NASA Astrophysics Data System (ADS)
Mahamood, Rasheedat M.; Akinlabi, Esther T.
2016-03-01
Ti6Al4V is an important Titanium alloy that is mostly used in many applications such as: aerospace, petrochemical and medicine. The excellent corrosion resistance property, the high strength to weight ratio and the retention of properties at high temperature makes them to be favoured in most applications. The high cost of Titanium and its alloys makes their use to be prohibitive in some applications. Ti6Al4V can be cladded on a less expensive material such as steel, thereby reducing cost and providing excellent properties. Laser Metal Deposition (LMD) process, an additive manufacturing process is capable of producing complex part directly from the 3-D CAD model of the part and it also has the capability of handling multiple materials. Processing parameters play an important role in LMD process and in order to achieve desired results at a minimum cost, then the processing parameters need to be properly controlled. This paper investigates the role of processing parameters: laser power, scanning speed, powder flow rate and gas flow rate, on the material utilization efficiency in laser metal deposited Ti6Al4V. A two-level full factorial design of experiment was used in this investigation, to be able to understand the processing parameters that are most significant as well as the interactions among these processing parameters. Four process parameters were used, each with upper and lower settings which results in a combination of sixteen experiments. The laser power settings used was 1.8 and 3 kW, the scanning speed was 0.05 and 0.1 m/s, the powder flow rate was 2 and 4 g/min and the gas flow rate was 2 and 4 l/min. The experiments were designed and analyzed using Design Expert 8 software. The software was used to generate the optimized process parameters which were found to be laser power of 3.2 kW, scanning speed of 0.06 m/s, powder flow rate of 2 g/min and gas flow rate of 3 l/min.
NASA Astrophysics Data System (ADS)
Zhang, Tao; Liu, Xuan; Sun, Fanghong; Zhang, Zhiming
2015-09-01
In the present work, microcrystalline diamond powders are deposited by using a bias-enhanced hot filament chemical vapor deposition (HFCVD) apparatus. Mirror-polished silicon wafers are served as substrates, pretreated by the scratching process for 10-15 s. A systematic investigation is under taken into the combined effects of deposition parameters on nucleation and growth characteristics of microcrystalline diamonds, based on the orthogonal collocation method. The results show that the morphology of final microcrystals depend mainly on that of nuclei rather than the deposition parameters, while the quality and grain size of crystals largely depend upon the deposition parameters. A high reactor pressure (3-4.5 kPa) in the nucleation process is a necessary condition for depositing the ideal nuclei with the single-crystal structure and euhedral diamond faces. Then under a set of optimized growth parameters, the final single crystals exhibit the regular-shaped morphology and smooth surfaces. The CVD microcrystals with various grain sizes in the range of 0.3-2 μm can be obtained by regulating the deposition time; moreover, they have a dramatically narrow particle size distribution, meeting the requirements on certain types of commercial powders without the process of sieving grain.
NASA Astrophysics Data System (ADS)
Kuai, Su-Lan; Hu, Xing-Fang; Haché, Alain; Truong, Vo-Van
2004-06-01
High-quality polystyrene colloidal crystals were fabricated from aqueous solutions with a vertical deposition technique. The role of sphere size, volume fraction, relative humidity (RH), evaporation temperature and the final drying conditions on the film quality were investigated. We found that all those parameters must be taken into account in order to achieve highest quality for a given particle size. With particles of 300 nm in diameter, the optimal conditions were found to be a 0.1-0.2% volume fraction, an RH between 80% and 90%, an evaporation temperature near 60°C and a quasi-equilibrium drying process.
Guo, Qing-Lin; Cui, Yong-Liang; Chen, Jian-Hui; Zhang, Jin-Ping; Huai, Su-Fang; Liu, Bao-Ting; Chen, Jin-Zhong
2010-12-01
The plasma emission spectra generated during the deposition process of Si-based thin films by radio frequency (RF) magnetron sputtering using Cu and Al targets in an argon atmosphere were acquired by the plasma analysis system, which consists of a magnetron sputtering apparatus, an Omni-lambda300 series grating spectrometer, a CCD data acquisition system and an optical fiber transmission system. The variation in Cu and Al plasma emission spectra intensity depending on sputtering conditions, such as sputtering time, sputtering power, the target-to-substrate distance and deposition pressure, was studied by using the analysis lines Cu I 324. 754 nm, Cu I 327. 396 nm, Cu I 333. 784 nm, Cu I 353. 039 nm, Al I 394. 403 nm and Al I 396. 153 nm. Compared with the option of experimental parameters of thin films deposited by RF magnetron sputtering, it was shown that emission spectra analysis methods play a guiding role in optimizing the deposition conditions of thin films in RF magnetron sputtering.
NASA Astrophysics Data System (ADS)
Wang, Xinchang; Shen, Xiaotian; Sun, Fanghong; Shen, Bin
2016-12-01
Chemical vapor deposition (CVD) diamond films have been widely applied as protective coatings on varieties of anti-frictional and wear-resistant components, owing to their excellent mechanical and tribological properties close to the natural diamond. In applications of some components, the inner hole surface will serve as the working surface that suffers severe frictional or erosive wear. It is difficult to realize uniform depositions of diamond films on surfaces of inner holes, especially ultra-large inner holes. Adopting a SiC compact die with an aperture of V80 mm as an example, a novel filament arrangement with a certain number of filaments evenly distributed on a circle is designed, and specific effects of filament parameters, including the filament number, arrangement direction, filament temperature, filament diameter, circumradius and the downward translation, on the substrate temperature distribution are studied by computational fluid dynamics (CFD) simulations based on the finite volume method (FVM), adopting a modified computational model well consistent with the actual deposition environment. Corresponding temperature measurement experiments are also conducted to verify the rationality of the computational model. From the aspect of depositing uniform boron-doped micro-crystalline, undoped micro-crystalline and undoped fine-grained composite diamond (BDM-UMC-UFGCD) film on such the inner hole surface, filament parameters as mentioned above are accurately optimized and compensated by orthogonal simulations. Moreover, deposition experiments adopting compensated optimized parameters and some typical contrastive parameters are also accomplished for further verifying the rationality of the computational model and the correctness of the compensation coefficient 0.7 defined for the downward translation determined by simulations. More importantly, on the basis of more simulations and verification tests, a general filament arrangement model suitable for V50-120 mm
Optimization of exchange bias in Co/CoO magnetic nanocaps by tuning deposition parameters
NASA Astrophysics Data System (ADS)
Sharma, A.; Tripathi, J.; Ugochukwu, K. C.; Tripathi, S.
2017-03-01
In the present work, we report exchange bias tuning by varying thin film deposition parameters such as synthesis method and underlying layer patterning. The patterned substrates for this study were prepared by self-assembly of polystyrene (PS) latex spheres ( 530 nm) on Si (100) substrate. The desired magnetic nanocaps composed of CoO/Co bilayer film on these patterned substrates were prepared by molecular beam epitaxy technique under ultra-high vacuum conditions. For this, a Co layer of 10 nm thickness was deposited on the substrates and then oxidized in-situ to form CoO/Co/PS in-situ oxidized film or ex-situ in ambiance which also gives CoO/Co/PS naturally oxidized film. Simultaneously, reference thin films of Co ( 10 nm) were also prepared on plane Si substrate and similar oxidation treatments were performed on them respectively. The magnetic properties studied using SQUID technique revealed higher exchange bias ( 1736 Oe) in the in-situ oxidized Co/PS film as compared to that in naturally oxidized Co/PS film ( 1544 Oe) and also compared to the reference film. The observed variations in the magnetic properties are explained in terms of surface patterning induced structural changes of the deposited films and different oxidation methods.
Dasgupta, K; Sen, D; Mazumder, S; Basak, C B; Joshi, J B; Banerjee, S
2010-06-01
The process parameters (viz. temperature of synthesis, type of catalyst, concentration of catalyst and type of catalyst-support material) for controlling purity of carbon nanotubes synthesized by catalytic chemical vapour deposition of acetylene have been optimized by analyzing the experimental results using Taguchi method. It has been observed that the catalyst-support material has the maximum (59.4%) and the temperature of synthesis has the minimum effect (2.1%) on purity of the nanotubes. At optimum condition (15% ferrocene supported on carbon black at the synthesis temperature of 700 degrees C) the purity of nanotubes was found out to be 96.2% with yield of 1900%. Thermogravimetry has been used to assess purity of nanotubes. These nantubes have been further characterized by scanning electron microscopy, transmission electron microscopy and Raman Spectroscopy. Small angle neutron scattering has been used to find out their average inner and outer diameter using an appropriate model. The nanotubes are well crystallized but with wide range of diameter varying between 20-150 nm.
NASA Astrophysics Data System (ADS)
Gupta, Manisha; Chowdhury, Fatema Rezwana; Barlage, Douglas; Tsui, Ying Yin
2013-03-01
In this work we present the optimization of zinc oxide (ZnO) film properties for a thin-film transistor (TFT) application. Thin films, 50±10 nm, of ZnO were deposited by Pulsed Laser Deposition (PLD) under a variety of growth conditions. The oxygen pressure, laser fluence, substrate temperature and annealing conditions were varied as a part of this study. Mobility and carrier concentration were the focus of the optimization. While room-temperature ZnO growths followed by air and oxygen annealing showed improvement in the (002) phase formation with a carrier concentration in the order of 1017-1018/cm3 with low mobility in the range of 0.01-0.1 cm2/V s, a Hall mobility of 8 cm2/V s and a carrier concentration of 5×1014/cm3 have been achieved on a relatively low temperature growth (250 °C) of ZnO. The low carrier concentration indicates that the number of defects have been reduced by a magnitude of nearly a 1000 as compared to the room-temperature annealed growths. Also, it was very clearly seen that for the (002) oriented films of ZnO a high mobility film is achieved.
Computer program for parameter optimization
NASA Technical Reports Server (NTRS)
Glatt, C. R.; Hague, D. S.
1968-01-01
Flexible, large scale digital computer program was designed for the solution of a wide range of multivariable parameter optimization problems. The program has the ability to solve constrained optimization problems involving up to one hundred parameters.
The Sequential Parameter Optimization Toolbox
NASA Astrophysics Data System (ADS)
Bartz-Beielstein, Thomas; Lasarczyk, Christian; Preuss, Mike
The sequential parameter optimization toolbox (SPOT) is one possible implementation of the SPO framework introduced in Chap. 2. It has been successfully applied to numerous heuristics for practical and theoretical optimization problems. We describe the mechanics and interfaces employed by SPOT to enable users to plug in their own algorithms. Furthermore, two case studies are presented to demonstrate how SPOT can be applied in practice, followed by a discussion of alternative metamodels to be plugged into it.We conclude with some general guidelines.
Optimization for minimum sensitivity to uncertain parameters
NASA Technical Reports Server (NTRS)
Pritchard, Jocelyn I.; Adelman, Howard M.; Sobieszczanski-Sobieski, Jaroslaw
1994-01-01
A procedure to design a structure for minimum sensitivity to uncertainties in problem parameters is described. The approach is to minimize directly the sensitivity derivatives of the optimum design with respect to fixed design parameters using a nested optimization procedure. The procedure is demonstrated for the design of a bimetallic beam for minimum weight with insensitivity to uncertainties in structural properties. The beam is modeled with finite elements based on two dimensional beam analysis. A sequential quadratic programming procedure used as the optimizer supplies the Lagrange multipliers that are used to calculate the optimum sensitivity derivatives. The method was perceived to be successful from comparisons of the optimization results with parametric studies.
Optimization of chemical bath deposited cadmium sulfide thin films
Oladeji, I.O.; Chow, L.
1997-07-01
Cadmium sulfide (CdS) is known to be an excellent heterojunction partner of p-type cadmium telluride (CdTe) or p-type copper indium diselenide (CuInSe{sub 2}) due essentially to its high electron affinity. It is widely used as a window material in high efficiency thin-film solar cells based on CdTe or CuInSe{sub 2} owing to its transparency and photoconductivity among other properties. The authors report the optimization of CdS thin film grown by chemical bath deposition where homogeneous reactions are minimized. The optimum parameters have enabled them to maximize the thickness of the deposited film in a single dip and to grow thicker films by periodically replenishing the concentration of reactants while the substrate remains continuously dipped in the reaction bath. Characterization results reveal the deposited CdS films exhibit improved optical and electrical properties.
Optimal design criteria - prediction vs. parameter estimation
NASA Astrophysics Data System (ADS)
Waldl, Helmut
2014-05-01
G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.
Cosmological parameter estimation using Particle Swarm Optimization
NASA Astrophysics Data System (ADS)
Prasad, J.; Souradeep, T.
2014-03-01
Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.
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.
Taguchi Method Applied in Optimization of Shipley SJR 5740 Positive Resist Deposition
NASA Technical Reports Server (NTRS)
Hui, A.; Blosiu, J. O.; Wiberg, D. V.
1998-01-01
Taguchi Methods of Robust Design presents a way to optimize output process performance through an organized set of experiments by using orthogonal arrays. Analysis of variance and signal-to-noise ratio is used to evaluate the contribution of each of the process controllable parameters in the realization of the process optimization. In the photoresist deposition process, there are numerous controllable parameters that can affect the surface quality and thickness of the final photoresist layer.
Optimal filtration of the atmospheric parameters profiles
NASA Technical Reports Server (NTRS)
Zuev, V. E.; Glazov, G. N.; Igonin, G. M.
1986-01-01
The idea of optimal Marcovian filtration of fluctuating profiles from lidar signals is developed but as applied to a double-frequency sounding which allows the use of large cross sections of elastic scattering and correct separation of the contributions due to aerosol and Rayleigh scatterings from the total lidar return. The filtration efficiency is shown under different conditions of sounding using a computer model. The accuracy of restituted profiles (temperature, pressure, density) is determined by the elements of a posteriori matrix K. The results obtained allow the determination of the lidar power required for providing the necessary accuracy of restitution of the atmospheric parameter profiles at chosen wavelengths of sounding in the ultraviolet and visible range.
Optimal diabatic states based on solvation parameters
NASA Astrophysics Data System (ADS)
Alguire, Ethan; Subotnik, Joseph E.
2012-11-01
A new method for obtaining diabatic electronic states of a molecular system in a condensed environment is proposed and evaluated. This technique, which we denote as Edmiston-Ruedenberg (ER)-ɛ diabatization, forms diabatic states as a linear combination of adiabatic states by minimizing an approximation to the total coupling between states in a medium with temperature T and with a characteristic Pekar factor C. ER-ɛ diabatization represents an improvement upon previous localized diabatization methods for two reasons: first, it is sensitive to the energy separation between adiabatic states, thus accounting for fluctuations in energy and effectively preventing over-mixing. Second, it responds to the strength of system-solvent interactions via parameters for the dielectric constant and temperature of the medium, which is physically reasonable. Here, we apply the ER-ɛ technique to both intramolecular and intermolecular excitation energy transfer systems. We find that ER-ɛ diabatic states satisfy three important properties: (1) they have small derivative couplings everywhere; (2) they have small diabatic couplings at avoided crossings, and (3) they have negligible diabatic couplings everywhere else. As such, ER-ɛ states are good candidates for so-called "optimal diabatic states."
Alternative Weights and Invariant Parameters in Optimal Scaling.
ERIC Educational Resources Information Center
McDonald, Roderick P.
1983-01-01
Under conditions commonly met in optimal scaling problems, arbitrary sets of optimal weights can be obtained by choices of generalized universe scores. It is suggested that the invariant parameters of optimal scaling should be interpreted according to latent trait theory, rather than the arbitrary weights. (Author/JKS)
Laboratory measurements of parameters affecting wet deposition of methyl iodide
Maeck, W.J.; Honkus, R.J.; Keller, J.H.; Voilleque, P.G.
1984-09-01
The transfer of gaseous methyl iodide (CH/sub 3/I) to raindrops and the initial retention by vegetation of CH/sub 3/I in raindrops have been studied in a laboratory experimental program. The measured air-to-drop transfer parameters and initial retention factors both affect the wet deposition of methyl iodide onto vegetation. No large effects on the air-to-drop transfer due to methyl iodide concentration, temperature, acidity, or rain type were observed. Differences between laboratory measurements and theoretical values of the mass transfer coefficient were found. Pasture grass, lettuce, and alfalfa were used to study the initial retention of methyl iodide by vegetation. Only a small fraction of the incident CH/sub 3/I in raindrops was held by any of the three vegetation types.
Optimization of Milling Parameters Employing Desirability Functions
NASA Astrophysics Data System (ADS)
Ribeiro, J. L. S.; Rubio, J. C. Campos; Abrão, A. M.
2011-01-01
The principal aim of this paper is to investigate the influence of tool material (one cermet and two coated carbide grades), cutting speed and feed rate on the machinability of hardened AISI H13 hot work steel, in order to identify the cutting conditions which lead to optimal performance. A multiple response optimization procedure based on tool life, surface roughness, milling forces and the machining time (required to produce a sample cavity) was employed. The results indicated that the TiCN-TiN coated carbide and cermet presented similar results concerning the global optimum values for cutting speed and feed rate per tooth, outperforming the TiN-TiCN-Al2O3 coated carbide tool.
Machine Self-Teaching Methods for Parameter Optimization.
1986-12-01
A199 285 MACHINE SELF- TEACHING METHODS FOR PARAMETER / OPTIMIZATION(U) NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA R A DILLARD DEC 86 NOSC/TR-1S39...Technical Document 1039 C) ,December 1986 Machine Self- Teaching Methods for Parameter Optimization Robin A. Dillard DTICS ELECTE MAY i01 STAra Approved...ELEMEWt NO PROECi’ No TASK NO ARC Locally FundedI I1 I TE (ewd* Seawmy Cft*Wi., Machine Self- Teaching Methods for Parameter Optimization it PERSONAL
Optimal parameters of leader development in lightning
NASA Technical Reports Server (NTRS)
Petrov, N. I.; Petrova, G. N.
1991-01-01
The dependences between the different parameters of a leader in lightning are obtained theoretically. The physical mechanism of the instability leading to the formation of the streamer zone is proposed. The instability has the wave nature and is caused by the self-influence effects of the space charge. Using a stability condition of the leader propagation, a dependence is obtained between the current across the leader head and its velocity of motion. The dependence of the streamer zone length on the gap length is also obtained. It is shown that the streamer zone length is saturated with the increasing of the gap length. A comparison between the obtained dependences and the experimental data is presented.
Quantum Tunneling Parameter in Global Optimization
NASA Astrophysics Data System (ADS)
Itami, Teturo
Quantum tunneling that helps particles escape from local minima has been applied in “quantum annealing” method to global optimization of nonlinear functions. To control size of kinetic energy of quantum particles, we form a “quantum tunneling parameter” QT≡m/HR2, where HR corresponds to a physical constant h, Planck's constant divided by 2π, that determines the lowest eigenvalue of quantum particles with mass m. Assumptions on profiles of the function V(x) around its minimum point x0, harmonic oscillator type and square well type, make us possible to write down analytical formulae of the kinetic energy K in terms of QT. The formulae tell that we can make quantum expectation value of particle coordinates x approximate to the minimum point x0 in QT→∞. For systems where we have almost degenerate eigenvalues, examination working with our QT, that x→x0 in QT→∞, is analytically shown also efficient. Similar results that x→x0 under QT→∞ are also obtained when we utilize random-walk quantum Monte Carlo method to represent tunneling phenomena according to conventional quantum annealing.
Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor
Ye, Lin; Yang, Ming; Xu, Liang; Zhuang, Xiaoqi; Dong, Zhaopeng; Li, Shiyang
2014-01-01
Using the finite element method (FEM) and particle swarm optimization (PSO), a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters' effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°. PMID:24590353
Optimized LOWESS normalization parameter selection for DNA microarray data
Berger, John A; Hautaniemi, Sampsa; Järvinen, Anna-Kaarina; Edgren, Henrik; Mitra, Sanjit K; Astola, Jaakko
2004-01-01
Background Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail. Results and discussion In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies. Conclusions Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical
Optimization of Nanostructuring Burnishing Technological Parameters by Taguchi Method
NASA Astrophysics Data System (ADS)
Kuznetsov, V. P.; Dmitriev, A. I.; Anisimova, G. S.; Semenova, Yu V.
2016-04-01
On the basis of application of Taguchi optimization method, an approach for researching influence of nanostructuring burnishing technological parameters, considering the surface layer microhardness criterion, is developed. Optimal values of burnishing force, feed and number of tool passes for hardened steel AISI 420 hardening treatment are defined.
Optimization of NLC machine parameters for specific physics processes
Thompson, Kathleen A
1999-10-11
We examine the optimization of NLC parameters at 500, 1000, and 1500 GeV c.m. energy for specific classes of physics processes, in particular, top and stop pair production, and W-W scattering processes. Our focus is on optimizing the luminosity spectrum, while maintaining or improving machine operability.
Optimization of Uranium Molecular Deposition for Alpha-Counting Sources
Monzo, Ellen; Parsons-Moss, Tashi; Genetti, Victoria; Knight, Kimberly
2016-12-12
Method development for molecular deposition of uranium onto aluminum 1100 plates was conducted with custom plating cells at Lawrence Livermore National Laboratory. The method development focused primarily on variation of electrode type, which was expected to directly influence plated sample homogeneity. Solid disc platinum and mesh platinum anodes were compared and data revealed that solid disc platinum anodes produced more homogenous uranium oxide films. However, the activity distribution also depended on the orientation of the platinum electrode relative to the aluminum cathode, starting current, and material composition of the plating cell. Experiments demonstrated these variables were difficult to control under the conditions available. Variation of plating parameters among a series of ten deposited plates yielded variations up to 30% in deposition efficiency. Teflon particles were observed on samples plated in Teflon cells, which poses a problem for alpha activity measurements of the plates. Preliminary electropolishing and chemical polishing studies were also conducted on the aluminum 1100 cathode plates.
Parameter optimization in HN-IMRT for Elekta linacs.
Worthy, Danielle; Wu, Qiuwen
2009-04-28
Planning and delivery in HN-IMRT has been challenging for the Elekta linac because of numerous machine limitations. Direct aperture optimization (DAO) algorithms have had success in simplifying the planning process and improving plan quality. Commercial adaptations of DAO allow for widespread use in many clinics; however clinical validation of these methods is still needed. In this work we evaluated Pinnacle3 commercial software for HN-IMRT on the Elekta linac. The purpose was to find a set of planning parameters that are applicable to most patients and optimal in terms of plan quality, delivery efficiency, and dosimetric accuracy. Four types of plans were created for each of 12 patients: ideal fluence optimization (FO), conventional two-step optimization (TS), segment weight optimization (SW), and direct machine parameter optimization (DMPO). Maximum number of segments (NS) and minimum segment area (MSA) were varied in DMPO. Results showed DMPO plans have the best optimization scores and dosimetric indices, and the most consistent IMRT output among patients. At larger NS (> or = 80), plan quality decreases with increasing MSA as expected, except for MSA<8 cm(2), suggesting presence of local minima in DMPO. Segment area and MUs can vary significantly between optimization methods and parameter settings; however, the quantity 'integral MU' remains constant. Irradiation time is linearly proportional to total plan segments, weakly dependent on MUs and independent of MSA. Dosimetric accuracy is independent of DMPO parameters. The superior quality of DMPO makes it the choice for HN-IMRT on Elekta linacs and its consistency allows development of 'class solutions'. However, planners should be aware of the local minima issue when pushing parameters to the limit such as NS<80 and MSA<8 cm(2). The optimal set of parameters should be chosen to balance plan quality and delivery efficiency based on a systematic evaluation of the planning technique and system constraints.
Parameter optimization toward optimal microneedle-based dermal vaccination.
van der Maaden, Koen; Varypataki, Eleni Maria; Yu, Huixin; Romeijn, Stefan; Jiskoot, Wim; Bouwstra, Joke
2014-11-20
Microneedle-based vaccination has several advantages over vaccination by using conventional hypodermic needles. Microneedles are used to deliver a drug into the skin in a minimally-invasive and potentially pain free manner. Besides, the skin is a potent immune organ that is highly suitable for vaccination. However, there are several factors that influence the penetration ability of the skin by microneedles and the immune responses upon microneedle-based immunization. In this study we assessed several different microneedle arrays for their ability to penetrate ex vivo human skin by using trypan blue and (fluorescently or radioactively labeled) ovalbumin. Next, these different microneedles and several factors, including the dose of ovalbumin, the effect of using an impact-insertion applicator, skin location of microneedle application, and the area of microneedle application, were tested in vivo in mice. The penetration ability and the dose of ovalbumin that is delivered into the skin were shown to be dependent on the use of an applicator and on the microneedle geometry and size of the array. Besides microneedle penetration, the above described factors influenced the immune responses upon microneedle-based vaccination in vivo. It was shown that the ovalbumin-specific antibody responses upon microneedle-based vaccination could be increased up to 12-fold when an impact-insertion applicator was used, up to 8-fold when microneedles were applied over a larger surface area, and up to 36-fold dependent on the location of microneedle application. Therefore, these influencing factors should be considered to optimize microneedle-based dermal immunization technologies.
NASA Astrophysics Data System (ADS)
Nayar, Priyanka; Zhu, Xue-Yi; Yang, Fuyi; Lu, Minghui; Lakshminarayana, G.; Liu, Xiao Ping; Chen, Yan-Feng; Kityk, I. V.
2016-10-01
Erbium doped amorphous alumina thin films were fabricated using Co-sputtering technique in various depositions runs with varying parameters for optimizing the deposition parameters to obtain the films with best optical performance. The main subject of investigation includes the effects of change in various deposition parameters such as substrate heating, radio frequency (RF) power and oxygen pressure inside the chamber while deposition. High quality as-deposited films with various Er concentrations and low carbon content have been confirmed by XPS. Substrate heating ∼500 °C was found to be very effective in getting highly dense films with high refractive index of 1.70 at 1530-1570 nm emission band. The Er3+-doped films showed very intense near-infrared luminescence peak at 1550 nm even without any post-deposition annealing treatment.
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Helical tomotherapy optimized planning parameters for nasopharyngeal cancer
NASA Astrophysics Data System (ADS)
Yawichai, K.; Chitapanarux, I.; Wanwilairat, S.
2016-03-01
Helical TomoTherapy(HT) planning depends on optimize parameters including field width (FW), pitch factor (PF) and modulation factor (MF). These optimize parameters are effect to quality of plans and treatment time. The aim of this study was to find the optimized parameters which compromise between plan quality and treatment times. Six nasopharyngeal cancer patients were used. For each patient data set, 18 treatment plans consisted of different optimize parameters combination (FW=5.0, 2.5, 1.0 cm; PF=0.43, 0.287, 0.215; MF2.0, 3.0) were created. The identical optimization procedure followed ICRU83 recommendations. The average D50 of both parotid glands and treatment times per fraction were compared for all plans. The study show treatment plan with FW1.0 cm showed the lowest average D50 of both parotid glands. The treatment time increased inversely to FW. The FW1.0 cm the average treatment time was 4 times longer than FW5.0 cm. PF was very little influence on the average D50 of both parotid glands. Finally, MF increased from 2.0 to 3.0 the average D50 of both parotid glands was slightly decreased. However, the average treatment time was increased 22.28%. For routine nasopharyngeal cancer patients with HT, we suggest the planning optimization parameters consist of FW=5.0 cm, PF=0.43 and MF=2.0.
Sequential ensemble-based optimal design for parameter estimation
NASA Astrophysics Data System (ADS)
Man, Jun; Zhang, Jiangjiang; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng
2016-10-01
The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.
Parameter extraction of solar cells using particle swarm optimization
NASA Astrophysics Data System (ADS)
Ye, Meiying; Wang, Xiaodong; Xu, Yousheng
2009-05-01
In this article, particle swarm optimization (PSO) was applied to extract the solar cell parameters from illuminated current-voltage characteristics. The performance of the PSO was compared with the genetic algorithms (GAs) for the single and double diode models. Based on synthetic and experimental current-voltage data, it has been confirmed that the proposed method can obtain higher parameter precision with better computational efficiency than the GA method. Compared with conventional gradient-based methods, even without a good initial guess, the PSO method can obtain the parameters of solar cells as close as possible to the practical parameters only based on a broad range specified for each of the parameters.
Optimizing chirped laser pulse parameters for electron acceleration in vacuum
Akhyani, Mina; Jahangiri, Fazel; Niknam, Ali Reza; Massudi, Reza
2015-11-14
Electron dynamics in the field of a chirped linearly polarized laser pulse is investigated. Variations of electron energy gain versus chirp parameter, time duration, and initial phase of laser pulse are studied. Based on maximizing laser pulse asymmetry, a numerical optimization procedure is presented, which leads to the elimination of rapid fluctuations of gain versus the chirp parameter. Instead, a smooth variation is observed that considerably reduces the accuracy required for experimentally adjusting the chirp parameter.
The influence of energy deposition parameters on laser plasma drag reduction
NASA Astrophysics Data System (ADS)
Dou, Zhiguo; Liu, Zhun; Yao, Honglin; Li, Xiuqian
2013-09-01
Laser plasma drag reduction is a new method to reduce the wave drag of hypersonic flight. The research of the laser plasma drag reduction performance is an important work. The purpose of this paper is investigating laser plasma drag reduction by numerical simulation to enhance the understanding of the drag reduction mechanism, get the drag reduction performance in different conditions, and provide references for laser plasma drag reduction experiment in the future. Based on summarizing correlative references systematically, through building the model of energy deposition and comparison the simulated results to the empirical formula and computation results to verify the program correctness, the influence of laser energy parameters to laser plasma drag reduction were simulated numerically for optimize the performance. The follow conclusions were got by numerical simulation: The computation program can well simulate the interacting of LSDW(laser supported detonation wave) to the bow shock in front of the blunt body. Results indicate that the blunt body drag could be decreased by injecting laser energy into the incoming hypersonic flow. The correctness of program was verified by compare result to the experiment and computation results. Blunt body drag will be greatly decreased with injected laser power increased, The bigger laser power is injected, the more drag decreases. There's an energy saturation value for each laser power level, the injecting laser power effectiveness values are never quite high for all laser power level. There is an optimized energy deposition location in upstream flow, this location is right ahead of the blunt body. When the distance from deposition location to the surface of blunt body is 5 times the blunt radius, blunt body drag decreased the most. This paper investigated the parameters which primary influence the performance of drag reduction. The numerical simulation data and obtained results are meaningful for laser plasma drag reduction
In situ growth optimization in focused electron-beam induced deposition
Weirich, Paul M; Winhold, Marcel; Huth, Michael
2013-01-01
Summary We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques. PMID:24367761
In situ growth optimization in focused electron-beam induced deposition.
Weirich, Paul M; Winhold, Marcel; Schwalb, Christian H; Huth, Michael
2013-01-01
We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt-C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques.
Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...
With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th
Optimization of Gas Metal Arc Welding Process Parameters
NASA Astrophysics Data System (ADS)
Kumar, Amit; Khurana, M. K.; Yadav, Pradeep K.
2016-09-01
This study presents the application of Taguchi method combined with grey relational analysis to optimize the process parameters of gas metal arc welding (GMAW) of AISI 1020 carbon steels for multiple quality characteristics (bead width, bead height, weld penetration and heat affected zone). An orthogonal array of L9 has been implemented to fabrication of joints. The experiments have been conducted according to the combination of voltage (V), current (A) and welding speed (Ws). The results revealed that the welding speed is most significant process parameter. By analyzing the grey relational grades, optimal parameters are obtained and significant factors are known using ANOVA analysis. The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions.
Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki
2015-01-01
Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest. PMID:25784880
Finding optimal vaccination strategies under parameter uncertainty using stochastic programming.
Tanner, Matthew W; Sattenspiel, Lisa; Ntaimo, Lewis
2008-10-01
We present a stochastic programming framework for finding the optimal vaccination policy for controlling infectious disease epidemics under parameter uncertainty. Stochastic programming is a popular framework for including the effects of parameter uncertainty in a mathematical optimization model. The problem is initially formulated to find the minimum cost vaccination policy under a chance-constraint. The chance-constraint requires that the probability that R(*)
Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki
2015-01-01
Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.
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.
NASA Astrophysics Data System (ADS)
Jakšić, Nikola
2015-03-01
The optimality of the procedure of parameter identification is scrutinized in this paper. It was shown, with the relations between the mathematical theory of function approximation, three parameter probability distributions, which can adjust their shape, and the maximum-likelihood method, that the optimal expression of the distance between measured data and model fitting it can be established by using the three parameter probability distributions on the basis of iteration procedure, where the noise contained in the measured signal is extracted as well. The iterative method for optimal system/model parameter identification is presented and tested by the numerical experimentation. Four types of noise added to the simple single-degree-of-freedom system response are considered: Gauss, Cauchy, Laplace and Uniform. The method performs well for the noise types at relatively high noise content in the signal.
Concurrently adjusting interrelated control parameters to achieve optimal engine performance
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2015-12-01
Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.
NASA Astrophysics Data System (ADS)
Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.
2016-07-01
In the RF magnetron sputtering process, the desirable layer properties are largely influenced by the process parameters and conditions. If the quality of the thin film has not reached up to its intended level, the experiments have to be repeated until the desirable quality has been met. This research is proposing Gravitational Search Algorithm (GSA) as the optimization model to reduce the time and cost to be spent in the thin film fabrication. The optimization model's engine has been developed using Java. The model is developed based on GSA concept, which is inspired by the Newtonian laws of gravity and motion. In this research, the model is expected to optimize four deposition parameters which are RF power, deposition time, oxygen flow rate and substrate temperature. The results have turned out to be promising and it could be concluded that the performance of the model is satisfying in this parameter optimization problem. Future work could compare GSA with other nature based algorithms and test them with various set of data.
NASA Astrophysics Data System (ADS)
Cai, Lanlan; Li, Peng; Luo, Qi; Zhai, Pengcheng; Zhang, Qingjie
2017-01-01
As no single thermoelectric material has presented a high figure-of-merit (ZT) over a very wide temperature range, segmented thermoelectric generators (STEGs), where the p- and n-legs are formed of different thermoelectric material segments joined in series, have been developed to improve the performance of thermoelectric generators. A crucial but difficult problem in a STEG design is to determine the optimal values of the geometrical parameters, like the relative lengths of each segment and the cross-sectional area ratio of the n- and p-legs. Herein, a multi-parameter and nonlinear optimization method, based on the Improved Powell Algorithm in conjunction with the discrete numerical model, was implemented to solve the STEG's geometrical optimization problem. The multi-parameter optimal results were validated by comparison with the optimal outcomes obtained from the single-parameter optimization method. Finally, the effect of the hot- and cold-junction temperatures on the geometry optimization was investigated. Results show that the optimal geometry parameters for maximizing the specific output power of a STEG are different from those for maximizing the conversion efficiency. Data also suggest that the optimal geometry parameters and the interfacial temperatures of the adjacent segments optimized for maximum specific output power or conversion efficiency vary with changing hot- and cold-junction temperatures. Through the geometry optimization, the CoSb3/Bi2Te3-based STEG can obtain a maximum specific output power up to 1725.3 W/kg and a maximum efficiency of 13.4% when operating at a hot-junction temperature of 823 K and a cold-junction temperature of 298 K.
NASA Astrophysics Data System (ADS)
Cai, Lanlan; Li, Peng; Luo, Qi; Zhai, Pengcheng; Zhang, Qingjie
2017-03-01
As no single thermoelectric material has presented a high figure-of-merit (ZT) over a very wide temperature range, segmented thermoelectric generators (STEGs), where the p- and n-legs are formed of different thermoelectric material segments joined in series, have been developed to improve the performance of thermoelectric generators. A crucial but difficult problem in a STEG design is to determine the optimal values of the geometrical parameters, like the relative lengths of each segment and the cross-sectional area ratio of the n- and p-legs. Herein, a multi-parameter and nonlinear optimization method, based on the Improved Powell Algorithm in conjunction with the discrete numerical model, was implemented to solve the STEG's geometrical optimization problem. The multi-parameter optimal results were validated by comparison with the optimal outcomes obtained from the single-parameter optimization method. Finally, the effect of the hot- and cold-junction temperatures on the geometry optimization was investigated. Results show that the optimal geometry parameters for maximizing the specific output power of a STEG are different from those for maximizing the conversion efficiency. Data also suggest that the optimal geometry parameters and the interfacial temperatures of the adjacent segments optimized for maximum specific output power or conversion efficiency vary with changing hot- and cold-junction temperatures. Through the geometry optimization, the CoSb3/Bi2Te3-based STEG can obtain a maximum specific output power up to 1725.3 W/kg and a maximum efficiency of 13.4% when operating at a hot-junction temperature of 823 K and a cold-junction temperature of 298 K.
Optimal line drop compensation parameters under multi-operating conditions
NASA Astrophysics Data System (ADS)
Wan, Yuan; Li, Hang; Wang, Kai; He, Zhe
2017-01-01
Line Drop Compensation (LDC) is a main function of Reactive Current Compensation (RCC) which is developed to improve voltage stability. While LDC has benefit to voltage, it may deteriorate the small-disturbance rotor angle stability of power system. In present paper, an intelligent algorithm which is combined by Genetic Algorithm (GA) and Backpropagation Neural Network (BPNN) is proposed to optimize parameters of LDC. The objective function proposed in present paper takes consideration of voltage deviation and power system oscillation minimal damping ratio under multi-operating conditions. A simulation based on middle area of Jiangxi province power system is used to demonstrate the intelligent algorithm. The optimization result shows that coordinate optimized parameters can meet the multioperating conditions requirement and improve voltage stability as much as possible while guaranteeing enough damping ratio.
