Voit, Eberhard O; Almeida, Jonas S
2008-01-01
Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well. PMID:18416837
Advanced rotorcraft control using parameter optimization
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1991-01-01
A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.
RTLS entry load relief parameter optimization
NASA Technical Reports Server (NTRS)
Crull, T. J.
1975-01-01
The results are presented of a study of a candidate load relief control law for use during the pullup phase of Return-to-Launch-Site (RTLS) abort entries. The control law parameters and cycle time which optimized performance of the normal load factor limiting phase (load relief phase) of an RTLS entry are examined. A set of control law gains, a smoothing parameter, and a normal force coefficient curve fit are established which resulted in good load relief performance considering the possible aerodynamic coefficient uncertainties defined. Also, the examination of various guidance cycle times revealed improved load relief performance with decreasing cycle time. A .5 second cycle provided smooth and adequate load relief in the presence of all the aerodynamic uncertainties examined.
Optimization of audio - ultrasonic plasma system parameters
NASA Astrophysics Data System (ADS)
Haleem, N. A.; Abdelrahman, M. M.; Ragheb, M. S.
2016-10-01
The present plasma is a special glow plasma type generated by an audio ultrasonic discharge voltage. A definite discharge frequency using a gas at a narrow band pressure creates and stabilizes this plasma type. The plasma cell is a self-extracted ion beam; it is featured with its high output intensity and its small size. The influence of the plasma column length on the output beam due to the variation of both the audio discharge frequency and the power applied to the plasma electrodes is investigated. In consequence, the aim of the present work is to put in evidence the parameters that influence the self-extracted collected ion beam and to optimize the conditions that enhance the collected ion beam. The experimental parameters studied are the nitrogen gas, the applied frequency from 10 to 100 kHz, the plasma length that varies from 8 to 14 cm, at a gas pressure of ≈ 0.25 Torr and finally the discharge power from 50 to 500 Watt. A sheet of polyethylene of 5 micrometer covers the collector electrode in order to confirm how much ions from the beam can go through the polymer and reach the collector. To diagnose the occurring events of the beam on the collector, the polymer used is analyzed by means of the FTIR and the XRF techniques. Optimization of the plasma cell parameters succeeded to enhance and to identify the parameters that influence the output ion beam and proved that its particles attaining the collector are multi-energetic.
Automatic parameter optimization in inspection systems
NASA Astrophysics Data System (ADS)
Bhatia, Peeyush
1997-08-01
Automatic inspection systems for IC mark, package and lead inspection are being widely used as in-process controls and check points. Here their primary function is not only to inspect and sort out defective parts but also to provide feedback on how well a process such as marking or trim and form is performing. Inspection results of every part inspected are often accumulated in a statistical process control (SPC) program that can monitor drifts in the process. Not all drifts are caused by problems in the process itself. For example the mark contrast on a package may be reduced not only because of some problem with the marking process but also because of changes in the mold compound of the package or changes in the light intensity of the inspection system. In latter case a statistical tool such as the SPC program may alert the user of a process drift and he will have to retune, recalibrate or change the parameters of the inspection system. Often the change in parameter is done by trail-and-error. A change too much or too little can result in excess overkill or even escapes. Alternatively the statistical data itself can be used to suggest the user what changes should be made to the inspection parameters. This method of automatic parameter optimization is discussed in detail in this paper. A mark inspection system is chosen as a specific example on how to apply this method.
XTC MRI: sensitivity improvement through parameter optimization.
Ruppert, Kai; Mata, Jaime F; Wang, Hsuan-Tsung J; Tobias, William A; Cates, Gordon D; Brookeman, James R; Hagspiel, Klaus D; Mugler, John P
2007-06-01
Xenon polarization Transfer Contrast (XTC) MRI pulse sequences permit the gas exchange of hyperpolarized xenon-129 in the lung to be measured quantitatively. However, the pulse sequence parameter values employed in previously published work were determined empirically without considering the now-known gas exchange rates and the underlying lung physiology. By using a theoretical model for the consumption of magnetization during data acquisition, the noise intensity in the computed gas-phase depolarization maps was minimized as a function of the gas-phase depolarization rate. With such optimization the theoretical model predicted an up to threefold improvement in precision. Experiments in rabbits demonstrated that for typical imaging parameter values the optimized XTC pulse sequence yielded a median noise intensity of only about 3% in the depolarization maps. Consequently, the reliable detection of variations in the average alveolar wall thickness of as little as 300 nm can be expected. This improvement in the precision of the XTC MRI technique should lead to a substantial increase in its sensitivity for detecting pathological changes in lung function.
Optimal filtration of the atmospheric parameters profiles
NASA Technical Reports Server (NTRS)
Zuev, V. E.; Glazov, G. N.; Igonin, G. M.
1986-01-01
The idea of optimal Marcovian filtration of fluctuating profiles from lidar signals is developed but as applied to a double-frequency sounding which allows the use of large cross sections of elastic scattering and correct separation of the contributions due to aerosol and Rayleigh scatterings from the total lidar return. The filtration efficiency is shown under different conditions of sounding using a computer model. The accuracy of restituted profiles (temperature, pressure, density) is determined by the elements of a posteriori matrix K. The results obtained allow the determination of the lidar power required for providing the necessary accuracy of restitution of the atmospheric parameter profiles at chosen wavelengths of sounding in the ultraviolet and visible range.
CMB Polarization Detector Operating Parameter Optimization
NASA Astrophysics Data System (ADS)
Randle, Kirsten; Chuss, David; Rostem, Karwan; Wollack, Ed
2015-04-01
Examining the polarization of the Cosmic Microwave Background (CMB) provides the only known way to probe the physics of inflation in the early universe. Gravitational waves produced during inflation are posited to produce a telltale pattern of polarization on the CMB and if measured would provide both tangible evidence for inflation along with a measurement of inflation's energy scale. Leading the effort to detect and measure this phenomenon, Goddard Space Flight Center has been developing high-efficiency detectors. In order to optimize signal-to-noise ratios, sources like the atmosphere and the instrumentation must be considered. In this work we examine operating parameters of these detectors such as optical power loading and photon noise. SPS Summer Internship at NASA Goddard Spaceflight Center.
Optimal parameters for linear second-degree stationary iterative methods
Manteuffel, T. A.
1980-11-01
It is shown that the optimal parameters for linear second-degree stationary iterative methods applied to nonsymmetric linear systems can be found by solving the same minimax problem used to find optimal parameters for the Tchebychev iteration. In fact, the Tchebychev iteration is asymptotically equivalent to a linear second-degree stationary method. The method of finding optimal parameters for the Tchebychev iteration given by Manteuffel (Numer. Math., 28, 307-27 (1977)) can be used to find optimal parameters for the stationary method as well. 1 figure.
Simultaneous optimal experimental design for in vitro binding parameter estimation.
Ernest, C Steven; Karlsson, Mats O; Hooker, Andrew C
2013-10-01
Simultaneous optimization of in vitro ligand binding studies using an optimal design software package that can incorporate multiple design variables through non-linear mixed effect models and provide a general optimized design regardless of the binding site capacity and relative binding rates for a two binding system. Experimental design optimization was employed with D- and ED-optimality using PopED 2.8 including commonly encountered factors during experimentation (residual error, between experiment variability and non-specific binding) for in vitro ligand binding experiments: association, dissociation, equilibrium and non-specific binding experiments. Moreover, a method for optimizing several design parameters (ligand concentrations, measurement times and total number of samples) was examined. With changes in relative binding site density and relative binding rates, different measurement times and ligand concentrations were needed to provide precise estimation of binding parameters. However, using optimized design variables, significant reductions in number of samples provided as good or better precision of the parameter estimates compared to the original extensive sampling design. Employing ED-optimality led to a general experimental design regardless of the relative binding site density and relative binding rates. Precision of the parameter estimates were as good as the extensive sampling design for most parameters and better for the poorly estimated parameters. Optimized designs for in vitro ligand binding studies provided robust parameter estimation while allowing more efficient and cost effective experimentation by reducing the measurement times and separate ligand concentrations required and in some cases, the total number of samples. PMID:23943088
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.
NASA Astrophysics Data System (ADS)
Weiss, Claire Victoria
Metallo-organic solution deposition (MOSD) and spin-coating were used to deposit strontium titanate (SrTiO3 or STO) thin films on Si and metalized Si substrates. In addition, a thermodynamic model was constructed based on the Landau polynomial for the free energy. Using this model, the thin film strain due to the difference in thermal expansion coefficients (TECs) of the film and substrate was calculated, as well as its effect on the permittivity and tunability. It was found that a large tensile thermal strain develops in the STO/Si material system, and this strain significantly lowers the dielectric response as compared to bulk STO. A multi-dimensional parameter optimization process was used to systematically vary the solution, deposition, and processing parameters of the STO thin films. These parameters include the precursor solution heating, solution molarity/concentration, solution aging, spin-coating recipe, pyrolysis procedure/temperature, annealing temperature, and annealing oxygen environment. X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), spectroscopic ellipsometry (SE), and dielectric/insulating measurements were used to characterize the STO thin film devices. By optimizing various deposition parameters, such as the solution molarity and the pyrolysis temperature, the tensile stress induced from the difference in TECs of the film and substrate, which was predicted by the thermodynamic theory, can be reduced or completely eliminated. This stress relaxation is achieved through the tailoring of compressive "growth stresses" by optimizing the precursor solution molarity as well as the post-deposition heat treatment processing. By utilizing the multi-dimensional parameter optimization process, high-quality, electronic-grade thin film STO can be deposited via the affordable, simple, and industry-standard MOSD technique.
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.
Optimal parameters of leader development in lightning
NASA Technical Reports Server (NTRS)
Petrov, N. I.; Petrova, G. N.
1991-01-01
The dependences between the different parameters of a leader in lightning are obtained theoretically. The physical mechanism of the instability leading to the formation of the streamer zone is proposed. The instability has the wave nature and is caused by the self-influence effects of the space charge. Using a stability condition of the leader propagation, a dependence is obtained between the current across the leader head and its velocity of motion. The dependence of the streamer zone length on the gap length is also obtained. It is shown that the streamer zone length is saturated with the increasing of the gap length. A comparison between the obtained dependences and the experimental data is presented.
Optimizing parameters for magnetorheological finishing supersmooth surface
NASA Astrophysics Data System (ADS)
Cheng, Haobo; Feng, Zhijing; Wang, Yingwei
2005-02-01
This paper presents a reasonable approach to this issue, i.e., computer controlled magnetorheological finishing (MRF). In MRF, magnetically stiffened magnetorheological (MR) abrasive fluid flows through a preset converging gap that is formed by a workpiece surface and a moving rigid wall, to create precise material removal and polishing. Tsinghua University recently completed a project with MRF technology, in which a 66 mm diameter, f/5 parabolic mirror was polished to the shape accuracy of λ/17 RMS (λ=632.8nm) and the surface roughness of 1.22 nm Ra. This was done on a home made novel aspheric computer controlled manufacturing system. It is a three-axis, self-rotating wheel machine, the polishing tool is driven with one motor through a belt. This paper presents the manufacturing and testing processes, including establish the mathematics model of MRF optics on the basis of Preston equation, profiler test and relative coefficients, i.e., pressure between workpiece and tool, velocity of MR fluid in polishing spot, tolerance control of geometrical parameters such as radius of curvature and conic constant also been analyzed in the paper. Experiments were carried out on the features of MRF. The results indicated that the required convergent speed, surface roughness could be achieved with high efficiency.
Identification of vehicle suspension parameters by design optimization
NASA Astrophysics Data System (ADS)
Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.
2014-05-01
The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Helical tomotherapy optimized planning parameters for nasopharyngeal cancer
NASA Astrophysics Data System (ADS)
Yawichai, K.; Chitapanarux, I.; Wanwilairat, S.
2016-03-01
Helical TomoTherapy(HT) planning depends on optimize parameters including field width (FW), pitch factor (PF) and modulation factor (MF). These optimize parameters are effect to quality of plans and treatment time. The aim of this study was to find the optimized parameters which compromise between plan quality and treatment times. Six nasopharyngeal cancer patients were used. For each patient data set, 18 treatment plans consisted of different optimize parameters combination (FW=5.0, 2.5, 1.0 cm; PF=0.43, 0.287, 0.215; MF2.0, 3.0) were created. The identical optimization procedure followed ICRU83 recommendations. The average D50 of both parotid glands and treatment times per fraction were compared for all plans. The study show treatment plan with FW1.0 cm showed the lowest average D50 of both parotid glands. The treatment time increased inversely to FW. The FW1.0 cm the average treatment time was 4 times longer than FW5.0 cm. PF was very little influence on the average D50 of both parotid glands. Finally, MF increased from 2.0 to 3.0 the average D50 of both parotid glands was slightly decreased. However, the average treatment time was increased 22.28%. For routine nasopharyngeal cancer patients with HT, we suggest the planning optimization parameters consist of FW=5.0 cm, PF=0.43 and MF=2.0.
Optimizing chirped laser pulse parameters for electron acceleration in vacuum
Akhyani, Mina; Jahangiri, Fazel; Niknam, Ali Reza; Massudi, Reza
2015-11-14
Electron dynamics in the field of a chirped linearly polarized laser pulse is investigated. Variations of electron energy gain versus chirp parameter, time duration, and initial phase of laser pulse are studied. Based on maximizing laser pulse asymmetry, a numerical optimization procedure is presented, which leads to the elimination of rapid fluctuations of gain versus the chirp parameter. Instead, a smooth variation is observed that considerably reduces the accuracy required for experimentally adjusting the chirp parameter.
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.
Genetic algorithm parameter optimization: applied to sensor coverage
NASA Astrophysics Data System (ADS)
Sahin, Ferat; Abbate, Giuseppe
2004-08-01
Genetic Algorithms are powerful tools, which when set upon a solution space will search for the optimal answer. These algorithms though have some associated problems, which are inherent to the method such as pre-mature convergence and lack of population diversity. These problems can be controlled with changes to certain parameters such as crossover, selection, and mutation. This paper attempts to tackle these problems in GA by having another GA controlling these parameters. The values for crossover parameter are: one point, two point, and uniform. The values for selection parameters are: best, worst, roulette wheel, inside 50%, outside 50%. The values for the mutation parameter are: random and swap. The system will include a control GA whose population will consist of different parameters settings. While this GA is attempting to find the best parameters it will be advancing into the search space of the problem and refining the population. As the population changes due to the search so will the optimal parameters. For every control GA generation each of the individuals in the population will be tested for fitness by being run through the problem GA with the assigned parameters. During these runs the population used in the next control generation is compiled. Thus, both the issue of finding the best parameters and the solution to the problem are attacked at the same time. The goal is to optimize the sensor coverage in a square field. The test case used was a 30 by 30 unit field with 100 sensor nodes. Each sensor node had a coverage area of 3 by 3 units. The algorithm attempts to optimize the sensor coverage in the field by moving the nodes. The results show that the control GA will provide better results when compared to a system with no parameter changes.
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.
Automatic parameter optimizer (APO) for multiple-point statistics
NASA Astrophysics Data System (ADS)
Bani Najar, Ehsanollah; Sharghi, Yousef; Mariethoz, Gregoire
2016-04-01
Multiple Point statistics (MPS) have gained popularity in recent years for generating stochastic realizations of complex natural processes. The main principle is that a training image (TI) is used to represent the spatial patterns to be modeled. One important feature of MPS is that the spatial model of the fields generated is made of 1) the chosen TI and 2) a set of algorithmic parameters that are specific to each MPS algorithm. While the choice of a training image can be guided by expert knowledge (e.g. for geological modeling) or by data acquisition methods (e.g. remote sensing) determining the algorithmic parameters can be more challenging. To date, only specific guidelines have been proposed for some simulation methods, and a general parameters inference methodology is still lacking, in particular for complex modeling settings such as when using multivariate training images. The common practice consists in carrying out an extensive parameters sensitivity analysis which can be cumbersome. An additional complexity is that the algorithmic parameters do influence CPU cost, and therefore finding optimal parameters is not only a modeling question, but also a computational challenge. To overcome these issues, we propose the automatic parameter optimizer (MPS-APO), a generic method based on stochastic optimization to rapidly determine acceptable parameters, in different settings and for any MPS method. The MPS automatic parameter optimizer proceeds in a 2-step approach. In the first step, it considers the set of input parameters of a given MPS algorithm and formulates an objective function that quantifies the reproduction of spatial patterns. The Simultaneous Perturbation Stochastic Approximation (SPSA) optimization method is used to minimize the objective function. SPSA is chosen because it is able to deal with the stochastic nature of the objective function and for its computational efficiency. At each iteration, small gaps are randomly placed in the input image
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.
Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki
2015-01-01
Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest. PMID:25784880
Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki
2015-01-01
Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest. PMID:25784880
MDSIMAID: automatic parameter optimization in fast electrostatic algorithms.
Crocker, Michael S; Hampton, Scott S; Matthey, Thierry; Izaguirre, Jesús A
2005-07-30
MDSIMAID is a recommender system that optimizes parallel Particle Mesh Ewald (PME) and both sequential and parallel multigrid (MG) summation fast electrostatic solvers. MDSIMAID optimizes the running time or parallel scalability of these methods within a given error tolerance. MDSIMAID performs a run time constrained search on the parameter space of each method starting from semiempirical performance models. Recommended parameters are presented to the user. MDSIMAID's optimization of MG leads to configurations that are up to 14 times faster or 17 times more accurate than published recommendations. Optimization of PME can improve its parallel scalability, making it run twice as fast in parallel in our tests. MDSIMAID and its Python source code are accessible through a Web portal located at http://mdsimaid.cse.nd.edu.
Optimization of stepper parameters and their influence on OPC
NASA Astrophysics Data System (ADS)
Vallishayee, Rakesh R.; Orszag, Steven A.; Barouch, Eytan
1996-06-01
An algorithm for the optimization of stepper parameters has been designed and implemented. The cost function used in this optimization is the contrast. The aerial image is computed using the computer code FAIM. First, the contrast of the image is calculated and the derivatives of the contrast with respect to the stepper parameters are evaluated. The computational cost of these calculations is only slightly more than that of one aerial image simulation. A conjugate gradient type algorithm is then used to obtain the minimum of the contrast.
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.
An Optimized Nanoparticle Separator Enabled by Electron Beam Induced Deposition
Fowlkes, Jason Davidson; Doktycz, Mitchel John; Rack, P. D.
2010-01-01
Size based separations technologies will inevitably benefit from advances in nanotechnology. Direct write nanofabrication provides a useful mechanism to deposit/etch nanoscale elements in environments otherwise inaccessible to conventional nanofabrication techniques. Here, electron beam induced deposition (EBID) was used to deposit an array of nanoscale features in a 3D environment with minimal material proximity effects outside the beam interaction region (BIR). Specifically, the membrane component of a nanoparticle separator was fabricated by depositing a linear array of sharply tipped nanopillars, with a singular pitch, designed for sub 50nm nanoparticle permeability. The nanopillar membrane was used in a dual capacity to control the flow of nanoparticles in the transaxial direction of the array while facilitating the sealing of the cellular sized compartment in the paraxial direction. An optimized growth recipe resulted which (1) maximized the growth efficiency of the membrane (which minimizes proximity effects), (2) preserved the fidelity of spacing between nanopillars (which maximizes the size based gating quality of the membrane) while (3) maintaining sharp nanopillar apexes for impaling an optically transparent polymeric lid critical for device sealing.
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.
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.
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.
Vallejos, S; Umek, P; Blackman, C
2011-09-01
Tungsten oxide films were deposited via Aerosol Assisted Chemical Vapour Deposition (AACVD) from the single-source precursor W(OPh)6. Film morphology and optimum deposition temperatures for formation of quasi-one-dimensional structures is influenced by the solvent 'carrier' used for deposition of the films with bulk porous films and nanostructured needles, hollow tubes and fibres obtained dependent on the solvent used and the deposition temperature. This influence of solvent could be exploited for the synthesis of other nanomaterials, and so provide a new and versatile route to develop and integrate nanostructured materials for device applications. PMID:22097557
Optimized chemical vapor deposition of borophosphosilicate glass films
NASA Astrophysics Data System (ADS)
Kern, W.; Kurylo, W. A.; Tino, C. J.
1985-06-01
The optimization of atmospheric-pressure chemical vapor deposition (APCVD) of borophosphosilicate glass (BPSG) to produce glass films with few particle containments is discussed. The tests that were conducted in order to determine the optimum deposition temperature and proper oxygen/hydride ratio are explained. A decrease in deposition temperature and an increase in the oxygen/hydride ratio maximized the APCVD reaction. The techniques used to analyze the composition of BPSG after densification are described; the tests revealed that the elemental composition of BPSG was not altered by APCVD. An explanation of the film profiling technique used to determine the stability of BPSG films during processing is provided; BPSG films remain stable if they are densified or fused prior to the application of wet treatments. A comparison of conventional tube-furnace heating with rapid isothermal heating for fusion flow of BPSG is presented; fusion tapering by rapid heating was attained in 30 seconds at 175 C versus 30 minutes for tube heating.
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.
Rajora, Manik; Zou, Pan; Yang, Yao Guang; Fan, Zhi Wen; Chen, Hung Yi; Wu, Wen Chieh; Li, Beizhi; Liang, Steven Y
2016-01-01
It can be observed from the experimental data of different processes that different process parameter combinations can lead to the same performance indicators, but during the optimization of process parameters, using current techniques, only one of these combinations can be found when a given objective function is specified. The combination of process parameters obtained after optimization may not always be applicable in actual production or may lead to undesired experimental conditions. In this paper, a split-optimization approach is proposed for obtaining multiple solutions in a single-objective process parameter optimization problem. This is accomplished by splitting the original search space into smaller sub-search spaces and using GA in each sub-search space to optimize the process parameters. Two different methods, i.e., cluster centers and hill and valley splitting strategy, were used to split the original search space, and their efficiency was measured against a method in which the original search space is split into equal smaller sub-search spaces. The proposed approach was used to obtain multiple optimal process parameter combinations for electrochemical micro-machining. The result obtained from the case study showed that the cluster centers and hill and valley splitting strategies were more efficient in splitting the original search space than the method in which the original search space is divided into smaller equal sub-search spaces. PMID:27625978
Parameter variations in prediction skill optimization at ECMWF
NASA Astrophysics Data System (ADS)
Ollinaho, P.; Bechtold, P.; Leutbecher, M.; Laine, M.; Solonen, A.; Haario, H.; Järvinen, H.
2013-11-01
Algorithmic numerical weather prediction (NWP) skill optimization has been tested using the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). We report the results of initial experimentation using importance sampling based on model parameter estimation methodology targeted for ensemble prediction systems, called the ensemble prediction and parameter estimation system (EPPES). The same methodology was earlier proven to be a viable concept in low-order ordinary differential equation systems, and in large-scale atmospheric general circulation models (ECHAM5). Here we show that prediction skill optimization is possible even in the context of a system that is (i) of very high dimensionality, and (ii) carefully tuned to very high skill. We concentrate on four closure parameters related to the parameterizations of sub-grid scale physical processes of convection and formation of convective precipitation. We launch standard ensembles of medium-range predictions such that each member uses different values of the four parameters, and make sequential statistical inferences about the parameter values. Our target criterion is the squared forecast error of the 500 hPa geopotential height at day three and day ten. The EPPES methodology is able to converge towards closure parameter values that optimize the target criterion. Therefore, we conclude that estimation and cost function-based tuning of low-dimensional static model parameters is possible despite the very high dimensional state space, as well as the presence of stochastic noise due to initial state and physical tendency perturbations. The remaining question before EPPES can be considered as a generally applicable tool in model development is the correct formulation of the target criterion. The one used here is, in our view, very selective. Considering the multi-faceted question of improving forecast model performance, a more general target criterion should be developed
Saoula, N.; Henda, K.; Kesri, R.
2008-09-23
In this study, we present the effect of the plasma deposition parameters on the mechanical properties of Ti/TiN multilayers. The elaboration of our films has been carried out by RF-Magnetron Sputtering (13.56 MHz) under nitrogen and argon reactive plasma at low pressure. The film depositions have been done on steel substrates. The first step of our study was the optimization of the depositions conditions in order to obtain good quality films. The amount of nitrogen in the sputtering gases being fixed at 10%. The total pressure was set between 2mTorr to 10mTorr. The deposited multilayers were characterized by X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), atomic force microscopy (AFM) and micro-indentation.
Identification of optimal parameter combinations for the emergence of bistability
NASA Astrophysics Data System (ADS)
Májer, Imre; Hajihosseini, Amirhossein; Becskei, Attila
2015-12-01
Bistability underlies cellular memory and maintains alternative differentiation states. Bistability can emerge only if its parameter range is either physically realizable or can be enlarged to become realizable. We derived a general rule and showed that the bistable range of a reaction parameter is maximized by a pair of other parameters in any gene regulatory network provided they satisfy a general condition. The resulting analytical expressions revealed whether or not such reaction pairs are present in prototypical positive feedback loops. They are absent from the feedback loop enclosed by protein dimers but present in both the toggle-switch and the feedback circuit inhibited by sequestration. Sequestration can generate bistability even at narrow feedback expression range at which cooperative binding fails to do so, provided inhibition is set to an optimal value. These results help to design bistable circuits and cellular reprogramming and reveal whether bistability is possible in gene networks in the range of realistic parameter values.
NWP model forecast skill optimization via closure parameter variations
NASA Astrophysics Data System (ADS)
Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.
2012-04-01
We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.
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.
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.
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
Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning
Brković, Milenko; Simić, Mirjana
2014-01-01
Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443
Using string invariants for prediction searching for optimal parameters
NASA Astrophysics Data System (ADS)
Bundzel, Marek; Kasanický, Tomáš; Pinčák, Richard
2016-02-01
We have developed a novel prediction method based on string invariants. The method does not require learning but a small set of parameters must be set to achieve optimal performance. We have implemented an evolutionary algorithm for the parametric optimization. We have tested the performance of the method on artificial and real world data and compared the performance to statistical methods and to a number of artificial intelligence methods. We have used data and the results of a prediction competition as a benchmark. The results show that the method performs well in single step prediction but the method's performance for multiple step prediction needs to be improved. The method works well for a wide range of parameters.
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.
Communication: Optimal parameters for basin-hopping global optimization based on Tsallis statistics
NASA Astrophysics Data System (ADS)
Shang, C.; Wales, D. J.
2014-08-01
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.
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.
Parameter Optimization for Laser Polishing of Niobium for SRF Applications
Zhao, Liang; Klopf, John Michael; Reece, Charles E.; Kelley, Michael J.
2013-06-01
Surface smoothness is critical to the performance of SRF cavities. As laser technology has been widely applied to metal machining and surface treatment, we are encouraged to use it on niobium as an alternative to the traditional wet polishing process where aggressive chemicals are involved. In this study, we describe progress toward smoothing by optimizing laser parameters on BCP treated niobium surfaces. Results shows that microsmoothing of the surface without ablation is achievable.
On optimization of sub-THz gyrotron parameters
Dumbrajs, O.; Nusinovich, G. S.
2012-10-15
The theory is developed describing how the optimization of gyrotron parameters should be done taking into account two effects deteriorating the gyrotron efficiency: the spread in electron velocities and the spread in the guiding center radii. The paper starts from qualitative analysis of the problem. This simplified theory is used for making some estimates for a specific gyrotron design. The same design is then studied by using more accurate numerical methods. Results of the latter treatment agree with former qualitative predictions.
A method of estimating optimal catchment model parameters
NASA Astrophysics Data System (ADS)
Ibrahim, Yaacob; Liong, Shie-Yui
1993-09-01
A review of a calibration method developed earlier (Ibrahim and Liong, 1992) is presented. The method generates optimal values for single events. It entails randomizing the calibration parameters over bounds such that a system response under consideration is bounded. Within the bounds, which are narrow and generated automatically, explicit response surface representation of the response is obtained using experimental design techniques and regression analysis. The optimal values are obtained by searching on the response surface for a point at which the predicted response is equal to the measured response and the value of the joint probability density function at that point in a transformed space is the highest. The method is demonstrated on a catchment in Singapore. The issue of global optimal values is addressed by applying the method on wider bounds. The results indicate that the optimal values arising from the narrow set of bounds are, indeed, global. Improvements which are designed to achieve comparably accurate estimates but with less expense are introduced. A linear response surface model is used. Two approximations of the model are studied. The first is to fit the model using data points generated from simple Monte Carlo simulation; the second is to approximate the model by a Taylor series expansion. Very good results are obtained from both approximations. Two methods of obtaining a single estimate from the individual event's estimates of the parameters are presented. The simulated and measured hydrographs of four verification storms using these estimates compare quite well.
Optimization of Parameter Selection for Partial Least Squares Model Development
NASA Astrophysics Data System (ADS)
Zhao, Na; Wu, Zhi-Sheng; Zhang, Qiao; Shi, Xin-Yuan; Ma, Qun; Qiao, Yan-Jiang
2015-07-01
In multivariate calibration using a spectral dataset, it is difficult to optimize nonsystematic parameters in a quantitative model, i.e., spectral pretreatment, latent factors and variable selection. In this study, we describe a novel and systematic approach that uses a processing trajectory to select three parameters including different spectral pretreatments, variable importance in the projection (VIP) for variable selection and latent factors in the Partial Least-Square (PLS) model. The root mean square errors of calibration (RMSEC), the root mean square errors of prediction (RMSEP), the ratio of standard error of prediction to standard deviation (RPD), and the determination coefficient of calibration (Rcal2) and validation (Rpre2) were simultaneously assessed to optimize the best modeling path. We used three different near-infrared (NIR) datasets, which illustrated that there was more than one modeling path to ensure good modeling. The PLS model optimizes modeling parameters step-by-step, but the robust model described here demonstrates better efficiency than other published papers.
Optimization of laser butt welding parameters with multiple performance characteristics
NASA Astrophysics Data System (ADS)
Sathiya, P.; Abdul Jaleel, M. Y.; Katherasan, D.; Shanmugarajan, B.
2011-04-01
This paper presents a study carried out on 3.5 kW cooled slab laser welding of 904 L super austenitic stainless steel. The joints have butts welded with different shielding gases, namely argon, helium and nitrogen, at a constant flow rate. Super austenitic stainless steel (SASS) normally contains high amount of Mo, Cr, Ni, N and Mn. The mechanical properties are controlled to obtain good welded joints. The quality of the joint is evaluated by studying the features of weld bead geometry, such as bead width (BW) and depth of penetration (DOP). In this paper, the tensile strength and bead profiles (BW and DOP) of laser welded butt joints made of AISI 904 L SASS are investigated. The Taguchi approach is used as a statistical design of experiment (DOE) technique for optimizing the selected welding parameters. Grey relational analysis and the desirability approach are applied to optimize the input parameters by considering multiple output variables simultaneously. Confirmation experiments have also been conducted for both of the analyses to validate the optimized parameters.
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.
Optimizing spectral CT parameters for material classification tasks.
Rigie, D S; La Rivière, P J
2016-06-21
In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC's) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC's predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.
Damage localization using experimental modal parameters and topology optimization
NASA Astrophysics Data System (ADS)
Niemann, Hanno; Morlier, Joseph; Shahdin, Amir; Gourinat, Yves
2010-04-01
This work focuses on the development of a damage detection and localization tool using the topology optimization feature of MSC.Nastran. This approach is based on the correlation of a local stiffness loss and the change in modal parameters due to damages in structures. The loss in stiffness is accounted by the topology optimization approach for updating undamaged numerical models towards similar models with embedded damages. Hereby, only a mass penalization and the changes in experimentally obtained modal parameters are used as objectives. The theoretical background for the implementation of this method is derived and programmed in a Nastran input file and the general feasibility of the approach is validated numerically, as well as experimentally by updating a model of an experimentally tested composite laminate specimen. The damages have been introduced to the specimen by controlled low energy impacts and high quality vibration tests have been conducted on the specimen for different levels of damage. These supervised experiments allow to test the numerical diagnosis tool by comparing the result with both NDT technics and results of previous works (concerning shifts in modal parameters due to damage). Good results have finally been achieved for the localization of the damages by the topology optimization.
Optimizing spectral CT parameters for material classification tasks.
Rigie, D S; La Rivière, P J
2016-06-21
In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC's) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC's predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430
NASA Astrophysics Data System (ADS)
Potters, M. G.; Bombois, X.; Mansoori, M.; Van den Hof, Paul M. J.
2016-08-01
Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.
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
Optimization of Neutrino Oscillation Parameters Using Differential Evolution
NASA Astrophysics Data System (ADS)
Ghulam, Mustafa; Faisal, Akram; Bilal, Masud
2013-03-01
We show how the traditional grid based method for finding neutrino oscillation parameters Δm2 and tan2 θ can be combined with an optimization technique, Differential Evolution (DE), to get a significant decrease in computer processing time required to obtain minimal chi-square (χ2) in four different regions of the parameter space. We demonstrate efficiency for the two-neutrinos case. For this, the χ2 function for neutrino oscillations is evaluated for grids with different density of points in standard allowed regions of the parameter space of Δm2 and tan2 θ using experimental and theoretical total event rates of chlorine (Homestake), Gallex+GNO, SAGE, Superkamiokande, and SNO detectors. We find that using DE in combination with the grid based method with small density of points can produce the results comparable with the one obtained using high density grid, in much lesser computation time.
Considerations for parameter optimization and sensitivity in climate models.
Neelin, J David; Bracco, Annalisa; Luo, Hao; McWilliams, James C; Meyerson, Joyce E
2010-12-14
Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention--here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models. PMID:21115841
Considerations for parameter optimization and sensitivity in climate models
Neelin, J. David; Bracco, Annalisa; Luo, Hao; McWilliams, James C.; Meyerson, Joyce E.
2010-01-01
Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention—here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models. PMID:21115841
Process Parameters Optimization in Single Point Incremental Forming
NASA Astrophysics Data System (ADS)
Gulati, Vishal; Aryal, Ashmin; Katyal, Puneet; Goswami, Amitesh
2016-04-01
This work aims to optimize the formability and surface roughness of parts formed by the single-point incremental forming process for an Aluminium-6063 alloy. The tests are based on Taguchi's L18 orthogonal array selected on the basis of DOF. The tests have been carried out on vertical machining center (DMC70V); using CAD/CAM software (SolidWorks V5/MasterCAM). Two levels of tool radius, three levels of sheet thickness, step size, tool rotational speed, feed rate and lubrication have been considered as the input process parameters. Wall angle and surface roughness have been considered process responses. The influential process parameters for the formability and surface roughness have been identified with the help of statistical tool (response table, main effect plot and ANOVA). The parameter that has the utmost influence on formability and surface roughness is lubrication. In the case of formability, lubrication followed by the tool rotational speed, feed rate, sheet thickness, step size and tool radius have the influence in descending order. Whereas in surface roughness, lubrication followed by feed rate, step size, tool radius, sheet thickness and tool rotational speed have the influence in descending order. The predicted optimal values for the wall angle and surface roughness are found to be 88.29° and 1.03225 µm. The confirmation experiments were conducted thrice and the value of wall angle and surface roughness were found to be 85.76° and 1.15 µm respectively.
Dynamic imaging model and parameter optimization for a star tracker.
Yan, Jinyun; Jiang, Jie; Zhang, Guangjun
2016-03-21
Under dynamic conditions, star spots move across the image plane of a star tracker and form a smeared star image. This smearing effect increases errors in star position estimation and degrades attitude accuracy. First, an analytical energy distribution model of a smeared star spot is established based on a line segment spread function because the dynamic imaging process of a star tracker is equivalent to the static imaging process of linear light sources. The proposed model, which has a clear physical meaning, explicitly reflects the key parameters of the imaging process, including incident flux, exposure time, velocity of a star spot in an image plane, and Gaussian radius. Furthermore, an analytical expression of the centroiding error of the smeared star spot is derived using the proposed model. An accurate and comprehensive evaluation of centroiding accuracy is obtained based on the expression. Moreover, analytical solutions of the optimal parameters are derived to achieve the best performance in centroid estimation. Finally, we perform numerical simulations and a night sky experiment to validate the correctness of the dynamic imaging model, the centroiding error expression, and the optimal parameters.
Optimizing experimental parameters for tracking of diffusing particles
NASA Astrophysics Data System (ADS)
Vestergaard, Christian L.
2016-08-01
We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion coefficient. The precision of estimators for the diffusion coefficient is affected by motion blur, limited photon statistics, and the length of recorded time series. We demonstrate for a particle undergoing free diffusion that precision is negligibly affected by motion blur in typical experiments, while optimizing photon counts and the number of recorded frames is the key to precision. Building on these results, we describe for a wide range of experimental scenarios how to choose experimental parameters in order to optimize the precision. Generally, one should choose quantity over quality: experiments should be designed to maximize the number of frames recorded in a time series, even if this means lower information content in individual frames.
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.
Optimizing experimental parameters for tracking of diffusing particles.
Vestergaard, Christian L
2016-08-01
We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion coefficient. The precision of estimators for the diffusion coefficient is affected by motion blur, limited photon statistics, and the length of recorded time series. We demonstrate for a particle undergoing free diffusion that precision is negligibly affected by motion blur in typical experiments, while optimizing photon counts and the number of recorded frames is the key to precision. Building on these results, we describe for a wide range of experimental scenarios how to choose experimental parameters in order to optimize the precision. Generally, one should choose quantity over quality: experiments should be designed to maximize the number of frames recorded in a time series, even if this means lower information content in individual frames. PMID:27627329
Shockwave lithotripsy-new concepts and optimizing treatment parameters.
Bhojani, Naeem; Lingeman, James E
2013-02-01
The treatment of kidney stone disease has changed dramatically over the past 30 years. This change is due in large part to the arrival of extracorporeal shock wave lithotripsy (ESWL). ESWL along with the advances in ureteroscopic and percutaneous techniques has led to the virtual extinction of open surgical treatments for kidney stone disease. Much research has gone into understanding how ESWL can be made more efficient and safe. This article discusses the parameters that can be used to optimize ESWL outcomes as well as the new concepts that are affecting the efficacy and efficiency of ESWL.
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.
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
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.
Optimization of drying process parameters for cauliflower drying.
Gupta, Manoj Kumar; Sehgal, V K; Arora, Sadhna
2013-02-01
The different sizes (3, 4 and 5 cm) of hybrid variety of cauliflower (variety no. 71) were dehydrated in thin layer at three temperatures of 55, 60 and 65 °C with velocities of 40, 50 and 60 m/min. Dehydrated samples were analyzed for vitamin C, rehydration ratio and browning. Statistical analysis indicated that drying time was dependent on initial size of cauliflower, drying air temperature and velocity, but rehydration ratio was significantly affected by the combined effect of temperature and airflow velocity. Vitamin C content of the dried cauliflower samples were significantly affected by temperature only and non enzymatic browning was function of temperature, airflow velocity, and combined effect of temperature and airflow velocity. Optimization of the drying process parameters for the given constraints resulted in 60.10(0)C, 59.28 m/min, 3.35 cm. The predicted responses for the optimized combination of process parameters were time, vitamin C content, rehydration ratio, and browning values of 491.22 min (time), 289.86 mg/100 g (Vitamin C), 6.91 ( rehydration ratio), and 0.14 (browning), respectively with the desirability factor of 0.787. PMID:24425888
Biohydrogen Production from Simple Carbohydrates with Optimization of Operating Parameters.
Muri, Petra; Osojnik-Črnivec, Ilja Gasan; Djinovič, Petar; Pintar, Albin
2016-01-01
Hydrogen could be alternative energy carrier in the future as well as source for chemical and fuel synthesis due to its high energy content, environmentally friendly technology and zero carbon emissions. In particular, conversion of organic substrates to hydrogen via dark fermentation process is of great interest. The aim of this study was fermentative hydrogen production using anaerobic mixed culture using different carbon sources (mono and disaccharides) and further optimization by varying a number of operating parameters (pH value, temperature, organic loading, mixing intensity). Among all tested mono- and disaccharides, glucose was shown as the preferred carbon source exhibiting hydrogen yield of 1.44 mol H(2)/mol glucose. Further evaluation of selected operating parameters showed that the highest hydrogen yield (1.55 mol H(2)/mol glucose) was obtained at the initial pH value of 6.4, T=37 °C and organic loading of 5 g/L. The obtained results demonstrate that lower hydrogen yield at all other conditions was associated with redirection of metabolic pathways from butyric and acetic (accompanied by H(2) production) to lactic (simultaneous H(2) production is not mandatory) acid production. These results therefore represent an important foundation for the optimization and industrial-scale production of hydrogen from organic substrates. PMID:26970800
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.
A novel force field parameter optimization method based on LSSVR for ECEPP.
Liu, Yunling; Tao, Lan; Lu, Jianjun; Xu, Shuo; Ma, Qin; Duan, Qingling
2011-03-23
In this paper, we propose a novel force field parameter optimization method based on LSSVR and optimize the torsion energy parameters of ECEPP force field. In this method force field parameter optimization problem is turned into a support vector regression problem. Protein samples for regression model training are chosen from Protein Data Bank. The experiments show that the optimized force-field parameters make both α-helix and β-hairpin structures more consistent with the experimental implications than the original parameters.
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.
Selection of optimal composition-control parameters for friable materials
Pak, Yu.N.; Vdovkin, A.V.
1988-05-01
A method for composition analysis of coal and minerals is proposed which uses scattered gamma radiation and does away with preliminary sample preparation to ensure homogeneous particle density, surface area, and size. Reduction of the error induced by material heterogeneity has previously been achieved by rotation of the control object during analysis. A further refinement is proposed which addresses the necessity that the contribution of the radiation scattered from each individual surface to the total intensity be the same. This is achieved by providing a constant linear rate of travel for the irradiated spot through back-and-forth motion of the sensor. An analytical expression is given for the laws of motion for the sensor and test tube which provides for uniform irradiated area movement along a path analogous to the Archimedes spiral. The relationships obtained permit optimization of measurement parameters in analyzing friable materials which are not uniform in grain size.
