Gyrokinetic linearized Landau collision operator
DEFF Research Database (Denmark)
Madsen, Jens
2013-01-01
, which is important in multiple ion-species plasmas. Second, the equilibrium operator describes drag and diffusion of the magnetic field aligned component of the vorticity associated with the E×B drift. Therefore, a correct description of collisional effects in turbulent plasmas requires the equilibrium......The full gyrokinetic electrostatic linearized Landau collision operator is calculated including the equilibrium operator, which represents the effect of collisions between gyrokinetic Maxwellian particles. First, the equilibrium operator describes energy exchange between different plasma species...... operator, even for like-particle collisions....
Linearized gyro-kinetic equation
International Nuclear Information System (INIS)
Catto, P.J.; Tsang, K.T.
1976-01-01
An ordering of the linearized Fokker-Planck equation is performed in which gyroradius corrections are retained to lowest order and the radial dependence appropriate for sheared magnetic fields is treated without resorting to a WKB technique. This description is shown to be necessary to obtain the proper radial dependence when the product of the poloidal wavenumber and the gyroradius is large (k rho much greater than 1). A like particle collision operator valid for arbitrary k rho also has been derived. In addition, neoclassical, drift, finite β (plasma pressure/magnetic pressure), and unperturbed toroidal electric field modifications are treated
Partially linearized algorithms in gyrokinetic particle simulation
Energy Technology Data Exchange (ETDEWEB)
Dimits, A.M.; Lee, W.W.
1990-10-01
In this paper, particle simulation algorithms with time-varying weights for the gyrokinetic Vlasov-Poisson system have been developed. The primary purpose is to use them for the removal of the selected nonlinearities in the simulation of gradient-driven microturbulence so that the relative importance of the various nonlinear effects can be assessed. It is hoped that the use of these procedures will result in a better understanding of the transport mechanisms and scaling in tokamaks. Another application of these algorithms is for the improvement of the numerical properties of the simulation plasma. For instance, implementations of such algorithms (1) enable us to suppress the intrinsic numerical noise in the simulation, and (2) also make it possible to regulate the weights of the fast-moving particles and, in turn, to eliminate the associated high frequency oscillations. Examples of their application to drift-type instabilities in slab geometry are given. We note that the work reported here represents the first successful use of the weighted algorithms in particle codes for the nonlinear simulation of plasmas.
Partially linearized algorithms in gyrokinetic particle simulation
International Nuclear Information System (INIS)
Dimits, A.M.; Lee, W.W.
1990-10-01
In this paper, particle simulation algorithms with time-varying weights for the gyrokinetic Vlasov-Poisson system have been developed. The primary purpose is to use them for the removal of the selected nonlinearities in the simulation of gradient-driven microturbulence so that the relative importance of the various nonlinear effects can be assessed. It is hoped that the use of these procedures will result in a better understanding of the transport mechanisms and scaling in tokamaks. Another application of these algorithms is for the improvement of the numerical properties of the simulation plasma. For instance, implementations of such algorithms (1) enable us to suppress the intrinsic numerical noise in the simulation, and (2) also make it possible to regulate the weights of the fast-moving particles and, in turn, to eliminate the associated high frequency oscillations. Examples of their application to drift-type instabilities in slab geometry are given. We note that the work reported here represents the first successful use of the weighted algorithms in particle codes for the nonlinear simulation of plasmas
Linear relativistic gyrokinetic equation in general magnetically confined plasmas
International Nuclear Information System (INIS)
Tsai, S.T.; Van Dam, J.W.; Chen, L.
1983-08-01
The gyrokinetic formalism for linear electromagnetic waves of arbitrary frequency in general magnetic-field configurations is extended to include full relativistic effects. The derivation employs the small adiabaticity parameter rho/L 0 where rho is the Larmor radius and L 0 the equilibrium scale length. The effects of the plasma and magnetic field inhomogeneities and finite Larmor-radii effects are also contained
A quasi-linear gyrokinetic transport model for tokamak plasmas
International Nuclear Information System (INIS)
Casati, A.
2009-10-01
After a presentation of some basics around nuclear fusion, this research thesis introduces the framework of the tokamak strategy to deal with confinement, hence the main plasma instabilities which are responsible for turbulent transport of energy and matter in such a system. The author also briefly introduces the two principal plasma representations, the fluid and the kinetic ones. He explains why the gyro-kinetic approach has been preferred. A tokamak relevant case is presented in order to highlight the relevance of a correct accounting of the kinetic wave-particle resonance. He discusses the issue of the quasi-linear response. Firstly, the derivation of the model, called QuaLiKiz, and its underlying hypotheses to get the energy and the particle turbulent flux are presented. Secondly, the validity of the quasi-linear response is verified against the nonlinear gyro-kinetic simulations. The saturation model that is assumed in QuaLiKiz, is presented and discussed. Then, the author qualifies the global outcomes of QuaLiKiz. Both the quasi-linear energy and the particle flux are compared to the expectations from the nonlinear simulations, across a wide scan of tokamak relevant parameters. Therefore, the coupling of QuaLiKiz within the integrated transport solver CRONOS is presented: this procedure allows the time-dependent transport problem to be solved, hence the direct application of the model to the experiment. The first preliminary results regarding the experimental analysis are finally discussed
Linear and nonlinear verification of gyrokinetic microstability codes
Bravenec, R. V.; Candy, J.; Barnes, M.; Holland, C.
2011-12-01
Verification of nonlinear microstability codes is a necessary step before comparisons or predictions of turbulent transport in toroidal devices can be justified. By verification we mean demonstrating that a code correctly solves the mathematical model upon which it is based. Some degree of verification can be accomplished indirectly from analytical instability threshold conditions, nonlinear saturation estimates, etc., for relatively simple plasmas. However, verification for experimentally relevant plasma conditions and physics is beyond the realm of analytical treatment and must rely on code-to-code comparisons, i.e., benchmarking. The premise is that the codes are verified for a given problem or set of parameters if they all agree within a specified tolerance. True verification requires comparisons for a number of plasma conditions, e.g., different devices, discharges, times, and radii. Running the codes and keeping track of linear and nonlinear inputs and results for all conditions could be prohibitive unless there was some degree of automation. We have written software to do just this and have formulated a metric for assessing agreement of nonlinear simulations. We present comparisons, both linear and nonlinear, between the gyrokinetic codes GYRO [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and GS2 [W. Dorland, F. Jenko, M. Kotschenreuther, and B. N. Rogers, Phys. Rev. Lett. 85, 5579 (2000)]. We do so at the mid-radius for the same discharge as in earlier work [C. Holland, A. E. White, G. R. McKee, M. W. Shafer, J. Candy, R. E. Waltz, L. Schmitz, and G. R. Tynan, Phys. Plasmas 16, 052301 (2009)]. The comparisons include electromagnetic fluctuations, passing and trapped electrons, plasma shaping, one kinetic impurity, and finite Debye-length effects. Results neglecting and including electron collisions (Lorentz model) are presented. We find that the linear frequencies with or without collisions agree well between codes, as do the time averages of
International Nuclear Information System (INIS)
Cottier, Pierre
2013-01-01
The magnetic confinement in tokamaks is for now the most advanced way towards energy production by nuclear fusion. Both theoretical and experimental studies showed that rotation generation can increase its performance by reducing the turbulent transport in tokamak plasmas. The rotation influence on the heat and particle fluxes is studied along with the angular momentum transport with the quasi-linear gyro-kinetic eigenvalue code QuaLiKiz. For this purpose, the QuaLiKiz code is modified in order to take the plasma rotation into account and compute the angular momentum flux. It is shown that QuaLiKiz framework is able to correctly predict the angular momentum flux including the E*B shear induced residual stress as well as the influence of rotation on the heat and particle fluxes. The major approximations of QuaLiKiz formalisms are reviewed, in particular the ballooning representation at its lowest order and the eigenfunctions calculated in the hydrodynamic limit. The construction of the quasi-linear fluxes is also reviewed in details and the quasi-linear angular momentum flux is derived. The different contributions to the turbulent momentum flux are studied and successfully compared both against non-linear gyro-kinetic simulations and experimental data. (author) [fr
Energy Technology Data Exchange (ETDEWEB)
Hager, Robert, E-mail: rhager@pppl.gov; Chang, C. S., E-mail: cschang@pppl.gov [Princeton Plasma Physics Laboratory, P.O. Box 451, Princeton, New Jersey 08543 (United States)
2016-04-15
As a follow-up on the drift-kinetic study of the non-local bootstrap current in the steep edge pedestal of tokamak plasma by Koh et al. [Phys. Plasmas 19, 072505 (2012)], a gyrokinetic neoclassical study is performed with gyrokinetic ions and drift-kinetic electrons. Besides the gyrokinetic improvement of ion physics from the drift-kinetic treatment, a fully non-linear Fokker-Planck collision operator—that conserves mass, momentum, and energy—is used instead of Koh et al.'s linearized collision operator in consideration of the possibility that the ion distribution function is non-Maxwellian in the steep pedestal. An inaccuracy in Koh et al.'s result is found in the steep edge pedestal that originated from a small error in the collisional momentum conservation. The present study concludes that (1) the bootstrap current in the steep edge pedestal is generally smaller than what has been predicted from the small banana-width (local) approximation [e.g., Sauter et al., Phys. Plasmas 6, 2834 (1999) and Belli et al., Plasma Phys. Controlled Fusion 50, 095010 (2008)], (2) the plasma flow evaluated from the local approximation can significantly deviate from the non-local results, and (3) the bootstrap current in the edge pedestal, where the passing particle region is small, can be dominantly carried by the trapped particles in a broad trapped boundary layer. A new analytic formula based on numerous gyrokinetic simulations using various magnetic equilibria and plasma profiles with self-consistent Grad-Shafranov solutions is constructed.
Non-linear gyrokinetic simulations of microturbulence in TCV electron internal transport barriers
Energy Technology Data Exchange (ETDEWEB)
Lapillonne, X; Brunner, S; Sauter, O; Villard, L [Centre de Recherches en Physique des Plasmas, Association EURATOM-Confederation Suisse, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland); Fable, E; Goerler, T; Jenko, F; Merz, F, E-mail: stephan.brunner@epfl.ch [Max-Planck-Institut fuer Plasmaphysik, EURATOM Association, Boltzmannstrasse 2, D-85748 Garching (Germany)
2011-05-15
Using the local (flux-tube) version of the Eulerian code GENE (Jenko et al 2000 Phys. Plasmas 7 1904), gyrokinetic simulations of microturbulence were carried out considering parameters relevant to electron-internal transport barriers (e-ITBs) in the TCV tokamak (Sauter et al 2005 Phys. Rev. Lett. 94 105002), generated under conditions of low or negative shear. For typical density and temperature gradients measured in such barriers, the corresponding simulated fluctuation spectra appears to simultaneously contain longer wavelength trapped electron modes (TEMs, for typically k{sub p}erpendicular{rho}{sub i} < 0.5, k{sub p}erpendicular being the characteristic perpendicular wavenumber and {rho}{sub i} the ion Larmor radius) and shorter wavelength ion temperature gradient modes (ITG, k{sub p}erpendicular{rho}{sub i} > 0.5). The contributions to the electron particle flux from these two types of modes are, respectively, outward/inward and may cancel each other for experimentally realistic gradients. This mechanism may partly explain the feasibility of e-ITBs. The non-linear simulation results confirm the predictions of a previously developed quasi-linear model (Fable et al 2010 Plasma Phys. Control. Fusion 52 015007), namely that the stationary condition of zero particle flux is obtained through the competitive contributions of ITG and TEM. A quantitative comparison of the electron heat flux with experimental estimates is presented as well.
Non-linear gyrokinetic simulations of microturbulence in TCV electron internal transport barriers
Lapillonne, X.; Brunner, S.; Sauter, O.; Villard, L.; Fable, E.; Görler, T.; Jenko, F.; Merz, F.
2011-05-01
Using the local (flux-tube) version of the Eulerian code GENE (Jenko et al 2000 Phys. Plasmas 7 1904), gyrokinetic simulations of microturbulence were carried out considering parameters relevant to electron-internal transport barriers (e-ITBs) in the TCV tokamak (Sauter et al 2005 Phys. Rev. Lett. 94 105002), generated under conditions of low or negative shear. For typical density and temperature gradients measured in such barriers, the corresponding simulated fluctuation spectra appears to simultaneously contain longer wavelength trapped electron modes (TEMs, for typically k⊥ρi 0.5). The contributions to the electron particle flux from these two types of modes are, respectively, outward/inward and may cancel each other for experimentally realistic gradients. This mechanism may partly explain the feasibility of e-ITBs. The non-linear simulation results confirm the predictions of a previously developed quasi-linear model (Fable et al 2010 Plasma Phys. Control. Fusion 52 015007), namely that the stationary condition of zero particle flux is obtained through the competitive contributions of ITG and TEM. A quantitative comparison of the electron heat flux with experimental estimates is presented as well.
Gyrokinetic analysis of linear microinstabilities for the stellarator Wendelstein 7-X
Xanthopoulos, P.; Jenko, F.
2007-04-01
A linear collisionless gyrokinetic investigation of ion temperature gradient (ITG) modes—considering both adiabatic and full electron dynamics—and trapped electron modes (TEMs) is presented for the stellarator Wendelstein 7-X (W7-X) [G. Grieger et al., Plasma Physics and Controlled Nuclear Fusion Research 1990 (International Atomic Energy Agency, Vienna, 1991), Vol. 3, p. 525]. The study of ITG modes reveals that in W7-X, microinstabilities of distinct character coexist. The effect of changes in the density gradient and temperature ratio is discussed. Substantial differences with respect to the axisymmetric geometry appear in W7-X, concerning the relative separation of regions with a large fraction of helically trapped particles and those of pronounced bad curvature. For both ITG modes and TEMs, the dependence of their linear growth rates on the background gradients is studied along with their parallel mode structure.
Biancalani, A.; Bottino, A.; Ehrlacher, C.; Grandgirard, V.; Merlo, G.; Novikau, I.; Qiu, Z.; Sonnendrücker, E.; Garbet, X.; Görler, T.; Leerink, S.; Palermo, F.; Zarzoso, D.
2017-06-01
The linear properties of the geodesic acoustic modes (GAMs) in tokamaks are investigated by means of the comparison of analytical theory and gyrokinetic numerical simulations. The dependence on the value of the safety factor, finite-orbit-width of the ions in relation to the radial mode width, magnetic-flux-surface shaping, and electron/ion mass ratio are considered. Nonuniformities in the plasma profiles (such as density, temperature, and safety factor), electro-magnetic effects, collisions, and the presence of minority species are neglected. Also, only linear simulations are considered, focusing on the local dynamics. We use three different gyrokinetic codes: the Lagrangian (particle-in-cell) code ORB5, the Eulerian code GENE, and semi-Lagrangian code GYSELA. One of the main aims of this paper is to provide a detailed comparison of the numerical results and analytical theory, in the regimes where this is possible. This helps understanding better the behavior of the linear GAM dynamics in these different regimes, the behavior of the codes, which is crucial in the view of a future work where more physics is present, and the regimes of validity of each specific analytical dispersion relation.
International Nuclear Information System (INIS)
Villard, L.; Allfrey, S.J.; Bottino, A.
2003-01-01
The aim of this paper is to report on recent advances made on global gyrokinetic simulations of Ion Temperature Gradient modes (ITG) and other microinstabilities. The nonlinear development and saturation of ITG modes and the role of E x B zonal flows are studied with a global nonlinear δ f formulation that retains parallel nonlinearity and thus allows for a check of the energy conservation property as a means to verify the quality of the numerical simulation. Due to an optimised loading technique the conservation property is satisfied with an unprecedented quality well into the nonlinear stage. The zonal component of the perturbation establishes a quasi-steady state with regions of ITG suppression, strongly reduced radial energy flux and steepened effective temperature profile alternating with regions of higher ITG mode amplitudes, larger radial energy flux and flattened effective temperature profile. A semi-Lagrangian approach free of statistical noise is proposed as an alternative to the nonlinear δf formulation. An ASDEX-Upgrade experiment with an Internal Transport Barrier (ITB) is analysed with a global gyrokinetic code that includes trapped electron dynamics. The weakly destabilizing effect of trapped electron dynamics on ITG modes in an axisymmetric bumpy configuration modelling W7-X is shown in global linear simulations that retain the full electron dynamics. Finite β effects on microinstabilities are investigated with a linear global spectral electromagnetic gyrokinetic formulation. The radial global structure of electromagnetic modes shows a resonant behaviour with rational q values. (author)
International Nuclear Information System (INIS)
Parra, Felix I; Catto, Peter J
2009-01-01
We compare two different derivations of the gyrokinetic equation: the Hamiltonian approach in Dubin D H E et al (1983 Phys. Fluids 26 3524) and the recursive methodology in Parra F I and Catto P J (2008 Plasma Phys. Control. Fusion 50 065014). We prove that both approaches yield the same result at least to second order in a Larmor radius over macroscopic length expansion. There are subtle differences in the definitions of some of the functions that need to be taken into account to prove the equivalence.
The Theory of Linear Prediction
Vaidyanathan, PP
2007-01-01
Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vecto
Gyrokinetic simulations of neoclassical transport using a minimal collision operator
International Nuclear Information System (INIS)
Dif-Pradalier, G.; Grandgirard, V.; Sarazin, Y.; Garbet, X.; Ghendrih, Ph.; Angelino, P.
2008-01-01
Conventional neoclassical predictions are successfully recovered within a gyrokinetic framework using a minimal Fokker-Planck collision operator. This operator is shown to accurately describe some essential features of neoclassical theory, namely the neoclassical transport, the poloidal rotation and the linear damping of axisymmetric flows while interestingly preserving a high numerical efficiency. Its form makes it especially adapted to Eulerian or Semi-Lagrangian schemes.
Global gyrokinetic and fluid hybrid simulations of tokamaks and stellarators
Energy Technology Data Exchange (ETDEWEB)
Cole, Michael David John
2016-07-15
simulations in this TAE case have been performed confirming the analytical prediction of a quadratic relationship between the linear growth rate of the TAE and the saturated amplitude of the TAE for a range of moderate values of the linear growth rate. At higher linear growth rate, a slower scaling of saturated amplitude with linear growth rate is observed. This analysis has been extended to include the non-linear wave-wave coupling between multiple TAE modes. It has been shown that wave-wave coupling results in a significant reduction in the saturated amplitude. It has been demonstrated that both plasma elongation and ion kinetic effects can exert a stabilising influence on the internal kink mode. A population of energetic particles can also exert a stabilising influence at low normalised pressure. At high normalised fast particle pressure the stabilised kink mode has been shown to give way to the m=1 EPM, which has been simulated both linearly and non-linearly (the 'fishbone' mode). The first self-consistent simulations of global modes in the magnetic geometry of the optimised stellarator Wendelstein 7-X have been performed both linearly and non-linearly. Limitations have been encountered in performing simulations in 3D geometry. A hypothesis for the cause of these problems is outlined and ideas for mitigation are briefly described. In addition to the hybrid model simulations, some of the first utilisations of a new scheme for mitigating the cancellation problem in the fully gyrokinetic regime have been carried out in the framework of this thesis. This scheme, which was developed separately, is concisely described in this work. The new scheme has been benchmarked with existing gyrokinetic and hybrid results. The linear Wendelstein 7-X simulations and linear and single mode non-linear TAE simulations have been repeated with the new model. It is shown that bulk plasma kinetics can suppress the growth rate of global modes in Wendelstein 7-X. The results of fully
Global gyrokinetic and fluid hybrid simulations of tokamaks and stellarators
International Nuclear Information System (INIS)
Cole, Michael David John
2016-01-01
in this TAE case have been performed confirming the analytical prediction of a quadratic relationship between the linear growth rate of the TAE and the saturated amplitude of the TAE for a range of moderate values of the linear growth rate. At higher linear growth rate, a slower scaling of saturated amplitude with linear growth rate is observed. This analysis has been extended to include the non-linear wave-wave coupling between multiple TAE modes. It has been shown that wave-wave coupling results in a significant reduction in the saturated amplitude. It has been demonstrated that both plasma elongation and ion kinetic effects can exert a stabilising influence on the internal kink mode. A population of energetic particles can also exert a stabilising influence at low normalised pressure. At high normalised fast particle pressure the stabilised kink mode has been shown to give way to the m=1 EPM, which has been simulated both linearly and non-linearly (the 'fishbone' mode). The first self-consistent simulations of global modes in the magnetic geometry of the optimised stellarator Wendelstein 7-X have been performed both linearly and non-linearly. Limitations have been encountered in performing simulations in 3D geometry. A hypothesis for the cause of these problems is outlined and ideas for mitigation are briefly described. In addition to the hybrid model simulations, some of the first utilisations of a new scheme for mitigating the cancellation problem in the fully gyrokinetic regime have been carried out in the framework of this thesis. This scheme, which was developed separately, is concisely described in this work. The new scheme has been benchmarked with existing gyrokinetic and hybrid results. The linear Wendelstein 7-X simulations and linear and single mode non-linear TAE simulations have been repeated with the new model. It is shown that bulk plasma kinetics can suppress the growth rate of global modes in Wendelstein 7-X. The results of fully gyrokinetic TAE
Hager, Robert; Yoon, E. S.; Ku, S.; D'Azevedo, E. F.; Worley, P. H.; Chang, C. S.
2015-11-01
We describe the implementation, and application of a time-dependent, fully nonlinear multi-species Fokker-Planck-Landau collision operator based on the single-species work of Yoon and Chang [Phys. Plasmas 21, 032503 (2014)] in the full-function gyrokinetic particle-in-cell codes XGC1 [Ku et al., Nucl. Fusion 49, 115021 (2009)] and XGCa. XGC simulations include the pedestal and scrape-off layer, where significant deviations of the particle distribution function from a Maxwellian can occur. Thus, in order to describe collisional effects on neoclassical and turbulence physics accurately, the use of a non-linear collision operator is a necessity. Our collision operator is based on a finite volume method using the velocity-space distribution functions sampled from the marker particles. Since the same fine configuration space mesh is used for collisions and the Poisson solver, the workload due to collisions can be comparable to or larger than the workload due to particle motion. We demonstrate that computing time spent on collisions can be kept affordable by applying advanced parallelization strategies while conserving mass, momentum, and energy to reasonable accuracy. We also show results of production scale XGCa simulations in the H-mode pedestal and compare to conventional theory. Work supported by US DOE OFES and OASCR.
Gyrokinetic simulation of microtearing turbulence
International Nuclear Information System (INIS)
Doerk, Hauke
2013-01-01
In modern fusion experiments, plasma turbulence is responsible for the radial heat transport and thus determines the plasma confinement within the magnetic field of tokamak devices. Deeper theoretical understanding is needed to explain today's and future fusion experiments. The goal of fusion research is to establish nuclear fusion as a safe and sustainable energy source. In future fusion power plants, and also in large fusion experiments like the presently constructed ITER, plasma heating predominantly affects the electron species. The reason is of fundamental nature: the collisional cross section of fast ions that are produced by the heating systems is larger for thermal electrons than for thermal ions. It is thus essential to correctly predict electron thermal transport, but the overall picture still continues to evolve. Besides microinstabilities on the electron gyroradius scales, also a stochastized magnetic field can contribute to enhanced electron transport. Already since the 1970's, the so-called microtearing instability is discussed as a source of stochastic fields. This microinstability deserves its name for breaking up the magnetic field structure by forming small-scale magnetic islands. The linear microtearing instability and its nonlinear, turbulent behavior is investigated in this thesis by means of numerical simulations with the gyrokinetic turbulence code Gene. The underlying gyrokinetic equations are not only appropriate to predict turbulent transport, but also describe neoclassical transport that is drift-kinetic in nature. Besides revealing interesting physics on long time scales, solving the neoclassical equation serves as an excellent test for the numerical implementation of the collision operator in Gene. Focusing on the local limit, it is found that a modification of this implementation that considers certain symmetries is necessary to obtain a satisfactory agreement with the well-established drift-kinetic neoclassical code Neo. Also the
International Nuclear Information System (INIS)
Sugama, H.
1999-08-01
The Lagrangian formulation of the gyrokinetic theory is generalized in order to describe the particles' dynamics as well as the self-consistent behavior of the electromagnetic fields. The gyrokinetic equation for the particle distribution function and the gyrokinetic Maxwell's equations for the electromagnetic fields are both derived from the variational principle for the Lagrangian consisting of the parts of particles, fields, and their interaction. In this generalized Lagrangian formulation, the energy conservation property for the total nonlinear gyrokinetic system of equations is directly shown from the Noether's theorem. This formulation can be utilized in order to derive the nonlinear gyrokinetic system of equations and the rigorously conserved total energy for fluctuations with arbitrary frequency. (author)
Similarities and Differences Between Warped Linear Prediction and Laguerre Linear Prediction
Brinker, Albertus C. den; Krishnamoorthi, Harish; Verbitskiy, Evgeny A.
2011-01-01
Linear prediction has been successfully applied in many speech and audio processing systems. This paper presents the similarities and differences between two classes of linear prediction schemes, namely, Warped Linear Prediction (WLP) and Laguerre Linear Prediction (LLP). It is shown that both
Gyrokinetic simulation of finite-β plasmas on parallel architectures
International Nuclear Information System (INIS)
Reynders, J.V.W.
1993-01-01
Much research exists on the linear and non-linear properties of plasma microinstabilities induced by density and temperature gradients. There has been an interest in the electromagnetic or finite-β effects on these microinstabilities. This thesis focuses on the finite-β modification of an ion temperature gradient (ITG) driven microinstability in a two-dimensional shearless and sheared-slab geometries. A gyrokinetic model is employed in the numerical and analytic studies of this instability. Chapter 1 introduces the electromagnetic gyrokinetic model employed in the numerical and analytic studies of the ITG instability. Some discussion of the Klimontovich particle representation of the gyrokinetic Vlasov equation and a multiple scale model of the background plasma gradient is presented. Chapter 2 details the computational issues facing an electromagnetic gyrokinetic particle simulation of the ITG mode. An electromagnetic extension of the partially linearized algorithm is presented with a comparison of quiet particle initialization routines. Chapter 3 presents and compares algorithms for the gyrokinetic particle simulation technique on SIMD and MIMD computing platforms. Chapter 4 discusses electromagnetic gyrokinetic fluctuation theory and provides a comparison of analytic and numerical results. Chapter 5 contains a linear and a non-linear three-wave coupling analysis of the finite-β modified ITG mode in a shearless slab geometry. Comparisons are made with linear and partially linearized gyrokinetic simulation results. Chapter 6 presents results from a finite-β modified ITG mode in a sheared slab geometry. The linear dispersion relation is derived and results from an integral eigenvalue code are presented. Comparisons are made with the gyrokinetic particle code in a variety of limits with both adiabatic and non-adiabatic electrons. Evidence of ITG driven microtearing is presented
The Use of Linear Programming for Prediction.
Schnittjer, Carl J.
The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)
Transport modelling and gyrokinetic analysis of advanced high performance discharges
International Nuclear Information System (INIS)
Kinsey, J.E.; Imbeaux, F.; Staebler, G.M.; Budny, R.; Bourdelle, C.; Fukuyama, A.; Garbet, X.; Tala, T.; Parail, V.
2005-01-01
Predictive transport modelling and gyrokinetic stability analyses of demonstration hybrid (HYBRID) and advanced tokamak (AT) discharges from the International Tokamak Physics Activity (ITPA) profile database are presented. Both regimes have exhibited enhanced core confinement (above the conventional ITER reference H-mode scenario) but differ in their current density profiles. Recent contributions to the ITPA database have facilitated an effort to study the underlying physics governing confinement in these advanced scenarios. In this paper, we assess the level of commonality of the turbulent transport physics and the relative roles of the transport suppression mechanisms (i.e. E x B shear and Shafranov shift (α) stabilization) using data for select HYBRID and AT discharges from the DIII-D, JET and AUG tokamaks. GLF23 transport modelling and gyrokinetic stability analysis indicate that E x B shear and Shafranov shift stabilization play essential roles in producing the improved core confinement in both HYBRID and AT discharges. Shafranov shift stabilization is found to be more important in AT discharges than in HYBRID discharges. We have also examined the competition between the stabilizing effects of E x B shear and Shafranov shift stabilization and the destabilizing effects of higher safety factors and parallel velocity shear. Linear and nonlinear gyrokinetic simulations of idealized low and high safety factor cases reveal some interesting consequences. A low safety factor (i.e. HYBRID relevant) is directly beneficial in reducing the transport, and E x B shear stabilization can dominate parallel velocity shear destabilization allowing the turbulence to be quenched. However, at low-q/high current, Shafranov shift stabilization plays less of a role. Higher safety factors (as found in AT discharges), on the other hand, have larger amounts of Shafranov shift stabilization, but parallel velocity shear destabilization can prevent E x B shear quenching of the turbulent
Transport modeling and gyrokinetic analysis of advanced high performance discharges
International Nuclear Information System (INIS)
Kinsey, J.; Imbeaux, F.; Bourdelle, C.; Garbet, X.; Staebler, G.; Budny, R.; Fukuyama, A.; Tala, T.; Parail, V.
2005-01-01
Predictive transport modeling and gyrokinetic stability analyses of demonstration hybrid (HYBRID) and Advanced Tokamak (AT) discharges from the International Tokamak Physics Activity (ITPA) profile database are presented. Both regimes have exhibited enhanced core confinement (above the conventional ITER reference H-mode scenario) but differ in their current density profiles. Recent contributions to the ITPA database have facilitated an effort to study the underlying physics governing confinement in these advanced scenarios. In this paper, we assess the level of commonality of the turbulent transport physics and the relative roles of the transport suppression mechanisms (i.e. ExB shear and Shafranov shift (α) stabilization) using data for select HYBRID and AT discharges from the DIII-D, JET, and AUG tokamaks. GLF23 transport modeling and gyrokinetic stability analysis indicates that ExB shear and Shafranov shift stabilization play essential roles in producing the improved core confinement in both HYBRID and AT discharges. Shafranov shift stabilization is found to be more important in AT discharges than in HYBRID discharges. We have also examined the competition between the stabilizing effects of ExB shear and Shafranov shift stabilization and the destabilizing effects of higher safety factors and parallel velocity shear. Linear and nonlinear gyrokinetic simulations of idealized low and high safety factor cases reveals some interesting consequences. A low safety factor (i.e. HYBRID relevant) is directly beneficial in reducing the transport, and ExB shear stabilization can win out over parallel velocity shear destabilization allowing the turbulence to be quenched. However, at low-q/high current, Shafranov shift stabilization plays less of a role. Higher safety factors (as found in AT discharges), on the other hand, have larger amounts of Shafranov shift stabilization, but parallel velocity shear destabilization can prevent ExB shear quenching of the turbulent
Linear zonal atmospheric prediction for adaptive optics
McGuire, Patrick C.; Rhoadarmer, Troy A.; Coy, Hanna A.; Angel, J. Roger P.; Lloyd-Hart, Michael
2000-07-01
We compare linear zonal predictors of atmospheric turbulence for adaptive optics. Zonal prediction has the possible advantage of being able to interpret and utilize wind-velocity information from the wavefront sensor better than modal prediction. For simulated open-loop atmospheric data for a 2- meter 16-subaperture AO telescope with 5 millisecond prediction and a lookback of 4 slope-vectors, we find that Widrow-Hoff Delta-Rule training of linear nets and Back- Propagation training of non-linear multilayer neural networks is quite slow, getting stuck on plateaus or in local minima. Recursive Least Squares training of linear predictors is two orders of magnitude faster and it also converges to the solution with global minimum error. We have successfully implemented Amari's Adaptive Natural Gradient Learning (ANGL) technique for a linear zonal predictor, which premultiplies the Delta-Rule gradients with a matrix that orthogonalizes the parameter space and speeds up the training by two orders of magnitude, like the Recursive Least Squares predictor. This shows that the simple Widrow-Hoff Delta-Rule's slow convergence is not a fluke. In the case of bright guidestars, the ANGL, RLS, and standard matrix-inversion least-squares (MILS) algorithms all converge to the same global minimum linear total phase error (approximately 0.18 rad2), which is only approximately 5% higher than the spatial phase error (approximately 0.17 rad2), and is approximately 33% lower than the total 'naive' phase error without prediction (approximately 0.27 rad2). ANGL can, in principle, also be extended to make non-linear neural network training feasible for these large networks, with the potential to lower the predictor error below the linear predictor error. We will soon scale our linear work to the approximately 108-subaperture MMT AO system, both with simulations and real wavefront sensor data from prime focus.
Alfven Waves in Gyrokinetic Plasmas
International Nuclear Information System (INIS)
Lee, W.W.; Qin, H.
2003-01-01
A brief comparison of the properties of Alfven waves that are based on the gyrokinetic description with those derived from the MHD equations is presented. The critical differences between these two approaches are the treatment of the ion polarization effects. As such, the compressional Alfven waves in a gyrokinetic plasma can be eliminated through frequency ordering, whereas geometric simplifications are needed to decouple the shear Alfven waves from the compressional Alfven waves within the context of MHD. Theoretical and numerical procedures of using gyrokinetic particle simulation for studying microturbulence and kinetic-MHD physics including finite Larmor radius effects are also presented
Conservation Laws for Gyrokinetic Equations for Large Perturbations and Flows
Dimits, Andris
2017-10-01
Gyrokinetic theory has proved to be very useful for the understanding of magnetized plasmas, both to simplify analytical treatments and as a basis for efficient numerical simulations. Gyrokinetic theories were previously developed in two extended orderings that are applicable to large fluctuations and flows as may arise in the tokamak edge and scrapeoff layer. In the present work, we cast the resulting equations in a field-theoretical variational form, and derive, up to second order in the respective orderings, the associated global and local energy and (linear and toroidal) momentum conservation relations that result from Noether's theorem. The consequences of these for the various possible choices of numerical discretization used in gyrokinetic simulations are considered. Prepared for US DOE by LLNL under Contract DE-AC52-07NA27344 and supported by the U.S. DOE, OFES.
Linear Prediction Using Refined Autocorrelation Function
Directory of Open Access Journals (Sweden)
M. Shahidur Rahman
2007-07-01
Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.
Citrin, J.; Bourdelle, C.; Casson, F. J.; Angioni, C.; Bonanomi, N.; Camenen, Y.; Garbet, X.; Garzotti, L.; Görler, T.; Gürcan, O.; Koechl, F.; Imbeaux, F.; Linder, O.; van de Plassche, K.; Strand, P.; Szepesi, G.; Contributors, JET
2017-12-01
Quasilinear turbulent transport models are a successful tool for prediction of core tokamak plasma profiles in many regimes. Their success hinges on the reproduction of local nonlinear gyrokinetic fluxes. We focus on significant progress in the quasilinear gyrokinetic transport model QuaLiKiz (Bourdelle et al 2016 Plasma Phys. Control. Fusion 58 014036), which employs an approximated solution of the mode structures to significantly speed up computation time compared to full linear gyrokinetic solvers. Optimisation of the dispersion relation solution algorithm within integrated modelling applications leads to flux calculations × {10}6-7 faster than local nonlinear simulations. This allows tractable simulation of flux-driven dynamic profile evolution including all transport channels: ion and electron heat, main particles, impurities, and momentum. Furthermore, QuaLiKiz now includes the impact of rotation and temperature anisotropy induced poloidal asymmetry on heavy impurity transport, important for W-transport applications. Application within the JETTO integrated modelling code results in 1 s of JET plasma simulation within 10 h using 10 CPUs. Simultaneous predictions of core density, temperature, and toroidal rotation profiles for both JET hybrid and baseline experiments are presented, covering both ion and electron turbulence scales. The simulations are successfully compared to measured profiles, with agreement mostly in the 5%-25% range according to standard figures of merit. QuaLiKiz is now open source and available at www.qualikiz.com.
Sparsity in Linear Predictive Coding of Speech
DEFF Research Database (Denmark)
Giacobello, Daniele
of the effectiveness of their application in audio processing. The second part of the thesis deals with introducing sparsity directly in the linear prediction analysis-by-synthesis (LPAS) speech coding paradigm. We first propose a novel near-optimal method to look for a sparse approximate excitation using a compressed...... one with direct applications to coding but also consistent with the speech production model of voiced speech, where the excitation of the all-pole filter can be modeled as an impulse train, i.e., a sparse sequence. Introducing sparsity in the LP framework will also bring to de- velop the concept...... sensing formulation. Furthermore, we define a novel re-estimation procedure to adapt the predictor coefficients to the given sparse excitation, balancing the two representations in the context of speech coding. Finally, the advantages of the compact parametric representation of a segment of speech, given...
Energy Technology Data Exchange (ETDEWEB)
Fahey, Mark R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Candy, Jeff [General Atomics, San Diego, CA (United States)
2013-11-07
This project initiated the development of TGYRO - a steady-state Gyrokinetic transport code (SSGKT) that integrates micro-scale GYRO turbulence simulations into a framework for practical multi-scale simulation of conventional tokamaks as well as future reactors. Using a lightweight master transport code, multiple independent (each massively parallel) gyrokinetic simulations are coordinated. The capability to evolve profiles using the TGLF model was also added to TGYRO and represents a more typical use-case for TGYRO. The goal of the project was to develop a steady-state Gyrokinetic transport code (SSGKT) that integrates micro-scale gyrokinetic turbulence simulations into a framework for practical multi-scale simulation of a burning plasma core ? the International Thermonuclear Experimental Reactor (ITER) in particular. This multi-scale simulation capability will be used to predict the performance (the fusion energy gain, Q) given the H-mode pedestal temperature and density. At present, projections of this type rely on transport models like GLF23, which are based on rather approximate fits to the results of linear and nonlinear simulations. Our goal is to make these performance projections with precise nonlinear gyrokinetic simulations. The method of approach is to use a lightweight master transport code to coordinate multiple independent (each massively parallel) gyrokinetic simulations using the GYRO code. This project targets the practical multi-scale simulation of a reactor core plasma in order to predict the core temperature and density profiles given the H-mode pedestal temperature and density. A master transport code will provide feedback to O(16) independent gyrokinetic simulations (each massively parallel). A successful feedback scheme offers a novel approach to predictive modeling of an important national and international problem. Success in this area of fusion simulations will allow US scientists to direct the research path of ITER over the next two
Intrinsic rotation with gyrokinetic models
International Nuclear Information System (INIS)
Parra, Felix I.; Barnes, Michael; Catto, Peter J.; Calvo, Iván
2012-01-01
The generation of intrinsic rotation by turbulence and neoclassical effects in tokamaks is considered. To obtain the complex dependences observed in experiments, it is necessary to have a model of the radial flux of momentum that redistributes the momentum within the tokamak in the absence of a preexisting velocity. When the lowest order gyrokinetic formulation is used, a symmetry of the model precludes this possibility, making small effects in the gyroradius over scale length expansion necessary. These effects that are usually small become important for momentum transport because the symmetry of the lowest order gyrokinetic formulation leads to the cancellation of the lowest order momentum flux. The accuracy to which the gyrokinetic equation needs to be obtained to retain all the physically relevant effects is discussed.
Gyrokinetic magnetohydrodynamics and the associated equilibria
Lee, W. W.; Hudson, S. R.; Ma, C. H.
2017-12-01
The gyrokinetic magnetohydrodynamic (MHD) equations, related to the recent paper by W. W. Lee ["Magnetohydrodynamics for collisionless plasmas from the gyrokinetic perspective," Phys. Plasmas 23, 070705 (2016)], and their associated equilibria properties are discussed. This set of equations consists of the time-dependent gyrokinetic vorticity equation, the gyrokinetic parallel Ohm's law, and the gyrokinetic Ampere's law as well as the equations of state, which are expressed in terms of the electrostatic potential, ϕ, and the vector potential, A , and support both spatially varying perpendicular and parallel pressure gradients and the associated currents. The corresponding gyrokinetic MHD equilibria can be reached when ϕ→0 and A becomes constant in time, which, in turn, gives ∇.(J∥+J⊥)=0 and the associated magnetic islands, if they exist. Examples of simple cylindrical geometry are given. These gyrokinetic MHD equations look quite different from the conventional MHD equations, and their comparisons will be an interesting topic in the future.
Freethy, S. J.; Görler, T.; Creely, A. J.; Conway, G. D.; Denk, S. S.; Happel, T.; Koenen, C.; Hennequin, P.; White, A. E.; ASDEX Upgrade Team
2018-05-01
Measurements of turbulent electron temperature fluctuation amplitudes, δTe ⊥/Te , frequency spectra, and radial correlation lengths, Lr(Te ⊥) , have been performed at ASDEX Upgrade using a newly upgraded Correlation ECE diagnostic in the range of scales k⊥scale non-linear gyrokinetic turbulence simulations of the outer core (ρtor = 0.75) of a low density, electron heated L-mode plasma, performed using the gyrokinetic simulation code, GENE. The ion and electron temperature gradients were scanned within uncertainties. It is found that gyrokinetic simulations are able to match simultaneously the electron and ion heat flux at this radius within the experimental uncertainties. The simulations were performed based on a reference discharge for which δTe ⊥/Te measurements were available, and Lr(Te ⊥) and αnT were then predicted using synthetic diagnostics prior to measurements in a repeat discharge. While temperature fluctuation amplitudes are overestimated by >50% for all simulations within the sensitivity scans performed, good quantitative agreement is found for Lr(Te ⊥) and αnT. A validation metric is used to quantify the level of agreement of individual simulations with experimental measurements, and the best agreement is found close to the experimental gradient values.
Self-consistent gyrokinetic modeling of neoclassical and turbulent impurity transport
Estève, D.; Sarazin, Y.; Garbet, X.; Grandgirard, V.; Breton, S.; Donnel, P.; Asahi, Y.; Bourdelle, C.; Dif-Pradalier, G.; Ehrlacher, C.; Emeriau, C.; Ghendrih, Ph.; Gillot, C.; Latu, G.; Passeron, C.
2018-03-01
Trace impurity transport is studied with the flux-driven gyrokinetic GYSELA code (Grandgirard et al 2016 Comput. Phys. Commun. 207 35). A reduced and linearized multi-species collision operator has been recently implemented, so that both neoclassical and turbulent transport channels can be treated self-consistently on an equal footing. In the Pfirsch-Schlüter regime that is probably relevant for tungsten, the standard expression for the neoclassical impurity flux is shown to be recovered from gyrokinetics with the employed collision operator. Purely neoclassical simulations of deuterium plasma with trace impurities of helium, carbon and tungsten lead to impurity diffusion coefficients, inward pinch velocities due to density peaking, and thermo-diffusion terms which quantitatively agree with neoclassical predictions and NEO simulations (Belli et al 2012 Plasma Phys. Control. Fusion 54 015015). The thermal screening factor appears to be less than predicted analytically in the Pfirsch-Schlüter regime, which can be detrimental to fusion performance. Finally, self-consistent nonlinear simulations have revealed that the tungsten impurity flux is not the sum of turbulent and neoclassical fluxes computed separately, as is usually assumed. The synergy partly results from the turbulence-driven in-out poloidal asymmetry of tungsten density. This result suggests the need for self-consistent simulations of impurity transport, i.e. including both turbulence and neoclassical physics, in view of quantitative predictions for ITER.
Gyrokinetic simulation of internal kink modes
International Nuclear Information System (INIS)
Naitou, Hiroshi; Tsuda, Kenji; Lee, W.W.; Sydora, R.D.
1995-05-01
Internal disruption in a tokamak has been simulated using a three-dimensional magneto-inductive gyrokinetic particle code. The code operates in both the standard gyrokinetic mode (total-f code) and the fully nonlinear characteristic mode (δf code). The latter, a recent addition, is a quiet low noise algorithm. The computational model represents a straight tokamak with periodic boundary conditions in the toroidal direction. The plasma is initially uniformly distributed in a square cross section with perfectly conducting walls. The linear mode structure of an unstable m = 1 (poloidal) and n = 1 (toroidal) kinetic internal kink mode is clearly observed, especially in the δf code. The width of the current layer around the x-point, where magnetic reconnection occurs, is found to be close to the collisionless electron skin depth. This is consistent with the theory in which electron inertia has a dominant role. The nonlinear behavior of the mode is found to be quite similar for both codes. Full reconnection in the Alfven time scale is observed along with the electrostatic potential structures created during the full reconnection phase. The E x B drift due to this electrostatic potential dominates the nonlinear phase of the development after the full reconnection
Pullback Transformations in Gyrokinetic Theory
International Nuclear Information System (INIS)
Qin, H.; Tang, W.M.
2003-01-01
The Pullback transformation of the distribution function is a key component of the gyrokinetic theory. In this paper, a systematic treatment of this subject is presented, and results from applications of the uniform framework developed are reviewed. The focus is on providing a clear exposition of the basic formalism which arises from the existence of three distinct coordinate systems in gyrokinetic theory. The familiar gyrocenter coordinate system, where the gyromotion is decoupled from the rest of particle's dynamics, is non-canonical and non-fabric. On the other hand, Maxwell's equations, which are needed to complete a kinetic system, are initially only defined in the fabric laboratory phase space coordinate system. The pullback transformations provide a rigorous connection between the distribution functions in gyrocenter coordinates and Maxwell's equations in laboratory phase space coordinates. This involves the generalization of the usual moment integrals originally defined on the cotangent fiber of the phase space to the moment integrals on a general 6D symplectic manifold, is shown to be an important step in the proper formulation of gyrokinetic theory. The resultant systematic treatment of the moment integrals enabled by the pullback transformation. Without this vital element, a number of prominent physics features, such as the presence of the compressional Alfven wave and a proper description of the gyrokinetic equilibrium, cannot be readily recovered
Linear regression crash prediction models : issues and proposed solutions.
2010-05-01
The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...
Global gyrokinetic simulations of TEM microturbulence
Vernay, T.; Brunner, S.; Villard, L.; McMillan, B. F.; Jolliet, S.; Bottino, A.; Görler, T.; Jenko, F.
2013-07-01
Global gyrokinetic simulations of electrostatic temperature-gradient-driven trapped-electron-mode (TEM) turbulence using the δf particle-in-cell code ORB5 are presented. The electron response is either fully kinetic or hybrid, i.e. considering kinetic trapped and adiabatic passing electrons. A linear benchmark in the TEM regime against the Eulerian-based code GENE is presented. Two different methods for controlling the numerical noise, based, respectively, on a Krook operator and a so-called coarse-graining approach, are discussed and successfully compared. Both linear and non-linear studies are carried out for addressing the issue of finite-ρ*-effects and finite electron collisionality on TEM turbulence. Electron collisions are found to damp TEMs through the detrapping process, while finite-ρ*-effects turn out to be important in the non-linear regime but very small in the linear regime. Finally, the effects of zonal flows on TEM turbulence are briefly considered as well and shown to be unimportant in the temperature-gradient-driven TEM regime. Consistently, basically no difference is found between linear and non-linear critical electron temperature gradients in the TEM regime.
Testing Gyrokinetics on C-Mod and NSTX
International Nuclear Information System (INIS)
Redi, M.H.; Dorland, W.; Fiore, C.L.; Stutman, D.; Baumgaertel, J.A.; Davis, B.; Kaye, S.M.; McCune, D.C.; Menard, J.; Rewoldt, G.
2005-01-01
Quantitative benchmarks of computational physics codes against experiment are essential for the credible application of such codes. Fluctuation measurements can provide necessary critical tests of nonlinear gyrokinetic simulations, but such require extraordinary computational resources. Linear micro-stability calculations with the GS2 [1] gyrokinetic code have been carried out for tokamak and ST experiments which exhibit internal transport barriers (ITB) and good plasma confinement. Qualitative correlation is found for improved confinement before and during ITB plasmas on Alcator C-Mod [2] and NSTX [3], with weaker long wavelength micro-instabilities in the plasma core regions. Mixing length transport models are discussed. The NSTX L-mode is found to be near marginal stability for kinetic ballooning modes. Fully electromagnetic, linear, gyrokinetic calculations of the Alcator C-Mod ITB during off-axis rf heating, following four plasma species and including the complete electron response show ITG/TEM microturbulence is suppressed in the plasma core and in the barrier region before barrier formation, without recourse to the usual requirements of velocity shear or reversed magnetic shear [4-5]. No strongly growing long or short wavelength drift modes are found in the plasma core but strong ITG/TEM and ETG drift wave turbulence is found outside the barrier region. Linear microstability analysis is qualitatively consistent with the experimental transport analysis, showing low transport inside and high transport outside the ITB region before barrier formation, without consideration of ExB shear stabilization
Verification of gyrokinetic microstability codes with an LHD configuration
Energy Technology Data Exchange (ETDEWEB)
Mikkelsen, D. R. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Nunami, M. [National Inst. for Fusion Science (Japan); Watanabe, T. -H. [Nagoya Univ. (Japan); Sugama, H. [National Inst. for Fusion Science (Japan); Tanaka, K. [National Inst. for Fusion Science (Japan)
2014-11-01
We extend previous benchmarks of the GS2 and GKV-X codes to verify their algorithms for solving the gyrokinetic Vlasov-Poisson equations for plasma microturbulence. Code benchmarks are the most complete way of verifying the correctness of implementations for the solution of mathematical models for complex physical processes such as those studied here. The linear stability calculations reported here are based on the plasma conditions of an ion-ITB plasma in the LHD configuration. The plasma parameters and the magnetic geometry differ from previous benchmarks involving these codes. We find excellent agreement between the independently written pre-processors that calculate the geometrical coefficients used in the gyrokinetic equations. Grid convergence tests are used to establish the resolution and domain size needed to obtain converged linear stability results. The agreement of the frequencies, growth rates and eigenfunctions in the benchmarks reported here provides additional verification that the algorithms used by the GS2 and GKV-X codes are correctly finding the linear eigenvalues and eigenfunctions of the gyrokinetic Vlasov-Poisson equations.
Momentum transport in gyrokinetic turbulence
Energy Technology Data Exchange (ETDEWEB)
Buchholz, Rico
2016-07-01
In this thesis, the gyrokinetic-Vlasov code GKW is used to study turbulent transport, with a focus on radial transport of toroidal momentum. To support the studies on turbulent transport an eigenvalue solver has been implemented into GKW. This allows to find, not only the most unstable mode, but also subdominant modes. Furthermore it is possible to follow the modes in parameter scans. Furthermore, two fundamental mechanisms that can generate an intrinsic rotation have been investigated: profile shearing and the velocity nonlinearity. The study of toroidal momentum transport in a tokamak due to profile shearing reveals that the momentum flux can not be accurately described by the gradient in the turbulent intensity. Consequently, a description using the profile variation is used. A linear model has been developed that is able to reproduce the variations in the momentum flux as the profiles of density and temperature vary, reasonably well. It uses, not only the gradient length of density and temperature profile, but also their derivative, i.e. the second derivative of the logarithm of the temperature and the density profile. It is shown that both first as well as second derivatives contribute to the generation of a momentum flux. A difference between the linear and nonlinear simulations has been found with respect to the behaviour of the momentum flux. In linear simulations the momentum flux is independent of the normalized Larmor radius ρ{sub *}, whereas it is linear in ρ{sub *} for nonlinear simulations, provided ρ{sub *} is small enough (≤4.10{sup -3}). Nonlinear simulations reveal that the profile shearing can generate an intrinsic rotation comparable to that of current experiments. Under reactor conditions, however, the intrinsic rotation from the profile shearing is expected to be small due to the small normalized Larmor radius ρ{sub *}
A generalized gyrokinetic Poisson solver
International Nuclear Information System (INIS)
Lin, Z.; Lee, W.W.
1995-03-01
A generalized gyrokinetic Poisson solver has been developed, which employs local operations in the configuration space to compute the polarization density response. The new technique is based on the actual physical process of gyrophase-averaging. It is useful for nonlocal simulations using general geometry equilibrium. Since it utilizes local operations rather than the global ones such as FFT, the new method is most amenable to massively parallel algorithms
Controlling fluctuations in an ITB and comparison with gyrokinetic simulations
Ernst, D. R.; Fiore, C. L.; Dominguez, A.; Podpaly, Y.; Reinke, M. L.; Terry, J. L.; Tsujii, N.; Bespamyatnov, I.; Churchill, M.; Greenwald, M.; Hubbard, A.; Hughes, J. W.; Lee, J.; Ma, Y.; Wolfe, S.; Wukitch, S.
2011-10-01
We have modulated on-axis ICRF minority heating to trigger fluctuations and core electron transport in Alcator C-Mod Internal Transport Barriers (ITB's). Temperature swings of 50% produced strong bursts of density fluctuations, measured by phase contrast imaging (PCI), while edge fluctuations from reflectometry, Mirnov coils, and gas puff imaging (GPI) simultaneously diminished. The PCI fluctuations are in phase with sawteeth, further evidence that they originate within the ITB foot. Linear gyrokinetic analysis with GS2 shows TEMs are driven unstable in the ITB by the on-axis heating, as in Refs.,. Nonlinear gyrokinetic simulations of turbulence in the ITB are compared with fluctuation data using a synthetic diagnostic. Strong ITB's were produced with high quality ion and electron profile data. Supported by U.S. DoE awards DE-FC02-99ER54512, DE-FG02-91ER54109, DE-FC02-08ER54966.
Deformation Prediction Using Linear Polynomial Functions ...
African Journals Online (AJOL)
By Deformation, we mean change of shape of any structure from its original shape and by monitoring over time using Geodetic means, the change in shape, size and the overall structural dynamics behaviors of structure can be detected. Prediction is therefor based on the epochs measurement obtained during monitoring, ...
Gyrokinetic modelling of the quasilinear particle flux for plasmas with neutral-beam fuelling
Narita, E.; Honda, M.; Nakata, M.; Yoshida, M.; Takenaga, H.; Hayashi, N.