Parameters optimization for magnetic resonance coupling wireless power transmission.
Li, Changsheng; Zhang, He; Jiang, Xiaohua
2014-01-01
Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.
Programmable physical parameter optimization for particle plasma simulations
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.
NASA Astrophysics Data System (ADS)
Chandrasekaram, Sandeep D.
Development of air travel technology is always increasing and fuel efficiency is one of the most important factors that's being looked into. For a 25% increase in fuel efficiency in the future aeroplanes, reduction in the weight of the engine is one of the factors that should be addressed while increasing the strength and power generated. For this purpose, General Electric Aviation has chosen Silicon Carbide as the material to build the turbine blades of its engines. Silicon carbide works best as it is strong, can withstand high temperature and lightweight. The downside of this material is that it reacts with water vapor at temperatures greater than 2700°F to form volatile Silicon hydroxide from Silicon dioxide, its protective layer; and furthermore it reduces to Silicon monoxide that vaporizes. To counter this problem, scientists at the National Aeronautics & Space Administration (NASA) have found that a rare earth silicate could be used as an environmental barrier coating (EBC) to prevent the exposure of Silicon Carbide to water vapor. The EBC can't be directly coated on the Silicon Carbide surface as it isn't chemically adhesive enough, therefore Silicon was chosen to act as the bond coat between the Silicon Carbide and EBC. The goal of this research is to design a reactor for the composites to be coated with Silicon using the reaction and diffusion kinetics determined at higher temperatures and different partial pressures compared to the standard electronics industry. Chemical Vapor Deposition is the technique that will be used in determining the necessary parameters. The findings from this research can be further used in optimizing the utilization of the reagents and optimizing the process economically.
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.
Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback
NASA Astrophysics Data System (ADS)
Bruni, Renato; Celani, Fabio
2016-10-01
The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.
Multiexposure imaging and parameter optimization for intensified star trackers.
Yu, Wenbo; Jiang, Jie; Zhang, Guangjun
2016-12-20
Due to the introduction of the intensified image detector, the dynamic performance of the intensified star tracker is effectively improved. However, its attitude update rate is still seriously restricted by the transmission and processing of pixel data. In order to break through the above limitation, a multiexposure imaging approach for intensified star trackers is proposed in this paper. One star image formed by this approach actually records N different groups of star positions, and then N corresponding groups of attitude information can be acquired. Compared with the existing exposure imaging approach, the proposed approach improves the attitude update rate by N times. Furthermore, for a dim star, the proposed approach can also accumulate the energy of its N positions and then effectively improve its signal-to-noise ratio. Subsequently, in order to obtain the optimal performance of the proposed approach, parameter optimization is carried out. First, the motion model of the star spot in the image plane is established, and then based on it, all the key parameters are optimized. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach and parameter optimization.
NASA Astrophysics Data System (ADS)
Mukhtar, Aiman; Shahzad Khan, Babar; Mehmood, Tahir
2016-12-01
The effect of deposition potential on the crystal structure and composition of Co-Ni alloy nanowires is studied by XRD, FE-SEM and EDX. The alloy nanowires deposited at -3.2 V are metastable fcc phase Co-Ni. The alloy nanowires deposited at -1.8 V are hcp phase Co-Ni. The formation of the metastable fcc alloy nanowires can be attributed to smaller critical clusters formed at the high potential as the smaller critical clusters favor fcc structure because of the significant surface energy effect. The content of Co inside nanowires increases with increasing potential. This can be understood by the polarization curves of depositing Co and Ni nanowires, which show that the current density ratio of Ni to Co at low potential has larger value than that at high potential.
Identification of optimal parameter combinations for the emergence of bistability.
Májer, Imre; Hajihosseini, Amirhossein; Becskei, Attila
2015-11-24
Bistability underlies cellular memory and maintains alternative differentiation states. Bistability can emerge only if its parameter range is either physically realizable or can be enlarged to become realizable. We derived a general rule and showed that the bistable range of a reaction parameter is maximized by a pair of other parameters in any gene regulatory network provided they satisfy a general condition. The resulting analytical expressions revealed whether or not such reaction pairs are present in prototypical positive feedback loops. They are absent from the feedback loop enclosed by protein dimers but present in both the toggle-switch and the feedback circuit inhibited by sequestration. Sequestration can generate bistability even at narrow feedback expression range at which cooperative binding fails to do so, provided inhibition is set to an optimal value. These results help to design bistable circuits and cellular reprogramming and reveal whether bistability is possible in gene networks in the range of realistic parameter values.
Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations
NASA Technical Reports Server (NTRS)
Hanson, Andrea; Reed, Erik; Cavanagh, Peter
2011-01-01
Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.
A Parameter Optimization for a National SASE FEL Facility
Yavas, O.; Yigit, S.
2007-04-23
The parameter optimization for a national SASE FEL facility was studied. Turkish State Planing Organization (DPT) gave financial support as an inter-universities project to begin technical design studies and test facility of National Accelerator Complex starting from 2006. In addition to a particle factory, the complex will contain a linac based free electron laser, positron ring based synchrotron radiation facilities and a proton accelerator. In this paper, we have given some results of main parameters of SASE FEL facility based on 130 MeV linac, application potential in basic and applied research.
Optimization of reserve lithium thionyl chloride battery electrochemical design parameters
NASA Astrophysics Data System (ADS)
Doddapaneni, N.; Godshall, N. A.
The performance of Reserve Lithium Thionyl Chloride (RLTC) batteries was optimized by conducting a parametric study of seven electrochemical parameters: electrode compression, carbon thickness, presence of catalyst, temperature, electrode limitation, discharge rate, and electrolyte acidity. Increasing electrode compression (from 0 to 15 percent) improved battery performance significantly (10 percent greater carbon capacity density). Although thinner carbon cathodes yielded less absolute capacity than did thicker cathodes, they did so with considerably higher volume efficiencies. The effect of these parameters, and their synergistic interactions, on electrochemical cell performance is illustrated.
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.
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.
Optimization of the selective frequency damping parameters using model reduction
NASA Astrophysics Data System (ADS)
Cunha, Guilherme; Passaggia, Pierre-Yves; Lazareff, Marc
2015-09-01
In the present work, an optimization methodology to compute the best control parameters, χ and Δ, for the selective frequency damping method is presented. The optimization does not suppose any a priori knowledge of the flow physics, neither of the underlying numerical methods, and is especially suited for simulations requiring large quantity of grid elements and processors. It allows for obtaining an optimal convergence rate to a steady state of the damped Navier-Stokes system. This is achieved using the Dynamic Mode Decomposition, which is a snapshot-based method, to estimate the eigenvalues associated with global unstable dynamics. Validations test cases are presented for the numerical configurations of a laminar flow past a 2D cylinder, a separated boundary-layer over a shallow bump, and a 3D turbulent stratified-Poiseuille flow.
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.
H-Infinity-Optimal Control for Distributed Parameter Systems
1991-02-28
F. Callier and C.A. Desoer , "An Algebra of Transfer Functions for Distributed Linear Time-Invariant Systems," IEEE Trans. Circuits Syst., Sept. 1978...neeuey and -f by blog* nu"bM) This report describes progress in the development and application of H-infinity-optimal control theory to distributed...parameter systems. This research is intended to develop both theory and algorithms capable of providing realistic control systems for physical plants which
Optimization of Parameters for Semiempirical Methods 1. Method
1989-01-01
average size."’ In con- the value of the orbital exponent for carbon . sequence, elements were parameterized only A new and completely general optimiza...the type used in MOPAC9 carbon , nitrogen, and oxygen), several other is described here. In this method, use is elements were parameterized rapidly. In...C angle in dimethyl ether. necessary condition for an optimized set of Two reference functions which have no parameters is that the error function, S
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.
Optimizing spectral CT parameters for material classification tasks
NASA Astrophysics Data System (ADS)
Rigie, D. S.; La Rivière, P. J.
2016-06-01
In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.
Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology
Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander
2015-01-01
Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250
Efficient global optimization of a limited parameter antenna design
NASA Astrophysics Data System (ADS)
O'Donnell, Teresa H.; Southall, Hugh L.; Kaanta, Bryan
2008-04-01
Efficient Global Optimization (EGO) is a competent evolutionary algorithm suited for problems with limited design parameters and expensive cost functions. Many electromagnetics problems, including some antenna designs, fall into this class, as complex electromagnetics simulations can take substantial computational effort. This makes simple evolutionary algorithms such as genetic algorithms or particle swarms very time-consuming for design optimization, as many iterations of large populations are usually required. When physical experiments are necessary to perform tradeoffs or determine effects which may not be simulated, use of these algorithms is simply not practical at all due to the large numbers of measurements required. In this paper we first present a brief introduction to the EGO algorithm. We then present the parasitic superdirective two-element array design problem and results obtained by applying EGO to obtain the optimal element separation and operating frequency to maximize the array directivity. We compare these results to both the optimal solution and results obtained by performing a similar optimization using the Nelder-Mead downhill simplex method. Our results indicate that, unlike the Nelder-Mead algorithm, the EGO algorithm did not become stuck in local minima but rather found the area of the correct global minimum. However, our implementation did not always drill down into the precise minimum and the addition of a local search technique seems to be indicated.
Parameters optimization and control in precision laser scribing
NASA Astrophysics Data System (ADS)
Zhang, Qiu'e.; Li, Yongda; Li, Yongzheng
2005-01-01
The positional precision of laser scribing and laser marking in precision metrological tools, such as scale plate and scale dial, is of the order of μm. The control of scribing must be very accurate. The laser beam parameters, focal length of the lens, and the position of the focal spot must be carefully selected and accurately controlled. The workpiece must also be accurately and repeatedly positioned. Any deviation from the required parameters would seriously affect the product quality. This paper studied an Nd:YAG laser scribing system specially designed for scribing of extremely high precision dial scale used in petroleum drilling machine. The relevant parameters were carefully selected and optimized. CAD, CAM, NC and automatic control technology were employed in the system. The integration of optics, mechanics, electronics and computer ensured high precision laser scribing.
Density-based penalty parameter optimization on C-SVM.
Liu, Yun; Lian, Jie; Bartolacci, Michael R; Zeng, Qing-An
2014-01-01
The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.
Drift parameters optimization of a TPC polarimeter: a simulation study
NASA Astrophysics Data System (ADS)
Rakhee, K.; Radhakrishna, V.; Koushal, V.; Baishali, G.; Vinodkumar, A. M.
2015-06-01
Time Projection Chamber (TPC) based X-ray polarimeters using Gas Electron Multiplier (GEM) are currently being developed to make sensitive measurement of polarization in 2-10 keV energy range. The emission direction of the photoelectron ejected via photoelectric effect carries the information of the polarization of the incident X-ray photon. Performance of a gas based polarimeter is affected by the operating drift parameters such as gas pressure, drift field and drift-gap. We present simulation studies carried out in order to understand the effect of these operating parameters on the modulation factor of a TPC polarimeter. Models of Garfield are used to study photoelectron interaction in gas and drift of electron cloud towards GEM. Our study is aimed at achieving higher modulation factors by optimizing drift parameters. Study has shown that Ne/DME (50/50) at lower pressure and drift field can lead to desired performance of a TPC polarimeter.
Density-Based Penalty Parameter Optimization on C-SVM
Liu, Yun; Lian, Jie; Bartolacci, Michael R.; Zeng, Qing-An
2014-01-01
The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall. PMID:25114978
Basin structure of optimization based state and parameter estimation
NASA Astrophysics Data System (ADS)
Schumann-Bischoff, Jan; Parlitz, Ulrich; Abarbanel, Henry D. I.; Kostuk, Mark; Rey, Daniel; Eldridge, Michael; Luther, Stefan
2015-05-01
Most data based state and parameter estimation methods require suitable initial values or guesses to achieve convergence to the desired solution, which typically is a global minimum of some cost function. Unfortunately, however, other stable solutions (e.g., local minima) may exist and provide suboptimal or even wrong estimates. Here, we demonstrate for a 9-dimensional Lorenz-96 model how to characterize the basin size of the global minimum when applying some particular optimization based estimation algorithm. We compare three different strategies for generating suitable initial guesses, and we investigate the dependence of the solution on the given trajectory segment (underlying the measured time series). To address the question of how many state variables have to be measured for optimal performance, different types of multivariate time series are considered consisting of 1, 2, or 3 variables. Based on these time series, the local observability of state variables and parameters of the Lorenz-96 model is investigated and confirmed using delay coordinates. This result is in good agreement with the observation that correct state and parameter estimation results are obtained if the optimization algorithm is initialized with initial guesses close to the true solution. In contrast, initialization with other exact solutions of the model equations (different from the true solution used to generate the time series) typically fails, i.e., the optimization procedure ends up in local minima different from the true solution. Initialization using random values in a box around the attractor exhibits success rates depending on the number of observables and the available time series (trajectory segment).
Basin structure of optimization based state and parameter estimation.
Schumann-Bischoff, Jan; Parlitz, Ulrich; Abarbanel, Henry D I; Kostuk, Mark; Rey, Daniel; Eldridge, Michael; Luther, Stefan
2015-05-01
Most data based state and parameter estimation methods require suitable initial values or guesses to achieve convergence to the desired solution, which typically is a global minimum of some cost function. Unfortunately, however, other stable solutions (e.g., local minima) may exist and provide suboptimal or even wrong estimates. Here, we demonstrate for a 9-dimensional Lorenz-96 model how to characterize the basin size of the global minimum when applying some particular optimization based estimation algorithm. We compare three different strategies for generating suitable initial guesses, and we investigate the dependence of the solution on the given trajectory segment (underlying the measured time series). To address the question of how many state variables have to be measured for optimal performance, different types of multivariate time series are considered consisting of 1, 2, or 3 variables. Based on these time series, the local observability of state variables and parameters of the Lorenz-96 model is investigated and confirmed using delay coordinates. This result is in good agreement with the observation that correct state and parameter estimation results are obtained if the optimization algorithm is initialized with initial guesses close to the true solution. In contrast, initialization with other exact solutions of the model equations (different from the true solution used to generate the time series) typically fails, i.e., the optimization procedure ends up in local minima different from the true solution. Initialization using random values in a box around the attractor exhibits success rates depending on the number of observables and the available time series (trajectory segment).
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
Estimation of Saxophone Control Parameters by Convex Optimization
Wang, Cheng-i; Smyth, Tamara; Lipton, Zachary C.
2015-01-01
In this work, an approach to jointly estimating the tone hole configuration (fingering) and reed model parameters of a saxophone is presented. The problem isn't one of merely estimating pitch as one applied fingering can be used to produce several different pitches by bugling or overblowing. Nor can a fingering be estimated solely by the spectral envelope of the produced sound (as it might for estimation of vocal tract shape in speech) since one fingering can produce markedly different spectral envelopes depending on the player's embouchure and control of the reed. The problem is therefore addressed by jointly estimating both the reed (source) parameters and the fingering (filter) of a saxophone model using convex optimization and 1) a bank of filter frequency responses derived from measurement of the saxophone configured with all possible fingerings and 2) sample recordings of notes produced using all possible fingerings, played with different overblowing, dynamics and timbre. The saxophone model couples one of several possible frequency response pairs (corresponding to the applied fingering), and a quasi-static reed model generating input pressure at the mouthpiece, with control parameters being blowing pressure and reed stiffness. Applied fingering and reed parameters are estimated for a given recording by formalizing a minimization problem, where the cost function is the error between the recording and the synthesized sound produced by the model having incremental parameter values for blowing pressure and reed stiffness. The minimization problem is nonlinear and not differentiable and is made solvable using convex optimization. The performance of the fingering identification is evaluated with better accuracy than previous reported value. PMID:27754493
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.
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.
Total energy control system autopilot design with constrained parameter optimization
NASA Technical Reports Server (NTRS)
Ly, Uy-Loi; Voth, Christopher
1990-01-01
A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.
Optimal segmentation of pupillometric images for estimating pupil shape parameters.
De Santis, A; Iacoviello, D
2006-12-01
The problem of determining the pupil morphological parameters from pupillometric data is considered. These characteristics are of great interest for non-invasive early diagnosis of the central nervous system response to environmental stimuli of different nature, in subjects suffering some typical diseases such as diabetes, Alzheimer disease, schizophrenia, drug and alcohol addiction. Pupil geometrical features such as diameter, area, centroid coordinates, are estimated by a procedure based on an image segmentation algorithm. It exploits the level set formulation of the variational problem related to the segmentation. A discrete set up of this problem that admits a unique optimal solution is proposed: an arbitrary initial curve is evolved towards the optimal segmentation boundary by a difference equation; therefore no numerical approximation schemes are needed, as required in the equivalent continuum formulation usually adopted in the relevant literature.
Parameter optimization in AQM controller design to support TCP traffic
NASA Astrophysics Data System (ADS)
Yang, Wei; Yang, Oliver W.
2004-09-01
TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.
Power Saving Optimization for Linear Collider Interaction Region Parameters
Seryi, Andrei; /SLAC
2009-10-30
Optimization of Interaction Region parameters of a TeV energy scale linear collider has to take into account constraints defined by phenomena such as beam-beam focusing forces, beamstrahlung radiation, and hour-glass effect. With those constraints, achieving a desired luminosity of about 2E34 would require use of e{sup +}e{sup -} beams with about 10 MW average power. Application of the 'travelling focus' regime may allow the required beam power to be reduced by at least a factor of two, helping reduce the cost of the collider, while keeping the beamstrahlung energy loss reasonably low. The technique is illustrated for the 500 GeV CM parameters of the International Linear Collider. This technique may also in principle allow recycling the e{sup +}e{sup -} beams and/or recuperation of their energy.
Vibration evaluation and parameter optimization of hydraulic thruster
NASA Astrophysics Data System (ADS)
Peng, Yong; Zhang, Haokun
2017-01-01
Two difficult problems which are drilling string vibration and drilling pressure control exist in the process of drilling large displacement horizontal well. Using hydraulic thruster can not only improve the mechanical drilling speed and increase the horizontal section of footage displacement but also obtain better drill string dynamic characteristics and reduce vibration of drilling tool and prolong the life of the bottom hole assembly. By using the spring-damping model of drill string, the dynamic response of the different excitation of the drill bit is analyzed, so as to evaluate the effect of vibration reduction of hydraulic thruster. Use the three factors four levels orthogonal test method to optimize the key design parameters of hydraulic thruster. The analysis shows that the different drilling mud density should be used in the hydraulic thruster with different key parameters, in order to display its superiority.
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.
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.
Optimal-control theoretic methods for optimization and regulation of distributed parameter systems
NASA Astrophysics Data System (ADS)
Goss, Jennifer Dawn
Optimal control and optimization of distributed parameter systems are discussed in the context of a common control framework. The adjoint method of optimization and the traditional linear quadratic regulator implementation of optimal control both employ adjoint or costate variables in the determination of control variable progression. As well both theories benefit from a reduced order model approximation in their execution. This research aims to draw clear parallels between optimization and optimal control utilizing these similarities. Several applications are presented showing the use of adjoint/costate variables and reduced order models in optimization and optimal control problems. The adjoint method for shape optimization is derived and implemented for the quasi-one-dimensional duct and two variations of a two-dimensional double ramp inlet. All applications are governed by the Euler equations. The quasi-one-dimensional duct is solved first to test the adjoint method and to verify the results against an analytical solution. The method is then adapted to solve the shape optimization of the double ramp inlet. A finite volume solver is tested on the flow equations and then implemented for the corresponding adjoint equations. The gradient of the cost function with respect to the shape parameters is derived based on the computed adjoint variables. The same inlet shape optimization problem is then solved using a reduced order model. The basis functions in the reduced order model are computed using the method of snapshots form of proper orthogonal decomposition. The corresponding weights are derived using an optimization in the design parameter space to match the reduced order model to the original snapshots. A continuous map of these weights in terms of the design variables is obtained via a response surface approximations and artificial neural networks. This map is then utilized in an optimization problem to determine the optimal inlet shape. As in the adjoint method
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.
Impact of sputter deposition parameters on molybdenum nitride thin film properties
NASA Astrophysics Data System (ADS)
Stöber, L.; Konrath, J. P.; Krivec, S.; Patocka, F.; Schwarz, S.; Bittner, A.; Schneider, M.; Schmid, U.
2015-07-01
Molybdenum and molybdenum nitride thin films are presented, which are deposited by reactive dc magnetron sputtering. The influence of deposition parameters, especially the amount of nitrogen during film synthesization, to mechanical and electrical properties is investigated. The crystallographic phase and lattice constants are determined by x-ray diffraction analyses. Further information on the microstructure as well as on the biaxial film stress are gained from techniques such as transmission electron microscopy, scanning electron microscopy and the wafer bow. Furthermore, the film resistivity and the temperature coefficient of resistance are measured by the van der Pauw technique starting from room temperature up to 300 °C. Independent of the investigated physical quantity, a dominant dependence on the sputtering gas nitrogen content is observed compared to other deposition parameters such as the plasma power or the sputtering gas pressure in the deposition chamber.
Multivariate Parameter Sets for Optimal Synthesis of Compliant Mechanisms
NASA Technical Reports Server (NTRS)
Shibakov, Alex; Hull, Patrick V.; Canfield, Stephen L.; Tinker, Mike
2005-01-01
This paper will propose the use of control maps along with discretized elements or meshes in the design parameter set for optimizing compliant mechanisms. The use of control maps will be demonstrated to encode the motion of groups of nodes or control points within a compliant mechanism design with simple mapping rules. The technique will serve as an alternative to increased mesh size or node wandering techniques that have been proposed to increase the number of alternative design shapes that may be considered. As an alternative approach, the proposed control map parameterization has the significant benefit that it minimizes the number of design parameters necessary (parameters increase linearly with the mesh size) in describing a given design making it computationally efficient. A limited number of tiles can produce a map that has a significant effect on the final shape. If the tiles are chosen appropriately, the problems such as material overlap and non-convex mesh elements are avoided automatically. This paper will describe the implementation of these control maps and provide several examples showing their implementation in the compliant mechanism topology synthesis process.
Prasad, Leena Kumari; LaFountaine, Justin S; Keen, Justin M; Williams, Robert O; McGinity, James W
2016-12-30
Electrostatic powder deposition (ESPD) has been developed as a solvent-free method to prepare pharmaceutical films. The aim of this work was to investigate the influence of process parameters during (1) electrostatic powder deposition, (2) curing, and (3) removal of the film from the substrate on the properties of the film. Polyethylene oxide (PEO) was used as the model polymer and stainless steel 316 as the substrate. Deposition efficiency (i.e. deposited weight) was measured with varying charging voltage, gun tip to substrate distance, and environmental humidity. Scanning electron microscopy was utilized to assess film formation, and adhesive and mechanical strength of films were measured with varying cure temperature and time. Adhesive strength was measured for films prepared on substrates of varying surface roughness. When deposition was performed at low humidity conditions, 25%RH, process parameters did not significantly affect deposition behavior. At 40%RH, increasing deposition efficiency with decreasing gun tip to substrate distance and increasing voltage (up to 60kV) was observed. Complete film formation was seen by 30min at 80°C, compared to lower curing temperatures and times. All films were readily removed from the substrates. The results show the ESPD process can be modified to produce films with good mechanical properties (e.g. tensile strength>0.06MPa), suggesting it is a promising dry powder process for preparing pharmaceutical films.
NASA Astrophysics Data System (ADS)
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
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.
Optimization of resistance spot welding parameters for microalloyed steel sheets
NASA Astrophysics Data System (ADS)
Viňáš, Ján; Kaščák, Ľuboš; Greš, Miroslav
2016-11-01
The paper presents the results of resistance spot welding of hot-dip galvanized microalloyed steel sheets used in car body production. The spot welds were made with various welding currents and welding time values, but with a constant pressing force of welding electrodes. The welding current and welding time are the dominant characteristics in spot welding that affect the quality of spot welds, as well as their dimensions and load-bearing capacity. The load-bearing capacity of welded joints was evaluated by tensile test according to STN 05 1122 standard and dimensions and inner defects were evaluated by metallographic analysis by light optical microscope. Thewelding parameters of investigated microalloyed steel sheets were optimized for resistance spot welding on the pneumatic welding machine BPK 20.
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
Optimization of system parameters for a complete multispectral polarimeter
Hollstein, Andre; Ruhtz, Thomas; Fischer, Juergen; Preusker, Rene
2009-08-20
We optimize a general class of complete multispectral polarimeters with respect to signal-to-noise ratio, stability against alignment errors, and the minimization of errors regarding a given set of polarization states. The class of polarimeters that are dealt with consists of at least four polarization optics each with a multispectral detector. A polarization optic is made of an azimuthal oriented wave plate and a polarizing filter. A general, but not unique, analytic solution that minimizes signal-to-noise ratio is introduced for a polarimeter that incorporates four simultaneous measurements with four independent optics. The optics consist of four sufficient wave plates, where at least one is a quarter-wave plate. The solution is stable with respect to the retardance of the quarter-wave plate; therefore, it can be applied to real-world cases where the retardance deviates from {lambda}/4. The solution is a set of seven rotational parameters that depends on the given retardances of the wave plates. It can be applied to a broad range of real world cases. A numerical method for the optimization of arbitrary polarimeters of the type discussed is also presented and applied for two cases. First, the class of polarimeters that were analytically dealt with are further optimized with respect to stability and error performance with respect to linear polarized states. Then a multispectral case for a polarimeter that consists of four optics with real achromatic wave plates is presented. This case was used as the theoretical background for the development of the Airborne Multi-Spectral Sunphoto- and Polarimeter (AMSSP), which is an instrument for the German research aircraft HALO.
Optimization of system parameters for a complete multispectral polarimeter.
Hollstein, André; Ruhtz, Thomas; Fischer, Jürgen; Preusker, René
2009-08-20
We optimize a general class of complete multispectral polarimeters with respect to signal-to-noise ratio, stability against alignment errors, and the minimization of errors regarding a given set of polarization states. The class of polarimeters that are dealt with consists of at least four polarization optics each with a multispectral detector. A polarization optic is made of an azimuthal oriented wave plate and a polarizing filter. A general, but not unique, analytic solution that minimizes signal-to-noise ratio is introduced for a polarimeter that incorporates four simultaneous measurements with four independent optics. The optics consist of four sufficient wave plates, where at least one is a quarter-wave plate. The solution is stable with respect to the retardance of the quarter-wave plate; therefore, it can be applied to real-world cases where the retardance deviates from lambda/4. The solution is a set of seven rotational parameters that depends on the given retardances of the wave plates. It can be applied to a broad range of real world cases. A numerical method for the optimization of arbitrary polarimeters of the type discussed is also presented and applied for two cases. First, the class of polarimeters that were analytically dealt with are further optimized with respect to stability and error performance with respect to linear polarized states. Then a multispectral case for a polarimeter that consists of four optics with real achromatic wave plates is presented. This case was used as the theoretical background for the development of the Airborne Multi-Spectral Sunphoto- and Polarimeter (AMSSP), which is an instrument for the German research aircraft HALO.
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.
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.
NASA Astrophysics Data System (ADS)
Kadyrmetov, A. M.; Sharifullin, S. N.
2016-11-01
This paper presents the results of simulation of plasma deposition and hardening of coatings in modulating the electrical parameters. Mathematical models are based on physical models of gas-dynamic mechanisms more dynamic and thermal processes of the plasma jet. As an example the modeling of dynamic processes of heterogeneous plasma jet, modulated current pulses indirect arc plasma torch.
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.
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)
Onishi, Takashi; Mizuno, Masao; Yoshikawa, Tetsuya; Munemasa, Jun; Mizuno, Masataka; Kihara, Teruo; Araki, Hideki; Shirai, Yasuharu
2013-07-01
Improving the reflow characteristics of sputtered Cu films was attempted by optimizing the sputtering conditions. The reflow characteristics of films deposited under various sputtering conditions were evaluated by measuring their filling level in via holes. It was found that the reflow characteristics of the Cu films are strongly influenced by the deposition parameters. Deposition at low temperatures and the addition of H2 or N2 to the Ar sputtering gas had a significant influence on the reflow characteristics. Imperfections in the Cu films before and after the high-temperature, high-pressure treatments were investigated by positron annihilation spectroscopy. The results showed that low temperature and the addition of H2 or N2 led to films containing a large number of mono-vacancies, which accelerate atomic diffusion creep and dislocation core diffusion creep, improving the reflow characteristics of the Cu films.
Deng, Zhang; He, Wenjie; Duan, Chenlong; Chen, Rong; Shan, Bin
2016-01-15
Spatial atomic layer deposition (SALD) is a promising technology with the aim of combining the advantages of excellent uniformity and conformity of temporal atomic layer deposition (ALD), and an industrial scalable and continuous process. In this manuscript, an experimental and numerical combined model of atmospheric SALD system is presented. To establish the connection between the process parameters and the growth efficiency, a quantitative model on reactant isolation, throughput, and precursor utilization is performed based on the separation gas flow rate, carrier gas flow rate, and precursor mass fraction. The simulation results based on this model show an inverse relation between the precursor usage and the carrier gas flow rate. With the constant carrier gas flow, the relationship of precursor usage and precursor mass fraction follows monotonic function. The precursor concentration, regardless of gas velocity, is the determinant factor of the minimal residual time. The narrow gap between precursor injecting heads and the substrate surface in general SALD system leads to a low Péclet number. In this situation, the gas diffusion act as a leading role in the precursor transport in the small gap rather than the convection. Fluid kinetics from the numerical model is independent of the specific structure, which is instructive for the SALD geometry design as well as its process optimization.
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.
Multivariable norm optimal and parameter optimal iterative learning control: a unified formulation
NASA Astrophysics Data System (ADS)
Owens, D. H.
2012-08-01
This article investigates the two paradigms of norm optimal iterative learning control (NOILC) and parameter optimal iterative learning control (POILC) for multivariable (MIMO) ℓ-input, m-output linear discrete-time systems. The main result is a proof that, despite their algebraic and conceptual differences, they can be unified using linear quadratic multi-parameter optimisation techniques. In particular, whilst POILC has been naturally regarded as an approximation to NOILC, it is shown that the NOILC control law can be generated from a suitable choice of control law parameterisation and objective function in a multi-parameter MIMO POILC problem. The form of this equivalence is used to propose a new general approach to the construction of POILC problems for MIMO systems that approximates the solution of a given NOILC problem. An infinite number of such approximations exist. This great diversity is illustrated by the derivation of new convergent algorithms based on time interval and gradient partition that extend previously published work.
Taguchi Method Applied in Optimization of Shipley 5740 Positive Resist Deposition
NASA Technical Reports Server (NTRS)
Hui, Allan; Wiberg, Dean V.; Blosiu, Julian
1997-01-01
Taguchi Methods of Robust Design Presents a way to optimize output process performance through organized experiments, by using orthogonal arrays for the evaluation of the process controlleable parameters.
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.
Analytically optimal parameters of dynamic vibration absorber with negative stiffness
NASA Astrophysics Data System (ADS)
Shen, Yongjun; Peng, Haibo; Li, Xianghong; Yang, Shaopu
2017-02-01
In this paper the optimal parameters of a dynamic vibration absorber (DVA) with negative stiffness is analytically studied. The analytical solution is obtained by Laplace transform method when the primary system is subjected to harmonic excitation. The research shows there are still two fixed points independent of the absorber damping in the amplitude-frequency curve of the primary system when the system contains negative stiffness. Then the optimum frequency ratio and optimum damping ratio are respectively obtained based on the fixed-point theory. A new strategy is proposed to obtain the optimum negative stiffness ratio and make the system remain stable at the same time. At last the control performance of the presented DVA is compared with those of three existing typical DVAs, which were presented by Den Hartog, Ren and Sims respectively. The comparison results in harmonic and random excitation show that the presented DVA in this paper could not only reduce the peak value of the amplitude-frequency curve of the primary system significantly, but also broaden the efficient frequency range of vibration mitigation.
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.
Comparisons of Solar Wind Coupling Parameters with Auroral Energy Deposition Rates
NASA Technical Reports Server (NTRS)
Elsen, R.; Brittnacher, M. J.; Fillingim, M. O.; Parks, G. K.; Germany G. A.; Spann, J. F., Jr.
1997-01-01
Measurement of the global rate of energy deposition in the ionosphere via auroral particle precipitation is one of the primary goals of the Polar UVI program and is an important component of the ISTP program. The instantaneous rate of energy deposition for the entire month of January 1997 has been calculated by applying models to the UVI images and is presented by Fillingim et al. In this session. A number of parameters that predict the rate of coupling of solar wind energy into the magnetosphere have been proposed in the last few decades. Some of these parameters, such as the epsilon parameter of Perrault and Akasofu, depend on the instantaneous values in the solar wind. Other parameters depend on the integrated values of solar wind parameters, especially IMF Bz, e.g. applied flux which predicts the net transfer of magnetic flux to the tail. While these parameters have often been used successfully with substorm studies, their validity in terms of global energy input has not yet been ascertained, largely because data such as that supplied by the ISTP program was lacking. We have calculated these and other energy coupling parameters for January 1997 using solar wind data provided by WIND and other solar wind monitors. The rates of energy input predicted by these parameters are compared to those measured through UVI data and correlations are sought. Whether these parameters are better at providing an instantaneous rate of energy input or an average input over some time period is addressed. We also study if either type of parameter may provide better correlations if a time delay is introduced; if so, this time delay may provide a characteristic time for energy transport in the coupled solar wind-magnetosphere-ionosphere system.
NASA Technical Reports Server (NTRS)
Rees, M. H.; Lummerzheim, D.; Roble, R. G.; Winningham, J. D.; Craven, J. D.
1988-01-01
Auroral images obtained by the Spin Scan Auroral Imager (SAI) aboard the DE-1 satellite were used to derive auroral energy deposition rate, characteristic electron energy, and ionospheric parameters. The principles involved in the imaging technique and the physical mechanisms that underlie the relationship between the spectral images and the geophysical parameters are discussed together with the methodology for implementing such analyses. It is shown that images obtained with the SAI provide global parameters at 12-min temporal resolution; the spatial resolution is limited by the field of view of a pixel. The analysis of the 12-min images presented yielded a representation of ionospheric parameters that was better than can be obtained using empirical models based on local measurements averaged over long periods of time.
Direct Multiple Shooting Optimization with Variable Problem Parameters
NASA Technical Reports Server (NTRS)
Whitley, Ryan J.; Ocampo, Cesar A.
2009-01-01
Taking advantage of a novel approach to the design of the orbital transfer optimization problem and advanced non-linear programming algorithms, several optimal transfer trajectories are found for problems with and without known analytic solutions. This method treats the fixed known gravitational constants as optimization variables in order to reduce the need for an advanced initial guess. Complex periodic orbits are targeted with very simple guesses and the ability to find optimal transfers in spite of these bad guesses is successfully demonstrated. Impulsive transfers are considered for orbits in both the 2-body frame as well as the circular restricted three-body problem (CRTBP). The results with this new approach demonstrate the potential for increasing robustness for all types of orbit transfer problems.
Lee, Chong Bum; Kim, Jeong, Sik; Kim, Yong Goog; Cho, Chang Rae; Byun, D.W.
1996-12-31
The dry deposition of pollutants can be calculated from the concentration of pollutants in the atmosphere and deposition velocity. To calculate deposition velocity, turbulence parameters such as friction velocity and Monin-Obukhov length are used. However, due to the difficulties in observation of turbulence parameters, usually mean values of wind speed and temperature observed using conventional meteorological instruments are used to estimate the dry deposition. The dry deposition velocity is the function of aerodynamic resistance (R{sub a}), sublayer resistance (R{sub b}), surface resistance (R{sub c}). R{sub a} and R{sub b} are calculated from turbulence parameters and R{sub c} is related to surface characteristics. The purpose of the present study is to compare the dry deposition obtained using the data sets of mean values and turbulence parameters measured by sonic anemometer-thermometer. The field observation was performed for 30 days from October 27 to November 25, 1995. The turbulence parameters were measured by 3 dimensional sonic anemometer-thermometer and mean meteorological variables are obtained at two heights, 2.5 m and 10 m. The results show that the dry deposition velocity is large, in daytime and small in nighttime. The major factor of diurnal variation is Ra. In the daytime the dry deposition velocity calculated using mean meteorological data show relatively similar to the dry deposition velocity calculated using the turbulence data, however there are big differences at night.
NASA Astrophysics Data System (ADS)
Zhang, Tao; Wang, Xinchang; Shen, Bin; Sun, Fanghong; Zhang, Zhiming
2013-06-01
The micron well-faceted diamond powders have attracted an increasing attention in the polishing filed, owing to improve the surface finish of components using the powders. In the present work, the hot filament chemical vapor deposition (HFCVD) technique is employed for synthesizing such diamond powders. A great many of micron diamonds are grown simultaneously but independently onto a large-area substrate. First, a novel seeding method, spraying the diamond seeds suspension toward the substrate using a spin coater machine, is proposed, with which the seeds with a controlled density are distributed evenly onto the substrate. Also, the method is more suitable for the fabrication of the micron isolated diamonds, compared with other nucleation initiation methods, such as the scratching pre-treatment and electrical biasing on substrates. Afterwards, a systematic investigation is under taken into the effects of deposition parameters on the basic growth characteristics of CVD micron diamonds, and on the inhibition of films growth. Furthermore, the reactive pressure, substrate temperature, carbon concentration, and growth duration are determined to be 4500 Pa, 850 °C, 1.3-1.4%, 60-90 min, respectively. Eventually, under the preferred deposition conditions, approximately 15 million cube-octahedral crystals with the mean size of 2-3 μm are deposited simultaneously on the 1000 mm2 substrate.
