K-ε Turbulence Model Parameter Estimates Using an Approximate Self-similar Jet-in-Crossflow Solution

DOE PAGES

DeChant, Lawrence; Ray, Jaideep; Lefantzi, Sophia; ...

2017-06-09

The k-ε turbulence model has been described as perhaps “the most widely used complete turbulence model.” This family of heuristic Reynolds Averaged Navier-Stokes (RANS) turbulence closures is supported by a suite of model parameters that have been estimated by demanding the satisfaction of well-established canonical flows such as homogeneous shear flow, log-law behavior, etc. While this procedure does yield a set of so-called nominal parameters, it is abundantly clear that they do not provide a universally satisfactory turbulence model that is capable of simulating complex flows. Recent work on the Bayesian calibration of the k-ε model using jet-in-crossflow wind tunnelmore » data has yielded parameter estimates that are far more predictive than nominal parameter values. In this paper, we develop a self-similar asymptotic solution for axisymmetric jet-in-crossflow interactions and derive analytical estimates of the parameters that were inferred using Bayesian calibration. The self-similar method utilizes a near field approach to estimate the turbulence model parameters while retaining the classical far-field scaling to model flow field quantities. Our parameter values are seen to be far more predictive than the nominal values, as checked using RANS simulations and experimental measurements. They are also closer to the Bayesian estimates than the nominal parameters. A traditional simplified jet trajectory model is explicitly related to the turbulence model parameters and is shown to yield good agreement with measurement when utilizing the analytical derived turbulence model coefficients. Finally, the close agreement between the turbulence model coefficients obtained via Bayesian calibration and the analytically estimated coefficients derived in this paper is consistent with the contention that the Bayesian calibration approach is firmly rooted in the underlying physical description.« less

Developing a methodology for the inverse estimation of root architectural parameters from field based sampling schemes

NASA Astrophysics Data System (ADS)

Morandage, Shehan; Schnepf, Andrea; Vanderborght, Jan; Javaux, Mathieu; Leitner, Daniel; Laloy, Eric; Vereecken, Harry

2017-04-01

Root traits are increasingly important in breading of new crop varieties. E.g., longer and fewer lateral roots are suggested to improve drought resistance of wheat. Thus, detailed root architectural parameters are important. However, classical field sampling of roots only provides more aggregated information such as root length density (coring), root counts per area (trenches) or root arrival curves at certain depths (rhizotubes). We investigate the possibility of obtaining the information about root system architecture of plants using field based classical root sampling schemes, based on sensitivity analysis and inverse parameter estimation. This methodology was developed based on a virtual experiment where a root architectural model was used to simulate root system development in a field, parameterized for winter wheat. This information provided the ground truth which is normally unknown in a real field experiment. The three sampling schemes coring, trenching, and rhizotubes where virtually applied to and aggregated information computed. Morris OAT global sensitivity analysis method was then performed to determine the most sensitive parameters of root architecture model for the three different sampling methods. The estimated means and the standard deviation of elementary effects of a total number of 37 parameters were evaluated. Upper and lower bounds of the parameters were obtained based on literature and published data of winter wheat root architectural parameters. Root length density profiles of coring, arrival curve characteristics observed in rhizotubes, and root counts in grids of trench profile method were evaluated statistically to investigate the influence of each parameter using five different error functions. Number of branches, insertion angle inter-nodal distance, and elongation rates are the most sensitive parameters and the parameter sensitivity varies slightly with the depth. Most parameters and their interaction with the other parameters show highly nonlinear effect to the model output. The most sensitive parameters will be subject to inverse estimation from the virtual field sampling data using DREAMzs algorithm. The estimated parameters can then be compared with the ground truth in order to determine the suitability of the sampling schemes to identify specific traits or parameters of the root growth model.

The four fixed points of scale invariant single field cosmological models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xue, BingKan, E-mail: bxue@princeton.edu

2012-10-01

We introduce a new set of flow parameters to describe the time dependence of the equation of state and the speed of sound in single field cosmological models. A scale invariant power spectrum is produced if these flow parameters satisfy specific dynamical equations. We analyze the flow of these parameters and find four types of fixed points that encompass all known single field models. Moreover, near each fixed point we uncover new models where the scale invariance of the power spectrum relies on having simultaneously time varying speed of sound and equation of state. We describe several distinctive new modelsmore » and discuss constraints from strong coupling and superluminality.« less

Scalar field cosmology in f(R,T) gravity via Noether symmetry

NASA Astrophysics Data System (ADS)

Sharif, M.; Nawazish, Iqra

2018-04-01

This paper investigates the existence of Noether symmetries of isotropic universe model in f(R,T) gravity admitting minimal coupling of matter and scalar fields. The scalar field incorporates two dark energy models such as quintessence and phantom models. We determine symmetry generators and corresponding conserved quantities for two particular f(R,T) models. We also evaluate exact solutions and investigate their physical behavior via different cosmological parameters. For the first model, the graphical behavior of these parameters indicate consistency with recent observations representing accelerated expansion of the universe. For the second model, these parameters identify a transition form accelerated to decelerated expansion of the universe. The potential function is found to be constant for the first model while it becomes V(φ )≈ φ 2 for the second model. We conclude that the Noether symmetry generators and corresponding conserved quantities appear in all cases.

Feasibility of employing model-based optimization of pulse amplitude and electrode distance for effective tumor electropermeabilization.

PubMed

Sel, Davorka; Lebar, Alenka Macek; Miklavcic, Damijan

2007-05-01

In electrochemotherapy (ECT) electropermeabilization, parameters (pulse amplitude, electrode setup) need to be customized in order to expose the whole tumor to electric field intensities above permeabilizing threshold to achieve effective ECT. In this paper, we present a model-based optimization approach toward determination of optimal electropermeabilization parameters for effective ECT. The optimization is carried out by minimizing the difference between the permeabilization threshold and electric field intensities computed by finite element model in selected points of tumor. We examined the feasibility of model-based optimization of electropermeabilization parameters on a model geometry generated from computer tomography images, representing brain tissue with tumor. Continuous parameter subject to optimization was pulse amplitude. The distance between electrode pairs was optimized as a discrete parameter. Optimization also considered the pulse generator constraints on voltage and current. During optimization the two constraints were reached preventing the exposure of the entire volume of the tumor to electric field intensities above permeabilizing threshold. However, despite the fact that with the particular needle array holder and pulse generator the entire volume of the tumor was not permeabilized, the maximal extent of permeabilization for the particular case (electrodes, tissue) was determined with the proposed approach. Model-based optimization approach could also be used for electro-gene transfer, where electric field intensities should be distributed between permeabilizing threshold and irreversible threshold-the latter causing tissue necrosis. This can be obtained by adding constraints on maximum electric field intensity in optimization procedure.

Towards adjoint-based inversion for rheological parameters in nonlinear viscous mantle flow

NASA Astrophysics Data System (ADS)

Worthen, Jennifer; Stadler, Georg; Petra, Noemi; Gurnis, Michael; Ghattas, Omar

2014-09-01

We address the problem of inferring mantle rheological parameter fields from surface velocity observations and instantaneous nonlinear mantle flow models. We formulate this inverse problem as an infinite-dimensional nonlinear least squares optimization problem governed by nonlinear Stokes equations. We provide expressions for the gradient of the cost functional of this optimization problem with respect to two spatially-varying rheological parameter fields: the viscosity prefactor and the exponent of the second invariant of the strain rate tensor. Adjoint (linearized) Stokes equations, which are characterized by a 4th order anisotropic viscosity tensor, facilitates efficient computation of the gradient. A quasi-Newton method for the solution of this optimization problem is presented, which requires the repeated solution of both nonlinear forward Stokes and linearized adjoint Stokes equations. For the solution of the nonlinear Stokes equations, we find that Newton’s method is significantly more efficient than a Picard fixed point method. Spectral analysis of the inverse operator given by the Hessian of the optimization problem reveals that the numerical eigenvalues collapse rapidly to zero, suggesting a high degree of ill-posedness of the inverse problem. To overcome this ill-posedness, we employ Tikhonov regularization (favoring smooth parameter fields) or total variation (TV) regularization (favoring piecewise-smooth parameter fields). Solution of two- and three-dimensional finite element-based model inverse problems show that a constant parameter in the constitutive law can be recovered well from surface velocity observations. Inverting for a spatially-varying parameter field leads to its reasonable recovery, in particular close to the surface. When inferring two spatially varying parameter fields, only an effective viscosity field and the total viscous dissipation are recoverable. Finally, a model of a subducting plate shows that a localized weak zone at the plate boundary can be partially recovered, especially with TV regularization.

Physical and mathematical modelling of ladle metallurgy operations. [steelmaking

NASA Technical Reports Server (NTRS)

El-Kaddah, N.; Szekely, J.

1982-01-01

Experimental measurements are reported, on the velocity fields and turbulence parameters on a water model of an argon stirred ladle. These velocity measurements are complemented by direct heat transfer measurements, obtained by studying the rate at which ice rods immersed into the system melt, at various locations. The theoretical work undertaken involved the use of the turbulence Navier-Stokes equations in conjunction with the kappa-epsilon model to predict the local velocity fields and the maps of the turbulence parameters. Theoretical predictions were in reasonably good agreement with the experimentally measured velocity fields; the agreement between the predicted and the measured turbulence parameters was less perfect, but still satisfactory. The implications of these findings to the modelling of ladle metallurgical operations are discussed.

Getting Ready for BepiColombo: A Modeling Approach to Infer the Solar Wind Plasma Parameters Upstream of Mercury from Magnetic Field Observations

NASA Astrophysics Data System (ADS)

Fatemi, S.; Poirier, N.; Holmström, M.; Wieser, M.; Barabash, S.

2018-05-01

We have developed a model to infer the solar wind plasma parameters upstream of Mercury from magnetic field observations in Mercury's magnetosphere. This is important for observations by MESSENGER and the future mission to Mercury, BepiColombo.

Estimating effective soil properties of heterogeneous areas for modeling infiltration and redistribution

USDA-ARS?s Scientific Manuscript database

Field scale water infiltration and soil-water and solute transport models require spatially-averaged “effective” soil hydraulic parameters to represent the average flux and storage. The values of these effective parameters vary for different conditions, processes, and component soils in a field. For...

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Reconstructing solar magnetic fields from historical observations. II. Testing the surface flux transport model

NASA Astrophysics Data System (ADS)

Virtanen, I. O. I.; Virtanen, I. I.; Pevtsov, A. A.; Yeates, A.; Mursula, K.

2017-07-01

Aims: We aim to use the surface flux transport model to simulate the long-term evolution of the photospheric magnetic field from historical observations. In this work we study the accuracy of the model and its sensitivity to uncertainties in its main parameters and the input data. Methods: We tested the model by running simulations with different values of meridional circulation and supergranular diffusion parameters, and studied how the flux distribution inside active regions and the initial magnetic field affected the simulation. We compared the results to assess how sensitive the simulation is to uncertainties in meridional circulation speed, supergranular diffusion, and input data. We also compared the simulated magnetic field with observations. Results: We find that there is generally good agreement between simulations and observations. Although the model is not capable of replicating fine details of the magnetic field, the long-term evolution of the polar field is very similar in simulations and observations. Simulations typically yield a smoother evolution of polar fields than observations, which often include artificial variations due to observational limitations. We also find that the simulated field is fairly insensitive to uncertainties in model parameters or the input data. Due to the decay term included in the model the effects of the uncertainties are somewhat minor or temporary, lasting typically one solar cycle.

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

Scaling methane oxidation: From laboratory incubation experiments to landfill cover field conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abichou, Tarek, E-mail: abichou@eng.fsu.edu; Mahieu, Koenraad; Chanton, Jeff

2011-05-15

Evaluating field-scale methane oxidation in landfill cover soils using numerical models is gaining interest in the solid waste industry as research has made it clear that methane oxidation in the field is a complex function of climatic conditions, soil type, cover design, and incoming flux of landfill gas from the waste mass. Numerical models can account for these parameters as they change with time and space under field conditions. In this study, we developed temperature, and water content correction factors for methane oxidation parameters. We also introduced a possible correction to account for the different soil structure under field conditions.more » These parameters were defined in laboratory incubation experiments performed on homogenized soil specimens and were used to predict the actual methane oxidation rates to be expected under field conditions. Water content and temperature corrections factors were obtained for the methane oxidation rate parameter to be used when modeling methane oxidation in the field. To predict in situ measured rates of methane with the model it was necessary to set the half saturation constant of methane and oxygen, K{sub m}, to 5%, approximately five times larger than laboratory measured values. We hypothesize that this discrepancy reflects differences in soil structure between homogenized soil conditions in the lab and actual aggregated soil structure in the field. When all of these correction factors were re-introduced into the oxidation module of our model, it was able to reproduce surface emissions (as measured by static flux chambers) and percent oxidation (as measured by stable isotope techniques) within the range measured in the field.« less

The Dynamics of Phonological Planning

ERIC Educational Resources Information Center

Roon, Kevin D.

2013-01-01

This dissertation proposes a dynamical computational model of the timecourse of phonological parameter setting. In the model, phonological representations embrace phonetic detail, with phonetic parameters represented as activation fields that evolve over time and determine the specific parameter settings of a planned utterance. Existing models of…

Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for ecosystem carbon cycle studies

Treesearch

Y. He; Q. Zhuang; A.D. McGuire; Y. Liu; M. Chen

2013-01-01

Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations inmodeling regional carbon dynamics and explore the...

Modelling of resonant MEMS magnetic field sensor with electromagnetic induction sensing

NASA Astrophysics Data System (ADS)

Liu, Song; Xu, Huaying; Xu, Dehui; Xiong, Bin

2017-06-01

This paper presents an analytical model of resonant MEMS magnetic field sensor with electromagnetic induction sensing. The resonant structure vibrates in square extensional (SE) mode. By analyzing the vibration amplitude and quality factor of the resonant structure, the magnetic field sensitivity as a function of device structure parameters and encapsulation pressure is established. The developed analytical model has been verified by comparing calculated results with experiment results and the deviation between them is only 10.25%, which shows the feasibility of the proposed device model. The model can provide theoretical guidance for further design optimization of the sensor. Moreover, a quantitative study of the magnetic field sensitivity is conducted with respect to the structure parameters and encapsulation pressure based on the proposed model.

EPR, optical and modeling of Mn(2+) doped sarcosinium oxalate monohydrate.

PubMed

Kripal, Ram; Singh, Manju

2015-01-25

Electron paramagnetic resonance (EPR) study of Mn(2+) ions doped in sarcosinium oxalate monohydrate (SOM) single crystal is done at liquid nitrogen temperature (LNT). EPR spectrum shows a bunch of five fine structure lines and further they split into six hyperfine components. Only one interstitial site was observed. With the help of EPR spectra the spin Hamiltonian parameters including zero field splitting (ZFS) parameters are evaluated. The optical absorption study at room temperature is also done in the wavelength range 195-1100 nm. From this study cubic crystal field splitting parameter, Dq=730 cm(-1) and Racah inter-electronic repulsion parameters B=792 cm(-1), C=2278 cm(-1) are determined. ZFS parameters D and E are also calculated using crystal field parameters from superposition model and microscopic spin Hamiltonian theory. The calculated ZFS parameter values are in good match with the experimental values obtained by EPR. Copyright © 2014 Elsevier B.V. All rights reserved.

EPR, optical and superposition model study of Mn2+ doped L+ glutamic acid

NASA Astrophysics Data System (ADS)

Kripal, Ram; Singh, Manju

2015-12-01

Electron paramagnetic resonance (EPR) study of Mn2+ doped L+ glutamic acid single crystal is done at room temperature. Four interstitial sites are observed and the spin Hamiltonian parameters are calculated with the help of large number of resonant lines for various angular positions of external magnetic field. The optical absorption study is also done at room temperature. The energy values for different orbital levels are calculated, and observed bands are assigned as transitions from 6A1g(s) ground state to various excited states. With the help of these assigned bands, Racah inter-electronic repulsion parameters B = 869 cm-1, C = 2080 cm-1 and cubic crystal field splitting parameter Dq = 730 cm-1 are calculated. Zero field splitting (ZFS) parameters D and E are calculated by the perturbation formulae and crystal field parameters obtained using superposition model. The calculated values of ZFS parameters are in good agreement with the experimental values obtained by EPR.

Permutation on hybrid natural inflation

NASA Astrophysics Data System (ADS)

Carone, Christopher D.; Erlich, Joshua; Ramos, Raymundo; Sher, Marc

2014-09-01

We analyze a model of hybrid natural inflation based on the smallest non-Abelian discrete group S3. Leading invariant terms in the scalar potential have an accidental global symmetry that is spontaneously broken, providing a pseudo-Goldstone boson that is identified as the inflaton. The S3 symmetry restricts both the form of the inflaton potential and the couplings of the inflaton field to the waterfall fields responsible for the end of inflation. We identify viable points in the model parameter space. Although the power in tensor modes is small in most of the parameter space of the model, we identify parameter choices that yield potentially observable values of r without super-Planckian initial values of the inflaton field.

Evaluating Parametrization Protocols for Hydration Free Energy Calculations with the AMOEBA Polarizable Force Field.

PubMed

Bradshaw, Richard T; Essex, Jonathan W

2016-08-09

Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed-point-charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard but showed substantially worse results than those using the fixed-point-charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 data set, we evaluate the cumulative effects of a series of incremental improvements in parametrization protocol, including both solute and solvent model changes. Ultimately, the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein-ligand binding studies.

Big Data Analytics for Modelling and Forecasting of Geomagnetic Field Indices

NASA Astrophysics Data System (ADS)

Wei, H. L.

2016-12-01

A massive amount of data are produced and stored in research areas of space weather and space climate. However, the value of a vast majority of the data acquired every day may not be effectively or efficiently exploited in our daily practice when we try to forecast solar wind parameters and geomagnetic field indices using these recorded measurements or digital signals, probably due to the challenges stemming from the dealing with big data which are characterized by the 4V futures: volume (a massively large amount of data), variety (a great number of different types of data), velocity (a requirement of quick processing of the data), and veracity (the trustworthiness and usability of the data). In order to obtain more reliable and accurate predictive models for geomagnetic field indices, it requires that models should be developed from the big data analytics perspective (or it at least benefits from such a perspective). This study proposes a few data-based modelling frameworks which aim to produce more efficient predictive models for space weather parameters forecasting by means of system identification and big data analytics. More specifically, it aims to build more reliable mathematical models that characterise the relationship between solar wind parameters and geomagnetic filed indices, for example the dependent relationship of Dst and Kp indices on a few solar wind parameters and magnetic field indices, namely, solar wind velocity (V), southward interplanetary magnetic field (Bs), solar wind rectified electric field (VBs), and dynamic flow pressure (P). Examples are provided to illustrate how the proposed modelling approaches are applied to Dst and Kp index prediction.

The multiscale coarse-graining method. II. Numerical implementation for coarse-grained molecular models

PubMed Central

Noid, W. G.; Liu, Pu; Wang, Yanting; Chu, Jhih-Wei; Ayton, Gary S.; Izvekov, Sergei; Andersen, Hans C.; Voth, Gregory A.

2008-01-01

The multiscale coarse-graining (MS-CG) method [S. Izvekov and G. A. Voth, J. Phys. Chem. B 109, 2469 (2005);J. Chem. Phys. 123, 134105 (2005)] employs a variational principle to determine an interaction potential for a CG model from simulations of an atomically detailed model of the same system. The companion paper proved that, if no restrictions regarding the form of the CG interaction potential are introduced and if the equilibrium distribution of the atomistic model has been adequately sampled, then the MS-CG variational principle determines the exact many-body potential of mean force (PMF) governing the equilibrium distribution of CG sites generated by the atomistic model. In practice, though, CG force fields are not completely flexible, but only include particular types of interactions between CG sites, e.g., nonbonded forces between pairs of sites. If the CG force field depends linearly on the force field parameters, then the vector valued functions that relate the CG forces to these parameters determine a set of basis vectors that span a vector subspace of CG force fields. The companion paper introduced a distance metric for the vector space of CG force fields and proved that the MS-CG variational principle determines the CG force force field that is within that vector subspace and that is closest to the force field determined by the many-body PMF. The present paper applies the MS-CG variational principle for parametrizing molecular CG force fields and derives a linear least squares problem for the parameter set determining the optimal approximation to this many-body PMF. Linear systems of equations for these CG force field parameters are derived and analyzed in terms of equilibrium structural correlation functions. Numerical calculations for a one-site CG model of methanol and a molecular CG model of the EMIM+∕NO3− ionic liquid are provided to illustrate the method. PMID:18601325

Numerical study of unsteady Williamson fluid flow and heat transfer in the presence of MHD through a permeable stretching surface

NASA Astrophysics Data System (ADS)

Bibi, Madiha; Khalil-Ur-Rehman; Malik, M. Y.; Tahir, M.

2018-04-01

In the present article, unsteady flow field characteristics of the Williamson fluid model are explored. The nanosized particles are suspended in the flow regime having the interaction of a magnetic field. The fluid flow is induced due to a stretching permeable surface. The flow model is controlled through coupled partial differential equations to the used shooting method for a numerical solution. The obtained partial differential equations are converted into ordinary differential equations as an initial value problem. The shooting method is used to find a numerical solution. The mathematical modeling yields physical parameters, namely the Weissenberg number, the Prandtl number, the unsteadiness parameter, the magnetic parameter, the mass transfer parameter, the Lewis number, the thermophoresis parameter and Brownian parameters. It is found that the Williamson fluid velocity, temperature and nanoparticles concentration are a decreasing function of the unsteadiness parameter.

Order parameter re-mapping algorithm for 3D phase field model of grain growth using FEM

DOE PAGES

Permann, Cody J.; Tonks, Michael R.; Fromm, Bradley; ...

2016-01-14

Phase field modeling (PFM) is a well-known technique for simulating microstructural evolution. To model grain growth using PFM, typically each grain is assigned a unique non-conserved order parameter and each order parameter field is evolved in time. Traditional approaches using a one-to-one mapping of grains to order parameters present a challenge when modeling large numbers of grains due to the computational expense of using many order parameters. This problem is exacerbated when using an implicit finite element method (FEM), as the global matrix size is proportional to the number of order parameters. While previous work has developed methods to reducemore » the number of required variables and thus computational complexity and run time, none of the existing approaches can be applied for an implicit FEM implementation of PFM. Here, we present a modular, dynamic, scalable reassignment algorithm suitable for use in such a system. Polycrystal modeling with grain growth and stress require careful tracking of each grain’s position and orientation which is lost when using a reduced order parameter set. In conclusion, the method presented in this paper maintains a unique ID for each grain even after reassignment, to allow the PFM to be tightly coupled to calculations of the stress throughout the polycrystal. Implementation details and comparative results of our approach are presented.« less

Fitting a Structured Juvenile-Adult Model for Green Tree Frogs to Population Estimates from Capture-Mark-Recapture Field Data

USGS Publications Warehouse

Ackleh, A.S.; Carter, J.; Deng, K.; Huang, Q.; Pal, N.; Yang, X.

2012-01-01

We derive point and interval estimates for an urban population of green tree frogs (Hyla cinerea) from capture-mark-recapture field data obtained during the years 2006-2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation. ?? 2011 Society for Mathematical Biology.

PP/PS anisotropic stereotomography

NASA Astrophysics Data System (ADS)

Nag, Steinar; Alerini, Mathias; Ursin, Bjørn

2010-04-01

Stereotomography is a slope tomographic method which gives good results for background velocity model estimation in 2-D isotropic media. We develop here the extension of the method to 3-D general anisotropic media for PP and PS events. We do not take into account the issue of shear wave degeneracy. As in isotropic media, the sensitivity matrix of the inversion can be computed by paraxial ray tracing. We introduce a `constant Z stereotomography' approach, which can reduce the size of the sensitivity matrix. Based on ray perturbation theory, we give all the derivatives of stereotomography data parameters with respect to model parameters in a 3-D general anisotropic medium. These general formulas for the derivatives can also be used in other applications that rely on anisotropic ray perturbation theory. In particular, we obtain derivatives of the phase velocity with respect to position, phase angle and elastic medium parameters, all for general anisotropic media. The derivatives are expressed using the Voigt notation for the elastic medium parameters. We include a Jacobian that allows to change the model parametrization from Voigt to Thomsen parameters. Explicit expressions for the derivatives of the data are given for the case of 2-D tilted transversely isotropic (TTI) media. We validate the method by single-parameter estimation of each Thomsen parameter field of a 2-D TTI synthetic model, where data are modelled by ray tracing. For each Thomsen parameter, the estimated velocity field fits well with the true velocity field.

Tikekar superdense stars in electric fields

NASA Astrophysics Data System (ADS)

Komathiraj, K.; Maharaj, S. D.

2007-04-01

We present exact solutions to the Einstein-Maxwell system of equations with a specified form of the electric field intensity by assuming that the hypersurface {t=constant} are spheroidal. The solution of the Einstein-Maxwell system is reduced to a recurrence relation with variable rational coefficients which can be solved in general using mathematical induction. New classes of solutions of linearly independent functions are obtained by restricting the spheroidal parameter K and the electric field intensity parameter α. Consequently, it is possible to find exact solutions in terms of elementary functions, namely, polynomials and algebraic functions. Our result contains models found previously including the superdense Tikekar neutron star model [J. Math. Phys. 31, 2454 (1990)] when K=-7 and α=0. Our class of charged spheroidal models generalize the uncharged isotropic Maharaj and Leach solutions [J. Math. Phys. 37, 430 (1996)]. In particular, we find an explicit relationship directly relating the spheroidal parameter K to the electromagnetic field.

Higgs field and cosmological parameters in the fractal quantum system

NASA Astrophysics Data System (ADS)

Abramov, Valeriy

2017-10-01

For the fractal model of the Universe the relations of cosmological parameters and the Higgs field are established. Estimates of the critical density, the expansion and speed-up parameters of the Universe (the Hubble constant and the cosmological redshift); temperature and anisotropy of the cosmic microwave background radiation were performed.

A Semi-analytical Line Transfer (SALT) Model. II: The Effects of a Bi-conical Geometry

NASA Astrophysics Data System (ADS)

Carr, Cody; Scarlata, Claudia; Panagia, Nino; Henry, Alaina

2018-06-01

We generalize the semi-analytical line transfer model recently introduced by Scarlata & Panagia for modeling galactic outflows, to account for bi-conical geometries of various opening angles and orientations with respect to the line of sight to the observer, as well as generalized velocity fields. We model the absorption and emission component of the line profile resulting from resonant absorption in the bi-conical outflow. We show how the outflow geometry impacts the resulting line profile. We use simulated spectra with different geometries and velocity fields to study how well the outflow parameters can be recovered. We find that geometrical parameters (including the opening angle and the orientation) are always well recovered. The density and velocity field parameters are reliably recovered when both an absorption and an emission component are visible in the spectra. This condition implies that the velocity and density fields for narrow cones oriented perpendicular to the line of sight will remain unconstrained.

An update of Leighton's solar dynamo model

NASA Astrophysics Data System (ADS)

Cameron, R. H.; Schüssler, M.

2017-03-01

In 1969, Leighton developed a quasi-1D mathematical model of the solar dynamo, building upon the phenomenological scenario of Babcock published in 1961. Here we present a modification and extension of Leighton's model. Using the axisymmetric component (longitudinal average) of the magnetic field, we consider the radial field component at the solar surface and the radially integrated toroidal magnetic flux in the convection zone, both as functions of latitude. No assumptions are made with regard to the radial location of the toroidal flux. The model includes the effects of (I) turbulent diffusion at the surface and in the convection zone; (II) poleward meridional flow at the surface and an equatorward return flow affecting the toroidal flux; (III) latitudinal differential rotation and the near-surface layer of radial rotational shear; (iv) downward convective pumping of magnetic flux in the shear layer; and (v) flux emergence in the form of tilted bipolar magnetic regions treated as a source term for the radial surface field. While the parameters relevant for the transport of the surface field are taken from observations, the model condenses the unknown properties of magnetic field and flow in the convection zone into a few free parameters (turbulent diffusivity, effective return flow, amplitude of the source term, and a parameter describing the effective radial shear). Comparison with the results of 2D flux transport dynamo codes shows that the model captures the essential features of these simulations. We make use of the computational efficiency of the model to carry out an extended parameter study. We cover an extended domain of the 4D parameter space and identify the parameter ranges that provide solar-like solutions. Dipole parity is always preferred and solutions with periods around 22 yr and a correct phase difference between flux emergence in low latitudes and the strength of the polar fields are found for a return flow speed around 2 m s-1, turbulent diffusivity below about 80 km2s-1, and dynamo excitation not too far above the threshold (linear growth rate less than 0.1 yr-1).

Constraining the String Gauge Field by Galaxy Rotation Curves and Perihelion Precession of Planets

NASA Astrophysics Data System (ADS)

Cheung, Yeuk-Kwan E.; Xu, Feng

2013-09-01

We discuss a cosmological model in which the string gauge field coupled universally to matter gives rise to an extra centripetal force and will have observable signatures on cosmological and astronomical observations. Several tests are performed using data including galaxy rotation curves of 22 spiral galaxies of varied luminosities and sizes and perihelion precessions of planets in the solar system. The rotation curves of the same group of galaxies are independently fit using a dark matter model with the generalized Navarro-Frenk-White (NFW) profile and the string model. A remarkable fit of galaxy rotation curves is achieved using the one-parameter string model as compared to the three-parameter dark matter model with the NFW profile. The average χ2 value of the NFW fit is 9% better than that of the string model at a price of two more free parameters. Furthermore, from the string model, we can give a dynamical explanation for the phenomenological Tully-Fisher relation. We are able to derive a relation between field strength, galaxy size, and luminosity, which can be verified with data from the 22 galaxies. To further test the hypothesis of the universal existence of the string gauge field, we apply our string model to the solar system. Constraint on the magnitude of the string field in the solar system is deduced from the current ranges for any anomalous perihelion precession of planets allowed by the latest observations. The field distribution resembles a dipole field originating from the Sun. The string field strength deduced from the solar system observations is of a similar magnitude as the field strength needed to sustain the rotational speed of the Sun inside the Milky Way. This hypothesis can be tested further by future observations with higher precision.

Assessing the performance of community-available global MHD models using key system parameters and empirical relationships

NASA Astrophysics Data System (ADS)

Gordeev, E.; Sergeev, V.; Honkonen, I.; Kuznetsova, M.; Rastätter, L.; Palmroth, M.; Janhunen, P.; Tóth, G.; Lyon, J.; Wiltberger, M.

2015-12-01

Global magnetohydrodynamic (MHD) modeling is a powerful tool in space weather research and predictions. There are several advanced and still developing global MHD (GMHD) models that are publicly available via Community Coordinated Modeling Center's (CCMC) Run on Request system, which allows the users to simulate the magnetospheric response to different solar wind conditions including extraordinary events, like geomagnetic storms. Systematic validation of GMHD models against observations still continues to be a challenge, as well as comparative benchmarking of different models against each other. In this paper we describe and test a new approach in which (i) a set of critical large-scale system parameters is explored/tested, which are produced by (ii) specially designed set of computer runs to simulate realistic statistical distributions of critical solar wind parameters and are compared to (iii) observation-based empirical relationships for these parameters. Being tested in approximately similar conditions (similar inputs, comparable grid resolution, etc.), the four models publicly available at the CCMC predict rather well the absolute values and variations of those key parameters (magnetospheric size, magnetic field, and pressure) which are directly related to the large-scale magnetospheric equilibrium in the outer magnetosphere, for which the MHD is supposed to be a valid approach. At the same time, the models have systematic differences in other parameters, being especially different in predicting the global convection rate, total field-aligned current, and magnetic flux loading into the magnetotail after the north-south interplanetary magnetic field turning. According to validation results, none of the models emerges as an absolute leader. The new approach suggested for the evaluation of the models performance against reality may be used by model users while planning their investigations, as well as by model developers and those interesting to quantitatively evaluate progress in magnetospheric modeling.

Magnetic field induced switching of the antiferromagnetic order parameter in thin films of magnetoelectric chromia

NASA Astrophysics Data System (ADS)

Fallarino, Lorenzo; Berger, Andreas; Binek, Christian

2015-02-01

A Landau-theoretical approach is utilized to model the magnetic field induced reversal of the antiferromagnetic order parameter in thin films of magnetoelectric antiferromagnets. A key ingredient of this peculiar switching phenomenon is the presence of a robust spin polarized state at the surface of the antiferromagnetic films. Surface or boundary magnetization is symmetry allowed in magnetoelectric antiferromagnets and experimentally established for chromia thin films. It couples rigidly to the antiferromagnetic order parameter and its Zeeman energy creates a pathway to switch the antiferromagnet via magnetic field application. In the framework of a minimalist Landau free energy expansion, the temperature dependence of the switching field and the field dependence of the transition width are derived. Least-squares fits to magnetometry data of (0001 ) textured chromia thin films strongly support this model of the magnetic reversal mechanism.

Supernatural inflation: inflation from supersymmetry with no (very) small parameters

NASA Astrophysics Data System (ADS)

Randall, Lisa; SoljačiĆ, Marin; Guth, Alan H.

1996-02-01

Most models of inflation have small parameters, either to guarantee sufficient inflation or the correct magnitude of the density perturbations. In this paper we show that, in supersymmetric theories with weak-scale supersymmetry breaking, one can construct viable inflationary models in which the requisite parameters appear naturally in the form of the ratio of mass scales that are already present in the theory. Successful inflationary models can be constructed from the flat-direction fields of a renormalizable supersymmetric potential, and such models can be realized even in the context of a simple GUT extension of the MSSM. We evade naive ``naturalness'' arguments by allowing for more than one field to be relevant to inflation, as in ``hybrid inflation'' models, and we argue that this is the most natural possibility if inflation fields are to be associated with flat direction fields of a supersymmetric theory. Such models predict a very low Hubble constant during inflation, of order 103-104 GeV, a scalar density perturbation index n which is very close to or greater than unity, and negligible tensor perturbations. In addition, these models lead to a large spike in the density perturbation spectrum at short wavelengths.

A novel prediction method about single components of analog circuits based on complex field modeling.

PubMed

Zhou, Jingyu; Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments.

Thermal inflation with a thermal waterfall scalar field coupled to a light spectator scalar field

NASA Astrophysics Data System (ADS)

Dimopoulos, Konstantinos; Lyth, David H.; Rumsey, Arron

2017-05-01

A new model of thermal inflation is introduced, in which the mass of the thermal waterfall field is dependent on a light spectator scalar field. Using the δ N formalism, the "end of inflation" scenario is investigated in order to ascertain whether this model is able to produce the dominant contribution to the primordial curvature perturbation. A multitude of constraints are considered so as to explore the parameter space, with particular emphasis on key observational signatures. For natural values of the parameters, the model is found to yield a sharp prediction for the scalar spectral index and its running, well within the current observational bounds.

qPIPSA: Relating enzymatic kinetic parameters and interaction fields

PubMed Central

Gabdoulline, Razif R; Stein, Matthias; Wade, Rebecca C

2007-01-01

Background The simulation of metabolic networks in quantitative systems biology requires the assignment of enzymatic kinetic parameters. Experimentally determined values are often not available and therefore computational methods to estimate these parameters are needed. It is possible to use the three-dimensional structure of an enzyme to perform simulations of a reaction and derive kinetic parameters. However, this is computationally demanding and requires detailed knowledge of the enzyme mechanism. We have therefore sought to develop a general, simple and computationally efficient procedure to relate protein structural information to enzymatic kinetic parameters that allows consistency between the kinetic and structural information to be checked and estimation of kinetic constants for structurally and mechanistically similar enzymes. Results We describe qPIPSA: quantitative Protein Interaction Property Similarity Analysis. In this analysis, molecular interaction fields, for example, electrostatic potentials, are computed from the enzyme structures. Differences in molecular interaction fields between enzymes are then related to the ratios of their kinetic parameters. This procedure can be used to estimate unknown kinetic parameters when enzyme structural information is available and kinetic parameters have been measured for related enzymes or were obtained under different conditions. The detailed interaction of the enzyme with substrate or cofactors is not modeled and is assumed to be similar for all the proteins compared. The protein structure modeling protocol employed ensures that differences between models reflect genuine differences between the protein sequences, rather than random fluctuations in protein structure. Conclusion Provided that the experimental conditions and the protein structural models refer to the same protein state or conformation, correlations between interaction fields and kinetic parameters can be established for sets of related enzymes. Outliers may arise due to variation in the importance of different contributions to the kinetic parameters, such as protein stability and conformational changes. The qPIPSA approach can assist in the validation as well as estimation of kinetic parameters, and provide insights into enzyme mechanism. PMID:17919319

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity. Copyright © 2017. Published by Elsevier Inc.

A study on the influence of corona on currents and electromagnetic fields predicted by a nonlinear lightning return-stroke model

NASA Astrophysics Data System (ADS)

De Conti, Alberto; Silveira, Fernando H.; Visacro, Silvério

2014-05-01

This paper investigates the influence of corona on currents and electromagnetic fields predicted by a return-stroke model that represents the lightning channel as a nonuniform transmission line with time-varying (nonlinear) resistance. The corona model used in this paper allows the calculation of corona currents as a function of the radial electric field in the vicinity of the channel. A parametric study is presented to investigate the influence of corona parameters, such as the breakdown electric field and the critical electric field for the stable propagation of streamers, on predicted currents and electromagnetic fields. The results show that, regardless of the assumed corona parameters, the incorporation of corona into the nonuniform and nonlinear transmission line model under investigation modifies the model predictions so that they consistently reproduce most of the typical features of experimentally observed lightning electromagnetic fields and return-stroke speed profiles. In particular, it is shown that the proposed model leads to close vertical electric fields presenting waveforms, amplitudes, and decay with distance in good agreement with dart leader electric field changes measured in triggered lightning experiments. A comparison with popular engineering return-stroke models further confirms the model's ability to predict consistent electric field waveforms in the close vicinity of the channel. Some differences observed in the field amplitudes calculated with the different models can be related to the fact that current distortion, while present in the proposed model, is ultimately neglected in the considered engineering return-stroke models.

Inflation in the mixed Higgs-R2 model

NASA Astrophysics Data System (ADS)

He, Minxi; Starobinsky, Alexei A.; Yokoyama, Jun'ichi

2018-05-01

We analyze a two-field inflationary model consisting of the Ricci scalar squared (R2) term and the standard Higgs field non-minimally coupled to gravity in addition to the Einstein R term. Detailed analysis of the power spectrum of this model with mass hierarchy is presented, and we find that one can describe this model as an effective single-field model in the slow-roll regime with a modified sound speed. The scalar spectral index predicted by this model coincides with those given by the R2 inflation and the Higgs inflation implying that there is a close relation between this model and the R2 inflation already in the original (Jordan) frame. For a typical value of the self-coupling of the standard Higgs field at the high energy scale of inflation, the role of the Higgs field in parameter space involved is to modify the scalaron mass, so that the original mass parameter in the R2 inflation can deviate from its standard value when non-minimal coupling between the Ricci scalar and the Higgs field is large enough.

Gradient parameter and axial and field rays in the gradient-index crystalline lens model

NASA Astrophysics Data System (ADS)

Pérez, M. V.; Bao, C.; Flores-Arias, M. T.; Rama, M. A.; Gómez-Reino, C.

2003-09-01

Gradient-index models of the human lens have received wide attention in optometry and vision sciences for considering how changes in the refractive index profile with age and accommodation may affect refractive power. This paper uses the continuous asymmetric bi-elliptical model to determine gradient parameter and axial and field rays of the human lens in order to study the paraxial propagation of light through the crystalline lens of the eye.

Electronegativity, charge transfer, crystal field strength, and the point charge model revisited.

PubMed

Tanner, Peter A; Ning, Lixin

2013-02-21

Although the optical spectra of LnCl(6)(3-) systems are complex, only two crystal field parameters, B(40) and B(60), are required to model the J-multiplet crystal field splittings in octahedral symmetry. It is found that these parameters exhibit R(-5) and R(-7) dependence, respectively, upon the ionic radius Ln(3+)(VI), but not upon the Ln-Cl distance. More generally, the crystal field strengths of LnX(6) systems (X = Br, Cl, F, O) exhibit linear relationships with ligand electronegativity, charge transfer energy, and fractional ionic character of the Ln-X bond.

An analysis of sensitivity of CLIMEX parameters in mapping species potential distribution and the broad-scale changes observed with minor variations in parameters values: an investigation using open-field Solanum lycopersicum and Neoleucinodes elegantalis as an example

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho

2018-04-01

A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Contraction of electroweak model and neutrino

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gromov, N. A., E-mail: gromov@dm.komisc.ru

The electroweak model, which lepton sector correspond to the contracted gauge group SU(2; j) Multiplication-Sign U(1), j {yields} 0, whereas boson and quark sectors are standard one, is suggested. The field space of the model is fibered under contraction in such a way that neutrino fields are in the fiber and all other fields are in the base. Properties of the fibered field space are understood in context of semi-Riemannian geometry. This model describes in a natural manner why neutrinos so rarely interact with matter, as well as why neutrino cross section increase with the energy. Dimensionfull parameter of themore » model is interpreted as neutrino energy. Dimensionless contraction parameter j at low energy is connected with the Fermi constant of weak interactions and is approximated as j{sup 2} Almost-Equal-To 10{sup -5}.« less

Estimating thermal performance curves from repeated field observations

USGS Publications Warehouse

Childress, Evan; Letcher, Benjamin H.

2017-01-01

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

Vectorlike fermions and Higgs effective field theory revisited

DOE PAGES

Chen, Chien-Yi; Dawson, S.; Furlan, Elisabetta

2017-07-10

Heavy vectorlike quarks (VLQs) appear in many models of beyond the Standard Model physics. Direct experimental searches require these new quarks to be heavy, ≳ 800 – 1000 GeV . Here, we perform a global fit of the parameters of simple VLQ models in minimal representations of S U ( 2 ) L to precision data and Higgs rates. One interesting connection between anomalous Z bmore » $$\\bar{b}$$ interactions and Higgs physics in VLQ models is discussed. Finally, we present our analysis in an effective field theory (EFT) framework and show that the parameters of VLQ models are already highly constrained. Exact and approximate analytical formulas for the S and T parameters in the VLQ models we consider are available in the Supplemental Material as Mathematica files.« less

Phase-field model for isothermal phase transitions in binary alloys

NASA Technical Reports Server (NTRS)

Wheeler, A. A.; Boettinger, W. J.; Mcfadden, G. B.

1992-01-01

A new phase field model is described which models isothermal phase transitions between ideal binary alloy solution phases. Equations are developed for the temporal and spatial variation of the phase field, which describes the identity of the phase, and of the composition. An asymptotic analysis, as the gradient energy coefficient of the phase field becomes small, was conducted. From the analysis, it is shown that the model recovers classical sharp interface models of this situation when the interfacial layers are thin, and they show how to relate the parameters appearing in the phase field model to material and growth parameters in real systems. Further, three stages of temporal evolution are identified: the first corresponding to interfacial genesis which occurs very rapidly; the second to interfacial motion controlled by the local energy difference across the interface and diffusion; the last taking place on a long time scale in which curvature effects are important and which correspond to Ostwald ripening. The results of the numerical calculations are presented.

Nonminimal coupling for the gravitational and electromagnetic fields: Black hole solutions and solitons

NASA Astrophysics Data System (ADS)

Balakin, Alexander B.; Bochkarev, Vladimir V.; Lemos, José P. S.

2008-04-01

Using a Lagrangian formalism, a three-parameter nonminimal Einstein-Maxwell theory is established. The three parameters q1, q2, and q3 characterize the cross-terms in the Lagrangian, between the Maxwell field and terms linear in the Ricci scalar, Ricci tensor, and Riemann tensor, respectively. Static spherically symmetric equations are set up, and the three parameters are interrelated and chosen so that effectively the system reduces to a one parameter only, q. Specific black hole and other type of one-parameter solutions are studied. First, as a preparation, the Reissner-Nordström solution, with q1=q2=q3=0, is displayed. Then, we search for solutions in which the electric field is regular everywhere as well as asymptotically Coulombian, and the metric potentials are regular at the center as well as asymptotically flat. In this context, the one-parameter model with q1≡-q, q2=2q, q3=-q, called the Gauss-Bonnet model, is analyzed in detail. The study is done through the solution of the Abel equation (the key equation), and the dynamical system associated with the model. There is extra focus on an exact solution of the model and its critical properties. Finally, an exactly integrable one-parameter model, with q1≡-q, q2=q, q3=0, is considered also in detail. A special submodel, in which the Fibonacci number appears naturally, of this one-parameter model is shown, and the corresponding exact solution is presented. Interestingly enough, it is a soliton of the theory, the Fibonacci soliton, without horizons and with a mild conical singularity at the center.

Evaluating Force-Field London Dispersion Coefficients Using the Exchange-Hole Dipole Moment Model.

PubMed

Mohebifar, Mohamad; Johnson, Erin R; Rowley, Christopher N

2017-12-12

London dispersion interactions play an integral role in materials science and biophysics. Force fields for atomistic molecular simulations typically represent dispersion interactions by the 12-6 Lennard-Jones potential using empirically determined parameters. These parameters are generally underdetermined, and there is no straightforward way to test if they are physically realistic. Alternatively, the exchange-hole dipole moment (XDM) model from density-functional theory predicts atomic and molecular London dispersion coefficients from first principles, providing an innovative strategy to validate the dispersion terms of molecular-mechanical force fields. In this work, the XDM model was used to obtain the London dispersion coefficients of 88 organic molecules relevant to biochemistry and pharmaceutical chemistry and the values compared with those derived from the Lennard-Jones parameters of the CGenFF, GAFF, OPLS, and Drude polarizable force fields. The molecular dispersion coefficients for the CGenFF, GAFF, and OPLS models are systematically higher than the XDM-calculated values by a factor of roughly 1.5, likely due to neglect of higher order dispersion terms and premature truncation of the dispersion-energy summation. The XDM dispersion coefficients span a large range for some molecular-mechanical atom types, suggesting an unrecognized source of error in force-field models, which assume that atoms of the same type have the same dispersion interactions. Agreement with the XDM dispersion coefficients is even poorer for the Drude polarizable force field. Popular water models were also examined, and TIP3P was found to have dispersion coefficients similar to the experimental and XDM references, although other models employ anomalously high values. Finally, XDM-derived dispersion coefficients were used to parametrize molecular-mechanical force fields for five liquids-benzene, toluene, cyclohexane, n-pentane, and n-hexane-which resulted in improved accuracy in the computed enthalpies of vaporization despite only having to evaluate a much smaller section of the parameter space.

Possible evolution of a bouncing universe in cosmological models with non-minimally coupled scalar fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pozdeeva, Ekaterina O.; Vernov, Sergey Yu.; Skugoreva, Maria A.

2016-12-01

We explore dynamics of cosmological models with bounce solutions evolving on a spatially flat Friedmann-Lemaître-Robertson-Walker background. We consider cosmological models that contain the Hilbert-Einstein curvature term, the induced gravity term with a negative coupled constant, and even polynomial potentials of the scalar field. Bounce solutions with non-monotonic Hubble parameters have been obtained and analyzed. The case when the scalar field has the conformal coupling and the Higgs-like potential with an opposite sign is studied in detail. In this model the evolution of the Hubble parameter of the bounce solution essentially depends on the sign of the cosmological constant.

Study of Far—Field Directivity Pattern for Linear Arrays

NASA Astrophysics Data System (ADS)

Ana-Maria, Chiselev; Luminita, Moraru; Laura, Onose

2011-10-01

A model to calculate directivity pattern in far field is developed in this paper. Based on this model, the three-dimensional beam pattern is introduced and analyzed in order to investigate geometric parameters of linear arrays and their influences on the directivity pattern. Simulations in azimuthal plane are made to highlight the influence of transducers parameters, including number of elements and inter-element spacing. It is true that these parameters are important factors that influence the directivity pattern and the appearance of side-lobes for linear arrays.

Two dimensional model for coherent synchrotron radiation

NASA Astrophysics Data System (ADS)

Huang, Chengkun; Kwan, Thomas J. T.; Carlsten, Bruce E.

2013-01-01

Understanding coherent synchrotron radiation (CSR) effects in a bunch compressor requires an accurate model accounting for the realistic beam shape and parameters. We extend the well-known 1D CSR analytic model into two dimensions and develop a simple numerical model based on the Liénard-Wiechert formula for the CSR field of a coasting beam. This CSR numerical model includes the 2D spatial dependence of the field in the bending plane and is accurate for arbitrary beam energy. It also removes the singularity in the space charge field calculation present in a 1D model. Good agreement is obtained with 1D CSR analytic result for free electron laser (FEL) related beam parameters but it can also give a more accurate result for low-energy/large spot size beams and off-axis/transient fields. This 2D CSR model can be used for understanding the limitation of various 1D models and for benchmarking fully electromagnetic multidimensional particle-in-cell simulations for self-consistent CSR modeling.

The Evolution of the Solar Magnetic Field: A Comparative Analysis of Two Models

NASA Astrophysics Data System (ADS)

McMichael, K. D.; Karak, B. B.; Upton, L.; Miesch, M. S.; Vierkens, O.

2017-12-01

Understanding the complexity of the solar magnetic cycle is a task that has plagued scientists for decades. However, with the help of computer simulations, we have begun to gain more insight into possible solutions to the plethora of questions inside the Sun. STABLE (Surface Transport and Babcock Leighton) is a newly developed 3D dynamo model that can reproduce features of the solar cycle. In this model, the tilted bipolar sunspots are formed on the surface (based on the toroidal field at the bottom of the convection zone) and then decay and disperse, producing the poloidal field. Since STABLE is a 3D model, it is able to solve the full induction equation in the entirety of the solar convection zone as well as incorporate many free parameters (such as spot depth and turbulent diffusion) which are difficult to observe. In an attempt to constrain some of these free parameters, we compare STABLE to a surface flux transport model called AFT (Advective Flux Transport) which solves the radial component of the magnetic field on the solar surface. AFT is a state-of-the-art surface flux transport model that has a proven record of being able to reproduce solar observations with great accuracy. In this project, we implement synthetic bipolar sunspots into both models, using identical surface parameters, and run the models for comparison. We demonstrate that the 3D structure of the sunspots in the interior and the vertical diffusion of the sunspot magnetic field play an important role in establishing the surface magnetic field in STABLE. We found that when a sufficient amount of downward magnetic pumping is included in STABLE, the surface magnetic field from this model becomes insensitive to the internal structure of the sunspot and more consistent with that of AFT.

A new car-following model for autonomous vehicles flow with mean expected velocity field

NASA Astrophysics Data System (ADS)

Wen-Xing, Zhu; Li-Dong, Zhang

2018-02-01

Due to the development of the modern scientific technology, autonomous vehicles may realize to connect with each other and share the information collected from each vehicle. An improved forward considering car-following model was proposed with mean expected velocity field to describe the autonomous vehicles flow behavior. The new model has three key parameters: adjustable sensitivity, strength factor and mean expected velocity field size. Two lemmas and one theorem were proven as criteria for judging the stability of homogeneousautonomous vehicles flow. Theoretical results show that the greater parameters means larger stability regions. A series of numerical simulations were carried out to check the stability and fundamental diagram of autonomous flow. From the numerical simulation results, the profiles, hysteresis loop and density waves of the autonomous vehicles flow were exhibited. The results show that with increased sensitivity, strength factor or field size the traffic jam was suppressed effectively which are well in accordance with the theoretical results. Moreover, the fundamental diagrams corresponding to three parameters respectively were obtained. It demonstrates that these parameters play almost the same role on traffic flux: i.e. before the critical density the bigger parameter is, the greater flux is and after the critical density, the opposite tendency is. In general, the three parameters have a great influence on the stability and jam state of the autonomous vehicles flow.

Fluctuations of the partition function in the generalized random energy model with external field

NASA Astrophysics Data System (ADS)

Bovier, Anton; Klimovsky, Anton

2008-12-01

We study Derrida's generalized random energy model (GREM) in the presence of uniform external field. We compute the fluctuations of the ground state and of the partition function in the thermodynamic limit for all admissible values of parameters. We find that the fluctuations are described by a hierarchical structure which is obtained by a certain coarse graining of the initial hierarchical structure of the GREM with external field. We provide an explicit formula for the free energy of the model. We also derive some large deviation results providing an expression for the free energy in a class of models with Gaussian Hamiltonians and external field. Finally, we prove that the coarse-grained parts of the system emerging in the thermodynamic limit tend to have a certain optimal magnetization, as prescribed by the strength of the external field and by parameters of the GREM.

A power-law coupled three-form dark energy model

NASA Astrophysics Data System (ADS)

Yao, Yan-Hong; Yan, Yang-Jie; Meng, Xin-He

2018-02-01

We consider a field theory model of coupled dark energy which treats dark energy as a three-form field and dark matter as a spinor field. By assuming the effective mass of dark matter as a power-law function of the three-form field and neglecting the potential term of dark energy, we obtain three solutions of the autonomous system of evolution equations, including a de Sitter attractor, a tracking solution and an approximate solution. To understand the strength of the coupling, we confront the model with the latest Type Ia Supernova, Baryon Acoustic Oscillations and Cosmic Microwave Background radiation observations, with the conclusion that the combination of these three databases marginalized over the present dark matter density parameter Ω _{m0} and the present three-form field κ X0 gives stringent constraints on the coupling constant, - 0.017< λ <0.047 (2σ confidence level), by which we present the model's applicable parameter range.

Finite element method (FEM) model of the mechanical stress on phospholipid membranes from shock waves produced in nanosecond electric pulses (nsEP)

NASA Astrophysics Data System (ADS)

Barnes, Ronald; Roth, Caleb C.; Shadaram, Mehdi; Beier, Hope; Ibey, Bennett L.

2015-03-01

The underlying mechanism(s) responsible for nanoporation of phospholipid membranes by nanosecond pulsed electric fields (nsEP) remains unknown. The passage of a high electric field through a conductive medium creates two primary contributing factors that may induce poration: the electric field interaction at the membrane and the shockwave produced from electrostriction of a polar submersion medium exposed to an electric field. Previous work has focused on the electric field interaction at the cell membrane, through such models as the transport lattice method. Our objective is to model the shock wave cell membrane interaction induced from the density perturbation formed at the rising edge of a high voltage pulse in a polar liquid resulting in a shock wave propagating away from the electrode toward the cell membrane. Utilizing previous data from cell membrane mechanical parameters, and nsEP generated shockwave parameters, an acoustic shock wave model based on the Helmholtz equation for sound pressure was developed and coupled to a cell membrane model with finite-element modeling in COMSOL. The acoustic structure interaction model was developed to illustrate the harmonic membrane displacements and stresses resulting from shockwave and membrane interaction based on Hooke's law. Poration is predicted by utilizing membrane mechanical breakdown parameters including cortical stress limits and hydrostatic pressure gradients.

Finite hedging in field theory models of interest rates

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.; Srikant, Marakani

2004-03-01

We use path integrals to calculate hedge parameters and efficacy of hedging in a quantum field theory generalization of the Heath, Jarrow, and Morton [Robert Jarrow, David Heath, and Andrew Morton, Econometrica 60, 77 (1992)] term structure model, which parsimoniously describes the evolution of imperfectly correlated forward rates. We calculate, within the model specification, the effectiveness of hedging over finite periods of time, and obtain the limiting case of instantaneous hedging. We use empirical estimates for the parameters of the model to show that a low-dimensional hedge portfolio is quite effective.

Mutated hilltop inflation revisited

NASA Astrophysics Data System (ADS)

Pal, Barun Kumar

2018-05-01

In this work we re-investigate pros and cons of mutated hilltop inflation. Applying Hamilton-Jacobi formalism we solve inflationary dynamics and find that inflation goes on along the {W}_{-1} branch of the Lambert function. Depending on the model parameter mutated hilltop model renders two types of inflationary solutions: one corresponds to small inflaton excursion during observable inflation and the other describes large field inflation. The inflationary observables from curvature perturbation are in tune with the current data for a wide range of the model parameter. The small field branch predicts negligible amount of tensor to scalar ratio r˜ O(10^{-4}), while the large field sector is capable of generating high amplitude for tensor perturbations, r˜ O(10^{-1}). Also, the spectral index is almost independent of the model parameter along with a very small negative amount of scalar running. Finally we find that the mutated hilltop inflation closely resembles the α -attractor class of inflationary models in the limit of α φ ≫ 1.

Notes on Born-Infeld-type electrodynamics

NASA Astrophysics Data System (ADS)

Kruglov, S. I.

2017-11-01

We propose a new model of nonlinear electrodynamics (NLED) with three parameters. Born-Infeld (BI) electrodynamics and exponential electrodynamics are particular cases of this model. The phenomenon of vacuum birefringence in the external magnetic field is studied. We show that there is no singularity of the electric field at the origin of point-like charged particles. The corrections to Coulomb’s law at r →∞ are obtained. We calculate the total electrostatic energy of charges, for different parameters of the model, which is finite.

Developing force fields when experimental data is sparse: AMBER/GAFF-compatible parameters for inorganic and alkyl oxoanions.

PubMed

Kashefolgheta, Sadra; Vila Verde, Ana

2017-08-09

We present a set of Lennard-Jones parameters for classical, all-atom models of acetate and various alkylated and non-alkylated forms of sulfate, sulfonate and phosphate ions, optimized to reproduce their interactions with water and with the physiologically relevant sodium, ammonium and methylammonium cations. The parameters are internally consistent and are fully compatible with the Generalized Amber Force Field (GAFF), the AMBER force field for proteins, the accompanying TIP3P water model and the sodium model of Joung and Cheatham. The parameters were developed primarily relying on experimental information - hydration free energies and solution activity derivatives at 0.5 m concentration - with ab initio, gas phase calculations being used for the cases where experimental information is missing. The ab initio parameterization scheme presented here is distinct from other approaches because it explicitly connects gas phase binding energies to intermolecular interactions in solution. We demonstrate that the original GAFF/AMBER parameters often overestimate anion-cation interactions, leading to an excessive number of contact ion pairs in solutions of carboxylate ions, and to aggregation in solutions of divalent ions. GAFF/AMBER parameters lead to excessive numbers of salt bridges in proteins and of contact ion pairs between sodium and acidic protein groups, issues that are resolved by using the optimized parameters presented here.