2018-02-01
A quasilinear particle flux is modelled based on gyrokinetic calculations. The particle flux is estimated by determining factors, namely, coefficients of off-diagonal terms and a particle diffusivity. In this paper, the methodology to estimate the factors is presented using a subset of JT-60U plasmas. First, the coefficients of off-diagonal terms are estimated by linear gyrokinetic calculations. Next, to obtain the particle diffusivity, a semi-empirical approach is taken. Most experimental analyses for particle transport have assumed that turbulent particle fluxes are zero in the core region. On the other hand, even in the stationary state, the plasmas in question have a finite turbulent particle flux due to neutral-beam fuelling. By combining estimates of the experimental turbulent particle flux and the coefficients of off-diagonal terms calculated earlier, the particle diffusivity is obtained. The particle diffusivity should reflect a saturation amplitude of instabilities. The particle diffusivity is investigated in terms of the effects of the linear instability and linear zonal flow response, and it is found that a formula including these effects roughly reproduces the particle diffusivity. The developed framework for prediction of the particle flux is flexible to add terms neglected in the current model. The methodology to estimate the quasilinear particle flux requires so low computational cost that a database consisting of the resultant coefficients of off-diagonal terms and particle diffusivity can be constructed to train a neural network. The development of the methodology is the first step towards a neural-network-based particle transport model for fast prediction of the particle flux.
Model Predictive Control for Linear Complementarity and Extended Linear Complementarity Systems
Directory of Open Access Journals (Sweden)
Bambang Riyanto
2005-11-01
Full Text Available In this paper, we propose model predictive control method for linear complementarity and extended linear complementarity systems by formulating optimization along prediction horizon as mixed integer quadratic program. Such systems contain interaction between continuous dynamics and discrete event systems, and therefore, can be categorized as hybrid systems. As linear complementarity and extended linear complementarity systems finds applications in different research areas, such as impact mechanical systems, traffic control and process control, this work will contribute to the development of control design method for those areas as well, as shown by three given examples.
Large-scale linear programs in planning and prediction.
2017-06-01
Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...
International Nuclear Information System (INIS)
Liu, Dongjian; Zhang, Wenlu; McClenaghan, Joseph; Wang, Jiaqi; Lin, Zhihong
2014-01-01
Global gyrokinetic particle simulation of resistive tearing modes has been developed and verified in the gyrokinetic toroidal code (GTC). GTC linear simulations in the fluid limit of the kink-tearing and resistive tearing modes in the cylindrical geometry agree well with the resistive magnetohydrodynamic eigenvalue and initial value codes. Ion kinetic effects are found to reduce the radial width of the tearing modes. GTC simulations of the resistive tearing modes in the toroidal geometry find that the toroidicity reduces the growth rates
Non-Maxwellian fast particle effects in gyrokinetic GENE simulations
Di Siena, A.; Görler, T.; Doerk, H.; Bilato, R.; Citrin, J.; Johnson, T.; Schneider, M.; Poli, E.; JET Contributors
2018-04-01
Fast ions have recently been found to significantly impact and partially suppress plasma turbulence both in experimental and numerical studies in a number of scenarios. Understanding the underlying physics and identifying the range of their beneficial effect is an essential task for future fusion reactors, where highly energetic ions are generated through fusion reactions and external heating schemes. However, in many of the gyrokinetic codes fast ions are, for simplicity, treated as equivalent-Maxwellian-distributed particle species, although it is well known that to rigorously model highly non-thermalised particles, a non-Maxwellian background distribution function is needed. To study the impact of this assumption, the gyrokinetic code GENE has recently been extended to support arbitrary background distribution functions which might be either analytical, e.g., slowing down and bi-Maxwellian, or obtained from numerical fast ion models. A particular JET plasma with strong fast-ion related turbulence suppression is revised with these new code capabilities both with linear and nonlinear gyrokinetic simulations. It appears that the fast ion stabilization tends to be less strong but still substantial with more realistic distributions, and this improves the quantitative power balance agreement with experiments.
Who Will Win?: Predicting the Presidential Election Using Linear Regression
Lamb, John H.
2007-01-01
This article outlines a linear regression activity that engages learners, uses technology, and fosters cooperation. Students generated least-squares linear regression equations using TI-83 Plus[TM] graphing calculators, Microsoft[C] Excel, and paper-and-pencil calculations using derived normal equations to predict the 2004 presidential election.…
Predicting birth weight with conditionally linear transformation models.
Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten
2016-12-01
Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.
Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A
2017-02-01
This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r = 0.71-0.88, RMSE: 1.11-1.61 METs; p > 0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r = 0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r = 0.88, RMSE: 1.10-1.11 METs; p > 0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r = 0.88, RMSE: 1.12 METs. Linear models-correlations: r = 0.86, RMSE: 1.18-1.19 METs; p linear models for the wrist-worn accelerometers (ANN-correlations: r = 0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r = 0.71-0.73, RMSE: 1.55-1.61 METs; p models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh
Energy Technology Data Exchange (ETDEWEB)
T.S. Hahm; Z. Lin; P.H. Diamond; G. Rewoldt; W.X. Wang; S. Ethier; O. Gurcan; W.W. Lee; W.M. Tang
2004-12-21
An integrated program of gyrokinetic particle simulation and theory has been developed to investigate several outstanding issues in both turbulence and neoclassical physics. Gyrokinetic particle simulations of toroidal ion temperature gradient (ITG) turbulence spreading using the GTC code and its related dynamical model have been extended to the case with radially increasing ion temperature gradient, to study the inward spreading of edge turbulence toward the core. Due to turbulence spreading from the edge, the turbulence intensity in the core region is significantly enhanced over the value obtained from simulations of the core region only. Even when the core gradient is within the Dimits shift regime (i.e., self-generated zonal flows reduce the transport to a negligible value), a significant level of turbulence and transport is observed in the core due to spreading from the edge. The scaling of the turbulent front propagation speed is closer to the prediction from our nonlinear diffusion model than one based on linear toroidal coupling. A calculation of ion poloidal rotation in the presence of sharp density and toroidal angular rotation frequency gradients from the GTC-Neo particle simulation code shows that the results are significantly different from the conventional neoclassical theory predictions. An energy conserving set of a fully electromagnetic nonlinear gyrokinetic Vlasov equation and Maxwell's equations, which is applicable to edge turbulence, is being derived via the phase-space action variational Lie perturbation method. Our generalized ordering takes the ion poloidal gyroradius to be on the order of the radial electric field gradient length.
International Nuclear Information System (INIS)
Hahm, T.S.; Lin, Z.; Diamond, P.H.; Gurcan, O.; Rewoldt, G.; Wang, W.X.; Ethier, S.; Lee, W.W.; Lewandowski, J.L.V.; Tang, W.M.
2005-01-01
An integrated program of gyrokinetic particle simulation and theory has been developed to investigate several outstanding issues in both turbulence and neoclassical physics. Gyrokinetic particle simulations of toroidal ion temperature gradient (ITG) turbulence spreading using the GTC code and its related dynamical model have been extended to the case with radially increasing ion temperature gradient, to study the inward spreading of edge turbulence toward the core. Due to turbulence spreading from the edge, the turbulence intensity in the core region is significantly enhanced over the value obtained from simulations of the core region only. Even when the core gradient is within the Dimits shift regime (i.e., self-generated zonal flows reduce the transport to a negligible value), a significant level of turbulence and transport is observed in the core due to spreading from the edge. The scaling of the turbulent front propagation speed is closer to the prediction from our nonlinear diffusion model than one based on linear toroidal coupling. A calculation of ion poloidal rotation in the presence of sharp density and toroidal angular rotation frequency gradients from the GTC-Neo particle simulation code shows that the results are significantly different from the conventional neoclassical theory predictions. An energy conserving set of a fully electromagnetic nonlinear gyrokinetic Vlasov equation and Maxwell's equations, which is applicable to edge turbulence, is being derived via the phase-space action variational Lie perturbation method. Our generalized ordering takes the ion poloidal gyroradius to be on the order of the radial electric field gradient length. (author)
Implementation of neural network based non-linear predictive
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....
An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control
DEFF Research Database (Denmark)
Henriksen, Lars Christian; Poulsen, Niels Kjølstad
This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making...
Burby, Joshua; Brizard, Alain
2017-10-01
Test-particle gyrocenter equations of motion play an essential role in the diagnosis of turbulent strongly-magnetized plasmas, and are playing an increasingly-important role in the formulation of kinetic-gyrokinetic hybrid models. Previous gyrocenter models required the knowledge of the perturbed electromagnetic potentials, which are not directly observable quantities (since they are gauge-dependent). A new gauge-free formulation of gyrocenter motion is presented, which enables gyrocenter trajectories to be determined using only measured values of the directly-observable electromagnetic field. Our gauge-free gyrokinetic theory is general enough to allow for gyroradius-scale fluctuations in both the electric and magnetic field. In addition, we provide gauge-free expressions for the charge and current densities produced by a distribution of gyrocenters, which explicitly include guiding-center and gyrocenter polarization and magnetization effects. This research was supported by the U.S. DOE Contract Nos. DE-SC0014032 (AB) and DE-AC05-06OR23100 (JB).
Limitations, insights and improvements to gyrokinetics
International Nuclear Information System (INIS)
Catto, Peter J.; Parra, Felix I.; Kagan, Grigory; Simakov, Andrei N.
2009-01-01
We first consider gyrokinetic quasineutrality limitations when evaluating the axisymmetric radial electric field in a non-turbulent tokamak by an improved examination of intrinsic ambipolarity. We next prove that the background ions in a pedestal of poloidal ion gyroradius scale must be Maxwellian and nearly isothermal in Pfirsch-Schlueter and banana regime tokamak plasmas, and then consider zonal flow behaviour in a pedestal. Finally, we focus on a simplifying procedure for our transport time scale hybrid gyrokinetic-fluid treatment that removes the limitations of gyrokinetic quasineutrality and remains valid in the pedestal.
Considering fluctuation energy as a measure of gyrokinetic turbulence
International Nuclear Information System (INIS)
Plunk, G G; Tatsuno, T; Dorland, W
2012-01-01
In gyrokinetic theory, there are two quadratic measures of fluctuation energy, left invariant under nonlinear interactions, that constrain turbulence. In a recent work (Plunk and Tatsuno 2011 Phys. Rev. Lett. 106 165003) we reported on the novel consequences that this constraint has for the direction and locality of spectral energy transfer. This paper builds on that previous work. We provide a detailed analysis in support of the results of Plunk and Tatsuno (2011 Phys. Rev. Lett. 106 165003), but significantly broaden the scope and use additional methods to address the problem of energy transfer. The perspective taken here is that the fluctuation energies are not merely formal invariants of an idealized model (two-dimensional gyrokinetics (Plunk et al 2010 J. Fluid Mech. 664 407–35)) but also general measures of gyrokinetic turbulence, i.e. quantities that can be used to predict the behavior of turbulence. Although many questions remain open, this paper collects evidence in favor of this perspective by demonstrating in several contexts that constrained spectral energy transfer governs the dynamics. (paper)
Parker, Jeffrey B.; LoDestro, Lynda L.; Told, Daniel; Merlo, Gabriele; Ricketson, Lee F.; Campos, Alejandro; Jenko, Frank; Hittinger, Jeffrey A. F.
2018-05-01
The vast separation dividing the characteristic times of energy confinement and turbulence in the core of toroidal plasmas makes first-principles prediction on long timescales extremely challenging. Here we report the demonstration of a multiple-timescale method that enables coupling global gyrokinetic simulations with a transport solver to calculate the evolution of the self-consistent temperature profile. This method, which exhibits resiliency to the intrinsic fluctuations arising in turbulence simulations, holds potential for integrating nonlocal gyrokinetic turbulence simulations into predictive, whole-device models.
Equilibrium fluctuation energy of gyrokinetic plasma
International Nuclear Information System (INIS)
Krommes, J.A.; Lee, W.W.; Oberman, C.
1985-11-01
The thermal equilibrium electric field fluctuation energy of the gyrokinetic model of magnetized plasma is computed, and found to be smaller than the well-known result (k)/8π = 1/2T/[1 + (klambda/sub D/) 2 ] valid for arbitrarily magnetized plasmas. It is shown that, in a certain sense, the equilibrium electric field energy is minimum in the gyrokinetic regime. 13 refs., 2 figs
Neoclassical equilibrium in gyrokinetic simulations
International Nuclear Information System (INIS)
Garbet, X.; Dif-Pradalier, G.; Nguyen, C.; Sarazin, Y.; Grandgirard, V.; Ghendrih, Ph.
2009-01-01
This paper presents a set of model collision operators, which reproduce the neoclassical equilibrium and comply with the constraints of a full-f global gyrokinetic code. The assessment of these operators is based on an entropy variational principle, which allows one to perform a fast calculation of the neoclassical diffusivity and poloidal velocity. It is shown that the force balance equation is recovered at lowest order in the expansion parameter, the normalized gyroradius, hence allowing one to calculate correctly the radial electric field. Also, the conventional neoclassical transport and the poloidal velocity are reproduced in the plateau and banana regimes. The advantages and drawbacks of the various model operators are discussed in view of the requirements for neoclassical and turbulent transport.
Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.
de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo
2018-03-01
Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.
Fluid and gyrokinetic simulations of impurity transport at JET
DEFF Research Database (Denmark)
Nordman, H; Skyman, A; Strand, P
2011-01-01
Impurity transport coefficients due to ion-temperature-gradient (ITG) mode and trapped-electron mode turbulence are calculated using profile data from dedicated impurity injection experiments at JET. Results obtained with a multi-fluid model are compared with quasi-linear and nonlinear gyrokinetic...... simulation results obtained with the code GENE. The sign of the impurity convective velocity (pinch) and its various contributions are discussed. The dependence of the impurity transport coefficients and impurity peaking factor −∇nZ/nZ on plasma parameters such as impurity charge number Z, ion logarithmic...
EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.
Lian, Yao; Ge, Meng; Pan, Xian-Ming
2014-12-19
B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .
Validation of Individual Non-Linear Predictive Pharmacokinetic ...
African Journals Online (AJOL)
3Department of Veterinary Medicine, Faculty of Agriculture, University of Novi Sad, Novi Sad, Republic of Serbia ... Purpose: To evaluate the predictive performance of phenytoin multiple dosing non-linear pharmacokinetic ... status epilepticus affects an estimated 152,000 ..... causal factors, i.e., infection, inflammation, tissue.
Neural Generalized Predictive Control of a non-linear Process
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability qu...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem.......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...
Implementation of neural network based non-linear predictive control
DEFF Research Database (Denmark)
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1999-01-01
This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....
GYSELA, a full-f global gyrokinetic Semi-Lagrangian code for ITG turbulence simulations
International Nuclear Information System (INIS)
Grandgirard, V.; Sarazin, Y.; Garbet, X.; Dif-Pradalier, G.; Ghendrih, Ph.; Crouseilles, N.; Latu, G.; Sonnendruecker, E.; Besse, N.; Bertrand, P.
2006-01-01
This work addresses non-linear global gyrokinetic simulations of ion temperature gradient (ITG) driven turbulence with the GYSELA code. The particularity of GYSELA code is to use a fixed grid with a Semi-Lagrangian (SL) scheme and this for the entire distribution function. The 4D non-linear drift-kinetic version of the code already showns the interest of such a SL method which exhibits good properties of energy conservation in non-linear regime as well as an accurate description of fine spatial scales. The code has been upgrated to run 5D simulations of toroidal ITG turbulence. Linear benchmarks and non-linear first results prove that semi-lagrangian codes can be a credible alternative for gyrokinetic simulations
A hybrid gyrokinetic ion and isothermal electron fluid code for astrophysical plasma
Kawazura, Y.; Barnes, M.
2018-05-01
This paper describes a new code for simulating astrophysical plasmas that solves a hybrid model composed of gyrokinetic ions (GKI) and an isothermal electron fluid (ITEF) Schekochihin et al. (2009) [9]. This model captures ion kinetic effects that are important near the ion gyro-radius scale while electron kinetic effects are ordered out by an electron-ion mass ratio expansion. The code is developed by incorporating the ITEF approximation into AstroGK, an Eulerian δf gyrokinetics code specialized to a slab geometry Numata et al. (2010) [41]. The new code treats the linear terms in the ITEF equations implicitly while the nonlinear terms are treated explicitly. We show linear and nonlinear benchmark tests to prove the validity and applicability of the simulation code. Since the fast electron timescale is eliminated by the mass ratio expansion, the Courant-Friedrichs-Lewy condition is much less restrictive than in full gyrokinetic codes; the present hybrid code runs ∼ 2√{mi /me } ∼ 100 times faster than AstroGK with a single ion species and kinetic electrons where mi /me is the ion-electron mass ratio. The improvement of the computational time makes it feasible to execute ion scale gyrokinetic simulations with a high velocity space resolution and to run multiple simulations to determine the dependence of turbulent dynamics on parameters such as electron-ion temperature ratio and plasma beta.
Gyrokinetic Magnetohydrodynamics and the Associated Equilibrium
Lee, W. W.; Hudson, S. R.; Ma, C. H.
2017-10-01
A proposed scheme for the calculations of gyrokinetic MHD and its associated equilibrium is discussed related a recent paper on the subject. The scheme is based on the time-dependent gyrokinetic vorticity equation and parallel Ohm's law, as well as the associated gyrokinetic Ampere's law. This set of equations, in terms of the electrostatic potential, ϕ, and the vector potential, ϕ , supports both spatially varying perpendicular and parallel pressure gradients and their associated currents. The MHD equilibrium can be reached when ϕ -> 0 and A becomes constant in time, which, in turn, gives ∇ . (J|| +J⊥) = 0 and the associated magnetic islands. Examples in simple cylindrical geometry will be given. The present work is partially supported by US DoE Grant DE-AC02-09CH11466.
Electromagnetic nonlinear gyrokinetics with polarization drift
International Nuclear Information System (INIS)
Duthoit, F.-X.; Hahm, T. S.; Wang, Lu
2014-01-01
A set of new nonlinear electromagnetic gyrokinetic Vlasov equation with polarization drift and gyrokinetic Maxwell equations is systematically derived by using the Lie-transform perturbation method in toroidal geometry. For the first time, we recover the drift-kinetic expression for parallel acceleration [R. M. Kulsrud, in Basic Plasma Physics, edited by A. A. Galeev and R. N. Sudan (North-Holland, Amsterdam, 1983)] from the nonlinear gyrokinetic equations, thereby bridging a gap between the two formulations. This formalism should be useful in addressing nonlinear ion Compton scattering of intermediate-mode-number toroidal Alfvén eigenmodes for which the polarization current nonlinearity [T. S. Hahm and L. Chen, Phys. Rev. Lett. 74, 266 (1995)] and the usual finite Larmor radius effects should compete
Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech
劉, 麗清
2015-01-01
Linear prediction (LP) analysis has been applied to speech system over the last few decades. LP technique is well-suited for speech analysis due to its ability to model speech production process approximately. Hence LP analysis has been widely used for speech enhancement, low-bit-rate speech coding in cellular telephony, speech recognition, characteristic parameter extraction (vocal tract resonances frequencies, fundamental frequency called pitch) and so on. However, the performance of the co...
Gyrokinetic energy conservation and Poisson-bracket formulation
International Nuclear Information System (INIS)
Brizard, A.
1989-01-01
An integral expression for the gyrokinetic total energy of a magnetized plasma, with general magnetic field configuration perturbed by fully electromagnetic fields, was recently derived through the use of a gyrocenter Lie transformation. It is shown that the gyrokinetic energy is conserved by the gyrokinetic Hamiltonian flow to all orders in perturbed fields. An explicit demonstration that a gyrokinetic Hamiltonian containing quadratic nonlinearities preserves the gyrokinetic energy up to third order is given. The Poisson-bracket formulation greatly facilitates this demonstration with the help of the Jacobi identity and other properties of the Poisson brackets
Linear and nonlinear dynamic systems in financial time series prediction
Directory of Open Access Journals (Sweden)
Salim Lahmiri
2012-10-01
Full Text Available Autoregressive moving average (ARMA process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX are compared by evaluating their ability to predict financial time series; for instance the S&P500 returns. Two classes of ARMA are considered. The first one is the standard ARMA model which is a linear static system. The second one uses Kalman filter (KF to estimate and predict ARMA coefficients. This model is a linear dynamic system. The forecasting ability of each system is evaluated by means of mean absolute error (MAE and mean absolute deviation (MAD statistics. Simulation results indicate that the ARMA-KF system performs better than the standard ARMA alone. Thus, introducing dynamics into the ARMA process improves the forecasting accuracy. In addition, the ARMA-KF outperformed the NARX. This result may suggest that the linear component found in the S&P500 return series is more dominant than the nonlinear part. In sum, we conclude that introducing dynamics into the ARMA process provides an effective system for S&P500 time series prediction.
Global gyrokinetic simulation of tokamak transport
International Nuclear Information System (INIS)
Furnish, G.; Horton, W.; Kishimoto, Y.; LeBrun, M.J.; Tajima, T.
1998-10-01
A kinetic simulation code based on the gyrokinetic ion dynamics in global general metric (including a tokamak with circular or noncircular cross-section) has been developed. This gyrokinetic simulation is capable of examining the global and semi-global driftwave structures and their associated transport in a tokamak plasma. The authors investigate the property of the ion temperature gradient (ITG) or η i (η i ≡ ∂ ell nT i /∂ ell n n i ) driven drift waves in a tokamak plasma. The emergent semi-global drift wave modes give rise to thermal transport characterized by the Bohm scaling
Non-linear aeroelastic prediction for aircraft applications
de C. Henshaw, M. J.; Badcock, K. J.; Vio, G. A.; Allen, C. B.; Chamberlain, J.; Kaynes, I.; Dimitriadis, G.; Cooper, J. E.; Woodgate, M. A.; Rampurawala, A. M.; Jones, D.; Fenwick, C.; Gaitonde, A. L.; Taylor, N. V.; Amor, D. S.; Eccles, T. A.; Denley, C. J.
2007-05-01
Current industrial practice for the prediction and analysis of flutter relies heavily on linear methods and this has led to overly conservative design and envelope restrictions for aircraft. Although the methods have served the industry well, it is clear that for a number of reasons the inclusion of non-linearity in the mathematical and computational aeroelastic prediction tools is highly desirable. The increase in available and affordable computational resources, together with major advances in algorithms, mean that non-linear aeroelastic tools are now viable within the aircraft design and qualification environment. The Partnership for Unsteady Methods in Aerodynamics (PUMA) Defence and Aerospace Research Partnership (DARP) was sponsored in 2002 to conduct research into non-linear aeroelastic prediction methods and an academic, industry, and government consortium collaborated to address the following objectives: To develop useable methodologies to model and predict non-linear aeroelastic behaviour of complete aircraft. To evaluate the methodologies on real aircraft problems. To investigate the effect of non-linearities on aeroelastic behaviour and to determine which have the greatest effect on the flutter qualification process. These aims have been very effectively met during the course of the programme and the research outputs include: New methods available to industry for use in the flutter prediction process, together with the appropriate coaching of industry engineers. Interesting results in both linear and non-linear aeroelastics, with comprehensive comparison of methods and approaches for challenging problems. Additional embryonic techniques that, with further research, will further improve aeroelastics capability. This paper describes the methods that have been developed and how they are deployable within the industrial environment. We present a thorough review of the PUMA aeroelastics programme together with a comprehensive review of the relevant research
Direct identification of predator-prey dynamics in gyrokinetic simulations
Energy Technology Data Exchange (ETDEWEB)
Kobayashi, Sumire, E-mail: sumire.kobayashi@lpp.polytechnique.fr; Gürcan, Özgür D [Laboratoire de Physique des Plasmas, CNRS, Paris-Sud, Ecole Polytechnique, UMR7648, F-91128 Palaiseau (France); Diamond, Patrick H. [University of California, San Diego, La Jolla, California 92093-0319 (United States)
2015-09-15
The interaction between spontaneously formed zonal flows and small-scale turbulence in nonlinear gyrokinetic simulations is explored in a shearless closed field line geometry. It is found that when clear limit cycle oscillations prevail, the observed turbulent dynamics can be quantitatively captured by a simple Lotka-Volterra type predator-prey model. Fitting the time traces of full gyrokinetic simulations by such a reduced model allows extraction of the model coefficients. Scanning physical plasma parameters, such as collisionality and density gradient, it was observed that the effective growth rates of turbulence (i.e., the prey) remain roughly constant, in spite of the higher and varying level of primary mode linear growth rates. The effective growth rate that was extracted corresponds roughly to the zonal-flow-modified primary mode growth rate. It was also observed that the effective damping of zonal flows (i.e., the predator) in the parameter range, where clear predator-prey dynamics is observed, (i.e., near marginal stability) agrees with the collisional damping expected in these simulations. This implies that the Kelvin-Helmholtz-like instability may be negligible in this range. The results imply that when the tertiary instability plays a role, the dynamics becomes more complex than a simple Lotka-Volterra predator prey.
Global full-f gyrokinetic simulations of plasma turbulence
Energy Technology Data Exchange (ETDEWEB)
Grandgirard, V [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Sarazin, Y [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Angelino, P [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Bottino, A [Max Plank Institut fr Plasmaphysik, IPP-EURATOM AssociationGarching (Germany); Crouseilles, N [IRMA, Universite Louis Pasteur, 7, rue Rene Descartes, 67084 Strasbourg Cedex (France); Darmet, G [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Dif-Pradalier, G [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Garbet, X [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Ghendrih, Ph [CEA/DSM/DRFC, Association Euratom-CEA, Cadarache, 13108 St Paul-lez-Durance (France); Jolliet, S [CRPP, Association Euratom-Confederation Suisse, EPFL, 1015 Lausanne (Switzerland); Latu, G [LaBRI, 341 Cours Liberation, 33405 Talence Cedex (France); Sonnendruecker, E [IRMA, Universite Louis Pasteur, 7, rue Rene Descartes, 67084 Strasbourg Cedex (France); Villard, L [CRPP, Association Euratom-Confederation Suisse, EPFL, 1015 Lausanne (Switzerland)
2007-12-15
Critical physical issues can be specifically tackled with the global full-f gyrokinetic code GYSELA. Three main results are presented. First, the self-consistent treatment of equilibrium and fluctuations highlights the competition between two compensation mechanisms for the curvature driven vertical charge separation, namely, parallel flow and polarization. The impact of the latter on the turbulent transport is discussed. In the non-linear regime, the benchmark with the Particle-In-Cell code ORB5 looks satisfactory. Second, the transport scaling with {rho}{sub *} is found to depend both on {rho}{sub *} itself and on the distance to the linear threshold. Finally, a statistical steady-state turbulent regime is achieved in a reduced version of GYSELA by prescribing a constant heat source.
Global full-f gyrokinetic simulations of plasma turbulence
International Nuclear Information System (INIS)
Grandgirard, V; Sarazin, Y; Angelino, P; Bottino, A; Crouseilles, N; Darmet, G; Dif-Pradalier, G; Garbet, X; Ghendrih, Ph; Jolliet, S; Latu, G; Sonnendruecker, E; Villard, L
2007-01-01
Critical physical issues can be specifically tackled with the global full-f gyrokinetic code GYSELA. Three main results are presented. First, the self-consistent treatment of equilibrium and fluctuations highlights the competition between two compensation mechanisms for the curvature driven vertical charge separation, namely, parallel flow and polarization. The impact of the latter on the turbulent transport is discussed. In the non-linear regime, the benchmark with the Particle-In-Cell code ORB5 looks satisfactory. Second, the transport scaling with ρ * is found to depend both on ρ * itself and on the distance to the linear threshold. Finally, a statistical steady-state turbulent regime is achieved in a reduced version of GYSELA by prescribing a constant heat source
Technical note: A linear model for predicting δ13 Cprotein.
Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M
2015-08-01
Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2) = 0.86, P analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.
Beyond scale separation in gyrokinetic turbulence
International Nuclear Information System (INIS)
Garbet, X.; Sarazin, Y.; Grandgirard, V.; Dif-Pradalier, G.; Darmet, G.; Ghendrih, Ph.; Angelino, P.; Bertrand, P.; Besse, N.; Gravier, E.; Morel, P.; Sonnendruecker, E.; Crouseilles, N.; Dischler, J.-M.; Latu, G.; Violard, E.; Brunetti, M.; Brunner, S.; Lapillonne, X.; Tran, T.-M.; Villard, L.; Boulet, M.
2007-01-01
This paper presents the results obtained with a set of gyrokinetic codes based on a semi-Lagrangian scheme. Several physics issues are addressed, namely, the comparison between fluid and kinetic descriptions, the intermittent behaviour of flux driven turbulence and the role of large scale flows in toroidal ITG turbulence. The question of the initialization of full-F simulations is also discussed
The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence
Energy Technology Data Exchange (ETDEWEB)
Staebler, G. M.; Candy, J. [General Atomics, San Diego, California 92186 (United States); Howard, N. T. [Oak Ridge Institute for Science Education (ORISE), Oak Ridge, Tennessee 37831 (United States); Holland, C. [University of California San Diego, San Diego, California 92093 (United States)
2016-06-15
The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the threshold for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.
Gyrokinetic simulations of ETG Turbulence*
Nevins, William
2005-10-01
Recent gyrokinetic simulations of electron temperature gradient (ETG) turbulence [1,2] produced different results despite similar plasma parameters. Ref.[1] differs from Ref.[2] in that [1] eliminates magnetically trapped particles ( r/R=0 ), while [2] retains magnetically trapped particles ( r/R 0.18 ). Differences between [1] and [2] have been attributed to insufficient phase-space resolution and novel physics associated with toroidicity and/or global simulations[2]. We have reproduced the results reported in [2] using a flux-tube, particle-in-cell (PIC) code, PG3EQ[3], thereby eliminating global effects as the cause of the discrepancy. We observe late-time decay of ETG turbulence and the steady-state heat transport in agreement with [2], and show this results from discrete particle noise. Discrete particle noise is a numerical artifact, so both the PG3EQ simulations reported here and those reported in Ref.[2] have little to say about steady-state ETG turbulence and the associated anomalous electron heat transport. Our attempts to benchmark PIC and continuum[4] codes at the plasma parameters used in Ref.[2] produced very large, intermittent transport. We will present an alternate benchmark point for ETG turbulence, where several codes reproduce the same transport levels. Parameter scans about this new benchmark point will be used to investigate the parameter dependence of ETG transport and to elucidate saturation mechanisms proposed in Refs.[1,2] and elsewhere[5-7].*In collaboration with A. Dimits (LLNL), J. Candy, C. Estrada-Mila (GA), W. Dorland (U of MD), F. Jenko, T. Dannert (Max-Planck Institut), and G. Hammett (PPPL). Work at LLNL performed for US DOE under Contract W7405-ENG-48.[1] F. Jenko and W. Dorland, PRL 89, 225001 (2002).[2] Z. Lin et al, 2004 Sherwood Mtg.; 2004 TTF Mtg.; Fusion Energy 2004 (IAEA, Vienna, 2005); Bull. Am. Phys. Soc. (November, 2004); 2005 TTF Mtg.; 2005 Sherwood Mtg.; Z. Lin, et al, Phys. Plasmas 12, 056125 (2005). [3] A.M. Dimits
Linear predictions of supercritical flow instability in two parallel channels
International Nuclear Information System (INIS)
Shah, M.
2008-01-01
A steady state linear code that can predict thermo-hydraulic instability boundaries in a two parallel channel system under supercritical conditions has been developed. Linear and non-linear solutions of the instability boundary in a two parallel channel system are also compared. The effect of gravity on the instability boundary in a two parallel channel system, by changing the orientation of the system flow from horizontal flow to vertical up-flow and vertical down-flow has been analyzed. Vertical up-flow is found to be more unstable than horizontal flow and vertical down flow is found to be the most unstable configuration. The type of instability present in each flow-orientation of a parallel channel system has been checked and the density wave oscillation type is observed in horizontal flow and vertical up-flow, while the static type of instability is observed in a vertical down-flow for the cases studied here. The parameters affecting the instability boundary, such as the heating power, inlet temperature, inlet and outlet K-factors are varied to assess their effects. This study is important for the design of future Generation IV nuclear reactors in which supercritical light water is proposed as the primary coolant. (author)
Predicting Madura cattle growth curve using non-linear model
Widyas, N.; Prastowo, S.; Widi, T. S. M.; Baliarti, E.
2018-03-01
Madura cattle is Indonesian native. It is a composite breed that has undergone hundreds of years of selection and domestication to reach nowadays remarkable uniformity. Crossbreeding has reached the isle of Madura and the Madrasin, a cross between Madura cows and Limousine semen emerged. This paper aimed to compare the growth curve between Madrasin and one type of pure Madura cows, the common Madura cattle (Madura) using non-linear models. Madura cattles are kept traditionally thus reliable records are hardly available. Data were collected from small holder farmers in Madura. Cows from different age classes (5years) were observed, and body measurements (chest girth, body length and wither height) were taken. In total 63 Madura and 120 Madrasin records obtained. Linear model was built with cattle sub-populations and age as explanatory variables. Body weights were estimated based on the chest girth. Growth curves were built using logistic regression. Results showed that within the same age, Madrasin has significantly larger body compared to Madura (plogistic models fit better for Madura and Madrasin cattle data; with the estimated MSE for these models were 39.09 and 759.28 with prediction accuracy of 99 and 92% for Madura and Madrasin, respectively. Prediction of growth curve using logistic regression model performed well in both types of Madura cattle. However, attempts to administer accurate data on Madura cattle are necessary to better characterize and study these cattle.
Comparison of Linear Prediction Models for Audio Signals
Directory of Open Access Journals (Sweden)
2009-03-01
Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.
Self-consistent gyrokinetic modeling of neoclassical and turbulent impurity transport
Estève , D. ,; Sarazin , Y.; Garbet , X.; Grandgirard , V.; Breton , S. ,; Donnel , P. ,; Asahi , Y. ,; Bourdelle , C.; Dif-Pradalier , G; Ehrlacher , C.; Emeriau , C.; Ghendrih , Ph; Gillot , C.; Latu , G.; Passeron , C.
2018-01-01
International audience; Trace impurity transport is studied with the flux-driven gyrokinetic GYSELA code [V. Grandgirard et al., Comp. Phys. Commun. 207, 35 (2016)]. A reduced and linearized multi-species collision operator has been recently implemented, so that both neoclassical and turbulent transport channels can be treated self-consistently on an equal footing. In the Pfirsch-Schlüter regime likely relevant for tungsten, the standard expression of the neoclassical impurity flux is shown t...
Gyrokinetic Simulation of Global Turbulent Transport Properties in Tokamak Experiments
Energy Technology Data Exchange (ETDEWEB)
Wang, W.X.; Lin, Z.; Tang, W.M.; Lee, W.W.; Ethier, S.; Lewandowski, J.L.V.; Rewoldt, G.; Hahm, T.S.; Manickam, J.
2006-01-01
A general geometry gyro-kinetic model for particle simulation of plasma turbulence in tokamak experiments is described. It incorporates the comprehensive influence of noncircular cross section, realistic plasma profiles, plasma rotation, neoclassical (equilibrium) electric fields, and Coulomb collisions. An interesting result of global turbulence development in a shaped tokamak plasma is presented with regard to nonlinear turbulence spreading into the linearly stable region. The mutual interaction between turbulence and zonal flows in collisionless plasmas is studied with a focus on identifying possible nonlinear saturation mechanisms for zonal flows. A bursting temporal behavior with a period longer than the geodesic acoustic oscillation period is observed even in a collisionless system. Our simulation results suggest that the zonal flows can drive turbulence. However, this process is too weak to be an effective zonal flow saturation mechanism.
Genomic prediction based on data from three layer lines: a comparison between linear methods
Calus, M.P.L.; Huang, H.; Vereijken, J.; Visscher, J.; Napel, ten J.; Windig, J.J.
2014-01-01
Background The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction. Methods Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we
Transport of momentum in full f gyrokinetics
International Nuclear Information System (INIS)
Parra, Felix I.; Catto, Peter J.
2010-01-01
Full f electrostatic gyrokinetic formulations employ two gyrokinetic equations, one for ions and the other for electrons, and quasineutrality to obtain the ion and electron distribution functions and the electrostatic potential. We demonstrate with several examples that the long wavelength radial electric field obtained with full f approaches is extremely sensitive to errors in the ion and electron density since small deviations in density give rise to large, nonphysical deviations in the conservation of toroidal angular momentum. For typical tokamak values, a relative error of 10 -7 in the ion or electron densities is enough to obtain the incorrect toroidal rotation. Based on the insights gained with the examples considered, three simple tests to check transport of toroidal angular momentum in full f simulations are proposed.
Parallel magnetic field perturbations in gyrokinetic simulations
International Nuclear Information System (INIS)
Joiner, N.; Hirose, A.; Dorland, W.
2010-01-01
At low β it is common to neglect parallel magnetic field perturbations on the basis that they are of order β 2 . This is only true if effects of order β are canceled by a term in the ∇B drift also of order β[H. L. Berk and R. R. Dominguez, J. Plasma Phys. 18, 31 (1977)]. To our knowledge this has not been rigorously tested with modern gyrokinetic codes. In this work we use the gyrokinetic code GS2[Kotschenreuther et al., Comput. Phys. Commun. 88, 128 (1995)] to investigate whether the compressional magnetic field perturbation B || is required for accurate gyrokinetic simulations at low β for microinstabilities commonly found in tokamaks. The kinetic ballooning mode (KBM) demonstrates the principle described by Berk and Dominguez strongly, as does the trapped electron mode, in a less dramatic way. The ion and electron temperature gradient (ETG) driven modes do not typically exhibit this behavior; the effects of B || are found to depend on the pressure gradients. The terms which are seen to cancel at long wavelength in KBM calculations can be cumulative in the ion temperature gradient case and increase with η e . The effect of B || on the ETG instability is shown to depend on the normalized pressure gradient β ' at constant β.
Gyrokinetic statistical absolute equilibrium and turbulence
International Nuclear Information System (INIS)
Zhu Jianzhou; Hammett, Gregory W.
2010-01-01
A paradigm based on the absolute equilibrium of Galerkin-truncated inviscid systems to aid in understanding turbulence [T.-D. Lee, Q. Appl. Math. 10, 69 (1952)] is taken to study gyrokinetic plasma turbulence: a finite set of Fourier modes of the collisionless gyrokinetic equations are kept and the statistical equilibria are calculated; possible implications for plasma turbulence in various situations are discussed. For the case of two spatial and one velocity dimension, in the calculation with discretization also of velocity v with N grid points (where N+1 quantities are conserved, corresponding to an energy invariant and N entropy-related invariants), the negative temperature states, corresponding to the condensation of the generalized energy into the lowest modes, are found. This indicates a generic feature of inverse energy cascade. Comparisons are made with some classical results, such as those of Charney-Hasegawa-Mima in the cold-ion limit. There is a universal shape for statistical equilibrium of gyrokinetics in three spatial and two velocity dimensions with just one conserved quantity. Possible physical relevance to turbulence, such as ITG zonal flows, and to a critical balance hypothesis are also discussed.
Gyrokinetic Statistical Absolute Equilibrium and Turbulence
International Nuclear Information System (INIS)
Zhu, Jian-Zhou; Hammett, Gregory W.
2011-01-01
A paradigm based on the absolute equilibrium of Galerkin-truncated inviscid systems to aid in understanding turbulence (T.-D. Lee, 'On some statistical properties of hydrodynamical and magnetohydrodynamical fields,' Q. Appl. Math. 10, 69 (1952)) is taken to study gyrokinetic plasma turbulence: A finite set of Fourier modes of the collisionless gyrokinetic equations are kept and the statistical equilibria are calculated; possible implications for plasma turbulence in various situations are discussed. For the case of two spatial and one velocity dimension, in the calculation with discretization also of velocity v with N grid points (where N + 1 quantities are conserved, corresponding to an energy invariant and N entropy-related invariants), the negative temperature states, corresponding to the condensation of the generalized energy into the lowest modes, are found. This indicates a generic feature of inverse energy cascade. Comparisons are made with some classical results, such as those of Charney-Hasegawa-Mima in the cold-ion limit. There is a universal shape for statistical equilibrium of gyrokinetics in three spatial and two velocity dimensions with just one conserved quantity. Possible physical relevance to turbulence, such as ITG zonal flows, and to a critical balance hypothesis are also discussed.
Comparisons of 'Identical' Simulations by the Eulerian Gyrokinetic Codes GS2 and GYRO
Bravenec, R. V.; Ross, D. W.; Candy, J.; Dorland, W.; McKee, G. R.
2003-10-01
A major goal of the fusion program is to be able to predict tokamak transport from first-principles theory. To this end, the Eulerian gyrokinetic code GS2 was developed years ago and continues to be improved [1]. Recently, the Eulerian code GYRO was developed [2]. These codes are not subject to the statistical noise inherent to particle-in-cell (PIC) codes, and have been very successful in treating electromagnetic fluctuations. GS2 is fully spectral in the radial coordinate while GYRO uses finite-differences and ``banded" spectral schemes. To gain confidence in nonlinear simulations of experiment with these codes, ``apples-to-apples" comparisons (identical profile inputs, flux-tube geometry, two species, etc.) are first performed. We report on a series of linear and nonlinear comparisons (with overall agreement) including kinetic electrons, collisions, and shaped flux surfaces. We also compare nonlinear simulations of a DIII-D discharge to measurements of not only the fluxes but also the turbulence parameters. [1] F. Jenko, et al., Phys. Plasmas 7, 1904 (2000) and refs. therein. [2] J. Candy, J. Comput. Phys. 186, 545 (2003).
Neoclassical and gyrokinetic analysis of time-dependent helium transport experiments on MAST
International Nuclear Information System (INIS)
Henderson, S.S.; O'Mullane, M.; Summers, H.P.; Garzotti, L.; Casson, F.J.; Dickinson, D.; Fox, M.F.J.; Patel, A.; Roach, C.M.; Valovič, M.
2014-01-01
Time-dependent helium gas puff experiments have been performed on the Mega Ampère Spherical Tokamak (MAST) during a two point plasma current scan in L-mode and a confinement scan at 900 kA. An evaluation of the He II (n = 4 → 3) spectrum line induced by charge exchange suggests anomalous rates of diffusion and inward convection in the outer regions of both L-mode plasmas. Similar rates of diffusion are found in the H-mode plasma, however these rates are consistent with neoclassical predictions. The anomalous inward pinch found in the core of L-mode plasmas is also not apparent in the H-mode core. Linear gyrokinetic simulations of one flux surface in L-mode using the GS2 and GKW codes find that equilibrium flow shear is sufficient to stabilize ITG modes, consistent with beam emission spectroscopy (BES) observations, and suggest that collisionless TEMs may dominate the anomalous helium particle transport. A quasilinear estimate of the dimensionless peaking factor associated with TEMs is in good agreement with experiment. Collisionless TEMs are more stable in H-mode because the electron density gradient is flatter. The steepness of this gradient is therefore pivotal in determining the inward neoclassical particle pinch and the particle flux associated with TEM turbulence. (paper)
Neoclassical and gyrokinetic analysis of time-dependent helium transport experiments on MAST
Henderson, S. S.; Garzotti, L.; Casson, F. J.; Dickinson, D.; Fox, M. F. J.; O'Mullane, M.; Patel, A.; Roach, C. M.; Summers, H. P.; Valovič, M.; The MAST Team
2014-09-01
Time-dependent helium gas puff experiments have been performed on the Mega Ampère Spherical Tokamak (MAST) during a two point plasma current scan in L-mode and a confinement scan at 900 kA. An evaluation of the He II (n = 4 → 3) spectrum line induced by charge exchange suggests anomalous rates of diffusion and inward convection in the outer regions of both L-mode plasmas. Similar rates of diffusion are found in the H-mode plasma, however these rates are consistent with neoclassical predictions. The anomalous inward pinch found in the core of L-mode plasmas is also not apparent in the H-mode core. Linear gyrokinetic simulations of one flux surface in L-mode using the GS2 and GKW codes find that equilibrium flow shear is sufficient to stabilize ITG modes, consistent with beam emission spectroscopy (BES) observations, and suggest that collisionless TEMs may dominate the anomalous helium particle transport. A quasilinear estimate of the dimensionless peaking factor associated with TEMs is in good agreement with experiment. Collisionless TEMs are more stable in H-mode because the electron density gradient is flatter. The steepness of this gradient is therefore pivotal in determining the inward neoclassical particle pinch and the particle flux associated with TEM turbulence.
Frequency prediction by linear stability analysis around mean flow
Bengana, Yacine; Tuckerman, Laurette
2017-11-01
The frequency of certain limit cycles resulting from a Hopf bifurcation, such as the von Karman vortex street, can be predicted by linear stability analysis around their mean flows. Barkley (2006) has shown this to yield an eigenvalue whose real part is zero and whose imaginary part matches the nonlinear frequency. This property was named RZIF by Turton et al. (2015); moreover they found that the traveling waves (TW) of thermosolutal convection have the RZIF property. They explained this as a consequence of the fact that the temporal Fourier spectrum is dominated by the mean flow and first harmonic. We could therefore consider that only the first mode is important in the saturation of the mean flow as presented in the Self-Consistent Model (SCM) of Mantic-Lugo et al. (2014). We have implemented a full Newton's method to solve the SCM for thermosolutal convection. We show that while the RZIF property is satisfied far from the threshold, the SCM model reproduces the exact frequency only very close to the threshold. Thus, the nonlinear interaction of only the first mode with itself is insufficiently accurate to estimate the mean flow. Our next step will be to take into account higher harmonics and to apply this analysis to the standing waves, for which RZIF does not hold.
Flow discharge prediction in compound channels using linear genetic programming
Azamathulla, H. Md.; Zahiri, A.
2012-08-01
SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.
Non-physical momentum sources in slab geometry gyrokinetics
International Nuclear Information System (INIS)
Parra, Felix I; Catto, Peter J
2010-01-01
We investigate momentum transport in the Hamiltonian electrostatic gyrokinetic formulation of Dubin et al (1983 Phys. Fluids 26 3524). We prove that the long wavelength electric field obtained from the gyrokinetic quasineutrality introduces a non-physical momentum source in the low flow ordering.
Nonlinear Gyrokinetic Theory With Polarization Drift
International Nuclear Information System (INIS)
Wang, L.; Hahm, T.S.
2010-01-01
A set of the electrostatic toroidal gyrokinetic Vlasov equation and the Poisson equation, which explicitly includes the polarization drift, is derived systematically by using Lie-transform method. The polarization drift is introduced in the gyrocenter equations of motion, and the corresponding polarization density is derived. Contrary to the wide-spread expectation, the inclusion of the polarization drift in the gyrocenter equations of motion does not affect the expression for the polarization density significantly. This is due to modification of the gyrocenter phase-space volume caused by the electrostatic potential [T. S. Hahm, Phys. Plasmas 3, 4658 (1996)].
Visualizing Gyrokinetic Turbulence in a Tokamak
Stantchev, George
2005-10-01
Multi-dimensional data output from gyrokinetic microturbulence codes are often difficult to visualize, in part due to the non-trivial geometry of the underlying grids, in part due to high irregularity of the relevant scalar field structures in turbulent regions. For instance, traditional isosurface extraction methods are likely to fail for the electrostatic potential field whose level sets may exhibit various geometric pathologies. To address these issues we develop an advanced interactive 3D gyrokinetic turbulence visualization framework which we apply in the study of microtearing instabilities calculated with GS2 in the MAST and NSTX geometries. In these simulations GS2 uses field-line-following coordinates such that the computational domain maps in physical space to a long, twisting flux tube with strong cross-sectional shear. Using statistical wavelet analysis we create a sparse multiple-scale volumetric representation of the relevant scalar fields, which we visualize via a variation of the so called splatting technique. To handle the problem of highly anisotropic flux tube configurations we adapt a geometry-driven surface illumination algorithm that places local light sources for effective feature-enhanced visualization.
Gyrokinetic particle-in-cell simulations of plasma microturbulence on advanced computing platforms
International Nuclear Information System (INIS)
Ethier, S; Tang, W M; Lin, Z
2005-01-01
Since its introduction in the early 1980s, the gyrokinetic particle-in-cell (PIC) method has been very successfully applied to the exploration of many important kinetic stability issues in magnetically confined plasmas. Its self-consistent treatment of charged particles and the associated electromagnetic fluctuations makes this method appropriate for studying enhanced transport driven by plasma turbulence. Advances in algorithms and computer hardware have led to the development of a parallel, global, gyrokinetic code in full toroidal geometry, the gyrokinetic toroidal code (GTC), developed at the Princeton Plasma Physics Laboratory. It has proven to be an invaluable tool to study key effects of low-frequency microturbulence in fusion plasmas. As a high-performance computing applications code, its flexible mixed-model parallel algorithm has allowed GTC to scale to over a thousand processors, which is routinely used for simulations. Improvements are continuously being made. As the US ramps up its support for the International Tokamak Experimental Reactor (ITER), the need for understanding the impact of turbulent transport in burning plasma fusion devices is of utmost importance. Accordingly, the GTC code is at the forefront of the set of numerical tools being used to assess and predict the performance of ITER on critical issues such as the efficiency of energy confinement in reactors
Fast Algorithms for High-Order Sparse Linear Prediction with Applications to Speech Processing
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Giacobello, Daniele; van Waterschoot, Toon
2016-01-01
In speech processing applications, imposing sparsity constraints on high-order linear prediction coefficients and prediction residuals has proven successful in overcoming some of the limitation of conventional linear predictive modeling. However, this modeling scheme, named sparse linear prediction...... problem with lower accuracy than in previous work. In the experimental analysis, we clearly show that a solution with lower accuracy can achieve approximately the same performance as a high accuracy solution both objectively, in terms of prediction gain, as well as with perceptual relevant measures, when...... evaluated in a speech reconstruction application....
The log-linear return approximation, bubbles, and predictability
DEFF Research Database (Denmark)
Engsted, Tom; Pedersen, Thomas Quistgaard; Tanggaard, Carsten
We study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log dividendprice ratio. Next, we simulate various rational bubbles which have explosive conditional expec...
The Log-Linear Return Approximation, Bubbles, and Predictability
DEFF Research Database (Denmark)
Engsted, Tom; Pedersen, Thomas Quistgaard; Tanggaard, Carsten
2012-01-01
We study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log dividend-price ratio. Next, we simulate various rational bubbles which have explosive conditional expe...
Nonlinear gyrokinetic Maxwell-Vlasov equations using magnetic coordinates
International Nuclear Information System (INIS)
Brizard, A.
1988-09-01
A gyrokinetic formalism using magnetic coordinates is used to derive self-consistent, nonlinear Maxwell-Vlasov equations that are suitable for particle simulation studies of finite-β tokamak microturbulence and its associated anomalous transport. The use of magnetic coordinates is an important feature of this work as it introduces the toroidal geometry naturally into our gyrokinetic formalism. The gyrokinetic formalism itself is based on the use of the Action-variational Lie perturbation method of Cary and Littlejohn, and preserves the Hamiltonian structure of the original Maxwell-Vlasov system. Previous nonlinear gyrokinetic sets of equations suitable for particle simulation analysis have considered either electrostatic and shear-Alfven perturbations in slab geometry, or electrostatic perturbations in toroidal geometry. In this present work, fully electromagnetic perturbations in toroidal geometry are considered. 26 refs
Linear-quadratic model predictions for tumor control probability
International Nuclear Information System (INIS)
Yaes, R.J.
1987-01-01
Sigmoid dose-response curves for tumor control are calculated from the linear-quadratic model parameters α and Β, obtained from human epidermoid carcinoma cell lines, and are much steeper than the clinical dose-response curves for head and neck cancers. One possible explanation is the presence of small radiation-resistant clones arising from mutations in an initially homogeneous tumor. Using the mutation theory of Delbruck and Luria and of Goldie and Coldman, the authors discuss the implications of such radiation-resistant clones for clinical radiation therapy
Genomic prediction based on data from three layer lines using non-linear regression models.
Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L
2014-11-06
Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional
Finite element approach to global gyrokinetic particle-in-cell simulations using magnetic coordinate
International Nuclear Information System (INIS)
Fivaz, M.; Brunner, S.; Ridder, G. de; Sauter, O.; Tran, T.M.; Vaclavik, J.; Villard, L.; Appert, K.
1997-08-01
We present a fully-global linear gyrokinetic simulation code (GYGLES) aimed at describing the instable spectrum of the ion-temperature-gradient modes in toroidal geometry. We formulate the Particle-In-Cell method with finite elements defined in magnetic coordinates, which provides excellent numerical convergence properties. The poloidal mode structure corresponding to k // =0 is extracted without approximation from the equations, which reduces drastically the numerical resolution needed. The code can simulate routinely modes with both very long and very short toroidal wavelengths, can treat realistic (MHD) equilibria of any size and runs on a massively parallel computer. (author) 10 figs., 28 refs
Effects of the magnetic equilibrium on gyrokinetic simulations of tokamak microinstabilities
Energy Technology Data Exchange (ETDEWEB)
Wan, Weigang; Chen, Yang; Parker, Scott E. [Department of Physics, University of Colorado, Boulder, Colorado 80309 (United States); Groebner, Richard J. [General Atomics, Post Office Box 85068, San Diego, California 92186 (United States)
2015-06-15
The general geometry of the experimental tokamak magnetic equilibrium is implemented in the global gyrokinetic simulation code GEM. Compared to the general geometry, the well used Miller parameterization of the magnetic equilibrium is a good approximation in the core region and up to the top of the pedestal. Linear simulations indicate that results with the two geometries agree for r/a ≤ 0.9. However, in the edge region, the instabilities are sensitive to the magnetic equilibrium in both the L-mode and the H-mode plasmas. A small variation of the plasma shaping parameters leads to large changes to the edge instability.