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)
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.
Parameter optimization for photonic nanojet of dielectric microsphere
NASA Astrophysics Data System (ADS)
Ku, Yu-long; Kuang, Cui-fang; Hao, Xiang; Li, Hai-feng; Liu, Xu
2013-03-01
The characteristics of photonic nanojets are analyzed by changing the parameters, such as the wavelength, refractive index of the surroundings, diameter and refractive index of the microsphere, in this paper. Quadratic functions are used to describe the relation between the above parameters and photonic nanojets' characteristics. Several techniques are proposed to control the photonic nanojets.
Bath Parameter Dependence of Chemically-Deposited Copper Selenide Thin Film
NASA Astrophysics Data System (ADS)
Al-Mamun; Islam, A. B. M. O.
In this article, a low cost chemical bath deposition (CBD) technique has been used for the preparation of Cu2-xSe thin films on to glass substrate. Different thin films (0.2-0.6 μm) were prepared by adjusting the bath parameter like concentration of ammonia, deposition time, temperature of the solution, and the ratios of the mixing composition between copper and selenium in the reaction bath. From these studies, it reveals that at low concentration of ammonia or TEA, the terminal thicknesses of the films are less, which gradually increases with the increase of concentrations and then drop down at still higher concentrations. It has been found that complexing the Cu2+ ions with TEA first, and then addition of ammonia yields better results than the reverse process. The film thickness increases with the decrease of value x of Cu2-xSe.
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.
Figueredo-Sobrinho, Francisco A A; Santos, Luis P M; Leite, Davi S; Craveiro, Diego C; Santos, Samir H; Eguiluz, Katlin I B; Salazar-Banda, Giancarlo R; Maciel, Cleiton D; Coutinho-Neto, Maurício D; Homem-de-Mello, Paula; de Lima-Neto, Pedro; Correia, Adriana N
2016-03-14
The low toxicity and environmentally compatible ionic liquids (ILs) are alternatives to the toxic and harmful cyanide-based baths used in industrial silver electrodeposition. Here, we report the successful galvanostatic electrodeposition of silver films using the air and water stable ILs 1-ethyl-3-methylimidazolium trifluoromethylsulfonate ([EMIM]TfO) and 1-H-3-methylimidazolium hydrogen sulphate ([HMIM(+)][HSO4(-)]) as solvents and AgTfO as the source of silver. The electrochemical deposition parameters were thoughtfully studied by cyclic voltammetry before deposition. The electrodeposits were characterized by scanning electron microscopy coupled with X-ray energy dispersive spectroscopy and X-ray diffraction. Molecular dynamics (MD) simulations were used to investigate the structural dynamic and energetic properties of AgTfO in both ILs. Cyclic voltammetry experiments revealed that the reduction of silver is a diffusion-controlled process. The morphology of the silver coatings obtained in [EMIM]TfO is independent of the applied current density, resulting in nodular electrodeposits grouped as crystalline clusters. However, the current density significantly influences the morphology of silver electrodeposits obtained in [HMIM(+)][HSO4(-)], thus evolving from dendrites at 15 mA cm(-2) to the coexistence of dendrites and columnar shapes at 30 mA cm(-2). These differences are probably due to the greater interaction of Ag(+) with [HSO4(-)] than with TfO(-), as indicated by the MD simulations. The morphology of Ag deposits is independent of the electrodeposition temperature for both ILs, but higher values of temperature promoted increased cluster sizes. Pure face-centred cubic polycrystalline Ag was deposited on the films with crystallite sizes on the nanometre scale. The morphological dependence of Ag electrodeposits obtained in the [HMIM(+)][HSO4(-)] IL on the current density applied opens up the opportunity to produce different and predetermined Ag deposits.
Stability and optimal parameters for continuous feedback chaos control.
Kouomou, Y Chembo; Woafo, P
2002-09-01
We investigate the conditions under which an optimal continuous feedback control can be achieved. Chaotic oscillations in the single-well Duffing model, with either a positive or a negative nonlinear stiffness term, are tuned to their related Ritz approximation. The Floquet theory enables the stability analysis of the control. Critical values of the feedback control coefficient fulfilling the optimization criteria are derived. The influence of the chosen target orbit, of the feedback coefficient, and of the onset time of control on its duration is discussed. The analytic approach is confirmed by numerical simulations.
Growth process optimization of ZnO thin film using atomic layer deposition
NASA Astrophysics Data System (ADS)
Weng, Binbin; Wang, Jingyu; Larson, Preston; Liu, Yingtao
2016-12-01
The work reports experimental studies of ZnO thin films grown on Si(100) wafers using a customized thermal atomic layer deposition. The impact of growth parameters including H2O/DiethylZinc (DEZn) dose ratio, background pressure, and temperature are investigated. The imaging results of scanning electron microscopy and atomic force microscopy reveal that the dose ratio is critical to the surface morphology. To achieve high uniformity, the H2O dose amount needs to be at least twice that of DEZn per each cycle. If the background pressure drops below 400 mTorr, a large amount of nanoflower-like ZnO grains would emerge and increase surface roughness significantly. In addition, the growth temperature range between 200 °C and 250 °C is found to be the optimal growth window. And the crystal structures and orientations are also strongly correlated to the temperature as proved by electron back-scattering diffraction and x-ray diffraction results.
Optimization of the Automated Spray Layer-by-Layer Technique for Thin Film Deposition
2010-06-01
SUPPLEMENTARY NOTES 14. ABSTRACT The operational parameters of the automated Spray- LbL technique for thin film deposition have been investigated in...order to-identify their effects on film thickness and roughness. We use the automated Spray- LbL system developed at MIT by the Hammond lab to build...This interdiffusion is investigated using both the conventional dipped LbL and Spray- LbL deposition techniques. Interdiffusion is shown to be dependent
Parameter estimation for chaotic systems based on improved boundary chicken swarm optimization
NASA Astrophysics Data System (ADS)
Chen, Shaolong; Yan, Renhuan
2016-10-01
Estimating unknown parameters for chaotic system is a key problem in the field of chaos control and synchronization. Through constructing an appropriate fitness function, parameter estimation of chaotic system could be converted to a multidimensional parameter optimization problem. In this paper, a new method base on improved boundary chicken swarm optimization (IBCSO) algorithm is proposed for solving the problem of parameter estimation in chaotic system. However, to the best of our knowledge, there is no published research work on chicken swarm optimization for parameters estimation of chaotic system. Computer simulation based on Lorenz system and comparisons with chicken swarm optimization, particle swarm optimization, and genetic algorithm shows the effectiveness and feasibility of the proposed method.
NASA Astrophysics Data System (ADS)
Kar, Siddhartha; Chakraborty, Sujoy; Dey, Vidyut; Ghosh, Subrata Kumar
2016-06-01
This paper investigates the application of Taguchi method with fuzzy logic for multi objective optimization of roughness parameters in electro discharge coating process of Al-6351 alloy with powder metallurgical compacted SiC/Cu tool. A Taguchi L16 orthogonal array was employed to investigate the roughness parameters by varying tool parameters like composition and compaction load and electro discharge machining parameters like pulse-on time and peak current. Crucial roughness parameters like Centre line average roughness, Average maximum height of the profile and Mean spacing of local peaks of the profile were measured on the coated specimen. The signal to noise ratios were fuzzified to optimize the roughness parameters through a single comprehensive output measure (COM). Best COM obtained with lower values of compaction load, pulse-on time and current and 30:70 (SiC:Cu) composition of tool. Analysis of variance is carried out and a significant COM model is observed with peak current yielding highest contribution followed by pulse-on time, compaction load and composition. The deposited layer is characterised by X-Ray Diffraction analysis which confirmed the presence of tool materials on the work piece surface.
NASA Astrophysics Data System (ADS)
Roller, Justin M.; Maric, Radenka
2015-12-01
Catalytic materials are complex systems in which achieving the desired properties (i.e., activity, selectivity and stability) depends on exploiting the many degrees of freedom in surface and bulk composition, geometry, and defects. Flame aerosol synthesis is a process for producing nanoparticles with ample processing parameter space to tune the desired properties. Flame dynamics inside the reactor are determined by the input process variables such as solubility of precursor in the fuel; solvent boiling point; reactant flow rate and concentration; flow rates of air, fuel and the carrier gas; and the burner geometry. In this study, the processing parameters for reactive spray deposition technology, a flame-based synthesis method, are systematically evaluated to understand the residence times, reactant mixing, and temperature profiles of flames used in the synthesis of Pt nanoparticles. This provides a framework for further study and modeling. The flame temperature and length are also studied as a function of O2 and fuel flow rates.
MoberlyChan, W J; Schalek, R
2007-11-08
Ion beams of sufficient energy to erode a surface can lead to surface modulations that depend on the ion beam, the material surface it impinges, and extrinsic parameters such as temperature and geometric boundary conditions. Focused Ion Beam technology both enables site-specific placement of these modulations and expedites research through fast, high dose and small efficient use of material. The DualBeam (FIB/SEM) enables in situ metrology, with movies observing ripple formation, wave motion, and the influence of line defects. Nanostructures (ripples of >400nm wavelength to dots spaced <40nm) naturally grow from atomically flat surfaces during erosion, however, a steady state size may or may not be achieved as a consequence of numerous controlled parameters: temperature, angle, energy, crystallography. Geometric factors, which can be easily invoked using a FIB, enable a controlled component of deposition (and/or redeposition) to occur during erosion, and conversely allow a component of etching to be incurred during (ion-beam assisted) deposition. High angles of ion beam inclination commonly lead to 'rougher' surfaces, however, the extreme case of 90.0{sup o} etching enables deposition of organized structures 1000 times smaller than the aforementioned, video-recorded nanostructures. Orientation and position of these picostructures (naturally quantized by their atomic spacings) may be controlled by the same parameters as for nanostructures (e.g. ion inclination and imposed boundary conditions, which are flexibly regulated by FIB). Judicious control of angles during FIB-CVD growth stimulates erosion with directionality that produces surface modulations akin to those observed for sputtering. Just as a diamond surface roughens from 1-D ripples to 2-D steps with increasing angle of ion sputtering, so do ripples and steps appear on carbon-grown surfaces with increase in angle of FIB-CVD. Ion beam processing has been a stalwart of the microelectronics industry, is now a
Parameter Space of Atomic Layer Deposition of Ultrathin Oxides on Graphene
2016-01-01
Atomic layer deposition (ALD) of ultrathin aluminum oxide (AlOx) films was systematically studied on supported chemical vapor deposition (CVD) graphene. We show that by extending the precursor residence time, using either a multiple-pulse sequence or a soaking period, ultrathin continuous AlOx films can be achieved directly on graphene using standard H2O and trimethylaluminum (TMA) precursors even at a high deposition temperature of 200 °C, without the use of surfactants or other additional graphene surface modifications. To obtain conformal nucleation, a precursor residence time of >2s is needed, which is not prohibitively long but sufficient to account for the slow adsorption kinetics of the graphene surface. In contrast, a shorter residence time results in heterogeneous nucleation that is preferential to defect/selective sites on the graphene. These findings demonstrate that careful control of the ALD parameter space is imperative in governing the nucleation behavior of AlOx on CVD graphene. We consider our results to have model system character for rational two-dimensional (2D)/non-2D material process integration, relevant also to the interfacing and device integration of the many other emerging 2D materials. PMID:27723305
Optimization of electrical stimulation parameters for cardiac tissue engineering.
Tandon, Nina; Marsano, Anna; Maidhof, Robert; Wan, Leo; Park, Hyoungshin; Vunjak-Novakovic, Gordana
2011-06-01
In vitro application of pulsatile electrical stimulation to neonatal rat cardiomyocytes cultured on polymer scaffolds has been shown to improve the functional assembly of cells into contractile engineered cardiac tissues. However, to date, the conditions of electrical stimulation have not been optimized. We have systematically varied the electrode material, amplitude and frequency of stimulation to determine the conditions that are optimal for cardiac tissue engineering. Carbon electrodes, exhibiting the highest charge-injection capacity and producing cardiac tissues with the best structural and contractile properties, were thus used in tissue engineering studies. Engineered cardiac tissues stimulated at 3 V/cm amplitude and 3 Hz frequency had the highest tissue density, the highest concentrations of cardiac troponin-I and connexin-43 and the best-developed contractile behaviour. These findings contribute to defining bioreactor design specifications and electrical stimulation regime for cardiac tissue engineering.
Optimization of 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
Optimal parameters of gyrotrons with weak electron-wave interaction
NASA Astrophysics Data System (ADS)
Glyavin, M. Yu.; Oparina, Yu. S.; Savilov, A. V.; Sedov, A. S.
2016-09-01
In low-power gyrotrons with weak electron-wave interaction, there is a problem of determining the optimal length of the operating cavity, which is found as a result of a tradeoff between the enhancement of the electron efficiency and the increase in the Ohmic loss share with increasing cavity length. In fact, this is the problem of an optimal ratio between the diffraction and Ohmic Q-factors of the operating gyrotron mode, which determines the share of the radiated rf power lost in the cavity wall. In this paper, this problem is studied on the basis of a universal set of equations, which are appropriate for a wide class of electron oscillators with low efficiencies of the electron-wave interaction.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
NASA Technical Reports Server (NTRS)
Dhawan, Atam P.
1998-01-01
This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.
NASA Astrophysics Data System (ADS)
Xia, Youlong; Yang, Zong-Liang; Stoffa, Paul L.; Sen, Mrinal K.
2005-01-01
Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI) to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing. The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes. Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.
NASA Astrophysics Data System (ADS)
Tahaei, Ali; Horley, Paul; Merlin, Mattia; Torres-Torres, David; Garagnani, Gian Luca; Praga, Rolando; Vázquez, Felipe J. García; Arizmendi-Morquecho, Ana
2017-01-01
This work is dedicated to optimization of carbide particle system in a weld bead deposited by PTAW technique over D2 tool steel with high chromium content. The paper reports partial melting of the original carbide grains of the Ni-based filling powder, and growing of the secondary carbide phase (Cr, Ni)_3 W_3 C in the form of dendrites with wide branches that enhanced mechanical properties of the weld. The optimization of bead parameters was made with design of experiment methodology complemented by a complex sample characterization including SEM, EDXS, XRD, and nanoindentation measurements. It was shown that the preheat of the substrate to a moderate temperature 523 K (250° C) establishes linear pattern of metal flow in the weld pool, resulting in the most homogeneous distribution of the primary carbides in the microstructure of weld bead.
NASA Astrophysics Data System (ADS)
Tahaei, Ali; Horley, Paul; Merlin, Mattia; Torres-Torres, David; Garagnani, Gian Luca; Praga, Rolando; Vázquez, Felipe J. García; Arizmendi-Morquecho, Ana
2017-03-01
This work is dedicated to optimization of carbide particle system in a weld bead deposited by PTAW technique over D2 tool steel with high chromium content. The paper reports partial melting of the original carbide grains of the Ni-based filling powder, and growing of the secondary carbide phase (Cr, Ni)_3W_3C in the form of dendrites with wide branches that enhanced mechanical properties of the weld. The optimization of bead parameters was made with design of experiment methodology complemented by a complex sample characterization including SEM, EDXS, XRD, and nanoindentation measurements. It was shown that the preheat of the substrate to a moderate temperature 523 K (250° C) establishes linear pattern of metal flow in the weld pool, resulting in the most homogeneous distribution of the primary carbides in the microstructure of weld bead.
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.
Calculation and optimization of parameters in low-flow pumps
NASA Astrophysics Data System (ADS)
Kraeva, E. M.; Masich, I. S.
2016-04-01
The materials on balance tests of high-speed centrifugal pumps with low flow rate are presented. On the bases of analysis and research synthesis, we demonstrate the rational use of impellers of semi-open and open types providing high values for energy parameters of feed system of low-flow pumps.
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.
Data Mining and Optimization Tools for Developing Engine Parameters Tools
NASA Technical Reports Server (NTRS)
Dhawan, Atam P.
1998-01-01
This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.
Process parameters optimization in ion exchange 238Pu aqueous processing
NASA Astrophysics Data System (ADS)
Pansoy-Hjelvik, M. E.; Nixon, J.; Laurinat, J.; Brock, J.; Silver, G.; Reimus, M.; Ramsey, K. B.
2000-07-01
This paper describes bench-scale efforts (5-7 grams of 238Pu) to optimize the ion exchange process for 234U separation with minimal 238Pu losses to the effluent and wash liquids. The bench-scale experiments also determine the methodology to be used for the full-scale process: 5 kg238Pu annual throughput. Heat transfer calculations used to determine the thermal gradients expected during ion exchange processing are also described. The calculations were performed in collaboration with Westinghouse Savannah River Technology Center (WSRTC) and provide information for the design of the full-scale ion exchange equipment.
Method for Predicting and Optimizing System Parameters for Electrospinning System
NASA Technical Reports Server (NTRS)
Wincheski, Russell A. (Inventor)
2011-01-01
An electrospinning system using a spinneret and a counter electrode is first operated for a fixed amount of time at known system and operational parameters to generate a fiber mat having a measured fiber mat width associated therewith. Next, acceleration of the fiberizable material at the spinneret is modeled to determine values of mass, drag, and surface tension associated with the fiberizable material at the spinneret output. The model is then applied in an inversion process to generate predicted values of an electric charge at the spinneret output and an electric field between the spinneret and electrode required to fabricate a selected fiber mat design. The electric charge and electric field are indicative of design values for system and operational parameters needed to fabricate the selected fiber mat design.
Optimizing the Yb:YAG thin disc laser design parameters
NASA Astrophysics Data System (ADS)
Javadi-Dashcasan, M.; Hajiesmaeilbaigi, F.; Razzaghi, H.; Mahdizadeh, M.; Moghadam, M.
2008-09-01
Based on quasi-three-level system, a numerical model of continuous wave thin disc laser is proposed. The fluorescence concentration quenching (FCQ), refractive index depending concentration effects and temperature distribution in the gain medium have been taken into account in the model. The first and second phenomena are not included in previously models. The model is used to determine optimum design parameters and to calculate the influence of various parameters like temperature, number of pump beam passes, active ions concentration and the crystal thickness on the operational efficiency of the laser. This model shows that for higher doping concentrations (>15%) the optical efficiency is decreased due to fluorescence concentration quenching. Our results are excellently in agreement with experimental results.
Optimal Regulation of Structural Systems with Uncertain Parameters.
1981-02-02
been addressed, in part, by Statistical Energy Analysis . Moti- vated by a concern with high frequency vibration and acoustical- structural...Parameter Systems," AFOSR-TR-79-0753 (May, 1979). 25. R. H. Lyon, Statistical Energy Analysis of Dynamical Systems: Theory and Applications, (M.I.T...Press, Cambridge, Mass., 1975). 26. E. E. Ungar, " Statistical Energy Analysis of Vibrating Systems," Trans. ASME, J. Eng. Ind. 89, 626 (1967). 139 27
Optimizing Hyperspectral Imagery Anomaly Detection through Robust Parameter Design
2011-10-01
THROUGH ROBUST PARAMETER DESIGN DISSERTATION Presented to the Faculty Graduate School of Engineering and Management Air Force Institute of Technology...Air University Air Education and Training Command in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Francis M. Mindrup...Graduate School of Engineering and Management For my loving wife, daughter and sons iv AFIT/DS/ENS/11-04 Abstract Advances in sensor technology
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.
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.
Design and parameter optimization of flip-chip bonder
NASA Astrophysics Data System (ADS)
Shim, Hyoungsub; Kang, Heuiseok; Jeong, Hoon; Cho, Youngjune; Kim, Wansoo; Kang, Shinill
2005-12-01
Bare-chip packaging becomes more popular along with the miniaturization of IT components. In this paper, we have studied flip-chip process, and developed automated bonding system. Among the several bonding method, NCP bonding is chosen and batch-type equipment is manufactured. The dual optics and vision system aligns the chip with the substrate. The bonding head equipped with temperature and force controllers bonds the chip. The system can be easily modified for other bonding methods such as ACF. In bonding process, the bonding force and temperature are known as the most dominant bonding parameters. A parametric study is performed for these two parameters. For the test sample, we used standard flip-chip test kit which consists of FR4 boards and dummy flip-chips. The bonding temperatures are chosen between 25°C to 300°C. The bonding forces are chosen between 5N and 300N. To test the bonding strength, a bonding strength tester was designed and constructed. After the bonding strength test, the samples are examined by microscope to determine the failure mode. The relations between the bonding strength and the bonding parameters are analyzed and compared with bonding models. Finally, the most suitable bonding condition is suggested in terms of temperature and force.
Optimization of technological parameters for preparation of lycopene microcapsules.
Guo, Hui; Huang, Ying; Qian, Jun-Qing; Gong, Qiu-Yi; Tang, Ying
2014-07-01
Lycopene belongs to the carotenoid family with high degree of unsaturation and all-trans form. Lycopene is easy to isomerize and auto oxide by heat, light, oxygen and different food matrices. With an increasing understanding of the health benefit of lycopene, to enhance stability and bioavailability of lycopene, ultrasonic emulsification was used to prepare lycopene microcapsules in this article. The results optimized by response surface methodology (RSM) for microcapsules consisted of four major steps: (1) 0.54 g glycerin monostearate was fully dissolved in 5 mL ethyl acetate and then added 0.02 g lycopene to form an organic phase, 100.7 mL distilled water which dissolved 0.61 g synperonic pe(R)/F68 as the aqueous phase; (2) the organic phase was pulled into the aqueous phase under stirring at 60 °C water bath for 5 min; (3) the mixture was then ultrasonic homogenized at 380 W for 20 min to form a homogenous emulsion; (4) the resulting emulsion was rotary evaporated at 50 °C water bath for 10 min under a pressure of 20 MPa. Encapsulation efficiency (EE) of lycopene microcapsules under the optimized conditions approached to 64.4%.
Wilbrandt, Steffen; Stenzel, Olaf; Kaiser, Norbert
2010-09-13
A new all-oxide design for broadband antireflection coatings with significantly reduced impact of deposition errors to the final reflectance is presented. Computational manufacturing including re-optimization during deposition has been used in the design work to account for maximum insensibility of the design with respect to deposition errors typical for plasma ion assisted deposition PIAD. Repeated deposition runs with the deducted monitoring and re-optimization strategy verify the validity of the simulations and the stability of the derived design solution.
The Study of the Optimal Parameter Settings in a Hospital Supply Chain System in Taiwan
Liao, Hung-Chang; Chen, Meng-Hao; Wang, Ya-huei
2014-01-01
This study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS's performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers. PMID:25250397
NASA Astrophysics Data System (ADS)
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Key parameter optimization and analysis of stochastic seismic inversion
NASA Astrophysics Data System (ADS)
Huang, Zhe-Yuan; Gan, Li-Deng; Dai, Xiao-Feng; Li, Ling-Gao; Wang, Jun
2012-03-01
Stochastic seismic inversion is the combination of geostatistics and seismic inversion technology which integrates information from seismic records, well logs, and geostatistics into a posterior probability density function (PDF) of subsurface models. The Markov chain Monte Carlo (MCMC) method is used to sample the posterior PDF and the subsurface model characteristics can be inferred by analyzing a set of the posterior PDF samples. In this paper, we first introduce the stochastic seismic inversion theory, discuss and analyze the four key parameters: seismic data signal-to-noise ratio (S/N), variogram, the posterior PDF sample number, and well density, and propose the optimum selection of these parameters. The analysis results show that seismic data S/N adjusts the compromise between the influence of the seismic data and geostatistics on the inversion results, the variogram controls the smoothness of the inversion results, the posterior PDF sample number determines the reliability of the statistical characteristics derived from the samples, and well density influences the inversion uncertainty. Finally, the comparison between the stochastic seismic inversion and the deterministic model based seismic inversion indicates that the stochastic seismic inversion can provide more reliable information of the subsurface character.
NASA Technical Reports Server (NTRS)
Foote, M. C.; Jones, B. B.; Hunt, B. D.; Barner, J. B.; Vasquez, R. P.; Bajuk, L. J.
1992-01-01
The composition of pulsed-ultraviolet-laser-deposited Y-Ba-Cu-O films was examined as a function of position across the substrate, laser fluence, laser spot size, substrate temperature, target conditioning, oxygen pressure and target-substrate distance. Laser fluence, laser spot size, and substrate temperature were found to have little effect on composition within the range investigated. Ablation from a fresh target surface results in films enriched in copper and barium, both of which decrease in concentration until a steady state condition is achieved. Oxygen pressure and target-substrate distance have a significant effect on film composition. In vacuum, copper and barium are slightly concentrated at the center of deposition. With the introduction of an oxygen background pressure, scattering results in copper and barium depletion in the deposition center, an effect which increases with increasing target-substrate distance. A balancing of these two effects results in stoichiometric deposition.
NASA Astrophysics Data System (ADS)
Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.
2017-03-01
Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.
Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis
NASA Astrophysics Data System (ADS)
Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo
2016-11-01
This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.
McCloy, John S.; Wolf, Walter; Wimmer, Erich; Zelinski, Brian
2013-01-09
The lattice parameter of cubic chemical vapor deposited (CVD) ZnS with measured oxygen concentrations < 0.6 at.% and hydrogen impurities of < 0.015 at.% have been measured and found to vary between -0.10% and +0.09% relative to the reference lattice parameter (5.4093 Å) of oxygen-free cubic ZnS as reported in the literature. Defects other than substitutional O must be invoked to explain these observed volume changes. The structure and thermodynamic stability of a wide range of native and impurity induced defects in ZnS have been determined by Ab initio calculations. Lattice contraction is caused by S-vacancies, substitutional O on S sites, Zn vacancies, H in S vacancies, peroxy defects, and dissociated water in S-vacancies. The lattice is expanded by interstitial H, H in Zn vacancies, dihydroxy defects, interstitial oxygen, Zn and [ZnHn] complexes (n=1,…,4), interstitial Zn, and S2 dumbbells. Oxygen, though present, likely forms substitutional defects for sulfur resulting in lattice contraction rather than as interstitial oxygen resulting in lattice expansion. It is concluded based on measurement and calculations that excess zinc atoms either at anti-sites (i.e. Zn atoms on S-sites) or possibly as interstitial Zn are responsible for the relative increase of the lattice parameter of commercially produced CVD ZnS.
NASA Astrophysics Data System (ADS)
Slawig, Thomas; Rückelt, Johannes; Sauerland, Volkmar; Srivastav, Anand; Ward, Ben
2010-05-01
Methods and results for parameter optimization and uncertainty analysis for a one dimensional marine biogeochemical model of NPZD type developed by Schartau and Oschlies are presented. The model simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean data. For the optimization, we use two strategies: At first, a genetic algorithm combined with a local search method. Secondly, a gradient-based quasi-newton SQP method to identify parameters and fit them to given observational data. For the SQP method, we use gradients generated by a source transformation tool for Automatic/Algorithmic Differentiation (AD). The algorithm is designed in a flexible way: The local method is a freely available code that can be replaced by other methods offering the same features, e.g. treatment of box constarints. Both optimization methods are parallized and can be viewed as instances of a hybrid, mixed evolutionary and deterministic optimization algorithm. We compare the performance of both approaches. Moreover, we present an uncertainty analysis of the optimized parameters with respect to Gaussian perturbed observations. Here, an ensemble of perturbed observations is taken as target or desired state for the optimization. After the optimization is applied, the distribution of the optimal parameters shows the dependenc of the parameters with respect to uncertainty in the observations.
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 Parameter Determination for Tritiated Water Storage in Polyacrylic Networks
Postolache, C.; Matei, Lidia; Georgescu, Rodica; Ionita, Gh.
2005-07-15
Due to the remarkable capacity of water retaining, croslinked polyacrylic acids (PAA) represent an interesting alternative for tritiated water trapping. The study was developed on radiolytical processes in PAA:HTO systems derivated from irradiation of polymeric network by disintegration of tritium atoms from HTO. The aim of these studies is the identification of polymeric structures and optimal storage conditions.Sol and gel fractions were determinated by radiometrical methods using PAA labeled with 14-C at carboxylic groups and T at main chains of the polymer. Simulation of radiolytical processes was realized using {gamma} radiation field emitted by a irradiation source of 60-Co which ensures a maximum of absorbed dose rate of 3 kGy/h. Self-radiolytical effects were investigated using labeled PAA in HTO with great radioactive concentration (37-185 GBq/mL). The experiment suggests as optimum for HTO storage as tritium liquid wastes a 1:30 PAA:HTO swelling degree at 18.5-37 MBqL. HTO radioactive concentration.RES studies of radiolytical processes were also realized on dry polyacrylic acid (PAA) and polyacrylic based hydrogels irradiated and determined at 77 K. In the study we observed the effect of swelling capacity of hydrogel o the formation of free radicals.
Parameter Optimization for the Gaussian Model of Folded Proteins
NASA Astrophysics Data System (ADS)
Erman, Burak; Erkip, Albert
2000-03-01
Recently, we proposed an analytical model of protein folding (B. Erman, K. A. Dill, J. Chem. Phys, 112, 000, 2000) and showed that this model successfully approximates the known minimum energy configurations of two dimensional HP chains. All attractions (covalent and non-covalent) as well as repulsions were treated as if the monomer units interacted with each other through linear spring forces. Since the governing potential of the linear springs are derived from a Gaussian potential, the model is called the ''Gaussian Model''. The predicted conformations from the model for the hexamer and various 9mer sequences all lie on the square lattice, although the model does not contain information about the lattice structure. Results of predictions for chains with 20 or more monomers also agreed well with corresponding known minimum energy lattice structures. However, these predicted conformations did not lie exactly on the square lattice. In the present work, we treat the specific problem of optimizing the potentials (the strengths of the spring constants) so that the predictions are in better agreement with the known minimum energy structures.
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.
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'.
Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method.
Parida, Arun Kumar; Routara, Bharat Chandra
2014-01-01
Taguchi's design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (v), feed (f), and depth of cut (d), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (R a ). The machining is conducted with Taguchi L9 orthogonal array, and based on the S/N analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, v 3-f 2-d 3. Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, v 1-f 1-d 3. Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach.
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
NASA Astrophysics Data System (ADS)
Hannachi, Amira; Maghraoui-Meherzi, Hager
2017-03-01
Manganese sulfide thin films have been deposited on glass slides by chemical bath deposition (CBD) method. The effects of preparative parameters such as deposition time, bath temperature, concentration of precursors, multi-layer deposition, different source of manganese, different complexing agent and thermal annealing on structural and morphological film properties have been investigated. The prepared thin films have been characterized using the X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). It exhibit the metastable forms of MnS, the hexagonal γ-MnS wurtzite phase with preferential orientation in the (002) plane or the cubic β-MnS zinc blende with preferential orientation in the (200) plane. Microstructural studies revealed the formation of MnS crystals with different morphologies, such as hexagons, spheres, cubes or flowers like.
Oliver, J.B.; Talbot, D.
2003-05-06
Multilayer coatings on large substrates with increasingly complex spectral requirements are essential for a number of optical systems, placing stringent requirements on the error tolerances of individual layers. Each layer must be deposited quite uniformly over the entire substrate surface since any nonuniformity will add to the layer-thickness error level achieved. A deposition system containing a planetary rotation system with stationary uniformity masking is modeled, with refinements of the planetary gearing, source placement, and uniformity mask shape being utilized to achieve an optimal configuration. The impact of improper planetary gearing is demonstrated theoretically, as well as experimentally, providing more comprehensive requirements than simply avoiding repetition of previous paths through the vapor plume, until all possible combinations of gear teeth have been used. Deposition efficiency and the impact on the uniformity achieved are used to validate improved source placement.
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
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
NASA Astrophysics Data System (ADS)
Li, Sui-xian; Chen, Haiyang; Sun, Min; Cheng, Zaijun
2009-11-01
Aimed at improving the calculation accuracy when calculating the energy deposition of electrons traveling in solids, a method we call optimal subdivision number searching algorithm is proposed. When treating the energy deposition of electrons traveling in solids, large calculation errors are found, we are conscious of that it is the result of dividing and summing when calculating the integral. Based on the results of former research, we propose a further subdividing and summing method. For β particles with the energy in the entire spectrum span, the energy data is set only to be the integral multiple of keV, and the subdivision number is set to be from 1 to 30, then the energy deposition calculation error collections are obtained. Searching for the minimum error in the collections, we can obtain the corresponding energy and subdivision number pairs, as well as the optimal subdivision number. The method is carried out in four kinds of solid materials, Al, Si, Ni and Au to calculate energy deposition. The result shows that the calculation error is reduced by one order with the improved algorithm.
A combinatorial optimization scheme for parameter structure identification in ground water modeling.
Tsai, Frank T C; Sun, Ne-Zheng; Yeh, William W G
2003-01-01
This research develops a methodology for parameter structure identification in ground water modeling. For a given set of observations, parameter structure identification seeks to identify the parameter dimension, its corresponding parameter pattern and values. Voronoi tessellation is used to parameterize the unknown distributed parameter into a number of zones. Accordingly, the parameter structure identification problem is equivalent to finding the number and locations as well as the values of the basis points associated with the Voronoi tessellation. A genetic algorithm (GA) is allied with a grid search method and a quasi-Newton algorithm to solve the inverse problem. GA is first used to search for the near-optimal parameter pattern and values. Next, a grid search method and a quasi-Newton algorithm iteratively improve the GA's estimates. Sensitivities of state variables to parameters are calculated by the sensitivity-equation method. MODFLOW and MT3DMS are employed to solve the coupled flow and transport model as well as the derived sensitivity equations. The optimal parameter dimension is determined using criteria based on parameter uncertainty and parameter structure discrimination. Numerical experiments are conducted to demonstrate the proposed methodology, in which the true transmissivity field is characterized by either a continuous distribution or a distribution that can be characterized by zones. We conclude that the optimized transmissivity zones capture the trend and distribution of the true transmissivity field.
NASA Astrophysics Data System (ADS)
Ashassi-Sorkhabi, H.; Dolati, H.; Parvini-Ahmadi, N.; Manzoori, J.
2002-01-01
Cupronickel alloys are known for their excellent corrosion resistance, especially in marine atmosphere. The development of an appropriate electroless bath involves the use of a reducing agent, complexing and stabilizing compounds and metallic salts. In this work, autocatalytic deposition of Ni-Cu-P alloys (28-95 wt.% Ni, 66-0 wt.% Cu, 7.5-3 wt.% P) has been carried out on 302 b steel sheets from bath containing: NiCl 2·6H 2O, CuCl 2·2H 2O, NaH 2PO 2, Na citrate, sulphosalicilic acid and triethanolamine. The effects of pH, temperature, and bath composition on the hardness and the composition of deposits have been studied. In addition, the deposition rates of alloy, nickel, copper and phosphorus were investigated and optimum conditions were obtained. The average rate of alloy deposition was 9 mg cm -2 h -1 and the optimum pH and temperature were 8.5 and 80 °C, respectively. The chemical stability of bath was desirable, and no spontaneous decomposition occurred. The changes in the structure of deposit by heat treatment were studied by the X-ray diffraction (XRD) method. The XRD patterns indicate that the copper content affects the structure changes. With increasing copper content, the phosphorus content decreased and the crystallinity of the deposits grew. After heat treatment of alloys with lower copper content at 400 °C for 1 h, the crystallization to Ni 3P was observed.
Optimization of parameters for coverage of low molecular weight proteins.