DRAINMOD-GIS: a lumped parameter watershed scale drainage and water quality model

Treesearch

G.P. Fernandez; G.M. Chescheir; R.W. Skaggs; D.M. Amatya

2006-01-01

A watershed scale lumped parameter hydrology and water quality model that includes an uncertainty analysis component was developed and tested on a lower coastal plain watershed in North Carolina. Uncertainty analysis was used to determine the impacts of uncertainty in field and network parameters of the model on the predicted outflows and nitrate-nitrogen loads at the...

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models.

PubMed

Butler, T; Graham, L; Estep, D; Dawson, C; Westerink, J J

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

NASA Astrophysics Data System (ADS)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Curvature perturbation and waterfall dynamics in hybrid inflation

NASA Astrophysics Data System (ADS)

Akbar Abolhasani, Ali; Firouzjahi, Hassan; Sasaki, Misao

2011-10-01

We investigate the parameter spaces of hybrid inflation model with special attention paid to the dynamics of waterfall field and curvature perturbations induced from its quantum fluctuations. Depending on the inflaton field value at the time of phase transition and the sharpness of the phase transition inflation can have multiple extended stages. We find that for models with mild phase transition the induced curvature perturbation from the waterfall field is too large to satisfy the COBE normalization. We investigate the model parameter space where the curvature perturbations from the waterfall quantum fluctuations vary between the results of standard hybrid inflation and the results obtained here.

Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Rychlik, Igor; Mao, Wengang

2018-02-01

The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules.

PubMed

Kim, Seonghoon; Lee, Jumin; Jo, Sunhwan; Brooks, Charles L; Lee, Hui Sun; Im, Wonpil

2017-06-05

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM-GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM-GUI modules to build a protein-ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM-GUI at http://www.charmm-gui.org/input/ligandrm. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

MHODE: a local-homogeneity theory for improved source-parameter estimation of potential fields

NASA Astrophysics Data System (ADS)

Fedi, Maurizio; Florio, Giovanni; Paoletti, Valeria

2015-08-01

We describe a multihomogeneity theory for source-parameter estimation of potential fields. Similar to what happens for random source models, where the monofractal scaling-law has been generalized into a multifractal law, we propose to generalize the homogeneity law into a multihomogeneity law. This allows a theoretically correct approach to study real-world potential fields, which are inhomogeneous and so do not show scale invariance, except in the asymptotic regions (very near to or very far from their sources). Since the scaling properties of inhomogeneous fields change with the scale of observation, we show that they may be better studied at a set of scales than at a single scale and that a multihomogeneous model is needed to explain its complex scaling behaviour. In order to perform this task, we first introduce fractional-degree homogeneous fields, to show that: (i) homogeneous potential fields may have fractional or integer degree; (ii) the source-distributions for a fractional-degree are not confined in a bounded region, similarly to some integer-degree models, such as the infinite line mass and (iii) differently from the integer-degree case, the fractional-degree source distributions are no longer uniform density functions. Using this enlarged set of homogeneous fields, real-world anomaly fields are studied at different scales, by a simple search, at any local window W, for the best homogeneous field of either integer or fractional-degree, this yielding a multiscale set of local homogeneity-degrees and depth estimations which we call multihomogeneous model. It is so defined a new technique of source parameter estimation (Multi-HOmogeneity Depth Estimation, MHODE), permitting retrieval of the source parameters of complex sources. We test the method with inhomogeneous fields of finite sources, such as faults or cylinders, and show its effectiveness also in a real-case example. These applications show the usefulness of the new concepts, multihomogeneity and fractional homogeneity-degree, to obtain valid estimates of the source parameters in a consistent theoretical framework, so overcoming the limitations imposed by global-homogeneity to widespread methods, such as Euler deconvolution.

Magnetization plateaus and ground-state phase diagrams of the S=1 Ising model on the Shastry Sutherland lattice

NASA Astrophysics Data System (ADS)

Deviren, Seyma Akkaya

2017-02-01

In this research, we have investigated the magnetic properties of the spin-1 Ising model on the Shastry Sutherland lattice with the crystal field interaction by using the effective-field theory with correlations. The effects of the applied field on the magnetization are examined in detail in order to obtain the magnetization plateaus, thus different types of magnetization plateaus, such as 1/4, 1/3, 1/2, 3/5, 2/3 and 7/9 of the saturation, are obtained for strong enough magnetic fields (h). Magnetization plateaus exhibit single, triple, quintuplet and sextuple forms according to the interaction parameters, hence the magnetization plateaus originate from the competition between the crystal field (D) and exchange interaction parameters (J, J‧). The ground-state phase diagrams of the system are presented in three varied planes, namely (h/J, J‧/J), (h/J, D/J) and (D/J, J‧/J) planes. These phase diagrams display the Néel (N), collinear (C) and ferromagnetic (F) phases for certain values of the model parameters. The obtained results are in good agreement with some theoretical and experimental studies.

Statistical characteristics of trajectories of diamagnetic unicellular organisms in a magnetic field.

PubMed

Gorobets, Yu I; Gorobets, O Yu

2015-01-01

The statistical model is proposed in this paper for description of orientation of trajectories of unicellular diamagnetic organisms in a magnetic field. The statistical parameter such as the effective energy is calculated on basis of this model. The resulting effective energy is the statistical characteristics of trajectories of diamagnetic microorganisms in a magnetic field connected with their metabolism. The statistical model is applicable for the case when the energy of the thermal motion of bacteria is negligible in comparison with their energy in a magnetic field and the bacteria manifest the significant "active random movement", i.e. there is the randomizing motion of the bacteria of non thermal nature, for example, movement of bacteria by means of flagellum. The energy of the randomizing active self-motion of bacteria is characterized by the new statistical parameter for biological objects. The parameter replaces the energy of the randomizing thermal motion in calculation of the statistical distribution. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mean field study of a propagation-turnover lattice model for the dynamics of histone marking

NASA Astrophysics Data System (ADS)

Yao, Fan; Li, FangTing; Li, TieJun

2017-02-01

We present a mean field study of a propagation-turnover lattice model, which was proposed by Hodges and Crabtree [Proc. Nat. Acad. Sci. 109, 13296 (2012)] for understanding how posttranslational histone marks modulate gene expression in mammalian cells. The kinetics of the lattice model consists of nucleation, propagation and turnover mechanisms, and exhibits second-order phase transition for the histone marking domain. We showed rigorously that the dynamics essentially depends on a non-dimensional parameter κ = k +/ k -, the ratio between the propagation and turnover rates, which has been observed in the simulations. We then studied the lowest order mean field approximation, and observed the phase transition with an analytically obtained critical parameter. The boundary layer analysis was utilized to investigate the structure of the decay profile of the mark density. We also studied the higher order mean field approximation to achieve sharper estimate of the critical transition parameter and more detailed features. The comparison between the simulation and theoretical results shows the validity of our theory.

Toward Improved Force-Field Accuracy through Sensitivity Analysis of Host-Guest Binding Thermodynamics

PubMed Central

Yin, Jian; Fenley, Andrew T.; Henriksen, Niel M.; Gilson, Michael K.

2015-01-01

Improving the capability of atomistic computer models to predict the thermodynamics of noncovalent binding is critical for successful structure-based drug design, and the accuracy of such calculations remains limited by non-optimal force field parameters. Ideally, one would incorporate protein-ligand affinity data into force field parametrization, but this would be inefficient and costly. We now demonstrate that sensitivity analysis can be used to efficiently tune Lennard-Jones parameters of aqueous host-guest systems for increasingly accurate calculations of binding enthalpy. These results highlight the promise of a comprehensive use of calorimetric host-guest binding data, along with existing validation data sets, to improve force field parameters for the simulation of noncovalent binding, with the ultimate goal of making protein-ligand modeling more accurate and hence speeding drug discovery. PMID:26181208

C-field cosmological models: revisited

NASA Astrophysics Data System (ADS)

Yadav, Anil Kumar; Tawfiq Ali, Ahmad; Ray, Saibal; Rahaman, Farook; Hossain Sardar, Iftikar

2016-12-01

We investigate plane symmetric spacetime filled with perfect fluid in the C-field cosmology of Hoyle and Narlikar. A new class of exact solutions has been obtained by considering the creation field C as a function of time only. To get the deterministic solution, it has been assumed that the rate of creation of matter-energy density is proportional to the strength of the existing C-field energy density. Several physical aspects and geometrical properties of the models are discussed in detail, especially showing that some of our solutions of C-field cosmology are free from singularity in contrast to the Big Bang cosmology. A comparative study has been carried out between two models, one singular and the other nonsingular, by contrasting the behaviour of the physical parameters. We note that the model in a unique way represents both the features of the accelerating as well as decelerating universe depending on the parameters and thus seems to provide glimpses of the oscillating or cyclic model of the universe without invoking any other agent or theory in allowing cyclicity.

An improved model for the Earth's gravity field

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Shum, C. K.; Yuan, D. N.; Ries, J. C.; Schutz, B. E.

1989-01-01

An improved model for the Earth's gravity field, TEG-1, was determined using data sets from fourteen satellites, spanning the inclination ranges from 15 to 115 deg, and global surface gravity anomaly data. The satellite measurements include laser ranging data, Doppler range-rate data, and satellite-to-ocean radar altimeter data measurements, which include the direct height measurement and the differenced measurements at ground track crossings (crossover measurements). Also determined was another gravity field model, TEG-1S, which included all the data sets in TEG-1 with the exception of direct altimeter data. The effort has included an intense scrutiny of the gravity field solution methodology. The estimated parameters included geopotential coefficients complete to degree and order 50 with selected higher order coefficients, ocean and solid Earth tide parameters, Doppler tracking station coordinates and the quasi-stationary sea surface topography. Extensive error analysis and calibration of the formal covariance matrix indicate that the gravity field model is a significant improvement over previous models and can be used for general applications in geodesy.

A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling

PubMed Central

Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments. PMID:25147853

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Joining direct and indirect inverse calibration methods to characterize karst, coastal aquifers

NASA Astrophysics Data System (ADS)

De Filippis, Giovanna; Foglia, Laura; Giudici, Mauro; Mehl, Steffen; Margiotta, Stefano; Negri, Sergio

2016-04-01

Parameter estimation is extremely relevant for accurate simulation of groundwater flow. Parameter values for models of large-scale catchments are usually derived from a limited set of field observations, which can rarely be obtained in a straightforward way from field tests or laboratory measurements on samples, due to a number of factors, including measurement errors and inadequate sampling density. Indeed, a wide gap exists between the local scale, at which most of the observations are taken, and the regional or basin scale, at which the planning and management decisions are usually made. For this reason, the use of geologic information and field data is generally made by zoning the parameter fields. However, pure zoning does not perform well in the case of fairly complex aquifers and this is particularly true for karst aquifers. In fact, the support of the hydraulic conductivity measured in the field is normally much smaller than the cell size of the numerical model, so it should be upscaled to a scale consistent with that of the numerical model discretization. Automatic inverse calibration is a valuable procedure to identify model parameter values by conditioning on observed, available data, limiting the subjective evaluations introduced with the trial-and-error technique. Many approaches have been proposed to solve the inverse problem. Generally speaking, inverse methods fall into two groups: direct and indirect methods. Direct methods allow determination of hydraulic conductivities from the groundwater flow equations which relate the conductivity and head fields. Indirect methods, instead, can handle any type of parameters, independently from the mathematical equations that govern the process, and condition parameter values and model construction on measurements of model output quantities, compared with the available observation data, through the minimization of an objective function. Both approaches have pros and cons, depending also on model complexity. For this reason, a joint procedure is proposed by merging both direct and indirect approaches, thus taking advantage of their strengths, first among them the possibility to get a hydraulic head distribution all over the domain, instead of a zonation. Pros and cons of such an integrated methodology, so far unexplored to the authors' knowledge, are derived after application to a highly heterogeneous karst, coastal aquifer located in southern Italy.

Systematic parameter inference in stochastic mesoscopic modeling

NASA Astrophysics Data System (ADS)

Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are "sparse". The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

Influence of anisotropy on anomalous scaling of a passive scalar advected by the Navier-Stokes velocity field.

PubMed

Jurcisinová, E; Jurcisin, M; Remecký, R

2009-10-01

The influence of weak uniaxial small-scale anisotropy on the stability of the scaling regime and on the anomalous scaling of the single-time structure functions of a passive scalar advected by the velocity field governed by the stochastic Navier-Stokes equation is investigated by the field theoretic renormalization group and operator-product expansion within one-loop approximation of a perturbation theory. The explicit analytical expressions for coordinates of the corresponding fixed point of the renormalization-group equations as functions of anisotropy parameters are found, the stability of the three-dimensional Kolmogorov-like scaling regime is demonstrated, and the dependence of the borderline dimension d(c) is an element of (2,3] between stable and unstable scaling regimes is found as a function of the anisotropy parameters. The dependence of the turbulent Prandtl number on the anisotropy parameters is also briefly discussed. The influence of weak small-scale anisotropy on the anomalous scaling of the structure functions of a passive scalar field is studied by the operator-product expansion and their explicit dependence on the anisotropy parameters is present. It is shown that the anomalous dimensions of the structure functions, which are the same (universal) for the Kraichnan model, for the model with finite time correlations of the velocity field, and for the model with the advection by the velocity field driven by the stochastic Navier-Stokes equation in the isotropic case, can be distinguished by the assumption of the presence of the small-scale anisotropy in the systems even within one-loop approximation. The corresponding comparison of the anisotropic anomalous dimensions for the present model with that obtained within the Kraichnan rapid-change model is done.

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

NASA Technical Reports Server (NTRS)

Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

2013-01-01

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

CONSTRAINING THE STRING GAUGE FIELD BY GALAXY ROTATION CURVES AND PERIHELION PRECESSION OF PLANETS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheung, Yeuk-Kwan E.; Xu Feng, E-mail: cheung@nju.edu.cn

2013-09-01

We discuss a cosmological model in which the string gauge field coupled universally to matter gives rise to an extra centripetal force and will have observable signatures on cosmological and astronomical observations. Several tests are performed using data including galaxy rotation curves of 22 spiral galaxies of varied luminosities and sizes and perihelion precessions of planets in the solar system. The rotation curves of the same group of galaxies are independently fit using a dark matter model with the generalized Navarro-Frenk-White (NFW) profile and the string model. A remarkable fit of galaxy rotation curves is achieved using the one-parameter stringmore » model as compared to the three-parameter dark matter model with the NFW profile. The average {chi}{sup 2} value of the NFW fit is 9% better than that of the string model at a price of two more free parameters. Furthermore, from the string model, we can give a dynamical explanation for the phenomenological Tully-Fisher relation. We are able to derive a relation between field strength, galaxy size, and luminosity, which can be verified with data from the 22 galaxies. To further test the hypothesis of the universal existence of the string gauge field, we apply our string model to the solar system. Constraint on the magnitude of the string field in the solar system is deduced from the current ranges for any anomalous perihelion precession of planets allowed by the latest observations. The field distribution resembles a dipole field originating from the Sun. The string field strength deduced from the solar system observations is of a similar magnitude as the field strength needed to sustain the rotational speed of the Sun inside the Milky Way. This hypothesis can be tested further by future observations with higher precision.« less

Application of the precipitation-runoff model in the Warrior coal field, Alabama

USGS Publications Warehouse

Kidd, Robert E.; Bossong, C.R.

1987-01-01

A deterministic precipitation-runoff model, the Precipitation-Runoff Modeling System, was applied in two small basins located in the Warrior coal field, Alabama. Each basin has distinct geologic, hydrologic, and land-use characteristics. Bear Creek basin (15.03 square miles) is undisturbed, is underlain almost entirely by consolidated coal-bearing rocks of Pennsylvanian age (Pottsville Formation), and is drained by an intermittent stream. Turkey Creek basin (6.08 square miles) contains a surface coal mine and is underlain by both the Pottsville Formation and unconsolidated clay, sand, and gravel deposits of Cretaceous age (Coker Formation). Aquifers in the Coker Formation sustain flow through extended rainless periods. Preliminary daily and storm calibrations were developed for each basin. Initial parameter and variable values were determined according to techniques recommended in the user's manual for the modeling system and through field reconnaissance. Parameters with meaningful sensitivity were identified and adjusted to match hydrograph shapes and to compute realistic water year budgets. When the developed calibrations were applied to data exclusive of the calibration period as a verification exercise, results were comparable to those for the calibration period. The model calibrations included preliminary parameter values for the various categories of geology and land use in each basin. The parameter values for areas underlain by the Pottsville Formation in the Bear Creek basin were transferred directly to similar areas in the Turkey Creek basin, and these parameter values were held constant throughout the model calibration. Parameter values for all geologic and land-use categories addressed in the two calibrations can probably be used in ungaged basins where similar conditions exist. The parameter transfer worked well, as a good calibration was obtained for Turkey Creek basin.

Temporal gravity field modeling based on least square collocation with short-arc approach

NASA Astrophysics Data System (ADS)

ran, jiangjun; Zhong, Min; Xu, Houze; Liu, Chengshu; Tangdamrongsub, Natthachet

2014-05-01

After the launch of the Gravity Recovery And Climate Experiment (GRACE) in 2002, several research centers have attempted to produce the finest gravity model based on different approaches. In this study, we present an alternative approach to derive the Earth's gravity field, and two main objectives are discussed. Firstly, we seek the optimal method to estimate the accelerometer parameters, and secondly, we intend to recover the monthly gravity model based on least square collocation method. The method has been paid less attention compared to the least square adjustment method because of the massive computational resource's requirement. The positions of twin satellites are treated as pseudo-observations and unknown parameters at the same time. The variance covariance matrices of the pseudo-observations and the unknown parameters are valuable information to improve the accuracy of the estimated gravity solutions. Our analyses showed that introducing a drift parameter as an additional accelerometer parameter, compared to using only a bias parameter, leads to a significant improvement of our estimated monthly gravity field. The gravity errors outside the continents are significantly reduced based on the selected set of the accelerometer parameters. We introduced the improved gravity model namely the second version of Institute of Geodesy and Geophysics, Chinese Academy of Sciences (IGG-CAS 02). The accuracy of IGG-CAS 02 model is comparable to the gravity solutions computed from the Geoforschungszentrum (GFZ), the Center for Space Research (CSR) and the NASA Jet Propulsion Laboratory (JPL). In term of the equivalent water height, the correlation coefficients over the study regions (the Yangtze River valley, the Sahara desert, and the Amazon) among four gravity models are greater than 0.80.

Impact of induced magnetic field on synovial fluid with peristaltic flow in an asymmetric channel

NASA Astrophysics Data System (ADS)

Afsar Khan, Ambreen; Farooq, Arfa; Vafai, Kambiz

2018-01-01

In this paper, we have worked for the impact of induced magnetic field on peristaltic motion of a non-Newtonian, incompressible, synovial fluid in an asymmetric channel. We have solved the problem for two models, Model-1 which behaves as shear thinning fluid and Model-2 which behaves as shear thickening fluid. The problem is solved by using modified Adomian Decomposition method. It has seen that two models behave quite opposite to each other for some parameters. The impact of various parameters on u, dp/dx, Δp and induced magnetic field bx have been studied graphically. The significant findings of this study is that the size of the trapped bolus and the pressure gradient increases by increasing M for both models.

Modelling the growth of Populus species using Ecosystem Demography (ED) model

NASA Astrophysics Data System (ADS)

Wang, D.; Lebauer, D. S.; Feng, X.; Dietze, M. C.

2010-12-01

Hybrid poplar plantations are an important source being evaluated for biomass production. Effective management of such plantations requires adequate growth and yield models. The Ecosystem Demography model (ED) makes predictions about the large scales of interest in above- and belowground ecosystem structure and the fluxes of carbon and water from a description of the fine-scale physiological processes. In this study, we used a workflow management tool, the Predictive Ecophysiological Carbon flux Analyzer (PECAn), to integrate literature data, field measurement and the ED model to provide predictions of ecosystem functioning. Parameters for the ED ensemble runs were sampled from the posterior distribution of ecophysiological traits of Populus species compiled from the literature using a Bayesian meta-analysis approach. Sensitivity analysis was performed to identify the parameters which contribute the most to the uncertainties of the ED model output. Model emulation techniques were used to update parameter posterior distributions using field-observed data in northern Wisconsin hybrid poplar plantations. Model results were evaluated with 5-year field-observed data in a hybrid poplar plantation at New Franklin, MO. ED was then used to predict the spatial variability of poplar yield in the coterminous United States (United States minus Alaska and Hawaii). Sensitivity analysis showed that root respiration, dark respiration, growth respiration, stomatal slope and specific leaf area contribute the most to the uncertainty, which suggests that our field measurements and data collection should focus on these parameters. The ED model successfully captured the inter-annual and spatial variability of the yield of poplar. Analyses in progress with the ED model focus on evaluating the ecosystem services of short-rotation woody plantations, such as impacts on soil carbon storage, water use, and nutrient retention.

Bianchi Type-II String Cosmological Model with Magnetic Field in f ( R, T) Gravity

NASA Astrophysics Data System (ADS)

Sharma, N. K.; Singh, J. K.

2014-09-01

The spatially homogeneous and totally anisotropic Bianchi type-II cosmological solutions of massive strings have been investigated in the presence of the magnetic field in the framework of f( R, T) gravity proposed by Harko et al. (Phys Rev D 84:024020, 2011). With the help of special law of variation for Hubble's parameter proposed by Berman (Nuovo Cimento B 74:182, 1983) cosmological model is obtained in this theory. We consider f( R, T) model and investigate the modification R+ f( T) in Bianchi type-II cosmology with an appropriate choice of a function f( T)= μ T. We use the power law relation between average Hubble parameter H and average scale factor R to find the solution. The assumption of constant deceleration parameter leads to two models of universe, i.e. power law model and exponential model. Some physical and kinematical properties of the model are also discussed.

Monodomain dynamics for rigid rod and platelet suspensions in strongly coupled coplanar linear flow and magnetic fields. II. Kinetic theory

NASA Astrophysics Data System (ADS)

Forest, M. Gregory; Sircar, Sarthok; Wang, Qi; Zhou, Ruhai

2006-10-01

We establish reciprocity relations of the Doi-Hess kinetic theory for rigid rod macromolecular suspensions governed by the strong coupling among an excluded volume potential, linear flow, and a magnetic field. The relation provides a reduction of the flow and field driven Smoluchowski equation: from five parameters for coplanar linear flows and magnetic field, to two field parameters. The reduced model distinguishes flows with a rotational component, which map to simple shear (with rate parameter) subject to a transverse magnetic field (with strength parameter), and irrotational flows, for which the reduced model consists of a triaxial extensional flow (with two extensional rate parameters). We solve the Smoluchowski equation of the reduced model to explore: (i) the effect of introducing a coplanar magnetic field on each sheared monodomain attractor of the Doi-Hess kinetic theory and (ii) the coupling of coplanar extensional flow and magnetic fields. For (i), we show each sheared attractor (steady and unsteady, with peak axis in and out of the shearing plane, periodic and chaotic orbits) undergoes its own transition sequence versus magnetic field strength. Nonetheless, robust predictions emerge: out-of-plane degrees of freedom are arrested with increasing field strength, and a unique flow-aligning or tumbling/wagging limit cycle emerges above a threshold magnetic field strength or modified geometry parameter value. For (ii), irrotational flows coupled with a coplanar magnetic field yield only steady states. We characterize all (generically biaxial) equilibria in terms of an explicit Boltzmann distribution, providing a natural generalization of analytical results on pure nematic equilibria [P. Constantin, I. Kevrekidis, and E. S. Titi, Arch. Rat. Mech. Anal. 174, 365 (2004); P. Constantin, I. Kevrekidis, and E. S. Titi, Discrete and Continuous Dynamical Systems 11, 101 (2004); P. Constantin and J. Vukadinovic, Nonlinearity 18, 441 (2005); H. Liu, H. Zhang, and P. Zhang, Comm. Math. Sci. 3, 201 (2005); C. Luo, H. Zhang, and P. Zhang, Nonlinearity 18, 379 (2005); I. Fatkullin and V. Slastikov, Nonlinearity 18, 2565 (2005); H. Zhou, H. Wang, Q. Wang, and M. G. Forest, Nonlinearity 18, 2815 (2005)] and extensional flow-induced equilibria [Q. Wang, S. Sircar, and H. Zhou, Comm. Math. Sci. 4, 605 (2005)]. We predict large parameter regions of bi-stable equilibria; the lowest energy state always has principal axis aligned in the flow plane, while another minimum energy state often exists, with primary alignment transverse to the coplanar field.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

Estimating ionospheric currents by inversion from ground-based geomagnetic data and calculating geoelectric fields for studies of geomagnetically induced currents

NASA Astrophysics Data System (ADS)

de Villiers, J. S.; Pirjola, R. J.; Cilliers, P. J.

2016-09-01

This research focuses on the inversion of geomagnetic variation field measurements to obtain the source currents in the ionosphere and magnetosphere, and to determine the geoelectric fields at the Earth's surface. During geomagnetic storms, the geoelectric fields create geomagnetically induced currents (GIC) in power networks. These GIC may disturb the operation of power systems, cause damage to power transformers, and even result in power blackouts. In this model, line currents running east-west along given latitudes are postulated to exist at a certain height above the Earth's surface. This physical arrangement results in the fields on the ground being composed of a zero magnetic east component and a nonzero electric east component. The line current parameters are estimated by inverting Fourier integrals (over wavenumber) of elementary geomagnetic fields using the Levenberg-Marquardt technique. The output parameters of the model are the ionospheric current strength and the geoelectric east component at the Earth's surface. A conductivity profile of the Earth is adapted from a shallow layered-Earth model for one observatory, together with a deep-layer model derived from satellite observations. This profile is used to obtain the ground surface impedance and therefore the reflection coefficient in the integrals. The inputs for the model are a spectrum of the geomagnetic data for 31 May 2013. The output parameters of the model are spectrums of the ionospheric current strength and of the surface geoelectric field. The inverse Fourier transforms of these spectra provide the time variations on the same day. The geoelectric field data can be used as a proxy for GIC in the prediction of GIC for power utilities. The current strength data can assist in the interpretation of upstream solar wind behaviour.

Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions

USGS Publications Warehouse

Liu, C.; Charpentier, R.R.; Su, J.

2011-01-01

Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.

Analytical models for coupling reliability in identical two-magnet systems during slow reversals

NASA Astrophysics Data System (ADS)

Kani, Nickvash; Naeemi, Azad

2017-12-01

This paper follows previous works which investigated the strength of dipolar coupling in two-magnet systems. While those works focused on qualitative analyses, this manuscript elucidates reversal through dipolar coupling culminating in analytical expressions for reversal reliability in identical two-magnet systems. The dipolar field generated by a mono-domain magnetic body can be represented by a tensor containing both longitudinal and perpendicular field components; this field changes orientation and magnitude based on the magnetization of neighboring nanomagnets. While the dipolar field does reduce to its longitudinal component at short time-scales, for slow magnetization reversals, the simple longitudinal field representation greatly underestimates the scope of parameters that ensure reliable coupling. For the first time, analytical models that map the geometric and material parameters required for reliable coupling in two-magnet systems are developed. It is shown that in biaxial nanomagnets, the x ̂ and y ̂ components of the dipolar field contribute to the coupling, while all three dimensions contribute to the coupling between a pair of uniaxial magnets. Additionally, the ratio of the longitudinal and perpendicular components of the dipolar field is also very important. If the perpendicular components in the dipolar tensor are too large, the nanomagnet pair may come to rest in an undesirable meta-stable state away from the free axis. The analytical models formulated in this manuscript map the minimum and maximum parameters for reliable coupling. Using these models, it is shown that there is a very small range of material parameters which can facilitate reliable coupling between perpendicular-magnetic-anisotropy nanomagnets; hence, in-plane nanomagnets are more suitable for coupled systems.

Hybrid Inflation: Multi-field Dynamics and Cosmological Constraints

NASA Astrophysics Data System (ADS)

Clesse, Sébastien

2011-09-01

The dynamics of hybrid models is usually approximated by the evolution of a scalar field slowly rolling along a nearly flat valley. Inflation ends with a waterfall phase, due to a tachyonic instability. This final phase is usually assumed to be nearly instantaneous. In this thesis, we go beyond these approximations and analyze the exact 2-field dynamics of hybrid models. Several effects are put in evidence: 1) the possible slow-roll violations along the valley induce the non existence of inflation at small field values. Provided super-planckian fields, the scalar spectrum of the original model is red, in agreement with observations. 2) The initial field values are not fine-tuned along the valley but also occupy a considerable part of the field space exterior to it. They form a structure with fractal boundaries. Using bayesian methods, their distribution in the whole parameter space is studied. Natural bounds on the potential parameters are derived. 3) For the original model, inflation is found to continue for more than 60 e-folds along waterfall trajectories in some part of the parameter space. The scalar power spectrum of adiabatic perturbations is modified and is generically red, possibly in agreement with CMB observations. Topological defects are conveniently stretched outside the observable Universe. 4) The analysis of the initial conditions is extended to the case of a closed Universe, in which the initial singularity is replaced by a classical bounce. In the third part of the thesis, we study how the present CMB constraints on the cosmological parameters could be ameliorated with the observation of the 21cm cosmic background, by future giant radio-telescopes. Forecasts are determined for a characteristic Fast Fourier Transform Telescope, by using both Fisher matrix and MCMC methods.

Fractional blood flow in oscillatory arteries with thermal radiation and magnetic field effects

NASA Astrophysics Data System (ADS)

Bansi, C. D. K.; Tabi, C. B.; Motsumi, T. G.; Mohamadou, A.

2018-06-01

A fractional model is proposed to study the effect of heat transfer and magnetic field on the blood flowing inside oscillatory arteries. The flow is due to periodic pressure gradient and the fractional model equations include body acceleration. The proposed velocity and temperature distribution equations are solved using the Laplace and Hankel transforms. The effect of the fluid parameters such as the Reynolds number (Re), the magnetic parameter (M) and the radiation parameter (N) is studied graphically with changing the fractional-order parameter. It is found that the fractional derivative is a valuable tool to control both the temperature and velocity of blood when flow parameters change under treatment, for example. Besides, this work highlights the fact that in the presence of strong magnetic field, blood velocity and temperature reduce. A reversed effect is observed where the applied thermal radiation increase; the velocity and temperature of blood increase. However, the temperature remains high around the artery centerline, which is appropriate during treatment to avoid tissues damage.

Analysis of variation in calibration curves for Kodak XV radiographic film using model-based parameters.

PubMed

Hsu, Shu-Hui; Kulasekere, Ravi; Roberson, Peter L

2010-08-05

Film calibration is time-consuming work when dose accuracy is essential while working in a range of photon scatter environments. This study uses the single-target single-hit model of film response to fit the calibration curves as a function of calibration method, processor condition, field size and depth. Kodak XV film was irradiated perpendicular to the beam axis in a solid water phantom. Standard calibration films (one dose point per film) were irradiated at 90 cm source-to-surface distance (SSD) for various doses (16-128 cGy), depths (0.2, 0.5, 1.5, 5, 10 cm) and field sizes (5 × 5, 10 × 10 and 20 × 20 cm²). The 8-field calibration method (eight dose points per film) was used as a reference for each experiment, taken at 95 cm SSD and 5 cm depth. The delivered doses were measured using an Attix parallel plate chamber for improved accuracy of dose estimation in the buildup region. Three fitting methods with one to three dose points per calibration curve were investigated for the field sizes of 5 × 5, 10 × 10 and 20 × 20 cm². The inter-day variation of model parameters (background, saturation and slope) were 1.8%, 5.7%, and 7.7% (1 σ) using the 8-field method. The saturation parameter ratio of standard to 8-field curves was 1.083 ± 0.005. The slope parameter ratio of standard to 8-field curves ranged from 0.99 to 1.05, depending on field size and depth. The slope parameter ratio decreases with increasing depth below 0.5 cm for the three field sizes. It increases with increasing depths above 0.5 cm. A calibration curve with one to three dose points fitted with the model is possible with 2% accuracy in film dosimetry for various irradiation conditions. The proposed fitting methods may reduce workload while providing energy dependence correction in radiographic film dosimetry. This study is limited to radiographic XV film with a Lumisys scanner.

Hygrothermal wave propagation in viscoelastic graphene under in-plane magnetic field based on nonlocal strain gradient theory

NASA Astrophysics Data System (ADS)

Karami, Behrouz; Shahsavari, Davood; Li, Li

2018-03-01

A size-dependent model is developed for the hygrothermal wave propagation analysis of an embedded viscoelastic single layer graphene sheet (SLGS) under the influence of in-plane magnetic field. The bi-Helmholtz nonlocal strain gradient theory involving three small scale parameters is introduced to account for the size-dependent effects. The size-dependent model is deduced based on Hamilton's principle. The closed-form solution of eigenfrequency relation between wave number and phase velocity is achieved. By studying the size-dependent effects on the flexural wave of SLGS, the dispersion relation predicted by the developed size-dependent model can show a good match with experimental data. The influence of in-plane magnetic field, temperature and moisture of environs, structural damping, damped substrate, lower and higher order nonlocal parameters and the material characteristic parameter on the phase velocity of SLGS is explored.

Virtual-source diffusion approximation for enhanced near-field modeling of photon-migration in low-albedo medium.

PubMed

Jia, Mengyu; Chen, Xueying; Zhao, Huijuan; Cui, Shanshan; Liu, Ming; Liu, Lingling; Gao, Feng

2015-01-26

Most analytical methods for describing light propagation in turbid medium exhibit low effectiveness in the near-field of a collimated source. Motivated by the Charge Simulation Method in electromagnetic theory as well as the established discrete source based modeling, we herein report on an improved explicit model for a semi-infinite geometry, referred to as "Virtual Source" (VS) diffuse approximation (DA), to fit for low-albedo medium and short source-detector separation. In this model, the collimated light in the standard DA is analogously approximated as multiple isotropic point sources (VS) distributed along the incident direction. For performance enhancement, a fitting procedure between the calculated and realistic reflectances is adopted in the near-field to optimize the VS parameters (intensities and locations). To be practically applicable, an explicit 2VS-DA model is established based on close-form derivations of the VS parameters for the typical ranges of the optical parameters. This parameterized scheme is proved to inherit the mathematical simplicity of the DA approximation while considerably extending its validity in modeling the near-field photon migration in low-albedo medium. The superiority of the proposed VS-DA method to the established ones is demonstrated in comparison with Monte-Carlo simulations over wide ranges of the source-detector separation and the medium optical properties.

Links between the charge model and bonded parameter force constants in biomolecular force fields

NASA Astrophysics Data System (ADS)

Cerutti, David S.; Debiec, Karl T.; Case, David A.; Chong, Lillian T.

2017-10-01

The ff15ipq protein force field is a fixed charge model built by automated tools based on the two charge sets of the implicitly polarized charge method: one set (appropriate for vacuum) for deriving bonded parameters and the other (appropriate for aqueous solution) for running simulations. The duality is intended to treat water-induced electronic polarization with an understanding that fitting data for bonded parameters will come from quantum mechanical calculations in the gas phase. In this study, we compare ff15ipq to two alternatives produced with the same fitting software and a further expanded data set but following more conventional methods for tailoring bonded parameters (harmonic angle terms and torsion potentials) to the charge model. First, ff15ipq-Qsolv derives bonded parameters in the context of the ff15ipq solution phase charge set. Second, ff15ipq-Vac takes ff15ipq's bonded parameters and runs simulations with the vacuum phase charge set used to derive those parameters. The IPolQ charge model and associated protocol for deriving bonded parameters are shown to be an incremental improvement over protocols that do not account for the material phases of each source of their fitting data. Both force fields incorporating the polarized charge set depict stable globular proteins and have varying degrees of success modeling the metastability of short (5-19 residues) peptides. In this particular case, ff15ipq-Qsolv increases stability in a number of α -helices, correctly obtaining 70% helical character in the K19 system at 275 K and showing appropriately diminishing content up to 325 K, but overestimating the helical fraction of AAQAA3 by 50% or more, forming long-lived α -helices in simulations of a β -hairpin, and increasing the likelihood that the disordered p53 N-terminal peptide will also form a helix. This may indicate a systematic bias imparted by the ff15ipq-Qsolv parameter development strategy, which has the hallmarks of strategies used to develop other popular force fields, and may explain some of the need for manual corrections in this force fields' evolution. In contrast, ff15ipq-Vac incorrectly depicts globular protein unfolding in numerous systems tested, including Trp cage, villin, lysozyme, and GB3, and does not perform any better than ff15ipq or ff15ipq-Qsolv in tests on short peptides. We analyze the free energy surfaces of individual amino acid dipeptides and the electrostatic potential energy surfaces of each charge model to explain the differences.

Evaluating indoor exposure modeling alternatives for LCA: A case study in the vehicle repair industry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demou, Evangelia; Hellweg, Stefanie; Wilson, Michael P.

2009-05-01

We evaluated three exposure models with data obtained from measurements among workers who use"aerosol" solvent products in the vehicle repair industry and with field experiments using these products to simulate the same exposure conditions. The three exposure models were the: 1) homogeneously-mixed-one-box model, 2) multi-zone model, and 3) eddy-diffusion model. Temporally differentiated real-time breathing zone volatile organic compound (VOC) concentration measurements, integrated far-field area samples, and simulated experiments were used in estimating parameters, such as emission rates, diffusivity, and near-field dimensions. We assessed differences in model input requirements and their efficacy for predictive modeling. The One-box model was not ablemore » to resemble the temporal profile of exposure concentrations, but it performed well concerning time-weighted exposure over extended time periods. However, this model required an adjustment for spatial concentration gradients. Multi-zone models and diffusion-models may solve this problem. However, we found that the reliable use of both these models requires extensive field data to appropriately define pivotal parameters such as diffusivity or near-field dimensions. We conclude that it is difficult to apply these models for predicting VOC exposures in the workplace. However, for comparative exposure scenarios in life-cycle assessment they may be useful.« less

Application of an automatic approach to calibrate the NEMURO nutrient-phytoplankton-zooplankton food web model in the Oyashio region

NASA Astrophysics Data System (ADS)

Ito, Shin-ichi; Yoshie, Naoki; Okunishi, Takeshi; Ono, Tsuneo; Okazaki, Yuji; Kuwata, Akira; Hashioka, Taketo; Rose, Kenneth A.; Megrey, Bernard A.; Kishi, Michio J.; Nakamachi, Miwa; Shimizu, Yugo; Kakehi, Shigeho; Saito, Hiroaki; Takahashi, Kazutaka; Tadokoro, Kazuaki; Kusaka, Akira; Kasai, Hiromi

2010-10-01

The Oyashio region in the western North Pacific supports high biological productivity and has been well monitored. We applied the NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) model to simulate the nutrients, phytoplankton, and zooplankton dynamics. Determination of parameters values is very important, yet ad hoc calibration methods are often used. We used the automatic calibration software PEST (model-independent Parameter ESTimation), which has been used previously with NEMURO but in a system without ontogenetic vertical migration of the large zooplankton functional group. Determining the performance of PEST with vertical migration, and obtaining a set of realistic parameter values for the Oyashio, will likely be useful in future applications of NEMURO. Five identical twin simulation experiments were performed with the one-box version of NEMURO. The experiments differed in whether monthly snapshot or averaged state variables were used, in whether state variables were model functional groups or were aggregated (total phytoplankton, small plus large zooplankton), and in whether vertical migration of large zooplankton was included or not. We then applied NEMURO to monthly climatological field data covering 1 year for the Oyashio, and compared model fits and parameter values between PEST-determined estimates and values used in previous applications to the Oyashio region that relied on ad hoc calibration. We substituted the PEST and ad hoc calibrated parameter values into a 3-D version of NEMURO for the western North Pacific, and compared the two sets of spatial maps of chlorophyll- a with satellite-derived data. The identical twin experiments demonstrated that PEST could recover the known model parameter values when vertical migration was included, and that over-fitting can occur as a result of slight differences in the values of the state variables. PEST recovered known parameter values when using monthly snapshots of aggregated state variables, but estimated a different set of parameters with monthly averaged values. Both sets of parameters resulted in good fits of the model to the simulated data. Disaggregating the variables provided to PEST into functional groups did not solve the over-fitting problem, and including vertical migration seemed to amplify the problem. When we used the climatological field data, simulated values with PEST-estimated parameters were closer to these field data than with the previously determined ad hoc set of parameter values. When these same PEST and ad hoc sets of parameter values were substituted into 3-D-NEMURO (without vertical migration), the PEST-estimated parameter values generated spatial maps that were similar to the satellite data for the Kuroshio Extension during January and March and for the subarctic ocean from May to November. With non-linear problems, such as vertical migration, PEST should be used with caution because parameter estimates can be sensitive to how the data are prepared and to the values used for the searching parameters of PEST. We recommend the usage of PEST, or other parameter optimization methods, to generate first-order parameter estimates for simulating specific systems and for insertion into 2-D and 3-D models. The parameter estimates that are generated are useful, and the inconsistencies between simulated values and the available field data provide valuable information on model behavior and the dynamics of the ecosystem.

Magnetic Doppler imaging of 53 Camelopardalis in all four Stokes parameters

NASA Astrophysics Data System (ADS)

Kochukhov, O.; Bagnulo, S.; Wade, G. A.; Sangalli, L.; Piskunov, N.; Landstreet, J. D.; Petit, P.; Sigut, T. A. A.

2004-02-01

We present the first investigation of the structure of the stellar surface magnetic field using line profiles in all four Stokes parameters. We extract the information about the magnetic field geometry and abundance distributions of the chemically peculiar star 53 Cam by modelling time-series of high-resolution spectropolarimetric observations with the help of a new magnetic Doppler imaging code. This combination of the unique four Stokes parameter data and state-of-the-art magnetic imaging technique makes it possible to infer the stellar magnetic field topology directly from the rotational variability of the Stokes spectra. In the magnetic imaging of 53 Cam we discard the traditional multipolar assumptions about the structure of magnetic fields in Ap stars and explore the stellar magnetic topology without introducing any global a priori constraints on the field structure. The complex magnetic model of 53 Cam derived with our magnetic Doppler imaging method achieves a good fit to the observed intensity, circular and linear polarization profiles of strong magnetically sensitive Fe II spectral lines. Such an agreement between observations and model predictions was not possible with any earlier multipolar magnetic models, based on modelling Stokes I spectra and fitting surface averaged magnetic observables (e.g., longitudinal field, magnetic field modulus, etc.). Furthermore, we demonstrate that even the direct inversion of the four Stokes parameters of 53 Cam assuming a low-order multipolar magnetic geometry is incapable of achieving an adequate fit to our spectropolarimetric observations. Thus, as a main result of our investigation, we discover that the magnetic field topology of 53 Cam is considerably more complex than any low-order multipolar expansion, raising a general question about the validity of the multipolar assumption in the studies of magnetic field structures of Ap stars. In addition to the analysis of the magnetic field of 53 Cam, we reconstruct surface abundance distributions of Si, Ca, Ti, Fe and Nd. These abundance maps confirm results of the previous studies of 53 Cam, in particular dramatic antiphase variation of Ca and Ti abundances. Based on observations obtained with the Bernard Lyot telescope of the Pic du Midi Observatory and Isaac Newton Telescope of the La Palma Observatory.

Introduction of Shear-Based Transport Mechanisms in Radial-Axial Hybrid Hall Thruster Simulations

NASA Astrophysics Data System (ADS)

Scharfe, Michelle; Gascon, Nicolas; Scharfe, David; Cappelli, Mark; Fernandez, Eduardo

2007-11-01

Electron diffusion across magnetic field lines in Hall effect thrusters is experimentally observed to be higher than predicted by classical diffusion theory. Motivated by theoretical work for fusion applications and experimental measurements of Hall thrusters, numerical models for the electron transport are implemented in radial-axial hybrid simulations in order to compute the electron mobility using simulated plasma properties and fitting parameters. These models relate the cross-field transport to the imposed magnetic field distribution through shear suppression of turbulence-enhanced transport. While azimuthal waves likely enhance cross field mobility, axial shear in the electron fluid may reduce transport due to a reduction in turbulence amplitudes and modification of phase shifts between fluctuating properties. The sensitivity of the simulation results to the fitting parameters is evaluated and an examination is made of the transportability of these parameters to several Hall thruster devices.

Angular overlap model analysis of the D 2d crystal field effect in uranium (4+) compounds

NASA Astrophysics Data System (ADS)

Gajek, Z.; Hubert, S.; Krupa, J. C.

1988-12-01

Recent interpretations of the D 2d crystal field of U 4+ in β-ThCl 4, α, β-ThBr 4, ThSiO 4 and UCl 4 are discussed in terms of the simplified one-, two- and three-parameter versions of the Angular Overlap Model which are shown to be a handy tool in a trial interpretation of the effect. The variation of the CF parameters with a small D 2 distortion of the coordination is well reproduced by the model.

Bernese advances towards a global analysis of Lunar geodesy

NASA Astrophysics Data System (ADS)

Bertone, S.; Girardin, V.; Bourgoin, A.; Arnold, D.; Jaeggi, A.

2017-12-01

In this presentation we discuss our latest GRAIL-based lunar gravity fields generated with the Celestial Mechanics Approach using the planetary extension of the Bernese GNSS Software (BSW) developed at the Astronomical Institute of the University of Bern (AIUB).Based on one-way X band and two-way S-band Doppler data, we perform orbit determination by solving six initial orbital elements, dynamical parameters, and stochastic parameters in daily arcs using a least-squares adjustment. Significative improvements to our solutions come from the recent implementation of an accurate modeling of non-gravitational forces, including accelerations due to solar and planetary (albedo and IR) radiation pressure, based on the 28-plate macromodel to represent the GRAIL satellites. Also, as suggested in previous works, we deal with imperfections in the modeling of solar eclipses by both an accurate data screening at mid-latitudes and by taking into account solar panel voltage data in our processing. Empirical and pseudo-stochastic parameters are estimated on top of our dynamical modeling to absorb its deficiencies. We analyze the impact of different parametrizations using either pulses (i.e., instantaneous velocity changes) and piecewise constant accelerations (PCA) on our orbits.Based on these improved orbits, one- and two-way Doppler and KBRR data are then used together with an appropriate weighting for a combined orbit and gravity field determination process.We present our latest solutions of the lunar gravity field, based on the recent GRAIL GRGM900C gravity field (as validation of our modeling and parametrization) and on iterations from the SELENE SGM150J gravity field (to check the independence of our solution). We detail our procedure to gradually enlarge the parameter space while adding new data to our gravity field solution. In addition, we present our latest solution for the Moon tidal Love number k_2.Moreover, some important lunar geophysical parameters are best obtained by processing data from Lunar Laser Ranging (LLR) stations. We analyze the impact of a combined processing on the recovery of a set of parameters and we provide some preliminary results.Finally, we compare all of our results with the most recent solutions of the lunar gravity field and of other geodetic parameters released by other groups.

An improved model of the Earth's gravitational field: GEM-T1

NASA Technical Reports Server (NTRS)

Marsh, J. G.; Lerch, F. J.; Christodoulidis, D. C.; Putney, B. H.; Felsentreger, T. L.; Sanchez, B. V.; Smith, D. E.; Klosko, S. M.; Martin, T. V.; Pavlis, E. C.

1987-01-01

Goddard Earth Model T1 (GEM-T1), which was developed from an analysis of direct satellite tracking observations, is the first in a new series of such models. GEM-T1 is complete to degree and order 36. It was developed using consistent reference parameters and extensive earth and ocean tidal models. It was simultaneously solved for gravitational and tidal terms, earth orientation parameters, and the orbital parameters of 580 individual satellite arcs. The solution used only satellite tracking data acquired on 17 different satellites and is predominantly based upon the precise laser data taken by third generation systems. In all, 800,000 observations were used. A major improvement in field accuracy was obtained. For marine geodetic applications, long wavelength geoidal modeling is twice as good as in earlier satellite-only GEM models. Orbit determination accuracy has also been substantially advanced over a wide range of satellites that have been tested.

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

DOE PAGES

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

2016-07-20

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

Parametrization of Stillinger-Weber potential based on valence force field model: application to single-layer MoS2 and black phosphorus

NASA Astrophysics Data System (ADS)

Jiang, Jin-Wu

2015-08-01

We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.

Parametrization of Stillinger-Weber potential based on valence force field model: application to single-layer MoS2 and black phosphorus.

PubMed

Jiang, Jin-Wu

2015-08-07

We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.

Vacuum-induced Berry phases in single-mode Jaynes-Cummings models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yu; Wei, L. F.; Jia, W. Z.

2010-10-15

Motivated by work [Phys. Rev. Lett. 89, 220404 (2002)] for detecting the vacuum-induced Berry phases with two-mode Jaynes-Cummings models (JCMs), we show here that, for a parameter-dependent single-mode JCM, certain atom-field states also acquired photon-number-dependent Berry phases after the parameter slowly changed and eventually returned to its initial value. This geometric effect related to the field quantization still exists, even if the field is kept in its vacuum state. Specifically, a feasible Ramsey interference experiment with a cavity quantum electrodynamics system is designed to detect the vacuum-induced Berry phase.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mori, Taro; Kohri, Kazunori; White, Jonathan, E-mail: moritaro@post.kek.jp, E-mail: kohri@post.kek.jp, E-mail: jwhite@post.kek.jp

We consider inflation in the system containing a Ricci scalar squared term and a canonical scalar field with quadratic mass term. In the Einstein frame this model takes the form of a two-field inflation model with a curved field space, and under the slow-roll approximation contains four free parameters corresponding to the masses of the two fields and their initial positions. We investigate how the inflationary dynamics and predictions for the primordial curvature perturbation depend on these four parameters. Our analysis is based on the δ N formalism, which allows us to determine predictions for the non-Gaussianity of the curvaturemore » perturbation as well as for quantities relating to its power spectrum. Depending on the choice of parameters, we find predictions that range from those of R {sup 2} inflation to those of quadratic chaotic inflation, with the non-Gaussianity of the curvature perturbation always remaining small. Using our results we are able to put constraints on the masses of the two fields.« less

Effect of Longitudinal Magnetic Field on Vibration Characteristics of Single-Walled Carbon Nanotubes in a Viscoelastic Medium

NASA Astrophysics Data System (ADS)

Zhang, D. P.; Lei, Y.; Shen, Z. B.

2017-12-01

The effect of longitudinal magnetic field on vibration response of a sing-walled carbon nanotube (SWCNT) embedded in viscoelastic medium is investigated. Based on nonlocal Euler-Bernoulli beam theory, Maxwell's relations, and Kelvin viscoelastic foundation model, the governing equations of motion for vibration analysis are established. The complex natural frequencies and corresponding mode shapes in closed form for the embedded SWCNT with arbitrary boundary conditions are obtained using transfer function method (TFM). The new analytical expressions for the complex natural frequencies are also derived for certain typical boundary conditions and Kelvin-Voigt model. Numerical results from the model are presented to show the effects of nonlocal parameter, viscoelastic parameter, boundary conditions, aspect ratio, and strength of the magnetic field on vibration characteristics for the embedded SWCNT in longitudinal magnetic field. The results demonstrate the efficiency of the proposed methods for vibration analysis of embedded SWCNTs under magnetic field.

Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models

DOE PAGES

Butler, Troy; Graham, L.; Estep, D.; ...

2015-02-03

The uncertainty in spatially heterogeneous Manning’s n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented in this paper. Technical details that arise in practice by applying the framework to determine the Manning’s n parameter field in amore » shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of “condition” for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. Finally, this notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning’s n parameter and the effect on model predictions is analyzed.« less

Parameterized source term in the diffusion approximation for enhanced near-field modeling of collimated light

NASA Astrophysics Data System (ADS)

Jia, Mengyu; Wang, Shuang; Chen, Xueying; Gao, Feng; Zhao, Huijuan

2016-03-01

Most analytical methods for describing light propagation in turbid medium exhibit low effectiveness in the near-field of a collimated source. Motivated by the Charge Simulation Method in electromagnetic theory as well as the established discrete source based modeling, we have reported on an improved explicit model, referred to as "Virtual Source" (VS) diffuse approximation (DA), to inherit the mathematical simplicity of the DA while considerably extend its validity in modeling the near-field photon migration in low-albedo medium. In this model, the collimated light in the standard DA is analogously approximated as multiple isotropic point sources (VS) distributed along the incident direction. For performance enhancement, a fitting procedure between the calculated and realistic reflectances is adopted in the nearfield to optimize the VS parameters (intensities and locations). To be practically applicable, an explicit 2VS-DA model is established based on close-form derivations of the VS parameters for the typical ranges of the optical parameters. The proposed VS-DA model is validated by comparing with the Monte Carlo simulations, and further introduced in the image reconstruction of the Laminar Optical Tomography system.

Optimization of the Magnetic Field Homogeneity Area for Solenoid Type Magnets

NASA Astrophysics Data System (ADS)

Perepelkin, Eugene; Polyakova, Rima; Tarelkin, Aleksandr; Kovalenko, Alexander; Sysoev, Pavel; Sadovnikova, Marianne; Yudin, Ivan

2018-02-01

Homogeneous magnetic fields are important requisites in modern physics research. In this paper we discuss the problem of magnetic field homogeneity area maximization for solenoid magnets. We discuss A-model and B-model, which are basic types of solenoid magnets used to provide a homogeneous field, and methods for their optimization. We propose C-model which can be used for the NICA project. We have also carried out a cross-check of the C-model with the parameters stated for the CLEO II detector.

On the predictiveness of single-field inflationary models

NASA Astrophysics Data System (ADS)

Burgess, C. P.; Patil, Subodh P.; Trott, Michael

2014-06-01

We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for A S , r and n s are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in principle) for a slightly larger range of Higgs masses. We comment on the origin of the various UV scales that arise at large field values for the SM Higgs, clarifying cut off scale arguments by further developing the formalism of a non-linear realization of SU L (2) × U(1) in curved space. We discuss the interesting fact that, outside of Higgs Inflation, the effect of a non-minimal coupling to gravity, even in the SM, results in a non-linear EFT for the Higgs sector. Finally, we briefly comment on post BICEP2 attempts to modify the Higgs Inflation scenario.

On the effect of the degeneracy among dark energy parameters

NASA Astrophysics Data System (ADS)

Gong, Yungui; Gao, Qing

2014-01-01

The dynamics of scalar fields as dark energy is well approximated by some general relations between the equation of state parameter and the fractional energy density . Based on the approximation, for slowly rolling scalar fields, we derived the analytical expressions of which reduce to the popular Chevallier-Polarski-Linder parametrization with an explicit degeneracy relation between and . The models approximate the dynamics of scalar fields well and help eliminate the degeneracies among , , and . With the explicit degeneracy relations, we test their effects on the constraints of the cosmological parameters. We find that: (1) The analytical relations between and for the two models are consistent with observational data. (2) The degeneracies have little effect on . (3) The error of was reduced about 30 % with the degeneracy relations.

Systematic parameter inference in stochastic mesoscopic modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lei, Huan; Yang, Xiu; Li, Zhen

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the priormore » knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.« less

Comment on ''Equivalence between the Thirring model and a derivative-coupling model''

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banerjee, R.

1988-06-15

An operator equivalence between the Thirring model and the fermionic sector of a Dirac field interacting via derivative coupling with two scalar fields is established in the path-integral framework. Relations between the coupling parameters of the two models, as found by Gomes and da Silva, can be reproduced.

An objective analysis of the dynamic nature of field capacity

NASA Astrophysics Data System (ADS)

Twarakavi, Navin K. C.; Sakai, Masaru; Å Imå¯Nek, Jirka

2009-10-01

Field capacity is one of the most commonly used, and yet poorly defined, soil hydraulic properties. Traditionally, field capacity has been defined as the amount of soil moisture after excess water has drained away and the rate of downward movement has materially decreased. Unfortunately, this qualitative definition does not lend itself to an unambiguous quantitative approach for estimation. Because of the vagueness in defining what constitutes "drainage of excess water" from a soil, the estimation of field capacity has often been based upon empirical guidelines. These empirical guidelines are either time, pressure, or flux based. In this paper, we developed a numerical approach to estimate field capacity using a flux-based definition. The resulting approach was implemented on the soil parameter data set used by Schaap et al. (2001), and the estimated field capacity was compared to traditional definitions of field capacity. The developed modeling approach was implemented using the HYDRUS-1D software with the capability of simultaneously estimating field capacity for multiple soils with soil hydraulic parameter data. The Richards equation was used in conjunction with the van Genuchten-Mualem model to simulate variably saturated flow in a soil. Using the modeling approach to estimate field capacity also resulted in additional information such as (1) the pressure head, at which field capacity is attained, and (2) the drainage time needed to reach field capacity from saturated conditions under nonevaporative conditions. We analyzed the applicability of the modeling-based approach to estimate field capacity on real-world soils data. We also used the developed method to create contour diagrams showing the variation of field capacity with texture. It was found that using benchmark pressure heads to estimate field capacity from the retention curve leads to inaccurate results. Finally, a simple analytical equation was developed to predict field capacity from soil hydraulic parameter information. The analytical equation was found to be effective in its ability to predict field capacities.

Ensemble Forecasting of Coronal Mass Ejections Using the WSA-ENLIL with CONED Model

NASA Technical Reports Server (NTRS)

Emmons, D.; Acebal, A.; Pulkkinen, A.; Taktakishvili, A.; MacNeice, P.; Odstricil, D.

2013-01-01

The combination of the Wang-Sheeley-Arge (WSA) coronal model, ENLIL heliospherical model version 2.7, and CONED Model version 1.3 (WSA-ENLIL with CONED Model) was employed to form ensemble forecasts for 15 halo coronal mass ejections (halo CMEs). The input parameter distributions were formed from 100 sets of CME cone parameters derived from the CONED Model. The CONED Model used image processing along with the bootstrap approach to automatically calculate cone parameter distributions from SOHO/LASCO imagery based on techniques described by Pulkkinen et al. (2010). The input parameter distributions were used as input to WSA-ENLIL to calculate the temporal evolution of the CMEs, which were analyzed to determine the propagation times to the L1 Lagrangian point and the maximum Kp indices due to the impact of the CMEs on the Earth's magnetosphere. The Newell et al. (2007) Kp index formula was employed to calculate the maximum Kp indices based on the predicted solar wind parameters near Earth assuming two magnetic field orientations: a completely southward magnetic field and a uniformly distributed clock-angle in the Newell et al. (2007) Kp index formula. The forecasts for 5 of the 15 events had accuracy such that the actual propagation time was within the ensemble average plus or minus one standard deviation. Using the completely southward magnetic field assumption, 10 of the 15 events contained the actual maximum Kp index within the range of the ensemble forecast, compared to 9 of the 15 events when using a uniformly distributed clock angle.