Gyrokinetic simulations in general geometry and applications to collisional damping of zonal flows
International Nuclear Information System (INIS)
Lin, Z.; Hahm, T.S.; Lee, W.W.; Tang, W.M.; White, R.B.
2000-01-01
A fully three-dimensional gyrokinetic particle code using magnetic coordinates for general geometry has been developed and applied to the investigation of zonal flows dynamics in toroidal ion-temperature-gradient turbulence. Full torus simulation results support the important conclusion that turbulence-driven zonal flows significantly reduce the turbulent transport. Linear collisionless simulations for damping of an initial poloidal flow perturbation exhibit an asymptotic residual flow. The collisional damping of this residual causes the dependence of ion thermal transport on the ion-ion collision frequency even in regimes where the instabilities are collisionless
Full-f gyrokinetic simulation over a confinement time
Energy Technology Data Exchange (ETDEWEB)
Idomura, Yasuhiro, E-mail: idomura.yasuhiro@jaea.go.jp [Japan Atomic Energy Agency, Kashiwanoha 5-1-5, Kashiwa, Chiba 277-8587 (Japan)
2014-02-15
A long time ion temperature gradient driven turbulence simulation over a confinement time is performed using the full-f gyrokinetic Eulerian code GT5D. The convergence of steady temperature and rotation profiles is examined, and it is shown that the profile relaxation can be significantly accelerated when the simulation is initialized with linearly unstable temperature profiles. In the steady state, the temperature profile and the ion heat diffusivity are self-consistently determined by the power balance condition, while the intrinsic rotation profile is sustained by complicated momentum transport processes without momentum input. The steady turbulent momentum transport is characterized by bursty non-diffusive fluxes, and the resulting turbulent residual stress is consistent with the profile shear stress theory [Y. Camenen et al., “Consequences of profile shearing on toroidal momentum transport,” Nucl. Fusion 51, 073039 (2011)] in which the residual stress depends not only on the profile shear and the radial electric field shear but also on the radial electric field itself. Based on the toroidal angular momentum conservation, it is found that in the steady null momentum transport state, the turbulent residual stress is cancelled by the neoclassical counterpart, which is greatly enhanced in the presence of turbulent fluctuations.
An Efficient Method for Verifying Gyrokinetic Microstability Codes
Bravenec, R.; Candy, J.; Dorland, W.; Holland, C.
2009-11-01
Benchmarks for gyrokinetic microstability codes can be developed through successful ``apples-to-apples'' comparisons among them. Unlike previous efforts, we perform the comparisons for actual discharges, rendering the verification efforts relevant to existing experiments and future devices (ITER). The process requires i) assembling the experimental analyses at multiple times, radii, discharges, and devices, ii) creating the input files ensuring that the input parameters are faithfully translated code-to-code, iii) running the codes, and iv) comparing the results, all in an organized fashion. The purpose of this work is to automate this process as much as possible: At present, a python routine is used to generate and organize GYRO input files from TRANSP or ONETWO analyses. Another routine translates the GYRO input files into GS2 input files. (Translation software for other codes has not yet been written.) Other python codes submit the multiple GYRO and GS2 jobs, organize the results, and collect them into a table suitable for plotting. (These separate python routines could easily be consolidated.) An example of the process -- a linear comparison between GYRO and GS2 for a DIII-D discharge at multiple radii -- will be presented.
Effects of Plasma Shaping on Nonlinear Gyrokinetic Turbulence
Energy Technology Data Exchange (ETDEWEB)
Belli, E. A. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Hammett, G. W. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Dorland, W. [Univ. of Maryland, College Park, MD (United States)
2008-08-01
The effects of flux surface shape on the gyrokinetic stability and transport of tokamak plasmas are studied using the GS2 code [M. Kotschenreuther, G. Rewoldt, and W.M. Tang, Comput. Phys. Commun. 88, 128 (1995); W. Dorland, F. Jenko, M. Kotschenreuther, and B.N. Rogers, Phys. Rev. Lett. 85, 5579 (2000)]. Studies of the scaling of nonlinear turbulence with shaping parameters are performed using analytic equilibria based on interpolations of representative shapes of the Joint European Torus (JET) [P.H. Rebut and B.E. Keen, Fusion Technol. 11, 13 (1987)]. High shaping is found to be a stabilizing influence on both the linear ion-temperature-gradient (ITG) instability and the nonlinear ITG turbulence. For the parameter regime studied here, a scaling of the heat flux with elongation of χ ~ κ^{-1.5} or κ^{-2.0}, depending on the triangularity, is observed at fixed average temperature gradient. While this is not as strong as empirical elongation scalings, it is also found that high shaping results in a larger Dimits upshift of the nonlinear critical temperature gradient due to an enhancement of the Rosenbluth-Hinton residual zonal flows.
Local gyrokinetic study of electrostatic microinstabilities in dipole plasmas
Xie, Hua-sheng; Zhang, Yi; Huang, Zi-cong; Ou, Wei-ke; Li, Bo
2017-12-01
A linear gyrokinetic particle-in-cell scheme, which is valid for an arbitrary perpendicular wavelength k⊥ρi and includes the parallel dynamic along the field line, is developed to study the local electrostatic drift modes in point and ring dipole plasmas. We find that the most unstable mode in this system can be either the electron mode or the ion mode. The properties and relations of these modes are studied in detail as a function of k⊥ρi , the density gradient κn, the temperature gradient κT, electron to ion temperature ratio τ=Te/Ti , and mass ratio mi/me . For conventional weak gradient parameters, the mode is on the ground state (with eigenstate number l = 0) and especially k∥˜0 for small k⊥ρi . Thus, the bounce averaged dispersion relation is also derived for comparison. For strong gradient and large k⊥ρi , most interestingly, higher order eigenstate modes with even (e.g., l = 2, 4) or odd (e.g., l = 1) parity can be most unstable, which is not expected in the previous studies. High order eigenstate can also easily be most unstable at weak gradient when τ>10 . This work can be particularly important to understand the turbulent transport in laboratory and space magnetosphere.
Effects of Plasma Shaping on Nonlinear Gyrokinetic Turbulence
International Nuclear Information System (INIS)
E.A. Belli, G.W. Hammett and W. Dorland
2008-01-01
The effects of flux surface shape on the gyrokinetic stability and transport of tokamak plasmas are studied using the GS2 code [M. Kotschenreuther, G. Rewoldt, and W.M. Tang, Comput. Phys. Commun. 88, 128 (1995); W. Dorland, F. Jenko, M. Kotschenreuther, and B.N. Rogers, Phys. Rev. Lett. 85, 5579 (2000)]. Studies of the scaling of nonlinear turbulence with shaping parameters are performed using analytic equilibria based on interpolations of representative shapes of the Joint European Torus (JET) [P.H. Rebut and B.E. Keen, Fusion Technol. 11, 13 (1987)]. High shaping is found to be a stabilizing influence on both the linear ion-temperature-gradient (ITG) instability and the nonlinear ITG turbulence. For the parameter regime studied here, a scaling of the heat flux with elongation of χ ∼ κ -1.5 or κ -2.0 , depending on the triangularity, is observed at fixed average temperature gradient. While this is not as strong as empirical elongation scalings, it is also found that high shaping results in a larger Dimits upshift of the nonlinear critical temperature gradient due to an enhancement of the Rosenbluth-Hinton residual zonal flows
Flux tube gyrokinetic simulations of the edge pedestal
Parker, Scott; Wan, Weigang; Chen, Yang
2011-10-01
The linear instabilities of DIII-D H-mode pedestal are studied with gyrokinetic micro-turbulence simulations. The simulation code GEM is an electromagnetic δf code with global tokamak geometry in the form of Miller equilibrium. Local flux tube simulations are carried out for multiple positions of two DIII-D profiles: shot #98889 and shot #131997. Near the top of the pedestal, the instability is clearly ITG. The dominant instability of the pedestal appears at the steep gradient region, and it is identified as a low frequency mode mostly driven by electron temperature gradient. The mode propagates along the electron diamagnetic direction for low n and may propagate along the ion direction for high n. At some positions near the steep gradient region, an ion instability is found which shows some characteristics of kinetic ballooning mode (KBM). These results will be compared to the results of E. Wang et al. and D. Fulton et al. in the same session. We thank R. Groebner and P. Snyder for providing experimental profiles and helpful discussions.
Glass, Alexis; Fukudome, Kimitoshi
2004-12-01
A sound recording of a plucked string instrument is encoded and resynthesized using two stages of prediction. In the first stage of prediction, a simple physical model of a plucked string is estimated and the instrument excitation is obtained. The second stage of prediction compensates for the simplicity of the model in the first stage by encoding either the instrument excitation or the model error using warped linear prediction. These two methods of compensation are compared with each other, and to the case of single-stage warped linear prediction, adjustments are introduced, and their applications to instrument synthesis and MPEG4's audio compression within the structured audio format are discussed.
Directory of Open Access Journals (Sweden)
R. Barbiero
2007-05-01
Full Text Available Model Output Statistics (MOS refers to a method of post-processing the direct outputs of numerical weather prediction (NWP models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511–L60 and LAMI-3. Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself.
International Nuclear Information System (INIS)
Baumgaertel J.A., Redi M.H., Budny R.V., Rewoldt G., Dorland W.
2005-01-01
Insight into plasma microturbulence and transport is being sought using linear simulations of drift waves on the National Spherical Torus Experiment (NSTX), following a study of drift wave modes on the Alcator C-Mod Tokamak. Microturbulence is likely generated by instabilities of drift waves, which cause transport of heat and particles. Understanding this transport is important because the containment of heat and particles is required for the achievement of practical nuclear fusion. Microtearing modes may cause high heat transport through high electron thermal conductivity. It is hoped that microtearing will be stable along with good electron transport in the proposed low collisionality International Thermonuclear Experimental Reactor (ITER). Stability of the microtearing mode is investigated for conditions at mid-radius in a high density NSTX high performance (H-mode) plasma, which is compared to the proposed ITER plasmas. The microtearing mode is driven by the electron temperature gradient, and believed to be mediated by ion collisions and magnetic shear. Calculations are based on input files produced by TRXPL following TRANSP (a time-dependent transport analysis code) analysis. The variability of unstable mode growth rates is examined as a function of ion and electron collisionalities using the parallel gyrokinetic computational code GS2. Results show the microtearing mode stability dependence for a range of plasma collisionalities. Computation verifies analytic predictions that higher collisionalities than in the NSTX experiment increase microtearing instability growth rates, but that the modes are stabilized at the highest values. There is a transition of the dominant mode in the collisionality scan to ion temperature gradient character at both high and low collisionalities. The calculations suggest that plasma electron thermal confinement may be greatly improved in the low-collisionality ITER
Verification of Gyrokinetic Particle of Turbulent Simulation of Device Size Scaling Transport
Institute of Scientific and Technical Information of China (English)
LIN Zhihong; S. ETHIER; T. S. HAHM; W. M. TANG
2012-01-01
Verification and historical perspective are presented on the gyrokinetic particle simulations that discovered the device size scaling of turbulent transport and indentified the geometry model as the source of the long-standing disagreement between gyrokinetic particle and continuum simulations.
Force prediction in permanent magnet flat linear motors (abstract)
International Nuclear Information System (INIS)
Eastham, J.F.; Akmese, R.
1991-01-01
The advent of neodymium iron boron rare-earth permanent magnet material has afforded the opportunity to construct linear machines of high force to weight ratio. The paper describes the design and construction of an axial flux machine and rotating drum test rig. The machine occupies an arc of 45 degree on a drum 1.22 m in diameter. The excitation is provided by blocks of NdFeB material which are skewed in order to minimize the force variations due to slotting. The stator carries a three-phase short-chorded double-layer winding of four poles. The machine is supplied by a PWM inverter the fundamental component of which is phase locked to the rotor position so that a ''dc brushless'' drive system is produced. Electromagnetic forces including ripple forces are measured at supply frequencies up to 100 Hz. They are compared with finite-element analysis which calculates the force variation over the time period. The paper then considers some of the causes of ripple torque. In particular, the force production due solely to the permanent magnet excitation is considered. This has two important components each acting along the line of motion of the machine, one is due to slotting and the other is due to the finite length of the primary. In the practical machine the excitation poles are skewed to minimize the slotting force and the effectiveness of this is confirmed by both results from the experiments and the finite-element analysis. The end effect force is shown to have a space period of twice that of the excitation. The amplitude of this force and its period are again confirmed by practical results
International Nuclear Information System (INIS)
Krommes, John A.
2007-01-01
The present state of the theory of fluctuations in gyrokinetic (GK) plasmas and especially its application to sampling noise in GK particle-in-cell (PIC) simulations is reviewed. Topics addressed include the Δf method, the fluctuation-dissipation theorem for both classical and GK many-body plasmas, the Klimontovich formalism, sampling noise in PIC simulations, statistical closure for partial differential equations, the theoretical foundations of spectral balance in the presence of arbitrary noise sources, and the derivation of Kadomtsev-type equations from the general formalism
Energy Technology Data Exchange (ETDEWEB)
John A. Krommes
2007-10-09
The present state of the theory of fluctuations in gyrokinetic GK plasmas and especially its application to sampling noise in GK particle-in-cell PIC simulations is reviewed. Topics addressed include the Δf method, the fluctuation-dissipation theorem for both classical and GK many-body plasmas, the Klimontovich formalism, sampling noise in PIC simulations, statistical closure for partial differential equations, the theoretical foundations of spectral balance in the presence of arbitrary noise sources, and the derivation of Kadomtsev-type equations from the general formalism.
Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression
Abdul Jameel, Abdul Gani; Naser, Nimal; Emwas, Abdul-Hamid M.; Dooley, Stephen; Sarathy, Mani
2016-01-01
An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN
Directory of Open Access Journals (Sweden)
Muayad Al-Qaisy
2015-02-01
Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.
Study of no-man's land physics in the total-f gyrokinetic code XGC1
Ku, Seung Hoe; Chang, C. S.; Lang, J.
2014-10-01
While the ``transport shortfall'' in the ``no-man's land'' has been observed often in delta-f codes, it has not yet been observed in the global total-f gyrokinetic particle code XGC1. Since understanding the interaction between the edge and core transport appears to be a critical element in the prediction for ITER performance, understanding the no-man's land issue is an important physics research topic. Simulation results using the Holland case will be presented and the physics causing the shortfall phenomenon will be discussed. Nonlinear nonlocal interaction of turbulence, secondary flows, and transport appears to be the key.
Genomic prediction based on data from three layer lines using non-linear regression models
Huang, H.; Windig, J.J.; Vereijken, A.; Calus, M.P.L.
2014-01-01
Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate
Energy Technology Data Exchange (ETDEWEB)
Besse, Nicolas, E-mail: Nicolas.Besse@oca.eu [Laboratoire J.-L. Lagrange, UMR CNRS/OCA/UCA 7293, Université Côte d’Azur, Observatoire de la Côte d’Azur, Bd de l’Observatoire CS 34229, 06304 Nice Cedex 4 (France); Institut Jean Lamour, UMR CNRS/UL 7198, Université de Lorraine, BP 70239 54506 Vandoeuvre-lès-Nancy Cedex (France); Coulette, David, E-mail: David.Coulette@ipcms.unistra.fr [Institut Jean Lamour, UMR CNRS/UL 7198, Université de Lorraine, BP 70239 54506 Vandoeuvre-lès-Nancy Cedex (France); Institut de Physique et Chimie des Matériaux de Strasbourg, UMR CNRS/US 7504, Université de Strasbourg, 23 Rue du Loess, 67034 Strasbourg (France)
2016-08-15
Achieving plasmas with good stability and confinement properties is a key research goal for magnetic fusion devices. The underlying equations are the Vlasov–Poisson and Vlasov–Maxwell (VPM) equations in three space variables, three velocity variables, and one time variable. Even in those somewhat academic cases where global equilibrium solutions are known, studying their stability requires the analysis of the spectral properties of the linearized operator, a daunting task. We have identified a model, for which not only equilibrium solutions can be constructed, but many of their stability properties are amenable to rigorous analysis. It uses a class of solution to the VPM equations (or to their gyrokinetic approximations) known as waterbag solutions which, in particular, are piecewise constant in phase-space. It also uses, not only the gyrokinetic approximation of fast cyclotronic motion around magnetic field lines, but also an asymptotic approximation regarding the magnetic-field-induced anisotropy: the spatial variation along the field lines is taken much slower than across them. Together, these assumptions result in a drastic reduction in the dimensionality of the linearized problem, which becomes a set of two nested one-dimensional problems: an integral equation in the poloidal variable, followed by a one-dimensional complex Schrödinger equation in the radial variable. We show here that the operator associated to the poloidal variable is meromorphic in the eigenparameter, the pulsation frequency. We also prove that, for all but a countable set of real pulsation frequencies, the operator is compact and thus behaves mostly as a finite-dimensional one. The numerical algorithms based on such ideas have been implemented in a companion paper [D. Coulette and N. Besse, “Numerical resolution of the global eigenvalue problem for gyrokinetic-waterbag model in toroidal geometry” (submitted)] and were found to be surprisingly close to those for the original
Energy Technology Data Exchange (ETDEWEB)
Weir, G. M.; Faber, B. J.; Likin, K. M.; Talmadge, J. N.; Anderson, D. T.; Anderson, F. S. B. [HSX Plasma Laboratory, University of Wisconsin–Madison, Madison, Wisconsin 53706 (United States)
2015-05-15
Stiffness measurements are presented in the quasi-helically symmetric experiment (HSX), in which the neoclassical transport is comparable to that in a tokamak and turbulent transport dominates throughout the plasma. Electron cyclotron emission is used to measure the local electron temperature response to modulated electron cyclotron resonant heating. The amplitude and phase of the heat wave through the steep electron temperature gradient (ETG) region of the plasma are used to determine a transient electron thermal diffusivity that is close to the steady-state diffusivity. The low stiffness in the region between 0.2 ≤ r/a ≤ 0.4 agrees with the scaling of the steady-state heat flux with temperature gradient in this region. These experimental results are compared to gyrokinetic calculations in a flux-tube geometry using the gyrokinetic electromagnetic numerical experiment code with two kinetic species. Linear simulations show that the ETG mode may be experimentally relevant within r/a ≤ 0.2, while the Trapped Electron Mode (TEM) is the dominant long-wavelength microturbulence instability across most of the plasma. The TEM is primarily driven by the density gradient. Non-linear calculations of the saturated heat flux driven by the TEM and ETG bracket the experimental heat flux.
Gyrokinetic particle simulation of neoclassical transport
International Nuclear Information System (INIS)
Lin, Z.; Tang, W.M.; Lee, W.W.
1995-01-01
A time varying weighting (δf ) scheme for gyrokinetic particle simulation is applied to a steady-state, multispecies simulation of neoclassical transport. Accurate collision operators conserving momentum and energy are developed and implemented. Simulation results using these operators are found to agree very well with neoclassical theory. For example, it is dynamically demonstrated that like-particle collisions produce no particle flux and that the neoclassical fluxes are ambipolar for an ion--electron plasma. An important physics feature of the present scheme is the introduction of toroidal flow to the simulations. Simulation results are in agreement with the existing analytical neoclassical theory. The poloidal electric field associated with toroidal mass flow is found to enhance density gradient-driven electron particle flux and the bootstrap current while reducing temperature gradient-driven flux and current. Finally, neoclassical theory in steep gradient profile relevant to the edge regime is examined by taking into account finite banana width effects. In general, in the present work a valuable new capability for studying important aspects of neoclassical transport inaccessible by conventional analytical calculation processes is demonstrated. copyright 1995 American Institute of Physics
Visual interrogation of gyrokinetic particle simulations
International Nuclear Information System (INIS)
Jones, Chad; Ma, K-L; Sanderson, Allen; Myers, Lee Roy Jr
2007-01-01
Gyrokinetic particle simulations are critical to the study of anomalous energy transport associated with plasma microturbulence in magnetic confinement fusion experiments. The simulations are conducted on massively parallel computers and produce large quantities of particles, variables, and time steps, thus presenting a formidable challenge to data analysis tasks. We present two new visualization techniques for scientists to improve their understanding of the time-varying, multivariate particle data. One technique allows scientists to examine correlations in multivariate particle data with tightly coupled views of the data in both physical space and variable space, and to visually identify and track features of interest. The second technique, built into SCIRun, allows scientists to perform range-based queries over a series of time slices and visualize the resulting particles using glyphs. The ability to navigate the multiple dimensions of the particle data, as well as query individual or a collection of particles, enables scientists to not only validate their simulations but also discover new phenomena in their data
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-12-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.
A unified frame of predicting side effects of drugs by using linear neighborhood similarity.
Zhang, Wen; Yue, Xiang; Liu, Feng; Chen, Yanlin; Tu, Shikui; Zhang, Xining
2017-12-14
Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame.
Energy Technology Data Exchange (ETDEWEB)
Sung, C., E-mail: csung@physics.ucla.edu [University of California, Los Angeles, Los Angeles, California 90095 (United States); White, A. E.; Greenwald, M.; Howard, N. T. [Plasma Science and Fusion Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Mikkelsen, D. R.; Churchill, R. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States); Holland, C. [University of California, San Diego, La Jolla, California 92093 (United States); Theiler, C. [Ecole Polytechnique Fédérale de Lausanne, SPC, Lausanne 1015 (Switzerland)
2016-04-15
Long wavelength turbulent electron temperature fluctuations (k{sub y}ρ{sub s} < 0.3) are measured in the outer core region (r/a > 0.8) of Ohmic L-mode plasmas at Alcator C-Mod [E. S. Marmar et al., Nucl. Fusion 49, 104014 (2009)] with a correlation electron cyclotron emission diagnostic. The relative amplitude and frequency spectrum of the fluctuations are compared quantitatively with nonlinear gyrokinetic simulations using the GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] in two different confinement regimes: linear Ohmic confinement (LOC) regime and saturated Ohmic confinement (SOC) regime. When comparing experiment with nonlinear simulations, it is found that local, electrostatic ion-scale simulations (k{sub y}ρ{sub s} ≲ 1.7) performed at r/a ∼ 0.85 reproduce the experimental ion heat flux levels, electron temperature fluctuation levels, and frequency spectra within experimental error bars. In contrast, the electron heat flux is robustly under-predicted and cannot be recovered by using scans of the simulation inputs within error bars or by using global simulations. If both the ion heat flux and the measured temperature fluctuations are attributed predominantly to long-wavelength turbulence, then under-prediction of electron heat flux strongly suggests that electron scale turbulence is important for transport in C-Mod Ohmic L-mode discharges. In addition, no evidence is found from linear or nonlinear simulations for a clear transition from trapped electron mode to ion temperature gradient turbulence across the LOC/SOC transition, and also there is no evidence in these Ohmic L-mode plasmas of the “Transport Shortfall” [C. Holland et al., Phys. Plasmas 16, 052301 (2009)].
Variational principle for nonlinear gyrokinetic Vlasov--Maxwell equations
International Nuclear Information System (INIS)
Brizard, Alain J.
2000-01-01
A new variational principle for the nonlinear gyrokinetic Vlasov--Maxwell equations is presented. This Eulerian variational principle uses constrained variations for the gyrocenter Vlasov distribution in eight-dimensional extended phase space and turns out to be simpler than the Lagrangian variational principle recently presented by H. Sugama [Phys. Plasmas 7, 466 (2000)]. A local energy conservation law is then derived explicitly by the Noether method. In future work, this new variational principle will be used to derive self-consistent, nonlinear, low-frequency Vlasov--Maxwell bounce-gyrokinetic equations, in which the fast gyromotion and bounce-motion time scales have been eliminated
Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities
Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred
2012-07-01
The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in
Machine learning-based methods for prediction of linear B-cell epitopes.
Wang, Hsin-Wei; Pai, Tun-Wen
2014-01-01
B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.
Applications of Kalman filters based on non-linear functions to numerical weather predictions
Directory of Open Access Journals (Sweden)
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Applications of Kalman filters based on non-linear functions to numerical weather predictions
Directory of Open Access Journals (Sweden)
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Benchmark test of drift-kinetic and gyrokinetic codes through neoclassical transport simulations
International Nuclear Information System (INIS)
Satake, S.; Sugama, H.; Watanabe, T.-H.; Idomura, Yasuhiro
2009-09-01
Two simulation codes that solve the drift-kinetic or gyrokinetic equation in toroidal plasmas are benchmarked by comparing the simulation results of neoclassical transport. The two codes are the drift-kinetic δf Monte Carlo code (FORTEC-3D) and the gyrokinetic full- f Vlasov code (GT5D), both of which solve radially-global, five-dimensional kinetic equation with including the linear Fokker-Planck collision operator. In a tokamak configuration, neoclassical radial heat flux and the force balance relation, which relates the parallel mean flow with radial electric field and temperature gradient, are compared between these two codes, and their results are also compared with the local neoclassical transport theory. It is found that the simulation results of the two codes coincide very well in a wide rage of plasma collisionality parameter ν * = 0.01 - 10 and also agree with the theoretical estimations. The time evolution of radial electric field and particle flux, and the radial profile of the geodesic acoustic mode frequency also coincide very well. These facts guarantee the capability of GT5D to simulate plasma turbulence transport with including proper neoclassical effects of collisional diffusion and equilibrium radial electric field. (author)
The spectral problem of global microinstabilities in tokamak-like plasmas using a gyrokinetic model
International Nuclear Information System (INIS)
Brunner, S.; Vaclavik, J.; Fivaz, M.; Appert, K.
1996-01-01
Tokamak-like plasmas are modeled by a periodic cylindrical system with magnetic shear and realistic density and temperature profiles. Linear electrostatic microinstabilities in such plasmas are studied by solving the eigenvalue problem starting from gyrokinetic theory. The actual eigenvalue equation is then of integral type. With this approach, finite Larmor radius (FLR) effects to all orders are taken into account. FLR effects provide for the only radial coupling in a cylinder and to lowest order correspond to polarization drift. This effectively one-dimensional problem helped us to gain useful knowledge for solving gyrokinetic equations in a curved system. When searching for the eigenfrequencies of the global modes, two different methods have been tested and compared. Either the true eigenvalue problem is solved by finding the zeros of the characteristic equation, or one considers a system driven by an antenna and looks for resonances in the power response of the plasma. In addition, mode structures were computed as well in direct as in Fourier space. The advantages and disadvantages of these various approaches are discussed. Ion temperature gradient (ITG) instabilities are studied over a wide range of parameters and for wavelengths perpendicular to the magnetic field down to the scale of ion Larmor radii. Flute instabilities driven by magnetic curvature drifts are also considered. Some of these results are compared with a time evolution PIC code. Such comparisons are valuable as the convergence of PIC results is often questioned. Work considering true toroidal geometry is in progress
I. Udeh; J.O. Isikwenu and G. Ukughere
2011-01-01
The objectives of this study were to compare the performance characteristics of four strains of broiler chicken from 2 to 8 weeks of age and predict body weight of the broilers using linear body measurements. The four strains of broiler chicken used were Anak, Arbor Acre, Ross and Marshall. The parameters recorded were bodyweight, weight gain, total feed intake, feed conversion ratio, mortality and some linear body measurements (body length, body width, breast width, drumstick length, shank l...
Predicting musically induced emotions from physiological inputs: linear and neural network models.
Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M
2013-01-01
Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.
Iterated non-linear model predictive control based on tubes and contractive constraints.
Murillo, M; Sánchez, G; Giovanini, L
2016-05-01
This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Gyrokinetic simulations of turbulent transport: size scaling and chaotic behaviour
International Nuclear Information System (INIS)
Villard, L; Brunner, S; Casati, A; Aghdam, S Khosh; Lapillonne, X; McMillan, B F; Bottino, A; Dannert, T; Goerler, T; Hatzky, R; Jenko, F; Merz, F; Chowdhury, J; Ganesh, R; Garbet, X; Grandgirard, V; Latu, G; Sarazin, Y; Idomura, Y; Jolliet, S
2010-01-01
Important steps towards the understanding of turbulent transport have been made with the development of the gyrokinetic framework for describing turbulence and with the emergence of numerical codes able to solve the set of gyrokinetic equations. This paper presents some of the main recent advances in gyrokinetic theory and computing of turbulence. Solving 5D gyrokinetic equations for each species requires state-of-the-art high performance computing techniques involving massively parallel computers and parallel scalable algorithms. The various numerical schemes that have been explored until now, Lagrangian, Eulerian and semi-Lagrangian, each have their advantages and drawbacks. A past controversy regarding the finite size effect (finite ρ * ) in ITG turbulence has now been resolved. It has triggered an intensive benchmarking effort and careful examination of the convergence properties of the different numerical approaches. Now, both Eulerian and Lagrangian global codes are shown to agree and to converge to the flux-tube result in the ρ * → 0 limit. It is found, however, that an appropriate treatment of geometrical terms is necessary: inconsistent approximations that are sometimes used can lead to important discrepancies. Turbulent processes are characterized by a chaotic behaviour, often accompanied by bursts and avalanches. Performing ensemble averages of statistically independent simulations, starting from different initial conditions, is presented as a way to assess the intrinsic variability of turbulent fluxes and obtain reliable estimates of the standard deviation. Further developments concerning non-adiabatic electron dynamics around mode-rational surfaces and electromagnetic effects are discussed.
Metriplectic Gyrokinetics and Discretization Methods for the Landau Collision Integral
Hirvijoki, Eero; Burby, Joshua W.; Kraus, Michael
2017-10-01
We present two important results for the kinetic theory and numerical simulation of warm plasmas: 1) We provide a metriplectic formulation of collisional electrostatic gyrokinetics that is fully consistent with the First and Second Laws of Thermodynamics. 2) We provide a metriplectic temporal and velocity-space discretization for the particle phase-space Landau collision integral that satisfies the conservation of energy, momentum, and particle densities to machine precision, as well as guarantees the existence of numerical H-theorem. The properties are demonstrated algebraically. These two result have important implications: 1) Numerical methods addressing the Vlasov-Maxwell-Landau system of equations, or its reduced gyrokinetic versions, should start from a metriplectic formulation to preserve the fundamental physical principles also at the discrete level. 2) The plasma physics community should search for a metriplectic reduction theory that would serve a similar purpose as the existing Lagrangian and Hamiltonian reduction theories do in gyrokinetics. The discovery of metriplectic formulation of collisional electrostatic gyrokinetics is strong evidence in favor of such theory and, if uncovered, the theory would be invaluable in constructing reduced plasma models. Supported by U.S. DOE Contract Nos. DE-AC02-09-CH11466 (EH) and DE-AC05-06OR23100 (JWB) and by European Union's Horizon 2020 research and innovation Grant No. 708124 (MK).
Turbulent transport of toroidal angular momentum in low flow gyrokinetics
International Nuclear Information System (INIS)
Parra, Felix I; Catto, Peter J
2010-01-01
We derive a self-consistent equation for the turbulent transport of toroidal angular momentum in tokamaks in the low flow ordering that only requires solving gyrokinetic Fokker-Planck and quasineutrality equations correct to second order in an expansion on the gyroradius over scale length. We also show that according to our orderings the long wavelength toroidal rotation and the long wavelength radial electric field satisfy the neoclassical relation that gives the toroidal rotation as a function of the radial electric field and the radial gradients of pressure and temperature. Thus, the radial electric field can be solved for once the toroidal rotation is calculated from the transport of toroidal angular momentum. Unfortunately, even though this methodology only requires a gyrokinetic model correct to second order in gyroradius over scale length, current gyrokinetic simulations are only valid to first order. To overcome this difficulty, we exploit the smallish ratio B p /B, where B is the total magnetic field and B p is its poloidal component. When B p /B is small, the usual first order gyrokinetic equation provides solutions that are accurate enough to employ for our expression for the transport of toroidal angular momentum. We show that current δf and full f simulations only need small corrections to achieve this accuracy. Full f simulations, however, are still unable to determine the long wavelength, radial electric field from the quasineutrality equation.
Hamiltonian reductions in plasma physics about intrinsic gyrokinetic
International Nuclear Information System (INIS)
Guillebon de Resnes, L. de
2013-01-01
Gyrokinetic is a key model for plasma micro-turbulence, commonly used for fusion plasmas or small-scale astrophysical turbulence, for instance. The model still suffers from several issues, which could imply to reconsider the equations. This thesis dissertation clarifies three of them. First, one of the coordinates caused questions, both from a physical and from a mathematical point of view; a suitable constrained coordinate is introduced, which removes the issues from the theory and explains the intrinsic structures underlying the questions. Second, the perturbative coordinate transformation for gyrokinetic was computed only at lowest orders; explicit induction relations are obtained to go arbitrary order in the expansion. Third, the introduction of the coupling between the plasma and the electromagnetic field was not completely satisfactory; using the Hamiltonian structure of the dynamics, it is implemented in a more appropriate way, with strong consequences on the gyrokinetic equations, especially about their Hamiltonian structure. In order to address these three main points, several other results are obtained, for instance about the origin of the guiding-center adiabatic invariant, about a very efficient minimal guiding center transformation, or about an intermediate Hamiltonian model between Vlasov-Maxwell and gyrokinetic, where the characteristics include both the slow guiding-center dynamics and the fast gyro-angle dynamics. In addition, various reduction methods are used, introduced or developed, e.g. a Lie-transform of the equations of motion, a lifting method to transfer particle reductions to the corresponding Hamiltonian field dynamics, or a truncation method related both to Dirac's theory of constraints and to a projection onto a Lie-subalgebra. Besides gyrokinetic, this is useful to clarify other Hamiltonian reductions in plasma physics, for instance for incompressible or electrostatic dynamics, for magnetohydrodynamics, or for fluid closures including
Including collisions in gyrokinetic tokamak and stellarator simulations
International Nuclear Information System (INIS)
Kauffmann, Karla
2012-01-01
Particle and heat transport in fusion devices often exceed the neoclassical prediction. This anomalous transport is thought to be produced by turbulence caused by microinstabilities such as ion and electron-temperature-gradient (ITG/ETG) and trapped-electron-mode (TEM) instabilities, the latter ones known for being strongly influenced by collisions. Additionally, in stellarators, the neoclassical transport can be important in the core, and therefore investigation of the effects of collisions is an important field of study. Prior to this thesis, however, no gyrokinetic simulations retaining collisions had been performed in stellarator geometry. In this work, collisional effects were added to EUTERPE, a previously collisionless gyrokinetic code which utilizes the δf method. To simulate the collisions, a pitch-angle scattering operator was employed, and its implementation was carried out following the methods proposed in [Takizuka and Abe 1977, Vernay Master's thesis 2008]. To test this implementation, the evolution of the distribution function in a homogeneous plasma was first simulated, where Legendre polynomials constitute eigenfunctions of the collision operator. Also, the solution of the Spitzer problem was reproduced for a cylinder and a tokamak. Both these tests showed that collisions were correctly implemented and that the code is suited for more complex simulations. As a next step, the code was used to calculate the neoclassical radial particle flux by neglecting any turbulent fluctuations in the distribution function and the electric field. Particle fluxes in the neoclassical analytical regimes were simulated for tokamak and stellarator (LHD) configurations. In addition to the comparison with analytical fluxes, a successful benchmark with the DKES code was presented for the tokamak case, which further validates the code for neoclassical simulations. In the final part of the work, the effects of collisions were investigated for slab and toroidal ITGs and
Including collisions in gyrokinetic tokamak and stellarator simulations
Energy Technology Data Exchange (ETDEWEB)
Kauffmann, Karla
2012-04-10
Particle and heat transport in fusion devices often exceed the neoclassical prediction. This anomalous transport is thought to be produced by turbulence caused by microinstabilities such as ion and electron-temperature-gradient (ITG/ETG) and trapped-electron-mode (TEM) instabilities, the latter ones known for being strongly influenced by collisions. Additionally, in stellarators, the neoclassical transport can be important in the core, and therefore investigation of the effects of collisions is an important field of study. Prior to this thesis, however, no gyrokinetic simulations retaining collisions had been performed in stellarator geometry. In this work, collisional effects were added to EUTERPE, a previously collisionless gyrokinetic code which utilizes the {delta}f method. To simulate the collisions, a pitch-angle scattering operator was employed, and its implementation was carried out following the methods proposed in [Takizuka and Abe 1977, Vernay Master's thesis 2008]. To test this implementation, the evolution of the distribution function in a homogeneous plasma was first simulated, where Legendre polynomials constitute eigenfunctions of the collision operator. Also, the solution of the Spitzer problem was reproduced for a cylinder and a tokamak. Both these tests showed that collisions were correctly implemented and that the code is suited for more complex simulations. As a next step, the code was used to calculate the neoclassical radial particle flux by neglecting any turbulent fluctuations in the distribution function and the electric field. Particle fluxes in the neoclassical analytical regimes were simulated for tokamak and stellarator (LHD) configurations. In addition to the comparison with analytical fluxes, a successful benchmark with the DKES code was presented for the tokamak case, which further validates the code for neoclassical simulations. In the final part of the work, the effects of collisions were investigated for slab and toroidal
Model for predicting non-linear crack growth considering load sequence effects (LOSEQ)
International Nuclear Information System (INIS)
Fuehring, H.
1982-01-01
A new analytical model for predicting non-linear crack growth is presented which takes into account the retardation as well as the acceleration effects due to irregular loading. It considers not only the maximum peak of a load sequence to effect crack growth but also all other loads of the history according to a generalised memory criterion. Comparisons between crack growth predicted by using the LOSEQ-programme and experimentally observed data are presented. (orig.) [de
Fluid and gyrokinetic modelling of particle transport in plasmas with hollow density profiles
International Nuclear Information System (INIS)
Tegnered, D; Oberparleiter, M; Nordman, H; Strand, P
2016-01-01
Hollow density profiles occur in connection with pellet fuelling and L to H transitions. A positive density gradient could potentially stabilize the turbulence or change the relation between convective and diffusive fluxes, thereby reducing the turbulent transport of particles towards the center, making the fuelling scheme inefficient. In the present work, the particle transport driven by ITG/TE mode turbulence in regions of hollow density profiles is studied by fluid as well as gyrokinetic simulations. The fluid model used, an extended version of the Weiland transport model, Extended Drift Wave Model (EDWM), incorporates an arbitrary number of ion species in a multi-fluid description, and an extended wavelength spectrum. The fluid model, which is fast and hence suitable for use in predictive simulations, is compared to gyrokinetic simulations using the code GENE. Typical tokamak parameters are used based on the Cyclone Base Case. Parameter scans in key plasma parameters like plasma β, R/L T , and magnetic shear are investigated. It is found that β in particular has a stabilizing effect in the negative R/L n region, both nonlinear GENE and EDWM show a decrease in inward flux for negative R/L n and a change of direction from inward to outward for positive R/L n . This might have serious consequences for pellet fuelling of high β plasmas. (paper)
Bayesian prediction of spatial count data using generalized linear mixed models
DEFF Research Database (Denmark)
Christensen, Ole Fredslund; Waagepetersen, Rasmus Plenge
2002-01-01
Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, ...
Fung, Karen; ElAtia, Samira
2015-01-01
Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…
An improved robust model predictive control for linear parameter-varying input-output models
Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.
2018-01-01
This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik
2014-01-01
This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP...
Akbulut, Yavuz
2007-01-01
Factors predicting vocabulary learning and reading comprehension of advanced language learners of English in a linear multimedia text were investigated in the current study. Predictor variables of interest were multimedia type, reading proficiency, learning styles, topic interest and background knowledge about the topic. The outcome variables of…
Convergence Guaranteed Nonlinear Constraint Model Predictive Control via I/O Linearization
Directory of Open Access Journals (Sweden)
Xiaobing Kong
2013-01-01
Full Text Available Constituting reliable optimal solution is a key issue for the nonlinear constrained model predictive control. Input-output feedback linearization is a popular method in nonlinear control. By using an input-output feedback linearizing controller, the original linear input constraints will change to nonlinear constraints and sometimes the constraints are state dependent. This paper presents an iterative quadratic program (IQP routine on the continuous-time system. To guarantee its convergence, another iterative approach is incorporated. The proposed algorithm can reach a feasible solution over the entire prediction horizon. Simulation results on both a numerical example and the continuous stirred tank reactors (CSTR demonstrate the effectiveness of the proposed method.
A study on two phase flows of linear compressors for the prediction of refrigerant leakage
International Nuclear Information System (INIS)
Hwang, Il Sun; Lee, Young Lim; Oh, Won Sik; Park, Kyeong Bae
2015-01-01
Usage of linear compressors is on the rise due to their high efficiency. In this paper, leakage of a linear compressor has been studied through numerical analysis and experiments. First, nitrogen leakage for a stagnant piston with fixed cylinder pressure as well as for a moving piston with fixed cylinder pressure was analyzed to verify the validity of the two-phase flow analysis model. Next, refrigerant leakage of a linear compressor in operation was finally predicted through 3-dimensional unsteady, two phase flow CFD (Computational fluid dynamics). According to the research results, the numerical analyses for the fixed cylinder pressure models were in good agreement with the experimental results. The refrigerant leakage of the linear compressor in operation mainly occurred through the oil exit and the leakage became negligible after about 0.4s following operation where the leakage became lower than 2.0x10 -4 kg/s.
Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme
2015-01-01
The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.
Suzuki, Makoto; Sugimura, Yuko; Yamada, Sumio; Omori, Yoshitsugu; Miyamoto, Masaaki; Yamamoto, Jun-ichi
2013-01-01
Cognitive disorders in the acute stage of stroke are common and are important independent predictors of adverse outcome in the long term. Despite the impact of cognitive disorders on both patients and their families, it is still difficult to predict the extent or duration of cognitive impairments. The objective of the present study was, therefore, to provide data on predicting the recovery of cognitive function soon after stroke by differential modeling with logarithmic and linear regression. This study included two rounds of data collection comprising 57 stroke patients enrolled in the first round for the purpose of identifying the time course of cognitive recovery in the early-phase group data, and 43 stroke patients in the second round for the purpose of ensuring that the correlation of the early-phase group data applied to the prediction of each individual's degree of cognitive recovery. In the first round, Mini-Mental State Examination (MMSE) scores were assessed 3 times during hospitalization, and the scores were regressed on the logarithm and linear of time. In the second round, calculations of MMSE scores were made for the first two scoring times after admission to tailor the structures of logarithmic and linear regression formulae to fit an individual's degree of functional recovery. The time course of early-phase recovery for cognitive functions resembled both logarithmic and linear functions. However, MMSE scores sampled at two baseline points based on logarithmic regression modeling could estimate prediction of cognitive recovery more accurately than could linear regression modeling (logarithmic modeling, R(2) = 0.676, PLogarithmic modeling based on MMSE scores could accurately predict the recovery of cognitive function soon after the occurrence of stroke. This logarithmic modeling with mathematical procedures is simple enough to be adopted in daily clinical practice.
A national-scale model of linear features improves predictions of farmland biodiversity.
Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H
2017-12-01
Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.
Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.
Zhang, Wen; Chen, Yanlin; Li, Dingfang
2017-11-25
Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.
Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.
Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu
2016-08-01
This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.
Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A
2017-01-01
For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.
Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling
Directory of Open Access Journals (Sweden)
Eric R. Edelman
2017-06-01
Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related
Efficient Eulerian gyrokinetic simulations with block-structured grids
International Nuclear Information System (INIS)
Jarema, Denis
2017-01-01
Gaining a deep understanding of plasma microturbulence is of paramount importance for the development of future nuclear fusion reactors, because it causes a strong outward transport of heat and particles. Gyrokinetics has proven itself as a valid mathematical model to simulate such plasma microturbulence effects. In spite of the advantages of this model, nonlinear radially extended (or global) gyrokinetic simulations are still extremely computationally expensive, involving a very large number of computational grid points. Hence, methods that reduce the number of grid points without a significant loss of accuracy are a prerequisite to be able to run high-fidelity simulations. At the level of the mathematical model, the gyrokinetic approach achieves a reduction from six to five coordinates in comparison to the fully kinetic models. This reduction leads to an important decrease in the total number of computational grid points. However, the velocity space mixed with the radial direction still requires a very fine resolution in grid based codes, due to the disparities in the thermal speed, which are caused by a strong temperature variation along the radial direction. An attempt to address this problem by modifying the underlying gyrokinetic set of equations leads to additional nonlinear terms, which are the most expensive parts to simulate. Furthermore, because of these modifications, well-established and computationally efficient implementations developed for the original set of equations can no longer be used. To tackle such issues, in this thesis we introduce an alternative approach of blockstructured grids. This approach reduces the number of grid points significantly, but without changing the underlying mathematical model. Furthermore, our technique is minimally invasive and allows the reuse of a large amount of already existing code using rectilinear grids, modifications being necessary only on the block boundaries. Moreover, the block-structured grid can be
Efficient Eulerian gyrokinetic simulations with block-structured grids
Energy Technology Data Exchange (ETDEWEB)
Jarema, Denis
2017-01-20
Gaining a deep understanding of plasma microturbulence is of paramount importance for the development of future nuclear fusion reactors, because it causes a strong outward transport of heat and particles. Gyrokinetics has proven itself as a valid mathematical model to simulate such plasma microturbulence effects. In spite of the advantages of this model, nonlinear radially extended (or global) gyrokinetic simulations are still extremely computationally expensive, involving a very large number of computational grid points. Hence, methods that reduce the number of grid points without a significant loss of accuracy are a prerequisite to be able to run high-fidelity simulations. At the level of the mathematical model, the gyrokinetic approach achieves a reduction from six to five coordinates in comparison to the fully kinetic models. This reduction leads to an important decrease in the total number of computational grid points. However, the velocity space mixed with the radial direction still requires a very fine resolution in grid based codes, due to the disparities in the thermal speed, which are caused by a strong temperature variation along the radial direction. An attempt to address this problem by modifying the underlying gyrokinetic set of equations leads to additional nonlinear terms, which are the most expensive parts to simulate. Furthermore, because of these modifications, well-established and computationally efficient implementations developed for the original set of equations can no longer be used. To tackle such issues, in this thesis we introduce an alternative approach of blockstructured grids. This approach reduces the number of grid points significantly, but without changing the underlying mathematical model. Furthermore, our technique is minimally invasive and allows the reuse of a large amount of already existing code using rectilinear grids, modifications being necessary only on the block boundaries. Moreover, the block-structured grid can be
Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling.
Kawashima, Issaku; Kumano, Hiroaki
2017-01-01
Mind-wandering (MW), task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG) variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR) to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.
Predicting musically induced emotions from physiological inputs: Linear and neural network models
Directory of Open Access Journals (Sweden)
Frank A. Russo
2013-08-01
Full Text Available Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of 'felt' emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants – heart rate, respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a nonlinear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The nonlinear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the nonlinear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.
Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling
Directory of Open Access Journals (Sweden)
Issaku Kawashima
2017-07-01
Full Text Available Mind-wandering (MW, task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.
Gyrokinetic Simulations of Solar Wind Turbulence from Ion to Electron Scales
International Nuclear Information System (INIS)
Howes, G. G.; TenBarge, J. M.; Dorland, W.; Numata, R.; Quataert, E.; Schekochihin, A. A.; Tatsuno, T.
2011-01-01
A three-dimensional, nonlinear gyrokinetic simulation of plasma turbulence resolving scales from the ion to electron gyroradius with a realistic mass ratio is presented, where all damping is provided by resolved physical mechanisms. The resulting energy spectra are quantitatively consistent with a magnetic power spectrum scaling of k -2.8 as observed in in situ spacecraft measurements of the 'dissipation range' of solar wind turbulence. Despite the strongly nonlinear nature of the turbulence, the linear kinetic Alfven wave mode quantitatively describes the polarization of the turbulent fluctuations. The collisional ion heating is measured at subion-Larmor radius scales, which provides evidence of the ion entropy cascade in an electromagnetic turbulence simulation.
A comprehensive gyrokinetic description of global electrostatic microinstabilities in a tokamak
Chowdhury, J.; Ganesh, R.; Brunner, S.; Vaclavik, J.; Villard, L.; Angelino, P.
2009-05-01
It is believed that low frequency microinstabilities such as ion temperature gradient (ITG) driven modes and trapped electron modes (TEMs) are largely responsible for the experimentally observed anomalous transport via the ion and electron channels in a tokamak. In the present work, a comprehensive global linear gyrokinetic model incorporating fully kinetic (trapped and passing) electrons and ions, actual ion to electron mass ratio, radial coupling, and profile variation is used to investigate the ITG driven modes and pure TEMs. These modes are found to exhibit multiscale structures in the presence of nonadiabatic passing electrons. The multiscale structure is related to the large nonadiabaticity of electrons in the vicinity of mode rational magnetic surfaces and leads to reduced mixing length estimates of transport compared to those obtained from adiabatic electron models.
Gyrokinetic Vlasov code including full three-dimensional geometry of experiments
International Nuclear Information System (INIS)
Nunami, Masanori; Watanabe, Tomohiko; Sugama, Hideo
2010-03-01
A new gyrokinetic Vlasov simulation code, GKV-X, is developed for investigating the turbulent transport in magnetic confinement devices with non-axisymmetric configurations. Effects of the magnetic surface shapes in a three-dimensional equilibrium obtained from the VMEC code are accurately incorporated. Linear simulations of the ion temperature gradient instabilities and the zonal flows in the Large Helical Device (LHD) configuration are carried out by the GKV-X code for a benchmark test against the GKV code. The frequency, the growth rate, and the mode structure of the ion temperature gradient instability are influenced by the VMEC geometrical data such as the metric tensor components of the Boozer coordinates for high poloidal wave numbers, while the difference between the zonal flow responses obtained by the GKV and GKV-X codes is found to be small in the core LHD region. (author)
Directory of Open Access Journals (Sweden)
Xiaoli Liu
2018-01-01
Full Text Available Alzheimer’s disease (AD has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer’s disease. Recently, the multitask learning (MTL methods with sparsity-inducing norm (e.g., l2,1-norm have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures. However, these previous works formulate the prediction tasks as a linear regression problem. The major limitation is that they assumed a linear relationship between the MRI features and the cognitive outcomes. Some multikernel-based MTL methods have been proposed and shown better generalization ability due to the nonlinear advantage. We quantify the power of existing linear and nonlinear MTL methods by evaluating their performance on cognitive score prediction of Alzheimer’s disease. Moreover, we extend the traditional l2,1-norm to a more general lql1-norm (q≥1. Experiments on the Alzheimer’s Disease Neuroimaging Initiative database showed that the nonlinear l2,1lq-MKMTL method not only achieved better prediction performance than the state-of-the-art competitive methods but also effectively fused the multimodality data.
International Nuclear Information System (INIS)
Ernst, Floris; Schweikard, Achim
2008-01-01
Forecasting of respiration motion in image-guided radiotherapy requires algorithms that can accurately and efficiently predict target location. Improved methods for respiratory motion forecasting were developed and tested. MULIN, a new family of prediction algorithms based on linear expansions of the prediction error, was developed and tested. Computer-generated data with a prediction horizon of 150 ms was used for testing in simulation experiments. MULIN was compared to Least Mean Squares-based predictors (LMS; normalized LMS, nLMS; wavelet-based multiscale autoregression, wLMS) and a multi-frequency Extended Kalman Filter (EKF) approach. The in vivo performance of the algorithms was tested on data sets of patients who underwent radiotherapy. The new MULIN methods are highly competitive, outperforming the LMS and the EKF prediction algorithms in real-world settings and performing similarly to optimized nLMS and wLMS prediction algorithms. On simulated, periodic data the MULIN algorithms are outperformed only by the EKF approach due to its inherent advantage in predicting periodic signals. In the presence of noise, the MULIN methods significantly outperform all other algorithms. The MULIN family of algorithms is a feasible tool for the prediction of respiratory motion, performing as well as or better than conventional algorithms while requiring significantly lower computational complexity. The MULIN algorithms are of special importance wherever high-speed prediction is required. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Ernst, Floris; Schweikard, Achim [University of Luebeck, Institute for Robotics and Cognitive Systems, Luebeck (Germany)
2008-06-15
Forecasting of respiration motion in image-guided radiotherapy requires algorithms that can accurately and efficiently predict target location. Improved methods for respiratory motion forecasting were developed and tested. MULIN, a new family of prediction algorithms based on linear expansions of the prediction error, was developed and tested. Computer-generated data with a prediction horizon of 150 ms was used for testing in simulation experiments. MULIN was compared to Least Mean Squares-based predictors (LMS; normalized LMS, nLMS; wavelet-based multiscale autoregression, wLMS) and a multi-frequency Extended Kalman Filter (EKF) approach. The in vivo performance of the algorithms was tested on data sets of patients who underwent radiotherapy. The new MULIN methods are highly competitive, outperforming the LMS and the EKF prediction algorithms in real-world settings and performing similarly to optimized nLMS and wLMS prediction algorithms. On simulated, periodic data the MULIN algorithms are outperformed only by the EKF approach due to its inherent advantage in predicting periodic signals. In the presence of noise, the MULIN methods significantly outperform all other algorithms. The MULIN family of algorithms is a feasible tool for the prediction of respiratory motion, performing as well as or better than conventional algorithms while requiring significantly lower computational complexity. The MULIN algorithms are of special importance wherever high-speed prediction is required. (orig.)
Linear local stability of electrostatic drift modes in helical systems
International Nuclear Information System (INIS)
Yamagishi, O.; Nakajima, N.; Sugama, H.; Nakamura, Y.
2003-01-01
We investigate the stability of the drift wave in helical systems. For this purpose, we solve the linear local gyrokinetic-Poisson equation, in the electrostatic regime. As a model of helical plasmas, Large helical Device (LHD) is considered. The equation we apply is rather exact in the framework of linear gyrokinetic theory, where only the approximation is the ballooning representation. In this paper, we consider only collisionless cases. All the frequency regime can be naturally reated without any assumptions, and in such cases, ion temperature gradient modes (ITG), trapped electron modes (TEM), and electron temperature gradient modes (ETG) are expected to become unstable linearly independently. (orig.)