Müller, Stephan A; Kohajda, Tibor; Findeiss, Sven; Stadler, Peter F; Washietl, Stefan; Kellis, Manolis; von Bergen, Martin; Kalkhof, Stefan
2010-12-01
Proteins with molecular weights of <25 kDa are involved in major biological processes such as ribosome formation, stress adaption (e.g., temperature reduction) and cell cycle control. Despite their importance, the coverage of smaller proteins in standard proteome studies is rather sparse. Here we investigated biochemical and mass spectrometric parameters that influence coverage and validity of identification. The underrepresentation of low molecular weight (LMW) proteins may be attributed to the low numbers of proteolytic peptides formed by tryptic digestion as well as their tendency to be lost in protein separation and concentration/desalting procedures. In a systematic investigation of the LMW proteome of Escherichia coli, a total of 455 LMW proteins (27% of the 1672 listed in the SwissProt protein database) were identified, corresponding to a coverage of 62% of the known cytosolic LMW proteins. Of these proteins, 93 had not yet been functionally classified, and five had not previously been confirmed at the protein level. In this study, the influences of protein extraction (either urea or TFA), proteolytic digestion (solely, and the combined usage of trypsin and AspN as endoproteases) and protein separation (gel- or non-gel-based) were investigated. Compared to the standard procedure based solely on the use of urea lysis buffer, in-gel separation and tryptic digestion, the complementary use of TFA for extraction or endoprotease AspN for proteolysis permits the identification of an extra 72 (32%) and 51 proteins (23%), respectively. Regarding mass spectrometry analysis with an LTQ Orbitrap mass spectrometer, collision-induced fragmentation (CID and HCD) and electron transfer dissociation using the linear ion trap (IT) or the Orbitrap as the analyzer were compared. IT-CID was found to yield the best identification rate, whereas IT-ETD provided almost comparable results in terms of LMW proteome coverage. The high overlap between the proteins identified with IT
NASA Astrophysics Data System (ADS)
Coon, Joshua
Magnetic Resonance guided High Intensity Focused Ultrasound (MRgHIFU) treatments are a promising modality for cancer treatments in which a focused beam of ultrasound energy is used to kill tumor tissue. However, obstacles still exist to its widespread clinical implementation, including long treatment times. This research demonstrates reductions in treatment times through intelligent selection of the user-controllable parameters, including: the focal zone treatment path, focal zone size, focal zone spacing, and whether to treat one or several focal zone locations at any given time. Several treatments using various combinations of these parameters were simulated using a finite difference method to solve the Pennes bio-heat transfer equation for an ultrasonically heated tissue region with a wide range of acoustic, thermal, geometric, and tumor properties. The total treatment time was iteratively optimized using either a heuristic method or routines included in the Matlab software package, with constraints imposed for patient safety and treatment efficacy. The results demonstrate that large reductions in treatment time are possible through the intelligent selection of user-controllable treatment parameters. For the treatment path, treatment times are reduced by as much as an order of magnitude if the focal zones are arranged into stacks along the axial direction and a middle-front-back ordering is followed. For situations where normal tissue heating constraints are less stringent, these focal zones should have high levels of adjacency to further decrease treatment times; however, adjacency should be reduced in some cases where normal tissue constraints are more stringent. Also, the use of smaller, more concentrated focal zones produces shorter treatment times than larger, more diluted focal zones, a result verified in an agar phantom model. Further, focal zones should be packed using only a small amount of overlap in the axial direction and with a small gap in the
NASA Astrophysics Data System (ADS)
Lü, Hui; Yu, Dejie
2014-12-01
An uncertain optimization method for brake squeal reduction of vehicle disc brake system with interval parameters is presented in this paper. In the proposed method, the parameters of frictional coefficient, material properties and the thicknesses of wearing components are treated as uncertain parameters, which are described as interval variables. Attention is focused on the stability analysis of a brake system in squeal, and the stability of brake system is investigated via the complex eigenvalue analysis (CEA) method. The dominant unstable mode is extracted by performing CEA based on a linear finite element (FE) model, and the negative damping ratio corresponding to the dominant unstable mode is selected as the indicator of instability. The response surface method (RSM) is applied to approximate the implicit relationship between the unstable mode and the system parameters. A reliability-based optimization model for improving the stability of the vehicle disc brake system with interval parameters is constructed based on RSM, interval analysis and reliability analysis. The Genetic Algorithm is used to get the optimal values of design parameters from the optimization model. The stability analysis and optimization of a disc brake system are carried out, and the results show that brake squeal propensity can be reduced by using stiffer back plates. The proposed approach can be used to improve the stability of the vehicle disc brake system with uncertain parameters effectively.
Optical Parameters of Spray-Deposited CdS1- y Te y Thin Films
NASA Astrophysics Data System (ADS)
Ikhmayies, Shadia J.
2017-02-01
CdS x Te1- x and CdS1- y Te y solid solutions are usually formed in the interfacial region in CdS/CdTe solar cells during the deposition of the CdTe layer and/or the processing steps of the device. In this work, indium-doped CdS1- y Te y thin films were prepared by first producing CdS:In thin films by the spray pyrolysis technique on glass substrates, then annealing the films in nitrogen atmosphere in the presence of elemental tellurium. The films were characterized by scanning electron microscopy, energy dispersive x-ray spectroscopy, and transmittance measurements. The transmittance was used to deduce the reflectance from which the optical parameters were computed. The extinction coefficient, refractive index, the real and imaginary parts of the dielectric constant, optical conductivity, and energy loss were computed, and their dependence on the composition was investigated. In addition, the dispersion of the refractive index was analyzed by the single oscillator model, and dispersion parameters were investigated.
NASA Astrophysics Data System (ADS)
Basavaraj, C. K.; Vishwas, M.
2016-09-01
This paper discusses the process parameters for fused deposition modelling (FDM). Layer thickness, Orientation angle and shell thickness are the process variables considered for studies. Ultimate tensile strength, dimensional accuracy and manufacturing time are the response parameters. For number of experimental runs the taguchi's L9 orthogonal array is used. Taguchis S/N ratio was used to identify a set of process parameters which give good results for respective response characteristics. Effectiveness of each parameter is investigated by using analysis of variance. The material used for the studies of process parameter is Nylon.
Optimization of pulsed DC PACVD parameters: Toward reducing wear rate of the DLC films
NASA Astrophysics Data System (ADS)
Ebrahimi, Mansoureh; Mahboubi, Farzad; Naimi-Jamal, M. Reza
2016-12-01
The effect of pulsed direct current (DC) plasma-assisted chemical vapor deposition (PACVD) parameters such as temperature, duty cycle, hydrogen flow, and argon/CH4 flow ratio on the wear behavior and wear durability of the diamond-like carbon (DLC) films was studied by using response surface methodology (RSM). DLC films were deposited on nitrocarburized AISI 4140 steel. Wear rate and wear durability of the DLC films were examined with the pin-on-disk method. Field emission scanning electron microscopy, Raman spectroscopy, and nanoindentation techniques were used for studying wear mechanisms, chemical structure, and hardness of the DLC films. RSM results show that duty cycle is one of the important parameters that affect the wear rate of the DLC samples. The wear rate of the samples deposited with a duty cycle of >75% decreases with an increase in the argon/CH4 ratio. In contrast, for a duty cycle of <65%, the wear rate increases with an increase in the argon/CH4 ratio. The wear durability of the DLC samples increases with an increase in the duty cycle, hydrogen flow, and argon/CH4 flow ratio at the deposition temperature between 85 °C and 110 °C. Oxidation, fatigue, abrasive wear, and graphitization are the wear mechanisms observed on the wear scar of the DLC samples deposited with the optimum deposition conditions.
NASA Astrophysics Data System (ADS)
Bulbul, Ferhat
2011-02-01
Electroless Ni-B coatings were deposited on AISI 304 stainless steels by electroless deposition method, which was performed for nine different test conditions at various levels of temperature, concentration of NaBH4, concentration of NiCl2, and time, using the Taguchi L9(34) experimental method. The effects of deposition parameters on the crystallographic orientation of electroless Ni-B coatings were investigated using SEM and XRD equipment. SEM analysis revealed that the Ni-B coatings developed six types (pea-like, maize-like, primary nodular, blackberry-like or grapes-like, broccoli-like, and cauliflower-like) of morphological structures depending on the deposition parameters. XRD results also showed that these structures exhibited different levels of amorphous character. The concentration of NaBH4 had the most dominant effect on the morphological and crystallographic development of electroless Ni-B coatings.
Regmi, Murari; Chisholm, Matthew F; Eres, Gyula
2012-01-01
We present a comprehensive study of the parameter space for single layer graphene growth by chemical vapor deposition on Cu. The temperature is the most widely recognized parameter in single layer graphene growth. We show that the methane-to-hydrogen ratio and the growth pressure also are critical parameters that affect the structural perfection and the cleanliness of graphene. The optimal conditions for suppressing double and multilayer graphene growth occur near 1000 C, 1:20 methane-to-hydrogen ratio, and a total pressure in the range from 0.5 to 1 Torr. Raman mapping of a 40x30 m2 area shows single layer domains with 5-10 m linear dimensions. Atomic resolution imaging of suspended graphene by aberration corrected scanning transmission electron microscopy shows that the cleanest single layer graphene consists of areas of 10-15 nm linear dimensions and smaller patches of residual contamination that was undetected by other characterization methods.
Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning
Kok, Kai Yit; Rajendran, Parvathy
2016-01-01
The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. 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.
Optimal Design of Material and Process Parameters in Powder Injection Molding
NASA Astrophysics Data System (ADS)
Ayad, G.; Barriere, T.; Gelin, J. C.; Song, J.; Liu, B.
2007-04-01
The paper is concerned with optimization and parametric identification for the different stages in Powder Injection Molding process that consists first in injection of powder mixture with polymer binder and then to the sintering of the resulting powders part by solid state diffusion. In the first part, one describes an original methodology to optimize the process and geometry parameters in injection stage based on the combination of design of experiments and an adaptive Response Surface Modeling. Then the second part of the paper describes the identification strategy that one proposes for the sintering stage, using the identification of sintering parameters from dilatometeric curves followed by the optimization of the sintering process. The proposed approaches are applied to the optimization of material and process parameters for manufacturing a ceramic femoral implant. One demonstrates that the proposed approach give satisfactory results.
NASA Technical Reports Server (NTRS)
Hotchkiss, G. B.; Burmeister, L. C.; Bishop, K. A.
1980-01-01
A discrete-gradient optimization algorithm is used to identify the parameters in a one-node and a two-node capacitance model of a flat-plate collector. Collector parameters are first obtained by a linear-least-squares fit to steady state data. These parameters, together with the collector heat capacitances, are then determined from unsteady data by use of the discrete-gradient optimization algorithm with less than 10 percent deviation from the steady state determination. All data were obtained in the indoor solar simulator at the NASA Lewis Research Center.
Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong
2017-01-01
Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060
Global optimization of parameters in the reactive force field ReaxFF for SiOH.
Larsson, Henrik R; van Duin, Adri C T; Hartke, Bernd
2013-09-30
We have used unbiased global optimization to fit a reactive force field to a given set of reference data. Specifically, we have employed genetic algorithms (GA) to fit ReaxFF to SiOH data, using an in-house GA code that is parallelized across reference data items via the message-passing interface (MPI). Details of GA tuning turn-ed out to be far less important for global optimization efficiency than using suitable ranges within which the parameters are varied. To establish these ranges, either prior knowledge can be used or successive stages of GA optimizations, each building upon the best parameter vectors and ranges found in the previous stage. We have finally arrive-ed at optimized force fields with smaller error measures than those published previously. Hence, this optimization approach will contribute to converting force-field fitting from a specialist task to an everyday commodity, even for the more difficult case of reactive force fields.
Oyster Creek cycle 10 nodal model parameter optimization study using PSMS
Dougher, J.D.
1987-01-01
The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed.
Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A
2009-02-26
The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process
NASA Astrophysics Data System (ADS)
Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa
2016-12-01
High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio (S/N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.
Fault detection of feed water treatment process using PCA-WD with parameter optimization.
Zhang, Shirong; Tang, Qian; Lin, Yu; Tang, Yuling
2017-04-03
Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T(2) and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA-WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T(2) and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an automatic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results.
Multi-parameter Optimization of a Thermoelectric Power Generator and Its Working Conditions
NASA Astrophysics Data System (ADS)
Zhang, T.
2017-01-01
The global optimal working conditions and optimal couple design for thermoelectric (TE) generators with realistic thermal coupling between the heat reservoirs and the TE couple were studied in the current work. The heat fluxes enforced by the heat reservoirs at the hot and the cold junctions of the TE couple were used in combination with parameter normalization to obtain a single cubic algebraic equation relating the temperature differences between the TE couple junctions and between the heat reservoirs, through the electric load resistance ratio, the reservoir thermal conductance ratio, the reservoir thermal conductance to the TE couple thermal conductance ratio, the Thomson to Seebeck coefficient ratio, and the figure of merit ( Z) of the material based on the linear TE transport equations and their solutions. A broad reservoir thermal conductance ranging between 0.01 W/K and 100 W/K and TE element length ranging from 10-7 m to 10-3 m were explored to find the global optimal systems. The global optimal parameters related to the working conditions, i.e., reservoir thermal conductance ratio and electric load resistance ratio, and the optimal design parameter related to the TE couple were determined for a given TE material. These results demonstrated that the internal and external electric resistance, the thermal resistance between the reservoirs, the thermal resistance between the reservoir and the TE couple, and the optimal thermoelement length have to be well coordinated to obtain optimal power production.
Influence of deposition parameters on the microstructure of ion-plated films
NASA Astrophysics Data System (ADS)
Broitman, Esteban; Zimmerman, Rosa
1996-07-01
Ion plating is essentially vapor deposition onto a substrate which is the cathode of a glow discharge. The most important characteristic of the technique is that the growing film is subjected to a flux of high energy particles (neutrals and ions). In this study we report information about the effect of ion plating parameters on grain diameter and crystallite size distribution. At a constant potential grain size remains constant with the increase of ion density. On the other hand, at a constant ion density the grain size decreases with the substrate potential increment. Ion bombardment also has an effect on the crystallite size distribution. The ion plated films show a higher degree of uniformity in grain size than vacuum evaporated films. In contrast with vacuum evaporated films, where the grain size is proportional to the thickness, no variation of grain size with film thickness has been observed for the ion-plated films. Electron diffraction patterns have shown that the orientation remains near random over the entire J and V range studied.
Influence of deposition parameters on the structure and optical property of Zn(S,O) films
NASA Astrophysics Data System (ADS)
Tsai, Du-Cheng; Kuo, Bing-Hau; Chang, Zue-Chin; Chen, Erh-Chiang; Shieu, Fuh-Sheng
2017-01-01
This paper presents the influence of process parameters, including sputtering power, oxygen partial pressure ( R O), and substrate temperature on the optical property of Zn(S,O) thin films fabricated by radio frequency magnetron sputtering technology and deposited on glass substrates. The chemical composition, structural and optical properties of the samples were investigated by electron spectroscopy for chemical analysis, X-ray diffraction, and spectrophotometer. All the films mainly exhibited β-ZnS phase with (111) preferred orientation. [S]/([S]+[O]) ratio increased at high sputtering power, low RO, and low substrate temperature. Moderate ranges in sputtering power and substrate temperature and low RO resulted in large grain size. Adatoms are expected to exhibit increased mobility under these conditions. Average transmittance exceeded 75% in the visible wavelength region. Bandgap under these conditions was dominated strongly by the change in grain size and [S]/([S]+[O]) ratio. Optical properties of Zn(S,O) thin films could be modified, which is promising for optoelectronic applications.
Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model
Quilot-Turion, Bénédicte; Génard, Michel; Valsesia, Pierre; Memmah, Mohamed-Mahmoud
2016-01-01
Process-based models are effective tools to predict the phenotype of an individual in different growing conditions. Combined with a quantitative trait locus (QTL) mapping approach, it is then possible to predict the behavior of individuals with any combinations of alleles. However the number of simulations to explore the realm of possibilities may become infinite. Therefore, the use of an efficient optimization algorithm to intelligently explore the search space becomes imperative. The optimization algorithm has to solve a multi-objective problem, since the phenotypes of interest are usually a complex of traits, to identify the individuals with best tradeoffs between those traits. In this study we proposed to unroll such a combined approach in the case of peach fruit quality described through three targeted traits, using a process-based model with seven parameters controlled by QTL. We compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimization of the alleles controlling the parameters. The optimization algorithm has been adapted to deal with both continuous and combinatorial problems. We compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces. The use of a genetic model enabled the restriction of the dimension of the parameter space toward more feasible combinations of parameter values, reproducing relationships between parameters as observed in a real progeny. The results of this study demonstrated the potential of such an approach to refine the solutions toward more realistic ideotypes. Perspectives of improvement are discussed. PMID:28066450
Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model.
Quilot-Turion, Bénédicte; Génard, Michel; Valsesia, Pierre; Memmah, Mohamed-Mahmoud
2016-01-01
Process-based models are effective tools to predict the phenotype of an individual in different growing conditions. Combined with a quantitative trait locus (QTL) mapping approach, it is then possible to predict the behavior of individuals with any combinations of alleles. However the number of simulations to explore the realm of possibilities may become infinite. Therefore, the use of an efficient optimization algorithm to intelligently explore the search space becomes imperative. The optimization algorithm has to solve a multi-objective problem, since the phenotypes of interest are usually a complex of traits, to identify the individuals with best tradeoffs between those traits. In this study we proposed to unroll such a combined approach in the case of peach fruit quality described through three targeted traits, using a process-based model with seven parameters controlled by QTL. We compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimization of the alleles controlling the parameters. The optimization algorithm has been adapted to deal with both continuous and combinatorial problems. We compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces. The use of a genetic model enabled the restriction of the dimension of the parameter space toward more feasible combinations of parameter values, reproducing relationships between parameters as observed in a real progeny. The results of this study demonstrated the potential of such an approach to refine the solutions toward more realistic ideotypes. Perspectives of improvement are discussed.
"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
Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model
Rengers, Francis; Lunacek, Monte; Tucker, Gregory
2016-06-01
Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.
Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei
2016-01-01
Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762
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.
Improving hot region prediction by parameter optimization of density clustering in PPI.
Hu, Jing; Zhang, Xiaolong
2016-11-01
This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius.
Huang, Yu; Guo, Feng; Li, Yongling; Liu, Yufeng
2015-01-01
Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO) is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.
An Integrated Framework for Parameter-based Optimization of Scientific Workflows
Kumar, Vijay S.; Sadayappan, P.; Mehta, Gaurang; Vahi, Karan; Deelman, Ewa; Ratnakar, Varun; Kim, Jihie; Gil, Yolanda; Hall, Mary; Kurc, Tahsin; Saltz, Joel
2011-01-01
Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as grouping of workflow components and their mapping to machines do not a ect the accuracy of the output, others may dictate trading the output quality of individual components (and of the whole workflow) for performance. This paper describes an integrated framework which is capable of supporting performance optimizations along multiple dimensions of the parameter space. Using two real-world applications in the spatial data analysis domain, we present an experimental evaluation of the proposed framework. PMID:22068617
NASA Astrophysics Data System (ADS)
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.
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
2016-09-01
The Johnson-Cook (J-C) constitutive model is widely used in the finite element simulation, as this model shows the relationship between stress and strain in a simple way. In this paper, a cluster global optimization algorithm is proposed to determine the J-C constitutive model parameters of materials. A set of assumed parameters is used for the accuracy verification of the procedure. The parameters of two materials (401 steel and 823 steel) are determined. Results show that the procedure is reliable and effective. The relative error between the optimized and assumed parameters is no more than 4.02%, and the relative error between the optimized and assumed stress is 0.2% × 10-5. The J-C constitutive parameters can be determined more precisely and quickly than the traditional manual procedure. Furthermore, all the parameters can be simultaneously determined using several curves under different experimental conditions. A strategy is also proposed to accurately determine the constitutive parameters.
Shah, Kamran; Haq, Izhar Ul; Shah, Shaukat Ali; Khan, Farid Ullah; Khan, Sikander
2014-01-01
Laser direct metal deposition (LDMD) has developed from a prototyping to a single metal manufacturing tool. Its potential for creating multimaterial and functionally graded structures is now beginning to be explored. This work is a first part of a study in which a single layer of Inconel 718 is deposited on Ti-6Al-4V substrate. Single layer tracks were built at a range of powder mass flow rates using a coaxial nozzle and 1.5 kW diode laser operating in both continuous and pulsed beam modes. This part of the study focused on the experimental findings during the deposition of Inconel 718 powder on Ti-6Al-4V substrate. Scanning electron microscopy (SEM) and X-ray diffraction analysis were performed for characterization and phase identification. Residual stress measurement had been carried out to ascertain the effects of laser pulse parameters on the crack development during the deposition process. PMID:24592190
Shah, Kamran; Izhar Ul Haq; Shah, Shaukat Ali; Khan, Farid Ullah; Khan, Muhammad Tahir; Khan, Sikander
2014-01-01
Laser direct metal deposition (LDMD) has developed from a prototyping to a single metal manufacturing tool. Its potential for creating multimaterial and functionally graded structures is now beginning to be explored. This work is a first part of a study in which a single layer of Inconel 718 is deposited on Ti-6Al-4V substrate. Single layer tracks were built at a range of powder mass flow rates using a coaxial nozzle and 1.5 kW diode laser operating in both continuous and pulsed beam modes. This part of the study focused on the experimental findings during the deposition of Inconel 718 powder on Ti-6Al-4V substrate. Scanning electron microscopy (SEM) and X-ray diffraction analysis were performed for characterization and phase identification. Residual stress measurement had been carried out to ascertain the effects of laser pulse parameters on the crack development during the deposition process.
NASA Astrophysics Data System (ADS)
Potters, M. G.; Mansoori, M.; Bombois, X.; Jansen, J. D.; Van den Hof, P. M. J.
2016-03-01
This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using either inlet pressure/outlet pressure measurements (Heller et al., 2002) or actuator position/outlet pressure measurements, where the latter is a novel approach. The solution to the optimization problem reveals that for both measurement methods an optimal excitation frequency, an optimal inlet volume, and an optimal outlet volume exist. We find that under the same parameter variance bounds and actuator constraints, actuator position/outlet pressure measurements result in required experiment times that are a factor fourteen smaller compared to inlet pressure/outlet pressure measurements. This result is analysed in detail and we find that the dominant effect driving this difference originates from an identifiability problem when using inlet-outlet pressure measurements for joint estimation of permeability and porosity. We illustrate our results with numerical simulations, and show excellent agreement with theoretical expectations.
Iterative optimization algorithm with parameter estimation for the ambulance location problem.
Kim, Sun Hoon; Lee, Young Hoon
2016-12-01
The emergency vehicle location problem to determine the number of ambulance vehicles and their locations satisfying a required reliability level is investigated in this study. This is a complex nonlinear issue involving critical decision making that has inherent stochastic characteristics. This paper studies an iterative optimization algorithm with parameter estimation to solve the emergency vehicle location problem. In the suggested algorithm, a linear model determines the locations of ambulances, while a hypercube simulation is used to estimate and provide parameters regarding ambulance locations. First, we suggest an iterative hypercube optimization algorithm in which interaction parameters and rules for the hypercube and optimization are identified. The interaction rules employed in this study enable our algorithm to always find the locations of ambulances satisfying the reliability requirement. We also propose an iterative simulation optimization algorithm in which the hypercube method is replaced by a simulation, to achieve computational efficiency. The computational experiments show that the iterative simulation optimization algorithm performs equivalently to the iterative hypercube optimization. The suggested algorithms are found to outperform existing algorithms suggested in the literature.
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.
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)
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.
Vackel, Andrew; Sampath, Sanjay
2017-02-27
Thermal spray deposited WC-CoCr coatings are extensively used for surface protection of wear prone components in a variety of applications. Although the primary purpose of the coating is wear and corrosion protection, many of the coated components are structural systems (aero landing gear, hydraulic cylinders, drive shafts etc.) and as such experience cyclic loading during service and are potentially prone to fatigue failure. It is of interest to ensure that the coating and the application process does not deleteriously affect the fatigue strength of the parent structural metal. It has long been appreciated that the relative fatigue life of amore » thermal sprayed component can be affected by the residual stresses arising from coating deposition. The magnitude of these stresses can be managed by torch processing parameters and can also be influenced by deposition effects, particularly the deposition temperature. In this study, the effect of both torch operating parameters (particle states) and deposition conditions (notably substrate temperature) were investigated through rotating bending fatigue studies. The results indicate a strong influence of process parameters on relative fatigue life, including credit or debit to the substrate's fatigue life measured via rotating bend beam studies. Damage progression within the substrate was further explored by stripping the coating off part way through fatigue testing, revealing a delay in the onset of substrate damage with more fatigue resistant coatings but no benefit with coatings with inadequate properties. Finally, the results indicate that compressive residual stress and adequate load bearing capability of the coating (both controlled by torch and deposition parameters) delay onset of substrate damage, enabling fatigue credit of the coated component.« less
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.
Factorization and the synthesis of optimal feedback gains for distributed parameter systems
NASA Technical Reports Server (NTRS)
Milman, Mark H.; Scheid, Robert E.
1990-01-01
An approach based on Volterra factorization leads to a new methodology for the analysis and synthesis of the optimal feedback gain in the finite-time linear quadratic control problem for distributed parameter systems. The approach circumvents the need for solving and analyzing Riccati equations and provides a more transparent connection between the system dynamics and the optimal gain. The general results are further extended and specialized for the case where the underlying state is characterized by autonomous differential-delay dynamics. Numerical examples are given to illustrate the second-order convergence rate that is derived for an approximation scheme for the optimal feedback gain in the differential-delay problem.
Evaluation of a new parallel numerical parameter optimization algorithm for a dynamical system
NASA Astrophysics Data System (ADS)
Duran, Ahmet; Tuncel, Mehmet
2016-10-01
It is important to have a scalable parallel numerical parameter optimization algorithm for a dynamical system used in financial applications where time limitation is crucial. We use Message Passing Interface parallel programming and present such a new parallel algorithm for parameter estimation. For example, we apply the algorithm to the asset flow differential equations that have been developed and analyzed since 1989 (see [3-6] and references contained therein). We achieved speed-up for some time series to run up to 512 cores (see [10]). Unlike [10], we consider more extensive financial market situations, for example, in presence of low volatility, high volatility and stock market price at a discount/premium to its net asset value with varying magnitude, in this work. Moreover, we evaluated the convergence of the model parameter vector, the nonlinear least squares error and maximum improvement factor to quantify the success of the optimization process depending on the number of initial parameter vectors.
NASA Astrophysics Data System (ADS)
Gelfenbaum, G. R.; La Selle, S.; Witter, R. C.; Sugawara, D.; Jaffe, B. E.
2015-12-01
Inferring the relative magnitude of tsunamis generated during earthquakes based on the characteristics of sandy coastal deposits is a challenging problem. Using a hydrodynamic and sediment transport model, we explore whether the volume of sandy tsunami deposits can be used to infer tsunami magnitude and seafloor deformation. For large subduction zone earthquakes specifically, we are testing the hypothesis that onshore tsunami deposit volume is correlated with nearshore tsunami wave height and coseismic slip. First, we test this hypothesis using onshore tsunami deposit volume data and offshore slip for the 2011 Tohoku earthquake and tsunami. This test considers tsunami deposit volume and offshore slip as they vary alongshore across a wide range of sediment sources, offshore and onshore slopes, and boundary roughness conditions. Preliminary analysis suggests that a strong correlation exists between onshore tsunami deposit volume and adjacent offshore coseismic slip, so long as ample sediment were available along the coast to be eroded. Second, we apply a Delft3D tsunami inundation and sediment transport model to Stardust Bay in the U.S. Aleutian Islands, where 6 tsunamis in the last ~1700 years deposited marine sand across a coastal plain as much as 800 m inland and up to ~15 m above mean sea level. The youngest sand sheet, probably deposited by a tsunami generated during the 1957 Andreanof Islands earthquake (Mw 8.6), has the smallest sediment volume. Several older deposits have larger volumes. Models show that ≥10 m of slip on the Aleutian subduction megathrust offshore of Stardust Bay could produce the onshore sediment volume measured for the 1957 deposit. Older tsunami deposits of greater volume require up to 14 m of megathrust slip. Model sensitivity studies show that onshore sediment volume is most sensitive to megathrust slip and less sensitive to other unknowns such as width of fault rupture and roughness of inundated terrain
Parameter optimization capability in the trajectory code PMAST (Point-Mass Simulation Tool)
Outka, D.E.
1987-01-28
Trajectory optimization capability has been added to PMAST through addition of the Recursive Quadratic Programming code VF02AD. The scope of trajectory optimization problems the resulting code can solve is very broad, as it takes advantage of the versatility of the original PMAST code. Most three-degree-of-freedom flight-vehicle problems can be simulated with PMAST, and up to 25 parameters specifying initial conditions, weights, control histories and other problem-deck inputs can be used to meet trajectory constraints in some optimal manner. This report outlines the mathematical formulation of the optimization technique, describes the input requirements and suggests guidelines for problem formulation. An example problem is presented to demonstrate the use and features of the optimization portions of the code.
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.
Abe, Tomomi; Hashimoto, Shuji; Matsumoto, Mitsuharu
2010-02-01
epsilon-filter can reduce most kinds of noise from a single-channel noisy signal while preserving signals that vary drastically such as speech signals. It can reduce not only stationary noise but also nonstationary noise. However, it has some parameters whose values are set empirically. So far, there have been few studies to evaluate the appropriateness of the parameter settings for epsilon-filter. This paper employs the correlation coefficient of the filter output and the difference between the filter input and output as the evaluation function of the parameter setting. This paper also describes the algorithm to set the optimal parameter value of epsilon-filter automatically. To evaluate the adequateness of the obtained parameter, the mean absolute error is calculated. The experimental results show that the adequate parameter in epsilon-filter can be obtained automatically by using the proposed method.
Fourier-based reconstruction for fully 3-D PET: optimization of interpolation parameters.
Matej, Samuel; Kazantsev, Ivan G
2006-07-01
Fourier-based approaches for three-dimensional (3-D) reconstruction are based on the relationship between the 3-D Fourier transform (FT) of the volume and the two-dimensional (2-D) FT of a parallel-ray projection of the volume. The critical step in the Fourier-based methods is the estimation of the samples of the 3-D transform of the image from the samples of the 2-D transforms of the projections on the planes through the origin of Fourier space, and vice versa for forward-projection (reprojection). The Fourier-based approaches have the potential for very fast reconstruction, but their straightforward implementation might lead to unsatisfactory results if careful attention is not paid to interpolation and weighting functions. In our previous work, we have investigated optimal interpolation parameters for the Fourier-based forward and back-projectors for iterative image reconstruction. The optimized interpolation kernels were shown to provide excellent quality comparable to the ideal sinc interpolator. This work presents an optimization of interpolation parameters of the 3-D direct Fourier method with Fourier reprojection (3D-FRP) for fully 3-D positron emission tomography (PET) data with incomplete oblique projections. The reprojection step is needed for the estimation (from an initial image) of the missing portions of the oblique data. In the 3D-FRP implementation, we use the gridding interpolation strategy, combined with proper weighting approaches in the transform and image domains. We have found that while the 3-D reprojection step requires similar optimal interpolation parameters as found in our previous studies on Fourier-based iterative approaches, the optimal interpolation parameters for the main 3D-FRP reconstruction stage are quite different. Our experimental results confirm that for the optimal interpolation parameters a very good image accuracy can be achieved even without any extra spectral oversampling, which is a common practice to decrease errors
2013-01-01
Background Recovering the network topology and associated kinetic parameter values from time-series data are central topics in systems biology. Nevertheless, methods that simultaneously do both are few and lack generality. Results Here, we present a rigorous approach for simultaneously estimating the parameters and regulatory topology of biochemical networks from time-series data. The parameter estimation task is formulated as a mixed-integer dynamic optimization problem with: (i) binary variables, used to model the existence of regulatory interactions and kinetic effects of metabolites in the network processes; and (ii) continuous variables, denoting metabolites concentrations and kinetic parameters values. The approach simultaneously optimizes the Akaike criterion, which captures the trade-off between complexity (measured by the number of parameters), and accuracy of the fitting. This simultaneous optimization mitigates a possible overfitting that could result from addition of spurious regulatory interactions. Conclusion The capabilities of our approach were tested in one benchmark problem. Our algorithm is able to identify a set of plausible network topologies with their associated parameters. PMID:24176044
Sequential deposition: optimization of solvent swelling for high-performance polymer solar cells.
Liu, Yao; Liu, Feng; Wang, Hsin-Wei; Nordlund, Dennis; Sun, Zhiwei; Ferdous, Sunzida; Russell, Thomas P
2015-01-14
Organic solar cells based on a typical DPP polymer were systematically optimized by a solvent swelling assisted sequential deposition process. We investigated the influence of solvent swelling on the morphology and structure order of the swollen film and the resultant device performance. Morphological and structural characterization confirmed the realization of ideal bulk heterojunctions using a suitable swelling solvent. A trilayered morphology was also found with the conjugated polymer concentrated bottom layer, PC71BM concentrated top layer, and interpenetrated networks of donor and acceptor in the middle by solvent swelling instead of thermal annealing in the sequential solution processing method. We proposed a simple strategy to optimize the sequential deposition fabricated devices by tuning the concentration of the PC71BM solution instead of thermal annealing. The best device showed a PCE of 7.59% with a Voc of 0.61 V, Jsc of 17.95 mA/cm(2), and FF of 69.6%, which is the highest reported efficiency for devices fabricated by a sequential processing method and among the best results for DPP polymers.
Variable ingestion rate and its role in optimal foraging behavior of marine deposit feeders
Taghon, G.L.; Jumars, P.A.
1984-04-01
Tests of optimal foraging theory have focused generally on food item selection by mobile, high-trophic-level predators. Deposit-feeding invertebrates are aquatic organisms with limited mobility and hence limited ability to forage actively for food-rich patches. In addition, there is little evidence for a major role of behaviorally mediated food item choice in these animals, and growing evidence of mechanical limitations in food particle choice. Given such limited food-selection ability, varying ingestion rate in response to changes in food value is likely to be an important animal response affecting feeding energetics. A previously developed optimal foraging model predicted that ingestion rate and food value should covary positively in order to maximize net time rate of energy gain. To test this general prediction, the authors fed three species of deposit-feeding polychaetes artifical sediments which varied only in protein content (food value); other physical and chemical properties which might affect ingestion rate were kept constant. In support of the model, ingestion rates increased as protein levels increased.
Lerondel, S; Le Pape, A; Sené, C; Faure, L; Bernard, S; Diot, P; Nicolis, E; Mehtali, M; Lusky, M; Cabrini, G; Pavirani, A
2001-01-01
Cystic fibrosis is a common, heriditary disease resulting from mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Airway transfer of the CFTR gene is a potential strategy to treat or prevent the lung pathology that is the main cause of morbidity and mortality. Among the vectors used for gene therapy, adenoviruses have shown their ability to transfer the CFTR gene to respiratory epithelial cells, using either instillation or nebulization. Our objective was to characterize the lung deposition of aerosolized adenovirus by quantitative radioisotopic imaging, the only noninvasive technique allowing in vivo quantitation of inhaled drugs. We first labeled an adenovirus expressing human CFTR with the gamma-emitting radioisotope, technetium 99m (99mTc), and determined the best labeling conditions to allow preservation of virus bioactivity. We then administered the radioaerosol to baboons, determined lung regional deposition of 99mTc-labeled adenovirus, and compared the expression of CFTR transcripts 3 and 21 days after inhalation. The expression of vector-encoded mRNA ranged from 4 to 22% with respect to the endogenous CFTR mRNA depending on the lung segments. Moreover, we have developed a model using 99mTc-DTPA (diethylenetriamine pentaacetic acid), which can be used, as an alternative to adenovirus, to determine the profile of lung deposition of the vector. This study demonstrates that scintigraphy is a useful technique to achieve optimization of gene administration to the airways.
Stock optimizing in choice when a token deposit is the operant.
Widholm, J J; Silberberg, A; Hursh, S R; Imam, A A; Warren-Boulton, F R
2001-11-01
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).
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
Andersson, Kasper G; Nielsen, Sven P; Thørring, Håvard; Hansen, Hanne S; Joensen, Hans Pauli; Isaksson, Mats; Kostiainen, Eila; Suolanen, Vesa; Pálsson, Sigurdur Emil
2011-11-01
The ECOSYS model is the ingestion dose model integrated in the ARGOS and RODOS decision support systems for nuclear emergency management. The parameters used in this model have however not been updated in recent years, where the level of knowledge on various environmental processes has increased considerably. A Nordic work group has carried out a series of evaluations of the general validity of current ECOSYS default parameters. This paper specifically discusses the parameter revisions required with respect to the modelling of deposition and natural weathering of contaminants on agricultural crops, to enable the trustworthy prognostic modelling that is essential to ensure justification and optimisation of countermeasure strategies. New modelling approaches are outlined, since it was found that current ECOSYS approaches for deposition and natural weathering could lead to large prognostic errors.
NASA Astrophysics Data System (ADS)
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
2015-04-01
A multi-scale parameter-estimation method, as presented by Samaniego et al. (2010), is implemented and extended for the conceptual hydrological model COSERO. COSERO is a HBV-type model that is specialized for alpine-environments, but has been applied over a wide range of basins all over the world (see: Kling et al., 2014 for an overview). Within the methodology available small-scale information (DEM, soil texture, land cover, etc.) is used to estimate the coarse-scale model parameters by applying a set of transfer-functions (TFs) and subsequent averaging methods, whereby only TF hyper-parameters are optimized against available observations (e.g. runoff data). The parameter regionalisation approach was extended in order to allow for a more meta-heuristical handling of the transfer-functions. The two main novelties are: 1. An explicit introduction of constrains into parameter estimation scheme: The constraint scheme replaces invalid parts of the transfer-function-solution space with valid solutions. It is inspired by applications in evolutionary algorithms and related to the combination of learning and evolution. This allows the consideration of physical and numerical constraints as well as the incorporation of a priori modeller-experience into the parameter estimation. 2. Spline-based transfer-functions: Spline-based functions enable arbitrary forms of transfer-functions: This is of importance since in many cases the general relationship between sub-grid information and parameters are known, but not the form of the transfer-function itself. The contribution presents the results and experiences with the adopted method and the introduced extensions. Simulation are performed for the pre-alpine/alpine Traisen catchment in Lower Austria. References: Samaniego, L., Kumar, R., Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., doi: 10.1029/2008WR007327 Kling, H., Stanzel, P., Fuchs, M., and
Heidari, M.; Ranjithan, S.R.
1998-01-01
In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is
Optimization of injection molding parameters for poly(styrene-isobutylene-styrene) block copolymer
NASA Astrophysics Data System (ADS)
Fittipaldi, Mauro; Garcia, Carla; Rodriguez, Luis A.; Grace, Landon R.