The Effects of Earth's Outer Core's Viscosity on Geodynamo Models

NASA Astrophysics Data System (ADS)

Dong, C.; Jiao, L.; Zhang, H.

2017-12-01

Geodynamo process is controlled by mathematic equations and input parameters. To study effects of parameters on geodynamo system, MoSST model has been used to simulate geodynamo outputs under different outer core's viscosity ν. With spanning ν for nearly three orders when other parameters fixed, we studied the variation of each physical field and its typical length scale. We find that variation of ν affects the velocity field intensely. The magnetic field almost decreases monotonically with increasing of ν, while the variation is no larger than 30%. The temperature perturbation increases monotonically with ν, but by a very small magnitude (6%). The averaged velocity field (u) of the liquid core increases with ν as a simple fitted scaling relation: u∝ν0.49. The phenomenon that u increases with ν is essentially that increasing of ν breaks the Taylor-Proudman constraint and drops the critical Rayleigh number, and thus u increases under the same thermal driving force. Forces balance is analyzed and balance mode shifts with variation of ν. When compared with former studies of scaling laws, this study supports the conclusion that in a certain parameter range, the magnetic field strength doesn't vary much with the viscosity, but opposes to the assumption that the velocity field has nothing to do with the outer core viscosity.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

Parameterization of the InVEST Crop Pollination Model to spatially predict abundance of wild blueberry (Vaccinium angustifolium Aiton) native bee pollinators in Maine, USA

USGS Publications Warehouse

Groff, Shannon C.; Loftin, Cynthia S.; Drummond, Frank; Bushmann, Sara; McGill, Brian J.

2016-01-01

Non-native honeybees historically have been managed for crop pollination, however, recent population declines draw attention to pollination services provided by native bees. We applied the InVEST Crop Pollination model, developed to predict native bee abundance from habitat resources, in Maine's wild blueberry crop landscape. We evaluated model performance with parameters informed by four approaches: 1) expert opinion; 2) sensitivity analysis; 3) sensitivity analysis informed model optimization; and, 4) simulated annealing (uninformed) model optimization. Uninformed optimization improved model performance by 29% compared to expert opinion-informed model, while sensitivity-analysis informed optimization improved model performance by 54%. This suggests that expert opinion may not result in the best parameter values for the InVEST model. The proportion of deciduous/mixed forest within 2000 m of a blueberry field also reliably predicted native bee abundance in blueberry fields, however, the InVEST model provides an efficient tool to estimate bee abundance beyond the field perimeter.

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

The dependence of the strength and thickness of field-aligned currents on solar wind and ionospheric parameters

PubMed Central

Johnson, Jay R.; Wing, Simon

2017-01-01

Sheared plasma flows at the low-latitude boundary layer (LLBL) correlate well with early afternoon auroral arcs and upward field-aligned currents. We present a simple analytic model that relates solar wind and ionospheric parameters to the strength and thickness of field-aligned currents (Λ) in a region of sheared velocity, such as the LLBL. We compare the predictions of the model with DMSP observations and find remarkably good scaling of the upward region 1 currents with solar wind and ionospheric parameters in region located at the boundary layer or open field lines at 1100–1700 magnetic local time. We demonstrate that Λ~nsw−0.5 and Λ ~ L when Λ/L < 5 where L is the auroral electrostatic scale length. The sheared boundary layer thickness (Δm) is inferred to be around 3000 km, which appears to have weak dependence on Vsw. J‖ has dependencies on Δm, Σp, nsw, and Vsw. The analytic model provides a simple way to organize data and to infer boundary layer structures from ionospheric data. PMID:29057194

Quantum model of a hysteresis in a single-domain magnetically soft ferromagnetic

NASA Astrophysics Data System (ADS)

Ignatiev, V. K.; Lebedev, N. G.; Orlov, A. A.

2018-01-01

A quantum model of a single-domain magnetically soft ferromagnetic is proposed. The α-Fe crystal in a state of the saturation magnetization and a variable magnetic field is considered as a sample. The method of an effective Hamiltonian, including the operators of the Zeeman energy, the spin-orbit interaction and the interaction with the crystal field, is used in the model. An expansion of trial single-electron wave function in a series in small parameter of the spin-orbit interaction is suggested to account for the magnetic anisotropy. Within the framework of the Heisenberg representation, the nonlinear equations of motion for the magnetization and the orbital moment of single domain are obtained. Parameters of the modelling Hamiltonian are found from a comparison with experimental data on the magnetic anisotropy of iron. A phenomenological term of the magnetic friction is introduced into equation of the magnetization motion. Nonlinear equations are solved numerically by the Runge-Kutta method. A dependence of the single domain magnetization on magnetic field intensity has a characteristic form of a hysteresis loop which parameters are quantitatively coordinated with experimental data of researches of magnetic properties of nanoparticles of iron and iron oxide. The method is extended for modelling the magnetization dynamics of multi-domain ferromagnetic in the approximation of a strong crystal field.

A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

NASA Astrophysics Data System (ADS)

Zi, Bin; Zhou, Bin

2016-07-01

For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

Growth rate in the dynamical dark energy models.

PubMed

Avsajanishvili, Olga; Arkhipova, Natalia A; Samushia, Lado; Kahniashvili, Tina

Dark energy models with a slowly rolling cosmological scalar field provide a popular alternative to the standard, time-independent cosmological constant model. We study the simultaneous evolution of background expansion and growth in the scalar field model with the Ratra-Peebles self-interaction potential. We use recent measurements of the linear growth rate and the baryon acoustic oscillation peak positions to constrain the model parameter [Formula: see text] that describes the steepness of the scalar field potential.

A model of the FAD redox cycle describes the dynamics of the effect of the geomagnetic field on the human visual system.

PubMed

Thoss, Franz; Bartsch, Bengt

2017-12-01

In experimental studies, we could show that the visual threshold of man is influenced by the geomagnetic field. One of the results was that the threshold shows periodic fluctuations when the vertical component of the field is reversed periodically. The maximum of these oscillations occurred at a period duration of 110 s. To explain this phenomenon, we chose the process that likely underlies the navigation of birds in the geomagnetic field: the light reaction of the FAD component of cryptochrome in the retina. The human retina contains cryptpochrome like the bird retina. Based on the investigations of Müller and Ahmad (J Biol Chem 286:21033-21040, 2011) and Solov'yov and Schulten (J Phys Chem B 116:1089-1099, 2012), we designed a model of the light-induced reduction and subsequent reoxidation of FAD. This model contains a radical pair, whose interconversion dynamics are affected by the geomagnetic field. The parameters of the model were partly calculated from the data of our experimental investigation and partly taken from the results of other authors. These parameters were then optimized by adjusting the model behaviour to the experimental results. The simulation of the finished model shows that the concentrations of all substances included show really oscillations with the frequency of the modelled magnetic field. After optimization of the parameters, the oscillations of FAD and FADH* show maximal amplitude at a period duration of 110 s, as was observed in the experiment. This makes it most likely that the signal, which influences the visual system, originates from FADH* (signalling state).

The ITSG-Grace2014 Gravity Field Model

NASA Astrophysics Data System (ADS)

Kvas, Andreas; Mayer-Gürr, Torsten; Zehenter, Norbert; Klinger, Beate

2015-04-01

The ITSG-Grace2014 GRACE-only gravity field model consists of a high resolution unconstrained static model (up to degree 200) with trend and annual signal, monthly unconstrained solutions with different spatial resolutions as well as daily snapshots derived by using a Kalman smoother. Apart from the estimated spherical harmonic coefficients, full variance-covariance matrices for the monthly solutions and the static gravity field component are provided. Compared to the previous release, multiple improvements in the processing chain are implemented: updated background models, better ionospheric modeling for GPS observations, an improved satellite attitude by combination of star camera and angular accelerations, estimation of K-band antenna center variations within the gravity field recovery process as well as error covariance function determination. Furthermore, daily gravity field variations have been modeled in the adjustment process to reduce errors caused by temporal leakage. This combined estimation of daily gravity variations field variations together with the static gravity field component represents a computational challenge due to the significantly increased parameter count. The modeling of daily variations up to a spherical harmonic degree of 40 for the whole GRACE observation period results in a system of linear equations with over 6 million unknown gravity field parameters. A least squares adjustment of this size is not solvable in a sensible time frame, therefore measures to reduce the problem size have to be taken. The ITSG-Grace2014 release is presented and selected parts of the processing chain and their effect on the estimated gravity field solutions are discussed.

Approaches to highly parameterized inversion: Pilot-point theory, guidelines, and research directions

USGS Publications Warehouse

Doherty, John E.; Fienen, Michael N.; Hunt, Randall J.

2011-01-01

Pilot points have been used in geophysics and hydrogeology for at least 30 years as a means to bridge the gap between estimating a parameter value in every cell of a model and subdividing models into a small number of homogeneous zones. Pilot points serve as surrogate parameters at which values are estimated in the inverse-modeling process, and their values are interpolated onto the modeling domain in such a way that heterogeneity can be represented at a much lower computational cost than trying to estimate parameters in every cell of a model. Although the use of pilot points is increasingly common, there are few works documenting the mathematical implications of their use and even fewer sources of guidelines for their implementation in hydrogeologic modeling studies. This report describes the mathematics of pilot-point use, provides guidelines for their use in the parameter-estimation software suite (PEST), and outlines several research directions. Two key attributes for pilot-point definitions are highlighted. First, the difference between the information contained in the every-cell parameter field and the surrogate parameter field created using pilot points should be in the realm of parameters which are not informed by the observed data (the null space). Second, the interpolation scheme for projecting pilot-point values onto model cells ideally should be orthogonal. These attributes are informed by the mathematics and have important ramifications for both the guidelines and suggestions for future research.

Linear functional minimization for inverse modeling

DOE PAGES

Barajas-Solano, David A.; Wohlberg, Brendt Egon; Vesselinov, Velimir Valentinov; ...

2015-06-01

In this paper, we present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulicmore » head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Finally, addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.« less

Modeling local structure using crystal field and spin Hamiltonian parameters: the tetragonal FeK3+-OI2- defect center in KTaO3 crystal

NASA Astrophysics Data System (ADS)

Gnutek, P.; Y Yang, Z.; Rudowicz, C.

2009-11-01

The local structure and the spin Hamiltonian (SH) parameters, including the zero-field-splitting (ZFS) parameters D and (a+2F/3), and the Zeeman g factors g_{\\parallel } and g_{\\perp } , are theoretically investigated for the FeK3+-OI2- center in KTaO3 crystal. The microscopic SH (MSH) parameters are modeled within the framework of the crystal field (CF) theory employing the CF analysis (CFA) package, which also incorporates the MSH modules. Our approach takes into account the spin-orbit interaction as well as the spin-spin and spin-other-orbit interactions omitted in previous studies. The superposition model (SPM) calculations are carried out to provide input CF parameters for the CFA/MSH package. The combined SPM-CFA/MSH approach is used to consider various structural models for the FeK3+-OI2- defect center in KTaO3. This modeling reveals that the off-center displacement of the Fe3+ ions, Δ1(Fe3+), combined with an inward relaxation of the nearest oxygen ligands, Δ2(O2-), and the existence of the interstitial oxygen OI2- give rise to a strong tetragonal crystal field. This finding may explain the large ZFS experimentally observed for the FeK3+-OI2- center in KTaO3. Matching the theoretical MSH predictions with the available structural data as well as electron magnetic resonance (EMR) and optical spectroscopy data enables predicting reasonable ranges of values of Δ1(Fe3+) and Δ2(O2-) as well as the possible location of OI2- ligands around Fe3+ ions in KTaO3. The defect structure model obtained using the SPM-CFA/MSH approach reproduces very well the ranges of the experimental SH parameters D, g_{\\parallel } and g_{\\perp } and importantly yields not only the correct magnitude of D but also the sign, unlike previous studies. More reliable predictions may be achieved when experimental data on (a+2F/3) and/or crystal field energy levels become available. Comparison of our results with those arising from alternative models existing in the literature indicates considerable advantages of our method and presumably higher reliability of our predictions.

Transverse fields to tune an Ising-nematic quantum phase transition

NASA Astrophysics Data System (ADS)

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.; Berg, Erez; Fernandes, Rafael M.; Fisher, Ian R.; Kivelson, Steven A.

2017-12-01

The paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated with spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.

Multiphase-field model of small strain elasto-plasticity according to the mechanical jump conditions

NASA Astrophysics Data System (ADS)

Herrmann, Christoph; Schoof, Ephraim; Schneider, Daniel; Schwab, Felix; Reiter, Andreas; Selzer, Michael; Nestler, Britta

2018-04-01

We introduce a small strain elasto-plastic multiphase-field model according to the mechanical jump conditions. A rate-independent J_2 -plasticity model with linear isotropic hardening and without kinematic hardening is applied exemplary. Generally, any physically nonlinear mechanical model is compatible with the subsequently presented procedure. In contrast to models with interpolated material parameters, the proposed model is able to apply different nonlinear mechanical constitutive equations for each phase separately. The Hadamard compatibility condition and the static force balance are employed as homogenization approaches to calculate the phase-inherent stresses and strains. Several verification cases are discussed. The applicability of the proposed model is demonstrated by simulations of the martensitic transformation and quantitative parameters.

Predictive simulations and optimization of nanowire field-effect PSA sensors including screening

NASA Astrophysics Data System (ADS)

Baumgartner, Stefan; Heitzinger, Clemens; Vacic, Aleksandar; Reed, Mark A.

2013-06-01

We apply our self-consistent PDE model for the electrical response of field-effect sensors to the 3D simulation of nanowire PSA (prostate-specific antigen) sensors. The charge concentration in the biofunctionalized boundary layer at the semiconductor-electrolyte interface is calculated using the propka algorithm, and the screening of the biomolecules by the free ions in the liquid is modeled by a sensitivity factor. This comprehensive approach yields excellent agreement with experimental current-voltage characteristics without any fitting parameters. Having verified the numerical model in this manner, we study the sensitivity of nanowire PSA sensors by changing device parameters, making it possible to optimize the devices and revealing the attributes of the optimal field-effect sensor.

High-resolution empirical geomagnetic field model TS07D: Investigating run-on-request and forecasting modes of operation

NASA Astrophysics Data System (ADS)

Stephens, G. K.; Sitnov, M. I.; Ukhorskiy, A. Y.; Vandegriff, J. D.; Tsyganenko, N. A.

2010-12-01

The dramatic increase of the geomagnetic field data volume available due to many recent missions, including GOES, Polar, Geotail, Cluster, and THEMIS, required at some point the appropriate qualitative transition in the empirical modeling tools. Classical empirical models, such as T96 and T02, used few custom-tailored modules to represent major magnetospheric current systems and simple data binning or loading-unloading inputs for their fitting with data and the subsequent applications. They have been replaced by more systematic expansions of the equatorial and field-aligned current contributions as well as by the advanced data-mining algorithms searching for events with the global activity parameters, such as the Sym-H index, similar to those at the time of interest, as is done in the model TS07D (Tsyganenko and Sitnov, 2007; Sitnov et al., 2008). The necessity to mine and fit data dynamically, with the individual subset of the database being used to reproduce the geomagnetic field pattern at every new moment in time, requires the corresponding transition in the use of the new empirical geomagnetic field models. It becomes more similar to runs-on-request offered by the Community Coordinated Modeling Center for many first principles MHD and kinetic codes. To provide this mode of operation for the TS07D model a new web-based modeling tool has been created and tested at the JHU/APL (http://geomag_field.jhuapl.edu/model/), and we discuss the first results of its performance testing and validation, including in-sample and out-of-sample modeling of a number of CME- and CIR-driven magnetic storms. We also report on the first tests of the forecasting version of the TS07D model, where the magnetospheric part of the macro-parameters involved in the data-binning process (Sym-H index and its trend parameter) are replaced by their solar wind-based analogs obtained using the Burton-McPherron-Russell approach.

Modeling Surface Roughness to Estimate Surface Moisture Using Radarsat-2 Quad Polarimetric SAR Data

NASA Astrophysics Data System (ADS)

Nurtyawan, R.; Saepuloh, A.; Budiharto, A.; Wikantika, K.

2016-08-01

Microwave backscattering from the earth's surface depends on several parameters such as surface roughness and dielectric constant of surface materials. The two parameters related to water content and porosity are crucial for estimating soil moisture. The soil moisture is an important parameter for ecological study and also a factor to maintain energy balance of land surface and atmosphere. Direct roughness measurements to a large area require extra time and cost. Heterogeneity roughness scale for some applications such as hydrology, climate, and ecology is a problem which could lead to inaccuracies of modeling. In this study, we modeled surface roughness using Radasat-2 quad Polarimetric Synthetic Aperture Radar (PolSAR) data. The statistical approaches to field roughness measurements were used to generate an appropriate roughness model. This modeling uses a physical SAR approach to predicts radar backscattering coefficient in the parameter of radar configuration (wavelength, polarization, and incidence angle) and soil parameters (surface roughness and dielectric constant). Surface roughness value is calculated using a modified Campbell and Shepard model in 1996. The modification was applied by incorporating the backscattering coefficient (σ°) of quad polarization HH, HV and VV. To obtain empirical surface roughness model from SAR backscattering intensity, we used forty-five sample points from field roughness measurements. We selected paddy field in Indramayu district, West Java, Indonesia as the study area. This area was selected due to intensive decreasing of rice productivity in the Northern Coast region of West Java. Third degree polynomial is the most suitable data fitting with coefficient of determination R2 and RMSE are about 0.82 and 1.18 cm, respectively. Therefore, this model is used as basis to generate the map of surface roughness.

A method for approximating acoustic-field-amplitude uncertainty caused by environmental uncertainties.

PubMed

James, Kevin R; Dowling, David R

2008-09-01

In underwater acoustics, the accuracy of computational field predictions is commonly limited by uncertainty in environmental parameters. An approximate technique for determining the probability density function (PDF) of computed field amplitude, A, from known environmental uncertainties is presented here. The technique can be applied to several, N, uncertain parameters simultaneously, requires N+1 field calculations, and can be used with any acoustic field model. The technique implicitly assumes independent input parameters and is based on finding the optimum spatial shift between field calculations completed at two different values of each uncertain parameter. This shift information is used to convert uncertain-environmental-parameter distributions into PDF(A). The technique's accuracy is good when the shifted fields match well. Its accuracy is evaluated in range-independent underwater sound channels via an L(1) error-norm defined between approximate and numerically converged results for PDF(A). In 50-m- and 100-m-deep sound channels with 0.5% uncertainty in depth (N=1) at frequencies between 100 and 800 Hz, and for ranges from 1 to 8 km, 95% of the approximate field-amplitude distributions generated L(1) values less than 0.52 using only two field calculations. Obtaining comparable accuracy from traditional methods requires of order 10 field calculations and up to 10(N) when N>1.

Study of some chaotic inflationary models in f(R) gravity

NASA Astrophysics Data System (ADS)

Sharif, M.; Nawazish, Iqra

2018-04-01

In this paper, we discuss an inflationary scenario via scalar field and fluid cosmology for an anisotropic homogeneous universe model in f(R) gravity. We consider an equation of state which corresponds to a quasi-de Sitter expansion and investigate the effect of the anisotropy parameter for different values of the deviation parameter. We evaluate potential models like linear, quadratic and quartic models which correspond to chaotic inflation. We construct the observational parameters for a power-law model of f(R) gravity and construct the graphical analysis of tensor-scalar ratio and spectral index which indicates the consistency of these parameters with Planck 2015 data.

Inferring soil salinity in a drip irrigation system from multi-configuration EMI measurements using adaptive Markov chain Monte Carlo

NASA Astrophysics Data System (ADS)

Zaib Jadoon, Khan; Umer Altaf, Muhammad; McCabe, Matthew Francis; Hoteit, Ibrahim; Muhammad, Nisar; Moghadas, Davood; Weihermüller, Lutz

2017-10-01

A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In MCMC the posterior distribution is computed using Bayes' rule. The electromagnetic forward model based on the full solution of Maxwell's equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD Mini-Explorer. Uncertainty in the parameters for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness as compared to layers electrical conductivity are not very informative and are therefore difficult to resolve. Application of the proposed MCMC-based inversion to field measurements in a drip irrigation system demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provides useful insight about parameter uncertainty for the assessment of the model outputs.

Refined Dummy Atom Model of Mg(2+) by Simple Parameter Screening Strategy with Revised Experimental Solvation Free Energy.

PubMed

Jiang, Yang; Zhang, Haiyang; Feng, Wei; Tan, Tianwei

2015-12-28

Metal ions play an important role in the catalysis of metalloenzymes. To investigate metalloenzymes via molecular modeling, a set of accurate force field parameters for metal ions is highly imperative. To extend its application range and improve the performance, the dummy atom model of metal ions was refined through a simple parameter screening strategy using the Mg(2+) ion as an example. Using the AMBER ff03 force field with the TIP3P model, the refined model accurately reproduced the experimental geometric and thermodynamic properties of Mg(2+). Compared with point charge models and previous dummy atom models, the refined dummy atom model yields an enhanced performance for producing reliable ATP/GTP-Mg(2+)-protein conformations in three metalloenzyme systems with single or double metal centers. Similar to other unbounded models, the refined model failed to reproduce the Mg-Mg distance and favored a monodentate binding of carboxylate groups, and these drawbacks needed to be considered with care. The outperformance of the refined model is mainly attributed to the use of a revised (more accurate) experimental solvation free energy and a suitable free energy correction protocol. This work provides a parameter screening strategy that can be readily applied to refine the dummy atom models for metal ions.

Primordial perturbations in multi-scalar inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abedi, Habib; Abbassi, Amir M., E-mail: h.abedi@ut.ac.ir, E-mail: amabasi@khayam.ut.ac.ir

2017-07-01

Multiple field models of inflation exhibit new features than single field models. In this work, we study the hierarchy of parameters based on Hubble expansion rate in curved field space and derive the system of flow equations that describe their evolutions. Then we focus on obtaining derivatives of number of e-folds with respect to scalar fields during inflation and at hypersurface of the end of inflation.

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

USGS Publications Warehouse

Clare, John; McKinney, Shawn T.; DePue, John E.; Loftin, Cynthia S.

2017-01-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture–recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters.

Sensitivity Analysis and Parameter Estimation for a Reactive Transport Model of Uranium Bioremediation

NASA Astrophysics Data System (ADS)

Meyer, P. D.; Yabusaki, S.; Curtis, G. P.; Ye, M.; Fang, Y.

2011-12-01

A three-dimensional, variably-saturated flow and multicomponent biogeochemical reactive transport model of uranium bioremediation was used to generate synthetic data . The 3-D model was based on a field experiment at the U.S. Dept. of Energy Rifle Integrated Field Research Challenge site that used acetate biostimulation of indigenous metal reducing bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. A key assumption in past modeling studies at this site was that a comprehensive reaction network could be developed largely through one-dimensional modeling. Sensitivity analyses and parameter estimation were completed for a 1-D reactive transport model abstracted from the 3-D model to test this assumption, to identify parameters with the greatest potential to contribute to model predictive uncertainty, and to evaluate model structure and data limitations. Results showed that sensitivities of key biogeochemical concentrations varied in space and time, that model nonlinearities and/or parameter interactions have a significant impact on calculated sensitivities, and that the complexity of the model's representation of processes affecting Fe(II) in the system may make it difficult to correctly attribute observed Fe(II) behavior to modeled processes. Non-uniformity of the 3-D simulated groundwater flux and averaging of the 3-D synthetic data for use as calibration targets in the 1-D modeling resulted in systematic errors in the 1-D model parameter estimates and outputs. This occurred despite using the same reaction network for 1-D modeling as used in the data-generating 3-D model. Predictive uncertainty of the 1-D model appeared to be significantly underestimated by linear parameter uncertainty estimates.

Determination of MLC model parameters for Monaco using commercial diode arrays.

PubMed

Kinsella, Paul; Shields, Laura; McCavana, Patrick; McClean, Brendan; Langan, Brian

2016-07-08

Multileaf collimators (MLCs) need to be characterized accurately in treatment planning systems to facilitate accurate intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT). The aim of this study was to examine the use of MapCHECK 2 and ArcCHECK diode arrays for optimizing MLC parameters in Monaco X-ray voxel Monte Carlo (XVMC) dose calculation algorithm. A series of radiation test beams designed to evaluate MLC model parameters were delivered to MapCHECK 2, ArcCHECK, and EBT3 Gafchromic film for comparison. Initial comparison of the calculated and ArcCHECK-measured dose distributions revealed it was unclear how to change the MLC parameters to gain agreement. This ambiguity arose due to an insufficient sampling of the test field dose distributions and unexpected discrepancies in the open parts of some test fields. Consequently, the XVMC MLC parameters were optimized based on MapCHECK 2 measurements. Gafchromic EBT3 film was used to verify the accuracy of MapCHECK 2 measured dose distributions. It was found that adjustment of the MLC parameters from their default values resulted in improved global gamma analysis pass rates for MapCHECK 2 measurements versus calculated dose. The lowest pass rate of any MLC-modulated test beam improved from 68.5% to 93.5% with 3% and 2 mm gamma criteria. Given the close agreement of the optimized model to both MapCHECK 2 and film, the optimized model was used as a benchmark to highlight the relatively large discrepancies in some of the test field dose distributions found with ArcCHECK. Comparison between the optimized model-calculated dose and ArcCHECK-measured dose resulted in global gamma pass rates which ranged from 70.0%-97.9% for gamma criteria of 3% and 2 mm. The simple square fields yielded high pass rates. The lower gamma pass rates were attributed to the ArcCHECK overestimating the dose in-field for the rectangular test fields whose long axis was parallel to the long axis of the ArcCHECK. Considering ArcCHECK measurement issues and the lower gamma pass rates for the MLC-modulated test beams, it was concluded that MapCHECK 2 was a more suitable detector than ArcCHECK for the optimization process. © 2016 The Authors

Substorm Electric And Magnetic Fields In The Earth's Magnetotail: Observations Compared To The WINDMI Model

NASA Astrophysics Data System (ADS)

Srinivas, P. G.; Spencer, E. A.; Vadepu, S. K.; Horton, W., Jr.

2017-12-01

We compare satellite observations of substorm electric fields and magnetic fields to the output of a low dimensional nonlinear physics model of the nightside magnetosphere called WINDMI. The electric and magnetic field satellite data are used to calculate the E X B drift, which is one of the intermediate variables of the WINDMI model. The model uses solar wind and IMF measurements from the ACE spacecraft as input into a system of 8 nonlinear ordinary differential equations. The state variables of the differential equations represent the energy stored in the geomagnetic tail, central plasma sheet, ring current and field aligned currents. The output from the model is the ground based geomagnetic westward auroral electrojet (AL) index, and the Dst index.Using ACE solar wind data, IMF data and SuperMAG identification of substorm onset times up to December 2015, we constrain the WINDMI model to trigger substorm events, and compare the model intermediate variables to THEMIS and GEOTAIL satellite data in the magnetotail. By forcing the model to be consistent with satellite electric and magnetic field observations, we are able to track the magnetotail energy dynamics, the field aligned current contributions, energy injections into the ring current, and ensure that they are within allowable limts. In addition we are able to constrain the physical parameters of the model, in particular the lobe inductance, the plasma sheet capacitance, and the resistive and conductive parameters in the plasma sheet and ionosphere.

Electron transfer from a carbon nanotube into vacuum under high electric fields

NASA Astrophysics Data System (ADS)

Filip, L. D.; Smith, R. C.; Carey, J. D.; Silva, S. R. P.

2009-05-01

The transfer of an electron from a carbon nanotube (CNT) tip into vacuum under a high electric field is considered beyond the usual one-dimensional semi-classical approach. A model of the potential energy outside the CNT cap is proposed in order to show the importance of the intrinsic CNT parameters such as radius, length and vacuum barrier height. This model also takes into account set-up parameters such as the shape of the anode and the anode-to-cathode distance, which are generically portable to any modelling study of electron emission from a tip emitter. Results obtained within our model compare well to experimental data. Moreover, in contrast to the usual one-dimensional Wentzel-Kramers-Brillouin description, our model retains the ability to explain non-standard features of the process of electron field emission from CNTs that arise as a result of the quantum behaviour of electrons on the surface of the CNT.

Theoretical and experimental studies of the molecular orbital bonding coefficients for Cu{sup 2+} ion in cesium hydrogen oxalate single crystals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalfaoğlu, Emel, E-mail: emelkalfaoglu@mynet.com; Karabulut, Bünyamin

2016-03-25

Electron paramagnetic resonance (EPR) and optical absorption spectra of Cu{sup 2+} ions in cesium hydrogen oxalate single crystals have been investigated at room temperature. The spin-Hamiltonian parameters (g and A), have been determined. Crystalline field around the Cu{sup 2+} ion is almost axially symmetric. The results show a single paramagnetic site which confirms the triclinic crystal symmetry. Molecular orbital bonding coefficients are studied from the EPR and optical data. Theoretical octahedral field parameter and the tetragonal field parameters have been evaluated from the superposition model. Using these parameters, various bonding parameters are analyzed and the nature of bonding in themore » complex is discussed. The theoretical results are supported by experimental results.« less

A magnetospheric magnetic field model with flexible current systems driven by independent physical parameters

NASA Technical Reports Server (NTRS)

Hilmer, Robert V.; Voigt, Gerd-Hannes

1995-01-01

A tilt-dependent magnetic field model of the Earth's magnetosphere with variable magnetopause standoff distance is presented. Flexible analytic representations for the ring and cross-tail currents, each composed of the elements derived from the Tsyganenko and Usmanov (1982) model, are combined with the fully shielded vacuum dipole configurations of Voigt (1981). Although the current sheet does not warp in the y-z plane, changes in the shape and position of the neutral sheet with dipole tilt are consistent with both MHD equilibrium theory and observations. In addition, there is good agreement with observed Delta B profiles and the average equatorial contours of magnetic field magnitude. While the dipole field is rigorously shielded within the defined magnetopause, the ring and cross-tails currents are not similarly confined, consequently, the model's region of validity is limited to the inner magnetosphere. The model depends on four independent external parameters. We present a simple but limited method of simulating several substorm related magnetic field changes associated with the disrupion of the near-Earth cross-tail current sheet and collapse of the midnight magnetotail field region. This feature further facilitates the generation of magnetic field configuration time sequences useful in plasma convection simulations of real magnetospheric events.

Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro.

PubMed

Yang, Yongji; Moser, Michael A J; Zhang, Edwin; Zhang, Wenjun; Zhang, Bing

2018-01-01

The aim of this study was to develop a statistical model for cell death by irreversible electroporation (IRE) and to show that the statistic model is more accurate than the electric field threshold model in the literature using cervical cancer cells in vitro. HeLa cell line was cultured and treated with different IRE protocols in order to obtain data for modeling the statistical relationship between the cell death and pulse-setting parameters. In total, 340 in vitro experiments were performed with a commercial IRE pulse system, including a pulse generator and an electric cuvette. Trypan blue staining technique was used to evaluate cell death after 4 hours of incubation following IRE treatment. Peleg-Fermi model was used in the study to build the statistical relationship using the cell viability data obtained from the in vitro experiments. A finite element model of IRE for the electric field distribution was also built. Comparison of ablation zones between the statistical model and electric threshold model (drawn from the finite element model) was used to show the accuracy of the proposed statistical model in the description of the ablation zone and its applicability in different pulse-setting parameters. The statistical models describing the relationships between HeLa cell death and pulse length and the number of pulses, respectively, were built. The values of the curve fitting parameters were obtained using the Peleg-Fermi model for the treatment of cervical cancer with IRE. The difference in the ablation zone between the statistical model and the electric threshold model was also illustrated to show the accuracy of the proposed statistical model in the representation of ablation zone in IRE. This study concluded that: (1) the proposed statistical model accurately described the ablation zone of IRE with cervical cancer cells, and was more accurate compared with the electric field model; (2) the proposed statistical model was able to estimate the value of electric field threshold for the computer simulation of IRE in the treatment of cervical cancer; and (3) the proposed statistical model was able to express the change in ablation zone with the change in pulse-setting parameters.

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

PubMed

Cole, Daniel J; Vilseck, Jonah Z; Tirado-Rives, Julian; Payne, Mike C; Jorgensen, William L

2016-05-10

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.

On the Collisionless Asymmetric Magnetic Reconnection Rate

NASA Astrophysics Data System (ADS)

Liu, Yi-Hsin; Hesse, M.; Cassak, P. A.; Shay, M. A.; Wang, S.; Chen, L.-J.

2018-04-01

A prediction of the steady state reconnection electric field in asymmetric reconnection is obtained by maximizing the reconnection rate as a function of the opening angle made by the upstream magnetic field on the weak magnetic field (magnetosheath) side. The prediction is within a factor of 2 of the widely examined asymmetric reconnection model (Cassak & Shay, 2007, https://doi.org/10.1063/1.2795630) in the collisionless limit, and they scale the same over a wide parameter regime. The previous model had the effective aspect ratio of the diffusion region as a free parameter, which simulations and observations suggest is on the order of 0.1, but the present model has no free parameters. In conjunction with the symmetric case (Liu et al., 2017, https://doi.org/10.1103/PhysRevLett.118.085101), this work further suggests that this nearly universal number 0.1, essentially the normalized fast-reconnection rate, is a geometrical factor arising from maximizing the reconnection rate within magnetohydrodynamic-scale constraints.

Dynamic phase transitions of the Blume-Emery-Griffiths model under an oscillating external magnetic field by the path probability method

NASA Astrophysics Data System (ADS)

Ertaş, Mehmet; Keskin, Mustafa

2015-03-01

By using the path probability method (PPM) with point distribution, we study the dynamic phase transitions (DPTs) in the Blume-Emery-Griffiths (BEG) model under an oscillating external magnetic field. The phases in the model are obtained by solving the dynamic equations for the average order parameters and a disordered phase, ordered phase and four mixed phases are found. We also investigate the thermal behavior of the dynamic order parameters to analyze the nature dynamic transitions as well as to obtain the DPT temperatures. The dynamic phase diagrams are presented in three different planes in which exhibit the dynamic tricritical point, double critical end point, critical end point, quadrupole point, triple point as well as the reentrant behavior, strongly depending on the values of the system parameters. We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory.

Balancing the Interactions of Ions, Water, and DNA in the Drude Polarizable Force Field

PubMed Central

2015-01-01

Recently we presented a first-generation all-atom Drude polarizable force field for DNA based on the classical Drude oscillator model, focusing on optimization of key dihedral angles followed by extensive validation of the force field parameters. Presently, we describe the procedure for balancing the electrostatic interactions between ions, water, and DNA as required for development of the Drude force field for DNA. The proper balance of these interactions is shown to impact DNA stability and subtler conformational properties, including the conformational equilibrium between the BI and BII states, and the A and B forms of DNA. The parametrization efforts were simultaneously guided by gas-phase quantum mechanics (QM) data on small model compounds and condensed-phase experimental data on the hydration and osmotic properties of biologically relevant ions and their solutions, as well as theoretical predictions for ionic distribution around DNA oligomer. In addition, fine-tuning of the internal base parameters was performed to obtain the final DNA model. Notably, the Drude model is shown to more accurately reproduce counterion condensation theory predictions of DNA charge neutralization by the condensed ions as compared to the CHARMM36 additive DNA force field, indicating an improved physical description of the forces dictating the ionic solvation of DNA due to the explicit treatment of electronic polarizability. In combination with the polarizable DNA force field, the availability of Drude polarizable parameters for proteins, lipids, and carbohydrates will allow for simulation studies of heterogeneous biological systems. PMID:24874104

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

NASA Technical Reports Server (NTRS)

Koren, Ilan; Feingold, Graham; Remer, Lorraine A.

2010-01-01

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

Transverse fields to tune an Ising-nematic quantum phase transition [Transverse fields to tune an Ising-nematic quantum critical transition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.

Here, the paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated withmore » spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.« less

Transverse fields to tune an Ising-nematic quantum phase transition [Transverse fields to tune an Ising-nematic quantum critical transition

DOE PAGES

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.; ...

2017-12-05

Here, the paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated withmore » spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.« less

A coastal three-dimensional water quality model of nitrogen in Jiaozhou Bay linking field experiments with modelling.

PubMed

Lu, Dongliang; Li, Keqiang; Liang, Shengkang; Lin, Guohong; Wang, Xiulin

2017-01-15

With anthropogenic changes, the structure and quantity of nitrogen nutrients have changed in coastal ocean, which has dramatically influenced the water quality. Water quality modeling can contribute to the necessary scientific grounding of coastal management. In this paper, some of the dynamic functions and parameters of nitrogen were calibrated based on coastal field experiments covering the dynamic nitrogen processes in Jiaozhou Bay (JZB), including phytoplankton growth, respiration, and mortality; particulate nitrogen degradation; and dissolved organic nitrogen remineralization. The results of the field experiments and box model simulations showed good agreement (RSD=20%±2% and SI=0.77±0.04). A three-dimensional water quality model of nitrogen (3DWQMN) in JZB was improved and the dynamic parameters were updated according to field experiments. The 3DWQMN was validated based on observed data from 2012 to 2013, with good agreement (RSD=27±4%, SI=0.68±0.06, and K=0.48±0.04), which testifies to the model's credibility. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combined Uncertainty and A-Posteriori Error Bound Estimates for CFD Calculations: Theory and Implementation

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2014-01-01

Simulation codes often utilize finite-dimensional approximation resulting in numerical error. Some examples include, numerical methods utilizing grids and finite-dimensional basis functions, particle methods using a finite number of particles. These same simulation codes also often contain sources of uncertainty, for example, uncertain parameters and fields associated with the imposition of initial and boundary data,uncertain physical model parameters such as chemical reaction rates, mixture model parameters, material property parameters, etc.

Geodetic Strain Analysis Tool

NASA Technical Reports Server (NTRS)

Kedar, Sharon; Baxter, Sean C.; Parker, Jay W.; Webb, Frank H.; Owen, Susan E.; Sibthorpe, Anthony J.; Dong, Danan

2011-01-01

A geodetic software analysis tool enables the user to analyze 2D crustal strain from geodetic ground motion, and create models of crustal deformation using a graphical interface. Users can use any geodetic measurements of ground motion and derive the 2D crustal strain interactively. This software also provides a forward-modeling tool that calculates a geodetic velocity and strain field for a given fault model, and lets the user compare the modeled strain field with the strain field obtained from the user s data. Users may change parameters on-the-fly and obtain a real-time recalculation of the resulting strain field. Four data products are computed: maximum shear, dilatation, shear angle, and principal components. The current view and data dependencies are processed first. The remaining data products and views are then computed in a round-robin fashion to anticipate view changes. When an analysis or display parameter is changed, the affected data products and views are invalidated and progressively re-displayed as available. This software is designed to facilitate the derivation of the strain fields from the GPS and strain meter data that sample it to facilitate the understanding of the strengths and weaknesses of the strain field derivation from continuous GPS (CGPS) and other geodetic data from a variety of tectonic settings, to converge on the "best practices" strain derivation strategy for the Solid Earth Science ESDR System (SESES) project given the CGPS station distribution in the western U.S., and to provide SESES users with a scientific and educational tool to explore the strain field on their own with user-defined parameters.

Building analytical three-field cosmological models

NASA Astrophysics Data System (ADS)

Santos, J. R. L.; Moraes, P. H. R. S.; Ferreira, D. A.; Neta, D. C. Vilar

2018-02-01

A difficult task to deal with is the analytical treatment of models composed of three real scalar fields, as their equations of motion are in general coupled and hard to integrate. In order to overcome this problem we introduce a methodology to construct three-field models based on the so-called "extension method". The fundamental idea of the procedure is to combine three one-field systems in a non-trivial way, to construct an effective three scalar field model. An interesting scenario where the method can be implemented is with inflationary models, where the Einstein-Hilbert Lagrangian is coupled with the scalar field Lagrangian. We exemplify how a new model constructed from our method can lead to non-trivial behaviors for cosmological parameters.

An overview of methods for developing bioenergetic and life history models for rare and endangered species

USGS Publications Warehouse

Petersen, J.H.; DeAngelis, D.L.; Paukert, C.P.

2008-01-01

Many fish species are at risk to some degree, and conservation efforts are planned or underway to preserve sensitive populations. For many imperiled species, models could serve as useful tools for researchers and managers as they seek to understand individual growth, quantify predator-prey dynamics, and identify critical sources of mortality. Development and application of models for rare species however, has been constrained by small population sizes, difficulty in obtaining sampling permits, limited opportunities for funding, and regulations on how endangered species can be used in laboratory studies. Bioenergetic and life history models should help with endangered species-recovery planning since these types of models have been used successfully in the last 25 years to address management problems for many commercially and recreationally important fish species. In this paper we discuss five approaches to developing models and parameters for rare species. Borrowing model functions and parameters from related species is simple, but uncorroborated results can be misleading. Directly estimating parameters with laboratory studies may be possible for rare species that have locally abundant populations. Monte Carlo filtering can be used to estimate several parameters by means of performing simple laboratory growth experiments to first determine test criteria. Pattern-oriented modeling (POM) is a new and developing field of research that uses field-observed patterns to build, test, and parameterize models. Models developed using the POM approach are closely linked to field data, produce testable hypotheses, and require a close working relationship between modelers and empiricists. Artificial evolution in individual-based models can be used to gain insight into adaptive behaviors for poorly understood species and thus can fill in knowledge gaps. ?? Copyright by the American Fisheries Society 2008.

Machine Learning for Mapping Groundwater Salinity with Oil Well Log Data

NASA Astrophysics Data System (ADS)

Chang, W. H.; Shimabukuro, D.; Gillespie, J. M.; Stephens, M.

2016-12-01

An oil field may have thousands of wells with detailed petrophysical logs, and far fewer direct measurements of groundwater salinity. Can the former be used to extrapolate the latter into a detailed map of groundwater salinity? California Senate Bill 4, with its requirement to identify Underground Sources of Drinking Water, makes this a question worth answering. A well-known obstacle is that the basic petrophysical equations describe ideal scenarios ("clean wet sand") and even these equations contain many parameters that may vary with location and depth. Accounting for other common scenarios such as high-conductivity shaly sands or low-permeability diatomite (both characteristic of California's Central Valley) causes parameters to proliferate to the point where the model is underdetermined by the data. When parameters outnumber data points, however, is when machine learning methods are most advantageous. We present a method for modeling a generic oil field, where groundwater salinity and lithology are depth series parameters, and the constants in petrophysical equations are scalar parameters. The data are well log measurements (resistivity, porosity, spontaneous potential, and gamma ray) and a small number of direct groundwater salinity measurements. Embedded in the model are petrophysical equations that account for shaly sand and diatomite formations. As a proof of concept, we feed in well logs and salinity measurements from the Lost Hills Oil Field in Kern County, California, and show that with proper regularization and validation the model makes reasonable predictions of groundwater salinity despite the large number of parameters. The model is implemented using Tensorflow, which is an open-source software released by Google in November, 2015 that has been rapidly and widely adopted by machine learning researchers. The code will be made available on Github, and we encourage scrutiny and modification by machine learning researchers and hydrogeologists alike.

Small field models with gravitational wave signature supported by CMB data

PubMed Central

Brustein, Ramy

2018-01-01

We study scale dependence of the cosmic microwave background (CMB) power spectrum in a class of small, single-field models of inflation which lead to a high value of the tensor to scalar ratio. The inflaton potentials that we consider are degree 5 polynomials, for which we precisely calculate the power spectrum, and extract the cosmological parameters: the scalar index ns, the running of the scalar index nrun and the tensor to scalar ratio r. We find that for non-vanishing nrun and for r as small as r = 0.001, the precisely calculated values of ns and nrun deviate significantly from what the standard analytic treatment predicts. We study in detail, and discuss the probable reasons for such deviations. As such, all previously considered models (of this kind) are based upon inaccurate assumptions. We scan the possible values of potential parameters for which the cosmological parameters are within the allowed range by observations. The 5 parameter class is able to reproduce all of the allowed values of ns and nrun for values of r that are as high as 0.001. Subsequently this study at once refutes previous such models built using the analytical Stewart-Lyth term, and revives the small field brand, by building models that do yield an appreciable r while conforming to known CMB observables. PMID:29795608

Modeling Coronal Mass Ejections with EUHFORIA: A Parameter Study of the Gibson-Low Flux Rope Model using Multi-Viewpoint Observations

NASA Astrophysics Data System (ADS)

Verbeke, C.; Asvestari, E.; Scolini, C.; Pomoell, J.; Poedts, S.; Kilpua, E.

2017-12-01

Coronal Mass Ejections (CMEs) are one of the big influencers on the coronal and interplanetary dynamics. Understanding their origin and evolution from the Sun to the Earth is crucial in order to determine the impact on our Earth and society. One of the key parameters that determine the geo-effectiveness of the coronal mass ejection is its internal magnetic configuration. We present a detailed parameter study of the Gibson-Low flux rope model. We focus on changes in the input parameters and how these changes affect the characteristics of the CME at Earth. Recently, the Gibson-Low flux rope model has been implemented into the inner heliosphere model EUHFORIA, a magnetohydrodynamics forecasting model of large-scale dynamics from 0.1 AU up to 2 AU. Coronagraph observations can be used to constrain the kinematics and morphology of the flux rope. One of the key parameters, the magnetic field, is difficult to determine directly from observations. In this work, we approach the problem by conducting a parameter study in which flux ropes with varying magnetic configurations are simulated. We then use the obtained dataset to look for signatures in imaging observations and in-situ observations in order to find an empirical way of constraining the parameters related to the magnetic field of the flux rope. In particular, we focus on events observed by at least two spacecraft (STEREO + L1) in order to discuss the merits of using observations from multiple viewpoints in constraining the parameters.

Parameter Estimation in Atmospheric Data Sets

NASA Technical Reports Server (NTRS)

Wenig, Mark; Colarco, Peter

2004-01-01

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

Effect of Surface Tension Anisotropy and Welding Parameters on Initial Instability Dynamics During Solidification: A Phase-Field Study

NASA Astrophysics Data System (ADS)

Yu, Fengyi; Wei, Yanhong

2018-05-01

The effects of surface tension anisotropy and welding parameters on initial instability dynamics during gas tungsten arc welding of an Al-alloy are investigated by a quantitative phase-field model. The results show that the surface tension anisotropy and welding parameters affect the initial instability dynamics in different ways during welding. The surface tension anisotropy does not influence the solute diffusion process but does affect the stability of the solid/liquid interface during solidification. The welding parameters affect the initial instability dynamics by varying the growth rate and thermal gradient. The incubation time decreases, and the initial wavelength remains stable as the welding speed increases. When welding power increases, the incubation time increases and the initial wavelength slightly increases. Experiments were performed for the same set of welding parameters used in modeling, and the results of the experiments and simulations were in good agreement.

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.

Dynamic evolution of double Λ five-level atom interacting with one-mode electromagnetic cavity field

NASA Astrophysics Data System (ADS)

Abdel-Wahab, N. H.; Salah, Ahmed

2017-12-01

In this paper, the model describing a double Λ five-level atom interacting with a single mode electromagnetic cavity field in the (off) non-resonate case is studied. We obtained the constants of motion for the considered model. Also, the state vector of the wave function is given by using the Schrödinger equation when the atom is initially prepared in its excited state. The dynamical evolutions for the collapse revivals, the antibunching of photons and the field squeezing phenomena are investigated when the field is considered in a coherent state. The influence of detuning parameters on these phenomena is investigated. We noticed that the atom-field properties are influenced by changing the detuning parameters. The investigation of these aspects by numerical simulations is carried out using the Quantum Toolbox in Python (QuTip).

Equivalent source modeling of the core magnetic field using magsat data

NASA Technical Reports Server (NTRS)

Mayhew, M. A.; Estes, R. H.

1983-01-01

Experiments are carried out on fitting the main field using different numbers of equivalent sources arranged in equal area at fixed radii at and inside the core-mantle boundary. In fixing the radius for a given series of runs, the convergence problems that result from the extreme nonlinearity of the problem when dipole positions are allowed to vary are avoided. Results are presented from a comparison between this approach and the standard spherical harmonic approach for modeling the main field in terms of accuracy and computational efficiency. The modeling of the main field with an equivalent dipole representation is found to be comparable to the standard spherical harmonic approach in accuracy. The 32 deg dipole density (42 dipoles) corresponds approximately to an eleventh degree/order spherical harmonic expansion (143 parameters), whereas the 21 dipole density (92 dipoles) corresponds to approximately a seventeenth degree and order expansion (323 parameters). It is pointed out that fixing the dipole positions results in rapid convergence of the dipole solutions for single-epoch models.

Retrieval of effective cloud field parameters from radiometric data

NASA Astrophysics Data System (ADS)

Paulescu, Marius; Badescu, Viorel; Brabec, Marek

2017-06-01

Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

Interpretation of Source Parameters from Total Gradient of Gravity and Magnetic Anomalies Caused by Thin Dyke using Nonlinear Global Optimization Technique

NASA Astrophysics Data System (ADS)

Biswas, A.

2016-12-01

A proficient way to deal with appraisal model parameters from total gradient of gravity and magnetic data in light of Very Fast Simulated Annealing (VFSA) has been exhibited. This is the first run through of applying VFSA in deciphering total gradient of potential field information with another detailing estimation brought on because of detached causative sources installed in the subsurface. The model parameters translated here are the amplitude coefficient (k), accurate origin of causative source (x0) depth (z0) and the shape factor (q). The outcome of VFSA improvement demonstrates that it can exceptionally decide all the model parameters when shape variable is fixed. The model parameters assessed by the present strategy, for the most part the shape and depth of the covered structures was observed to be in astounding concurrence with the genuine parameters. The technique has likewise the capability of dodging very uproarious information focuses and enhances the understanding results. Investigation of Histogram and cross-plot examination likewise proposes the translation inside the assessed ambiguity. Inversion of noise-free and noisy synthetic data information for single structures and field information shows the viability of the methodology. The procedure has been carefully and adequately connected to genuine field cases (Leona Anomaly, Senegal for gravity and Pima copper deposit, USA for magnetic) with the nearness of mineral bodies. The present technique can be to a great degree material for mineral investigation or ore bodies of dyke-like structure rooted in the shallow and more deep subsurface. The calculation time for the entire procedure is short.

A validation of dynamic causal modelling for 7T fMRI.

PubMed

Tak, S; Noh, J; Cheong, C; Zeidman, P; Razi, A; Penny, W D; Friston, K J

2018-07-15

There is growing interest in ultra-high field magnetic resonance imaging (MRI) in cognitive and clinical neuroscience studies. However, the benefits offered by higher field strength have not been evaluated in terms of effective connectivity and dynamic causal modelling (DCM). In this study, we address the validity of DCM for 7T functional MRI data at two levels. First, we evaluate the predictive validity of DCM estimates based upon 3T and 7T in terms of reproducibility. Second, we assess improvements in the efficiency of DCM estimates at 7T, in terms of the entropy of the posterior distribution over model parameters (i.e., information gain). Using empirical data recorded during fist-closing movements with 3T and 7T fMRI, we found a high reproducibility of average connectivity and condition-specific changes in connectivity - as quantified by the intra-class correlation coefficient (ICC = 0.862 and 0.936, respectively). Furthermore, we found that the posterior entropy of 7T parameter estimates was substantially less than that of 3T parameter estimates; suggesting the 7T data are more informative - and furnish more efficient estimates. In the framework of DCM, we treated field-dependent parameters for the BOLD signal model as free parameters, to accommodate fMRI data at 3T and 7T. In addition, we made the resting blood volume fraction a free parameter, because different brain regions can differ in their vascularization. In this paper, we showed DCM enables one to infer changes in effective connectivity from 7T data reliably and efficiently. Copyright © 2018 Elsevier B.V. All rights reserved.

Invariant models in the inversion of gravity and magnetic fields and their derivatives

NASA Astrophysics Data System (ADS)

Ialongo, Simone; Fedi, Maurizio; Florio, Giovanni

2014-11-01

In potential field inversion problems we usually solve underdetermined systems and realistic solutions may be obtained by introducing a depth-weighting function in the objective function. The choice of the exponent of such power-law is crucial. It was suggested to determine it from the field-decay due to a single source-block; alternatively it has been defined as the structural index of the investigated source distribution. In both cases, when k-order derivatives of the potential field are considered, the depth-weighting exponent has to be increased by k with respect that of the potential field itself, in order to obtain consistent source model distributions. We show instead that invariant and realistic source-distribution models are obtained using the same depth-weighting exponent for the magnetic field and for its k-order derivatives. A similar behavior also occurs in the gravity case. In practice we found that the depth weighting-exponent is invariant for a given source-model and equal to that of the corresponding magnetic field, in the magnetic case, and of the 1st derivative of the gravity field, in the gravity case. In the case of the regularized inverse problem, with depth-weighting and general constraints, the mathematical demonstration of such invariance is difficult, because of its non-linearity, and of its variable form, due to the different constraints used. However, tests performed on a variety of synthetic cases seem to confirm the invariance of the depth-weighting exponent. A final consideration regards the role of the regularization parameter; we show that the regularization can severely affect the depth to the source because the estimated depth tends to increase proportionally with the size of the regularization parameter. Hence, some care is needed in handling the combined effect of the regularization parameter and depth weighting.

Self-Consistent Drift-Diffusion Transport in Thermoelectrics and Implications for Measuring the Scattering Parameter

NASA Astrophysics Data System (ADS)

Santhanam, Parthiban; Ram, Rajeev J.

2010-09-01

We present a microscopic model of the Seebeck effect based on a generalized drift-diffusion equation and use it to predict a simple relationship between the electric field within an operating thermoelectric and the scattering parameter. Our model replicates existing theoretical results and permits an intuitive spatial picture of the Seebeck effect. A similar formalism was independently developed by Cai and Mahan, but this work includes numerical results for high dopant concentrations where the thermoelectric power factor is maximized. Based on these results, we propose that measurement of the bulk electric field should constitute a measurement of the scattering parameter, the improvement of which could lead to greater thermoelectric efficiency.

Unparticle dark energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, D.-C.; Stojkovic, Dejan; Dutta, Sourish

2009-09-15

We examine a dark energy model where a scalar unparticle degree of freedom plays the role of quintessence. In particular, we study a model where the unparticle degree of freedom has a standard kinetic term and a simple mass potential, the evolution is slowly rolling and the field value is of the order of the unparticle energy scale ({lambda}{sub u}). We study how the evolution of w depends on the parameters B (a function of unparticle scaling dimension d{sub u}), the initial value of the field {phi}{sub i} (or equivalently, {lambda}{sub u}) and the present matter density {omega}{sub m0}. Wemore » use observational data from type Ia supernovae, baryon acoustic oscillations and the cosmic microwave background to constrain the model parameters and find that these models are not ruled out by the observational data. From a theoretical point of view, unparticle dark energy model is very attractive, since unparticles (being bound states of fundamental fermions) are protected from radiative corrections. Further, coupling of unparticles to the standard model fields can be arbitrarily suppressed by raising the fundamental energy scale M{sub F}, making the unparticle dark energy model free of most of the problems that plague conventional scalar field quintessence models.« less

Ray Tracing through the Edge Focusing of Rectangular Benders and an Improved Model for the Los Alamos Proton Storage Ring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolski, Jeffrey S.; Barlow, David B.; Macek, Robert J.

2011-01-01

Particle ray tracing through simulated 3D magnetic fields was executed to investigate the effective quadrupole strength of the edge focusing of the rectangular bending magnets in the Los Alamos Proton Storage Ring (PSR). The particle rays receive a kick in the edge field of the rectangular dipole. A focal length may be calculated from the particle tracking and related to the fringe field integral (FINT) model parameter. This tech note introduces the baseline lattice model of the PSR and motivates the need for an improvement in the baseline model's vertical tune prediction, which differs from measurement by .05. An improvedmore » model of the PSR is created by modifying the fringe field integral parameter to those suggested by the ray tracing investigation. This improved model is then verified against measurement at the nominal PSR operating set point and at set points far away from the nominal operating conditions. Lastly, Linear Optics from Closed Orbits (LOCO) is employed in an orbit response matrix method for model improvement to verify the quadrupole strengths of the improved model.« less

Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains.

PubMed

Dettmer, Jan; Dosso, Stan E

2012-10-01

This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.

Comparison between two scalar field models using rotation curves of spiral galaxies

NASA Astrophysics Data System (ADS)

Fernández-Hernández, Lizbeth M.; Rodríguez-Meza, Mario A.; Matos, Tonatiuh

2018-04-01

Scalar fields have been used as candidates for dark matter in the universe, from axions with masses ∼ 10-5eV until ultra-light scalar fields with masses ∼ Axions behave as cold dark matter while the ultra-light scalar fields galaxies are Bose-Einstein condensate drops. The ultra-light scalar fields are also called scalar field dark matter model. In this work we study rotation curves for low surface brightness spiral galaxies using two scalar field models: the Gross-Pitaevskii Bose-Einstein condensate in the Thomas-Fermi approximation and a scalar field solution of the Klein-Gordon equation. We also used the zero disk approximation galaxy model where photometric data is not considered, only the scalar field dark matter model contribution to rotation curve is taken into account. From the best-fitting analysis of the galaxy catalog we use, we found the range of values of the fitting parameters: the length scale and the central density. The worst fitting results (values of χ red2 much greater than 1, on the average) were for the Thomas-Fermi models, i.e., the scalar field dark matter is better than the Thomas- Fermi approximation model to fit the rotation curves of the analysed galaxies. To complete our analysis we compute from the fitting parameters the mass of the scalar field models and two astrophysical quantities of interest, the dynamical dark matter mass within 300 pc and the characteristic central surface density of the dark matter models. We found that the value of the central mass within 300 pc is in agreement with previous reported results, that this mass is ≈ 107 M ⊙/pc2, independent of the dark matter model. And, on the contrary, the value of the characteristic central surface density do depend on the dark matter model.