Gyrokinetic theory for particle and energy transport in fusion plasmas
Falessi, Matteo Valerio; Zonca, Fulvio
2018-03-01
A set of equations is derived describing the macroscopic transport of particles and energy in a thermonuclear plasma on the energy confinement time. The equations thus derived allow studying collisional and turbulent transport self-consistently, retaining the effect of magnetic field geometry without postulating any scale separation between the reference state and fluctuations. Previously, assuming scale separation, transport equations have been derived from kinetic equations by means of multiple-scale perturbation analysis and spatio-temporal averaging. In this work, the evolution equations for the moments of the distribution function are obtained following the standard approach; meanwhile, gyrokinetic theory has been used to explicitly express the fluctuation induced fluxes. In this way, equations for the transport of particles and energy up to the transport time scale can be derived using standard first order gyrokinetics.
Nonlinear electromagnetic gyrokinetic equations for rotating axisymmetric plasmas
International Nuclear Information System (INIS)
Artun, M.; Tang, W.M.
1994-03-01
The influence of sheared equilibrium flows on the confinement properties of tokamak plasmas is a topic of much current interest. A proper theoretical foundation for the systematic kinetic analysis of this important problem has been provided here by presented the derivation of a set of nonlinear electromagnetic gyrokinetic equations applicable to low frequency microinstabilities in a rotating axisymmetric plasma. The subsonic rotation velocity considered is in the direction of symmetry with the angular rotation frequency being a function of the equilibrium magnetic flux surface. In accordance with experimental observations, the rotation profile is chosen to scale with the ion temperature. The results obtained represent the shear flow generalization of the earlier analysis by Frieman and Chen where such flows were not taken into account. In order to make it readily applicable to gyrokinetic particle simulations, this set of equations is cast in a phase-space-conserving continuity equation form
A Numerical Instability in an ADI Algorithm for Gyrokinetics
International Nuclear Information System (INIS)
Belli, E.A.; Hammett, G.W.
2004-01-01
We explore the implementation of an Alternating Direction Implicit (ADI) algorithm for a gyrokinetic plasma problem and its resulting numerical stability properties. This algorithm, which uses a standard ADI scheme to divide the field solve from the particle distribution function advance, has previously been found to work well for certain plasma kinetic problems involving one spatial and two velocity dimensions, including collisions and an electric field. However, for the gyrokinetic problem we find a severe stability restriction on the time step. Furthermore, we find that this numerical instability limitation also affects some other algorithms, such as a partially implicit Adams-Bashforth algorithm, where the parallel motion operator v parallel ∂/∂z is treated implicitly and the field terms are treated with an Adams-Bashforth explicit scheme. Fully explicit algorithms applied to all terms can be better at long wavelengths than these ADI or partially implicit algorithms
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Standardi, Laura; Edlund, Kristian
2014-01-01
This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input...... limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm...... is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers. It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ1-regularization term...
Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.
Gilra, Aditya; Gerstner, Wulfram
2017-11-27
The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.
Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine
Santoso, Noviyanti; Wibowo, Wahyu
2018-03-01
A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.
Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor
DEFF Research Database (Denmark)
de los Campos, Gustavo; Vazquez, Ana I; Fernando, Rohan
2013-01-01
Despite important advances from Genome Wide Association Studies (GWAS), for most complex human traits and diseases, a sizable proportion of genetic variance remains unexplained and prediction accuracy (PA) is usually low. Evidence suggests that PA can be improved using Whole-Genome Regression (WGR......) models where phenotypes are regressed on hundreds of thousands of variants simultaneously. The Genomic Best Linear Unbiased Prediction G-BLUP, a ridge-regression type method) is a commonly used WGR method and has shown good predictive performance when applied to plant and animal breeding populations....... However, breeding and human populations differ greatly in a number of factors that can affect the predictive performance of G-BLUP. Using theory, simulations, and real data analysis, we study the erformance of G-BLUP when applied to data from related and unrelated human subjects. Under perfect linkage...
Directory of Open Access Journals (Sweden)
Avval Zhila Mohajeri
2015-01-01
Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.
The application of sparse linear prediction dictionary to compressive sensing in speech signals
Directory of Open Access Journals (Sweden)
YOU Hanxu
2016-04-01
Full Text Available Appling compressive sensing (CS,which theoretically guarantees that signal sampling and signal compression can be achieved simultaneously,into audio and speech signal processing is one of the most popular research topics in recent years.In this paper,K-SVD algorithm was employed to learn a sparse linear prediction dictionary regarding as the sparse basis of underlying speech signals.Compressed signals was obtained by applying random Gaussian matrix to sample original speech frames.Orthogonal matching pursuit (OMP and compressive sampling matching pursuit (CoSaMP were adopted to recovery original signals from compressed one.Numbers of experiments were carried out to investigate the impact of speech frames length,compression ratios,sparse basis and reconstruction algorithms on CS performance.Results show that sparse linear prediction dictionary can advance the performance of speech signals reconstruction compared with discrete cosine transform (DCT matrix.
DEFF Research Database (Denmark)
Christensen, M. G.; Jensen, Søren Holdt
2006-01-01
A method for amplitude modulated sinusoidal audio coding is presented that has low complexity and low delay. This is based on a subband processing system, where, in each subband, the signal is modeled as an amplitude modulated sum of sinusoids. The envelopes are estimated using frequency......-domain linear prediction and the prediction coefficients are quantized. As a proof of concept, we evaluate different configurations in a subjective listening test, and this shows that the proposed method offers significant improvements in sinusoidal coding. Furthermore, the properties of the frequency...
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2015-01-01
In this paper, we compare the performance of an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) to a linear tracking Model Predictive Controller (MPC) for a spray drying plant. We find in this simulation study, that the economic performance of the two controllers are almost...... equal. We evaluate the economic performance with an industrially recorded disturbance scenario, where unmeasured disturbances and model mismatch are present. The state of the spray dryer, used in the E-NMPC and MPC, is estimated using Kalman Filters with noise covariances estimated by a maximum...
Modified linear predictive coding approach for moving target tracking by Doppler radar
Ding, Yipeng; Lin, Xiaoyi; Sun, Ke-Hui; Xu, Xue-Mei; Liu, Xi-Yao
2016-07-01
Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.
Tewarie, P.; Bright, M.G.; Hillebrand, A.; Robson, S.E.; Gascoyne, L.E.; Morris, P.G.; Meier, J.; Van Mieghem, P.; Brookes, M.J.
2016-01-01
Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typically measured using haemodynamic signals) and electrophysiology has been explored using functional Magnetic Resonance Imaging (fMRI) and magnetoencephalography (MEG). Significant progress has been made, with similar spatial structure observable in both modalities. However, there is a pressing need to understand this relationship beyond simple visual similarity of RSN patterns. Here, we introduce a mathematical model to predict fMRI-based RSNs using MEG. Our unique model, based upon a multivariate Taylor series, incorporates both phase and amplitude based MEG connectivity metrics, as well as linear and non-linear interactions within and between neural oscillations measured in multiple frequency bands. We show that including non-linear interactions, multiple frequency bands and cross-frequency terms significantly improves fMRI network prediction. This shows that fMRI connectivity is not only the result of direct electrophysiological connections, but is also driven by the overlap of connectivity profiles between separate regions. Our results indicate that a complete understanding of the electrophysiological basis of RSNs goes beyond simple frequency-specific analysis, and further exploration of non-linear and cross-frequency interactions will shed new light on distributed network connectivity, and its perturbation in pathology. PMID:26827811
Ling, Ru; Liu, Jiawang
2011-12-01
To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.
MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY
Chayalakshmi C.L
2018-01-01
MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY ABSTRACT Calculation of boiler efficiency is essential if its parameters need to be controlled for either maintaining or enhancing its efficiency. But determination of boiler efficiency using conventional method is time consuming and very expensive. Hence, it is not recommended to find boiler efficiency frequently. The work presented in this paper deals with establishing the statistical mo...
Integrating piecewise linear representation and ensemble neural network for stock price prediction
Asaduzzaman, Md.; Shahjahan, Md.; Ahmed, Fatema Johera; Islam, Md. Monirul; Murase, Kazuyuki
2014-01-01
Stock Prices are considered to be very dynamic and susceptible to quick changes because of the underlying nature of the financial domain, and in part because of the interchange between known parameters and unknown factors. Of late, several researchers have used Piecewise Linear Representation (PLR) to predict the stock market pricing. However, some improvements are needed to avoid the appropriate threshold of the trading decision, choosing the input index as well as improving the overall perf...
Effects of collisions on conservation laws in gyrokinetic field theory
Energy Technology Data Exchange (ETDEWEB)
Sugama, H.; Nunami, M. [National Institute for Fusion Science, Toki 509-5292 (Japan); Department of Fusion Science, SOKENDAI (The Graduate University for Advanced Studies), Toki 509-5292 (Japan); Watanabe, T.-H. [Department of Physics, Nagoya University, Nagoya 464-8602 (Japan)
2015-08-15
Effects of collisions on conservation laws for toroidal plasmas are investigated based on the gyrokinetic field theory. Associating the collisional system with a corresponding collisionless system at a given time such that the two systems have the same distribution functions and electromagnetic fields instantaneously, it is shown how the collisionless conservation laws derived from Noether's theorem are modified by the collision term. Effects of the external source term added into the gyrokinetic equation can be formulated similarly with the collisional effects. Particle, energy, and toroidal momentum balance equations including collisional and turbulent transport fluxes are systematically derived using a novel gyrokinetic collision operator, by which the collisional change rates of energy and canonical toroidal angular momentum per unit volume in the gyrocenter space can be given in the conservative forms. The ensemble-averaged transport equations of particles, energy, and toroidal momentum given in the present work are shown to include classical, neoclassical, and turbulent transport fluxes which agree with those derived from conventional recursive formulations.
COMPREHENSIVE GYROKINETIC SIMULATION OF TOKAMAK TURBULENCE AT FINITE RELATIVE GYRORADIUS
International Nuclear Information System (INIS)
WALTZ, R.E.; CANDY, J.; ROSENBLUTH, M.N.
2002-01-01
OAK B202 COMPREHENSIVE GYROKINETIC SIMULATION OF TOKAMAK TURBULENCE AT FINITE RELATIVE GYRORADIUS. A continuum global gyrokinetic code GYRO has been developed to comprehensively simulate turbulent transport in actual experimental profiles and allow direct quantitative comparisons to the experimental transport flows. GYRO not only treats the now standard ion temperature gradient (ITG) mode turbulence, but also treats trapped and passing electrons with collisions and finite beta, and all in real tokamak geometry. Most importantly the code operates at finite relative gyroradius (ρ*) so as to treat the profile shear stabilization effects which break gyroBohm scaling. The code operates in a cyclic flux tube limit which allows only gyroBohm scaling and a noncyclic radial annulus with physical profile variation. The later requires an adaptive source to maintain equilibrium profiles. Simple ITG simulations demonstrate the broken gyroBohm scaling depends on the actual rotational velocity shear rates competing with mode growth rates, direct comprehensive simulations of the DIII-D ρ*-scaled L-mode experiments are presented as a quantitative test of gyrokinetics and the paradigm
On push-forward representations in the standard gyrokinetic model
International Nuclear Information System (INIS)
Miyato, N.; Yagi, M.; Scott, B. D.
2015-01-01
Two representations of fluid moments in terms of a gyro-center distribution function and gyro-center coordinates, which are called push-forward representations, are compared in the standard electrostatic gyrokinetic model. In the representation conventionally used to derive the gyrokinetic Poisson equation, the pull-back transformation of the gyro-center distribution function contains effects of the gyro-center transformation and therefore electrostatic potential fluctuations, which is described by the Poisson brackets between the distribution function and scalar functions generating the gyro-center transformation. Usually, only the lowest order solution of the generating function at first order is considered to explicitly derive the gyrokinetic Poisson equation. This is true in explicitly deriving representations of scalar fluid moments with polarization terms. One also recovers the particle diamagnetic flux at this order because it is associated with the guiding-center transformation. However, higher-order solutions are needed to derive finite Larmor radius terms of particle flux including the polarization drift flux from the conventional representation. On the other hand, the lowest order solution is sufficient for the other representation, in which the gyro-center transformation part is combined with the guiding-center one and the pull-back transformation of the distribution function does not appear
On push-forward representations in the standard gyrokinetic model
Energy Technology Data Exchange (ETDEWEB)
Miyato, N., E-mail: miyato.naoaki@jaea.go.jp; Yagi, M. [Japan Atomic Energy Agency, 2-116 Omotedate, Obuchi, Rokkasho, Aomori 039-3212 (Japan); Scott, B. D. [Max-Planck-Institut für Plasmaphysik, D-85748 Garching (Germany)
2015-01-15
Two representations of fluid moments in terms of a gyro-center distribution function and gyro-center coordinates, which are called push-forward representations, are compared in the standard electrostatic gyrokinetic model. In the representation conventionally used to derive the gyrokinetic Poisson equation, the pull-back transformation of the gyro-center distribution function contains effects of the gyro-center transformation and therefore electrostatic potential fluctuations, which is described by the Poisson brackets between the distribution function and scalar functions generating the gyro-center transformation. Usually, only the lowest order solution of the generating function at first order is considered to explicitly derive the gyrokinetic Poisson equation. This is true in explicitly deriving representations of scalar fluid moments with polarization terms. One also recovers the particle diamagnetic flux at this order because it is associated with the guiding-center transformation. However, higher-order solutions are needed to derive finite Larmor radius terms of particle flux including the polarization drift flux from the conventional representation. On the other hand, the lowest order solution is sufficient for the other representation, in which the gyro-center transformation part is combined with the guiding-center one and the pull-back transformation of the distribution function does not appear.
Hu, J H; Wang, Y; Cahill, P T
1997-01-01
This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.
Quantifying the predictive consequences of model error with linear subspace analysis
White, Jeremy T.; Doherty, John E.; Hughes, Joseph D.
2014-01-01
All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.
Parker, Jeffrey; Lodestro, Lynda; Told, Daniel; Merlo, Gabriele; Ricketson, Lee; Campos, Alejandro; Jenko, Frank; Hittinger, Jeffrey
2017-10-01
Predictive whole-device simulation models will play an increasingly important role in ensuring the success of fusion experiments and accelerating the development of fusion energy. In the core of tokamak plasmas, a separation of timescales between turbulence and transport makes a single direct simulation of both processes computationally expensive. We present the first demonstration of a multiple-timescale method coupling global gyrokinetic simulations with a transport solver to calculate the self-consistent, steady-state temperature profile. Initial results are highly encouraging, with the coupling method appearing robust to the difficult problem of turbulent fluctuations. The method holds potential for integrating first-principles turbulence simulations into whole-device models and advancing the understanding of global plasma behavior. Work supported by US DOE under Contract DE-AC52-07NA27344 and the Exascale Computing Project (17-SC-20-SC).
Linear filters as a method of real-time prediction of geomagnetic activity
International Nuclear Information System (INIS)
McPherron, R.L.; Baker, D.N.; Bargatze, L.F.
1985-01-01
Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance
Linear Model-Based Predictive Control of the LHC 1.8 K Cryogenic Loop
Blanco-Viñuela, E; De Prada-Moraga, C
1999-01-01
The LHC accelerator will employ 1800 superconducting magnets (for guidance and focusing of the particle beams) in a pressurized superfluid helium bath at 1.9 K. This temperature is a severely constrained control parameter in order to avoid the transition from the superconducting to the normal state. Cryogenic processes are difficult to regulate due to their highly non-linear physical parameters (heat capacity, thermal conductance, etc.) and undesirable peculiarities like non self-regulating process, inverse response and variable dead time. To reduce the requirements on either temperature sensor or cryogenic system performance, various control strategies have been investigated on a reduced-scale LHC prototype built at CERN (String Test). Model Based Predictive Control (MBPC) is a regulation algorithm based on the explicit use of a process model to forecast the plant output over a certain prediction horizon. This predicted controlled variable is used in an on-line optimization procedure that minimizes an approp...
Directory of Open Access Journals (Sweden)
Mariana Santos Matos Cavalca
2012-01-01
Full Text Available One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC strategies based on linear matrix inequalities (LMIs. However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output constraints in integrating SISO systems. Such technique guarantees robust constraint satisfaction and convergence of the state to the desired equilibrium point. A case study using numerical simulation indicates that satisfactory results can be achieved.
Madarang, Krish J; Kang, Joo-Hyon
2014-06-01
Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days (ADD), have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency's Storm Water Management Model (SWMM). The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid (TSS) discharge loads and event mean concentrations (EMC) were extracted. From these data, linear regression models were developed. R(2) and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data. Copyright © 2014 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.
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Luiz Augusto da Cruz Meleiro
2005-06-01
Full Text Available In this work a MIMO non-linear predictive controller was developed for an extractive alcoholic fermentation process. The internal model of the controller was represented by two MISO Functional Link Networks (FLNs, identified using simulated data generated from a deterministic mathematical model whose kinetic parameters were determined experimentally. The FLN structure presents as advantages fast training and guaranteed convergence, since the estimation of the weights is a linear optimization problem. Besides, the elimination of non-significant weights generates parsimonious models, which allows for fast execution in an MPC-based algorithm. The proposed algorithm showed good potential in identification and control of non-linear processes.Neste trabalho um controlador preditivo não linear multivariável foi desenvolvido para um processo de fermentação alcoólica extrativa. O modelo interno do controlador foi representado por duas redes do tipo Functional Link (FLN, identificadas usando dados de simulação gerados a partir de um modelo validado experimentalmente. A estrutura FLN apresenta como vantagem o treinamento rápido e convergência garantida, já que a estimação dos seus pesos é um problema de otimização linear. Além disso, a eliminação de pesos não significativos gera modelos parsimoniosos, o que permite a rápida execução em algoritmos de controle preditivo baseado em modelo. Os resultados mostram que o algoritmo proposto tem grande potencial para identificação e controle de processos não lineares.
Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G
2015-12-01
The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.
Zhang, Langwen; Xie, Wei; Wang, Jingcheng
2017-11-01
In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.
Predictive IP controller for robust position control of linear servo system.
Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi
2016-07-01
Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Sun, Lei; Jin, Hong-Yu; Tian, Run-Tao; Wang, Ming-Juan; Liu, Li-Na; Ye, Liu-Ping; Zuo, Tian-Tian; Ma, Shuang-Cheng
2017-01-01
Analysis of related substances in pharmaceutical chemicals and multi-components in traditional Chinese medicines needs bulk of reference substances to identify the chromatographic peaks accurately. But the reference substances are costly. Thus, the relative retention (RR) method has been widely adopted in pharmacopoeias and literatures for characterizing HPLC behaviors of those reference substances unavailable. The problem is it is difficult to reproduce the RR on different columns due to the error between measured retention time (t R ) and predicted t R in some cases. Therefore, it is useful to develop an alternative and simple method for prediction of t R accurately. In the present study, based on the thermodynamic theory of HPLC, a method named linear calibration using two reference substances (LCTRS) was proposed. The method includes three steps, procedure of two points prediction, procedure of validation by multiple points regression and sequential matching. The t R of compounds on a HPLC column can be calculated by standard retention time and linear relationship. The method was validated in two medicines on 30 columns. It was demonstrated that, LCTRS method is simple, but more accurate and more robust on different HPLC columns than RR method. Hence quality standards using LCTRS method are easy to reproduce in different laboratories with lower cost of reference substances.
Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki
2017-05-01
The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong
2011-01-21
Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.
Drzewiecki, Wojciech
2016-12-01
In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.
Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.
Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko
2016-03-01
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.
Smith, Paul F; Ganesh, Siva; Liu, Ping
2013-10-30
Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.
Towards Automated Binding Affinity Prediction Using an Iterative Linear Interaction Energy Approach
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C. Ruben Vosmeer
2014-01-01
Full Text Available Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.
Linear genetic programming application for successive-station monthly streamflow prediction
Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit
2014-09-01
In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.
The Dangers of Estimating V˙O2max Using Linear, Nonexercise Prediction Models.
Nevill, Alan M; Cooke, Carlton B
2017-05-01
This study aimed to compare the accuracy and goodness of fit of two competing models (linear vs allometric) when estimating V˙O2max (mL·kg·min) using nonexercise prediction models. The two competing models were fitted to the V˙O2max (mL·kg·min) data taken from two previously published studies. Study 1 (the Allied Dunbar National Fitness Survey) recruited 1732 randomly selected healthy participants, 16 yr and older, from 30 English parliamentary constituencies. Estimates of V˙O2max were obtained using a progressive incremental test on a motorized treadmill. In study 2, maximal oxygen uptake was measured directly during a fatigue limited treadmill test in older men (n = 152) and women (n = 146) 55 to 86 yr old. In both studies, the quality of fit associated with estimating V˙O2max (mL·kg·min) was superior using allometric rather than linear (additive) models based on all criteria (R, maximum log-likelihood, and Akaike information criteria). Results suggest that linear models will systematically overestimate V˙O2max for participants in their 20s and underestimate V˙O2max for participants in their 60s and older. The residuals saved from the linear models were neither normally distributed nor independent of the predicted values nor age. This will probably explain the absence of a key quadratic age term in the linear models, crucially identified using allometric models. Not only does the curvilinear age decline within an exponential function follow a more realistic age decline (the right-hand side of a bell-shaped curve), but the allometric models identified either a stature-to-body mass ratio (study 1) or a fat-free mass-to-body mass ratio (study 2), both associated with leanness when estimating V˙O2max. Adopting allometric models will provide more accurate predictions of V˙O2max (mL·kg·min) using plausible, biologically sound, and interpretable models.
International Nuclear Information System (INIS)
Montoya Andrade, Dan-El; Villa Jaén, Antonio de la; García Santana, Agustín
2014-01-01
Highlights: • We considered the linear generator copper losses in the proposed MPC strategy. • We maximized the power transferred to the generator side power converter. • The proposed MPC increases the useful average power injected into the grid. • The stress level of the PTO system can be reduced by the proposed MPC. - Abstract: The amount of energy that a wave energy converter can extract depends strongly on the control strategy applied to the power take-off system. It is well known that, ideally, the reactive control allows for maximum energy extraction from waves. However, the reactive control is intrinsically noncausal in practice and requires some kind of causal approach to be applied. Moreover, this strategy does not consider physical constraints and this could be a problem because the system could achieve unacceptable dynamic values. These, and other control techniques have focused on the wave energy extraction problem in order to maximize the energy absorbed by the power take-off device without considering the possible losses in intermediate devices. In this sense, a reactive control that considers the linear generator copper losses has been recently proposed to increase the useful power injected into the grid. Among the control techniques that have emerged recently, the model predictive control represents a promising strategy. This approach performs an optimization process on a time prediction horizon incorporating dynamic constraints associated with the physical features of the power take-off system. This paper proposes a model predictive control technique that considers the copper losses in the control optimization process of point absorbers with direct drive linear generators. This proposal makes the most of reactive control as it considers the copper losses, and it makes the most of the model predictive control, as it considers the system constraints. This means that the useful power transferred from the linear generator to the power
Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development
2015-01-01
Background High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine development. Owing to the variability in B-cell epitope length, the prediction of B-cell epitopes is much more complex than that of T-cell epitopes. Furthermore, the motifs of linear B-cell epitopes in different pathogens are quite different (e. g. HCV and hepatitis B virus). To cope with this challenge, this work aims to propose an HCV-customized sequence-based prediction method to identify B-cell epitopes of HCV. Results This work establishes an experimentally verified dataset comprising the B-cell response of HCV dataset consisting of 774 linear B-cell epitopes and 774 non B-cell epitopes from the Immune Epitope Database. An interpretable rule mining system of B-cell epitopes (IRMS-BE) is proposed to select informative physicochemical properties (PCPs) and then extracts several if-then rule-based knowledge for identifying B-cell epitopes. A web server Bcell-HCV was implemented using an SVM with the 34 informative PCPs, which achieved a training accuracy of 79.7% and test accuracy of 70.7% better than the SVM-based methods for identifying B-cell epitopes of HCV and the two general-purpose methods. This work performs advanced analysis of the 34 informative properties, and the results indicate that the most effective property is the alpha-helix structure of epitopes, which influences the connection between host cells and the E2 proteins of HCV. Furthermore, 12 interpretable rules are acquired from top-five PCPs and achieve a sensitivity of 75.6% and specificity of 71.3%. Finally, a conserved promising vaccine candidate, PDREMVLYQE, is identified for inclusion in a vaccine against HCV. Conclusions This work
Directory of Open Access Journals (Sweden)
Longge Zhang
2013-01-01
Full Text Available Two automatic robust model predictive control strategies are presented for uncertain polytopic linear plants with input and output constraints. A sequence of nested geometric proportion asymptotically stable ellipsoids and controllers is constructed offline first. Then the feedback controllers are automatically selected with the receding horizon online in the first strategy. Finally, a modified automatic offline robust MPC approach is constructed to improve the closed system's performance. The new proposed strategies not only reduce the conservatism but also decrease the online computation. Numerical examples are given to illustrate their effectiveness.
Morales, Esteban; de Leon, John Mark S; Abdollahi, Niloufar; Yu, Fei; Nouri-Mahdavi, Kouros; Caprioli, Joseph
2016-03-01
The study was conducted to evaluate threshold smoothing algorithms to enhance prediction of the rates of visual field (VF) worsening in glaucoma. We studied 798 patients with primary open-angle glaucoma and 6 or more years of follow-up who underwent 8 or more VF examinations. Thresholds at each VF location for the first 4 years or first half of the follow-up time (whichever was greater) were smoothed with clusters defined by the nearest neighbor (NN), Garway-Heath, Glaucoma Hemifield Test (GHT), and weighting by the correlation of rates at all other VF locations. Thresholds were regressed with a pointwise exponential regression (PER) model and a pointwise linear regression (PLR) model. Smaller root mean square error (RMSE) values of the differences between the observed and the predicted thresholds at last two follow-ups indicated better model predictions. The mean (SD) follow-up times for the smoothing and prediction phase were 5.3 (1.5) and 10.5 (3.9) years. The mean RMSE values for the PER and PLR models were unsmoothed data, 6.09 and 6.55; NN, 3.40 and 3.42; Garway-Heath, 3.47 and 3.48; GHT, 3.57 and 3.74; and correlation of rates, 3.59 and 3.64. Smoothed VF data predicted better than unsmoothed data. Nearest neighbor provided the best predictions; PER also predicted consistently more accurately than PLR. Smoothing algorithms should be used when forecasting VF results with PER or PLR. The application of smoothing algorithms on VF data can improve forecasting in VF points to assist in treatment decisions.
MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.
2005-01-01
Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.
Flexible non-linear predictive models for large-scale wind turbine diagnostics
DEFF Research Database (Denmark)
Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole
2017-01-01
We demonstrate how flexible non-linear models can provide accurate and robust predictions on turbine component temperature sensor data using data-driven principles and only a minimum of system modeling. The merits of different model architectures are evaluated using data from a large set...... of turbines operating under diverse conditions. We then go on to test the predictive models in a diagnostic setting, where the output of the models are used to detect mechanical faults in rotor bearings. Using retrospective data from 22 actual rotor bearing failures, the fault detection performance...... of the models are quantified using a structured framework that provides the metrics required for evaluating the performance in a fleet wide monitoring setup. It is demonstrated that faults are identified with high accuracy up to 45 days before a warning from the hard-threshold warning system....
Dynamics and control of quadcopter using linear model predictive control approach
Islam, M.; Okasha, M.; Idres, M. M.
2017-12-01
This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.
TBM performance prediction in Yucca Mountain welded tuff from linear cutter tests
International Nuclear Information System (INIS)
Gertsch, R.; Ozdemir, L.; Gertsch, L.
1992-01-01
This paper discusses performance prediction which were developed for tunnel boring machines operating in welded tuff for the construction of the experimental study facility and the potential nuclear waste repository at Yucca Mountain. The predictions were based on test data obtained from an extensive series of linear cutting tests performed on samples of Topopah String welded tuff from the Yucca Mountain Project site. Using the cutter force, spacing, and penetration data from the experimental program, the thrust, torque, power, and rate of penetration were estimated for a 25 ft diameter tunnel boring machine (TBM) operating in welded tuff. The result show that the Topopah Spring welded tuff (TSw2) can be excavated at relatively high rates of advance with state-of-the-art TBMs. The result also show, however, that the TBM torque and power requirements will be higher than estimated based on rock physical properties and past tunneling experience in rock formations of similar strength
Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari
2018-01-01
Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg
Wilson, S. R.; Close, M. E.; Abraham, P.
2018-01-01
Diffuse nitrate losses from agricultural land pollute groundwater resources worldwide, but can be attenuated under reducing subsurface conditions. In New Zealand, the ability to predict where groundwater denitrification occurs is important for understanding the linkage between land use and discharges of nitrate-bearing groundwater to streams. This study assesses the application of linear discriminant analysis (LDA) for predicting groundwater redox status for Southland, a major dairy farming region in New Zealand. Data cases were developed by assigning a redox status to samples derived from a regional groundwater quality database. Pre-existing regional-scale geospatial databases were used as training variables for the discriminant functions. The predictive accuracy of the discriminant functions was slightly improved by optimising the thresholds between sample depth classes. The models predict 23% of the region as being reducing at shallow depths (water table, and low-permeability clastic sediments. The coastal plains are an area of widespread groundwater discharge, and the soil and hydrology characteristics require the land to be artificially drained to render the land suitable for farming. For the improvement of water quality in coastal areas, it is therefore important that land and water management efforts focus on understanding hydrological bypassing that may occur via artificial drainage systems.
Energy Technology Data Exchange (ETDEWEB)
Hong Junjie, E-mail: hongjjie@mail.sysu.edu.cn [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China); Li Liyi, E-mail: liliyi@hit.edu.cn [Dept. Electrical Engineering, Harbin Institute of Technology, Harbin 150000 (China); Zong Zhijian; Liu Zhongtu [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China)
2011-10-15
Highlights: {yields} The structure of the permanent magnet linear synchronous motor (SW-PMLSM) is new. {yields} A new current control method CEVPC is employed in this motor. {yields} The sectional power supply method is different to the others and effective. {yields} The performance gets worse with voltage and current limitations. - Abstract: To include features such as greater thrust density, higher efficiency without reducing the thrust stability, this paper proposes a section winding permanent magnet linear synchronous motor (SW-PMLSM), whose iron core is continuous, whereas winding is divided. The discrete system model of the motor is derived. With the definition of the current error vector and selection of the value function, the theory of the current error vector based prediction control (CEVPC) for the motor currents is explained clearly. According to the winding section feature, the motion region of the mover is divided into five zones, in which the implementation of the current predictive control method is proposed. Finally, the experimental platform is constructed and experiments are carried out. The results show: the current control effect has good dynamic response, and the thrust on the mover remains constant basically.
A review of model predictive control: moving from linear to nonlinear design methods
International Nuclear Information System (INIS)
Nandong, J.; Samyudia, Y.; Tade, M.O.
2006-01-01
Linear model predictive control (LMPC) has now been considered as an industrial control standard in process industry. Its extension to nonlinear cases however has not yet gained wide acceptance due to many reasons, e.g. excessively heavy computational load and effort, thus, preventing its practical implementation in real-time control. The application of nonlinear MPC (NMPC) is advantageous for processes with strong nonlinearity or when the operating points are frequently moved from one set point to another due to, for instance, changes in market demands. Much effort has been dedicated towards improving the computational efficiency of NMPC as well as its stability analysis. This paper provides a review on alternative ways of extending linear MPC to the nonlinear one. We also highlight the critical issues pertinent to the applications of NMPC and discuss possible solutions to address these issues. In addition, we outline the future research trend in the area of model predictive control by emphasizing on the potential applications of multi-scale process model within NMPC
Using NCAP to predict RFI effects in linear bipolar integrated circuits
Fang, T.-F.; Whalen, J. J.; Chen, G. K. C.
1980-11-01
Applications of the Nonlinear Circuit Analysis Program (NCAP) to calculate RFI effects in electronic circuits containing discrete semiconductor devices have been reported upon previously. The objective of this paper is to demonstrate that the computer program NCAP also can be used to calcuate RFI effects in linear bipolar integrated circuits (IC's). The IC's reported upon are the microA741 operational amplifier (op amp) which is one of the most widely used IC's, and a differential pair which is a basic building block in many linear IC's. The microA741 op amp was used as the active component in a unity-gain buffer amplifier. The differential pair was used in a broad-band cascode amplifier circuit. The computer program NCAP was used to predict how amplitude-modulated RF signals are demodulated in the IC's to cause undesired low-frequency responses. The predicted and measured results for radio frequencies in the 0.050-60-MHz range are in good agreement.
Robust entry guidance using linear covariance-based model predictive control
Directory of Open Access Journals (Sweden)
Jianjun Luo
2017-02-01
Full Text Available For atmospheric entry vehicles, guidance design can be accomplished by solving an optimal issue using optimal control theories. However, traditional design methods generally focus on the nominal performance and do not include considerations of the robustness in the design process. This paper proposes a linear covariance-based model predictive control method for robust entry guidance design. Firstly, linear covariance analysis is employed to directly incorporate the robustness into the guidance design. The closed-loop covariance with the feedback updated control command is initially formulated to provide the expected errors of the nominal state variables in the presence of uncertainties. Then, the closed-loop covariance is innovatively used as a component of the cost function to guarantee the robustness to reduce its sensitivity to uncertainties. After that, the models predictive control is used to solve the optimal problem, and the control commands (bank angles are calculated. Finally, a series of simulations for different missions have been completed to demonstrate the high performance in precision and the robustness with respect to initial perturbations as well as uncertainties in the entry process. The 3σ confidence region results in the presence of uncertainties which show that the robustness of the guidance has been improved, and the errors of the state variables are decreased by approximately 35%.
Optimized Loading for Particle-in-cell Gyrokinetic Simulations
International Nuclear Information System (INIS)
Lewandowski, J.L.V.
2004-01-01
The problem of particle loading in particle-in-cell gyrokinetic simulations is addressed using a quadratic optimization algorithm. Optimized loading in configuration space dramatically reduces the short wavelength modes in the electrostatic potential that are partly responsible for the non-conservation of total energy; further, the long wavelength modes are resolved with good accuracy. As a result, the conservation of energy for the optimized loading is much better that the conservation of energy for the random loading. The method is valid for any geometry and can be coupled to optimization algorithms in velocity space
Global gyrokinetic simulation of Tokamak edge pedestal instabilities.
Wan, Weigang; Parker, Scott E; Chen, Yang; Yan, Zheng; Groebner, Richard J; Snyder, Philip B
2012-11-02
Global electromagnetic gyrokinetic simulations show the existence of near threshold conditions for both a high-n kinetic ballooning mode (KBM) and an intermediate-n kinetic version of peeling-ballooning mode (KPBM) in the edge pedestal of two DIII-D H-mode discharges. When the magnetic shear is reduced in a narrow region of steep pressure gradient, the KPBM is significantly stabilized, while the KBM is weakly destabilized and hence becomes the most-unstable mode. Collisions decrease the KBM's critical β and increase the growth rate.
Progress in gyrokinetic simulations of toroidal ITG turbulence
International Nuclear Information System (INIS)
Nevins, W.M.; Dimits, A.M.; Cohen, B.I.; Shumaker, D.E.
2001-01-01
The 3-D nonlinear toroidal gyrokinetic simulation code PG3EQ is used to study toroidal ion temperature gradient (ITG) driven turbulence - a key cause of the anomalous transport that limits tokamak plasma performance. Systematic studies of the dependence of ion thermal transport on various parameters and effects are presented, including dependence on E-vectorxB-vector and toroidal velocity shear, sensitivity to the force balance in simulations with radial temperature gradient variation, and the dependences on magnetic shear and ion temperature gradient. (author)
International Nuclear Information System (INIS)
Jolliet, S.
2009-02-01
The goal of thermonuclear fusion research is to provide power plants, that will be able to produce one gigawatt of electricity. Among the different ways to achieve fusion, the tokamak, based on magnetic confinement, is the most promising one. A gas is heated up to hundreds of millions of degrees and becomes a plasma, which is maintained - or confined - in a toroidal vessel by helical magnetic field lines. Then, deuterium and tritium are injected and fuse to create an α particle and an energetic neutron. In order to have a favorable power balance, the power produced by fusion reactions must exceed the power needed to heat the plasma and the power losses. This can be cast in a very simple expression which stipulates that the product of the density, the temperature and the energy confinement time must exceed some given value. Unfortunately, present-days tokamaks are not able to reach this condition, mostly due to plasma turbulence. The latter phenomenon enhances the heat losses and degrades the energy confinement time, which cannot be predicted by analytical theories such as the so-called neoclassical theory in which the heat losses are caused by Coulomb collisions. Therefore, numerical simulations are being developed to model plasma turbulence, mainly caused by the Ion and Electron Temperature-Gradient and the Trapped-Electron-Mode (TEM) instabilities. The plasma is described by a distribution function which evolves according to the Vlasov equation. The electromagnetic fields created by the particles are self-consistently obtained through Maxwell’s equations. The resulting Vlasov-Maxwell system is greatly simplified by using the gyrokinetic theory, which consists, through an appropriate ordering, of eliminating the fast gyromotion (compared to the typical frequency of instabilities). Nevertheless, it is still extremely difficult to solve this system numerically due to the large range of time and spatial scales to be resolved. In this thesis, the Vlasov
Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression
Abdul Jameel, Abdul Gani
2016-09-14
An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN) of 71 pure hydrocarbons and 54 hydrocarbon blends were utilized as a data set to study the relationship between ignition quality and molecular structure. CN and DCN are functional equivalents and collectively referred to as D/CN, herein. The effect of molecular weight and weight percent of structural parameters such as paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic CH–CH2 groups, naphthenic CH–CH2 groups, and aromatic C–CH groups on D/CN was studied. A particular emphasis on the effect of branching (i.e., methyl substitution) on the D/CN was studied, and a new parameter denoted as the branching index (BI) was introduced to quantify this effect. A new formula was developed to calculate the BI of hydrocarbon fuels using 1H NMR spectroscopy. Multiple linear regression (MLR) modeling was used to develop an empirical relationship between D/CN and the eight structural parameters. This was then used to predict the DCN of many hydrocarbon fuels. The developed model has a high correlation coefficient (R2 = 0.97) and was validated with experimentally measured DCN of twenty-two real fuel mixtures (e.g., gasolines and diesels) and fifty-nine blends of known composition, and the predicted values matched well with the experimental data.
Zounemat-Kermani, Mohammad
2012-08-01
In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.
Rogers, Barrett N.; Zhu, Ben; Francisquez, Manaure
2018-05-01
A gyrokinetic linear stability analysis of a collisionless slab geometry in the local approximation is presented. We focus on k∥=0 universal (or entropy) modes driven by plasma gradients at small and large plasma β. These are small scale non-MHD instabilities with growth rates that typically peak near k⊥ρi˜1 and vanish in the long wavelength k⊥→0 limit. This work also discusses a mode known as the Gradient Drift Coupling (GDC) instability previously reported in the gyrokinetic literature, which has a finite growth rate γ=√{β/[2 (1 +β)] }Cs/|Lp| with Cs2=p0/ρ0 for k⊥→0 and is universally unstable for 1 /Lp≠0 . We show that the GDC instability is a spurious, unphysical artifact that erroneously arises due to the failure to respect the total equilibrium pressure balance p0+B02/(8 π)=constant , which renders the assumption B0'=0 inconsistent if p0'≠0 .
Bao, J.; Liu, D.; Lin, Z.
2017-10-01
A conservative scheme of drift kinetic electrons for gyrokinetic simulations of kinetic-magnetohydrodynamic processes in toroidal plasmas has been formulated and verified. Both vector potential and electron perturbed distribution function are decomposed into adiabatic part with analytic solution and non-adiabatic part solved numerically. The adiabatic parallel electric field is solved directly from the electron adiabatic response, resulting in a high degree of accuracy. The consistency between electrostatic potential and parallel vector potential is enforced by using the electron continuity equation. Since particles are only used to calculate the non-adiabatic response, which is used to calculate the non-adiabatic vector potential through Ohm's law, the conservative scheme minimizes the electron particle noise and mitigates the cancellation problem. Linear dispersion relations of the kinetic Alfvén wave and the collisionless tearing mode in cylindrical geometry have been verified in gyrokinetic toroidal code simulations, which show that the perpendicular grid size can be larger than the electron collisionless skin depth when the mode wavelength is longer than the electron skin depth.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Frison, Gianluca; Edlund, Kristian
2013-01-01
In this paper, we develop an efficient interior-point method (IPM) for the linear programs arising in economic model predictive control of linear systems. The novelty of our algorithm is that it combines a homogeneous and self-dual model, and a specialized Riccati iteration procedure. We test...
Directory of Open Access Journals (Sweden)
C. Makendran
2015-01-01
Full Text Available Prediction models for low volume village roads in India are developed to evaluate the progression of different types of distress such as roughness, cracking, and potholes. Even though the Government of India is investing huge quantum of money on road construction every year, poor control over the quality of road construction and its subsequent maintenance is leading to the faster road deterioration. In this regard, it is essential that scientific maintenance procedures are to be evolved on the basis of performance of low volume flexible pavements. Considering the above, an attempt has been made in this research endeavor to develop prediction models to understand the progression of roughness, cracking, and potholes in flexible pavements exposed to least or nil routine maintenance. Distress data were collected from the low volume rural roads covering about 173 stretches spread across Tamil Nadu state in India. Based on the above collected data, distress prediction models have been developed using multiple linear regression analysis. Further, the models have been validated using independent field data. It can be concluded that the models developed in this study can serve as useful tools for the practicing engineers maintaining flexible pavements on low volume roads.
Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa
2015-11-03
Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.
International Nuclear Information System (INIS)
Bunyamin, Muhammad Afif; Yap, Keem Siah; Aziz, Nur Liyana Afiqah Abdul; Tiong, Sheih Kiong; Wong, Shen Yuong; Kamal, Md Fauzan
2013-01-01
This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. It is able to estimate unknown model parameters from inputs data. On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. By combining the LR and GA (GA-LR), this new technique is able to select the most important input features as well as giving more accurate prediction by minimizing the prediction errors. This new technique is able to produce more consistent of gas emission estimation, which may help in reducing population to the environment. In this paper, the study's interest is focused on nitrous oxides (NOx) prediction. The results of the experiment are encouraging.
Fully Electromagnetic Nonlinear Gyrokinetic Equations for Tokamak Edge Turbulence
International Nuclear Information System (INIS)
Hahm, T.S.; Wang, Lu; Madsen, J.
2008-01-01
An energy conserving set of the fully electromagnetic nonlinear gyrokinetic Vlasov equation and Maxwell's equations, which is applicable to both L-mode turbulence with large amplitude and H-mode turbulence in the presence of high E x B shear has been derived. The phase-space action variational Lie perturbation method ensures the preservation of the conservation laws of the underlying Vlasov-Maxwell system. Our generalized ordering takes ρ i θi ∼ L E ∼ L p i is the thermal ion Larmor radius and ρ θi = B/B θ ρ i ), as typically observed in the tokamak H-mode edge, with L E and L p being the radial electric field and pressure gradient lengths. We take k # perpendicular# ρ i ∼ 1 for generality, and keep the relative fluctuation amplitudes e(delta)φ/T i ∼ (delta)B/B up to the second order. Extending the electrostatic theory in the presence of high E x B shear [Hahm, Phys. Plasmas 3, 4658 (1996)], contributions of electromagnetic fluctuations to the particle charge density and current are explicitly evaluated via pull-back transformation from the gyrocenter distribution function in the gyrokinetic Maxwell's equation
Comprehensive gyrokinetic simulation of tokamak turbulence at finite relative gyroradius
International Nuclear Information System (INIS)
Waltz, R.E.; Candy, J.; Rosenbluth, M.N.
2003-01-01
A continuum global gyrokinetic code GYRO has been developed to comprehensively simulate turbulent transport in actual experimental profiles and allow direct quantitative comparisons to the experimental transport flows. GYRO not only treats the now standard ion temperature gradient (ITG) mode turbulence, but also treats trapped and passing electrons with collisions and finite beta, and all in real tokamak geometry. Most importantly the code operates at finite relative gyroradius (ρ*) so as to treat the profile shear stabilization effects which break gyro Bohm scaling. The code operates in a cyclic flux tube limit which allows only gyro Bohm scaling and a noncylic radial annulus with physical profile variation. The later requires an adaptive source to maintain equilibrium profiles. Simple ITG simulations demonstrate the broken gyro Bohm scaling paradigm of Garbet and Waltz [Phys. Plasmas 3, 1898 (1996)]. Since broken gyro Bohm scaling depends on the actual rotational velocity shear rates competing with mode growth rates, direct comprehensive simulations of the DIII-D ρ*-scaled L-mode experiments are presented as a quantitative test of gyrokinetics and the paradigm. (author)
International Nuclear Information System (INIS)
Kotschenreuther, M.; Wong, H.V.; Lyster, P.L.; Berk, H.L.; Denton, R.; Miner, W.H.; Valanju, P.
1991-12-01
The theoretical transport from kinetic micro-instabilities driven by ion temperature gradients is a sheared slab is compared to experimentally inferred transport in L-mode tokamaks. Low noise gyrokinetic simulation techniques are used to obtain the ion thermal transport coefficient X. This X is much smaller than in experiments, and so cannot explain L-mode confinement. Previous predictions based on fluid models gave much greater X than experiments. Linear and nonlinear comparisons with the fluid model show that it greatly overestimates transport for experimental parameters. In addition, disagreements among previous analytic and simulation calculations of X in the fluid model are reconciled
Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E
2014-05-01
The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.
A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes
Martin, Rodney Alexander
2009-01-01
In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I
Real-time detection of musical onsets with linear prediction and sinusoidal modeling
Glover, John; Lazzarini, Victor; Timoney, Joseph
2011-12-01
Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This article provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets.
Bayesian techniques for fatigue life prediction and for inference in linear time dependent PDEs
Scavino, Marco
2016-01-08
In this talk we introduce first the main characteristics of a systematic statistical approach to model calibration, model selection and model ranking when stress-life data are drawn from a collection of records of fatigue experiments. Focusing on Bayesian prediction assessment, we consider fatigue-limit models and random fatigue-limit models under different a priori assumptions. In the second part of the talk, we present a hierarchical Bayesian technique for the inference of the coefficients of time dependent linear PDEs, under the assumption that noisy measurements are available in both the interior of a domain of interest and from boundary conditions. We present a computational technique based on the marginalization of the contribution of the boundary parameters and apply it to inverse heat conduction problems.
Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan
2016-12-02
In the postgenomic era, the number of unreviewed protein sequences is remarkably larger and grows tremendously faster than that of reviewed ones. However, existing methods for protein subchloroplast localization often ignore the information from these unlabeled proteins. This paper proposes a multi-label predictor based on ensemble linear neighborhood propagation (LNP), namely, LNP-Chlo, which leverages hybrid sequence-based feature information from both labeled and unlabeled proteins for predicting localization of both single- and multi-label chloroplast proteins. Experimental results on a stringent benchmark dataset and a novel independent dataset suggest that LNP-Chlo performs at least 6% (absolute) better than state-of-the-art predictors. This paper also demonstrates that ensemble LNP significantly outperforms LNP based on individual features. For readers' convenience, the online Web server LNP-Chlo is freely available at http://bioinfo.eie.polyu.edu.hk/LNPChloServer/ .
Real time implementation of a linear predictive coding algorithm on digital signal processor DSP32C
International Nuclear Information System (INIS)
Sheikh, N.M.; Usman, S.R.; Fatima, S.
2002-01-01
Pulse Code Modulation (PCM) has been widely used in speech coding. However, due to its high bit rate. PCM has severe limitations in application where high spectral efficiency is desired, for example, in mobile communication, CD quality broadcasting system etc. These limitation have motivated research in bit rate reduction techniques. Linear predictive coding (LPC) is one of the most powerful complex techniques for bit rate reduction. With the introduction of powerful digital signal processors (DSP) it is possible to implement the complex LPC algorithm in real time. In this paper we present a real time implementation of the LPC algorithm on AT and T's DSP32C at a sampling frequency of 8192 HZ. Application of the LPC algorithm on two speech signals is discussed. Using this implementation , a bit rate reduction of 1:3 is achieved for better than tool quality speech, while a reduction of 1.16 is possible for speech quality required in military applications. (author)
Hariharan, M; Chee, Lim Sin; Yaacob, Sazali
2012-06-01
Acoustic analysis of infant cry signals has been proven to be an excellent tool in the area of automatic detection of pathological status of an infant. This paper investigates the application of parameter weighting for linear prediction cepstral coefficients (LPCCs) to provide the robust representation of infant cry signals. Three classes of infant cry signals were considered such as normal cry signals, cry signals from deaf babies and babies with asphyxia. A Probabilistic Neural Network (PNN) is suggested to classify the infant cry signals into normal and pathological cries. PNN is trained with different spread factor or smoothing parameter to obtain better classification accuracy. The experimental results demonstrate that the suggested features and classification algorithms give very promising classification accuracy of above 98% and it expounds that the suggested method can be used to help medical professionals for diagnosing pathological status of an infant from cry signals.
Directory of Open Access Journals (Sweden)
Rachid Darnag
2017-02-01
Full Text Available Support vector machines (SVM represent one of the most promising Machine Learning (ML tools that can be applied to develop a predictive quantitative structure–activity relationship (QSAR models using molecular descriptors. Multiple linear regression (MLR and artificial neural networks (ANNs were also utilized to construct quantitative linear and non linear models to compare with the results obtained by SVM. The prediction results are in good agreement with the experimental value of HIV activity; also, the results reveal the superiority of the SVM over MLR and ANN model. The contribution of each descriptor to the structure–activity relationships was evaluated.
The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.
Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun
2017-01-01
Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.
Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei
2017-12-21
In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.
Gyrokinetic global analysis of ion temperature gradient driven mode in reversed shear tokamaks
International Nuclear Information System (INIS)
Idomura, Y.; Tokuda, S.; Kishimoto, Y.
2003-01-01
A new toroidal gyrokinetic particle code has been developed to study the ion temperature gradient driven (ITG) turbulence in reactor relevant tokamak parameters. We use a new method based on a canonical Maxwellian distribution F CM (P φ , ε, μ), which is defined by three constants of motion in the axisymmetric toroidal system, the canonical angular momentum P φ , the energy ε, and the magnetic moment μ. A quasi-ballooning representation enables linear and nonlinear high-m,n global calculations with a good numerical convergence. Conservation properties are improved by using the optimized loading method. From comprehensive linear global analyses over a wide range of an unstable toroidal mode number spectrum (n=0∼100) in large tokamak parameters (a/ρ ti =320∼460), properties of the ITG modes in reversed shear tokamaks are discussed. In the nonlinear simulation, it is found that a new method based on F CM can simulate a zonal flow damping correctly, and spurious zonal flow oscillations, which are observed in a conventional method based on a local Maxwellian distribution F LM (ψ, ε, μ), do not appear in the nonlinear regime. (author)
International Nuclear Information System (INIS)
Narita, Emi; Fukuda, Takeshi; Honda, Mitsuru; Hayashi, Nobuhiko; Urano, Hajime; Ide, Shunsuke
2015-01-01
Tokamak plasmas with an internal transport barrier (ITB) are capable of maintaining improved confinement performance. The ITBs formed in plasmas with the weak magnetic shear and the weak radial electric field shear are often observed to be modest. In these ITB plasmas, it has been found that the electron temperature ITB is steeper when toroidal rotation is in a co-direction with respect to the plasma current than when toroidal rotation is in a counter-direction. To clarify the relationship between the direction of toroidal rotation and heat transport in the ITB region, we examine dominant instabilities using the flux-tube gyrokinetic code GS2. The linear calculations show a difference in the real frequencies; the counter-rotation case has a more trapped electron mode than the co-rotation case. In addition, the nonlinear calculations show that with this difference, the ratio of the electron heat diffusivity χ_e to the ion's χ_i is higher for the counter-rotation case than for the co-rotation case. The difference in χ_e /χ_i agrees with the experiment. We also find that the effect of the difference in the flow shear between the two cases due to the toroidal rotation direction on the linear growth rate is not significant. (author)
Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control
Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.
1997-01-01
One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.
Predictive inference for best linear combination of biomarkers subject to limits of detection.
Coolen-Maturi, Tahani
2017-08-15
Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
AUTHOR|(SzGeCERN)673023; Blanco Viñuela, Enrique
In each of eight arcs of the 27 km circumference Large Hadron Collider (LHC), 2.5 km long strings of super-conducting magnets are cooled with superfluid Helium II at 1.9 K. The temperature stabilisation is a challenging control problem due to complex non-linear dynamics of the magnets temperature and presence of multiple operational constraints. Strong nonlinearities and variable dead-times of the dynamics originate at strongly heat-flux dependent effective heat conductivity of superfluid that varies three orders of magnitude over the range of possible operational conditions. In order to improve the temperature stabilisation, a proof of concept on-line economic output-feedback Non-linear Model Predictive Controller (NMPC) is presented in this thesis. The controller is based on a novel complex first-principles distributed parameters numerical model of the temperature dynamics over a 214 m long sub-sector of the LHC that is characterized by very low computational cost of simulation needed in real-time optimizat...
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders
2015-01-01
We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...
Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process
Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.
2018-03-01
Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.
International Nuclear Information System (INIS)
Gertsch, R.; Ozdemir, L.