2016-03-01
Poly(styrene-isobutylene-styrene) (SIBS) is a widely used thermoplastic elastomer in bioimplantable devices due to its inherent stability in vivo. However, the properties of the material are highly dependent on the fabrication conditions, molecular weight, and styrene content. An optimization method for injection molding is herein proposed which can be applied to varying SIBS formulations in order to maximize ultimate tensile strength, which is critical to certain load-bearing implantable applications. The number of injection molded samples required to ascertain the optimum conditions for maximum ultimate tensile strength is limited in order to minimize experimental time and effort. Injection molding parameters including nozzle temperature (three levels: 218, 246, and 274 °C), mold temperature (three levels: 50, 85, and 120 °C), injection speed (three levels: slow, medium and fast) and holding pressure time (three levels: 2, 6, and 10 seconds) were varied to fabricate dumbbell specimens for tensile testing. A three-level L9 Taguchi method utilizing orthogonal arrays was used in order to rank the importance of the different injection molding parameters and to find an optimal parameter setting to maximize the ultimate tensile strength of the thermoplastic elastomer. Based on the Taguchi design results, a Response Surface Methodology (RSM) was applied in order to build a model to predict the tensile strength of the material at different injection parameters. Finally, the model was optimized to find the injection molding parameters providing maximum ultimate tensile strength. Subsequently, the theoretically-optimum injection molding parameters were used to fabricate additional dumbbell specimens. The experimentally-determined ultimate tensile strength of these samples was found to be in close agreement (1.2%) with the theoretical results, successfully demonstrating the suitability of the Taguchi Method and RSM for optimizing injection molding parameters of SIBS.
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 operating parameters of endothermic generators with electric heating of retort
NASA Astrophysics Data System (ADS)
Dubinin, A. M.; Fink, A. V.; Kagarmanov, G. R.
2009-07-01
Equations of heat and gas balance of endothermic generator at air conversion of methane are used for optimizing the parameters with respect to maximum yield of hydrogen and carbon oxide at minimum consumption of electric energy for heating the retort with catalyst.
An analysis of the accuracy of a parameter optimization. M.S. Thesis
NASA Technical Reports Server (NTRS)
Baram, Y.
1974-01-01
The numerical operations involved in a currently used optimization technique are discussed and analyzed with special attention to the numerical accuracy. Alternative methods for deriving linear system transfer functions, finding the relationships between the transfer function coefficients and the design parameters, and solving a matrix equation are presented for more accurate and cost effective solutions.
NASA Astrophysics Data System (ADS)
Gao, P.; Shetty, S.; Momm, H. G.
2014-11-01
Evolutionary computation is used for improved information extraction from high-resolution satellite imagery. The utilization of evolutionary computation is based on stochastic selection of input parameters often defined in a trial-and-error approach. However, exploration of optimal input parameters can yield improved candidate solutions while requiring reduced computation resources. In this study, the design and implementation of a system that investigates the optimal input parameters was researched in the problem of feature extraction from remotely sensed imagery. The two primary assessment criteria were the highest fitness value and the overall computational time. The parameters explored include the population size and the percentage and order of mutation and crossover. The proposed system has two major subsystems; (i) data preparation: the generation of random candidate solutions; and (ii) data processing: evolutionary process based on genetic programming, which is used to spectrally distinguish the features of interest from the remaining image background of remote sensed imagery. The results demonstrate that the optimal generation number is around 1500, the optimal percentage of mutation and crossover ranges from 35% to 40% and 5% to 0%, respectively. Based on our findings the sequence that yielded better results was mutation over crossover. These findings are conducive to improving the efficacy of utilizing genetic programming for feature extraction from remotely sensed imagery.
NASA Astrophysics Data System (ADS)
Evstigneev, Vladislav P.; Pashkova, Irina S.; Kostjukov, Viktor V.; Hernandez Santiago, Adrian A.; Evstigneev, Maxim P.
2016-11-01
The principal condition for optimal experiment design, required for getting reasonable error for equilibrium aggregation constant, K, determination is obtained. This condition states that the selected concentration range for performing titration experiment should be inversely proportional to the expected value of K. As a consequence, the choice of physico-chemical methods for determination of aggregation parameters must obey this condition.
Parkhomchuk, V.V.; Shiltsev, V.D.
1993-06-01
The paper considers the Superconducting Super Collider (SSC) site ground motion measurements as well as data from accelerators worldwide about noises that worsen beam performance. Unacceptably fast emittance growth due to these noises is predicted for the SSC. A transverse feedback system was found to be the only satisfactory alternative to prevent emittance decay. Optimization of the primary feedback parameters was done.
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.
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 optimization of a dual-comb ranging system by using a numerical simulation method.
Wu, Guanhao; Xiong, Shilin; Ni, Kai; Zhu, Zebin; Zhou, Qian
2015-12-14
Dual-comb system parameters have significant impacts on the ranging accuracy. We present a theoretical model and a numerical simulation method for the parameter optimization of a dual-comb ranging system. With this method we investigate the impacts of repetition rate difference, repetition rate, and carrier-envelope-offset frequency on the ranging accuracy. Firstly, the simulation results suggest a series of discrete zones of repetition rate difference in an optimal range, which are consistent with the experimental results. Secondly, the simulation results of the repetition rate indicate that a higher repetition rate is very favorable to improve the ranging accuracy. Finally, the simulation results suggest a series of discrete optimal ranges of the carrier-envelope-offset frequency for the dual-comb system. The simulated results were verified by our experiments.
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.
Optimization of jet parameters to control the flow on a ramp
NASA Astrophysics Data System (ADS)
Guilmineau, Emmanuel; Duvigneau, Régis; Labroquère, Jérémie
2014-06-01
This study deals with the use of optimization algorithms to determine efficient parameters of flow control devices. To improve the performance of systems characterized by detached flows and vortex shedding, the use of flow control devices such as oscillatory jets are intensively studied. However, the determination of efficient control parameters is still a bottleneck for industrial problems. Therefore, we propose to couple a global optimization algorithm with an unsteady flow simulation to derive efficient flow control rules. We consider as a test case a backward-facing step with a slope of 25°, including a synthetic jet actuator. The aim is to reduce the time-averaged recirculation length behind the step by optimizing the jet blowing/suction amplitude and frequency.
Issues in optimal parameter estimation for the nonlinear Muskingum flood routing model
NASA Astrophysics Data System (ADS)
Geem, Zong Woo
2014-03-01
This study answers two questions raised in the parameter estimation optimization for the nonlinear Muskingum flood routing model. The first question is whether a new global optimum was still found after the existing global optimum had already been found. In order to fairly verify this question, a standard routing procedure for the nonlinear Muskingum model, which has not been clearly described previously, is proposed. Because the routing procedure was coded in a spreadsheet, any researcher can easily test it after downloading it. The second question is the reason why various approaches, such as Lagrange multiplier, Broyden-Fletcher-Goldfarb-Shanno (BFGS), genetic algorithm, harmony search and particle swarm optimization, have tackled only Wilson's data set as the parameter estimation optimization for the nonlinear Muskingum model, because Wilson's data have a unique structure which is differentiated from other data sets. This study also provides various data sets to compare.
Automated Optimization of Water–Water Interaction Parameters for a Coarse-Grained Model
2015-01-01
We have developed an automated parameter optimization software framework (ParOpt) that implements the Nelder–Mead simplex algorithm and applied it to a coarse-grained polarizable water model. The model employs a tabulated, modified Morse potential with decoupled short- and long-range interactions incorporating four water molecules per interaction site. Polarizability is introduced by the addition of a harmonic angle term defined among three charged points within each bead. The target function for parameter optimization was based on the experimental density, surface tension, electric field permittivity, and diffusion coefficient. The model was validated by comparison of statistical quantities with experimental observation. We found very good performance of the optimization procedure and good agreement of the model with experiment. PMID:24460506
Optimization of the blade trailing edge geometric parameters for a small scale ORC turbine
NASA Astrophysics Data System (ADS)
Zhang, L.; Zhuge, W. L.; Peng, J.; Liu, S. J.; Zhang, Y. J.
2013-12-01
In general, the method proposed by Whitfield and Baines is adopted for the turbine preliminary design. In this design procedure for the turbine blade trailing edge geometry, two assumptions (ideal gas and zero discharge swirl) and two experience values (WR and γ) are used to get the three blade trailing edge geometric parameters: relative exit flow angle β6, the exit tip radius R6t and hub radius R6h for the purpose of maximizing the rotor total-to-static isentropic efficiency. The method above is established based on the experience and results of testing using air as working fluid, so it does not provide a mathematical optimal solution to instruct the optimization of geometry parameters and consider the real gas effects of the organic, working fluid which must be taken into consideration for the ORC turbine design procedure. In this paper, a new preliminary design and optimization method is established for the purpose of reducing the exit kinetic energy loss to improve the turbine efficiency ηts, and the blade trailing edge geometric parameters for a small scale ORC turbine with working fluid R123 are optimized based on this method. The mathematical optimal solution to minimize the exit kinetic energy is deduced, which can be used to design and optimize the exit shroud/hub radius and exit blade angle. And then, the influence of blade trailing edge geometric parameters on turbine efficiency ηts are analysed and the optimal working ranges of these parameters for the equations are recommended in consideration of working fluid R123. This method is used to modify an existing ORC turbine exit kinetic energy loss from 11.7% to 7%, which indicates the effectiveness of the method. However, the internal passage loss increases from 7.9% to 9.4%, so the only way to consider the influence of geometric parameters on internal passage loss is to give the empirical ranges of these parameters, such as the recommended ranges that the value of γ is at 0.3 to 0.4, and the value
Improving flash flood forecasting with distributed hydrological model by parameter optimization
NASA Astrophysics Data System (ADS)
Chen, Yangbo
2016-04-01
In China, flash food is usually regarded as flood occured in small and medium sized watersheds with drainage area less than 200 km2, and is mainly induced by heavy rains, and occurs in where hydrological observation is lacked. Flash flood is widely observed in China, and is the flood causing the most casualties nowadays in China. Due to hydrological data scarcity, lumped hydrological model is difficult to be employed for flash flood forecasting which requires lots of observed hydrological data to calibrate model parameters. Physically based distributed hydrological model discrete the terrain of the whole watershed into a number of grid cells at fine resolution, assimilate different terrain data and precipitation to different cells, and derive model parameteris from the terrain properties, thus having the potential to be used in flash flood forecasting and improving flash flood prediction capability. In this study, the Liuxihe Model, a physically based distributed hydrological model mainly proposed for watershed flood forecasting is employed to simulate flash floods in the Ganzhou area in southeast China, and models have been set up in 5 watersheds. Model parameters have been derived from the terrain properties including the DEM, the soil type and land use type, but the result shows that the flood simulation uncertainty is high, which may be caused by parameter uncertainty, and some kind of uncertainty control is needed before the model could be used in real-time flash flood forecastin. Considering currently many Chinese small and medium sized watersheds has set up hydrological observation network, and a few flood events could be collected, it may be used for model parameter optimization. For this reason, an automatic model parameter optimization algorithm using Particle Swam Optimization(PSO) is developed to optimize the model parameters, and it has been found that model parameters optimized even only with one observed flood events could largely reduce the flood
Optimization of injection molding process parameters for a plastic cell phone housing component
NASA Astrophysics Data System (ADS)
Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya
2016-11-01
To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.
Parameter optimization for the visco-hyperelastic constitutive model of tendon using FEM.
Tang, C Y; Ng, G Y F; Wang, Z W; Tsui, C P; Zhang, G
2011-01-01
Numerous constitutive models describing the mechanical properties of tendons have been proposed during the past few decades. However, few were widely used owing to the lack of implementation in the general finite element (FE) software, and very few systematic studies have been done on selecting the most appropriate parameters for these constitutive laws. In this work, the visco-hyperelastic constitutive model of the tendon implemented through the use of three-parameter Mooney-Rivlin form and sixty-four-parameter Prony series were firstly analyzed using ANSYS FE software. Afterwards, an integrated optimization scheme was developed by coupling two optimization toolboxes (OPTs) of ANSYS and MATLAB for estimating these unknown constitutive parameters of the tendon. Finally, a group of Sprague-Dawley rat tendons was used to execute experimental and numerical simulation investigation. The simulated results showed good agreement with the experimental data. An important finding revealed that too many Maxwell elements was not necessary for assuring accuracy of the model, which is often neglected in most open literatures. Thus, all these proved that the constitutive parameter optimization scheme was reliable and highly efficient. Furthermore, the approach can be extended to study other tendons or ligaments, as well as any visco-hyperelastic solid materials.
Land cover classification using random forest with genetic algorithm-based parameter optimization
NASA Astrophysics Data System (ADS)
Ming, Dongping; Zhou, Tianning; Wang, Min; Tan, Tian
2016-07-01
Land cover classification based on remote sensing imagery is an important means to monitor, evaluate, and manage land resources. However, it requires robust classification methods that allow accurate mapping of complex land cover categories. Random forest (RF) is a powerful machine-learning classifier that can be used in land remote sensing. However, two important parameters of RF classification, namely, the number of trees and the number of variables tried at each split, affect classification accuracy. Thus, optimal parameter selection is an inevitable problem in RF-based image classification. This study uses the genetic algorithm (GA) to optimize the two parameters of RF to produce optimal land cover classification accuracy. HJ-1B CCD2 image data are used to classify six different land cover categories in Changping, Beijing, China. Experimental results show that GA-RF can avoid arbitrariness in the selection of parameters. The experiments also compare land cover classification results by using GA-RF method, traditional RF method (with default parameters), and support vector machine method. When the GA-RF method is used, classification accuracies, respectively, improved by 1.02% and 6.64%. The comparison results show that GA-RF is a feasible solution for land cover classification without compromising accuracy or incurring excessive time.
Effect of ablation parameters on infrared pulsed laser deposition of poly(ethylene glycol) films
NASA Astrophysics Data System (ADS)
Bubb, Daniel M.; Papantonakis, M. R.; Toftmann, B.; Horwitz, J. S.; McGill, R. A.; Chrisey, D. B.; Haglund, R. F., Jr.
2002-06-01
Polymer thin films were deposited by laser ablation using infrared radiation both resonant (2.90, 3.40, 3.45, and 8.96 mum) and nonresonant (3.30, 3.92, and 4.17 mum) with vibrational modes in the starting material, polyethylene glycol. The chemical structure of the films was characterized by Fourier transform infrared spectroscopy, while the molecular weight distribution was investigated using gel permeation chromatography. The films deposited by resonant irradiation are superior to those deposited with nonresonant radiation with respect to both the chemical structure and the molecular weight distribution of the films. However, the molecular-weight distributions of films deposited at nonresonant infrared wavelengths show marked polymer fragmentation. Fluence and wavelength dependence studies show that the effects may be related to the degree of thermal confinement, and hence to the relative absorption strengths of the targeted vibrational modes.
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
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.
Wang, Jun; Zhou, Bihua; Zhou, Shudao
2016-01-01
This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior.
NASA Technical Reports Server (NTRS)
Starlinger, Alois; Duffy, Stephen F.; Palko, Joseph L.
1993-01-01
New methods are presented that utilize the optimization of goodness-of-fit statistics in order to estimate Weibull parameters from failure data. It is assumed that the underlying population is characterized by a three-parameter Weibull distribution. Goodness-of-fit tests are based on the empirical distribution function (EDF). The EDF is a step function, calculated using failure data, and represents an approximation of the cumulative distribution function for the underlying population. Statistics (such as the Kolmogorov-Smirnov statistic and the Anderson-Darling statistic) measure the discrepancy between the EDF and the cumulative distribution function (CDF). These statistics are minimized with respect to the three Weibull parameters. Due to nonlinearities encountered in the minimization process, Powell's numerical optimization procedure is applied to obtain the optimum value of the EDF. Numerical examples show the applicability of these new estimation methods. The results are compared to the estimates obtained with Cooper's nonlinear regression algorithm.
NASA Astrophysics Data System (ADS)
Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.
2016-09-01
The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.
Optimal Feedback Scheme and Universal Time Scaling for Hamiltonian Parameter Estimation
NASA Astrophysics Data System (ADS)
Yuan, Haidong; Fung, Chi-Hang Fred
2015-09-01
Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.
NASA Technical Reports Server (NTRS)
Stahara, S. S.
1984-01-01
An investigation was carried out to complete the preliminary development of a combined perturbation/optimization procedure and associated computational code for designing optimized blade-to-blade profiles of turbomachinery blades. The overall purpose of the procedures developed is to provide demonstration of a rapid nonlinear perturbation method for minimizing the computational requirements associated with parametric design studies of turbomachinery flows. The method combines the multiple parameter nonlinear perturbation method, successfully developed in previous phases of this study, with the NASA TSONIC blade-to-blade turbomachinery flow solver, and the COPES-CONMIN optimization procedure into a user's code for designing optimized blade-to-blade surface profiles of turbomachinery blades. Results of several design applications and a documented version of the code together with a user's manual are provided.
NASA Astrophysics Data System (ADS)
von Wilpert, Jason
2013-01-01
Iron pyrite (FeS2) is a promising material to act as the light absorbing layer in a thin film solar cell. This thesis focuses on the design and optimization of a chemical vapor deposition (CVD) chamber capable of depositing iron pyrite thin films by the reaction of iron acetylacetoneate and tert-butyl disulphide in argon at 300 °C at a base pressure ranging from 10 mTorr to 760 Torr. A custom, as-built 5" CVD system is first characterized by performing experiments attempting to deposit thin films of iron pyrite at a base pressure of 10 mTorr. After initial efforts are unsuccessful, a series of modifications are made to the system, and experiments at both low and atmospheric pressure are pursued. It is found that an external chamber for the iron acetylacetoneate precursor is necessary for better control over its vapor pressure, and that the growth rate must be slow to deposit homogeneous films. Optimal results at atmospheric pressure are achieved when the flow lines of the TBDS vapor, iron acetylacetoneate vapor, and argon carrier gas are combined prior to the deposition chamber.
Caglar, Yasemin; Gorgun, Kamuran; Aksoy, Seval
2015-03-05
ZnO nanopowders were synthesized via microwave-assisted hydrothermal method at different deposition (microwave irradiation) times and pH values. The effects of pH and deposition (microwave irradiation) time on the crystalline structure and orientation of the ZnO nanopowders have been investigated by X-ray diffraction (XRD) study. XRD observations showed that the crystalline quality of ZnO nanopowders increased with increasing pH value. The crystallite size and texture coefficient values of ZnO nanopowders were calculated. The structural quality of ZnO nanopowder was improved by deposition parameters. Field emission scanning electron microscope (FESEM) was used to analyze the surface morphology of the ZnO nanopowders. Microwave irradiation time and pH value showed a significant effect on the surface morphology.
NASA Astrophysics Data System (ADS)
Caglar, Yasemin; Gorgun, Kamuran; Aksoy, Seval
2015-03-01
ZnO nanopowders were synthesized via microwave-assisted hydrothermal method at different deposition (microwave irradiation) times and pH values. The effects of pH and deposition (microwave irradiation) time on the crystalline structure and orientation of the ZnO nanopowders have been investigated by X-ray diffraction (XRD) study. XRD observations showed that the crystalline quality of ZnO nanopowders increased with increasing pH value. The crystallite size and texture coefficient values of ZnO nanopowders were calculated. The structural quality of ZnO nanopowder was improved by deposition parameters. Field emission scanning electron microscope (FESEM) was used to analyze the surface morphology of the ZnO nanopowders. Microwave irradiation time and pH value showed a significant effect on the surface morphology.
NASA Astrophysics Data System (ADS)
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.
Daneshvar, N; Khataee, A R; Rasoulifard, M H; Pourhassan, M
2007-05-08
In this paper, optimization of biological decolorization of synthetic dye solution containing Malachite Green was investigated. The effect of temperature, initial pH of the solution, type of algae, dye concentration and time of the reaction was studied and optimized using Taguchi method. Sixteen experiments were required to study the effect of parameters on biodegradation of the dye. Each of experiments was repeated three times to calculate signal/noise (S/N). Our results showed that initial pH of the solution was the most effective parameter in comparison with others and the basic pH was favorable. In this study, we also optimized the experimental parameters and chose the best condition by determination effective factors. Based on the S/N ratio, the optimized conditions for dye removal were temperature 25 degrees C, initial pH 10, dye concentration 5 ppm, algae type Chlorella and time 2.5h. The stability and efficiency of Chlorella sp. in long-term repetitive operations were also examined.
Zeng, Rongping; Badano, Aldo; Myers, Kyle
2017-02-02
We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hoteling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre-Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.
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.
NASA Astrophysics Data System (ADS)
Zeng, Rongping; Badano, Aldo; Myers, Kyle J.
2017-04-01
We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hotelling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre–Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.
NASA Technical Reports Server (NTRS)
Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian
1992-01-01
A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.
NASA Technical Reports Server (NTRS)
Schmidt, Phillip H.; Garg, Sanjay; Holowecky, Brian R.
1993-01-01
A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.
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.
Matheny, Michael E.; Resnic, Frederic S.; Arora, Nipun; Ohno-Machado, Lucila
2007-01-01
Support Vector Machines (SVM) have become popular among machine learning researchers, but their applications in biomedicine have been somewhat limited. A number of methods, such as grid search and evolutionary algorithms, have been utilized to optimize model parameters of SVMs. The sensitivity of the results to changes in optimization methods has not been investigated in the context of medical applications. In this study, radial-basis kernel SVM and polynomial kernel SVM mortality prediction models for percutaneous coronary interventions were optimized using (a) Mean Squared Error, (b) Mean Cross-Entropy Error, (c) the Area Under the Receiver Operating Characteristic, and (d) the Hosmer-Lemeshow goodness-of-fit test (HL χ2). A 3-fold cross-validation inner and outer loop method was used to select the best models using the training data, and evaluations were based on previously unseen test data. The results were compared to those produced by logistic regression models optimized using the same indices. The choice of optimization parameters had a significant impact on performance in both SVM kernel types. PMID:17600771
Matheny, Michael E; Resnic, Frederic S; Arora, Nipun; Ohno-Machado, Lucila
2007-12-01
Support vector machines (SVM) have become popular among machine learning researchers, but their applications in biomedicine have been somewhat limited. A number of methods, such as grid search and evolutionary algorithms, have been utilized to optimize model parameters of SVMs. The sensitivity of the results to changes in optimization methods has not been investigated in the context of medical applications. In this study, radial-basis kernel SVM and polynomial kernel SVM mortality prediction models for percutaneous coronary interventions were optimized using (a) mean-squared error, (b) mean cross-entropy error, (c) the area under the receiver operating characteristic, and (d) the Hosmer-Lemeshow goodness-of-fit test (HL chi(2)). A threefold cross-validation inner and outer loop method was used to select the best models using the training data, and evaluations were based on previously unseen test data. The results were compared to those produced by logistic regression models optimized using the same indices. The choice of optimization parameters had a significant impact on performance in both SVM kernel types.
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.
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.
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
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.
NASA Astrophysics Data System (ADS)
Cardiff, M. A.; Kitanidis, P. K.
2005-12-01
In this presentation we revisit the problem of semivariogram estimation and present a modular, reusable, and encapsulated set of MATLAB programs that use a hybrid Ant Colony Optimization (ACO) heuristic to solve the "optimal fit" problem. Though the ACO heuristic involves a stochastic component, advantages of the heuristic over traditional gradient-search methods, like the Gauss-Newton method, include the ability to estimate model semivariogram parameters accurately without initial guesses input by the user. The ACO heuristic is also superiorly suited for strongly nonlinear optimization over spaces that may contain several local minima. The presentation will focus on the application of ACO to existing weighted least squares and restricted maximum likelihood estimation methods with a comparison of results. The presentation will also discuss parameter uncertainty, particularly in the context of restricted maximum likelihood and Bayesian methods. We compare the local linearized parameter estimates (or Cramer-Rao lower bounds) with modern Monte Carlo methods, such as acceptance-rejection. Finally, we present ensemble kriging in which conditional realizations are generated in a way that uncertainty in semi-variogram parameters is fully accounted for. Results for a variety of sample problems will be presented along with a discussion of solution accuracy and computational efficiency.
Optimizing physical parameters in 1-D particle-in-cell simulations with Python
NASA Astrophysics Data System (ADS)
Ragan-Kelley, Benjamin; Verboncoeur, John P.; Lin, Ming-Chieh
2014-10-01
A particle-in-cell (PIC) simulation tool, OOPD1, is wrapped in the Python programming language, enabling automated algorithmic optimization of physical and numerical parameters. The Python-based environment exposes internal variables, enabling modification of simulation parameters, as well as run-time generation of new diagnostics based on calculations with internal data. For problems requiring an iterative optimization approach, this enables a programmable interactive feedback loop style simulation model, where the input to one simulation is a programmable function of the output of the previous one. This approach is applied to field-emission of electrons in a diode, in order to explore space charge effects in bipolar flow. We find an analytical solution for maximizing the space-charge limited current through a diode with an upstream ion current, and confirm the result with simulations, demonstrating the efficacy of the feedback scheme. We also demonstrate and analyze a modeling approach for scaling the ion mass, which can shorten simulation time without changing the ultimate result. The methods presented can be generalized to handle other applications where it is desirable to evolve simulation parameters based on algorithmic results from the simulation, including models in which physical or numerical parameter tuning is used to converge or optimize a system in one or more variables.
Yang, Anxiong; Stingl, Michael; Berry, David A.; Lohscheller, Jörg; Voigt, Daniel; Eysholdt, Ulrich; Döllinger, Michael
2011-01-01
With the use of an endoscopic, high-speed camera, vocal fold dynamics may be observed clinically during phonation. However, observation and subjective judgment alone may be insufficient for clinical diagnosis and documentation of improved vocal function, especially when the laryngeal disease lacks any clear morphological presentation. In this study, biomechanical parameters of the vocal folds are computed by adjusting the corresponding parameters of a three-dimensional model until the dynamics of both systems are similar. First, a mathematical optimization method is presented. Next, model parameters (such as pressure, tension and masses) are adjusted to reproduce vocal fold dynamics, and the deduced parameters are physiologically interpreted. Various combinations of global and local optimization techniques are attempted. Evaluation of the optimization procedure is performed using 50 synthetically generated data sets. The results show sufficient reliability, including 0.07 normalized error, 96% correlation, and 91% accuracy. The technique is also demonstrated on data from human hemilarynx experiments, in which a low normalized error (0.16) and high correlation (84%) values were achieved. In the future, this technique may be applied to clinical high-speed images, yielding objective measures with which to document improved vocal function of patients with voice disorders. PMID:21877808
Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1993-01-01
The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.
Kane, David B; Asgharian, Bahman; Price, Owen T; Rostami, Ali; Oldham, Michael J
2010-02-01
It is known that puffing conditions such as puff volume, duration, and frequency vary substantially among individual smokers. This study investigates how these parameters affect the particle size distribution and concentration of fresh mainstream cigarette smoke (MCS) and how these changes affect the predicted deposition of MCS particles in a model human respiratory tract. Measurements of the particle size distribution made with an electrical low pressure impactor for a variety of puffing conditions are presented. The average flow rate of the puff is found to be the major factor effecting the measured particle size distribution of the MCS. The results of these measurements were then used as input to a deterministic dosimetry model (MPPD) to estimate the changes in the respiratory tract deposition fraction of smoke particles. The MPPD dosimetry model was modified by incorporating mechanisms involved in respiratory tract deposition of MCS: hygroscopic growth, coagulation, evaporation of semivolatiles, and mixing of the smoke with inhaled dilution air. The addition of these mechanisms to MPPD resulted in reasonable agreement between predicted airway deposition and human smoke retention measurements. The modified MPPD model predicts a modest 10% drop in the total deposition efficiency in a model human respiratory tract as the puff flow rate is increased from 1050 to 3100 ml/min, for a 2-s puff.
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Optimal input design for aircraft parameter estimation using dynamic programming principles
NASA Technical Reports Server (NTRS)
Klein, Vladislav; Morelli, Eugene A.
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Algorithms of D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters
NASA Astrophysics Data System (ADS)
Widiharih, Tatik; Haryatmi, Sri; Gunardi, Wilandari, Yuciana
2016-02-01
Morgan Mercer Flodin (MMF) model is used in many areas including biological growth studies, animal and husbandry, chemistry, finance, pharmacokinetics and pharmacodynamics. Locally D-optimal designs for Morgan Mercer Flodin (MMF) models with three parameters are investigated. We used the Generalized Equivalence Theorem of Kiefer and Wolvowitz to determine D-optimality criteria. Number of roots for standardized variance are determined using Tchebysheff system concept and it is used to decide that the design is minimally supported design. In these models, designs are minimally supported designs with uniform weight on its support, and the upper bound of the design region is a support point.
NASA Astrophysics Data System (ADS)
Reimer, Joscha; Piwonski, Jaroslaw; Slawig, Thomas
2016-04-01
The statistical significance of any model-data comparison strongly depends on the quality of the used data and the criterion used to measure the model-to-data misfit. The statistical properties (such as mean values, variances and covariances) of the data should be taken into account by choosing a criterion as, e.g., ordinary, weighted or generalized least squares. Moreover, the criterion can be restricted onto regions or model quantities which are of special interest. This choice influences the quality of the model output (also for not measured quantities) and the results of a parameter estimation or optimization process. We have estimated the parameters of a three-dimensional and time-dependent marine biogeochemical model describing the phosphorus cycle in the ocean. For this purpose, we have developed a statistical model for measurements of phosphate and dissolved organic phosphorus. This statistical model includes variances and correlations varying with time and location of the measurements. We compared the obtained estimations of model output and parameters for different criteria. Another question is if (and which) further measurements would increase the model's quality at all. Using experimental design criteria, the information content of measurements can be quantified. This may refer to the uncertainty in unknown model parameters as well as the uncertainty regarding which model is closer to reality. By (another) optimization, optimal measurement properties such as locations, time instants and quantities to be measured can be identified. We have optimized such properties for additional measurement for the parameter estimation of the marine biogeochemical model. For this purpose, we have quantified the uncertainty in the optimal model parameters and the model output itself regarding the uncertainty in the measurement data using the (Fisher) information matrix. Furthermore, we have calculated the uncertainty reduction by additional measurements depending on time
Sankaran, Sethuraman; Humphrey, Jay D.; Marsden, Alison L.
2013-01-01
Computational models for vascular growth and remodeling (G&R) are used to predict the long-term response of vessels to changes in pressure, flow, and other mechanical loading conditions. Accurate predictions of these responses are essential for understanding numerous disease processes. Such models require reliable inputs of numerous parameters, including material properties and growth rates, which are often experimentally derived, and inherently uncertain. While earlier methods have used a brute force approach, systematic uncertainty quantification in G&R models promises to provide much better information. In this work, we introduce an efficient framework for uncertainty quantification and optimal parameter selection, and illustrate it via several examples. First, an adaptive sparse grid stochastic collocation scheme is implemented in an established G&R solver to quantify parameter sensitivities, and near-linear scaling with the number of parameters is demonstrated. This non-intrusive and parallelizable algorithm is compared with standard sampling algorithms such as Monte-Carlo. Second, we determine optimal arterial wall material properties by applying robust optimization. We couple the G&R simulator with an adaptive sparse grid collocation approach and a derivative-free optimization algorithm. We show that an artery can achieve optimal homeostatic conditions over a range of alterations in pressure and flow; robustness of the solution is enforced by including uncertainty in loading conditions in the objective function. We then show that homeostatic intramural and wall shear stress is maintained for a wide range of material properties, though the time it takes to achieve this state varies. We also show that the intramural stress is robust and lies within 5% of its mean value for realistic variability of the material parameters. We observe that prestretch of elastin and collagen are most critical to maintaining homeostasis, while values of the material properties are
Studies of Discharge Parameters Influence on the IPD Plasma Deposition Process
Rabinski, Marek; Zdunek, Krzysztof
2006-01-15
The paper presents recent studies of a current sheet dynamics influence on the surface engineering process of impulse plasma deposition (IPD). During the IPD process plasma is generated in the working gas due to a high-voltage high-current oscillating pulse discharge, ignited within an interelectrode region of a coaxial accelerator. The changes of plasma dynamics and generation mechanisms, e.g. the electric arc instead of the plasma sheet formation during the consecutive half-periods of discharge, cause the different deposition efficiency for accelerator with the outer electrode system composed of stainless steel rods instead of standard tubular one. The coating efficiency and deposited layer quality have been examined for the titanium nitride as the model material for surface engineering.
Gholami-Boroujeny, Shiva; Bolic, Miodrag
2016-04-01
Fitting the measured bioimpedance spectroscopy (BIS) data to the Cole model and then extracting the Cole parameters is a common practice in BIS applications. The extracted Cole parameters then can be analysed as descriptors of tissue electrical properties. To have a better evaluation of physiological or pathological properties of biological tissue, accurate extraction of Cole parameters is of great importance. This paper proposes an improved Cole parameter extraction based on bacterial foraging optimization (BFO) algorithm. We employed simulated datasets to test the performance of the BFO fitting method regarding parameter extraction accuracy and noise sensitivity, and we compared the results with those of a least squares (LS) fitting method. The BFO method showed better robustness to the noise and higher accuracy in terms of extracted parameters. In addition, we applied our method to experimental data where bioimpedance measurements were obtained from forearm in three different positions of the arm. The goal of the experiment was to explore how robust Cole parameters are in classifying position of the arm for different people, and measured at different times. The extracted Cole parameters obtained by LS and BFO methods were applied to different classifiers. Two other evolutionary algorithms, GA and PSO were also used for comparison purpose. We showed that when the classifiers are fed with the extracted feature sets by BFO fitting method, higher accuracy is obtained both when applying on training data and test data.
Optimal likelihood-based matching of volcanic sources and deposits in the Auckland Volcanic Field
NASA Astrophysics Data System (ADS)
Kawabata, Emily; Bebbington, Mark S.; Cronin, Shane J.; Wang, Ting
2016-09-01
In monogenetic volcanic fields, where each eruption forms a new volcano, focusing and migration of activity over time is a very real possibility. In order for hazard estimates to reflect future, rather than past, behavior, it is vital to assemble as much reliable age data as possible on past eruptions. Multiple swamp/lake records have been extracted from the Auckland Volcanic Field, underlying the 1.4 million-population city of Auckland. We examine here the problem of matching these dated deposits to the volcanoes that produced them. The simplest issue is separation in time, which is handled by simulating prior volcano age sequences from direct dates where known, thinned via ordering constraints between the volcanoes. The subproblem of varying deposition thicknesses (which may be zero) at five locations of known distance and azimuth is quantified using a statistical attenuation model for the volcanic ash thickness. These elements are combined with other constraints, from widespread fingerprinted ash layers that separate eruptions and time-censoring of the records, into a likelihood that was optimized via linear programming. A second linear program was used to optimize over the Monte-Carlo simulated set of prior age profiles to determine the best overall match and consequent volcano age assignments. Considering all 20 matches, and the multiple factors of age, direction, and size/distance simultaneously, results in some non-intuitive assignments which would not be produced by single factor analyses. Compared with earlier work, the results provide better age control on a number of smaller centers such as Little Rangitoto, Otuataua, Taylors Hill, Wiri Mountain, Green Hill, Otara Hill, Hampton Park and Mt Cambria. Spatio-temporal hazard estimates are updated on the basis of the new ordering, which suggest that the scale of the 'flare-up' around 30 ka, while still highly significant, was less than previously thought.
Raj, A. Moses Ezhil; Ravidhas, C.; Ravishankar, R.; Kumar, A. Rathish; Selvan, G.; Jayachandran, M.; Sanjeeviraja, C.
2009-05-06
Transparent conducting magnesium indium oxide films (MgIn{sub 2}O{sub 4}) were deposited on to quartz substrates without a buffer layer at an optimized deposition temperature of 450 deg. C to achieve high transmittance in the visible spectral range and electrical conductivity in the low temperature region. Magnesium ions are distributed over the tetrahedral and octahedral sites of the inverted spinel structure with preferential orientation along (3 1 1) Miller plane. The possible mechanism that promotes conductivity in this system is the charge transfer between the resident divalent (Mg{sup 2+}) and trivalent (In{sup 3+}) cations in addition to the available oxygen vacancies in the lattice. A room temperature electrical conductivity of 1.5 x 10{sup -5} S cm{sup -1} and an average transmittance >75% have been achieved. Hall measurements showed n-type conductivity with electron mobility value 0.95 x 10{sup -2} cm{sup 2} V{sup -1} s{sup -1} and carrier concentration 2.7 x 10{sup 19} cm{sup -3}. Smoothness of the film surface observed through atomic force microscope measurements favors this material for gas sensing and opto-electronic device development.
Parameter Identification of a Chaotic Circuit with a Hidden Attractor Using Krill Herd Optimization
NASA Astrophysics Data System (ADS)
Panahi, Shirin; Jafari, Sajad; Pham, Viet-Thanh; Kingni, Sifeu Takougang; Zahedi, Abdulhamid; Sedighy, Seyed Hassan
2016-12-01
Parameter estimation plays an important role in modeling and system identification. However, parameter estimation of chaotic systems has some basic differences with other dynamical systems due to butterfly effect. In this paper, we apply a new cost function for parameter estimation in a very interesting chaotic system, a system with a plane of equilibrium which belongs to a newly introduced category of dynamical systems: systems with hidden attractor. The nonlinear dynamics of this system is described in terms of equilibria and its stability, phase portraits, bifurcation diagram and Lyapunov exponents. In order to minimize the proposed cost function and obtain the correct parameters, we use a new efficient optimization method, Krill Herd algorithm. The results show the success of proposed procedures.