Design of Life Extending Controls Using Nonlinear Parameter Optimization
NASA Technical Reports Server (NTRS)
Lorenzo, Carl F.; Holmes, Michael S.; Ray, Asok
1998-01-01
This report presents the conceptual development of a life extending control system where the objective is to achieve high performance and structural durability of the plant. A life extending controller is designed for a reusable rocket engine via damage mitigation in both the fuel and oxidizer turbines while achieving high performance for transient responses of the combustion chamber pressure and the O2/H2 mixture ratio. This design approach makes use of a combination of linear and nonlinear controller synthesis techniques and also allows adaptation of the life extending controller module to augment a conventional performance controller of a rocket engine. The nonlinear aspect of the design is achieved using nonlinear parameter optimization of a prescribed control structure.
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.
Robust integrated autopilot/autothrottle design using constrained parameter optimization
NASA Technical Reports Server (NTRS)
Ly, Uy-Loi; Voth, Christopher; Sanjay, Swamy
1990-01-01
A multivariable control design method based on constrained parameter optimization was applied to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the following: (1) direct synthesis of a multivariable 'inner-loop' feedback control system based on total energy control principles; (2) synthesis of speed/altitude-hold designs as 'outer-loop' feedback/feedforward control systems around the above inner loop; and (3) direct synthesis of a combined 'inner-loop' and 'outer-loop' multivariable control system. The design procedure offers a direct and structured approach for the determination of a set of controller gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The presented approach may be applied to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by this method following careful problem formulation of the design objectives and constraints. Performance characteristics of the optimization design were improved over the current autopilot design on the B737-100 Transport Research Vehicle (TSRV) at the landing approach and cruise flight conditions; particularly in the areas of closed-loop damping, command responses, and control activity in the presence of turbulence.
Parameter optimization in differential geometry based solvation models
Wang, Bao; Wei, G. W.
2015-01-01
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
Parameter optimization in differential geometry based solvation models.
Wang, Bao; Wei, G W
2015-10-01
Differential geometry (DG) based solvation models are a new class of variational implicit solvent approaches that are able to avoid unphysical solvent-solute boundary definitions and associated geometric singularities, and dynamically couple polar and non-polar interactions in a self-consistent framework. Our earlier study indicates that DG based non-polar solvation model outperforms other methods in non-polar solvation energy predictions. However, the DG based full solvation model has not shown its superiority in solvation analysis, due to its difficulty in parametrization, which must ensure the stability of the solution of strongly coupled nonlinear Laplace-Beltrami and Poisson-Boltzmann equations. In this work, we introduce new parameter learning algorithms based on perturbation and convex optimization theories to stabilize the numerical solution and thus achieve an optimal parametrization of the DG based solvation models. An interesting feature of the present DG based solvation model is that it provides accurate solvation free energy predictions for both polar and non-polar molecules in a unified formulation. Extensive numerical experiment demonstrates that the present DG based solvation model delivers some of the most accurate predictions of the solvation free energies for a large number of molecules.
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.
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.
NASA Astrophysics Data System (ADS)
Gao, Hao
2016-04-01
For the treatment planning during intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT), beam fluence maps can be first optimized via fluence map optimization (FMO) under the given dose prescriptions and constraints to conformally deliver the radiation dose to the targets while sparing the organs-at-risk, and then segmented into deliverable MLC apertures via leaf or arc sequencing algorithms. This work is to develop an efficient algorithm for FMO based on alternating direction method of multipliers (ADMM). Here we consider FMO with the least-square cost function and non-negative fluence constraints, and its solution algorithm is based on ADMM, which is efficient and simple-to-implement. In addition, an empirical method for optimizing the ADMM parameter is developed to improve the robustness of the ADMM algorithm. The ADMM based FMO solver was benchmarked with the quadratic programming method based on the interior-point (IP) method using the CORT dataset. The comparison results suggested the ADMM solver had a similar plan quality with slightly smaller total objective function value than IP. A simple-to-implement ADMM based FMO solver with empirical parameter optimization is proposed for IMRT or VMAT.
NASA Astrophysics Data System (ADS)
Chen, Xu; Zhang, Ji-Hong; Liu, Wei; Liang, Yong-Sheng; Feng, Ji-Qiang
2013-12-01
In the situation of limited bandwidth, how to improve the performance of scalable video coding plays an important role in video coding. The previously proposed scalable video coding optimization schemes concentrate on reducing coding computation or trying to achieve consistent video quality; however, the connections between coding scheme, transmission environments, and users' accesses manner were not jointly considered. This article proposes a H.264/SVC (scalable video codec) parameter optimization scheme, which attempt to make full use of limited bandwidth, to achieve better peak signal-to-noise ratio, based on the joint measure of user bandwidth range and probability density distribution. This algorithm constructs a relationship map which consists of the bandwidth range of multiple users and the quantified quality increments measure, QP e , in order to make effective use of the video coding bit-stream. A medium grain scalability fragmentation optimization algorithm is also presented with respect to user bandwidth probability density distribution, encoding bit rate, and scalability. Experiments on a public dataset show that this method provides significant average quality improvement for streaming video applications.
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)
Klein, Stefan; Finger, Friedhelm; Carius, Reinhard; Stutzmann, Martin
2005-07-01
Microcrystalline silicon (μc-Si:H) of superior quality can be prepared using the hot-wire chemical-vapor deposition method (HWCVD). At a low substrate temperature (TS) of 185 °C excellent material properties and solar cell performance were obtained with spin densities of 6×1015cm-3 and solar cell efficiencies up to 9.4%, respectively. In this study we have systematically investigated the influence of various deposition parameters on the deposition rate and the material properties. For this purpose, thin films and solar cells were prepared at specific substrate and filament temperatures and deposition pressures (pD), covering the complete range from amorphous to highly crystalline material by adjusting the silane concentration. The influence of these deposition parameters on the chemical reactions at the filament and in the gas phase qualitatively explains the behavior of the structural composition and the formation of defects. In particular, we propose that the deposition rate is determined by the production of reactive species at the filament and a particular atomic-hydrogen-to-silicon ratio is found at the microcrystalline/amorphous transition. The structural, optical, and electronic properties were studied using Raman and infrared spectroscopies, optical-absorption measurements, electron-spin resonance, and dark and photoconductivities. These experiments show that higher TS and pD lead to a deterioration of the material quality, i.e., much higher defect densities, oxygen contaminations, and SiH absorption at 2100cm-1. Similar to plasma enhanced chemical-vapor deposition material, μc-Si:H solar cells prepared with HW i layers show increasing open circuit voltages (Voc) with increasing silane concentration and best performance is achieved near the transition to amorphous growth. Such solar cells prepared at low TS exhibit very high Voc up to 600 mV and fill factors above 70% with i layers prepared by HWCVD.
NASA Astrophysics Data System (ADS)
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
He, C.N.; Zhao, N.Q.; Shi, C.S.; Song, S.Z.
2010-09-15
In order to optimize the chemical vapor deposition process for fabrication of carbon nanotube/Al composite powders, the effect of different reaction conditions (such as reaction temperature, reaction time, and reaction gas ratio) on the morphological and structural development of the powder and dispersion of CNTs in Al powder was investigated using transmission electron microscope. The results showed that low temperatures (500-550 {sup o}C) give rise to herringbone-type carbon nanofibers and high temperatures (600-630 {sup o}C) lead to multi-walled CNTs. Long reaction times broaden the CNT size distribution and increase the CNT yield. Appropriate nitrogen flow is preferred for CNT growth, but high and low nitrogen flow result in carbon nanospheres and CNTs with coarse surfaces, respectively. Above results show that appropriate parameters are effective in dispersing the nanotubes in the Al powder which simultaneously protects the nanotubes from damage.
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.
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.
NASA Astrophysics Data System (ADS)
Vahedein, Yashar Seyed
Template-based chemical vapor deposition (TB-CVD) is a versatile technique for manufacturing carbon nanotubes (CNTs) or CNT-based devices for various applications. In this process, carbon is deposited by thermal decomposition of a carbon-based precursor gas inside the nanoscopic cylindrical pores of anodized aluminum oxide (AAO) templates to form CNTs. Experimental results show CNT formation in templates is controlled by TB-CVD process parameters, such as time, temperature and flow rate. Optimization of this process is done empirically, requiring tremendous time and effort. Moreover, there is a need for a more comprehensive and low cost way to characterize the flow in the furnace in order to understand how process parameters may affect CNT formation. In this report, we describe the development of four, three-dimensional numerical models, each varying in complexity, to elucidate the thermo-fluid behavior inside the TB-CVD process. Using computational fluid dynamic (CFD) commercial codes, the four models were compared to determine how the presence of the template and boat, composition of the precursor gas, and consumption of species at the template surface affect the temperature profiles and velocity fields in the system. The most accurate model will be used to conduct particle injection/tracking near the templates and to characterize the particle residence time as a function of time and consumption rate. The developments in this work build the groundwork for explaining how flow characteristics affect carbon deposition on templates in any CVD reactor.
Effect of processing parameters on surface finish for fused deposition machinable wax patterns
NASA Technical Reports Server (NTRS)
Roberts, F. E., III
1995-01-01
This report presents a study on the effect of material processing parameters used in layer-by-layer material construction on the surface finish of a model to be used as an investment casting pattern. The data presented relate specifically to fused deposition modeling using a machinable wax.
Mathematical modeling of plasma deposition and hardening of coatings-switched electrical parameters
NASA Astrophysics Data System (ADS)
Kadyrmetov, A. M.; Sharifullin, S. N.; Pustovalov, AS
2016-01-01
This paper presents the results of simulation of plasma deposition and hardening of coatings in modulating the electrical parameters. Mathematical models are based on physical models of gas-dynamic mechanisms more dynamic and thermal processes of the plasma jet. As an example the modeling of dynamic processes of heterogeneous plasma jet, modulated current pulses indirect arc plasma torch.
Influence of deposition parameters on hard Cr-Al-N coatings deposited by multi-arc ion plating
NASA Astrophysics Data System (ADS)
Wang, Lei; Zhang, Shihong; Chen, Zhong; Li, Jinlong; Li, Mingxi
2012-02-01
The Cr-Al-N coatings were synthesized at various substrate bias voltages and nitrogen partial pressures by multi-arc ion plating (M-AIP). The relationships between deposition parameters and coating properties were investigated. Morphologies, phase structures, hardness and adhesion strength of the coatings were analyzed by SEM, XRD, XPS, nano-indenter and scratch tester. The results indicated that with the increase of substrate bias voltages, the surface macroparticles and deposition rate reduced mainly for the resputtering phenomenon. The (Cr, Al)N solid-solution phase kept unchanged, but the Cr2N and AlN phases disappeared gradually. Due to the change of phase structures and residual compressive stress, the hardness values decreased and the adhesion strength decreased initially and then increased. Similarly, with the increase of nitrogen partial pressures, the phase structures of CrAlN coatings varied from Cr + Cr2N + (Cr,Al)N to Cr2N + (Cr,Al)N. The surface macroparticles increased due to the decreasing resputtering efficiency, and the deposition rate increased initially and then decreased due to the resputtering phenomenon. With increasing nitrogen partial pressures, adhesion strength decreased initially and then increased. The microhardness increased mainly due to the increase of Cr2N contents and decrease of metal macroparticles.
Bolch, W E; Farfán, E B; Huh, C; Huston, T E; Bolch, W E
2001-10-01
Risk assessment associated with the inhalation of radioactive aerosols requires as an initial step the determination of particle deposition within the various anatomic regions of the respiratory tract. The model outlined in ICRP Publication 66 represents to date one of the most complete overall descriptions of not only particle deposition, but of particle clearance and local radiation dosimetry of lung tissues. In this study, a systematic review of the deposition component within the ICRP 66 respiratory tract model was conducted in which probability density functions were assigned to all input parameters. These distributions were subsequently incorporated within a computer code LUDUC (LUng Dose Uncertainty Code) in which Latin hypercube sampling techniques are used to generate multiple (e.g., 1,000) sets of input vectors (i.e., trials) for all of the model parameters needed to assess particle deposition within the extrathoracic (anterior and posterior), bronchial, bronchiolar, and alveolar-interstitial regions of the ICRP 66 respiratory tract model. Particle deposition values for the various trial simulations were shown to be well described by lognormal probability distributions. Geometric mean deposition fractions from LUDUC were found to be within approximately +/- 10% of the single-value estimates from the LUDEP computer code for each anatomic region and for particle diameters ranging from 0.001 to 50 microm. In all regions of the respiratory tract, LUDUC simulations for an adult male at light exertion show that uncertainties in particle deposition fractions are distributed only over a range of about a factor of approximately 2-4 for particle sizes between 0.005 to 0.2 microm. Below 0.005 microm, uncertainties increase only for deposition within the alveolar region. At particle sizes exceeding 1 microm, uncertainties in the deposition fraction within the extrathoracic regions are relatively small, but approach a factor of 20 for deposition in the bronchial
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.
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.
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.
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.
Direct Multiple Shooting Optimization with Variable Problem Parameters
NASA Technical Reports Server (NTRS)
Whitley, Ryan J.; Ocampo, Cesar A.
2009-01-01
Taking advantage of a novel approach to the design of the orbital transfer optimization problem and advanced non-linear programming algorithms, several optimal transfer trajectories are found for problems with and without known analytic solutions. This method treats the fixed known gravitational constants as optimization variables in order to reduce the need for an advanced initial guess. Complex periodic orbits are targeted with very simple guesses and the ability to find optimal transfers in spite of these bad guesses is successfully demonstrated. Impulsive transfers are considered for orbits in both the 2-body frame as well as the circular restricted three-body problem (CRTBP). The results with this new approach demonstrate the potential for increasing robustness for all types of orbit transfer problems.
Adaptive neuro-fuzzy estimation of optimal lens system parameters
NASA Astrophysics Data System (ADS)
Petković, Dalibor; Pavlović, Nenad T.; Shamshirband, Shahaboddin; Mat Kiah, Miss Laiha; Badrul Anuar, Nor; Idna Idris, Mohd Yamani
2014-04-01
Due to the popularization of digital technology, the demand for high-quality digital products has become critical. The quantitative assessment of image quality is an important consideration in any type of imaging system. Therefore, developing a design that combines the requirements of good image quality is desirable. Lens system design represents a crucial factor for good image quality. Optimization procedure is the main part of the lens system design methodology. Lens system optimization is a complex non-linear optimization task, often with intricate physical constraints, for which there is no analytical solutions. Therefore lens system design provides ideal problems for intelligent optimization algorithms. There are many tools which can be used to measure optical performance. One very useful tool is the spot diagram. The spot diagram gives an indication of the image of a point object. In this paper, one optimization criterion for lens system, the spot size radius, is considered. This paper presents new lens optimization methods based on adaptive neuro-fuzzy inference strategy (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.
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
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.
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 Russian roulette parameters for the KENO computer code
Hoffman, T.J.
1982-10-01
Proper specification of the (statistical) weight standards for Monte Carlo calculations can lead to a substantial reduction in computer time. Frequently these weights are set intuitively. When optimization is performed, it is usually based on a simplified model (to enable mathematical analysis) and involves minimization of the sample variance. In this report, weight standards are optimized through consideration of the actual implementation of Russian roulette in the KENO computer code. The goal is minimization of computer time rather than minimization of sample variance. Verification of the development and assumptions is obtained from Monte Carlo simulations. The results indicate that the current default weight standards are appropriate for most problems in which thermal neutron transport is not a major consumer of computer time. For thermal systems, the optimization technique described in this report should be used.
Certain optimal parameters of high-velocity Venturi ejection tubes
NASA Astrophysics Data System (ADS)
Stark, S. B.; Reznichenko, I. G.; Pavlenko, Y. P.
1984-11-01
The influence of the geometrical characteristics of centrifugal nozzles in high velocity Venturi ejection tubes for atomizing liquid in gas cleaning plant is analyzed. An optimal value of the nozzle geometrical characteristic, which is a function of the degree of filling of the nozzle outlet opening by the liquid, is given, at which the throat length is independent of water pressure before the nozzle.
Zhang, L.; Franke, J.E.; Niemczyk, T.M.; Haaland, D.M.
1997-02-01
Infrared (IR) external reflection spectroscopy has been optimized for the quantitative determination of composition and film thickness of borophosphosilicate glass (BPSG) deposited on silicon wafer substrates. The precision of the partial least-squares calibrations for boron and phosphorus contents and thin-film thickness were measured as the cross-validated standard error of prediction statistic. The results showed that BPSG IR reflection spectra collected over a wide range of incident IR radiation angles (15{degree}, 25{degree}, 45{degree}, and 60{degree}) can be used for the simultaneous quantification of these three BPSG parameters. When high angles of incidence were employed, the measurement was found to be more sensitive to small errors in the angle of incidence. The polarization state of the incident IR radiation did not noticeably affect the prediction of the three calibrated BPSG parameters. The results achieved in this study provide guidelines for at-line process monitoring and quality control of BPSG thin films used in the fabrication of microelectronic devices. {copyright} {ital 1997} {ital Society for Applied Spectroscopy}
An all-at-once factorial method to optimize dip-pen deposition of liquid protein inks
NASA Astrophysics Data System (ADS)
Henning, A. K.; Rozhok, S.; Fragala, J.; Shile, R.; Ouyang, K.
2013-03-01
An all-at-once factorial method is presented, which optimizes protein ink deposition using microfabricated pens by identifying the pen design which writes the greatest number of uniform-size spots or droplets without re-inking. Pen features associated with capillary ink transport are varied according to statistical design-of-experiment (SDOE) principles, and evaluated using a special 1D pen array of twelve pens. Variable parameter pens are bracketed by control pens. Each pen array element embodies one component of the SDOE matrix. All parameters are evaluated simultaneously with a single droplet writing pass. Results can also be evaluated simultaneously, leading to rapid choice of those pen parameters which deliver the greatest number of printed features having the smallest coefficient of variation.
Optimal parameters of 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.
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.
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.
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)
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.
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.
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.
Optimal parameters of monolithic high-contrast grating mirrors.
Marciniak, Magdalena; Gębski, Marcin; Dems, Maciej; Haglund, Erik; Larsson, Anders; Riaziat, Majid; Lott, James A; Czyszanowski, Tomasz
2016-08-01
In this Letter a fully vectorial numerical model is used to search for the construction parameters of monolithic high-contrast grating (MHCG) mirrors providing maximal power reflectance. We determine the design parameters of highly reflecting MHCG mirrors where the etching depth of the stripes is less than two wavelengths in free space. We analyze MHCGs in a broad range of real refractive index values corresponding to most of the common optoelectronic materials in use today. Our results comprise a complete image of possible highly reflecting MHCG mirror constructions for potential use in optoelectronic devices and systems. We support the numerical analysis by experimental verification of the high reflectance via a GaAs MHCG designed for a wavelength of 980 nm.
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.
GEANT4 for breast dosimetry: parameters optimization study
NASA Astrophysics Data System (ADS)
Fedon, C.; Longo, F.; Mettivier, G.; Longo, R.
2015-08-01
Mean glandular dose (MGD) is the main dosimetric quantity in mammography. MGD evaluation is obtained by multiplying the entrance skin air kerma (ESAK) by normalized glandular dose (DgN) coefficients. While ESAK is an empirical quantity, DgN coefficients can only be estimated with Monte Carlo (MC) methods. Thus, a MC parameters benchmark is needed for effectively evaluating DgN coefficients. GEANT4 is a MC toolkit suitable for medical purposes that offers to the users several computational choices. In this work we investigate the GEANT4 performances testing the main PhysicsLists for medical applications. Four electromagnetic PhysicsLists were implemented: the linear attenuation coefficients were calculated for breast glandularity 0%, 50%, 100% in the energetic range 8-50 keV and DgN coefficients were evaluated. The results were compared with published data. Fit equations for the estimation of the G-factor parameter, introduced by the literature for converting the dose delivered in the heterogeneous medium to that in the glandular tissue, are proposed and the application of this parameter interaction-by-interaction or retrospectively is discussed. G4EmLivermorePhysicsList shows the best agreement for the linear attenuation coefficients both with theoretical values and published data. Moreover, excellent correlation factor ({{r}2}>0.99 ) is found for the DgN coefficients with the literature. The final goal of this study is to identify, for the first time, a benchmark of parameters that could be useful for future breast dosimetry studies with GEANT4.
GEANT4 for breast dosimetry: parameters optimization study.
Fedon, C; Longo, F; Mettivier, G; Longo, R
2015-08-21
Mean glandular dose (MGD) is the main dosimetric quantity in mammography. MGD evaluation is obtained by multiplying the entrance skin air kerma (ESAK) by normalized glandular dose (DgN) coefficients. While ESAK is an empirical quantity, DgN coefficients can only be estimated with Monte Carlo (MC) methods. Thus, a MC parameters benchmark is needed for effectively evaluating DgN coefficients. GEANT4 is a MC toolkit suitable for medical purposes that offers to the users several computational choices. In this work we investigate the GEANT4 performances testing the main PhysicsLists for medical applications. Four electromagnetic PhysicsLists were implemented: the linear attenuation coefficients were calculated for breast glandularity 0%, 50%, 100% in the energetic range 8-50 keV and DgN coefficients were evaluated. The results were compared with published data. Fit equations for the estimation of the G-factor parameter, introduced by the literature for converting the dose delivered in the heterogeneous medium to that in the glandular tissue, are proposed and the application of this parameter interaction-by-interaction or retrospectively is discussed. G4EmLivermorePhysicsList shows the best agreement for the linear attenuation coefficients both with theoretical values and published data. Moreover, excellent correlation factor (r2>0.99) is found for the DgN coefficients with the literature. The final goal of this study is to identify, for the first time, a benchmark of parameters that could be useful for future breast dosimetry studies with GEANT4. PMID:26267405
Parameter selection for the SSC trade-offs and optimization
Edwards, D.A.; Syphers, M.J.
1991-10-14
In November of 1988, a site was selected in the state of Texas for the SSC. In January of 1989, the SSC Laboratory was established in Texas to adapt the design of the collider to the site and to manage the construction of the project. This paper describes the evolution of the SSC design since site selection, notes the increased concentration on the injector system, and addresses the rationale for choice of parameters.
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 parameters in hybrid welding of aluminum alloy
NASA Astrophysics Data System (ADS)
Jokinen, Tommi; Jernstroem, Petteri; Karhu, Miikka; Vanttaja, Ilkka; Kujanpaeae, Veli
2003-03-01
Numerous advantages of hybrid welding, in which laser beam and arc has combined, over autogenous laser welding has been reported. Especially in case of inaccurate joint preparation or fixturing of the plates to be welded because of the filler metal added to the process through MIG-welding. Also additional heat, coming from the arc to the process, enables higher welding speed and deeper penetration. Aluminum alloy (AlMg3) was used in the experiments. Welding was carried out by using the hybrid process (combination of Nd:YAG- and MIG-welding) in the flat position. The joint preparation was carried out as shear cut and different gap widths were used. Welding experiments were made systematically using a statistical experiment procedure called TAGUCHI-method. Parameters, for example alignment of point of arc and laser, varied in experiments. Also characteristic parameters of both welding methods were changed according to the experimental procedure. In this paper results of welding experiments are reported as well as parameters used. A phenomenona of the hybrid process with aluminum is discussed and also reasons for weld defects occurred are pointed out.
Optimization of technological parameters for preparation of lycopene microcapsules.
Guo, Hui; Huang, Ying; Qian, Jun-Qing; Gong, Qiu-Yi; Tang, Ying
2014-07-01
Lycopene belongs to the carotenoid family with high degree of unsaturation and all-trans form. Lycopene is easy to isomerize and auto oxide by heat, light, oxygen and different food matrices. With an increasing understanding of the health benefit of lycopene, to enhance stability and bioavailability of lycopene, ultrasonic emulsification was used to prepare lycopene microcapsules in this article. The results optimized by response surface methodology (RSM) for microcapsules consisted of four major steps: (1) 0.54 g glycerin monostearate was fully dissolved in 5 mL ethyl acetate and then added 0.02 g lycopene to form an organic phase, 100.7 mL distilled water which dissolved 0.61 g synperonic pe(R)/F68 as the aqueous phase; (2) the organic phase was pulled into the aqueous phase under stirring at 60 °C water bath for 5 min; (3) the mixture was then ultrasonic homogenized at 380 W for 20 min to form a homogenous emulsion; (4) the resulting emulsion was rotary evaporated at 50 °C water bath for 10 min under a pressure of 20 MPa. Encapsulation efficiency (EE) of lycopene microcapsules under the optimized conditions approached to 64.4%. PMID:24966425
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
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
Design parameter analysis of hybrid optimal controlled structures
Cheng, F.Y.; Tian, P.
1994-12-31
This paper presents a hybrid control system composed of an active hydraulic actuator and a passive liquid-mass damper. The system is built with structural bracing and can reduce structural dynamic response by providing passive inertia force, passive damping force and active control force. Fundamental equations governing the hybrid control system are derived and influence parameters are numerically analyzed. Numerical results show that in this hybrid control system the effective liquid-mass plays an important role in reducing structural dynamic response and requiring smaller control forces than either passive or active control system.
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.
Enhancing parameter precision of optimal quantum estimation by quantum screening
NASA Astrophysics Data System (ADS)
Jiang, Huang; You-Neng, Guo; Qin, Xie
2016-02-01
We propose a scheme of quantum screening to enhance the parameter-estimation precision in open quantum systems by means of the dynamics of quantum Fisher information. The principle of quantum screening is based on an auxiliary system to inhibit the decoherence processes and erase the excited state to the ground state. By comparing the case without quantum screening, the results show that the dynamics of quantum Fisher information with quantum screening has a larger value during the evolution processes. Project supported by the National Natural Science Foundation of China (Grant No. 11374096), the Natural Science Foundation of Guangdong Province, China (Grants No. 2015A030310354), and the Project of Enhancing School with Innovation of Guangdong Ocean University (Grants Nos. GDOU2014050251 and GDOU2014050252).
Measuring Digital PCR Quality: Performance Parameters and Their Optimization.
Lievens, A; Jacchia, S; Kagkli, D; Savini, C; Querci, M
2016-01-01
Digital PCR is rapidly being adopted in the field of DNA-based food analysis. The direct, absolute quantification it offers makes it an attractive technology for routine analysis of food and feed samples for their composition, possible GMO content, and compliance with labelling requirements. However, assessing the performance of dPCR assays is not yet well established. This article introduces three straightforward parameters based on statistical principles that allow users to evaluate if their assays are robust. In addition, we present post-run evaluation criteria to check if quantification was accurate. Finally, we evaluate the usefulness of Poisson confidence intervals and present an alternative strategy to better capture the variability in the analytical chain. PMID:27149415
Optimal FES parameters based on mechanomyographic efficiency index.
Krueger-Beck, Eddy; Scheeren, Eduardo M; Nogueira-Neto, Guilherme N; Button, Vera Lucia S N; Nohama, Percy
2010-01-01
Functional electrical stimulation (FES) can artificially elicit movements in spinal cord injured (SCI) subjects. FES control strategies involve monitoring muscle features and setting FES profiles so as to postpone the installation of muscle fatigue or nerve cell adaptation. Mechanomyography (MMG) sensors register the lateral oscillations of contracting muscles. This paper presents an MMG efficiency index (EI) that may indicate most efficient FES electrical parameters to control functional movements. Ten healthy and three SCI volunteers participated in the study. Four FES profiles with two FES sessions were applied with in-between 15min rest interval. MMG RMS and median frequency were inserted into the EI equation. EI increased along the test. FES profile set to 1kHz pulse frequency, 200εs active pulse duration and burst frequency of 50Hz was the most efficient.
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.
Parameter and cost optimizations for a modular stellarator reactor
NASA Astrophysics Data System (ADS)
Hitchon, W. N. G.; Johnson, P. C.; Watson, C. J. H.
1983-02-01
The physical scaling and cost scaling of a modular stellarator reactor are described. It is shown that configurations based on l=2 are best able to support adequate beta, and physical relationships are derived which enable the geometry and parameters of an l=2 modular stellarator to be defined. A cost scaling for the components of the nuclear island is developed using Starfire (tokamak reactor study) engineering as a basis. It is shown that for minimum cost the stellarator should be of small aspect ratio. For a 4000 MWth plant, as Starfire, the optimum configuration is a 15 coil, 3 field period, l=2 device with a major radius of 16 m and a plasma minor radius of 2 m; and with a conservative wall loading of 2 MW/m2 and an average beta of 3.9%; the estimated cost per kilowatt (electrical) is marginally (7%) greater than Starfire.
Measuring Digital PCR Quality: Performance Parameters and Their Optimization
Lievens, A.; Jacchia, S.; Kagkli, D.; Savini, C.; Querci, M.
2016-01-01
Digital PCR is rapidly being adopted in the field of DNA-based food analysis. The direct, absolute quantification it offers makes it an attractive technology for routine analysis of food and feed samples for their composition, possible GMO content, and compliance with labelling requirements. However, assessing the performance of dPCR assays is not yet well established. This article introduces three straightforward parameters based on statistical principles that allow users to evaluate if their assays are robust. In addition, we present post-run evaluation criteria to check if quantification was accurate. Finally, we evaluate the usefulness of Poisson confidence intervals and present an alternative strategy to better capture the variability in the analytical chain. PMID:27149415
Parameter Optimization for the Gaussian Model of Folded Proteins
NASA Astrophysics Data System (ADS)
Erman, Burak; Erkip, Albert
2000-03-01
Recently, we proposed an analytical model of protein folding (B. Erman, K. A. Dill, J. Chem. Phys, 112, 000, 2000) and showed that this model successfully approximates the known minimum energy configurations of two dimensional HP chains. All attractions (covalent and non-covalent) as well as repulsions were treated as if the monomer units interacted with each other through linear spring forces. Since the governing potential of the linear springs are derived from a Gaussian potential, the model is called the ''Gaussian Model''. The predicted conformations from the model for the hexamer and various 9mer sequences all lie on the square lattice, although the model does not contain information about the lattice structure. Results of predictions for chains with 20 or more monomers also agreed well with corresponding known minimum energy lattice structures. However, these predicted conformations did not lie exactly on the square lattice. In the present work, we treat the specific problem of optimizing the potentials (the strengths of the spring constants) so that the predictions are in better agreement with the known minimum energy structures.
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.
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)
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.
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.
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'.
Rethinking design parameters in the search for optimal dynamic seating.
Pynt, Jennifer
2015-04-01
Dynamic seating design purports to lessen damage incurred during sedentary occupations by increasing sitter movement while modifying muscle activity. Dynamic sitting is currently defined by O'Sullivan et al. ( 2013a) as relating to 'the increased motion in sitting which is facilitated by the use of specific chairs or equipment' (p. 628). Yet the evidence is conflicting that dynamic seating creates variation in the sitter's lumbar posture or muscle activity with the overall consensus being that current dynamic seating design fails to fulfill its goals. Research is needed to determine if a new generation of chairs requiring active sitter involvement fulfills the goals of dynamic seating and aids cardio/metabolic health. This paper summarises the pursuit of knowledge regarding optimal seated spinal posture and seating design. Four new forms of dynamic seating encouraging active sitting are discussed. These are 1) The Core-flex with a split seatpan to facilitate a walking action while seated 2) the Duo balans requiring body action to create rocking 3) the Back App and 4) Locus pedestal stools both using the sitter's legs to drive movement. Unsubstantiated claims made by the designers of these new forms of dynamic seating are outlined. Avenues of research are suggested to validate designer claims and investigate whether these designs fulfill the goals of dynamic seating and assist cardio/metabolic health. Should these claims be efficacious then a new definition of dynamic sitting is suggested; 'Sitting in which the action is provided by the sitter, while the dynamic mechanism of the chair accommodates that action'. PMID:25892386
CH4 parameter estimation in CLM4.5bgc using surrogate global optimization
NASA Astrophysics Data System (ADS)
Müller, J.; Paudel, R.; Shoemaker, C. A.; Woodbury, J.; Wang, Y.; Mahowald, N.
2015-10-01
Over the anthropocene methane has increased dramatically. Wetlands are one of the major sources of methane to the atmosphere, but the role of changes in wetland emissions is not well understood. The Community Land Model (CLM) of the Community Earth System Models contains a module to estimate methane emissions from natural wetlands and rice paddies. Our comparison of CH4 emission observations at 16 sites around the planet reveals, however, that there are large discrepancies between the CLM predictions and the observations. The goal of our study is to adjust the model parameters in order to minimize the root mean squared error (RMSE) between model predictions and observations. These parameters have been selected based on a sensitivity analysis. Because of the cost associated with running the CLM simulation (15 to 30 min on the Yellowstone Supercomputing Facility), only relatively few simulations can be allowed in order to find a near-optimal solution within an acceptable time. Our results indicate that the parameter estimation problem has multiple local minima. Hence, we use a computationally efficient global optimization algorithm that uses a radial basis function (RBF) surrogate model to approximate the objective function. We use the information from the RBF to select parameter values that are most promising with respect to improving the objective function value. We show with pseudo data that our optimization algorithm is able to make excellent progress with respect to decreasing the RMSE. Using the true CH4 emission observations for optimizing the parameters, we are able to significantly reduce the overall RMSE between observations and model predictions by about 50 %. The methane emission predictions of the CLM using the optimized parameters agree better with the observed methane emission data in northern and tropical latitudes. With the optimized parameters, the methane emission predictions are higher in northern latitudes than when the default parameters are
NASA 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.
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
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
Multi-objective parameter optimization of common land model using adaptive surrogate modeling
NASA Astrophysics Data System (ADS)
Gong, W.; Duan, Q.; Li, J.; Wang, C.; Di, Z.; Dai, Y.; Ye, A.; Miao, C.
2015-05-01
Parameter specification usually has significant influence on the performance of land surface models (LSMs). However, estimating the parameters properly is a challenging task due to the following reasons: (1) LSMs usually have too many adjustable parameters (20 to 100 or even more), leading to the curse of dimensionality in the parameter input space; (2) LSMs usually have many output variables involving water/energy/carbon cycles, so that calibrating LSMs is actually a multi-objective optimization problem; (3) Regional LSMs are expensive to run, while conventional multi-objective optimization methods need a large number of model runs (typically ~105-106). It makes parameter optimization computationally prohibitive. An uncertainty quantification framework was developed to meet the aforementioned challenges, which include the following steps: (1) using parameter screening to reduce the number of adjustable parameters, (2) using surrogate models to emulate the responses of dynamic models to the variation of adjustable parameters, (3) using an adaptive strategy to improve the efficiency of surrogate modeling-based optimization; (4) using a weighting function to transfer multi-objective optimization to single-objective optimization. In this study, we demonstrate the uncertainty quantification framework on a single column application of a LSM - the Common Land Model (CoLM), and evaluate the effectiveness and efficiency of the proposed framework. The result indicate that this framework can efficiently achieve optimal parameters in a more effective way. Moreover, this result implies the possibility of calibrating other large complex dynamic models, such as regional-scale LSMs, atmospheric models and climate models.
Optimization of parameters for coverage of low molecular weight proteins.
Müller, Stephan A; Kohajda, Tibor; Findeiss, Sven; Stadler, Peter F; Washietl, Stefan; Kellis, Manolis; von Bergen, Martin; 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)
Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.
2013-07-01
Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (μGA) as an example of a stochastic approach. The optimizations were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations were conducted that differ in the model formulation ("smoothed code" versus standard code) with respect to the FD method and in the population size and number of possibilities with respect to the μGA method. The FD method fails to estimate optimal parameters due to the ill-shaped nature of the cost function caused by the strong non-linearity of the system, whereas the genetic algorithms can effectively estimate near optimal parameters. The results of the study indicate that the sophisticated stochastic approach (μGA) is of practical use for parameter optimization of a coupled ocean-sea ice model with a medium-sized horizontal resolution of 50 km × 50 km as used in this study.
NASA Astrophysics Data System (ADS)
Yousefi, Amin Termeh; Mahmood, Mohamad Rusop; Ikeda, Shoichiro
2016-07-01
According to the unique properties of Carbon nanotubes (CNTs), they have been under scientific investigation for more than fifteen years in different applications. Here we reported the effect of temperature on camphor in a wide range of 500-1150 ˚C. The results indicate that camphor did not decompose below 500 ˚C but very short-length tubes emerged from the silicon substrate at 550 ˚C which is suggesting that the catalyst activity. According to the results, the CNT growth rate was abruptly increased at 600 ˚C. This process was done on the same condition by optimizing the temperature up to 900 ˚C. FESEM images indicate the highest catalyst activity at 850 ˚C which direct the experiment to grow purified CNT up to 3 µm in the length. This result suggests that, at low temperatures, the catalyst-support interaction is strong enough not to let the metal particles to involve in deposition process, but at 850 ˚C MWCNTs and SWCNTs can be selectively grown as a function of CVD temperature. The optimum deposition time was found in 30 minutes, which based on the Raman shift results the growth CNTs has shown high purity and crystallinity as well as high aspect ratio.
NASA Astrophysics Data System (ADS)
Hu, Li-Yun; Liao, Zeyang; Ma, Shengli; Zubairy, M. Suhail
2016-03-01
We introduce three tunable parameters to optimize the fidelity of quantum teleportation with continuous variables in a nonideal scheme. By using the characteristic-function formalism, we present the condition that the teleportation fidelity is independent of the amplitude of input coherent states for any entangled resource. Then we investigate the effects of tunable parameters on the fidelity with or without the presence of the environment and imperfect measurements by analytically deriving the expression of fidelity for three different input coherent-state distributions. It is shown that, for the linear distribution, the optimization with three tunable parameters is the best one with respect to single- and two-parameter optimization. Our results reveal the usefulness of tunable parameters for improving the fidelity of teleportation and the ability against decoherence.
NASA Astrophysics Data System (ADS)
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
Multi-Objective Optimization of Vehicle Suspension Parameters Considering Various Road Classes
NASA Astrophysics Data System (ADS)
Havelka, Ferdinand; Musil, Miloš
2014-12-01
Vehicle suspension optimization for various road classes travelled at different velocities is performed. Road excitation is modeled using a first order shaping filter. A half-car model is adopted to simulate the vehicle's vertical dynamics. The excitation time delay between the rear and the front tire is modeled using Pade approximation. Suspension parameters are optimized using a random search method with respect to "comfort" and "sporty driving" considering the design constraints of the suspension and road holding and maximum suspension travel constraints. Optimal suspension parameters suitable for various road classes and vehicle velocities have been chosen.
Jackson, E.; Aga, R. Jr.; Steigerwald, A.; Ueda, A.; Pan, Z.; Collins, W. E.; Mu, R.
2008-03-13
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.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630
NASA 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.
Optimization of parameters for the inline-injection system at Brookhaven Accelerator Test Facility
Parsa, Z.; Ko, S.K.
1995-10-01
We present some of our parameter optimization results utilizing code PARMLEA, for the ATF Inline-Injection System. The new solenoid-Gun-Solenoid -- Drift-Linac Scheme would improve the beam quality needed for FEL and other experiments at ATF as compared to the beam quality of the original design injection system. To optimize the gain in the beam quality we have considered various parameters including the accelerating field gradient on the photoathode, the Solenoid field strengths, separation between the gun and entrance to the linac as well as the (type size) initial charge distributions. The effect of the changes in the parameters on the beam emittance is also given.
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. PMID:20543439
Metamodel based optimization of material parameters in a finite element simulation of tensile tests
NASA Astrophysics Data System (ADS)
Brown, Justin; McKay, Cavendish
2010-04-01
We determine the optimum set of parameters for simulating a tensile test of a sample of Zytelnylon resin in a finite element model. Using manufacturer supplied data and initial tensile measurements as starting data, we use a metamodel based optimization scheme to iteratively improve the choice of parameters. The commercial finite element solver LS-DYNA and optimization package LS-Opt are used to assess the quality of the material parameter choice. A map of the response surface is presented to illustrate some challenges with the metamodel based approach.
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
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.
Optimization of Ta_{2}O_{5} optical thin film deposited by radio frequency magnetron sputtering.
Shakoury, R; Willey, Ronald R
2016-07-10
Radio frequency magnetron sputtering has been used here to find the parameters at which to deposit Ta_{2}O_{5} optical thin films with negligible absorption in the visible spectrum. The design of experiment methodology was employed to minimize the number of experiments needed to find the optimal results. Two independent approaches were used to determine the index of refraction n and k values.
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.
[Development of an Optimizing Program of Scanning Parameters for Double Inversion Recovery MRI].
Hayashi, Norio; Yarita, Kazuma; Sakata, Kozue; Motegi, Shunichi; Nagase, Hiroyuki; Ujita, Kouichi; Ogura, Akio; Ogura, Toshihiro; Shimada, Takehiro; Tsushima, Yoshito
2015-06-01
The purpose of this study was to develop an optimizing program of scanning parameters for double inversion recovery (DIR) MRI. The optimization algorithm consists of the following steps: (1) obtaining the initial parameters (TR, TE, and T1 values of the two attenuated tissues); (2) iterative calculation for minimization of errors; and (3) determination of the optimized TI(1st) and TI(2nd). To evaluate the developed algorithm, we performed the phantom and simulation studies using the phantoms which were imitated T1 values of white and gray matters and cerebrospinal fluid. In addition, white matter attenuated inversion recovery (WAIR) and gray matter attenuated inversion recovery (GAIR) images were obtained by optimized scan parameters in one volunteer. The developed algorithm could calculate the optimized TI(1st) and TI(2nd) values at once. Results of summation of signal intensity (SI) of two attenuated tissues shows that the SI of the two tissues were well-attenuated using the theoretical values which were calculated using the developed algorithm. The correlation coefficient of the SI of the phantom of the gray matter between actual and simulation measurements was r=0.997. The SI obtained by actual measurements well correlated with the SI obtained by the simulation measurements. The WAIR and GAIR images in the volunteer were well enhanced gray or white matters. We thus conclude that it is possible to calculate the optimized parameters for the DIR-MRI using the developed algorithm.
Multi-parameter Optimization of a Thermoelectric Power Generator and Its Working Conditions
NASA Astrophysics Data System (ADS)
Zhang, T.