1992-09-01
The performances of mechanical excavators are predicted for excavations in welded tuff. Emphasis is given to tunnel boring machine evaluations based on linear cutting machine test data obtained on samples of Topopah Spring welded tuff. The tests involve measurement of forces as cutters are applied to the rock surface at certain spacing and penetrations. Two disc and two point-attack cutters representing currently available technology are thus evaluated. The performance predictions based on these direct experimental measurements are believed to be more accurate than any previous values for mechanical excavation of welded tuff. The calculations of performance are predicated on minimizing the amount of energy required to excavate the welded tuff. Specific energy decreases with increasing spacing and penetration, and reaches its lowest at the widest spacing and deepest penetration used in this test program. Using the force, spacing, and penetration data from this experimental program, the thrust, torque, power, and rate of penetration are calculated for several types of mechanical excavators. The results of this study show that the candidate excavators will require higher torque and power than heretofore estimated
Chaos and loss of predictability in the periodically kicked linear oscillator
International Nuclear Information System (INIS)
Luna-Acosta, G.A.; Cantoral, E.
1989-01-01
Chernikov et.al. [2] have discovered new features in the dynamics of a periodically kicked LHO x'' + ω 0 2 x = ( K/ k 0 T 2 ) sin (k 0 x) x Σ n δ (t / T - n). They report that its phase space motion under exact resonance (p ω 0 = (2 π / T) q; p, q integers), and with initial conditions on the separatrix of the average Hamiltonian , accelerates unboundedly along a fractal stochastic web with q-fold symmetry. Here we investigate with numerical experiments the effects of small deviations from exact resonance on the diffusion and symmetry patterns. We show graphically that the stochastic webs are (topologically) unstable and thus the unbounded motion becomes considerably truncated. Moreover, we analyze numerically and analytically a simpler (integrable) version. We give its exact closed-form solution in complex numbers, realize that it accelerates unboundedly only when ω 0 = (2 π/T) q (q = ± 1,2,...), and show that for small uncertainties in these frequencies, total predictability is lost as time evolves. That is, trajectories of a set of systems, initially described by close neighboring points in phase space strongly diverge in a non-linear way. The great loss of predictability in the integrable model is due to the combination of translational and rotational symmetries, inherent in these systems. (Author)
TRM performance prediction in Yucca Mountain welded tuff from linear cutter tests
International Nuclear Information System (INIS)
Gertsch, R.; Ozdemir, L.; Gertsch, L.
1992-01-01
Performance predictions were developed for tunnel boring machines operating in welded tuff for the construction of the experimental study facility and the potential nuclear waste repository at Yucca Mountain. The predictions were based on test data obtained from an extensive series of linear cutting tests performed on samples of Topopah Spring welded tuff from the Yucca Mountain Project site. Using the cutter force, spacing, and penetration data from the experimental program, the thrust, torque, power, and rate of penetration were estimated for a 25 ft diameter tunnel boring machine (TBM) operating in welded tuff. Guidelines were developed for the optimal design of the TBM cutterhead to achieve high production rates at the lowest possible excavation costs. The results show that the Topopah Spring welded tuff (TSw2) can be excavated at relatively high rates of advance with state-of-the-art TBMs. The results also show, however, that the TBM torque and power requirements will be higher than estimated based on rock physical properties and past tunneling experience in rock formations of similar strength
Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian
2018-05-12
Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.
Chaos and loss of predictability in the periodically kicked linear oscillator
Energy Technology Data Exchange (ETDEWEB)
Luna-Acosta, G A [Universidad Autonoma de Puebla (Mexico). Inst. de Ciencias; Cantoral, E [Universidad Autonoma de Puebla (Mexico). Escuela de Fisica
1989-01-01
Chernikov et.al. [2] have discovered new features in the dynamics of a periodically kicked LHO x'' + [omega] [sub 0] [sup 2] x = ( K/ k[sub 0] T [sup 2]) sin (k[sub 0] x) x [Sigma][sub n] [delta] (t / T - n). They report that its phase space motion under exact resonance (p [omega] [sub 0] = (2 [pi] / T) q; p, q integers), and with initial conditions on the separatrix of the average Hamiltonian , accelerates unboundedly along a fractal stochastic web with q-fold symmetry. Here we investigate with numerical experiments the effects of small deviations from exact resonance on the diffusion and symmetry patterns. We show graphically that the stochastic webs are (topologically) unstable and thus the unbounded motion becomes considerably truncated. Moreover, we analyze numerically and analytically a simpler (integrable) version. We give its exact closed-form solution in complex numbers, realize that it accelerates unboundedly only when [omega][sub 0] = (2 [pi]/T) q (q = [+-] 1,2,...), and show that for small uncertainties in these frequencies, total predictability is lost as time evolves. That is, trajectories of a set of systems, initially described by close neighboring points in phase space strongly diverge in a non-linear way. The great loss of predictability in the integrable model is due to the combination of translational and rotational symmetries, inherent in these systems. (Author).
Predicting stem borer density in maize using RapidEye data and generalized linear models
Abdel-Rahman, Elfatih M.; Landmann, Tobias; Kyalo, Richard; Ong'amo, George; Mwalusepo, Sizah; Sulieman, Saad; Ru, Bruno Le
2017-05-01
Average maize yield in eastern Africa is 2.03 t ha-1 as compared to global average of 6.06 t ha-1 due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In eastern Africa, maize yield losses due to stem borers are currently estimated between 12% and 21% of the total production. The objective of the present study was to explore the possibility of RapidEye spectral data to assess stem borer larva densities in maize fields in two study sites in Kenya. RapidEye images were acquired for the Bomet (western Kenya) test site on the 9th of December 2014 and on 27th of January 2015, and for Machakos (eastern Kenya) a RapidEye image was acquired on the 3rd of January 2015. Five RapidEye spectral bands as well as 30 spectral vegetation indices (SVIs) were utilized to predict per field maize stem borer larva densities using generalized linear models (GLMs), assuming Poisson ('Po') and negative binomial ('NB') distributions. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were used to assess the models performance using a leave-one-out cross-validation approach. The Zero-inflated NB ('ZINB') models outperformed the 'NB' models and stem borer larva densities could only be predicted during the mid growing season in December and early January in both study sites, respectively (RMSE = 0.69-1.06 and RPD = 8.25-19.57). Overall, all models performed similar when all the 30 SVIs (non-nested) and only the significant (nested) SVIs were used. The models developed could improve decision making regarding controlling maize stem borers within integrated pest management (IPM) interventions.
Wang, J; Wang, F; Liu, Y; Xu, J; Lin, H; Jia, B; Zuo, W; Jiang, Y; Hu, L; Lin, F
2016-01-01
Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose prediction model tailored to overweight patients. A total of 346 overweight Chinese people patients ages 18-81 years were involved in this study. Their levels of fasting glucose (fs-GLU), blood lipids, and hepatic and renal functions were measured and analyzed by multiple linear regression (MLR). Based the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tansig as the transfer function of the hidden layers nodes, and purelin for the output layer nodes, with training goal of 0.5×10(-5). There was significant correlation between fs-GLU with age, BMI, and blood biochemical indexes (P<0.05). The results of MLR analysis indicated that age, fasting alanine transaminase (fs-ALT), blood urea nitrogen (fs-BUN), total protein (fs-TP), uric acid (fs-BUN), and BMI are 6 independent variables related to fs-GLU. Based on these parameters, the BP-ANN model was performed well and reached high prediction accuracy when training 1 000 epoch (R=0.9987). The level of fs-GLU was predictable using the proposed BP-ANN model based on 6 related parameters (age, fs-ALT, fs-BUN, fs-TP, fs-UA and BMI) in overweight patients. © Georg Thieme Verlag KG Stuttgart · New York.
Integrating genomics and proteomics data to predict drug effects using binary linear programming.
Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo
2014-01-01
The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be
Yakubu, A.; Oluremi, O. I. A.; Ekpo, E. I.
2018-03-01
There is an increasing use of robust analytical algorithms in the prediction of heat stress. The present investigation therefore, was carried out to forecast heat stress index (HSI) in Sasso laying hens. One hundred and sixty seven records on the thermo-physiological parameters of the birds were utilized. They were reared on deep litter and battery cage systems. Data were collected when the birds were 42- and 52-week of age. The independent variables fitted were housing system, age of birds, rectal temperature (RT), pulse rate (PR), and respiratory rate (RR). The response variable was HSI. Data were analyzed using automatic linear modeling (ALM) and artificial neural network (ANN) procedures. The ALM model building method involved Forward Stepwise using the F Statistic criterion. As regards ANN, multilayer perceptron (MLP) with back-propagation network was used. The ANN network was trained with 90% of the data set while 10% were dedicated to testing for model validation. RR and PR were the two parameters of utmost importance in the prediction of HSI. However, the fractional importance of RR was higher than that of PR in both ALM (0.947 versus 0.053) and ANN (0.677 versus 0.274) models. The two models also predicted HSI effectively with high degree of accuracy [r = 0.980, R 2 = 0.961, adjusted R 2 = 0.961, and RMSE = 0.05168 (ALM); r = 0.983, R 2 = 0.966; adjusted R 2 = 0.966, and RMSE = 0.04806 (ANN)]. The present information may be exploited in the development of a heat stress chart based largely on RR. This may aid detection of thermal discomfort in a poultry house under tropical and subtropical conditions.
Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs.
Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul
2017-07-20
Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source. In this paper, we propose Linear Energy Prediction "LINE-P", a lightweight, yet relatively accurate model based on approximation and sampling theory; LINE-P is suitable for dual-source energy harvesting. Simulations and comparisons against existing similar models have been conducted with low and medium resolutions (i.e., 60 and 22 min intervals/24 h) for the solar energy source (low variations) and with high resolutions (15 min intervals/24 h) for the wind energy source. The results show that the accuracy of the solar-based and wind-based predictions is up to approximately 98% and 96%, respectively, while requiring a lower complexity and memory than the other models. For the cases where LINE-P's accuracy is lower than that of other approaches, it still has the advantage of lower computing requirements, making it more suitable for embedded implementation, e.g., in wireless sensor network coordinator nodes or gateways.
Directory of Open Access Journals (Sweden)
Shandilya Sharad
2012-10-01
.6% and 60.9%, respectively. Conclusion We report the development and first-use of a nontraditional non-linear method of analyzing the VF ECG signal, yielding high predictive accuracies of defibrillation success. Furthermore, incorporation of features from the PetCO2 signal noticeably increased model robustness. These predictive capabilities should further improve with the availability of a larger database.
International Nuclear Information System (INIS)
Raisee, M.; Hejazi, S.H.
2007-01-01
This paper presents comparisons between heat transfer predictions and measurements for developing turbulent flow through straight rectangular channels with sudden contractions at the mid-channel section. The present numerical results were obtained using a two-dimensional finite-volume code which solves the governing equations in a vertical plane located at the lateral mid-point of the channel. The pressure field is obtained with the well-known SIMPLE algorithm. The hybrid scheme was employed for the discretization of convection in all transport equations. For modeling of the turbulence, a zonal low-Reynolds number k-ε model and the linear and non-linear low-Reynolds number k-ε models with the 'Yap' and 'NYP' length-scale correction terms have been employed. The main objective of present study is to examine the ability of the above turbulence models in the prediction of convective heat transfer in channels with sudden contraction at a mid-channel section. The results of this study show that a sudden contraction creates a relatively small recirculation bubble immediately downstream of the channel contraction. This separation bubble influences the distribution of local heat transfer coefficient and increases the heat transfer levels by a factor of three. Computational results indicate that all the turbulence models employed produce similar flow fields. The zonal k-ε model produces the wrong Nusselt number distribution by underpredicting heat transfer levels in the recirculation bubble and overpredicting them in the developing region. The linear low-Re k-ε model, on the other hand, returns the correct Nusselt number distribution in the recirculation region, although it somewhat overpredicts heat transfer levels in the developing region downstream of the separation bubble. The replacement of the 'Yap' term with the 'NYP' term in the linear low-Re k-ε model results in a more accurate local Nusselt number distribution. Moreover, the application of the non-linear k
Comparison of Linear Microinstability Calculations of Varying Input Realism
International Nuclear Information System (INIS)
Rewoldt, G.
2003-01-01
The effect of varying ''input realism'' or varying completeness of the input data for linear microinstability calculations, in particular on the critical value of the ion temperature gradient for the ion temperature gradient mode, is investigated using gyrokinetic and gyrofluid approaches. The calculations show that varying input realism can have a substantial quantitative effect on the results
Comparison of linear microinstability calculations of varying input realism
International Nuclear Information System (INIS)
Rewoldt, G.; Kinsey, J.E.
2004-01-01
The effect of varying 'input realism' or varying completeness of the input data for linear microinstability calculations, in particular on the critical value of the ion temperature gradient for the ion temperature gradient mode, is investigated using gyrokinetic and gyrofluid approaches. The calculations show that varying input realism can have a substantial quantitative effect on the results
ADVANCES IN COMPREHENSIVE GYROKINETIC SIMULATIONS OF TRANSPORT IN TOKAMAKS
International Nuclear Information System (INIS)
WALTZ, R. E; CANDY, J; HINTON, F. L; ESTRADA-MILA, C; KINSEY, J.E
2004-01-01
A continuum global gyrokinetic code GYRO has been developed to comprehensively simulate core turbulent transport in actual experimental profiles and enable direct quantitative comparisons to the experimental transport flows. GYRO not only treats the now standard ion temperature gradient (ITG) mode turbulence, but also treats trapped and passing electrons with collisions and finite β, equilibrium ExB shear stabilization, and all in real tokamak geometry. Most importantly the code operates at finite relative gyroradius (ρ * ) so as to treat the profile shear stabilization and nonlocal effects which can break gyroBohm scaling. The code operates in either a cyclic flux-tube limit (which allows only gyroBohm scaling) or globally with physical profile variation. Bohm scaling of DIII-D L-mode has been simulated with power flows matching experiment within error bars on the ion temperature gradient. Mechanisms for broken gyroBohm scaling, neoclassical ion flows embedded in turbulence, turbulent dynamos and profile corrugations, are illustrated
Astrophysical gyrokinetics: turbulence in pressure-anisotropic plasmas at ion scales and beyond
Kunz, M. W.; Abel, I. G.; Klein, K. G.
2018-04-01
We present a theoretical framework for describing electromagnetic kinetic turbulence in a multi-species, magnetized, pressure-anisotropic plasma. The turbulent fluctuations are assumed to be small compared to the mean field, to be spatially anisotropic with respect to it and to have frequencies small compared to the ion cyclotron frequency. At scales above the ion-Larmor radius, the theory reduces to the pressure-anisotropic generalization of kinetic reduced magnetohydrodynamics (KRMHD) formulated by Kunz et al. (J. Plasma Phys., vol. 81, 2015, 325810501). At scales at and below the ion-Larmor radius, three main objectives are achieved. First, we analyse the linear response of the pressure-anisotropic gyrokinetic system, and show it to be a generalization of previously explored limits. The effects of pressure anisotropy on the stability and collisionless damping of Alfvénic and compressive fluctuations are highlighted, with attention paid to the spectral location and width of the frequency jump that occurs as Alfvén waves transition into kinetic Alfvén waves. Secondly, we derive and discuss a very general gyrokinetic free-energy conservation law, which captures both the KRMHD free-energy conservation at long wavelengths and dual cascades of kinetic Alfvén waves and ion entropy at sub-ion-Larmor scales. We show that non-Maxwellian features in the distribution function change the amount of phase mixing and the efficiency of magnetic stresses, and thus influence the partitioning of free energy amongst the cascade channels. Thirdly, a simple model is used to show that pressure anisotropy, even within the bounds imposed on it by firehose and mirror instabilities, can cause order-of-magnitude variations in the ion-to-electron heating ratio due to the dissipation of Alfvénic turbulence. Our theory provides a foundation for determining how pressure anisotropy affects turbulent fluctuation spectra, the differential heating of particle species and the ratio of parallel
Xing, Yafei; Macq, Benoit
2017-11-01
With the emergence of clinical prototypes and first patient acquisitions for proton therapy, the research on prompt gamma imaging is aiming at making most use of the prompt gamma data for in vivo estimation of any shift from expected Bragg peak (BP). The simple problem of matching the measured prompt gamma profile of each pencil beam with a reference simulation from the treatment plan is actually made complex by uncertainties which can translate into distortions during treatment. We will illustrate this challenge and demonstrate the robustness of a predictive linear model we proposed for BP shift estimation based on principal component analysis (PCA) method. It considered the first clinical knife-edge slit camera design in use with anthropomorphic phantom CT data. Particularly, 4115 error scenarios were simulated for the learning model. PCA was applied to the training input randomly chosen from 500 scenarios for eliminating data collinearities. A total variance of 99.95% was used for representing the testing input from 3615 scenarios. This model improved the BP shift estimation by an average of 63+/-19% in a range between -2.5% and 86%, comparing to our previous profile shift (PS) method. The robustness of our method was demonstrated by a comparative study conducted by applying 1000 times Poisson noise to each profile. 67% cases obtained by the learning model had lower prediction errors than those obtained by PS method. The estimation accuracy ranged between 0.31 +/- 0.22 mm and 1.84 +/- 8.98 mm for the learning model, while for PS method it ranged between 0.3 +/- 0.25 mm and 20.71 +/- 8.38 mm.
Experimental and gyrokinetic investigation of core impurity transport in Alcator C-mod
Howard, N.; Greenwald, M.; Podpaly, Y.; Reinke, M. L.; Rice, J. E.; White, A. E.; Mikkelsen, D. R.; Puetterich, T.
2010-11-01
A new multiple pulse laser blow-off system coupled with an upgraded high resolution x-ray spectrometer with spatial resolution allow for the most detailed studies of impurity transport on Alcator C-mod to date. Trace impurity injections created by the laser blow-off technique were introduced into plasmas with a wide range of parameters and time evolving profiles of He-like calcium were measured. The unique measurement of a single charge state profile and line integrated emission measurements from spectroscopic diagnostics were compared with the simulated emission from the impurity transport code STRAHL. A nonlinear least squares fitting routine was coupled with STRAHL, allowing for core impurity transport coefficients with errors to be determined. With this method, experimental data from trace calcium injections were analyzed and radially dependent, core values (< r/a ˜.6) of the diffusive and convective components of the impurity flux were obtained. The STRAHL results are compared with linear and global, nonlinear simulations from the gyrokinetic code GYRO. Results of this comparison and an investigation of the underlying physics associated with turbulent impurity transport will be presented.
A study of self organized criticality in ion temperature gradient mode driven gyrokinetic turbulence
Mavridis, M.; Isliker, H.; Vlahos, L.; Görler, T.; Jenko, F.; Told, D.
2014-10-01
An investigation on the characteristics of self organized criticality (Soc) in ITG mode driven turbulence is made, with the use of various statistical tools (histograms, power spectra, Hurst exponents estimated with the rescaled range analysis, and the structure function method). For this purpose, local non-linear gyrokinetic simulations of the cyclone base case scenario are performed with the GENE software package. Although most authors concentrate on global simulations, which seem to be a better choice for such an investigation, we use local simulations in an attempt to study the locally underlying mechanisms of Soc. We also study the structural properties of radially extended structures, with several tools (fractal dimension estimate, cluster analysis, and two dimensional autocorrelation function), in order to explore whether they can be characterized as avalanches. We find that, for large enough driving temperature gradients, the local simulations exhibit most of the features of Soc, with the exception of the probability distribution of observables, which show a tail, yet they are not of power-law form. The radial structures have the same radial extent at all temperature gradients examined; radial motion (transport) though appears only at large temperature gradients, in which case the radial structures can be interpreted as avalanches.
A study of self organized criticality in ion temperature gradient mode driven gyrokinetic turbulence
International Nuclear Information System (INIS)
Mavridis, M.; Isliker, H.; Vlahos, L.; Görler, T.; Jenko, F.; Told, D.
2014-01-01
An investigation on the characteristics of self organized criticality (Soc) in ITG mode driven turbulence is made, with the use of various statistical tools (histograms, power spectra, Hurst exponents estimated with the rescaled range analysis, and the structure function method). For this purpose, local non-linear gyrokinetic simulations of the cyclone base case scenario are performed with the GENE software package. Although most authors concentrate on global simulations, which seem to be a better choice for such an investigation, we use local simulations in an attempt to study the locally underlying mechanisms of Soc. We also study the structural properties of radially extended structures, with several tools (fractal dimension estimate, cluster analysis, and two dimensional autocorrelation function), in order to explore whether they can be characterized as avalanches. We find that, for large enough driving temperature gradients, the local simulations exhibit most of the features of Soc, with the exception of the probability distribution of observables, which show a tail, yet they are not of power-law form. The radial structures have the same radial extent at all temperature gradients examined; radial motion (transport) though appears only at large temperature gradients, in which case the radial structures can be interpreted as avalanches
A study of self organized criticality in ion temperature gradient mode driven gyrokinetic turbulence
Energy Technology Data Exchange (ETDEWEB)
Mavridis, M.; Isliker, H.; Vlahos, L. [Section of Astrophysics, Astronomy and Mechanics, Department of Physics, Aristotle University of Thessaloniki, GR-54124 Thessaloniki (Greece); Görler, T.; Jenko, F.; Told, D. [Max Planck Institute for Plasma Physics, Boltzmannstr. 2, 85748 Garching (Germany)
2014-10-15
An investigation on the characteristics of self organized criticality (Soc) in ITG mode driven turbulence is made, with the use of various statistical tools (histograms, power spectra, Hurst exponents estimated with the rescaled range analysis, and the structure function method). For this purpose, local non-linear gyrokinetic simulations of the cyclone base case scenario are performed with the GENE software package. Although most authors concentrate on global simulations, which seem to be a better choice for such an investigation, we use local simulations in an attempt to study the locally underlying mechanisms of Soc. We also study the structural properties of radially extended structures, with several tools (fractal dimension estimate, cluster analysis, and two dimensional autocorrelation function), in order to explore whether they can be characterized as avalanches. We find that, for large enough driving temperature gradients, the local simulations exhibit most of the features of Soc, with the exception of the probability distribution of observables, which show a tail, yet they are not of power-law form. The radial structures have the same radial extent at all temperature gradients examined; radial motion (transport) though appears only at large temperature gradients, in which case the radial structures can be interpreted as avalanches.
International Nuclear Information System (INIS)
Brunner, S.
1997-08-01
Ion temperature gradient (ITG)-related instabilities are studied in tokamak-like plasmas with the help of a new global eigenvalue code. Ions are modelled in the frame of gyrokinetic theory so that finite Larmor radius effects of these particles are retained to all orders. Non-adiabatic trapped electron dynamics is taken into account through the bounce-averaged drift kinetic equation. Assuming electrostatic perturbations, the system is closed with the quasineutrality relation. Practical methods are presented which make this global approach feasible. These include a non-standard wave decomposition compatible with the curved geometry as well as adapting an efficient root finding algorithm for computing the unstable spectrum. These techniques are applied to a low pressure configuration given by a large aspect ratio torus with circular, concentric magnetic surfaces. Simulations from a linear, time evolution, particle in cell code provide a useful benchmark. Comparisons with local ballooning calculations for different parameter scans enable further validation while illustrating the limits of that representation at low toroidal wave numbers or for non-interchange-like instabilities. The stabilizing effect of negative magnetic shear is also considered, in which case the global results show not only an attenuation of the growth rate but also a reduction of the radial extent induced by a transition from the toroidal- to the slab-ITG mode. Contributions of trapped electrons to the ITG instability as well as the possible coupling to the trapped electron mode are clearly brought to the fore. (author) figs., tabs., 69 refs
Gyrokinetic theory of perpendicular cyclotron resonance in a nonuniformly magnetized plasma
International Nuclear Information System (INIS)
Lashmore-Davies, C.N.; Dendy, R.O.
1989-01-01
The extension of gyrokinetic theory to arbitrary frequencies by Chen and Tsai [Phys. Fluids 26, 141 (1983); Plasma Phys. 25, 349 (1983)] is used to study cyclotron absorption in a straight magnetic field with a perpendicular, linear gradient in strength. The analysis includes the effects of magnetic field variation across the Larmor orbit and is restricted to propagation perpendicular to the field. It yields the following results for propagation into the field gradient. The standard optical depths for the fundamental O-mode and second harmonic X-mode resonances are obtained from the absorption profiles given in this paper, without invoking relativistic mass variation [see also Antonsen and Manheimer, Phys. Fluids 21, 2295 (1978)]. The compressional Alfven wave is shown to undergo perpendicular cyclotron damping at the fundamental minority resonance in a two-ion species plasma and at second harmonic resonance in a single-ion species plasma. Ion Bernstein waves propagating into the second harmonic resonance are no longer unattenuated, but are increasingly damped as they approach the resonance. It is shown how the kinetic power flow affects absorption profiles, yielding information previously obtainable only from full-wave theory. In all cases, the perpendicular cyclotron damping arises from the inclusion of magnetic field variation across the Larmor orbit
Data Normalization to Accelerate Training for Linear Neural Net to Predict Tropical Cyclone Tracks
Directory of Open Access Journals (Sweden)
Jian Jin
2015-01-01
Full Text Available When pure linear neural network (PLNN is used to predict tropical cyclone tracks (TCTs in South China Sea, whether the data is normalized or not greatly affects the training process. In this paper, min.-max. method and normal distribution method, instead of standard normal distribution, are applied to TCT data before modeling. We propose the experimental schemes in which, with min.-max. method, the min.-max. value pair of each variable is mapped to (−1, 1 and (0, 1; with normal distribution method, each variable’s mean and standard deviation pair is set to (0, 1 and (100, 1. We present the following results: (1 data scaled to the similar intervals have similar effects, no matter the use of min.-max. or normal distribution method; (2 mapping data to around 0 gains much faster training speed than mapping them to the intervals far away from 0 or using unnormalized raw data, although all of them can approach the same lower level after certain steps from their training error curves. This could be useful to decide data normalization method when PLNN is used individually.
Wheel slip control with torque blending using linear and nonlinear model predictive control
Basrah, M. Sofian; Siampis, Efstathios; Velenis, Efstathios; Cao, Dongpu; Longo, Stefano
2017-11-01
Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.
A turbulent mixing Reynolds stress model fitted to match linear interaction analysis predictions
International Nuclear Information System (INIS)
Griffond, J; Soulard, O; Souffland, D
2010-01-01
To predict the evolution of turbulent mixing zones developing in shock tube experiments with different gases, a turbulence model must be able to reliably evaluate the production due to the shock-turbulence interaction. In the limit of homogeneous weak turbulence, 'linear interaction analysis' (LIA) can be applied. This theory relies on Kovasznay's decomposition and allows the computation of waves transmitted or produced at the shock front. With assumptions about the composition of the upstream turbulent mixture, one can connect the second-order moments downstream from the shock front to those upstream through a transfer matrix, depending on shock strength. The purpose of this work is to provide a turbulence model that matches LIA results for the shock-turbulent mixture interaction. Reynolds stress models (RSMs) with additional equations for the density-velocity correlation and the density variance are considered here. The turbulent states upstream and downstream from the shock front calculated with these models can also be related through a transfer matrix, provided that the numerical implementation is based on a pseudo-pressure formulation. Then, the RSM should be modified in such a way that its transfer matrix matches the LIA one. Using the pseudo-pressure to introduce ad hoc production terms, we are able to obtain a close agreement between LIA and RSM matrices for any shock strength and thus improve the capabilities of the RSM.
International Nuclear Information System (INIS)
Vullings, R; Sluijter, R J; Mischi, M; Bergmans, J W M; Peters, C H L; Oei, S G
2009-01-01
Monitoring the fetal heart rate (fHR) and fetal electrocardiogram (fECG) during pregnancy is important to support medical decision making. Before labor, the fHR is usually monitored using Doppler ultrasound. This method is inaccurate and therefore of limited clinical value. During labor, the fHR can be monitored more accurately using an invasive electrode; this method also enables monitoring of the fECG. Antenatally, the fECG and fHR can also be monitored using electrodes on the maternal abdomen. The signal-to-noise ratio of these recordings is, however, low, the maternal electrocardiogram (mECG) being the main interference. Existing techniques to remove the mECG from these non-invasive recordings are insufficiently accurate or do not provide all spatial information of the fECG. In this paper a new technique for mECG removal in antenatal abdominal recordings is presented. This technique operates by the linear prediction of each separate wave in the mECG. Its performance in mECG removal and fHR detection is evaluated by comparison with spatial filtering, adaptive filtering, template subtraction and independent component analysis techniques. The new technique outperforms the other techniques in both mECG removal and fHR detection (by more than 3%)
Kim, T. W.; Park, G. H.
2014-12-01
Seasonal variation of aragonite saturation state (Ωarag) in the North Pacific Ocean (NPO) was investigated, using multiple linear regression (MLR) models produced from the PACIFICA (Pacific Ocean interior carbon) dataset. Data within depth ranges of 50-1200m were used to derive MLR models, and three parameters (potential temperature, nitrate, and apparent oxygen utilization (AOU)) were chosen as predictor variables because these parameters are associated with vertical mixing, DIC (dissolved inorganic carbon) removal and release which all affect Ωarag in water column directly or indirectly. The PACIFICA dataset was divided into 5° × 5° grids, and a MLR model was produced in each grid, giving total 145 independent MLR models over the NPO. Mean RMSE (root mean square error) and r2 (coefficient of determination) of all derived MLR models were approximately 0.09 and 0.96, respectively. Then the obtained MLR coefficients for each of predictor variables and an intercept were interpolated over the study area, thereby making possible to allocate MLR coefficients to data-sparse ocean regions. Predictability from the interpolated coefficients was evaluated using Hawaiian time-series data, and as a result mean residual between measured and predicted Ωarag values was approximately 0.08, which is less than the mean RMSE of our MLR models. The interpolated MLR coefficients were combined with seasonal climatology of World Ocean Atlas 2013 (1° × 1°) to produce seasonal Ωarag distributions over various depths. Large seasonal variability in Ωarag was manifested in the mid-latitude Western NPO (24-40°N, 130-180°E) and low-latitude Eastern NPO (0-12°N, 115-150°W). In the Western NPO, seasonal fluctuations of water column stratification appeared to be responsible for the seasonal variation in Ωarag (~ 0.5 at 50 m) because it closely followed temperature variations in a layer of 0-75 m. In contrast, remineralization of organic matter was the main cause for the seasonal
International Nuclear Information System (INIS)
Yock, Adam D.; Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.
2014-01-01
Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography
Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan
2017-08-28
The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical
Cardoso, F F; Tempelman, R J
2012-07-01
The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of
Performance prediction of gas turbines by solving a system of non-linear equations
Energy Technology Data Exchange (ETDEWEB)
Kaikko, J
1998-09-01
This study presents a novel method for implementing the performance prediction of gas turbines from the component models. It is based on solving the non-linear set of equations that corresponds to the process equations, and the mass and energy balances for the engine. General models have been presented for determining the steady state operation of single components. Single and multiple shad arrangements have been examined with consideration also being given to heat regeneration and intercooling. Emphasis has been placed upon axial gas turbines of an industrial scale. Applying the models requires no information of the structural dimensions of the gas turbines. On comparison with the commonly applied component matching procedures, this method incorporates several advantages. The application of the models for providing results is facilitated as less attention needs to be paid to calculation sequences and routines. Solving the set of equations is based on zeroing co-ordinate functions that are directly derived from the modelling equations. Therefore, controlling the accuracy of the results is easy. This method gives more freedom for the selection of the modelling parameters since, unlike for the matching procedures, exchanging these criteria does not itself affect the algorithms. Implicit relationships between the variables are of no significance, thus increasing the freedom for the modelling equations as well. The mathematical models developed in this thesis will provide facilities to optimise the operation of any major gas turbine configuration with respect to the desired process parameters. The computational methods used in this study may also be adapted to any other modelling problems arising in industry. (orig.) 36 refs.
Ensemble prediction of floods – catchment non-linearity and forecast probabilities
Directory of Open Access Journals (Sweden)
C. Reszler
2007-07-01
Full Text Available Quantifying the uncertainty of flood forecasts by ensemble methods is becoming increasingly important for operational purposes. The aim of this paper is to examine how the ensemble distribution of precipitation forecasts propagates in the catchment system, and to interpret the flood forecast probabilities relative to the forecast errors. We use the 622 km2 Kamp catchment in Austria as an example where a comprehensive data set, including a 500 yr and a 1000 yr flood, is available. A spatially-distributed continuous rainfall-runoff model is used along with ensemble and deterministic precipitation forecasts that combine rain gauge data, radar data and the forecast fields of the ALADIN and ECMWF numerical weather prediction models. The analyses indicate that, for long lead times, the variability of the precipitation ensemble is amplified as it propagates through the catchment system as a result of non-linear catchment response. In contrast, for lead times shorter than the catchment lag time (e.g. 12 h and less, the variability of the precipitation ensemble is decreased as the forecasts are mainly controlled by observed upstream runoff and observed precipitation. Assuming that all ensemble members are equally likely, the statistical analyses for five flood events at the Kamp showed that the ensemble spread of the flood forecasts is always narrower than the distribution of the forecast errors. This is because the ensemble forecasts focus on the uncertainty in forecast precipitation as the dominant source of uncertainty, and other sources of uncertainty are not accounted for. However, a number of analyses, including Relative Operating Characteristic diagrams, indicate that the ensemble spread is a useful indicator to assess potential forecast errors for lead times larger than 12 h.
A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mer...
Efficient Implementation of Solvers for Linear Model Predictive Control on Embedded Devices
DEFF Research Database (Denmark)
Frison, Gianluca; Kwame Minde Kufoalor, D.; Imsland, Lars
2014-01-01
This paper proposes a novel approach for the efficient implementation of solvers for linear MPC on embedded devices. The main focus is to explain in detail the approach used to optimize the linear algebra for selected low-power embedded devices, and to show how the high-performance implementation...
Linear regressive model structures for estimation and prediction of compartmental diffusive systems
Vries, D; Keesman, K.J.; Zwart, Heiko J.
In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state space
Linear regressive model structures for estimation and prediction of compartmental diffusive systems
Vries, D.; Keesman, K.J.; Zwart, H.
2006-01-01
Abstract In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state
Prediction of failures in linear systems with the use of tolerance ranges
International Nuclear Information System (INIS)
Gadzhiev, Ch.M.
1993-01-01
The problem of predicting the technical state of an object can be stated in a general case as that of predicting potential failures on the basis of a quantitative evaluation of the predicted parameters in relation to the set of tolerances on these parameters. The main stages in the prediction are collecting and preparing source data on the prehistory of the predicted phenomenon, forming a mathematical model of this phenomenon, working out the algorithm for the prediction, and adopting a solution from the prediction results. The final two stages of prediction are considered in this article. The prediction algorithm is proposed based on construction of the tolerance range for the signal of error between output coordinates of the system and its mathematical model. A solution regarding possible occurrence of failure in the system is formulated as a result of comparison of the tolerance range and the found confidence interval. 5 refs
International Nuclear Information System (INIS)
Lapillonne, X.; Brunner, S.; Dannert, T.; Jolliet, S.; Marinoni, A.; Villard, L.; Goerler, T.; Jenko, F.; Merz, F.
2009-01-01
In the context of gyrokinetic flux-tube simulations of microturbulence in magnetized toroidal plasmas, different treatments of the magnetic equilibrium are examined. Considering the Cyclone DIII-D base case parameter set [Dimits et al., Phys. Plasmas 7, 969 (2000)], significant differences in the linear growth rates, the linear and nonlinear critical temperature gradients, and the nonlinear ion heat diffusivities are observed between results obtained using either an s-α or a magnetohydrodynamic (MHD) equilibrium. Similar disagreements have been reported previously [Redd et al., Phys. Plasmas 6, 1162 (1999)]. In this paper it is shown that these differences result primarily from the approximation made in the standard implementation of the s-α model, in which the straight field line angle is identified to the poloidal angle, leading to inconsistencies of order ε (ε=a/R is the inverse aspect ratio, a the minor radius and R the major radius). An equilibrium model with concentric, circular flux surfaces and a correct treatment of the straight field line angle gives results very close to those using a finite ε, low β MHD equilibrium. Such detailed investigation of the equilibrium implementation is of particular interest when comparing flux tube and global codes. It is indeed shown here that previously reported agreements between local and global simulations in fact result from the order ε inconsistencies in the s-α model, coincidentally compensating finite ρ * effects in the global calculations, where ρ * =ρ s /a with ρ s the ion sound Larmor radius. True convergence between local and global simulations is finally obtained by correct treatment of the geometry in both cases, and considering the appropriate ρ * →0 limit in the latter case.
DEFF Research Database (Denmark)
Choi, Ui-Min; Ma, Ke; Blaabjerg, Frede
2018-01-01
In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime ...... prediction of IGBT modules under power converter applications.......In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime...... model in respect to junction temperature swing duration. This model has been built based on 39 power cycling test results of 600-V 30-A three-phase-molded IGBT modules. Six tests are performed under three superimposed power cycling conditions using an advanced power cycling test setup. The experimental...
International Nuclear Information System (INIS)
Ernst, D.R.; Basse, N.; Bonoli, P.T.; Catto, P.J.; Fiore, C.L.; Greenwald, M.; Hubbard, A.E.; Marmar, E.S.; Porkolab, M.; Rice, J.E.; Zeller, K.; Zhurovich, K.; Dorland, W.
2005-01-01
Internal particle and thermal energy transport barriers are produced in Alcator C-Mod with off-axis ICRF heating, with core densities exceeding 10 21 m -3 , without core fueling, and with little change in the temperature profile. Applying on-axis ICRF heating controls the core density gradient and rate of rise. The present study employs linear and nonlinear gyrokinetic simulations of trapped electron mode (TEM) turbulence to explore mechanisms for ITB formation and control in Alcator C-Mod ITB experiments. Anomalous pinches are found to be negligible in our simulations; further, the collisional Ware pinch is sufficient to account for the slow density rise, lasting many energy confinement times. The simulations have revealed new nonlinear physics of TEM turbulence. The critical density gradient for onset of TEM turbulent transport is nonlinearly up-shifted by zonal flows. As the density profile peaks, during ITB formation, this nonlinear critical gradient is eventually exceeded, and the turbulent particle diffusivity from GS2 gyrokinetic simulations matches the particle diffusivity from transport analysis, within experimental errors. A stable equilibrium is then established when the TEM turbulent diffusion balances the Ware pinch in the ITB. This equilibrium is sensitive to temperature through gyroBohm scaling of the TEM turbulent transport, and the collisionality dependence of the neoclassical pinch, providing for control of the density rate of rise with on-axis RF heating. With no core particle fueling, and ∼1 mm between density spatial channels, the C-Mod experiments provide a nearly ideal test bed for particle transport studies. The pure TEM is the only unstable drift mode in the ITB, producing particle transport driven by the density gradient. (author)
Augmented chaos-multiple linear regression approach for prediction of wave parameters
Directory of Open Access Journals (Sweden)
M.A. Ghorbani
2017-06-01
The inter-comparisons demonstrated that the Chaos-MLR and pure MLR models yield almost the same accuracy in predicting the significant wave heights and the zero-up-crossing wave periods. Whereas, the augmented Chaos-MLR model is performed better results in term of the prediction accuracy vis-a-vis the previous prediction applications of the same case study.
Energy Technology Data Exchange (ETDEWEB)
Mikkelsen, D. R., E-mail: dmikkelsen@pppl.gov; Bitter, M.; Delgado-Aparicio, L.; Hill, K. W. [Princeton Plasma Physics Laboratory, P.O. Box 451, Princeton, New Jersey 08543 (United States); Greenwald, M.; Howard, N. T.; Hughes, J. W.; Rice, J. E. [MIT Plasma Science and Fusion Center, 175 Albany St., Cambridge, Massachusetts 02139 (United States); Reinke, M. L. [MIT Plasma Science and Fusion Center, 175 Albany St., Cambridge, Massachusetts 02139 (United States); York Plasma Institute, Department of Physics, University of York, Heslington, York YO10 5DD (United Kingdom); Podpaly, Y. [MIT Plasma Science and Fusion Center, 175 Albany St., Cambridge, Massachusetts 02139 (United States); AAAS S and T Fellow placed in the Directorate for Engineering, NSF, 4201 Wilson Blvd., Arlington, Virginia 22230 (United States); Ma, Y. [MIT Plasma Science and Fusion Center, 175 Albany St., Cambridge, Massachusetts 02139 (United States); ITER Organization, Route de Vinon-sur-Verdon, CS 90 046, 13067 St Paul Lez Durance Cedex (France); Candy, J.; Waltz, R. E. [General Atomics, P.O. Box 85608, San Diego, California 92186-5608 (United States)
2015-06-15
Peaked density profiles in low-collisionality AUG and JET H-mode plasmas are probably caused by a turbulently driven particle pinch, and Alcator C-Mod experiments confirmed that collisionality is a critical parameter. Density peaking in reactors could produce a number of important effects, some beneficial, such as enhanced fusion power and transport of fuel ions from the edge to the core, while others are undesirable, such as lower beta limits, reduced radiation from the plasma edge, and consequently higher divertor heat loads. Fundamental understanding of the pinch will enable planning to optimize these impacts. We show that density peaking is predicted by nonlinear gyrokinetic turbulence simulations based on measured profile data from low collisionality H-mode plasma in Alcator C-Mod. Multiple ion species are included to determine whether hydrogenic density peaking has an isotope dependence or is influenced by typical levels of low-Z impurities, and whether impurity density peaking depends on the species. We find that the deuterium density profile is slightly more peaked than that of hydrogen, and that experimentally relevant levels of boron have no appreciable effect on hydrogenic density peaking. The ratio of density at r/a = 0.44 to that at r/a = 0.74 is 1.2 for the majority D and minority H ions (and for electrons), and increases with impurity Z: 1.1 for helium, 1.15 for boron, 1.3 for neon, 1.4 for argon, and 1.5 for molybdenum. The ion temperature profile is varied to match better the predicted heat flux with the experimental transport analysis, but the resulting factor of two change in heat transport has only a weak effect on the predicted density peaking.
McDowell, J J; Wood, H M
1984-03-01
Eight human subjects pressed a lever on a range of variable-interval schedules for 0.25 cent to 35.0 cent per reinforcement. Herrnstein's hyperbola described seven of the eight subjects' response-rate data well. For all subjects, the y-asymptote of the hyperbola increased with increasing reinforcer magnitude and its reciprocal was a linear function of the reciprocal of reinforcer magnitude. These results confirm predictions made by linear system theory; they contradict formal properties of Herrnstein's account and of six other mathematical accounts of single-alternative responding.
International Nuclear Information System (INIS)
Kim, J. Y.; Shin, C. H.; Kim, J. K.; Lee, J. K.; Park, Y. J.
2003-01-01
The variation transitions of the inventories for the liquid radwaste system and the radioactive gas have being released in containment, and their predictive values according to the operation histories of Yonggwang(YGN) 3 and 4 were analyzed by linear regression analysis methodology. The results show that the variation transitions of the inventories for those systems are linearly increasing according to the operation histories but the inventories released to the environment are considerably lower than the recommended values based on the FSAR suggestions. It is considered that some conservation were presented in the estimation methodology in preparing stage of FSAR
Gyrokinetic theory and dynamics of the tokamak edge
Energy Technology Data Exchange (ETDEWEB)
Scott, B. [Max-Planck-Institut fuer Plasmaphysik, Garching (Germany)
2016-08-15
The validity of modern gyrokinetic field theory is assessed for the tokamak edge. The basic structure of the Lagrangian and resulting equations and their conservation laws is reviewed. The conventional microturbulence ordering for expansion is small potential/arbitrary wavelength. The equilibrium ordering for expansion is long wavelength/arbitrary amplitude. The long-wavelength form of the conventional Lagrangian is derived in detail. The two Lagrangians are shown to match at long wavelength if the E x B Mach number is small enough for its corrections to the gyroaveraging to be neglected. Therefore, the conventional derivation and its Lagrangian can be used at all wavelengths if these conditions are satisfied. Additionally, dynamical compressibility of the magnetic field can be neglected if the plasma beta is small. This allows general use of a shear-Alfven Lagrangian for edge turbulence and self consistent equilibrium-scale phenomena for flows, currents, and heat fluxes for conventional tokamaks without further modification by higher-order terms. Corrections in polarisation and toroidal angular momentum transport due to these higher-order terms for global edge turbulence computations are shown to be small. (copyright 2016 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Gyrokinetic continuum simulations of turbulence in the Texas Helimak
Bernard, T. N.; Shi, E. L.; Hammett, G. W.; Hakim, A.; Taylor, E. I.
2017-10-01
We have used the Gkeyll code to perform 3x-2v full-f gyrokinetic continuum simulations of electrostatic plasma turbulence in the Texas Helimak. The Helimak is an open field-line experiment with magnetic curvature and shear. It is useful for validating numerical codes due to its extensive diagnostics and simple, helical geometry, which is similar to the scrape-off layer region of tokamaks. Interchange and drift-wave modes are the main turbulence mechanisms in the device, and potential biasing is applied to study the effect of velocity shear on turbulence reduction. With Gkeyll, we varied field-line pitch angle and simulated biased and unbiased cases to study different turbulent regimes and turbulence reduction. These are the first kinetic simulations of the Helimak and resulting plasma profiles agree fairly well with experimental data. This research demonstrates Gkeyll's progress towards 5D simulations of the SOL region of fusion devices. Supported by the U.S. DOE SCGSR program under contract DE-SC0014664, the Max-Planck/Princeton Center for Plasma Physics, the SciDAC Center for the Study of Plasma Microturbulence, and DOE contract DE-AC02-09CH11466.
Database-driven web interface automating gyrokinetic simulations for validation
Ernst, D. R.
2010-11-01
We are developing a web interface to connect plasma microturbulence simulation codes with experimental data. The website automates the preparation of gyrokinetic simulations utilizing plasma profile and magnetic equilibrium data from TRANSP analysis of experiments, read from MDSPLUS over the internet. This database-driven tool saves user sessions, allowing searches of previous simulations, which can be restored to repeat the same analysis for a new discharge. The website includes a multi-tab, multi-frame, publication quality java plotter Webgraph, developed as part of this project. Input files can be uploaded as templates and edited with context-sensitive help. The website creates inputs for GS2 and GYRO using a well-tested and verified back-end, in use for several years for the GS2 code [D. R. Ernst et al., Phys. Plasmas 11(5) 2637 (2004)]. A centralized web site has the advantage that users receive bug fixes instantaneously, while avoiding the duplicated effort of local compilations. Possible extensions to the database to manage run outputs, toward prototyping for the Fusion Simulation Project, are envisioned. Much of the web development utilized support from the DoE National Undergraduate Fellowship program [e.g., A. Suarez and D. R. Ernst, http://meetings.aps.org/link/BAPS.2005.DPP.GP1.57.
Advances in comprehensive gyrokinetic simulations of transport in tokamaks
International Nuclear Information System (INIS)
Waltz, R.E.; Candy, J.; Hinton, F.L.; Estrada-Mila, C.; Kinsey, J.E.
2005-01-01
A continuum global gyrokinetic code GYRO has been developed to comprehensively simulate core turbulent transport in actual experimental profiles and enable direct quantitative comparisons to the experimental transport flows. GYRO not only treats the now standard ion temperature gradient (ITG) mode turbulence, but also treats trapped and passing electrons with collisions and finite β, equilibrium ExB shear stabilization, and all in real tokamak geometry. Most importantly the code operates at finite relative gyroradius (ρ*) so as to treat the profile shear stabilization and nonlocal effects which can break gyroBohm scaling. The code operates in either a cyclic flux-tube limit (which allows only gyroBohm scaling) or globally with physical profile variation. Bohm scaling of DIII-D L-mode has been simulated with power flows matching experiment within error bars on the ion temperature gradient. Mechanisms for broken gyroBohm scaling, neoclassical ion flows embedded in turbulence, turbulent dynamos and profile corrugations, are illustrated. (author)
ADVANCES IN COMPREHENSIVE GYROKINETIC SIMULATIONS OF TRANSPORT IN TOKAMAKS
International Nuclear Information System (INIS)
WALTZ, RE; CANDY, J; HINTON, FL; ESTRADA-MILA, C; KINSEY, JE.
2004-01-01
A continuum global gyrokinetic code GYRO has been developed to comprehensively simulate core turbulent transport in actual experimental profiles and enable direct quantitative comparisons to the experimental transport flows. GYRO not only treats the now standard ion temperature gradient (ITG) mode turbulence, but also treats trapped and passing electrons with collisions and finite β, equilibrium ExB shear stabilization, and all in real tokamak geometry. Most importantly the code operates at finite relative gyroradius (ρ * ) so as to treat the profile shear stabilization and nonlocal effects which can break gyroBohm scaling. The code operates in either a cyclic flux-tube limit (which allows only gyroBohm scaling) or a globally with physical profile variation. Rohm scaling of DIII-D L-mode has been simulated with power flows matching experiment within error bars on the ion temperature gradient. Mechanisms for broken gyroBohm scaling, neoclassical ion flows embedded in turbulence, turbulent dynamos and profile corrugations, plasma pinches and impurity flow, and simulations at fixed flow rather than fixed gradient are illustrated and discussed
Zhang, Hua; Kurgan, Lukasz
2014-12-01
Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.
International Nuclear Information System (INIS)
Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina
2009-01-01
Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R 2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R 2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.
A 3D gyrokinetic particle-in-cell simulation of fusion plasma microturbulence on parallel computers
Williams, T. J.
1992-12-01
One of the grand challenge problems now supported by HPCC is the Numerical Tokamak Project. A goal of this project is the study of low-frequency micro-instabilities in tokamak plasmas, which are believed to cause energy loss via turbulent thermal transport across the magnetic field lines. An important tool in this study is gyrokinetic particle-in-cell (PIC) simulation. Gyrokinetic, as opposed to fully-kinetic, methods are particularly well suited to the task because they are optimized to study the frequency and wavelength domain of the microinstabilities. Furthermore, many researchers now employ low-noise delta(f) methods to greatly reduce statistical noise by modelling only the perturbation of the gyrokinetic distribution function from a fixed background, not the entire distribution function. In spite of the increased efficiency of these improved algorithms over conventional PIC algorithms, gyrokinetic PIC simulations of tokamak micro-turbulence are still highly demanding of computer power--even fully-vectorized codes on vector supercomputers. For this reason, we have worked for several years to redevelop these codes on massively parallel computers. We have developed 3D gyrokinetic PIC simulation codes for SIMD and MIMD parallel processors, using control-parallel, data-parallel, and domain-decomposition message-passing (DDMP) programming paradigms. This poster summarizes our earlier work on codes for the Connection Machine and BBN TC2000 and our development of a generic DDMP code for distributed-memory parallel machines. We discuss the memory-access issues which are of key importance in writing parallel PIC codes, with special emphasis on issues peculiar to gyrokinetic PIC. We outline the domain decompositions in our new DDMP code and discuss the interplay of different domain decompositions suited for the particle-pushing and field-solution components of the PIC algorithm.
Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J
2014-08-27
State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients. In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study. Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.
International Nuclear Information System (INIS)
Burr, T.L.
1994-04-01
This report is a primer on the analysis of both linear and nonlinear time series with applications in nuclear safeguards and nonproliferation. We analyze eight simulated and two real time series using both linear and nonlinear modeling techniques. The theoretical treatment is brief but references to pertinent theory are provided. Forecasting is our main goal. However, because our most common approach is to fit models to the data, we also emphasize checking model adequacy by analyzing forecast errors for serial correlation or nonconstant variance
Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David
2017-10-01
Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.
Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo
2017-09-01
Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.
Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga
2006-08-01
A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.
Directory of Open Access Journals (Sweden)
Luis Gonzaga Baca Ruiz
2016-08-01
Full Text Available This paper addresses the problem of energy consumption prediction using neural networks over a set of public buildings. Since energy consumption in the public sector comprises a substantial share of overall consumption, the prediction of such consumption represents a decisive issue in the achievement of energy savings. In our experiments, we use the data provided by an energy consumption monitoring system in a compound of faculties and research centers at the University of Granada, and provide a methodology to predict future energy consumption using nonlinear autoregressive (NAR and the nonlinear autoregressive neural network with exogenous inputs (NARX, respectively. Results reveal that NAR and NARX neural networks are both suitable for performing energy consumption prediction, but also that exogenous data may help to improve the accuracy of predictions.
High-performance small-scale solvers for linear Model Predictive Control
DEFF Research Database (Denmark)
Frison, Gianluca; Sørensen, Hans Henrik Brandenborg; Dammann, Bernd
2014-01-01
, with the two main research areas of explicit MPC and tailored on-line MPC. State-of-the-art solvers in this second class can outperform optimized linear-algebra libraries (BLAS) only for very small problems, and do not explicitly exploit the hardware capabilities, relying on compilers for that. This approach...
Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Chapman, Robin S.; Hesketh, Linda J.; Kistler, Doris J.
2002-01-01
Longitudinal change in syntax comprehension and production skill, measured over six years, was modeled in 31 individuals (ages 5-20) with Down syndrome. The best fitting Hierarchical Linear Modeling model of comprehension uses age and visual and auditory short-term memory as predictors of initial status, and age for growth trajectory. (Contains…
Eric J. Gustafson; L. Jay Roberts; Larry A. Leefers
2006-01-01
Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (...
Gyrokinetic analysis of ion temperature gradient modes in the presence of sheared flows
International Nuclear Information System (INIS)
Artun, M.; Tang, W.M.