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.
Research on the optimal selection method of image complexity assessment model index parameter
NASA Astrophysics Data System (ADS)
Zhu, Yong; Duan, Jin; Qian, Xiaofei; Xiao, Bo
2015-10-01
Target recognition is widely used in national economy, space technology and national defense and other fields. There is great difference between the difficulty of the target recognition and target extraction. The image complexity is evaluating the difficulty level of extracting the target from background. It can be used as a prior evaluation index of the target recognition algorithm's effectiveness. The paper, from the perspective of the target and background characteristics measurement, describe image complexity metrics parameters using quantitative, accurate mathematical relationship. For the collinear problems between each measurement parameters, image complexity metrics parameters are clustered with gray correlation method. It can realize the metrics parameters of extraction and selection, improve the reliability and validity of image complexity description and representation, and optimize the image the complexity assessment calculation model. Experiment results demonstrate that when gray system theory is applied to the image complexity analysis, target characteristics image complexity can be measured more accurately and effectively.
NASA Astrophysics Data System (ADS)
Wang, Dong; Tsui, Kwok-Leung; Zhou, Qiang
2016-05-01
Rolling element bearings are commonly used in machines to provide support for rotating shafts. Bearing failures may cause unexpected machine breakdowns and increase economic cost. To prevent machine breakdowns and reduce unnecessary economic loss, bearing faults should be detected as early as possible. Because wavelet transform can be used to highlight impulses caused by localized bearing faults, wavelet transform has been widely investigated and proven to be one of the most effective and efficient methods for bearing fault diagnosis. In this paper, a new Gauss-Hermite integration based Bayesian inference method is proposed to estimate the posterior distribution of wavelet parameters. The innovations of this paper are illustrated as follows. Firstly, a non-linear state space model of wavelet parameters is constructed to describe the relationship between wavelet parameters and hypothetical measurements. Secondly, the joint posterior probability density function of wavelet parameters and hypothetical measurements is assumed to follow a joint Gaussian distribution so as to generate Gaussian perturbations for the state space model. Thirdly, Gauss-Hermite integration is introduced to analytically predict and update moments of the joint Gaussian distribution, from which optimal wavelet parameters are derived. At last, an optimal wavelet filtering is conducted to extract bearing fault features and thus identify localized bearing faults. Two instances are investigated to illustrate how the proposed method works. Two comparisons with the fast kurtogram are used to demonstrate that the proposed method can achieve better visual inspection performances than the fast kurtogram.
Optimizing parameters of a technical system using quality function deployment method
NASA Astrophysics Data System (ADS)
Baczkowicz, M.; Gwiazda, A.
2015-11-01
The article shows the practical use of Quality Function Deployment (QFD) on the example of a mechanized mining support. Firstly it gives a short description of this method and shows how the designing process, from the constructor point of view, looks like. The proposed method allows optimizing construction parameters and comparing them as well as adapting to customer requirements. QFD helps to determine the full set of crucial construction parameters and then their importance and difficulty of their execution. Secondly it shows chosen technical system and presents its construction with figures of the existing and future optimized model. The construction parameters were selected from the designer point of view. The method helps to specify a complete set of construction parameters, from the point of view, of the designed technical system and customer requirements. The QFD matrix can be adjusted depending on designing needs and not every part of it has to be considered. Designers can choose which parts are the most important. Due to this QFD can be a very flexible tool. The most important is to define relationships occurring between parameters and that part cannot be eliminated from the analysis.
Optimal Parameters of High Energy Ion Microprobe Systems Comprised of Lafayette Lenses
NASA Astrophysics Data System (ADS)
Dymnikov, Alexander D.; Glass, Gary A.; Rout, Bibhudutta; Dias, Johnny F.
2009-03-01
High energy optimal ion microprobes comprised of new compact magnetic quadrupole lenses (Lafayette Quadrupole Lens) are numerically investigated. The smallest beam spot size and appropriate radii of object and divergence slits are presented for different emittances and compared with the corresponding parameters of the Oxford triplet for the same total length. The parameters of the calculated microprobes include demagnification, the magnetic field in the lenses and the coefficients of spherical and chromatic aberrations for several quadrupole system configurations including the doublet, the Lafayette symmetric triplet, the Russian magnetic quadruplets and sextuplets.
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.
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.
Capdevielle, Aurélie; Sýkorová, Eva; Biscans, Béatrice; Béline, Fabrice; Daumer, Marie-Line
2013-01-15
A sustainable way to recover phosphorus (P) in swine wastewater involves a preliminary step of P dissolution followed by the separation of particulate organic matter. The next two steps are firstly the precipitation of struvite crystals done by adding a crystallization reagent (magnesia) and secondly the filtration of the crystals. A design of experiments with five process parameters was set up to optimize the size of the struvite crystals in a synthetic swine wastewater. More than 90% of P was recovered as large crystals of struvite in optimal conditions which were: low Mg:Ca ratio (2.25:1), the leading parameter, high N:P ratio (3:1), moderate stirring rate (between 45 and 90 rpm) and low temperature (below 20 °C).These results were obtained despite the presence of a large amount of calcium and using a cheap reactant (MgO). The composition of the precipitates was identified by Raman analysis and solid dissolution. Results showed that amorphous calcium phosphate (ACP) co-precipitated with struvite and that carbonates were incorporated with solid fractions.
Compton, Philip D; Strukl, Joseph V; Bai, Dina L; Shabanowitz, Jeffrey; Hunt, Donald F
2012-02-07
Electron transfer dissociation (ETD) has improved the mass spectrometric analysis of proteins and peptides with labile post-translational modifications and larger intact masses. Here, the parameters governing the reaction rate of ETD are examined experimentally. Currently, due to reagent injection and isolation events as well as longer reaction times, ETD spectra require significantly more time to acquire than collision-induced dissociation (CID) spectra (>100 ms), resulting in a trade-off in the dynamic range of tandem MS analyses when ETD-based methods are compared to CID-based methods. Through fine adjustment of reaction parameters and the selection of reagents with optimal characteristics, we demonstrate a drastic reduction in the time taken per ETD event. In fact, ETD can be performed with optimal efficiency in nearly the same time as CID at low precursor charge state (z = +3) and becomes faster at higher charge state (z > +3).
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.
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.
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.
Barz, Tilman; Löffler, Verena; Arellano-Garcia, Harvey; Wozny, Günter
2010-06-25
In this work, parameters of the steric mass-formalism SMA are optimally ascertained for a reliable determination of the adsorption isotherms of beta-lactoglobulin A and B under non-isocratic conditions. For this purpose, static batch experiments are used in contrast to the protocols based on different experimental steps, which use a chromatographic column. It is shown that parameters can already be determined for a small number of experiments by using a systematic procedure based on optimal model-based experimental design and an efficient NLP-solver. The in different works observed anti-Langmuir shape of the isotherm for small concentrations of beta-lactoglobulin A was corroborated. Moreover, we also found indications for a porosity variation with changing protein concentrations.
Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2006-01-01
This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.
NASA Astrophysics Data System (ADS)
Mu, Wen-Ying; Cui, Bao-Tong; Lou, Xu-Yang; Li, Wen
2014-07-01
This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.
Bi- and Poly- Optimal Confidence Limits for a Location and Parameter.
1983-11-01
In this report we define poly-optimal confidence intervals for a location-parameter. The formulas are given for the case of two shapes, but can easily be extended to the case of many shapes. For the case of two situations, the Gaussian and the slash, the resulting family of confidence interval estimators is examined. These interval estimators are competitors of existing so-called robust procedures. A comparison to a few of these is included. (Author)
2007-01-01
38th Annual Precise Time and Time Interval (PTTI) Meeting VERIFICATION AND OPTIMIZATION OF THE PHYSICS PARAMETERS OF THE ONBOARD GALILEO...PASSIVE HYDROGEN MASER Qinghua Wang, Pierre Mosset, Fabien Droz, Pascal Rochat Temex Time Vauseyon 29, 2000 Neuchâtel, Switzerland E-mail...clock in the Galileo navigation satellite payload, and will be the first one of its type ever to fly. Temex Neuchâtel Time is responsible for the
Ng, Sook Kien; Zygmanski, Piotr; Jeung, Andrew; Mostafavi, Hassan; Hesser, Juergen; Bellon, Jennifer R; Wong, Julia S; Lyatskaya, Yulia
2012-05-10
Digital tomosynthesis (DTS) was evaluated as an alternative to cone-beam computed tomography (CBCT) for patient setup. DTS is preferable when there are constraints with setup time, gantry-couch clearance, and imaging dose using CBCT. This study characterizes DTS data acquisition and registration parameters for the setup of breast cancer patients using nonclinical Varian DTS software. DTS images were reconstructed from CBCT projections acquired on phantoms and patients with surgical clips in the target volume. A shift-and-add algorithm was used for DTS volume reconstructions, while automated cross-correlation matches were performed within Varian DTS software. Triangulation on two short DTS arcs separated by various angular spread was done to improve 3D registration accuracy. Software performance was evaluated on two phantoms and ten breast cancer patients using the registration result as an accuracy measure; investigated parameters included arc lengths, arc orientations, angular separation between two arcs, reconstruction slice spacing, and number of arcs. The shifts determined from DTS-to-CT registration were compared to the shifts based on CBCT-to-CT registration. The difference between these shifts was used to evaluate the software accuracy. After findings were quantified, optimal parameters for the clinical use of DTS technique were determined. It was determined that at least two arcs were necessary for accurate 3D registration for patient setup. Registration accuracy of 2 mm was achieved when the reconstruction arc length was > 5° for clips with HU ≥ 1000; larger arc length (≥ 8°) was required for very low HU clips. An optimal arc separation was found to be ≥ 20° and optimal arc length was 10°. Registration accuracy did not depend on DTS slice spacing. DTS image reconstruction took 10-30 seconds and registration took less than 20 seconds. The performance of Varian DTS software was found suitable for the accurate setup of breast cancer patients
SU-E-T-478: IMRT Delivery Parameter Dependence of Dose-Mass Optimization
Couto, M; Mihaylov, I
2015-06-15
Purpose: To compare DMH and DVH optimization sensitivity to changes in IMRT delivery parameters. Methods: Two lung and two head and neck (HN) cases were retrospectively optimized using DVH and DMH optimization. For both optimization approaches, changes to two parameters were studied: number of IMRT segments (5 and 10 per beam) and the minimum segment area (2 and 6 cm2). The number of beams, beam angles, and minimum MUs per segment were the same for both optimizations approaches for each patient. During optimization, doses to the organs at risk (OARs) were iteratively lowered until the standard deviation across the PTV was above ∼3.0%. For each patient DVH and DMH plans were normalized such that 95% of the PTV received the same dose. Plan quality was evaluated by dose indices (DIs), which represent the dose delivered to a certain anatomical structure volume. For the lung cases, DIs assessed included: 1% cord, 33% heart, both lungs 20% and 30%, and 50% esophagus. In the HN cases: 1% cord, 1% brainstem, left/right parotids 50%, 50% larynx, and 50% esophagus. Results: When increasing the number of segments, while keeping a small segment area (2cm2), the average percent change of all DIs for DVH/DMH optimizations for each patient were: −4.66/4.71, 3.21/3.46, −9.62/21.69 and −3.28/−7.62. For a large segment area (6cm2): −0.26/−1.46, −5.04/−1.92, −5.23/−2.19 and 4.12/19.63. Results from increasing segment area while keeping a small number of segments (5segments/beam) were: 1.41/7.90, 8.17/11.66, 0.09/33.58 and −4.83/−11.60 for each case. For large number of segments (10 segments/beam): 8.35/1.30, −0.91/5.77, 6.29/7.08 and 2.62/5.16. Conclusion: This preliminary study showed case dependent results. Changes in IMRT parameters did not show consistent DI changes for either optimization approach. A larger population of patients is warranted for such comparison.
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.
Xie, Dongming; Liu, Dehua; Zhu, Haoli; Zhang, Jianan
2002-05-01
To optimize the fed-batch processes of glycerol fermentation in different reactor states, typical bioreactors including 500-mL shaking flask, 600-mL and 15-L airlift loop reactor, and 5-L stirred vessel were investigated. It was found that by reestimating the values of only two variable kinetic parameters associated with physical transport phenomena in a reactor, the macrokinetic model of glycerol fermentation proposed in previous work could describe well the batch processes in different reactor states. This variable kinetic parameter (VKP) approach was further applied to model-based optimization of discrete-pulse feed (DPF) strategies of both glucose and corn steep slurry for glycerol fed-batch fermentation. The experimental results showed that, compared with the feed strategies determined just by limited experimental optimization in previous work, the DPF strategies with VKPs adjusted could improve glycerol productivity at least by 27% in the scale-down and scale-up reactor states. The approach proposed appeared promising for further modeling and optimization of glycerol fermentation or the similar bioprocesses in larger scales.
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.
Azzeroni, R; Maggio, A; Fiorino, C; Mangili, P; Cozzarini, C; De Cobelli, F; Di Muzio, N G; Calandrino, R
2013-11-01
The aim of this investigation was to explore the potential of biological optimization in the case of simultaneous integrated boost on intra-prostatic dominant lesions (DIL) and evaluating the impact of TCP parameters uncertainty. Different combination of TCP parameters (TD50 and γ50 in the Poisson-like model), were considered for DILs and the prostate outside DILs (CTV) for 7 intermediate/high-risk prostate patients. The aim was to maximize TCP while constraining NTCPs below 5% for all organs at risk. TCP values were highly depending on the parameters used and ranged between 38.4% and 99.9%; the optimized median physical doses were in the range 94-116 Gy and 69-77 Gy for DIL and CTV respectively. TCP values were correlated with the overlap PTV-rectum and the minimum distance between rectum and DIL. In conclusion, biological optimization for selective dose escalation is feasible and suggests prescribed dose around 90-120 Gy to the DILs. The obtained result is critically depending on the assumptions concerning the higher radioresistence in the DILs. In case of very resistant clonogens into the DIL, it may be difficult to maximize TCP to acceptable levels without violating NTCP constraints.
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.
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
Khan, Naveed; McClean, Sally; Zhang, Shuai; Nugent, Chris
2016-01-01
In recent years, smart phones with inbuilt sensors have become popular devices to facilitate activity recognition. The sensors capture a large amount of data, containing meaningful events, in a short period of time. The change points in this data are used to specify transitions to distinct events and can be used in various scenarios such as identifying change in a patient’s vital signs in the medical domain or requesting activity labels for generating real-world labeled activity datasets. Our work focuses on change-point detection to identify a transition from one activity to another. Within this paper, we extend our previous work on multivariate exponentially weighted moving average (MEWMA) algorithm by using a genetic algorithm (GA) to identify the optimal set of parameters for online change-point detection. The proposed technique finds the maximum accuracy and F_measure by optimizing the different parameters of the MEWMA, which subsequently identifies the exact location of the change point from an existing activity to a new one. Optimal parameter selection facilitates an algorithm to detect accurate change points and minimize false alarms. Results have been evaluated based on two real datasets of accelerometer data collected from a set of different activities from two users, with a high degree of accuracy from 99.4% to 99.8% and F_measure of up to 66.7%. PMID:27792177
Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.
Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei
2015-06-25
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.
NASA Astrophysics Data System (ADS)
Jeffrey Kuo, Chung-Feng; Chiu, Hsuan-Yen; Syu, Sheng-Siang; Huy Vu, Quang
2014-01-01
This study investigated the touch panel conductive film processing quality by using a CO2 laser system. The processing material chooses ethylene terephthalate with a size of 10 cm×4 cm. Experimental results measuring the three characteristics included line width, heat-affected zone and bump height. It further analyzed the relationship between the control parameters of a CO2 laser cutting system and the quality characteristics. First, the orthogonal array in the Taguchi Method was applied to plan the experiment. The signal noise ratio (S/N) of the quality characteristics was calculated according to data obtained from the experiments. Second, data were pre-processed using the gray relation method and the processed data showed a relationship between the control parameters and various quality characteristics. Next, the fuzzy inference system was applied to solve the multiple quality characteristics to determine the optimal solution and the combinations of the optimal multiple laser control parameters. Moreover, the Back-Propagation Neural Networks (BPNN) with the Levenberg-Marquardt algorithm was applied to construct a prediction system and simulate experimental results. Finally, the optimal solution was experimentally verified. The results showed that the prediction error rate was within 5%, proving that the proposed prediction system can effectively predict the laser processing of transparent conductive film.
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.
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
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
The geological parameters affecting in-situ leaching of uranium deposits
Brooks, Robert A.
1979-01-01
This report contains material presented at the Uranium Leach Conference, which was held in Vail, Colo., August 25-27, 1976. The purpose of the presentation was to summarize some important geological concepts to a largely nongeological audience involved in the in situ extraction of uranium from buried uranium ore deposits. The major geological feature affecting the leaching of sandstone-type deposits is permeability. Important permeability variations may be caused by sedimentary structures, texture, structure, composition, and lithology. The effects of these features on leaching uranium are discussed. The major uranium districts of the U.S. and the various factors that would affect permeability and, consequently, uranium extraction in these districts are also discussed.
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.
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.
Azizi, Seyed N; Asemi, Neda
2010-11-01
This study employs the Taguchi optimization methodology to optimize the effective parameters for the pesticide (Vapam) sorption onto soil modified with natural zeolite (clinoptilolite). The experimental factors and their ranges chosen for determination of the effective parameters were: initial Vapam concentration (0.4-1.6 mg/L), initial pH of the pesticide solution (2-12), the percentage of clinoptilolite in the modified soil (0-6 %), temperature (15-35°C) and shaking time (2-24 h). The orthogonal array (OA) L(16) and the bigger the better response category of the Taguchi method were selected to determine the optimum conditions: initial Vapam concentration (1.2 mg/L), initial pH of the pesticide solution (2), the percentage of clinoptilolite in the modified soil (4 %), temperature (15°C) and shaking time (2 h). The results showed that in comparison with other parameters, the initial Vapam concentration was the most effective one for the sorption of this pesticide onto soil, modified with clinoptilolite. Moreover, after determining the optimum levels of the sorption process parameters, confirmation experiments were performed to prove the effectiveness of the Taguchi's experimental design methodology.
Temporal artifact minimization in sonoelastography through optimal selection of imaging parameters.
Torres, Gabriela; Chau, Gustavo R; Parker, Kevin J; Castaneda, Benjamin; Lavarello, Roberto J
2016-07-01
Sonoelastography is an ultrasonic technique that uses Kasai's autocorrelation algorithms to generate qualitative images of tissue elasticity using external mechanical vibrations. In the absence of synchronization between the mechanical vibration device and the ultrasound system, the random initial phase and finite ensemble length of the data packets result in temporal artifacts in the sonoelastography frames and, consequently, in degraded image quality. In this work, the analytic derivation of an optimal selection of acquisition parameters (i.e., pulse repetition frequency, vibration frequency, and ensemble length) is developed in order to minimize these artifacts, thereby eliminating the need for complex device synchronization. The proposed rule was verified through experiments with heterogeneous phantoms, where the use of optimally selected parameters increased the average contrast-to-noise ratio (CNR) by more than 200% and reduced the CNR standard deviation by 400% when compared to the use of arbitrarily selected imaging parameters. Therefore, the results suggest that the rule for specific selection of acquisition parameters becomes an important tool for producing high quality sonoelastography images.
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.
NASA Astrophysics Data System (ADS)
Tabbal, M.; Mérel, P.; Chaker, M.
We present an investigation of the effect of the process parameters, namely deposition pressure and laser intensity, on the growth and mechanical properties of carbon nitride (CNx) thin films synthesized by plasma assisted pulsed laser deposition. Deposition at high remote plasma pressure (200 mTorr) enhances both growth rate and nitrogen incorporation (up to 40 at.%), but nano-indentation measurements indicate that these films are very soft and have poor mechanical properties. At low remote plasma pressure (0.5 mTorr), the nitrogen content varies from 24 to 16 at.% with increasing laser intensity as the films become much harder and more elastic, with hardness and Young's modulus values reaching 24 GPa and 230 GPa, respectively. These effects are explained in terms of a thermalization of the laser plasma at 200 mTorr and indicate that plasma activation of nitrogen does not provide any particular benefit to the film properties when deposition is performed at high pressure. However, at low pressure, the benefit of plasma activation is evidenced through enhanced nitrogen incorporation in the films while preserving the highly energetic species in the ablation plume. Such conditions lead to the synthesis, at room temperature, of hard and elastic films having properties close to those of fullerene-like CNx.
NASA Astrophysics Data System (ADS)
Xu, Junqi; Kousaka, Hiroyuki; Umehara, Noritsugu; Diao, Dongfeng
2006-01-01
Hydrogen-free diamond-like carbon (DLC) films were deposited by a new-type surface wave-sustained plasma physical vapor deposition (SWP-PVD) system under various technique conditions. Electron density was measured by a Langmuir probe, while the film thickness and hardness were characterized using a surface profilometer and a nanoindenter, respectively. Surface morphology was investigated by an atomic force microscope (AFM). It was found that the electron density and deposition rate increased following the increase in microwave power, target voltage, or gas pressure. The typical electron density and deposition rate were about 1.87-2.04×10 11 cm -3 and 1.61-14.32 nm/min respectively. AFM images indicated that the grains of films changes as the technique parameters vary. The optical constants, refractive index n and extinction coefficient k, were obtained using an optical ellipsometry. With the increase in microwave power from 150 to 270 W, the extinction coefficient of DLC films increased from 0.05 to 0.27 while the refractive index decreased from 2.31 to 2.18.
NASA Astrophysics Data System (ADS)
Reimer, J.; Schuerch, M.; Slawig, T.
2015-03-01
The geosciences are a highly suitable field of application for optimizing model parameters and experimental designs especially because many data are collected. In this paper, the weighted least squares estimator for optimizing model parameters is presented together with its asymptotic properties. A popular approach to optimize experimental designs called local optimal experimental designs is described together with a lesser known approach which takes into account the potential nonlinearity of the model parameters. These two approaches have been combined with two methods to solve their underlying discrete optimization problem. All presented methods were implemented in an open-source MATLAB toolbox called the Optimal Experimental Design Toolbox whose structure and application is described. In numerical experiments, the model parameters and experimental design were optimized using this toolbox. Two existing models for sediment concentration in seawater and sediment accretion on salt marshes of different complexity served as an application example. The advantages and disadvantages of these approaches were compared based on these models. Thanks to optimized experimental designs, the parameters of these models could be determined very accurately with significantly fewer measurements compared to unoptimized experimental designs. The chosen optimization approach played a minor role for the accuracy; therefore, the approach with the least computational effort is recommended.
Xu, Lin
2014-10-01
Sudden cardiac arrest is one of the critical clinical syndromes in emergency situations. A cardiopulmonary resuscitation (CPR) is a necessary curing means for those patients with sudden cardiac arrest. In order to simulate effectively the hemodynamic effects of human under AEI-CPR, which is active compression-decompression CPR coupled with enhanced external counter-pulsation and inspiratory impedance threshold valve, and research physiological parameters of each part of lower limbs in more detail, a CPR simulation model established by Babbs was refined. The part of lower limbs was divided into iliac, thigh and calf, which had 15 physiological parameters. Then, these 15 physiological parameters based on genetic algorithm were optimized, and ideal simulation results were obtained finally.
Multiobjective optimization in structural design with uncertain parameters and stochastic processes
NASA Technical Reports Server (NTRS)
Rao, S. S.
1984-01-01
The application of multiobjective optimization techniques to structural design problems involving uncertain parameters and random processes is studied. The design of a cantilever beam with a tip mass subjected to a stochastic base excitation is considered for illustration. Several of the problem parameters are assumed to be random variables and the structural mass, fatigue damage, and negative of natural frequency of vibration are considered for minimization. The solution of this three-criteria design problem is found by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It is observed that the game theory approach is superior in finding a better optimum solution, assuming the proper balance of the various objective functions. The procedures used in the present investigation are expected to be useful in the design of general dynamic systems involving uncertain parameters, stochastic process, and multiple objectives.
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.
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.
Optimization of image process parameters through factorial experiments using a flat panel detector
NASA Astrophysics Data System (ADS)
Norrman, Eva; Geijer, Håkan; Persliden, Jan
2007-09-01
In the optimization process of lumbar spine examinations, factorial experiments were performed addressing the question of whether the effective dose can be reduced and the image quality maintained by adjusting the image processing parameters. A 2k-factorial design was used which is a systematic and effective method of investigating the influence of many parameters on a result variable. Radiographic images of a Contrast Detail phantom were exposed using the default settings of the process parameters for lumbar spine examinations. The image was processed using different settings of the process parameters. The parameters studied were ROI density, gamma, detail contrast enhancement (DCE), noise compensation, unsharp masking and unsharp masking kernel (UMK). The images were computer analysed and an image quality figure (IQF) was calculated and used as a measurement of the image quality. The parameters with the largest influence on image quality were noise compensation, unsharp masking, unsharp masking kernel and detail contrast enhancement. There was an interaction between unsharp masking and kernel indicating that increasing the unsharp masking improved the image quality when combined with a large kernel size. Combined with a small kernel size however the unsharp masking had a deteriorating effect. Performing a factorial experiment gave an overview of how the image quality was influenced by image processing. By adjusting the level of noise compensation, unsharp masking and kernel, the IQF was improved to a 30% lower effective dose.
Optimization of image process parameters through factorial experiments using a flat panel detector.
Norrman, Eva; Geijer, Håkan; Persliden, Jan
2007-09-07
In the optimization process of lumbar spine examinations, factorial experiments were performed addressing the question of whether the effective dose can be reduced and the image quality maintained by adjusting the image processing parameters. A 2k-factorial design was used which is a systematic and effective method of investigating the influence of many parameters on a result variable. Radiographic images of a Contrast Detail phantom were exposed using the default settings of the process parameters for lumbar spine examinations. The image was processed using different settings of the process parameters. The parameters studied were ROI density, gamma, detail contrast enhancement (DCE), noise compensation, unsharp masking and unsharp masking kernel (UMK). The images were computer analysed and an image quality figure (IQF) was calculated and used as a measurement of the image quality. The parameters with the largest influence on image quality were noise compensation, unsharp masking, unsharp masking kernel and detail contrast enhancement. There was an interaction between unsharp masking and kernel indicating that increasing the unsharp masking improved the image quality when combined with a large kernel size. Combined with a small kernel size however the unsharp masking had a deteriorating effect. Performing a factorial experiment gave an overview of how the image quality was influenced by image processing. By adjusting the level of noise compensation, unsharp masking and kernel, the IQF was improved to a 30% lower effective dose.
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.
Benton, David
2013-01-01
The criteria used to establish dietary reference values are discussed and it is suggested that the too often the "need" they aim to satisfy is at the best vaguely specified. The proposition is considered that if we aim to establish optimal nutrition we will gain from considering psychological in addition to physiological parameters. The brain is by a considerable extent the most complex and metabolically active organ in the body. As such it would be predicted that the first signs of minor subclinical deficiencies will be the disruption of the functioning of the brain. The output of the brain is the product of countless millions of biochemical processes, such that if enzyme activity is only a few percentage points less than maximum, a cumulative influence would result. A series of studies of micronutrient supplementation in well-designed trials were reviewed. In metaanalyses the cognitive functioning of children and the mood and memory of adults has been shown to respond to multivitamin/mineral supplementation. Given the concerns that have been expressed about the negative responses to high levels of micronutrients, the implications are discussed of the finding that psychological functioning may benefits from an intake greater than those currently recommended.
NASA Astrophysics Data System (ADS)
Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas
2016-04-01
Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.
NASA Astrophysics Data System (ADS)
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
2010-10-01
TECHNOLOGY INSERTION RISK REDUCTION (ESTCP Project WP-0411) Ruben Prado & John Benfer Naval Air Systems Command Diana Facchini Integran...Phosphorus Alloy Electroplating for Technology Insertion Risk Reduction" Ruben Prado, John Benfer, Diana Facchini, Keith Legg NAVAIR ISSC/FRC-SE NAS...coating. Attempts were then made to pry the coating with a sharp blade to assess whether there was any lift off of the coating which would indicate
NASA Astrophysics Data System (ADS)
Jiang, Qingsong; Su, Han; Liu, Yong; Zou, Rui; Ye, Rui; Guo, Huaicheng
2017-04-01
Nutrients loading reduction in watershed is essential for lake restoration from eutrophication. The efficient and optimal decision-making on loading reduction is generally based on water quality modeling and the quantitative identification of nutrient sources at the watershed scale. The modeling process is influenced inevitably by inherent uncertainties, especially by uncertain parameters due to equifinality. Therefore, the emerging question is: if there is parameter uncertainty, how to ensure the robustness of the optimal decisions? Based on simulation-optimization models, an integrated approach of pattern identification and analysis of robustness was proposed in this study that focuses on the impact of parameter uncertainty in water quality modeling. Here the pattern represents the discernable regularity of solutions for load reduction under multiple parameter sets. Pattern identification is achieved by using a hybrid clustering analysis (i.e., Ward-Hierarchical and K-means), which was flexible and efficient in analyzing Lake Bali near the Yangtze River in China. The results demonstrated that urban domestic nutrient load is the most potential source that should be reduced, and there are two patterns for Total Nitrogen (TN) reduction and three patterns for Total Phosphorus (TP) reduction. The patterns indicated different total reduction of nutrient loads, which reflect diverse decision preferences. The robust solution was identified by the highest accomplishment with the water quality at monitoring stations that were improved uniformly with this solution. We conducted a process analysis of robust decision-making that was based on pattern identification and uncertainty, which provides effective support for decision-making with preference under uncertainty.
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.
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)
Rosolem, R.; Shuttleworth, W. J.; Gupta, H. V.; Goncalves, L.; Zeng, X.; Restrepo-Coupe, N.
2010-12-01
About eight years of data (1999-2006) collected from a variety of sites located in the Amazon basin under the Large-scale Biosphere-Atmosphere experiment in Amazonia (LBA) are now being used to compare a large number of land surface parameterization (LSP) schemes as part of the LBA Data-Model Intercomparison Project (LBA-DMIP). We use continuous hourly meteorological data obtained from the LBA-DMIP to drive the third generation of the Simple Biosphere model (SiB3), and to conduct a comprehensive parameter estimation study in the region. The validation data comprise of sensible and latent heat flux densities (i.e., H and LE, respectively) and Net Ecosystem Exchange of CO2 (i.e., NEE). Given the large number of parameters found in current LSP schemes (such as SiB3), manual calibration can be intractable and, consequently, automatic calibration techniques have become the preferred alternative. Parameter sensitivity analysis contributes to the understanding of potential structural characteristics of a model, and also reduces the dimension of the optimization problem by fixing insensitive parameters to their nominal values. In this study, we use the variance-based Sobol sensitivity analysis approach which determines the sensitivity of each parameter based on its percent contribution to the total output variance in the model. We then conduct the optimization of the most significant parameters in SiB3 using the so called “A Multi-Algorithm, Genetically Adaptive Multiobjective” (AMALGAM) which combines two highly desired concepts in evolutionary algorithms: (1) simultaneous multimethod search, and (2) self-adaptive offspring creation. The ultimate goal of this study is to identify key parameters related to individual LBA sites that need to be properly analyzed and calibrated in order to improve simulated land surface processes in the region. We anticipate that this will also help how measurements of these parameters are obtained in situ. The performance of SiB3 prior
NASA Astrophysics Data System (ADS)
Kler, A. M.; Zakharov, Yu. B.; Potanina, Yu. M.
2014-06-01
In the present paper, we evaluate the effectiveness of the coordinated solution to the optimization problem for the parameters of cycles in gas turbine and combined cycle power plants and to the optimization problem for the gas-turbine flow path parameters within an integral complex problem. We report comparative data for optimizations of the combined cycle power plant at coordinated and separate optimizations, when, first, the gas turbine and, then, the steam part of a combined cycle plant is optimized. The comparative data are presented in terms of economic indicators, energy-effectiveness characteristics, and specific costs. Models that were used in the present study for calculating the flow path enable taking into account, as a factor influencing the economic and energy effectiveness of the power plant, the heat stability of alloys from which the nozzle and rotor blades of gas-turbine stages are made.
Optimal control of distributed parameter systems using adaptive critic neural networks
NASA Astrophysics Data System (ADS)
Padhi, Radhakant
In this dissertation, two systematic optimal control synthesis techniques are presented for distributed parameter systems based on the adaptive critic neural networks. Following the philosophy of dynamic programming, this adaptive critic optimal control synthesis approach has many desirable features, viz. having a feedback form of the control, ability for on-line implementation, no need for approximating the nonlinear system dynamics, etc. More important, unlike the dynamic programming, it can accomplish these objectives without getting overwhelmed by the computational and storage requirements. First, an approximate dynamic programming based adaptive critic control synthesis formulation was carried out assuming an approximation of the system dynamics in a discrete form. A variety of example problems were solved using this proposed general approach. Next a different formulation is presented, which is capable of directly addressing the continuous form of system dynamics for control design. This was obtained following the methodology of Galerkin projection based weighted residual approximation using a set of orthogonal basis functions. The basis functions were designed by with the help of proper orthogonal decomposition, which leads to a very low-dimensional lumped parameter representation. The regulator problems of linear and nonlinear heat equations were revisited. Optimal controllers were synthesized first assuming a continuous controller and then a set of discrete controllers in the spatial domain. Another contribution of this study is the formulation of simplified adaptive critics for a large class of problems, which can be interpreted as a significant improvement of the existing adaptive critic technique.
Jevtić, Aleksandar; Gutiérrez, Alvaro
2011-01-01
Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the distributed bees algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA's control parameters by means of a genetic algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots' distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce.
Jevtić, Aleksandar; Gutiérrez, Álvaro
2011-01-01
Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677
Optimization of process parameters for the rapid biosynthesis of hematite nanoparticles.
Rajendran, Kumar; Sen, Shampa
2016-06-01
Hematite (α-Fe2O3) nanoparticles are widely used in various applications including gas sensors, pigments owing to its low cost, environmental friendliness, non-toxicity and high resistance to corrosion. These nanoparticles were generally synthesized by different chemical methods. In the present study, nanoparticles were synthesized rapidly without heat treatment by biosynthesis approach using culture supernatant of Bacillus cereus SVK1. The physiochemical parameters for rapid synthesis were optimized by using UV-visible spectroscopy. The time taken for hematite nanoparticle synthesis was found to increase with the increasing concentration of the precursor. This might be due to the inadequate proportion of quantity of biomolecules present in the culture supernatant to the precursor which led to delayed bioreduction. Greater quantities of culture supernatant with respect to precursor lead to rapid synthesis of hematite nanoparticles. The nucleation of the hematite nucleus happens more easily when the solution pH was less than 10. The optimum parameters identified for the rapid biosynthesis of hematite nanoparticles were pH9, 37°C (temperature) and 1mM ferric chloride as precursor. The particles were well crystallized hexagonal structured hematite nanoparticles and are predominantly (110)-oriented. The synthesized nanoparticles were found to contain predominantly iron (73.47%) and oxygen (22.58%) as evidenced by Energy Dispersive X-ray analysis. Hematite nanoparticles of 15-40nm diameters were biosynthesized in 48h under optimized conditions, compared to 21days before optimization.
Alessandri, Angelo; Gaggero, Mauro; Zoppoli, Riccardo
2012-06-01
Optimal control for systems described by partial differential equations is investigated by proposing a methodology to design feedback controllers in approximate form. The approximation stems from constraining the control law to take on a fixed structure, where a finite number of free parameters can be suitably chosen. The original infinite-dimensional optimization problem is then reduced to a mathematical programming one of finite dimension that consists in optimizing the parameters. The solution of such a problem is performed by using sequential quadratic programming. Linear combinations of fixed and parameterized basis functions are used as the structure for the control law, thus giving rise to two different finite-dimensional approximation schemes. The proposed paradigm is general since it allows one to treat problems with distributed and boundary controls within the same approximation framework. It can be applied to systems described by either linear or nonlinear elliptic, parabolic, and hyperbolic equations in arbitrary multidimensional domains. Simulation results obtained in two case studies show the potentials of the proposed approach as compared with dynamic programming.
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)
Ahmed, Naveed; Alahmari, Abdulrahman M.; Darwish, Saied; Naveed, Madiha
2016-12-01
Micro-channels are considered as the integral part of several engineering devices such as micro-channel heat exchangers, micro-coolers, micro-pulsating heat pipes and micro-channels used in gas turbine blades for aerospace applications. In such applications, a fluid flow is required to pass through certain micro-passages such as micro-grooves and micro-channels. The fluid flow characteristics (flow rate, turbulence, pressure drop and fluid dynamics) are mainly established based on the size and accuracy of micro-passages. Variations (oversizing and undersizing) in micro-passage's geometry directly affect the fluid flow characteristics. In this study, the micro-channels of several sizes are fabricated in well-known aerospace nickel alloy (Inconel 718) through laser beam micro-milling. The variations in geometrical characteristics of different-sized micro-channels are studied under the influences of different parameters of Nd:YAG laser. In order to have a minimum variation in the machined geometries of each size of micro-channel, the multi-objective optimization of laser parameters has been carried out utilizing the response surface methodology approach. The objective was set to achieve the targeted top widths and depths of micro-channels with minimum degree of taperness associated with the micro-channel's sidewalls. The optimized sets of laser parameters proposed for each size of micro-channel can be used to fabricate the micro-channels in Inconel 718 with minimum amount of geometrical variations.