2016-09-01
The global optimal working conditions and optimal couple design for thermoelectric (TE) generators with realistic thermal coupling between the heat reservoirs and the TE couple were studied in the current work. The heat fluxes enforced by the heat reservoirs at the hot and the cold junctions of the TE couple were used in combination with parameter normalization to obtain a single cubic algebraic equation relating the temperature differences between the TE couple junctions and between the heat reservoirs, through the electric load resistance ratio, the reservoir thermal conductance ratio, the reservoir thermal conductance to the TE couple thermal conductance ratio, the Thomson to Seebeck coefficient ratio, and the figure of merit (Z) of the material based on the linear TE transport equations and their solutions. A broad reservoir thermal conductance ranging between 0.01 W/K and 100 W/K and TE element length ranging from 10-7 m to 10-3 m were explored to find the global optimal systems. The global optimal parameters related to the working conditions, i.e., reservoir thermal conductance ratio and electric load resistance ratio, and the optimal design parameter related to the TE couple were determined for a given TE material. These results demonstrated that the internal and external electric resistance, the thermal resistance between the reservoirs, the thermal resistance between the reservoir and the TE couple, and the optimal thermoelement length have to be well coordinated to obtain optimal power production.
When the Optimal Is Not the Best: Parameter Estimation in Complex Biological Models
Fernández Slezak, Diego; Suárez, Cecilia; Cecchi, Guillermo A.; Marshall, Guillermo; Stolovitzky, Gustavo
2010-01-01
Background The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system and point to the need of a theory that addresses this problem more generally. PMID:21049094
"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
"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 Instantaneous
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.
Landmark-driven parameter optimization for non-linear image registration
NASA Astrophysics Data System (ADS)
Schmidt-Richberg, Alexander; Werner, René; Ehrhardt, Jan; Wolf, Jan-Christoph; Handels, Heinz
2011-03-01
Image registration is one of the most common research areas in medical image processing. It is required for example for image fusion, motion estimation, patient positioning, or generation of medical atlases. In most intensity-based registration approaches, parameters have to be determined, most commonly a parameter indicating to which extend the transformation is required to be smooth. Its optimal value depends on multiple factors like the application and the occurrence of noise in the images, and may therefore vary from case to case. Moreover, multi-scale approaches are commonly applied on registration problems and demand for further adjustment of the parameters. In this paper, we present a landmark-based approach for automatic parameter optimization in non-linear intensity-based image registration. In a first step, corresponding landmarks are automatically detected in the images to match. The landmark-based target registration error (TRE), which is shown to be a valid metric for quantifying registration accuracy, is then used to optimize the parameter choice during the registration process. The approach is evaluated for the registration of lungs based on 22 thoracic 4D CT data sets. Experiments show that the TRE can be reduced on average by 0.07 mm using automatic parameter optimization.
Optimization of van der Waals Density Functionals using Data Projection onto Parameter Space (DPPS)
NASA Astrophysics Data System (ADS)
Fritz, Michelle; Fernandez-Serra, Marivi; Gillan, Mike; Soler, Jose M.
2014-03-01
The parameterization and optimization of complex models fitted to reproduce a reference data set is an important part of the development of interatomic potentials. It is an approach that can also be used to design exchange and correlation functionals in density functional theory. Generally, this is a problem that requires choosing functional forms that depend on many parameters. The balance between the number of parameters and the size of the fitted data sets involves difficult and subjective decisions that are nevertheless critical for obtaining good results. We present a general and powerful optimization scheme, data projection onto parameter space (DPPS). The DPPS method tries to find the optimal parameters for a complex model which depends on a scalar function F which is determined by a large number of variables and parameters. The procedure involves the projection a vector of unknown parameters onto the vectors of known data. As an example, we apply DPPS to the optimization of the local exchange in a vdW density functional (vdW-DF). Our goal is to obtain an improved vdW-DF for water. To do so, we use an accurate potential energy surface for the water dimer as our initial data set.
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
Antes, Iris; Merkwirth, Christian; Lengauer, Thomas
2005-01-01
In computational biology processes such as docking, binding, and folding are often described by simplified, empirical models. These models are fitted to physical properties of the process by adjustable parameters. An appropriate choice of these parameters is crucial for the quality of the models. Locating the best choices for the parameters is often is a difficult task, depending on the complexity of the model. We describe a new method and program, POEM (Parameter Optimization using Ensemble Methods), for this task. In POEM we combine the DOE (Design Of Experiment) procedure with ensembles of different regression methods. We apply the method to the optimization of target specific scoring functions in molecular docking. The method consists of an iterative procedure that uses alternate evaluation and prediction steps. During each cycle of optimization we fit an approximate function to a defined loss function landscape and improve the quality of this fit from cycle to cycle by constantly augmenting our data set. As test applications we fitted the FlexX and Screenscore scoring functions to the kinase and ATPase protein classes. The results are promising: Starting from random parameters we are able to locate parameter sets which show superior performance compared to the original values. The POEM approach converges quickly and the approximated loss function landscapes are smooth, thus making the approach a suitable method for optimizations on rugged landscapes.
NASA Astrophysics Data System (ADS)
Chen, Y.; Li, J.; Xu, H.
2016-01-01
Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show
[The kinetic parameters of retainment and release of deposited in human tissue structures calcium].
Ermakova, I P; Potanina, T V; Pronchenko, I A; Larina, I M; Sevast'ianov, V I
2014-11-01
The analysis of retainment and release kinetics of deposited in tissue structures calcium was made in the hypercalcemic conditions in 28 healthy volunteers (22 males and 6 females) of the age of 33 ± 6.5 years via drip infusion (Groups 1, 2) and in 9 individuals (3 males and 6 females) in 12 trials via stream infusion (Group 3). By the end of each hour after the termination of calcium infusion the amount of calcium retained in tissues was calculated (Mtis./kg); the parameters of its binding (specific buffer volume--β3 sp, association constant--Ka, number of binding centers--n) were established using the Langmuir and Scetchard coordinates. The Group 1 volunteers (n = = 12) showed a section of positive cooperativity (a direct regression on Sketchard coordinates, Hill coefficient 3.36 ± 1.63) and 2 sections of the consecutive calcium separation from one set of noninteracting centers. 5 volunteers of Group 2 and 8 volunteers of Group 3 demonstrated a slight calcium delivery to tissues after 1 hour of observation which then followed for 2 volunteers of Group 2 and for 2 volunteers of Group 3. Other volunteers of Groups 2 and 3 showed a release of tissue-deposited calcium via the mechanism of the consecutive separation from one set of noninteracting centers with βsp 3 times less and Ka 7 times higher than with the calcium infusion. The excretion of calcium in urine was the highest in Group 1 and the lowest in Group 3. The [Ca2+] and Mtis./kg values were normalized in Groups 1 and 2 the next morning and in Group 3 after 2-3 hours of observation. An assumption was made about the relationship between the tissue and kidney [Ca2+] normalizing mechanisms with hypercalcemia.
NASA Astrophysics Data System (ADS)
Kumar, S.; Gerhardt, R. A.
2012-03-01
The effects of film thickness, electrode size and substrate thickness on the impedance parameters of alternating frequency dielectric measurements of insulating thin films deposited on conductive substrates were studied through parametric finite-element simulations. The quasi-static forms of Maxwell's electromagnetic equations in a time harmonic mode were solved using COMSOL Multiphysics® for several types of 2D models (linear and axisymmetric). The full 2D model deals with a configuration in which the impedance is measured between two surface electrodes on top of a film deposited on a conductive substrate. For the simplified 2D models, the conductive substrate is ignored and the two electrodes are placed on the top and bottom of the film. By comparing the full model and the simplified models, approximations and generalizations are deduced. For highly insulating films, such as the case of insulating SiO2 films on a conducting Si substrate, even the simplified models predict accurate capacitance values at all frequencies. However, the edge effects on the capacitance are found to be significant when the film thickness increases and/or the top electrode contact size decreases. The thickness of the substrate affects predominantly the resistive components of the dielectric response while having no significant effect on the capacitive components. Changing the electrode contact size or the film thickness determines the specific values of the measured resistance or capacitance while the material time constant remains the same, and thus this affects the frequency dependence that is able to be detected. This work highlights the importance of keeping in mind the film thickness and electrode contact size for the correct interpretation of the measured dielectric properties of micro/nanoscale structures that are often investigated using nanoscale capacitance measurements.
NASA Astrophysics Data System (ADS)
Kadyrmetov, A. M.; Sharifullin, S. N.; Maltsev, A. F.
2016-06-01
In the work on the basis of mathematical modeling analysis of processes of plasma deposition of coatings with modulation of the electrical parameters of the extension arc. The effect of modulation on the temperature field in the system "coating-basis" on a local scale, proportionate to the diameter of the spot attachment of the arc to the surface, and at the macrolevel of evaporation surface. It justifies the preconditions of the improvement of plasma deposition and hardening coatings.
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
Li, Pengsong; Huang, Jinyang; Luo, Liang; Kuang, Yun; Sun, Xiaoming
2016-09-01
Density gradient ultracentrifugation (DGUC) has recently emerged as an effective nanoseparation method to sort polydispersed colloidal NPs mainly according to their size differences to reach monodispersed fractions (NPs), but its separation modeling is still lack and the separation parameters' optimization mainly based on experience of operators. In this paper, we gave mathematical descriptions on the DGUC separation, which suggested the best separation parameters for a given system. The separation parameters, including media density, centrifuge speed and time, which affected the separation efficiency, were discussed in details. Further mathematical optimization model was established to calculate and yield the "best" (optimized) linear gradient for a colloidal system with given size and density. The practical experiment results matched well with theoretical prediction, demonstrating the DGUC method, an efficient, practical, and predictable separation technique with universal utilization for colloid sorting. PMID:27457445
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.
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.
NASA Astrophysics Data System (ADS)
Huang, Zhipeng; Gao, Lihong; Wang, Yangwei; Wang, Fuchi
2016-06-01
The Johnson-Cook (J-C) constitutive model is widely used in the finite element simulation, as this model shows the relationship between stress and strain in a simple way. In this paper, a cluster global optimization algorithm is proposed to determine the J-C constitutive model parameters of materials. A set of assumed parameters is used for the accuracy verification of the procedure. The parameters of two materials (401 steel and 823 steel) are determined. Results show that the procedure is reliable and effective. The relative error between the optimized and assumed parameters is no more than 4.02%, and the relative error between the optimized and assumed stress is 0.2% × 10-5. The J-C constitutive parameters can be determined more precisely and quickly than the traditional manual procedure. Furthermore, all the parameters can be simultaneously determined using several curves under different experimental conditions. A strategy is also proposed to accurately determine the constitutive parameters.
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.
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
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.
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)
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.
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.
Gas separation using membranes. 1: Optimization of the separation process using new cost parameters
Hinchliffe, A.B.; Porter, K.E.
1997-03-01
This is the first in a series of papers presenting new concepts for the development of membranes for gas separation. In this paper two new cost parameters, which are useful for costing and optimization of membrane gas separation systems, are described. The new parameters, cost permeability and effective selectivity, can be used to show the direction to be taken in membrane research and development. The new parameters are shown to predict accurately the cost of membrane separation plant by correlating bids from membrane plant suppliers using the new parameters with cross-flow design equations. The parameters are used to optimize the membrane gas separation of hydrogen and carbon monoxide for two commercially available membrane systems. The membrane separation is compared with the currently used method, cryogenic flash distillation. Economic evaluation methods are developed to compare different separation methods so that the process as a whole can be optimized. The evaluation shows that, for membrane gas separation, it is important to find the optimum degree of separation; when membrane separation is evaluated at the separation specification for the established cryogenic method, membranes are not competitive; however, when the process is optimized for membrane separation, the cost of separation reduces to less than 60% of the cryogenic separation.
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 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.
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.
Topographic study of sputter-deposited film with different process parameters
NASA Astrophysics Data System (ADS)
Ju, Shin-Pon; Weng, Cheng-I.; Chang, Jee-Gong; Hwang, Chi-Chuan
2001-06-01
In this study, molecular dynamics simulation is employed to investigate the surface topography of thin films produced by the sputtering process for different parameters such as substrate temperature, incident energy, and incident angle. Interface width is used to quantify the quality of the deposited film. The Morse potential is used to model the atomic interaction between atoms. From the results of this study, it is found that for lower substrate temperature, lower incident energy, and larger incident angle, the growing film structure tends toward a three-dimensional columnar structure, and a rougher film is produced. Conversely, for higher substrate temperature, higher incident energy, and smaller incident angle, the growing film structure tends toward a two-dimensional (Frank-van der Merwe) quasi-layer-by-layer structure, and a smoother film is produced. Finally, average surface kinetic energy is found to be an important factor in determining the surface properties produced in the process. Generally, the produced film is smoother when the average surface kinetic energy is larger.
Optimization of a plasma focus device as an electron beam source for thin film deposition
NASA Astrophysics Data System (ADS)
Zhang, T.; Lin, J.; Patran, A.; Wong, D.; Hassan, S. M.; Mahmood, S.; White, T.; Tan, T. L.; Springham, S. V.; Lee, S.; Lee, P.; Rawat, R. S.
2007-05-01
Electron beam emission characteristics from neon, argon, hydrogen and helium in an NX2 dense plasma focus (DPF) device were investigated in order to optimize the plasma focus device for deposition of thin films using energetic electron beams. A Rogowski coil and CCD based magnetic spectrometer were used to obtain temporal characteristics, total electron charge and energy distributions of electron emission from the NX2 DPF device. It is found that hydrogen should be the first choice for thin film deposition as it produces the highest electron beam charge and higher energy (from 50 to 200 keV) electrons. Neon is the next best choice as it gives the next highest electron beam charge with mid-energy (from 30 to 70 keV) electrons. The operation of NX2 with helium at voltages above 12 kV produces a mid-energy (from 30 to 70 keV) electron beam with low-electron beam charge, however, argon is not a good electron beam source for our NX2 DPF device. Preliminary results of the first ever thin film deposition using plasma focus assisted pulsed electron deposition using a hydrogen operated NX2 plasma focus device are presented.
A novel optimization method of camera parameters used for vision measurement
NASA Astrophysics Data System (ADS)
Zhou, Fuqiang; Cui, Yi; Peng, Bin; Wang, Yexin
2012-09-01
Camera calibration plays an important role in the field of machine vision applications. During the process of camera calibration, nonlinear optimization technique is crucial to obtain the best performance of camera parameters. Currently, the existing optimization method aims at minimizing the distance error between the detected image point and the calculated back-projected image point, based on 2D image pixels coordinate. However, the vision measurement process is conducted in 3D space while the optimization method generally adopted is carried out in 2D image plane. Moreover, the error criterion with respect to optimization and measurement is different. In other words, the equal pixel distance error in 2D image plane leads to diverse 3D metric distance error at different position before the camera. All the reasons mentioned above will cause accuracy decrease for 3D vision measurement. To solve the problem, a novel optimization method of camera parameters used for vision measurement is proposed. The presented method is devoted to minimizing the metric distance error between the calculated point and the real point in 3D measurement coordinate system. Comparatively, the initial camera parameters acquired through linear calibration are optimized through two different methods: one is the conventional method and the other is the novel method presented by this paper. Also, the calibration accuracy and measurement accuracy of the parameters obtained by the two methods are thoroughly analyzed and the choice of a suitable accuracy evaluation method is discussed. Simulative and real experiments to estimate the performance of the proposed method on test data are reported, and the results show that the proposed 3D optimization method is quite efficient to improve measurement accuracy compared with traditional method. It can meet the practical requirement of high precision in 3D vision metrology engineering.
NASA Astrophysics Data System (ADS)
Qi, Wei; Zhang, Chi; Fu, Guangtao; Zhou, Huicheng
2016-02-01
It is widely recognized that optimization algorithm parameters have significant impacts on algorithm performance, but quantifying the influence is very complex and difficult due to high computational demands and dynamic nature of search parameters. The overall aim of this paper is to develop a global sensitivity analysis based framework to dynamically quantify the individual and interactive influence of algorithm parameters on algorithm performance. A variance decomposition sensitivity analysis method, Analysis of Variance (ANOVA), is used for sensitivity quantification, because it is capable of handling small samples and more computationally efficient compared with other approaches. The Shuffled Complex Evolution method developed at the University of Arizona algorithm (SCE-UA) is selected as an optimization algorithm for investigation, and two criteria, i.e., convergence speed and success rate, are used to measure the performance of SCE-UA. Results show the proposed framework can effectively reveal the dynamic sensitivity of algorithm parameters in the search processes, including individual influences of parameters and their interactive impacts. Interactions between algorithm parameters have significant impacts on SCE-UA performance, which has not been reported in previous research. The proposed framework provides a means to understand the dynamics of algorithm parameter influence, and highlights the significance of considering interactive parameter influence to improve algorithm performance in the search processes.
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
Generation of pareto optimal ensembles of calibrated parameter sets for climate models.
Dalbey, Keith R.; Levy, Michael Nathan
2010-12-01
Climate models have a large number of inputs and outputs. In addition, diverse parameters sets can match observations similarly well. These factors make calibrating the models difficult. But as the Earth enters a new climate regime, parameters sets may cease to match observations. History matching is necessary but not sufficient for good predictions. We seek a 'Pareto optimal' ensemble of calibrated parameter sets for the CCSM climate model, in which no individual criteria can be improved without worsening another. One Multi Objective Genetic Algorithm (MOGA) optimization typically requires thousands of simulations but produces an ensemble of Pareto optimal solutions. Our simulation budget of 500-1000 runs allows us to perform the MOGA optimization once, but with far fewer evaluations than normal. We devised an analytic test problem to aid in the selection MOGA settings. The test problem's Pareto set is the surface of a 6 dimensional hypersphere with radius 1 centered at the origin, or rather the portion of it in the [0,1] octant. We also explore starting MOGA from a space-filling Latin Hypercube sample design, specifically Binning Optimal Symmetric Latin Hypercube Sampling (BOSLHS), instead of Monte Carlo (MC). We compare the Pareto sets based on: their number of points, N, larger is better; their RMS distance, d, to the ensemble's center, 0.5553 is optimal; their average radius, {mu}(r), 1 is optimal; their radius standard deviation, {sigma}(r), 0 is optimal. The estimated distributions for these metrics when starting from MC and BOSLHS are shown in Figs. 1 and 2.
NASA Astrophysics Data System (ADS)
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
2015-04-01
A multi-scale parameter-estimation method, as presented by Samaniego et al. (2010), is implemented and extended for the conceptual hydrological model COSERO. COSERO is a HBV-type model that is specialized for alpine-environments, but has been applied over a wide range of basins all over the world (see: Kling et al., 2014 for an overview). Within the methodology available small-scale information (DEM, soil texture, land cover, etc.) is used to estimate the coarse-scale model parameters by applying a set of transfer-functions (TFs) and subsequent averaging methods, whereby only TF hyper-parameters are optimized against available observations (e.g. runoff data). The parameter regionalisation approach was extended in order to allow for a more meta-heuristical handling of the transfer-functions. The two main novelties are: 1. An explicit introduction of constrains into parameter estimation scheme: The constraint scheme replaces invalid parts of the transfer-function-solution space with valid solutions. It is inspired by applications in evolutionary algorithms and related to the combination of learning and evolution. This allows the consideration of physical and numerical constraints as well as the incorporation of a priori modeller-experience into the parameter estimation. 2. Spline-based transfer-functions: Spline-based functions enable arbitrary forms of transfer-functions: This is of importance since in many cases the general relationship between sub-grid information and parameters are known, but not the form of the transfer-function itself. The contribution presents the results and experiences with the adopted method and the introduced extensions. Simulation are performed for the pre-alpine/alpine Traisen catchment in Lower Austria. References: Samaniego, L., Kumar, R., Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., doi: 10.1029/2008WR007327 Kling, H., Stanzel, P., Fuchs, M., and
Heidari, M.; Ranjithan, S.R.
1998-01-01
In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is
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.
Optimization of injection molding parameters for poly(styrene-isobutylene-styrene) block copolymer
NASA Astrophysics Data System (ADS)
Fittipaldi, Mauro; Garcia, Carla; Rodriguez, Luis A.; Grace, Landon R.
2016-03-01
Poly(styrene-isobutylene-styrene) (SIBS) is a widely used thermoplastic elastomer in bioimplantable devices due to its inherent stability in vivo. However, the properties of the material are highly dependent on the fabrication conditions, molecular weight, and styrene content. An optimization method for injection molding is herein proposed which can be applied to varying SIBS formulations in order to maximize ultimate tensile strength, which is critical to certain load-bearing implantable applications. The number of injection molded samples required to ascertain the optimum conditions for maximum ultimate tensile strength is limited in order to minimize experimental time and effort. Injection molding parameters including nozzle temperature (three levels: 218, 246, and 274 °C), mold temperature (three levels: 50, 85, and 120 °C), injection speed (three levels: slow, medium and fast) and holding pressure time (three levels: 2, 6, and 10 seconds) were varied to fabricate dumbbell specimens for tensile testing. A three-level L9 Taguchi method utilizing orthogonal arrays was used in order to rank the importance of the different injection molding parameters and to find an optimal parameter setting to maximize the ultimate tensile strength of the thermoplastic elastomer. Based on the Taguchi design results, a Response Surface Methodology (RSM) was applied in order to build a model to predict the tensile strength of the material at different injection parameters. Finally, the model was optimized to find the injection molding parameters providing maximum ultimate tensile strength. Subsequently, the theoretically-optimum injection molding parameters were used to fabricate additional dumbbell specimens. The experimentally-determined ultimate tensile strength of these samples was found to be in close agreement (1.2%) with the theoretical results, successfully demonstrating the suitability of the Taguchi Method and RSM for optimizing injection molding parameters of SIBS.
NASA Astrophysics Data System (ADS)
Yücel, Ersin; Yücel, Yasin; Beleli, Buse
2015-07-01
In this study, lead sulfide (PbS) thin films were synthesized by a successive ionic layer adsorption and reaction (SILAR) method with different pH, dipping time and dipping cycles. Response surface methodology (RSM) and central composite design (CCD) were successfully used to optimize the PbS films deposition parameters and understand the significance and interaction of the factors affecting the film quality. 5-level-3-factor central composite design was employed to evaluate the effects of the deposition parameters (pH, dipping time and dipping cycles) on the response (the optical band gap of the films). Data obtained from RSM were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation. The optimal conditions for the PbS films deposition have been found to be: pH of 9.1, dipping time of 10 s and dipping cycles of 10 cycles. The predicted band gap of PbS film was 2.13 eV under the optimal conditions. Verification experiment (2.24 eV) confirmed the validity of the predicted model. The film structures were characterized by X-ray diffractometer (XRD). Morphological properties of the films were studied with a scanning electron microscopy (SEM). The optical properties of the films were investigated using a UV-visible spectrophotometer.
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.
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 control parameters of a hot cold controller by means of Simplex type methods.
Porte, C; Caron-Poussin, M; Carot, S; Couriol, C; Moreno, M M; Delacroix, A
1997-01-01
This paper describes a hot/cold controller for regulating crystallization operations. The system was identified with a common method (the Broida method) and the parameters were obtained by the Ziegler-Nichols method. The paper shows that this empirical method will only allow a qualitative approach to regulation and that, in some instances, the parameters obtained are unreliable and therefore cannot be used to cancel variations between the set point and the actual values. Optimization methods were used to determine the regulation parameters and solve this identcation problem. It was found that the weighted centroid method was the best one. PMID:18924791
Fittschen, Ursula E A; Havrilla, George J
2010-01-01
In this study, we introduce a Hewlett-Packard prototype picoliter pipette, the "thermal inkjet picofluidic system" (TIPS), for analytical purposes. In contrast to the use of actual inkjet printers, this instrument allows for control of all energy and time settings. We are able to show that in contrast to techniques delivering microliter and nanoliter volumes, evaporation has a major influence on the deposition of picoliter volumes and has to be treated seriously when picoliter depositions are applied in the laboratory for calibration purposes. We developed a strategy to reduce evaporation by varying different parameters, thereby achieving a precision of less than 10% for elemental depositions ranging from 1 to 300 picoliters and 1 to 2000 pg elemental deposits. Additionally, we determined the performance of the micro X-ray fluorescence (MXRF) instruments in terms of limit of detection (LODs), focal spot size, sensitivity, and precision and evaluated the TIPS deposits as reference materials for MXRF using single and multielement solutions. A linear response was observed with correlation coefficients from 0.991 to 0.999 for elemental deposits on AP1 film, and there was a standard deviation from 1 to 40%, depending on the element and the mass deposited. LOD's for Ni deposits on AP1 films were found to range from low picogram levels to subpicogram levels. The dried deposits were characterized for size and shape using light microscopy and atomic force microscopy (AFM) to estimate matrix effects and the area covered with sample material for the MXRF analysis. Diameters from 14 to 39 microm and thicknesses from 200 nm to 2 microm were measured. The accuracy of the dried spot approach was demonstrated by comparing multielement deposits from the TIPS with the NIST SRMs 1833 and 1832 thin film standards for MXRF analysis. The deviation from the SRMs was found to be better than 10%.
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.
NASA Astrophysics Data System (ADS)
Xu, Dexiang
This dissertation presents a novel method of designing finite word length Finite Impulse Response (FIR) digital filters using a Real Parameter Parallel Genetic Algorithm (RPPGA). This algorithm is derived from basic Genetic Algorithms which are inspired by natural genetics principles. Both experimental results and theoretical studies in this work reveal that the RPPGA is a suitable method for determining the optimal or near optimal discrete coefficients of finite word length FIR digital filters. Performance of RPPGA is evaluated by comparing specifications of filters designed by other methods with filters designed by RPPGA. The parallel and spatial structures of the algorithm result in faster and more robust optimization than basic genetic algorithms. A filter designed by RPPGA is implemented in hardware to attenuate high frequency noise in a data acquisition system for collecting seismic signals. These studies may lead to more applications of the Real Parameter Parallel Genetic Algorithms in Electrical Engineering.
Khan, M A; Ngo, H H; Guo, W S; Liu, Y; Nghiem, L D; Hai, F I; Deng, L J; Wang, J; Wu, Y
2016-11-01
The anaerobic digestion process has been primarily utilized for methane containing biogas production over the past few years. However, the digestion process could also be optimized for producing volatile fatty acids (VFAs) and biohydrogen. This is the first review article that combines the optimization approaches for all three possible products from the anaerobic digestion. In this review study, the types and configurations of the bioreactor are discussed for each type of product. This is followed by a review on optimization of common process parameters (e.g. temperature, pH, retention time and organic loading rate) separately for the production of VFA, biohydrogen and methane. This review also includes additional parameters, treatment methods or special additives that wield a significant and positive effect on production rate and these products' yield. PMID:27570139
He, Li; Huang, Guo-He; Lu, Hong-Wei; Zeng, Guang-Ming
2008-03-15
This study develops a nonlinear chance-constrained programming (NCCP) model for optimizing surfactant-enhanced aquifer remediation (SEAR) processes. The model can not only address the parameter uncertainty, but provide a reliability level for the identified optimal remediation strategy. To solve the NCCP model, stepwise cluster analysis (SCA) is used to create a set of proxy simulators for quantifying the relationships between operating conditions (i.e., pumping rate) and probabilities of benzene levels in violation of standard. Compared to conventional parametric inference techniques, SCA is independent of prior assumptions for model forms (e.g., linear or exponential ones) and capable of reflecting complex nonlinear relationships between operating conditions and probabilities. To alleviate the computational efforts in the optimization process, the generated proxy simulators are repeatedly called by simulated annealing (SA) to test the feasibility of each potential solution. The implicit of the optimal NCCP solutions is discussed through a laboratory-scale SEAR system where porosity and intrinsic permeability are treated as stochastic parameters. It is observed that well locations, environmental standards, reliability levels and remediation durations would have significant effects on optimal SEAR strategies. By comparing the predicted benzene concentration without and with remediation actions, it is indicated that the optimal SEAR process can guarantee the benzene concentration to meet the environmental standard with a high reliability level.
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.
Improving flash flood forecasting with distributed hydrological model by parameter optimization
NASA Astrophysics Data System (ADS)
Chen, Yangbo
2016-04-01
In China, flash food is usually regarded as flood occured in small and medium sized watersheds with drainage area less than 200 km2, and is mainly induced by heavy rains, and occurs in where hydrological observation is lacked. Flash flood is widely observed in China, and is the flood causing the most casualties nowadays in China. Due to hydrological data scarcity, lumped hydrological model is difficult to be employed for flash flood forecasting which requires lots of observed hydrological data to calibrate model parameters. Physically based distributed hydrological model discrete the terrain of the whole watershed into a number of grid cells at fine resolution, assimilate different terrain data and precipitation to different cells, and derive model parameteris from the terrain properties, thus having the potential to be used in flash flood forecasting and improving flash flood prediction capability. In this study, the Liuxihe Model, a physically based distributed hydrological model mainly proposed for watershed flood forecasting is employed to simulate flash floods in the Ganzhou area in southeast China, and models have been set up in 5 watersheds. Model parameters have been derived from the terrain properties including the DEM, the soil type and land use type, but the result shows that the flood simulation uncertainty is high, which may be caused by parameter uncertainty, and some kind of uncertainty control is needed before the model could be used in real-time flash flood forecastin. Considering currently many Chinese small and medium sized watersheds has set up hydrological observation network, and a few flood events could be collected, it may be used for model parameter optimization. For this reason, an automatic model parameter optimization algorithm using Particle Swam Optimization(PSO) is developed to optimize the model parameters, and it has been found that model parameters optimized even only with one observed flood events could largely reduce the flood
NASA 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.
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
Optimizing Friction Stir Welding via Statistical Design of Tool Geometry and Process Parameters
NASA Astrophysics Data System (ADS)
Blignault, C.; Hattingh, D. G.; James, M. N.
2012-06-01
This article considers optimization procedures for friction stir welding (FSW) in 5083-H321 aluminum alloy, via control of weld process parameters and tool design modifications. It demonstrates the potential utility of the "force footprint" (FF) diagram in providing a real-time graphical user interface (GUI) for process optimization of FSW. Multiple force, torque, and temperature responses were recorded during FS welding using 24 different tool pin geometries, and these data were statistically analyzed to determine the relative influence of a number of combinations of important process and tool geometry parameters on tensile strength. Desirability profile charts are presented, which show the influence of seven key combinations of weld process variables on tensile strength. The model developed in this study allows the weld tensile strength to be predicted for other combinations of tool geometry and process parameters to fall within an average error of 13%. General guidelines for tool profile selection and the likelihood of influencing weld tensile strength are also provided.
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.
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.
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 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.
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.
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.
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.
Chrzanowski, J.; Meng-Burany, S.; Xing, W.B.; Curzon, A.E.; Heinrich, B.; Irwin, J.C.; Cragg, R.A.; Zhou, H.; Habib, F.; Angus, V.
1995-04-01
Two series of Y1Ba2Cu3O(z) thin films deposited on (001) LaAl03 single crystals by excimer laser ablation under two different protocols have been investigated. The research has yielded well defined deposition conditions in terms of oxygen partial pressure p(O2) and substrate temperature of the deposition process Th, for the growth of high quality epitaxial films of YBCO. The films grown under conditions close to optimal for both J{sub c} and T{sub c} exhibited T{sub c} greater than or equal to 91 K and J{sub c} greater than or equal to 4 x 10{sup 6} A/sq cm, at 77 K. Close correlations between the structural quality of the film, the growth parameters (p(O2), T{sub h}) and J{sub c} and T{sub c} have been found.
NASA Astrophysics Data System (ADS)
Garzillo, Valerio; Jukna, Vytautas; Couairon, Arnaud; Grigutis, Robertas; Di Trapani, Paolo; Jedrkiewicz, Ottavia
2016-07-01
We investigate the generation of high aspect ratio microstructures across 0.7 mm thick glass by means of single shot Bessel beam laser direct writing. We study the effect on the photoinscription of the cone angle, as well as of the energy and duration of the ultrashort laser pulse. The aim of the study is to optimize the parameters for the writing of a regular microstructure due to index modification along the whole sample thickness. By using a spectrally resolved single pulse transmission diagnostics at the output surface of the glass, we correlate the single shot material modification with observations of the absorption in different portions of the retrieved spectra, and with the absence or presence of spectral modulation. Numerical simulations of the evolution of the Bessel pulse intensity and of the energy deposition inside the sample help us interpret the experimental results that suggest to use picosecond pulses for an efficient and more regular energy deposition. Picosecond pulses take advantage of nonlinear plasma absorption and avoid temporal dynamics effects which can compromise the stationarity of the Bessel beam propagation.
NASA Technical Reports Server (NTRS)
Stahara, S. S.
1984-01-01
An investigation was carried out to complete the preliminary development of a combined perturbation/optimization procedure and associated computational code for designing optimized blade-to-blade profiles of turbomachinery blades. The overall purpose of the procedures developed is to provide demonstration of a rapid nonlinear perturbation method for minimizing the computational requirements associated with parametric design studies of turbomachinery flows. The method combines the multiple parameter nonlinear perturbation method, successfully developed in previous phases of this study, with the NASA TSONIC blade-to-blade turbomachinery flow solver, and the COPES-CONMIN optimization procedure into a user's code for designing optimized blade-to-blade surface profiles of turbomachinery blades. Results of several design applications and a documented version of the code together with a user's manual are provided.
An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This
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)
Yan, Yiming; Zhang, Ye; Gao, Fengjiao
2012-12-01
This article proposes a `dynamic' artificial bee colony (D-ABC) algorithm for solving optimizing problems. It overcomes the poor performance of artificial bee colony (ABC) algorithm, when applied to multi-parameters optimization. A dynamic `activity' factor is introduced to D-ABC algorithm to speed up convergence and improve the quality of solution. This D-ABC algorithm is employed for multi-parameters optimization of support vector machine (SVM)-based soft-margin classifier. Parameter optimization is significant to improve classification performance of SVM-based classifier. Classification accuracy is defined as the objection function, and the many parameters, including `kernel parameter', `cost factor', etc., form a solution vector to be optimized. Experiments demonstrate that D-ABC algorithm has better performance than traditional methods for this optimizing problem, and better parameters of SVM are obtained which lead to higher classification accuracy.
Decision support system for optimal reservoir operation modeling within sediment deposition control.
Hadihardaja, Iwan K
2009-01-01
Suspended sediment deals with surface runoff moving toward watershed affects reservoir sustainability due to the reduction of storage capacity. The purpose of this study is to introduce a reservoir operation model aimed at minimizing sediment deposition and maximizing energy production expected to obtain optimal decision policy for both objectives. The reservoir sediment-control operation model is formulated by using Non-Linear Programming with an iterative procedure based on a multi-objective measurement in order to achieve optimal decision policy that is established in association with the development of a relationship between stream inflow and sediment rate by utilizing the Artificial Neural Network. Trade off evaluation is introduced to generate a strategy for controlling sediment deposition at same level of target ratio while producing hydroelectric energy. The case study is carried out at the Sanmenxia Reservoir in China where redesign and reconstruction have been accomplished. However, this model deals only with the original design and focuses on a wet year operation. This study will also observe a five-year operation period to show the accumulation of sediment due to the impact of reservoir storage capacity.
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.
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). PMID:11768710
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.
Seeker optimization algorithm for parameter estimation of time-delay chaotic systems
NASA Astrophysics Data System (ADS)
Dai, Chaohua; Chen, Weirong; Li, Lixiang; Zhu, Yunfang; Yang, Yixian
2011-03-01
Time-delay chaotic systems have some very interesting properties, and their parameter estimation has received increasing interest in the recent years. It is well known that parameter estimation of a chaotic system is a nonlinear, multivariable, and multimodal optimization problem for which global optimization techniques are required in order to avoid local minima. In this work, a seeker-optimization-algorithm (SOA)-based method is proposed to address this issue. In the SOA, search direction is based on the empirical gradients by evaluating the response to the position changes, and step length is based on uncertainty reasoning by using a simple fuzzy rule. The performance of the algorithm is evaluated on two typical test systems. Moreover, two state-of-the-art algorithms (i.e., particle swarm optimization and differential evolution) are also considered for comparison. The simulation results show that the proposed algorithm is better than or at least as good as the other two algorithms and can effectively solve the parameter estimation problem of time-delay chaotic systems.
2011-01-01
Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These
Sun, Jun; Fang, Wei; Wu, Xiaojun; Palade, Vasile; Xu, Wenbo
2012-01-01
Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little analysis on how it works in detail. This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms of probability measure. Since the particle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of the theoretical analysis is to find out the upper bound of the CE coefficient, within which the value of the CE coefficient selected can guarantee the convergence or boundedness of the particle's position. In the experimental analysis, the theoretical results are first validated by stochastic simulations for the particle's behavior. Then, based on the derived upper bound of the CE coefficient, we perform empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient, in order to obtain generally good algorithmic performance in real world applications. Finally, a further performance comparison between QPSO and other variants of PSO on the benchmarks is made to show the efficiency of the QPSO algorithm with the proposed parameter control and selection methods.
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. PMID:26604356
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)
Oby, Emily R.; Perel, Sagi; Sadtler, Patrick T.; Ruff, Douglas A.; Mischel, Jessica L.; Montez, David F.; Cohen, Marlene R.; Batista, Aaron P.; Chase, Steven M.
2016-06-01
Objective. A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain–computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach. We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent
NASA Astrophysics Data System (ADS)
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
Effect of experimental parameters on optimal reflection of light from opaque media
NASA Astrophysics Data System (ADS)
Anderson, Benjamin R.; Gunawidjaja, Ray; Eilers, Hergen
2016-01-01
Previously we considered the effect of experimental parameters on optimized transmission through opaque media using spatial light modulator (SLM)-based wavefront shaping. In this study we consider the opposite geometry, in which we optimize reflection from an opaque surface such that the backscattered light is focused onto a spot on an imaging detector. By systematically varying different experimental parameters (genetic algorithm iterations, bin size, SLM active area, target area, spot size, and sample angle with respect to the optical axis) and optimizing the reflected light we determine how each parameter affects the intensity enhancement. We find that the effects of the experimental parameters on the enhancement are similar to those measured for a transmissive geometry, but with the exact functional forms changed due to the different geometry and the use of a genetic algorithm instead of an iterative algorithm. Additionally, we find preliminary evidence of greater enhancements than predicted by random matrix theory, suggesting a possibly new physical mechanism to be investigated in future work.
Son, Seok Hyun; Jang, Hong Seok; Sung, Soo Yoon; Kang, Hye Jin; Lee, Sojung; Kay, Chul Seung
2015-12-01
The purpose of this study is to identify the optimal criteria of the radiotherapeutic parameters in patients with unresectable locally advanced hepatocellular carcinoma (HCC). 103 patients were enrolled in this study. All patients received RT delivered using the TomoTherapy Hi-Art system between March 2006 and February 2012. We evaluated the planning target volume (PTV), total dose (Gy10), and NTNL-V(BED20) (non-target normal liver volume receiving more than a biologically effective dose of 20 Gy8) as significant radiotherapeutic parameters associated with hepatic function deterioration and local progression-free survival (PFS). A PTV of 279 cm3 or 304 cm3, a total dose of 60 Gy10, and a NTNL-V(BED20) of 40.8% were identified as the optimal cut-off values of radiotherapeutic parameters to prevent hepatic function deterioration and prolong local PFS. Based on these findings, patients were divided in a favorable and an unfavorable prognosis group. The differences in median local PFS, overall survival, and incidence of deteriorated hepatic function between the two groups were 11.2 months, 11.1 months, and 71.7%, respectively (p < 0.001 in each case). In conclusion, we suggest that the optimal criteria of the radiotherapeutic parameters for patients with unresectable locally advanced HCC are: PTV ≤ 279 cm3, total dose > 60 Gy10, and NTNL-V(BED20) ≤ 40.8%. PMID:26510905
Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1993-01-01
The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.
An Approach to Optimize Size Parameters of Forging by Combining Hot-Processing Map and FEM
NASA Astrophysics Data System (ADS)
Hu, H. E.; Wang, X. Y.; Deng, L.
2014-11-01
The size parameters of 6061 aluminum alloy rib-web forging were optimized by using hot-processing map and finite element method (FEM) based on high-temperature compression data. The results show that the stress level of the alloy can be represented by a Zener-Holloman parameter in a hyperbolic sine-type equation with the hot deformation activation energy of 343.7 kJ/mol. Dynamic recovery and dynamic recrystallization concurrently preceded during high-temperature deformation of the alloy. Optimal hot-processing parameters for the alloy corresponding to the peak value of 0.42 are 753 K and 0.001 s-1. The instability domain occurs at deformation temperature lower than 653 K. FEM is an available method to validate hot-processing map in actual manufacture by analyzing the effect of corner radius, rib width, and web thickness on workability of rib-web forging of the alloy. Size parameters of die forgings can be optimized conveniently by combining hot-processing map and FEM.
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)
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.
Optimization of culture parameters and novel strategies to improve protein solubility.
Arya, Ranjana; Sabir, Jamal S M; Bora, Roop S; Saini, Kulvinder S
2015-01-01
The production of recombinant proteins, in soluble form in a prokaryotic expression system, still remains a challenge for the biotechnologist. Innovative strategies have been developed to improve protein solubility in various protein overexpressing hosts. In this chapter, we would focus on methods currently available and amenable to "desired modifications," such as (a) the use of molecular chaperones; (b) the optimization of culture conditions; (c) the reengineering of a variety of host strains and vectors with affinity tags; and (d) optimal promoter strengths. All these parameters are evaluated with the primary objective of increasing the solubilization of recombinant protein(s) during overexpression in Escherichia coli. PMID:25447858
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
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.
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.
Chang, Liang-Cheng; Chu, Hone-Jay; Lin, Yu-Pin; Chen, Yu-Wen
2010-10-01
This research develops an optimum design model of groundwater network using genetic algorithm (GA) and modified Newton approach, based on the experimental design conception. The goal of experiment design is to minimize parameter uncertainty, represented by the covariance matrix determinant of estimated parameters. The design problem is constrained by a specified cost and solved by GA and a parameter identification model. The latter estimates optimum parameter value and its associated sensitivity matrices. The general problem is simplified into two classes of network design problems: an observation network design problem and a pumping network design problem. Results explore the relationship between the experimental design and the physical processes. The proposed model provides an alternative to solve optimization problems for groundwater experimental design. PMID:19757116
NASA Astrophysics Data System (ADS)
Sumata, H.; Kauker, F.; Gerdes, R.; Köberle, C.; Karcher, M.