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Process Optimization of Dual-Laser Beam Welding of Advanced Al-Li Alloys Through Hot Cracking Susceptibility Modeling

NASA Astrophysics Data System (ADS)

Tian, Yingtao; Robson, Joseph D.; Riekehr, Stefan; Kashaev, Nikolai; Wang, Li; Lowe, Tristan; Karanika, Alexandra

2016-07-01

Laser welding of advanced Al-Li alloys has been developed to meet the increasing demand for light-weight and high-strength aerospace structures. However, welding of high-strength Al-Li alloys can be problematic due to the tendency for hot cracking. Finding suitable welding parameters and filler material for this combination currently requires extensive and costly trial and error experimentation. The present work describes a novel coupled model to predict hot crack susceptibility (HCS) in Al-Li welds. Such a model can be used to shortcut the weld development process. The coupled model combines finite element process simulation with a two-level HCS model. The finite element process model predicts thermal field data for the subsequent HCS hot cracking prediction. The model can be used to predict the influences of filler wire composition and welding parameters on HCS. The modeling results have been validated by comparing predictions with results from fully instrumented laser welds performed under a range of process parameters and analyzed using high-resolution X-ray tomography to identify weld defects. It is shown that the model is capable of accurately predicting the thermal field around the weld and the trend of HCS as a function of process parameters.

Two phase modeling of nanofluid flow in existence of melting heat transfer by means of HAM

NASA Astrophysics Data System (ADS)

Sheikholeslami, M.; Jafaryar, M.; Bateni, K.; Ganji, D. D.

2018-02-01

In this article, Buongiorno Model is applied for investigation of nanofluid flow over a stretching plate in existence of magnetic field. Radiation and Melting heat transfer are taken into account. Homotopy analysis method (HAM) is selected to solve ODEs which are obtained from similarity transformation. Roles of Brownian motion, thermophoretic parameter, Hartmann number, porosity parameter, Melting parameter and Eckert number are presented graphically. Results indicate that nanofluid velocity and concentration enhance with rise of melting parameter. Nusselt number reduces with increase of porosity and melting parameters.

Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for carbon cycle studies

USGS Publications Warehouse

He, Yujie; Zhuang, Qianlai; McGuire, David; Liu, Yaling; Chen, Min

2013-01-01

Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations in modeling regional carbon dynamics and explore the implications of those options. We calibrated the Terrestrial Ecosystem Model on a hierarchy of three vegetation classification levels for the Alaskan boreal forest: species level, plant-functional-type level (PFT level), and biome level, and we examined the differences in simulated carbon dynamics. Species-specific field-based estimates were directly used to parameterize the model for species-level simulations, while weighted averages based on species percent cover were used to generate estimates for PFT- and biome-level model parameterization. We found that calibrated key ecosystem process parameters differed substantially among species and overlapped for species that are categorized into different PFTs. Our analysis of parameter sets suggests that the PFT-level parameterizations primarily reflected the dominant species and that functional information of some species were lost from the PFT-level parameterizations. The biome-level parameterization was primarily representative of the needleleaf PFT and lost information on broadleaf species or PFT function. Our results indicate that PFT-level simulations may be potentially representative of the performance of species-level simulations while biome-level simulations may result in biased estimates. Improved theoretical and empirical justifications for grouping species into PFTs or biomes are needed to adequately represent the dynamics of ecosystem functioning and structure.

Forward Bay Cover Separation Modeling and Testing for the Orion Multi-Purpose Crew Vehicle

NASA Technical Reports Server (NTRS)

Ali, Yasmin; Radke, Tara; Chuhta, Jesse; Hughes, Michael

2014-01-01

Spacecraft multi-body separation events during atmospheric descent require complex testing and analysis to validate the flight separation dynamics model and to verify no recontact. NASA Orion Multi-Purpose Crew Vehicle (MPCV) teams examined key model parameters and risk areas to develop a robust but affordable test campaign in order to validate and verify the Forward Bay Cover (FBC) separation event for Exploration Flight Test-1 (EFT-1). The FBC jettison simulation model is highly complex, consisting of dozens of parameters varied simultaneously, with numerous multi-parameter interactions (coupling and feedback) among the various model elements, and encompassing distinct near-field, mid-field, and far-field regimes. The test campaign was composed of component-level testing (for example gas-piston thrusters and parachute mortars), ground FBC jettison tests, and FBC jettison air-drop tests that were accomplished by a highly multi-disciplinary team. Three ground jettison tests isolated the testing of mechanisms and structures to anchor the simulation models excluding aerodynamic effects. Subsequently, two air-drop tests added aerodynamic and parachute parameters, and served as integrated system demonstrations, which had been preliminarily explored during the Orion Pad Abort-1 (PA-1) flight test in May 2010. Both ground and drop tests provided extensive data to validate analytical models and to verify the FBC jettison event for EFT-1, but more testing is required to support human certification, for which NASA and Lockheed Martin are applying knowledge from Apollo and EFT-1 testing and modeling to develop a robust but affordable human spacecraft capability.

Residential magnetic fields predicted from wiring configurations: I. Exposure model.

PubMed

Bowman, J D; Thomas, D C; Jiang, L; Jiang, F; Peters, J M

1999-10-01

A physically based model for residential magnetic fields from electric transmission and distribution wiring was developed to reanalyze the Los Angeles study of childhood leukemia by London et al. For this exposure model, magnetic field measurements were fitted to a function of wire configuration attributes that was derived from a multipole expansion of the Law of Biot and Savart. The model parameters were determined by nonlinear regression techniques, using wiring data, distances, and the geometric mean of the ELF magnetic field magnitude from 24-h bedroom measurements taken at 288 homes during the epidemiologic study. The best fit to the measurement data was obtained with separate models for the two major utilities serving Los Angeles County. This model's predictions produced a correlation of 0.40 with the measured fields, an improvement on the 0.27 correlation obtained with the Wertheimer-Leeper (WL) wire code. For the leukemia risk analysis in a companion paper, the regression model predicts exposures to the 24-h geometric mean of the ELF magnetic fields in Los Angeles homes where only wiring data and distances have been obtained. Since these input parameters for the exposure model usually do not change for many years, the predicted magnetic fields will be stable over long time periods, just like the WL code. If the geometric mean is not the exposure metric associated with cancer, this regression technique could be used to estimate long-term exposures to temporal variability metrics and other characteristics of the ELF magnetic field which may be cancer risk factors.

Cosmological reconstruction and Om diagnostic analysis of Einstein-Aether theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasqua, Antonio; Chattopadhyay, Surajit; Momeni, Davood

In this paper, we analyze the cosmological models in Einstein-Aether gravity, which is a modified theory of gravity in which a time-like vector field breaks the Lorentz symmetry. We use this formalism to analyse different cosmological models with different behavior of the scale factor. In this analysis, we use a certain functional dependence of the Dark Energy (DE) on the Hubble parameter H . It will be demonstrated that the Aether vector field has a non-trivial effect on these cosmological models. We also perform the Om diagnostic in Einstein-Aether gravity and we fit the parameters of the cosmological models usingmore » recent observational data.« less

Model parameter uncertainty analysis for an annual field-scale P loss model

NASA Astrophysics Data System (ADS)

Bolster, Carl H.; Vadas, Peter A.; Boykin, Debbie

2016-08-01

Phosphorous (P) fate and transport models are important tools for developing and evaluating conservation practices aimed at reducing P losses from agricultural fields. Because all models are simplifications of complex systems, there will exist an inherent amount of uncertainty associated with their predictions. It is therefore important that efforts be directed at identifying, quantifying, and communicating the different sources of model uncertainties. In this study, we conducted an uncertainty analysis with the Annual P Loss Estimator (APLE) model. Our analysis included calculating parameter uncertainties and confidence and prediction intervals for five internal regression equations in APLE. We also estimated uncertainties of the model input variables based on values reported in the literature. We then predicted P loss for a suite of fields under different management and climatic conditions while accounting for uncertainties in the model parameters and inputs and compared the relative contributions of these two sources of uncertainty to the overall uncertainty associated with predictions of P loss. Both the overall magnitude of the prediction uncertainties and the relative contributions of the two sources of uncertainty varied depending on management practices and field characteristics. This was due to differences in the number of model input variables and the uncertainties in the regression equations associated with each P loss pathway. Inspection of the uncertainties in the five regression equations brought attention to a previously unrecognized limitation with the equation used to partition surface-applied fertilizer P between leaching and runoff losses. As a result, an alternate equation was identified that provided similar predictions with much less uncertainty. Our results demonstrate how a thorough uncertainty and model residual analysis can be used to identify limitations with a model. Such insight can then be used to guide future data collection and model development and evaluation efforts.

Controlling the transmitted information of a multi-photon interacting with a single-Cooper pair box

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kadry, Heba, E-mail: hkadry1@yahoo.com; Abdel-Aty, Abdel-Haleem, E-mail: hkadry1@yahoo.com; Zakaria, Nordin, E-mail: hkadry1@yahoo.com

2014-10-24

We study a model of a multi-photon interaction of a single Cooper pair box with a cavity field. The exchange of the information using this system is studied. We quantify the fidelity of the transmitted information. The effect of the system parameters (detuning parameter, field photons, state density and mean photon number) in the fidelity of the transmitted information is investigated. We found that the fidelity of the transmitted information can be controlled using the system parameters.

Magnetic and velocity fields in a dynamo operating at extremely small Ekman and magnetic Prandtl numbers

NASA Astrophysics Data System (ADS)

Šimkanin, Ján; Kyselica, Juraj

2017-12-01

Numerical simulations of the geodynamo are becoming more realistic because of advances in computer technology. Here, the geodynamo model is investigated numerically at the extremely low Ekman and magnetic Prandtl numbers using the PARODY dynamo code. These parameters are more realistic than those used in previous numerical studies of the geodynamo. Our model is based on the Boussinesq approximation and the temperature gradient between upper and lower boundaries is a source of convection. This study attempts to answer the question how realistic the geodynamo models are. Numerical results show that our dynamo belongs to the strong-field dynamos. The generated magnetic field is dipolar and large-scale while convection is small-scale and sheet-like flows (plumes) are preferred to a columnar convection. Scales of magnetic and velocity fields are separated, which enables hydromagnetic dynamos to maintain the magnetic field at the low magnetic Prandtl numbers. The inner core rotation rate is lower than that in previous geodynamo models. On the other hand, dimensional magnitudes of velocity and magnetic fields and those of the magnetic and viscous dissipation are larger than those expected in the Earth's core due to our parameter range chosen.

Applying "domino" model to study dipolar geomagnetic field reversals and secular variation

NASA Astrophysics Data System (ADS)

Peqini, Klaudio; Duka, Bejo

2014-05-01

Aiming to understand the physical processes underneath the reversals events of geomagnetic field, different numerical models have been conceived. We considered the so named "domino" model, an Ising-Heisenberg model of interacting magnetic spins aligned along a ring [Mazaud and Laj, EPSL, 1989; Mori et al., arXiv:1110.5062v2, 2012]. We will present here some results which are slightly different from the already published results, and will give our interpretation on the differences. Following the empirical studies of the long series of the axial magnetic moment (dipolar moment or "magnetization") generated by the model varying all model parameters, we defined the set of parameters that supply the longest mean time between reversals. Using this set of parameters, a short time series (about 10,000 years) of axial magnetic moment was generated. After de-noising the fluctuation of this time series, we compared it with the series of dipolar magnetic moment values supplied by CALS10K.1b model for the last 10000 years. We found similar behavior of the both series, even if the "domino" model could not supply a full explanation of the geomagnetic field SV. In a similar way we will compare a 14000 years long series with the dipolar magnetic moment obtained by the model SHA.DIF.14k [Pavón-Carrasco et al., EPSL, 2014].

Influence of Weak External Magnetic Field on Amorphous and Nanocrystalline Fe-based Alloys

NASA Astrophysics Data System (ADS)

Degmová, J.; Sitek, J.

2010-07-01

Nanoperm, Hitperm and Finamet amorphous and nanocrystalline alloys were measured by Mössbauer spectrometry in a weak external magnetic field of 0.5 T. It was shown that the most sensitive parameters of Mössbauer spectra are the intensities of the 2nd and the 5th lines. Rather small changes were observed also in the case of internal magnetic field values. The spectrum of nanocrystalline Nanoperm showed the increase in A23 parameter (ratio of line intensities) from 2.4 to 3.7 and decrease of internal magnetic field from 20 to 19 T for amorphous subspectrum under the influence of magnetic field. Spectrum of nanocrystalline Finemet shown decrease in A23 parameter from 3.5 to 2.6 almost without a change in the internal magnetic field value. In the case of amorphous Nanoperm and Finemet samples, the changes are almost negligible. Hitperm alloy showed the highest sensitivity to the weak magnetic field, when the A23 parameter increased from 0.4 to 2.5 in the external magnetic fields. The A23 parameter of crystalline subspectrum increased from 2.7 to 3.8 and the value of internal magnetic field corresponding to amorphous subspectrum increased from 22 to 24 T. The behavior of nanocrystalline alloys under weak external magnetic field was analyzed within the three-level relaxation model of magnetic dynamics in an assembly of single-domain particles.

Consistent parameter fixing in the quark-meson model with vacuum fluctuations

NASA Astrophysics Data System (ADS)

Carignano, Stefano; Buballa, Michael; Elkamhawy, Wael

2016-08-01

We revisit the renormalization prescription for the quark-meson model in an extended mean-field approximation, where vacuum quark fluctuations are included. At a given cutoff scale the model parameters are fixed by fitting vacuum quantities, typically including the sigma-meson mass mσ and the pion decay constant fπ. In most publications the latter is identified with the expectation value of the sigma field, while for mσ the curvature mass is taken. When quark loops are included, this prescription is however inconsistent, and the correct identification involves the renormalized pion decay constant and the sigma pole mass. In the present article we investigate the influence of the parameter-fixing scheme on the phase structure of the model at finite temperature and chemical potential. Despite large differences between the model parameters in the two schemes, we find that in homogeneous matter the effect on the phase diagram is relatively small. For inhomogeneous phases, on the other hand, the choice of the proper renormalization prescription is crucial. In particular, we show that if renormalization effects on the pion decay constant are not considered, the model does not even present a well-defined renormalized limit when the cutoff is sent to infinity.

Modelling the water balance of irrigated fields in tropical floodplain soils using Hydrus-1D

NASA Astrophysics Data System (ADS)

Beyene, Abebech; Frankl, Amaury; Verhoest, Niko E. C.; Tilahun, Seifu; Alamirew, Tena; Adgo, Enyew; Nyssen, Jan

2017-04-01

Accurate estimation of evaporation, transpiration and deep percolation is crucial in irrigated agriculture and the sustainable management of water resources. Here, the Hydrus-1D process-based numerical model was used to estimate the actual transpiration, soil evaporation and deep percolation from irrigated fields of floodplain soils. Field experiments were conducted from Dec 2015 to May 2016 in a small irrigation scheme (50 ha) called 'Shina' located in the Lake Tana floodplains of Ethiopia. Six experimental plots (three for onion and three for maize) were selected along a topographic transect to account for soil and groundwater variability. Irrigation amount (400 to 550 mm during the growing period) was measured using V-notches installed at each plot boundary and daily groundwater levels were measured manually from piezometers. There was no surface runoff observed in the growing period and rainfall was measured using a manual rain gauge. All daily weather data required for the evapotranspiration calculation using Pen Man Monteith equation were collected from a nearby metrological station. The soil profiles were described for each field to include the vertical soil heterogeneity in the soil water balance simulations. The soil texture, organic matter, bulk density, field capacity, wilting point and saturated moisture content were measured for all the soil horizons. Soil moisture monitoring at 30 and 60 cm depths was performed. The soil hydraulic parameters for each horizon was estimated using KNN pedotransfer functions for tropical soils and were effectively fitted using the RETC program (R2= 0.98±0.011) for initial prediction. A local sensitivity analysis was performed to select and optimize the most important hydraulic parameters for soil water flow in the unsaturated zone. The most sensitive parameters were saturated hydraulic conductivity (Ks), saturated moisture content (θs) and pore size distribution (n). Inverse modelling using Hydrus-1D further optimized these parameters (R2 =0.74±0.13). Using the optimized hydraulic parameters, the soil water dynamics were simulated using Hydrus-1D. The atmospheric boundary conditions with surface runoff was used as upper boundary condition with measured rainfall and irrigation input data. The variable pressure head was selected as lower boundary conditions with daily records of groundwater level as time-variable input data. The Hydrus-1D model was successfully applied and calibrated in the study area. The average seasonal actual transpiration values are 310±13 mm for onion and 429±24.7 mm for maize fields. The seasonal average soil evaporation ranges from 12±2.05 mm for maize fields to 38±2.85 mm for onion fields. The seasonal deep percolation from irrigation appeared to be 12 to 40% of applied irrigation. The Hydrus-1D model was able to simulate the temporal and the spatial variations of soil water dynamics in the unsaturated zone of tropical floodplain soils. Key words: floodplains, hydraulic parameters, parameter optimization, small-scale irrigation

Vacuum Microelectronic Field Emission Array Devices for Microwave Amplification.

NASA Astrophysics Data System (ADS)

Mancusi, Joseph Edward

This dissertation presents the design, analysis, and measurement of vacuum microelectronic devices which use field emission to extract an electron current from arrays of silicon cones. The arrays of regularly-spaced silicon cones, the field emission cathodes or emitters, are fabricated with an integrated gate electrode which controls the electric field at the tip of the cone, and thus the electron current. An anode or collector electrode is placed above the array to collect the emission current. These arrays, which are fabricated in a standard silicon processing facility, are developed for use as high power microwave amplifiers. Field emission has been studied extensively since it was first characterized in 1928, however due to the large electric fields required practical field emission devices are difficult to make. With the development of the semiconductor industry came the development of fabrication equipment and techniques which allow for the manufacture of the precision micron-scale structures necessary for practical field emission devices. The active region of a field emission device is a vacuum, therefore the electron travel is ballistic. This analysis of field emission devices includes electric field and electron emission modeling, development of a device equivalent circuit, analysis of the parameters in the equivalent circuit, and device testing. Variations in device structure are taken into account using a statistical model based upon device measurements. Measurements of silicon field emitter arrays at DC and RF are presented and analyzed. In this dissertation, the equivalent circuit is developed from the analysis of the device structure. The circuit parameters are calculated from geometrical considerations and material properties, or are determined from device measurements. It is necessary to include the emitter resistance in the equivalent circuit model since relatively high resistivity silicon wafers are used. As is demonstrated, the circuit model accurately predicts the magnitude of the emission current at a number of typical bias current levels when the device is operating at frequencies within the range of 10 MHz to 1 GHz. At low frequencies and at high frequencies within this range, certain parameters are negligible, and simplifications may be made in the equivalent circuit model.

Calibration of a turbidity meter for making estimates of total suspended solids concentrations and beam attenuation coefficients in field experiments

NASA Technical Reports Server (NTRS)

Usry, J. W.; Whitlock, C. H.

1981-01-01

Management of water resources such as a reservoir requires using analytical models which describe such parameters as the suspended sediment field. To select or develop an appropriate model requires making many measurements to describe the distribution of this parameter in the water column. One potential method for making those measurements expeditiously is to measure light transmission or turbidity and relate that parameter to total suspended solids concentrations. An instrument which may be used for this purpose was calibrated by generating curves of transmission measurements plotted against measured values of total suspended solids concentrations and beam attenuation coefficients. Results of these experiments indicate that field measurements made with this instrument using curves generated in this study should correlate with total suspended solids concentrations and beam attenuation coefficients in the water column within 20 percent.

Magnetic field effect on the structural properties of a peptide model: Molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Housaindokht, Mohammad Reza; Moosavi, Fatemeh

2018-06-01

The effect of magnetization on the properties of a system containing a peptide model is studied by molecular dynamics simulation at a range of 298-318 K. Two mole fractions of 0.001 and 0.002 of peptide were simulated and the variation of hydrogen bond number, orientational ordering parameter, gyration radius, mean square displacement, as well as radial distribution function, were under consideration. The results show that applying magnetic field will increase the number of hydrogen bonds between water molecules by clustering them and decreases the interaction of water and peptide. This reduction may cause more available free space and enhance the movement of the peptide. As a result, the diffusion coefficient of the peptide becomes greater and its conformation changes. Orientational ordering parameter besides radius of gyration demonstrates that peptide is expanded by static magnetic field and its orientational ordering parameter is affected.

Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

PubMed Central

Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

2014-01-01

A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline. PMID:25025089

Coupling of three-dimensional field and human thermoregulatory models in a crowded enclosure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xue, H.; Kang, Z.J.; Bong, T.Y.

1999-11-12

Health, comfort, and energy conservation are important factors to consider in the design of a building and its HVAC systems. Advanced tools are required to evaluate parameters regarding airflow, temperature, and humidity ratio in buildings, with the end results being better indoor air quality and thermal environment as well as increased confidence in the performance of buildings. A numerical model coupling the three-dimensional field and human thermoregulatory models is proposed and developed. A high-Re {kappa}-{epsilon} turbulence model is used for the field simulation. A modified 25-mode model of human thermoregulation is adopted to predict human thermal response in physiological parameters,more » such as body temperature and body heat loss. Distributions of air velocity, temperature, and moisture content are demonstrated in a crowded enclosure with mechanical ventilation under two ventilation rates. The results are analyzed and discussed. The coupling model is useful in assisting and verifying ventilation and air-conditioning system designs.« less

Estimating turbulent electrovortex flow parameters hear the dynamo cycle bifurcation point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zimin, V.D.; Kolpakov, N.Yu.; Khripchenko, S.Yu.

1988-07-01

Models for estimating turbulent electrovortex flow parameters, derived in earlier studies, were delineated and extended in this paper to express those parameters near the dynamo cycle bifurcation point in a spherical cavity. Toroidal and poloidal fields rising from the induction currents within the liquid metal and their electrovortex interactions were calculated. Toroidal field strengthening by the poloidal electrovortex flow, the first part of the dynamo loop, was determined by the viscous dissipation in the liquid metal. The second part of the loop, in which the toroidal field localized in the liquid metal is converted to a poloidal field and emergesmore » from the sphere, was also established. The dissipative effects near the critical magnetic Reynolds number were estimated.« less

Precision constraints on the top-quark effective field theory at future lepton colliders

NASA Astrophysics Data System (ADS)

Durieux, G.

We examine the constraints that future lepton colliders would impose on the effective field theory describing modifications of top-quark interactions beyond the standard model, through measurements of the $e^+e^-\\to bW^+\\:\\bar bW^-$ process. Statistically optimal observables are exploited to constrain simultaneously and efficiently all relevant operators. Their constraining power is sufficient for quadratic effective-field-theory contributions to have negligible impact on limits which are therefore basis independent. This is contrasted with the measurements of cross sections and forward-backward asymmetries. An overall measure of constraints strength, the global determinant parameter, is used to determine which run parameters impose the strongest restriction on the multidimensional effective-field-theory parameter space.

Dynamics of entanglement of a three-level atom in motion interacting with two coupled modes including parametric down conversion

NASA Astrophysics Data System (ADS)

Faghihi, M. J.; Tavassoly, M. K.; Hatami, M.

In this paper, a model by which we study the interaction between a motional three-level atom and two-mode field injected simultaneously in a bichromatic cavity is considered; the three-level atom is assumed to be in a Λ-type configuration. As a result, the atom-field and the field-field interaction (parametric down conversion) will be appeared. It is shown that, by applying a canonical transformation, the introduced model can be reduced to a well-known form of the generalized Jaynes-Cummings model. Under particular initial conditions, which may be prepared for the atom and the field, the time evolution of state vector of the entire system is analytically evaluated. Then, the dynamics of atom by considering ‘atomic population inversion’ and two different measures of entanglement, i.e., ‘von Neumann entropy’ and ‘idempotency defect’ is discussed, in detail. It is deduced from the numerical results that, the duration and the maximum amount of the considered physical quantities can be suitably tuned by selecting the proper field-mode structure parameter p and the detuning parameters.

A method for establishing constraints on galactic magnetic field models using ultra high energy cosmic rays and results from the data of the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Sutherland, Michael Stephen

2010-12-01

The Galactic magnetic field is poorly understood. Essentially the only reliable measurements of its properties are the local orientation and field strength. Its behavior at galactic scales is unknown. Historically, magnetic field measurements have been performed using radio astronomy techniques which are sensitive to certain regions of the Galaxy and rely upon models of the distribution of gas and dust within the disk. However, the deflection of trajectories of ultra high energy cosmic rays arriving from extragalactic sources depends only on the properties of the magnetic field. In this work, a method is developed for determining acceptable global models of the Galactic magnetic field by backtracking cosmic rays through the field model. This method constrains the parameter space of magnetic field models by comparing a test statistic between backtracked cosmic rays and isotropic expectations for assumed cosmic ray source and composition hypotheses. Constraints on Galactic magnetic field models are established using data from the southern site of the Pierre Auger Observatory under various source distribution and cosmic ray composition hypotheses. Field models possessing structure similar to the stellar spiral arms are found to be inconsistent with hypotheses of an iron cosmic ray composition and sources selected from catalogs tracing the local matter distribution in the universe. These field models are consistent with hypothesis combinations of proton composition and sources tracing the local matter distribution. In particular, strong constraints are found on the parameter space of bisymmetric magnetic field models scanned under hypotheses of proton composition and sources selected from the 2MRS-VS, Swift 39-month, and VCV catalogs. Assuming that the Galactic magnetic field is well-described by a bisymmetric model under these hypotheses, the magnetic field strength near the Sun is less than 3-4 muG and magnetic pitch angle is less than -8°. These results comprise the first measurements of the Galactic magnetic field using ultra-high energy cosmic rays and supplement existing radio astronomical measurements of the Galactic magnetic field.

Understanding controls of hydrologic processes across two monolithological catchments using model-data integration

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Li, L.

2016-12-01

Field measurements are important to understand the fluxes of water, energy, sediment, and solute in the Critical Zone however are expensive in time, money, and labor. This study aims to assess the model predictability of hydrological processes in a watershed using information from another intensively-measured watershed. We compare two watersheds of different lithology using national datasets, field measurements, and physics-based model, Flux-PIHM. We focus on two monolithological, forested watersheds under the same climate in the Shale Hills Susquehanna CZO in central Pennsylvania: the Shale-based Shale Hills (SSH, 0.08 km2) and the sandstone-based Garner Run (GR, 1.34 km2). We firstly tested the transferability of calibration coefficients from SSH to GR. We found that without any calibration the model can successfully predict seasonal average soil moisture and discharge which shows the advantage of a physics-based model, however, cannot precisely capture some peaks or the runoff in summer. The model reproduces the GR field data better after calibrating the soil hydrology parameters. In particular, the percentage of sand turns out to be a critical parameter in reproducing data. With sandstone being the dominant lithology, GR has much higher sand percentage than SSH (48.02% vs. 29.01%), leading to higher hydraulic conductivity, lower overall water storage capacity, and in general lower soil moisture. This is consistent with area averaged soil moisture observations using the cosmic-ray soil moisture observing system (COSMOS) at the two sites. This work indicates that some parameters, including evapotranspiration parameters, are transferrable due to similar climatic and land cover conditions. However, the key parameters that control soil moisture, including the sand percentage, need to be recalibrated, reflecting the key role of soil hydrological properties.

Nonlinear multidimensional cosmological models with form fields: Stabilization of extra dimensions and the cosmological constant problem

NASA Astrophysics Data System (ADS)

Günther, U.; Moniz, P.; Zhuk, A.

2003-08-01

We consider multidimensional gravitational models with a nonlinear scalar curvature term and form fields in the action functional. In our scenario it is assumed that the higher dimensional spacetime undergoes a spontaneous compactification to a warped product manifold. Particular attention is paid to models with quadratic scalar curvature terms and a Freund-Rubin-like ansatz for solitonic form fields. It is shown that for certain parameter ranges the extra dimensions are stabilized. In particular, stabilization is possible for any sign of the internal space curvature, the bulk cosmological constant, and of the effective four-dimensional cosmological constant. Moreover, the effective cosmological constant can satisfy the observable limit on the dark energy density. Finally, we discuss the restrictions on the parameters of the considered nonlinear models and how they follow from the connection between the D-dimensional and the four-dimensional fundamental mass scales.

Using GRACE and climate model simulations to predict mass loss of Alaskan glaciers through 2100

DOE PAGES

Wahr, John; Burgess, Evan; Swenson, Sean

2016-05-30

Glaciers in Alaska are currently losing mass at a rate of ~–50 Gt a –1, one of the largest ice loss rates of any regional collection of mountain glaciers on Earth. Existing projections of Alaska's future sea-level contributions tend to be divergent and are not tied directly to regional observations. Here we develop a simple, regional observation-based projection of Alaska's future sea-level contribution. We compute a time series of recent Alaska glacier mass variability using monthly GRACE gravity fields from August 2002 through December 2014. We also construct a three-parameter model of Alaska glacier mass variability based on monthly ERA-Interimmore » snowfall and temperature fields. When these three model parameters are fitted to the GRACE time series, the model explains 94% of the variance of the GRACE data. Using these parameter values, we then apply the model to simulated fields of monthly temperature and snowfall from the Community Earth System Model, to obtain predictions of mass variations through 2100. Here, we conclude that mass loss rates may increase between –80 and –110 Gt a –1by 2100, with a total sea-level rise contribution of 19 ± 4 mm during the 21st century.« less

Delineation and Prediction Uncertainty of Areas Contributing Recharge to Selected Well Fields in Wetland and Coastal Settings, Southern Rhode Island

USGS Publications Warehouse

Friesz, Paul J.

2010-01-01

Areas contributing recharge to four well fields in two study sites in southern Rhode Island were delineated on the basis of steady-state groundwater-flow models representing average hydrologic conditions. The wells are screened in sand and gravel deposits in wetland and coastal settings. The groundwater-flow models were calibrated by inverse modeling using nonlinear regression. Summary statistics from nonlinear regression were used to evaluate the uncertainty associated with the predicted areas contributing recharge to the well fields. In South Kingstown, two United Water Rhode Island well fields are in Mink Brook watershed and near Worden Pond and extensive wetlands. Wetland deposits of peat near the well fields generally range in thickness from 5 to 8 feet. Analysis of water-level drawdowns in a piezometer screened beneath the peat during a 20-day pumping period indicated vertical leakage and a vertical hydraulic conductivity for the peat of roughly 0.01 ft/d. The simulated area contributing recharge for average withdrawals of 2,138 gallons per minute during 2003-07 extended to groundwater divides in mostly till and morainal deposits, and it encompassed 2.30 square miles. Most of a sand and gravel mining operation between the well fields was in the simulated contributing area. For the maximum pumping capacity (5,100 gallons per minute), the simulated area contributing recharge expanded to 5.54 square miles. The well fields intercepted most of the precipitation recharge in Mink Brook watershed and in an adjacent small watershed, and simulated streams ceased to flow. The simulated contributing area to the well fields included an area beneath Worden Pond and a remote, isolated area in upland till on the opposite side of Worden Pond from the well fields. About 12 percent of the pumped water was derived from Worden Pond. In Charlestown, the Central Beach Fire District and the East Beach Water Association well fields are on a small (0.85 square mile) peninsula in a coastal setting. The wells are screened in a coarse-grained, ice-proximal part of a morphosequence with saturated thicknesses generally less than 30 feet on the peninsula. The simulated area contributing recharge for the average withdrawal (16 gallons per minute) during 2003-07 was 0.018 square mile. The contributing area extended southwestward from the well fields to a simulated groundwater mound; it underlay part of a small nearby wetland, and it included isolated areas on the side of the wetland opposite the well fields. For the maximum pumping rate (230 gallons per minute), the simulated area contributing recharge (0.26 square mile) expanded in all directions; it included a till area on the peninsula, and it underlay part of a nearby pond. Because the well fields are screened in a thin aquifer, simulated groundwater traveltimes from recharge locations to the discharging wells were short: 94 percent of the traveltimes were 10 years or less, and the median traveltime was 1.3 years. Model-prediction uncertainty was evaluated using a Monte Carlo analysis; the parameter variance-covariance matrix from nonlinear regression was used to create parameter sets for the analysis. Important parameters for model prediction that could not be estimated by nonlinear regression were incorporated into the variance-covariance matrix. For the South Kingstown study site, observations provided enough information to constrain the uncertainty of these parameters within realistic ranges, but for the Charlestown study site, prior information on parameters was required. Thus, the uncertainty analysis for the South Kingstown study site was an outcome of calibrating the model to available observations, but the Charlestown study site was also dependent on information provided by the modeler. A water budget and model-fit statistical criteria were used to assess parameter sets so that prediction uncertainty was not overestimated. For the scenarios using maximum pumping rates at both study

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Equivalence between the Lovelock-Cartan action and a constrained gauge theory

NASA Astrophysics Data System (ADS)

Junqueira, O. C.; Pereira, A. D.; Sadovski, G.; Santos, T. R. S.; Sobreiro, R. F.; Tomaz, A. A.

2017-04-01

We show that the four-dimensional Lovelock-Cartan action can be derived from a massless gauge theory for the SO(1, 3) group with an additional BRST trivial part. The model is originally composed of a topological sector and a BRST exact piece and has no explicit dependence on the metric, the vierbein or a mass parameter. The vierbein is introduced together with a mass parameter through some BRST trivial constraints. The effect of the constraints is to identify the vierbein with some of the additional fields, transforming the original action into the Lovelock-Cartan one. In this scenario, the mass parameter is identified with Newton's constant, while the gauge field is identified with the spin connection. The symmetries of the model are also explored. Moreover, the extension of the model to a quantum version is qualitatively discussed.

A new exact anisotropic solution of embedding class one

NASA Astrophysics Data System (ADS)

Maurya, S. K.; Gupta, Y. K.; T. T., Smitha; Rahaman, Farook

2016-07-01

We have presented a new anisotropic solution of Einstein's field equations for compact-star models. Einstein's field equations are solved by using the class-one condition (S.N. Pandey, S.P. Sharma, Gen. Relativ. Gravit. 14, 113 (1982)). We constructed the expression for the anisotropy factor ( Δ by using the pressure anisotropy condition and thereafter we obtained the physical parameters like energy density, radial and transverse pressure. These models parameters are well-behaved inside the star and satisfy all the required physical conditions. Also we observed the very interesting result that all physical parameters depend upon the anisotropy factor ( Δ. The mass and radius of the present compact-star models are quite compatible with the observational astrophysical compact stellar objects like Her X-1, RXJ 1856-37, SAX J1808.4-3658(SS1), SAX J1808.4-3658(SS2).

Interaction of Low Frequency External Electric Fields and Pancreatic β-Cell: A Mathematical Modeling Approach to Identify the Influence of Excitation Parameters.

PubMed

Farashi, Sajjad; Sasanpour, Pezhman; Rafii-Tabar, Hashem

2018-05-24

Purpose-Although the effect of electromagnetic fields on biological systems has attracted attraction in recent years, there has not been any conclusive result concerning the effects of interaction and the underlying mechanisms involved. Besides the complexity of biological systems, the parameters of the applied electromagnetic field have not been estimated in most of the experiments. Material and Method-In this study, we have used computational approach in order to find the excitation parameters of an external electric field which produces sensible effects in the function of insulin secretory machinery, whose failure triggers the diabetes disease. A mathematical model of the human β-cell has been used and the effects of external electric fields with different amplitudes, frequencies and wave shapes have been studied. Results-The results from our simulations show that the external electric field can influence the membrane electrical activity and perhaps the insulin secretion when its amplitude exceeds a threshold value. Furthermore, our simulations reveal that different waveforms have distinct effects on the β-cell membrane electrical activity and the characteristic features of the excitation like frequency would change the interaction mechanism. Conclusion-The results could help the researchers to investigate the possible role of the environmental electromagnetic fields on the promotion of diabetes disease.

Solutions on a brane in a bulk spacetime with Kalb–Ramond field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakraborty, Sumanta, E-mail: sumanta@iucaa.in; SenGupta, Soumitra, E-mail: tpssg@iacs.res.in

Effective gravitational field equations on a brane have been derived, when the bulk spacetime is endowed with the second rank antisymmetric Kalb–Ramond field. Since both the graviton and the Kalb–Ramond field are closed string excitations, they can propagate in the bulk. After deriving the effective gravitational field equations on the brane, we solve them for a static spherically symmetric solution. It turns out that the solution so obtained represents a black hole or naked singularity depending on the parameter space of the model. The stability of this model is also discussed. Cosmological solutions to the gravitational field equations have beenmore » obtained, where the Kalb–Ramond field is found to behave as normal pressure free matter. For certain specific choices of the parameters in the cosmological solution, the solution exhibits a transition in the behaviour of the scale factor and hence a transition in the expansion history of the universe. The possibility of accelerated expansion of the universe in this scenario is also discussed.« less

Evaluation of Two Soil Water Redistribution Models (Finite Difference and Hourly Cascade Approach) Through The Comparison of Continuous field Sensor-Based Measurements

NASA Astrophysics Data System (ADS)

Ferreyra, R.; Stockle, C. O.; Huggins, D. R.

2014-12-01

Soil water storage and dynamics are of critical importance for a variety of processes in terrestrial ecosystems, including agriculture. Many of those systems are under significant pressure in terms of water availability and use. Therefore, assessing alternative scenarios through hydrological models is an increasingly valuable exercise. Soil water holding capacity is defined by the concepts of soil field capacity and plant available water, which are directly related to soil physical properties. Both concepts define the energy status of water in the root system and closely interact with plant physiological processes. Furthermore, these concepts play a key role in the environmental transport of nutrients and pollutants. Soil physical parameters (e.g. saturated hydraulic conductivity, total porosity and water release curve) are required as input for field-scale soil water redistribution models. These parameters are normally not easy to measure or monitor, and estimation through pedotransfer functions is often inadequate. Our objectives are to improve field-scale hydrological modeling by: (1) assessing new undisturbed methodologies for determining important soil physical parameters necessary for model inputs; and (2) evaluating model outputs, making a detailed specification of soil parameters and the particular boundary condition that are driving water movement under two contrasting environments. Soil physical properties (saturated hydraulic conductivity and determination of water release curves) were quantified using undisturbed laboratory methodologies for two different soil textural classes (silt loam and sandy loam) and used to evaluate two soil water redistribution models (finite difference solution and hourly cascade approach). We will report on model corroboration results performed using in situ, continuous, field measurements with soil water content capacitance probes and digital tensiometers. Here, natural drainage and water redistribution were monitored following a controlled water application where the study areas were isolated from other water inputs and outputs. We will also report on the assessment of two soil water sensors (Decagon Devices 5TM capacitance probe and UMS T4 tensiometers) for the two soil textural classes in terms of consistency and replicability.

Spatiotemporal mapping of scalp potentials.

PubMed

Fender, D H; Santoro, T P

1977-11-01

Computerized analysis and display techniques are applied to the problem of identifying the origins of visually evoked scalped potentials (VESP's). A new stimulus for VESP work, white noise, is being incorporated in the solution of this problem. VESP's for white-noise stimulation exhibit time domain behavior similar to the classical response for flash stimuli but with certain significant differences. Contour mapping algorithms are used to display the time behavior of equipotential surfaces on the scalp during the VESP. The electrical and geometrical parameters of the head are modeled. Electrical fields closely matching those obtained experimentally are generated on the surface of the model head by optimally selecting the location and strength parameters of one or two dipole current sources contained within the model. Computer graphics are used to display as a movie the actual and model scalp potential field and the parameters of the dipole generators whithin the model head during the time course of the VESP. These techniques are currently used to study retinotopic mapping, fusion, and texture perception in the human.

Using sensitivity analysis in model calibration efforts

USGS Publications Warehouse

Tiedeman, Claire; Hill, Mary C.

2003-01-01

In models of natural and engineered systems, sensitivity analysis can be used to assess relations among system state observations, model parameters, and model predictions. The model itself links these three entities, and model sensitivities can be used to quantify the links. Sensitivities are defined as the derivatives of simulated quantities (such as simulated equivalents of observations, or model predictions) with respect to model parameters. We present four measures calculated from model sensitivities that quantify the observation-parameter-prediction links and that are especially useful during the calibration and prediction phases of modeling. These four measures are composite scaled sensitivities (CSS), prediction scaled sensitivities (PSS), the value of improved information (VOII) statistic, and the observation prediction (OPR) statistic. These measures can be used to help guide initial calibration of models, collection of field data beneficial to model predictions, and recalibration of models updated with new field information. Once model sensitivities have been calculated, each of the four measures requires minimal computational effort. We apply the four measures to a three-layer MODFLOW-2000 (Harbaugh et al., 2000; Hill et al., 2000) model of the Death Valley regional ground-water flow system (DVRFS), located in southern Nevada and California. D’Agnese et al. (1997, 1999) developed and calibrated the model using nonlinear regression methods. Figure 1 shows some of the observations, parameters, and predictions for the DVRFS model. Observed quantities include hydraulic heads and spring flows. The 23 defined model parameters include hydraulic conductivities, vertical anisotropies, recharge rates, evapotranspiration rates, and pumpage. Predictions of interest for this regional-scale model are advective transport paths from potential contamination sites underlying the Nevada Test Site and Yucca Mountain.

Population models for passerine birds: structure, parameterization, and analysis

USGS Publications Warehouse

Noon, B.R.; Sauer, J.R.; McCullough, D.R.; Barrett, R.H.

1992-01-01

Population models have great potential as management tools, as they use infonnation about the life history of a species to summarize estimates of fecundity and survival into a description of population change. Models provide a framework for projecting future populations, determining the effects of management decisions on future population dynamics, evaluating extinction probabilities, and addressing a variety of questions of ecological and evolutionary interest. Even when insufficient information exists to allow complete identification of the model, the modelling procedure is useful because it forces the investigator to consider the life history of the species when determining what parameters should be estimated from field studies and provides a context for evaluating the relative importance of demographic parameters. Models have been little used in the study of the population dynamics of passerine birds because of: (1) widespread misunderstandings of the model structures and parameterizations, (2) a lack of knowledge of life histories of many species, (3) difficulties in obtaining statistically reliable estimates of demographic parameters for most passerine species, and (4) confusion about functional relationships among demographic parameters. As a result, studies of passerine demography are often designed inappropriately and fail to provide essential data. We review appropriate models for passerine bird populations and illustrate their possible uses in evaluating the effects of management or other environmental influences on population dynamics. We identify environmental influences on population dynamics. We identify parameters that must be estimated from field data, briefly review existing statistical methods for obtaining valid estimates, and evaluate the present status of knowledge of these parameters.

Tachyon warm-intermediate inflationary universe model in high dissipative regime

DOE Office of Scientific and Technical Information (OSTI.GOV)

Setare, M.R.; Kamali, V., E-mail: rezakord@ipm.ir, E-mail: vkamali1362@gmail.com

2012-08-01

We consider tachyonic warm-inflationary models in the context of intermediate inflation. We derive the characteristics of this model in slow-roll approximation and develop our model in two cases, 1- For a constant dissipative parameter Γ. 2- Γ as a function of tachyon field φ. We also describe scalar and tensor perturbations for this scenario. The parameters appearing in our model are constrained by recent observational data. We find that the level of non-Gaussianity for this model is comparable with non-tachyonic model.

Complete set of homogeneous isotropic analytic solutions in scalar-tensor cosmology with radiation and curvature

NASA Astrophysics Data System (ADS)

Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

2012-10-01

We study a model of a scalar field minimally coupled to gravity, with a specific potential energy for the scalar field, and include curvature and radiation as two additional parameters. Our goal is to obtain analytically the complete set of configurations of a homogeneous and isotropic universe as a function of time. This leads to a geodesically complete description of the Universe, including the passage through the cosmological singularities, at the classical level. We give all the solutions analytically without any restrictions on the parameter space of the model or initial values of the fields. We find that for generic solutions the Universe goes through a singular (zero-size) bounce by entering a period of antigravity at each big crunch and exiting from it at the following big bang. This happens cyclically again and again without violating the null-energy condition. There is a special subset of geodesically complete nongeneric solutions which perform zero-size bounces without ever entering the antigravity regime in all cycles. For these, initial values of the fields are synchronized and quantized but the parameters of the model are not restricted. There is also a subset of spatial curvature-induced solutions that have finite-size bounces in the gravity regime and never enter the antigravity phase. These exist only within a small continuous domain of parameter space without fine-tuning the initial conditions. To obtain these results, we identified 25 regions of a 6-parameter space in which the complete set of analytic solutions are explicitly obtained.

QCD nature of dark energy at finite temperature: Cosmological implications

NASA Astrophysics Data System (ADS)

Azizi, K.; Katırcı, N.

2016-05-01

The Veneziano ghost field has been proposed as an alternative source of dark energy, whose energy density is consistent with the cosmological observations. In this model, the energy density of the QCD ghost field is expressed in terms of QCD degrees of freedom at zero temperature. We extend this model to finite temperature to search the model predictions from late time to early universe. We depict the variations of QCD parameters entering the calculations, dark energy density, equation of state, Hubble and deceleration parameters on temperature from zero to a critical temperature. We compare our results with the observations and theoretical predictions existing at different eras. It is found that this model safely defines the universe from quark condensation up to now and its predictions are not in tension with those of the standard cosmology. The EoS parameter of dark energy is dynamical and evolves from -1/3 in the presence of radiation to -1 at late time. The finite temperature ghost dark energy predictions on the Hubble parameter well fit to those of Λ CDM and observations at late time.

Study of the method of water-injected meat identifying based on low-field nuclear magnetic resonance

NASA Astrophysics Data System (ADS)

Xu, Jianmei; Lin, Qing; Yang, Fang; Zheng, Zheng; Ai, Zhujun

2018-01-01

The aim of this study to apply low-field nuclear magnetic resonance technique was to study regular variation of the transverse relaxation spectral parameters of water-injected meat with the proportion of water injection. Based on this, the method of one-way ANOVA and discriminant analysis was used to analyse the differences between these parameters in the capacity of distinguishing water-injected proportion, and established a model for identifying water-injected meat. The results show that, except for T 21b, T 22e and T 23b, the other parameters of the T 2 relaxation spectrum changed regularly with the change of water-injected proportion. The ability of different parameters to distinguish water-injected proportion was different. Based on S, P 22 and T 23m as the prediction variable, the Fisher model and the Bayes model were established by discriminant analysis method, qualitative and quantitative classification of water-injected meat can be realized. The rate of correct discrimination of distinguished validation and cross validation were 88%, the model was stable.

Fracture characterization by hybrid enumerative search and Gauss-Newton least-squares inversion methods

NASA Astrophysics Data System (ADS)

Alkharji, Mohammed N.

Most fracture characterization methods provide a general description of the fracture parameters as part of the reservoirs parameters; the fracture interaction and geometry within the reservoir is given less attention. T-Matrix and Linear Slip effective medium fracture models are implemented to invert the elastic tensor for the parameters and geometries of the fractures within the reservoir. The fracture inverse problem has an ill-posed, overdetermined, underconstrained rank-deficit system of equations. Least-squares inverse methods are used to solve the problem. A good starting initial model for the parameters is a key factor in the reliability of the inversion. Most methods assume that the starting parameters are close to the solution to avoid inaccurate local minimum solutions. The prior knowledge of the fracture parameters and their geometry is not available. We develop a hybrid, enumerative and Gauss-Newton, method that estimates the fracture parameters and geometry from the elastic tensor with no prior knowledge of the initial parameter values. The fracture parameters are separated into two groups. The first group contains the fracture parameters with no prior information, and the second group contains the parameters with known prior information. Different models are generated from the first group parameters by sampling the solution space over a predefined range of possible solutions for each parameter. Each model generated by the first group is fixed and used as a starting model to invert for the second group of parameters using the Gauss-Newton method. The least-squares residual between the observed elastic tensor and the estimated elastic tensor is calculated for each model. The model parameters that yield the least-squares residual corresponds to the correct fracture reservoir parameters and geometry. Two synthetic examples of fractured reservoirs with oil and gas saturations were inverted with no prior information about the fracture properties. The results showed that the hybrid algorithm successfully predicted the fracture parametrization, geometry, and the fluid content within the modeled reservoir. The method was also applied on an elastic tensor extracted from the Weyburn field in Saskatchewan, Canada. The solution suggested no presence of fractures but only a VTI system caused by the shale layering in the targeted reservoir, this interpretation is supported by other Weyburn field data.

Parameter estimation uncertainty: Comparing apples and apples?

NASA Astrophysics Data System (ADS)

Hart, D.; Yoon, H.; McKenna, S. A.

2012-12-01

Given a highly parameterized ground water model in which the conceptual model of the heterogeneity is stochastic, an ensemble of inverse calibrations from multiple starting points (MSP) provides an ensemble of calibrated parameters and follow-on transport predictions. However, the multiple calibrations are computationally expensive. Parameter estimation uncertainty can also be modeled by decomposing the parameterization into a solution space and a null space. From a single calibration (single starting point) a single set of parameters defining the solution space can be extracted. The solution space is held constant while Monte Carlo sampling of the parameter set covering the null space creates an ensemble of the null space parameter set. A recently developed null-space Monte Carlo (NSMC) method combines the calibration solution space parameters with the ensemble of null space parameters, creating sets of calibration-constrained parameters for input to the follow-on transport predictions. Here, we examine the consistency between probabilistic ensembles of parameter estimates and predictions using the MSP calibration and the NSMC approaches. A highly parameterized model of the Culebra dolomite previously developed for the WIPP project in New Mexico is used as the test case. A total of 100 estimated fields are retained from the MSP approach and the ensemble of results defining the model fit to the data, the reproduction of the variogram model and prediction of an advective travel time are compared to the same results obtained using NSMC. We demonstrate that the NSMC fields based on a single calibration model can be significantly constrained by the calibrated solution space and the resulting distribution of advective travel times is biased toward the travel time from the single calibrated field. To overcome this, newly proposed strategies to employ a multiple calibration-constrained NSMC approach (M-NSMC) are evaluated. Comparison of the M-NSMC and MSP methods suggests that M-NSMC can provide a computationally efficient and practical solution for predictive uncertainty analysis in highly nonlinear and complex subsurface flow and transport models. This material is based upon work supported as part of the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0001114. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

NASA Astrophysics Data System (ADS)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace such that the dimensionality of the problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2-D and a random hydraulic conductivity field in 3-D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ˜101 to ˜102 in a multicore computational environment. Therefore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate to large-scale problems.

Diffusion model of penetration of a chloride-containing environment in the volume of a constructive element

NASA Astrophysics Data System (ADS)

Ovchinnikov, I. I.; Snezhkina, O. V.; Ovchinnikov, I. G.

2018-06-01

A generalized model of diffusional penetration of a chloride-containing medium into the volume of a compressed reinforced concrete element is considered. The equations of deformation values of reinforced concrete structure are presented, taking into account the degradation of concrete and corrosion of reinforcement. At the initial stage, an applied force calculation of section of the structural element with mechanical properties of the material which are determined by the initial field of concentration of aggressive medium, is carried out. Furthermore, at each discrete instant moment of time, the following properties are determined: the distribution law of concentration for chloride field, corresponding to the parameters of the stress-strain state; the calculation of corrosion damage field of reinforcing elements and the applied force calculation of section of the structural element with parameters corresponding to the distribution of the concentration field and the field of corrosion damage are carried out.

Synthesis and Characterization of Liquid Crystalline Epoxy Resins

DTIC Science & Technology

2014-01-01

Temperature dependence of the four parameters in the Burgers model. ......... 81 Figure 4.7 Dependence of creep compliance on creep time at different...Kinetic parameters for LCERs. ......................................................................... 65 Table 3.4 Kinetic parameters for non-LCERs...curing in a high strength magnetic field. The orientation was quantified by an orientation parameter determined with two-dimensional X-ray diffraction

LEOrbit: A program to calculate parameters relevant to modeling Low Earth Orbit spacecraft-plasma interaction

NASA Astrophysics Data System (ADS)

Marchand, R.; Purschke, D.; Samson, J.

2013-03-01

Understanding the physics of interaction between satellites and the space environment is essential in planning and exploiting space missions. Several computer models have been developed over the years to study this interaction. In all cases, simulations are carried out in the reference frame of the spacecraft and effects such as charging, the formation of electrostatic sheaths and wakes are calculated for given conditions of the space environment. In this paper we present a program used to compute magnetic fields and a number of space plasma and space environment parameters relevant to Low Earth Orbits (LEO) spacecraft-plasma interaction modeling. Magnetic fields are obtained from the International Geophysical Reference Field (IGRF) and plasma parameters are obtained from the International Reference Ionosphere (IRI) model. All parameters are computed in the spacecraft frame of reference as a function of its six Keplerian elements. They are presented in a format that can be used directly in most spacecraft-plasma interaction models. Catalogue identifier: AENY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 270308 No. of bytes in distributed program, including test data, etc.: 2323222 Distribution format: tar.gz Programming language: FORTRAN 90. Computer: Non specific. Operating system: Non specific. RAM: 7.1 MB Classification: 19, 4.14. External routines: IRI, IGRF (included in the package). Nature of problem: Compute magnetic field components, direction of the sun, sun visibility factor and approximate plasma parameters in the reference frame of a Low Earth Orbit satellite. Solution method: Orbit integration, calls to IGRF and IRI libraries and transformation of coordinates from geocentric to spacecraft frame reference. Restrictions: Low Earth orbits, altitudes between 150 and 2000 km. Running time: Approximately two seconds to parameterize a full orbit with 1000 points.

Calculation of the Initial Magnetic Field for Mercury's Magnetosphere Hybrid Model

NASA Astrophysics Data System (ADS)

Alexeev, Igor; Parunakian, David; Dyadechkin, Sergey; Belenkaya, Elena; Khodachenko, Maxim; Kallio, Esa; Alho, Markku

2018-03-01

Several types of numerical models are used to analyze the interactions of the solar wind flow with Mercury's magnetosphere, including kinetic models that determine magnetic and electric fields based on the spatial distribution of charges and currents, magnetohydrodynamic models that describe plasma as a conductive liquid, and hybrid models that describe ions kinetically in collisionless mode and represent electrons as a massless neutralizing liquid. The structure of resulting solutions is determined not only by the chosen set of equations that govern the behavior of plasma, but also by the initial and boundary conditions; i.e., their effects are not limited to the amount of computational work required to achieve a quasi-stationary solution. In this work, we have proposed using the magnetic field computed by the paraboloid model of Mercury's magnetosphere as the initial condition for subsequent hybrid modeling. The results of the model have been compared to measurements performed by the Messenger spacecraft during a single crossing of the magnetosheath and the magnetosphere. The selected orbit lies in the terminator plane, which allows us to observe two crossings of the bow shock and the magnetopause. In our calculations, we have defined the initial parameters of the global magnetospheric current systems in a way that allows us to minimize paraboloid magnetic field deviation along the trajectory of the Messenger from the experimental data. We have shown that the optimal initial field parameters include setting the penetration of a partial interplanetary magnetic field into the magnetosphere with a penetration coefficient of 0.2.

Parameter Stability of the Functional–Structural Plant Model GREENLAB as Affected by Variation within Populations, among Seasons and among Growth Stages

PubMed Central

Ma, Yuntao; Li, Baoguo; Zhan, Zhigang; Guo, Yan; Luquet, Delphine; de Reffye, Philippe; Dingkuhn, Michael

2007-01-01

Background and Aims It is increasingly accepted that crop models, if they are to simulate genotype-specific behaviour accurately, should simulate the morphogenetic process generating plant architecture. A functional–structural plant model, GREENLAB, was previously presented and validated for maize. The model is based on a recursive mathematical process, with parameters whose values cannot be measured directly and need to be optimized statistically. This study aims at evaluating the stability of GREENLAB parameters in response to three types of phenotype variability: (1) among individuals from a common population; (2) among populations subjected to different environments (seasons); and (3) among different development stages of the same plants. Methods Five field experiments were conducted in the course of 4 years on irrigated fields near Beijing, China. Detailed observations were conducted throughout the seasons on the dimensions and fresh biomass of all above-ground plant organs for each metamer. Growth stage-specific target files were assembled from the data for GREENLAB parameter optimization. Optimization was conducted for specific developmental stages or the entire growth cycle, for individual plants (replicates), and for different seasons. Parameter stability was evaluated by comparing their CV with that of phenotype observation for the different sources of variability. A reduced data set was developed for easier model parameterization using one season, and validated for the four other seasons. Key Results and Conclusions The analysis of parameter stability among plants sharing the same environment and among populations grown in different environments indicated that the model explains some of the inter-seasonal variability of phenotype (parameters varied less than the phenotype itself), but not inter-plant variability (parameter and phenotype variability were similar). Parameter variability among developmental stages was small, indicating that parameter values were largely development-stage independent. The authors suggest that the high level of parameter stability observed in GREENLAB can be used to conduct comparisons among genotypes and, ultimately, genetic analyses. PMID:17158141

Force-field parameters of the Psi and Phi around glycosidic bonds to oxygen and sulfur atoms.

PubMed

Saito, Minoru; Okazaki, Isao

2009-12-01

The Psi and Phi torsion angles around glycosidic bonds in a glycoside chain are the most important determinants of the conformation of a glycoside chain. We determined force-field parameters for Psi and Phi torsion angles around a glycosidic bond bridged by a sulfur atom, as well as a bond bridged by an oxygen atom as a preparation for the next study, i.e., molecular dynamics free energy calculations for protein-sugar and protein-inhibitor complexes. First, we extracted the Psi or Phi torsion energy component from a quantum mechanics (QM) total energy by subtracting all the molecular mechanics (MM) force-field components except for the Psi or Phi torsion angle. The Psi and Phi energy components extracted (hereafter called "the remaining energy components") were calculated for simple sugar models and plotted as functions of the Psi and Phi angles. The remaining energy component curves of Psi and Phi were well represented by the torsion force-field functions consisting of four and three cosine functions, respectively. To confirm the reliability of the force-field parameters and to confirm its compatibility with other force-fields, we calculated adiabatic potential curves as functions of Psi and Phi for the model glycosides by adopting the Psi and Phi force-field parameters obtained and by energetically optimizing other degrees of freedom. The MM potential energy curves obtained for Psi and Phi well represented the QM adiabatic curves and also these curves' differences with regard to the glycosidic oxygen and sulfur atoms. Our Psi and Phi force-fields of glycosidic oxygen gave MM potential energy curves that more closely represented the respective QM curves than did those of the recently developed GLYCAM force-field. (c) 2009 Wiley Periodicals, Inc.