1992-01-01
The linearized gyrokinetic equation governing electrostatic microinstabilities in the presence of sheared equilibrium flow in both the z and y directions has been systematically derived for a sheared slab geometry, where in the large aspect ratio limit z and y directions correspond to the toroidal and poloidal directions respectively. In the familiar long perpendicular wavelength regime (κ perpendicular ρi > 1), the analysis leads to a comprehensive kinetic differential eigenmode equation which is solved numerically. The numerical results have been successfully cross-checked against analytic estimates in the fluid limit. For typical conditions, the Ion Temperature Gradient (ηi) modes are found to be stabilized for y-direction flows with a velocity shear scale comparable to that of the ion temperature gradient and velocities of a few percent of the sound speed. Sheared flows in the z-direction taken along are usually destabilizing, with the effect being independent of the sign of the flow. However, when both types are simultaneously considered, it is found that in the presence of shared z-direction flow, sheared y-direction flow can be either stabilizing or destabilizing depending on the relative sign of these flows. However, for sufficiently large values of υ' y the mode is completely stabilized regardless of the sign of υ' z υ' y . The importance of a proper kinetic treatment of this problem is supported by comparisons with fluid estimates. In particular, when such effects are favorable, significantly smaller values of sheared y-direction flow are required for stability than fluid estimates would indicate
DEFF Research Database (Denmark)
Rohde, Palle Duun; Demontis, Ditte; Børglum, Anders
is enriched for causal variants. Here we apply the GFBLUP model to a small schizophrenia case-control study to test the promise of this model on psychiatric disorders, and hypothesize that the performance will be increased when applying the model to a larger ADHD case-control study if the genomic feature...... contains the causal variants. Materials and Methods: The schizophrenia study consisted of 882 controls and 888 schizophrenia cases genotyped for 520,000 SNPs. The ADHD study contained 25,954 controls and 16,663 ADHD cases with 8,4 million imputed genotypes. Results: The predictive ability for schizophrenia.......6% for the null model). Conclusion: The improvement in predictive ability for schizophrenia was marginal, however, greater improvement is expected for the larger ADHD data....
A linear regression model for predicting PNW estuarine temperatures in a changing climate
Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...
2017-10-01
ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID PROPELLANT GRAIN GEOMETRIES Brian...distribution is unlimited. AD U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER Munitions Engineering Technology Center Picatinny...U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID
Interaction between the neoclassical equilibrium and microturbulence in gyrokinetic simulations
Energy Technology Data Exchange (ETDEWEB)
Oberparleiter, Michael
2015-07-10
For the application of the nuclear fusion of hydrogen as a heat source for electricity generation understanding of the magnetic fuel confinement is crucial. Most of the cross-field transport in modern-day tokamaks is carried by turbulence driven by steep pressure gradients. Background neoclassical transport, however, provides a steady level of cross-field flux even in cases when turbulence becomes weak or suppressed. The goal of this work is to quantify how neoclassical (NC) effects and turbulence can influence each other. For this purpose the nonlinear gyrokinetic turbulence code GENE is employed. Firstly, its ability to self-consistently calculate the NC radial electric field is successfully benchmarked against the radial force balance equation and NC transport in the plasma region close to the center of a tokamak is studied. In the next step a model system where a long-wavelength external potential is imposed on ion temperature gradient-driven (ITG) turbulence is investigated. It is found that the self-generated shear flow pattern of the turbulence adapts to the imposed pattern and a small external shear is sufficient to notably reduce turbulent transport. Motivated by this global ITG simulations with fixed pressure gradient profiles are performed with and without inclusion of NC effects. Their comparison reveals that the NC field enhances turbulent transport by 20-30 % for a ratio of ion gyroradius and device radius larger than 1/300. An explanation is that the NC field aligns a region of low shear with the maximum of the gradient profile where the turbulent drive is strongest. Further investigation reveals that NC effects also change the dependence of the system on collisionality or safety factor. Finally, in physically more comprehensive simulations with fixed power input and a self-consistently evolving temperature profile, the additional NC transport channel is found to reduce the frequency and amplitude of intermittent turbulent transport bursts.
HPC parallel programming model for gyrokinetic MHD simulation
International Nuclear Information System (INIS)
Naitou, Hiroshi; Yamada, Yusuke; Tokuda, Shinji; Ishii, Yasutomo; Yagi, Masatoshi
2011-01-01
The 3-dimensional gyrokinetic PIC (particle-in-cell) code for MHD simulation, Gpic-MHD, was installed on SR16000 (“Plasma Simulator”), which is a scalar cluster system consisting of 8,192 logical cores. The Gpic-MHD code advances particle and field quantities in time. In order to distribute calculations over large number of logical cores, the total simulation domain in cylindrical geometry was broken up into N DD-r × N DD-z (number of radial decomposition times number of axial decomposition) small domains including approximately the same number of particles. The axial direction was uniformly decomposed, while the radial direction was non-uniformly decomposed. N RP replicas (copies) of each decomposed domain were used (“particle decomposition”). The hybrid parallelization model of multi-threads and multi-processes was employed: threads were parallelized by the auto-parallelization and N DD-r × N DD-z × N RP processes were parallelized by MPI (message-passing interface). The parallelization performance of Gpic-MHD was investigated for the medium size system of N r × N θ × N z = 1025 × 128 × 128 mesh with 4.196 or 8.192 billion particles. The highest speed for the fixed number of logical cores was obtained for two threads, the maximum number of N DD-z , and optimum combination of N DD-r and N RP . The observed optimum speeds demonstrated good scaling up to 8,192 logical cores. (author)
Bogachev, Mikhail I.; Bunde, Armin
2011-06-01
We study the predictability of extreme events in records with linear and nonlinear long-range memory in the presence of additive white noise using two different approaches: (i) the precursory pattern recognition technique (PRT) that exploits solely the information about short-term precursors, and (ii) the return interval approach (RIA) that exploits long-range memory incorporated in the elapsed time after the last extreme event. We find that the PRT always performs better when only linear memory is present. In the presence of nonlinear memory, both methods demonstrate comparable efficiency in the absence of white noise. When additional white noise is present in the record (which is the case in most observational records), the efficiency of the PRT decreases monotonously with increasing noise level. In contrast, the RIA shows an abrupt transition between a phase of low level noise where the prediction is as good as in the absence of noise, and a phase of high level noise where the prediction becomes poor. In the phase of low and intermediate noise the RIA predicts considerably better than the PRT, which explains our recent findings in physiological and financial records.
On the Use of Linearized Euler Equations in the Prediction of Jet Noise
Mankbadi, Reda R.; Hixon, R.; Shih, S.-H.; Povinelli, L. A.
1995-01-01
Linearized Euler equations are used to simulate supersonic jet noise generation and propagation. Special attention is given to boundary treatment. The resulting solution is stable and nearly free from boundary reflections without the need for artificial dissipation, filtering, or a sponge layer. The computed solution is in good agreement with theory and observation and is much less CPU-intensive as compared to large-eddy simulations.
Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei
2017-09-25
It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).
Multi input single output model predictive control of non-linear bio-polymerization process
Energy Technology Data Exchange (ETDEWEB)
Arumugasamy, Senthil Kumar; Ahmad, Z. [School of Chemical Engineering, Univerisiti Sains Malaysia, Engineering Campus, Seri Ampangan,14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)
2015-05-15
This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.
Zhou, L; Lund, M S; Wang, Y; Su, G
2014-08-01
This study investigated genomic predictions across Nordic Holstein and Nordic Red using various genomic relationship matrices. Different sources of information, such as consistencies of linkage disequilibrium (LD) phase and marker effects, were used to construct the genomic relationship matrices (G-matrices) across these two breeds. Single-trait genomic best linear unbiased prediction (GBLUP) model and two-trait GBLUP model were used for single-breed and two-breed genomic predictions. The data included 5215 Nordic Holstein bulls and 4361 Nordic Red bulls, which was composed of three populations: Danish Red, Swedish Red and Finnish Ayrshire. The bulls were genotyped with 50 000 SNP chip. Using the two-breed predictions with a joint Nordic Holstein and Nordic Red reference population, accuracies increased slightly for all traits in Nordic Red, but only for some traits in Nordic Holstein. Among the three subpopulations of Nordic Red, accuracies increased more for Danish Red than for Swedish Red and Finnish Ayrshire. This is because closer genetic relationships exist between Danish Red and Nordic Holstein. Among Danish Red, individuals with higher genomic relationship coefficients with Nordic Holstein showed more increased accuracies in the two-breed predictions. Weighting the two-breed G-matrices by LD phase consistencies, marker effects or both did not further improve accuracies of the two-breed predictions. © 2014 Blackwell Verlag GmbH.
Albajes-Eizagirre, Anton; Romero, Laia; Soria-Frisch, Aureli; Vanhellemont, Quinten
2011-11-01
Impact of jellyfish in human activities has been increasingly reported worldwide in recent years. Segments such as tourism, water sports and leisure, fisheries and aquaculture are commonly damaged when facing blooms of gelatinous zooplankton. Hence the prediction of the appearance and disappearance of jellyfish in our coasts, which is not fully understood from its biological point of view, has been approached as a pattern recognition problem in the paper presented herein, where a set of potential ecological cues was selected to test their usefulness for prediction. Remote sensing data was used to describe environmental conditions that could support the occurrence of jellyfish blooms with the aim of capturing physical-biological interactions: forcing, coastal morphology, food availability, and water mass characteristics are some of the variables that seem to exert an effect on jellyfish accumulation on the shoreline, under specific spatial and temporal windows. A data-driven model based on computational intelligence techniques has been designed and implemented to predict jellyfish events on the beach area as a function of environmental conditions. Data from 2009 over the NW Mediterranean continental shelf have been used to train and test this prediction protocol. Standard level 2 products are used from MODIS (NASA OceanColor) and MERIS (ESA - FRS data). The procedure for designing the analysis system can be described as following. The aforementioned satellite data has been used as feature set for the performance evaluation. Ground truth has been extracted from visual observations by human agents on different beach sites along the Catalan area. After collecting the evaluation data set, the performance between different computational intelligence approaches have been compared. The outperforming one in terms of its generalization capability has been selected for prediction recall. Different tests have been conducted in order to assess the prediction capability of the
Three dimensional force prediction in a model linear brushless dc motor
Energy Technology Data Exchange (ETDEWEB)
Moghani, J.S.; Eastham, J.F.; Akmese, R.; Hill-Cottingham, R.J. (Univ. of Bath (United Kingdom). School of Electronic and Electric Engineering)
1994-11-01
Practical results are presented for the three axes forces produced on the primary of a linear brushless dc machine which is supplied from a three-phase delta-modulated inverter. Conditions of both lateral alignment and lateral displacement are considered. Finite element analysis using both two and three dimensional modeling is compared with the practical results. It is shown that a modified two dimensional model is adequate, where it can be used, in the aligned position and that the full three dimensional method gives good results when the machine is axially misaligned.
Directory of Open Access Journals (Sweden)
Drzewiecki Wojciech
2016-12-01
Full Text Available In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques.
A minimal collision operator for implementing neoclassical transport in gyrokinetic simulations
International Nuclear Information System (INIS)
Garbet, X.; Dif-Pradalier, G.; Nguyen, C.; Angelino, P.; Sarazin, Y.; Grandgirard, V.; Ghendrih, P.; Samain, A.
2008-01-01
This paper presents a class of collision operators, which reproduce neoclassical transport and comply with the constraints of a full-f global gyrokinetic code. The assessment of these operators is based on a variational entropy method, which allows a fast calculation of the neoclassical diffusivity and poloidal velocity.
International Nuclear Information System (INIS)
Lee, W.W.
2003-01-01
Particle simulation has played an important role for the recent investigations on turbulence in magnetically confined plasmas. In this paper, theoretical and numerical properties of a gyrokinetic plasma as well as its relationship with magnetohydrodynamics (MHD) are discussed with the ultimate aim of simulating microturbulence in transport time scale using massively parallel computers
Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X
2016-09-01
The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.
Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.
2010-01-01
Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.
Merlo, G.; Brunner, S.; Huang, Z.; Coda, S.; Görler, T.; Villard, L.; Bañón Navarro, A.; Dominski, J.; Fontana, M.; Jenko, F.; Porte, L.; Told, D.
2018-03-01
Axisymmetric (n = 0) density fluctuations measured in the TCV tokamak are observed to possess a frequency f 0 which is either varying (radially dispersive oscillations) or a constant over a large fraction of the plasma minor radius (radially global oscillations) as reported in a companion paper (Z Huang et al, this issue). Given that f 0 scales with the sound speed and given the poloidal structure of density fluctuations, these oscillations were interpreted as Geodesic Acoustic Modes, even though f 0 is in fact smaller than the local linear GAM frequency {f}{GAM}. In this work we employ the Eulerian gyrokinetic code GENE to simulate TCV relevant conditions and investigate the nature and properties of these oscillations, in particular their relation to the safety factor profile. Local and global simulations are carried out and a good qualitative agreement is observed between experiments and simulations. By varying also the plasma temperature and density profiles, we conclude that a variation of the edge safety factor alone is not sufficient to induce a transition from global to radially inhomogeneous oscillations, as was initially suggested by experimental results. This transition appears instead to be the combined result of variations in the different plasma profiles, collisionality and finite machine size effects. Simulations also show that radially global GAM-like oscillations can be observed in all fluxes and fluctuation fields, suggesting that they are the result of a complex nonlinear process involving also finite toroidal mode numbers and not just linear global GAM eigenmodes.
Christiansen, Bo
2015-04-01
Linear regression methods are without doubt the most used approaches to describe and predict data in the physical sciences. They are often good first order approximations and they are in general easier to apply and interpret than more advanced methods. However, even the properties of univariate regression can lead to debate over the appropriateness of various models as witnessed by the recent discussion about climate reconstruction methods. Before linear regression is applied important choices have to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. We seek to give a unified probabilistic - Bayesian with flat priors - treatment of univariate linear regression and prediction by taking, as starting point, the general errors-in-variables model (Christiansen, J. Clim., 27, 2014-2031, 2014). Other versions of linear regression can be obtained as limits of this model. We derive the likelihood of the model parameters and predictands of the general errors-in-variables model by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The well known unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference can not be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. We also include a probabilistic version of classical calibration and show how it is related to the errors-in-variables model. The results are illustrated by an example from the coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter.
Directory of Open Access Journals (Sweden)
Sharad Shandilya
Full Text Available The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR, rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals.Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA technique.358 defibrillations were evaluated (218 unsuccessful and 140 successful. Non-linear properties (Lyapunov exponent > 0 of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity outperformed AMSA (53.6% sensitivity. At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity.At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations
Czech Academy of Sciences Publication Activity Database
Pčolka, M.; Žáčeková, E.; Robinett, R.; Čelikovský, Sergej; Šebek, M.
2016-01-01
Roč. 53, č. 1 (2016), s. 124-138 ISSN 0967-0661 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Model predictive control * Identification for control * Building climatecontrol Subject RIV: BC - Control Systems Theory Impact factor: 2.602, year: 2016 http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf
Prediction of high airway pressure using a non-linear autoregressive model of pulmonary mechanics.
Langdon, Ruby; Docherty, Paul D; Schranz, Christoph; Chase, J Geoffrey
2017-11-02
For mechanically ventilated patients with acute respiratory distress syndrome (ARDS), suboptimal PEEP levels can cause ventilator induced lung injury (VILI). In particular, high PEEP and high peak inspiratory pressures (PIP) can cause over distension of alveoli that is associated with VILI. However, PEEP must also be sufficient to maintain recruitment in ARDS lungs. A lung model that accurately and precisely predicts the outcome of an increase in PEEP may allow dangerous high PIP to be avoided, and reduce the incidence of VILI. Sixteen pressure-flow data sets were collected from nine mechanically ventilated ARDs patients that underwent one or more recruitment manoeuvres. A nonlinear autoregressive (NARX) model was identified on one or more adjacent PEEP steps, and extrapolated to predict PIP at 2, 4, and 6 cmH 2 O PEEP horizons. The analysis considered whether the predicted and measured PIP exceeded a threshold of 40 cmH 2 O. A direct comparison of the method was made using the first order model of pulmonary mechanics (FOM(I)). Additionally, a further, more clinically appropriate method for the FOM was tested, in which the FOM was trained on a single PEEP prior to prediction (FOM(II)). The NARX model exhibited very high sensitivity (> 0.96) in all cases, and a high specificity (> 0.88). While both FOM methods had a high specificity (> 0.96), the sensitivity was much lower, with a mean of 0.68 for FOM(I), and 0.82 for FOM(II). Clinically, false negatives are more harmful than false positives, as a high PIP may result in distension and VILI. Thus, the NARX model may be more effective than the FOM in allowing clinicians to reduce the risk of applying a PEEP that results in dangerously high airway pressures.
Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O
2016-06-01
The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.
International Nuclear Information System (INIS)
Huo, Pengfei; Miller, Thomas F. III; Coker, David F.
2013-01-01
A partial linearized path integral approach is used to calculate the condensed phase electron transfer (ET) rate by directly evaluating the flux-flux/flux-side quantum time correlation functions. We demonstrate for a simple ET model that this approach can reliably capture the transition between non-adiabatic and adiabatic regimes as the electronic coupling is varied, while other commonly used semi-classical methods are less accurate over the broad range of electronic couplings considered. Further, we show that the approach reliably recovers the Marcus turnover as a function of thermodynamic driving force, giving highly accurate rates over four orders of magnitude from the normal to the inverted regimes. We also demonstrate that the approach yields accurate rate estimates over five orders of magnitude of inverse temperature. Finally, the approach outlined here accurately captures the electronic coherence in the flux-flux correlation function that is responsible for the decreased rate in the inverted regime
Directory of Open Access Journals (Sweden)
Ririn Kusumawati
2016-05-01
In the classification, using Hidden Markov Model, voice signal is analyzed and searched the maximum possible value that can be recognized. The modeling results obtained parameters are used to compare with the sound of Arabic speakers. From the test results' Classification, Hidden Markov Models with Linear Predictive Coding extraction average accuracy of 78.6% for test data sampling frequency of 8,000 Hz, 80.2% for test data sampling frequency of 22050 Hz, 79% for frequencies sampling test data at 44100 Hz.
International Nuclear Information System (INIS)
Sharma, P.; Khare, M.
2000-01-01
Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box-Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India. (author)
International Nuclear Information System (INIS)
Waltz, R. E.; Candy, J.; Fahey, M.
2007-01-01
Electron temperature gradient (ETG) transport is conventionally defined as the electron energy transport at high wave number (high-k) where ions are adiabatic and there can be no ion energy or plasma transport. Previous gyrokinetic simulations have assumed adiabatic ions (ETG-ai) and work on the small electron gyroradius scale. However such ETG-ai simulations with trapped electrons often do not have well behaved nonlinear saturation unless fully kinetic ions (ki) and proper ion scale zonal flow modes are included. Electron energy transport is separated into ETG-ki at high-k and ion temperature gradient-trapped electron mode (ITG/TEM) at low-k. Expensive (more computer-intensive), high-resolution, large-ion-scale flux-tube simulations coupling ITG/TEM and ETG-ki turbulence are presented. These require a high effective Reynolds number R≡[k(max)/k(min)] 2 =μ 2 , where μ=[ρ si /ρ si ] is the ratio of ion to electron gyroradii. Compute times scale faster than μ 3 . By comparing the coupled expensive simulations with (1) much cheaper (less compute-intensive), uncoupled, high-resolution, small, flux-tube ETG-ki and with (2) uncoupled low-resolution, large, flux-tube ITG/TEM simulations, and also by artificially turning ''off'' the low-k or high-k drives, it appears that ITG/TEM and ETG-ki transport are not strongly coupled so long as ETG-ki can access some nonadiabatic ion scale zonal flows and both high-k and low-k are linearly unstable. However expensive coupled simulations are required for physically accurate k-spectra of the transport and turbulence. Simulations with μ≥30 appear to represent the physical range μ>40. ETG-ki transport measured in ion gyro-Bohm units is weakly dependent on μ. For the mid-radius core tokamak plasma parameters studied, ETG-ki is about 10% of the electron energy transport, which in turn is about 30% of the total energy transport (with negligible ExB shear). However at large ExB shear sufficient to quench the low-k ITG
DEFF Research Database (Denmark)
Møldrup, Per; Chamindu, T. K. K. Deepagoda; Hamamoto, S.
2013-01-01
The soil-gas diffusion is a primary driver of transport, reactions, emissions, and uptake of vadose zone gases, including oxygen, greenhouse gases, fumigants, and spilled volatile organics. The soil-gas diffusion coefficient, Dp, depends not only on soil moisture content, texture, and compaction...... but also on the local-scale variability of these. Different predictive models have been developed to estimate Dp in intact and repacked soil, but clear guidelines for model choice at a given soil state are lacking. In this study, the water-induced linear reduction (WLR) model for repacked soil is made...... air) in repacked soils containing between 0 and 54% clay. With Cm = 2.1, the SWLR model on average gave excellent predictions for 290 intact soils, performing well across soil depths, textures, and compactions (dry bulk densities). The SWLR model generally outperformed similar, simple Dp/Do models...
A Family of High-Performance Solvers for Linear Model Predictive Control
DEFF Research Database (Denmark)
Frison, Gianluca; Sokoler, Leo Emil; Jørgensen, John Bagterp
2014-01-01
In Model Predictive Control (MPC), an optimization problem has to be solved at each sampling time, and this has traditionally limited the use of MPC to systems with slow dynamic. In this paper, we propose an e_cient solution strategy for the unconstrained sub-problems that give the search......-direction in Interior-Point (IP) methods for MPC, and that usually are the computational bottle-neck. This strategy combines a Riccati-like solver with the use of high-performance computing techniques: in particular, in this paper we explore the performance boost given by the use of single precision computation...
International Nuclear Information System (INIS)
Lee, Jae Yong; Na, Man Gyun
2011-01-01
Diametral creep of the pressure tube (PT) is one of the principal aging mechanisms governing the heat transfer and hydraulic degradation of a heat transport system. PT diametral creep leads to diametral expansion that affects the thermal hydraulic characteristics of the coolant channels and the critical heat flux. Therefore, it is essential to predict the PT diametral creep in CANDU reactors, which is caused mainly by fast neutron irradiation, reactor coolant temperature and so forth. The currently used PT diametral creep prediction model considers the complex interactions between the effects of temperature and fast neutron flux on the deformation of PT zirconium alloys. The model assumes that long-term steady-state deformation consists of separable, additive components from thermal creep, irradiation creep and irradiation growth. This is a mechanistic model based on measured data. However, this model has high prediction uncertainty. Recently, a statistical error modeling method was developed using plant inspection data from the Bruce B CANDU reactor. The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict PT diametral creep employing previously measured PT diameters and HTS operating conditions. There are twelve bundles in a fuel channel and for each bundle, a linear model was developed by using the dependent variables, such as the fast neutron fluxes and the bundle temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3 and 4 were used to develop the BPLM models. The remaining 10 channels' data were used to test the developed BPLM models. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from the Units 2,3 and 4 in Korea. Two error components for the BPLM, which are the epistemic
Directory of Open Access Journals (Sweden)
M. Khamforoush
2009-12-01
Full Text Available Anew and effective electrospinning method has been developed for producing aligned polymer nanofibers. The conventional electrospinning technique has been modified to fabricate nanofibers as uniaxially aligned array. The key to the success of this technique is the creation of a rotating jet by using a cylindrical collector in which the needle tip is located at its center. The unique advantage of this method among the current methods is the ability of apparatus to weave continuously nanofibers in uniaxially aligned form. Fibers produced by this method are well-aligned, with several meters in length, and can be spread over a large area. We have employed a voltage range of (6-16 kV, a collector diameter in the range of 20-50 cm and various concentrations of PAN solutions ranging from 15 wt% to 19 wt %. The electrospun nanofibers could be conveniently formed onto the surface of any thin substrate such as glass sampling plate for subsequent treatments and other applications. Therefore, the linear speed of electrospinning process is determined experimentally as a function of cylindrical collector diameter, polymer concentration and field potential difference.
International Nuclear Information System (INIS)
Leerink, S.; Heikkinen, J. A.; Janhunen, S. J.; Kiviniemi, T. P.; Nora, M.; Ogando, F.
2008-01-01
The ELMFIRE gyrokinetic simulation code has been used to perform full f simulations of the FT-2 tokamak. The dynamics of the radial electric field and the creation of poloidal velocity in the presence of turbulence are presented.
Directory of Open Access Journals (Sweden)
Alessandra Bianchin
Full Text Available The purpose of this study was to investigate the blood stage of the malaria causing parasite, Plasmodium falciparum, to predict potential protein interactions between the parasite merozoite and the host erythrocyte and design peptides that could interrupt these predicted interactions. We screened the P. falciparum and human proteomes for computationally predicted short linear motifs (SLiMs in cytoplasmic portions of transmembrane proteins that could play roles in the invasion of the erythrocyte by the merozoite, an essential step in malarial pathogenesis. We tested thirteen peptides predicted to contain SLiMs, twelve of them palmitoylated to enhance membrane targeting, and found three that blocked parasite growth in culture by inhibiting the initiation of new infections in erythrocytes. Scrambled peptides for two of the most promising peptides suggested that their activity may be reflective of amino acid properties, in particular, positive charge. However, one peptide showed effects which were stronger than those of scrambled peptides. This was derived from human red blood cell glycophorin-B. We concluded that proteome-wide computational screening of the intracellular regions of both host and pathogen adhesion proteins provides potential lead peptides for the development of anti-malarial compounds.
Tang, Zaixiang; Shen, Yueping; Li, Yan; Zhang, Xinyan; Wen, Jia; Qian, Chen'ao; Zhuang, Wenzhuo; Shi, Xinghua; Yi, Nengjun
2018-03-15
Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). nyi@uab.edu. Supplementary data are available at Bioinformatics online.
Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes.
Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul
2018-04-05
In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90-94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.
McDowell, J. J; Wood, Helena M.
1985-01-01
Four human subjects worked on all combinations of five variable-interval schedules and five reinforcer magnitudes (¢/reinforcer) in each of two phases of the experiment. In one phase the force requirement on the operandum was low (1 or 11 N) and in the other it was high (25 or 146 N). Estimates of Herrnstein's κ were obtained at each reinforcer magnitude. The results were: (1) response rate was more sensitive to changes in reinforcement rate at the high than at the low force requirement, (2) κ increased from the beginning to the end of the magnitude range for all subjects at both force requirements, (3) the reciprocal of κ was a linear function of the reciprocal of reinforcer magnitude for seven of the eight data sets, and (4) the rate of change of κ was greater at the high than at the low force requirement by an order of magnitude or more. The second and third findings confirm predictions made by linear system theory, and replicate the results of an earlier experiment (McDowell & Wood, 1984). The fourth finding confirms a further prediction of the theory and supports the theory's interpretation of conflicting data on the constancy of Herrnstein's κ. PMID:16812408
McDowell, J J; Wood, H M
1985-01-01
Four human subjects worked on all combinations of five variable-interval schedules and five reinforcer magnitudes ( cent/reinforcer) in each of two phases of the experiment. In one phase the force requirement on the operandum was low (1 or 11 N) and in the other it was high (25 or 146 N). Estimates of Herrnstein's kappa were obtained at each reinforcer magnitude. The results were: (1) response rate was more sensitive to changes in reinforcement rate at the high than at the low force requirement, (2) kappa increased from the beginning to the end of the magnitude range for all subjects at both force requirements, (3) the reciprocal of kappa was a linear function of the reciprocal of reinforcer magnitude for seven of the eight data sets, and (4) the rate of change of kappa was greater at the high than at the low force requirement by an order of magnitude or more. The second and third findings confirm predictions made by linear system theory, and replicate the results of an earlier experiment (McDowell & Wood, 1984). The fourth finding confirms a further prediction of the theory and supports the theory's interpretation of conflicting data on the constancy of Herrnstein's kappa.
Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A
2016-03-01
In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Luigi Capoferri
Full Text Available Prediction of human Cytochrome P450 (CYP binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD simulations and Linear Interaction Energy (LIE theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE of 4.1 kJ mol-1 and a standard error in prediction (SDEP in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units.
Directory of Open Access Journals (Sweden)
Deborah Apthorp
Full Text Available Visually-induced illusions of self-motion (vection can be compelling for some people, but they are subject to large individual variations in strength. Do these variations depend, at least in part, on the extent to which people rely on vision to maintain their postural stability? We investigated by comparing physical posture measures to subjective vection ratings. Using a Bertec balance plate in a brightly-lit room, we measured 13 participants' excursions of the centre of foot pressure (CoP over a 60-second period with eyes open and with eyes closed during quiet stance. Subsequently, we collected vection strength ratings for large optic flow displays while seated, using both verbal ratings and online throttle measures. We also collected measures of postural sway (changes in anterior-posterior CoP in response to the same visual motion stimuli while standing on the plate. The magnitude of standing sway in response to expanding optic flow (in comparison to blank fixation periods was predictive of both verbal and throttle measures for seated vection. In addition, the ratio between eyes-open and eyes-closed CoP excursions during quiet stance (using the area of postural sway significantly predicted seated vection for both measures. Interestingly, these relationships were weaker for contracting optic flow displays, though these produced both stronger vection and more sway. Next we used a non-linear analysis (recurrence quantification analysis, RQA of the fluctuations in anterior-posterior position during quiet stance (both with eyes closed and eyes open; this was a much stronger predictor of seated vection for both expanding and contracting stimuli. Given the complex multisensory integration involved in postural control, our study adds to the growing evidence that non-linear measures drawn from complexity theory may provide a more informative measure of postural sway than the conventional linear measures.
A model for preemptive maintenance of medical linear accelerators—predictive maintenance
International Nuclear Information System (INIS)
Able, Charles M.; Baydush, Alan H.; Nguyen, Callistus; Gersh, Jacob; Ndlovu, Alois; Rebo, Igor; Booth, Jeremy; Perez, Mario; Sintay, Benjamin; Munley, Michael T.
2016-01-01
Unscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks. The proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. There are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid ) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid ). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty
A Non-linear Predictive Model of Borderline Personality Disorder Based on Multilayer Perceptron.
Maldonato, Nelson M; Sperandeo, Raffaele; Moretto, Enrico; Dell'Orco, Silvia
2018-01-01
Borderline Personality Disorder is a serious mental disease, classified in Cluster B of DSM IV-TR personality disorders. People with this syndrome presents an anamnesis of traumatic experiences and shows dissociative symptoms. Since not all subjects who have been victims of trauma develop a Borderline Personality Disorder, the emergence of this serious disease seems to have the fragility of character as a predisposing condition. Infect, numerous studies show that subjects positive for diagnosis of Borderline Personality Disorder had scores extremely high or extremely low to some temperamental dimensions (harm Avoidance and reward dependence) and character dimensions (cooperativeness and self directedness). In a sample of 602 subjects, who have had consecutive access to an Outpatient Mental Health Service, it was evaluated the presence of Borderline Personality Disorder using the semi-structured interview for the DSM IV-TR personality disorders. In this population we assessed the presence of dissociative symptoms with the Dissociative Experiences Scale and the personality traits with the Temperament and Character Inventory developed by Cloninger. To assess the weight and the predictive value of these psychopathological dimensions in relation to the Borderline Personality Disorder diagnosis, a neural network statistical model called "multilayer perceptron," was implemented. This model was developed with a dichotomous dependent variable, consisting in the presence or absence of the diagnosis of borderline personality disorder and with five covariates. The first one is the taxonomic subscale of dissociative experience scale, the others are temperamental and characterial traits: Novelty-Seeking, Harm-Avoidance, Self-Directedness and Cooperativeness. The statistical model, that results satisfactory, showed a significance capacity (89%) to predict the presence of borderline personality disorder. Furthermore, the dissociative symptoms seem to have a greater influence than
A Non-linear Predictive Model of Borderline Personality Disorder Based on Multilayer Perceptron
Directory of Open Access Journals (Sweden)
Nelson M. Maldonato
2018-04-01
Full Text Available Borderline Personality Disorder is a serious mental disease, classified in Cluster B of DSM IV-TR personality disorders. People with this syndrome presents an anamnesis of traumatic experiences and shows dissociative symptoms. Since not all subjects who have been victims of trauma develop a Borderline Personality Disorder, the emergence of this serious disease seems to have the fragility of character as a predisposing condition. Infect, numerous studies show that subjects positive for diagnosis of Borderline Personality Disorder had scores extremely high or extremely low to some temperamental dimensions (harm Avoidance and reward dependence and character dimensions (cooperativeness and self directedness. In a sample of 602 subjects, who have had consecutive access to an Outpatient Mental Health Service, it was evaluated the presence of Borderline Personality Disorder using the semi-structured interview for the DSM IV-TR personality disorders. In this population we assessed the presence of dissociative symptoms with the Dissociative Experiences Scale and the personality traits with the Temperament and Character Inventory developed by Cloninger. To assess the weight and the predictive value of these psychopathological dimensions in relation to the Borderline Personality Disorder diagnosis, a neural network statistical model called “multilayer perceptron,” was implemented. This model was developed with a dichotomous dependent variable, consisting in the presence or absence of the diagnosis of borderline personality disorder and with five covariates. The first one is the taxonomic subscale of dissociative experience scale, the others are temperamental and characterial traits: Novelty-Seeking, Harm-Avoidance, Self-Directedness and Cooperativeness. The statistical model, that results satisfactory, showed a significance capacity (89% to predict the presence of borderline personality disorder. Furthermore, the dissociative symptoms seem to have a
A model for preemptive maintenance of medical linear accelerators-predictive maintenance.
Able, Charles M; Baydush, Alan H; Nguyen, Callistus; Gersh, Jacob; Ndlovu, Alois; Rebo, Igor; Booth, Jeremy; Perez, Mario; Sintay, Benjamin; Munley, Michael T
2016-03-10
Unscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks. The proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. There are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty
Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.
2011-01-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques
International Nuclear Information System (INIS)
Rhodes, T.L.; Doyle, E.J.; Hillesheim, J.C.; Peebles, W.A.; Schmitz, L.; Holland, C.; Smith, S.P.; Burrell, K.H.; Candy, J.; DeBoo, J.C.; Kinsey, J.E.; Petty, C.C.; Prater, R.; Staebler, G.M.; Waltz, R.E.; White, A.E.; McKee, G.R.; Mikkelsen, D.; Parker, S.; Chen, Y.
2011-01-01
A series of carefully designed experiments on DIII-D have taken advantage of a broad set of turbulence and profile diagnostics to rigorously test gyrokinetic turbulence simulations. In this paper the goals, tools and experiments performed in these validation studies are reviewed and specific examples presented. It is found that predictions of transport and fluctuation levels in the mid-core region (0.4 < ρ < 0.75) are in better agreement with experiment than those in the outer region (ρ ≥ 0.75) where edge coupling effects may become increasingly important and multiscale simulations may also be necessary. Validation studies such as these are crucial in developing confidence in a first-principles based predictive capability for ITER.
Milquez-Sanabria, Harvey; Blanco-Cocom, Luis; Alzate-Gaviria, Liliana
2016-10-03
Agro-industrial wastes are an energy source for different industries. However, its application has not reached small industries. Previous and current research activities performed on the acidogenic phase of two-phase anaerobic digestion processes deal particularly with process optimization of the acid-phase reactors operating with a wide variety of substrates, both soluble and complex in nature. Mathematical models for anaerobic digestion have been developed to understand and improve the efficient operation of the process. At present, lineal models with the advantages of requiring less data, predicting future behavior and updating when a new set of data becomes available have been developed. The aim of this research was to contribute to the reduction of organic solid waste, generate biogas and develop a simple but accurate mathematical model to predict the behavior of the UASB reactor. The system was maintained separate for 14 days during which hydrolytic and acetogenic bacteria broke down onion waste, produced and accumulated volatile fatty acids. On this day, two reactors were coupled and the system continued for 16 days more. The biogas and methane yields and volatile solid reduction were 0.6 ± 0.05 m 3 (kg VS removed ) -1 , 0.43 ± 0.06 m 3 (kg VS removed ) -1 and 83.5 ± 9.8 %, respectively. The model application showed a good prediction of all process parameters defined; maximum error between experimental and predicted value was 1.84 % for alkalinity profile. A linear predictive adaptive model for anaerobic digestion of onion waste in a two-stage process was determined under batch-fed condition. Organic load rate (OLR) was maintained constant for the entire operation, modifying effluent hydrolysis reactor feed to UASB reactor. This condition avoids intoxication of UASB reactor and also limits external buffer addition.
International Nuclear Information System (INIS)
Saba, V.; Setayeshi, S.; Ghannadi-Maragheh, M.
2011-01-01
We have developed an algorithm for real-time detection and complete correction of the patient motion effects during single photon emission computed tomography. The algorithm is based on a linear prediction filter (LPC). The new prediction of projection data algorithm (PPDA) detects most motions-such as those of the head, legs, and hands-using comparison of the predicted and measured frame data. When the data acquisition for a specific frame is completed, the accuracy of the acquired data is evaluated by the PPDA. If patient motion is detected, the scanning procedure is stopped. After the patient rests in his or her true position, data acquisition is repeated only for the corrupted frame and the scanning procedure is continued. Various experimental data were used to validate the motion detection algorithm; on the whole, the proposed method was tested with approximately 100 test cases. The PPDA shows promising results. Using the PPDA enables us to prevent the scanner from collecting disturbed data during the scan and replaces them with motion-free data by real-time rescanning for the corrupted frames. As a result, the effects of patient motion is corrected in real time. (author)
International Nuclear Information System (INIS)
Lashmore-Davies, C.N.; Dendy, R.O.
1990-01-01
The gyrokinetic theory of ion cyclotron resonance is extended to include propagation at arbitrary angles to a straight equilibrium magnetic field with a linear perpendicular gradient in strength. The case of the compressional Alfven wave propagating in a D( 3 He) plasma is analyzed in detail, for arbitrary concentrations of the two species. A self-consistent local dispersion relation is obtained using a single mode description; this approach enables three-dimensional effects to be included and permits efficient calculation of the transmission coefficient. The dependence of this quantity on the species density ratio, minority temperature, plasma density, magnetic field and equilibrium scale length is obtained. A self-consistent treatment of the variation of the field polarization across the resonant region is included. Families of transmission curves are given as a function of the normalized parallel wave number for parameters relevant to Joint European Torus. Perpendicular absorption by the minority ions is also discussed, and shown to depend on a single parameter, the ratio of the ion thermal velocity to the Alfven speed. (author)
Directory of Open Access Journals (Sweden)
Paulino Pérez
2010-09-01
Full Text Available The availability of dense molecular markers has made possible the use of genomic selection in plant and animal breeding. However, models for genomic selection pose several computational and statistical challenges and require specialized computer programs, not always available to the end user and not implemented in standard statistical software yet. The R-package BLR (Bayesian Linear Regression implements several statistical procedures (e.g., Bayesian Ridge Regression, Bayesian LASSO in a unified framework that allows including marker genotypes and pedigree data jointly. This article describes the classes of models implemented in the BLR package and illustrates their use through examples. Some challenges faced when applying genomic-enabled selection, such as model choice, evaluation of predictive ability through cross-validation, and choice of hyper-parameters, are also addressed.
Fleming, David P.; Poplawski, J. V.
2002-01-01
Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus an accurate rotordynamic transient analysis requires bearing forces to be determined at each step of the transient solution. Analyses have been carried out to show the effect of accurate bearing transient forces (accounting for non-linear speed and load dependent bearing stiffness) as compared to conventional use of average rolling-element bearing stiffness. Bearing forces were calculated by COBRA-AHS (Computer Optimized Ball and Roller Bearing Analysis - Advanced High Speed) and supplied to the rotordynamics code ARDS (Analysis of Rotor Dynamic Systems) for accurate simulation of rotor transient behavior. COBRA-AHS is a fast-running 5 degree-of-freedom computer code able to calculate high speed rolling-element bearing load-displacement data for radial and angular contact ball bearings and also for cylindrical and tapered roller beatings. Results show that use of nonlinear bearing characteristics is essential for accurate prediction of rotordynamic behavior.
Yu, Donghai; Du, Ruobing; Xiao, Ji-Chang
2016-07-05
Ninety-six acidic phosphorus-containing molecules with pKa 1.88 to 6.26 were collected and divided into training and test sets by random sampling. Structural parameters were obtained by density functional theory calculation of the molecules. The relationship between the experimental pKa values and structural parameters was obtained by multiple linear regression fitting for the training set, and tested with the test set; the R(2) values were 0.974 and 0.966 for the training and test sets, respectively. This regression equation, which quantitatively describes the influence of structural parameters on pKa , and can be used to predict pKa values of similar structures, is significant for the design of new acidic phosphorus-containing extractants. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Benchmark studies of the gyro-Landau-fluid code and gyro-kinetic codes on kinetic ballooning modes
Energy Technology Data Exchange (ETDEWEB)
Tang, T. F. [Dalian University of Technology, Dalian 116024 (China); Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Xu, X. Q. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Ma, C. H. [Fusion Simulation Center, School of Physics, Peking University, Beijing (China); Bass, E. M.; Candy, J. [General Atomics, P.O. Box 85608, San Diego, California 92186-5608 (United States); Holland, C. [University of California San Diego, La Jolla, California 92093-0429 (United States)
2016-03-15
A Gyro-Landau-Fluid (GLF) 3 + 1 model has been recently implemented in BOUT++ framework, which contains full Finite-Larmor-Radius effects, Landau damping, and toroidal resonance [Ma et al., Phys. Plasmas 22, 055903 (2015)]. A linear global beta scan has been conducted using the JET-like circular equilibria (cbm18 series), showing that the unstable modes are kinetic ballooning modes (KBMs). In this work, we use the GYRO code, which is a gyrokinetic continuum code widely used for simulation of the plasma microturbulence, to benchmark with GLF 3 + 1 code on KBMs. To verify our code on the KBM case, we first perform the beta scan based on “Cyclone base case parameter set.” We find that the growth rate is almost the same for two codes, and the KBM mode is further destabilized as beta increases. For JET-like global circular equilibria, as the modes localize in peak pressure gradient region, a linear local beta scan using the same set of equilibria has been performed at this position for comparison. With the drift kinetic electron module in the GYRO code by including small electron-electron collision to damp electron modes, GYRO generated mode structures and parity suggest that they are kinetic ballooning modes, and the growth rate is comparable to the GLF results. However, a radial scan of the pedestal for a particular set of cbm18 equilibria, using GYRO code, shows different trends for the low-n and high-n modes. The low-n modes show that the linear growth rate peaks at peak pressure gradient position as GLF results. However, for high-n modes, the growth rate of the most unstable mode shifts outward to the bottom of pedestal and the real frequency of what was originally the KBMs in ion diamagnetic drift direction steadily approaches and crosses over to the electron diamagnetic drift direction.
Nature of turbulent transport across sheared zonal flows: insights from gyrokinetic simulations
International Nuclear Information System (INIS)
Sanchez, R; Newman, D E; Leboeuf, J-N; Decyk, V K
2011-01-01
The traditional view regarding the reduction of turbulence-induced transport across a stable sheared flow invokes a reduction of the characteristic length scale in the direction perpendicular to the flow as a result of the shearing and stretching of eddies caused by the differential pull exerted in the direction of the flow. A reduced effective transport coefficient then suffices to capture the reduction, that can then be readily incorporated into a transport model. However, recent evidence from gyrokinetic simulations of the toroidal ion-temperature-gradient mode suggests that the dynamics of turbulent transport across sheared flows changes in a more fundamental manner, and that the use of reduced effective transport coefficients fails to capture the full dynamics that may exhibit both subdiffusion and non-Gaussian statistics. In this contribution, after briefly reviewing these results, we propose some candidates for the physical mechanisms responsible for endowing transport with such non-diffusive characteristics, backing these proposals with new numerical gyrokinetic data.
Guedes, Rafael Lucas Muniz; Rodrigues, Carla Monadeli Filgueira; Coatnoan, Nicolas; Cosson, Alain; Cadioli, Fabiano Antonio; Garcia, Herakles Antonio; Gerber, Alexandra Lehmkuhl; Machado, Rosangela Zacarias; Minoprio, Paola Marcella Camargo; Teixeira, Marta Maria Geraldes; de Vasconcelos, Ana Tereza Ribeiro
2018-02-27
Trypanosoma vivax is a parasite widespread across Africa and South America. Immunological methods using recombinant antigens have been developed aiming at specific and sensitive detection of infections caused by T. vivax. Here, we sequenced for the first time the transcriptome of a virulent T. vivax strain (Lins), isolated from an outbreak of severe disease in South America (Brazil) and performed a computational integrated analysis of genome, transcriptome and in silico predictions to identify and characterize putative linear B-cell epitopes from African and South American T. vivax. A total of 2278, 3936 and 4062 linear B-cell epitopes were respectively characterized for the transcriptomes of T. vivax LIEM-176 (Venezuela), T. vivax IL1392 (Nigeria) and T. vivax Lins (Brazil) and 4684 for the genome of T. vivax Y486 (Nigeria). The results presented are a valuable theoretical source that may pave the way for highly sensitive and specific diagnostic tools. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Elizabeth I. SKLAR
2016-04-01
Full Text Available Using pliable materials for the construction of robot bodies presents new and interesting challenges for the robotics community. Within the EU project entitled STIFFness controllable Flexible & Learnable manipulator for surgical Operations (STIFF-FLOP, a bendable, segmented robot arm has been developed. The exterior of the arm is composed of a soft material (silicone, encasing an internal structure that contains air-chamber actuators and a variety of sensors for monitoring applied force, position and shape of the arm as it bends. Due to the physical characteristics of the arm, a proper model of robot kinematics and dynamics is difficult to infer from the sensor data. Here we propose a non-linear approach to predicting the robot arm posture, by training a feed-forward neural network with a structured series of pressures values applied to the arm's actuators. The model is developed across a set of seven different experiments. Because the STIFF-FLOP arm is intended for use in surgical procedures, traditional methods for position estimation (based on visual information or electromagnetic tracking will not be possible to implement. Thus the ability to estimate pose based on data from a custom fiber-optic bending sensor and accompanying model is a valuable contribution. Results are presented which demonstrate the utility of our non-linear modelling approach across a range of data collection procedures.
International Nuclear Information System (INIS)
Lapillonne, X.
2010-04-01
this work also focused on the description of the magnetic equilibrium. A circular concentric flux surface model as well as an interface with an MHD equilibrium code were implemented. A detailed investigation concerning the s -- α model, previously used in local codes, was also carried out. It was shown that inconsistencies in this model had resulted in misinterpreted agreement between local and global results at large ρ * = ρ s /a values, with ρ s the Larmor radius and a the minor radius of the Tokamak. True convergence between local and global simulations was finally obtained by correct treatment of the geometry in both cases and considering the appropriate ρ * → 0 limit in the latter case. The new global code was furthermore successfully tested and benchmarked against various other codes in the adiabatic electron limit in both the linear and nonlinear regime. A nonlinear ρ * scan was in addition carried out showing convergence to the local results in the limit ρ * → 0 and also providing further insight on previous disagreements between two other global gyrokinetic codes concerning ρ * convergence. Linear global simulations with kinetic electrons have shown consistent behavior with respect to local results. Using the interface with the MHD equilibrium code, the effects of plasma shaping on Ion Temperature Gradient (ITG) instabilities were investigated by means of local simulations. A favorable influence of elongation and negative triangularity was observed. It was shown that these effects could be mostly accounted for by the modifications of the effective flux-surface averaged temperature gradient. Most importantly, a unique effective nonlinear critical temperature gradient could be determined for the different considered elongations and triangularities. The local code was finally used to investigate particle and energy transport in the case of TCV discharges presenting an electron Internal Transport Barrier (eITB). It was shown that at the transition
Renormalized perturbation theory: Vlasov-Poisson System, weak turbulence limit and gyrokinetics
International Nuclear Information System (INIS)
Zhang, Y.Z.; Mahajan, S.M.
1987-10-01
The Self-consistency of the renormalized perturbation theory is demonstrated by applying it to the Vlasov-Poisson System and showing that the theory has the correct weak turbulence limit. Energy conservation is proved to arbitrary high order for the electrostatic drift waves. The theory is applied to derive renormalized equations for a low-β gyrokinetic system. Comparison of our theory with other current theories is presented. 22 refs
Directory of Open Access Journals (Sweden)
Kyle A McQuisten
2009-10-01
Full Text Available Exogenous short interfering RNAs (siRNAs induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models.Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs, General Linear Models (GLMs and Support Vector Machines (SVMs. Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation.The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features found to result in maximally predictive models are
Neoclassical simulation of tokamak plasmas using the continuum gyrokinetic code TEMPEST.
Xu, X Q
2008-07-01
We present gyrokinetic neoclassical simulations of tokamak plasmas with a self-consistent electric field using a fully nonlinear (full- f ) continuum code TEMPEST in a circular geometry. A set of gyrokinetic equations are discretized on a five-dimensional computational grid in phase space. The present implementation is a method of lines approach where the phase-space derivatives are discretized with finite differences, and implicit backward differencing formulas are used to advance the system in time. The fully nonlinear Boltzmann model is used for electrons. The neoclassical electric field is obtained by solving the gyrokinetic Poisson equation with self-consistent poloidal variation. With a four-dimensional (psi,theta,micro) version of the TEMPEST code, we compute the radial particle and heat fluxes, the geodesic-acoustic mode, and the development of the neoclassical electric field, which we compare with neoclassical theory using a Lorentz collision model. The present work provides a numerical scheme for self-consistently studying important dynamical aspects of neoclassical transport and electric field in toroidal magnetic fusion devices.
Olive, David J
2017-01-01
This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...
Alexeeff, Stacey E; Carroll, Raymond J; Coull, Brent
2016-04-01
Spatial modeling of air pollution exposures is widespread in air pollution epidemiology research as a way to improve exposure assessment. However, there are key sources of exposure model uncertainty when air pollution is modeled, including estimation error and model misspecification. We examine the use of predicted air pollution levels in linear health effect models under a measurement error framework. For the prediction of air pollution exposures, we consider a universal Kriging framework, which may include land-use regression terms in the mean function and a spatial covariance structure for the residuals. We derive the bias induced by estimation error and by model misspecification in the exposure model, and we find that a misspecified exposure model can induce asymptotic bias in the effect estimate of air pollution on health. We propose a new spatial simulation extrapolation (SIMEX) procedure, and we demonstrate that the procedure has good performance in correcting this asymptotic bias. We illustrate spatial SIMEX in a study of air pollution and birthweight in Massachusetts. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Zhe Zhang
2010-09-01
Full Text Available With the availability of high density whole-genome single nucleotide polymorphism chips, genomic selection has become a promising method to estimate genetic merit with potentially high accuracy for animal, plant and aquaculture species of economic importance. With markers covering the entire genome, genetic merit of genotyped individuals can be predicted directly within the framework of mixed model equations, by using a matrix of relationships among individuals that is derived from the markers. Here we extend that approach by deriving a marker-based relationship matrix specifically for the trait of interest.In the framework of mixed model equations, a new best linear unbiased prediction (BLUP method including a trait-specific relationship matrix (TA was presented and termed TABLUP. The TA matrix was constructed on the basis of marker genotypes and their weights in relation to the trait of interest. A simulation study with 1,000 individuals as the training population and five successive generations as candidate population was carried out to validate the proposed method. The proposed TABLUP method outperformed the ridge regression BLUP (RRBLUP and BLUP with realized relationship matrix (GBLUP. It performed slightly worse than BayesB with an accuracy of 0.79 in the standard scenario.The proposed TABLUP method is an improvement of the RRBLUP and GBLUP method. It might be equivalent to the BayesB method but it has additional benefits like the calculation of accuracies for individual breeding values. The results also showed that the TA-matrix performs better in predicting ability than the classical numerator relationship matrix and the realized relationship matrix which are derived solely from pedigree or markers without regard to the trait. This is because the TA-matrix not only accounts for the Mendelian sampling term, but also puts the greater emphasis on those markers that explain more of the genetic variance in the trait.