2012-11-01
Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean-sea ice model, and applicability and efficiency of the respective methods were examined. One is a finite difference method based on a traditional gradient descent approach, while the other adopts genetic algorithms as an example of stochastic approaches. Several series of parameter optimization experiments were performed by minimizing a cost function composed of model-data misfit of ice concentration, ice drift velocity and ice thickness. The finite difference method fails to estimate optimal parameters due to an ill-shaped nature of the cost function, whereas the genetic algorithms can effectively estimate near optimal parameters with a practical number of iterations. The results of the study indicate that a sophisticated stochastic approach is of practical use to a parameter optimization of a coupled ocean-sea ice model.
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.
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.
Data set of optimal parameters for colorimetric red assay of epoxide hydrolase activity.
de Oliveira, Gabriel Stephani; Adriani, Patricia Pereira; Borges, Flavia Garcia; Lopes, Adriana Rios; Campana, Patricia T; Chambergo, Felipe S
2016-09-01
The data presented in this article are related to the research article entitled "Epoxide hydrolase of Trichoderma reesei: Biochemical properties and conformational characterization" [1]. Epoxide hydrolases (EHs) are enzymes that catalyze the hydrolysis of epoxides to the corresponding vicinal diols. This article describes the optimal parameters for the colorimetric red assay to determine the enzymatic activity, with an emphasis on the characterization of the kinetic parameters, pH optimum and thermal stability of this enzyme. The effects of reagents that are not resistant to oxidation by sodium periodate on the reactions can generate false positives and interfere with the final results of the red assay. PMID:27366781
Factorization and reduction methods for optimal control of distributed parameter systems
NASA Technical Reports Server (NTRS)
Burns, J. A.; Powers, R. K.
1985-01-01
A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.
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.
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.
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.
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.
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.
The pump parameters optimization in LDA pumped solid-state laser
NASA Astrophysics Data System (ADS)
Han, Yaofeng; Zhang, Ruofan; Yang, Hongru
2015-02-01
Based on the propagation of Gaussian light, Zemax program is used to simulate the pump light propagating process and absorbing distribution for LDA side-pump laser rod,and the corresponding heat load distribution analysis of the rod is done by using Lascad program.On the basis of simulation results,the pump parameters of LDA side-pump Nd:YAG are optimized which provide valuable guidances for side-pump LDA designing and pump module engineering.
Application of stochastic parameter optimization to the Sacramento Soil Moisture Accounting model
NASA Astrophysics Data System (ADS)
Vrugt, Jasper A.; Gupta, Hoshin V.; Dekker, Stefan C.; Sorooshian, Soroosh; Wagener, Thorsten; Bouten, Willem
2006-06-01
Hydrological models generally contain parameters that cannot be measured directly, but can only be meaningfully inferred by calibration against a historical record of input-output data. While considerable progress has been made in the development and application of automatic procedures for model calibration, such methods have received criticism for their lack of rigor in treating uncertainty in the parameter estimates. In this paper, we apply the recently developed Shuffled Complex Evolution Metropolis algorithm (SCEM-UA) to stochastic calibration of the parameters in the Sacramento Soil Moisture Accounting model (SAC-SMA) model using historical data from the Leaf River in Mississippi. The SCEM-UA algorithm is a Markov Chain Monte Carlo sampler that provides an estimate of the most likely parameter set and underlying posterior distribution within a single optimization run. In particular, we explore the relationship between the length and variability of the streamflow data and the Bayesian uncertainty associated with the SAC-SMA model parameters and compare SCEM-UA derived parameter values with those obtained using deterministic SCE-UA calibrations. Most significantly, for the Leaf River catchments under study our results demonstrate that most of the 13 SAC-SMA parameters are well identified by calibration to daily streamflow data suggesting that this data contains more information than has previously been reported in the literature.
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.
Response of a quarter car model with optimal magnetorheological damper parameters
NASA Astrophysics Data System (ADS)
Prabakar, R. S.; Sujatha, C.; Narayanan, S.
2013-04-01
In this paper, the control of the stationary response of a quarter car model to random road excitation with a Magnetorheological (MR) damper as a semi-active suspension device is considered. The MR damper is a hypothetical analytical damper whose parameters are determined optimally using a multi-objective optimization technique Non-dominated Sorting Genetic Algorithm II (NSGA II). The hysteretic behaviour of the MR damper is characterized using Bingham and modified Bouc-Wen models. The multi-objective optimization problem is solved by minimizing the difference between the root mean square (rms) sprung mass acceleration, suspension stroke and the road holding responses of the quarter car model with the MR damper and those of the active suspension system based on linear quadratic regulator (LQR) control with the constraint that the MR damper control force lies between ±5 percent of the LQR control force. It is observed that the MR damper suspension systems with optimal parameters perform an order of magnitude better than the passive suspension and perform as well as active suspensions with limited state feedback and closer to the performance of fully active suspensions.
Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization.
Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri
2013-09-01
Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors.
Parameters optimization of laser brazing in crimping butt using Taguchi and BPNN-GA
NASA Astrophysics Data System (ADS)
Rong, Youmin; Zhang, Zhen; Zhang, Guojun; Yue, Chen; Gu, Yafei; Huang, Yu; Wang, Chunming; Shao, Xinyu
2015-04-01
The laser brazing (LB) is widely used in the automotive industry due to the advantages of high speed, small heat affected zone, high quality of welding seam, and low heat input. Welding parameters play a significant role in determining the bead geometry and hence quality of the weld joint. This paper addresses the optimization of the seam shape in LB process with welding crimping butt of 0.8 mm thickness using back propagation neural network (BPNN) and genetic algorithm (GA). A 3-factor, 5-level welding experiment is conducted by Taguchi L25 orthogonal array through the statistical design method. Then, the input parameters are considered here including welding speed, wire speed rate, and gap with 5 levels. The output results are efficient connection length of left side and right side, top width (WT) and bottom width (WB) of the weld bead. The experiment results are embed into the BPNN network to establish relationship between the input and output variables. The predicted results of the BPNN are fed to GA algorithm that optimizes the process parameters subjected to the objectives. Then, the effects of welding speed (WS), wire feed rate (WF), and gap (GAP) on the sum values of bead geometry is discussed. Eventually, the confirmation experiments are carried out to demonstrate the optimal values were effective and reliable. On the whole, the proposed hybrid method, BPNN-GA, can be used to guide the actual work and improve the efficiency and stability of LB process.
Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System
Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei
2015-01-01
Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm. PMID:26121614
Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.
Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei
2015-01-01
Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm. PMID:26121614
Spectral gap optimization of order parameters for sampling complex molecular systems.
Tiwary, Pratyush; Berne, B J
2016-03-15
In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs.
Variational optimization of sub-grid scale convection parameters. Final report
Zivkovic-Rothman, M.
1997-11-25
Under the DOE CHAMMP/CLIMATE Program, a convective scheme was developed for use in climate models. The purpose of the present study was to develop an adjoint model of its tangent-linear model. the convective scheme was integrated within a single column model which provides radiative-convective equilibrium solutions applicable to climate models. The main goal of this part of the project was to develop an adjoint of the scheme to facilitate the optimization of its convective parameters. For that purpose, adjoint sensitivities were calculated with the adjoint code. Parameter optimization was based on TOGA COARE data which were also used in this study to obtain integrations of the nonlinear and tangent-linear models as well as the integrations of the adjoint model. Some inadequacies of the inner IFA data array were found, and did not permit a single numerical integration during the entire 4 months of data. However, reliable monthly radiative-convective equilibrium solutions and associated adjoint sensitivities were obtained and used to bring about the parameter optimization.
Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization
Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri
2013-01-01
Abstract Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors. PMID:24065871
Spectral gap optimization of order parameters for sampling complex molecular systems
Tiwary, Pratyush; Berne, B. J.
2016-01-01
In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365
Jussen, Daniel; Soltner, Helmut; Stute, Birgit; Wiechert, Wolfgang; von Lieres, Eric; Pohl, Martina
2016-08-10
Enzymatic parameter determination is an essential step in biocatalytic process development. Therefore higher throughput in miniaturized devices is urgently needed. An ideal microfluidic device should combine easy immobilization and retention of a minimal amount of biocatalyst with a well-mixed reaction volume. Together, all criteria are hardly met by current tools. Here we describe a microfluidic reactor (μMORE) which employs magnetic particles for both enzyme immobilization and efficient mixing using two permanent magnets placed in rotating cylinders next to the a glass chip reactor. The chip geometry and agitation speed was optimized by investigation of the mixing and retention characteristics using simulation and dye distribution analysis. Subsequently, the μMORE was successfully applied to determine critical biocatalytic process parameters in a parallelized manner for the carboligation of benzaldehyde and acetaldehyde to (S)-2-hydroxy-1-phenylpropan-1-one with less than 5μg of benzoylformate decarboxylase from Pseudomonas putida immobilized on magnetic beads. Here, one run of the device in six parallelized glass reactors took only 2-3h for an immobilized enzyme with very low activity (∼2U/mg). The optimized parameter set was finally tested in a 10mL enzyme membrane reactor, demonstrating that the μMORE provides a solid data base for biocatalytic process optimization. PMID:27288595
NASA Astrophysics Data System (ADS)
Portnoy, David; Feuerbach, Robert; Heimberg, Jennifer
2011-10-01
Today there is a tremendous amount of interest in systems that can detect radiological or nuclear threats. Many of these systems operate in extremely high throughput situations where delays caused by false alarms can have a significant negative impact. Thus, calculating the tradeoff between detection rates and false alarm rates is critical for their successful operation. Receiver operating characteristic (ROC) curves have long been used to depict this tradeoff. The methodology was first developed in the field of signal detection. In recent years it has been used increasingly in machine learning and data mining applications. It follows that this methodology could be applied to radiological/nuclear threat detection systems. However many of these systems do not fit into the classic principles of statistical detection theory because they tend to lack tractable likelihood functions and have many parameters, which, in general, do not have a one-to-one correspondence with the detection classes. This work proposes a strategy to overcome these problems by empirically finding parameter values that maximize the probability of detection for a selected number of probabilities of false alarm. To find these parameter values a statistical global optimization technique that seeks to estimate portions of a ROC curve is proposed. The optimization combines elements of simulated annealing with elements of genetic algorithms. Genetic algorithms were chosen because they can reduce the risk of getting stuck in local minima. However classic genetic algorithms operate on arrays of Booleans values or bit strings, so simulated annealing is employed to perform mutation in the genetic algorithm. The presented initial results were generated using an isotope identification algorithm developed at Johns Hopkins University Applied Physics Laboratory. The algorithm has 12 parameters: 4 real-valued and 8 Boolean. A simulated dataset was used for the optimization study; the "threat" set of spectra
Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin
2016-01-01
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974
Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin
2016-01-01
The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974
Modenese, Luca; Ceseracciu, Elena; Reggiani, Monica; Lloyd, David G
2016-01-25
A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par.
Fast and Efficient Black Box Optimization Using the Parameter-less Population Pyramid.
Goldman, B W; Punch, W F
2015-01-01
The parameter-less population pyramid (P3) is a recently introduced method for performing evolutionary optimization without requiring any user-specified parameters. P3's primary innovation is to replace the generational model with a pyramid of multiple populations that are iteratively created and expanded. In combination with local search and advanced crossover, P3 scales to problem difficulty, exploiting previously learned information before adding more diversity. Across seven problems, each tested using on average 18 problem sizes, P3 outperformed all five advanced comparison algorithms. This improvement includes requiring fewer evaluations to find the global optimum and better fitness when using the same number of evaluations. Using both algorithm analysis and comparison, we find P3's effectiveness is due to its ability to properly maintain, add, and exploit diversity. Unlike the best comparison algorithms, P3 was able to achieve this quality without any problem-specific tuning. Thus, unlike previous parameter-less methods, P3 does not sacrifice quality for applicability. Therefore we conclude that P3 is an efficient, general, parameter-less approach to black box optimization which is more effective than existing state-of-the-art techniques.
Pan, C M; Fan, Y T; Xing, Y; Hou, H W; Zhang, M L
2008-05-01
Statistically based experimental designs were applied to optimizing process parameters for hydrogen production from glucose by Clostridium sp. Fanp2 which was isolated from effluent sludge of anaerobic hydrogen-producing bioreactor. The important factors influencing hydrogen production, which identified by initial screening method of Plackett-Burman, were glucose, phosphate buffer and vitamin solution. The path of steepest ascent was undertaken to approach the optimal region of the three significant factors. Box-Behnken design and response surface analysis were adopted to further investigate the mutual interaction between the variables and identify optimal values that bring maximum hydrogen production. Experimental results showed that glucose, vitamin solution and phosphate buffer concentration all had an individual significant influence on the specific hydrogen production potential (Ps). Simultaneously, glucose and vitamin solution, glucose and phosphate buffer were interdependent. The optimal conditions for the maximal Ps were: glucose 23.75 g/l, phosphate buffer 0.159 M and vitamin solution 13.3 ml/l. Using this statistical optimization method, the hydrogen production from glucose was increased from 2248.5 to 4165.9 ml H2/l.
Analysis and optimization of process parameters in Al-SiCp laser cladding
NASA Astrophysics Data System (ADS)
Riquelme, Ainhoa; Rodrigo, Pilar; Escalera-Rodríguez, María Dolores; Rams, Joaquín
2016-03-01
The laser cladding process parameters have great effect on the clad geometry and on dilution in the single and multi-pass aluminum matrix composite reinforced with SiC particles (Al/SiCp) coatings on ZE41 magnesium alloys deposited using a high-power diode laser (HPLD). The influence of the laser power (500-700 W), scan speed (3-17 mm/s) and laser beam focal position (focus, positive and negative defocus) on the shape factor, cladding-bead geometry, cladding-bead microstructure (including the presence of pores and cracks), and hardness has been evaluated. The correlation of these process parameters and their influence on the properties and ultimately, on the feasibility of the cladding process, is demonstrated. The importance of focal position is demonstrated. The different energy distribution of the laser beam cross section in focus plane or in positive and negative defocus plane affect on the cladding-bead properties.
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.
Parameter-space correlations of the optimal statistic for continuous gravitational-wave detection
Pletsch, Holger J.
2008-11-15
The phase parameters of matched-filtering searches for continuous gravitational-wave signals are sky position, frequency, and frequency time-derivatives. The space of these parameters features strong global correlations in the optimal detection statistic. For observation times smaller than 1 yr, the orbital motion of the Earth leads to a family of global-correlation equations which describes the 'global maximum structure' of the detection statistic. The solution to each of these equations is a different hypersurface in parameter space. The expected detection statistic is maximal at the intersection of these hypersurfaces. The global maximum structure of the detection statistic from stationary instrumental-noise artifacts is also described by the global-correlation equations. This permits the construction of a veto method which excludes false candidate events.
Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization.
Yu, Jing; Li, Yaan
2016-06-30
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target's velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms.
AuBuchon, J P; Carter, C S; Adde, M A; Meyer, D R; Klein, H G
1986-01-01
Automated apheresis techniques afford the opportunity of tailoring collection parameters for each donor's hematologic profile. This study investigated the effect of various settings of the volume offset parameter as utilized in the Haemonetics Model V50 instrumentation during platelet- and lymphocytapheresis to optimize product yield, purity, and collection efficiency. In both types of procedures, increased product yield could be obtained by using an increased volume offset for donors having lower hematocrits. This improvement was related to an increase in collection efficiency. Platelet products also contained fewer contaminating lymphocytes with this approach. Adjustment of the volume offset parameter can be utilized to make the most efficient use of donors and provide higher-quality products.
Madgulkar, A; Kadam, S; Pokharkar, V
2009-05-01
The purpose of the present work was to prepare buccal adhesive tablets of miconazole nitrate. The simplex centroid experimental design was used to arrive at optimum ratio of carbopol 934P, hydroxypropylmethylcellulose K4M and polyvinylpyrollidone, which will provide desired drug release and mucoadhesion. Swelling index, mucoadhesive strength and in vitro drug release of the prepared tablet was determined. The drug release and bioadhesion was dependent on type and relative amounts of the polymers. The optimized combination was subjected to in vitro antifungal activity, transmucosal permeation, drug deposition in mucosa, residence time and bioadhesion studies. IR spectroscopy was used to investigate any interaction between drug and excipients. Dissolution of miconazole from tablets was sustained for 6 h. based on the results obtained, it can be concluded that the prepared slow release buccoadhesive tablets of miconazole would markedly prolong the duration of antifungal activity. Comparison of in vitro antifungal activity of tablet with marketed gel showed that drug concentrations above the minimum inhibitory concentration were achieved immediately from both formulations but release from tablet was sustained up to 6 h, while the gel showed initially fast drug release, which did not sustain later. Drug permeation across buccal mucosa was minimum from the tablet as well as marketed gel; the deposition of drug in mucosa was higher in case of tablet. In vitro residence time and bioadhesive strength of tablet was higher than gel. Thus the buccoadhesive tablet of miconazole nitrate may offer better control of antifungal activity as compared to the gel formulation. PMID:20490296
Paramfit: automated optimization of force field parameters for molecular dynamics simulations.
Betz, Robin M; Walker, Ross C
2015-01-15
The generation of bond, angle, and torsion parameters for classical molecular dynamics force fields typically requires fitting parameters such that classical properties such as energies and gradients match precalculated quantum data for structures that scan the value of interest. We present a program, Paramfit, distributed as part of the AmberTools software package that automates and extends this fitting process, allowing for simplified parameter generation for applications ranging from single molecules to entire force fields. Paramfit implements a novel combination of a genetic and simplex algorithm to find the optimal set of parameters that replicate either quantum energy or force data. The program allows for the derivation of multiple parameters simultaneously using significantly fewer quantum calculations than previous methods, and can also fit parameters across multiple molecules with applications to force field development. Paramfit has been applied successfully to systems with a sparse number of structures, and has already proven crucial in the development of the Assisted Model Building with Energy Refinement Lipid14 force field. PMID:25413259
Paramfit: automated optimization of force field parameters for molecular dynamics simulations.
Betz, Robin M; Walker, Ross C
2015-01-15
The generation of bond, angle, and torsion parameters for classical molecular dynamics force fields typically requires fitting parameters such that classical properties such as energies and gradients match precalculated quantum data for structures that scan the value of interest. We present a program, Paramfit, distributed as part of the AmberTools software package that automates and extends this fitting process, allowing for simplified parameter generation for applications ranging from single molecules to entire force fields. Paramfit implements a novel combination of a genetic and simplex algorithm to find the optimal set of parameters that replicate either quantum energy or force data. The program allows for the derivation of multiple parameters simultaneously using significantly fewer quantum calculations than previous methods, and can also fit parameters across multiple molecules with applications to force field development. Paramfit has been applied successfully to systems with a sparse number of structures, and has already proven crucial in the development of the Assisted Model Building with Energy Refinement Lipid14 force field.
He, L; Huang, G H; Lu, H W
2010-04-15
Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the "true" ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes.
Mestrovic, Ante . E-mail: amestrovic@bccancer.bc.ca; Clark, Brenda G.
2005-11-01
Purpose: To develop a method of predicting the values of dose distribution parameters of different radiosurgery techniques for treatment of arteriovenous malformation (AVM) based on internal geometric parameters. Methods and Materials: For each of 18 previously treated AVM patients, four treatment plans were created: circular collimator arcs, dynamic conformal arcs, fixed conformal fields, and intensity-modulated radiosurgery. An algorithm was developed to characterize the target and critical structure shape complexity and the position of the critical structures with respect to the target. Multiple regression was employed to establish the correlation between the internal geometric parameters and the dose distribution for different treatment techniques. The results from the model were applied to predict the dosimetric outcomes of different radiosurgery techniques and select the optimal radiosurgery technique for a number of AVM patients. Results: Several internal geometric parameters showing statistically significant correlation (p < 0.05) with the treatment planning results for each technique were identified. The target volume and the average minimum distance between the target and the critical structures were the most effective predictors for normal tissue dose distribution. The structure overlap volume with the target and the mean distance between the target and the critical structure were the most effective predictors for critical structure dose distribution. The predicted values of dose distribution parameters of different radiosurgery techniques were in close agreement with the original data. Conclusions: A statistical model has been described that successfully predicts the values of dose distribution parameters of different radiosurgery techniques and may be used to predetermine the optimal technique on a patient-to-patient basis.
NASA Astrophysics Data System (ADS)
Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas
2016-04-01
Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.
Cabeza, I O; López, R; Ruiz-Montoya, M; Díaz, M J
2013-10-15
Composting is one of the most successful biological processes for the treatment of the residues enriched in putrescible materials. The optimization of parameters which have an influence on the stability of the products is necessary in order to maximize recycling and recovery of waste components. The influence of the composting process parameters (aeration, moisture, C/N ratio, and time) on the stability parameters (organic matter, N-losses, chemical oxygen demand, nitrate, biodegradability coefficient) of the compost was studied. The composting experiment was carried out using Municipal Solid Waste (MSW) and Legume Trimming Residues (LTR) in 200 L isolated acrylic barrels following a Box-Behnken central composite experimental design. Second-order polynomial models were found for each of the studied compost stability parameter, which accurately described the relationship between the parameters. The differences among the experimental values and those estimated by using the equations never exceeded 10% of the former. Results of the modelling showed that excluding the time, the C/N ratio is the strongest variable influencing almost all the stability parameters studied in this case, with the exception of N-losses which is strongly dependent on moisture. Moreover, an optimized ratio MSW/LTR of 1/1 (w/w), moisture content in the range of 40-55% and moderate to low aeration rate (0.05-0.175 Lair kg(-)(1) min(-1)) is recommended to maximise degradation and to obtain a stable product during co-composting of MSW and LTR. PMID:23764508
Leong, Wai Fun; Che Man, Yaakob B; Lai, Oi Ming; Long, Kamariah; Misran, Misni; Tan, Chin Ping
2009-09-23
The purpose of this study was to optimize the parameters involved in the production of water-soluble phytosterol microemulsions for use in the food industry. In this study, response surface methodology (RSM) was employed to model and optimize four of the processing parameters, namely, the number of cycles of high-pressure homogenization (1-9 cycles), the pressure used for high-pressure homogenization (100-500 bar), the evaporation temperature (30-70 degrees C), and the concentration ratio of microemulsions (1-5). All responses-particle size (PS), polydispersity index (PDI), and percent ethanol residual (%ER)-were well fit by a reduced cubic model obtained by multiple regression after manual elimination. The coefficient of determination (R(2)) and absolute average deviation (AAD) value for PS, PDI, and %ER were 0.9628 and 0.5398%, 0.9953 and 0.7077%, and 0.9989 and 1.0457%, respectively. The optimized processing parameters were 4.88 (approximately 5) homogenization cycles, homogenization pressure of 400 bar, evaporation temperature of 44.5 degrees C, and concentration ratio of microemulsions of 2.34 cycles (approximately 2 cycles) of high-pressure homogenization. The corresponding responses for the optimized preparation condition were a minimal particle size of 328 nm, minimal polydispersity index of 0.159, and <0.1% of ethanol residual. The chi-square test verified the model, whereby the experimental values of PS, PDI, and %ER agreed with the predicted values at a 0.05 level of significance. PMID:19694442
Optimizing galvanic pulse plating parameters to improve indium bump to bump bonding
NASA Astrophysics Data System (ADS)
Coleman, Jonathan J.; Rowen, Adam; Mani, Seethambal S.; Yelton, W. Graham; Arrington, Christian; Gillen, Rusty; Hollowell, Andrew E.; Okerlund, Daniel; Ionescu, Adrian
2010-02-01
The plating characteristics of a commercially available indium plating solution are examined and optimized to help meet the increasing performance demands of integrated circuits requiring substantial numbers of electrical interconnections over large areas. Current fabrication techniques rely on evaporation of soft metals, such as indium, into lift-off resist profiles. This becomes increasingly difficult to accomplish as pitches decrease and aspect ratios increase. To minimize pixel dimensions and maximize the number of pixels per unit area, lithography and electrochemical deposition (ECD) of indium has been investigated. Pulse ECD offers the capability of improving large area uniformity ideal for large area device hybridization. Electrochemical experimentation into lithographically patterned molds allow for large areas of bumps to be fabricated for low temperature indium to indium bonds. The galvanic pulse profile, in conjunction with the bath configuration, determines the uniformity of the plated array. This pulse is manipulated to produce optimal properties for hybridizing arrays of aligned and bonded indium bumps. The physical properties of the indium bump arrays are examined using a white light interferometer, a SEM and tensile pull testing. This paper provides details from the electroplating processes as well as conclusions leading to optimized plating conditions.
Brevet, Romain; Richter, Daniel; Graeff, Christian; Durante, Marco; Bert, Christoph
2015-01-01
Scanned ion beam therapy of lung tumors is severely limited in its clinical applicability by intrafractional organ motion, interference effects between beam and tumor motion (interplay), as well as interfractional anatomic changes. To compensate for dose deterioration caused by intrafractional motion, motion mitigation techniques, such as gating, have been developed. However, optimization of the treatment parameters is needed to further improve target dose coverage and normal tissue sparing. The aim of this study was to determine treatment-planning parameters that permit to recover good target coverage for each fraction of lung tumor treatments. For 9 lung tumor patients from MD Anderson Cancer Center (Houston, Texas), a total of 70 weekly time-resolved computed tomography (4DCT) datasets, which depict the evolution of the patient anatomy over the several fractions of the treatment, were available. Using the GSI in-house treatment planning system TRiP4D, 4D simulations were performed on each weekly 4DCT for each patient using gating and optimization of a single treatment plan based on a planning CT acquired prior to treatment. The impact on target dose coverage (V 95%,CTV) of variations in focus size and length of the gating window, as well as different additional margins and the number of fields was analyzed. It appeared that interfractional variability could potentially have a larger impact on V 95%,CTV than intrafractional motion. However, among the investigated parameters, the use of a large beam spot size, a short gating window, additional margins, and multiple fields permitted to obtain an average V 95%,CTV of 96.5%. In the presented study, it was shown that optimized treatment parameters have an important impact on target dose coverage in the treatment of moving tumors. Indeed, intrafractional motion occurring during the treatment of lung tumors and interfractional variability were best mitigated using a large focus, a short gating window, additional margins
Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling
Hamrick, Todd
2011-01-01
Efficiency in drilling is measured by Mechanical Specific Energy (MSE). MSE is the measure of the amount of energy input required to remove a unit volume of rock, expressed in units of energy input divided by volume removed. It can be expressed mathematically in terms of controllable parameters; Weight on Bit, Torque, Rate of Penetration, and RPM. It is well documented that minimizing MSE by optimizing controllable factors results in maximum Rate of Penetration. Current methods for computing MSE make it possible to minimize MSE in the field only through a trial-and-error process. This work makes it possible to compute the optimum drilling parameters that result in minimum MSE. The parameters that have been traditionally used to compute MSE are interdependent. Mathematical relationships between the parameters were established, and the conventional MSE equation was rewritten in terms of a single parameter, Weight on Bit, establishing a form that can be minimized mathematically. Once the optimum Weight on Bit was determined, the interdependent relationship that Weight on Bit has with Torque and Penetration per Revolution was used to determine optimum values for those parameters for a given drilling situation. The improved method was validated through laboratory experimentation and analysis of published data. Two rock types were subjected to four treatments each, and drilled in a controlled laboratory environment. The method was applied in each case, and the optimum parameters for minimum MSE were computed. The method demonstrated an accurate means to determine optimum drilling parameters of Weight on Bit, Torque, and Penetration per Revolution. A unique application of micro-cracking is also presented, which demonstrates that rock failure ahead of the bit is related to axial force more than to rotation speed.
NASA Astrophysics Data System (ADS)
Sif Gylfadóttir, Sigríður; Kim, Jihwan; Kristinn Helgason, Jón; Brynjólfsson, Sveinn; Höskuldsson, Ármann; Jóhannesson, Tómas; Bonnevie Harbitz, Carl; Løvholt, Finn
2016-04-01
The Askja central volcano is located in the Northern Volcanic Zone of Iceland. Within the main caldera an inner caldera was formed in an eruption in 1875 and over the next 40 years it gradually subsided and filled up with water, forming Lake Askja. A large rockslide was released from the Southeast margin of the inner caldera into Lake Askja on 21 July 2014. The release zone was located from 150 m to 350 m above the water level and measured 800 m across. The volume of the rockslide is estimated to have been 15-30 million m3, of which 10.5 million m3 was deposited in the lake, raising the water level by almost a meter. The rockslide caused a large tsunami that traveled across the lake, and inundated the shores around the entire lake after 1-2 minutes. The vertical run-up varied typically between 10-40 m, but in some locations close to the impact area it ranged up to 70 m. Lake Askja is a popular destination visited by tens of thousands of tourists every year but as luck would have it, the event occurred near midnight when no one was in the area. Field surveys conducted in the months following the event resulted in an extensive dataset. The dataset contains e.g. maximum inundation, high-resolution digital elevation model of the entire inner caldera, as well as a high resolution bathymetry of the lake displaying the landslide deposits. Using these data, a numerical model of the Lake Askja landslide and tsunami was developed using GeoClaw, a software package for numerical analysis of geophysical flow problems. Both the shallow water version and an extension of GeoClaw that includes dispersion, was employed to simulate the wave generation, propagation, and run-up due to the rockslide plunging into the lake. The rockslide was modeled as a block that was allowed to stretch during run-out after entering the lake. An optimization approach was adopted to constrain the landslide parameters through inverse modeling by comparing the calculated inundation with the observed run
NASA Astrophysics Data System (ADS)
Galbán, Craig J.; Spencer, Richard G. S.
2002-06-01
We present an analysis of the effects of chemical exchange and changes in T1 on metabolite quantitation for heart, skeletal muscle, and brain using the one-pulse experiment for a sample which is subject to temporal variation. We use an optimization algorithm to calculate interpulse delay times, TRs, and flip angles, θ, resulting in maximal root-mean-squared signal-to-noise per unit time ( S/ N) for all exchanging species under 5 and 10% constraints on quantitation errors. The optimization yields TR and θ pairs giving signal-to-noise per unit time close or superior to typical literature values. Additional simulations were performed to demonstrate explicitly the dependence of the quantitation errors on pulse parameters and variations in the properties of the sample, such as may occur after an intervention. We find that (i) correction for partial saturation in accordance with the usual analysis neglecting variations in metabolite concentrations and rate constants may readily result in quantitation errors of 15% or more; the exact degree of error depends upon the details of the system under consideration; (ii) if T1's vary as well, significantly larger quantitation errors may occur; and (iii) optimal values of pulse parameters may minimize errors in quantitation with minimal S/ N loss.
Jevtić, Aleksandar; Gutiérrez, Álvaro
2011-01-01
Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677
Optimization of kinetic parameters for the degradation of plasmid DNA in rat plasma
NASA Astrophysics Data System (ADS)
Chaudhry, Q. A.
2014-12-01
Biotechnology is a rapidly growing area of research work in the field of pharmaceutical sciences. The study of pharmacokinetics of plasmid DNA (pDNA) is an important area of research work. It has been observed that the process of gene delivery faces many troubles on the transport of pDNA towards their target sites. The topoforms of pDNA has been termed as super coiled (S-C), open circular (O-C) and linear (L), the kinetic model of which will be presented in this paper. The kinetic model gives rise to system of ordinary differential equations (ODEs), the exact solution of which has been found. The kinetic parameters, which are responsible for the degradation of super coiled, and the formation of open circular and linear topoforms have a great significance not only in vitro but for modeling of further processes as well, therefore need to be addressed in great detail. For this purpose, global optimization techniques have been adopted, thus finding the optimal results for the said model. The results of the model, while using the optimal parameters, were compared against the measured data, which gives a nice agreement.
Optimizing gravitational-wave searches for a population of coalescing binaries: Intrinsic parameters
NASA Astrophysics Data System (ADS)
Dent, T.; Veitch, J.
2014-03-01
We revisit the problem of searching for gravitational waves from inspiralling compact binaries in Gaussian colored noise. If the intrinsic parameters of a quasicircular, nonprecessing binary are known, then the optimal statistic for detecting the dominant mode signal in a single interferometer is given by the well-known two-phase matched filter. However, the matched filter signal-to-noise ratio (SNR) is not in general an optimal statistic for an astrophysical population of signals, since their distribution over the intrinsic parameters will almost certainly not mirror that of noise events, which is determined by the (Fisher) information metric. Instead, the optimal statistic for a given astrophysical distribution will be the Bayes factor, which we approximate using the output of a standard template matched filter search. We then quantify the improvement in number of signals detected for various populations of nonspinning binaries: for a distribution of signals uniformly distributed in volume and with component masses distributed uniformly over the range 1≤m1,2/M⊙≤24, (m1+m2)/M⊙≤25 at fixed expected SNR, we find ≳20% more signals at a false alarm threshold of 10-6 Hz in a single detector. The method may easily be generalized to binaries with nonprecessing spins.
NASA Astrophysics Data System (ADS)
Rajagopalan, Ramakrishnan
Polyaniline-polypyrrole composite coatings were formed on low carbon steel using oxalic acid as electrolyte by aqueous potentiostatic electrodeposition. Potentiostatic method is a powerful technique that can force simultaneous polymerization of both pyrrole and aniline. A passive layer of iron (II) oxalate is deposited on the steel surface prior to the formation of composite coatings. The electrochemical deposition process shows three distinct regimes---dissolution of steel, formation of passive layer and formation of polymeric composite coatings. These three regimes have been studied in depth using spectroscopic techniques and electron microscopy. Quantitative analysis of the Current-time transient (I-t) curves show that the nucleation and growth of the passive layer occur by diffusion controlled 3-D instantaneous nucleation. It has also been shown that the morphology and the chemical structure of the composite coatings depend upon the electrochemical deposition (ECD) parameters. The ECD parameters that affect the formation of the coatings are the applied potential; molar feed ratio of monomers and the reaction time. The development of the composite coatings on steel was studied in depth using Infrared Spectroscopy, Scanning Electron Microscopy and X-ray Photoelectron Spectroscopy. For equimolar feed ratio of monomers (aniline and pyrrole), it was shown that polypyrrole starts to form on the steel surface prior to the incorporation of polyaniline. Corrosion resistance and adhesion strength of the coatings were evaluated using DC polarization tests and Lap Joint tests respectively. It was shown that the electrochemical deposition parameters (molar feed ratio of monomers, applied potential and reaction time) influence the corrosion and adhesion performance of the coatings. In general, polyaniline-polypyrrole composite coatings show much better performance than the homopolymers. Especially, the coatings formed using equimolar feed ratio of monomers showed better
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
Yazdani, Nuri; Chawla, Vipin; Edwards, Eve; Wood, Vanessa; Park, Hyung Gyu; Utke, Ivo
2014-01-01
Many energy conversion and storage devices exploit structured ceramics with large interfacial surface areas. Vertically aligned carbon nanotube (VACNT) arrays have emerged as possible scaffolds to support large surface area ceramic layers. However, obtaining conformal and uniform coatings of ceramics on structures with high aspect ratio morphologies is non-trivial, even with atomic layer deposition (ALD). Here we implement a diffusion model to investigate the effect of the ALD parameters on coating kinetics and use it to develop a guideline for achieving conformal and uniform thickness coatings throughout the depth of ultra-high aspect ratio structures. We validate the model predictions with experimental data from ALD coatings of VACNT arrays. However, the approach can be applied to predict film conformality as a function of depth for any porous topology, including nanopores and nanowire arrays. PMID:24778944
NASA Astrophysics Data System (ADS)
Lafrenière-Bérubé, Charles; Chouteau, Michel; Shamsipour, Pejman; Olivo, Gema R.
2016-04-01
Spectral induced polarization (SIP) parameters can be extracted from field or laboratory complex resistivity measurements, and even airborne or ground frequency domain electromagnetic data. With the growing interest in application of complex resistivity measurements to environmental and mineral exploration problems, there is a need for accurate and easy-to-use inversion tools to estimate SIP parameters. These parameters, which often include chargeability and relaxation time may then be studied and related to other rock attributes such as porosity or metallic grain content, in the case of mineral exploration. We present an open source program, available both as a standalone application or Python module, to estimate SIP parameters using Markov-chain Monte Carlo (MCMC) sampling. The Python language is a high level, open source language that is now widely used in scientific computing. Our program allows the user to choose between the more common Cole-Cole (Pelton), Dias, or Debye decomposition models. Simple circuits composed of resistances and constant phase elements may also be used to represent SIP data. Initial guesses are required when using more classic inversion techniques such as the least-squares formulation, and wrong estimates are often the cause of bad curve fitting. In stochastic optimization using MCMC, the effect of the starting values disappears as the simulation proceeds. Our program is then optimized to do batch inversion over large data sets with as little user-interaction as possible. Additionally, the Bayesian formulation allows the user to do quality control by fully propagating the measurement errors in the inversion process, providing an estimation of the SIP parameters uncertainty. This information is valuable when trying to relate chargeability or relaxation time to other physical properties. We test the inversion program on complex resistivity measurements of 12 core samples from the world-class gold deposit of Canadian Malartic. Results show
NASA Astrophysics Data System (ADS)
Maheshwari, Arpit; Dumitrescu, Mihaela Aneta; Destro, Matteo; Santarelli, Massimo
2016-03-01
Battery models are riddled with incongruous values of parameters considered for validation. In this work, thermally coupled electrochemical model of the pouch is developed and discharge tests on a LiFePO4 pouch cell at different discharge rates are used to optimize the LiFePO4 battery model by determining parameters for which there is no consensus in literature. A discussion on parameter determination, selection and comparison with literature values has been made. The electrochemical model is a P2D model, while the thermal model considers heat transfer in 3D. It is seen that even with no phase change considered for LiFePO4 electrode, the model is able to simulate the discharge curves over a wide range of discharge rates with a single set of parameters provided a dependency of the radius of the LiFePO4 electrode on discharge rate. The approach of using a current dependent radius is shown to be equivalent to using a current dependent diffusion coefficient. Both these modelling approaches are a representation of the particle size distribution in the electrode. Additionally, the model has been thermally validated, which increases the confidence level in the selection of values of parameters.
NASA Astrophysics Data System (ADS)
Reza, M. S.; Yusoff, A. R.; Shaharun, M. A.
2012-09-01
The operating control parameters of injection flushing type of electrical discharge machining process on stainless steel 304 workpiece with copper tools are being optimized according to its individual machining characteristic i.e. surface roughness (SR). Higher SR during EDM machining process results for poor surface integrity of the workpiece. Hence, the quality characteristic for SR is set to lower-the-better to achieve the optimum surface integrity. Taguchi method has been used for the construction, layout and analysis of the experiment for each of the machining characteristic for the SR. The use of Taguchi method in the experiment saves a lot of time and cost of machining the experiment samples. Therefore, an L18 Orthogonal array which was the fundamental component in the statistical design of experiments has been used to plan the experiments and Analysis of Variance (ANOVA) is used to determine the optimum machining parameters for this machining characteristic. The control parameters selected for this optimization experiments are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. The result had shown that the lower the machining diameter, the lower will be the SR.
Garland, Joshua; James, Ryan G; Bradley, Elizabeth
2016-02-01
Delay-coordinate reconstruction is a proven modeling strategy for building effective forecasts of nonlinear time series. The first step in this process is the estimation of good values for two parameters, the time delay and the embedding dimension. Many heuristics and strategies have been proposed in the literature for estimating these values. Few, if any, of these methods were developed with forecasting in mind, however, and their results are not optimal for that purpose. Even so, these heuristics-intended for other applications-are routinely used when building delay coordinate reconstruction-based forecast models. In this paper, we propose an alternate strategy for choosing optimal parameter values for forecast methods that are based on delay-coordinate reconstructions. The basic calculation involves maximizing the shared information between each delay vector and the future state of the system. We illustrate the effectiveness of this method on several synthetic and experimental systems, showing that this metric can be calculated quickly and reliably from a relatively short time series, and that it provides a direct indication of how well a near-neighbor based forecasting method will work on a given delay reconstruction of that time series. This allows a practitioner to choose reconstruction parameters that avoid any pathologies, regardless of the underlying mechanism, and maximize the predictive information contained in the reconstruction. PMID:26986345
Bauri, Ranjit; Yadav, Devinder; Shyam Kumar, C.N.; Janaki Ram, G.D.
2015-01-01
Metal matrix composites (MMCs) exhibit improved strength but suffer from low ductility. Metal particles reinforcement can be an alternative to retain the ductility in MMCs (Bauri and Yadav, 2010; Thakur and Gupta, 2007) [1,2]. However, processing such composites by conventional routes is difficult. The data presented here relates to friction stir processing (FSP) that was used to process metal particles reinforced aluminum matrix composites. The data is the processing parameters, rotation and traverse speeds, which were optimized to incorporate Ni particles. A wide range of parameters covering tool rotation speeds from 1000 rpm to 1800 rpm and a range of traverse speeds from 6 mm/min to 24 mm/min were explored in order to get a defect free stir zone and uniform distribution of particles. The right combination of rotation and traverse speed was found from these experiments. Both as-received coarse particles (70 μm) and ball-milled finer particles (10 μm) were incorporated in the Al matrix using the optimized parameters. PMID:26566541
Parameter optimization of Dome A site testing DIMM by data mining
NASA Astrophysics Data System (ADS)
Xu, Lingzhe; Pei, Chong
2012-10-01
The extreme environment of Antarctic is valuable for astronomical observations. Dome C is proved has excellent seeing and transmission by site testing works. While the higher, colder inland plateau Dome A is widely predicted as even better astronomical site than Dome C. Preliminary site testing developed since the beginning of 2008 shows that Dome A has lower boundary layer and lower precipitable water vapour. Now the automated seeing monitor is urgently needed to quantify the site's optical character which is necessary for the telescope design and deployment. In addition, it has the requirement that DIMM must realize automatic measurement for nearly one year under the case of unmanned intervention during which a great quantity of data will be generated because of the limitation of Dome A. This paper aims at researching how to use the method of mining association rules to automatically analyze observation data, what the relationship between various parameters effecting on optical quality is, and improving the efficiency of telescope observation by parameter optimization. We have modified a commercial telescope with diameter of 35cm to function as site testing DIMM which has been installed at XingLong observation station of National Astronomical Observatories, Chinese Academy of Sciences, acquired long term observation data, and identified that this method is suitable for optimizing the parameters of DIMM system.