Two-electrons quantum dot in plasmas under the external fields

NASA Astrophysics Data System (ADS)

Bahar, M. K.; Soylu, A.

2018-02-01

In this study, for the first time, the combined effects of the external electric field, magnetic field, and confinement frequency on energies of two-electron parabolic quantum dots in Debye and quantum plasmas modeled by more general exponential cosine screened Coulomb (MGECSC) potential are investigated by numerically solving the Schrödinger equation using the asymptotic iteration method. The MGECSC potential includes four different potential forms when considering different sets of the parameters in potential. Since the plasma is an important experimental argument for quantum dots, the influence of plasmas modeled by the MGECSC potential on quantum dots is probed. The confinement frequency of quantum dots and the external fields created significant quantum restrictions on quantum dot. In this study, as well as discussion of the functionalities of the quantum restrictions for experimental applications, the parameters are also compared with each other in terms of influence and behaviour. In this manner, the motivation points of this study are summarized as follows: Which parameter can be alternative to which parameter, in terms of experimental applications? Which parameters exhibit similar behaviour? What is the role of plasmas on the corresponding behaviours? In the light of these research studies, it can be said that obtained results and performed discussions would be important in experimental and theoretical research related to plasma physics and/or quantum dots.

The influence of Monte Carlo source parameters on detector design and dose perturbation in small field dosimetry

NASA Astrophysics Data System (ADS)

Charles, P. H.; Crowe, S. B.; Kairn, T.; Knight, R.; Hill, B.; Kenny, J.; Langton, C. M.; Trapp, J. V.

2014-03-01

To obtain accurate Monte Carlo simulations of small radiation fields, it is important model the initial source parameters (electron energy and spot size) accurately. However recent studies have shown that small field dosimetry correction factors are insensitive to these parameters. The aim of this work is to extend this concept to test if these parameters affect dose perturbations in general, which is important for detector design and calculating perturbation correction factors. The EGSnrc C++ user code cavity was used for all simulations. Varying amounts of air between 0 and 2 mm were deliberately introduced upstream to a diode and the dose perturbation caused by the air was quantified. These simulations were then repeated using a range of initial electron energies (5.5 to 7.0 MeV) and electron spot sizes (0.7 to 2.2 FWHM). The resultant dose perturbations were large. For example 2 mm of air caused a dose reduction of up to 31% when simulated with a 6 mm field size. However these values did not vary by more than 2 % when simulated across the full range of source parameters tested. If a detector is modified by the introduction of air, one can be confident that the response of the detector will be the same across all similar linear accelerators and the Monte Carlo modelling of each machine is not required.

Model parameter estimations from residual gravity anomalies due to simple-shaped sources using Differential Evolution Algorithm

NASA Astrophysics Data System (ADS)

Ekinci, Yunus Levent; Balkaya, Çağlayan; Göktürkler, Gökhan; Turan, Seçil

2016-06-01

An efficient approach to estimate model parameters from residual gravity data based on differential evolution (DE), a stochastic vector-based metaheuristic algorithm, has been presented. We have showed the applicability and effectiveness of this algorithm on both synthetic and field anomalies. According to our knowledge, this is a first attempt of applying DE for the parameter estimations of residual gravity anomalies due to isolated causative sources embedded in the subsurface. The model parameters dealt with here are the amplitude coefficient (A), the depth and exact origin of causative source (zo and xo, respectively) and the shape factors (q and ƞ). The error energy maps generated for some parameter pairs have successfully revealed the nature of the parameter estimation problem under consideration. Noise-free and noisy synthetic single gravity anomalies have been evaluated with success via DE/best/1/bin, which is a widely used strategy in DE. Additionally some complicated gravity anomalies caused by multiple source bodies have been considered, and the results obtained have showed the efficiency of the algorithm. Then using the strategy applied in synthetic examples some field anomalies observed for various mineral explorations such as a chromite deposit (Camaguey district, Cuba), a manganese deposit (Nagpur, India) and a base metal sulphide deposit (Quebec, Canada) have been considered to estimate the model parameters of the ore bodies. Applications have exhibited that the obtained results such as the depths and shapes of the ore bodies are quite consistent with those published in the literature. Uncertainty in the solutions obtained from DE algorithm has been also investigated by Metropolis-Hastings (M-H) sampling algorithm based on simulated annealing without cooling schedule. Based on the resulting histogram reconstructions of both synthetic and field data examples the algorithm has provided reliable parameter estimations being within the sampling limits of M-H sampler. Although it is not a common inversion technique in geophysics, it can be stated that DE algorithm is worth to get more interest for parameter estimations from potential field data in geophysics considering its good accuracy, less computational cost (in the present problem) and the fact that a well-constructed initial guess is not required to reach the global minimum.

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance.

PubMed

Clare, John; McKinney, Shawn T; DePue, John E; Loftin, Cynthia S

2017-10-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters. © 2017 by the Ecological Society of America.

MCPB.py: A Python Based Metal Center Parameter Builder.

PubMed

Li, Pengfei; Merz, Kenneth M

2016-04-25

MCPB.py, a python based metal center parameter builder, has been developed to build force fields for the simulation of metal complexes employing the bonded model approach. It has an optimized code structure, with far fewer required steps than the previous developed MCPB program. It supports various AMBER force fields and more than 80 metal ions. A series of parametrization schemes to derive force constants and charge parameters are available within the program. We give two examples (one metalloprotein example and one organometallic compound example), indicating the program's ability to build reliable force fields for different metal ion containing complexes. The original version was released with AmberTools15. It is provided via the GNU General Public License v3.0 (GNU_GPL_v3) agreement and is free to download and distribute. MCPB.py provides a bridge between quantum mechanical calculations and molecular dynamics simulation software packages thereby enabling the modeling of metal ion centers. It offers an entry into simulating metal ions in a number of situations by providing an efficient way for researchers to handle the vagaries and difficulties associated with metal ion modeling.

A simple model of hysteresis behavior using spreadsheet analysis

NASA Astrophysics Data System (ADS)

Ehrmann, A.; Blachowicz, T.

2015-01-01

Hysteresis loops occur in many scientific and technical problems, especially as field dependent magnetization of ferromagnetic materials, but also as stress-strain-curves of materials measured by tensile tests including thermal effects, liquid-solid phase transitions, in cell biology or economics. While several mathematical models exist which aim to calculate hysteresis energies and other parameters, here we offer a simple model for a general hysteretic system, showing different hysteresis loops depending on the defined parameters. The calculation which is based on basic spreadsheet analysis plus an easy macro code can be used by students to understand how these systems work and how the parameters influence the reactions of the system on an external field. Importantly, in the step-by-step mode, each change of the system state, compared to the last step, becomes visible. The simple program can be developed further by several changes and additions, enabling the building of a tool which is capable of answering real physical questions in the broad field of magnetism as well as in other scientific areas, in which similar hysteresis loops occur.

FIT: statistical modeling tool for transcriptome dynamics under fluctuating field conditions

PubMed Central

Iwayama, Koji; Aisaka, Yuri; Kutsuna, Natsumaro

2017-01-01

Abstract Motivation: Considerable attention has been given to the quantification of environmental effects on organisms. In natural conditions, environmental factors are continuously changing in a complex manner. To reveal the effects of such environmental variations on organisms, transcriptome data in field environments have been collected and analyzed. Nagano et al. proposed a model that describes the relationship between transcriptomic variation and environmental conditions and demonstrated the capability to predict transcriptome variation in rice plants. However, the computational cost of parameter optimization has prevented its wide application. Results: We propose a new statistical model and efficient parameter optimization based on the previous study. We developed and released FIT, an R package that offers functions for parameter optimization and transcriptome prediction. The proposed method achieves comparable or better prediction performance within a shorter computational time than the previous method. The package will facilitate the study of the environmental effects on transcriptomic variation in field conditions. Availability and Implementation: Freely available from CRAN (https://cran.r-project.org/web/packages/FIT/). Contact: anagano@agr.ryukoku.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online PMID:28158396

Chaplygin gas inspired scalar fields inflation via well-known potentials

NASA Astrophysics Data System (ADS)

Jawad, Abdul; Butt, Sadaf; Rani, Shamaila

2016-08-01

Brane inflationary universe models in the context of modified Chaplygin gas and generalized cosmic Chaplygin gas are being studied. We develop these models in view of standard scalar and tachyon fields. In both models, the implemented inflationary parameters such as scalar and tensor power spectra, scalar spectral index and tensor to scalar ratio are derived under slow roll approximations. We also use chaotic and exponential potential in high energy limits and discuss the characteristics of inflationary parameters for both potentials. These models are compatible with recent astronomical observations provided by WMAP7{+}9 and Planck data, i.e., ηs=1.027±0.051, 1.009±0.049, 0.096±0.025 and r<0.38, 0.36, 0.11.

Ensemble Kalman Filter Data Assimilation in a Solar Dynamo Model

NASA Astrophysics Data System (ADS)

Dikpati, M.

2017-12-01

Despite great advancement in solar dynamo models since the first model by Parker in 1955, there remain many challenges in the quest to build a dynamo-based prediction scheme that can accurately predict the solar cycle features. One of these challenges is to implement modern data assimilation techniques, which have been used in the oceanic and atmospheric prediction models. Development of data assimilation in solar models are in the early stages. Recently, observing system simulation experiments (OSSE's) have been performed using Ensemble Kalman Filter data assimilation, in the framework of Data Assimilation Research Testbed of NCAR (NCAR-DART), for estimating parameters in a solar dynamo model. I will demonstrate how the selection of ensemble size, number of observations, amount of error in observations and the choice of assimilation interval play important role in parameter estimation. I will also show how the results of parameter reconstruction improve when accuracy in low-latitude observations is increased, despite large error in polar region data. I will then describe how implementation of data assimilation in a solar dynamo model can bring more accuracy in the prediction of polar fields in North and South hemispheres during the declining phase of cycle 24. Recent evidence indicates that the strength of the Sun's polar field during the cycle minima might be a reliable predictor for the next sunspot cycle's amplitude; therefore it is crucial to accurately predict the polar field strength and pattern.

Holographic reconstruction of scalar fields in extended Kaluza-Klein cosmology

NASA Astrophysics Data System (ADS)

Korunur, Murat

2018-01-01

In recent years, many studies have been conducted to reconstruct the physical properties of scalar fields by establishing a connection between some energy densities and a scalar field of dark energies. In this paper, using the extended five-dimensional (5D) Kaluza-Klein model, we establish a correspondence among modified holographic dark energy and the tachyon, K-essence and dilaton scalar-field models. We also graphically illustrate the evolution of the equation-of-state parameter versus time.

Spectroscopic and magnetic properties of Fe2+ (3d6; S = 2) ions in Fe(NH4)2(SO4)2·6H2O - Modeling zero-field splitting and Zeeman electronic parameters by microscopic spin Hamiltonian approach

NASA Astrophysics Data System (ADS)

Zając, Magdalena; Rudowicz, Czesław; Ohta, Hitoshi; Sakurai, Takahiro

2018-03-01

Utilizing the package MSH/VBA, based on the microscopic spin Hamiltonian (MSH) approach, spectroscopic and magnetic properties of Fe2+ (3d6; S = 2) ions at (nearly) orthorhombic sites in Fe(NH4)2(SO4)2·6H2O (FASH) are modeled. The zero-field splitting (ZFS) parameters and the Zeeman electronic (Ze) factors are predicted for wide ranges of values of the microscopic parameters, i.e. the spin-orbit (λ), spin-spin (ρ) coupling constants, and the crystal-field (ligand-field) energy levels (Δi) within the 5D multiplet. This enables to consider the dependence of the ZFS parameters bkq (in the Stevens notation), or the conventional ones (e.g., D and E), and the Zeeman factors gi on λ, ρ, and Δi. By matching the theoretical SH parameters and the experimental ones measured by electron magnetic resonance (EMR), the values of λ, ρ, and Δi best describing Fe2+ ions in FASH are determined. The novel aspect is prediction of the fourth-rank ZFS parameters and the ρ(spin-spin)-related contributions, not considered in previous studies. The higher-order contributions to the second- and fourth-rank ZFSPs are found significant. The MSH predictions provide guidance for high-magnetic field and high-frequency EMR (HMF-EMR) measurements and enable assessment of suitability of FASH for application as high-pressure probes for HMF-EMR studies. The method employed here and the present results may be also useful for other structurally related Fe2+ (S = 2) systems.

Bottled SAFT: A Web App Providing SAFT-γ Mie Force Field Parameters for Thousands of Molecular Fluids.

PubMed

Ervik, Åsmund; Mejía, Andrés; Müller, Erich A

2016-09-26

Coarse-grained molecular simulation has become a popular tool for modeling simple and complex fluids alike. The defining aspects of a coarse grained model are the force field parameters, which must be determined for each particular fluid. Because the number of molecular fluids of interest in nature and in engineering processes is immense, constructing force field parameter tables by individually fitting to experimental data is a futile task. A step toward solving this challenge was taken recently by Mejía et al., who proposed a correlation that provides SAFT-γ Mie force field parameters for a fluid provided one knows the critical temperature, the acentric factor and a liquid density, all relatively accessible properties. Building on this, we have applied the correlation to more than 6000 fluids, and constructed a web application, called "Bottled SAFT", which makes this data set easily searchable by CAS number, name or chemical formula. Alternatively, the application allows the user to calculate parameters for components not present in the database. Once the intermolecular potential has been found through Bottled SAFT, code snippets are provided for simulating the desired substance using the "raaSAFT" framework, which leverages established molecular dynamics codes to run the simulations. The code underlying the web application is written in Python using the Flask microframework; this allows us to provide a modern high-performance web app while also making use of the scientific libraries available in Python. Bottled SAFT aims at taking the complexity out of obtaining force field parameters for a wide range of molecular fluids, and facilitates setting up and running coarse-grained molecular simulations. The web application is freely available at http://www.bottledsaft.org . The underlying source code is available on Bitbucket under a permissive license.

A new monthly gravity field model based on GRACE observations computed by the modified dynamic approach

NASA Astrophysics Data System (ADS)

Zhou, H.; Luo, Z.; Li, Q.; Zhong, B.

2016-12-01

The monthly gravity field model can be used to compute the information about the mass variation within the system Earth, i.e., the relationship between mass variation in the oceans, land hydrology, and ice sheets. For more than ten years, GRACE has provided valuable information for recovering monthly gravity field model. In this study, a new time series of GRACE monthly solution, which is truncated to degree and order 60, is computed by the modified dynamic approach. Compared with the traditional dynamic approach, the major difference of our modified approach is the way to process the nuisance parameters. This type of parameters is mainly used to absorb low-frequency errors in KBRR data. One way is to remove the nuisance parameters before estimating the geo-potential coefficients, called Pure Predetermined Strategy (PPS). The other way is to determine the nuisance parameters and geo-potential coefficients simultaneously, called Pure Simultaneous Strategy (PSS). It is convenient to detect the gross error by PPS, while there is also obvious signal loss compared with the solutions derived from PSS. After comparing the difference of practical calculation formulas between PPS and PSS, we create the Filter Predetermine Strategy (FPS), which can combine the advantages of PPS and PSS efficiently. With FPS, a new monthly gravity field model entitled HUST-Grace2016s is developed. The comparisons of geoid degree powers and mass change signals in the Amazon basin, the Greenland and the Antarctic demonstrate that our model is comparable with the other published models, e.g., the CSR RL05, JPL RL05 and GFZ RL05 models. Acknowledgements: This work is supported by China Postdoctoral Science Foundation (Grant No.2016M592337), the National Natural Science Foundation of China (Grant Nos. 41131067, 41504014), the Open Research Fund Program of the State Key Laboratory of Geodesy and Earth's Dynamics (Grant No. SKLGED2015-1-3-E).

Revisiting the cape cod bacteria injection experiment using a stochastic modeling approach

USGS Publications Warehouse

Maxwell, R.M.; Welty, C.; Harvey, R.W.

2007-01-01

Bromide and resting-cell bacteria tracer tests conducted in a sandy aquifer at the U.S. Geological Survey Cape Cod site in 1987 were reinterpreted using a three-dimensional stochastic approach. Bacteria transport was coupled to colloid filtration theory through functional dependence of local-scale colloid transport parameters upon hydraulic conductivity and seepage velocity in a stochastic advection - dispersion/attachment - detachment model. Geostatistical information on the hydraulic conductivity (K) field that was unavailable at the time of the original test was utilized as input. Using geostatistical parameters, a groundwater flow and particle-tracking model of conservative solute transport was calibrated to the bromide-tracer breakthrough data. An optimization routine was employed over 100 realizations to adjust the mean and variance ofthe natural-logarithm of hydraulic conductivity (InK) field to achieve best fit of a simulated, average bromide breakthrough curve. A stochastic particle-tracking model for the bacteria was run without adjustments to the local-scale colloid transport parameters. Good predictions of mean bacteria breakthrough were achieved using several approaches for modeling components of the system. Simulations incorporating the recent Tufenkji and Elimelech (Environ. Sci. Technol. 2004, 38, 529-536) correlation equation for estimating single collector efficiency were compared to those using the older Rajagopalan and Tien (AIChE J. 1976, 22, 523-533) model. Both appeared to work equally well at predicting mean bacteria breakthrough using a constant mean bacteria diameter for this set of field conditions. Simulations using a distribution of bacterial cell diameters available from original field notes yielded a slight improvement in the model and data agreement compared to simulations using an average bacterial diameter. The stochastic approach based on estimates of local-scale parameters for the bacteria-transport process reasonably captured the mean bacteria transport behavior and calculated an envelope of uncertainty that bracketed the observations in most simulation cases. ?? 2007 American Chemical Society.

Geophysical monitoring of solute transport in dual-domain environments through laboratory experiments, field-scale solute tracer tests, and numerical simulation

NASA Astrophysics Data System (ADS)

Swanson, Ryan David

The advection-dispersion equation (ADE) fails to describe non-Fickian solute transport breakthrough curves (BTCs) in saturated porous media in both laboratory and field experiments, necessitating the use of other models. The dual-domain mass transfer (DDMT) model partitions the total porosity into mobile and less-mobile domains with an exchange of mass between the two domains, and this model can reproduce better fits to BTCs in many systems than ADE-based models. However, direct experimental estimation of DDMT model parameters remains elusive and model parameters are often calculated a posteriori by an optimization procedure. Here, we investigate the use of geophysical tools (direct-current resistivity, nuclear magnetic resonance, and complex conductivity) to estimate these model parameters directly. We use two different samples of the zeolite clinoptilolite, a material shown to demonstrate solute mass transfer due to a significant internal porosity, and provide the first evidence that direct-current electrical methods can track solute movement into and out of a less-mobile pore space in controlled laboratory experiments. We quantify the effects of assuming single-rate DDMT for multirate mass transfer systems. We analyze pore structures using material characterization methods (mercury porosimetry, scanning electron microscopy, and X-ray computer tomography), and compare these observations to geophysical measurements. Nuclear magnetic resonance in conjunction with direct-current resistivity measurements can constrain mobile and less-mobile porosities, but complex conductivity may have little value in relation to mass transfer despite the hypothesis that mass transfer and complex conductivity lengths scales are related. Finally, we conduct a geoelectrical monitored tracer test at the Macrodispersion Experiment (MADE) site in Columbus, MS. We relate hydraulic and electrical conductivity measurements to generate a 3D hydraulic conductivity field, and compare to hydraulic conductivity fields estimated through ordinary kriging and sequential Gaussian simulation. Time-lapse electrical measurements are used to verify or dismiss aspects of breakthrough curves for different hydraulic conductivity fields. Our results quantify the potential for geophysical measurements to infer on single-rate DDMT parameters, show site-specific relations between hydraulic and electrical conductivity, and track solute exchange into and out of less-mobile domains.

Inverse models: A necessary next step in ground-water modeling

USGS Publications Warehouse

Poeter, E.P.; Hill, M.C.

1997-01-01

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares repression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.

Joint inversion of marine seismic AVA and CSEM data using statistical rock-physics models and Markov random fields: Stochastic inversion of AVA and CSEM data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, J.; Hoversten, G.M.

2011-09-15

Joint inversion of seismic AVA and CSEM data requires rock-physics relationships to link seismic attributes to electrical properties. Ideally, we can connect them through reservoir parameters (e.g., porosity and water saturation) by developing physical-based models, such as Gassmann’s equations and Archie’s law, using nearby borehole logs. This could be difficult in the exploration stage because information available is typically insufficient for choosing suitable rock-physics models and for subsequently obtaining reliable estimates of the associated parameters. The use of improper rock-physics models and the inaccuracy of the estimates of model parameters may cause misleading inversion results. Conversely, it is easy tomore » derive statistical relationships among seismic and electrical attributes and reservoir parameters from distant borehole logs. In this study, we develop a Bayesian model to jointly invert seismic AVA and CSEM data for reservoir parameter estimation using statistical rock-physics models; the spatial dependence of geophysical and reservoir parameters are carried out by lithotypes through Markov random fields. We apply the developed model to a synthetic case, which simulates a CO{sub 2} monitoring application. We derive statistical rock-physics relations from borehole logs at one location and estimate seismic P- and S-wave velocity ratio, acoustic impedance, density, electrical resistivity, lithotypes, porosity, and water saturation at three different locations by conditioning to seismic AVA and CSEM data. Comparison of the inversion results with their corresponding true values shows that the correlation-based statistical rock-physics models provide significant information for improving the joint inversion results.« less

Force Field for Peptides and Proteins based on the Classical Drude Oscillator

PubMed Central

Lopes, Pedro E.M.; Huang, Jing; Shim, Jihyun; Luo, Yun; Li, Hui; Roux, Benoît; MacKerell, Alexander D.

2013-01-01

Presented is a polarizable force field based on a classical Drude oscillator framework, currently implemented in the programs CHARMM and NAMD, for modeling and molecular dynamics (MD) simulation studies of peptides and proteins. Building upon parameters for model compounds representative of the functional groups in proteins, the development of the force field focused on the optimization of the parameters for the polypeptide backbone and the connectivity between the backbone and side chains. Optimization of the backbone electrostatic parameters targeted quantum mechanical conformational energies, interactions with water, molecular dipole moments and polarizabilities and experimental condensed phase data for short polypeptides such as (Ala)5. Additional optimization of the backbone φ, ψ conformational preferences included adjustments of the tabulated two-dimensional spline function through the CMAP term. Validation of the model included simulations of a collection of peptides and proteins. This 1st generation polarizable model is shown to maintain the folded state of the studied systems on the 100 ns timescale in explicit solvent MD simulations. The Drude model typically yields larger RMS differences as compared to the additive CHARMM36 force field (C36) and shows additional flexibility as compared to the additive model. Comparison with NMR chemical shift data shows a small degradation of the polarizable model with respect to the additive, though the level of agreement may be considered satisfactory, while for residues shown to have significantly underestimated S2 order parameters in the additive model, improvements are calculated with the polarizable model. Analysis of dipole moments associated with the peptide backbone and tryptophan side chains show the Drude model to have significantly larger values than those present in C36, with the dipole moments of the peptide backbone enhanced to a greater extent in sheets versus helices and the dipoles of individual moieties observed to undergo significant variations during the MD simulations. Although there are still some limitations, the presented model, termed Drude-2013, is anticipated to yield a molecular picture of peptide and protein structure and function that will be of increased physical validity and internal consistency in a computationally accessible fashion. PMID:24459460

Effects of Anisotropy on Scalar Field Ghost Dark Energy and the Non-Equilibrium Thermodynamics in Fractal Cosmology

NASA Astrophysics Data System (ADS)

Najafi, A.; Hossienkhani, H.

2017-10-01

Since the fractal cosmology has been created in early universe, therefore their models were mostly isotropic. The majority of previous studies had been based on FRW universe, while in the early universe, the best model for describing fractal cosmology is actually the anisotropic universe. Therefore in this work, by assuming the anisotropic universe, the cosmological implications of ghost and generalized ghost dark energy models with dark matter in fractal cosmology has been discussed. Moreover, the different kinds of dark energy models such as quintessence and tachyon field, with the generalized ghost dark energy in fractal universe has been investigated. In addition, we have reconstructed the Hubble parameter, H, the energy density, ρ, the deceleration parameter, q, the equations of state parameter, {ω }{{}D}, for both ghost and generalized ghost dark energy models. This correspondence allows us to reconstruct the potential and the dynamics of a fractal canonical scalar field according to the evolution of generalized ghost dark energy density. Eventually, thermodynamics of the cosmological apparent horizon in fractal cosmology was investigated and the validity of the Generalized second law of thermodynamics (GSLT) have been examined in an anisotropic universe. The results show the influence of the anisotropy on the GSLT of thermodynamics in a fractal cosmology.

Physics of GAM-initiated L-H transition in a tokamak

NASA Astrophysics Data System (ADS)

Askinazi, L. G.; Belokurov, A. A.; Bulanin, V. V.; Gurchenko, A. D.; Gusakov, E. Z.; Kiviniemi, T. P.; Lebedev, S. V.; Kornev, V. A.; Korpilo, T.; Krikunov, S. V.; Leerink, S.; Machielsen, M.; Niskala, P.; Petrov, A. V.; Tukachinsky, A. S.; Yashin, A. Yu; Zhubr, N. A.

2017-01-01

Based on experimental observations using the TUMAN-3M and FT-2 tokamaks, and the results of gyrokinetic modeling of the interplay between turbulence and the geodesic acoustic mode (GAM) in these installations, a simple model is proposed for the analysis of the conditions required for L-H transition triggering by a burst of radial electric field oscillations in a tokamak. In the framework of this model, one-dimensional density evolution is considered to be governed by an anomalous diffusion coefficient dependent on radial electric field shear. The radial electric field is taken as the sum of the oscillating term and the quasi-stationary one determined by density and ion temperature gradients through a neoclassical formula. If the oscillating field parameters (amplitude, frequency, etc) are properly adjusted, a transport barrier forms at the plasma periphery and sustains after the oscillations are switched off, manifesting a transition into the high confinement mode with a strong inhomogeneous radial electric field and suppressed transport at the plasma edge. The electric field oscillation parameters required for L-H transition triggering are compared with the GAM parameters observed at the TUMAN-3M (in the discharges with ohmic L-H transition) and FT-2 tokamaks (where no clear L-H transition was observed). It is concluded based on this comparison that the GAM may act as a trigger for the L-H transition, provided that certain conditions for GAM oscillation and tokamak discharge are met.

Further along the Road Less Traveled: AMBER ff15ipq, an Original Protein Force Field Built on a Self-Consistent Physical Model

PubMed Central

2016-01-01

We present the AMBER ff15ipq force field for proteins, the second-generation force field developed using the Implicitly Polarized Q (IPolQ) scheme for deriving implicitly polarized atomic charges in the presence of explicit solvent. The ff15ipq force field is a complete rederivation including more than 300 unique atomic charges, 900 unique torsion terms, 60 new angle parameters, and new atomic radii for polar hydrogens. The atomic charges were derived in the context of the SPC/Eb water model, which yields more-accurate rotational diffusion of proteins and enables direct calculation of nuclear magnetic resonance (NMR) relaxation parameters from molecular dynamics simulations. The atomic radii improve the accuracy of modeling salt bridge interactions relative to contemporary fixed-charge force fields, rectifying a limitation of ff14ipq that resulted from its use of pair-specific Lennard-Jones radii. In addition, ff15ipq reproduces penta-alanine J-coupling constants exceptionally well, gives reasonable agreement with NMR relaxation rates, and maintains the expected conformational propensities of structured proteins/peptides, as well as disordered peptides—all on the microsecond (μs) time scale, which is a critical regime for drug design applications. These encouraging results demonstrate the power and robustness of our automated methods for deriving new force fields. All parameters described here and the mdgx program used to fit them are included in the AmberTools16 distribution. PMID:27399642

Simplified contaminant source depletion models as analogs of multiphase simulators

NASA Astrophysics Data System (ADS)

Basu, Nandita B.; Fure, Adrian D.; Jawitz, James W.

2008-04-01

Four simplified dense non-aqueous phase liquid (DNAPL) source depletion models recently introduced in the literature are evaluated for the prediction of long-term effects of source depletion under natural gradient flow. These models are simple in form (a power function equation is an example) but are shown here to serve as mathematical analogs to complex multiphase flow and transport simulators. The spill and subsequent dissolution of DNAPLs was simulated in domains having different hydrologic characteristics (variance of the log conductivity field = 0.2, 1 and 3) using the multiphase flow and transport simulator UTCHEM. The dissolution profiles were fitted using four analytical models: the equilibrium streamtube model (ESM), the advection dispersion model (ADM), the power law model (PLM) and the Damkohler number model (DaM). All four models, though very different in their conceptualization, include two basic parameters that describe the mean DNAPL mass and the joint variability in the velocity and DNAPL distributions. The variability parameter was observed to be strongly correlated with the variance of the log conductivity field in the ESM and ADM but weakly correlated in the PLM and DaM. The DaM also includes a third parameter that describes the effect of rate-limited dissolution, but here this parameter was held constant as the numerical simulations were found to be insensitive to local-scale mass transfer. All four models were able to emulate the characteristics of the dissolution profiles generated from the complex numerical simulator, but the one-parameter PLM fits were the poorest, especially for the low heterogeneity case.

Simplified contaminant source depletion models as analogs of multiphase simulators.

PubMed

Basu, Nandita B; Fure, Adrian D; Jawitz, James W

2008-04-28

Four simplified dense non-aqueous phase liquid (DNAPL) source depletion models recently introduced in the literature are evaluated for the prediction of long-term effects of source depletion under natural gradient flow. These models are simple in form (a power function equation is an example) but are shown here to serve as mathematical analogs to complex multiphase flow and transport simulators. The spill and subsequent dissolution of DNAPLs was simulated in domains having different hydrologic characteristics (variance of the log conductivity field=0.2, 1 and 3) using the multiphase flow and transport simulator UTCHEM. The dissolution profiles were fitted using four analytical models: the equilibrium streamtube model (ESM), the advection dispersion model (ADM), the power law model (PLM) and the Damkohler number model (DaM). All four models, though very different in their conceptualization, include two basic parameters that describe the mean DNAPL mass and the joint variability in the velocity and DNAPL distributions. The variability parameter was observed to be strongly correlated with the variance of the log conductivity field in the ESM and ADM but weakly correlated in the PLM and DaM. The DaM also includes a third parameter that describes the effect of rate-limited dissolution, but here this parameter was held constant as the numerical simulations were found to be insensitive to local-scale mass transfer. All four models were able to emulate the characteristics of the dissolution profiles generated from the complex numerical simulator, but the one-parameter PLM fits were the poorest, especially for the low heterogeneity case.

Estimation of transversely isotropic material properties from magnetic resonance elastography using the optimised virtual fields method.

PubMed

Miller, Renee; Kolipaka, Arunark; Nash, Martyn P; Young, Alistair A

2018-03-12

Magnetic resonance elastography (MRE) has been used to estimate isotropic myocardial stiffness. However, anisotropic stiffness estimates may give insight into structural changes that occur in the myocardium as a result of pathologies such as diastolic heart failure. The virtual fields method (VFM) has been proposed for estimating material stiffness from image data. This study applied the optimised VFM to identify transversely isotropic material properties from both simulated harmonic displacements in a left ventricular (LV) model with a fibre field measured from histology as well as isotropic phantom MRE data. Two material model formulations were implemented, estimating either 3 or 5 material properties. The 3-parameter formulation writes the transversely isotropic constitutive relation in a way that dissociates the bulk modulus from other parameters. Accurate identification of transversely isotropic material properties in the LV model was shown to be dependent on the loading condition applied, amount of Gaussian noise in the signal, and frequency of excitation. Parameter sensitivity values showed that shear moduli are less sensitive to noise than the other parameters. This preliminary investigation showed the feasibility and limitations of using the VFM to identify transversely isotropic material properties from MRE images of a phantom as well as simulated harmonic displacements in an LV geometry. Copyright © 2018 John Wiley & Sons, Ltd.

The influence of atmospheric turbulence on partially coherent two-photon entangled field

NASA Astrophysics Data System (ADS)

Qiu, Y.; She, W.

2012-09-01

The propagation of a two-photon field from down-conversion of a partially coherent Gaussian Schell-model (GSM) pump beam in free space has been reported. However, the propagation of this two-photon field through a turbulent atmosphere has not been investigated yet. In this paper, an analytical expression of the coincidence count rate of the two-photon entangled field is derived. Unlike what has been reported, the field is from a parameter down-conversion of a partially coherent dark hollow pump beam and propagates through a turbulent atmosphere. The effects of the propagation parameters on the coincidence count rate are evaluated and illustrated. The results show that the pump beam parameters and atmospheric turbulence can evidently affect the detection probability of the photon pair at two different positions. It is found that the detection probability of the two-photon field is higher, and thus less susceptible to turbulence, if the field is produced by a lower mode of partially coherent pump beam.

Effect of dc field on ac-loss peak in a commercial Bi:2223/Ag tape

NASA Astrophysics Data System (ADS)

Öztürk, Ali; Düzgün, İbrahim; Çelebi, Selahattin

2017-12-01

Measurements of the ac susceptibility in a commercial Bi:2223/Ag tape for some different ac magnetic field amplitudes, Hac, in the presence of bias magnetic field Hdc directed along Hac are reported. It is found that the peak values of the imaginary component of ac susceptibility χ″max versus Hac trace a valley for the orientation where applied field Ha perpendicular to wide face of the tape total. We note that the observation of the valley depends on various parameters such as field dependence parameter n in the critical current density, in the simple power law expression jc = α(T)/Bn, choice of the bias field Hdc together with selected ac field amplitudes Hac, and dimension and geometry of sample studied. Our calculations based on critical state model with jc = α(1 - T/Tcm)p/Bn using the fitting parameters of n = 0.25, p = 2.2, Tcm = 108 K gives quite good results to compare the experimental and calculated curves.

Quantum Treatment of Two Coupled Oscillators in Interaction with a Two-Level Atom:

NASA Astrophysics Data System (ADS)

Khalil, E. M.; Abdalla, M. Sebawe; Obada, A. S.-F.

In this communication we handle a modified model representing the interaction between a two-level atom and two modes of the electromagnetic field in a cavity. The interaction between the modes is assumed to be of a parametric amplifier type. The model consists of two different systems, one represents the Jaynes-Cummings model (atom-field interaction) and the other represents the two mode parametric amplifier model (field-field interaction). After some canonical transformations the constants of the motion have been obtained and used to derive the time evolution operator. The wave function in the Schrödinger picture is constructed and employed to discuss some statistical properties related to the system. Further discussion related to the statistical properties of some physical quantities is given where we have taken into account an initial correlated pair-coherent state for the modes. We concentrate in our examination on the system behavior that occurred as a result of the variation of the parametric amplifier coupling parameter as well as the detuning parameter. It has been shown that the interaction of the parametric amplifier term increases the revival period and consequently longer period of strong interaction between the atom and the fields.

Fragmentation modeling of a resin bonded sand

NASA Astrophysics Data System (ADS)

Hilth, William; Ryckelynck, David

2017-06-01

Cemented sands exhibit a complex mechanical behavior that can lead to sophisticated models, with numerous parameters without real physical meaning. However, using a rather simple generalized critical state bonded soil model has proven to be a relevant compromise between an easy calibration and good results. The constitutive model formulation considers a non-associated elasto-plastic formulation within the critical state framework. The calibration procedure, using standard laboratory tests, is complemented by the study of an uniaxial compression test observed by tomography. Using finite elements simulations, this test is simulated considering a non-homogeneous 3D media. The tomography of compression sample gives access to 3D displacement fields by using image correlation techniques. Unfortunately these fields have missing experimental data because of the low resolution of correlations for low displacement magnitudes. We propose a recovery method that reconstructs 3D full displacement fields and 2D boundary displacement fields. These fields are mandatory for the calibration of the constitutive parameters by using 3D finite element simulations. The proposed recovery technique is based on a singular value decomposition of available experimental data. This calibration protocol enables an accurate prediction of the fragmentation of the specimen.

Vastly accelerated linear least-squares fitting with numerical optimization for dual-input delay-compensated quantitative liver perfusion mapping.

PubMed

Jafari, Ramin; Chhabra, Shalini; Prince, Martin R; Wang, Yi; Spincemaille, Pascal

2018-04-01

To propose an efficient algorithm to perform dual input compartment modeling for generating perfusion maps in the liver. We implemented whole field-of-view linear least squares (LLS) to fit a delay-compensated dual-input single-compartment model to very high temporal resolution (four frames per second) contrast-enhanced 3D liver data, to calculate kinetic parameter maps. Using simulated data and experimental data in healthy subjects and patients, whole-field LLS was compared with the conventional voxel-wise nonlinear least-squares (NLLS) approach in terms of accuracy, performance, and computation time. Simulations showed good agreement between LLS and NLLS for a range of kinetic parameters. The whole-field LLS method allowed generating liver perfusion maps approximately 160-fold faster than voxel-wise NLLS, while obtaining similar perfusion parameters. Delay-compensated dual-input liver perfusion analysis using whole-field LLS allows generating perfusion maps with a considerable speedup compared with conventional voxel-wise NLLS fitting. Magn Reson Med 79:2415-2421, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Two interacting current model of holographic Dirac fluid in graphene

NASA Astrophysics Data System (ADS)

Rogatko, Marek; Wysokinski, Karol I.

2018-02-01

The electrons in graphene for energies close to the Dirac point have been found to form strongly interacting fluid. Taking this fact into account we have extended previous work on the transport properties of graphene by taking into account possible interactions between the currents and adding the external magnetic field directed perpendicularly to the graphene sheet. The perpendicular magnetic field B severely modifies the transport parameters. In the present approach the quantization of the spectrum and formation of Landau levels is ignored. Gauge/gravity duality has been used in the probe limit. The dependence on the charge density of the Seebeck coefficient and thermoelectric parameters αi j nicely agree with recent experimental data for graphene. The holographic model allows for the interpretation of one of the fields representing the currents as resulting from the dark matter sector. For the studied geometry with electric field perpendicular to the thermal gradient the effect of the dark sector has been found to modify the transport parameters but mostly in a quantitative way only. This makes difficult the detection of this elusive component of the Universe by studying transport properties of graphene.

Exploring entropic uncertainty relation in the Heisenberg XX model with inhomogeneous magnetic field

NASA Astrophysics Data System (ADS)

Huang, Ai-Jun; Wang, Dong; Wang, Jia-Ming; Shi, Jia-Dong; Sun, Wen-Yang; Ye, Liu

2017-08-01

In this work, we investigate the quantum-memory-assisted entropic uncertainty relation in a two-qubit Heisenberg XX model with inhomogeneous magnetic field. It has been found that larger coupling strength J between the two spin-chain qubits can effectively reduce the entropic uncertainty. Besides, we observe the mechanics of how the inhomogeneous field influences the uncertainty, and find out that when the inhomogeneous field parameter b<1, the uncertainty will decrease with the decrease of the inhomogeneous field parameter b, conversely, the uncertainty will increase with decreasing b under the condition that b>1. Intriguingly, the entropic uncertainty can shrink to zero when the coupling coefficients are relatively large, while the entropic uncertainty only reduces to 1 with the increase of the homogeneous magnetic field. Additionally, we observe the purity of the state and Bell non-locality and obtain that the entropic uncertainty is anticorrelated with both the purity and Bell non-locality of the evolution state.

Magnetized string cosmological models of accelerated expansion of the Universe in f(R,T) theory of gravity

NASA Astrophysics Data System (ADS)

Pradhan, Anirudh; Jaiswal, Rekha

A class of spatially homogeneous and anisotropic Bianchi-V massive string models have been studied in the modified f(R,T)-theory of gravity proposed by Harko et al. [Phys. Rev. D 84:024020, 2011] in the presence of magnetic field. For a specific choice of f(R,T)=f1(R) + f2(T), where f1(R) = ν1R and f2(T) = ν2T; ν1, ν2 being arbitrary parameters, solutions of modified gravity field equations have been generated. To find the deterministic solution of the field equations, we have considered the time varying deceleration parameter which is consistent with observational data of standard cosmology (SNIa, BAO and CMB). As a result to study the transit behavior of Universe, we consider a law of variation for the specifically chosen scale factor, which yields a time-dependent deceleration parameter comprising a class of models that depicts a transition of the Universe from the early decelerated phase to the recent accelerating phase. In this context, for the model of the Universe, the field equations are solved and corresponding cosmological aspects have been discussed. The Energy conditions in this modified gravity theory are also studied. Stability analysis of the solutions through cosmological perturbation is performed and it is concluded that the expanding solution is stable against the perturbation with respect to anisotropic spatial direction. Some physical and geometric properties of the models are also discussed.

{gamma} parameter and Solar System constraint in chameleon-Brans-Dicke theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saaidi, Kh.; Mohammadi, A.; Sheikhahmadi, H.

2011-05-15

The post Newtonian parameter is considered in the chameleon-Brans-Dicke model. In the first step, the general form of this parameter and also effective gravitational constant is obtained. An arbitrary function for f({Phi}), which indicates the coupling between matter and scalar field, is introduced to investigate validity of solar system constraint. It is shown that the chameleon-Brans-Dicke model can satisfy the solar system constraint and gives us an {omega} parameter of order 10{sup 4}, which is in comparable to the constraint which has been indicated in [19].

A review of the meteorological parameters which affect aerial application

NASA Technical Reports Server (NTRS)

Christensen, L. S.; Frost, W.

1979-01-01

The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

DOE PAGES

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.; ...

2012-05-01

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Dynamics of Mount Somma-Vesuvius edifice: from stress field inversion to analogue and numerical modelling

NASA Astrophysics Data System (ADS)

De Matteo, Ada; Massa, Bruno; D'Auria, Luca; Castaldo, Raffaele

2017-04-01

Geological processes are generally very complex and too slow to be directly observed in their completeness; modelling procedures overcome this limit. The state of stress in the upper lithosphere is the main responsible for driving geodynamical processes; in order to retrieve the active stress field in a rock volume, stress inversion techniques can be applied on both seismological and structural datasets. This approach has been successfully applied to active tectonics as well as volcanic areas. In this context the best approach in managing heterogeneous datasets in volcanic environments consists in the analysis of spatial variations of the stress field by applying robust techniques of inversion. The study of volcanic seismicity is an efficient tool to retrieve spatial and temporal pattern of the pre-, syn- and inter-eruptive stress field: magma migration as well as dynamics of magma chamber and hydrothermal system are directly connected to the volcanic seismicity. Additionally, analysis of the temporal variations of stress field pattern in volcanoes could be a useful monitoring tool. Recently the stress field acting on several active volcanoes has been investigated by using stress inversion techniques on seismological datasets (Massa et al., 2016). The Bayesian Right Trihedra Method (BRTM; D'Auria and Massa, 2015) is able to successfully manage heterogeneous datasets allowing the identification of regional fields locally overcame by the stress field due to volcano specific dynamics. In particular, the analysis of seismicity and stress field inversion at the Somma-Vesuvius highlighted the presence of two superposed volumes characterized by different behaviour and stress field pattern: a top volume dominated by an extensional stress field, in accordance with a gravitational spreading-style of deformation, and a bottom volume related to a regional extensional stress field. In addition, in order to evaluate the dynamics of deformation, both analogue and numerical modelling are being performed. Scaled analogue models of the Somma-Vesuvius are being built accordingly with the actual geometrical asymmetry of the volcano, varying just few parameters connected to the uncertainty of the depth and thickness of a buried decoupling layer. Experiments are being monitored by an optical stereo image system, useful to build a 3D time-lapsed models used to retrieve the model deformations. Simultaneously, a time-dependent 3D Finite Element model is being carried out in a fluid-dynamic context by fixing the same parameters of the proposed analogue model. Finally, a comparative analysis is being made between the model deformations and the DInSAR measurements derived from satellite data in order to estimate the uncertain parameters (i.e., thickness and viscosity of ductile layer). Preliminary results of the analogue models fit with the hypothesis of a spreading deformation active at the Somma-Vesuvius.

Modes of self-organization of diluted bubbly liquids in acoustic fields: One-dimensional theory.

PubMed

Gumerov, Nail A; Akhatov, Iskander S

2017-02-01

The paper is dedicated to mathematical modeling of self-organization of bubbly liquids in acoustic fields. A continuum model describing the two-way interaction of diluted polydisperse bubbly liquids and acoustic fields in weakly-nonlinear approximation is studied analytically and numerically in the one-dimensional case. It is shown that the regimes of self-organization of monodisperse bubbly liquids can be controlled by only a few dimensionless parameters. Two basic modes, clustering and propagating shock waves of void fraction (acoustically induced transparency), are identified and criteria for their realization in the space of parameters are proposed. A numerical method for solving of one-dimensional self-organization problems is developed. Computational results for mono- and polydisperse systems are discussed.

Tilted Kantowski-Sachs cosmological model in Brans-Dicke theory of gravitation

NASA Astrophysics Data System (ADS)

Pawar, D. D.; Shahare, S. P.; Dagwal, V. J.

2018-02-01

Tilted Kantowski-Sachs cosmological model in Brans-Dicke theory for perfect fluid has been investigated. The general solution of field equations in Brans-Dicke theory for the combined scalar and tensor field are obtained by using power law relation. Also, some physical and geometrical parameters are obtained and discussed.

Statistical electric field and switching time distributions in PZT 1Nb2Sr ceramics: Crystal- and microstructure effects

NASA Astrophysics Data System (ADS)

Zhukov, Sergey; Kungl, Hans; Genenko, Yuri A.; von Seggern, Heinz

2014-01-01

Dispersive polarization response of ferroelectric PZT ceramics is analyzed assuming the inhomogeneous field mechanism of polarization switching. In terms of this model, the local polarization switching proceeds according to the Kolmogorov-Avrami-Ishibashi scenario with the switching time determined by the local electric field. As a result, the total polarization reversal is dominated by the statistical distribution of the local field magnitudes. Microscopic parameters of this model (the high-field switching time and the activation field) as well as the statistical field and consequent switching time distributions due to disorder at a mesoscopic scale can be directly determined from a set of experiments measuring the time dependence of the total polarization switching, when applying electric fields of different magnitudes. PZT 1Nb2Sr ceramics with Zr/Ti ratios 51.5/48.5, 52.25/47.75, and 60/40 with four different grain sizes each were analyzed following this approach. Pronounced differences of field and switching time distributions were found depending on the Zr/Ti ratios. Varying grain size also affects polarization reversal parameters, but in another way. The field distributions remain almost constant with grain size whereas switching times and activation field tend to decrease with increasing grain size. The quantitative changes of the latter parameters with grain size are very different depending on composition. The origin of the effects on the field and switching time distributions are related to differences in structural and microstructural characteristics of the materials and are discussed with respect to the hysteresis loops observed under bipolar electrical cycling.

Modeling of a pitching and plunging airfoil using experimental flow field and load measurements

NASA Astrophysics Data System (ADS)

Troshin, Victor; Seifert, Avraham

2018-01-01

The main goal of the current paper is to outline a low-order modeling procedure of a heaving airfoil in a still fluid using experimental measurements. Due to its relative simplicity, the proposed procedure is applicable for the analysis of flow fields within complex and unsteady geometries and it is suitable for analyzing the data obtained by experimentation. Currently, this procedure is used to model and predict the flow field evolution using a small number of low profile load sensors and flow field measurements. A time delay neural network is used to estimate the flow field. The neural network estimates the amplitudes of the most energetic modes using four sensory inputs. The modes are calculated using proper orthogonal decomposition of the flow field data obtained experimentally by time-resolved, phase-locked particle imaging velocimetry. To permit the use of proper orthogonal decomposition, the measured flow field is mapped onto a stationary domain using volume preserving transformation. The analysis performed by the model showed good estimation quality within the parameter range used in the training procedure. However, the performance deteriorates for cases out of this range. This situation indicates that, to improve the robustness of the model, both the decomposition and the training data sets must be diverse in terms of input parameter space. In addition, the results suggest that the property of volume preservation of the mapping does not affect the model quality as long as the model is not based on the Galerkin approximation. Thus, it may be relaxed for cases with more complex geometry and kinematics.

Quantifying model-structure- and parameter-driven uncertainties in spring wheat phenology prediction with Bayesian analysis

DOE PAGES

Alderman, Phillip D.; Stanfill, Bryan

2016-10-06

Recent international efforts have brought renewed emphasis on the comparison of different agricultural systems models. Thus far, analysis of model-ensemble simulated results has not clearly differentiated between ensemble prediction uncertainties due to model structural differences per se and those due to parameter value uncertainties. Additionally, despite increasing use of Bayesian parameter estimation approaches with field-scale crop models, inadequate attention has been given to the full posterior distributions for estimated parameters. The objectives of this study were to quantify the impact of parameter value uncertainty on prediction uncertainty for modeling spring wheat phenology using Bayesian analysis and to assess the relativemore » contributions of model-structure-driven and parameter-value-driven uncertainty to overall prediction uncertainty. This study used a random walk Metropolis algorithm to estimate parameters for 30 spring wheat genotypes using nine phenology models based on multi-location trial data for days to heading and days to maturity. Across all cases, parameter-driven uncertainty accounted for between 19 and 52% of predictive uncertainty, while model-structure-driven uncertainty accounted for between 12 and 64%. Here, this study demonstrated the importance of quantifying both model-structure- and parameter-value-driven uncertainty when assessing overall prediction uncertainty in modeling spring wheat phenology. More generally, Bayesian parameter estimation provided a useful framework for quantifying and analyzing sources of prediction uncertainty.« less

A sensitivity analysis of cloud properties to CLUBB parameters in the single-column Community Atmosphere Model (SCAM5)

DOE PAGES

Guo, Zhun; Wang, Minghuai; Qian, Yun; ...

2014-08-13

In this study, we investigate the sensitivity of simulated shallow cumulus and stratocumulus clouds to selected tunable parameters of Cloud Layers Unified by Binormals (CLUBB) in the single column version of Community Atmosphere Model version 5 (SCAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is adopted to study the responses of simulated cloud fields to tunable parameters. One stratocumulus and two shallow convection cases are configured at both coarse and fine vertical resolutions in this study.. Our results show that most of the variance in simulated cloudmore » fields can be explained by a small number of tunable parameters. The parameters related to Newtonian and buoyancy-damping terms of total water flux are found to be the most influential parameters for stratocumulus. For shallow cumulus, the most influential parameters are those related to skewness of vertical velocity, reflecting the strong coupling between cloud properties and dynamics in this regime. The influential parameters in the stratocumulus case are sensitive to the choice of the vertical resolution while little sensitivity is found for the shallow convection cases, as eddy mixing length (or dissipation time scale) plays a more important role and depends more strongly on the vertical resolution in stratocumulus than in shallow convections. The influential parameters remain almost unchanged when the number of tunable parameters increases from 16 to 35. This study improves understanding of the CLUBB behavior associated with parameter uncertainties.« less

Simulation of a Radio-Frequency Photogun for the Generation of Ultrashort Beams

NASA Astrophysics Data System (ADS)

Nikiforov, D. A.; Levichev, A. E.; Barnyakov, A. M.; Andrianov, A. V.; Samoilov, S. L.

2018-04-01

A radio-frequency photogun for the generation of ultrashort electron beams to be used in fast electron diffractoscopy, wakefield acceleration experiments, and the design of accelerating structures of the millimeter range is modeled. The beam parameters at the photogun output needed for each type of experiment are determined. The general outline of the photogun is given, its electrodynamic parameters are calculated, and the accelerating field distribution is obtained. The particle dynamics is analyzed in the context of the required output beam parameters. The optimal initial beam characteristics and field amplitudes are chosen. A conclusion is made regarding the obtained beam parameters.

A Generalized 2D-Dynamical Mean-Field Ising Model with a Rich Set of Bifurcations (Inspired and Applied to Financial Crises)

NASA Astrophysics Data System (ADS)

Smug, Damian; Sornette, Didier; Ashwin, Peter

We analyze an extended version of the dynamical mean-field Ising model. Instead of classical physical representation of spins and external magnetic field, the model describes traders' opinion dynamics. The external field is endogenized to represent a smoothed moving average of the past state variable. This model captures in a simple set-up the interplay between instantaneous social imitation and past trends in social coordinations. We show the existence of a rich set of bifurcations as a function of the two parameters quantifying the relative importance of instantaneous versus past social opinions on the formation of the next value of the state variable. Moreover, we present a thorough analysis of chaotic behavior, which is exhibited in certain parameter regimes. Finally, we examine several transitions through bifurcation curves and study how they could be understood as specific market scenarios. We find that the amplitude of the corrections needed to recover from a crisis and to push the system back to “normal” is often significantly larger than the strength of the causes that led to the crisis itself.

Field-sensitivity To Rheological Parameters

NASA Astrophysics Data System (ADS)

Freund, Jonathan; Ewoldt, Randy

2017-11-01

We ask this question: where in a flow is a quantity of interest Q quantitatively sensitive to the model parameters θ-> describing the rheology of the fluid? This field sensitivity is computed via the numerical solution of the adjoint flow equations, as developed to expose the target sensitivity δQ / δθ-> (x) via the constraint of satisfying the flow equations. Our primary example is a sphere settling in Carbopol, for which we have experimental data. For this Carreau-model configuration, we simultaneously calculate how much a local change in the fluid intrinsic time-scale λ, limit-viscosities ηo and η∞, and exponent n would affect the drag D. Such field sensitivities can show where different fluid physics in the model (time scales, elastic versus viscous components, etc.) are important for the target observable and generally guide model refinement based on predictive goals. In this case, the computational cost of solving the local sensitivity problem is negligible relative to the flow. The Carreau-fluid/sphere example is illustrative; the utility of field sensitivity is in the design and analysis of less intuitive flows, for which we provide some additional examples.

The Sensitivity of Parameter Estimates to the Latent Ability Distribution. Research Report. ETS RR-11-40

ERIC Educational Resources Information Center

Xu, Xueli; Jia, Yue

2011-01-01

Estimation of item response model parameters and ability distribution parameters has been, and will remain, an important topic in the educational testing field. Much research has been dedicated to addressing this task. Some studies have focused on item parameter estimation when the latent ability was assumed to follow a normal distribution,…

Tripartite entanglement dynamics and entropic squeezing of a three-level atom interacting with a bimodal cavity field

NASA Astrophysics Data System (ADS)

Faghihi, M. J.; Tavassoly, M. K.; Bagheri Harouni, M.

2014-04-01

In this paper, we study the interaction between a Λ-type three-level atom and two quantized electromagnetic fields which are simultaneously injected in a bichromatic cavity surrounded by a Kerr medium in the presence of field-field interaction (parametric down conversion) and detuning parameters. By applying a canonical transformation, the introduced model is reduced to a well-known form of the generalized Jaynes-Cummings model. Under particular initial conditions which may be prepared for the atom and the field, the time evolution of the state vector of the entire system is analytically evaluated. Then, the dynamics of the atom is studied through the evolution of the atomic population inversion. In addition, two different measures of entanglement between the tripartite system (three entities make the system: two field modes and one atom), i.e., von Neumann and linear entropy are investigated. Also, two kinds of entropic uncertainty relations, from which entropy squeezing can be obtained, are discussed. In each case, the influences of the detuning parameters and Kerr medium on the above nonclassicality features are analyzed in detail via numerical results. It is illustrated that the amount of the above-mentioned physical phenomena can be tuned by choosing the evolved parameters, appropriately.

Higher derivative extensions of 3 d Chern-Simons models: conservation laws and stability

NASA Astrophysics Data System (ADS)

Kaparulin, D. S.; Karataeva, I. Yu.; Lyakhovich, S. L.

2015-11-01

We consider the class of higher derivative 3 d vector field models with the field equation operator being a polynomial of the Chern-Simons operator. For the nth-order theory of this type, we provide a general recipe for constructing n-parameter family of conserved second rank tensors. The family includes the canonical energy-momentum tensor, which is unbounded, while there are bounded conserved tensors that provide classical stability of the system for certain combinations of the parameters in the Lagrangian. We also demonstrate the examples of consistent interactions which are compatible with the requirement of stability.

Machine Learning Force Field Parameters from Ab Initio Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ying; Li, Hui; Pickard, Frank C.

Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. The results were further improved by introducing an offset factor duringmore » the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.« less

Adiabatic model of field reversal by fast ions in an axisymmetric open trap

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsidulko, Yu. A., E-mail: tsidulko@mail.ru

2016-06-15

A model of field reversal by fast ions has been developed under the assumption of preservation of fast-ion adiabatic invariants. Analytical solutions obtained in the approximation of a narrow fast-ion layer and numerical solutions to the evolutionary problem are presented. The solutions demonstrate the process of formation of a field reversed configuration with parameters close to those of the planned experiment.

Reduction of optically observed artillery blast wave trajectories using low dimensionality models

NASA Astrophysics Data System (ADS)

Steward, Bryan J.; Gross, Kevin C.; Perram, Glen P.

2011-05-01

Muzzle blast trajectories from firings of a 152 mm caliber gun howitzer were obtained with high-speed optical imagers and used to assess the fidelity with which low dimensionality models can be used for data reduction. Characteristic flow regions were defined for the blast waves. The near-field region was estimated to extend to 0.98 - 1.25 meters from the muzzle and the far-field region was estimated to begin at 2.61 - 3.31 meters. Blast wave geometries and radial trajectories were collected in the near through far-fields with visible imagers operating at 1,600 Hz. Beyond the near-field the blast waves exhibited a near-spherical geometry in which the major axis of the blast lay along the axis of the gun barrel and measured within 95% of the minor axis. Several blast wave propagation models were applied to the mid and far-field data to determine their ability to reduce the blast wave trajectories to fewer parameters while retaining the ability to distinguish amongst three munitions configurations. A total of 147 firings were observed and used to assess within-configuration variability relative to separation between configurations. Results show that all models perform well, and drag and point blast model parameters additionally provide insight into phenomenology of the blast.