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
NASA Astrophysics Data System (ADS)
Spooner, Greg J. R.; Marre, Gabrielle; Miller, Doug L.; Williams, A. R.
2000-06-01
Laser induced optical breakdown (LIOB) in fluids produces a localized plasma, an expanding radial shock wave front, heat transfer from the plasma to the fluid, and the formation of cavitation bubbles. Collectively these phenomena are referred to as photodisruption. Subjecting photodisruptively produced cavitation bubble nuclei to an ultrasonic field can result in strong cavitation and local cellular destruction. The ability of ultrafast lasers to produce spatially localized photodisruptions with microJoule pulse energies in combination with the possibility of larger scale tissue destruction using ultrasound presents an attractive and novel technique for selective and non-invasive tissue modification, referred to as photodisruptively nucleated ultrasonic cavitation (PNUC). Optimization of PNUC parameters in a confocal laser and ultrasound geometry is presented. The cavitation signal as measured with an ultrasound receiver was maximized to determine optimal laser and ultrasound spatial overlap in water. A flow chamber was used to evaluate the effect of the laser and ultrasound parameters on the lysis of whole canine red blood cells in saline. Parameters evaluated included laser pulse energy and ultrasound pressure amplitude.
NASA Astrophysics Data System (ADS)
Garland, Joshua; James, Ryan G.; Bradley, Elizabeth
2016-02-01
Delay-coordinate reconstruction is a proven modeling strategy for building effective forecasts of nonlinear time series. The first step in this process is the estimation of good values for two parameters, the time delay and the embedding dimension. Many heuristics and strategies have been proposed in the literature for estimating these values. Few, if any, of these methods were developed with forecasting in mind, however, and their results are not optimal for that purpose. Even so, these heuristics—intended for other applications—are routinely used when building delay coordinate reconstruction-based forecast models. In this paper, we propose an alternate strategy for choosing optimal parameter values for forecast methods that are based on delay-coordinate reconstructions. The basic calculation involves maximizing the shared information between each delay vector and the future state of the system. We illustrate the effectiveness of this method on several synthetic and experimental systems, showing that this metric can be calculated quickly and reliably from a relatively short time series, and that it provides a direct indication of how well a near-neighbor based forecasting method will work on a given delay reconstruction of that time series. This allows a practitioner to choose reconstruction parameters that avoid any pathologies, regardless of the underlying mechanism, and maximize the predictive information contained in the reconstruction.
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.
Schliebs, Stefan; Defoin-Platel, Michaël; Worner, Sue; Kasabov, Nikola
2009-01-01
This study introduces a quantum-inspired spiking neural network (QiSNN) as an integrated connectionist system, in which the features and parameters of an evolving spiking neural network are optimized together with the use of a quantum-inspired evolutionary algorithm. We propose here a novel optimization method that uses different representations to explore the two search spaces: A binary representation for optimizing feature subsets and a continuous representation for evolving appropriate real-valued configurations of the spiking network. The properties and characteristics of the improved framework are studied on two different synthetic benchmark datasets. Results are compared to traditional methods, namely a multi-layer-perceptron and a naïve Bayesian classifier (NBC). A previously used real world ecological dataset on invasive species establishment prediction is revisited and new results are obtained and analyzed by an ecological expert. The proposed method results in a much faster convergence to an optimal solution (or a close to it), in a better accuracy, and in a more informative set of features selected.
Optimization of parameters in the emulsification process by two different methods.
Carlotti, M E; Pattarino, F; Gasco, M R; Brusasca, P
1993-12-01
Synopsis An O/W emulsion with a lipopeptidic emulsifier was optimized by means of two different methods, specifically by experimental design and by selective variation of the parameters. Two optimized emulsions were obtained; they had similar values of emulsification (time and rate of homogenization) and amounts of components. Résumé Une émulsion O/E, avec un lipopeptide comme tensioactif, a été optimisée par deux méthodes d'optimisation différentes, notamment par l'experimental design et par la variation selective de certain paramètres. Deux émulsions optimisées ont été ainsi obtenues: ces émulsions ont des valeurs d'emulsification (temp et vitesse d'homogénéisation) et des quantités des composantes très proches.
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 Astrophysics Data System (ADS)
Zhai, Guofu; Wang, Qiya; Ren, Wanbin
The cooperative characteristics of electromagnetic relay's attraction torque and reaction torque are the key property to ensure its reliability, and it is important to attain better cooperative characteristics by analyzing and optimizing relay's electromagnetic system and mechanical system. From the standpoint of changing reaction torque of mechanical system, in this paper, adjusted parameters (armature's maximum angular displacement αarm_max, initial return spring's force Finiti_return_spring, normally closed (NC) contacts' force FNC_contacts, contacts' gap δgap, and normally opened (NO) contacts' over travel δNO_contacts) were adopted as design variables, and objective function was provided for with the purpose of increasing breaking velocities of both NC contacts and NO contacts. Finally, genetic algorithm (GA) was used to attain optimization of the objective function. Accuracy of calculation for the relay's dynamic characteristics was verified by experiment.
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.
Ficarro, Scott B; Adelmant, Guillaume; Tomar, Maria N; Zhang, Yi; Cheng, Vincent J; Marto, Jarrod A
2009-06-01
Qualitative and quantitative analysis of phosphorylation continues to be both an important and a challenging experimental paradigm in proteomics-based research. Unfortunately researchers face difficulties inherent to the optimization of complex, multivariable methods and their application to the analysis of rare and often experimentally intractable phosphorylated peptides. Here we describe a platform based on manipulation of magnetic beads in a 96-well format that facilitates rapid evaluation of experimental parameters required for enrichment of phosphopeptides. Optimized methods provided for automated enrichment and subsequent LC-MS/MS detection of over 1000 unique phosphopeptides (approximately 1% FDR) from 50 microg of cell lysates. In addition we demonstrate use of this platform for identification of phosphopeptides derived from proteins separated by SDS-PAGE and visualized near the detection limit of silver staining.
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.
Auto-tuning of PID controller parameters with supervised receding horizon optimization.
Xu, Min; Li, Shaoyuan; Qi, Chenkun; Cai, Wenjian
2005-10-01
In this paper, a novel two-layer online auto-tuning algorithm is presented for a nonlinear time-varying system. The lower layer consists of a conventional proportional-integral-derivative (PID) controller and a plant process, while the upper layer is composed of identification and tuning modules. The purpose of the upper layer is to find a set of optimal PID parameters for the lower layer via an online receding horizon optimization approach, which result in a time-varying PID controller. Through mathematical analysis, the proposed system performance is equivalent to that of a standard generalized predictive control. Simulation and experiment demonstrate that the new method has a better control system performance compared with conventional PID controllers.
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.
Torres-Acosta, Mario A; Aguilar-Yañez, Jose M; Rito-Palomares, Marco; Titchener-Hooker, Nigel J
2015-01-01
Royalactin is a protein with several different potential uses in humans. Research, in insects and in mammalian cells, has shown that it can accelerate cell division and prevent apoptosis. The method of action is through the use of the epidermal growth factor receptor, which is present in humans. Potential use in humans could be to lower cholesterolemic levels in blood, and to elicit similar effects to those seen in bees, e.g., increased lifespan. Mass production of Royalactin has not been accomplished, though a recent article presented a Pichia pastoris fermentation and recovery by aqueous two-phase systems at laboratory scale as a possible basis for production. Economic modelling is a useful tool with which compare possible outcomes for the production of such a molecule and in particular, to locate areas where additional research is needed and optimization may be required. This study uses the BioSolve software to perform an economic analysis on the scale-up of the putative process for Royalactin. The key parameters affecting the cost of production were located via a sensitivity analysis and then evaluated by Monte Carlo analysis. Results show that if titer is not optimized the strategy to maintain a low cost of goods is process oriented. After optimization of this parameter the strategy changes to a product-oriented and the target output becomes the critical parameter determining the cost of goods. This study serves to provide a framework for the evaluation of strategies for future production of Royalactin, by analyzing the factors that influence its cost of manufacture.
Optimization of HNA etching parameters to produce high aspect ratio solid silicon microneedles
NASA Astrophysics Data System (ADS)
Hamzah, A. A.; Abd Aziz, N.; Yeop Majlis, B.; Yunas, J.; Dee, C. F.; Bais, B.
2012-09-01
High aspect ratio solid silicon microneedles with a concave conic shape were fabricated. Hydrofluoric acid-nitric acid-acetic acid (HNA) etching parameters were characterized and optimized to produce microneedles that have long and narrow bodies with smooth surfaces, suitable for transdermal drug delivery applications. The etching parameters were characterized by varying the HNA composition, the optical mask's window size, the etching temperature and bath agitation. An L9 orthogonal Taguchi experiment with three factors, each having three levels, was utilized to determine the optimal fabrication parameters. Isoetch contours for HNA composition with 0% and 10% acetic acid concentrations were presented and a high nitric acid region was identified to produce microneedles with smooth surfaces. It is observed that an increase in window size indiscriminately increases the etch rate in both the vertical and lateral directions, while an increase in etching temperature beyond 35 °C causes the etching to become rapid and uncontrollable. Bath agitation and sample placement could be manipulated to achieve a higher vertical etch rate compared to its lateral counterpart in order to construct high aspect ratio microneedles. The Taguchi experiment performed suggests that a HNA composition of 2:7:1 (HF:HNO3:CH3COOH), window size of 500 µm and agitation rate of 450 RPM are optimal. Solid silicon microneedles with an average height of 159.4 µm, an average base width of 110.9 µm, an aspect ratio of 1.44, and a tip angle and diameter of 19.2° and 0.38 µm respectively were successfully fabricated.
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.
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)
Gao, Zhongmei; Shao, Xinyu; Jiang, Ping; Cao, Longchao; Zhou, Qi; Yue, Chen; Liu, Yang; Wang, Chunming
2016-09-01
It is of great significance to select appropriate welding process parameters for obtaining optimal weld geometry in hybrid laser-arc welding. An integrated optimization approach by combining Kriging model and GA is proposed to optimize process parameters. A four-factor, five-level experiment using Taguchi L25 is conducted considering laser power (P), welding current (A), distance between laser and arc (D) and traveling speed (V). Kriging model is adopted to approximate the relationship between process parameters and weld geometry, namely depth of penetration (DP), bead width (BW) and bead reinforcement (BR). The constructed Kriging model was used for parameters optimization by GA to maximize DP, minimize BW and ensure BR at a desired value. The effects of process parameters on weld geometry are analyzed. Microstructure and micro-hardness are also discussed. Verification experiments demonstrate that the obtained optimum values are in good agreement with experimental results.
NASA Astrophysics Data System (ADS)
Prieß, M.; Piwonski, J.; Koziel, S.; Oschlies, A.; Slawig, T.
2013-08-01
We present the application of the Surrogate-based Optimization (SBO) method on a parameter identification problem for a 3-D biogeochemical model. SBO is a method for acceleration of optimization processes when the underlying model itself is of very high computational complexity. In these cases, coupled simulation runs require large amounts of computer time, where optimization runs may become unfeasible even with high-performance hardware. As a consequence, the key idea of SBO is to replace the original and computationally expensive (high-fidelity) model by a so-called surrogate, which is created from a less accurate but computationally cheaper (low-fidelity) model and a suitable correction approach to increase its accuracy. To date, the SBO approach has been widely and successfully used in engineering applications and also for parameter identification in a 1-D marine ecosystem model of NPZD type. In this paper, we apply the approach onto a two-component biogeochemical model. The model is spun-up into a steady seasonal cycle via the Transport Matrix Approach. The low-fidelity model we use consists of a reduced number of spin-up iterations (several decades instead of millennia used for the original model). A multiplicative correction operator is further exploited to extrapolate the rather inaccurate low-fidelity model onto the original one. This corrected model builds our surrogate. We validate this SBO method by twin-experiments that use synthetic observations generated by the original model. We motivate our choice of the low-fidelity model and the multiplicative correction and discuss the computational advantage of SBO in comparison to an expensive parameter optimization in the context of the high-fidelity model. The proposed SBO technique is shown to yield a solution close to the target at a significant gain of computational efficiency. Without further regularization techniques, the method is able to identify most model parameters. The method is simple to
NASA Astrophysics Data System (ADS)
Baelmans, M.; Blommaert, M.; Dekeyser, W.; Van Oevelen, T.
2017-03-01
Plasma edge transport codes play a key role in the design of future divertor concepts. Their long simulation times in combination with a large number of control parameters turn the design into a challenging task. In aerodynamics and structural mechanics, adjoint-based optimization techniques have proven successful to tackle similar design challenges. This paper provides an overview of achievements and remaining challenges with these techniques for complex divertor design. It is shown how these developments pave the way for fast sensitivity analysis and improved design from different perspectives.
Fine tuning of phase qubit parameters for optimization of fast single-pulse readout
Revin, Leonid S.; Pankratov, Andrey L.
2011-04-18
We analyze a two-level quantum system, describing the phase qubit, during a single-pulse readout process by a numerical solution of the time-dependent Schroedinger equation. It has been demonstrated that the readout error has a minimum for certain values of the system's basic parameters. In particular, the optimization of the qubit capacitance and the readout pulse shape leads to significant reduction in the readout error. It is shown that in an ideal case the fidelity can be increased to almost 97% for 2 ns pulse duration and to 96% for 1 ns pulse duration.
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)
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
A Reduced Extended Kalman Filter Method For Data Assimilation And Parameter Optimization
NASA Astrophysics Data System (ADS)
Kao, C. J.
2007-12-01
This work is an extension of our two recent papers [Kao et al., Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys., 196 (2004), 705-723, and Kao et al., Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter, J. Comp. Phys., 214 (2006), 725-737 ] about the applications of the extended Kalman filter (EKF) to data assimilation in predictive codes. We have shown through the above two studies that the EKF method successfully estimates the evolving model state variables as well as model parameters of a shock-wave system by merging single-point pressure data into an Euler-equations computer code. We here intend to introduce a reduced EKF for the same purposes in terms of data assimilation and parameter optimization, but with a much smaller computational cost so that the applications of EKF to multi-dimensional realistic problems can be made possible. One of the distinctive features of EKF is that, as the system evolves forward in time, the EKF algorithm tracks the time-dependent error-covariance matrix of the model's state variables and parameters based on a consistent tangent-linear approximation of the model dynamics. When data becomes available at one instant in time, the update of the model state variables and parameters is achieved through a functional form of the linear merger of the model prediction and the data, subjective to the minimization of the trace of the error-covariance matrix of the model state variables and parameters. It, however, has been a concern that the calculation for the time evolution of the error-covariance matrix in applying EKF is computationally demanding and prohibitively expensive for real multi-dimensional problems. Several simplified approaches of EKF have been proposed to reduce the computational burden. This current study was actually motivated by Dee's work [Dee, P. D., 1991: Simplification of the
Optimizing Aqua Splicer Parameters for Lycra-Cotton Core Spun Yarn Using Taguchi Method
NASA Astrophysics Data System (ADS)
Midha, Vinay Kumar; Hiremath, ShivKumar; Gupta, Vaibhav
2015-10-01
In this paper, optimization of the aqua splicer parameters viz opening time, splicing time, feed arm code (i.e. splice length) and duration of water joining was carried out for 37 tex lycra-cotton core spun yarn for better retained splice strength (RSS%), splice abrasion resistance (RYAR%) and splice appearance (RYA%) using Taguchi experimental design. It is observed that as opening time, splicing time and duration of water joining increase, the RSS% and RYAR% increases, whereas increase in feed arm code leads to decrease in both. The opening time and feed arm code do not have significant effect on RYA%. The optimum RSS% of 92.02 % was obtained at splicing parameters of 350 ms opening time, 180 ms splicing time, 65 feed arm code and 600 ms duration of water joining.
Optimal harvesting of prey-predator system with interval biological parameters: a bioeconomic model.
Pal, D; Mahaptra, G S; Samanta, G P
2013-02-01
The paper presents the study of one prey one predator harvesting model with imprecise biological parameters. Due to the lack of precise numerical information of the biological parameters such as prey population growth rate, predator population decay rate and predation coefficients, we consider the model with imprecise data as form of an interval in nature. Many authors have studied prey-predator harvesting model in different form, here we consider a simple prey-predator model under impreciseness and introduce parametric functional form of an interval and then study the model. We identify the equilibrium points of the model and discuss their stabilities. The existence of bionomic equilibrium of the model is discussed. We study the optimal harvest policy and obtain the solution in the interior equilibrium using Pontryagin's maximum principle. Numerical examples are presented to support the proposed model.
Mandal, Subhamoy; Nasonova, Elena; Deán-Ben, Xosé Luís; Razansky, Daniel
2014-01-01
In tomographic optoacoustic imaging, multiple parameters related to both light and ultrasound propagation characteristics of the medium need to be adequately selected in order to accurately recover maps of local optical absorbance. Speed of sound in the imaged object and surrounding medium is a key parameter conventionally assumed to be uniform. Mismatch between the actual and predicted speed of sound values may lead to image distortions but can be mitigated by manual or automatic optimization based on metrics of image sharpness. Although some simple approaches based on metrics of image sharpness may readily mitigate distortions in the presence of highly contrasting and sharp image features, they may not provide an adequate performance for smooth signal variations as commonly present in realistic whole-body optoacoustic images from small animals. Thus, three new hybrid methods are suggested in this work, which are shown to outperform well-established autofocusing algorithms in mouse experiments in vivo. PMID:25431756
NASA Astrophysics Data System (ADS)
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.
Girard, S.; Ouerdane, Y.; Boukenter, A.; Meunier, J.-P.
2006-01-15
We characterized the behaviors of eight prototype single-mode optical fibers, made by the modified chemical-vapor deposition process, under pulsed x-ray ({approx}1 MeV) irradiation. For this purpose, we measured the time-dependent changes (10{sup -6}-10{sup 2} s) in the radiation-induced attenuation at 1.55 and 1.31 {mu}m after exposure to an x-ray pulse. By using a dedicated set of prototype germanosilicate fibers with carefully designed process parameters, we show the predominant impact on their vulnerability of the two codopants (germanium and phosphorus) incorporated in their claddings ({approx}0.3 Wt %). Compared to these influences on the radiation-induced loss levels and recovery kinetics, the impacts of the preform deposition temperature and of the fiber drawing tension on the fiber radiation sensitivity are less important. However, our results show that lowering the standard preform deposition temperature from 2000 to 1600 deg. C and the drawing tension from 140 to 20 g slightly decreases the induced losses at both wavelengths. We propose some hypotheses on the radiation-induced defects and physical mechanisms at the origin of these influences.
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
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.
Mente, Carsten; Prade, Ina; Brusch, Lutz; Breier, Georg; Deutsch, Andreas
2011-07-01
Lattice-gas cellular automata (LGCAs) can serve as stochastic mathematical models for collective behavior (e.g. pattern formation) emerging in populations of interacting cells. In this paper, a two-phase optimization algorithm for global parameter estimation in LGCA models is presented. In the first phase, local minima are identified through gradient-based optimization. Algorithmic differentiation is adopted to calculate the necessary gradient information. In the second phase, for global optimization of the parameter set, a multi-level single-linkage method is used. As an example, the parameter estimation algorithm is applied to a LGCA model for early in vitro angiogenic pattern formation.
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.
NASA Astrophysics Data System (ADS)
Wu, Xinrong; Han, Guijun; Zhang, Shaoqing; Liu, Zhengyu
2016-02-01
Model error is a major obstacle for enhancing the forecast skill of El Niño-Southern Oscillation (ENSO). Among three kinds of model error sources—dynamical core misfitting, physical scheme approximation and model parameter errors, the model parameter errors are treatable by observations. Based on the Zebiak-Cane model, an ensemble coupled data assimilation system is established to study the impact of parameter optimization (PO) on ENSO predictions within a biased twin experiment framework. "Observations" of sea surface temperature anomalies drawn from the "truth" model are assimilated into a biased prediction model in which model parameters are erroneously set from the "truth" values. The degree by which the assimilation and prediction with or without PO recover the "truth" is a measure of the impact of PO. Results show that PO improves ENSO predictability—enhancing the seasonal-interannual forecast skill by about 18 %, extending the valid lead time up to 33 % and ameliorating the spring predictability barrier. Although derived from idealized twin experiments, results here provide some insights when a coupled general circulation model is initialized from the observing system.
OPTIMIZATION-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.
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.
NASA Astrophysics Data System (ADS)
nabili, sara; shahbazi majd, nafiseh
2013-04-01
Liquefaction has been a source of major damages during severe earthquakes. To evaluate this phenomenon there are several stress, strain and energy based approaches. Use of the energy method has been more focused by researchers due to its advantages with respect to other approaches. The use of the energy concept to define the liquefaction potential is validated through laboratory element and centrifuge tests as well as field studies. This approach is based on the hypothesis that pore pressure buildup is directly related to the dissipated energy in sands which is the accumulated areas between the stress-strain loops. Numerous investigations were performed to find a relationship which correlates the dissipated energy to the soil parameters, but there are not sufficient studies to relate this dissipated energy, known as demand energy, concurrently, to the seismological and the soil parameters. The aim of this paper is to investigate the dependency of the demand energy in sands to seismological and the soil parameters. To perform this task, an effective stress analysis has been executed using FLAC finite difference program. Finn model, which is a built-in constitutive model implemented in FLAC program, was utilized. Since an important stage to predict the liquefaction is the prediction of excess pore water pressure at a given point, a simple numerical framework is presented to assess its generation during a cyclic loading in a given centrifuge test. According to the results, predicted excess pore water pressures did not closely match to the measured excess pore water pressure values in the centrifuge test but they can be used in the numerical assessment of excess pore water pressure with an acceptable degree of preciseness. Subsequently, the centrifuge model was reanalyzed using several real earthquake acceleration records with different seismological parameters such as earthquake magnitude and Hypocentral distance. The accumulated energies (demand energy) dissipated in
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)
Pawłowski, Dominik; Okupny, Daniel; Włodarski, Wojciech; Zieliński, Tomasz
2014-12-01
Geostatistical methods for 2D and 3D modelling spatial variability of selected physicochemical properties of biogenic sediments were applied to a small valley mire in order to identify the processes that lead to the formation of various types of peat. A sequential Gaussian simulation was performed to reproduce the statistical distribution of the input data (pH and organic matter) and their semivariances, as well as to honouring of data values, yielding more `realistic' models that show microscale spatial variability, despite the fact that the input sample cores were sparsely distributed in the X-Y space of the study area. The stratigraphy of peat deposits in the Ldzań mire shows a record of long-term evolution of water conditions, which is associated with the variability in water supply over time. Ldzań is a fen (a rheotrophic mire) with a through-flow of groundwater. Additionally, the vicinity of the Grabia River is marked by seasonal inundations of the southwest part of the mire and increased participation of mineral matter in the peat. In turn, the upper peat layers of some of the central part of Ldzań mire are rather spongy, and these peat-forming phytocoenoses probably formed during permanent waterlogging.
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
Chan, Emory M; Xu, Chenxu; Mao, Alvin W; Han, Gang; Owen, Jonathan S; Cohen, Bruce E; Milliron, Delia J
2010-05-12
While colloidal nanocrystals hold tremendous potential for both enhancing fundamental understanding of materials scaling and enabling advanced technologies, progress in both realms can be inhibited by the limited reproducibility of traditional synthetic methods and by the difficulty of optimizing syntheses over a large number of synthetic parameters. Here, we describe an automated platform for the reproducible synthesis of colloidal nanocrystals and for the high-throughput optimization of physical properties relevant to emerging applications of nanomaterials. This robotic platform enables precise control over reaction conditions while performing workflows analogous to those of traditional flask syntheses. We demonstrate control over the size, size distribution, kinetics, and concentration of reactions by synthesizing CdSe nanocrystals with 0.2% coefficient of variation in the mean diameters across an array of batch reactors and over multiple runs. Leveraging this precise control along with high-throughput optical and diffraction characterization, we effectively map multidimensional parameter space to tune the size and polydispersity of CdSe nanocrystals, to maximize the photoluminescence efficiency of CdTe nanocrystals, and to control the crystal phase and maximize the upconverted luminescence of lanthanide-doped NaYF(4) nanocrystals. On the basis of these demonstrative examples, we conclude that this automated synthesis approach will be of great utility for the development of diverse colloidal nanomaterials for electronic assemblies, luminescent biological labels, electroluminescent devices, and other emerging applications.
Stewart, James J P
2007-12-01
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.
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.
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
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.
Chapek, Julie . E-mail: Julie.chapek@hci.utah.edu; Tobler, Matt; Toy, Beau J.; Lee, Christopher M.; Leavitt, Dennis D.
2005-01-01
The inability to avoid rectal wall irradiation has been a limiting factor in prostate cancer treatment planning. Treatment planners must not only consider the maximum dose that the rectum receives throughout a course of treatment, but also the dose that any volume of the rectum receives. As treatment planning techniques have evolved and prescription doses have escalated, limitations of rectal dose have remained an area of focus. External pelvic immobilization devices have been incorporated to aid in daily reproducibility and lessen concern for daily patient motion. Internal immobilization devices (such as the intrarectal balloon) and visualization techniques (including daily ultrasound or placement of fiducial markers) have been utilized to reduce the uncertainty of intrafractional prostate positional variation, thus allowing for minimization of treatment volumes. Despite these efforts, prostate volumes continue to abut portions of the rectum, and the necessary volume expansions continue to include portions of the anterior rectal wall within high-dose regions. The addition of collimator parameter optimization (both collimator angle and primary jaw settings) to intensity-modulated radiotherapy (IMRT) allows greater rectal sparing compared to the use of IMRT alone. We use multiple patient examples to illustrate the positive effects seen when utilizing collimator parameter optimization in conjunction with IMRT to further reduce rectal doses.
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
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
Srinivas, K; King, J W; Monrad, J K; Howard, L R; Hansen, C M
2009-08-01
Process engineering operations in food and nutraceutical industries pertaining to the design of extraction of value-added products from biomass using pressurized liquids involve a careful selection of the solvent and optimal temperature conditions to achieve maximum yield. Complex molecular structure and limited physical property data in the literature of biological solutes extracted from biomass compounds have necessitated the process modeling of such operations. In this study, we have applied the Hansen 3-dimensional solubility parameter concept to optimize the extraction of molecularly complex solutes using subcritical fluid solvents. Hansen solubility spheres characterized by the relative energy differences (RED) have been used to characterize and quantify the solute-subcritical solvent interactions as a function of temperature. The solvent power of subcritical water and compressed hydroethanolic mixtures above their boiling points has been characterized using the above-mentioned method. The use of group contribution methods in collaboration with computerized algorithms to plot the Hansen spheres provides a quantitative prediction tool for optimizing the design of extraction conditions. The method can be used to estimate conditions for solute-solvent miscibility, an optimum temperature range for conducting extractions under pressurized conditions, and approximate extraction conditions of solutes from natural matrices.
Optimization of processing parameters for the analysis and detection of embolic signals.
Aydin, N; Markus, H S
2000-09-01
The fast Fourier transform (FFT), which is employed by all commercially available ultrasonic systems, provides a time-frequency representation of Doppler ultrasonic signals obtained from blood flow. The FFT assumes that the signal is stationary within the analysis window. However, the presence of short duration embolic signals invalidates this assumption. For optimal detection of embolic signals if FFT is used for signal processing, it is important that the FFT parameters such as window size, window type, and required overlap ratio should be optimized. The effect of varying window type, window size and window overlap ratio were investigated for both simulated embolic signals, and recorded from patients with carotid artery stenosis. An optimal compromise is the use of a Hamming or Hanning window with a FFT size of 64 (8.9 ms) or 128 (17.9 ms). A high overlap ratio should also be employed in order not to miss embolic events occurring at the edges of analysis windows. The degree of overlap required will depend on the FFT size. The minimum overlap should be 65% for a 64-point window and 80% for a 128-point window.
Auto-score system to optimize OPC recipe parameters using genetic algorithm
NASA Astrophysics Data System (ADS)
Cao, Liang; Asthana, Abhishek; Ning, Guoxiang; Feng, Jui-Hsuan; Zhang, Jie; Wilkinson, William
2016-10-01
The ever increasing pattern densities and design complexities make the tuning of optical proximity correction (OPC) recipes more challenging. There are various recipe tuning methods to meet the challenge, such as genetic algorithm (GA), simulated annealing, and OPC software vendor provided recipe optimizers. However, these methodologies usually only consider edge placement errors (EPEs). Therefore, these techniques may not provide adequate freedom to solve unique problems at special geometries, for example bridge, pinch, and process variation band related violations at complex 2D geometries. This paper introduces a general methodology to fix specific problems identified at the OPC verification stage and demonstrates its successful application to two test-cases. The algorithm and method of the automatic scoring system is introduced in order to identify and prioritize the problems that need to be fixed based on severity, with the POR recipe score used as the baseline reference. A GA optimizer, whose objective function is based on the scoring system, is applied to tune the OPC recipe parameters to optimum condition after generations of selections. The GA optimized recipe would be compared to existing recipe to quantify the amount of improvement. This technique was subsequently applied to eliminate certain chronic OPC verification problems which were encountered in the past. Though the benefits have been demonstrated for limited test cases, employing this technique more universally will enable users to efficiently reduce the number of OPC verification violations and provide robust OPC solutions.
NASA Astrophysics Data System (ADS)
Zarnescu, George
2015-02-01
In a shallow underwater acoustic channel the delayed replicas of a transmitted signal are mainly due to the interactions with the sea surface and the bottom layer. If a specific underwater region on the globe is considered, for which the sedimentary layer structure is constant across the transmission distance, then the variability of the amplitude-delay profile is determined by daily and seasonal changes of the sound speed profile (SSP) and by weather changes, such as variations of the wind speed. Such a parameter will influence the attenuation at the surface, the noise level and the profile of the sea surface. The temporal variation of the impulse response in a shallow underwater acoustic channel determines the variability of the optimal transmission frequency. If the ways in which the optimal frequency changes can be predicted, then an adaptive analog transceiver can be easily designed for an underwater acoustic modem or it can be found when a communication link has high throughput. In this article it will be highlighted the way in which the amplitude-delay profile is affected by the sound speed profile, wind speed and channel depth and also will be emphasized the changes of the optimal transmission frequency in a configuration, where the transmitter and receiver are placed on the seafloor and the bathymetry profile will be considered flat, having a given composition.
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.
NASA Astrophysics Data System (ADS)
Alston, Robert; Iyer, Shanthi; Bradley, Tanina; Lewis, Jay; Cunningham, Garry; Forsythe, Eric
2014-02-01
Low temperature gallium tin zinc oxide (GSZO) based thin film transistors fabricated on silicon has been investigated as a potential indium free transparent amorphous oxide semiconductor thin film transistor (TAOS TFT) with potential device applications on plastic substrates. A comprehensive and detailed study on the performance of GSZO TFTs has been carried out by studying the effects of processing parameters such as deposition temperature and annealing temperature/duration, as well as the channel thickness with all temperatures held below 150 °C. Variety of characterization techniques, namely Rutherford backscattering (RBS), x-ray photoelectron spectroscopy (XPS) and x-ray reflectivity (XRR) in addition to I-V and C-V measurements were employed to determine the effects of the above parameters on the composition and quality of the channel. Optimized TFT characteristics of ID=3×10-7 A, ION/OFF =2×106, VON ~ -2 V, SS ~ 1 V/dec and μFE = 0.14 cm2/V· s with a ΔVON of 3.3 V under 3 hours electrical stress were produced.
NASA 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.
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)
Wei, Ying-Kang; Luo, Xiao-Tao; Li, Cheng-Xin; Li, Chang-Jiu
2017-01-01
Magnesium-based alloys have excellent physical and mechanical properties for a lot of applications. However, due to high chemical reactivity, magnesium and its alloys are highly susceptible to corrosion. In this study, Al6061 coating was deposited on AZ31B magnesium by cold spray with a commercial Al6061 powder blended with large-sized stainless steel particles (in-situ shot-peening particles) using nitrogen gas. Microstructure and corrosion behavior of the sprayed coating was investigated as a function of shot-peening particle content in the feedstock. It is found that by introducing the in-situ tamping effect using shot-peening (SP) particles, the plastic deformation of deposited particles is significantly enhanced, thereby resulting in a fully dense Al6061 coating. SEM observations reveal that no SP particle is deposited into Al6061 coating at the optimization spraying parameters. Porosity of the coating significantly decreases from 10.7 to 0.4% as the SP particle content increases from 20 to 60 vol.%. The electrochemical corrosion experiments reveal that this novel in-situ SP-assisted cold spraying is effective to deposit fully dense Al6061 coating through which aqueous solution is not permeable and thus can provide exceptional protection of the magnesium-based materials from corrosion.
NASA Astrophysics Data System (ADS)
Chen, Z.; Chen, J.; Zheng, X.; Jiang, F.; Zhang, S.; Ju, W.; Yuan, W.; Mo, G.
2014-12-01
In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation pattern of the net carbon flux. An optimization scheme is proposed to estimate two key parameters (Vcmax and Q10) by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate Vcmax and Q10 of the Boreal Ecosystem Productivity Simulator (BEPS) to improve its NEP simulation in the Boreal North America (BNA) region. Simultaneously, in-situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results have the implication on using atmospheric CO2 data for optimizing ecosystem parameters through atmospheric inversion or data assimilation techniques.
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.
Optimizing Parameters of Process-Based Terrestrial Ecosystem Model with Particle Filter
NASA Astrophysics Data System (ADS)
Ito, A.
2014-12-01
Present terrestrial ecosystem models still contain substantial uncertainties, as model intercomparison studies have shown, because of poor model constraint by observational data. So, development of advanced methodology of data-model fusion, or data-assimilation, is an important task to reduce the uncertainties and improve model predictability. In this study, I apply the Particle filter (or Sequential Monte Carlo filer) to optimize parameters of a process-based terrestrial ecosystem model (VISIT). The Particle filter is one of the data-assimilation methods, in which probability distribution of model state is approximated by many samples of parameter set (i.e., particle). This is a computationally intensive method and applicable to nonlinear systems; this is an advantage of the method in comparison with other techniques like Ensemble Kalman filter and variational method. At several sites, I used flux measurement data of atmosphere-ecosystem CO2 exchange in sequential and non-sequential manners. In the sequential data assimilation, a time-series data at 30-min or daily steps were used to optimize gas-exchange-related parameters; this method would be also effective to assimilate satellite observational data. On the other hand, in the non-sequential case, annual or long-term mean budget was adjusted to observations; this method would be also effective to assimilate carbon stock data. Although there remain technical issues (e.g., appropriate number of particles and likelihood function), I demonstrate that the Partile filter is an effective method of data-assimilation for process-based models, enhancing collaboration between field and model researchers.
NASA Astrophysics Data System (ADS)
Ozkat, Erkan Caner; Franciosa, Pasquale; Ceglarek, Dariusz
2017-08-01
Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500 °C) and the vapourizing temperature of the zinc (∼907 °C). In fact, the zinc layer at the faying surface is vapourized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple-inputs (i.e. key control characteristics) and multiple-outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp-Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii
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.
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.
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.
Optimization of automated matrix deposition for biomolecular mapping using a spotter
Delvolve, Alice M.; Woods, Amina S.
2011-01-01
Imaging mass spectrometry using Matrix-Assisted Laser Desorption/Ionization allows the detailed mapping of biomolecules directly from tissue. Matrix deposition is the key step for successful imaging. Appropriate concentration and deposition of matrix is critical for extraction, desorption and ionization of molecules from tissue without losing molecular localization. The main challenge to meet these criteria is to deposit matrix droplets homogeneously on the tissue section. This work shows how a chemical inkjet printer was used for this purpose resulting in the imaging of phosphatidylcholines and sulfatides. The intricacies involved in effective matrix deposition are discussed. PMID:22012671
Processing parameter optimization for the laser dressing of bronze-bonded diamond wheels
NASA Astrophysics Data System (ADS)
Deng, H.; Chen, G. Y.; Zhou, C.; Li, S. C.; Zhang, M. J.
2014-01-01
In this paper, a pulsed fiber-laser dressing method for bronze-bonded diamond wheels was studied systematically and comprehensively. The mechanisms for the laser dressing of bronze-bonded diamond wheels were theoretically analyzed, and the key processing parameters that determine the results of laser dressing, including the laser power density, pulse overlap ratio, ablation track line overlap ratio, and number of scanning cycles, were proposed for the first time. Further, the effects of these four key parameters on the oxidation-damaged layer of the material surface, the material removal efficiency, the material surface roughness, and the average protrusion height of the diamond grains were explored and summarized through pulsed laser ablation experiments. Under the current experimental conditions, the ideal values of the laser power density, pulse overlap ratio, ablation track line overlap ratio, and number of scanning cycles were determined to be 4.2 × 107 W/cm2, 30%, 30%, and 16, respectively. Pulsed laser dressing experiments were conducted on bronze-bonded diamond wheels using the optimized processing parameters; next, both the normal and tangential grinding forces produced by the dressed grinding wheel were measured while grinding alumina ceramic materials. The results revealed that the normal and tangential grinding forces produced by the laser-dressed grinding wheel during grinding were smaller than those of grinding wheels dressed using the conventional mechanical method, indicating that the pulsed laser dressing technology provides irreplaceable advantages relative to the conventional mechanical dressing method.