Optimization of intermolecular potential parameters for the CO2/H2O mixture.
Orozco, Gustavo A; Economou, Ioannis G; Panagiotopoulos, Athanassios Z
2014-10-01
Monte Carlo simulations in the Gibbs ensemble were used to obtain optimized intermolecular potential parameters to describe the phase behavior of the mixture CO2/H2O, over a range of temperatures and pressures relevant for carbon capture and sequestration processes. Commonly used fixed-point-charge force fields that include Lennard-Jones 12-6 (LJ) or exponential-6 (Exp-6) terms were used to describe CO2 and H2O intermolecular interactions. For force fields based on the LJ functional form, changes of the unlike interactions produced higher variations in the H2O-rich phase than in the CO2-rich phase. A major finding of the present study is that for these potentials, no combination of unlike interaction parameters is able to adequately represent properties of both phases. Changes to the partial charges of H2O were found to produce significant variations in both phases and are able to fit experimental data in both phases, at the cost of inaccuracies for the pure H2O properties. By contrast, for the Exp-6 case, optimization of a single parameter, the oxygen-oxygen unlike-pair interaction, was found sufficient to give accurate predictions of the solubilities in both phases while preserving accuracy in the pure component properties. These models are thus recommended for future molecular simulation studies of CO2/H2O mixtures. PMID:25198539
Alshetaili, Abdullah S; Almutairy, Bjad K; Alshahrani, Saad M; Ashour, Eman A; Tiwari, Roshan V; Alshehri, Sultan M; Feng, Xin; Alsulays, Bader B; Majumdar, Soumyajit; Langley, Nigel; Kolter, Karl; Gryczke, Andreas; Martin, Scott T; Repka, Michael A
2016-11-01
The aim of this study was to formulate face-cut, melt-extruded pellets, and to optimize hot melt process parameters to obtain maximized sphericity and hardness by utilizing Soluplus(®) as a polymeric carrier and carbamazepine (CBZ) as a model drug. Thermal gravimetric analysis (TGA) was used to detect thermal stability of CBZ. The Box-Behnken design for response surface methodology was developed using three factors, processing temperature ( °C), feeding rate (%), and screw speed (rpm), which resulted in 17 experimental runs. The influence of these factors on pellet sphericity and mechanical characteristics was assessed and evaluated for each experimental run. Pellets with optimal sphericity and mechanical properties were chosen for further characterization. This included differential scanning calorimetry, drug release, hardness friability index (HFI), flowability, bulk density, tapped density, Carr's index, and fourier transform infrared radiation (FTIR) spectroscopy. TGA data showed no drug degradation upon heating to 190 °C. Hot melt extrusion processing conditions were found to have a significant effect on the pellet shape and hardness profile. Pellets with maximum sphericity and hardness exhibited no crystalline peak after extrusion. The rate of drug release was affected mainly by pellet size, where smaller pellets released the drug faster. All optimized formulations were found to be of superior hardness and not friable. The flow properties of optimized pellets were excellent with high bulk and tapped density.
Assimilation of AMSR-E snow products with optimized snow parameters in mountainous basins
NASA Astrophysics Data System (ADS)
Lin, C.; Li, X.; Tsang, L.; Josberger, E. G.; Lettenmaier, D. P.
2012-12-01
Of the factors that affect microwave emissions of snowpacks, and in turn recoveries of snow radiative temperature, the snow pack grain size is among the most important. In an attempt to improve the ability to retrieve snow water equivalent from satellite passive microwave observations, we attempt first to improve estimates of the radiative temperature of the snow pack, and then use data assimilation techniques in a forward model. First, we partition the snow accumulation season based on the snow accumulation rate. For each period we calculate the brightness temperature (TB) of bare snow from AMSR-E observations, corrected for the forest cover fraction of each AMSR-E footprint. Given the observed snow depth (SD) and snow water equivalent (SWE), we then calculate the snow density and absorption coefficient (κa) of the snow. The optimal scattering coefficient (κs) is determined using Dense Media Radiative Transfer (DMRT) model of QCA and also of the bicontinuous medium. Finally, the optimal grain size is determined with respect to the optimal scattering coefficient. We verify the approach using field measurements from the Stanley Basin, Idaho. Finally, we assimilate the AMSR-E satellite observations of brightness temperature into the Variable Infiltration Capacity (VIC) hydrologic model. Combination of the VIC SWE simulation with the DMRT output using optimal physical parameters is expected to improve satellite-based SWE estimates in the mountainous region.
Impact of deposition parameters on the performance of ceria based resistive switching memories
NASA Astrophysics Data System (ADS)
Zhang, Lepeng; Younis, Adnan; Chu, Dewei; Li, Sean
2016-07-01
Resistive-switching memories stacked in a metal–insulator–metal (MIM) like structure have shown great potential for next generation non-volatile memories. In this study, ceria based resistive memory stacks are fabricated by implementing different sputter conditions (temperatures and powers). The films deposited at low temperatures were found to have random grain orientations, less porosity and dense structure. The effect of deposition conditions on resistive switching characteristics of as-prepared films were also investigated. Improved and reliable resistive switching behaviors were achieved for the memory devices occupying less porosity and densely packed structures prepared at low temperatures. Finally, the underlying switching mechanism was also explained on the basis of quantitative analysis.
Optimization of measure parameters for an X- and gamma-ray spectrometry portable system
NASA Astrophysics Data System (ADS)
Fernandes, Jaquiel S.; Appoloni, Carlos R.
2008-01-01
In order to optimize the use of a system for in situ gamma ( γ)- and X-ray spectrometry composed of a 3×3×1 mm 3 Cadmium Telluride (CdTe) detector with respect to the detection of low-activity radioactive sources, a two level factorial planning was accomplished, involving three factors that could modify the system response. This planning was made with a 137Cs punctual source, analyzing the X-ray energy line of 32 keV from 137mBa. It was concluded that, for the system optimization, the best configuration for the involved parameters was to work with the detector at temperature of -22 °C, shaping time of 3 μs and rise time discrimination (RTD) with value 3.
Optimizing treatment parameters for the vascular malformations using 1064-nm Nd:YAG laser
NASA Astrophysics Data System (ADS)
Gong, Wei; Lin, He; Xie, Shusen
2010-02-01
Near infrared Nd:YAG pulsed laser treatment had been proved to be an efficient method to treat large-sized vascular malformations like leg telangiectasia for deep penetrating depth into skin and uniform light distribution in vessel. However, optimal clinical outcome was achieved by various laser irradiation parameters and the key factor governing the treatment efficacy was still unclear. A mathematical model in combination with Monte Carlo algorithm and finite difference method was developed to estimate the light distribution, temperature profile and thermal damage in epidermis, dermis and vessel during and after 1064 nm pulsed Nd:YAG laser irradiation. Simulation results showed that epidermal protection could be achieved during 1064 nm Nd:YAG pulsed laser irradiation in conjunction with cryogen spray cooling. However, optimal vessel closure and blood coagulation depend on a compromise between laser spot size and pulse duration.
Using support vector machine and dynamic parameter encoding to enhance global optimization
NASA Astrophysics Data System (ADS)
Zheng, Z.; Chen, X.; Liu, C.; Huang, K.
2016-05-01
This study presents an approach which combines support vector machine (SVM) and dynamic parameter encoding (DPE) to enhance the run-time performance of global optimization with time-consuming fitness function evaluations. SVMs are used as surrogate models to partly substitute for fitness evaluations. To reduce the computation time and guarantee correct convergence, this work proposes a novel strategy to adaptively adjust the number of fitness evaluations needed according to the approximate error of the surrogate model. Meanwhile, DPE is employed to compress the solution space, so that it not only accelerates the convergence but also decreases the approximate error. Numerical results of optimizing a few benchmark functions and an antenna in a practical application are presented, which verify the feasibility, efficiency and robustness of the proposed approach.
NASA Technical Reports Server (NTRS)
Seidel, R. C.; Lehtinen, B.
1974-01-01
A technique is described for designing feedback control systems using frequency domain models, a quadratic cost function, and a parameter optimization computer program. FORTRAN listings for the computer program are included. The approach is applied to the design of shock position controllers for a supersonic inlet. Deterministic or random system disturbances, and the presence of random measurement noise are considered. The cost function minimization is formulated in the time domain, but the problem solution is obtained using a frequency domain system description. A scaled and constrained conjugate gradient algorithm is used for the minimization. The approach to a supersonic inlet included the calculations of the optimal proportional-plus integral (PI) and proportional-plus-integral-plus-derivative controllers. A single-loop PI controller was the most desirable of the designs considered.
NASA Technical Reports Server (NTRS)
Bernstein, Dennis S.; Rosen, I. G.
1988-01-01
In controlling distributed parameter systems it is often desirable to obtain low-order, finite-dimensional controllers in order to minimize real-time computational requirements. Standard approaches to this problem employ model/controller reduction techniques in conjunction with LQG theory. In this paper we consider the finite-dimensional approximation of the infinite-dimensional Bernstein/Hyland optimal projection theory. This approach yields fixed-finite-order controllers which are optimal with respect to high-order, approximating, finite-dimensional plant models. The technique is illustrated by computing a sequence of first-order controllers for one-dimensional, single-input/single-output, parabolic (heat/diffusion) and hereditary systems using spline-based, Ritz-Galerkin, finite element approximation. Numerical studies indicate convergence of the feedback gains with less than 2 percent performance degradation over full-order LQG controllers for the parabolic system and 10 percent degradation for the hereditary system.
Yang, Jie; Yang, Xiaodan; Ye, Xiuyun; Lin, Juan
2016-01-01
The data presented in this article are related to the research article entitled “Destaining of Coomassie Brilliant Blue R-250-stained polyacrylamide gels with fungal laccase” [1]. Laccase is a class of multicopper oxidases that can catalyze oxidation of recalcitrant dyestuffs. This article describes optimal parameters for destaining of polyacrylamide gels, stained with Coomassie Brilliant Blue R-250, with laccase from basidiomycete Cerrena sp. strain HYB07. Effects of laccase activity, mediator type and concentration, temperature and time on destaining of polyacrylamide gels were evaluated with respect to gel background intensity and protein band signals, and the optimal destaining effects were obtained with 15 U mL−1 laccase and 2 μM ABTS at 37 °C after 2 h. PMID:26955647
NASA Astrophysics Data System (ADS)
Mehedi, H.-A.; Baudrillart, B.; Alloyeau, D.; Mouhoub, O.; Ricolleau, C.; Pham, V. D.; Chacon, C.; Gicquel, A.; Lagoute, J.; Farhat, S.
2016-08-01
This article describes the significant roles of process parameters in the deposition of graphene films via cobalt-catalyzed decomposition of methane diluted in hydrogen using plasma-enhanced chemical vapor deposition (PECVD). The influence of growth temperature (700-850 °C), molar concentration of methane (2%-20%), growth time (30-90 s), and microwave power (300-400 W) on graphene thickness and defect density is investigated using Taguchi method which enables reaching the optimal parameter settings by performing reduced number of experiments. Growth temperature is found to be the most influential parameter in minimizing the number of graphene layers, whereas microwave power has the second largest effect on crystalline quality and minor role on thickness of graphene films. The structural properties of PECVD graphene obtained with optimized synthesis conditions are investigated with Raman spectroscopy and corroborated with atomic-scale characterization performed by high-resolution transmission electron microscopy and scanning tunneling microscopy, which reveals formation of continuous film consisting of 2-7 high quality graphene layers.
NASA Astrophysics Data System (ADS)
Murphy, Neil R.; Sun, Lirong; Grant, John T.; Jones, John G.; Jakubiak, Rachel
2015-10-01
Molybdenum oxide films were deposited using modulated pulse power magnetron sputtering (MPPMS) from a molybdenum target in a reactive environment where the flow rate of oxygen was varied from 0 sccm to 2.00 sccm. By varying the amount of reactive oxygen available during deposition, the composition of the films ranged from metallic Mo to fully stoichiometric MoO3, when the molybdenum target became poisoned, due to the formation of a dielectric surface oxide coating. Film compositions were verified using high energy resolution x-ray photoelectron spectroscopy. Target poisoning occurred at an oxygen flow rate of 1.25 sccm and reversed when the flow rate decreased to about 1.00 sccm. MoO3 films deposited via MPPMS had densities of 3.8 g cm-3, 81% of the density of crystalline α-MoO3 as determined by x-ray reflectivity (XRR). In addition, XRR and atomic force microscopy data showed sub-nanometer surface roughness values. From spectroscopic ellipsometry, the measured refractive index of the MoO3 films at 589 nm was 1.97 with extinction coefficient values <0.02 at wavelengths above the measured absorption edge of 506 nm (2.45 eV).
NASA Technical Reports Server (NTRS)
Pindera, Marek-Jerzy; Salzar, Robert S.
1996-01-01
The objective of this work was the development of efficient, user-friendly computer codes for optimizing fabrication-induced residual stresses in metal matrix composites through the use of homogeneous and heterogeneous interfacial layer architectures and processing parameter variation. To satisfy this objective, three major computer codes have been developed and delivered to the NASA-Lewis Research Center, namely MCCM, OPTCOMP, and OPTCOMP2. MCCM is a general research-oriented code for investigating the effects of microstructural details, such as layered morphology of SCS-6 SiC fibers and multiple homogeneous interfacial layers, on the inelastic response of unidirectional metal matrix composites under axisymmetric thermomechanical loading. OPTCOMP and OPTCOMP2 combine the major analysis module resident in MCCM with a commercially-available optimization algorithm and are driven by user-friendly interfaces which facilitate input data construction and program execution. OPTCOMP enables the user to identify those dimensions, geometric arrangements and thermoelastoplastic properties of homogeneous interfacial layers that minimize thermal residual stresses for the specified set of constraints. OPTCOMP2 provides additional flexibility in the residual stress optimization through variation of the processing parameters (time, temperature, external pressure and axial load) as well as the microstructure of the interfacial region which is treated as a heterogeneous two-phase composite. Overviews of the capabilities of these codes are provided together with a summary of results that addresses the effects of various microstructural details of the fiber, interfacial layers and matrix region on the optimization of fabrication-induced residual stresses in metal matrix composites.
Ju, Jonghyun; Han, Yun-ah; Kim, Seok-min
2013-01-01
The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC) label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV), full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1) the PWV can be measured by the reflection peak measurement instruments, (2) the grating pitch and duty can be manufactured using conventional lithography systems, and (3) the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU-1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm.
Ju, Jonghyun; Han, Yun-ah; Kim, Seok-min
2013-01-01
The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC) label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV), full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1) the PWV can be measured by the reflection peak measurement instruments, (2) the grating pitch and duty can be manufactured using conventional lithography systems, and (3) the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU-1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm. PMID:23470487
NASA Astrophysics Data System (ADS)
Salas, Y.; Vera, E.; Moreno, M.; Pineda, Y.
2016-02-01
Parameters required for the preparation of coatings of aluminium oxide deposited on AISI 1020 steels were determined according to their thickness and type of flame to differentiate their behaviour against corrosion. Commercial powders were used by the method of thermal spraying deposition. The coatings were analysed by OM (optical microscopy), the thickness was measured by means of a coating thickness gauge and electrochemical techniques variables measured was the Linear Polarization Resistance (LPR) and approximation Tafel potentiodynamic curves. The corrosion current for steel 1020 with Na2SO4 electrolyte of 3.5% is of the order of hundreds of A/cm2 and coated steel given in the order of A/cm2, which leads to think that the projection produces coatings uniform low closed porosity, although techniques DC indicate a significant porosity as is observable current response to the potentiodynamic curve. The observed thicknesses fall into the hundreds of microns and little uniformity was noted in this coatings. The coatings deposited by oxidizing flame was better performance in corrosion than the coating deposited by neutral flame.
The impact of different dose response parameters on biologically optimized IMRT in breast cancer
NASA Astrophysics Data System (ADS)
Costa Ferreira, Brigida; Mavroidis, Panayiotis; Adamus-Górka, Magdalena; Svensson, Roger; Lind, Bengt K.
2008-05-01
The full potential of biologically optimized radiation therapy can only be maximized with the prediction of individual patient radiosensitivity prior to treatment. Unfortunately, the available biological parameters, derived from clinical trials, reflect an average radiosensitivity of the examined populations. In the present study, a breast cancer patient of stage I II with positive lymph nodes was chosen in order to analyse the effect of the variation of individual radiosensitivity on the optimal dose distribution. Thus, deviations from the average biological parameters, describing tumour, heart and lung response, were introduced covering the range of patient radiosensitivity reported in the literature. Two treatment configurations of three and seven biologically optimized intensity-modulated beams were employed. The different dose distributions were analysed using biological and physical parameters such as the complication-free tumour control probability (P+), the biologically effective uniform dose (\\bar{\\bar{D}} ), dose volume histograms, mean doses, standard deviations, maximum and minimum doses. In the three-beam plan, the difference in P+ between the optimal dose distribution (when the individual patient radiosensitivity is known) and the reference dose distribution, which is optimal for the average patient biology, ranges up to 13.9% when varying the radiosensitivity of the target volume, up to 0.9% when varying the radiosensitivity of the heart and up to 1.3% when varying the radiosensitivity of the lung. Similarly, in the seven-beam plan, the differences in P+ are up to 13.1% for the target, up to 1.6% for the heart and up to 0.9% for the left lung. When the radiosensitivity of the most important tissues in breast cancer radiation therapy was simultaneously changed, the maximum gain in outcome was as high as 7.7%. The impact of the dose response uncertainties on the treatment outcome was clinically insignificant for the majority of the simulated patients
NASA Astrophysics Data System (ADS)
Cheng, Lishui; Hobbs, Robert F.; Segars, Paul W.; Sgouros, George; Frey, Eric C.
2013-06-01
smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.
NASA Astrophysics Data System (ADS)
Suman, A.; Mukerji, T.; Fernandez Martinez, J.
2010-12-01
Time lapse seismic data has begun to play an important role in reservoir characterization, management and monitoring. It can provide information on the dynamics of fluids in the reservoir based on the relation between variations of seismic signals and movement of hydrocarbons and changes in formation pressure. Reservoir monitoring by repeated seismic or time lapse surveys can help in reducing the uncertainties attached to reservoir models. In combination with geological and flow modeling as a part of history matching process it can provide better description of the reservoir and thus better reservoir forecasting. However joint inversion of seismic and flow data for reservoir parameter is highly non-linear and complex. Stochastic optimization based inversion has shown very good results in integration of time-lapse seismic and production data in reservoir history matching. In this paper we have used a family of particle swarm optimizers for inversion of semi-synthetic Norne field data set. We analyze the performance of the different PSO optimizers, both in terms of exploration and convergence rate. Finally we also show some promising and preliminary results of the application of differential evolution. All of the versions of PSO provide an acceptable match with the original synthetic model. The advantage of using global optimization method is that uncertainty can be assessed near the optimum point. To assess uncertainty near the optimum point we keep track of all particles over all iterations that have an objective function value below a selected cutoff. With these particles we plot the best, E-type and IQR (Inter quartile range) of porosity and permeability for each version of PSO. To compute uncertainty measures using a stochastic optimizer algorithm care has to be taken not to oversample the optimal point. We keep track of the evolution of the median distance between the global best in each of the iterations and the particles of the swarm. When this distance is
Macías, Demetrio; Luna, Ana; Skigin, Diana; Inchaussandague, Marina; Vial, Alexandre; Schinca, Daniel
2013-04-10
Natural photonic structures exhibit remarkable color effects such as metallic appearance and iridescence. A rigorous study of the electromagnetic response of such complex structures requires to accurately determine some of their relevant optical parameters, such as the refractive indices of the materials involved. In this paper, we apply different heuristic optimization strategies to retrieve the real and imaginary parts of the refractive index of the materials comprising natural multilayer systems. Through some examples, we compare the performances of the inversion methods proposed and show that these kinds of algorithms have a great potential as a tool to investigate natural photonic structures.
Yang, Chao; Jiang, Wen; Chen, Dong-Hua; Adiga, Umesh; Ng, Esmond G.; Chiu, Wah
2008-07-28
The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes.
OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE
Xie, Xianchao; Kou, S. C.; Brown, Lawrence
2015-01-01
This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results. PMID:27041778
NASA Astrophysics Data System (ADS)
Gao, Zhongmei; Shao, Xinyu; Jiang, Ping; Cao, Longchao; Zhou, Qi; Yue, Chen; Liu, Yang; Wang, Chunming
2016-09-01
It is of great significance to select appropriate welding process parameters for obtaining optimal weld geometry in hybrid laser-arc welding. An integrated optimization approach by combining Kriging model and GA is proposed to optimize process parameters. A four-factor, five-level experiment using Taguchi L25 is conducted considering laser power (P), welding current (A), distance between laser and arc (D) and traveling speed (V). Kriging model is adopted to approximate the relationship between process parameters and weld geometry, namely depth of penetration (DP), bead width (BW) and bead reinforcement (BR). The constructed Kriging model was used for parameters optimization by GA to maximize DP, minimize BW and ensure BR at a desired value. The effects of process parameters on weld geometry are analyzed. Microstructure and micro-hardness are also discussed. Verification experiments demonstrate that the obtained optimum values are in good agreement with experimental results.
Optimal design parameters of the bicycle-rider system for maximal muscle power output.
Yoshihuku, Y; Herzog, W
1990-01-01
The purpose of this study was to find the optimal values of design parameters for a bicycle-rider system (crank length, pelvic inclination, seat height, and rate of crank rotation) which maximize the power output from muscles of the human lower limb during bicycling. The human lower limb was modelled as a planar system of five rigid bodies connected by four smooth pin joints and driven by seven functional muscle groups. The muscles were assumed to behave according to an adapted form of Hill's equation. The dependence of the average power on the design parameters was examined. The instantaneous power of each muscle group was studied and simultaneous activity of two seemingly antagonistic muscle groups was analyzed. Average peak power for one full pedal revolution was found to be around 1100 W. The upper body position corresponding to this peak power output was slightly reclined, and the pedalling rate was 155 rpm for a nominal crank length of 170 mm.
NASA Astrophysics Data System (ADS)
Wu, Z.; Gao, Y.; Gong, H.; Li, L.
2016-04-01
Lacking of efficient methods, industry currently uses one only parameter—fuel flow rate—to evaluate the nozzle quality, which is far from satisfying the current emission regulations worldwide. By utilizing synchrotron radiation high energy X-ray in Shanghai Synchrotron Radiation Facility (SSRF), together with the imaging techniques, the 3D models of two nozzles with the same design dimensions were established, and the influence of parameters fluctuation in the azimuthal direction were analyzed in detail. Results indicate that, due to the orifice misalignment, even with the same design dimension, the inlet rounding radius of orifices differs greatly, and its fluctuation in azimuthal direction is also large. This difference will cause variation in the flow characteristics at orifice outlet and then further affect the spray characteristics. The study also indicates that, more precise investigation and insight into the evaluation and optimization of diesel nozzle structural parameter are needed.
NASA Astrophysics Data System (ADS)
Dhanapal, P.; Mohamed Nazirudeen, S. S.; Chandrasekar, A.
2012-04-01
Carbide Austempered Ductile Iron (CADI) is the family of ductile iron containing wear resistance alloy carbides in the ausferrite matrix. This CADI is manufactured by selecting and characterizing the proper material composition through the melting route done. In an effort to arrive the optimal production parameters of multi responses, Taguchi method and Grey relational analysis have been applied. To analyze the effect of production parameters on the mechanical properties signal-to-noise ratio and Grey relational grade have been calculated based on the design of experiments. An analysis of variance was calculated to find the amount of contribution of factors on mechanical properties and their significance. The analytical results of Taguchi method were compared with the experimental values, and it shows that both are identical.
Loewe, Axel; Wilhelms, Mathias; Schmid, Jochen; Krause, Mathias J.; Fischer, Fathima; Thomas, Dierk; Scholz, Eberhard P.; Dössel, Olaf; Seemann, Gunnar
2016-01-01
Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today’s high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non
NASA Astrophysics Data System (ADS)
Trudinger, Cathy M.; Raupach, Michael R.; Rayner, Peter J.; Kattge, Jens; Liu, Qing; Pak, Bernard; Reichstein, Markus; Renzullo, Luigi; Richardson, Andrew D.; Roxburgh, Stephen H.; Styles, Julie; Wang, Ying Ping; Briggs, Peter; Barrett, Damian; Nikolova, Sonja
2007-06-01
We describe results of a project known as OptIC (Optimisation InterComparison) for comparison of parameter estimation methods in terrestrial biogeochemical models. A highly simplified test model was used to generate pseudo-data to which noise with different characteristics was added. Participants in the OptIC project were asked to estimate the model parameters used to generate this data, and to predict model variables into the future. Ten participants contributed results using one of the following methods: Levenberg-Marquardt, adjoint, Kalman filter, Markov chain Monte Carlo and genetic algorithm. Methods differed in how they locate the minimum (gradient-descent or global search), how observations are processed (all at once sequentially), or the number of iterations used, or assumptions about the statistics (some methods assume Gaussian probability density functions; others do not). We found the different methods equally successful at estimating the parameters in our application. The biggest variation in parameter estimates arose from the choice of cost function, not the choice of optimization method. Relatively poor results were obtained when the model-data mismatch in the cost function included weights that were instantaneously dependent on noisy observations. This was the case even when the magnitude of residuals varied with the magnitude of observations. Missing data caused estimates to be more scattered, and the uncertainty of predictions increased correspondingly. All methods gave biased results when the noise was temporally correlated or non-Gaussian, or when incorrect model forcing was used. Our results highlight the need for care in choosing the error model in any optimization.
Parameter Optimization and Field Validation of the Functional–Structural Model GREENLAB for Maize
GUO, YAN; MA, YUNTAO; ZHAN, ZHIGANG; LI, BAOGUO; DINGKUHN, MICHAEL; LUQUET, DELPHINE; DE REFFYE, PHILIPPE
2006-01-01
• Background and Aims There are three reasons for the increasing demand for crop models that build the plant on the basis of architectural principles and organogenetic processes: (1) realistic concepts for developing new crops need to be guided by such models; (2) there is an increasing interest in crop phenotypic plasticity, based on variable architecture and morphology; and (3) engineering of mechanized cropping systems requires information on crop architecture. The functional–structural model GREENLAB was recently presented that simulates resource-dependent plasticity of plant architecture. This study introduces a new methodology for crop parameter optimization against measured data called multi-fitting, validates the calibrated model for maize with independent field data, and describes a technique for 3D visualization of outputs. • Methods Maize was grown near Beijing during the 2000, 2001 and 2003 (two sowing dates) summer seasons in a block design with four to five replications. Detailed morphological and topological observations were made on the plant architecture throughout the development of the four crops. Data obtained in 2000 was used to establish target files for parameter optimization using the generalized least square method, and parameter accuracy was evaluated by coefficient of variance. In situ plant digitization was used to establish 3D symbol files for organs that were then used to translate model outputs directly into 3D representations for each time step of model execution. •Key Results and Conclusions Multi-fitting against several target files obtained at different growth stages gave better parameter accuracy than single fitting at maturity only, and permitted extracting generic organ expansion kinetics from the static observations. The 2000 model gave excellent predictions of plant architecture and vegetative growth for the other three seasons having different temperature regimes, but predictions of inter-seasonal variability of
Ryumin, Pavel; Brown, Jeffery; Morris, Michael; Cramer, Rainer
2016-07-15
Liquid matrix-assisted laser desorption/ionization (MALDI) allows the generation of predominantly multiply charged ions in atmospheric pressure (AP) MALDI ion sources for mass spectrometry (MS) analysis. The charge state distribution of the generated ions and the efficiency of the ion source in generating such ions crucially depend on the desolvation regime of the MALDI plume after desorption in the AP-to-vacuum inlet. Both high temperature and a flow regime with increased residence time of the desorbed plume in the desolvation region promote the generation of multiply charged ions. Without such measures the application of an electric ion extraction field significantly increases the ion signal intensity of singly charged species while the detection of multiply charged species is less dependent on the extraction field. In general, optimization of high temperature application facilitates the predominant formation and detection of multiply charged compared to singly charged ion species. In this study an experimental set-up and optimization strategy is described for liquid AP-MALDI MS which improves the ionization efficiency of selected ion species up to 14 times. In combination with ion mobility separation, the method allows the detection of multiply charged peptide and protein ions for analyte solution concentrations as low as 2fmol/μL (0.5μL, i.e. 1fmol, deposited on the target) with very low sample consumption in the low nL-range. PMID:26827934
Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)
NASA Astrophysics Data System (ADS)
Xing, Lei; Li, Ruijiang
2014-03-01
The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.
Optimization principle of operating parameters of heat exchanger by using CFD simulation
NASA Astrophysics Data System (ADS)
Mičieta, Jozef; Jiří, Vondál; Jandačka, Jozef; Lenhard, Richard
2016-03-01
Design of effective heat transfer devices and minimizing costs are desired sections in industry and they are important for both engineers and users due to the wide-scale use of heat exchangers. Traditional approach to design is based on iterative process in which is gradually changed design parameters, until a satisfactory solution is achieved. The design process of the heat exchanger is very dependent on the experience of the engineer, thereby the use of computational software is a major advantage in view of time. Determination of operating parameters of the heat exchanger and the subsequent estimation of operating costs have a major impact on the expected profitability of the device. There are on the one hand the material and production costs, which are immediately reflected in the cost of device. But on the other hand, there are somewhat hidden costs in view of economic operation of the heat exchanger. The economic balance of operation significantly affects the technical solution and accompanies the design of the heat exchanger since its inception. Therefore, there is important not underestimate the choice of operating parameters. The article describes an optimization procedure for choice of cost-effective operational parameters for a simple double pipe heat exchanger by using CFD software and the subsequent proposal to modify its design for more economical operation.
Optimization of process parameters of pulsed TIG welded maraging steel C300
NASA Astrophysics Data System (ADS)
Deepak, P.; Jualeash, M. J.; Jishnu, J.; Srinivasan, P.; Arivarasu, M.; Padmanaban, R.; Thirumalini, S.
2016-09-01
Pulsed TIG welding technology provides excellent welding performance on thin sections which helps to increase productivity, enhance weld quality, minimize weld costs, and boost operator efficiency and this has drawn the attention of the welding society. Maraging C300 steel is extensively used in defence and aerospace industry and thus its welding becomes an area of paramount importance. In pulsed TIG welding, weld quality depends on the process parameters used. In this work, Pulsed TIG bead-on-plate welding is performed on a 5mm thick maraging C300 plate at different combinations of input parameters: peak current (Ip), base current (Ib) and pulsing frequency (HZ) as per box behnken design with three-levels for each factor. Response surface methodology is utilized for establishing a mathematical model for predicting the weld bead depth. The effect of Ip, Ib and HZ on the weld bead depth is investigated using the developed model. The weld bead depth is found to be affected by all the three parameters. Surface and contour plots developed from regression equation are used to optimize the processing parameters for maximizing the weld bead depth. Optimum values of Ip, Ib and HZ are obtained as 259 A, 120 A and 8 Hz respectively. Using this optimum condition, maximum bead depth of the weld is predicted to be 4.325 mm.
OPTIMIZATION-BASED CONSTITUTIVE PARAMETER IDENTIFICATION FROM SPARSE TAYLOR CYLINDER DATA
J.M. Lacy
2010-10-01
The classic Taylor impact test imparts temporally and spatially varying fields of strain, strain rate, and temperature through the specimen. It is possible to exploit this complexity to directly identify constitutive model parameters from the deformed shape of the specimen. Where prior investigators have employed various mathematical fitting methods to identify or improve strength model parameters from Taylor cylinder profiles, we extend the method to employ a multi-objective genetic optimization algorithm to minimize the cylinder profile errors simultaneously on three cylinders impacted at different velocities. No experimental data other than the three Taylor cylinders is employed in developing the constitutive model parameter set, and generic starting coefficients are employed. To validate the accuracy of the resulting coefficients, both split Hopkinson pressure bar and axisymmetric expanding ring tests were conducted and compared to the resultant Johnson-Cook strength model. The derived strength model agreed well with experimental data available to date. Further work is necessary to evaluate the range of rates and temperatures over which parameters derived by this method may be applied.
Kang, Mingon; Gao, Jean; Tang, Liping
2011-01-01
Developing vigorous mathematical equations and estimating accurate parameters within feasible computational time are two indispensable parts to build reliable system models for representing biological properties of the system and for producing reliable simulation. For a complex biological system with limited observations, one of the daunting tasks is the large number of unknown parameters in the mathematical modeling whose values directly determine the performance of computational modeling. To tackle this problem, we have developed a data-driven global optimization method, nonlinear RANSAC, based on RANdom SAmple Consensus (a.k.a. RANSAC) method for parameter estimation of nonlinear system models. Conventional RANSAC method is sound and simple, but it is oriented for linear system models. We not only adopt the strengths of RANSAC, but also extend the method to nonlinear systems with outstanding performance. As a specific application example, we have targeted understanding phagocyte transmigration which is involved in the fibrosis process for biomedical device implantation. With well-defined mathematical nonlinear equations of the system, nonlinear RANSAC is performed for the parameter estimation. In order to evaluate the general performance of the method, we also applied the method to signalling pathways with ordinary differential equations as a general format. PMID:23227455
Lilja, Mirjam; Welch, Ken; Astrand, Maria; Engqvist, Håkan; Strømme, Maria
2012-05-01
This article evaluates the influence of the main parameters in a cathodic arc deposition process on the microstructure of titanium dioxide thin coatings and correlates these to the photocatalytic activity (PCA) and in vitro bioactivity of the coatings. Bioactivity of all as deposited coatings was confirmed by the growth of uniform layers of hydroxyapatite (HA) after 7 days in phosphate buffered saline at 37°C. Comparison of the HA growth after 24 h indicated enhanced HA formation on coatings with small titanium dioxide grains of rutile and anatase phase. The results from the PCA studies showed that coatings containing a mixed microstructure of both anatase and rutile phases, with small grain sizes in the range of 26-30 nm and with a coating thickness of about 250 nm, exhibited enhanced activity as compared with other microstructures and higher coating thickness. The results of this study should be valuable for the development of new bioactive implant coatings with photocatalytically induced on-demand antibacterial properties.
2007-01-01
Several modifications that have been made to the NDDO core-core interaction term and to the method of parameter optimization are described. These changes have resulted in a more complete parameter optimization, called PM6, which has, in turn, allowed 70 elements to be parameterized. The average unsigned error (AUE) between calculated and reference heats of formation for 4,492 species was 8.0 kcal mol−1. For the subset of 1,373 compounds involving only the elements H, C, N, O, F, P, S, Cl, and Br, the PM6 AUE was 4.4 kcal mol−1. The equivalent AUE for other methods were: RM1: 5.0, B3LYP 6–31G*: 5.2, PM5: 5.7, PM3: 6.3, HF 6–31G*: 7.4, and AM1: 10.0 kcal mol−1. Several long-standing faults in AM1 and PM3 have been corrected and significant improvements have been made in the prediction of geometries. Figure Calculated structure of the complex ion [Ta6Cl12]2+ (footnote): Reference value in parenthesis Electronic supplementary material The online version of this article (doi:10.1007/s00894-007-0233-4) contains supplementary material, which is available to authorized users. PMID:17828561
Heidari, Ali; Forouzan, Mohammad R.
2012-01-01
Chatter has been recognized as major restriction for the increase in productivity of cold rolling processes, limiting the rolling speed for thin steel strips. It is shown that chatter has close relation with rolling conditions. So the main aim of this paper is to attain the optimum set points of rolling to achieve maximum rolling speed, preventing chatter to occur. Two combination methods were used for optimization. First method is done in four steps: providing a simulation program for chatter analysis, preparing data from simulation program based on central composite design of experiment, developing a statistical model to relate system tendency to chatter and rolling parameters by response surface methodology, and finally optimizing the process by genetic algorithm. Second method has analogous stages. But central composite design of experiment is replaced by Taguchi method and response surface methodology is replaced by neural network method. Also a study on the influence of the rolling parameters on system stability has been carried out. By using these combination methods, new set points were determined and significant improvement achieved in rolling speed. PMID:25685398
Huang, X N; Ren, H P
2016-01-01
Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043
Atkinson, Ian C.; Lu, Aiming; Thulborn, Keith R.
2011-01-01
The rapid transverse relaxation of the sodium magnetic resonance (MR) signal during spatial encoding causes a loss of image resolution, an effect known as T2-blurring. Conventional wisdom suggests that spatial resolution is maximized by keeping the readout duration as short as possible to minimize T2-blurring. Flexible twisted projection imaging (flexTPI) performed with an ultra-short echo time, relative to T2, and a long repetition time, relative to T1, has been shown to be effective for quantitative sodium MR imaging. A minimized readout duration requires a very large number of projections and, consequentially, results in an impractically long total acquisition time to meet these conditions. When the total acquisition time is limited to a clinically practical duration (e.g., 10 minutes), the optimal parameters for maximal spatial resolution of a flexTPI acquisition do not correspond to the shortest possible readout. Simulation and experimental results for resolution optimized acquisition parameters of quantitative sodium flexTPI of parenchyma and cerebrospinal fluid are presented for the human brain at 9.4T and 3T. The effect of signal loss during data collection on sodium quantification bias and image signal-to-noise ratio are discussed. PMID:21446034
NASA Astrophysics Data System (ADS)
Toghi Eshghi, Amin; Lee, Soobum; Lee, Hanmin; Kim, Young-Cheol
2016-04-01
In this paper, we perform design parameter study and design optimization for a piezoelectric energy harvester considering vehicle speed variation. Initially, a FEM model using ANSYS is developed to appraise the performance of a piezoelectric harvester in a rotating tire. The energy harvester proposed here uses the vertical deformation at contact patch area from the car weight and centrifugal acceleration. This harvester is composed of a beam which is clamped at both ends and a piezoelectric material is attached on the top of that. The piezoelectric material possesses the 31 mode of transduction in which the direction of applied field is perpendicular to that of the electric field. To optimize the harvester performance, we would change the geometrical parameters of the harvester to obtain the maximum power. One of the main challenges in the design process is obtaining the required power while considering the constraints for harvester weight and volume. These two concerns are addressed in this paper. Since the final goal of this study is the development of an energy harvester with a wireless sensor system installed in a real car, the real time data for varied velocity of a vehicle are taken into account for power measurements. This study concludes that the proposed design is applicable to wireless tire sensor systems.
Heidari, Ali; Forouzan, Mohammad R
2013-01-01
Chatter has been recognized as major restriction for the increase in productivity of cold rolling processes, limiting the rolling speed for thin steel strips. It is shown that chatter has close relation with rolling conditions. So the main aim of this paper is to attain the optimum set points of rolling to achieve maximum rolling speed, preventing chatter to occur. Two combination methods were used for optimization. First method is done in four steps: providing a simulation program for chatter analysis, preparing data from simulation program based on central composite design of experiment, developing a statistical model to relate system tendency to chatter and rolling parameters by response surface methodology, and finally optimizing the process by genetic algorithm. Second method has analogous stages. But central composite design of experiment is replaced by Taguchi method and response surface methodology is replaced by neural network method. Also a study on the influence of the rolling parameters on system stability has been carried out. By using these combination methods, new set points were determined and significant improvement achieved in rolling speed.
SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier
Huang, Mei-Ling; Hung, Yung-Hsiang; Lee, W. M.; Li, R. K.; Jiang, Bo-Ru
2014-01-01
Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. Dermatology dataset contains 33 feature variables, 1 class variable, and 366 testing instances; and the Zoo dataset contains 16 feature variables, 1 class variable, and 101 testing instances. The feature variables in the two datasets were sorted in descending order by explanatory power, and different feature sets were selected by SVM-RFE to explore classification accuracy. Meanwhile, Taguchi method was jointly combined with SVM classifier in order to optimize parameters C and γ to increase classification accuracy for multiclass classification. The experimental results show that the classification accuracy can be more than 95% after SVM-RFE feature selection and Taguchi parameter optimization for Dermatology and Zoo databases. PMID:25295306
Parameter Sweep and Optimization of Loosely Coupled Simulations Using the DAKOTA Toolkit
Elwasif, Wael R; Bernholdt, David E; Pannala, Sreekanth; Allu, Srikanth; Foley, Samantha S
2012-01-01
The increasing availability of large scale computing capabilities has accelerated the development of high-fidelity coupled simulations. Such simulations typically involve the integration of models that implement various aspects of the complex phenomena under investigation. Coupled simulations are playing an integral role in fields such as climate modeling, earth systems modeling, rocket simulations, computational chemistry, fusion research, and many other computational fields. Model coupling provides scientists with systematic ways to virtually explore the physical, mathematical, and computational aspects of the problem. Such exploration is rarely done using a single execution of a simulation, but rather by aggregating the results from many simulation runs that, together, serve to bring to light novel knowledge about the system under investigation. Furthermore, it is often the case (particularly in engineering disciplines) that the study of the underlying system takes the form of an optimization regime, where the control parameter space is explored to optimize an objective functions that captures system realizability, cost, performance, or a combination thereof. Novel and flexible frameworks that facilitate the integration of the disparate models into a holistic simulation are used to perform this research, while making efficient use of the available computational resources. In this paper, we describe the integration of the DAKOTA optimization and parameter sweep toolkit with the Integrated Plasma Simulator (IPS), a component-based framework for loosely coupled simulations. The integration allows DAKOTA to exploit the internal task and resource management of the IPS to dynamically instantiate simulation instances within a single IPS instance, allowing for greater control over the trade-off between efficiency of resource utilization and time to completion. We present a case study showing the use of the combined DAKOTA-IPS system to aid in the design of a lithium ion
Parameter optimization for image denoising based on block matching and 3D collaborative filtering
NASA Astrophysics Data System (ADS)
Pedada, Ramu; Kugu, Emin; Li, Jiang; Yue, Zhanfeng; Shen, Yuzhong
2009-02-01
Clinical MRI images are generally corrupted by random noise during acquisition with blurred subtle structure features. Many denoising methods have been proposed to remove noise from corrupted images at the expense of distorted structure features. Therefore, there is always compromise between removing noise and preserving structure information for denoising methods. For a specific denoising method, it is crucial to tune it so that the best tradeoff can be obtained. In this paper, we define several cost functions to assess the quality of noise removal and that of structure information preserved in the denoised image. Strength Pareto Evolutionary Algorithm 2 (SPEA2) is utilized to simultaneously optimize the cost functions by modifying parameters associated with the denoising methods. The effectiveness of the algorithm is demonstrated by applying the proposed optimization procedure to enhance the image denoising results using block matching and 3D collaborative filtering. Experimental results show that the proposed optimization algorithm can significantly improve the performance of image denoising methods in terms of noise removal and structure information preservation.