Scalar field propagation in the ϕ 4 κ-Minkowski model

NASA Astrophysics Data System (ADS)

Meljanac, S.; Samsarov, A.; Trampetić, J.; Wohlgenannt, M.

2011-12-01

In this article we use the noncommutative (NC) κ-Minkowski ϕ 4 model based on the κ-deformed star product, (★ h ). The action is modified by expanding up to linear order in the κ-deformation parameter a, producing an effective model on commutative spacetime. For the computation of the tadpole diagram contributions to the scalar field propagation/self-energy, we anticipate that statistics on the κ-Minkowski is specifically κ-deformed. Thus our prescription in fact represents hybrid approach between standard quantum field theory (QFT) and NCQFT on the κ-deformed Minkowski spacetime, resulting in a κ-effective model. The propagation is analyzed in the framework of the two-point Green's function for low, intermediate, and for the Planckian propagation energies, respectively. Semiclassical/hybrid behavior of the first order quantum correction do show up due to the κ-deformed momentum conservation law. For low energies, the dependence of the tadpole contribution on the deformation parameter a drops out completely, while for Planckian energies, it tends to a fixed finite value. The mass term of the scalar field is shifted and these shifts are very different at different propagation energies. At the Planck-ian energies we obtain the direction dependent κ-modified dispersion relations. Thus our κ-effective model for the massive scalar field shows a birefringence effect.

Thermodynamic properties for applications in chemical industry via classical force fields.

PubMed

Guevara-Carrion, Gabriela; Hasse, Hans; Vrabec, Jadran

2012-01-01

Thermodynamic properties of fluids are of key importance for the chemical industry. Presently, the fluid property models used in process design and optimization are mostly equations of state or G (E) models, which are parameterized using experimental data. Molecular modeling and simulation based on classical force fields is a promising alternative route, which in many cases reasonably complements the well established methods. This chapter gives an introduction to the state-of-the-art in this field regarding molecular models, simulation methods, and tools. Attention is given to the way modeling and simulation on the scale of molecular force fields interact with other scales, which is mainly by parameter inheritance. Parameters for molecular force fields are determined both bottom-up from quantum chemistry and top-down from experimental data. Commonly used functional forms for describing the intra- and intermolecular interactions are presented. Several approaches for ab initio to empirical force field parameterization are discussed. Some transferable force field families, which are frequently used in chemical engineering applications, are described. Furthermore, some examples of force fields that were parameterized for specific molecules are given. Molecular dynamics and Monte Carlo methods for the calculation of transport properties and vapor-liquid equilibria are introduced. Two case studies are presented. First, using liquid ammonia as an example, the capabilities of semi-empirical force fields, parameterized on the basis of quantum chemical information and experimental data, are discussed with respect to thermodynamic properties that are relevant for the chemical industry. Second, the ability of molecular simulation methods to describe accurately vapor-liquid equilibrium properties of binary mixtures containing CO(2) is shown.

Surrogate models for sheet metal stamping problem based on the combination of proper orthogonal decomposition and radial basis function

NASA Astrophysics Data System (ADS)

Dang, Van Tuan; Lafon, Pascal; Labergere, Carl

2017-10-01

In this work, a combination of Proper Orthogonal Decomposition (POD) and Radial Basis Function (RBF) is proposed to build a surrogate model based on the Benchmark Springback 3D bending from the Numisheet2011 congress. The influence of the two design parameters, the geometrical parameter of the die radius and the process parameter of the blank holder force, on the springback of the sheet after a stamping operation is analyzed. The classical Design of Experience (DoE) uses Full Factorial to design the parameter space with sample points as input data for finite element method (FEM) numerical simulation of the sheet metal stamping process. The basic idea is to consider the design parameters as additional dimensions for the solution of the displacement fields. The order of the resultant high-fidelity model is reduced through the use of POD method which performs model space reduction and results in the basis functions of the low order model. Specifically, the snapshot method is used in our work, in which the basis functions is derived from snapshot deviation of the matrix of the final displacements fields of the FEM numerical simulation. The obtained basis functions are then used to determine the POD coefficients and RBF is used for the interpolation of these POD coefficients over the parameter space. Finally, the presented POD-RBF approach which is used for shape optimization can be performed with high accuracy.

Electrostatics of cysteine residues in proteins: Parameterization and validation of a simple model

PubMed Central

Salsbury, Freddie R.; Poole, Leslie B.; Fetrow, Jacquelyn S.

2013-01-01

One of the most popular and simple models for the calculation of pKas from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pKas. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pKas; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pKas. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pKa values (where the calculation should reproduce the pKa within experimental error). Both the general behavior of cysteines in proteins and the perturbed pKa in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pKa should be shifted, and validation of force field parameters for cysteine residues. PMID:22777874

How CMB and large-scale structure constrain chameleon interacting dark energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boriero, Daniel; Das, Subinoy; Wong, Yvonne Y.Y., E-mail: boriero@physik.uni-bielefeld.de, E-mail: subinoy@iiap.res.in, E-mail: yvonne.y.wong@unsw.edu.au

2015-07-01

We explore a chameleon type of interacting dark matter-dark energy scenario in which a scalar field adiabatically traces the minimum of an effective potential sourced by the dark matter density. We discuss extensively the effect of this coupling on cosmological observables, especially the parameter degeneracies expected to arise between the model parameters and other cosmological parameters, and then test the model against observations of the cosmic microwave background (CMB) anisotropies and other cosmological probes. We find that the chameleon parameters α and β, which determine respectively the slope of the scalar field potential and the dark matter-dark energy coupling strength,more » can be constrained to α < 0.17 and β < 0.19 using CMB data and measurements of baryon acoustic oscillations. The latter parameter in particular is constrained only by the late Integrated Sachs-Wolfe effect. Adding measurements of the local Hubble expansion rate H{sub 0} tightens the bound on α by a factor of two, although this apparent improvement is arguably an artefact of the tension between the local measurement and the H{sub 0} value inferred from Planck data in the minimal ΛCDM model. The same argument also precludes chameleon models from mimicking a dark radiation component, despite a passing similarity between the two scenarios in that they both delay the epoch of matter-radiation equality. Based on the derived parameter constraints, we discuss possible signatures of the model for ongoing and future large-scale structure surveys.« less

Multi-focused microlens array optimization and light field imaging study based on Monte Carlo method.

PubMed

Li, Tian-Jiao; Li, Sai; Yuan, Yuan; Liu, Yu-Dong; Xu, Chuan-Long; Shuai, Yong; Tan, He-Ping

2017-04-03

Plenoptic cameras are used for capturing flames in studies of high-temperature phenomena. However, simulations of plenoptic camera models can be used prior to the experiment improve experimental efficiency and reduce cost. In this work, microlens arrays, which are based on the established light field camera model, are optimized into a hexagonal structure with three types of microlenses. With this improved plenoptic camera model, light field imaging of static objects and flame are simulated using the calibrated parameters of the Raytrix camera (R29). The optimized models improve the image resolution, imaging screen utilization, and shooting range of depth of field.

Unified Dark Matter scalar field models with fast transition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bertacca, Daniele; Bruni, Marco; Piattella, Oliver F.

2011-02-01

We investigate the general properties of Unified Dark Matter (UDM) scalar field models with Lagrangians with a non-canonical kinetic term, looking specifically for models that can produce a fast transition between an early Einstein-de Sitter CDM-like era and a later Dark Energy like phase, similarly to the barotropic fluid UDM models in JCAP01(2010)014. However, while the background evolution can be very similar in the two cases, the perturbations are naturally adiabatic in fluid models, while in the scalar field case they are necessarily non-adiabatic. The new approach to building UDM Lagrangians proposed here allows to escape the common problem ofmore » the fine-tuning of the parameters which plague many UDM models. We analyse the properties of perturbations in our model, focusing on the the evolution of the effective speed of sound and that of the Jeans length. With this insight, we can set theoretical constraints on the parameters of the model, predicting sufficient conditions for the model to be viable. An interesting feature of our models is that what can be interpreted as w{sub DE} can be < −1 without violating the null energy conditions.« less

[Tasseled cap triangle (TCT)-leaf area index (LAI)model of rice fields based on PROSAIL model and its application].

PubMed

Li, Ya Ni; Lu, Lei; Liu, Yong

2017-12-01

The tasseled cap triangle (TCT)-leaf area index (LAI) isoline is a model that reflects the distribution of LAI isoline in the spectral space constituted by reflectance of red and near-infrared (NIR) bands, and the LAI retrieval model developed on the basis of this is more accurate than the commonly used statistical relationship models. This study used ground-based measurements of the rice field, validated the applicability of PROSAIL model in simulating canopy reflectance of rice field, and calibrated the input parameters of the model. The ranges of values of PROSAIL input parameters for simulating rice canopy reflectance were determined. Based on this, the TCT-LAI isoline model of rice field was established, and a look-up table (LUT) required in remote sensing retrieval of LAI was developed. Then, the LUT was used for Landsat 8 and WorldView 3 data to retrieve LAI of rice field, respectively. The results showed that the LAI retrieved using the LUT developed from TCT-LAI isoline model had a good linear relationship with the measured LAI R 2 =0.76, RMSE=0.47. Compared with the LAI retrieved from Landsat 8, LAI values retrieved from WorldView 3 va-ried with wider range, and data distribution was more scattered. Resampling the Landsat 8 and WorldView 3 reflectance data to 1 km to retrieve LAI, the result of MODIS LAI product was significantly underestimated compared to that of retrieved LAI.

[Simulation on remediation of benzene contaminated groundwater by air sparging].

PubMed

Fan, Yan-Ling; Jiang, Lin; Zhang, Dan; Zhong, Mao-Sheng; Jia, Xiao-Yang

2012-11-01

Air sparging (AS) is one of the in situ remedial technologies which are used in groundwater remediation for pollutions with volatile organic compounds (VOCs). At present, the field design of air sparging system was mainly based on experience due to the lack of field data. In order to obtain rational design parameters, the TMVOC module in the Petrasim software package, combined with field test results on a coking plant in Beijing, is used to optimize the design parameters and simulate the remediation process. The pilot test showed that the optimal injection rate was 23.2 m3 x h(-1), while the optimal radius of influence (ROI) was 5 m. The simulation results revealed that the pressure response simulated by the model matched well with the field test results, which indicated a good representation of the simulation. The optimization results indicated that the optimal injection location was at the bottom of the aquifer. Furthermore, simulated at the optimized injection location, the optimal injection rate was 20 m3 x h(-1), which was in accordance with the field test result. Besides, 3 m was the optimal ROI, less than the field test results, and the main reason was that field test reflected the flow behavior at the upper space of groundwater and unsaturated area, in which the width of flow increased rapidly, and became bigger than the actual one. With the above optimized operation parameters, in addition to the hydro-geological parameters measured on site, the model simulation result revealed that 90 days were needed to remediate the benzene from 371 000 microg x L(-1) to 1 microg x L(-1) for the site, and that the opeation model in which the injection wells were progressively turned off once the groundwater around them was "clean" was better than the one in which all the wells were kept operating throughout the remediation process.

Critical Behavior of Spatial Evolutionary Game with Altruistic to Spiteful Preferences on Two-Dimensional Lattices

NASA Astrophysics Data System (ADS)

Yang, Bo; Li, Xiao-Teng; Chen, Wei; Liu, Jian; Chen, Xiao-Song

2016-10-01

Self-questioning mechanism which is similar to single spin-flip of Ising model in statistical physics is introduced into spatial evolutionary game model. We propose a game model with altruistic to spiteful preferences via weighted sums of own and opponent's payoffs. This game model can be transformed into Ising model with an external field. Both interaction between spins and the external field are determined by the elements of payoff matrix and the preference parameter. In the case of perfect rationality at zero social temperature, this game model has three different phases which are entirely cooperative phase, entirely non-cooperative phase and mixed phase. In the investigations of the game model with Monte Carlo simulation, two paths of payoff and preference parameters are taken. In one path, the system undergoes a discontinuous transition from cooperative phase to non-cooperative phase with the change of preference parameter. In another path, two continuous transitions appear one after another when system changes from cooperative phase to non-cooperative phase with the prefenrence parameter. The critical exponents v, β, and γ of two continuous phase transitions are estimated by the finite-size scaling analysis. Both continuous phase transitions have the same critical exponents and they belong to the same universality class as the two-dimensional Ising model. Supported by the National Natural Science Foundation of China under Grant Nos. 11121403 and 11504384

Gravitational particle creation in a stiff matter dominated universe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lankinen, Juho; Vilja, Iiro, E-mail: jumila@utu.fi, E-mail: vilja@utu.fi

A scenario for gravitational particle creation in a stiff matter dominated flat Friedmann-Robertson-Walker universe is presented. The primary creation of scalar particles is calculated using quantum field theory in curved spacetime and it is found to be strongly dependent on the scalar mass and the expansion parameter of the universe. The particle creation is most effective for a very massive scalar field and large expansion parameter. We demonstrate the phenomenon by applying it to cosmological toy model scenario, where secondary particles are created by the scalar field decay.

Gravitational particle creation in a stiff matter dominated universe

NASA Astrophysics Data System (ADS)

Lankinen, Juho; Vilja, Iiro

2017-08-01

A scenario for gravitational particle creation in a stiff matter dominated flat Friedmann-Robertson-Walker universe is presented. The primary creation of scalar particles is calculated using quantum field theory in curved spacetime and it is found to be strongly dependent on the scalar mass and the expansion parameter of the universe. The particle creation is most effective for a very massive scalar field and large expansion parameter. We demonstrate the phenomenon by applying it to cosmological toy model scenario, where secondary particles are created by the scalar field decay.

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling

NASA Astrophysics Data System (ADS)

Florian Wellmann, J.; Thiele, Sam T.; Lindsay, Mark D.; Jessell, Mark W.

2016-03-01

We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilize the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling

NASA Astrophysics Data System (ADS)

Wellmann, J. F.; Thiele, S. T.; Lindsay, M. D.; Jessell, M. W.

2015-11-01

We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilise the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a~link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential-fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

Very low scale Coleman-Weinberg inflation with nonminimal coupling

NASA Astrophysics Data System (ADS)

Kaneta, Kunio; Seto, Osamu; Takahashi, Ryo

2018-03-01

We study viable small-field Coleman-Weinberg (CW) inflation models with the help of nonminimal coupling to gravity. The simplest small-field CW inflation model (with a low-scale potential minimum) is incompatible with the cosmological constraint on the scalar spectral index. However, there are possibilities to make the model realistic. First, we revisit the CW inflation model supplemented with a linear potential term. We next consider the CW inflation model with a logarithmic nonminimal coupling and illustrate that the model can open a new viable parameter space that includes the model with a linear potential term. We also show parameter spaces where the Hubble scale during the inflation can be as small as 10-4 GeV , 1 GeV, 1 04 GeV , and 1 08 GeV for the number of e -folds of 40, 45, 50, and 55, respectively, with other cosmological constraints being satisfied.

Nanosecond electric modification of order parameters

NASA Astrophysics Data System (ADS)

Borshch, Volodymyr

In this Dissertation, we study a nanosecond electro-optic response of a nematic liquid crystal in a geometry where an applied electric field E modifies the tensor order parameter but does not change the orientation of the optic axis (director N̂). We use nematics with negative dielectric anisotropy with the electric field applied perpendicularly to N̂. The field changes the dielectric tensor at optical frequencies (optic tensor), due to the following mechanisms: (a) nanosecond creation of biaxial orientational order; (b) uniaxial modification of the orientational order that occurs over the timescales of tens of nanoseconds, and (c) quenching of director fluctuations with a wide range of characteristic times up to milliseconds. We develop a model to describe the dynamics of all three mechanisms. We design the experimental conditions to selectively suppress the contributions from the quenching of director fluctuations (c) and from the biaxial order effect (a) and thus, separate the contributions of the three mechanisms in the electro-optic response. As a result, the experimental data can be well fitted with the model parameters. The analysis provides a rather detailed physical picture of how the liquid crystal responds to a strong electric field, E ˜ 108 V/m, on a timescale of nanoseconds. This work provides a useful guide in the current search of the biaxial nematic phase. Namely, the temperature dependence of the biaxial susceptibility allows one to estimate the temperature of the potential uniaxial-to-biaxial phase transition. An analysis of the quenching of director fluctuations indicates that on a timescale of nanoseconds, the classic model with constant viscoelastic material parameters might reach its limit of validity. The effect of nanosecond electric modification of the order parameter (NEMOP) can be used in applications in which one needs to achieve ultrafast (nanosecond) changes of optical characteristics, such as birefringence.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE PAGES

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

Soil warming response: field experiments to Earth system models

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Bradford, M.; Wieder, W. R.; Crowther, T. W.

2017-12-01

The soil carbon response to climate change is extremely uncertain at the global scale, in part because of the uncertainty in the magnitude of the temperature response. To address this uncertainty we collected data from 48 soil warming manipulations studies and examined the temperature response using two different methods. First, we constructed a mixed effects model and extrapolated the effect of soil warming on soil carbon stocks under anticipated shifts in surface temperature during the 21st century. We saw significant vulnerability of soil carbon stocks, especially in high carbon soils. To place this effect in the context of anticipated changes in carbon inputs and moisture shifts, we applied a one pool decay model with temperature sensitivities to the field data and imposed a post-hoc correction on the Earth system model simulations to integrate the field with the simulated temperature response. We found that there was a slight elevation in the overall soil carbon losses, but that the field uncertainty of the temperature sensitivity parameter was as large as the variation in the among model soil carbon projections. This implies that model-data integration is unlikely to constrain soil carbon simulations and highlights the importance of representing parameter uncertainty in these Earth system models to inform emissions targets.

Bayesian methods for characterizing unknown parameters of material models

DOE PAGES

Emery, J. M.; Grigoriu, M. D.; Field Jr., R. V.

2016-02-04

A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). As a result, the Bayesian method is also employed tomore » characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.« less

Bayesian methods for characterizing unknown parameters of material models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emery, J. M.; Grigoriu, M. D.; Field Jr., R. V.

A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). As a result, the Bayesian method is also employed tomore » characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.« less

Agent-Based Multicellular Modeling for Predictive Toxicology

EPA Science Inventory

Biological modeling is a rapidly growing field that has benefited significantly from recent technological advances, expanding traditional methods with greater computing power, parameter-determination algorithms, and the development of novel computational approaches to modeling bi...

A gridded global description of the ionosphere and thermosphere for 1996 - 2000

NASA Astrophysics Data System (ADS)

Ridley, A.; Kihn, E.; Kroehl, H.

The modeling and simulation community has asked for a realistic representation of the near-Earth space environment covering a significant number of years to be used in scientific and engineering applications. The data, data management systems, assimilation techniques, physical models, and computer resources are now available to construct a realistic description of the ionosphere and thermosphere over a 5 year period. DMSP and NOAA POES satellite data and solar emissions were used to compute Hall and Pederson conductances in the ionosphere. Interplanetary magnetic field measurements on the ACE satellite define average electrostatic potential patterns over the northern and southern Polar Regions. These conductances, electric field patterns, and ground-based magnetometer data were input to the Assimilative Mapping of Ionospheric Electrodynamics model to compute the distribution of electric fields and currents in the ionosphere. The Global Thermosphere Ionosphere Model (GITM) used the ionospheric electrodynamic parameters to compute the distribution of particles and fields in the ionosphere and thermosphere. GITM uses a general circulation approach to solve the fundamental equations. Model results offer a unique opportunity to assess the relative importance of different forcing terms under a variety of conditions as well as the accuracies of different estimates of ionospheric electrodynamic parameters.

FDTD Modeling of LEMP Propagation in the Earth-Ionosphere Waveguide With Emphasis on Realistic Representation of Lightning Source

NASA Astrophysics Data System (ADS)

Tran, Thang H.; Baba, Yoshihiro; Somu, Vijaya B.; Rakov, Vladimir A.

2017-12-01

The finite difference time domain (FDTD) method in the 2-D cylindrical coordinate system was used to compute the nearly full-frequency-bandwidth vertical electric field and azimuthal magnetic field waveforms produced on the ground surface by lightning return strokes. The lightning source was represented by the modified transmission-line model with linear current decay with height, which was implemented in the FDTD computations as an appropriate vertical phased-current-source array. The conductivity of atmosphere was assumed to increase exponentially with height, with different conductivity profiles being used for daytime and nighttime conditions. The fields were computed at distances ranging from 50 to 500 km. Sky waves (reflections from the ionosphere) were identified in computed waveforms and used for estimation of apparent ionospheric reflection heights. It was found that our model reproduces reasonably well the daytime electric field waveforms measured at different distances and simulated (using a more sophisticated propagation model) by Qin et al. (2017). Sensitivity of model predictions to changes in the parameters of atmospheric conductivity profile, as well as influences of the lightning source characteristics (current waveshape parameters, return-stroke speed, and channel length) and ground conductivity were examined.

A Gibbs point field model for the spatial pattern of coronary capillaries

NASA Astrophysics Data System (ADS)

Karch, R.; Neumann, M.; Neumann, F.; Ullrich, R.; Neumüller, J.; Schreiner, W.

2006-09-01

We propose a Gibbs point field model for the pattern of coronary capillaries in transverse histologic sections from human hearts, based on the physiology of oxygen supply from capillaries to tissue. To specify the potential energy function of the Gibbs point field, we draw on an analogy between the equation of steady-state oxygen diffusion from an array of parallel capillaries to the surrounding tissue and Poisson's equation for the electrostatic potential of a two-dimensional distribution of identical point charges. The influence of factors other than diffusion is treated as a thermal disturbance. On this basis, we arrive at the well-known two-dimensional one-component plasma, a system of identical point charges exhibiting a weak (logarithmic) repulsive interaction that is completely characterized by a single dimensionless parameter. By variation of this parameter, the model is able to reproduce many characteristics of real capillary patterns.

Dense motion estimation using regularization constraints on local parametric models.

PubMed

Patras, Ioannis; Worring, Marcel; van den Boomgaard, Rein

2004-11-01

This paper presents a method for dense optical flow estimation in which the motion field within patches that result from an initial intensity segmentation is parametrized with models of different order. We propose a novel formulation which introduces regularization constraints between the model parameters of neighboring patches. In this way, we provide the additional constraints for very small patches and for patches whose intensity variation cannot sufficiently constrain the estimation of their motion parameters. In order to preserve motion discontinuities, we use robust functions as a regularization mean. We adopt a three-frame approach and control the balance between the backward and forward constraints by a real-valued direction field on which regularization constraints are applied. An iterative deterministic relaxation method is employed in order to solve the corresponding optimization problem. Experimental results show that the proposed method deals successfully with motions large in magnitude, motion discontinuities, and produces accurate piecewise-smooth motion fields.

Effects of magnetic, radiation and chemical reaction on unsteady heat and mass transfer flow of an oscillating cylinder

NASA Astrophysics Data System (ADS)

Ahmed, Rubel; Rana, B. M. Jewel; Ahmmed, S. F.

2017-06-01

The effects of magnetic, radiation and chemical reaction parameters on the unsteady heat and mass transfer boundary layer flow past an oscillating cylinder is considered. The dimensionless momentum, energy and concentration equations are solved numerically by using explicit finite difference method with the help of a computer programming language Compaq visual FORTRAN 6.6a. The obtained results of this study have been discussed for different values of well-known parameters with different time steps. The effect of these parameters on the velocity field, temperature field and concentration field, skin-friction, Nusselt number, streamlines and isotherms has been studied and results are presented by graphically represented by the tabular form quantitatively. The stability and convergence analysis of the solution parameters that have been used in the mathematical model have been tested.

Uncertainty quantification of overpressure buildup through inverse modeling of compaction processes in sedimentary basins

NASA Astrophysics Data System (ADS)

Colombo, Ivo; Porta, Giovanni M.; Ruffo, Paolo; Guadagnini, Alberto

2017-03-01

This study illustrates a procedure conducive to a preliminary risk analysis of overpressure development in sedimentary basins characterized by alternating depositional events of sandstone and shale layers. The approach rests on two key elements: (1) forward modeling of fluid flow and compaction, and (2) application of a model-complexity reduction technique based on a generalized polynomial chaos expansion (gPCE). The forward model considers a one-dimensional vertical compaction processes. The gPCE model is then used in an inverse modeling context to obtain efficient model parameter estimation and uncertainty quantification. The methodology is applied to two field settings considered in previous literature works, i.e. the Venture Field (Scotian Shelf, Canada) and the Navarin Basin (Bering Sea, Alaska, USA), relying on available porosity and pressure information for model calibration. It is found that the best result is obtained when porosity and pressure data are considered jointly in the model calibration procedure. Uncertainty propagation from unknown input parameters to model outputs, such as pore pressure vertical distribution, is investigated and quantified. This modeling strategy enables one to quantify the relative importance of key phenomena governing the feedback between sediment compaction and fluid flow processes and driving the buildup of fluid overpressure in stratified sedimentary basins characterized by the presence of low-permeability layers. The results here illustrated (1) allow for diagnosis of the critical role played by the parameters of quantitative formulations linking porosity and permeability in compacted shales and (2) provide an explicit and detailed quantification of the effects of their uncertainty in field settings.

BANYAN. IV. Fundamental parameters of low-mass star candidates in nearby young stellar kinematic groups—isochronal age determination using magnetic evolutionary models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malo, Lison; Doyon, René; Albert, Loïc

2014-09-01

Based on high-resolution optical spectra obtained with ESPaDOnS at Canada-France-Hawaii Telescope, we determine fundamental parameters (T {sub eff}, R, L {sub bol}, log g, and metallicity) for 59 candidate members of nearby young kinematic groups. The candidates were identified through the BANYAN Bayesian inference method of Malo et al., which takes into account the position, proper motion, magnitude, color, radial velocity, and parallax (when available) to establish a membership probability. The derived parameters are compared to Dartmouth magnetic evolutionary models and field stars with the goal of constraining the age of our candidates. We find that, in general, low-mass starsmore » in our sample are more luminous and have inflated radii compared to older stars, a trend expected for pre-main-sequence stars. The Dartmouth magnetic evolutionary models show a good fit to observations of field K and M stars, assuming a magnetic field strength of a few kG, as typically observed for cool stars. Using the low-mass members of the β Pictoris moving group, we have re-examined the age inconsistency problem between lithium depletion age and isochronal age (Hertzspring-Russell diagram). We find that the inclusion of the magnetic field in evolutionary models increases the isochronal age estimates for the K5V-M5V stars. Using these models and field strengths, we derive an average isochronal age between 15 and 28 Myr and we confirm a clear lithium depletion boundary from which an age of 26 ± 3 Myr is derived, consistent with previous age estimates based on this method.« less

Study on superconducting state parameters of Cu1-xZrx metallic glasses using model potentials

NASA Astrophysics Data System (ADS)

Jambusarwala, Tasneem S.; Gajjar, P. N.

2018-05-01

The superconducting state parameters (SSP) of Cu1-xZrx metallic glasses over the full range of concentration x of Zr have been investigated to study influence of various local pseudopotentials. The study includes the computation of electron-phonon coupling strength (λ), transition temperature (TC), isotope effect exponent (α) and effective interaction strength (N0V) using fourteen different forms of local model potentials. The local field correction function proposed by Taylor (T) is used. The influence of model potential on various parameters is ranging from 6% to 83% for pure Zr and 28% to 84% for pure Cu. The present study confirms that the identification of model potential is vital in studying Superconducting State Parameters.

Method for Predicting and Optimizing System Parameters for Electrospinning System

NASA Technical Reports Server (NTRS)

Wincheski, Russell A. (Inventor)

2011-01-01

An electrospinning system using a spinneret and a counter electrode is first operated for a fixed amount of time at known system and operational parameters to generate a fiber mat having a measured fiber mat width associated therewith. Next, acceleration of the fiberizable material at the spinneret is modeled to determine values of mass, drag, and surface tension associated with the fiberizable material at the spinneret output. The model is then applied in an inversion process to generate predicted values of an electric charge at the spinneret output and an electric field between the spinneret and electrode required to fabricate a selected fiber mat design. The electric charge and electric field are indicative of design values for system and operational parameters needed to fabricate the selected fiber mat design.

Simultaneous estimation of local-scale and flow path-scale dual-domain mass transfer parameters using geoelectrical monitoring

USGS Publications Warehouse

Briggs, Martin A.; Day-Lewis, Frederick D.; Ong, John B.; Curtis, Gary P.; Lane, John W.

2013-01-01

Anomalous solute transport, modeled as rate-limited mass transfer, has an observable geoelectrical signature that can be exploited to infer the controlling parameters. Previous experiments indicate the combination of time-lapse geoelectrical and fluid conductivity measurements collected during ionic tracer experiments provides valuable insight into the exchange of solute between mobile and immobile porosity. Here, we use geoelectrical measurements to monitor tracer experiments at a former uranium mill tailings site in Naturita, Colorado. We use nonlinear regression to calibrate dual-domain mass transfer solute-transport models to field data. This method differs from previous approaches by calibrating the model simultaneously to observed fluid conductivity and geoelectrical tracer signals using two parameter scales: effective parameters for the flow path upgradient of the monitoring point and the parameters local to the monitoring point. We use regression statistics to rigorously evaluate the information content and sensitivity of fluid conductivity and geophysical data, demonstrating multiple scales of mass transfer parameters can simultaneously be estimated. Our results show, for the first time, field-scale spatial variability of mass transfer parameters (i.e., exchange-rate coefficient, porosity) between local and upgradient effective parameters; hence our approach provides insight into spatial variability and scaling behavior. Additional synthetic modeling is used to evaluate the scope of applicability of our approach, indicating greater range than earlier work using temporal moments and a Lagrangian-based Damköhler number. The introduced Eulerian-based Damköhler is useful for estimating tracer injection duration needed to evaluate mass transfer exchange rates that range over several orders of magnitude.

Predicting pneumonitis risk: a dosimetric alternative to mean lung dose.

PubMed

Tucker, Susan L; Mohan, Radhe; Liengsawangwong, Raweewan; Martel, Mary K; Liao, Zhongxing

2013-02-01

To determine whether the association between mean lung dose (MLD) and risk of severe (grade ≥3) radiation pneumonitis (RP) depends on the dose distribution pattern to normal lung among patients receiving 3-dimensional conformal radiation therapy for non-small-cell lung cancer. Three cohorts treated with different beam arrangements were identified. One cohort (2-field boost [2FB]) received 2 parallel-opposed (anteroposterior-posteroanterior) fields per fraction initially, followed by a sequential boost delivered using 2 oblique beams. The other 2 cohorts received 3 or 4 straight fields (3FS and 4FS, respectively), ie, all fields were irradiated every day. The incidence of severe RP was plotted against MLD in each cohort, and data were analyzed using the Lyman-Kutcher-Burman (LKB) model. The incidence of grade ≥3 RP rose more steeply as a function of MLD in the 2FB cohort (N=120) than in the 4FS cohort (N=138), with an intermediate slope for the 3FS group (N=99). The estimated volume parameter from the LKB model was n=0.41 (95% confidence interval, 0.15-1.0) and led to a significant improvement in fit (P=.05) compared to a fit with volume parameter fixed at n=1 (the MLD model). Unlike the MLD model, the LKB model with n=0.41 provided a consistent description of the risk of severe RP in all three cohorts (2FB, 3FS, 4FS) simultaneously. When predicting risk of grade ≥3 RP, the mean lung dose does not adequately take into account the effects of high doses. Instead, the effective dose, computed from the LKB model using volume parameter n=0.41, may provide a better dosimetric parameter for predicting RP risk. If confirmed, these findings support the conclusion that for the same MLD, high doses to small lung volumes ("a lot to a little") are worse than low doses to large volumes ("a little to a lot"). Copyright © 2013 Elsevier Inc. All rights reserved.

Mathematical modeling of heat treatment processes conserving biological activity of plant bioresources

NASA Astrophysics Data System (ADS)

Rodionova, N. S.; Popov, E. S.; Pozhidaeva, E. A.; Pynzar, S. S.; Ryaskina, L. O.

2018-05-01

The aim of this study is to develop a mathematical model of the heat exchange process of LT-processing to estimate the dynamics of temperature field changes and optimize the regime parameters, due to the non-stationarity process, the physicochemical and thermophysical properties of food systems. The application of LT-processing, based on the use of low-temperature modes in thermal culinary processing of raw materials with preliminary vacuum packaging in a polymer heat- resistant film is a promising trend in the development of technics and technology in the catering field. LT-processing application of food raw materials guarantees the preservation of biologically active substances in food environments, which are characterized by a certain thermolability, as well as extend the shelf life and high consumer characteristics of food systems that are capillary-porous bodies. When performing the mathematical modeling of the LT-processing process, the packet of symbolic mathematics “Maple” was used, as well as the mathematical packet flexPDE that uses the finite element method for modeling objects with distributed parameters. The processing of experimental results was evaluated with the help of the developed software in the programming language Python 3.4. To calculate and optimize the parameters of the LT processing process of polycomponent food systems, the differential equation of non-stationary thermal conductivity was used, the solution of which makes it possible to identify the temperature change at any point of the solid at different moments. The present study specifies data on the thermophysical characteristics of the polycomponent food system based on plant raw materials, with the help of which the physico-mathematical model of the LT- processing process has been developed. The obtained mathematical model allows defining of the dynamics of the temperature field in different sections of the LT-processed polycomponent food systems on the basis of calculating the evolution profiles of temperature fields, which enable one to analyze the efficiency of the regime parameters of heat treatment.

Assessing the pollution risk of a groundwater source field at western Laizhou Bay under seawater intrusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Xiankui; Wu, Jichun; Wang, Dong, E-mail: wangdong@nju.edu.cn

Coastal areas have great significance for human living, economy and society development in the world. With the rapid increase of pressures from human activities and climate change, the safety of groundwater resource is under the threat of seawater intrusion in coastal areas. The area of Laizhou Bay is one of the most serious seawater intruded areas in China, since seawater intrusion phenomenon was firstly recognized in the middle of 1970s. This study assessed the pollution risk of a groundwater source filed of western Laizhou Bay area by inferring the probability distribution of groundwater Cl{sup −} concentration. The numerical model ofmore » seawater intrusion process is built by using SEAWAT4. The parameter uncertainty of this model is evaluated by Markov Chain Monte Carlo (MCMC) simulation, and DREAM{sub (ZS)} is used as sampling algorithm. Then, the predictive distribution of Cl{sup -} concentration at groundwater source field is inferred by using the samples of model parameters obtained from MCMC. After that, the pollution risk of groundwater source filed is assessed by the predictive quantiles of Cl{sup -} concentration. The results of model calibration and verification demonstrate that the DREAM{sub (ZS)} based MCMC is efficient and reliable to estimate model parameters under current observation. Under the condition of 95% confidence level, the groundwater source point will not be polluted by seawater intrusion in future five years (2015–2019). In addition, the 2.5% and 97.5% predictive quantiles show that the Cl{sup −} concentration of groundwater source field always vary between 175 mg/l and 200 mg/l. - Highlights: • The parameter uncertainty of seawater intrusion model is evaluated by MCMC. • Groundwater source field won’t be polluted by seawater intrusion in future 5 years. • The pollution risk is assessed by the predictive quantiles of Cl{sup −} concentration.« less

Numerical Investigation of Plasma Detachment in Magnetic Nozzle Experiments

NASA Technical Reports Server (NTRS)

Sankaran, Kamesh; Polzin, Kurt A.

2008-01-01

At present there exists no generally accepted theoretical model that provides a consistent physical explanation of plasma detachment from an externally-imposed magnetic nozzle. To make progress towards that end, simulation of plasma flow in the magnetic nozzle of an arcjet experiment is performed using a multidimensional numerical simulation tool that includes theoretical models of the various dispersive and dissipative processes present in the plasma. This is an extension of the simulation tool employed in previous work by Sankaran et al. The aim is to compare the computational results with various proposed magnetic nozzle detachment theories to develop an understanding of the physical mechanisms that cause detachment. An applied magnetic field topology is obtained using a magnetostatic field solver (see Fig. I), and this field is superimposed on the time-dependent magnetic field induced in the plasma to provide a self-consistent field description. The applied magnetic field and model geometry match those found in experiments by Kuriki and Okada. This geometry is modeled because there is a substantial amount of experimental data that can be compared to the computational results, allowing for validation of the model. In addition, comparison of the simulation results with the experimentally obtained plasma parameters will provide insight into the mechanisms that lead to plasma detachment, revealing how they scale with different input parameters. Further studies will focus on modeling literature experiments both for the purpose of additional code validation and to extract physical insight regarding the mechanisms driving detachment.

A statistical-based approach for acoustic tomography of the atmosphere.

PubMed

Kolouri, Soheil; Azimi-Sadjadi, Mahmood R; Ziemann, Astrid

2014-01-01

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter unscented Kalman filter (UKF) which is capable of reconstructing and tracking, in time, temperature, and wind velocity fields (state variables) as well as the dynamic model parameters within a specified investigation area. An adaptive 3-D spatial-temporal autoregressive model is used to capture the state evolution in the UKF. The observations used in the dual state-parameter UKF process consist of the acoustic time of arrivals measured for every pair of transmitter/receiver nodes deployed in the investigation area. The proposed method is then applied to the data set collected at the Meteorological Observatory Lindenberg, Germany, as part of the STINHO experiment, and the reconstruction results are presented.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields.

PubMed

Jahandideh, Samad; Abdolmaleki, Parviz; Movahedi, Mohammad Mehdi

2010-02-01

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes. (c) 2009 Wiley-Liss, Inc.

Effect of external fields in Axelrod's model of social dynamics

NASA Astrophysics Data System (ADS)

Peres, Lucas R.; Fontanari, José F.

2012-09-01

The study of the effects of spatially uniform fields on the steady-state properties of Axelrod's model has yielded plenty of counterintuitive results. Here, we reexamine the impact of this type of field for a selection of parameters such that the field-free steady state of the model is heterogeneous or multicultural. Analyses of both one- and two-dimensional versions of Axelrod's model indicate that the steady state remains heterogeneous regardless of the value of the field strength. Turning on the field leads to a discontinuous decrease on the number of cultural domains, which we argue is due to the instability of zero-field heterogeneous absorbing configurations. We find, however, that spatially nonuniform fields that implement a consensus rule among the neighborhood of the agents enforce homogenization. Although the overall effects of the fields are essentially the same irrespective of the dimensionality of the model, we argue that the dimensionality has a significant impact on the stability of the field-free homogeneous steady state.

Disordered λ φ4+ρ φ6 Landau-Ginzburg model

NASA Astrophysics Data System (ADS)

Diaz, R. Acosta; Svaiter, N. F.; Krein, G.; Zarro, C. A. D.

2018-03-01

We discuss a disordered λ φ4+ρ φ6 Landau-Ginzburg model defined in a d -dimensional space. First we adopt the standard procedure of averaging the disorder-dependent free energy of the model. The dominant contribution to this quantity is represented by a series of the replica partition functions of the system. Next, using the replica-symmetry ansatz in the saddle-point equations, we prove that the average free energy represents a system with multiple ground states with different order parameters. For low temperatures we show the presence of metastable equilibrium states for some replica fields for a range of values of the physical parameters. Finally, going beyond the mean-field approximation, the one-loop renormalization of this model is performed, in the leading-order replica partition function.

Tensor non-Gaussianity from axion-gauge-fields dynamics: parameter search

NASA Astrophysics Data System (ADS)

Agrawal, Aniket; Fujita, Tomohiro; Komatsu, Eiichiro

2018-06-01

We calculate the bispectrum of scale-invariant tensor modes sourced by spectator SU(2) gauge fields during inflation in a model containing a scalar inflaton, a pseudoscalar axion and SU(2) gauge fields. A large bispectrum is generated in this model at tree-level as the gauge fields contain a tensor degree of freedom, and its production is dominated by self-coupling of the gauge fields. This is a unique feature of non-Abelian gauge theory. The shape of the tensor bispectrum is approximately an equilateral shape for 3lesssim mQlesssim 4, where mQ is an effective dimensionless mass of the SU(2) field normalised by the Hubble expansion rate during inflation. The amplitude of non-Gaussianity of the tensor modes, characterised by the ratio Bh/P2h, is inversely proportional to the energy density fraction of the gauge field. This ratio can be much greater than unity, whereas the ratio from the vacuum fluctuation of the metric is of order unity. The bispectrum is effective at constraining large mQ regions of the parameter space, whereas the power spectrum constrains small mQ regions.

A Comprehensive Model of the Near-Earth Magnetic Field. Phase 3

NASA Technical Reports Server (NTRS)

Sabaka, Terence J.; Olsen, Nils; Langel, Robert A.

2000-01-01

The near-Earth magnetic field is due to sources in Earth's core, ionosphere, magnetosphere, lithosphere, and from coupling currents between ionosphere and magnetosphere and between hemispheres. Traditionally, the main field (low degree internal field) and magnetospheric field have been modeled simultaneously, and fields from other sources modeled separately. Such a scheme, however, can introduce spurious features. A new model, designated CMP3 (Comprehensive Model: Phase 3), has been derived from quiet-time Magsat and POGO satellite measurements and observatory hourly and annual means measurements as part of an effort to coestimate fields from all of these sources. This model represents a significant advancement in the treatment of the aforementioned field sources over previous attempts, and includes an accounting for main field influences on the magnetosphere, main field and solar activity influences on the ionosphere, seasonal influences on the coupling currents, a priori characterization of ionospheric and magnetospheric influence on Earth-induced fields, and an explicit parameterization and estimation of the lithospheric field. The result of this effort is a model whose fits to the data are generally superior to previous models and whose parameter states for the various constituent sources are very reasonable.

Kinklike structures in models of the Dirac-Born-Infeld type

NASA Astrophysics Data System (ADS)

Bazeia, D.; Lima, Elisama E. M.; Losano, L.

2018-01-01

The present work investigates several models of a single real scalar field, engendering kinetic term of the Dirac-Born- Infeld type. Such theories introduce nonlinearities to the kinetic part of the Lagrangian, which presents a square root restricting the field evolution and including additional powers in derivatives of the scalar field, controlled by a real parameter. In order to obtain topological solutions analytically, we propose a first-order framework that simplifies the equation of motion ensuring solutions that are linearly stable. This is implemented using the deformation method, and we introduce examples presenting two categories of potentials, one having polynomial interactions and the other with nonpolynomial interactions. We also explore how the Dirac-Born-Infeld kinetic term affects the properties of the solutions. In particular, we note that the kinklike solutions are similar to the ones obtained through models with standard kinetic term and canonical potential, but their energy densities and stability potentials vary according to the parameter introduced to control the new models.

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J. D.

2017-09-01

Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

No Future in the Past? The role of initial topography on landform evolution model predictions

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Coulthard, T. J.; Lowry, J.

2014-12-01

Our understanding of earth surface processes is based on long-term empirical understandings, short-term field measurements as well as numerical models. In particular, numerical landscape evolution models (LEMs) have been developed which have the capability to capture a range of both surface (erosion and deposition), tectonics, as well as near surface or critical zone processes (i.e. pedogenesis). These models have a range of applications for understanding both surface and whole of landscape dynamics through to more applied situations such as degraded site rehabilitation. LEMs are now at the stage of development where if calibrated, can provide some level of reliability. However, these models are largely calibrated based on parameters determined from present surface conditions which are the product of much longer-term geology-soil-climate-vegetation interactions. Here, we assess the effect of the initial landscape dimensions and associated error as well as parameterisation for a potential post-mining landform design. The results demonstrate that subtle surface changes in the initial DEM as well as parameterisation can have a large impact on landscape behaviour, erosion depth and sediment discharge. For example, the predicted sediment output from LEM's is shown to be highly variable even with very subtle changes in initial surface conditions. This has two important implications in that decadal time scale field data is needed to (a) better parameterise models and (b) evaluate their predictions. We question how a LEM using parameters derived from field plots can firstly be employed to examine long-term landscape evolution. Secondly, the potential range of outcomes is examined based on estimated temporal parameter change and thirdly, the need for more detailed and rigorous field data for calibration and validation of these models is discussed.

Perennial rhizomatous grasses as bioenergy feedstock in SWAT: parameter development and model improvement

DOE PAGES

Trybula, Elizabeth M.; Cibin, Raj; Burks, Jennifer L.; ...

2014-06-13

The Soil and Water Assessment Tool (SWAT) is increasingly used to quantify hydrologic and water quality impacts of bioenergy production, but crop-growth parameters for candidate perennial rhizomatous grasses (PRG) Miscanthus × giganteus and upland ecotypes of Panicum virgatum (switchgrass) are limited by the availability of field data. Crop-growth parameter ranges and suggested values were developed in this study using agronomic and weather data collected at the Purdue University Water Quality Field Station in northwestern Indiana. During the process of parameterization, the comparison of measured data with conceptual representation of PRG growth in the model led to three changes in themore » SWAT 2009 code: the harvest algorithm was modified to maintain belowground biomass over winter, plant respiration was extended via modified-DLAI to better reflect maturity and leaf senescence, and nutrient uptake algorithms were revised to respond to temperature, water, and nutrient stress. Parameter values and changes to the model resulted in simulated biomass yield and leaf area index consistent with reported values for the region. Code changes in the SWAT model improved nutrient storage during dormancy period and nitrogen and phosphorus uptake by both switchgrass and Miscanthus.« less

Effects of anisotropies in turbulent magnetic diffusion in mean-field solar dynamo models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pipin, V. V.; Kosovichev, A. G.

2014-04-10

We study how anisotropies of turbulent diffusion affect the evolution of large-scale magnetic fields and the dynamo process on the Sun. The effect of anisotropy is calculated in a mean-field magnetohydrodynamics framework assuming that triple correlations provide relaxation to the turbulent electromotive force (so-called the 'minimal τ-approximation'). We examine two types of mean-field dynamo models: the well-known benchmark flux-transport model and a distributed-dynamo model with a subsurface rotational shear layer. For both models, we investigate effects of the double- and triple-cell meridional circulation, recently suggested by helioseismology and numerical simulations. To characterize the anisotropy effects, we introduce a parameter ofmore » anisotropy as a ratio of the radial and horizontal intensities of turbulent mixing. It is found that the anisotropy affects the distribution of magnetic fields inside the convection zone. The concentration of the magnetic flux near the bottom and top boundaries of the convection zone is greater when the anisotropy is stronger. It is shown that the critical dynamo number and the dynamo period approach to constant values for large values of the anisotropy parameter. The anisotropy reduces the overlap of toroidal magnetic fields generated in subsequent dynamo cycles, in the time-latitude 'butterfly' diagram. If we assume that sunspots are formed in the vicinity of the subsurface shear layer, then the distributed dynamo model with the anisotropic diffusivity satisfies the observational constraints from helioseismology and is consistent with the value of effective turbulent diffusion estimated from the dynamics of surface magnetic fields.« less

Actuator model of electrostrictive polymers (EPs) for microactuators

NASA Astrophysics Data System (ADS)

Kim, Hunmo; Oh, Sinjong; Hwang, Kyoil; Choi, Hyoukryeol; Jeon, Jaewook; Nam, Jaedo

2001-07-01

Recently, Electrostrictive polymers (EPs) are studied for micro-actuator, because of similarity of body tissue. Electrostrictive polymers (EPs) are based on the deformation of dielectric elastomer polymer in the presence of an electric field. Modeling of electrostrictive polymer has been studied, which is about voltage and displacement. And there are many parameters such as Young's modulus, voltage, thickness of EPs, pre-strain, dielectric, frequency and temperature which effect to movement of EPs. To do exact modeling, all parameters are included. In order to use as actuator, we accurately understood about the parameter that we refer above. And we have to execute modeling which parameters are considered. We used FEM in order to understand effects of parameters. Specially, because of pre-strain effects are very important, we derive the relations of stress and strain by using elastic strain energy.

Detecting seasonal variations of soil parameters via field measurements and stochastic simulations in the hillslope

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun

2015-04-01

Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.

CHARMM Drude Polarizable Force Field for Aldopentofuranoses and Methyl-aldopentofuranosides

PubMed Central

Jana, Madhurima; MacKerell, Alexander D.

2015-01-01

An empirical all-atom CHARMM polarizable force filed for aldopentofuranoses and methyl-aldopentofuranosides based on the classical Drude oscillator is presented. A single electrostatic model is developed for eight different diastereoisomers of aldopentofuranoses by optimizing the existing electrostatic and bonded parameters as transferred from ethers, alcohols and hexopyranoses to reproduce quantum mechanical (QM) dipole moments, furanose-water interaction energies and conformational energies. Optimization of selected electrostatic and dihedral parameters was performed to generate a model for methyl-aldopentofuranosides. Accuracy of the model was tested by reproducing experimental data for crystal intramolecular geometries and lattice unit cell parameters, aqueous phase densities, and ring pucker and exocyclic rotamer populations as obtained from NMR experiments. In most cases the model is found to reproduce both QM data and experimental observables in an excellent manner, while for the remainder the level of agreement is in the satisfactory regimen. In aqueous phase simulations the monosaccharides have significantly enhanced dipoles as compared to the gas phase. The final model from this study is transferrable for future studies on carbohydrates and can be used with the existing CHARMM Drude polarizable force field for biomolecules. PMID:26018564

Sensitivity analysis and calibration of a dynamic physically based slope stability model

NASA Astrophysics Data System (ADS)

Zieher, Thomas; Rutzinger, Martin; Schneider-Muntau, Barbara; Perzl, Frank; Leidinger, David; Formayer, Herbert; Geitner, Clemens

2017-06-01

Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that precipitation intensities during the investigated landslide-triggering rainfall events were already close to or above the soil's infiltration capacity.

An empirical model for prediction of geomagnetic storms using initially observed CME parameters at the Sun

NASA Astrophysics Data System (ADS)

Kim, R.-S.; Cho, K.-S.; Moon, Y.-J.; Dryer, M.; Lee, J.; Yi, Y.; Kim, K.-H.; Wang, H.; Park, Y.-D.; Kim, Yong Ha

2010-12-01

In this study, we discuss the general behaviors of geomagnetic storm strength associated with observed parameters of coronal mass ejection (CME) such as speed (V) and earthward direction (D) of CMEs as well as the longitude (L) and magnetic field orientation (M) of overlaying potential fields of the CME source region, and we develop an empirical model to predict geomagnetic storm occurrence with its strength (gauged by the Dst index) in terms of these CME parameters. For this we select 66 halo or partial halo CMEs associated with M-class and X-class solar flares, which have clearly identifiable source regions, from 1997 to 2003. After examining how each of these CME parameters correlates with the geoeffectiveness of the CMEs, we find several properties as follows: (1) Parameter D best correlates with storm strength Dst; (2) the majority of geoeffective CMEs have been originated from solar longitude 15°W, and CMEs originated away from this longitude tend to produce weaker storms; (3) correlations between Dst and the CME parameters improve if CMEs are separated into two groups depending on whether their magnetic fields are oriented southward or northward in their source regions. Based on these observations, we present two empirical expressions for Dst in terms of L, V, and D for two groups of CMEs, respectively. This is a new attempt to predict not only the occurrence of geomagnetic storms, but also the storm strength (Dst) solely based on the CME parameters.

3-D ballistic transport of ellipsoidal volcanic projectiles considering horizontal wind field and variable shape-dependent drag coefficients

NASA Astrophysics Data System (ADS)

Bertin, Daniel

2017-02-01

An innovative 3-D numerical model for the dynamics of volcanic ballistic projectiles is presented here. The model focuses on ellipsoidal particles and improves previous approaches by considering horizontal wind field, virtual mass forces, and drag forces subjected to variable shape-dependent drag coefficients. Modeling suggests that the projectile's launch velocity and ejection angle are first-order parameters influencing ballistic trajectories. The projectile's density and minor radius are second-order factors, whereas both intermediate and major radii of the projectile are of third order. Comparing output parameters, assuming different input data, highlights the importance of considering a horizontal wind field and variable shape-dependent drag coefficients in ballistic modeling, which suggests that they should be included in every ballistic model. On the other hand, virtual mass forces should be discarded since they almost do not contribute to ballistic trajectories. Simulation results were used to constrain some crucial input parameters (launch velocity, ejection angle, wind speed, and wind azimuth) of the block that formed the biggest and most distal ballistic impact crater during the 1984-1993 eruptive cycle of Lascar volcano, Northern Chile. Subsequently, up to 106 simulations were performed, whereas nine ejection parameters were defined by a Latin-hypercube sampling approach. Simulation results were summarized as a quantitative probabilistic hazard map for ballistic projectiles. Transects were also done in order to depict aerial hazard zones based on the same probabilistic procedure. Both maps combined can be used as a hazard prevention tool for ground and aerial transits nearby unresting volcanoes.

First and Higher Order Effects on Zero Order Radiative Transfer Model

NASA Astrophysics Data System (ADS)

Neelam, M.; Mohanty, B.

2014-12-01

Microwave radiative transfer model are valuable tool in understanding the complex land surface interactions. Past literature has largely focused on local sensitivity analysis for factor priotization and ignoring the interactions between the variables and uncertainties around them. Since land surface interactions are largely nonlinear, there always exist uncertainties, heterogeneities and interactions thus it is important to quantify them to draw accurate conclusions. In this effort, we used global sensitivity analysis to address the issues of variable uncertainty, higher order interactions, factor priotization and factor fixing for zero-order radiative transfer (ZRT) model. With the to-be-launched Soil Moisture Active Passive (SMAP) mission of NASA, it is very important to have a complete understanding of ZRT for soil moisture retrieval to direct future research and cal/val field campaigns. This is a first attempt to use GSA technique to quantify first order and higher order effects on brightness temperature from ZRT model. Our analyses reflect conditions observed during the growing agricultural season for corn and soybeans in two different regions in - Iowa, U.S.A and Winnipeg, Canada. We found that for corn fields in Iowa, there exist significant second order interactions between soil moisture, surface roughness parameters (RMS height and correlation length) and vegetation parameters (vegetation water content, structure and scattering albedo), whereas in Winnipeg, second order interactions are mainly due to soil moisture and vegetation parameters. But for soybean fields in both Iowa and Winnipeg, we found significant interactions only to exist between soil moisture and surface roughness parameters.

A model for polar cap electric fields

NASA Technical Reports Server (NTRS)

Dangelo, N.

1976-01-01

A model is proposed relating polar cap ionospheric electric fields to the parameters of the solar wind near the orbit of the earth. The model ignores the notion of field line merging. An essential feature is the role played by velocity shear instabilities in regions of the outer magnetosphere, in which mapping of the magnetosheath electric field would produce sunward convection. The anomalous resistivity which arises from velocity shear turbulence, suffices to essentially disconnect the magnetosphere from the magnetosheath, at any place where that resistivity is large enough. The magnetosheath-magnetosphere system, as a consequence, acts as a kind of diode or rectifier for the magnetosheath electric fields. Predictions of the model are compared with several observations related to polar cap convection.

Optimum data weighting and error calibration for estimation of gravitational parameters

NASA Technical Reports Server (NTRS)

Lerch, F. J.

1989-01-01

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 (Goddard Earth Model, 36x36 spherical harmonic field) were employed toward application of this technique for gravity field parameters. Also, GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized here. The method employs subset solutions of the data associated with the complete solution and uses an algorithm to adjust the data weights by requiring the differences of parameters between solutions to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting as compared to the nominal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

ff14ipq: A Self-Consistent Force Field for Condensed-Phase Simulations of Proteins

PubMed Central

2015-01-01

We present the ff14ipq force field, implementing the previously published IPolQ charge set for simulations of complete proteins. Minor modifications to the charge derivation scheme and van der Waals interactions between polar atoms are introduced. Torsion parameters are developed through a generational learning approach, based on gas-phase MP2/cc-pVTZ single-point energies computed of structures optimized by the force field itself rather than the quantum benchmark. In this manner, we sacrifice information about the true quantum minima in order to ensure that the force field maintains optimal agreement with the MP2/cc-pVTZ benchmark for the ensembles it will actually produce in simulations. A means of making the gas-phase torsion parameters compatible with solution-phase IPolQ charges is presented. The ff14ipq model is an alternative to ff99SB and other Amber force fields for protein simulations in programs that accommodate pair-specific Lennard–Jones combining rules. The force field gives strong performance on α-helical and β-sheet oligopeptides as well as globular proteins over microsecond time scale simulations, although it has not yet been tested in conjunction with lipid and nucleic acid models. We show how our choices in parameter development influence the resulting force field and how other choices that may have appeared reasonable would actually have led to poorer results. The tools we developed may also aid in the development of future fixed-charge and even polarizable biomolecular force fields. PMID:25328495

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Protein labeling reactions in electrochemical microchannel flow: Numerical simulation and uncertainty propagation

NASA Astrophysics Data System (ADS)

Debusschere, Bert J.; Najm, Habib N.; Matta, Alain; Knio, Omar M.; Ghanem, Roger G.; Le Maître, Olivier P.

2003-08-01

This paper presents a model for two-dimensional electrochemical microchannel flow including the propagation of uncertainty from model parameters to the simulation results. For a detailed representation of electroosmotic and pressure-driven microchannel flow, the model considers the coupled momentum, species transport, and electrostatic field equations, including variable zeta potential. The chemistry model accounts for pH-dependent protein labeling reactions as well as detailed buffer electrochemistry in a mixed finite-rate/equilibrium formulation. Uncertainty from the model parameters and boundary conditions is propagated to the model predictions using a pseudo-spectral stochastic formulation with polynomial chaos (PC) representations for parameters and field quantities. Using a Galerkin approach, the governing equations are reformulated into equations for the coefficients in the PC expansion. The implementation of the physical model with the stochastic uncertainty propagation is applied to protein-labeling in a homogeneous buffer, as well as in two-dimensional electrochemical microchannel flow. The results for the two-dimensional channel show strong distortion of sample profiles due to ion movement and consequent buffer disturbances. The uncertainty in these results is dominated by the uncertainty in the applied voltage across the channel.

Static shape control for flexible structures

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

A Monte Carlo investigation of contaminant electrons due to a novel in vivo transmission detector.