Lee, Ayoung; Jin, Howon; Dang, Hyun-Woo; Choi, Kyung-Hyun; Ahn, Kyung Hyun
2013-11-05
The harmony of ink and printing method is of importance in producing on-demand droplets and jets of ink. Many factors including the material properties, the processing conditions, and the nozzle geometry affect the printing quality. In electrohydrodynamic (EHD) printing where droplets or jets are generated by the electrostatic force, the physical as well as the electrical properties of the fluid should be taken into account to achieve the desired performance. In this study, a systematic approach was suggested for finding the processing windows of the EHD printing. Six dimensionless parameters were organized and applied to the printing system of ethanol/terpineol mixtures. On the basis of the correlation of the dimensionless voltage and the charge relaxation length, the jet diameter of cone-jet mode was characterized, and the semicone angle was compared with the theoretical Taylor angle. In addition, the ratio of electric normal force and electric tangential force on the charged surface of the Taylor cone was recommended as a parameter that determines the degree of cone-jet stability. The cone-jet became more stable as this ratio got smaller. This approach was a systematic and effective way of obtaining the Taylor cone of the cone-jet mode and evaluating the jetting stability. The control of the inks with optimized experimental parameters by this method will improve the jetting performance in EHD inkjet printing.
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.
Parameter Estimation of a Ground Moving Target Using Image Sharpness Optimization
Yu, Jing; Li, Yaan
2016-01-01
Motion parameter estimation of a ground moving target is an important issue in synthetic aperture radar ground moving target indication (SAR-GMTI) which has significant applications for civilian and military. The SAR image of a moving target may be displaced and defocused due to the radial and along-track velocity components, respectively. The sharpness cost function presents a measure of the degree of focus of the image. In this work, a new ground moving target parameter estimation algorithm based on the sharpness optimization criterion is proposed. The relationships between the quadratic phase errors and the target’s velocity components are derived. Using two-dimensional searching of the sharpness cost function, we can obtain the velocity components of the target and the focused target image simultaneously. The proposed moving target parameter estimation method and image sharpness metrics are analyzed in detail. Finally, numerical results illustrate the effective and superior velocity estimation performance of the proposed method when compared to existing algorithms. PMID:27376294
NASA Astrophysics Data System (ADS)
Wu, Li-Li; Zhou, Qihou H.; Chen, Tie-Jun; Liang, J. J.; Wu, Xin
2015-09-01
Simultaneous derivation of multiple ionospheric parameters from the incoherent scatter power spectra in the F1 region is difficult because the spectra have only subtle differences for different combinations of parameters. In this study, we apply a particle swarm optimizer (PSO) to incoherent scatter power spectrum fitting and compare it to the commonly used least squares fitting (LSF) technique. The PSO method is found to outperform the LSF method in practically all scenarios using simulated data. The PSO method offers the advantages of not being sensitive to initial assumptions and allowing physical constraints to be easily built into the model. When simultaneously fitting for molecular ion fraction (fm), ion temperature (Ti), and ratio of ion to electron temperature (γT), γT is largely stable. The uncertainty between fm and Ti can be described as a quadratic relationship. The significance of this result is that Ti can be retroactively corrected for data archived many years ago where the assumption of fm may not be accurate, and the original power spectra are unavailable. In our discussion, we emphasize the fitting for fm, which is a difficult parameter to obtain. PSO method is often successful in obtaining fm, whereas LSF fails. We apply both PSO and LSF to actual observations made by the Arecibo incoherent scatter radar. The results show that PSO method is a viable method to simultaneously determine ion and electron temperatures and molecular ion fraction when the last is greater than 0.3.
Parameter Optimization Of Natural Hydroxyapatite/SS316l Via Metal Injection Molding (MIM)
NASA Astrophysics Data System (ADS)
Mustafa, N.; Ibrahim1, M. H. I.; Amin, A. M.; Asmawi, R.
2017-01-01
Metal injection molding (MIM) are well known as a worldwide application of powder injection molding (PIM) where as applied the shaping concept and the beneficial of plastic injection molding but develops the applications to various high performance metals and alloys, plus metal matrix composites and ceramics. This study investigates the strength of green part by using stainless steel 316L/ Natural hydroxyapatite composite as a feedstock. Stainless steel 316L (SS316L) was mixed with Natural hydroxyapatite (NHAP) by adding 40 wt. % Low Density Polyethylene and 60 %wt. Palm Stearin as a binder system at 63 wt. % powder loading consist of 90 % wt. of SS316 L and 10 wt. % NHAP prepared thru critical powder volume percentage (CPVC). Taguchi method was functional as a tool in determining the optimum green strength for Metal Injection Molding (MIM) parameters. The green strength was optimized with 4 significant injection parameter such as Injection temperature (A), Mold temperature (B), Pressure (C) and Speed (D) were selected throughout screening process. An orthogonal array of L9 (3)4 was conducted. The optimum injection parameters for highest green strength were established at A1, B2, C0 and D1 and where as calculated based on Signal to Noise Ratio.
Oliver, J.B.; Talbot, D.
2006-05-17
Multilayer coatings on large substrates with increasingly complex spectral requirements are essential for a number of optical systems, placing stringent requirements on the error tolerances of individual layers. Each layer must be deposited quite uniformly over the entire substate surface since any nonuniformity will add to the layer-thickness error level achieved. A deposition system containing a planetary rotation system with stationary uniformity masking is modeled, with refinements of the planetary gearing, source placement, and uniformity mask shape being utilized to achieve an optimal configuration. The impact of improper planetary gearing is demonstrated theoretically, as well as experimentally, providing more comprehensive requirements than simply avoiding repetition of previous paths through the vapor plume, until all possible combinations of gear teeth have been used. Deposition efficiency and the impact of changing vapor plume conditions on the uniformity achieved are used to validate improved source placement.
NASA Astrophysics Data System (ADS)
El Jarbi, M.; Rückelt, J.; Slawig, T.; Oschlies, A.
2013-02-01
This paper presents the application of the Linear Quadratic Optimal Control (LQOC) method to a parameter optimization problem for a one-dimensional marine ecosystem model of NPZD (N for dissolved inorganic nitrogen, P for phytoplankton, Z for zooplankton and D for detritus) type. This ecosystem model, developed by Oschlies and Garcon, simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. The LQOC method is used to introduce annually periodic model parameters in a linearized version of the model. We show that the obtained version of the model gives a significant reduction of the model-data misfit, compared to the one obtained for the original model with optimized constant parameters. The found inner-annual variability of the optimized parameters provides hints for improvement of the original model. We use the obtained optimal periodic parameters also in validation and prediction experiments with the original non-linear version of the model. In both cases, the results are significantly better than those obtained with optimized constant parameters.
2010-03-19
sandwich immunoassay used a capture Ab adsorbed to the Ppy and a reporter Ab labeled for fluorescence detection or ECD, and results from these methods of...Targeted Deposition of Antibodies on a Multiplex CMOS Microarray and Optimization of a Sensitive Immunoassay Using Electrochemical Detection John...Sensitive Immunoassay Using Electrochemical Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT
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
2011-01-01
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 [“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 40×40 cm2 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 3×3 to 40×40 cm2 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 as the
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
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.
Rietveld, Ivo B; Kobayashi, Kei; Yamada, Hirofumi; Matsushige, Kazumi
2009-11-15
Poly(vinylidene fluoride) films between 60 and 120nm have been prepared with electrostatic spray deposition (ESD) in 25-45s. The films are robust and exhibit a strong adhesion to the substrate surface. The important electrospray parameters for ultra-thin film formation are droplet size, initial polymer concentration, shear rate at impact, and volume flux. The latter can be understood as a measure for the solvent balance between deposition and evaporation; it affects overall film quality. The droplet size determines the minimum film thickness at which continuous film forms without voids. Polymer concentration affects thin-film smoothness and below a fixed concentration threshold, films cease to appear. For the very first droplets, wetting behavior on the substrate is most important. Subsequently, shear rate determines how voids are filled up and it determines final film smoothness. In addition to the electrospray conditions, substrates that favor wetting and have a capability to conduct charges away from the surface contribute to the formation of well-defined, ultra-thin films.
Bonhoeffer, Bastian; Kwade, Arno; Juhnke, Michael
2017-04-01
Flexible manufacturing processes with continuously adjustable dose strengths are considered particularly innovative and interesting for applications in personalized medicine, continuous manufacturing, or early drug development. A piezo-actuated micro-valve has been investigated for the dispensing and depositioning of drug nanosuspensions onto substrates to facilitate the manufacturing of solid oral dosage forms. The investigated micro-valve has been characterized regarding dispensing behavior, mass flow, accuracy, and robustness. The amount of dispensed drug compound during 1 dispensing event could be continuously adjusted from a few micrograms to several milligrams with high accuracy. Fluid properties, dispensing parameters of the micro-valve, and the resulting steady state mass flow could be correlated adequately for low-viscous drug nanosuspensions. High-speed imaging was used to investigate the dispensing behavior of the micro-valve regarding the evolution of the dispensed drug nanosuspension after ejection from the nozzle and the behavior during impact on flat and dry solid substrates. The experimentally determined breakup length of the dispensed liquid jet could be correlated with a semiempirical equation. From image sequences of the jet impact, We-Re phase diagrams could be established, providing a profound understanding and systematic guidance for the controlled depositioning of the entire dispensed drug nanosuspension onto the substrate.
Optimizing the sputter deposition process of polymers for the Storing Matter technique using PMMA.
Turgut, Canan; Sinha, Godhuli; Lahtinen, Jouko; Nordlund, Kai; Belmahi, Mohammed; Philipp, Patrick
2016-10-01
Quantitative analyses in secondary ion mass spectrometry (SIMS) become possible only if ionization processes are controlled. The Storing Matter technique has been developed to circumvent this so-called matrix effect, primarily for inorganic samples, but has also been extended to organic samples. For the latter, it has been applied to polystyrene in order to investigate the extent of damage in the polymer, its fragmentation during the sputter deposition process and the effect of the deposition process on the spectra taken by Time-of-Flight SIMS (ToF-SIMS). In this work, a multi-technique approach, which employs the Storing Matter technique for deposition and ToF-SIMS and X-ray photoelectron spectroscopy for characterization, is used to enhance the control of the deposition process, including the thickness of the deposit, the alteration of the source film and the influence of polymer composition on the Storing Matter process. Poly (methyl methacrylate) (PMMA) is used for this work. More detailed information about the sticking of polymer fragments on the metal collector is obtained by density functional theory calculations. This work allows for the conclusion that a part of the fragments deposited on the collector surface diffuses on the latter, reacts and recombines to form larger fragments. The behaviour observed for PMMA is similar to polystyrene, showing that oxygen has no major influence on the processes occurring during the sputter deposition process. Additionally, we have developed a new methodology using 2D ToF-SIMS images of the deposit to monitor the deposit thickness and to identify surface contaminations. The latter are not only located at the position of the deposit but all over the collector surface. Copyright © 2016 John Wiley & Sons, Ltd.
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.
[Numerical simulation and optimization research of needle parameters in vial washing machine].
Zhang, Haowei; Li, Zhen; Liu, Ying; Liu, Haigang; Peng, Delian; Wei, Guoqin
2014-10-01
According to the working principle of vertical ultrasonic vial washing machine, receiving respective force of small water droplets on the inside wall of vials and the minimum air velocity of blowing off water droplets can be obtained based on the analysis of water-droplet-related parameters. The inside wall model of 7 mL vial created by GAMBIT was divided into fine grids. Then the Realizable k-epsilon Two Equation Turbulence Model was adopted and the flow field of vial by FLUENT software was simulated when air was flushing inside the wall. In that case, the optimal position, inner diameter and the corresponding minimum air velocity of needle can be acquired to meet the needs of vial washing machine applied to 7 mL vial.
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.
NASA Astrophysics Data System (ADS)
Wang, Jing Jing; McCloskey, David; Donegan, John F.
2011-12-01
A new concept of "photonic nanojet" SNOM is proposed in this paper and the system is based on a dielectric microsphere which is mounted on a cantilever. The dielectric microsphere works as a superlens to focus the laser energy into a small volume with subwavelength spatial resolution. The numerical simulation by using Finite Element Method (FEM) has been done to optimize the parameters of the photonic nanojet of dielectic microsphere for "photonic nanojet" SNOM. The microspheres with different diameters have been investigated numerically and the results show that bigger microspheres produce higher intensity "photonic nanojets". The simulation result on the interaction between a silicon cylinder and a photonic nanojet reveals that a "hot spot" is formed inside the silicon cylinder and is confined into a small volume. Therefore a new area on high spatial resolution spectral analyzing for nanostructures is in prospect.
Optimal process parameters for phosphorus spin-on-doping of germanium
NASA Astrophysics Data System (ADS)
Boldrini, Virginia; Carturan, Sara Maria; Maggioni, Gianluigi; Napolitani, Enrico; Napoli, Daniel Ricardo; Camattari, Riccardo; De Salvador, Davide
2017-01-01
The fabrication of homogeneously doped germanium layers characterized by total electrical activation is currently a hot topic in many fields, such as microelectronics, photovoltaics, optics and radiation detectors. Phosphorus spin-on-doping technique has been implemented on Ge wafers, by developing a protocol for the curing process and subsequent diffusion annealing for optimal doping. Parameters such as relative humidity and curing time turned out to affect the surface morphology, the degree of reticulation reached by the dopant source and the amount of dopant available for diffusion. After spike annealing in a conventional furnace, diffusion profiles and electrical properties have been measured. Ge loss from the surface during high-temperature annealing, due to diffusion into the source film, has been observed and quantified.
Belite cement clinker from coal fly ash of high Ca content. Optimization of synthesis parameters.
Guerrero, A; Goñi, S; Campillo, I; Moragues, A
2004-06-01
The optimization of parameters of synthesis of belite cement clinker from coal fly ash of high Ca content is presented in this paper. The synthesis process is based on the hydrothermal-calcination-route of the fly ash without extra additions. The hydrothermal treatment was carried out in demineralized water and a 1 M NaOH solution for 4 h at the temperatures of 100 degrees C, 150 degrees C, and 200 degrees C. The precursors obtained during the hydrothermal treatmentwere heated at temperatures of 700 degrees C, 800 degrees C, 900 degrees C, and 1000 degrees C. The changes of fly ash composition after the different treatments were characterized by X-ray diffraction (XRD), FT infrared (FTIR) spectroscopy, surface area (BET-N2), and thermal analyses. From the results obtained we concluded that the optimum temperature of the hydrothermal treatment was 200 degrees C, and the optimum temperature for obtaining the belite cement clinker was 800 degrees C.
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 Astrophysics Data System (ADS)
Choi, Seungyeon; Choi, Sunghoon; Kim, Ye-seul; Lee, Haenghwa; Lee, Donghoon; Jeon, Pil-Hyun; Jang, Dong-Hyuk; Kim, Hee-Joung
2016-03-01
Digital tomosynthesis system (DTS), which scans an object in a limited angle, has been considered as an innovative imaging modality which can present lower patient dose than computed tomography and solve the problem of poor depth resolution in conventional digital radiography. Although it has many powerful advantages, only breast tomosynthesis system has been adopted in many hospitals. In order to reduce the patient dose while maintaining image quality, the acquisition conditions need to be studied. In this study, we analyzed effective dose and image qualities of chest phantom using commercialized universal chest digital tomosynthesis (CDT) R/F system to study the optimized exposure parameters. We set 10 different acquisition conditions including the default acquisition condition by user manual of Shimadzu (100 kVp with 0.5 mAs). The effective dose was calculated from PCXMC software version 1.5.1 by utilizing the total X-ray exposure measured by ion chamber. The image quality was evaluated by signal difference to noise ratio (SDNR) in the regions of interest (ROIs) pulmonary arteries at different axial in-plane. We analyzed a figure of merit (FOM) which considers both the effective dose and the SDNR in order to determine the optimal acquisition condition. The results indicated that the most suitable acquisition parameters among 10 conditions were condition 7 and 8 (120 kVp with 0.04 mAs and 0.1 mAs, respectively), which indicated lower effective dose while maintaining reasonable SDNRs and FOMs for three specified regions. Further studies are needed to be conducted for detailed outcomes in CDT acquisition conditions.
NASA Astrophysics Data System (ADS)
Kuo, Chung-Feng Jeffery; Tu, Hung-Min; Liang, Shin-Wei; Tsai, Wei-Lun
2010-09-01
This study used ultraviolet laser to perform the microcrystalline silicon thin film solar cell isolation scribing process, and applied the Taguchi method and an L 18 orthogonal array to plan the experiment. The isolation scribing materials included ZnO:Al, AZO transparent conductive film with a thickness of 200 nm, microcrystalline silicon thin film at 38% crystallinity and of thickness of 500 nm, and the aluminum back contact layer with a thickness of 300 nm. The main objective was to ensure the success of isolation scribing. After laser scribing isolation, using the minimum scribing line width, the flattest trough bottom, and the minimum processing edge surface bumps as the quality characteristics, this study performed main effect analysis and applied the ANOVA (analysis of variance) theory of the Taguchi method to identify the single quality optimal parameter. It then employed the hierarchical structure of the AHP (analytic hierarchy process) theory to establish the positive contrast matrix. After consistency verification, global weight calculation, and priority sequencing, the optimal multi-attribute parameters were obtained. Finally, the experimental results were verified by a Taguchi confirmation experiment and confidence interval calculation. The minimum scribing line width of AZO (200 nm) was 45.6 μm, the minimum scribing line width of the microcrystalline silicon (at 38% crystallinity) was 50.63 μm and the minimum line width of the aluminum thin film (300 nm) was 30.96 μm. The confirmation experiment results were within the 95% confidence interval, verifying that using ultraviolet laser in the isolation scribing process for microcrystalline silicon thin film solar cell has high reproducibility.
NASA Astrophysics Data System (ADS)
Wang, Xin; Zhang, Lei; Fan, Juanjuan; Li, Yufang; Gong, Yao; Dong, Lei; Ma, Weiguang; Yin, Wangbao; Jia, Suotang
2015-11-01
Improvement of measurement precision and repeatability is one of the issues currently faced by the laser-induced breakdown spectroscopy (LIBS) technique, which is expected to be capable of precise and accurate quantitative analysis. It was found that there was great potential to improve the signal quality and repeatability by reducing the laser beam divergence angle using a suitable beam expander (BE). In the present work, the influences of several experimental parameters for the case with BE are studied in order to optimize the analytical performances: the signal to noise ratio (SNR) and the relative standard deviation (RSD). We demonstrate that by selecting the optimal experimental parameters, the BE-included LIBS setup can give higher SNR and lower RSD values of the line intensity normalized by the whole spectrum area. For validation purposes, support vector machine (SVM) regression combined with principal component analysis (PCA) was used to establish a calibration model to realize the quantitative analysis of the ash content. Good agreement has been found between the laboratory measurement results from the LIBS method and those from the traditional method. The measurement accuracy presented here for ash content analysis is estimated to be 0.31%, while the average relative error is 2.36%. supported by the 973 Program of China (No. 2012CB921603), National Natural Science Foundation of China (Nos. 61475093, 61127017, 61178009, 61108030, 61378047, 61275213, 61475093, and 61205216), the National Key Technology R&D Program of China (No. 2013BAC14B01), the Shanxi Natural Science Foundation (Nos. 2013021004-1 and 2012021022-1), the Shanxi Scholarship Council of China (Nos. 2013-011 and 2013-01), and the Program for the Outstanding Innovative Teams of Higher Learning Institutions of Shanxi, China
Optimization of ultrasound parameters for microbubble-nanoliposome complex-mediated delivery
Yoon, Young Il; Yoon, Tae-Jong; Lee, Hak Jong
2015-01-01
Purpose: The aim of this study was to identify the optimal ultrasound (US) parameters for gene and drug delivery. Methods: In order to target SkBr3, which is a breast cancer cell overexpressing the Her2 receptor, trastuzumab (Herceptin) was used. Micobubble-nanoliposome complex (MLC) was mixed with trastuzumab and stored overnight. Finally, MLC was combined with Her2Ab. A US device equipped with a 1-MHz probe was used for delivery to the cell. Several parameters, including intensity (w/cm2), time (minutes), and duty cycle (%), were varied within a range from 1 w/cm2, 1 minute, and 20% to 2 w/cm2, 2 minutes, and 60%, respectively. A confocal laser scanning microscope (CLSM) was used to confirm the delivery of MLC to the cells after US treatment. Results: MLC with fluorescent dyes and trastuzumab was synthesized successfully. By delivering MLC with Her2Ab to cells, the targeting effect of trastuzumab with MLC was confirmed by CLSM. The cell membranes showed green (fluorescein isothiocyanate) and red (Texas red) fluorescence but treatments with MLC without Her2Ab did not show any fluorescence. Optimal conditions for US-mediated delivery were 1 or 2 w/cm2, 2 minutes, and 60% (uptake ratio, 95.9% for 1 w/cm2 and 95.7% for 2 w/cm2) for hydrophobic materials and 2 w/cm2, 2 minutes, and 60% (uptake ratio, 95.0%) for hydrophilic materials. Conclusion: The greater the strength, duty cycle, and period of US application within the tested range, the more efficiently the fluorescent contents were conveyed. PMID:26044281
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.
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)
Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.
2015-02-01
In this paper, the optimal least-squares state estimation problem is addressed for a class of discrete-time multisensor linear stochastic systems with state transition and measurement random parameter matrices and correlated noises. It is assumed that at any sampling time, as a consequence of possible failures during the transmission process, one-step delays with different delay characteristics may occur randomly in the received measurements. The random delay phenomenon is modelled by using a different sequence of Bernoulli random variables in each sensor. The process noise and all the sensor measurement noises are one-step autocorrelated and different sensor noises are one-step cross-correlated. Also, the process noise and each sensor measurement noise are two-step cross-correlated. Based on the proposed model and using an innovation approach, the optimal linear filter is designed by a recursive algorithm which is very simple computationally and suitable for online applications. A numerical simulation is exploited to illustrate the feasibility of the proposed filtering algorithm.
Baykal, Cenk; Torres, Luis G; Alterovitz, Ron
2015-09-28
Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot's behavior and reachable workspace. Optimizing a robot's design by appropriately selecting tube parameters can improve the robot's effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot's configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy.
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.
Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning
Baykal, Cenk; Torres, Luis G.; Alterovitz, Ron
2015-01-01
Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot’s behavior and reachable workspace. Optimizing a robot’s design by appropriately selecting tube parameters can improve the robot’s effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot’s configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy. PMID:26951790
Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi
2014-01-01
Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236
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.
Optimization of Processing Condition for Deposition of DLC Using FIB-CVD Method
NASA Astrophysics Data System (ADS)
Sakamoto, Naomichi; Kogo, Yasuo; Yagi, Takahiro; Yasuno, Takuya; Taniguchi, Jun; Miyamoto, Iwao
The processing conditions for deposition of DLC using the FIB-CVD method were examined in detail. Microstructures and mechanical properties of the DLC specimens were also investigated. The deposition process of the DLC specimen is varied by the probe current of the ion beam. Through these examinations, optimum deposition condition was discussed. HRTEM image and diffraction pattern showed that the DLC specimen had amorphous structures. Young’s modulus and Vickers hardness were in the range of 110-140GPa and 1100-1400HV, respectively. These mechanical properties were obtained similarly even though the processing conditions were changed in our study.
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.
NASA Astrophysics Data System (ADS)
Ike, Innocent S.; Sigalas, Iakovos; Iyuke, Sunny E.
2017-03-01
Theoretical expressions for performance parameters of different electrochemical capacitors (ECs) have been optimized by solving them using MATLAB scripts as well as via the MATLAB R2014a optimization toolbox. The performance of the different kinds of ECs under given conditions was compared using theoretical equations and simulations of various models based on the conditions of device components, using optimal values for the coefficient associated with the battery-kind material ( K BMopt) and the constant associated with the electrolyte material ( K Eopt), as well as our symmetric electric double-layer capacitor (EDLC) experimental data. Estimation of performance parameters was possible based on values for the mass ratio of electrodes, operating potential range ratio, and specific capacitance of electrolyte. The performance of asymmetric ECs with suitable electrode mass and operating potential range ratios using aqueous or organic electrolyte at appropriate operating potential range and specific capacitance was 2.2 and 5.56 times greater, respectively, than for the symmetric EDLC and asymmetric EC using the same aqueous electrolyte, respectively. This enhancement was accompanied by reduced cell mass and volume. Also, the storable and deliverable energies of the asymmetric EC with suitable electrode mass and operating potential range ratios using the proper organic electrolyte were 12.9 times greater than those of the symmetric EDLC using aqueous electrolyte, again with reduced cell mass and volume. The storable energy, energy density, and power density of the asymmetric EDLC with suitable electrode mass and operating potential range ratios using the proper organic electrolyte were 5.56 times higher than for a similar symmetric EDLC using aqueous electrolyte, with cell mass and volume reduced by a factor of 1.77. Also, the asymmetric EDLC with the same type of electrode and suitable electrode mass ratio, working potential range ratio, and proper organic electrolyte
NASA Astrophysics Data System (ADS)
Ike, Innocent S.; Sigalas, Iakovos; Iyuke, Sunny E.
2017-01-01
Theoretical expressions for performance parameters of different electrochemical capacitors (ECs) have been optimized by solving them using MATLAB scripts as well as via the MATLAB R2014a optimization toolbox. The performance of the different kinds of ECs under given conditions was compared using theoretical equations and simulations of various models based on the conditions of device components, using optimal values for the coefficient associated with the battery-kind material (K BMopt) and the constant associated with the electrolyte material (K Eopt), as well as our symmetric electric double-layer capacitor (EDLC) experimental data. Estimation of performance parameters was possible based on values for the mass ratio of electrodes, operating potential range ratio, and specific capacitance of electrolyte. The performance of asymmetric ECs with suitable electrode mass and operating potential range ratios using aqueous or organic electrolyte at appropriate operating potential range and specific capacitance was 2.2 and 5.56 times greater, respectively, than for the symmetric EDLC and asymmetric EC using the same aqueous electrolyte, respectively. This enhancement was accompanied by reduced cell mass and volume. Also, the storable and deliverable energies of the asymmetric EC with suitable electrode mass and operating potential range ratios using the proper organic electrolyte were 12.9 times greater than those of the symmetric EDLC using aqueous electrolyte, again with reduced cell mass and volume. The storable energy, energy density, and power density of the asymmetric EDLC with suitable electrode mass and operating potential range ratios using the proper organic electrolyte were 5.56 times higher than for a similar symmetric EDLC using aqueous electrolyte, with cell mass and volume reduced by a factor of 1.77. Also, the asymmetric EDLC with the same type of electrode and suitable electrode mass ratio, working potential range ratio, and proper organic electrolyte
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.
Optimization of CO2 laser cutting parameters on Austenitic type Stainless steel sheet
NASA Astrophysics Data System (ADS)
Parthiban, A.; Sathish, S.; Chandrasekaran, M.; Ravikumar, R.
2017-03-01
Thin AISI 316L stainless steel sheet widely used in sheet metal processing industries for specific applications. CO2 laser cutting is one of the most popular sheet metal cutting processes for cutting of sheets in different profile. In present work various cutting parameters such as laser power (2000 watts-4000 watts), cutting speed (3500mm/min – 5500 mm/min) and assist gas pressure (0.7 Mpa-0.9Mpa) for cutting of AISI 316L 2mm thickness stainless sheet. This experimentation was conducted based on Box-Behenken design. The aim of this work is to develop a mathematical model kerf width for straight and curved profile through response surface methodology. The developed mathematical models for straight and curved profile have been compared. The Quadratic models have the best agreement with experimental data, and also the shape of the profile a substantial role in achieving to minimize the kerf width. Finally the numerical optimization technique has been used to find out best optimum laser cutting parameter for both straight and curved profile cut.
NASA Astrophysics Data System (ADS)
Babu, S.; Elangovan, K.; Balasubramanian, V.; Balasubramanian, M.
2009-04-01
AA2219 aluminium alloy (Al-Cu-Mn alloy) has gathered wide acceptance in the fabrication of lightweight structures requiring a high strength-to-weight ratio and good corrosion resistance. In contrast to the fusion welding processes that are routinely used for joining structural aluminium alloys, the friction stir welding (FSW) process is an emerging solid state joining process in which the material that is being welded does not melt and recast. This process uses a non-consumable tool to generate frictional heat in the abutting surfaces. The welding parameters such as tool rotational speed, welding speed, axial force etc., and the tool pin profile play a major role in determining the joint strength. An attempt has been made here to develop a mathematical model to predict the tensile strength of friction stir welded AA2219 aluminium alloy by incorporating FSW process parameters. A central composite design with four factors and five levels has been used to minimize the number of experimental conditions. The response surface method (RSM) has been used to develop the model. The developed mathematical model has been optimized using the Hooke and Jeeves search technique to maximize the tensile strength of the friction stir welded AA2219 aluminium alloy joints.
Optimizing experimental parameters for the projection requirement in HAADF-STEM tomography.
Aveyard, R; Zhong, Z; Batenburg, K J; Rieger, B
2017-03-07
Tomographic reconstruction algorithms offer a means by which a tilt-series of transmission images can be combined to yield a three dimensional model of the specimen. Conventional reconstruction algorithms assume that the measured signal is a linear projection of some property, typically the density, of the material. Here we report the use of multislice simulations to investigate the extent to which this assumption is met in HAADF-STEM imaging. The use of simulations allows for a systematic survey of a range of materials and microscope parameters to inform optimal experimental design. Using this approach it is demonstrated that the imaging of amorphous materials is in good agreement with the projection assumption in most cases. Images of crystalline specimens taken along zone-axes are found to be poorly suited for conventional linear reconstruction algorithms due to channelling effects which produce enhanced intensities compared with off-axis images, and poor compliance with the projection requirement. Off-axis images are found to be suitable for reconstruction, though they do not strictly meet the linearity requirement in most cases. It is demonstrated that microscope parameters can be selected to yield improved compliance with the projection requirement.
Optimization of Machining Process Parameters for Surface Roughness of Al-Composites
NASA Astrophysics Data System (ADS)
Sharma, S.
2013-10-01
Metal matrix composites (MMCs) have become a leading material among the various types of composite materials for different applications due to their excellent engineering properties. Among the various types of composites materials, aluminum MMCs have received considerable attention in automobile and aerospace applications. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like silicon carbide particles. In the present investigation Al-SiC composite was produced by stir casting process. The Brinell hardness of the alloy after SiC addition had increased from 74 ± 2 to 95 ± 5 respectively. The composite was machined using CNC turning center under different machining parameters such as cutting speed (S), feed rate (F), depth of cut (D) and nose radius (R). The effect of machining parameters on surface roughness (Ra) was studied using response surface methodology. Face centered composite design with three levels of each factor was used for surface roughness study of the developed composite. A response surface model for surface roughness was developed in terms of main factors (S, F, D and R) and their significant interactions (SD, SR, FD and FR). The developed model was validated by conducting experiments under different conditions. Further the model was optimized for minimum surface roughness. An error of 3-7 % was observed in the modeled and experimental results. Further, it was fond that the surface roughness of Al-alloy at optimum conditions is lower than that of Al-SiC composite.
NASA Astrophysics Data System (ADS)
Baughman, Adam C.; Huang, Xinqun; Martin, Lealon L.
2012-07-01
We adapt a general-purpose optimization-based parameter estimation technique previously described in the literature [1] to evaluate the suitability of a number of common kinetic models for the representation of key performance characteristics (conversion and selectivity) of catalysts used for the preferential oxidation of CO in the presence of H2. We find that, for process engineering applications, there is no clear practical advantage to using mechanistically based kinetic models (e.g. Langmuir-Hinshelwood) unless the precise chemical mechanism is known. Empirical rate models are found generally to provide equivalent or better simulations of key performance variables for a diverse group of catalyst formulations. Furthermore, we demonstrate that the water-gas-shift (WGS) reaction is relevant within PROX reaction systems under conditons containing high fractions of CO2 and H2, confirming the expectations of Choi and Stenger (2004) [2]. Finally, we attempt to identify any emergent trends in kinetic parameters among catalysts sharing similar active metal or metal oxide components. Unfortunately, apart from confirming that the activation barrier for CO oxidation is generally less than the barrier for H2 oxidation (an expected relationship for PROX catalysts), no such trends are found.
NASA Astrophysics Data System (ADS)
Malhotra, C. P.
With increasing national and global demand for energy and concerns about the effect of fossil fuels on global climate change, there is an increasing emphasis on the development and use of renewable sources of energy. Solar cells or photovoltaics constitute an important renewable energy technology but the major impediment to their widespread adoption has been their high initial cost. Although thin-film photovoltaic semiconductors such as cadmium sulfide-cadmium telluride (CdS/CdTe) can potentially be inexpensively manufactured using large area deposition techniques such as close-spaced sublimation (CSS), their low stability has prevented them from becoming an alternative to traditional polycrystalline silicon solar cells. A key factor affecting the stability of CdS/CdTe cells is the uniformity of deposition of the thin films. Currently no models exist that can relate the processing parameters in a CSS setup with the film deposition uniformity. Central to the development of these models is a fundamental understanding of the complex transport phenomena which constitute the deposition process which include coupled conduction and radiation as well as transition regime rarefied gas flow. This thesis is aimed at filling these knowledge gaps and thereby leading to the development of the relevant models. The specific process under consideration is the CSS setup developed by the Materials Engineering Group at the Colorado State University (CSU). Initially, a 3-D radiation-conduction model of a single processing station was developed using the commercial finite-element software ABAQUS and validated against data from steady-state experiments carried out at CSU. A simplified model was then optimized for maximizing the steady-state thermal uniformity within the substrate. It was inferred that contrary to traditional top and bottom infrared lamp heating, a lamp configuration that directs heat from the periphery of the sources towards the center results in the minimum temperature
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.
Optimization strategies for evaluation of brain hemodynamic parameters with qBOLD technique.
Wang, Xiaoqi; Sukstanskii, Alexander L; Yablonskiy, Dmitriy A
2013-04-01
Quantitative blood oxygenation level dependent technique provides an MRI-based method to measure tissue hemodynamic parameters such as oxygen extraction fraction and deoxyhemoglobin-containing (veins and prevenous part of capillaries) cerebral blood volume fraction. It is based on a theory of MR signal dephasing in the presence of blood vessel network and experimental method-gradient echo sampling of spin echo previously proposed and validated on phantoms and animals. In vivo human studies also demonstrated feasibility of this approach but also recognized that obtaining reliable results requires high signal-to-noise ratio in the data. In this paper, we analyze in detail the uncertainties of the quantitative blood oxygenation level dependent parameter estimates in the framework of the Bayesian probability theory, namely, we examine how the estimated parameters oxygen extraction fraction and deoxygenated cerebral blood volume fraction depend on their "true values," signal-to-noise ratio, and data sampling strategies. On the basis of this analysis, we develop strategies for optimization of the quantitative blood oxygenation level dependent technique for deoxygenated cerebral blood volume and oxygen extraction fraction evaluation. In particular, it is demonstrated that the use of gradient echo sampling of spin echo sequence allows substantial decrease of measurement errors as the data are acquired on both sides of spin echo. We test our theory on phantom mimicking the structure of blood vessel network. A 3D gradient echo sampling of spin echo pulse sequence is used for the acquisition of the MRI signal that was subsequently analyzed by Bayesian Application Software. The experimental results demonstrated a good agreement with theoretical predictions.
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)
Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li
2015-05-01
In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.
NASA Astrophysics Data System (ADS)
Bundesmann, C.; Lautenschläger, T.; Thelander, E.; Spemann, D.
2017-03-01
Several sets of TiO2 films were grown by Ar ion beam sputter deposition under systematic variation of ion energy and geometrical parameters (ion incidence angle and polar emission angle). The films were characterized concerning thickness, growth rate, structural properties, composition, mass density, and optical properties. The film thicknesses show a cosine-like angular distribution, and the growth rates were found to increase with increasing ion incidence angle and ion energy. All films are amorphous and stoichiometric, but can contain a considerable amount of backscattered primary particles. The atomic fraction of Ar particles decreases systematically with increasing scattering angle, independent from ion energy and ion incidence angle. Mass density and index of refraction show similar systematic variations with ion energy and geometrical parameters. The film properties are mainly influenced by the scattering geometry, and only slightly by ion energy and ion incidence angle. The variations in the film properties are tentatively assigned to changes in the angular and energy distribution of the sputtered target particles and back-scattered primary particles.
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.
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)
Shahdan, Dalila; Ahmad, Sahrim Hj.; Chen, Ruey Shan; Ali, Adilah Mat; Zailan, Farrah Diyana
2016-11-01
A study on processing parameter of polylactic acid (PLA) and graphene nanoplatelet (GNP) prepared via melt blending method using Haake Rheomix internal mixer. In this study liquid natural rubber (LNR) was used as compatibilizer and at the same time introducing ductile property into the nanocomposite blending. In order to determine the optimal processing parameter, nanocomposites were fabricated from PLA: LNR with ratio of 90:10, and 0.2 wt. % of graphene nanoplatelet with different mixing parameter condition; mixing temperature, rotor speed and mixing time. The optimal processing parameter was determined from the results of tensile testing. An optimum processing parameter of polymer nanocomposite was obtained at 180 °C of mixing temperature, 100 rpm of mixing speed and 14 min of mixing time. The SEM micrographs confirmed the dispersio