Parameters optimization for the energy management system of hybrid electric vehicle
NASA Astrophysics Data System (ADS)
Tseng, Chyuan-Yow; Hung, Yi-Hsuan; Tsai, Chien-Hsiung; Huang, Yu-Jen
2007-12-01
Hybrid electric vehicle (HEV) has been widely studied recently due to its high potential in reduction of fuel consumption, exhaust emission, and lower noise. Because of comprised of two power sources, the HEV requires an energy management system (EMS) to distribute optimally the power sources for various driving conditions. The ITRI in Taiwan has developed a HEV consisted of a 2.2L internal combustion engine (ICE), a 18KW motor/generator (M/G), a 288V battery pack, and a continuous variable transmission (CVT). The task of the present study is to design an energy management strategy of the EMS for the HEV. Due to the nonlinear nature and the fact of unknown system model of the system, a kind of simplex method based energy management strategy is proposed for the HEV system. The simplex method is a kind of optimization strategy which is generally used to find out the optimal parameters for un-modeled systems. The way to apply the simplex method for the design of the EMS is presented. The feasibility of the proposed method was verified by perform numerical simulation on the FTP75 drive cycles.
Comparison of global optimization approaches for robust calibration of hydrologic model parameters
NASA Astrophysics Data System (ADS)
Jung, I. W.
2015-12-01
Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.
Taniguchi, Yoichi; Aoki, Akira; Mizutani, Koji; Takeuchi, Yasuo; Ichinose, Shizuko; Takasaki, Aristeo Atsushi; Schwarz, Frank; Izumi, Yuichi
2013-07-01
Er:YAG laser (ErL) irradiation has been reported to be effective for treating peri-implant disease. The present study seeks to evaluate morphological and elemental changes induced on microstructured surfaces of dental endosseous implants by high-pulse-repetition-rate ErL irradiation and to determine the optimal irradiation conditions for debriding contaminated microstructured surfaces. In experiment 1, dual acid-etched microstructured implants were irradiated by ErL (pulse energy, 30-50 mJ/pulse; repetition rate, 30 Hz) with and without water spray and for used and unused contact tips. Experiment 2 compared the ErL treatment with conventional mechanical treatments (metal/plastic curettes and ultrasonic scalers). In experiment 3, five commercially available microstructures were irradiated by ErL light (pulse energy, 30-50 mJ/pulse; pulse repetition rate, 30 Hz) while spraying water. In experiment 4, contaminated microstructured surfaces of three failed implants were debrided by ErL irradiation. After the experiments, all treated surfaces were assessed by stereomicroscopy, scanning electron microscopy (SEM), and/or energy-dispersive X-ray spectroscopy (EDS). The stereomicroscopy, SEM, and EDS results demonstrate that, unlike mechanical treatments, ErL irradiation at 30 mJ/pulse and 30 Hz with water spray induced no color or morphological changes to the microstructures except for the anodized implant surface, which was easily damaged. The optimized irradiation parameters effectively removed calcified deposits from contaminated titanium microstructures without causing substantial thermal damage. ErL irradiation at pulse energies below 30 mJ/pulse (10.6 J/cm(2)/pulse) and 30 Hz with water spray in near-contact mode seems to cause no damage and to be effective for debriding microstructured surfaces (except for anodized microstructures). PMID:22886137
NASA Astrophysics Data System (ADS)
Zidikheri, Meelis J.; Potts, Rodney J.
2015-09-01
A simple inversion scheme for optimizing volcanic emission dispersion model parameters with respect to satellite detections is presented in this paper. In this scheme, multiple dispersion model simulations, obtained by varying relevant model parameters, are created and compared against satellite detections using pattern correlation as a measure of model agreement with observations. It is shown that the scheme is successful in inferring emission source parameters such as those describing the vertical extent of the nascent sulfur dioxide emissions in the November 2010 Mount Merapi eruption in Java, Indonesia. These optimal parameter values then become a basis for improved forecasts of the transport of volcanic emissions.
Kafizas, Andreas; Parkin, Ivan P
2011-12-21
We demonstrate how combinatorial atmospheric pressure chemical vapor deposition (cAPCVD) can be used as a synthetic tool for rapidly optimizing the functional properties of thin-films, by analyzing the self-cleaning properties of tungsten doped anatase as an example. By introducing reagents at separate points inside the reactor, a tungsten/titanium compositional gradient was formed and a diverse range of film growth conditions were obtained. By partially mixing the metal sources, a combinatorial film with a compositional profile that varied primarily in the lateral plane was synthesized. A combinatorial thin-film of anatase TiO(2) doped with an array of tungsten levels as a solid solution ranging from 0.38-13.8 W/Ti atom % was formed on a single glass substrate. The compositional-functional relationships were understood through comprehensively analyzing combinatorial phase space, with 200 positions investigated by high-throughput methods in this study. Physical and functional properties, and their compositional dependencies, were intercorrelated. It was found that increases in photocatalytic activity and conductivity were most highly dependent on film crystallinity within the 0.38-13.8 atom % W/Ti doping regime. However, enhancements in photoinduced surface wetting were primarily dependent on increases in preferred growth in the (211) crystal plane. PMID:22050427
NASA Astrophysics Data System (ADS)
Salavati, S.; Coyle, T. W.; Mostaghimi, J.
2015-10-01
Open pore metallic foam core sandwich panels prepared by thermal spraying of a coating on the foam structures can be used as high-efficiency heat transfer devices due to their high surface area to volume ratio. The structural, mechanical, and physical properties of thermally sprayed skins play a significant role in the performance of the related devices. These properties are mainly controlled by the porosity content, oxide content, adhesion strength, and stiffness of the deposited coating. In this study, the effects of grit-blasting process parameters on the characteristics of the temporary surface created on the metallic foam substrate and on the twin-wire arc-sprayed alloy 625 coating subsequently deposited on the foam were investigated through response surface methodology. Characterization of the prepared surface and sprayed coating was conducted by scanning electron microscopy, roughness measurements, and adhesion testing. Using statistical design of experiments, response surface method, a model was developed to predict the effect of grit-blasting parameters on the surface roughness of the prepared foam and also the porosity content of the sprayed coating. The coating porosity and adhesion strength were found to be determined by the substrate surface roughness, which could be controlled by grit-blasting parameters. Optimization of the grit-blasting parameters was conducted using the fitted model to minimize the porosity content of the coating while maintaining a high adhesion strength.
NASA Astrophysics Data System (ADS)
Shamsipour, Majid; Pahlevani, Zahra; Shabani, Mohsen Ostad; Mazahery, Ali
2016-04-01
Understanding of the electromagnetic stirrer (EMS) process parameters-wear relation in nanocomposite is required for further creation of tailored modifications of process in accordance with the demands for various applications. This study depicts the performance of hybrid algorithm for optimization of the parameters in EMS compocasting of nano-TiC-reinforced Al-Si alloys. Adaptive neuro-fuzzy inference system (ANFIS) coupled with particle swarm optimization (PSO) was applied to find the optimum combination of the inputs including mold temperature, mix time, impeller speed, powder temperature, cast temperature and average particle size. The optimized condition was obtained in minimization of objective function. The objective function is calculated by ANFIS and then minimized by PSO. The optimized parameters were used to produce semisolid cast aluminum matrix composites reinforced with nano-TiC particles. The optimized nanocomposites were then studied for their tribological properties.
Methodology for Determining Optimal Exposure Parameters of a Hyperspectral Scanning Sensor
NASA Astrophysics Data System (ADS)
Walczykowski, P.; Siok, K.; Jenerowicz, A.
2016-06-01
The purpose of the presented research was to establish a methodology that would allow the registration of hyperspectral images with a defined spatial resolution on a horizontal plane. The results obtained within this research could then be used to establish the optimum sensor and flight parameters for collecting aerial imagery data using an UAV or other aerial system. The methodology is based on an user-selected optimal camera exposure parameters (i.e. time, gain value) and flight parameters (i.e. altitude, velocity). A push-broom hyperspectral imager- the Headwall MicroHyperspec A-series VNIR was used to conduct this research. The measurement station consisted of the following equipment: a hyperspectral camera MicroHyperspec A-series VNIR, a personal computer with HyperSpec III software, a slider system which guaranteed the stable motion of the sensor system, a white reference panel and a Siemens star, which was used to evaluate the spatial resolution. Hyperspectral images were recorded at different distances between the sensor and the target- from 5m to 100m. During the registration process of each acquired image, many exposure parameters were changed, such as: the aperture value, exposure time and speed of the camera's movement on the slider. Based on all of the registered hyperspectral images, some dependencies between chosen parameters had been developed: - the Ground Sampling Distance - GSD and the distance between the sensor and the target, - the speed of the camera and the distance between the sensor and the target, - the exposure time and the gain value, - the Density Number and the gain value. The developed methodology allowed us to determine the speed and the altitude of an unmanned aerial vehicle on which the sensor would be mounted, ensuring that the registered hyperspectral images have the required spatial resolution.
Optimization of parameters for enhanced oil recovery from enzyme treated wild apricot kernels.
Rajaram, Mahatre R; Kumbhar, Baburao K; Singh, Anupama; Lohani, Umesh Chandra; Shahi, Navin C
2012-08-01
Present investigation was undertaken with the overall objective of optimizing the enzymatic parameters i.e. moisture content during hydrolysis, enzyme concentration, enzyme ratio and incubation period on wild apricot kernel processing for better oil extractability and increased oil recovery. Response surface methodology was adopted in the experimental design. A central composite rotatable design of four variables at five levels was chosen. The parameters and their range for the experiments were moisture content during hydrolysis (20-32%, w.b.), enzyme concentration (12-16% v/w of sample), combination of pectolytic and cellulolytic enzyme i.e. enzyme ratio (30:70-70:30) and incubation period (12-16 h). Aspergillus foetidus and Trichoderma viride was used for production of crude enzyme i.e. pectolytic and cellulolytic enzyme respectively. A complete second order model for increased oil recovery as the function of enzymatic parameters fitted the data well. The best fit model for oil recovery was also developed. The effect of various parameters on increased oil recovery was determined at linear, quadric and interaction level. The increased oil recovery ranged from 0.14 to 2.53%. The corresponding conditions for maximum oil recovery were 23% (w.b.), 15 v/w of the sample, 60:40 (pectolytic:cellulolytic), 13 h. Results of the study indicated that incubation period during enzymatic hydrolysis is the most important factor affecting oil yield followed by enzyme ratio, moisture content and enzyme concentration in the decreasing order. Enzyme ratio, incubation period and moisture content had insignificant effect on oil recovery. Second order model for increased oil recovery as a function of enzymatic hydrolysis parameters predicted the data adequately. PMID:23904657
Huang, Yang; Liu, Guang-Jian; Liao, Bing; Huang, Guang-Liang; Liang, Jin-Yu; Zhou, Lu-Yao; Wang, Fen; Li, Wei; Xie, Xiao-Yan; Wang, Wei; Lu, Ming-De
2015-09-01
The aims of the present study are to assess the impact factors on acoustic structure quantification (ASQ) ultrasound and find the optimal parameter for the assessment of liver fibrosis. Twenty healthy volunteers underwent ASQ examinations to evaluate impact factors in ASQ image acquisition and analysis. An additional 113 patients with liver diseases underwent standardized ASQ examinations, and the results were compared with histologic staging of liver fibrosis. We found that the right liver displayed lower values of ASQ parameters than the left (p = 0.000-0.021). Receive gain experienced no significant impact except gain 70 (p = 0.193-1.000). With regard to different diameter of involved vessels in regions of interest, the group ≤2.0 mm differed significantly with the group 2.1-5.0 mm (p = 0.000-0.033) and the group >5.0 mm (p = 0.000-0.062). However, the region of interest size (p = 0.438-1.000) and depth (p = 0.072-0.764) had no statistical impact. Good intra- and inter-operator reproducibilities were found in both image acquisitions and offline image analyses. In the liver fibrosis study, the focal disturbance ratio had the highest correlation with histologic fibrosis stage (r = 0.67, p < 0.001). In conclusion, the testing position, receive gain and involved vessels were the main factors in ASQ examinations and focal disturbance ratio was the optimal parameter in the assessment of liver fibrosis. PMID:26055966
NASA Astrophysics Data System (ADS)
Quaranta, Giuseppe; Monti, Giorgio; Marano, Giuseppe Carlo
2010-10-01
Many of the proposed approaches for non-linear systems control are developed under the assumption that all involved parameters are known in advance. Unfortunately, their estimation is not so simple because the nature of the non-linear behaviors is very complex in the most part of the cases. In view of this complication, parameters identification of non-linear oscillators has attracted increasing interests in various research fields: from a pure mathematical point-of-view, parameters identification can be formalized as a multi-dimensional optimization problem, typically over real bounded domains. In doing this, the use of the so-called non-classical methods based on soft computing theories seems to be promising because they do not require a priori information and the robustness of the identification against the noise contamination is satisfactory. However, further studies are required to evaluate the general effectiveness of these methodologies. In this sense, the paper addresses the consistency of two classes of soft computing based methods for the identification of Van der Pol-Duffing oscillators. A large numerical investigation has been conducted to evaluate the performances of six differential evolution algorithms (including a modified differential evolution algorithm proposed by the authors) and four swarm intelligence based algorithms (including a chaotic particle swarm optimization algorithm). Single well, double well and double-hump oscillators are identified and noisy system responses are considered in order to evaluate the robustness of the identification processes. The investigated soft computing techniques behave very well and thus they are suitable for practical applications.
NASA Astrophysics Data System (ADS)
Zhu, D. L.; Wang, Q.; Han, S.; Cao, P. J.; Liu, W. J.; Jia, F.; Zeng, Y. X.; Ma, X. C.; Lu, Y. M.
2014-04-01
Ga-doped ZnO (GZO) transparent conductive thin films have been deposited on quartz substrates by r.f. magnetron sputtering. The optimization of four process parameters (i.e., vacuum annealing temperature, r.f. power, sputtering pressure, and Ar flow rate) based on Taguchi method has been systematically studied in order to obtain the minimum resistivity. Compared to the optimal parameter set selected from orthogonal array by Taguchi method, the optimal prediction design can receive an improvement of 22.3% in electrical resistivity, and the corresponding resistivity is 8.08 × 10-4 Ω cm. The analysis of variance shows that vacuum annealing temperature is the most significant influencing parameter on the electrical properties in GZO films. X-ray photoelectron spectroscopy and photoluminescence results exhibit that the enhancement in electrical conductivity after vacuum annealing is ascribed to the variation of the chemical states of oxygen in GZO films. With the increase in annealing temperature, the content of absorbed oxygen and interstitial oxygen as acceptors will decrease.
Influence of deposition parameters on residual stress of YbF3 thin film
NASA Astrophysics Data System (ADS)
Zhang, Yao-ping; Fan, Jun-qi; Long, Guo-yun
2016-01-01
YbF3 was proposed as a substitute for ThF4 in anti-reflection or reflection coatings for the infrared range, and the residual stress of YbF3 thin film using APS plasma ion assisted deposition(PIAD) was studied. From the results, we found the anode voltage of PIAD has a large effect on the residual stress of YbF3 thin film, and the refractive index of YbF3 produced with PIAD was higher than without it, with a possible reason close to packing density. Finally, we produced multi-layer reflection coating on a 260mm diameter mono-crystalline silicon substrate. Its surface contour was approximately 0.240λ (λ＝632.8nm), and the absorption was lower than 200ppm, which can satisfy the practical requirement.
Shapiro, C.S.
1984-08-01
The GLODEP2 computer code was utilized to determine biological impact to humans on a global scale using up-to-date estimates of biological risk. These risk factors use varied biological damage models for assessing effects. All the doses reported are the unsheltered, unweathered, smooth terrain, external gamma dose. We assume the unperturbed atmosphere in determining injection and deposition. Effects due to ''nuclear winter'' may invalidate this assumption. The calculations also include scenarios that attempt to assess the impact of the changing nature of the nuclear stockpile. In particular, the shift from larger to smaller yield nuclear devices significantly changes the injection pattern into the atmosphere, and hence significantly affects the radiation doses that ensue. We have also looked at injections into the equatorial atmosphere. In total, we report here the results for 8 scenarios. 10 refs., 6 figs., 11 tabs.
Zhang, Yu-xin; Cheng, Zhi-feng; Xu, Zheng-ping; Bai, Jing
2015-01-01
In order to solve the problems such as complex operation, consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis (DGA), this paper proposes a new method which is detecting 5 types of characteristic gas content in transformer oil such as CH4, C2H2, C2H4, C2H6 and H2 based on photoacoustic Spectroscopy and C2H2/C2H4, CH4/H2, C2H4/C2H6 three-ratios data are calculated. The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g, which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed. Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization. The simulation result shows that SVM model composed of C-SVC, RBF kernel functions and genetic algorithm obtain 97. 5% accuracy in test sample set and 98. 333 3% accuracy in train sample set, and genetic algorithm was about two times faster than particles swarm optimization in computing speed. The methods described in this paper has many advantages such as simple operation, non-contact measurement, no consumption for the carrier gas, long test period, high stability and sensitivity, the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis.
Optimization of accelerator parameters using normal form methods on high-order transfer maps
Snopok, Pavel
2007-05-01
in a way that is easy to understand, such important characteristics as the strengths of the resonances and the tune shifts with amplitude and various parameters of the system are calculated. Each major section is supplied with the results of applying various numerical optimization methods to the problems stated. The emphasis is made on the efficiency comparison of various approaches and methods. The main simulation tool is the arbitrary order code COSY INFINITY written by M. Berz, K. Makino, et al. at Michigan State University. Also, the code MAD is utilized to design the 750 x 750 GeV Muon Collider storage ring baseline lattice.
Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization.
Yu, Jing; Li, Yaan
2016-01-01
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target's velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms. PMID:27376294
Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization
Yu, Jing; Li, Yaan
2016-01-01
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target’s velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms. PMID:27376294
Optimization of Stunning Electrical Parameters to Improve Animal Welfare in a Poultry Slaughterhouse
Chirollo, Claudia; Ceruso, Marina; Vollano, Lucia; Chianese, Antonio; Cortesi, Maria Luisa
2015-01-01
Animal killing for food production and the related operations are events that may induce pain, stress, fear and other forms of suffering to the animals. To face this problem and guarantee the animal welfare, the EU has adopted the Regulation (EC) N. 1099/2009 on the protection of animals at the time of killing. Electrical water bath stunning is one of the methods used in commercial slaughterhouses to protect poultry welfare. In particular, this method induces unconsciousness into the birds due to run of electrical current through the head and body. The aim of the present work was to find an optimal setting of electrical parameters to obtain an effective water bath stunning in a commercial poultry slaughterhouse. Moreover, the influence of the tested electrical parameters on meat quality was evaluated. All the experiments confirmed that high stunning frequencies induce a lower occurrence of lesions on carcasses but, on the other hand, require greater current intensities to be effective. A frequency of 750 Hz and an average current intensity of 200 mA for each bird in the water bath resulted as the best combination of electrical parameters to obtain a proper stunning without any consequence on the meat quality. PMID:27800406
Ghacham, Alia Ben; Pasquier, Louis-César; Cecchi, Emmanuelle; Blais, Jean-François; Mercier, Guy
2016-09-01
This work focuses on the influence of different parameters on the efficiency of steel slag carbonation in slurry phase under ambient temperature. In the first part, a response surface methodology was used to identify the effect and the interactions of the gas pressure, liquid/solid (L/S) ratio, gas/liquid ratio (G/L), and reaction time on the CO2 removed/sample and to optimize the parameters. In the second part, the parameters' effect on the dissolution of CO2 and its conversion into carbonates were studied more in detail. The results show that the pressure and the G/L ratio have a positive effect on both the dissolution and the conversion of CO2. These results have been correlated with the higher CO2 mass introduced in the reactor. On the other hand, an important effect of the L/S ratio on the overall CO2 removal and more specifically on the carbonate precipitation has been identified. The best results were obtained L/S ratios of 4:1 and 10:1 with respectively 0.046 and 0.052 gCO2 carbonated/g sample. These yields were achieved after 10 min reaction, at ambient temperature, and 10.68 bar of total gas pressure following direct gas treatment.
Ghacham, Alia Ben; Pasquier, Louis-César; Cecchi, Emmanuelle; Blais, Jean-François; Mercier, Guy
2016-09-01
This work focuses on the influence of different parameters on the efficiency of steel slag carbonation in slurry phase under ambient temperature. In the first part, a response surface methodology was used to identify the effect and the interactions of the gas pressure, liquid/solid (L/S) ratio, gas/liquid ratio (G/L), and reaction time on the CO2 removed/sample and to optimize the parameters. In the second part, the parameters' effect on the dissolution of CO2 and its conversion into carbonates were studied more in detail. The results show that the pressure and the G/L ratio have a positive effect on both the dissolution and the conversion of CO2. These results have been correlated with the higher CO2 mass introduced in the reactor. On the other hand, an important effect of the L/S ratio on the overall CO2 removal and more specifically on the carbonate precipitation has been identified. The best results were obtained L/S ratios of 4:1 and 10:1 with respectively 0.046 and 0.052 gCO2 carbonated/g sample. These yields were achieved after 10 min reaction, at ambient temperature, and 10.68 bar of total gas pressure following direct gas treatment. PMID:27236443
Anode power deposition in a MPD thruster with a magnetically annulled Hall parameter anode
NASA Technical Reports Server (NTRS)
Gallimore, Alec D.; Kelly, Arnold J.; Jahn, Robert G.
1992-01-01
Results from previous studies indicate that the anode fall increases monotonically with the electron Hall parameter. In an attempt to reduce the anode fall by decreasing the local electron Hall parameter, a proof-of-concept test was performed in which an array of 36 permanent magnets were imbedded within the anode of a high power quasi-steady MPD thruster to decrease the local azimuthal component of the induced magnetic field. The modified thruster was operated at power levels between 150 kW and 4 MW with Ar and He propellants. Terminal voltage, triple probe, floating probe, and magnetic probe measurements were made to characterize the performance of the thruster with new anode. Incorporation of the modified anode resulted in a reduction of the anode fall by up to 15 V with Ar and 20 V with He, which corresponded to decreased anode power fractions of 40 and 45 percent with Ar and He, respectively.
NASA Astrophysics Data System (ADS)
Siddiqui, Jamil; Hussain, Tousif; Ahmad, Riaz; Khalid, Nida
2015-06-01
Effects of deposition angle and axial distance on the structural and mechanical properties of niobium nitride synthesized by a dense plasma focus (DPF) system are studied. The x-ray diffraction (XRD) confirms that the deposition parameters affect the growth of multi-phase niobium nitride. Scanning electron microscopy (SEM) shows the granular surface morphology with strong thermally assisted coagulation effects observed at the 5-cm axial distance. The non-porous granular morphology observed at the 9-cm distance along the anode axis is different from those observed at deposition angles of 10° and 20°. Energy dispersive x-ray (EDX) spectroscopy reveals the maximum nitrogen content at the shortest (5 cm) axial position. Atomic force microscopy (AFM) exhibits that the roughness of coated films varies for coatings synthesized at different axial and angular positions, and the Vickers micro-hardness test shows that a maximum hardness value is (08.44 ± 0.01) GPa for niobium nitride synthesized at 5-cm axial distance, which is about 500% more than that of a virgin sample. Project supported by the HEC, Pakistan.
NASA Astrophysics Data System (ADS)
Haghmoradi, Navid; Dehghanian, Changiz; Yari, Saeed
2016-07-01
The present work explores how deposition parameters affect structural and morphological characteristics of ZnNi/nano-SiC composites in order to engineer an environmentally benign corrosion-resistant coating. In this regard, ZnNi and ZnNi coatings containing SiC nanoparticles were electrodeposited from chloride bath by direct current method, and the effects of SiC concentration, deposition current density and two types of surfactant (sodium dodecyl sulfate, SDS, and hexadecyltrimethyl ammonium bromide, HTAB) were investigated. Increasing SiC nanoparticles concentration in the electrolyte enhances the SiC content of the coating and can affect the coating composition, structure and morphology. Elevation of deposition current density may reduce SiC content of the coating, yet this decline can be compensated by the addition of HTAB. Application of 11 g/L SiC nanoparticles produced a coating with a more even surface and less porosity that had the highest corrosion resistance. The presence of nanoparticles seemingly reduces the available surface for electrochemical reactions and decelerates corrosion.
NASA Astrophysics Data System (ADS)
Haghmoradi, Navid; Dehghanian, Changiz; Yari, Saeed
2016-09-01
The present work explores how deposition parameters affect structural and morphological characteristics of ZnNi/nano-SiC composites in order to engineer an environmentally benign corrosion-resistant coating. In this regard, ZnNi and ZnNi coatings containing SiC nanoparticles were electrodeposited from chloride bath by direct current method, and the effects of SiC concentration, deposition current density and two types of surfactant (sodium dodecyl sulfate, SDS, and hexadecyltrimethyl ammonium bromide, HTAB) were investigated. Increasing SiC nanoparticles concentration in the electrolyte enhances the SiC content of the coating and can affect the coating composition, structure and morphology. Elevation of deposition current density may reduce SiC content of the coating, yet this decline can be compensated by the addition of HTAB. Application of 11 g/L SiC nanoparticles produced a coating with a more even surface and less porosity that had the highest corrosion resistance. The presence of nanoparticles seemingly reduces the available surface for electrochemical reactions and decelerates corrosion.
NASA Astrophysics Data System (ADS)
Miyauchi, T.; Machimura, T.
2013-12-01
In the simulation using an ecosystem process model, the adjustment of parameters is indispensable for improving the accuracy of prediction. This procedure, however, requires much time and effort for approaching the simulation results to the measurements on models consisting of various ecosystem processes. In this study, we tried to apply a general purpose optimization tool in the parameter optimization of an ecosystem model, and examined its validity by comparing the simulated and measured biomass growth of a woody plantation. A biometric survey of tree biomass growth was performed in 2009 in an 11-year old Eucommia ulmoides plantation in Henan Province, China. Climate of the site was dry temperate. Leaf, above- and below-ground woody biomass were measured from three cut trees and converted into carbon mass per area by measured carbon contents and stem density. Yearly woody biomass growth of the plantation was calculated according to allometric relationships determined by tree ring analysis of seven cut trees. We used Biome-BGC (Thornton, 2002) to reproduce biomass growth of the plantation. Air temperature and humidity from 1981 to 2010 was used as input climate condition. The plant functional type was deciduous broadleaf, and non-optimizing parameters were left default. 11-year long normal simulations were performed following a spin-up run. In order to select optimizing parameters, we analyzed the sensitivity of leaf, above- and below-ground woody biomass to eco-physiological parameters. Following the selection, optimization of parameters was performed by using the Dakota optimizer. Dakota is an optimizer developed by Sandia National Laboratories for providing a systematic and rapid means to obtain optimal designs using simulation based models. As the object function, we calculated the sum of relative errors between simulated and measured leaf, above- and below-ground woody carbon at each of eleven years. In an alternative run, errors at the last year (at the
Tachiev, F.; Yaari, G.; Foster, N.; Blaine, B.
2007-07-01
fresh water. The effects of hydrodynamic dispersion variations were analyzed to predict the uncertainty of the volumes that must be added and pumped for the concentration of cesium to drop below the limits required by the Demonstration Bulk Vitrification System (DBVS) facility. These parameters were used to determine the most optimal drainage scenarios, which are driven by minimization of the Double Shell Tank (DST) space needed. (authors)
Multisource modeling of flattening filter free (FFF) beam and the optimization of model parameters
Cho, Woong; Kielar, Kayla N.; Mok, Ed; Xing Lei; Park, Jeong-Hoon; Jung, Won-Gyun; Suh, Tae-Suk
2011-04-15
Purpose: With the introduction of flattening filter free (FFF) linear accelerators to radiation oncology, new analytical source models for a FFF beam applicable to current treatment planning systems is needed. In this work, a multisource model for the FFF beam and the optimization of involved model parameters were designed. Methods: The model is based on a previous three source model proposed by Yang et al. [''A three-source model for the calculation of head scatter factors,'' Med. Phys. 29, 2024-2033 (2002)]. An off axis ratio (OAR) of photon fluence was introduced to the primary source term to generate cone shaped profiles. The parameters of the source model were determined from measured head scatter factors using a line search optimization technique. The OAR of the photon fluence was determined from a measured dose profile of a 40x40 cm{sup 2} field size with the same optimization technique, but a new method to acquire gradient terms for OARs was developed to enhance the speed of the optimization process. The improved model was validated with measured dose profiles from 3x3 to 40x40 cm{sup 2} field sizes at 6 and 10 MV from a TrueBeam STx linear accelerator. Furthermore, planar dose distributions for clinically used radiation fields were also calculated and compared to measurements using a 2D array detector using the gamma index method. Results: All dose values for the calculated profiles agreed with the measured dose profiles within 0.5% at 6 and 10 MV beams, except for some low dose regions for larger field sizes. A slight overestimation was seen in the lower penumbra region near the field edge for the large field sizes by 1%-4%. The planar dose calculations showed comparable passing rates (>98%) when the criterion of the gamma index method was selected to be 3%/3 mm. Conclusions: The developed source model showed good agreements between measured and calculated dose distributions. The model is easily applicable to any other linear accelerator using FFF beams
NASA Astrophysics Data System (ADS)
Espinoza, Néstor; Jordán, Andrés
2016-04-01
Very precise measurements of exoplanet transit light curves both from ground- and space-based observatories make it now possible to fit the limb-darkening coefficients in the transit-fitting procedure rather than fix them to theoretical values. This strategy has been shown to give better results, as fixing the coefficients to theoretical values can give rise to important systematic errors which directly impact the physical properties of the system derived from such light curves such as the planetary radius. However, studies of the effect of limb-darkening assumptions on the retrieved parameters have mostly focused on the widely used quadratic limb-darkening law, leaving out other proposed laws that are either simpler or better descriptions of model intensity profiles. In this work, we show that laws such as the logarithmic, square-root and three-parameter law do a better job that the quadratic and linear laws when deriving parameters from transit light curves, both in terms of bias and precision, for a wide range of situations. We therefore recommend to study which law to use on a case-by-case basis. We provide code to guide the decision of when to use each of these laws and select the optimal one in a mean-square error sense, which we note has a dependence on both stellar and transit parameters. Finally, we demonstrate that the so-called exponential law is non-physical as it typically produces negative intensities close to the limb and should therefore not be used.
Cotter, Meghan M.; Whyms, Brian J.; Kelly, Michael P.; Doherty, Benjamin M.; Gentry, Lindell R.; Bersu, Edward T.; Vorperian, Houri K.
2015-01-01
The hyoid bone anchors and supports the vocal tract. Its complex shape is best studied in three dimensions, but it is difficult to capture on computed tomography (CT) images and three-dimensional volume renderings. The goal of this study was to determine the optimal CT scanning and rendering parameters to accurately measure the growth and developmental anatomy of the hyoid and to determine whether it is feasible and necessary to use these parameters in the measurement of hyoids from in vivo CT scans. Direct linear and volumetric measurements of skeletonized hyoid bone specimens were compared to corresponding CT images to determine the most accurate scanning parameters and three-dimensional rendering techniques. A pilot study was undertaken using in vivo scans from a retrospective CT database to determine feasibility of quantifying hyoid growth. Scanning parameters and rendering technique affected accuracy of measurements. Most linear CT measurements were within 10% of direct measurements; however, volume was overestimated when CT scans were acquired with a slice thickness greater than 1.25 mm. Slice-by-slice thresholding of hyoid images decreased volume overestimation. The pilot study revealed that the linear measurements tested correlate with age. A fine-tuned rendering approach applied to small slice thickness CT scans produces the most accurate measurements of hyoid bones. However, linear measurements can be accurately assessed from in vivo CT scans at a larger slice thickness. Such findings imply that investigation into the growth and development of the hyoid bone, and the vocal tract as a whole, can now be performed using these techniques. PMID:25810349
NASA Astrophysics Data System (ADS)
Krenn, Julia; Mergili, Martin
2016-04-01
r.randomwalk is a GIS-based, multi-functional conceptual tool for mass movement routing. Starting from one to many release points or release areas, mass points are routed down through the digital elevation model until a defined break criterion is reached. Break criteria are defined by the user and may consist in an angle of reach or a related parameter (empirical-statistical relationships), in the drop of the flow velocity to zero (two-parameter friction model), or in the exceedance of a maximum runup height. Multiple break criteria may be combined. A constrained random walk approach is applied for the routing procedure, where the slope and the perpetuation of the flow direction determine the probability of the flow to move in a certain direction. r.randomwalk is implemented as a raster module of the GRASS GIS software and, as such, is open source. It can be obtained from http://www.mergili.at/randomwalk.html. Besides other innovative functionalities, r.randomwalk serves with built-in functionalities for the derivation of an impact indicator index (III) map with values in the range 0-1. III is derived from multiple model runs with different combinations of input parameters varied in a random or controlled way. It represents the fraction of model runs predicting an impact at a given pixel and is evaluated against the observed impact area through an ROC Plot. The related tool r.ranger facilitates the automated generation and evaluation of many III maps from a variety of sets of parameter combinations. We employ r.randomwalk and r.ranger for parameter optimization and sensitivity analysis. Thereby we do not focus on parameter values, but - accounting for the uncertainty inherent in all parameters - on parameter ranges. In this sense, we demonstrate two strategies for parameter sensitivity analysis and optimization. We avoid to (i) use one-at-a-time parameter testing which would fail to account for interdependencies of the parameters, and (ii) to explore all possible
Liu, Huasong; Jiang, Yugang; Wang, Lishuan; Leng, Jian; Sun, Peng; Zhuang, Kewen; Ji, Yiqin; Cheng, Xinbin; Jiao, Hongfei; Wang, Zhanshan; Wu, Bingjun
2014-02-01
Ion beam sputtering is one of the most important technologies for preparing hafnium dioxide thin films. In this paper, the correlation between properties of hafnium dioxide thin films and preparing parameters was systematically researched by using the orthogonal experiment design method. The properties of hafnium oxide films (refractive index, extinction coefficient, deposition rate, stress, and inhomogeneity of refractive index) were studied. The refractive index, extinction coefficient, physical thickness, and inhomogeneity of refractive index were obtained by the multiple wavelength curve-fitting method from the reflectance and transmittance of single layers. The stress of thin film was measured by elastic deformation of the thin film-substrate system. An orthogonal experimental strategy was designed using substrate temperature, ion beam voltage, ion beam current, and oxygen flow rate as the variables. The experimental results indicated that the temperature of the substrate is the key influencing parameter on the properties of hafnium oxide films, while other preparing parameters are also correlated with specific properties. The experimental results are significant for selecting proper parameters for preparing hafnium oxide films with different applications.
Bendall; Skinner
1998-10-01
To provide the most efficient conditions for spin decoupling with least RF power, master calibration curves are provided for the maximum centerband amplitude, and the minimum amplitude for the largest cycling sideband, resulting from STUD+ adiabatic decoupling applied during a single free induction decay. The principal curve is defined as a function of the four most critical experimental input parameters: the maximum amplitude of the RF field, RFmax, the length of the sech/tanh pulse, Tp, the extent of the frequency sweep, bwdth, and the coupling constant, Jo. Less critical parameters, the effective (or actual) decoupled bandwidth, bweff, and the sech/tanh truncation factor, beta, which become more important as bwdth is decreased, are calibrated in separate curves. The relative importance of nine additional factors in determining optimal decoupling performance in a single transient are considered. Specific parameters for efficient adiabatic decoupling can be determined via a set of four equations which will be most useful for 13C decoupling, covering the range of one-bond 13C1H coupling constants from 125 to 225 Hz, and decoupled bandwidths of 7 to 100 kHz, with a bandwidth of 100 kHz being the requirement for a 2 GHz spectrometer. The four equations are derived from a recent vector model of adiabatic decoupling, and experiment, supported by computer simulations. The vector model predicts an inverse linear relation between the centerband and maximum sideband amplitudes, and it predicts a simple parabolic relationship between maximum sideband amplitude and the product JoTp. The ratio bwdth/(RFmax)2 can be viewed as a characteristic time scale, tauc, affecting sideband levels, with tauc approximately Tp giving the most efficient STUD+ decoupling, as suggested by the adiabatic condition. Functional relationships between bwdth and less critical parameters, bweff and beta, for efficient decoupling can be derived from Bloch-equation calculations of the inversion profile
Panigrahi, Swapnesh; Fade, Julien; Ramachandran, Hema; Alouini, Mehdi
2016-07-11
The efficiency of using intensity modulated light for the estimation of scattering properties of a turbid medium and for ballistic photon discrimination is theoretically quantified in this article. Using the diffusion model for modulated photon transport and considering a noisy quadrature demodulation scheme, the minimum-variance bounds on estimation of parameters of interest are analytically derived and analyzed. The existence of a variance-minimizing optimal modulation frequency is shown and its evolution with the properties of the intervening medium is derived and studied. Furthermore, a metric is defined to quantify the efficiency of ballistic photon filtering which may be sought when imaging through turbid media. The analytical derivation of this metric shows that the minimum modulation frequency required to attain significant ballistic discrimination depends only on the reduced scattering coefficient of the medium in a linear fashion for a highly scattering medium.
Elements of an algorithm for optimizing a parameter-structural neural network
NASA Astrophysics Data System (ADS)
Mrówczyńska, Maria
2016-06-01
The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH), which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.
Samavati, Vahid; D-jomeh, Zahra Emam
2013-11-01
Optimization for retention and partition coefficient of ethyl acetate in emulsion model systems was investigated using response surface methodology in this paper. The effects of emulsion model ingredients, tragacanth gum (TG) (0.5-1 wt%), whey protein isolate (WPI) (2-4 wt%) and oleic acid (5-10%, v/v) on retention and partition coefficient of ethyl acetate were studied using a five-level three-factor central composite rotatable design (CCRD). Results showed that the regression models generated adequately explained the data variation and significantly represented the actual relationships between the independent and response parameters. The results showed that the highest retention (97.20±0.51%) and lowest partition coefficient (4.51±0.13%) of ethyl acetate were reached at the TG concentration 1 wt%, WPI concentration 4 wt% and oleic acid volume fraction 10% (v/v).
Measurements of alpha-gamma coincidences with an optimized dual-parameter multichannel system.
Jurado Vargas, M; Caro Marroyo, B; Martín Sánchez, A
2013-12-01
Measurements of alpha-gamma coincidences have usually been carried out using a single channel to detect alpha-particles of a given energy, and a multichannel analyser for the detection of the corresponding coincident gamma-rays. An alpha-gamma coincidence chamber coupled to the electronic chain ending with a dual-parameter multichannel analyser has been developed and optimized. This system simultaneously stores alpha-particle, gamma-ray, and alpha-gamma coincidence spectra, which allows a general analysis to be made of the degree of coincidence between each alpha-particle and each gamma-ray emission. With this technique, a two-dimensional spectrum was obtained and analysed using "contour graphics". An application to the study of the decay scheme of (241)Am is described. PMID:24140879
Calculation of optimal parameters of an NH{sub 3}-CO{sub 2} lidar
Vasil'ev, B I; Mannoun, Oussama
2005-06-30
The basic parameters (range, signal-to-noise ratio, and sensitivity) of a lidar using NH{sub 3} and CO{sub 2} lasers are calculated. The principle of lidar operation is based on the differential absorption recording. Absorption spectra of all known Freons are considered in the spectral range 9-13.5 {mu}m and optimal wavelengths suitable for sensing them are determined. It is shown that the NH{sub 3}-CO{sub 2} lidar can sense Freons at distances up to 10 km at a signal-to-noise ratio exceeding 10. Sensitivities of the lidar for sensing Freon-11 using various lines of the ammonia laser are calculated. It is shown that remote sensing of Freon-11 at concentrations of the order of 5x10{sup -6}% is possible at distances up to 8.5 km. (laser applications and other topics in quantum electronics)
NASA Astrophysics Data System (ADS)
Korkut, Zeynep D.; Tabakoglu, Haşim Ö.; Bozkulak, Özgüncem; Aksel, Ayla A.; Gulsoy, Murat
2006-02-01
In this study, tissue welding with 980-nm laser system, which is first-time in the literature, was performed. Hence, a preliminary study was done to determine optimal parameters for further studies. 1 cm long incisions done on the Wistar rat's dorsal skin were welded. Tissue welding with 980-nm wavelength depends on the degree of photothermal interaction. Thus, different power levels and exposure schedule were investigated. Dorsal sides of all animals were photographed from the date of surgery until they were sacrificed. The clinical examination - opening of wound and presence of infection - was noted. The rats did not show any abnormality on their health, behavior and nutrition manner. As a result, 980-nm diode laser was concluded to be a good candidate for tissue welding applications.