PubMed

Asuni, G; Jensen, J M; McCurdy, B M C

2011-02-21

A novel transmission detector (IBA Dosimetry, Germany) developed as an IMRT quality assurance tool, intended for in vivo patient dose measurements, is studied here. The goal of this investigation is to use Monte Carlo techniques to characterize treatment beam parameters in the presence of the detector and to compare to those of a plastic block tray (a frequently used clinical device). Particular attention is paid to the impact of the detector on electron contamination model parameters of two commercial dose calculation algorithms. The linac head together with the COMPASS transmission detector (TRD) was modeled using BEAMnrc code. To understand the effect of the TRD on treatment beams, the contaminant electron fluence, energy spectra, and angular distributions at different SSDs were analyzed for open and non-open (i.e. TRD and block tray) fields. Contaminant electrons in the BEAMnrc simulations were separated according to where they were created. Calculation of surface dose and the evaluation of contributions from contaminant electrons were performed using the DOSXYZnrc user code. The effect of the TRD on contaminant electrons model parameters in Eclipse AAA and Pinnacle(3) dose calculation algorithms was investigated. Comparisons of the fluence of contaminant electrons produced in the non-open fields versus open field show that electrons created in the non-open fields increase at shorter SSD, but most of the electrons at shorter SSD are of low energy with large angular spread. These electrons are out-scattered or absorbed in air and contribute less to surface dose at larger SSD. Calculated surface doses with the block tray are higher than those with the TRD. Contribution of contaminant electrons to dose in the buildup region increases with increasing field size. The additional contribution of electrons to surface dose increases with field size for TRD and block tray. The introduction of the TRD results in a 12% and 15% increase in the Gaussian widths used in the contaminant electron source model of the Eclipse AAA dose algorithm. The off-axis coefficient in the Pinnacle(3) dose calculation algorithm decreases in the presence of TRD compared to without the device. The electron model parameters were modified to reflect the increase in electron contamination with the TRD, a necessary step for accurate beam modeling when using the device.

Simulations of Cold Electroweak Baryogenesis: quench from portal coupling to new singlet field

NASA Astrophysics Data System (ADS)

Mou, Zong-Gang; Saffin, Paul M.; Tranberg, Anders

2018-01-01

We compute the baryon asymmetry generated from Cold Electroweak Baryogenesis, when a dynamical Beyond-the-Standard-Model scalar singlet field triggers the spinodal transition. Using a simple potential for this additional field, we match the speed of the quench to earlier simulations with a "by-hand" mass flip. We find that for the parameter subspace most similar to a by-hand transition, the final baryon asymmetry shows a similar dependence on quench time and is of the same magnitude. For more general parameter choices the Higgs-singlet dynamics can be very complicated, resulting in an enhancement of the final baryon asymmetry. Our results validate and generalise results of simulations in the literature and open up the Cold Electroweak Baryogenesis scenario to further model building.

Stochastic modelling of non-stationary financial assets

NASA Astrophysics Data System (ADS)

Estevens, Joana; Rocha, Paulo; Boto, João P.; Lind, Pedro G.

2017-11-01

We model non-stationary volume-price distributions with a log-normal distribution and collect the time series of its two parameters. The time series of the two parameters are shown to be stationary and Markov-like and consequently can be modelled with Langevin equations, which are derived directly from their series of values. Having the evolution equations of the log-normal parameters, we reconstruct the statistics of the first moments of volume-price distributions which fit well the empirical data. Finally, the proposed framework is general enough to study other non-stationary stochastic variables in other research fields, namely, biology, medicine, and geology.

NONLINEAR OPTICAL EFFECTS AND FIBER OPTICS: Theory of four-wave mixing in photorefractive media when the response of a medium is nonlinear in respect of the modulation parameter

NASA Astrophysics Data System (ADS)

Zozulya, A. A.

1988-12-01

A theoretical model is constructed for four-wave mixing in a photorefractive crystal where a transmission grating is formed by the drift-diffusion nonlinearity mechanism in the absence of an external electrostatic field and the response of the medium is nonlinear in respect of the modulation parameter. A comparison is made with a model in which the response of the medium is linear in respect of the modulation parameter. Theoretical models of four-wave and two-wave mixing are also compared with experiments.

Separation of variables in anisotropic models: anisotropic Rabi and elliptic Gaudin model in an external magnetic field

NASA Astrophysics Data System (ADS)

Skrypnyk, T.

2017-08-01

We study the problem of separation of variables for classical integrable Hamiltonian systems governed by non-skew-symmetric non-dynamical so(3)\\otimes so(3) -valued elliptic r-matrices with spectral parameters. We consider several examples of such models, and perform separation of variables for classical anisotropic one- and two-spin Gaudin-type models in an external magnetic field, and for Jaynes-Cummings-Dicke-type models without the rotating wave approximation.

Crack problem in superconducting cylinder with exponential distribution of critical-current density

NASA Astrophysics Data System (ADS)

Zhao, Yufeng; Xu, Chi; Shi, Liang

2018-04-01

The general problem of a center crack in a long cylindrical superconductor with inhomogeneous critical-current distribution is studied based on the extended Bean model for zero-field cooling (ZFC) and field cooling (FC) magnetization processes, in which the inhomogeneous parameter η is introduced for characterizing the critical-current density distribution in inhomogeneous superconductor. The effect of the inhomogeneous parameter η on both the magnetic field distribution and the variations of the normalized stress intensity factors is also obtained based on the plane strain approach and J-integral theory. The numerical results indicate that the exponential distribution of critical-current density will lead a larger trapped field inside the inhomogeneous superconductor and cause the center of the cylinder to fracture more easily. In addition, it is worth pointing out that the nonlinear field distribution is unique to the Bean model by comparing the curve shapes of the magnetization loop with homogeneous and inhomogeneous critical-current distribution.

Box-Cox Mixed Logit Model for Travel Behavior Analysis

NASA Astrophysics Data System (ADS)

Orro, Alfonso; Novales, Margarita; Benitez, Francisco G.

2010-09-01

To represent the behavior of travelers when they are deciding how they are going to get to their destination, discrete choice models, based on the random utility theory, have become one of the most widely used tools. The field in which these models were developed was halfway between econometrics and transport engineering, although the latter now constitutes one of their principal areas of application. In the transport field, they have mainly been applied to mode choice, but also to the selection of destination, route, and other important decisions such as the vehicle ownership. In usual practice, the most frequently employed discrete choice models implement a fixed coefficient utility function that is linear in the parameters. The principal aim of this paper is to present the viability of specifying utility functions with random coefficients that are nonlinear in the parameters, in applications of discrete choice models to transport. Nonlinear specifications in the parameters were present in discrete choice theory at its outset, although they have seldom been used in practice until recently. The specification of random coefficients, however, began with the probit and the hedonic models in the 1970s, and, after a period of apparent little practical interest, has burgeoned into a field of intense activity in recent years with the new generation of mixed logit models. In this communication, we present a Box-Cox mixed logit model, original of the authors. It includes the estimation of the Box-Cox exponents in addition to the parameters of the random coefficients distribution. Probability of choose an alternative is an integral that will be calculated by simulation. The estimation of the model is carried out by maximizing the simulated log-likelihood of a sample of observed individual choices between alternatives. The differences between the predictions yielded by models that are inconsistent with real behavior have been studied with simulation experiments.

Force Field Development and Molecular Dynamics of [NiFe] Hydrogenase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Dayle MA; Xiong, Yijia; Straatsma, TP

2012-05-09

Classical molecular force-field parameters describing the structure and motion of metal clusters in [NiFe] hydrogenase enzymes can be used to compare the dynamics and thermodynamics of [NiFe] under different oxidation, protonation, and ligation circumstances. Using density functional theory (DFT) calculations of small model clusters representative of the active site and the proximal, medial, and distal Fe/S metal centers and their attached protein side chains, we have calculated classical force-field parameters for [NiFe] in reduced and oxidized states, including internal coordinates, force constants, and atom-centered charges. Derived force constants revealed that cysteinate ligands bound to the metal ions are more flexiblemore » in the Ni-B active site, which has a bridging hydroxide ligand, than in the Ni-C active site, which has a bridging hydride. Ten nanosecond all-atom, explicit-solvent MD simulations of [NiFe] hydrogenase in oxidized and reduced catalytic states established the stability of the derived force-field parameters in terms of C{alpha} and metal cluster fluctuations. Average active site structures from the protein MD simulations are consistent with [NiFe] structures from the Protein Data Bank, suggesting that the derived force-field parameters are transferrable to other hydrogenases beyond the structure used for testing. A comparison of experimental H{sub 2}-production rates demonstrated a relationship between cysteinate side chain rotation and activity, justifying the use of a fully dynamic model of [NiFe] metal cluster motion.« less

Thermodynamics of anisotropic antiferromagnetic Heisenberg chain in the presence of longitudinal magnetic field

NASA Astrophysics Data System (ADS)

Rezania, H.

2018-07-01

We have addressed the specific heat and magnetization of one dimensional spin-1/2 anisotropic antiferromagnetic Heisenberg chain at finite magnetic field. We have investigated the thermodynamic properties by means of excitation spectrum in terms of a hard core Bosonic representation. The effect of in-plane anisotropy thermodynamic properties has also been studied via the Bosonic model by Green's function approach. This anisotropy is considered for exchange constants that couple spin components perpendicular to magnetic field direction. We have found the temperature dependence of the specific heat and longitudinal magnetization in the gapped field induced spin-polarized phase for various magnetic fields and anisotropy parameters. Furthermore we have studied the magnetic field dependence of specific heat and magnetization for various anisotropy parameters. Our results show temperature dependence of specific heat includes a peak so that its temperature position goes to higher temperature with increase of magnetic field. We have found the magnetic field dependence of specific heat shows a monotonic decreasing behavior for various magnetic fields due to increase of energy gap in the excitation spectrum. Also we have studied the temperature dependence of magnetization for different magnetic fields and various anisotropy parameters.

Bayesian Modeling of Exposure and Airflow Using Two-Zone Models

PubMed Central

Zhang, Yufen; Banerjee, Sudipto; Yang, Rui; Lungu, Claudiu; Ramachandran, Gurumurthy

2009-01-01

Mathematical modeling is being increasingly used as a means for assessing occupational exposures. However, predicting exposure in real settings is constrained by lack of quantitative knowledge of exposure determinants. Validation of models in occupational settings is, therefore, a challenge. Not only do the model parameters need to be known, the models also need to predict the output with some degree of accuracy. In this paper, a Bayesian statistical framework is used for estimating model parameters and exposure concentrations for a two-zone model. The model predicts concentrations in a zone near the source and far away from the source as functions of the toluene generation rate, air ventilation rate through the chamber, and the airflow between near and far fields. The framework combines prior or expert information on the physical model along with the observed data. The framework is applied to simulated data as well as data obtained from the experiments conducted in a chamber. Toluene vapors are generated from a source under different conditions of airflow direction, the presence of a mannequin, and simulated body heat of the mannequin. The Bayesian framework accounts for uncertainty in measurement as well as in the unknown rate of airflow between the near and far fields. The results show that estimates of the interzonal airflow are always close to the estimated equilibrium solutions, which implies that the method works efficiently. The predictions of near-field concentration for both the simulated and real data show nice concordance with the true values, indicating that the two-zone model assumptions agree with the reality to a large extent and the model is suitable for predicting the contaminant concentration. Comparison of the estimated model and its margin of error with the experimental data thus enables validation of the physical model assumptions. The approach illustrates how exposure models and information on model parameters together with the knowledge of uncertainty and variability in these quantities can be used to not only provide better estimates of model outputs but also model parameters. PMID:19403840

Towards quantifying uncertainty in Greenland's contribution to 21st century sea-level rise

NASA Astrophysics Data System (ADS)

Perego, M.; Tezaur, I.; Price, S. F.; Jakeman, J.; Eldred, M.; Salinger, A.; Hoffman, M. J.

2015-12-01

We present recent work towards developing a methodology for quantifying uncertainty in Greenland's 21st century contribution to sea-level rise. While we focus on uncertainties associated with the optimization and calibration of the basal sliding parameter field, the methodology is largely generic and could be applied to other (or multiple) sets of uncertain model parameter fields. The first step in the workflow is the solution of a large-scale, deterministic inverse problem, which minimizes the mismatch between observed and computed surface velocities by optimizing the two-dimensional coefficient field in a linear-friction sliding law. We then expand the deviation in this coefficient field from its estimated "mean" state using a reduced basis of Karhunen-Loeve Expansion (KLE) vectors. A Bayesian calibration is used to determine the optimal coefficient values for this expansion. The prior for the Bayesian calibration can be computed using the Hessian of the deterministic inversion or using an exponential covariance kernel. The posterior distribution is then obtained using Markov Chain Monte Carlo run on an emulator of the forward model. Finally, the uncertainty in the modeled sea-level rise is obtained by performing an ensemble of forward propagation runs. We present and discuss preliminary results obtained using a moderate-resolution model of the Greenland Ice sheet. As demonstrated in previous work, the primary difficulty in applying the complete workflow to realistic, high-resolution problems is that the effective dimension of the parameter space is very large.

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

NASA Astrophysics Data System (ADS)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at the Field Research Facility at Duck, NC in September 2010 focused on assimilation of tower-based electo-optical, infrared, and radar measurements in predictions of longshore currents. Here we provide an overview of our contribution to the RIVET I experiment at New River Inlet, NC in May 2012. During the course of the 3-week measurement period, continuous tower-based remote sensing measurements were made using electro-optical, infrared, and radar techniques covering the nearshore zone and the inlet mouth. A total of 50 hours of airborne measurements were made using high-resolution infrared imagers and a customized along track interferometric synthetic aperture radar (ATI SAR). The airborne IR imagery provides kilometer-scale mapping of frontal features that evolve as the inlet flow interacts with the oceanic wave and current fields. The ATI SAR provides maps of the two-dimensional surface currents. Near-surface measurements of turbulent velocities and surface waves using SWIFT drifters, designed to measures near-surface properties relevant to remote sensing, complimented the extensive in situ measurements by RIVET investigators.

Thermodynamic States of the Mixed Spin 1/2 and Spin 1 Hexagonal Nanowire System Obtained from a Seven-Site Cluster Within an Improved Mean Field Approximation

NASA Astrophysics Data System (ADS)

Mendes, R. G. B.; Barreto, F. C. Sá; Santos, J. P.

2018-04-01

The mean field approximation results in the mixedspin 1/2 Ising model and spin 1 Blume-Capel model, in the hexagonal nanowire system, are obtained from the Bogoliubov inequality. The Gibbs free energy, magnetization, and critical frontiers are obtained. Besides the stable branches of the order parameters, we obtain the metastable and unstable parts of these curves and also find phase transitions of the metastable branches of the order parameters. The classification of the stable, metastable, and unstable states is made by comparing the free energy values of these states.

Drifting oscillations in axion monodromy

DOE PAGES

Flauger, Raphael; McAllister, Liam; Silverstein, Eva; ...

2017-10-31

In this paper, we study the pattern of oscillations in the primordial power spectrum in axion monodromy inflation, accounting for drifts in the oscillation period that can be important for comparing to cosmological data. In these models the potential energy has a monomial form over a super-Planckian field range, with superimposed modulations whose size is model-dependent. The amplitude and frequency of the modulations are set by the expectation values of moduli fields. We show that during the course of inflation, the diminishing energy density can induce slow adjustments of the moduli, changing the modulations. We provide templates capturing the effectsmore » of drifting moduli, as well as drifts arising in effective field theory models based on softly broken discrete shift symmetries, and we estimate the precision required to detect a drifting period. A non-drifting template suffices over a wide range of parameters, but for the highest frequencies of interest, or for sufficiently strong drift, it is necessary to include parameters characterizing the change in frequency over the e-folds visible in the CMB. Finally, we use these templates to perform a preliminary search for drifting oscillations in a part of the parameter space in the Planck nominal mission data.« less

Physical, Hydraulic, and Transport Properties of Sediments and Engineered Materials Associated with Hanford Immobilized Low-Activity Waste

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rockhold, Mark L.; Zhang, Z. F.; Meyer, Philip D.

2015-02-28

Current plans for treatment and disposal of immobilized low-activity waste (ILAW) from Hanford’s underground waste storage tanks include vitrification and storage of the glass waste form in a nearsurface disposal facility. This Integrated Disposal Facility (IDF) is located in the 200 East Area of the Hanford Central Plateau. Performance assessment (PA) of the IDF requires numerical modeling of subsurface flow and reactive transport processes over very long periods (thousands of years). The models used to predict facility performance require parameters describing various physical, hydraulic, and transport properties. This report provides updated estimates of physical, hydraulic, and transport properties and parametersmore » for both near- and far-field materials, intended for use in future IDF PA modeling efforts. Previous work on physical and hydraulic property characterization for earlier IDF PA analyses is reviewed and summarized. For near-field materials, portions of this document and parameter estimates are taken from an earlier data package. For far-field materials, a critical review is provided of methodologies used in previous data packages. Alternative methods are described and associated parameters are provided.« less

Low-field NMR logging sensor for measuring hydraulic parameters of model soils

NASA Astrophysics Data System (ADS)

Sucre, Oscar; Pohlmeier, Andreas; Minière, Adrien; Blümich, Bernhard

2011-08-01

SummaryKnowing the exact hydraulic parameters of soils is very important for improving water management in agriculture and for the refinement of climate models. Up to now, however, the investigation of such parameters has required applying two techniques simultaneously which is time-consuming and invasive. Thus, the objective of this current study is to present only one technique, i.e., a new non-invasive method to measure hydraulic parameters of model soils by using low-field nuclear magnetic resonance (NMR). Hereby, two model clay or sandy soils were respectively filled in a 2 m-long acetate column having an integrated PVC tube. After the soils were completely saturated with water, a low-field NMR sensor was moved up and down in the PVC tube to quantitatively measure along the whole column the initial water content of each soil sample. Thereafter, both columns were allowed to drain. Meanwhile, the NMR sensor was set at a certain depth to measure the water content of that soil slice. Once the hydraulic equilibrium was reached in each of the two columns, a final moisture profile was taken along the whole column. Three curves were subsequently generated accordingly: (1) the initial moisture profile, (2) the evolution curve of the moisture depletion at that particular depth, and (3) the final moisture profile. All three curves were then inverse analyzed using a MATLAB code over numerical data produced with the van Genuchten-Mualem model. Hereby, a set of values ( α, n, θr and θs) was found for the hydraulic parameters for the soils under research. Additionally, the complete decaying NMR signal could be analyzed through Inverse Laplace Transformation and averaged on the 1/ T2 space. Through measurement of the decay in pure water, the effect on the relaxation caused by the sample could be estimated from the obtained spectra. The migration of the sample-related average <1/ T2, Sample> with decreasing saturation speaks for a enhancement of the surface relaxation as the soil dries, in concordance with results found by other authors. In conclusion, this low-field mobile NMR technique has proven itself to be a fast and a non-invasive mean to investigate the hydraulic behavior of soils and to explore microscopical aspect of the water retained in them. In the future, the sensor should allow easy soil moisture measurements on-field.

Displacement-based back-analysis of the model parameters of the Nuozhadu high earth-rockfill dam.

PubMed

Wu, Yongkang; Yuan, Huina; Zhang, Bingyin; Zhang, Zongliang; Yu, Yuzhen

2014-01-01

The parameters of the constitutive model, the creep model, and the wetting model of materials of the Nuozhadu high earth-rockfill dam were back-analyzed together based on field monitoring displacement data by employing an intelligent back-analysis method. In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. To avoid simultaneous back-analysis of many parameters, the model parameters of the three main dam materials are decoupled and back-analyzed separately in a particular order. Displacement back-analyses were performed at different stages of the construction period, with and without considering the creep and wetting deformations. Good agreement between the numerical results and the monitoring data was obtained for most observation points, which implies that the back-analysis method and decoupling method are effective for solving complex problems with multiple models and parameters. The comparison of calculation results based on different sets of back-analyzed model parameters indicates the necessity of taking the effects of creep and wetting into consideration in the numerical analyses of high earth-rockfill dams. With the resulting model parameters, the stress and deformation distributions at completion are predicted and analyzed.

Field-aligned currents and large-scale magnetospheric electric fields

NASA Technical Reports Server (NTRS)

Dangelo, N.

1979-01-01

The existence of field-aligned currents (FAC) at northern and southern high latitudes was confirmed by a number of observations, most clearly by experiments on the TRIAD and ISIS 2 satellites. The high-latitude FAC system is used to relate what is presently known about the large-scale pattern of high-latitude ionospheric electric fields and their relation to solar wind parameters. Recently a simplified model was presented for polar cap electric fields. The model is of considerable help in visualizing the large-scale features of FAC systems. A summary of the FAC observations is given. The simplified model is used to visualize how the FAC systems are driven by their generators.

Upper critical and irreversibility fields in Ni- and Co-doped pnictide bulk superconductors

NASA Astrophysics Data System (ADS)

Nikolo, Martin; Singleton, John; Solenov, Dmitry; Jiang, Jianyi; Weiss, Jeremy; Hellstrom, Eric

2018-05-01

A comprehensive study of upper critical and irreversibility magnetic fields in Ba(Fe0.95Ni0.05)2As2 (large grain and small grain samples), Ba(Fe0.94Ni0.06)2As2, Ba(Fe0.92Co0.08)2As2, and Ba(Fe0.92Co0.09)2As2 polycrystalline bulk pnictide superconductors was made in pulsed fields of up to 65 T. The full magnetic field-temperature (H-T) phase diagrams, starting at 1.5 K, were measured. The higher temperature, upper critical field Hc2 data are well described by the one-band Werthamer, Helfand, and Hohenberg (WHH) model. At low temperatures, the experimental data depart from the fitted WHH curves, suggesting an emergence of a new phase that could be attributed to the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state. The large values of the Maki fitting parameter α indicate that the Zeeman pair breaking dominates over the orbital pair breaking and spin-paramagnetic pair-breaking effect is significant in these materials. Possible multi-band structure of these materials is lumped into effective parameters of the single-band model. Table of measured physical parameters allows us to compare these pnictide superconductors for different Co- and Ni- doping levels and granularity.

A new approach to modeling aerosol effects on East Asian climate: Parametric uncertainties associated with emissions, cloud microphysics, and their interactions: AEROSOL EFFECTS ON EAST ASIAN CLIMATE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Huiping; Qian, Yun; Zhao, Chun

2015-09-09

In this study, we adopt a parametric sensitivity analysis framework that integrates the quasi-Monte Carlo parameter sampling approach and a surrogate model to examine aerosol effects on the East Asian Monsoon climate simulated in the Community Atmosphere Model (CAM5). A total number of 256 CAM5 simulations are conducted to quantify the model responses to the uncertain parameters associated with cloud microphysics parameterizations and aerosol (e.g., sulfate, black carbon (BC), and dust) emission factors and their interactions. Results show that the interaction terms among parameters are important for quantifying the sensitivity of fields of interest, especially precipitation, to the parameters. Themore » relative importance of cloud-microphysics parameters and emission factors (strength) depends on evaluation metrics or the model fields we focused on, and the presence of uncertainty in cloud microphysics imposes an additional challenge in quantifying the impact of aerosols on cloud and climate. Due to their different optical and microphysical properties and spatial distributions, sulfate, BC, and dust aerosols have very different impacts on East Asian Monsoon through aerosol-cloud-radiation interactions. The climatic effects of aerosol do not always have a monotonic response to the change of emission factors. The spatial patterns of both sign and magnitude of aerosol-induced changes in radiative fluxes, cloud, and precipitation could be different, depending on the aerosol types, when parameters are sampled in different ranges of values. We also identify the different cloud microphysical parameters that show the most significant impact on climatic effect induced by sulfate, BC and dust, respectively, in East Asia.« less

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Electrostatics of cysteine residues in proteins: parameterization and validation of a simple model.

PubMed

Salsbury, Freddie R; Poole, Leslie B; Fetrow, Jacquelyn S

2012-11-01

One of the most popular and simple models for the calculation of pK(a) s from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pK(a) s. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pK(a) s; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pK(a) s. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pK(a) values (where the calculation should reproduce the pK(a) within experimental error). Both the general behavior of cysteines in proteins and the perturbed pK(a) in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pK(a) should be shifted, and validation of force field parameters for cysteine residues. Copyright © 2012 Wiley Periodicals, Inc.

MICROSCOPE Mission: First Constraints on the Violation of the Weak Equivalence Principle by a Light Scalar Dilaton

NASA Astrophysics Data System (ADS)

Bergé, Joel; Brax, Philippe; Métris, Gilles; Pernot-Borràs, Martin; Touboul, Pierre; Uzan, Jean-Philippe

2018-04-01

The existence of a light or massive scalar field with a coupling to matter weaker than gravitational strength is a possible source of violation of the weak equivalence principle. We use the first results on the Eötvös parameter by the MICROSCOPE experiment to set new constraints on such scalar fields. For a massive scalar field of mass smaller than 10-12 eV (i.e., range larger than a few 1 05 m ), we improve existing constraints by one order of magnitude to |α |<10-11 if the scalar field couples to the baryon number and to |α |<10-12 if the scalar field couples to the difference between the baryon and the lepton numbers. We also consider a model describing the coupling of a generic dilaton to the standard matter fields with five parameters, for a light field: We find that, for masses smaller than 10-12 eV , the constraints on the dilaton coupling parameters are improved by one order of magnitude compared to previous equivalence principle tests.

MICROSCOPE Mission: First Constraints on the Violation of the Weak Equivalence Principle by a Light Scalar Dilaton.

PubMed

Bergé, Joel; Brax, Philippe; Métris, Gilles; Pernot-Borràs, Martin; Touboul, Pierre; Uzan, Jean-Philippe

2018-04-06

The existence of a light or massive scalar field with a coupling to matter weaker than gravitational strength is a possible source of violation of the weak equivalence principle. We use the first results on the Eötvös parameter by the MICROSCOPE experiment to set new constraints on such scalar fields. For a massive scalar field of mass smaller than 10^{-12}  eV (i.e., range larger than a few 10^{5}  m), we improve existing constraints by one order of magnitude to |α|<10^{-11} if the scalar field couples to the baryon number and to |α|<10^{-12} if the scalar field couples to the difference between the baryon and the lepton numbers. We also consider a model describing the coupling of a generic dilaton to the standard matter fields with five parameters, for a light field: We find that, for masses smaller than 10^{-12}  eV, the constraints on the dilaton coupling parameters are improved by one order of magnitude compared to previous equivalence principle tests.

Simulating settlement during waste placement at a landfill with waste lifts placed under frozen conditions.

PubMed

Van Geel, Paul J; Murray, Kathleen E

2015-12-01

Twelve instrument bundles were placed within two waste profiles as waste was placed in an operating landfill in Ste. Sophie, Quebec, Canada. The settlement data were simulated using a three-component model to account for primary or instantaneous compression, secondary compression or mechanical creep and biodegradation induced settlement. The regressed model parameters from the first waste layer were able to predict the settlement of the remaining four waste layers with good agreement. The model parameters were compared to values published in the literature. A MSW landfill scenario referenced in the literature was used to illustrate how the parameter values from the different studies predicted settlement. The parameters determined in this study and other studies with total waste heights between 15 and 60 m provided similar estimates of total settlement in the long term while the settlement rates and relative magnitudes of the three components varied. The parameters determined based on studies with total waste heights less than 15m resulted in larger secondary compression indices and lower biodegradation induced settlements. When these were applied to a MSW landfill scenario with a total waste height of 30 m, the settlement was overestimated and provided unrealistic values. This study concludes that more field studies are needed to measure waste settlement during the filling stage of landfill operations and more field data are needed to assess different settlement models and their respective parameters. Copyright © 2015 Elsevier Ltd. All rights reserved.

FIRST ZEEMAN DOPPLER IMAGING OF A COOL STAR USING ALL FOUR STOKES PARAMETERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosén, L.; Kochukhov, O.; Wade, G. A.

Magnetic fields are ubiquitous in active cool stars, but they are in general complex and weak. Current Zeeman Doppler imaging (ZDI) studies of cool star magnetic fields chiefly employ circular polarization observations because linear polarization is difficult to detect and requires a more sophisticated radiative transfer modeling to interpret. But it has been shown in previous theoretical studies, and in the observational analyses of magnetic Ap stars, that including linear polarization in the magnetic inversion process makes it possible to correctly recover many otherwise lost or misinterpreted magnetic features. We have obtained phase-resolved observations in all four Stokes parameters ofmore » the RS CVn star II Peg at two separate epochs. Here we present temperature and magnetic field maps reconstructed for this star using all four Stokes parameters. This is the very first such ZDI study of a cool active star. Our magnetic inversions reveal a highly structured magnetic field topology for both epochs. The strength of some surface features is doubled or even quadrupled when linear polarization is taken into account. The total magnetic energy of the reconstructed field map also becomes about 2.1–3.5 times higher. The overall complexity is also increased as the field energy is shifted toward higher harmonic modes when four Stokes parameters are used. As a consequence, the potential field extrapolation of the four Stokes parameter ZDI results indicates that magnetic field becomes weaker at a distance of several stellar radii due to a decrease of the large-scale field component.« less

Influence of periodic external fields in multiagent models with language dynamics

NASA Astrophysics Data System (ADS)

Palombi, Filippo; Ferriani, Stefano; Toti, Simona

2017-12-01

We investigate large-scale effects induced by external fields, phenomenologically interpreted as mass media, in multiagent models evolving with the microscopic dynamics of the binary naming game. In particular, we show that a single external field, broadcasting information at regular time intervals, can reverse the majority opinion of the population, provided the frequency and the effectiveness of the sent messages lie above well-defined thresholds. We study the phase structure of the model in the mean field approximation and in numerical simulations with several network topologies. We also investigate the influence on the agent dynamics of two competing external fields, periodically broadcasting different messages. In finite regions of the parameter space we observe periodic equilibrium states in which the average opinion densities are reversed with respect to naive expectations. Such equilibria occur in two cases: (i) when the frequencies of the competing messages are different but close to each other; (ii) when the frequencies are equal and the relative time shift of the messages does not exceed half a period. We interpret the observed phenomena as a result of the interplay between the external fields and the internal dynamics of the agents and conclude that, depending on the model parameters, the naming game is consistent with scenarios of first- or second-mover advantage (to borrow an expression from the jargon of business strategy).

Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system

USGS Publications Warehouse

Tiedeman, C.R.; Hill, M.C.; D'Agnese, F. A.; Faunt, C.C.

2003-01-01

Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about parameter values and associated flow system features and can lead to improved predictions. Methods for identifying parameters important to predictions include prediction scaled sensitivities (PSS), which account for uncertainty on individual parameters as well as prediction sensitivity to parameters, and a new "value of improved information" (VOII) method presented here, which includes the effects of parameter correlation in addition to individual parameter uncertainty and prediction sensitivity. In this work, the PSS and VOII methods are demonstrated and evaluated using a model of the Death Valley regional groundwater flow system. The predictions of interest are advective transport paths originating at sites of past underground nuclear testing. Results show that for two paths evaluated the most important parameters include a subset of five or six of the 23 defined model parameters. Some of the parameters identified as most important are associated with flow system attributes that do not lie in the immediate vicinity of the paths. Results also indicate that the PSS and VOII methods can identify different important parameters. Because the methods emphasize somewhat different criteria for parameter importance, it is suggested that parameters identified by both methods be carefully considered in subsequent data collection efforts aimed at improving model predictions.

Acoustic source localization in mixed field using spherical microphone arrays

NASA Astrophysics Data System (ADS)

Huang, Qinghua; Wang, Tong

2014-12-01

Spherical microphone arrays have been used for source localization in three-dimensional space recently. In this paper, a two-stage algorithm is developed to localize mixed far-field and near-field acoustic sources in free-field environment. In the first stage, an array signal model is constructed in the spherical harmonics domain. The recurrent relation of spherical harmonics is independent of far-field and near-field mode strengths. Therefore, it is used to develop spherical estimating signal parameter via rotational invariance technique (ESPRIT)-like approach to estimate directions of arrival (DOAs) for both far-field and near-field sources. In the second stage, based on the estimated DOAs, simple one-dimensional MUSIC spectrum is exploited to distinguish far-field and near-field sources and estimate the ranges of near-field sources. The proposed algorithm can avoid multidimensional search and parameter pairing. Simulation results demonstrate the good performance for localizing far-field sources, or near-field ones, or mixed field sources.

A FOUR-FLUID MHD MODEL OF THE SOLAR WIND/INTERSTELLAR MEDIUM INTERACTION WITH TURBULENCE TRANSPORT AND PICKUP PROTONS AS SEPARATE FLUID

DOE Office of Scientific and Technical Information (OSTI.GOV)

Usmanov, Arcadi V.; Matthaeus, William H.; Goldstein, Melvyn L., E-mail: arcadi.usmanov@nasa.gov

2016-03-20

We have developed a four-fluid, three-dimensional magnetohydrodynamic model of the solar wind interaction with the local interstellar medium. The unique features of the model are: (a) a three-fluid description for the charged components of the solar wind and interstellar plasmas (thermal protons, electrons, and pickup protons), (b) the built-in turbulence transport equations based on Reynolds decomposition and coupled with the mean-flow Reynolds-averaged equations, and (c) a solar corona/solar wind model that supplies inner boundary conditions at 40 au by computing solar wind and magnetic field parameters outward from the coronal base. The three charged species are described by separate energy equationsmore » and are assumed to move with the same velocity. The fourth fluid in the model is the interstellar hydrogen which is treated by separate continuity, momentum, and energy equations and is coupled with the charged components through photoionization and charge exchange. We evaluate the effects of turbulence transport and pickup protons on the global heliospheric structure and compute the distribution of plasma, magnetic field, and turbulence parameters throughout the heliosphere for representative solar minimum and maximum conditions. We compare our results with Voyager 1 observations in the outer heliosheath and show that the relative amplitude of magnetic fluctuations just outside the heliopause is in close agreement with the value inferred from Voyager 1 measurements by Burlaga et al. The simulated profiles of magnetic field parameters in the outer heliosheath are in qualitative agreement with the Voyager 1 observations and with the analytical model of magnetic field draping around the heliopause of Isenberg et al.« less

Sub-poissonian photon statistics in the coherent state Jaynes-Cummings model in non-resonance

NASA Astrophysics Data System (ADS)

Zhang, Jia-tai; Fan, An-fu

1992-03-01

We study a model with a two-level atom (TLA) non-resonance interacting with a single-mode quantized cavity field (QCF). The photon number probability function, the mean photon number and Mandel's fluctuation parameter are calculated. The sub-Poissonian distributions of the photon statistics are obtained in non-resonance interaction. This statistical properties are strongly dependent on the detuning parameters.

Analyzing Electric Field Morphology Through Data-Model Comparisons of the GEM IM/S Assessment Challenge Events

NASA Technical Reports Server (NTRS)

Liemohn, Michael W.; Ridley, Aaron J.; Kozyra, Janet U.; Gallagher, Dennis L.; Thomsen, Michelle F.; Henderson, Michael G.; Denton, Michael H.; Brandt, Pontus C.; Goldstein, Jerry

2006-01-01

The storm-time inner magnetospheric electric field morphology and dynamics are assessed by comparing numerical modeling results of the plasmasphere and ring current with many in situ and remote sensing data sets. Two magnetic storms are analyzed, April 22,2001 and October 21-23,2001, which are the events selected for the Geospace Environment Modeling (GEM) Inner Magnetosphere/Storms (IM/S) Assessment Challenge (IMSAC). The IMSAC seeks to quantify the accuracy of inner magnetospheric models as well as synthesize our understanding of this region. For each storm, the ring current-atmosphere interaction model (RAM) and the dynamic global core plasma model (DGCPM) were run together with various settings for the large-scale convection electric field and the nightside ionospheric conductance. DGCPM plasmaspheric parameters were compared with IMAGE-EUV plasmapause extractions and LANL-MPA plume locations and velocities. RAM parameters were compared with Dst*, LANL-MPA fluxes and moments, IMAGE-MENA images, and IMAGE-HENA images. Both qualitative and quantitative comparisons were made to determine the electric field morphology that allows the model results to best fit the plasma data at various times during these events. The simulations with self-consistent electric fields were, in general, better than those with prescribed field choices. This indicates that the time-dependent modulation of the inner magnetospheric electric fields by the nightside ionosphere is quite significant for accurate determination of these fields (and their effects). It was determined that a shielded Volland-Stern field description driven by the 3-hour Kp index yields accurate results much of the time, but can be quite inconsistent. The modified Mcllwain field description clearly lagged in overall accuracy compared to the other fields, but matched some data sets (like Dst*) quite well. The rankings between the simulations varied depending on the storm and the individual data sets, indicating that each field description did well for some place, time, and energy range during the events, as well as doing less well in other places, times, and energies. Several unresolved issues regarding the storm-time inner magnetospheric electric field are discussed.

Study of parameter identification using hybrid neural-genetic algorithm in electro-hydraulic servo system

NASA Astrophysics Data System (ADS)

Moon, Byung-Young

2005-12-01

The hybrid neural-genetic multi-model parameter estimation algorithm was demonstrated. This method can be applied to structured system identification of electro-hydraulic servo system. This algorithms consist of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. To evaluate the proposed method, electro-hydraulic servo system was designed and manufactured. The experiment was carried out to figure out the hybrid neural-genetic multi-model parameter estimation algorithm. As a result, the dynamic characteristics were obtained such as the parameters(mass, damping coefficient, bulk modulus, spring coefficient), which minimize total square error. The result of this study can be applied to hydraulic systems in industrial fields.

Excitonic magnet in external field: Complex order parameter and spin currents

NASA Astrophysics Data System (ADS)

Geffroy, D.; Hariki, A.; Kuneš, J.

2018-04-01

We investigate spin-triplet exciton condensation in the two-orbital Hubbard model close to half-filling by means of dynamical mean-field theory. Employing an impurity solver that handles complex off-diagonal hybridization functions, we study the behavior of excitonic condensate in stoichiometric and doped systems subject to external magnetic field. We find a general tendency of the triplet order parameter to lie perpendicular with the applied field and identify exceptions from this rule. For solutions exhibiting k -odd spin textures, we discuss the Bloch theorem, which, in the absence of spin-orbit coupling, forbids the appearance of spontaneous net spin current. We demonstrate that the Bloch theorem is not obeyed by the dynamical mean-field theory.

Weak-field limit of Kaluza-Klein models with spherically symmetric static scalar field: observational constraints

NASA Astrophysics Data System (ADS)

Zhuk, Alexander; Chopovsky, Alexey; Fakhr, Seyed Hossein; Shulga, Valerii; Wei, Han

2017-11-01

In a multidimensional Kaluza-Klein model with Ricci-flat internal space, we study the gravitational field in the weak-field limit. This field is created by two coupled sources. First, this is a point-like massive body which has a dust-like equation of state in the external space and an arbitrary parameter Ω of equation of state in the internal space. The second source is a static spherically symmetric massive scalar field centered at the origin where the point-like massive body is. The found perturbed metric coefficients are used to calculate the parameterized post-Newtonian (PPN) parameter γ . We define under which conditions γ can be very close to unity in accordance with the relativistic gravitational tests in the solar system. This can take place for both massive or massless scalar fields. For example, to have γ ≈ 1 in the solar system, the mass of scalar field should be μ ≳ 5.05× 10^{-49}g ˜ 2.83× 10^{-16}eV. In all cases, we arrive at the same conclusion that to be in agreement with the relativistic gravitational tests, the gravitating mass should have tension: Ω = - 1/2.

Neutron stars in a perturbative f(R) gravity model with strong magnetic fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheoun, Myung-Ki; Deliduman, Cemsinan; Güngör, Can

2013-10-01

In Kaluza-Klein electromagnetism it is natural to associate modified gravity with strong electromagnetic fields. Hence, in this paper we investigate the combined effects of a strong magnetic field and perturbative f(R) gravity on the structure of neutron stars. The effect of an interior strong magnetic field of about 10{sup 17−18} G on the equation of state is derived in the context of a quantum hadrodynamics (QHD) equation of state (EoS) including effects of the magnetic pressure and energy along with occupied Landau levels. Adopting a random orientation of interior field domains, we solve the modified spherically symmetric hydrostatic equilibrium equationsmore » derived for a gravity model with f(R) = R+αR{sup 2}. Effects of both the finite magnetic field and the modified gravity are detailed for various values of the magnetic field and the perturbation parameter α along with a discussion of their physical implications. We show that there exists a parameter space of the modified gravity and the magnetic field strength, in which even a soft equation of state can accommodate a large ( > 2 M{sub s}un) maximum neutron star mass.« less

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

PubMed

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-06-12

Particle swarm optimization (PSO) is a powerful metaheuristic population-based global optimization algorithm. However, when it is applied to nonseparable objective functions, its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates superior performance across several nonlinear, multimodal benchmark functions compared with the rotation-invariant PSO algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in the ReaxFF- lg reactive force field was carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents better performance compared to a genetic algorithm optimization method in the optimization of the parameters of a ReaxFF- lg correction model. The computational framework is implemented in a stand-alone C++ code that allows the straightforward development of ReaxFF reactive force fields.

Modeling of microstructure evolution in direct metal laser sintering: A phase field approach

NASA Astrophysics Data System (ADS)

Nandy, Jyotirmoy; Sarangi, Hrushikesh; Sahoo, Seshadev

2017-02-01

Direct Metal Laser Sintering (DMLS) is a new technology in the field of additive manufacturing, which builds metal parts in a layer by layer fashion directly from the powder bed. The process occurs within a very short time period with rapid solidification rate. Slight variations in the process parameters may cause enormous change in the final build parts. The physical and mechanical properties of the final build parts are dependent on the solidification rate which directly affects the microstructure of the material. Thus, the evolving of microstructure plays a vital role in the process parameters optimization. Nowadays, the increase in computational power allows for direct simulations of microstructures during materials processing for specific manufacturing conditions. In this study, modeling of microstructure evolution of Al-Si-10Mg powder in DMLS process was carried out by using a phase field approach. A MATLAB code was developed to solve the set of phase field equations, where simulation parameters include temperature gradient, laser scan speed and laser power. The effects of temperature gradient on microstructure evolution were studied and found that with increase in temperature gradient, the dendritic tip grows at a faster rate.

Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

NASA Astrophysics Data System (ADS)

Gao, S.; Fang, N. Z.

2017-12-01

A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher peak discharge.

Characterization of commercial magnetorheological fluids at high shear rate: influence of the gap

NASA Astrophysics Data System (ADS)

Golinelli, Nicola; Spaggiari, Andrea

2018-07-01

This paper reports the experimental tests on the behaviour of a commercial MR fluid at high shear rates and the effect of the gap. Three gaps were considered at multiple magnetic fields and shear rates. From an extended set of almost two hundred experimental flow curves, a set of parameters for the apparent viscosity are retrieved by using the Ostwald de Waele model for non-Newtonian fluids. It is possible to simplify the parameter correlation by making the following considerations: the consistency of the model depends only on the magnetic field, the flow index depends on the fluid type and the gap shows an important effect only at null or very low magnetic fields. This lead to a simple and useful model, especially in the design phase of a MR based product. During the off state, with no applied field, it is possible to use a standard viscous model. During the active state, with high magnetic field, a strong non-Newtonian nature becomes prevalent over the viscous one even at very high shear rate; the magnetic field dominates the apparent viscosity change, while the gap does not play any relevant role on the system behaviour. This simple assumption allows the designer to dimension the gap only considering the non-active state, as in standard viscous systems, and taking into account only the magnetic effect in the active state, where the gap does not change the proposed fluid model.

Connecting the large- and the small-scale magnetic fields of solar-like stars

NASA Astrophysics Data System (ADS)

Lehmann, L. T.; Jardine, M. M.; Mackay, D. H.; Vidotto, A. A.

2018-05-01

A key question in understanding the observed magnetic field topologies of cool stars is the link between the small- and the large-scale magnetic field and the influence of the stellar parameters on the magnetic field topology. We examine various simulated stars to connect the small-scale with the observable large-scale field. The highly resolved 3D simulations we used couple a flux transport model with a non-potential coronal model using a magnetofrictional technique. The surface magnetic field of these simulations is decomposed into spherical harmonics which enables us to analyse the magnetic field topologies on a wide range of length scales and to filter the large-scale magnetic field for a direct comparison with the observations. We show that the large-scale field of the self-consistent simulations fits the observed solar-like stars and is mainly set up by the global dipolar field and the large-scale properties of the flux pattern, e.g. the averaged latitudinal position of the emerging small-scale field and its global polarity pattern. The stellar parameters flux emergence rate, differential rotation and meridional flow affect the large-scale magnetic field topology. An increased flux emergence rate increases the magnetic flux in all field components and an increased differential rotation increases the toroidal field fraction by decreasing the poloidal field. The meridional flow affects the distribution of the magnetic energy across the spherical harmonic modes.

Stability analysis in tachyonic potential chameleon cosmology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farajollahi, H.; Salehi, A.; Tayebi, F.

2011-05-01

We study general properties of attractors for tachyonic potential chameleon scalar-field model which possess cosmological scaling solutions. An analytic formulation is given to obtain fixed points with a discussion on their stability. The model predicts a dynamical equation of state parameter with phantom crossing behavior for an accelerating universe. We constrain the parameters of the model by best fitting with the recent data-sets from supernovae and simulated data points for redshift drift experiment generated by Monte Carlo simulations.

Including gauge-group parameters into the theory of interactions: an alternative mass-generating mechanism for gauge fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aldaya, V.; Lopez-Ruiz, F. F.; Sanchez-Sastre, E.

2006-11-03

We reformulate the gauge theory of interactions by introducing the gauge group parameters into the model. The dynamics of the new 'Goldstone-like' bosons is accomplished through a non-linear {sigma}-model Lagrangian. They are minimally coupled according to a proper prescription which provides mass terms to the intermediate vector bosons without spoiling gauge invariance. The present formalism is explicitly applied to the Standard Model of electroweak interactions.

[Measures of occupational exposure to time-varying low frequency magnetic fields of non-uniform spatial distribution in the light of international guidelines and electrodynamic exposure effects in the human body].

PubMed

Karpowicz, Jolanta; Zradziński, Patryk; Gryz, Krzysztof

2012-01-01

The aim of study was to analyze by computer simulations the electrodynamic effects of magnetic field (MF) on workers, to harmonize the principles of occupational hazards assessment with international guidelines. Simulations involved 50 Hz MF of various spatial distributions, representing workers' exposure in enterprises. Homogeneous models of sigma = 0.2 S/m conductivity and dimensions of body parts - palm, head and trunk - were located at 50 cm ("hand-distance") or 5 cm (adjacent) from the source (circle conductor of 20 cm or 200 cm in diameter). Parameters of magnetic flux density (B(i)) affecting the models were the exposure measures, and the induced electric field strength (E(in)) was the measure of MF exposure effects. The ratio E(in)/B(i) in the analyzed cases ranged from 2.59 to 479 (V/m)/T. The strongest correlation (p < 0.001) between B(i) and E(in) was found for parameters characterizing MF at the surface of body models. Parameters characterizing the averaged value of the field affecting models (measures of non-uniform field exposure following ICNIRP guidelines), were less correlated with exposure effects (p < 0.005). E(in)(trunk)/E(in) (palm) estimated from E(in) calculations was 3.81-4.56 but estimated from parameters representing B(i) measurement accounted for 3.96-9.74. It is justified to accept 3.96-9.74 times higher exposure to limb than that to trunk. This supports the regulation of labor law in Poland, which provides that the ceiling value for limb exposure to MF below 800 kHz is fivefold higher than that of the trunk. High uncertainty in assessing the effects of non-uniform fields exposure, resulting from a strong dependence of the E(in)/B(i) ratio on the conditions of exposure and its applied measures, requires special caution when defining the permissible MF levels and the principles of exposure assessment at workplace.

Study of the Vertical Magnetic Field in Face-on Galaxies Using Faraday Tomography

NASA Astrophysics Data System (ADS)

Ideguchi, Shinsuke; Tashiro, Yuichi; Akahori, Takuya; Takahashi, Keitaro; Ryu, Dongsu

2017-07-01

Faraday tomography allows astronomers to probe the distribution of the magnetic field along the line of sight (LOS), but that can be achieved only after the Faraday spectrum is interpreted. However, the interpretation is not straightforward, mainly because the Faraday spectrum is complicated due to a turbulent magnetic field; it ruins the one-to-one relation between the Faraday depth and the physical depth, and appears as many small-scale features in the Faraday spectrum. In this paper, by employing “simple toy models” for the magnetic field, we describe numerically as well as analytically the characteristic properties of the Faraday spectrum. We show that the Faraday spectrum along “multiple LOSs” can be used to extract the global properties of the magnetic field. Specifically, considering face-on spiral galaxies and modeling turbulent magnetic field as a random field with a single coherence length, we numerically calculate the Faraday spectrum along a number of LOSs and its shape-characterizing parameters, that is, the moments. When multiple LOSs cover a region of ≳(10 coherence length)2, the shape of the Faraday spectrum becomes smooth and the shape-characterizing parameters are well specified. With the Faraday spectrum constructed as a sum of Gaussian functions with different means and variances, we analytically show that the parameters are expressed in terms of the regular and turbulent components of the LOS magnetic field and the coherence length. We also consider the turbulent magnetic field modeled with a power-law spectrum, and study how the magnetic field is revealed in the Faraday spectrum. Our work suggests a way to obtain information on the magnetic field from a Faraday tomography study.

Study of the Vertical Magnetic Field in Face-on Galaxies Using Faraday Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ideguchi, Shinsuke; Ryu, Dongsu; Tashiro, Yuichi

Faraday tomography allows astronomers to probe the distribution of the magnetic field along the line of sight (LOS), but that can be achieved only after the Faraday spectrum is interpreted. However, the interpretation is not straightforward, mainly because the Faraday spectrum is complicated due to a turbulent magnetic field; it ruins the one-to-one relation between the Faraday depth and the physical depth, and appears as many small-scale features in the Faraday spectrum. In this paper, by employing “simple toy models” for the magnetic field, we describe numerically as well as analytically the characteristic properties of the Faraday spectrum. We showmore » that the Faraday spectrum along “multiple LOSs” can be used to extract the global properties of the magnetic field. Specifically, considering face-on spiral galaxies and modeling turbulent magnetic field as a random field with a single coherence length, we numerically calculate the Faraday spectrum along a number of LOSs and its shape-characterizing parameters, that is, the moments. When multiple LOSs cover a region of ≳(10 coherence length){sup 2}, the shape of the Faraday spectrum becomes smooth and the shape-characterizing parameters are well specified. With the Faraday spectrum constructed as a sum of Gaussian functions with different means and variances, we analytically show that the parameters are expressed in terms of the regular and turbulent components of the LOS magnetic field and the coherence length. We also consider the turbulent magnetic field modeled with a power-law spectrum, and study how the magnetic field is revealed in the Faraday spectrum. Our work suggests a way to obtain information on the magnetic field from a Faraday tomography study.« less

Perceiving while producing: Modeling the dynamics of phonological planning

PubMed Central

Roon, Kevin D.; Gafos, Adamantios I.

2016-01-01

We offer a dynamical model of phonological planning that provides a formal instantiation of how the speech production and perception systems interact during online processing. The model is developed on the basis of evidence from an experimental task that requires concurrent use of both systems, the so-called response-distractor task in which speakers hear distractor syllables while they are preparing to produce required responses. The model formalizes how ongoing response planning is affected by perception and accounts for a range of results reported across previous studies. It does so by explicitly addressing the setting of parameter values in representations. The key unit of the model is that of the dynamic field, a distribution of activation over the range of values associated with each representational parameter. The setting of parameter values takes place by the attainment of a stable distribution of activation over the entire field, stable in the sense that it persists even after the response cue in the above experiments has been removed. This and other properties of representations that have been taken as axiomatic in previous work are derived by the dynamics of the proposed model. PMID:27440947

Computing mammographic density from a multiple regression model constructed with image-acquisition parameters from a full-field digital mammographic unit

PubMed Central

Lu, Lee-Jane W.; Nishino, Thomas K.; Khamapirad, Tuenchit; Grady, James J; Leonard, Morton H.; Brunder, Donald G.

2009-01-01

Breast density (the percentage of fibroglandular tissue in the breast) has been suggested to be a useful surrogate marker for breast cancer risk. It is conventionally measured using screen-film mammographic images by a labor intensive histogram segmentation method (HSM). We have adapted and modified the HSM for measuring breast density from raw digital mammograms acquired by full-field digital mammography. Multiple regression model analyses showed that many of the instrument parameters for acquiring the screening mammograms (e.g. breast compression thickness, radiological thickness, radiation dose, compression force, etc) and image pixel intensity statistics of the imaged breasts were strong predictors of the observed threshold values (model R2=0.93) and %density (R2=0.84). The intra-class correlation coefficient of the %-density for duplicate images was estimated to be 0.80, using the regression model-derived threshold values, and 0.94 if estimated directly from the parameter estimates of the %-density prediction regression model. Therefore, with additional research, these mathematical models could be used to compute breast density objectively, automatically bypassing the HSM step, and could greatly facilitate breast cancer research studies. PMID:17671343

Flow of magnetic particles in blood with isothermal heating: A fractional model for two-phase flow

NASA Astrophysics Data System (ADS)

Ali, Farhad; Imtiaz, Anees; Khan, Ilyas; Sheikh, Nadeem Ahmad

2018-06-01

In the sixteenth century, medical specialists were of the conclusion that magnet can be utilized for the treatment or wipe out the illnesses from the body. On this basis, the research on magnet advances day by day for the treatment of different types of diseases in mankind. This study aims to investigate the effect of magnetic field and their applications in human body specifically in blood. Blood is a non-Newtonian fluid because its viscosity depends strongly on the fraction of volume occupied by red cells also called the hematocrit. Therefore, in this paper blood is considered as an example of non-Newtonian Casson fluid. The blood flow is considered in a vertical cylinder together with heat transfer due to mixed conviction caused by buoyancy force and the external pressure gradient. Effect of magnetic field on the velocities of blood and magnetic particles is also considered. The problem is modelled using the Caputo-Fabrizio derivative approach. The governing fractional partial differential equations are solved using Laplace and Hankel transformation techniques and exact solutions are obtained. Effects of different parameters such as Grashof number, Prandtl number, Casson fluid parameter and fractional parameters, and magnetic field are shown graphically. Both velocity profiles increase with the increase of Grashoff number and Casson fluid parameter and reduce with the increase of magnetic field.

Parity Deformed Jaynes-Cummings Model: “Robust Maximally Entangled States”

PubMed Central

Dehghani, A.; Mojaveri, B.; Shirin, S.; Faseghandis, S. Amiri

2016-01-01

The parity-deformations of the quantum harmonic oscillator are used to describe the generalized Jaynes-Cummings model based on the λ-analog of the Heisenberg algebra. The behavior is interestingly that of a coupled system comprising a two-level atom and a cavity field assisted by a continuous external classical field. The dynamical characters of the system is explored under the influence of the external field. In particular, we analytically study the generation of robust and maximally entangled states formed by a two-level atom trapped in a lossy cavity interacting with an external centrifugal field. We investigate the influence of deformation and detuning parameters on the degree of the quantum entanglement and the atomic population inversion. Under the condition of a linear interaction controlled by an external field, the maximally entangled states may emerge periodically along with time evolution. In the dissipation regime, the entanglement of the parity deformed JCM are preserved more with the increase of the deformation parameter, i.e. the stronger external field induces better degree of entanglement. PMID:27917882

Quantifying the Model-Related Variability of Biomass Stock and Change Estimates in the Norwegian National Forest Inventory

Treesearch

Johannes Breidenbach; Clara Antón-Fernández; Hans Petersson; Ronald E. McRoberts; Rasmus Astrup

2014-01-01

National Forest Inventories (NFIs) provide estimates of forest parameters for national and regional scales. Many key variables of interest, such as biomass and timber volume, cannot be measured directly in the field. Instead, models are used to predict those variables from measurements of other field variables. Therefore, the uncertainty or variability of NFI estimates...

MIRO Computational Model

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2010-01-01

A computational model calculates the excitation of water rotational levels and emission-line spectra in a cometary coma with applications for the Micro-wave Instrument for Rosetta Orbiter (MIRO). MIRO is a millimeter-submillimeter spectrometer that will be used to study the nature of cometary nuclei, the physical processes of outgassing, and the formation of the head region of a comet (coma). The computational model is a means to interpret the data measured by MIRO. The model is based on the accelerated Monte Carlo method, which performs a random angular, spatial, and frequency sampling of the radiation field to calculate the local average intensity of the field. With the model, the water rotational level populations in the cometary coma and the line profiles for the emission from the water molecules as a function of cometary parameters (such as outgassing rate, gas temperature, and gas and electron density) and observation parameters (such as distance to the comet and beam width) are calculated.

Field-scale prediction of enhanced DNAPL dissolution based on partitioning tracers.

PubMed

Wang, Fang; Annable, Michael D; Jawitz, James W

2013-09-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a tetrachloroethylene (PCE)-contaminated dry cleaner site, located in Jacksonville, Florida. The EST model is an analytical solution with field-measurable input parameters. Measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ ethanol flood. In addition, a simulated partitioning tracer test from a calibrated, three-dimensional, spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The EST ethanol prediction based on both the field partitioning tracer test and the simulation closely matched the total recovery well field ethanol data with Nash-Sutcliffe efficiency E=0.96 and 0.90, respectively. The EST PCE predictions showed a peak shift to earlier arrival times for models based on either field-measured or simulated partitioning tracer tests, resulting in poorer matches to the field PCE data in both cases. The peak shifts were concluded to be caused by well screen interval differences between the field tracer test and ethanol flood. Both the EST model and UTCHEM were also used to predict PCE aqueous dissolution under natural gradient conditions, which has a much less complex flow pattern than the forced-gradient double five spot used for the ethanol flood. The natural gradient EST predictions based on parameters determined from tracer tests conducted with a complex flow pattern underestimated the UTCHEM-simulated natural gradient total mass removal by 12% after 170 pore volumes of water flushing indicating that some mass was not detected by the tracers likely due to stagnation zones in the flow field. These findings highlight the important influence of well configuration and the associated flow patterns on dissolution. © 2013.

Field-scale prediction of enhanced DNAPL dissolution based on partitioning tracers

NASA Astrophysics Data System (ADS)

Wang, Fang; Annable, Michael D.; Jawitz, James W.