Gyrokinetic Electron and Fully Kinetic Ion Particle Simulation of Collisionless Plasma Dynamics
Energy Technology Data Exchange (ETDEWEB)
Yu Lin; Xueyi Wang; Liu Chen; Zhihong Lin
2009-08-11
Fully kinetic-particle simulations and hybrid simulations have been utilized for decades to investigate various fundamental plasma processes, such as magnetic reconnection, fast compressional waves, and wave-particle interaction. Nevertheless, due to disparate temporal and spatial scales between electrons and ions, existing fully kinetic-particle codes have to employ either unrealistically high electron-to-ion mass ratio, me/mi, or simulation domain limited to a few or a few ten's of the ion Larmor radii, or/and time much less than the global Alfven time scale in order to accommodate available computing resources. On the other hand, in the hybrid simulation, the ions are treated as fully kinetic particles but the electrons are treated as a massless fluid. The electron kinetic effects, e.g., wave-particle resonances and finite electron Larmor radius effects, are completely missing. Important physics, such as the electron transit time damping of fast compressional waves or the triggering mechanism of magnetic reconnection in collisionless plasmas is absent in the hybrid codes. Motivated by these considerations and noting that dynamics of interest to us has frequencies lower than the electron gyrofrequency, we planned to develop an innovative particle simulation model, gyrokinetic (GK) electrons and fully kinetic (FK) ions. In the GK-electron and FK-ion (GKe/FKi) particle simulation model, the rapid electron cyclotron motion is removed, while keeping finite electron Larmor radii, realistic me/mi ratio, wave-particle interactions, and off-diagonal components of electron pressure tensor. The computation power can thus be significantly improved over that of the full-particle codes. As planned in the project DE-FG02-05ER54826, we have finished the development of the new GK-electron and FK-ion scheme, finished its benchmark for a uniform plasma in 1-D, 2-D, and 3-D systems against linear waves obtained from analytical theories, and carried out a further convergence
Gyrokinetic Electron and Fully Kinetic Ion Particle Simulation of Collisionless Plasma Dynamics
International Nuclear Information System (INIS)
Lin, Yu; Wang, Xueyi; Chen, Liu; Lin, Zhihong
2009-01-01
Fully kinetic-particle simulations and hybrid simulations have been utilized for decades to investigate various fundamental plasma processes, such as magnetic reconnection, fast compressional waves, and wave-particle interaction. Nevertheless, due to disparate temporal and spatial scales between electrons and ions, existing fully kinetic-particle codes have to employ either unrealistically high electron-to-ion mass ratio, me/mi, or simulation domain limited to a few or a few ten's of the ion Larmor radii, or/and time much less than the global Alfven time scale in order to accommodate available computing resources. On the other hand, in the hybrid simulation, the ions are treated as fully kinetic particles but the electrons are treated as a massless fluid. The electron kinetic effects, e.g., wave-particle resonances and finite electron Larmor radius effects, are completely missing. Important physics, such as the electron transit time damping of fast compressional waves or the triggering mechanism of magnetic reconnection in collisionless plasmas is absent in the hybrid codes. Motivated by these considerations and noting that dynamics of interest to us has frequencies lower than the electron gyrofrequency, we planned to develop an innovative particle simulation model, gyrokinetic (GK) electrons and fully kinetic (FK) ions. In the GK-electron and FK-ion (GKe/FKi) particle simulation model, the rapid electron cyclotron motion is removed, while keeping finite electron Larmor radii, realistic me/mi ratio, wave-particle interactions, and off-diagonal components of electron pressure tensor. The computation power can thus be significantly improved over that of the full-particle codes. As planned in the project DE-FG02-05ER54826, we have finished the development of the new GK-electron and FK-ion scheme, finished its benchmark for a uniform plasma in 1-D, 2-D, and 3-D systems against linear waves obtained from analytical theories, and carried out a further convergence test
More, Anand Govind; Gupta, Sunil Kumar
2018-03-24
Bioelectrochemical system (BES) is a novel, self-sustaining metal removal technology functioning on the utilization of chemical energy of organic matter with the help of microorganisms. Experimental trials of two chambered BES reactor were conducted with varying substrate concentration using sodium acetate (500 mg/L to 2000 mg/L COD) and different initial chromium concentration (Cr i ) (10-100 mg/L) at different cathode pH (pH 1-7). In the current study mathematical models based on multiple linear regression (MLR) and non-linear regression (NLR) approach were developed using laboratory experimental data for determining chromium removal efficiency (CRE) in the cathode chamber of BES. Substrate concentration, rate of substrate consumption, Cr i , pH, temperature and hydraulic retention time (HRT) were the operating process parameters of the reactor considered for development of the proposed models. MLR showed a better correlation coefficient (0.972) as compared to NLR (0.952). Validation of the models using t-test analysis revealed unbiasedness of both the models, with t critical value (2.04) greater than t-calculated values for MLR (-0.708) and NLR (-0.86). The root-mean-square error (RMSE) for MLR and NLR were 5.06 % and 7.45 %, respectively. Comparison between both models suggested MLR to be best suited model for predicting the chromium removal behavior using the BES technology to specify a set of operating conditions for BES. Modelling the behavior of CRE will be helpful for scale up of BES technology at industrial level. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Pivatelli Flávio
2012-10-01
Full Text Available Abstract Background Decreased heart rate variability (HRV is related to higher morbidity and mortality. In this study we evaluated the linear and nonlinear indices of the HRV in stable angina patients submitted to coronary angiography. Methods We studied 77 unselected patients for elective coronary angiography, which were divided into two groups: coronary artery disease (CAD and non-CAD groups. For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 40 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal], NN50 [total number of adjacent RR intervals with a difference of duration greater than 50ms] and RMSSD [root-mean square of differences] and frequency domains ultra-low frequency (ULF ≤ 0,003 Hz, very low frequency (VLF 0,003 – 0,04 Hz, low frequency (LF (0.04–0.15 Hz, and high frequency (HF (0.15–0.40 Hz as well as the ratio between LF and HF components (LF/HF. In relation to the nonlinear indices we evaluated SD1, SD2, SD1/SD2, approximate entropy (−ApEn, α1, α2, Lyapunov Exponent, Hurst Exponent, autocorrelation and dimension correlation. The definition of the cutoff point of the variables for predictive tests was obtained by the Receiver Operating Characteristic curve (ROC. The area under the ROC curve was calculated by the extended trapezoidal rule, assuming as relevant areas under the curve ≥ 0.650. Results Coronary arterial disease patients presented reduced values of SDNN, RMSSD, NN50, HF, SD1, SD2 and -ApEn. HF ≤ 66 ms2, RMSSD ≤ 23.9 ms, ApEn ≤−0.296 and NN50 ≤ 16 presented the best discriminatory power for the presence of significant coronary obstruction. Conclusion We suggest the use of Heart Rate Variability Analysis in linear and nonlinear domains, for prognostic purposes in patients with stable angina pectoris, in view of their overall impairment.
DeForest, David K; Brix, Kevin V; Tear, Lucinda M; Adams, William J
2018-01-01
The bioavailability of aluminum (Al) to freshwater aquatic organisms varies as a function of several water chemistry parameters, including pH, dissolved organic carbon (DOC), and water hardness. We evaluated the ability of multiple linear regression (MLR) models to predict chronic Al toxicity to a green alga (Pseudokirchneriella subcapitata), a cladoceran (Ceriodaphnia dubia), and a fish (Pimephales promelas) as a function of varying DOC, pH, and hardness conditions. The MLR models predicted toxicity values that were within a factor of 2 of observed values in 100% of the cases for P. subcapitata (10 and 20% effective concentrations [EC10s and EC20s]), 91% of the cases for C. dubia (EC10s and EC20s), and 95% (EC10s) and 91% (EC20s) of the cases for P. promelas. The MLR models were then applied to all species with Al toxicity data to derive species and genus sensitivity distributions that could be adjusted as a function of varying DOC, pH, and hardness conditions (the P. subcapitata model was applied to algae and macrophytes, the C. dubia model was applied to invertebrates, and the P. promelas model was applied to fish). Hazardous concentrations to 5% of the species or genera were then derived in 2 ways: 1) fitting a log-normal distribution to species-mean EC10s for all species (following the European Union methodology), and 2) fitting a triangular distribution to genus-mean EC20s for animals only (following the US Environmental Protection Agency methodology). Overall, MLR-based models provide a viable approach for deriving Al water quality guidelines that vary as a function of DOC, pH, and hardness conditions and are a significant improvement over bioavailability corrections based on single parameters. Environ Toxicol Chem 2018;37:80-90. © 2017 SETAC. © 2017 SETAC.
Energy Technology Data Exchange (ETDEWEB)
Prada-Sanchez, J.M.; Febrero-Bande, M.; Gonzalez-Manteiga, W. [Universidad de Santiago de Compostela, Dept. de Estadistica e Investigacion Operativa, Santiago de Compostela (Spain); Costos-Yanez, T. [Universidad de Vigo, Dept. de Estadistica e Investigacion Operativa, Orense (Spain); Bermudez-Cela, J.L.; Lucas-Dominguez, T. [Laboratorio, Central Termica de As Pontes, La Coruna (Spain)
2000-07-01
Atmospheric SO{sub 2} concentrations at sampling stations near the fossil fuel fired power station at As Pontes (La Coruna, Spain) were predicted using a model for the corresponding time series consisting of a self-explicative term and a linear combination of exogenous variables. In a supplementary simulation study, models of this kind behaved better than the corresponding pure self-explicative or pure linear regression models. (Author)
International Nuclear Information System (INIS)
Prada-Sanchez, J.M.; Febrero-Bande, M.; Gonzalez-Manteiga, W.; Costos-Yanez, T.; Bermudez-Cela, J.L.; Lucas-Dominguez, T.
2000-01-01
Atmospheric SO 2 concentrations at sampling stations near the fossil fuel fired power station at As Pontes (La Coruna, Spain) were predicted using a model for the corresponding time series consisting of a self-explicative term and a linear combination of exogenous variables. In a supplementary simulation study, models of this kind behaved better than the corresponding pure self-explicative or pure linear regression models. (Author)
International Nuclear Information System (INIS)
Bataille, F.; Younis, B.A.; Bellettre, J.; Lallemand, A.
2003-01-01
The paper reports on the prediction of the effects of blowing on the evolution of the thermal and velocity fields in a flat-plate turbulent boundary layer developing over a porous surface. Closure of the time-averaged equations governing the transport of momentum and thermal energy is achieved using a complete Reynolds-stress transport model for the turbulent stresses and a non-linear, algebraic and explicit model for the turbulent heat fluxes. The latter model accounts explicitly for the dependence of the turbulent heat fluxes on the gradients of mean velocity. Results are reported for the case of a heated boundary layer which is first developed into equilibrium over a smooth impervious wall before encountering a porous section through which cooler fluid is continuously injected. Comparisons are made with LDA measurements for an injection rate of 1%. The reduction of the wall shear stress with increase in injection rate is obtained in the calculations, and the computed rates of heat transfer between the hot flow and the wall are found to agree well with the published data
DEFF Research Database (Denmark)
Troen, Ib; Bechmann, Andreas; Kelly, Mark C.
2014-01-01
Using the Wind Atlas methodology to predict the average wind speed at one location from measured climatological wind frequency distributions at another nearby location we analyse the relative prediction errors using a linearized flow model (IBZ) and a more physically correct fully non-linear 3D...... flow model (CFD) for a number of sites in very complex terrain (large terrain slopes). We first briefly describe the Wind Atlas methodology as implemented in WAsP and the specifics of the “classical” model setup and the new setup allowing the use of the CFD computation engine. We discuss some known...
Tahani, Masoud; Askari, Amir R.
2014-09-01
In spite of the fact that pull-in instability of electrically actuated nano/micro-beams has been investigated by many researchers to date, no explicit formula has been presented yet which can predict pull-in voltage based on a geometrically non-linear and distributed parameter model. The objective of present paper is to introduce a simple and accurate formula to predict this value for a fully clamped electrostatically actuated nano/micro-beam. To this end, a non-linear Euler-Bernoulli beam model is employed, which accounts for the axial residual stress, geometric non-linearity of mid-plane stretching, distributed electrostatic force and the van der Waals (vdW) attraction. The non-linear boundary value governing equation of equilibrium is non-dimensionalized and solved iteratively through single-term Galerkin based reduced order model (ROM). The solutions are validated thorough direct comparison with experimental and other existing results reported in previous studies. Pull-in instability under electrical and vdW loads are also investigated using universal graphs. Based on the results of these graphs, non-dimensional pull-in and vdW parameters, which are defined in the text, vary linearly versus the other dimensionless parameters of the problem. Using this fact, some linear equations are presented to predict pull-in voltage, the maximum allowable length, the so-called detachment length, and the minimum allowable gap for a nano/micro-system. These linear equations are also reduced to a couple of universal pull-in formulas for systems with small initial gap. The accuracy of the universal pull-in formulas are also validated by comparing its results with available experimental and some previous geometric linear and closed-form findings published in the literature.
Linear and nonlinear kinetic-stability studies in tokamaks
International Nuclear Information System (INIS)
Tang, W.M.; Chance, M.S.; Chen, L.; Krommes, J.A.; Lee, W.W.; Rewoldt, G.
1982-09-01
This paper presents results of theoretical investigations on important linear kinetic properties of low frequency instabilities in toroidal systems and on nonlinear processes which could significantly influence their impact on anomalous transport. Analytical and numerical methods and also particle simulations have been employed to carry out these studies. In particular, the following subjects are considered: (1) linear stability analysis of kinetic instabilities for realistic tokamak equilibria and the application of such calculations to the PDX and PLT tokamak experiments including the influence of a hot beam-ion component; (2) determination of nonlinearly saturated, statistically steady states of three interacting drift modes; and (3) gyrokinetic particle simulation of drift instabilities
International Nuclear Information System (INIS)
Idomura, Yasuhiro; Jolliet, Sebastien
2010-01-01
A gyrokinetic toroidal five dimensional Eulerian code GT5D is ported on six advanced massively parallel platforms and comprehensive benchmark tests are performed. A parallelisation technique based on physical properties of the gyrokinetic equation is presented. By extending the parallelisation technique with a hybrid parallel model, the scalability of the code is improved on platforms with multi-core processors. In the benchmark tests, a good salability is confirmed up to several thousands cores on every platforms, and the maximum sustained performance of ∼18.6 Tflops is achieved using 16384 cores of BX900. (author)
Energy Technology Data Exchange (ETDEWEB)
McClenaghan, J.; Lin, Z.; Holod, I.; Deng, W.; Wang, Z. [University of California, Irvine, California 92697 (United States)
2014-12-15
The gyrokinetic toroidal code (GTC) capability has been extended for simulating internal kink instability with kinetic effects in toroidal geometry. The global simulation domain covers the magnetic axis, which is necessary for simulating current-driven instabilities. GTC simulation in the fluid limit of the kink modes in cylindrical geometry is verified by benchmarking with a magnetohydrodynamic eigenvalue code. Gyrokinetic simulations of the kink modes in the toroidal geometry find that ion kinetic effects significantly reduce the growth rate even when the banana orbit width is much smaller than the radial width of the perturbed current layer at the mode rational surface.
International Nuclear Information System (INIS)
Lin, Z; Rewoldt, G; Ethier, S; Hahm, T S; Lee, W W; Lewandowski, J L V; Nishimura, Y; Wang, W X
2005-01-01
Recent progress in gyrokinetic particle-in-cell simulations of turbulent plasmas using the gyrokinetic toroidal code (GTC) is surveyed. In particular, recent results for electron temperature gradient (ETG) modes and their resulting transport are presented. Also, turbulence spreading, and the effects of the parallel nonlinearity, are described. The GTC code has also been generalized for non-circular plasma cross-section, and initial results are presented. In addition, two distinct methods of generalizing the GTC code to be electromagnetic are described, along with preliminary results. Finally, a related code, GTC-Neo, for calculating neoclassical fluxes, electric fields, and velocities, are described
Energy Technology Data Exchange (ETDEWEB)
White, A. E., E-mail: whitea@mit.edu; Howard, N. T.; Creely, A. J.; Chilenski, M. A.; Greenwald, M.; Hubbard, A. E.; Hughes, J. W.; Marmar, E.; Rice, J. E.; Sierchio, J. M.; Sung, C.; Walk, J. R.; Whyte, D. G. [MIT Plasma Science and Fusion Center, Cambridge, Massachusetts 02139 (United States); Mikkelsen, D. R.; Edlund, E. M.; Kung, C. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08540 (United States); Holland, C. [University of California, San Diego (UCSD) San Diego, California 92093 (United States); Candy, J.; Petty, C. C. [General Atomics, P.O. Box 85608, San Diego, California 92186 (United States); Reinke, M. L. [York University, Heslington, York YO10 5DD (United Kingdom); and others
2015-05-15
For the first time, nonlinear gyrokinetic simulations of I-mode plasmas are performed and compared with experiment. I-mode is a high confinement regime, featuring energy confinement similar to H-mode, but without enhanced particle and impurity particle confinement [D. G. Whyte et al., Nucl. Fusion 50, 105005 (2010)]. As a consequence of the separation between heat and particle transport, I-mode exhibits several favorable characteristics compared to H-mode. The nonlinear gyrokinetic code GYRO [J. Candy and R. E. Waltz, J Comput. Phys. 186, 545 (2003)] is used to explore the effects of E × B shear and profile stiffness in I-mode and compare with L-mode. The nonlinear GYRO simulations show that I-mode core ion temperature and electron temperature profiles are more stiff than L-mode core plasmas. Scans of the input E × B shear in GYRO simulations show that E × B shearing of turbulence is a stronger effect in the core of I-mode than L-mode. The nonlinear simulations match the observed reductions in long wavelength density fluctuation levels across the L-I transition but underestimate the reduction of long wavelength electron temperature fluctuation levels. The comparisons between experiment and gyrokinetic simulations for I-mode suggest that increased E × B shearing of turbulence combined with increased profile stiffness are responsible for the reductions in core turbulence observed in the experiment, and that I-mode resembles H-mode plasmas more than L-mode plasmas with regards to marginal stability and temperature profile stiffness.
Jensen, Dan B; Hogeveen, Henk; De Vries, Albert
2016-09-01
Rapid detection of dairy cow mastitis is important so corrective action can be taken as soon as possible. Automatically collected sensor data used to monitor the performance and the health state of the cow could be useful for rapid detection of mastitis while reducing the labor needs for monitoring. The state of the art in combining sensor data to predict clinical mastitis still does not perform well enough to be applied in practice. Our objective was to combine a multivariate dynamic linear model (DLM) with a naïve Bayesian classifier (NBC) in a novel method using sensor and nonsensor data to detect clinical cases of mastitis. We also evaluated reductions in the number of sensors for detecting mastitis. With the DLM, we co-modeled 7 sources of sensor data (milk yield, fat, protein, lactose, conductivity, blood, body weight) collected at each milking for individual cows to produce one-step-ahead forecasts for each sensor. The observations were subsequently categorized according to the errors of the forecasted values and the estimated forecast variance. The categorized sensor data were combined with other data pertaining to the cow (week in milk, parity, mastitis history, somatic cell count category, and season) using Bayes' theorem, which produced a combined probability of the cow having clinical mastitis. If this probability was above a set threshold, the cow was classified as mastitis positive. To illustrate the performance of our method, we used sensor data from 1,003,207 milkings from the University of Florida Dairy Unit collected from 2008 to 2014. Of these, 2,907 milkings were associated with recorded cases of clinical mastitis. Using the DLM/NBC method, we reached an area under the receiver operating characteristic curve of 0.89, with a specificity of 0.81 when the sensitivity was set at 0.80. Specificities with omissions of sensor data ranged from 0.58 to 0.81. These results are comparable to other studies, but differences in data quality, definitions of
Energy Technology Data Exchange (ETDEWEB)
Herbert, Christopher, E-mail: cherbert@bccancer.bc.ca [Department of Radiation Oncology, British Columbia Cancer Agency, Vancouver, BC (Canada); Moiseenko, Vitali [Department of Medical Physics, British Columbia Cancer Agency, Vancouver, BC (Canada); McKenzie, Michael [Department of Radiation Oncology, British Columbia Cancer Agency, Vancouver, BC (Canada); Redekop, Gary [Division of Neurosurgery, Vancouver General Hospital, University of British Columbia, Vancouver, BC (Canada); Hsu, Fred [Department of Radiation Oncology, British Columbia Cancer Agency, Abbotsford, BC (Canada); Gete, Ermias; Gill, Brad; Lee, Richard; Luchka, Kurt [Department of Medical Physics, British Columbia Cancer Agency, Vancouver, BC (Canada); Haw, Charles [Division of Neurosurgery, Vancouver General Hospital, University of British Columbia, Vancouver, BC (Canada); Lee, Andrew [Department of Neurosurgery, Royal Columbian Hospital, New Westminster, BC (Canada); Toyota, Brian [Division of Neurosurgery, Vancouver General Hospital, University of British Columbia, Vancouver, BC (Canada); Martin, Montgomery [Department of Medical Imaging, British Columbia Cancer Agency, Vancouver, BC (Canada)
2012-07-01
Purpose: To investigate predictive factors in the development of symptomatic radiation injury after treatment with linear accelerator-based stereotactic radiosurgery for intracerebral arteriovenous malformations and relate the findings to the conclusions drawn by Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC). Methods and Materials: Archived plans for 73 patients who were treated at the British Columbia Cancer Agency were studied. Actuarial estimates of freedom from radiation injury were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of incidence of radiation injury. Log-rank test was used to search for dosimetric parameters associated with freedom from radiation injury. Results: Symptomatic radiation injury was exhibited by 14 of 73 patients (19.2%). Actuarial rate of symptomatic radiation injury was 23.0% at 4 years. Most patients (78.5%) had mild to moderate deficits according to Common Terminology Criteria for Adverse Events, version 4.0. On univariate analysis, lesion volume and diameter, dose to isocenter, and a V{sub x} for doses {>=}8 Gy showed statistical significance. Only lesion diameter showed statistical significance (p < 0.05) in a multivariate model. According to the log-rank test, AVM volumes >5 cm{sup 3} and diameters >30 mm were significantly associated with the risk of radiation injury (p < 0.01). The V{sub 12} also showed strong association with the incidence of radiation injury. Actuarial incidence of radiation injury was 16.8% if V{sub 12} was <28 cm{sup 3} and 53.2% if >28 cm{sup 3} (log-rank test, p = 0.001). Conclusions: This study confirms that the risk of developing symptomatic radiation injury after radiosurgery is related to lesion diameter and volume and irradiated volume. Results suggest a higher tolerance than proposed by QUANTEC. The widely differing findings reported in the literature, however, raise considerable uncertainties.
Directory of Open Access Journals (Sweden)
E. Çelebi
2012-11-01
Full Text Available The objective of this paper focuses primarily on the numerical approach based on two-dimensional (2-D finite element method for analysis of the seismic response of infinite soil-structure interaction (SSI system. This study is performed by a series of different scenarios that involved comprehensive parametric analyses including the effects of realistic material properties of the underlying soil on the structural response quantities. Viscous artificial boundaries, simulating the process of wave transmission along the truncated interface of the semi-infinite space, are adopted in the non-linear finite element formulation in the time domain along with Newmark's integration. The slenderness ratio of the superstructure and the local soil conditions as well as the characteristics of input excitations are important parameters for the numerical simulation in this research. The mechanical behavior of the underlying soil medium considered in this prediction model is simulated by an undrained elasto-plastic Mohr-Coulomb model under plane-strain conditions. To emphasize the important findings of this type of problems to civil engineers, systematic calculations with different controlling parameters are accomplished to evaluate directly the structural response of the vibrating soil-structure system. When the underlying soil becomes stiffer, the frequency content of the seismic motion has a major role in altering the seismic response. The sudden increase of the dynamic response is more pronounced for resonance case, when the frequency content of the seismic ground motion is close to that of the SSI system. The SSI effects under different seismic inputs are different for all considered soil conditions and structural types.
International Nuclear Information System (INIS)
Herbert, Christopher; Moiseenko, Vitali; McKenzie, Michael; Redekop, Gary; Hsu, Fred; Gete, Ermias; Gill, Brad; Lee, Richard; Luchka, Kurt; Haw, Charles; Lee, Andrew; Toyota, Brian; Martin, Montgomery
2012-01-01
Purpose: To investigate predictive factors in the development of symptomatic radiation injury after treatment with linear accelerator–based stereotactic radiosurgery for intracerebral arteriovenous malformations and relate the findings to the conclusions drawn by Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC). Methods and Materials: Archived plans for 73 patients who were treated at the British Columbia Cancer Agency were studied. Actuarial estimates of freedom from radiation injury were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of incidence of radiation injury. Log–rank test was used to search for dosimetric parameters associated with freedom from radiation injury. Results: Symptomatic radiation injury was exhibited by 14 of 73 patients (19.2%). Actuarial rate of symptomatic radiation injury was 23.0% at 4 years. Most patients (78.5%) had mild to moderate deficits according to Common Terminology Criteria for Adverse Events, version 4.0. On univariate analysis, lesion volume and diameter, dose to isocenter, and a V x for doses ≥8 Gy showed statistical significance. Only lesion diameter showed statistical significance (p 5 cm 3 and diameters >30 mm were significantly associated with the risk of radiation injury (p 12 also showed strong association with the incidence of radiation injury. Actuarial incidence of radiation injury was 16.8% if V 12 was 3 and 53.2% if >28 cm 3 (log–rank test, p = 0.001). Conclusions: This study confirms that the risk of developing symptomatic radiation injury after radiosurgery is related to lesion diameter and volume and irradiated volume. Results suggest a higher tolerance than proposed by QUANTEC. The widely differing findings reported in the literature, however, raise considerable uncertainties.
Development of a global toroidal gyrokinetic Vlasov code with new real space field solver
International Nuclear Information System (INIS)
Obrejan, Kevin; Imadera, Kenji; Li, Ji-Quan; Kishimoto, Yasuaki
2015-01-01
This work introduces a new full-f toroidal gyrokinetic (GK) Vlasov simulation code that uses a real space field solver. This solver enables us to compute the gyro-averaging operators in real space to allow proper treatment of finite Larmor radius (FLR) effects without requiring any particular hypothesis and in any magnetic field configuration (X-point, D-shaped etc). The code was well verified through benchmark tests such as toroidal Ion Temperature Gradient (ITG) instability and collisionless damping of zonal flow. (author)
International Nuclear Information System (INIS)
Ibrahim, Khaled Z.; Madduri, Kamesh; Williams, Samuel; Wang, Bei; Oliker, Leonid
2013-01-01
The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This paper presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Finally, our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2× speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.
Chang, C S; Ku, S; Tynan, G R; Hager, R; Churchill, R M; Cziegler, I; Greenwald, M; Hubbard, A E; Hughes, J W
2017-04-28
Transport barrier formation and its relation to sheared flows in fluids and plasmas are of fundamental interest in various natural and laboratory observations and of critical importance in achieving an economical energy production in a magnetic fusion device. Here we report the first observation of an edge transport barrier formation event in an electrostatic gyrokinetic simulation carried out in a realistic diverted tokamak edge geometry under strong forcing by a high rate of heat deposition. The results show that turbulent Reynolds-stress-driven sheared E×B flows act in concert with neoclassical orbit loss to quench turbulent transport and form a transport barrier just inside the last closed magnetic flux surface.
Szadkowski, Zbigniew; Fraenkel, E. D.; van den Berg, Ad M.
2013-01-01
We present the FPGA/NIOS implementation of an adaptive finite impulse response (FIR) filter based on linear prediction to suppress radio frequency interference (RFI). This technique will be used for experiments that observe coherent radio emission from extensive air showers induced by
Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally
2018-02-01
1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.
Azadi, Sama; Karimi-Jashni, Ayoub
2016-02-01
Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study of 20 cities located in Fars Province, Iran. Four performance measures, MAE, MAPE, RMSE and R were used to evaluate the performance of these models. The MLR, as a conventional model, showed poor prediction performance. On the other hand, the results indicated that the ANN model, as a non-linear model, has a higher predictive accuracy when it comes to prediction of the mean SMSWG rate. As a result, in order to develop a more cost-effective strategy for waste management in the future, the ANN model could be used to predict the mean SMSWG rate. Copyright © 2015 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Tang, W.M.
2005-01-01
The present lecture provides an introduction to the subject of gyrokinetic theory with applications in the area of magnetic confinement research in plasma physics--the research arena from which this formalism was originally developed. It was presented as a component of the ''Short Course in Kinetic Theory within the Thematic Program in Partial Differential Equations'' held at the Fields Institute for Research in Mathematical Science (24 March 2004). This lecture also discusses the connection between the gyrokinetic formalism and powerful modern numerical simulations. Indeed, simulation, which provides a natural bridge between theory and experiment, is an essential modern tool for understanding complex plasma behavior. Progress has been stimulated in particular by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modeling. This was enabled by two key factors: (i) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (ii) access to powerful new computational resources
Hakim, Ammar; Shi, Eric; Juno, James; Bernard, Tess; Hammett, Greg
2017-10-01
For weakly collisional (or collisionless) plasmas, kinetic effects are required to capture the physics of micro-turbulence. We have implemented solvers for kinetic and gyrokinetic equations in the computational plasma physics framework, Gkeyll. We use a version of discontinuous Galerkin scheme that conserves energy exactly. Plasma sheaths are modeled with novel boundary conditions. Positivity of distribution functions is maintained via a reconstruction method, allowing robust simulations that continue to conserve energy even with positivity limiters. We have performed a large number of benchmarks, verifying the accuracy and robustness of our code. We demonstrate the application of our algorithm to two classes of problems (a) Vlasov-Maxwell simulations of turbulence in a magnetized plasma, applicable to space plasmas; (b) Gyrokinetic simulations of turbulence in open-field-line geometries, applicable to laboratory plasmas. Supported by the Max-Planck/Princeton Center for Plasma Physics, the SciDAC Center for the Study of Plasma Microturbulence, and DOE Contract DE-AC02-09CH11466.
Waltz, R. E.; Waelbroeck, F. L.
2012-03-01
Static external resonant magnetic perturbations (RMPs) have been added to the δf gyrokinetic code GYRO. This allows nonlinear gyrokinetic simulations of the nonambipolar radial current flow jr and the corresponding plasma torque (density) R[jrBθ/c], induced by islands that break the toroidal symmetry of a tokamak. This extends previous GYRO simulations for the transport of toroidal angular momentum (TAM) [1,2]. The focus is on full torus radial slice electrostatic simulations of induced q=m/n=6/3 islands with widths 5% of the minor radius. The island torque scales with the radial electric field Er the island width w, and the intensity I of the high-n micro-turbulence, as wErI^1/2. The net island torque is null at zero Er rather than at zero toroidal rotation. This means that there is a small co-directed magnetic acceleration to the small diamagnetic co-rotation corresponding to the zero Er which can be called the residual stress [2] from an externally induced island. Finite-beta GYRO simulations of a core radial slice demonstrate island unlocking and the RMP screening. 6pt[1] R.E. Waltz, et al., Phys. Plasmas 14, 122507 (2007). [2] R.E. Waltz, et al., Phys. Plasmas 18, 042504 (2011).
Jendeberg, Johan; Geijer, Håkan; Alshamari, Muhammed; Lidén, Mats
2018-01-24
To compare the ability of different size estimates to predict spontaneous passage of ureteral stones using a 3D-segmentation and to investigate the impact of manual measurement variability on the prediction of stone passage. We retrospectively included 391 consecutive patients with ureteral stones on non-contrast-enhanced CT (NECT). Three-dimensional segmentation size estimates were compared to the mean of three radiologists' measurements. Receiver-operating characteristic (ROC) analysis was performed for the prediction of spontaneous passage for each estimate. The difference in predicted passage probability between the manual estimates in upper and lower stones was compared. The area under the ROC curve (AUC) for the measurements ranged from 0.88 to 0.90. Between the automated 3D algorithm and the manual measurements the 95% limits of agreement were 0.2 ± 1.4 mm for the width. The manual bone window measurements resulted in a > 20 percentage point (ppt) difference between the readers in the predicted passage probability in 44% of the upper and 6% of the lower ureteral stones. All automated 3D algorithm size estimates independently predicted the spontaneous stone passage with similar high accuracy as the mean of three readers' manual linear measurements. Manual size estimation of upper stones showed large inter-reader variations for spontaneous passage prediction. • An automated 3D technique predicts spontaneous stone passage with high accuracy. • Linear, areal and volumetric measurements performed similarly in predicting stone passage. • Reader variability has a large impact on the predicted prognosis for stone passage.
Chandler, T L; Pralle, R S; Dórea, J R R; Poock, S E; Oetzel, G R; Fourdraine, R H; White, H M
2018-03-01
Although cowside testing strategies for diagnosing hyperketonemia (HYK) are available, many are labor intensive and costly, and some lack sufficient accuracy. Predicting milk ketone bodies by Fourier transform infrared spectrometry during routine milk sampling may offer a more practical monitoring strategy. The objectives of this study were to (1) develop linear and logistic regression models using all available test-day milk and performance variables for predicting HYK and (2) compare prediction methods (Fourier transform infrared milk ketone bodies, linear regression models, and logistic regression models) to determine which is the most predictive of HYK. Given the data available, a secondary objective was to evaluate differences in test-day milk and performance variables (continuous measurements) between Holsteins and Jerseys and between cows with or without HYK within breed. Blood samples were collected on the same day as milk sampling from 658 Holstein and 468 Jersey cows between 5 and 20 d in milk (DIM). Diagnosis of HYK was at a serum β-hydroxybutyrate (BHB) concentration ≥1.2 mmol/L. Concentrations of milk BHB and acetone were predicted by Fourier transform infrared spectrometry (Foss Analytical, Hillerød, Denmark). Thresholds of milk BHB and acetone were tested for diagnostic accuracy, and logistic models were built from continuous variables to predict HYK in primiparous and multiparous cows within breed. Linear models were constructed from continuous variables for primiparous and multiparous cows within breed that were 5 to 11 DIM or 12 to 20 DIM. Milk ketone body thresholds diagnosed HYK with 64.0 to 92.9% accuracy in Holsteins and 59.1 to 86.6% accuracy in Jerseys. Logistic models predicted HYK with 82.6 to 97.3% accuracy. Internally cross-validated multiple linear regression models diagnosed HYK of Holstein cows with 97.8% accuracy for primiparous and 83.3% accuracy for multiparous cows. Accuracy of Jersey models was 81.3% in primiparous and 83
International Nuclear Information System (INIS)
Maiya, P.S.
1978-07-01
The creep-fatigue life results for five different heats of Type 304 stainless steel at 593 0 C (1100 0 F), generated under push-pull conditions in the axial strain-control mode, are presented. The life predictions for the various heats based on the linear-damage rule, strain-range partitioning method, and damage-rate approach are discussed. The appropriate material properties required for computation of fatigue life are also included
DEFF Research Database (Denmark)
Lund, Claus Otto; Nilas, Lisbeth; Bangsgaard, Nannie
2002-01-01
CG levels had a low diagnostic sensitivity (0.38-0.66) and specificity (0.74-0.77) for predicting PEP. In multivariate logistic analysis, none of the following clinical variables were predictive of PEP: duration of surgery, laparoscopic approach, history of previous EP, history of previous lower abdominal...
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Skajaa, Anders; Frison, Gianluca
2013-01-01
algorithm in MATLAB and its performance is analyzed based on a smart grid power management case study. Closed loop simulations show that 1) our algorithm is significantly faster than state-of-the-art IPMs based on sparse linear algebra routines, and 2) warm-starting reduces the number of iterations...
de Bruin, A.B.H.; Smits, N.; Rikers, R.M.J.P.; Schmidt, H.G.
2008-01-01
In this study, the longitudinal relation between deliberate practice and performance in chess was examined using a linear mixed models analysis. The practice activities and performance ratings of young elite chess players, who were either in, or had dropped out of the Dutch national chess training,
Rico Rico, A.; Droge, S.T.J.|info:eu-repo/dai/nl/304834017; Hermens, J.L.M.|info:eu-repo/dai/nl/069681384
2010-01-01
The effect of the molecular structure and the salinity on the sorption of the anionic surfactant linear alkylbenzenesulfonate (LAS) to marine sediment has been studied. The analysis of several individual LAS congeners in seawater and of one specific LAS congener at different dilutions of seawater
Berngard, Samuel Clark; Berngard, Jennifer Bishop; Krebs, Nancy F; Garcés, Ana; Miller, Leland V; Westcott, Jamie; Wright, Linda L; Kindem, Mark; Hambidge, K Michael
2013-12-01
Stunting is prevalent by the age of 6 months in the indigenous population of the Western Highlands of Guatemala. The objective of this study was to determine the time course and predictors of linear growth failure and weight-for-age in early infancy. One hundred and forty eight term newborns had measurements of length and weight in their homes, repeated at 3 and 6 months. Maternal measurements were also obtained. Mean ± SD length-for-age Z-score (LAZ) declined from newborn -1.0 ± 1.01 to -2.20 ± 1.05 and -2.26 ± 1.01 at 3 and 6 months respectively. Stunting rates for newborn, 3 and 6 months were 47%, 53% and 56% respectively. A multiple regression model (R(2) = 0.64) demonstrated that the major predictor of LAZ at 3 months was newborn LAZ with the other predictors being newborn weight-for-age Z-score (WAZ), gender and maternal education∗maternal age interaction. Because WAZ remained essentially constant and LAZ declined during the same period, weight-for-length Z-score (WLZ) increased from -0.44 to +1.28 from birth to 3 months. The more severe the linear growth failure, the greater WAZ was in proportion to the LAZ. The primary conclusion is that impaired fetal linear growth is the major predictor of early infant linear growth failure indicating that prevention needs to start with maternal interventions. © 2013.
International Nuclear Information System (INIS)
Childs, Jessie T.; Thoirs, Kerry A.; Esterman, Adrian J.
2016-01-01
This study sought to develop a practical and uncomplicated predictive equation that could accurately calculate liver volumes, using multiple simple linear ultrasound measurements combined with measurements of body size. Penalized (lasso) regression was used to develop a new model and compare it to the ultrasonic linear measurements currently used clinically. A Bland–Altman analysis showed that the large limits of agreement of the new model render it too inaccurate to be of clinical use for estimating liver volume per se, but it holds value in tracking disease progress or response to treatment over time in individuals, and is certainly substantially better as an indicator of overall liver size than the ultrasonic linear measurements currently being used clinically. - Highlights: • A new model to calculate liver volumes from simple linear ultrasound measurements. • This model was compared to the linear measurements currently used clinically. • The new model holds value in tracking disease progress or response to treatment. • This model is better as an indicator of overall liver size.
Joshi, Shuchi N; Srinivas, Nuggehally R; Parmar, Deven V
2018-03-01
Our aim was to develop and validate the extrapolative performance of a regression model using a limited sampling strategy for accurate estimation of the area under the plasma concentration versus time curve for saroglitazar. Healthy subject pharmacokinetic data from a well-powered food-effect study (fasted vs fed treatments; n = 50) was used in this work. The first 25 subjects' serial plasma concentration data up to 72 hours and corresponding AUC 0-t (ie, 72 hours) from the fasting group comprised a training dataset to develop the limited sampling model. The internal datasets for prediction included the remaining 25 subjects from the fasting group and all 50 subjects from the fed condition of the same study. The external datasets included pharmacokinetic data for saroglitazar from previous single-dose clinical studies. Limited sampling models were composed of 1-, 2-, and 3-concentration-time points' correlation with AUC 0-t of saroglitazar. Only models with regression coefficients (R 2 ) >0.90 were screened for further evaluation. The best R 2 model was validated for its utility based on mean prediction error, mean absolute prediction error, and root mean square error. Both correlations between predicted and observed AUC 0-t of saroglitazar and verification of precision and bias using Bland-Altman plot were carried out. None of the evaluated 1- and 2-concentration-time points models achieved R 2 > 0.90. Among the various 3-concentration-time points models, only 4 equations passed the predefined criterion of R 2 > 0.90. Limited sampling models with time points 0.5, 2, and 8 hours (R 2 = 0.9323) and 0.75, 2, and 8 hours (R 2 = 0.9375) were validated. Mean prediction error, mean absolute prediction error, and root mean square error were prediction of saroglitazar. The same models, when applied to the AUC 0-t prediction of saroglitazar sulfoxide, showed mean prediction error, mean absolute prediction error, and root mean square error model predicts the exposure of
Directory of Open Access Journals (Sweden)
Giovanni Leopoldo Rozza
2015-09-01
Full Text Available With world becoming each day a global village, enterprises continuously seek to optimize their internal processes to hold or improve their competitiveness and make better use of natural resources. In this context, decision support tools are an underlying requirement. Such tools are helpful on predicting operational issues, avoiding cost risings, loss of productivity, work-related accident leaves or environmental disasters. This paper has its focus on the prediction of spent liquor caustic concentration of Bayer process for alumina production. Caustic concentration measuring is essential to keep it at expected levels, otherwise quality issues might arise. The organization requests caustic concentration by chemical analysis laboratory once a day, such information is not enough to issue preventive actions to handle process inefficiencies that will be known only after new measurement on the next day. Thereby, this paper proposes using Multiple Linear Regression and Artificial Neural Networks techniques a mathematical model to predict the spent liquor´s caustic concentration. Hence preventive actions will occur in real time. Such models were built using software tool for numerical computation (MATLAB and a statistical analysis software package (SPSS. The models output (predicted caustic concentration were compared with the real lab data. We found evidence suggesting superior results with use of Artificial Neural Networks over Multiple Linear Regression model. The results demonstrate that replacing laboratorial analysis by the forecasting model to support technical staff on decision making could be feasible.
Recent advances in gyrokinetic full-f particle simulation of medium sized Tokamaks with ELMFIRE
International Nuclear Information System (INIS)
Janhunen, S.J.; Kiviniemi, T.P.; Korpio, T.; Leerink, S.; Nora, M.; Heikkinen, J.A.; Ogando, F.
2010-01-01
Large-scale kinetic simulations of toroidal plasmas based on first principles are called for in studies of transition from low to high confinement mode and internal transport barrier formation in the core plasma. Such processes are best observed and diagnosed in detached plasma conditions in mid-sized tokamaks, so gyrokinetic simulations for these conditions are warranted. A first principles test-particle based kinetic model ELMFIRE[1] has been developed and used in interpretation[1,2] of FT-2 and DIII-D experiments. In this work we summarize progress in Cyclone (DIII-D core) and ASDEX Upgrade pedestal region simulations, and show that in simulations the choice of adiabatic electrons results in quenching of turbulence (copyright 2010 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Grid-based Parallel Data Streaming Implemented for the Gyrokinetic Toroidal Code
International Nuclear Information System (INIS)
Klasky, S.; Ethier, S.; Lin, Z.; Martins, K.; McCune, D.; Samtaney, R.
2003-01-01
We have developed a threaded parallel data streaming approach using Globus to transfer multi-terabyte simulation data from a remote supercomputer to the scientist's home analysis/visualization cluster, as the simulation executes, with negligible overhead. Data transfer experiments show that this concurrent data transfer approach is more favorable compared with writing to local disk and then transferring this data to be post-processed. The present approach is conducive to using the grid to pipeline the simulation with post-processing and visualization. We have applied this method to the Gyrokinetic Toroidal Code (GTC), a 3-dimensional particle-in-cell code used to study microturbulence in magnetic confinement fusion from first principles plasma theory
Gyrokinetic Calculations of Microturbulence and Transport for NSTX and Alcator-CMOD H-modes
International Nuclear Information System (INIS)
Redi, M.H.; Dorland, W.; Bell, R.; Bonoli, P.; Bourdelle, C.; Candy, J.; Ernst, D.; Fiore, C.; Gates, D.; Hammett, G.; Hill, K.; Kaye, S.; LeBlanc, B.; Menard, J.; Mikkelsen, D.; Rewoldt, G.; Rice, J.; Waltz, R.; Wukitch, S.
2003-01-01
Recent H-mode experiments on NSTX [National Spherical Torus Experiment] and experiments on Alcator-CMOD, which also exhibit internal transport barriers (ITB), have been examined with gyrokinetic simulations with the GS2 and GYRO codes to identify the underlying key plasma parameters for control of plasma performance and, ultimately, the successful operation of future reactors such as ITER [International Thermonuclear Experimental Reactor]. On NSTX the H-mode is characterized by remarkably good ion confinement and electron temperature profiles highly resilient in time. On CMOD, an ITB with a very steep electron density profile develops following off-axis radio-frequency heating and establishment of H-mode. Both experiments exhibit ion thermal confinement at the neoclassical level. Electron confinement is also good in the CMOD core
Nonlinear gyrokinetic equations for low-frequency electromagnetic waves in general plasma equilibria
International Nuclear Information System (INIS)
Frieman, E.A.; Chen, L.
1981-10-01
A nonlinear gyrokinetic formalism for low-frequency (less than the cyclotron frequency) microscopic electromagnetic perturbations in general magnetic field configurations is developed. The nonlinear equations thus derived are valid in the strong-turbulence regime and contain effects due to finite Larmor radius, plasma inhomogeneities, and magentic field geometries. The specific case of axisymmetric tokamaks is then considered, and a model nonlinear equation is derived for electrostatic drift waves. Also, applying the formalism to the shear Alfven wave heating sceme, it is found that nonlinear ion Landau damping of kinetic shear-Alfven waves is modified, both qualitatively and quantitatively, by the diamagnetic drift effects. In particular, wave energy is found to cascade in wavenumber instead of frequency
The implementation of a toroidal limiter model into the gyrokinetic code ELMFIRE
Energy Technology Data Exchange (ETDEWEB)
Leerink, S.; Janhunen, S.J.; Kiviniemi, T.P.; Nora, M. [Euratom-Tekes Association, Helsinki University of Technology (Finland); Heikkinen, J.A. [Euratom-Tekes Association, VTT, P.O. Box 1000, FI-02044 VTT (Finland); Ogando, F. [Universidad Nacional de Educacion a Distancia, Madrid (Spain)
2008-03-15
The ELMFIRE full nonlinear gyrokinetic simulation code has been developed for calculations of plasma evolution and dynamics of turbulence in tokamak geometry. The code is applicable for calculations of strong perturbations in particle distribution function, rapid transients and steep gradients in plasma. Benchmarking against experimental reflectometry data from the FT2 tokamak is being discussed and in this paper a model for comparison and studying poloidal velocity is presented. To make the ELMFIRE code suitable for scrape-off layer simulations a simplified toroidal limiter model has been implemented. The model is be discussed and first results are presented. (copyright 2008 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Recent advances in gyrokinetic full-f particle simulation of medium sized Tokamaks with ELMFIRE
Energy Technology Data Exchange (ETDEWEB)
Janhunen, S.J.; Kiviniemi, T.P.; Korpio, T.; Leerink, S.; Nora, M. [Helsinki University of Technology, Euratom-Tekes Association, Espoo (Finland); Heikkinen, J.A. [VTT, Euratom-Tekes Association, Espoo (Finland); Ogando, F. [Helsinki University of Technology, Euratom-Tekes Association, Espoo (Finland); Universidad Nacional de Educacion a Distancia, Madrid (Spain)
2010-05-15
Large-scale kinetic simulations of toroidal plasmas based on first principles are called for in studies of transition from low to high confinement mode and internal transport barrier formation in the core plasma. Such processes are best observed and diagnosed in detached plasma conditions in mid-sized tokamaks, so gyrokinetic simulations for these conditions are warranted. A first principles test-particle based kinetic model ELMFIRE[1] has been developed and used in interpretation[1,2] of FT-2 and DIII-D experiments. In this work we summarize progress in Cyclone (DIII-D core) and ASDEX Upgrade pedestal region simulations, and show that in simulations the choice of adiabatic electrons results in quenching of turbulence (copyright 2010 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Managing locality in grand challenge applications: a case study of the gyrokinetic toroidal code
Energy Technology Data Exchange (ETDEWEB)
Marin, G; Jin, G; Mellor-Crummey, J [Department of Computer Science, Rice University, Houston, TX 77005 (United States)
2008-07-15
Achieving high performance with grand challenge applications on today's large-scale parallel systems requires tailoring applications for the characteristics of the modern microprocessor architectures. As part of the US Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, we studied and tuned the Gyrokinetic Toroidal Code (GTC), a particle-in-cell code for simulating turbulent transport of particles and energy in burning plasma, developed at Princeton Plasma Physics Laboratory. In this paper, we present a performance study of the application that revealed several opportunities for improving performance by enhancing its data locality. We tuned GTC by performing three kinds of transformations: static data structure reorganization to improve spatial locality, loop nest restructuring for better temporal locality, and dynamic data reordering at run-time to enhance both spatial and temporal reuse. Experimental results show that these changes improve execution time by more than 20% on large parallel systems, including a Cray XT4.
A Systematic Method for Verification and Validation of Gyrokinetic Microstability Codes
Energy Technology Data Exchange (ETDEWEB)
Bravenec, Ronald [Fourth State Research, Austin, TX (United States)
2017-11-14
My original proposal for the period Feb. 15, 2014 through Feb. 14, 2017 called for an integrated validation and verification effort carried out by myself with collaborators. The validation component would require experimental profile and power-balance analysis. In addition, it would require running the gyrokinetic codes varying the input profiles within experimental uncertainties to seek agreement with experiment before discounting a code as invalidated. Therefore, validation would require a major increase of effort over my previous grant periods which covered only code verification (code benchmarking). Consequently, I had requested full-time funding. Instead, I am being funded at somewhat less than half time (5 calendar months per year). As a consequence, I decided to forego the validation component and to only continue the verification efforts.
Managing locality in grand challenge applications: a case study of the gyrokinetic toroidal code
International Nuclear Information System (INIS)
Marin, G; Jin, G; Mellor-Crummey, J
2008-01-01
Achieving high performance with grand challenge applications on today's large-scale parallel systems requires tailoring applications for the characteristics of the modern microprocessor architectures. As part of the US Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, we studied and tuned the Gyrokinetic Toroidal Code (GTC), a particle-in-cell code for simulating turbulent transport of particles and energy in burning plasma, developed at Princeton Plasma Physics Laboratory. In this paper, we present a performance study of the application that revealed several opportunities for improving performance by enhancing its data locality. We tuned GTC by performing three kinds of transformations: static data structure reorganization to improve spatial locality, loop nest restructuring for better temporal locality, and dynamic data reordering at run-time to enhance both spatial and temporal reuse. Experimental results show that these changes improve execution time by more than 20% on large parallel systems, including a Cray XT4
SciDAC GSEP: Gyrokinetic Simulation of Energetic Particle Turbulence and Transport
Energy Technology Data Exchange (ETDEWEB)
Lin, Zhihong [Univ. of California, Irvine, CA (United States)
2017-12-30
Energetic particle (EP) confinement is a key physics issue for burning plasma experiment ITER, the crucial next step in the quest for clean and abundant energy, since ignition relies on self-heating by energetic fusion products (α-particles). Due to the strong coupling of EP with burning thermal plasmas, plasma confinement property in the ignition regime is one of the most uncertain factors when extrapolating from existing fusion devices to the ITER tokamak. EP population in current tokamaks are mostly produced by auxiliary heating such as neutral beam injection (NBI) and radio frequency (RF) heating. Remarkable progress in developing comprehensive EP simulation codes and understanding basic EP physics has been made by two concurrent SciDAC EP projects GSEP funded by the Department of Energy (DOE) Office of Fusion Energy Science (OFES), which have successfully established gyrokinetic turbulence simulation as a necessary paradigm shift for studying the EP confinement in burning plasmas. Verification and validation have rapidly advanced through close collaborations between simulation, theory, and experiment. Furthermore, productive collaborations with computational scientists have enabled EP simulation codes to effectively utilize current petascale computers and emerging exascale computers. We review here key physics progress in the GSEP projects regarding verification and validation of gyrokinetic simulations, nonlinear EP physics, EP coupling with thermal plasmas, and reduced EP transport models. Advances in high performance computing through collaborations with computational scientists that enable these large scale electromagnetic simulations are also highlighted. These results have been widely disseminated in numerous peer-reviewed publications including many Phys. Rev. Lett. papers and many invited presentations at prominent fusion conferences such as the biennial International Atomic Energy Agency (IAEA) Fusion Energy Conference and the annual meeting of the
Nonlinear Gyrokinetics: A Powerful Tool for the Description of Microturbulence in Magnetized Plasmas
International Nuclear Information System (INIS)
Krommes, John E.
2010-01-01
Gyrokinetics is the description of low-frequency dynamics in magnetized plasmas. In magnetic-confinement fusion, it provides the most fundamental basis for numerical simulations of microturbulence; there are astrophysical applications as well. In this tutorial, a sketch of the derivation of the novel dynamical system comprising the nonlinear gyrokinetic (GK) equation (GKE) and the coupled electrostatic GK Poisson equation will be given by using modern Lagrangian and Lie perturbation methods. No background in plasma physics is required in order to appreciate the logical development. The GKE describes the evolution of an ensemble of gyrocenters moving in a weakly inhomogeneous background magnetic field and in the presence of electromagnetic perturbations with wavelength of the order of the ion gyroradius. Gyrocenters move with effective drifts, which may be obtained by an averaging procedure that systematically, order by order, removes gyrophase dependence. To that end, the use of the Lagrangian differential one-form as well as the content and advantages of Lie perturbation theory will be explained. The electromagnetic fields follow via Maxwell's equations from the charge and current density of the particles. Particle and gyrocenter densities differ by an important polarization effect. That is calculated formally by a 'pull-back' (a concept from differential geometry) of the gyrocenter distribution to the laboratory coordinate system. A natural truncation then leads to the closed GK dynamical system. Important properties such as GK energy conservation and fluctuation noise will be mentioned briefly, as will the possibility (and diffculties) of deriving nonlinear gyro fluid equations suitable for rapid numerical solution - although it is probably best to directly simulate the GKE. By the end of the tutorial, students should appreciate the GKE as an extremely powerful tool and will be prepared for later lectures describing its applications to physical problems.
Nonlinear gyrokinetics: a powerful tool for the description of microturbulence in magnetized plasmas
International Nuclear Information System (INIS)
Krommes, John A
2010-01-01
Gyrokinetics is the description of low-frequency dynamics in magnetized plasmas. In magnetic-confinement fusion, it provides the most fundamental basis for numerical simulations of microturbulence; there are astrophysical applications as well. In this tutorial, a sketch of the derivation of the novel dynamical system comprising the nonlinear gyrokinetic (GK) equation (GKE) and the coupled electrostatic GK Poisson equation will be given by using modern Lagrangian and Lie perturbation methods. No background in plasma physics is required in order to appreciate the logical development. The GKE describes the evolution of an ensemble of gyrocenters moving in a weakly inhomogeneous background magnetic field and in the presence of electromagnetic perturbations with wavelength of the order of the ion gyroradius. Gyrocenters move with effective drifts, which may be obtained by an averaging procedure that systematically, order by order, removes gyrophase dependence. To that end, the use of the Lagrangian differential one-form as well as the content and advantages of Lie perturbation theory will be explained. The electromagnetic fields follow via Maxwell's equations from the charge and current density of the particles. Particle and gyrocenter densities differ by an important polarization effect. That is calculated formally by a 'pull-back' (a concept from differential geometry) of the gyrocenter distribution to the laboratory coordinate system. A natural truncation then leads to the closed GK dynamical system. Important properties such as GK energy conservation and fluctuation noise will be mentioned briefly, as will the possibility (and difficulties) of deriving nonlinear gyrofluid equations suitable for rapid numerical solution-although it is probably best to directly simulate the GKE. By the end of the tutorial, students should appreciate the GKE as an extremely powerful tool and will be prepared for later lectures describing its applications to physical problems.