2014-01-01
Background In the recent study, optimum operational conditions of cathode compartment of microbial fuel cell were determined by using Response Surface Methodology (RSM) with a central composite design to maximize power density and COD removal. Methods The interactive effects of parameters such as, pH, buffer concentration and ionic strength on power density and COD removal were evaluated in two-chamber microbial batch-mode fuel cell. Results Power density and COD removal for optimal conditions (pH of 6.75, buffer concentration of 0.177 M and ionic strength of cathode chamber of 4.69 mM) improve by 17 and 5%, respectively, in comparison with normal conditions (pH of 7, buffer concentration of 0.1 M and ionic strength of 2.5 mM). Conclusions In conclusion, results verify that response surface methodology could successfully determine cathode chamber optimum operational conditions. PMID:24423039
NASA Astrophysics Data System (ADS)
Flores, Jorge L.; García-Torales, G.; Ponce Ávila, Cristina
2006-08-01
This paper describes an in situ image recognition system designed to inspect the quality standards of the chocolate pops during their production. The essence of the recognition system is the localization of the events (i.e., defects) in the input images that affect the quality standards of pops. To this end, processing modules, based on correlation filter, and segmentation of images are employed with the objective of measuring the quality standards. Therefore, we designed the correlation filter and defined a set of features from the correlation plane. The desired values for these parameters are obtained by exploiting information about objects to be rejected in order to find the optimal discrimination capability of the system. Regarding this set of features, the pop can be correctly classified. The efficacy of the system has been tested thoroughly under laboratory conditions using at least 50 images, containing 3 different types of possible defects.
Estimation and Optimization of the Parameters Preserving the Lustre of the Fabrics
NASA Astrophysics Data System (ADS)
Prodanova, Krasimira
2009-11-01
The paper discusses the optimization of the continuance of the Damp-Heating Process of a steaming iron press machine, and the preserving of the lustre of the fabrics. In order to be obtained high qualitative damp-heating processing, it is necessary to monitor parameters such as temperature, damp, and pressure during the process. The purpose of the present paper is a mathematical model to be constructed that adequately describes the technological process using multivariate data analysis. It was established that the full factorial design of type 23 is not adequate. The research has proceeded with central rotatable design of experiment. The obtained model adequately describes the technological process of damp-heating treatment in the defined factor space. The present investigation is helpful to the technological improvement and modernization in sewing companies.
NASA Astrophysics Data System (ADS)
Choi, Seungyeon; Choi, Sunghoon; Kim, Ye-seul; Lee, Haenghwa; Lee, Donghoon; Jeon, Pil-Hyun; Jang, Dong-Hyuk; Kim, Hee-Joung
2016-03-01
Digital tomosynthesis system (DTS), which scans an object in a limited angle, has been considered as an innovative imaging modality which can present lower patient dose than computed tomography and solve the problem of poor depth resolution in conventional digital radiography. Although it has many powerful advantages, only breast tomosynthesis system has been adopted in many hospitals. In order to reduce the patient dose while maintaining image quality, the acquisition conditions need to be studied. In this study, we analyzed effective dose and image qualities of chest phantom using commercialized universal chest digital tomosynthesis (CDT) R/F system to study the optimized exposure parameters. We set 10 different acquisition conditions including the default acquisition condition by user manual of Shimadzu (100 kVp with 0.5 mAs). The effective dose was calculated from PCXMC software version 1.5.1 by utilizing the total X-ray exposure measured by ion chamber. The image quality was evaluated by signal difference to noise ratio (SDNR) in the regions of interest (ROIs) pulmonary arteries at different axial in-plane. We analyzed a figure of merit (FOM) which considers both the effective dose and the SDNR in order to determine the optimal acquisition condition. The results indicated that the most suitable acquisition parameters among 10 conditions were condition 7 and 8 (120 kVp with 0.04 mAs and 0.1 mAs, respectively), which indicated lower effective dose while maintaining reasonable SDNRs and FOMs for three specified regions. Further studies are needed to be conducted for detailed outcomes in CDT acquisition conditions.
Stimulation parameter optimization for FES supported standing up and walking in SCI patients.
Bijak, Manfred; Rakos, Monika; Hofer, Christian; Mayr, Winfried; Strohhofer, Maria; Raschka, Doris; Kern, Helmut
2005-03-01
Functional Electrical Stimulation (FES) to restore leg movement for standing up and walking (stepping) in SCI patients with intact lower motor neuron is used by several groups. Usually quadriceps muscles are stimulated for hip and knee extension, gluteus muscles for hip stabilization, and the common peroneal nerve to elicit the flexion reflex. The requirement to get a natural movement would need a huge number of stimulation channels--a request that could be easily fulfillled from the engineer's point of view but not from the point of practicability since each stimulated muscle requires two skin-attached electrodes resulting in a prolonged time for donning and doffing. In the described project a newly developed eight channel stimulator that can vary the stimulation parameters in many ways and over a wide range is used. The goal is to achieve a natural movement with a minimum of surface electrodes by optimizing the stimulation parameters. Seven experienced FES users and five unexperienced persons (all between Th4-Th11) participate in this study. Standing up can be significantly improved by optimizing the time delay between the onset of quadriceps and gluteus muscles (0.2-0.4 s) and the duration of the ramp. A 0.2 s delay gives good results in heavy patients while slower ramps (0.4 s) are required in slim patients. During stepping, gluteus muscle timing is not very crucial. Gluteus stimulation is turned off 0.1-0.2 s before quadriceps muscle and with the same delay turned on again. Of major influence on the gait quality is the timing during heel strike when peroneal stimulation is switched off and quadriceps stimulation is turned on. Six patients require 0.0-0.1 s where neither peroneal nor quadriceps stimulation is applied, the others require an overlap of 0.1-0.2 s. Activation of adductor muscles during standing up and during the swing phase helps to avoid hip abduction and improves knee trajectories.
Singh, G; Kumar, A; Kumbhar, B K; Dar, B N
2015-02-01
Increasing demand of low calorie and high fibre containing products give impetus to dairy industry for development of a well palatable low calorie dairy products like paneer. The objective of the present study was to develop low-fat fibre-supplemented paneer. The ingredients were chosen for low-fat fibre- supplemented paneer to reduce the cost and calorie content besides providing the functional benefits. Optimization of ingredients was carried out in terms of independent variables viz wheat bran (0.4-0.8 %), maltodextrin (1-5 %), coagulation temperature (60-80 °C) and amount of citric acid solution (150-210 ml). Response Surface Methodology (RSM) was used to design the experiments and to select the optimum levels of ingredients. Paneer was made by using different levels of ingredients by coagulating hot milk using citric acid solution followed by pressing and dipping in chilled water for texturization. These parameters were evaluated in terms of physico-chemical parameters viz water activity, pH and acidity. Instrumental texture profile analysis (TPA) of paneer during optimization trials was done using TAXT 2i Texture Analyzer. The textural responses namely hardness, adhesiveness, springiness, cohesiveness, gumminess and chewiness were measured via Texture Analyzer. The sensory properties namely flavor, appearance, body and texture, mouth feel and overall acceptability of paneer samples were evaluated by a semi-trained panel of judges using 9-point hedonic scale. Full second order polynomial was developed to predict each response. All the textural and sensory responses were statistically analysed.
On the optimal use of fictitious time in variation of parameters methods with application to BG14
NASA Technical Reports Server (NTRS)
Gottlieb, Robert G.
1991-01-01
The optimal way to use fictitious time in variation of parameter methods is presented. Setting fictitious time to zero at the end of each step is shown to cure the instability associated with some types of problems. Only some parameters are reinitialized, thereby retaining redundant information.
NASA Technical Reports Server (NTRS)
Noffke, Nora; Knoll, Andrew H.
2001-01-01
Shallow-marine, siliciclastic depositional systems are governed by physical sedimentary processes. Mineral precipitation or penecontemporaneous cementation play minor roles. Today, coastal siliciclastic environments may be colonized by a variety of epibenthic, mat-forming cyanobacteria. Studies on microbial mats showed that they are not randomly distributed in modern tidal environments. Distribution and abundancy is mainly function of a particular sedimentary facies. Fine-grained sands composed of "clear" (translucent) quartz particles constitute preferred substrates for cyanobacteria. Mat-builders also favor sites characterized by moderate hydrodynamic flow regimes, which permit biomass enrichment and construction of mat fabrics without lethal burial of mat populations by fine sediments. A comparable facies relationship can be observed in ancient siliciclastic shelf successions from the terminal Neoproterozoic Nama Group, Namibia. Wrinkle structures that record microbial mats are present but sparsely distributed in mid- to inner shelf sandstones of the Nudaus Formation. The sporadic distribution of these structures reflects both the narrow ecological window that governs mat development and the distinctive taphonomic conditions needed to preserve the structures. These observations caution that statements about changing mat abundance across the Proterozoic-Cambrian boundary must be firmly rooted in paleoenvironmental and taphonomic analysis. Understanding the factors that influence the formation and preservation of microbial structures in siliciclastic regimes can facilitate exploration for biological signatures in Earth's oldest rocks. Moreover, insofar as these structures can be preserved on bedding surfaces and are not easily mimicked by physical processes, they constitute a set of biological markers that can be searched for on Mars by remotely controlled rovers.
NASA Astrophysics Data System (ADS)
Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen
2016-07-01
Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.
Singh, Gurmeet; Jain, Vivek; Gupta, Dheeraj; Ghai, Aman
2016-09-01
Orthopaedic surgery involves drilling of bones to get them fixed at their original position. The drilling process used in orthopaedic surgery is most likely to the mechanical drilling process and there is all likelihood that it may harm the already damaged bone, the surrounding bone tissue and nerves, and the peril is not limited at that. It is very much feared that the recovery of that part may be impeded so that it may not be able to sustain life long. To achieve sustainable orthopaedic surgery, a surgeon must try to control the drilling damage at the time of bone drilling. The area around the holes decides the life of bone joint and so, the contiguous area of drilled hole must be intact and retain its properties even after drilling. This study mainly focuses on optimization of drilling parameters like rotational speed, feed rate and the type of tool at three levels each used by Taguchi optimization for surface roughness and material removal rate. The confirmation experiments were also carried out and results found with the confidence interval. Scanning electrode microscopy (SEM) images assisted in getting the micro level information of bone damage.
NASA Astrophysics Data System (ADS)
Mozdgir, A.; Mahdavi, Iraj; Seyyedi, I.; Shiraqei, M. E.
2011-06-01
An assembly line is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The assembly line balancing problem arises and has to be solved when an assembly line has to be configured or redesigned. The so-called simple assembly line balancing problem (SALBP), a basic version of the general problem, has attracted attention of researchers and practitioners of operations research for almost half a century. There are four types of objective functions which are considered to this kind of problem. The versions of SALBP may be complemented by a secondary objective which consists of smoothing station loads. Many heuristics have been proposed for the assembly line balancing problem due to its computational complexity and difficulty in identifying an optimal solution and so many heuristic solutions are supposed to solve this problem. In this paper a differential evolution algorithm is developed to minimize workload smoothness index in SALBP-2 and the algorithm parameters are optimized using Taguchi method.
Li, Xingyuan; He, Zhili; Zhou, Jizhong
2005-10-30
The oligonucleotide specificity for microarray hybridizationcan be predicted by its sequence identity to non-targets, continuousstretch to non-targets, and/or binding free energy to non-targets. Mostcurrently available programs only use one or two of these criteria, whichmay choose 'false' specific oligonucleotides or miss 'true' optimalprobes in a considerable proportion. We have developed a software tool,called CommOligo using new algorithms and all three criteria forselection of optimal oligonucleotide probes. A series of filters,including sequence identity, free energy, continuous stretch, GC content,self-annealing, distance to the 3'-untranslated region (3'-UTR) andmelting temperature (Tm), are used to check each possibleoligonucleotide. A sequence identity is calculated based on gapped globalalignments. A traversal algorithm is used to generate alignments for freeenergy calculation. The optimal Tm interval is determined based on probecandidates that have passed all other filters. Final probes are pickedusing a combination of user-configurable piece-wise linear functions andan iterative process. The thresholds for identity, stretch and freeenergy filters are automatically determined from experimental data by anaccessory software tool, CommOligo_PE (CommOligo Parameter Estimator).The program was used to design probes for both whole-genome and highlyhomologous sequence data. CommOligo and CommOligo_PE are freely availableto academic users upon request.
Automatic Parameter Tuning for the Morpheus Vehicle Using Particle Swarm Optimization
NASA Technical Reports Server (NTRS)
Birge, B.
2013-01-01
A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.
Optimization of important early ADME(T) parameters of NADPH oxidase-4 inhibitor molecules.
Borbély, Gábor; Huszár, Ménika; Varga, Attila; Futosi, Krisztina; Mócsai, Attila; Orfi, László; Idei, Miklós; Mandl, József; Kéri, György; Vántus, Tibor
2012-03-01
Through their reactive oxygen species (ROS) producing function, NADPH oxidase (NOX) enzymes have been linked to several oxidative stress related diseases. In our recently published paper [1] we have already shown the NOX4 inhibitory effect of diverse, molecule sub-libraries and their biological importance. We also presented our work connected to potential anti-tumour molecules and the relationship between their biological activity and physico-chemical properties [2]. As an extension of these studies further physico-chemical and biological investigation has been carried out on a molecule group included NOX4 inhibitory chromanone compounds. Here we describe the optimization of early ADME(T) parameters determining lipophilicity, phospholipophilicity and permeability linked to structure-activity relationship. We prove that optimal lipo- and phospholipophilicty can be also determined in case of NOX4 inhibitors and a comparison will be made between the chemically similar isochromanone and chromanone molecular libraries. It will be also shown how to predict the effect of different substituents on permeability, lipo- and phospholipophilicity and also the biological differences between anti-tumour molecules and NOX4 inhibitors according to their penetration ability.
Optimization of microstructural parameters for hard-soft nanocomposite permanent magnets
NASA Astrophysics Data System (ADS)
Wysocki, Aleksander; Janicka, Karolina; Antropov, Vladimir
2015-03-01
We use finite temperature micromagnetic simulations to investigate hysteretic properties of hard/soft nanocomposite permanent magnets. Several generic geometries are considered including bilayers, superlatices, and different core-shell structures. We perform multiparameter optimization of the permanent magnet properties with respect to grain sizes, texture, and soft phase volume content. In addition, the effects of thermal fluctuations and the variation of the micromagnetic parameters at the hard/soft interface are studied. In particular, we find that the properties show typically only a small dependence on the interface exchange unless it becomes order of magnitude smaller than exchange in common 3d magnets in which case energy products and optimal soft phase content decrease dramatically. This behavior is, however, different for bilayer system with perpendicular anisotropy. Here we demonstrate that the competition between dipolar interactions and the interlayer exchange leads to significant dependence on the latter even for moderate exchange coupling strengths. Our results are compared with existing experimental data for Nd2Fe14B/Fe, SmCo5/Co, and MnBi/FeCo nanocomposites. This work was supported by the project: ``Solid State Processing of Fully Dense Anisotropic Nanocomposite Magnets,'' ARPA-E Control Number 0670-4987. Ames Laboratory is operated by Iowa State University under Contract DE-AC02-07CH11358.
Singh, Gurmeet; Jain, Vivek; Gupta, Dheeraj; Ghai, Aman
2016-09-01
Orthopaedic surgery involves drilling of bones to get them fixed at their original position. The drilling process used in orthopaedic surgery is most likely to the mechanical drilling process and there is all likelihood that it may harm the already damaged bone, the surrounding bone tissue and nerves, and the peril is not limited at that. It is very much feared that the recovery of that part may be impeded so that it may not be able to sustain life long. To achieve sustainable orthopaedic surgery, a surgeon must try to control the drilling damage at the time of bone drilling. The area around the holes decides the life of bone joint and so, the contiguous area of drilled hole must be intact and retain its properties even after drilling. This study mainly focuses on optimization of drilling parameters like rotational speed, feed rate and the type of tool at three levels each used by Taguchi optimization for surface roughness and material removal rate. The confirmation experiments were also carried out and results found with the confidence interval. Scanning electrode microscopy (SEM) images assisted in getting the micro level information of bone damage. PMID:27254280
Si-based thin film coating on Y-TZP: Influence of deposition parameters on adhesion of resin cement
NASA Astrophysics Data System (ADS)
Queiroz, José Renato Cavalcanti; Nogueira Junior, Lafayette; Massi, Marcos; Silva, Alecssandro de Moura; Bottino, Marco Antonio; Sobrinho, Argemiro Soares da Silva; Özcan, Mutlu
2013-10-01
This study evaluated the influence of deposition parameters for Si-based thin films using magnetron sputtering for coating zirconia and subsequent adhesion of resin cement. Zirconia ceramic blocks were randomly divided into 8 groups and specimens were either ground finished and polished or conditioned using air-abrasion with alumina particles coated with silica. In the remaining groups, the polished specimens were coated with Si-based film coating with argon/oxygen magnetron discharge at 8:1 or 20:1 flux. In one group, Si-based film coating was performed on air-abraded surfaces. After application of bonding agent, resin cement was bonded. Profilometry, goniometry, Energy Dispersive X-ray Spectroscopy and Rutherford Backscattering Spectroscopy analysis were performed on the conditioned zirconia surfaces. Adhesion of resin cement to zirconia was tested using shear bond test and debonded surfaces were examined using Scanning Electron Microscopy. Si-based film coating applied on air-abraded rough zirconia surfaces increased the adhesion of the resin cement (22.78 ± 5.2 MPa) compared to those of other methods (0-14.62 MPa) (p = 0.05). Mixed type of failures were more frequent in Si film coated groups on either polished or air-abraded groups. Si-based thin films increased wettability compared to the control group but did not change the roughness, considering the parameters evaluated. Deposition parameters of Si-based thin film and after application of air-abrasion influenced the initial adhesion of resin cement to zirconia.
Ibáñez-Escriche, N; Magallón, E; Gonzalez, E; Tejeda, J F; Noguera, J L
2016-01-01
The aim of this study was to estimate the genetic and environmental parameters and crossbreeding effects on fatty acid and fat traits in the Iberian pig. Our final goal is to explore target selection traits and define crossbreeding strategies. The phenotypes were obtained under intensive management from 470 animals in a diallelic experiment involving Retinto, Torbiscal, and Entrepelado lines. The data set was composed of backfat thickness at the fourth rib (BFT), intramuscular fat (IMF) in the longissimus thoracis (LT), and the fatty acid profile for IMF and subcutaneous fat (SCF) traits. Data were analyzed through a Bayesian bivariate animal model by using a reparameterization of Dickerson's model. The results obtained showed an important genetic determinism for all traits analyzed with heritability ranging from 0.09 to 0.67. The common environment litter effect also had an important effect on IMF (0.34) and its fatty acid composition (0.06-0.53) at slaughter. The additive genetic correlation between BFT and IMF (additive genetic correlation [] = 0.31) suggested that it would be possible to improve lean growth independent of the IMF with an appropriate selection index. Furthermore, the high additive genetic correlation ( = 0.68) found between MUFA tissues would seem to indicate that either the LT or SCF could be used as the reference tissue for MUFA selection. The relevance of the crossbreeding parameters varied according to the traits analyzed. Backfat thickness at the fourth rib and the fatty acid profile of the IMF showed relevant differences between crosses, mostly due to line additive genetic effects associated with the Retinto line. On the contrary, those for IMF crosses were probably mainly attributable to heterosis effects. Particularly, heterosis effects were relevant for the Retinto and Entrepelado crosses (approximately 16% of the trait), which could be valuable for a crossbreeding system involving these lines.
The improvement of OPC accuracy and stability by the model parameters' analysis and optimization
NASA Astrophysics Data System (ADS)
Chung, No-Young; Choi, Woon-Hyuk; Lee, Sung-Ho; Kim, Sung-Il; Lee, Sun-Yong
2007-10-01
because this huge intensity difference can't be caused by the scanner system with respect to the X-Y intensity difference specification in the scanner. Therefore this source map should be well organized for the OPC modeling and a manipulated source map improves the horizontal and vertical mask bias and even OPC convergence. The focus parameter which is critical for the process window OPC and ORC should be matched to the tilted Bossung plot which is caused by uncorrectable aberration to predict the CD change in the through focus with a new devised method. Pupil polarization data can be applied into the OPC modeling and this parameter is also used for the unpolarized source and the polarized source and specially this parameter helps Apodization loss to be 0 and is evaluated for the effect into the modeling. With the analysis and optimization about the model parameters the robust model is achieved in the sub 45nm device node.
Sensitivity study and parameter optimization of OCD tool for 14nm finFET process
NASA Astrophysics Data System (ADS)
Zhang, Zhensheng; Chen, Huiping; Cheng, Shiqiu; Zhan, Yunkun; Huang, Kun; Shi, Yaoming; Xu, Yiping
2016-03-01
Optical critical dimension (OCD) measurement has been widely demonstrated as an essential metrology method for monitoring advanced IC process in the technology node of 90 nm and beyond. However, the rapidly shrunk critical dimensions of the semiconductor devices and the increasing complexity of the manufacturing process bring more challenges to OCD. The measurement precision of OCD technology highly relies on the optical hardware configuration, spectral types, and inherently interactions between the incidence of light and various materials with various topological structures, therefore sensitivity analysis and parameter optimization are very critical in the OCD applications. This paper presents a method for seeking the optimum sensitive measurement configuration to enhance the metrology precision and reduce the noise impact to the greatest extent. In this work, the sensitivity of different types of spectra with a series of hardware configurations of incidence angles and azimuth angles were investigated. The optimum hardware measurement configuration and spectrum parameter can be identified. The FinFET structures in the technology node of 14 nm were constructed to validate the algorithm. This method provides guidance to estimate the measurement precision before measuring actual device features and will be beneficial for OCD hardware configuration.
Determining System Parameters for Optimal Performance of Hybrid DS/FFH Spread-Spectrum
Ma, Xiao; Olama, Mohammed M; Kuruganti, Phani Teja; Smith, Stephen Fulton; Djouadi, Seddik M
2012-01-01
In recent years there has been great interest in using hybrid spread-spectrum (HSS) techniques for commercial applications, particularly in the Smart Grid, in addition to their use in military communications because they accommodate high data rates with high link integrity, even in the presence of significant multipath effects and interfering signals. A highly useful form of this transmission technique for many types of command, control, and sensing applications is the specific code-related combination of standard direct sequence (DS) modulation with "fast" frequency hopping (FFH), denoted hybrid DS/FFH, wherein multiple frequency hops occur within a single data-bit time. In this paper, an optimization problem is formulated that maximizes the DS/FFH communication system performance in terms of probability of bit error and solves for the system design parameters. The objective function is non-convex and can be solved by applying the Karush-Kuhn-Tucker conditions. System design parameters of interest are the length of the DS code sequence, number of frequency hopping channels, number of channels corrupted by wide-band jamming, and number of hops per bit. The proposed formulation takes into account the effects from wide-band and partial-band jamming, multi-user interference and/or varying degrees of Rayleigh and Rician multipath fading. Numerical results are presented to demonstrate the method s viability.
Zhao, An-Xin; Tang, Xiao-Jun; Zhang, Zhong-Hua; Liu, Jun-Hua
2014-07-01
In the multicomponent mixture hydrocarbon gases Fourier transform infrared (FTIR) quantitative analysis, especially for light alkane gases, it is not easy to establish the quantitative analysis model because their IR spectra absorption peaks are seriously overlapped. Aiming at this problem, the Tikhonov regularization algorithm was used to select the characteristic wavelengths for seven kinds of light alkane mixture gases FTIR which are composed with methane, ethane, propane, iso-butane, n-butane, iso-pentane and n-pentane. And then the wavelength selection was used to establish the quantitative analysis model. By comparing the analysis characteristics wavelength selection and TR parameters optimization of the mixed gases in the infrared all wave band, the first absorption peak band and the second peak band, the characteristic wavelength of 7 kinds of gases were selected by Tikhonov algorithm. The wavelength selection and Tikhonov regularization parameters were used to test the actual measured methane spectral data, and then we got that with other gas components the max cross sensitivity was 11.153 7%, the minimum cross sensitivity was 1.239 7%, and the root mean square prediction error was 0.004 8. The Tikhonov regularization algorithm effectively enhanced the accuracy in the light alkane mixed gas quantitative analysis. The feasibility of alkane gases mixture Fourier transform infrared spectrum wavelength selection was preliminarily verified by using the Tikhonov regularization algorithm. PMID:25269291
Patient performance-based plan parameter optimization for prostate cancer in tomotherapy.
Cao, Yuan Jie; Lee, Suk; Chang, Kyung Hwan; Shim, Jang Bo; Kim, Kwang Hyeon; Park, Young Je; Kim, Chul Yong
2015-01-01
The purpose of this study is to evaluate the influence of treatment-planning parameters on the quality of treatment plans in tomotherapy and to find the optimized planning parameter combinations when treating patients with prostate cancer under different performances. A total of 3 patients with prostate cancer with Eastern Cooperative Oncology Group (ECOG) performance status of 2 or 3 were included in this study. For each patient, 27 treatment plans were created using a combination of planning parameters (field width of 1, 2.5, and 5cm; pitch of 0.172, 0.287, and 0.43; and modulation factor of 1.8, 3, and 3.5). Then, plans were analyzed using several dosimetrical indices: the prescription isodose to target volume (PITV) ratio, homogeneity index (HI), conformity index (CI), target coverage index (TCI), modified dose HI (MHI), conformity number (CN), and quality factor (QF). Furthermore, dose-volume histogram of critical structures and critical organ scoring index (COSI) were used to analyze organs at risk (OAR) sparing. Interestingly, treatment plans with a field width of 1cm showed more favorable results than others in the planning target volume (PTV) and OAR indices. However, the treatment time of the 1-cm field width was 3 times longer than that of plans with a field width of 5cm. There was no substantial decrease in treatment time when the pitch was increased from 0.172 to 0.43, but the PTV indices were slightly compromised. As expected, field width had the most significant influence on all of the indices including PTV, OAR, and treatment time. For the patients with good performance who can tolerate a longer treatment time, we suggest a field width of 1cm, pitch of 0.172, and modulation factor of 1.8; for the patients with poor performance status, field width of 5cm, pitch of 0.287, and a modulation factor of 3.5 should be considered.
NASA Astrophysics Data System (ADS)
Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina
2016-03-01
This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.
NASA Astrophysics Data System (ADS)
Venkatesan, K.; Ramanujam, R.; Kuppan, P.
2016-04-01
This paper presents a parametric effect, microstructure, micro-hardness and optimization of laser scanning parameters (LSP) on heating experiments during laser assisted machining of Inconel 718 alloy. The laser source used for experiments is a continuous wave Nd:YAG laser with maximum power of 2 kW. The experimental parameters in the present study are cutting speed in the range of 50-100 m/min, feed rate of 0.05-0.1 mm/rev, laser power of 1.25-1.75 kW and approach angle of 60-90°of laser beam axis to tool. The plan of experiments are based on central composite rotatable design L31 (43) orthogonal array. The surface temperature is measured via on-line measurement using infrared pyrometer. Parametric significance on surface temperature is analysed using response surface methodology (RSM), analysis of variance (ANOVA) and 3D surface graphs. The structural change of the material surface is observed using optical microscope and quantitative measurement of heat affected depth that are analysed by Vicker's hardness test. The results indicate that the laser power and approach angle are the most significant parameters to affect the surface temperature. The optimum ranges of laser power and approach angle was identified as 1.25-1.5 kW and 60-65° using overlaid contour plot. The developed second order regression model is found to be in good agreement with experimental values with R2 values of 0.96 and 0.94 respectively for surface temperature and heat affected depth.
Application of particle swarm optimization to parameter search in dynamical systems
NASA Astrophysics Data System (ADS)
Matsushita, Haruna; Saito, Toshimichi
This paper proposes an application of the particle swarm optimization (PSO) to analysis of switched dynamical systems (SDS). This is the first application of PSO to bifurcation analysis. We consider the application to an example of the SDS which relates to a simplified model of photovoltaic systems such that the input is a single solar cell and is converted to the output via a boost converter. Our SDS includes a piecewise linear current-controlled voltage source that is a simplified model of the solar cell and the switching rule is a variant of peak-current-controlled switching. We derive two equations that give period-doubling bifurcation set and the maximum power point (MPP) for the parameter: they are objective of the analysis. The two equations are transformed into an multi objective problem (MOP) described by the hybrid fitness function consisting of two functions evaluating the validity of parameters and criteria. The proposed method permits increase (deteriorate) of some component below the criterion and the increase can help to exclude the bad component. This criteria effect helps an improvement of trade-off problems in existing MOP solvers. Furthermore, by using the piecewise exact solution and return map for the simulation, the MOP is described exactly and the PSO can find the precise (approximate) solution. From simulation results, we confirm that the PSO for the MOP can easily find the solution parameters although a standard numerical calculation needs huge calculation amount. The efficiency of the proposed algorithm is confirmed by measuring in terms of accuracy, computation amount and robustness.
Aljimaee, Yazeed HM; El-Helw, Abdel-Rahim M; Ahmed, Osama AA; El-Say, Khalid M
2015-01-01
Background Carvedilol (CVD) is used for the treatment of essential hypertension, heart failure, and systolic dysfunction after myocardial infarction. Due to its lower aqueous solubility and extensive first-pass metabolism, the absolute bioavailability of CVD does not exceed 30%. To overcome these drawbacks, the objective of this work was to improve the solubility and onset of action of CVD through complexation with hydroxypropyl-β-cyclodextrin and formulation of the prepared complex as orodispersible tablets (ODTs). Methods Compatibility among CVD and all tablet excipients using differential scanning calorimetry and Fourier transform infrared spectroscopy, complexation of CVD with different polymers, and determination of the solubility of CVD in the prepared complexes were first determined. A Box-Behnken design (BBD) was used to study the effect of tablet formulation variables on the characteristics of the prepared tablets and to optimize preparation conditions. According to BBD design, 15 formulations of CVD-ODTs were prepared by direct compression and then evaluated for their quality attributes. The relative pharmacokinetic parameters of the optimized CVD-ODTs were compared with those of the marketed CVD tablet. A single dose, equivalent to 2.5 mg/kg CVD, was administered orally to New Zealand white rabbits using a double-blind, randomized, crossover design. Results The solubility of CVD was improved from 7.32 to 22.92 mg/mL after complexation with hydroxypropyl-β-cyclodextrin at a molar ratio of 1:2 (CVD to cyclodextrin). The formulated CVD-ODTs showed satisfactory results concerning tablet hardness (5.35 kg/cm2), disintegration time (18 seconds), and maximum amount of CVD released (99.72%). The pharmacokinetic data for the optimized CVD-ODT showed a significant (P<0.05) increase in maximum plasma concentration from 363.667 to 496.4 ng/mL, and a shortening of the time taken to reach maximum plasma concentration to 2 hours in comparison with the marketed tablet
NASA Astrophysics Data System (ADS)
Narayanan, S.; Mohan Kumar, M.; Hassanizadeh, S. M.; Raoof, A.
2014-12-01
The colloid deposition behavior observed at the Darcy scale represents an average of the processes occurring at the pore scale. Hence, a better understanding of the processes occurring at the Darcy scale can be obtained by studying colloid transport at the pore-scale and then upscaling the results. In this study, we have developed a mathematical model to simulate the transport of colloids in a cylindrical pore by considering various processes such as advection, diffusion, colloid-soil surface interactions and hydrodynamic wall effects. The pore space is divided into three different regions, namely, the bulk, diffusion and potential regions, based on the dominant processes acting in each of these regions. In the bulk region, colloid transport is governed by advection and diffusion; whereas in the diffusion region, colloid mobility due to diffusion is retarded by hydrodynamic wall effects. Colloid-solid interaction forces dominate the transport in the potential region where colloid deposition occurs and are calculated using DLVO theory. The expressions for mass transfer rate coefficients between the diffusion and potential regions have been derived for different DLVO energy profiles. These are incorporated in the pore-scale equations in the form of a boundary condition at the diffusion-potential region interface. The model results are used to obtain the colloid breakthrough curve at the end of a long pore, and then it is fitted with 1D advection-dispersion-adsorption model so as to determine the averaged attachment and detachment rate coefficients at the scale of a single pore. A sensitivity analysis of the model to six pore-scale parameters (colloid and wall surface potentials, solution ionic strength, average pore-water velocity, colloid radius, and pore radius) is carried out so as to find the relation between the averaged deposition rate coefficients at pore scale vs the pore-scale parameters. We found an hyper exponential relation between the colloid attachment
NASA Astrophysics Data System (ADS)
Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li
2015-05-01
In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.
Hanaki, Satoshi; Leng, Bo; Uchida, Hitoshi
2010-10-13
Boron nitride (BN) films have been attractive due to their excellent properties such as high hardness, thermal conductivity and chemical stability. In this study, BN films were prepared by depositing B vapor under simultaneous irradiation of N ions, that is ion mixing and vapor deposition (IVD) technique. The effects of processing parameters such as, acceleration voltage of N ions, transport ratio B/N and substrate temperature, on the internal stress of BN films were investigated. As a result, compressive internal stress increases at low acceleration voltage and high transport ratio B/N, which corresponded to the condition for formation of cBN phase. The hardness also becomes high at this condition and there is a strong correlation between internal stress and hardness of BN film. In addition to that, relaxation of internal stress by inserting inner layer between substrate and cBN layer has been carried out. It is confirmed that internal stress can be decreased by inner layer. Especially, relaxation of internal stress without degradation of high hardness can be achieved when the crystal structure of inner layer is hBN.
NASA Technical Reports Server (NTRS)
Stahara, S. S.; Elliott, J. P.; Spreiter, J. R.
1983-01-01
An investigation was conducted to continue the development of perturbation procedures and associated computational codes for rapidly determining approximations to nonlinear flow solutions, with the purpose of establishing a method for minimizing computational requirements associated with parametric design studies of transonic flows in turbomachines. The results reported here concern the extension of the previously developed successful method for single parameter perturbations to simultaneous multiple-parameter perturbations, and the preliminary application of the multiple-parameter procedure in combination with an optimization method to blade design/optimization problem. In order to provide as severe a test as possible of the method, attention is focused in particular on transonic flows which are highly supercritical. Flows past both isolated blades and compressor cascades, involving simultaneous changes in both flow and geometric parameters, are considered. Comparisons with the corresponding exact nonlinear solutions display remarkable accuracy and range of validity, in direct correspondence with previous results for single-parameter perturbations.
NASA Astrophysics Data System (ADS)
Romanov, A. A.; Serkov, A. V.; Hruleva, E. S.
2016-07-01
In this article a formation process of dielectric films on silicon (100) and silicon carbide using plasma-chemical deposition is described. Experimental relationships of SiO2 films thickness and main technological parameters are presented. Values of electro-physical parameters of films are measured.
Optimization of exposure parameters for pediatric chest x-ray imaging
NASA Astrophysics Data System (ADS)
Park, Hye-Suk; Kim, Ye-Seul; Kim, Hee-Joung
2012-03-01
The pediatric patients are more susceptible to the effects of ionizing radiation than adults. Pediatric patients are smaller, more radiosensitive than adult patients and many cannot stand unassisted. Their characteristics affect the method of imaging projection and how dose is optimized. The purpose of this study was to investigate the effect of various technical parameters for the dose optimization in pediatric chest radiological examinations by evaluating effective dose and effective detective quantum efficiency (eDQE) including the scatter radiation from the object, the blur caused by the focal spot, geometric magnification and detector characteristics. For the tube voltages ranging from 40 to 90 kV in 10 kV increments at the focus-to-detector distance of 100, 110, 120, 150, 180 cm, the eDQE was evaluated at same effective dose. The results showed that the eDQE was largest at 60 kVp without and with an anti-scatter grid. Especially, the eDQE was considerably higher without the use of an anti-scatter grid on equivalent effective dose. This indicates that the reducing the scatter radiation did not compensate for the loss of absorbed effective photons in the grid. When the grid is not used the eDQE increased with increasing focus-to-detector distance because of the greater effective modulation transfer function (eMTF) with the lower focal spot blurring. In conclusion, for pediatric patients, the amount of scattered radiation is less, and the amount of grid attenuation increased unnecessary radiation dose.
Sathiyamoorthy, V.; Sekar, T.; Elango, N.
2015-01-01
Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm3/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm3/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models. PMID:26167538
Sathiyamoorthy, V; Sekar, T; Elango, N
2015-01-01
Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm(3)/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm(3)/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models.
Sathiyamoorthy, V; Sekar, T; Elango, N
2015-01-01
Formation of spikes prevents achievement of the better material removal rate (MRR) and surface finish while using plain NaNO3 aqueous electrolyte in electrochemical machining (ECM) of die tool steel. Hence this research work attempts to minimize the formation of spikes in the selected workpiece of high carbon high chromium die tool steel using copper nanoparticles suspended in NaNO3 aqueous electrolyte, that is, nanofluid. The selected influencing parameters are applied voltage and electrolyte discharge rate with three levels and tool feed rate with four levels. Thirty-six experiments were designed using Design Expert 7.0 software and optimization was done using multiobjective genetic algorithm (MOGA). This tool identified the best possible combination for achieving the better MRR and surface roughness. The results reveal that voltage of 18 V, tool feed rate of 0.54 mm/min, and nanofluid discharge rate of 12 lit/min would be the optimum values in ECM of HCHCr die tool steel. For checking the optimality obtained from the MOGA in MATLAB software, the maximum MRR of 375.78277 mm(3)/min and respective surface roughness Ra of 2.339779 μm were predicted at applied voltage of 17.688986 V, tool feed rate of 0.5399705 mm/min, and nanofluid discharge rate of 11.998816 lit/min. Confirmatory tests showed that the actual performance at the optimum conditions was 361.214 mm(3)/min and 2.41 μm; the deviation from the predicted performance is less than 4% which proves the composite desirability of the developed models. PMID:26167538
Parameter Design and Optimal Control of an Open Core Flywheel Energy Storage System
NASA Technical Reports Server (NTRS)
Pang, D.; Anand, D. K.; Kirk, J. A.
1996-01-01
In low earth orbit (LEO) satellite applications spacecraft power is provided by photovoltaic cells and batteries. To overcome battery shortcomings the University of Maryland, working in cooperation with NASA/GSFC and NASA/LeRC, has developed a magnetically suspended flywheel for energy storage applications. The system is referred to as an Open Core Composite Flywheel (OCCF) energy storage system. Successful application of flywheel energy storage requires integration of several technologies, viz. bearings, rotor design, motor/generator, power conditioning, and system control. In this paper we present a parameter design method which has been developed for analyzing the linear SISO model of the magnetic bearing controller for the OCCF. The objective of this continued research is to principally analyze the magnetic bearing system for nonlinear effects in order to increase the region of stability, as determined by high speed and large air gap control. This is achieved by four tasks: (1) physical modeling, design, prototyping, and testing of an improved magnetically suspended flywheel energy storage system, (2) identification of problems that limit performance and their corresponding solutions, (3) development of a design methodology for magnetic bearings, and (4) design of an optimal controller for future high speed applications. Both nonlinear SISO and MIMO models of the magnetic system were built to study limit cycle oscillations and power amplifier saturation phenomenon observed in experiments. The nonlinear models include the inductance of EM coils, the power amplifier saturation, and the physical limitation of the flywheel movement as discussed earlier. The control program EASY5 is used to study the nonlinear SISO and MIMO models. Our results have shown that the characteristics and frequency responses of the magnetic bearing system obtained from modeling are comparable to those obtained experimentally. Although magnetic saturation is shown in the bearings, there
Kong, Fansheng; Yu, Shujuan; Bi, Yongguang; Huang, Xiaojun; Huang, Mengqian
2016-01-01
Objective: To optimize and verify the cellulase extraction of polyphenols from honeysuckle and provide a reference for enzymatic extracting polyphenols from honeysuckle. Materials and Methods: The uniform design was used According to Fick's first law and kinetic model, fitting analysis of the dynamic process of enzymatic extracting polyphenols was conducted. Results: The optimum enzymatic extraction parameters for polyphenols from honeysuckle are found to be 80% (v/v) of alcohol, 35:1 (mL/g) of liquid-solid ratio, 80°C of extraction temperature, 8.5 of pH, 6.0 mg of enzyme levels, and 130 min of extraction time. Under the optimal conditions, the extraction rate of polyphenols was 3.03%. The kinetic experiments indicated kinetic equation had a good linear relationship with t even under the conditions of different levels of enzyme and temperature, which means fitting curve tallies well with the experimental values. Conclusion: The results of quantification showed that the results provide a reference for enzymatic extracting polyphenols from honeysuckle. SUMMARY Lonicerae flos (Lonicera japonica Thunb.) is a material of traditional Chinese medicine and healthy drinks, of which active compounds mainly is polyphenols. At present, plant polyphenols are the hotspots centents of food, cosmetic and medicine, because it has strong bioactivity. Several traditional methods are available for the extraction of plant polyphenols including impregnation, solvent extraction, ultrasonic extraction, hot-water extraction, alkaline dilute alcohol or alkaline water extraction, microwave extraction and Supercritical CO2 extraction. But now, an increasing number of research on using cellulase to extract active ingredients from plants. Enzymatic method is widely used for enzyme have excellent properties of high reaction efficiency and specificity, moderate reaction conditions, shorter extraction time and easier to control, less damage to the active ingredient. At present, the enzymatic
Groves, James R; Matias, Vladimir; Stan, Liliana; De Paula, Raymond F; Hammond, Robert H; Clemens, Bruce M
2010-01-01
Recent efforts in investigating the mechanism of ion beam assisted deposition (IBAD) of biaxially textured thin films of magnesium oxide (MgO) template layers have shown that the texture develops suddenly during the initial 2 nm of deposition. To help understand and tune the behavior during this initial stage, we pre-deposited thin layers of MgO with no ion assist prior to IBAD growth of MgO. We found that biaxial texture develops for pre-deposited thicknesses < 2 nm, and that the thinnest layer tested, at 1 nm, resulted in the best qualitative RHEED image, indicative of good biaxial texture development. The texture developed during IBAD growth on the 1.5 nm pre-deposited layer is slightly worse and IBAD growth on the 2 nm pre-deposited layer produces a fiber texture. Application of these layers on an Al{sub 2}O{sub 3} starting surface, which has been shown to impede texture development, improves the overall quality of the IBAD MgO and has some of the characteristics of a biaxially texture RHEED pattern. It is suggested that the use of thin (<2 nm) pre-deposited layers may eliminate the need for bed layers like Si{sub 3}N{sub 4} and Y{sub 2}O{sub 3} that are currently thought to be required for proper biaxial texture development in IBAD MgO.
Investigation and Parameter Optimization of a Hydraulic Ram Pump Using Taguchi Method
NASA Astrophysics Data System (ADS)
Sarma, Dhrupad; Das, Monotosh; Brahma, Bipul; Pandwar, Deepak; Rongphar, Sermirlong; Rahman, Mafidur
2016-06-01
The main objective of this research work is to investigate the effect of Waste Valve height and Pressure Chamber height on the output flow rate of a Hydraulic ram pump. Also the second objective of this work is to optimize them for a hydraulic ram pump delivering water up to a height of 3.81 m (12.5 feet ) from the ground with a drive head (inlet head) of 1.86 m (6.11 feet). Two one-factor-at-a-time experiments have been conducted to decide the levels of the selected input parameters. After deciding the input parameters, an experiment has been designed using Taguchi's L9 Orthogonal Array with three repetitions. Analysis of Variance (ANOVA) is carried out to verify the significance of effect of the factors on the output flow rate of the pump. Results show that the height of the Waste Valve and height of the Pressure Chamber have significant effect on the outlet flow of the pump. For a pump of drive pipe diameter (inlet pipe) 31.75 mm (1.25 in.) and delivery pipe diameter of 12.7 mm (0.5 in.) the optimum setting was found out to be at a height of 114.3 mm (4.5 in.) of the Waste Valve and 406.4 mm (16 in.) of the Pressure vessel providing a delivery flow rate of 93.14 l per hour. For the same pump estimated range of output flow rate is, 90.65-94.97 l/h.
Mekala, Naveen Kumar; Singhania, Reeta Rani; Sukumaran, Rajeev K; Pandey, Ashok
2008-12-01
Sugar cane bagasse was used as substrate for cellulase production using Trichoderma reesei RUT C30, and the culture parameters were optimized for enhancing cellulase yield. The culture parameters, such as incubation temperature, duration of incubation, and inducer concentration, were optimized for enhancing cellulase yield using a Box-Behnken experimental design. The optimal level of each parameter for maximum cellulase production by the fungus was determined. Predicted results showed that cellulase production was highest (25.6 FPAase units per gram dry substrate) when the inducer concentration was 0.331 ml/gds, and the incubation temperature and time were 33 degrees C and 67 h, respectively. Crude inducer generated by cellulase action was found to be very effective in inducing cellulases. Validation of predicted results was done, and the experimental values correlated well with that of the predicted.
He, L; Huang, G H; Lu, H W
2010-04-15
A new stochastic optimization model under modeling uncertainty (SOMUM) and parameter certainty is applied to a practical site located in western Canada. Various groundwater remediation strategies under different significance levels are obtained from the SOMUM model. The impact of modeling uncertainty (proxy-simulator residuals) on optimal remediation strategies is compared to that of parameter uncertainty (arising from physical properties). The results show that the increased remediation cost for mitigating modeling-uncertainty impact would be higher than those from models where the coefficient of variance of input parameters approximates to 40%. This provides new evidence that the modeling uncertainty in proxy-simulator residuals can hardly be ignored; there is thus a need of investigating and mitigating the impact of such uncertainties on groundwater remediation design. This work would be helpful for lowering the risk of system failure due to potential environmental-standard violation when determining optimal groundwater remediation strategies.
Device parameter optimization for sub-20 nm node HK/MG-last bulk FinFETs
NASA Astrophysics Data System (ADS)
Miao, Xu; Huaxiang, Yin; Huilong, Zhu; Xiaolong, Ma; Weijia, Xu; Yongkui, Zhang; Zhiguo, Zhao; Jun, Luo; Hong, Yang; Chunlong, Li; Lingkuan, Meng; Peizhen, Hong; Jinjuan, Xiang; Jianfeng, Gao; Qiang, Xu; Wenjuan, Xiong; Dahai, Wang; Junfeng, Li; Chao, Zhao; Dapeng, Chen; Simon, Yang; Tianchun, Ye
2015-04-01
Sub-20 nm node bulk FinFET PMOS devices with an all-last high-k/metal gate (HK/MG) process are fabricated and the influence of a series of device parameters on the device scaling is investigated. The high and thin Fin structure with a tapered sidewall shows better performance than the normal Fin structure. The punch through stop layer (PTSL) and source drain extension (SDE) doping profiles are carefully optimized. The device without SDE annealing shows a larger drive current than that with SDE annealing due to better Si crystal regrowth in the amorphous Fin structure after source/drain implantation. The band-edged MG has a better short channel effect immunity, but the lower effective work function (EWF) MG shows a larger driveability. A tradeoff choice for different EWF MGs should be carefully designed for the device's scaling. Project supported by the National 02 IC Projects and the Opening Project of Key Laboratory of Microelectronics Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences.
Finite Element Based Optimization of Material Parameters for Enhanced Ballistic Protection
NASA Astrophysics Data System (ADS)
Ramezani, Arash; Huber, Daniel; Rothe, Hendrik
2013-06-01
The threat imposed by terrorist attacks is a major hazard for military installations, vehicles and other items. The large amounts of firearms and projectiles that are available, pose serious threats to military forces and even civilian facilities. An important task for international research and development is to avert danger to life and limb. This work will evaluate the effect of modern armor with numerical simulations. It will also provide a brief overview of ballistic tests in order to offer some basic knowledge of the subject, serving as a basis for the comparison of simulation results. The objective of this work is to develop and improve the modern armor used in the security sector. Numerical simulations should replace the expensive ballistic tests and find vulnerabilities of items and structures. By progressively changing the material parameters, the armor is to be optimized. Using a sensitivity analysis, information regarding decisive variables is yielded and vulnerabilities are easily found and eliminated afterwards. To facilitate the simulation, advanced numerical techniques have been employed in the analyses.
NASA Astrophysics Data System (ADS)
Cherng, An-Pan
2003-03-01
Placing vibration sensors at appropriate locations plays an important role in experimental modal analysis. It is known that maximising the determinant of Fisher information matrix (FIM) can result in an optimal configuration of sensors from a set of candidate locations. Some methods have already been proposed in the literature, such as maximising the determinant of the diagonal elements of mode shape correlation matrix, ranking the sensor contributions by Hankel singular values (HSVs), and using perturbation theory to achieve minimum variance of estimation, etc. The objectives of this work were to systematically analyse existing methods and to propose methods that either improve their performance or accelerate the searching process for modal parameter identification. The approach used in this article is based on the analytical formulation of singular value decomposition (SVD) for a candidate-blocked Hankel matrix using signal subspace correlation (SSC) techniques developed earlier by the author. The SSC accounts for factors that contribute to the estimated results, such as mode shapes, damping ratios, sampling rate and matrix size (or number of data used). With the aid of SSC, it will be shown that using information of mode shapes and that of singular values are equivalent under certain conditions. The results of this work are not only consistent with those of existing methods, but also demonstrate a more general viewpoint to the optimisation problem. Consequently, the insight of the sensor placement problem is clearly interpreted. Finally, two modified methods that inherit the merits of existing methods are proposed, and their effectiveness is demonstrated by numerical examples.
Autonomous Growing Neural Gas for applications with time constraint: optimal parameter estimation.
García-Rodríguez, José; Angelopoulou, Anastassia; García-Chamizo, Juan Manuel; Psarrou, Alexandra; Orts Escolano, Sergio; Morell Giménez, Vicente
2012-08-01
This paper aims to address the ability of self-organizing neural network models to manage real-time applications. Specifically, we introduce fAGNG (fast Autonomous Growing Neural Gas), a modified learning algorithm for the incremental model Growing Neural Gas (GNG) network. The Growing Neural Gas network with its attributes of growth, flexibility, rapid adaptation, and excellent quality of representation of the input space makes it a suitable model for real time applications. However, under time constraints GNG fails to produce the optimal topological map for any input data set. In contrast to existing algorithms, the proposed fAGNG algorithm introduces multiple neurons per iteration. The number of neurons inserted and input data generated is controlled autonomous and dynamically based on a priory or online learnt model. A detailed study of the topological preservation and quality of representation depending on the neural network parameter selection has been developed to find the best alternatives to represent different linear and non-linear input spaces under time restrictions or specific quality of representation requirements. PMID:22386599
Gougoutsa, Chrysa; Christophoridis, Christophoros; Zacharis, Constantinos K; Fytianos, Konstantinos
2016-08-01
This study focused on (a) the development of a screening methodology, in order to determine the main experimental variables affecting chlorinated and brominated disinfection by-product (DBP) formation in water during chlorination experiments and (b) the application of a central composite design (CCD) using response surface methodology (RSM) for the mathematical description and optimization of DBP formation. Chlorine dose and total organic carbon (TOC) were proven to be the main factors affecting the formation of total chlorinated DBPs, while chlorine dose and bromide concentration were the main parameters affecting the total brominated THMs. Longer contact time promoted a rise in chlorinated DBPs' concentration even in the presence of a minimal amount of organic matter. A maximum production of chlorinated DBPs was observed under a medium TOC value and it reduced at high TOC concentrations, possibly due to the competitive production of brominated THMs. The highest concentrations of chlorinated THMs were observed at chlorine dose 10 mg L(-1) and TOC 5.5 mg L(-1). The formation of brominated DBPs is possible even with a minimum amount of NaOCl in the presence of high concentration of bromide ions. Brominated DBPs were observed in maximum concentrations using 8 mg L(-1) of chlorine in the presence of 300 μg L(-1) bromides. PMID:27178297
Optimization of processing parameters and metrology for novel NCA negative resists for NGL
NASA Astrophysics Data System (ADS)
Singh, Vikram; Satyanarayana, V. S. V.; Kessler, Felipe; Scheffer, Francine R.; Weibel, Daniel E.; Sharma, Satinder K.; Ghosh, Subrata; Gonsalves, Kenneth E.
2014-04-01
It is expected that EUV resists must simultaneously pattern 20-nm half-pitch and below, with an LWR of <1.8 nm, and a sensitivity of 5-20 mJ/cm2. In order to make a resist perform optimally, new resist chemistry is required. One such approach being investigated by us is the development of polymeric non-CAR negative photo resists for sub 16 nm technology which is directly sensitive to radiation without utilizing the concept of chemical amplification (CARs). These resist designs are accomplished by homopolymers which are prepared from monomers containing sulfonium groups. We have achieved 20 nm patterns by e-beam lithography using this system. Here we will discuss in detail process parameters such as: spinning conditions for film thicknesses <50 nm and resulting surface topographies, baking regimes, exposure conditions and protocols on sensitivity, contrast, resolution and LER/LWR. Etch resistance data on these thin films will also be provided. Our results are aimed to provide a clear understanding of how these critical steps in the lithographic imaging process will affect extendibility of the non-CAR resist concept to sub 20 nanoscale features. Photodynamics and EUV exposure data will be covered.
NASA Astrophysics Data System (ADS)
Swain, Basudev; Mishra, Chinmayee; Kang, Leeseung; Park, Kyung-Soo; Lee, Chan Gi; Hong, Hyun Seon; Park, Jeung-Jin
2015-05-01
Recovery of metal values from GaN, a metal-organic chemical vapor deposition (MOCVD) waste of GaN based power device and LED industry is investigated by acidic leaching. Leaching kinetics of gallium rich MOCVD waste is studied and the process is optimized. The gallium rich waste MOCVD dust is characterized by XRD and ICP-AES analysis followed by aqua regia digestion. Different mineral acids are used to find out the best lixiviant for selective leaching of the gallium and indium. Concentrated HCl is relatively better lixiviant having reasonably faster kinetic and better leaching efficiency. Various leaching process parameters like effect of acidity, pulp density, temperature and concentration of catalyst on the leaching efficiency of gallium and indium are investigated. Reasonably, 4 M HCl, a pulp density of 50 g/L, 100 °C and stirring rate of 400 rpm are the effective optimum condition for quantitative leaching of gallium and indium.
Chester, T L
2003-10-24
The goal of a separation can be defined in terms of business needs. One goal often used is to provide the required separation in minimum time, but many other goals are also possible. These include maximizing resolution within an analysis-time limit, or minimizing the overall cost. The remaining requirements of the separation can be applied as constraints in the optimization of the goal. We will present a flexible, business-objective-based approach for optimizing the operational parameters of high performance liquid chromatography (HPLC) methods. After selecting the stationary phase and the mobile-phase components, several isocratic experiments are required to build a retention model. Multivariate optimization is performed, within the model, to find the best combination of the parameters being varied so that the result satisfies the goal to the fullest extent possible within the constraints. Interdependencies of parameters can be revealed by plotting the loci of optimal variable values or the function being optimized against a constraint. We demonstrate the concepts with a model separation originally requiring a 54 min analysis time. Multivariate optimization reduces the predicted analysis time to as short as 8 min, depending on the goals and constraints specified. PMID:14601838
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 example demonstrates the dV savings from the feasible solution to the optimal solution.
Optimization of ISOCS Parameters for Quantitative Non-Destructive Analysis of Uranium in Bulk Form
NASA Astrophysics Data System (ADS)
Kutniy, D.; Vanzha, S.; Mikhaylov, V.; Belkin, F.
2011-12-01
and chemical composition of the matrix of the specimen. Obviously, not all parameters can be characterized when measuring samples of unknown composition or uranium in bulk form. Because of this, and especially for uranium materials, the IAEA developed an ISOCS optimization procedure. The target values for the optimization are Μmatrixfixed, the matrix mass determined by weighing with a known mass container, and Εfixed, the 235U enrichment, determined by MGAU. Target values are fitted by varying the matrix density (ρ), and the concentration of uranium in the matrix of the unknown (w). For each (ρi, wi), an efficiency curve is generated, and the masses of uranium isotopes, Μ235Ui and Μ238Ui, determined using spectral activity data and known specific activities for U. Finally, fitted parameters are obtained for Μmatrixi = Μmatrixfixed ± 1σ, Εi = Εfixed ± 1σ, as well as important parameters (ρi, wi, Μ235Ui, Μ238Ui, ΜUi). We examined multiple forms of uranium (powdered, pressed, and scrap UO2 and U3O8) to test this method for its utility in accurately identifying the mass and enrichment of uranium materials, and will present the results of this research.
Tian, Chao; Chen, Jia; Zhang, Bo; Shan, Lianqiang; Zhou, Weimin; Liu, Dongxiao; Bi, Bi; Zhang, Feng; Wang, Weiwu; Zhang, Baohan; Gu, Yuqiu
2015-05-01
The uniformity of the compression driver is of fundamental importance for inertial confinement fusion (ICF). In this paper, the illumination uniformity on a spherical capsule during the initial imprinting phase directly driven by laser beams has been considered. We aim to explore methods to achieve high direct drive illumination uniformity on laser facilities designed for indirect drive ICF. There are many parameters that would affect the irradiation uniformity, such as Polar Direct Drive displacement quantity, capsule radius, laser spot size and intensity distribution within a laser beam. A novel approach to reduce the root mean square illumination non-uniformity based on multi-parameter optimizing approach (particle swarm optimization) is proposed, which enables us to obtain a set of optimal parameters over a large parameter space. Finally, this method is applied to improve the direct drive illumination uniformity provided by Shenguang III laser facility and the illumination non-uniformity is reduced from 5.62% to 0.23% for perfectly balanced beams. Moreover, beam errors (power imbalance and pointing error) are taken into account to provide a more practical solution and results show that this multi-parameter optimization approach is effective.
NASA Astrophysics Data System (ADS)
Sumesh, A.; Sai Ramnadh, L. V.; Manish, P.; Harnath, V.; Lakshman, V.
2016-09-01
Welding is one of the most common metal joining techniques used in industry for decades. As in the global manufacturing scenario the products should be more cost effective. Therefore the selection of right process with optimal parameters will help the industry in minimizing their cost of production. SA 106 Grade B steel has a wide application in Automobile chassis structure, Boiler tubes and pressure vessels industries. Employing central composite design the process parameters for Gas Tungsten Arc Welding was optimized. The input parameters chosen were weld current, peak current and frequency. The joint tensile strength was the response considered in this study. Analysis of variance was performed to determine the statistical significance of the parameters and a Regression analysis was performed to determine the effect of input parameters over the response. From the experiment the maximum tensile strength obtained was 95 KN reported for a weld current of 95 Amp, frequency of 50 Hz and peak current of 100 Amp. With an aim of maximizing the joint strength using Response optimizer a target value of 100 KN is selected and regression models were optimized. The output results are achievable with a Weld current of 62.6148 Amp, Frequency of 23.1821 Hz, and Peak current of 65.9104 Amp. Using Die penetration test the weld joints were also classified in to 2 categories as good weld and weld with defect. This will also help in getting a defect free joint when welding is performed using GTAW process.
NASA Astrophysics Data System (ADS)
Mughal, Maqsood Ali
Clean and environmentally friendly technologies are centralizing industry focus towards obtaining long term solutions to many large-scale problems such as energy demand, pollution, and environmental safety. Thin film solar cell (TFSC) technology has emerged as an impressive photovoltaic (PV) technology to create clean energy from fast production lines with capabilities to reduce material usage and energy required to manufacture large area panels, hence, lowering the costs. Today, cost ($/kWh) and toxicity are the primary challenges for all PV technologies. In that respect, electrodeposited indium sulfide (In2S3) films are proposed as an alternate to hazardous cadmium sulfide (CdS) films, commonly used as buffer layers in solar cells. This dissertation focuses upon the optimization of electrodeposition parameters to synthesize In2S3 films of PV quality. The work describe herein has the potential to reduce the hazardous impact of cadmium (Cd) upon the environment, while reducing the manufacturing cost of TFSCs through efficient utilization of materials. Optimization was performed through use of a statistical approach to study the effect of varying electrodeposition parameters upon the properties of the films. A robust design method referred-to as the "Taguchi Method" helped in engineering the properties of the films, and improved the PV characteristics including optical bandgap, absorption coefficient, stoichiometry, morphology, crystalline structure, thickness, etc. Current density (also a function of deposition voltage) had the most significant impact upon the stoichiometry and morphology of In2S3 films, whereas, deposition temperature and composition of the solution had the least significant impact. The dissertation discusses the film growth mechanism and provides understanding of the regions of low quality (for example, cracks) in films. In2S3 films were systematically and quantitatively investigated by varying electrodeposition parameters including bath
Moench, A.F.; Garabedian, Stephen P.; LeBlanc, Denis R.
2000-01-01
An aquifer test conducted in a sand and gravel, glacial outwash deposit on Cape Cod, Massachusetts was analyzed by means of a model for flow to a partially penetrating well in a homogeneous, anisotropic unconfined aquifer. The model is designed to account for all significant mechanisms expected to influence drawdown in observation piezometers and in the pumped well. In addition to the usual fluid-flow and storage processes, additional processes include effects of storage in the pumped well, storage in observation piezometers, effects of skin at the pumped-well screen, and effects of drainage from the zone above the water table. The aquifer was pumped at a rate of 320 gallons per minute for 72-hours and drawdown measurements were made in the pumped well and in 20 piezometers located at various distances from the pumped well and depths below the land surface. To facilitate the analysis, an automatic parameter estimation algorithm was used to obtain relevant unconfined aquifer parameters, including the saturated thickness and a set of empirical parameters that relate to gradual drainage from the unsaturated zone. Drainage from the unsaturated zone is treated in this paper as a finite series of exponential terms, each of which contains one empirical parameter that is to be determined. It was necessary to account for effects of gradual drainage from the unsaturated zone to obtain satisfactory agreement between measured and simulated drawdown, particularly in piezometers located near the water table. The commonly used assumption of instantaneous drainage from the unsaturated zone gives rise to large discrepancies between measured and predicted drawdown in the intermediate-time range and can result in inaccurate estimates of aquifer parameters when automatic parameter estimation procedures are used. The values of the estimated hydraulic parameters are consistent with estimates from prior studies and from what is known about the aquifer at the site. Effects of
Schmitt, B; Borgogno, J P; Albrand, G; Pelletier, E
1986-11-01
We measure the refractive index of thin films of TiO2 and SiO2 for given deposition parameters. Two complementary methods are used. The first is a postdeposition technique which uses the measurements of reflectance and transmittance in air. The second, in contrast, makes use of in situ measurements (under vacuum and during the actual deposition of the layer). The differences between the values deduced from the two methods can be explained by the amount of atmospheric moisture adsorbed by films. One tries to minimize these shifts for the two materials by choosing deposition parameters. The difficulties come from the absorption losses which must be as small as possible. We use the measured refractive indices of individual layers to give good numerical prediction of the wavelength shift (observed during the admittance of air after deposition in the vacuum chamber) of the transmittance peak of multidielectric Fabry-Perot filters.
Chenel, Marylore; Ogungbenro, Kayode; Duval, Vincent; Laveille, Christian; Jochemsen, Roeline; Aarons, Leon
2005-12-01
The objective of this paper is to determine optimal blood sampling time windows for the estimation of pharmacokinetic (PK) parameters by a population approach within the clinical constraints. A population PK model was developed to describe a reference phase II PK dataset. Using this model and the parameter estimates, D-optimal sampling times were determined by optimising the determinant of the population Fisher information matrix (PFIM) using PFIM_ _M 1.2 and the modified Fedorov exchange algorithm. Optimal sampling time windows were then determined by allowing the D-optimal windows design to result in a specified level of efficiency when compared to the fixed-times D-optimal design. The best results were obtained when K(a) and IIV on K(a) were fixed. Windows were determined using this approach assuming 90% level of efficiency and uniform sample distribution. Four optimal sampling time windows were determined as follow: at trough between 22 h and new drug administration; between 2 and 4 h after dose for all patients; and for 1/3 of the patients only 2 sampling time windows between 4 and 10 h after dose, equal to [4 h-5 h 05] and [9 h 10-10 h]. This work permitted the determination of an optimal design, with suitable sampling time windows which was then evaluated by simulations. The sampling time windows will be used to define the sampling schedule in a prospective phase II study.
Eldred, Michael Scott; Vigil, Dena M.; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Lefantzi, Sophia; Hough, Patricia Diane; Eddy, John P.
2011-12-01
The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the DAKOTA software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of DAKOTA-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of DAKOTA's iterative analysis capabilities.
NASA Astrophysics Data System (ADS)
Guo, Qian; Lu, Zhichang; Hirata, Yoshito; Aihara, Kazuyuki
2013-12-01
We propose an algorithm based on cross-entropy to determine parameters of a piecewise linear model, which describes intermittent androgen suppression therapy for prostate cancer. By comparing with clinical data, the parameter estimation for the switched system shows good fitting accuracy and efficiency. We further optimize switching time points for the piecewise linear model to obtain a feasible therapeutic schedule. The simulation results of therapeutic effect are superior to those of previous strategy.
Singh, Aarti Schröder, Uwe; Klumbies, Hannes; Müller-Meskamp, Lars; Leo, Karl; Geidel, Marion; Knaut, Martin; Hoßbach, Christoph; Albert, Matthias; Mikolajick, Thomas
2013-12-02
The importance of O{sub 3} pulse duration for encapsulation of organic light emitting diodes (OLEDs) with ultra thin inorganic atomic layer deposited Al{sub 2}O{sub 3} layers is demonstrated for deposition temperatures of 50 °C. X-ray reflectivity (XRR) measurements show that O{sub 3} pulse durations longer than 15 s produce dense and thin Al{sub 2}O{sub 3} layers. Correspondingly, black spot growth is not observed in OLEDs encapsulated with such layers during 91 days of aging under ambient conditions. This implies that XRR can be used as a tool for process optimization of OLED encapsulation layers leading to devices with long lifetimes.
NASA Astrophysics Data System (ADS)
Avadhani, G. S.
2003-12-01
Maraging steels possess ultrahigh strength combined with ductility and toughness and could be easily fabricated and heat-treated. Bulk metalworking of maraging steels is an important step in the component manufacture. To optimize the hot-working parameters (temperature and strain rate) for the ring rolling process of maraging steel used for the manufacture of rocket casings, a systematic study was conducted to characterize the hot working behavior by developing processing maps for γ-iron and an indigenous 250 grade maraging steel. The hot deformation behavior of binary alloys of iron with Ni, Co, and Mo, which are major constituents of maraging steel, is also studied. Results from the investigation suggest that all the materials tested exhibit a domain of dynamic recrystallization (DRX). From the instability maps, it was revealed that strain rates above 10 s-1 are not suitable for hot working of these materials. An important result from the stress-strain behavior is that while Co strengthens γ-iron, Ni and Mo cause flow softening. Temperatures around 1125 °C and strain rate range between 0.001 and 0.1 s-1 are suitable for the hot working of maraging steel in the DRX domain. Also, higher strain rates may be used in the meta-dynamic recrystallization domain above 1075 °C for high strain rate applications such as ring rolling. The microstructural mechanisms identified from the processing maps along with grain size analyses and hot ductility measurements could be used to design hot-working schedules for maraging steel.
Suter, Melissa J; Kashiwagi, Manabu; Gallagher, Kevin A; Nadkarni, Seemantini K; Asanani, Nayan; Tanaka, Atsushi; Conditt, Gerard B; Tellez, Armando; Milewski, Krzysztof; Kaluza, Greg L; Granada, Juan F; Bouma, Brett E; Tearney, Guillermo J
2015-08-01
Intracoronary optical frequency domain imaging (OFDI), requires the displacement of blood for clear visualization of the artery wall. Radiographic contrast agents are highly effective at displacing blood however, may increase the risk of contrast-induced nephropathy. Flushing media viscosity, flow rate, and flush duration influence the efficiency of blood displacement necessary for obtaining diagnostic quality OFDI images. The aim of this work was to determine the optimal flushing parameters necessary to reliably perform intracoronary OFDI while reducing the volume of administered radiographic contrast, and assess the influence of flushing media choice on vessel wall measurements. 144 OFDI pullbacks were acquired together with synchronized EKG and intracoronary pressure wire recordings in three swine. OFDI images were graded on diagnostic quality and quantitative comparisons of flushing efficiency and intracoronary cross-sectional area with and without precise refractive index calibration were performed. Flushing media with higher viscosities resulted in rapid and efficient blood displacement. Media with lower viscosities resulted in increased blood-media transition zones, reducing the pullback length of diagnostic quality images obtained. Flushing efficiency was found to increase with increases in flow rate and duration. Calculations of lumen area using different flushing media were significantly different, varying up to 23% (p < 0.0001). This error was eliminated with careful refractive index calibration. Flushing media viscosity, flow rate, and flush duration influence the efficiency of blood displacement necessary for obtaining diagnostic quality OFDI images. For patients with sensitivity to contrast, to reduce the risk of contrast induced nephrotoxicity we recommend that intracoronary OFDI be conducted with flushing solutions containing little or no radiographic contrast. In addition, our findings show that careful refractive index compensation should be
NASA Astrophysics Data System (ADS)
Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta
2016-06-01
With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.
NASA Astrophysics Data System (ADS)
Arakawa, Masahiro; Fuyuki, Masahiko; Inoue, Ichiro
Aiming at the elimination of tardy jobs in a job shop production schedule, an optimization-oriented simulation-based scheduling (OSBS) method incorporating capacity adjustment function is proposed. In order to determine the pertinent additional capacities and to control job allocations simultaneously the proposed method incorporates the parameter-space search improvement (PSSI) method into the scheduling procedure. In previous papers, we have introduced four parameters; two of them are used to control the upper limit to the additional capacity and the balance of the capacity distribution among machines, while the others are used to control the job allocation procedure. We found that a ‘direct' optimization procedure which uses the enumeration method produces a best solution with practical significance, but it takes too much computation time for practical use. In this paper, we propose a new method which adopts a pattern search method in the schedule generation procedure to obtain an approximate optimal solution. It is found that the computation time becomes short enough for a practical use. Moreover, the extension of the parameter domain yields an approximate optimal solution which is better than the best solution obtained by the ‘direct' optimization.
Eroshenko, V.A.; Kirillov, G.A.; Mochalov, M.R.; Shemyakin, V.I.; Shurygin, V.K.
1981-09-01
A theoretical basis is given for the optimization of the parameters of an iodine switch. The results are reported of an experimental study of the pressure dependence of the width of the absorption line of atomic iodine. The broadening coefficient of molecular iodine is 3.2 MHz/Torr in the temperature range 800--1000 /sup 0/C.
NASA Astrophysics Data System (ADS)
Shirazi, Masoud Jahromi; Vatankhah, Ramin; Boroushaki, Mehrdad; Salarieh, Hassan; Alasty, Aria
2012-02-01
In this paper, particle swarm optimization (PSO) is applied to synchronize chaotic systems in presence of parameter uncertainties and measurement noise. Particle swarm optimization is an evolutionary algorithm which is introduced by Kennedy and Eberhart. This algorithm is inspired by birds flocking. Optimization algorithms can be applied to control by defining an appropriate cost function that guarantees stability of system. In presence of environment noise and parameter uncertainty, robustness plays a crucial role in succeed of controller. Since PSO needs only rudimentary information about the system, it can be a suitable algorithm for this case. Simulation results confirm that the proposed controller can handle the uncertainty and environment noise without any extra information about them. A comparison with some earlier works is performed during simulations.
NASA Astrophysics Data System (ADS)
Widesott, L.; Strigari, L.; Pressello, M. C.; Benassi, M.; Landoni, V.
2008-03-01
We investigated the role and the weight of the parameters involved in the intensity modulated radiation therapy (IMRT) optimization based on the generalized equivalent uniform dose (gEUD) method, for prostate and head-and-neck plans. We systematically varied the parameters (gEUDmax and weight) involved in the gEUD-based optimization of rectal wall and parotid glands. We found that the proper value of weight factor, still guaranteeing planning treatment volumes coverage, produced similar organs at risks dose-volume (DV) histograms for different gEUDmax with fixed a = 1. Most of all, we formulated a simple relation that links the reference gEUDmax and the associated weight factor. As secondary objective, we evaluated plans obtained with the gEUD-based optimization and ones based on DV criteria, using the normal tissue complication probability (NTCP) models. gEUD criteria seemed to improve sparing of rectum and parotid glands with respect to DV-based optimization: the mean dose, the V40 and V50 values to the rectal wall were decreased of about 10%, the mean dose to parotids decreased of about 20-30%. But more than the OARs sparing, we underlined the halving of the OARs optimization time with the implementation of the gEUD-based cost function. Using NTCP models we enhanced differences between the two optimization criteria for parotid glands, but no for rectum wall.
Tomlinson, E.J.; Barber, Z.H.; Morris, G.W.; Somekh, R.E.; Evetts, J.E.
1989-03-01
The authors report on the deposition of Yba/sub 2/Cu/sub 3/O/sub 7/ thin films onto epitaxial magnesia coated single crystal sapphire substrates at deposition temperatures in the range 600/sup 0/-850/sup 0/C. Using a UHV dc magnetron sputter deposition system with both composite metal and ceramic oxide targets, the dependence of film composition on sputtering parameters has been investigated. Films deposited onto epitaxial magnesia are compared with those deposited directly onto sapphire and yttria stabilized zirconia (YSZ).
Optimization of Transparent Conducting ZnO Films Deposited on PVC Substrate by PLD Method
NASA Astrophysics Data System (ADS)
Maeda, Tsuyoshi; Agura, Hideaki; Aoki, Takanori; Suzuki, Akio; Matsushita, Tatsuhiko; Okuda, Masahiro
Approximately 300 nm-thick Al-doped transparent conducting zinc oxide films (AZO(Al2O3:1.5 wt.%)) have been deposited on glass and PVC substrates by a pulsed laser deposition (PLD) using ArF excimer laser (λ=193 nm) with energy of 40-100 mJ at the repetition frequency of 50 Hz. When fabricated with the laser energy of 40-100 mJ, similar characteristics of electrical properties and optical transmittance were obtained for the AZO films deposited on glass or PVC substrates. Namely, the lowest resistivity obtained was 6.34×10-4Ω·cm and an average optical transmittance was more than 80 % in the visible range. But, when prepared with the laser energy of 80-100 mJ, surface roughness for the AZO films fabricated on PVC substrates decreased compared to the films deposited on glass substrates. Moreover, for the AZO films fabricated on PVC substrates, an average optical transmittance in the visible range was reduced to 30-50 %.
NASA Astrophysics Data System (ADS)
Aristovich, K. Y.; Khan, S. H.; Borovkov, A. I.
2011-08-01
This paper presents an investigation of optimal parameters for finite element (FE) solution of the forward problem in magnetic field tomography (MFT) brain imaging based on magnetoencephalography (MEG). It highlights detailed analyses of the main parameters involved and evaluates their optimal values for various cases of FE model solutions (e.g., steady-state, transient, etc.). In each case, a detail study of some of the main parameters and their effects on FE solution and its accuracy are carefully tested and evaluated. These parameters include: total number and size of 3D FE elements used, number and size of elements used in surface discretisation (of both white and grey matters of the brain), number and size of elements used for approximation of current sources, number of anisotropic properties used in steady-state and transient solutions, and the time steps used in transient analyses. The optimal values of these parameters in relation to solution accuracy and mesh convergence criteria have been found and presented.
NASA Astrophysics Data System (ADS)
Bharti, P. K.; Khan, M. I.; Singh, Harbinder
2010-10-01
Off-line quality control is considered to be an effective approach to improve product quality at a relatively low cost. The Taguchi method is one of the conventional approaches for this purpose. Through this approach, engineers can determine a feasible combination of design parameters such that the variability of a product's response can be reduced and the mean is close to the desired target. The traditional Taguchi method was focused on ensuring good performance at the parameter design stage with one quality characteristic, but most products and processes have multiple quality characteristics. The optimal parameter design minimizes the total quality loss for multiple quality characteristics. Several studies have presented approaches addressing multiple quality characteristics. Most of these papers were concerned with maximizing the parameter combination of signal to noise (SN) ratios. The results reveal the advantages of this approach are that the optimal parameter design is the same as the traditional Taguchi method for the single quality characteristic; the optimal design maximizes the amount of reduction of total quality loss for multiple quality characteristics. This paper presents a literature review on solving multi-response problems in the Taguchi method and its successful implementation in various industries.
Ngo, Viet V; Michel, Julien; Gujisaite, Valérie; Latifi, Abderrazak; Simonnot, Marie-Odile
2014-03-01
The soil and groundwater at former industrial sites polluted by polycyclic aromatic hydrocarbons (PAHs) produce a very challenging environmental issue. The description of PAH transport by means of mathematical models is therefore needed for risk assessment and remediation strategies at these sites. Due to the complexity of release kinetics and transport behavior of the PAHs in the aged contaminated soils, their transport is usually evaluated at the laboratory scale. Transport parameters are then estimated from the experimental data via the inverse method. To better assess the uncertainty of optimized parameters, an estimability method was applied to firstly investigate the information content of experimental data and the possible correlations among parameters in the two-site sorption model. These works were based on the concentrations of three PAHs, Acenaphthene (ACE), Fluoranthene (FLA) and Pyrene (PYR), in the leaching solutions of the experiments under saturated and unsaturated flow conditions. The estimability results showed that the experiment under unsaturated flow conditions contained more information content for estimating four transport parameters than under the saturated one. In addition, whatever the experimental conditions for all three PAHs the fraction of sites with instantaneous sorption, f, was highly correlated with the adsorption distribution coefficient, Kd. The very strong correlation between the two parameters f and Kd suggests that they should not be simultaneously calibrated. Transport parameters were optimized using HYDRUS-1D software with different scenarios based on the estimability analysis results. The optimization results were not always reliable, especially in the case of the experiment under saturated flow conditions because of its low information content. In addition, the estimation of transport parameters became very uncertain if two parameters f and Kd were optimized simultaneously. The findings of the current work can suggest some
NASA Astrophysics Data System (ADS)
Enescu (Balaş, M. L.; Alexandru, C.
2016-08-01
The paper deals with the optimal design of the control system for a 6-DOF robot used in thin layers deposition. The optimization is based on parametric technique, by modelling the design objective as a numerical function, and then establishing the optimal values of the design variables so that to minimize the objective function. The robotic system is a mechatronic product, which integrates the mechanical device and the controlled operating device.The mechanical device of the robot was designed in the CAD (Computer Aided Design) software CATIA, the 3D-model being then transferred to the MBS (Multi-Body Systems) environment ADAMS/View. The control system was developed in the concurrent engineering concept, through the integration with the MBS mechanical model, by using the DFC (Design for Control) software solution EASY5. The necessary angular motions in the six joints of the robot, in order to obtain the imposed trajectory of the end-effector, have been established by performing the inverse kinematic analysis. The positioning error in each joint of the robot is used as design objective, the optimization goal being to minimize the root mean square during simulation, which is a measure of the magnitude of the positioning error varying quantity.
NASA Astrophysics Data System (ADS)
Gulik, Volodymyr; Tkaczyk, Alan Henry
2014-06-01
An optimization study of a subcritical two-zone homogeneous reactor was carried out, taking into consideration geometry, material, and economic parameters. The advantage of a two-zone subcritical system over a single-zone system is demonstrated. The study investigated the optimal volume ratio for the inner and outer zones of the subcritical reactor, in terms of the neutron-physical parameters as well as fuel cost. Optimal geometrical parameters of the system are suggested for different material compositions.
NASA Astrophysics Data System (ADS)
Dasgupta, S.; Mukherjee, S.
2016-09-01
One of the most significant factors in metal cutting is tool life. In this research work, the effects of machining parameters on tool under wet machining environment were studied. Tool life characteristics of brazed carbide cutting tool machined against mild steel and optimization of machining parameters based on Taguchi design of experiments were examined. The experiments were conducted using three factors, spindle speed, feed rate and depth of cut each having three levels. Nine experiments were performed on a high speed semi-automatic precision central lathe. ANOVA was used to determine the level of importance of the machining parameters on tool life. The optimum machining parameter combination was obtained by the analysis of S/N ratio. A mathematical model based on multiple regression analysis was developed to predict the tool life. Taguchi's orthogonal array analysis revealed the optimal combination of parameters at lower levels of spindle speed, feed rate and depth of cut which are 550 rpm, 0.2 mm/rev and 0.5mm respectively. The Main Effects plot reiterated the same. The variation of tool life with different process parameters has been plotted. Feed rate has the most significant effect on tool life followed by spindle speed and depth of cut.
NASA Astrophysics Data System (ADS)
Rings, J.; Kamai, T.; Mollaei Kandelous, M.; Nasta, P.; Vrugt, J. A.; Hartsough, P. C.; Hopmans, J. W.
2011-12-01
We use statistical optimization with a hydrologic model to obtain the van Genuchten parameters of a large White Fir tree in a mid-latitude montane forest ecosystem, located in the King's River Experimental Watershed as part of the Southern Sierra Critical Zone Observatory. The site is instrumented for spatially distributed monitoring of soil water content, matric potential and sap flux. The physical tree is represented in a HYDRUS model that models the interactions betweens soil, tree and atmosphere as a continuum. The soil and tree domains are modeled as variably saturated porous media, while atmospheric forcing taken from a nearby flux tower is used to determine the potential evapotranspiration (ET) and root uptake (RU). Actual ET and RU are modeled by accounting for canopy and root distributions together with matric potential stress in the soil-tree domains. This model is embedded within a Markov Chain Monte Carlo (MCMC) framework using current versions of the DREAM_ZS optimization code. We present results of the parameter optimization for time periods in different seasons, analyze the uncertainty and information content in the different measurement methods and use the optimized parameters to study the influence of soil water stress on the soil-root-tree system.
Bhoite, Roopali N; Navya, P N; Murthy, Pushpa S
2013-01-01
Gallic acid (3,4,5-trihydroxybenzoic acid) was produced by microbial biotransformation of coffee pulp tannins by Penicillium verrucosum. Gallic acid production was optimized using response surface methodology (RSM) based on central composite rotatable design. Process parameters such as pH, moisture, and fermentation period were considered for optimization. Among the various fungi isolated from coffee by-products, Penicillium verrucosum produced 35.23 µg/g of gallic acid on coffee pulp as sole carbon source in solid-state fermentation. The optimum values of the parameters obtained from the RSM were pH 3.32, moisture 58.40%, and fermentation period of 96 hr. Gallic acid production with an increase of 4.6-fold was achieved upon optimization of the process parameters. The results optimized could be translated to 1-kg tray fermentation. High-performance liquid chromatography (HPLC) analysis and spectral studies such as mass spectroscopy (MS) and (1)H-nuclear magnetic resonance (NMR) confirmed that the bioactive compound isolated was gallic acid. Thus, coffee pulp, which is available in enormous quantity, could be used for the production of value-added products that can find avenues in food, pharmaceutical, and chemical industries.
NASA Astrophysics Data System (ADS)
Ai, Yuewei; Shao, Xinyu; Jiang, Ping; Li, Peigen; Liu, Yang; Yue, Chen
2015-11-01
The welded joints of dissimilar materials have been widely used in automotive, ship and space industries. The joint quality is often evaluated by weld seam geometry, microstructures and mechanical properties. To obtain the desired weld seam geometry and improve the quality of welded joints, this paper proposes a process modeling and parameter optimization method to obtain the weld seam with minimum width and desired depth of penetration for laser butt welding of dissimilar materials. During the process, Taguchi experiments are conducted on the laser welding of the low carbon steel (Q235) and stainless steel (SUS301L-HT). The experimental results are used to develop the radial basis function neural network model, and the process parameters are optimized by genetic algorithm. The proposed method is validated by a confirmation experiment. Simultaneously, the microstructures and mechanical properties of the weld seam generated from optimal process parameters are further studied by optical microscopy and tensile strength test. Compared with the unoptimized weld seam, the welding defects are eliminated in the optimized weld seam and the mechanical properties are improved. The results show that the proposed method is effective and reliable for improving the quality of welded joints in practical production.
Optimization and Analysis of Laser Beam Machining Parameters for Al7075-TiB2 In-situ Composite
NASA Astrophysics Data System (ADS)
Manjoth, S.; Keshavamurthy, R.; Pradeep Kumar, G. S.
2016-09-01
The paper focuses on laser beam machining (LBM) of In-situ synthesized Al7075-TiB2 metal matrix composite. Optimization and influence of laser machining process parameters on surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy of composites were studied. Al7075-TiB2 metal matrix composite was synthesized by in-situ reaction technique using stir casting process. Taguchi's L9 orthogonal array was used to design experimental trials. Standoff distance (SOD) (0.3 - 0.5mm), Cutting Speed (1000 - 1200