First-principle description of collisional gyrokinetic turbulence in tokamak plasmas
Energy Technology Data Exchange (ETDEWEB)
Dif-Pradalier, G
2008-10-15
This dissertation starts in chapter 1 with a comprehensive introduction to nuclear fusion, its basic physics, goals and means. It especially defines the concept of a fusion plasma and some of its essential physical properties. The following chapter 2 discusses some fundamental concepts of statistical physics. It introduces the kinetic and the fluid frameworks, compares them and highlights their respective strengths and limitations. The end of the chapter is dedicated to the fluid theory. It presents two new sets of closure relations for fluid equations which retain important pieces of physics, relevant in the weakly collisional tokamak regimes: collective resonances which lead to Landau damping and entropy production. Nonetheless, since the evolution of the turbulence is intrinsically nonlinear and deeply influenced by velocity space effects, a kinetic collisional description is most relevant. First focusing on the kinetic aspect, chapter 3 introduces the so-called gyrokinetic framework along with the numerical solver - the GYSELA code - which will be used throughout this dissertation. Very generically, code solving is an initial value problem. The impact on turbulent nonlinear evolution of out of equilibrium initial conditions is discussed while studying transient flows, self-organizing dynamics and memory effects due to initial conditions. This dissertation introduces an operational definition, now of routine use in the GYSELA code, for the initial state and concludes on the special importance of the accurate calculation of the radial electric field. The GYSELA framework is further extended in chapter 4 to describe Coulomb collisions. The implementation of a collision operator acting on the full distribution function is presented. Its successful confrontation to collisional theory (neoclassical theory) is also shown. GYSELA is now part of the few gyrokinetic codes which can self-consistently address the interplay between turbulence and collisions. While
First-principle description of collisional gyrokinetic turbulence in tokamak plasmas
International Nuclear Information System (INIS)
Dif-Pradalier, G.
2008-10-01
This dissertation starts in chapter 1 with a comprehensive introduction to nuclear fusion, its basic physics, goals and means. It especially defines the concept of a fusion plasma and some of its essential physical properties. The following chapter 2 discusses some fundamental concepts of statistical physics. It introduces the kinetic and the fluid frameworks, compares them and highlights their respective strengths and limitations. The end of the chapter is dedicated to the fluid theory. It presents two new sets of closure relations for fluid equations which retain important pieces of physics, relevant in the weakly collisional tokamak regimes: collective resonances which lead to Landau damping and entropy production. Nonetheless, since the evolution of the turbulence is intrinsically nonlinear and deeply influenced by velocity space effects, a kinetic collisional description is most relevant. First focusing on the kinetic aspect, chapter 3 introduces the so-called gyrokinetic framework along with the numerical solver - the GYSELA code - which will be used throughout this dissertation. Very generically, code solving is an initial value problem. The impact on turbulent nonlinear evolution of out of equilibrium initial conditions is discussed while studying transient flows, self-organizing dynamics and memory effects due to initial conditions. This dissertation introduces an operational definition, now of routine use in the GYSELA code, for the initial state and concludes on the special importance of the accurate calculation of the radial electric field. The GYSELA framework is further extended in chapter 4 to describe Coulomb collisions. The implementation of a collision operator acting on the full distribution function is presented. Its successful confrontation to collisional theory (neoclassical theory) is also shown. GYSELA is now part of the few gyrokinetic codes which can self-consistently address the interplay between turbulence and collisions. While
Cui, Haibo; Wei, Xiaomei; Huang, Yu; Hu, Bin; Fang, Yaping; Wang, Jia
2014-01-01
Among human influenza viruses, strain A/H3N2 accounts for over a quarter of a million deaths annually. Antigenic variants of these viruses often render current vaccinations ineffective and lead to repeated infections. In this study, a computational model was developed to predict antigenic variants of the A/H3N2 strain. First, 18 critical antigenic amino acids in the hemagglutinin (HA) protein were recognized using a scoring method combining phi (ϕ) coefficient and information entropy. Next, a prediction model was developed by integrating multiple linear regression method with eight types of physicochemical changes in critical amino acid positions. When compared to other three known models, our prediction model achieved the best performance not only on the training dataset but also on the commonly-used testing dataset composed of 31878 antigenic relationships of the H3N2 influenza virus.
Fragkaki, A G; Farmaki, E; Thomaidis, N; Tsantili-Kakoulidou, A; Angelis, Y S; Koupparis, M; Georgakopoulos, C
2012-09-21
The comparison among different modelling techniques, such as multiple linear regression, partial least squares and artificial neural networks, has been performed in order to construct and evaluate models for prediction of gas chromatographic relative retention times of trimethylsilylated anabolic androgenic steroids. The performance of the quantitative structure-retention relationship study, using the multiple linear regression and partial least squares techniques, has been previously conducted. In the present study, artificial neural networks models were constructed and used for the prediction of relative retention times of anabolic androgenic steroids, while their efficiency is compared with that of the models derived from the multiple linear regression and partial least squares techniques. For overall ranking of the models, a novel procedure [Trends Anal. Chem. 29 (2010) 101-109] based on sum of ranking differences was applied, which permits the best model to be selected. The suggested models are considered useful for the estimation of relative retention times of designer steroids for which no analytical data are available. Copyright © 2012 Elsevier B.V. All rights reserved.
Mendez, Javier; Monleon-Getino, Antonio; Jofre, Juan; Lucena, Francisco
2017-10-01
The present study aimed to establish the kinetics of the appearance of coliphage plaques using the double agar layer titration technique to evaluate the feasibility of using traditional coliphage plaque forming unit (PFU) enumeration as a rapid quantification method. Repeated measurements of the appearance of plaques of coliphages titrated according to ISO 10705-2 at different times were analysed using non-linear mixed-effects regression to determine the most suitable model of their appearance kinetics. Although this model is adequate, to simplify its applicability two linear models were developed to predict the numbers of coliphages reliably, using the PFU counts as determined by the ISO after only 3 hours of incubation. One linear model, when the number of plaques detected was between 4 and 26 PFU after 3 hours, had a linear fit of: (1.48 × Counts 3 h + 1.97); and the other, values >26 PFU, had a fit of (1.18 × Counts 3 h + 2.95). If the number of plaques detected was PFU after 3 hours, we recommend incubation for (18 ± 3) hours. The study indicates that the traditional coliphage plating technique has a reasonable potential to provide results in a single working day without the need to invest in additional laboratory equipment.
A linear model to predict with a multi-spectral radiometer the amount of nitrogen in winter wheat
Reyniers, M.; Walvoort, D.J.J.; Baardemaaker, De J.
2006-01-01
The objective was to develop an optimal vegetation index (VIopt) to predict with a multi-spectral radiometer nitrogen in wheat crop (kg[N] ha-1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are
Comparison between measured and predicted turbulence frequency spectra in ITG and TEM regimes
Citrin, J.; Arnichand, H.; Bernardo, J.; Bourdelle, C.; Garbet, X.; Jenko, F.; Hacquin, S.; Pueschel, M. J.; Sabot, R.
2017-06-01
The observation of distinct peaks in tokamak core reflectometry measurements—named quasi-coherent-modes (QCMs)—are identified as a signature of trapped-electron-mode (TEM) turbulence (Arnichand et al 2016 Plasma Phys. Control. Fusion 58 014037). This phenomenon is investigated with detailed linear and nonlinear gyrokinetic simulations using the Gene code. A Tore-Supra density scan is studied, which traverses through a linear (LOC) to saturated (SOC) ohmic confinement transition. The LOC and SOC phases are both simulated separately. In the LOC phase, where QCMs are observed, TEMs are robustly predicted unstable in linear studies. In the later SOC phase, where QCMs are no longer observed, ion-temperature-gradient (ITG) modes are identified. In nonlinear simulations, in the ITG (SOC) phase, a broadband spectrum is seen. In the TEM (LOC) phase, a clear emergence of a peak at the TEM frequencies is seen. This is due to reduced nonlinear frequency broadening of the underlying linear modes in the TEM regime compared with the ITG regime. A synthetic diagnostic of the nonlinearly simulated frequency spectra reproduces the features observed in the reflectometry measurements. These results support the identification of core QCMs as an experimental marker for TEM turbulence.
DEFF Research Database (Denmark)
Minko, Tomasz; Wisniewski, Rafal; Bendtsen, Jan Dimon
2016-01-01
. The retrieved heat excess can be stored in the water tank. For this purpose the charging and the discharging water loops has been designed. We present the non-linear model of the above described system and a non-linear model predictive supervisory controller that according to the received price signal......, occupancy information and ambient temperature minimizes the operation cost of the whole system and distributes set points to local controllers of supermarkets subsystems. We find that when reliable information about the high price period is available, it is profitable to use the refrigeration system...... to generate heat during the low price period, store it and use it to substitute the conventional heater during the high price period....
International Nuclear Information System (INIS)
Diani, J.; Bedoui, F.; Regnier, G.
2008-01-01
The relevance of micromechanics modeling to the linear viscoelastic behavior of semi-crystalline polymers is studied. For this purpose, the linear viscoelastic behaviors of amorphous and semi-crystalline PETs are characterized. Then, two micromechanics modeling methods, which have been proven in a previous work to apply to the PET elastic behavior, are used to predict the viscoelastic behavior of three semi-crystalline PETs. The microstructures of the crystalline PETs are clearly defined using WAXS techniques. Since microstructures and mechanical properties of both constitutive phases (the crystalline and the amorphous) are defined, the simulations are run without adjustable parameters. Results show that the models are unable to reproduce the substantial decrease of viscosity induced by the increase of crystallinity. Unlike the real materials, for moderate crystallinity, both models show materials of viscosity nearly identical to the amorphous material
Kim, Kyuho; Kwon, Jae-Min; Chang, C. S.; Seo, Janghoon; Ku, S.; Choe, W.
2017-06-01
Flux-driven full-f gyrokinetic simulations are performed to study carbon impurity effects on the ion temperature gradient (ITG) turbulence and ion thermal transport in a toroidal geometry. Employing the full-f gyrokinetic code XGC1, both main ions and impurities are evolved self-consistently including turbulence and neoclassical physics. It is found that the carbon impurity profile self-organizes to form an inwardly peaked density profile, which weakens the ITG instabilities and reduces the overall fluctuations and ion thermal transport. A stronger reduction appears in the low frequency components of the fluctuations. The global structure of E × B flow also changes, resulting in the reduction of global avalanche like transport events in the impure plasma. Detailed properties of impurity transport are also studied, and it is revealed that both the inward neoclassical pinch and the outward turbulent transport are equally important in the formation of the steady state impurity profile.
Directory of Open Access Journals (Sweden)
Xiaowei Li
2017-01-01
Full Text Available The risk of coal and gas outbursts can be predicted using a method that is linear and continuous and based on the initial gas flow in the borehole (IGFB; this method is significantly superior to the traditional point prediction method. Acquiring accurate critical values is the key to ensuring accurate predictions. Based on ideal rock cross-cut coal uncovering model, the IGFB measurement device was developed. The present study measured the data of the initial gas flow over 3 min in a 1 m long borehole with a diameter of 42 mm in the laboratory. A total of 48 sets of data were obtained. These data were fuzzy and chaotic. Fisher’s discrimination method was able to transform these spatial data, which were multidimensional due to the factors influencing the IGFB, into a one-dimensional function and determine its critical value. Then, by processing the data into a normal distribution, the critical values of the outbursts were analyzed using linear discriminant analysis with Fisher’s criterion. The weak and strong outbursts had critical values of 36.63 L and 80.85 L, respectively, and the accuracy of the back-discriminant analysis for the weak and strong outbursts was 94.74% and 92.86%, respectively. Eight outburst tests were simulated in the laboratory, the reverse verification accuracy was 100%, and the accuracy of the critical value was verified.
Directory of Open Access Journals (Sweden)
M Taki
2017-05-01
Full Text Available Introduction Controlling greenhouse microclimate not only influences the growth of plants, but also is critical in the spread of diseases inside the greenhouse. The microclimate parameters were inside air, greenhouse roof and soil temperature, relative humidity and solar radiation intensity. Predicting the microclimate conditions inside a greenhouse and enabling the use of automatic control systems are the two main objectives of greenhouse climate model. The microclimate inside a greenhouse can be predicted by conducting experiments or by using simulation. Static and dynamic models are used for this purpose as a function of the metrological conditions and the parameters of the greenhouse components. Some works were done in past to 2015 year to simulation and predict the inside variables in different greenhouse structures. Usually simulation has a lot of problems to predict the inside climate of greenhouse and the error of simulation is higher in literature. The main objective of this paper is comparison between heat transfer and regression models to evaluate them to predict inside air and roof temperature in a semi-solar greenhouse in Tabriz University. Materials and Methods In this study, a semi-solar greenhouse was designed and constructed at the North-West of Iran in Azerbaijan Province (geographical location of 38°10′ N and 46°18′ E with elevation of 1364 m above the sea level. In this research, shape and orientation of the greenhouse, selected between some greenhouses common shapes and according to receive maximum solar radiation whole the year. Also internal thermal screen and cement north wall was used to store and prevent of heat lost during the cold period of year. So we called this structure, ‘semi-solar’ greenhouse. It was covered with glass (4 mm thickness. It occupies a surface of approximately 15.36 m2 and 26.4 m3. The orientation of this greenhouse was East–West and perpendicular to the direction of the wind prevailing
Directory of Open Access Journals (Sweden)
Elena Vital'evna Bykova
2011-09-01
Full Text Available This paper describes the concept of energy security and a system of indicators for its monitoring. The indicator system includes more than 40 parameters that reflect the structure and state of fuel and energy complex sectors (fuel, electricity and heat & power, as well as takes into account economic, environmental and social aspects. A brief description of the structure of the computer system to monitor and analyze energy security is given. The complex contains informational, analytical and calculation modules, provides applications for forecasting and modeling energy scenarios, modeling threats and determining levels of energy security. Its application to predict the values of the indicators and methods developed for it are described. This paper presents a method developed by conventional nonlinear mathematical programming needed to address several problems of energy and, in particular, the prediction problem of the security. An example of its use and implementation of this method in the application, "Prognosis", is also given.
Prinstein, Mitchell J; Choukas-Bradley, Sophia C; Helms, Sarah W; Brechwald, Whitney A; Rancourt, Diana
2011-10-01
In contrast to prior work, recent theory suggests that high, not low, levels of adolescent peer popularity may be associated with health risk behavior. This study examined (a) whether popularity may be uniquely associated with cigarette use, marijuana use, and sexual risk behavior, beyond the predictive effects of aggression; (b) whether the longitudinal association between popularity and health risk behavior may be curvilinear; and (c) gender moderation. A total of 336 adolescents, initially in 10-11th grades, reported cigarette use, marijuana use, and number of sexual intercourse partners at two time points 18 months apart. Sociometric peer nominations were used to examine popularity and aggression. Longitudinal quadratic effects and gender moderation suggest that both high and low levels of popularity predict some, but not all, health risk behaviors. New theoretical models can be useful for understanding the complex manner in which health risk behaviors may be reinforced within the peer context.
Melchiorre, C.; Castellanos Abella, E. A.; van Westen, C. J.; Matteucci, M.
2011-04-01
This paper describes a procedure for landslide susceptibility assessment based on artificial neural networks, and focuses on the estimation of the prediction capability, robustness, and sensitivity of susceptibility models. The study is carried out in the Guantanamo Province of Cuba, where 186 landslides were mapped using photo-interpretation. Twelve conditioning factors were mapped including geomorphology, geology, soils, landuse, slope angle, slope direction, internal relief, drainage density, distance from roads and faults, rainfall intensity, and ground peak acceleration. A methodology was used that subdivided the database in 3 subsets. A training set was used for updating the weights. A validation set was used to stop the training procedure when the network started losing generalization capability, and a test set was used to calculate the performance of the network. A 10-fold cross-validation was performed in order to show that the results are repeatable. The prediction capability, the robustness analysis, and the sensitivity analysis were tested on 10 mutually exclusive datasets. The results show that by means of artificial neural networks it is possible to obtain models with high prediction capability and high robustness, and that an exploration of the effect of the individual variables is possible, even if they are considered as a black-box model.
Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol
2010-12-01
Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Lashmore-Davies, C.N.; Fuchs, V.; Dendy, R.O.
1993-01-01
A full-wave equation has been obtained from the gyrokinetic theory for the fast wave traversing a minority cyclotron resonance [Phys. Fluids B 4, 493 (1992)] with the aid of the fast wave approximation [Phys. Fluids 31, 1614 (1988)]. This theory describes the transmission, reflection, and absorption of the fast wave for arbitrary values of the parallel wave number. For oblique propagation the absorption is due to both ion cyclotron damping by minority ions and mode conversion to the ion Bernstein wave. The results for a 3 He minority in a D plasma indicate that for perpendicular propagation and minority temperatures of a few keV the power lost by the fast wave is all mode converted whereas for minority temperatures ∼100 keV∼30% of the incident power is dissipated by the minority ions due to the gyrokinetic correction. The gyrokinetic correction also results in a significant reduction in the reflection coefficient for low field side incidence when k zLB approx-lt 1 and the minority and hybrid resonances overlap
International Nuclear Information System (INIS)
Kumar, Ajay; Ravi, P.M.; Guneshwar, S.L.; Rout, Sabyasachi; Mishra, Manish K.; Pulhani, Vandana; Tripathi, R.M.
2018-01-01
Numerous common methods (batch laboratory, the column laboratory, field-batch method, field modeling and K 0c method) are used frequently for determination of K d values. Recently, multiple regression models are considered as new best estimates for predicting the K d of radionuclides in the environment. It is also well known fact that the K d value is highly influenced by physico-chemical properties of sediment. Due to the significant variability in influencing parameters, the measured K d values can range over several orders of magnitude under different environmental conditions. The aim of this study is to develop a predictive model for K d values of 137 Cs and 60 Co based on the sediment properties using multiple linear regression analysis
Energy Technology Data Exchange (ETDEWEB)
Chowdhury, J.; Wan, Weigang; Chen, Yang; Parker, Scott E. [Department of Physics, University of Colorado, Boulder, Colorado 80309 (United States); Groebner, Richard J. [General Atomics, Post Office Box 85068, San Diego, California 92186 (United States); Holland, C. [University of California at San Diego, La Jolla, California 92093 (United States); Howard, N. T. [Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee 37831 (United States)
2014-11-15
The δ f particle-in-cell code GEM is used to study the transport “shortfall” problem of gyrokinetic simulations. In local simulations, the GEM results confirm the previously reported simulation results of DIII-D [Holland et al., Phys. Plasmas 16, 052301 (2009)] and Alcator C-Mod [Howard et al., Nucl. Fusion 53, 123011 (2013)] tokamaks with the continuum code GYRO. Namely, for DIII-D the simulations closely predict the ion heat flux at the core, while substantially underpredict transport towards the edge; while for Alcator C-Mod, the simulations show agreement with the experimental values of ion heat flux, at least within the range of experimental error. Global simulations are carried out for DIII-D L-mode plasmas to study the effect of edge turbulence on the outer core ion heat transport. The edge turbulence enhances the outer core ion heat transport through turbulence spreading. However, this edge turbulence spreading effect is not enough to explain the transport underprediction.
de Bruin, Anique B H; Smits, Niels; Rikers, Remy M J P; Schmidt, Henk G
2008-11-01
In this study, the longitudinal relation between deliberate practice and performance in chess was examined using a linear mixed models analysis. The practice activities and performance ratings of young elite chess players, who were either in, or had dropped out of the Dutch national chess training, were analysed since they had started playing chess seriously. The results revealed that deliberate practice (i.e. serious chess study alone and serious chess play) strongly contributed to chess performance. The influence of deliberate practice was not only observable in current performance, but also over chess players' careers. Moreover, although the drop-outs' chess ratings developed more slowly over time, both the persistent and drop-out chess players benefited to the same extent from investments in deliberate practice. Finally, the effect of gender on chess performance proved to be much smaller than the effect of deliberate practice. This study provides longitudinal support for the monotonic benefits assumption of deliberate practice, by showing that over chess players' careers, deliberate practice has a significant effect on performance, and to the same extent for chess players of different ultimate performance levels. The results of this study are not in line with critique raised against the deliberate practice theory that the factors deliberate practice and talent could be confounded.
International Nuclear Information System (INIS)
Maï, S El; Petit, J; Mercier, S; Molinari, A
2014-01-01
The fragmentation of structures subject to dynamic conditions is a matter of interest for civil industries as well as for Defence institutions. Dynamic expansions of structures, such as cylinders or rings, have been performed to obtain crucial information on fragment distributions. Many authors have proposed to capture by FEA the experimental distribution of fragment size by introducing in the FE model a perturbation. Stability and bifurcation analyses have also been proposed to describe the evolution of the perturbation growth rate. In the proposed contribution, the multiple necking of a round bar in dynamic tensile loading is analysed by the FE method. A perturbation on the initial flow stress is introduced in the numerical model to trigger instabilities. The onset time and the dominant mode of necking have been characterized precisely and showed power law evolutions, with the loading velocities and moderately with the amplitudes and the cell sizes of the perturbations. In the second part of the paper, the development of linear stability analysis and the use of salient criteria in terms of the growth rate of perturbations enabled comparisons with the numerical results. A good correlation in terms of onset time of instabilities and of number of necks is shown.
Nakamura, Kengo; Yasutaka, Tetsuo; Kuwatani, Tatsu; Komai, Takeshi
2017-11-01
In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multiscale gyrokinetics for rotating tokamak plasmas: fluctuations, transport and energy flows.
Abel, I G; Plunk, G G; Wang, E; Barnes, M; Cowley, S C; Dorland, W; Schekochihin, A A
2013-11-01
This paper presents a complete theoretical framework for studying turbulence and transport in rapidly rotating tokamak plasmas. The fundamental scale separations present in plasma turbulence are codified as an asymptotic expansion in the ratio ε = ρi/α of the gyroradius to the equilibrium scale length. Proceeding order by order in this expansion, a set of coupled multiscale equations is developed. They describe an instantaneous equilibrium, the fluctuations driven by gradients in the equilibrium quantities, and the transport-timescale evolution of mean profiles of these quantities driven by the interplay between the equilibrium and the fluctuations. The equilibrium distribution functions are local Maxwellians with each flux surface rotating toroidally as a rigid body. The magnetic equilibrium is obtained from the generalized Grad-Shafranov equation for a rotating plasma, determining the magnetic flux function from the mean pressure and velocity profiles of the plasma. The slow (resistive-timescale) evolution of the magnetic field is given by an evolution equation for the safety factor q. Large-scale deviations of the distribution function from a Maxwellian are given by neoclassical theory. The fluctuations are determined by the 'high-flow' gyrokinetic equation, from which we derive the governing principle for gyrokinetic turbulence in tokamaks: the conservation and local (in space) cascade of the free energy of the fluctuations (i.e. there is no turbulence spreading). Transport equations for the evolution of the mean density, temperature and flow velocity profiles are derived. These transport equations show how the neoclassical and fluctuating corrections to the equilibrium Maxwellian act back upon the mean profiles through fluxes and heating. The energy and entropy conservation laws for the mean profiles are derived from the transport equations. Total energy, thermal, kinetic and magnetic, is conserved and there is no net turbulent heating. Entropy is produced
Waltz, R. E.; Waelbroeck, F. L.
2012-03-01
Static external resonant magnetic field perturbations (RMPs) have been added to the gyrokinetic code GYRO [J. Candy and R. E. Waltz, J. Comp. Phys. 186, 545 (2003)]. This allows nonlinear gyrokinetic simulations of the nonambipolar radial current flow jr, and the corresponding j→×B→ plasma torque (density) R[jrBp/c], induced by magnetic islands that break the toroidal symmetry of a tokamak. This extends the previous GYRO formulation for the transport of toroidal angular momentum (TAM) [R. E. Waltz, G. M. Staebler, J. Candy, and F. L. Hinton, Phys. Plasmas 14, 122507 (2007); errata 16, 079902 (2009)]. The focus is on electrostatic full torus radial slice simulations of externally induced q =m/n=6/3 islands with widths 5% of the minor radius or about 20 ion gyroradii. Up to moderately strong E ×B rotation, the island torque scales with the radial electric field at the resonant surface Er, the island width w, and the intensity I of the high-n micro-turbulence, as Erw√I . The radial current inside the island is carried (entirely in the n =3 component) and almost entirely by the ion E ×B flux, since the electron E ×B and magnetic flutter particle fluxes are cancelled. The net island torque is null at zero Er rather than at zero toroidal rotation. This means that while the expected magnetic braking of the toroidal plasma rotation occurs at strong co- and counter-current rotation, at null toroidal rotation, there is a small co-directed magnetic acceleration up to the small diamagnetic (ion pressure gradient driven) co-rotation corresponding to the zero Er and null torque. This could be called the residual stress from an externally induced island. At zero Er, the only effect is the expected partial flattening of the electron temperature gradient within the island. Finite-beta GYRO simulations demonstrate almost complete RMP field screening and n =3 mode unlocking at strong Er.
Center for Gyrokinetic Particle Simulation of Turbulent Transport in Burning Plasma
International Nuclear Information System (INIS)
Decyk, Viktor K.
2008-01-01
The UCLA work on this grant was to design and help implement an object-oriented version of the GTC code, which is written in Fortran90. The GTC code is the main global gyrokinetic code used in this project, and over the years multiple, incompatible versions have evolved. The reason for this effort is to allow multiple authors to work together on GTC and to simplify future enhancements to GTC. The effort was designed to proceed incrementally. Initially, an upper layer of classes (derived types and methods) was implemented which called the original GTC code 'under the hood.' The derived types pointed to data in the original GTC code, and the methods called the original GTC subroutines. The original GTC code was modified only very slightly. This allowed one to define (and refine) a set of classes which described the important features of the GTC code in a new, more abstract way, with a minimum of implementation. Furthermore, classes could be added one at a time, and at the end of the each day, the code continued to work correctly. This work was done in close collaboration with Y. Nishimura from UC Irvine and Stefan Ethier from PPPL. Ten classes were ultimately defined and implemented: gyrokinetic and drift kinetic particles, scalar and vector fields, a mesh, jacobian, FLR, equilibrium, interpolation, and particles species descriptors. In the second state of this development, some of the scaffolding was removed. The constructors in the class objects now allocated the data and the array data in the original GTC code was removed. This isolated the components and now allowed multiple instantiations of the objects to be created, in particular, multiple ion species. Again, the work was done incrementally, one class at a time, so that the code was always working properly. This work was done in close collaboration with Y. Nishimura and W. Zhang from UC Irvine and Stefan Ethier from PPPL. The third stage of this work was to integrate the capabilities of the various versions of
International Nuclear Information System (INIS)
Monte, Luigi
2013-01-01
The present work describes the application of a non-linear Leslie model for predicting the effects of ionising radiation on wild populations. The model assumes that, for protracted chronic irradiation, the effect-dose relationship is linear. In particular, the effects of radiation are modelled by relating the increase in the mortality rates of the individuals to the dose rates through a proportionality factor C. The model was tested using independent data and information from a series of experiments that were aimed at assessing the response to radiation of wild populations of meadow voles and whose results were described in the international literature. The comparison of the model results with the data selected from the above mentioned experiments showed that the model overestimated the detrimental effects of radiation on the size of irradiated populations when the values of C were within the range derived from the median lethal dose (L 50 ) for small mammals. The described non-linear model suggests that the non-expressed biotic potential of the species whose growth is limited by processes of environmental resistance, such as the competition among the individuals of the same or of different species for the exploitation of the available resources, can be a factor that determines a more effective response of population to the radiation effects. -- Highlights: • A model to assess the radiation effects on wild population is described. • The model is based on non-linear Leslie matrix. • The model is applied to small mammals living in an irradiated meadow. • Model output is conservative if effect-dose factor estimated from L 50 is used. • Systemic response to stress of populations in competitive conditions may be more effective
Directory of Open Access Journals (Sweden)
Orkun Oztürk
Full Text Available BACKGROUND: Predicting type-1 Human Immunodeficiency Virus (HIV-1 protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy. RESULTS: We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs. We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations. CONCLUSION: Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper. SOFTWARE AVAILABILITY: The software is available at http
Energy Technology Data Exchange (ETDEWEB)
Buerke, Boris; Puesken, Michael; Heindel, Walter; Wessling, Johannes (Dept. of Clinical Radiology, Univ. of Muenster (Germany)), email: buerkeb@uni-muenster.de; Gerss, Joachim (Dept. of Medical Informatics and Biomathematics, Univ. of Muenster (Germany)); Weckesser, Matthias (Dept. of Nuclear Medicine, Univ. of Muenster (Germany))
2011-06-15
Background Volumetry of lymph nodes potentially better reflect asymmetric size alterations independently of lymph node orientation in comparison to metric parameters (e.g. long-axis diameter). Purpose To distinguish between benign and malignant lymph nodes by comparing 2D and semi-automatic 3D measurements in MSCT. Material and Methods FDG-18 PET-CT was performed in 33 patients prior to therapy for malignant melanoma at stage III/IV. One hundred and eighty-six cervico-axillary, abdominal and inguinal lymph nodes were evaluated independently by two radiologists, both manually and with the use of semi-automatic segmentation software. Long axis (LAD), short axis (SAD), maximal 3D diameter, volume and elongation were obtained. PET-CT, PET-CT follow-up and/or histology served as a combined reference standard. Statistics encompassed intra-class correlation coefficients and ROC curves. Results Compared to manual assessment, semi-automatic inter-observer variability was found to be lower, e.g. at 2.4% (95% CI 0.05-4.8) for LAD. The standard of reference revealed metastases in 90 (48%) of 186 lymph nodes. Semi-automatic prediction of lymph node metastases revealed highest areas under the ROC curves for volume (reader 1 0.77, 95%CI 0.64-0.90; reader 2 0.76, 95%CI 0.59-0.86) and SAD (reader 1 0.76, 95%CI 0.64-0.88; reader 2 0.75, 95%CI 0.62-0.89). The findings for LAD (reader 1 0.73, 95%CI 0.60-0.86; reader 2 0.71, 95%CI 0.71, 95%CI 0.57-0.85) and maximal 3D diameter (reader 1 0.70, 95%CI 0.53-0.86; reader 2 0.76, 95%CI 0.50-0.80) were found substantially lower and for elongation (reader 1 0.65, 95%CI 0.50-0.79; reader 2 0.66, 95%CI 0.52-0.81) significantly lower (p < 0.05). Conclusion Semi-automatic analysis of lymph nodes in malignant melanoma is supported by high segmentation quality and reproducibility. As compared to established SAD, semi-automatic lymph node volumetry does not have an additive role for categorizing lymph nodes as normal or metastatic in malignant
Memory-efficient optimization of Gyrokinetic particle-to-grid interpolation for multicore processors
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Madduri, Kamesh [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ethier, Stephane [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Shalf, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Strohmaier, Erich [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yelicky, Katherine [Univ. of California, Berkeley, CA (United States)
2009-01-01
We present multicore parallelization strategies for the particle-to-grid interpolation step in the Gyrokinetic Toroidal Code (GTC), a 3D particle-in-cell (PIC) application to study turbulent transport in magnetic-confinement fusion devices. Particle-grid interpolation is a known performance bottleneck in several PIC applications. In GTC, this step involves particles depositing charges to a 3D toroidal mesh, and multiple particles may contribute to the charge at a grid point. We design new parallel algorithms for the GTC charge deposition kernel, and analyze their performance on three leading multicore platforms. We implement thirteen different variants for this kernel and identify the best-performing ones given typical PIC parameters such as the grid size, number of particles per cell, and the GTC-specific particle Larmor radius variation. We find that our best strategies can be 2x faster than the reference optimized MPI implementation, and our analysis provides insight into desirable architectural features for high-performance PIC simulation codes.
Continuum Gyrokinetic Simulations of Turbulence in a Helical Model SOL with NSTX-type parameters
Hammett, G. W.; Shi, E. L.; Hakim, A.; Stoltzfus-Dueck, T.
2017-10-01
We have developed the Gkeyll code to carry out 3D2V full- F gyrokinetic simulations of electrostatic plasma turbulence in open-field-line geometries, using special versions of discontinuous-Galerkin algorithms to help with the computational challenges of the edge region. (Higher-order algorithms can also be helpful for exascale computing as they reduce the ratio of communications to computations.) Our first simulations with straight field lines were done for LAPD-type cases. Here we extend this to a helical model of an SOL plasma and show results for NSTX-type parameters. These simulations include the basic elements of a scrape-off layer: bad-curvature/interchange drive of instabilities, narrow sources to model plasma leaking from the core, and parallel losses with model sheath boundary conditions (our model allows currents to flow in and out of the walls). The formation of blobs is observed. By reducing the strength of the poloidal magnetic field, the heat flux at the divertor plate is observed to broaden. Supported by the Max-Planck/Princeton Center for Plasma Physics, the SciDAC Center for the Study of Plasma Microturbulence, and DOE Contract DE-AC02-09CH11466.
Gyrokinetic Calculations of Microinstabilities and Transport During RF H-Modes on Alcator C-Mod
International Nuclear Information System (INIS)
Redi, M.H.; Fiore, C.; Bonoli, P.; Bourdelle, C.; Budny, R.; Dorland, W.D.; Ernst, D.; Hammett, G.; Mikkelsen, D.; Rice, J.; Wukitch, S.
2002-01-01
Physics understanding for the experimental improvement of particle and energy confinement is being advanced through massively parallel calculations of microturbulence for simulated plasma conditions. The ultimate goal, an experimentally validated, global, non-local, fully nonlinear calculation of plasma microturbulence is still not within reach, but extraordinary progress has been achieved in understanding microturbulence, driving forces and the plasma response in recent years. In this paper we discuss gyrokinetic simulations of plasma turbulence being carried out to examine a reproducible, H-mode, RF heated experiment on the Alcator CMOD tokamak3, which exhibits an internal transport barrier (ITB). This off axis RF case represents the early phase of a very interesting dual frequency RF experiment, which shows density control with central RF heating later in the discharge. The ITB exhibits steep, spontaneous density peaking: a reduction in particle transport occurring without a central particle source. Since the central temperature is maintained while the central density is increasing, this also suggests a thermal transport barrier exists. TRANSP analysis shows that ceff drops inside the ITB. Sawtooth heat pulse analysis also shows a localized thermal transport barrier. For this ICRF EDA H-mode, the minority resonance is at r/a * 0.5 on the high field side. There is a normal shear profile, with q monotonic
Global gyrokinetic simulations of the H-mode tokamak edge pedestal
Energy Technology Data Exchange (ETDEWEB)
Wan, Weigang; Parker, Scott E.; Chen, Yang [Department of Physics, University of Colorado, Boulder, Colorado 80309 (United States); Groebner, Richard J. [General Atomics, Post Office Box 85068, San Diego, California 92186 (United States); Yan, Zheng [University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States); Pankin, Alexei Y.; Kruger, Scott E. [Tech-X Corporation, 5621 Arapahoe Ave., Boulder, Colorado 80305 (United States)
2013-05-15
Global gyrokinetic simulations of DIII-D H-mode edge pedestal show two types of instabilities may exist approaching the onset of edge localized modes: an intermediate-n, high frequency mode which we identify as the “kinetic peeling ballooning mode (KPBM),” and a high-n, low frequency mode. Our previous study [W. Wan et al., Phys. Rev. Lett. 109, 185004 (2012)] has shown that when the safety factor profile is flattened around the steep pressure gradient region, the high-n mode is clearly kinetic ballooning mode and becomes the dominant instability. Otherwise, the KPBM dominates. Here, the properties of the two instabilities are studied by varying the density and temperature profiles. It is found that the KPBM is destabilized by density and ion temperature gradient, and the high-n mode is mostly destabilized by electron temperature gradient. Nonlinear simulations with the KPBM saturate at high levels. The equilibrium radial electric field (E{sub r}) reduces the transport. The effect of the parallel equilibrium current is found to be weak.
Smoniewski, J.; Faber, B. J.; Sánchez, E.; Calvo, I.; Pueschel, M. J.; Likin, K. M.; Deng, C. B.; Talmadge, J. N.
2017-10-01
The Helically Symmetric eXperiment (HSX) has demonstrated reduced neoclassical transport in the plasma core with quasi-symmetry [Lore Thesis 2010], while outside this region the electron thermal diffusivity is well above the neoclassical level, likely due to the Trapped Electron Mode (TEM) [Weir PoP 2015, Faber PoP 2015]. We compare gyrokinetic simulations of the TEM to experimental heat flux and density fluctuation measurements for two configurations: Quasi-Helical Symmetry (QHS) and broken symmetry (Mirror). Both experiment and simulation show that the heat flux for Mirror is larger than for QHS by about a factor of two. Initial interferometer measurements provide evidence that density-gradient-driven TEMs are driving turbulence. Calculations of the collisionless damping of zonal flows provide another perspective into the difference between geometries. Similar to other stellarators [Monreal PPCF 2016], the zonal flow residual goes to zero at long wavelengths in both configurations. Additionally, the very short time decay of the zonal flow due to neoclassical polarization is constant between configurations. However, the collisionless damping time is longer and the zonal flow oscillation frequency is smaller in QHS than Mirror, consistent with reduced radial particle drifts. Work supported by the US DOE under Grant DE-FG02-93ER54222.
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Canciam, Cesar Augusto [Universidade Tecnologica Federal do Parana (UTFPR), Campus Ponta Grossa, PR (Brazil)], e-mail: canciam@utfpr.edu.br
2012-07-01
When evaluating the consumption of bio fuels, the knowledge of the density is of great importance for rectify the effect of temperature. The thermal expansion coefficient is a thermodynamic property that provides a measure of the density variation in response to temperature variation, keeping the pressure constant. This study aimed to predict the thermal expansion coefficients of ethyl bio diesels from castor beans, soybeans, sunflower seeds and Mabea fistulifera Mart. oils and of methyl bio diesels from soybeans, sunflower seeds, souari nut, cotton, coconut, castor beans and palm oils, from beef tallow, chicken fat and hydrogenated vegetable fat residual. For this purpose, there was a linear regression analysis of the density of each bio diesel a function of temperature. These data were obtained from other works. The thermal expansion coefficients for bio diesels are between 6.3729x{sup 10-4} and 1.0410x10{sup -3} degree C-1. In all the cases, the correlation coefficients were over 0.99. (author)
International Nuclear Information System (INIS)
Parra, Felix I.; Catto, Peter J.
2009-01-01
A recent publication [F. I. Parra and P. J. Catto, Plasma Phys. Controlled Fusion 50, 065014 (2008)] warned against the use of the lower order gyrokinetic Poisson equation at long wavelengths because the long wavelength, radial electric field must remain undetermined to the order the equation is obtained. Another reference [W. W. Lee and R. A. Kolesnikov, Phys. Plasmas 16, 044506 (2009)] criticizes these results by arguing that the higher order terms neglected in the most common gyrokinetic Poisson equation are formally smaller than the terms that are retained. This argument is flawed and ignores that the lower order terms, although formally larger, must cancel without determining the long wavelength, radial electric field. The reason for this cancellation is discussed. In addition, the origin of a nonlinear term present in the gyrokinetic Poisson equation [F. I. Parra and P. J. Catto, Plasma Phys. Controlled Fusion 50, 065014 (2008)] is explained.
Kouramas, K.I.
2011-08-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Xu, H.; Wang, Y.
1999-01-01
In this letter, a linear free energy relationship is used to predict the Gibbs free energies of formation of crystalline phases of pyrochlore and zirconolite families with stoichiometry of MCaTi 2 O 7 (or, CaMTi 2 O 7 ,) from the known thermodynamic properties of aqueous tetravalent cations (M 4+ ). The linear free energy relationship for tetravalent cations is expressed as ΔG f,M v X 0 =a M v X ΔG n,M 4+ 0 +b M v X +β M v X r M 4+ , where the coefficients a M v X , b M v X , and β M v X characterize a particular structural family of M v X, r M 4+ is the ionic radius of M 4+ cation, ΔG f,M v X 0 is the standard Gibbs free energy of formation of M v X, and ΔG n,M 4+ 0 is the standard non-solvation energy of cation M 4+ . The coefficients for the structural family of zirconolite with the stoichiometry of M 4+ CaTi 2 O 7 are estimated to be: a M v X =0.5717, b M v X =-4284.67 (kJ/mol), and β M v X =27.2 (kJ/mol nm). The coefficients for the structural family of pyrochlore with the stoichiometry of M 4+ CaTi 2 O 7 are estimated to be: a M v X =0.5717, b M v X =-4174.25 (kJ/mol), and β M v X =13.4 (kJ/mol nm). Using the linear free energy relationship, the Gibbs free energies of formation of various zirconolite and pyrochlore phases are calculated. (orig.)
Fridgeirsdottir, Gudrun A; Harris, Robert J; Dryden, Ian L; Fischer, Peter M; Roberts, Clive J
2018-03-29
Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two manufacturing techniques, spray-drying and melt extrusion. Each formulation underwent a six-month stability study at accelerated conditions, 40 °C and 75% relative humidity (RH). Significant differences in times to crystallization (onset of crystallization) were observed between both the different polymers and the two processing methods. Stability from zero days to over one year was observed. The extensive experimental data set obtained from this stability study was used to build multiple linear regression models to correlate physicochemical properties of the active pharmaceutical ingredients (API) with the stability data. The purpose of these models is to indicate which combination of processing method and polymer carrier is most likely to give a stable solid dispersion. Six quantitative mathematical multiple linear regression-based models were produced based on selection of the most influential independent physical and chemical parameters from a set of 33 possible factors, one model for each combination of polymer and processing method, with good predictability of stability. Three general rules are proposed from these models for the formulation development of suitably stable solid dispersions. Namely, increased stability is correlated with increased glass transition temperature ( T g ) of solid dispersions, as well as decreased number of H-bond donors and increased molecular flexibility (such as rotatable bonds and ring count) of the drug molecule.
Baba, Toshimi; Gotoh, Yusaku; Yamaguchi, Satoshi; Nakagawa, Satoshi; Abe, Hayato; Masuda, Yutaka; Kawahara, Takayoshi
2017-08-01
This study aimed to evaluate a validation reliability of single-step genomic best linear unbiased prediction (ssGBLUP) with a multiple-lactation random regression test-day model and investigate an effect of adding genotyped cows on the reliability. Two data sets for test-day records from the first three lactations were used: full data from February 1975 to December 2015 (60 850 534 records from 2 853 810 cows) and reduced data cut off in 2011 (53 091 066 records from 2 502 307 cows). We used marker genotypes of 4480 bulls and 608 cows. Genomic enhanced breeding values (GEBV) of 305-day milk yield in all the lactations were estimated for at least 535 young bulls using two marker data sets: bull genotypes only and both bulls and cows genotypes. The realized reliability (R 2 ) from linear regression analysis was used as an indicator of validation reliability. Using only genotyped bulls, R 2 was ranged from 0.41 to 0.46 and it was always higher than parent averages. The very similar R 2 were observed when genotyped cows were added. An application of ssGBLUP to a multiple-lactation random regression model is feasible and adding a limited number of genotyped cows has no significant effect on reliability of GEBV for genotyped bulls. © 2016 Japanese Society of Animal Science.
Yan, Jun; Huang, Jian-Hua; He, Min; Lu, Hong-Bing; Yang, Rui; Kong, Bo; Xu, Qing-Song; Liang, Yi-Zeng
2013-08-01
Retention indices for frequently reported compounds of plant essential oils on three different stationary phases were investigated. Multivariate linear regression, partial least squares, and support vector machine combined with a new variable selection approach called random-frog recently proposed by our group, were employed to model quantitative structure-retention relationships. Internal and external validations were performed to ensure the stability and predictive ability. All the three methods could obtain an acceptable model, and the optimal results by support vector machine based on a small number of informative descriptors with the square of correlation coefficient for cross validation, values of 0.9726, 0.9759, and 0.9331 on the dimethylsilicone stationary phase, the dimethylsilicone phase with 5% phenyl groups, and the PEG stationary phase, respectively. The performances of two variable selection approaches, random-frog and genetic algorithm, are compared. The importance of the variables was found to be consistent when estimated from correlation coefficients in multivariate linear regression equations and selection probability in model spaces. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Shilov, Georgi E
1977-01-01
Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space. Problems with hints and answers.
Kavuncuoglu, Hatice; Kavuncuoglu, Erhan; Karatas, Seyda Merve; Benli, Büsra; Sagdic, Osman; Yalcin, Hasan
2018-04-09
The mathematical model was established to determine the diameter of inhibition zone of the walnut extract on the twelve bacterial species. Type of extraction, concentration, and pathogens were taken as input variables. Two models were used with the aim of designing this system. One of them was developed with artificial neural networks (ANN), and the other was formed with multiple linear regression (MLR). Four common training algorithms were used. Levenberg-Marquardt (LM), Bayesian regulation (BR), scaled conjugate gradient (SCG) and resilient back propagation (RP) were investigated, and the algorithms were compared. Root mean squared error and correlation coefficient were evaluated as performance criteria. When these criteria were analyzed, ANN showed high prediction performance, while MLR showed low prediction performance. As a result, it is seen that when the different input values are provided to the system developed with ANN, the most accurate inhibition zone (IZ) estimates were obtained. The results of this study could offer new perspectives, particularly in the field of microbiology, because these could be applied to other type of extraction, concentrations, and pathogens, without resorting to experiments. Copyright © 2018 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Kim, Yong-il; Kim, Yong Joong; Paeng, Jin Chul; Cheon, Gi Jeong; Lee, Dong Soo; Chung, June-Key; Kang, Keon Wook
2017-01-01
18 F-Fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) has been investigated as a method to predict pancreatic cancer recurrence after pancreatic surgery. We evaluated the recently introduced heterogeneity indices of 18 F-FDG PET/CT used for predicting pancreatic cancer recurrence after surgery and compared them with current clinicopathologic and 18 F-FDG PET/CT parameters. A total of 93 pancreatic ductal adenocarcinoma patients (M:F = 60:33, mean age = 64.2 ± 9.1 years) who underwent preoperative 18 F-FDG PET/CT following pancreatic surgery were retrospectively enrolled. The standardized uptake values (SUVs) and tumor-to-background ratios (TBR) were measured on each 18 F-FDG PET/CT, as metabolic parameters. Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were examined as volumetric parameters. The coefficient of variance (heterogeneity index-1; SUVmean divided by the standard deviation) and linear regression slopes (heterogeneity index-2) of the MTV, according to SUV thresholds of 2.0, 2.5 and 3.0, were evaluated as heterogeneity indices. Predictive values of clinicopathologic and 18 F-FDG PET/CT parameters and heterogeneity indices were compared in terms of pancreatic cancer recurrence. Seventy patients (75.3%) showed recurrence after pancreatic cancer surgery (mean recurrence = 9.4 ± 8.4 months). Comparing the recurrence and no recurrence patients, all of the 18 F-FDG PET/CT parameters and heterogeneity indices demonstrated significant differences. In univariate Cox-regression analyses, MTV (P = 0.013), TLG (P = 0.007), and heterogeneity index-2 (P = 0.027) were significant. Among the clinicopathologic parameters, CA19-9 (P = 0.025) and venous invasion (P = 0.002) were selected as significant parameters. In multivariate Cox-regression analyses, MTV (P = 0.005), TLG (P = 0.004), and heterogeneity index-2 (P = 0.016) with venous invasion (P < 0.001, 0.001, and 0.001, respectively) demonstrated significant results
Herrig, Ilona M; Böer, Simone I; Brennholt, Nicole; Manz, Werner
2015-11-15
Since rivers are typically subject to rapid changes in microbiological water quality, tools are needed to allow timely water quality assessment. A promising approach is the application of predictive models. In our study, we developed multiple linear regression (MLR) models in order to predict the abundance of the fecal indicator organisms Escherichia coli (EC), intestinal enterococci (IE) and somatic coliphages (SC) in the Lahn River, Germany. The models were developed on the basis of an extensive set of environmental parameters collected during a 12-months monitoring period. Two models were developed for each type of indicator: 1) an extended model including the maximum number of variables significantly explaining variations in indicator abundance and 2) a simplified model reduced to the three most influential explanatory variables, thus obtaining a model which is less resource-intensive with regard to required data. Both approaches have the ability to model multiple sites within one river stretch. The three most important predictive variables in the optimized models for the bacterial indicators were NH4-N, turbidity and global solar irradiance, whereas chlorophyll a content, discharge and NH4-N were reliable model variables for somatic coliphages. Depending on indicator type, the extended mode models also included the additional variables rainfall, O2 content, pH and chlorophyll a. The extended mode models could explain 69% (EC), 74% (IE) and 72% (SC) of the observed variance in fecal indicator concentrations. The optimized models explained the observed variance in fecal indicator concentrations to 65% (EC), 70% (IE) and 68% (SC). Site-specific efficiencies ranged up to 82% (EC) and 81% (IE, SC). Our results suggest that MLR models are a promising tool for a timely water quality assessment in the Lahn area. Copyright © 2015 Elsevier Ltd. All rights reserved.
A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma
Energy Technology Data Exchange (ETDEWEB)
Ku, S., E-mail: sku@pppl.gov [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Hager, R.; Chang, C.S. [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Kwon, J.M. [National Fusion Research Institute (Korea, Republic of); Parker, S.E. [University of Colorado Boulder (United States)
2016-06-15
In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles provide scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. The numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.
SciDAC Center for Gyrokinetic Particle Simulation of Turbulent Transport in Burning Plasmas
Energy Technology Data Exchange (ETDEWEB)
Lin, Zhihong [Univ. of California, Irvine, CA (United States)
2013-12-18
During the first year of the SciDAC gyrokinetic particle simulation (GPS) project, the GPS team (Zhihong Lin, Liu Chen, Yasutaro Nishimura, and Igor Holod) at the University of California, Irvine (UCI) studied the tokamak electron transport driven by electron temperature gradient (ETG) turbulence, and by trapped electron mode (TEM) turbulence and ion temperature gradient (ITG) turbulence with kinetic electron effects, extended our studies of ITG turbulence spreading to core-edge coupling. We have developed and optimized an elliptic solver using finite element method (FEM), which enables the implementation of advanced kinetic electron models (split-weight scheme and hybrid model) in the SciDAC GPS production code GTC. The GTC code has been ported and optimized on both scalar and vector parallel computer architectures, and is being transformed into objected-oriented style to facilitate collaborative code development. During this period, the UCI team members presented 11 invited talks at major national and international conferences, published 22 papers in peer-reviewed journals and 10 papers in conference proceedings. The UCI hosted the annual SciDAC Workshop on Plasma Turbulence sponsored by the GPS Center, 2005-2007. The workshop was attended by about fifties US and foreign researchers and financially sponsored several gradual students from MIT, Princeton University, Germany, Switzerland, and Finland. A new SciDAC postdoc, Igor Holod, has arrived at UCI to initiate global particle simulation of magnetohydrodynamics turbulence driven by energetic particle modes. The PI, Z. Lin, has been promoted to the Associate Professor with tenure at UCI.
Angulo, Raul E.; Hilbert, Stefan
2015-03-01
We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.
International Nuclear Information System (INIS)
Ohana, N; Lanti, E; Tran, T M; Brunner, S; Hariri, F; Villard, L; Jocksch, A; Gheller, C
2016-01-01
With the aim of enabling state-of-the-art gyrokinetic PIC codes to benefit from the performance of recent multithreaded devices, we developed an application from a platform called the “PIC-engine” [1, 2, 3] embedding simplified basic features of the PIC method. The application solves the gyrokinetic equations in a sheared plasma slab using B-spline finite elements up to fourth order to represent the self-consistent electrostatic field. Preliminary studies of the so-called Particle-In-Fourier (PIF) approach, which uses Fourier modes as basis functions in the periodic dimensions of the system instead of the real-space grid, show that this method can be faster than PIC for simulations with a small number of Fourier modes. Similarly to the PIC-engine, multiple levels of parallelism have been implemented using MPI+OpenMP [2] and MPI+OpenACC [1], the latter exploiting the computational power of GPUs without requiring complete code rewriting. It is shown that sorting particles [3] can lead to performance improvement by increasing data locality and vectorizing grid memory access. Weak scalability tests have been successfully run on the GPU-equipped Cray XC30 Piz Daint (at CSCS) up to 4,096 nodes. The reduced time-to-solution will enable more realistic and thus more computationally intensive simulations of turbulent transport in magnetic fusion devices. (paper)
Deville, Anne-Sophie; Grémillet, David; Gauthier-Clerc, Michel; Guillemain, Matthieu; Von Houwald, Friederike; Gardelli, Bruno; Béchet, Arnaud
2013-01-01
Accurate knowledge of the functional response of predators to prey density is essential for understanding food web dynamics, to parameterize mechanistic models of animal responses to environmental change, and for designing appropriate conservation measures. Greater flamingos (Phoenicopterus roseus), a flagship species of Mediterranean wetlands, primarily feed on Artemias (Artemia spp.) in commercial salt pans, an industry which may collapse for economic reasons. Flamingos also feed on alternative prey such as Chironomid larvae (e.g., Chironomid spp.) and rice seeds (Oryza sativa). However, the profitability of these food items for flamingos remains unknown. We determined the functional responses of flamingos feeding on Artemias, Chironomids, or rice. Experiments were conducted on 11 captive flamingos. For each food item, we offered different ranges of food densities, up to 13 times natural abundance. Video footage allowed estimating intake rates. Contrary to theoretical predictions for filter feeders, intake rates did not increase linearly with increasing food density (type I). Intake rates rather increased asymptotically with increasing food density (type II) or followed a sigmoid shape (type III). Hence, flamingos were not able to ingest food in direct proportion to their abundance, possibly because of unique bill structure resulting in limited filtering capabilities. Overall, flamingos foraged m