2013-09-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a tetrachloroethylene (PCE)-contaminated dry cleaner site, located in Jacksonville, Florida. The EST model is an analytical solution with field-measurable input parameters. Measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ ethanol flood. In addition, a simulated partitioning tracer test from a calibrated, three-dimensional, spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The EST ethanol prediction based on both the field partitioning tracer test and the simulation closely matched the total recovery well field ethanol data with Nash-Sutcliffe efficiency E = 0.96 and 0.90, respectively. The EST PCE predictions showed a peak shift to earlier arrival times for models based on either field-measured or simulated partitioning tracer tests, resulting in poorer matches to the field PCE data in both cases. The peak shifts were concluded to be caused by well screen interval differences between the field tracer test and ethanol flood. Both the EST model and UTCHEM were also used to predict PCE aqueous dissolution under natural gradient conditions, which has a much less complex flow pattern than the forced-gradient double five spot used for the ethanol flood. The natural gradient EST predictions based on parameters determined from tracer tests conducted with a complex flow pattern underestimated the UTCHEM-simulated natural gradient total mass removal by 12% after 170 pore volumes of water flushing indicating that some mass was not detected by the tracers likely due to stagnation zones in the flow field. These findings highlight the important influence of well configuration and the associated flow patterns on dissolution.

1D Cole-Cole inversion of TEM transients influenced by induced polarization

NASA Astrophysics Data System (ADS)

Seidel, Marc; Tezkan, Bülent

2017-03-01

Effects of induced polarization (IP) can have an impact on time-domain electromagnetic measurements (TEM) and may lead to sign reversals in the recorded transients. To study these IP effects on TEM data, a new 1D inversion algorithm was developed for both, the central-loop and the separate-loop TEM configurations using the Cole-Cole relaxation model. 1D forward calculations for a homogeneous half-space were conducted with the aim of analyzing the impacts of the Cole-Cole parameters on TEM transients with respect to possible sign reversals. The forward modelings showed that the variation of different parameters have comparable effects on the TEM transients. This leads to an increasing number of equivalent models as a result of inversion calculations. Subsequently, 1D inversions of synthetic data were performed to study the potentials and limitations of the algorithm regarding the resolution of the Cole-Cole parameters. In order to achieve optimal inversion results, it was essential to error-weight the data points in the direct vicinity of sign reversals. The obtained findings were eventually adopted on the inversion of real field data which contained considerable IP signatures such as sign reversals. One field data set was recorded at the Nakyn kimberlite field in Western Yakutiya, Russia, in the central-loop configuration. Another field data set originates from a waste site in Cologne, Germany, and was measured utilizing the separate-loop configuration.

ON IDENTIFIABILITY OF NONLINEAR ODE MODELS AND APPLICATIONS IN VIRAL DYNAMICS

PubMed Central

MIAO, HONGYU; XIA, XIAOHUA; PERELSON, ALAN S.; WU, HULIN

2011-01-01

Ordinary differential equations (ODE) are a powerful tool for modeling dynamic processes with wide applications in a variety of scientific fields. Over the last 2 decades, ODEs have also emerged as a prevailing tool in various biomedical research fields, especially in infectious disease modeling. In practice, it is important and necessary to determine unknown parameters in ODE models based on experimental data. Identifiability analysis is the first step in determing unknown parameters in ODE models and such analysis techniques for nonlinear ODE models are still under development. In this article, we review identifiability analysis methodologies for nonlinear ODE models developed in the past one to two decades, including structural identifiability analysis, practical identifiability analysis and sensitivity-based identifiability analysis. Some advanced topics and ongoing research are also briefly reviewed. Finally, some examples from modeling viral dynamics of HIV, influenza and hepatitis viruses are given to illustrate how to apply these identifiability analysis methods in practice. PMID:21785515

Parametrization of 2,2,2-trifluoroethanol based on the generalized AMBER force field provides realistic agreement between experimental and calculated properties of pure liquid as well as water-mixed solutions.

PubMed

Vymětal, Jiří; Vondrášek, Jiří

2014-09-04

We present a novel force field model of 2,2,2-trifluoroethanol (TFE) based on the generalized AMBER force field. The model was exhaustively parametrized to reproduce liquid-state properties of pure TFE, namely, density, enthalpy of vaporization, self-diffusion coefficient, and population of trans and gauche conformers. The model predicts excellently other liquid-state properties such as shear viscosity, thermal expansion coefficient, and isotropic compressibility. The resulting model describes unexpectedly well the state equation of the liquid region in the range of 100 K and 10 MPa. More importantly, the proposed TFE model was optimized for use in combination with the TIP4P/Ew and TIP4P/2005 water models. It does not manifest excessive aggregation, which is known for other models, and therefore, it is supposed to more realistically describe the behavior of TFE/water mixtures. This was demonstrated by means of the Kirkwood-Buff theory of solutions and reasonable agreement with experimental data. We explored a considerable part of the parameter space and systematically tested individual combinations of parameters for performance in combination with the TIP4P/Ew and TIP4P/2005 water models. We observed ambiguity in parameters describing pure liquid TFE; however, most of them failed for TFE/water mixtures. We clearly demonstrated the necessity for balanced TFE-TFE, TFE-water, and water-water interactions which can be acquired only by employing implicit polarization correction in the course of parametrization.

Sensitivity Analysis Reveals Critical Factors that Affect Wetland Methane Emissions using Soil Biogeochemistry Model

NASA Astrophysics Data System (ADS)

Alonso-Contes, C.; Gerber, S.; Bliznyuk, N.; Duerr, I.

2017-12-01

Wetlands contribute approximately 20 to 40 % to global sources of methane emissions. We build a Methane model for tropical and subtropical forests, that allows inundated conditions, following the approaches used in more complex global biogeochemical emission models (LPJWhyMe and CLM4Me). The model was designed to replace model formulations with field and remotely sensed collected data for 2 essential drivers: plant productivity and hydrology. This allows us to directly focus on the central processes of methane production, consumption and transport. One of our long term goals is to make the model available to a scientists interested in including methane modeling in their location of study. Sensitivity analysis results help in focusing field data collection efforts. Here, we present results from a pilot global sensitivity analysis of the model order to determine which parameters and processes contribute most to the model's uncertainty of methane emissions. Results show that parameters related to water table behavior, carbon input (in form of plant productivity) and rooting depth affect simulated methane emissions the most. Current efforts include to perform the sensitivity analysis again on methane emissions outputs from an updated model that incorporates a soil heat flux routine and to determine the extent by which the soil temperature parameters affect CH4 emissions. Currently we are conducting field collection of data during Summer 2017 for comparison among 3 different landscapes located in the Ordway-Swisher Biological Station in Melrose, FL. We are collecting soil moisture and CH4 emission data from 4 different wetland types. Having data from 4 wetland types allows for calibration of the model to diverse soil, water and vegetation characteristics.

Feasibility study of a procedure to detect and warn of low level wind shear

NASA Technical Reports Server (NTRS)

Turkel, B. S.; Kessel, P. A.; Frost, W.

1981-01-01

A Doppler radar system which provides an aircraft with advanced warning of longitudinal wind shear is described. This system uses a Doppler radar beamed along the glide slope linked with an on line microprocessor containing a two dimensional, three degree of freedom model of the motion of an aircraft including pilot/autopilot control. The Doppler measured longitudinal glide slope winds are entered into the aircraft motion model, and a simulated controlled aircraft trajectory is calculated. Several flight path deterioration parameters are calculated from the computed aircraft trajectory information. The aircraft trajectory program, pilot control models, and the flight path deterioration parameters are discussed. The performance of the computer model and a test pilot in a flight simulator through longitudinal and vertical wind fields characteristic of a thunderstorm wind field are compared.

A Biologically Constrained, Mathematical Model of Cortical Wave Propagation Preceding Seizure Termination

PubMed Central

González-Ramírez, Laura R.; Ahmed, Omar J.; Cash, Sydney S.; Wayne, C. Eugene; Kramer, Mark A.

2015-01-01

Epilepsy—the condition of recurrent, unprovoked seizures—manifests in brain voltage activity with characteristic spatiotemporal patterns. These patterns include stereotyped semi-rhythmic activity produced by aggregate neuronal populations, and organized spatiotemporal phenomena, including waves. To assess these spatiotemporal patterns, we develop a mathematical model consistent with the observed neuronal population activity and determine analytically the parameter configurations that support traveling wave solutions. We then utilize high-density local field potential data recorded in vivo from human cortex preceding seizure termination from three patients to constrain the model parameters, and propose basic mechanisms that contribute to the observed traveling waves. We conclude that a relatively simple and abstract mathematical model consisting of localized interactions between excitatory cells with slow adaptation captures the quantitative features of wave propagation observed in the human local field potential preceding seizure termination. PMID:25689136

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

Is ET often oversimplified in hydrologic models? Using long records to elucidate unaccounted for controls on ET

NASA Astrophysics Data System (ADS)

Kelleher, Christa A.; Shaw, Stephen B.

2018-02-01

Recent research has found that hydrologic modeling over decadal time periods often requires time variant model parameters. Most prior work has focused on assessing time variance in model parameters conceptualizing watershed features and functions. In this paper, we assess whether adding a time variant scalar to potential evapotranspiration (PET) can be used in place of time variant parameters. Using the HBV hydrologic model and four different simple but common PET methods (Hamon, Priestly-Taylor, Oudin, and Hargreaves), we simulated 60+ years of daily discharge on four rivers in New York state. Allowing all ten model parameters to vary in time achieved good model fits in terms of daily NSE and long-term water balance. However, allowing single model parameters to vary in time - including a scalar on PET - achieved nearly equivalent model fits across PET methods. Overall, varying a PET scalar in time is likely more physically consistent with known biophysical controls on PET as compared to varying parameters conceptualizing innate watershed properties related to soil properties such as wilting point and field capacity. This work suggests that the seeming need for time variance in innate watershed parameters may be due to overly simple evapotranspiration formulations that do not account for all factors controlling evapotranspiration over long time periods.

CHARMM Force-Fields with Modified Polyphosphate Parameters Allow Stable Simulation of the ATP-Bound Structure of Ca(2+)-ATPase.

PubMed

Komuro, Yasuaki; Re, Suyong; Kobayashi, Chigusa; Muneyuki, Eiro; Sugita, Yuji

2014-09-09

Adenosine triphosphate (ATP) is an indispensable energy source in cells. In a wide variety of biological phenomena like glycolysis, muscle contraction/relaxation, and active ion transport, chemical energy released from ATP hydrolysis is converted to mechanical forces to bring about large-scale conformational changes in proteins. Investigation of structure-function relationships in these proteins by molecular dynamics (MD) simulations requires modeling of ATP in solution and ATP bound to proteins with accurate force-field parameters. In this study, we derived new force-field parameters for the triphosphate moiety of ATP based on the high-precision quantum calculations of methyl triphosphate. We tested our new parameters on membrane-embedded sarcoplasmic reticulum Ca(2+)-ATPase and four soluble proteins. The ATP-bound structure of Ca(2+)-ATPase remains stable during MD simulations, contrary to the outcome in shorter simulations using original parameters. Similar results were obtained with the four ATP-bound soluble proteins. The new force-field parameters were also tested by investigating the range of conformations sampled during replica-exchange MD simulations of ATP in explicit water. Modified parameters allowed a much wider range of conformational sampling compared with the bias toward extended forms with original parameters. A diverse range of structures agrees with the broad distribution of ATP conformations in proteins deposited in the Protein Data Bank. These simulations suggest that the modified parameters will be useful in studies of ATP in solution and of the many ATP-utilizing proteins.

Statistical approach to Higgs boson couplings in the standard model effective field theory

NASA Astrophysics Data System (ADS)

Murphy, Christopher W.

2018-01-01

We perform a parameter fit in the standard model effective field theory (SMEFT) with an emphasis on using regularized linear regression to tackle the issue of the large number of parameters in the SMEFT. In regularized linear regression, a positive definite function of the parameters of interest is added to the usual cost function. A cross-validation is performed to try to determine the optimal value of the regularization parameter to use, but it selects the standard model (SM) as the best model to explain the measurements. Nevertheless as proof of principle of this technique we apply it to fitting Higgs boson signal strengths in SMEFT, including the latest Run-2 results. Results are presented in terms of the eigensystem of the covariance matrix of the least squares estimators as it has a degree model-independent to it. We find several results in this initial work: the SMEFT predicts the total width of the Higgs boson to be consistent with the SM prediction; the ATLAS and CMS experiments at the LHC are currently sensitive to non-resonant double Higgs boson production. Constraints are derived on the viable parameter space for electroweak baryogenesis in the SMEFT, reinforcing the notion that a first order phase transition requires fairly low-scale beyond the SM physics. Finally, we study which future experimental measurements would give the most improvement on the global constraints on the Higgs sector of the SMEFT.

The dimensional reduction method for identification of parameters that trade-off due to similar model roles.

PubMed

Davidson, Shaun M; Docherty, Paul D; Murray, Rua

2017-03-01

Parameter identification is an important and widely used process across the field of biomedical engineering. However, it is susceptible to a number of potential difficulties, such as parameter trade-off, causing premature convergence at non-optimal parameter values. The proposed Dimensional Reduction Method (DRM) addresses this issue by iteratively reducing the dimension of hyperplanes where trade off occurs, and running subsequent identification processes within these hyperplanes. The DRM was validated using clinical data to optimize 4 parameters of the widely used Bergman Minimal Model of glucose and insulin kinetics, as well as in-silico data to optimize 5 parameters of the Pulmonary Recruitment (PR) Model. Results were compared with the popular Levenberg-Marquardt (LMQ) Algorithm using a Monte-Carlo methodology, with both methods afforded equivalent computational resources. The DRM converged to a lower or equal residual value in all tests run using the Bergman Minimal Model and actual patient data. For the PR model, the DRM attained significantly lower overall median parameter error values and lower residuals in the vast majority of tests. This shows the DRM has potential to provide better resolution of optimum parameter values for the variety of biomedical models in which significant levels of parameter trade-off occur. Copyright © 2017 Elsevier Inc. All rights reserved.

Constraints on single-field inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pirtskhalava, David; Santoni, Luca; Trincherini, Enrico

2016-06-28

Many alternatives to canonical slow-roll inflation have been proposed over the years, one of the main motivations being to have a model, capable of generating observable values of non-Gaussianity. In this work, we (re-)explore the physical implications of a great majority of such models within a single, effective field theory framework (including novel models with large non-Gaussianity discussed for the first time below). The constraints we apply — both theoretical and experimental — are found to be rather robust, determined to a great extent by just three parameters: the coefficients of the quadratic EFT operators (δN){sup 2} and δNδE, andmore » the slow-roll parameter ε. This allows to significantly limit the majority of single-field alternatives to canonical slow-roll inflation. While the existing data still leaves some room for most of the considered models, the situation would change dramatically if the current upper limit on the tensor-to-scalar ratio decreased down to r<10{sup −2}. Apart from inflationary models driven by plateau-like potentials, the single-field model that would have a chance of surviving this bound is the recently proposed slow-roll inflation with weakly-broken galileon symmetry. In contrast to canonical slow-roll inflation, the latter model can support r<10{sup −2} even if driven by a convex potential, as well as generate observable values for the amplitude of non-Gaussianity.« less

Inference of soil hydrologic parameters from electronic soil moisture records

USDA-ARS?s Scientific Manuscript database

Soil moisture is an important control on hydrologic function, as it governs vertical fluxes from and to the atmosphere, groundwater recharge, and lateral fluxes through the soil. Historically, the traditional model parameters of saturation, field capacity, and permanent wilting point have been deter...

Bayesian population receptive field modelling.

PubMed

Zeidman, Peter; Silson, Edward Harry; Schwarzkopf, Dietrich Samuel; Baker, Chris Ian; Penny, Will

2017-09-08

We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental stimuli enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuronal and haemodynamic parameters are estimated together on a voxel-by-voxel or region-of-interest basis using a Bayesian estimation algorithm (variational Laplace). This offers several novel contributions to receptive field modelling. The variance/covariance of parameters are estimated, enabling receptive fields to be plotted while properly representing uncertainty about pRF size and location. Variability in the haemodynamic response across the brain is accounted for. Furthermore, the framework introduces formal hypothesis testing to pRF analysis, enabling competing models to be evaluated based on their log model evidence (approximated by the variational free energy), which represents the optimal tradeoff between accuracy and complexity. Using simulations and empirical data, we found that parameters typically used to represent pRF size and neuronal scaling are strongly correlated, which is taken into account by the Bayesian methods we describe when making inferences. We used the framework to compare the evidence for six variants of pRF model using 7 T functional MRI data and we found a circular Difference of Gaussians (DoG) model to be the best explanation for our data overall. We hope this framework will prove useful for mapping stimulus spaces with any number of dimensions onto the anatomy of the brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A study of the kinematic dynamo equation with time-dependent coefficients

NASA Technical Reports Server (NTRS)

Ko, Chung-Ming

1990-01-01

During an active star formation epoch the interstellar medium of a galaxy is in a hyperactive state, and the average turbulent velocity is higher than in the long periods between star formation epochs. The galactic magnetic field generated by dynamo action depends strongly on the turbulent velocity, so that generation of magnetic field should vary with star formation activity. This paper is a preliminary study of the kinematic dynamo equation with time-dependent coefficients simulating the time dependence of the star formation activities. Ko and Parker argued in a simple model that the thickness of the dynamo region is the most sensitive dynamo parameter. The present work shows that the effect of inflating the galactic disk suddenly is to transform a stationary magnetic field into a growing field while keeping the profile more or less intact. Plane wave solutions for a dynamo with power-law time-dependent parameters show that the field may decay first and then grow, and vice versa, which is quite different from a constant parameter dynamo.

SU-E-T-17: A Mathematical Model for PinPoint Chamber Correction in Measuring Small Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, T; Zhang, Y; Li, X

2014-06-01

Purpose: For small field dosimetry, such as measuring the cone output factor for stereotactic radiosurgery, ion chambers often result in underestimation of the dose, due to both the volume averaging effect and the lack of electron equilibrium. The purpose of this work is to develop a mathematical model, specifically for the pinpoint chamber, to calculate the correction factors corresponding to different type of small fields, including single cone-based circular field and non-standard composite fields. Methods: A PTW 0.015cc PinPoint chamber was used in the study. Its response in a certain field was modeled as the total contribution of many smallmore » beamlets, each with different response factor depending on the relative strength, radial distance to the chamber axis, and the beam angle. To get these factors, 12 cone-shaped circular fields (5mm,7.5mm, 10mm, 12.5mm, 15mm, 20mm, 25mm, 30mm, 35mm, 40mm, 50mm, 60mm) were irradiated and measured with the PinPoint chamber. For each field size, hundreds of readings were recorded for every 2mm chamber shift in the horizontal plane. These readings were then compared with the theoretical doses as obtained with Monte Carlo calculation. A penalized-least-square optimization algorithm was developed to find out the beamlet response factors. After the parameter fitting, the established mathematical model was validated with the same MC code for other non-circular fields. Results: The optimization algorithm used for parameter fitting was stable and the resulted response factors were smooth in spatial domain. After correction with the mathematical model, the chamber reading matched with the Monte Carlo calculation for all the tested fields to within 2%. Conclusion: A novel mathematical model has been developed for the PinPoint chamber for dosimetric measurement of small fields. The current model is applicable only when the beam axis is perpendicular to the chamber axis. It can be applied to non-standard composite fields. Further validation with other type of detectors is being conducted.« less

Simulation of aerobic and anaerobic biodegradation processes at a crude oil spill site

USGS Publications Warehouse

Essaid, Hedeff I.; Bekins, Barbara A.; Godsy, E. Michael; Warren, Ean; Baedecker, Mary Jo; Cozzarelli, Isabelle M.

1995-01-01

A two-dimensional, multispecies reactive solute transport model with sequential aerobic and anaerobic degradation processes was developed and tested. The model was used to study the field-scale solute transport and degradation processes at the Bemidji, Minnesota, crude oil spill site. The simulations included the biodegradation of volatile and nonvolatile fractions of dissolved organic carbon by aerobic processes, manganese and iron reduction, and methanogenesis. Model parameter estimates were constrained by published Monod kinetic parameters, theoretical yield estimates, and field biomass measurements. Despite the considerable uncertainty in the model parameter estimates, results of simulations reproduced the general features of the observed groundwater plume and the measured bacterial concentrations. In the simulation, 46% of the total dissolved organic carbon (TDOC) introduced into the aquifer was degraded. Aerobic degradation accounted for 40% of the TDOC degraded. Anaerobic processes accounted for the remaining 60% of degradation of TDOC: 5% by Mn reduction, 19% by Fe reduction, and 36% by methanogenesis. Thus anaerobic processes account for more than half of the removal of DOC at this site.

Specific heats and thermodynamic critical fields in Zn-doped YBa2Cu3O(7-x) according to an induced-pairing model

NASA Technical Reports Server (NTRS)

Eagles, D. M.

1993-01-01

Electronic specific heats and thermodynamic critical fields are calculated in a mean-field version of an induced-pairing model for superconductivity, and compared with results of Loram et al. (1990) on YBa2(Cu(1-y)Zn(y))3O(7-x). This model involves induction of pairing of holes in a wideband by strongly bound electronlike pairs. It is assumed that the planar hole concentration for no Zn addition is close to, but slightly higher than, that for the maximum Tc, and that it increases by 0.015 per planar Cu ion for each increase of y by 0.01. Parameters of the model are taken to be the same as in a previous publication in which energy gaps were discussed, except that an effective hybridization parameter is adjusted for each Zn concentration to give agreement with the observed Tc. Results are presented for y = 0.0, 0.01, and 0.03. The agreement with experiment is good for thermodynamic critical fields, and is fair for specific heats. For specimens with larger y, with relatively low T(c)s, it is argued that the model should be supplemented to include effects of a BCS-type interaction amongst the wideband carriers.

Automated optimization of water-water interaction parameters for a coarse-grained model.

PubMed

Fogarty, Joseph C; Chiu, See-Wing; Kirby, Peter; Jakobsson, Eric; Pandit, Sagar A

2014-02-13

We have developed an automated parameter optimization software framework (ParOpt) that implements the Nelder-Mead simplex algorithm and applied it to a coarse-grained polarizable water model. The model employs a tabulated, modified Morse potential with decoupled short- and long-range interactions incorporating four water molecules per interaction site. Polarizability is introduced by the addition of a harmonic angle term defined among three charged points within each bead. The target function for parameter optimization was based on the experimental density, surface tension, electric field permittivity, and diffusion coefficient. The model was validated by comparison of statistical quantities with experimental observation. We found very good performance of the optimization procedure and good agreement of the model with experiment.

Determining fundamental properties of matter created in ultrarelativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Novak, J.; Novak, K.; Pratt, S.; Vredevoogd, J.; Coleman-Smith, C. E.; Wolpert, R. L.

2014-03-01

Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamic-based transport models to experimental results from 100AGeV+100AGeV Au +Au collisions at the Relativistic Heavy Ion Collider. By simultaneously varying six parameters and by evaluating several classes of observables, we are able to explore the complex intertwined dependencies of observables on model parameters. The methods provide a full multidimensional posterior distribution for the model output, including a range of acceptable values for each parameter, and reveal correlations between them. The breadth of observables and the number of parameters considered here go beyond previous studies in this field. The statistical tools, which are based upon Gaussian process emulators, are tested in detail and should be extendable to larger data sets and a higher number of parameters.

Peristaltic Transport of Prandtl-Eyring Liquid in a Convectively Heated Curved Channel

PubMed Central

Hayat, Tasawar; Bibi, Shahida; Alsaadi, Fuad; Rafiq, Maimona

2016-01-01

Here peristaltic activity for flow of a Prandtl-Eyring material is modeled and analyzed for curved geometry. Heat transfer analysis is studied using more generalized convective conditions. The channel walls satisfy complaint walls properties. Viscous dissipation in the thermal equation accounted. Unlike the previous studies is for uniform magnetic field on this topic, the radial applied magnetic field has been utilized in the problems development. Solutions for stream function (ψ), velocity (u), and temperature (θ) for small parameter β have been derived. The salient features of heat transfer coefficient Z and trapping are also discussed for various parameters of interest including magnetic field, curvature, material parameters of fluid, Brinkman, Biot and compliant wall properties. Main observations of present communication have been included in the conclusion section. PMID:27304458

Petermann I and II spot size: Accurate semi analytical description involving Nelder-Mead method of nonlinear unconstrained optimization and three parameter fundamental modal field

NASA Astrophysics Data System (ADS)

Roy Choudhury, Raja; Roy Choudhury, Arundhati; Kanti Ghose, Mrinal

2013-01-01

A semi-analytical model with three optimizing parameters and a novel non-Gaussian function as the fundamental modal field solution has been proposed to arrive at an accurate solution to predict various propagation parameters of graded-index fibers with less computational burden than numerical methods. In our semi analytical formulation the optimization of core parameter U which is usually uncertain, noisy or even discontinuous, is being calculated by Nelder-Mead method of nonlinear unconstrained minimizations as it is an efficient and compact direct search method and does not need any derivative information. Three optimizing parameters are included in the formulation of fundamental modal field of an optical fiber to make it more flexible and accurate than other available approximations. Employing variational technique, Petermann I and II spot sizes have been evaluated for triangular and trapezoidal-index fibers with the proposed fundamental modal field. It has been demonstrated that, the results of the proposed solution identically match with the numerical results over a wide range of normalized frequencies. This approximation can also be used in the study of doped and nonlinear fiber amplifier.

Classifying the Sizes of Explosive Eruptions using Tephra Deposits: The Advantages of a Numerical Inversion Approach

NASA Astrophysics Data System (ADS)

Connor, C.; Connor, L.; White, J.

2015-12-01

Explosive volcanic eruptions are often classified by deposit mass and eruption column height. How well are these eruption parameters determined in older deposits, and how well can we reduce uncertainty using robust numerical and statistical methods? We describe an efficient and effective inversion and uncertainty quantification approach for estimating eruption parameters given a dataset of tephra deposit thickness and granulometry. The inversion and uncertainty quantification is implemented using the open-source PEST++ code. Inversion with PEST++ can be used with a variety of forward models and here is applied using Tephra2, a code that simulates advective and dispersive tephra transport and deposition. The Levenburg-Marquardt algorithm is combined with formal Tikhonov and subspace regularization to invert eruption parameters; a linear equation for conditional uncertainty propagation is used to estimate posterior parameter uncertainty. Both the inversion and uncertainty analysis support simultaneous analysis of the full eruption and wind-field parameterization. The combined inversion/uncertainty-quantification approach is applied to the 1992 eruption of Cerro Negro (Nicaragua), the 2011 Kirishima-Shinmoedake (Japan), and the 1913 Colima (Mexico) eruptions. These examples show that although eruption mass uncertainty is reduced by inversion against tephra isomass data, considerable uncertainty remains for many eruption and wind-field parameters, such as eruption column height. Supplementing the inversion dataset with tephra granulometry data is shown to further reduce the uncertainty of most eruption and wind-field parameters. We think the use of such robust models provides a better understanding of uncertainty in eruption parameters, and hence eruption classification, than is possible with more qualitative methods that are widely used.

Efficient Bayesian parameter estimation with implicit sampling and surrogate modeling for a vadose zone hydrological problem

NASA Astrophysics Data System (ADS)

Liu, Y.; Pau, G. S. H.; Finsterle, S.

2015-12-01

Parameter inversion involves inferring the model parameter values based on sparse observations of some observables. To infer the posterior probability distributions of the parameters, Markov chain Monte Carlo (MCMC) methods are typically used. However, the large number of forward simulations needed and limited computational resources limit the complexity of the hydrological model we can use in these methods. In view of this, we studied the implicit sampling (IS) method, an efficient importance sampling technique that generates samples in the high-probability region of the posterior distribution and thus reduces the number of forward simulations that we need to run. For a pilot-point inversion of a heterogeneous permeability field based on a synthetic ponded infiltration experiment simu­lated with TOUGH2 (a subsurface modeling code), we showed that IS with linear map provides an accurate Bayesian description of the parameterized permeability field at the pilot points with just approximately 500 forward simulations. We further studied the use of surrogate models to improve the computational efficiency of parameter inversion. We implemented two reduced-order models (ROMs) for the TOUGH2 forward model. One is based on polynomial chaos expansion (PCE), of which the coefficients are obtained using the sparse Bayesian learning technique to mitigate the "curse of dimensionality" of the PCE terms. The other model is Gaussian process regression (GPR) for which different covariance, likelihood and inference models are considered. Preliminary results indicate that ROMs constructed based on the prior parameter space perform poorly. It is thus impractical to replace this hydrological model by a ROM directly in a MCMC method. However, the IS method can work with a ROM constructed for parameters in the close vicinity of the maximum a posteriori probability (MAP) estimate. We will discuss the accuracy and computational efficiency of using ROMs in the implicit sampling procedure for the hydrological problem considered. This work was supported, in part, by the U.S. Dept. of Energy under Contract No. DE-AC02-05CH11231

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

MODELED MESOSCALE METEOROLOGICAL FIELDS WITH FOUR-DIMENSIONAL DATA ASSIMILATION IN REGIONAL SCALE AIR QUALITY MODELS

EPA Science Inventory

This paper addresses the need to increase the temporal and spatial resolution of meteorological data currently used in air quality simulation models, AQSMs. ransport and diffusion parameters including mixing heights and stability used in regulatory air quality dispersion models a...

Parameter uncertainty analysis for the annual phosphorus loss estimator (APLE) model

USDA-ARS?s Scientific Manuscript database

Technical abstract: Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analys...

Dispersive MHD Shock Properties and Interactions with Alfven Solitons

NASA Astrophysics Data System (ADS)

Hamilton, R.; Toll, K.; Ellis, C.

2017-12-01

The weakly nonlinear, weakly dispersive limit of Hall MHD with resistivity for 1D waves travelling nearly parallel to the ambient magnetic field reduces to the derivative nonlinear Schrödinger-Burgers (DNLSB) equation. This model equation describes the coupling between the Alfvenic and magnetosonic modes for a low b plasma. Without dissipation this model equation reduces to the DNLS which can be solved as an initial value problem using the Inverse Scattering Transformation through which the nonlinear component of the magnetic field profile can be represented as a combination of one-parameter bright and dark solitons as well as two-parameter solitons. The one-parameter solitons are constrained to travel at speeds ranging between the Alfvenic and magnetosonic characteristic speeds of the ambient field. We have found that these one-parameter solitons are effectively bound to a 1-2 Fast Shock and will pass back and forth across the shock until they are damped away with no apparent effect on the Fast Shock. A similar mechanism is expected for a sufficiently compressive Intermediate Shock as it arises simply from two effects: damping of a one-parameter soliton causes it to speed up and, if it does not damp away, it will eventually overtake the shock; passing forwards through a compressive shock the decrease of the field strength leads to a slowing of the soliton. We also discuss an extension of results [C. F. Kennel, R. D. Blandford, C. C. Wu, Phys. Fluids B 2(2), 1990] related to the time dependence of Intermediate Shocks in the presence of dispersion.

Mixing effects on apparent reaction rates and isotope fractionation during denitrification in a heterogeneous aquifer

USGS Publications Warehouse

Green, Christopher T.; Böhlke, John Karl; Bekins, Barbara A.; Phillips, Steven P.

2010-01-01

Gradients in contaminant concentrations and isotopic compositions commonly are used to derive reaction parameters for natural attenuation in aquifers. Differences between field‐scale (apparent) estimated reaction rates and isotopic fractionations and local‐scale (intrinsic) effects are poorly understood for complex natural systems. For a heterogeneous alluvial fan aquifer, numerical models and field observations were used to study the effects of physical heterogeneity on reaction parameter estimates. Field measurements included major ions, age tracers, stable isotopes, and dissolved gases. Parameters were estimated for the O2 reduction rate, denitrification rate, O2 threshold for denitrification, and stable N isotope fractionation during denitrification. For multiple geostatistical realizations of the aquifer, inverse modeling was used to establish reactive transport simulations that were consistent with field observations and served as a basis for numerical experiments to compare sample‐based estimates of “apparent” parameters with “true“ (intrinsic) values. For this aquifer, non‐Gaussian dispersion reduced the magnitudes of apparent reaction rates and isotope fractionations to a greater extent than Gaussian mixing alone. Apparent and true rate constants and fractionation parameters can differ by an order of magnitude or more, especially for samples subject to slow transport, long travel times, or rapid reactions. The effect of mixing on apparent N isotope fractionation potentially explains differences between previous laboratory and field estimates. Similarly, predicted effects on apparent O2threshold values for denitrification are consistent with previous reports of higher values in aquifers than in the laboratory. These results show that hydrogeological complexity substantially influences the interpretation and prediction of reactive transport.

Unsteady MHD blood flow through porous medium in a parallel plate channel

NASA Astrophysics Data System (ADS)

Latha, R.; Rushi Kumar, B.

2017-11-01

In this study, we have analyzed heat and mass transfer effects on unsteady blood flow through parallel plate channel in a saturated porous medium in the presence of a transverse magnetic field with thermal radiation. The governing higher order nonlinear PDE’S are converted to dimensionless equations using dimensionless variables. The dimensionless equations are then solved analytically using boundary conditions by choosing the axial flow transport and the fields of concentration and temperature apart from the normal velocity as a function of y and t. The effects of different pertinent parameters appeared in this model viz thermal radiation, Prandtl number, Heat source parameter, Hartmann number, Permeability parameter, Decay parameter on axial flow transport and the normal velocity are analyzed in detail.

Compact stars in the non-minimally coupled electromagnetic fields to gravity

NASA Astrophysics Data System (ADS)

Sert, Özcan

2018-03-01

We investigate the gravitational models with the non-minimal Y(R)F^2 coupled electromagnetic fields to gravity, in order to describe charged compact stars, where Y( R) denotes a function of the Ricci curvature scalar R and F^2 denotes the Maxwell invariant term. We determine two parameter family of exact spherically symmetric static solutions and the corresponding non-minimal model without assuming any relation between energy density of matter and pressure. We give the mass-radius, electric charge-radius ratios and surface gravitational redshift which are obtained by the boundary conditions. We reach a wide range of possibilities for the parameters k and α in these solutions. Lastly we show that the models can describe the compact stars even in the more simple case α =3.

Three-dimensional time domain model of lightning including corona effects

NASA Technical Reports Server (NTRS)

Podgorski, Andrew S.

1991-01-01

A new 3-D lightning model that incorporates the effect of corona is described for the first time. The new model is based on a Thin Wire Time Domain Lightning (TWTDL) Code developed previously. The TWTDL Code was verified during the 1985 and 1986 lightning seasons by the measurements conducted at the 553 m CN Tower in Toronto, Ontario. The inclusion of corona in the TWTDL code allowed study of the corona effects on the lightning current parameters and the associated electric field parameters.

α-Attractor and reheating in a model with noncanonical scalar fields

NASA Astrophysics Data System (ADS)

Rashidi, Narges; Nozari, Kourosh

We consider two noncanonical scalar fields [tachyon and Dirac-Born-Infeld (DBI)] with E-model type of the potential. We study cosmological inflation in these models to find possible α-attractors. We show that similar to the canonical scalar field case, in both tachyon and DBI models there is a value of the scalar spectral index in small α limit which is just a function of the e-folds number. However, the value of ns in DBI model is somewhat different from the other ones. We also compare the results with Planck2015 TT, TE, EE+lowP data. The reheating phase after inflation is studied in these models which gives some more constraints on the model parameters.

Abundance and recruitment data for Undaria pinnatifida in Brest harbour, France: Model versus field results.

PubMed

Murphy, James T; Voisin, Marie; Johnson, Mark; Viard, Frédérique

2016-06-01

The data presented in this article are related to the research article entitled "A modelling approach to explore the critical environmental parameters influencing the growth and establishment of the invasive seaweed Undaria pinnatifida in Europe" [1]. This article describes raw simulation data output from a novel individual-based model of the invasive kelp species Undaria pinnatifida. It also includes field data of monthly abundance and recruitment values for a population of invasive U. pinnatifida (in Brest harbour, France) that were used to validate the model. The raw model output and field data are made publicly available in order to enable critical analysis of the model predictions and to inform future modelling efforts of the study species.

Calibration of a biome-biogeochemical cycles model for modeling the net primary production of teak forests through inverse modeling of remotely sensed data

NASA Astrophysics Data System (ADS)

Imvitthaya, Chomchid; Honda, Kiyoshi; Lertlum, Surat; Tangtham, Nipon

2011-01-01

In this paper, we present the results of a net primary production (NPP) modeling of teak (Tectona grandis Lin F.), an important species in tropical deciduous forests. The biome-biogeochemical cycles or Biome-BGC model was calibrated to estimate net NPP through the inverse modeling approach. A genetic algorithm (GA) was linked with Biome-BGC to determine the optimal ecophysiological model parameters. The Biome-BGC was calibrated by adjusting the ecophysiological model parameters to fit the simulated LAI to the satellite LAI (SPOT-Vegetation), and the best fitness confirmed the high accuracy of generated ecophysioligical parameter from GA. The modeled NPP, using optimized parameters from GA as input data, was evaluated using daily NPP derived by the MODIS satellite and the annual field data in northern Thailand. The results showed that NPP obtained using the optimized ecophysiological parameters were more accurate than those obtained using default literature parameterization. This improvement occurred mainly because the model's optimized parameters reduced the bias by reducing systematic underestimation in the model. These Biome-BGC results can be effectively applied in teak forests in tropical areas. The study proposes a more effective method of using GA to determine ecophysiological parameters at the site level and represents a first step toward the analysis of the carbon budget of teak plantations at the regional scale.

Quasi 3D modelling of water flow in the sandy soil

NASA Astrophysics Data System (ADS)

Rezaei, Meisam; Seuntjens, Piet; Joris, Ingeborg; Boënne, Wesley; De Pue, Jan; Cornelis, Wim

2016-04-01

Monitoring and modeling tools may improve irrigation strategies in precision agriculture. Spatial interpolation is required for analyzing the effects of soil hydraulic parameters, soil layer thickness and groundwater level on irrigation management using hydrological models at field scale. We used non-invasive soil sensor, a crop growth (LINGRA-N) and a soil hydrological model (Hydrus-1D) to predict soil-water content fluctuations and crop yield in a heterogeneous sandy grassland soil under supplementary irrigation. In the first step, the sensitivity of the soil hydrological model to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed after integrating models at one soil column. Free drainage and incremental constant head conditions were implemented in a lower boundary sensitivity analysis. In the second step, to predict Ks over the whole field, the spatial distributions of Ks and its relationship between co-located soil ECa measured by a DUALEM-21S sensor were investigated. Measured groundwater levels and soil layer thickness were interpolated using ordinary point kriging (OK) to a 0.5 by 0.5 m in aim of digital elevation maps. In the third step, a quasi 3D modelling approach was conducted using interpolated data as input hydraulic parameter, geometric information and boundary conditions in the integrated model. In addition, three different irrigation scenarios namely current, no irrigation and optimized irrigations were carried out to find out the most efficient irrigation regime. In this approach, detailed field scale maps of soil water stress, water storage and crop yield were produced at each specific time interval to evaluate the best and most efficient distribution of water using standard gun sprinkler irrigation. The results show that the effect of the position of the groundwater level was dominant in soil-water content prediction and associated water stress. A time-dependent sensitivity analysis of the hydraulic parameters showed that changes in soil water content are mainly affected by the soil saturated hydraulic conductivity Ks in a two-layered soil. Results demonstrated the large spatial variability of Ks (CV = 86.21%). A significant negative correlation was found between ln Ks and ECa (r = 0.83; P≤0.01). This site-specific relation between ln Ks and ECa was used to predict Ks for the whole field after validation using an independent dataset of measured Ks. Result showed that this approach can accurately determine the field scale irrigation requirements, taking into account variations in boundary conditions and spatial variations of model parameters across the field. We found that uniform distribution of water using standard gun sprinkler irrigation is not an efficient approach since at locations with shallow groundwater, the amount of water applied will be excessive as compared to the crop requirements, while in locations with a deeper groundwater table, the crop irrigation requirements will not be met during crop water stress. Numerical results showed that optimal irrigation scheduling using the aforementioned water stress calculations can save up to ~25% irrigation water as compared to the current irrigation regime. This resulted in a yield increase of ~7%, simulated by the crop growth model.

A Bayesian approach to modeling diffraction profiles and application to ferroelectric materials

DOE PAGES

Iamsasri, Thanakorn; Guerrier, Jonathon; Esteves, Giovanni; ...

2017-02-01

A new statistical approach for modeling diffraction profiles is introduced, using Bayesian inference and a Markov chain Monte Carlo (MCMC) algorithm. This method is demonstrated by modeling the degenerate reflections during application of an electric field to two different ferroelectric materials: thin-film lead zirconate titanate (PZT) of composition PbZr 0.3Ti 0.7O 3and a bulk commercial PZT polycrystalline ferroelectric. Here, the new method offers a unique uncertainty quantification of the model parameters that can be readily propagated into new calculated parameters.

Is site-specific APEX calibration necessary for field scale BMP assessment?

USDA-ARS?s Scientific Manuscript database

The possibility of extending parameter sets obtained at one site to sites with similar characteristics is appealing. This study was undertaken to test model performance and compare the effectiveness of best management practices (BMPs) using three parameters sets obtained from three watersheds when a...

Image Discrimination Models With Stochastic Channel Selection

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

1995-01-01

Many models of human image processing feature a large fixed number of channels representing cortical units varying in spatial position (visual field direction and eccentricity) and spatial frequency (radial frequency and orientation). The values of these parameters are usually sampled at fixed values selected to ensure adequate overlap considering the bandwidth and/or spread parameters, which are usually fixed. Even high levels of overlap does not always ensure that the performance of the model will vary smoothly with image translation or scale changes. Physiological measurements of bandwidth and/or spread parameters result in a broad distribution of estimated parameter values and the prediction of some psychophysical results are facilitated by the assumption that these parameters also take on a range of values. Selecting a sample of channels from a continuum of channels rather than using a fixed set can make model performance vary smoothly with changes in image position, scale, and orientation. It also facilitates the addition of spatial inhomogeneity, nonlinear feature channels, and focus of attention to channel models.

Model verification of mixed dynamic systems. [POGO problem in liquid propellant rockets

NASA Technical Reports Server (NTRS)

Chrostowski, J. D.; Evensen, D. A.; Hasselman, T. K.

1978-01-01

A parameter-estimation method is described for verifying the mathematical model of mixed (combined interactive components from various engineering fields) dynamic systems against pertinent experimental data. The model verification problem is divided into two separate parts: defining a proper model and evaluating the parameters of that model. The main idea is to use differences between measured and predicted behavior (response) to adjust automatically the key parameters of a model so as to minimize response differences. To achieve the goal of modeling flexibility, the method combines the convenience of automated matrix generation with the generality of direct matrix input. The equations of motion are treated in first-order form, allowing for nonsymmetric matrices, modeling of general networks, and complex-mode analysis. The effectiveness of the method is demonstrated for an example problem involving a complex hydraulic-mechanical system.

Extended Czjzek model applied to NMR parameter distributions in sodium metaphosphate glass

NASA Astrophysics Data System (ADS)

Vasconcelos, Filipe; Cristol, Sylvain; Paul, Jean-François; Delevoye, Laurent; Mauri, Francesco; Charpentier, Thibault; Le Caër, Gérard

2013-06-01

The extended Czjzek model (ECM) is applied to the distribution of NMR parameters of a simple glass model (sodium metaphosphate, NaPO3) obtained by molecular dynamics (MD) simulations. Accurate NMR tensors, electric field gradient (EFG) and chemical shift anisotropy (CSA) are calculated from density functional theory (DFT) within the well-established PAW/GIPAW framework. The theoretical results are compared to experimental high-resolution solid-state NMR data and are used to validate the considered structural model. The distributions of the calculated coupling constant CQ ∝ |Vzz| and the asymmetry parameter ηQ that characterize the quadrupolar interaction are discussed in terms of structural considerations with the help of a simple point charge model. Finally, the ECM analysis is shown to be relevant for studying the distribution of CSA tensor parameters and gives new insight into the structural characterization of disordered systems by solid-state NMR.

Extended Czjzek model applied to NMR parameter distributions in sodium metaphosphate glass.

PubMed

Vasconcelos, Filipe; Cristol, Sylvain; Paul, Jean-François; Delevoye, Laurent; Mauri, Francesco; Charpentier, Thibault; Le Caër, Gérard

2013-06-26

The extended Czjzek model (ECM) is applied to the distribution of NMR parameters of a simple glass model (sodium metaphosphate, NaPO3) obtained by molecular dynamics (MD) simulations. Accurate NMR tensors, electric field gradient (EFG) and chemical shift anisotropy (CSA) are calculated from density functional theory (DFT) within the well-established PAW/GIPAW framework. The theoretical results are compared to experimental high-resolution solid-state NMR data and are used to validate the considered structural model. The distributions of the calculated coupling constant C(Q) is proportional to |V(zz)| and the asymmetry parameter η(Q) that characterize the quadrupolar interaction are discussed in terms of structural considerations with the help of a simple point charge model. Finally, the ECM analysis is shown to be relevant for studying the distribution of CSA tensor parameters and gives new insight into the structural characterization of disordered systems by solid-state NMR.

Development of an electrical model for integrated magnetic inductors

NASA Astrophysics Data System (ADS)

Bechir, M. B.; Yaya, D. D.; Youssouf, M. K.; Soultan, M.; Capraro, S.; Siblini, A.; Chatelon, J. P.; Rousseau, J. J.

2014-07-01

Nowadays, the current trend consists in the development of new technologies with the aim of reducing volume, weight as well as production cost. With the aim of decreasing occupied component area, it will be interesting to use magnetic materials to confine the fields. Therefore, our works concern the modelling and the characterization of magnetic planar inductors. The proposed model is detailed for inductors fabricated with one magnetic layer. The model can take into account, the capacitance between turns and the capacitance between the last turn and the ground plane, the magnetic permeability, the skin and proximity effects of the conductors according to the frequency. The structure of optimization developed to extract the parameters of the model will be presented. Results of extracted parameters are compared with the simulation parameters. A good correlation is observed on Y11 and Y12 parameters on all the broad band frequency.

POSSIBLE EVIDENCE FOR A FISK-TYPE HELIOSPHERIC MAGNETIC FIELD. I. ANALYZING ULYSSES/KET ELECTRON OBSERVATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sternal, O.; Heber, B.; Kopp, A.

The propagation of energetic charged particles in the heliospheric magnetic field is one of the fundamental problems in heliophysics. In particular, the structure of the heliospheric magnetic field remains an unsolved problem and is discussed as a controversial topic. The first successful analytic approach to the structure of the heliospheric magnetic field was the Parker field. However, the measurements of the Ulysses spacecraft at high latitudes revealed the possible need for refinements of the existing magnetic field model during solar minimum. Among other reasons, this led to the development of the Fisk field. This approach is highly debated and couldmore » not be ruled out with magnetic field measurements so far. A promising method to trace this magnetic field structure is to model the propagation of electrons in the energy range of a few MeV. Employing three-dimensional and time-dependent simulations of the propagation of energetic electrons, this work shows that the influence of a Fisk-type field on the particle transport in the heliosphere leads to characteristic variations of the electron intensities on the timescale of a solar rotation. For the first time it is shown that the Ulysses count rates of 2.5-7 MeV electrons contain the imprint of a Fisk-type heliospheric magnetic field structure. From a comparison of simulation results and the Ulysses count rates, realistic parameters for the Fisk theory are derived. Furthermore, these parameters are used to investigate the modeled relative amplitudes of protons and electrons, including the effects of drifts.« less

Theoretical modeling of the plasma-assisted catalytic growth and field emission properties of graphene sheet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Suresh C.; Gupta, Neha

2015-12-15

A theoretical modeling for the catalyst-assisted growth of graphene sheet in the presence of plasma has been investigated. It is observed that the plasma parameters can strongly affect the growth and field emission properties of graphene sheet. The model developed accounts for the charging rate of the graphene sheet; number density of electrons, ions, and neutral atoms; various elementary processes on the surface of the catalyst nanoparticle; surface diffusion and accretion of ions; and formation of carbon-clusters and large graphene islands. In our investigation, it is found that the thickness of the graphene sheet decreases with the plasma parameters, numbermore » density of hydrogen ions and RF power, and consequently, the field emission of electrons from the graphene sheet surface increases. The time evolution of the height of graphene sheet with ion density and sticking coefficient of carbon species has also been examined. Some of our theoretical results are in compliance with the experimental observations.« less

Predicting thermal history a-priori for magnetic nanoparticle hyperthermia of internal carcinoma

NASA Astrophysics Data System (ADS)

Dhar, Purbarun; Sirisha Maganti, Lakshmi

2017-08-01

This article proposes a simplistic and realistic method where a direct analytical expression can be derived for the temperature field within a tumour during magnetic nanoparticle hyperthermia. The approximated analytical expression for thermal history within the tumour is derived based on the lumped capacitance approach and considers all therapy protocols and parameters. The present method is simplistic and provides an easy framework for estimating hyperthermia protocol parameters promptly. The model has been validated with respect to several experimental reports on animal models such as mice/rabbit/hamster and human clinical trials. It has been observed that the model is able to accurately estimate the thermal history within the carcinoma during the hyperthermia therapy. The present approach may find implications in a-priori estimation of the thermal history in internal tumours for optimizing magnetic hyperthermia treatment protocols with respect to the ablation time, tumour size, magnetic drug concentration, field strength, field frequency, nanoparticle material and size, tumour location, and so on.

Cyclic steaming in heavy oil diatomite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, M.; Beatty, F.D.

1995-12-31

Chevron currently uses cyclic steaming as a recovery method to produce economically its heavy oil diatomite resource in the Cymric field, San Joaquin Valley, California. A highly instrumented, cyclically steaming well from this field was simulated in this study to delineate important production mechanisms, to optimize operations, and to improve reservoir management. The model was constrained, as much as possible, by the available measured data. Results show that fluid flow from the well to the reservoir is primarily through the hydraulic fracture induced by the injected steam. Parameters with unique importance to modeling cyclic steaming in diatomites are: (1) inducedmore » fracture dimension (length and height), (2) matrix permeability, (3) oil/water capillary pressure, (4) grid size perpendicular to fracture face, and (5) producing bottomhole pressures. Additionally, parameters important for conventional steam injection processes, such as relative permeabilities and injected steam volume, quality, and rate, are important for diatomites also. Oil production rates and steam/oil ratios calculated by this model compare reasonably with field data.« less

Study of potential health effects of electromagnetic fields of telephony and Wi-Fi, using chicken embryo development as animal model.

PubMed

Woelders, Henri; de Wit, Agnes; Lourens, Alexander; Stockhofe, Norbert; Engel, Bas; Hulsegge, Ina; Schokker, Dirkjan; van Heijningen, Paula; Vossen, Stefan; Bekers, Dave; Zwamborn, Peter

2017-04-01

The objective of this study is to investigate possible biological effects of radiofrequency electromagnetic fields (RF-EMF) as used in modern wireless telecommunication in a well-controlled experimental environment using chicken embryo development as animal model. Chicken eggs were incubated under continuous experimental exposure to GSM (1.8 GHz), DECT (1.88 GHz), UMTS (2.1 GHz), and WLAN (5.6 GHz) radiation, with the appropriate modulation protocol, using a homogeneous field distribution at a field strength of approximately 3 V/m, representing the maximum field level in a normal living environment. Radiation-shielded exposure units/egg incubators were operating in parallel for exposed and control eggs in a climatized homogeneous environment, using 450 eggs per treatment in three successive rounds per treatment. Dosimetry of the exposure (field characteristics and specific absorption rate) were studied. Biological parameters studied included embryo death during incubation, hatching percentage, and various morphological and histological parameters of embryos and chicks and their organs, and gene expression profiles of embryos on day 7 and day 18 of incubation by microarray and qPCR. No conclusive evidence was found for induced embryonic mortality or malformations by exposure to the used EMFs, or for effects on the other measured parameters. Estimated differences between treatment groups were always small and the effect of treatment was not significant. In a statistical model that ignored possible interaction between rounds and exposure units, some of the many pairwise comparisons of exposed versus control had P-values lower than 0.05, but were not significant after correction for multiple testing. Bioelectromagnetics. 38:186-203, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Assessment of municipal solid waste settlement models based on field-scale data analysis.

PubMed

Bareither, Christopher A; Kwak, Seungbok

2015-08-01

An evaluation of municipal solid waste (MSW) settlement model performance and applicability was conducted based on analysis of two field-scale datasets: (1) Yolo and (2) Deer Track Bioreactor Experiment (DTBE). Twelve MSW settlement models were considered that included a range of compression behavior (i.e., immediate compression, mechanical creep, and biocompression) and range of total (2-22) and optimized (2-7) model parameters. A multi-layer immediate settlement analysis developed for Yolo provides a framework to estimate initial waste thickness and waste thickness at the end-of-immediate compression. Model application to the Yolo test cells (conventional and bioreactor landfills) via least squares optimization yielded high coefficient of determinations for all settlement models (R(2)>0.83). However, empirical models (i.e., power creep, logarithmic, and hyperbolic models) are not recommended for use in MSW settlement modeling due to potential non-representative long-term MSW behavior, limited physical significance of model parameters, and required settlement data for model parameterization. Settlement models that combine mechanical creep and biocompression into a single mathematical function constrain time-dependent settlement to a single process with finite magnitude, which limits model applicability. Overall, all models evaluated that couple multiple compression processes (immediate, creep, and biocompression) provided accurate representations of both Yolo and DTBE datasets. A model presented in Gourc et al. (2010) included the lowest number of total and optimized model parameters and yielded high statistical performance for all model applications (R(2)⩾0.97). Copyright © 2015 Elsevier Ltd. All rights reserved.

Simulation of carbohydrates, from molecular docking to dynamics in water.

PubMed

Sapay, Nicolas; Nurisso, Alessandra; Imberty, Anne

2013-01-01

Modeling of carbohydrates is particularly challenging because of the variety of structures resulting for the high number of monosaccharides and possible linkages and also because of their intrinsic flexibility. The development of carbohydrate parameters for molecular modeling is still an active field. Nowadays, main carbohydrates force fields are GLYCAM06, CHARMM36, and GROMOS 45A4. GLYCAM06 includes the largest choice of compounds and is compatible with the AMBER force fields and associated. Furthermore, AMBER includes tools for the implementation of new parameters. When looking at protein-carbohydrate interaction, the choice of the starting structure is of importance. Such complex can be sometimes obtained from the Protein Data Bank-although the stereochemistry of sugars may require some corrections. When no experimental data is available, molecular docking simulation is generally used to the obtain protein-carbohydrate complex coordinates. As molecular docking parameters are not specifically dedicated to carbohydrates, inaccuracies should be expected, especially for the docking of polysaccharides. This issue can be addressed at least partially by combining molecular docking with molecular dynamics simulation in water.

The effects of small field dosimetry on the biological models used in evaluating IMRT dose distributions

NASA Astrophysics Data System (ADS)

Cardarelli, Gene A.

The primary goal in radiation oncology is to deliver lethal radiation doses to tumors, while minimizing dose to normal tissue. IMRT has the capability to increase the dose to the targets and decrease the dose to normal tissue, increasing local control, decrease toxicity and allow for effective dose escalation. This advanced technology does present complex dose distributions that are not easily verified. Furthermore, the dose inhomogeneity caused by non-uniform dose distributions seen in IMRT treatments has caused the development of biological models attempting to characterize the dose-volume effect in the response of organized tissues to radiation. Dosimetry of small fields can be quite challenging when measuring dose distributions for high-energy X-ray beams used in IMRT. The proper modeling of these small field distributions is essential in reproducing accurate dose for IMRT. This evaluation was conducted to quantify the effects of small field dosimetry on IMRT plan dose distributions and the effects on four biological model parameters. The four biological models evaluated were: (1) the generalized Equivalent Uniform Dose (gEUD), (2) the Tumor Control Probability (TCP), (3) the Normal Tissue Complication Probability (NTCP) and (4) the Probability of uncomplicated Tumor Control (P+). These models are used to estimate local control, survival, complications and uncomplicated tumor control. This investigation compares three distinct small field dose algorithms. Dose algorithms were created using film, small ion chamber, and a combination of ion chamber measurements and small field fitting parameters. Due to the nature of uncertainties in small field dosimetry and the dependence of biological models on dose volume information, this examination quantifies the effects of small field dosimetry techniques on radiobiological models and recommends pathways to reduce the errors in using these models to evaluate IMRT dose distributions. This study demonstrates the importance of valid physical dose modeling prior to the use of biological modeling. The success of using biological function data, such as hypoxia, in clinical IMRT planning will greatly benefit from the results of this study.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

Inverse modeling of geochemical and mechanical compaction in sedimentary basins

NASA Astrophysics Data System (ADS)

Colombo, Ivo; Porta, Giovanni Michele; Guadagnini, Alberto

2015-04-01

We study key phenomena driving the feedback between sediment compaction processes and fluid flow in stratified sedimentary basins formed through lithification of sand and clay sediments after deposition. Processes we consider are mechanic compaction of the host rock and the geochemical compaction due to quartz cementation in sandstones. Key objectives of our study include (i) the quantification of the influence of the uncertainty of the model input parameters on the model output and (ii) the application of an inverse modeling technique to field scale data. Proper accounting of the feedback between sediment compaction processes and fluid flow in the subsurface is key to quantify a wide set of environmentally and industrially relevant phenomena. These include, e.g., compaction-driven brine and/or saltwater flow at deep locations and its influence on (a) tracer concentrations observed in shallow sediments, (b) build up of fluid overpressure, (c) hydrocarbon generation and migration, (d) subsidence due to groundwater and/or hydrocarbons withdrawal, and (e) formation of ore deposits. Main processes driving the diagenesis of sediments after deposition are mechanical compaction due to overburden and precipitation/dissolution associated with reactive transport. The natural evolution of sedimentary basins is characterized by geological time scales, thus preventing direct and exhaustive measurement of the system dynamical changes. The outputs of compaction models are plagued by uncertainty because of the incomplete knowledge of the models and parameters governing diagenesis. Development of robust methodologies for inverse modeling and parameter estimation under uncertainty is therefore crucial to the quantification of natural compaction phenomena. We employ a numerical methodology based on three building blocks: (i) space-time discretization of the compaction process; (ii) representation of target output variables through a Polynomial Chaos Expansion (PCE); and (iii) model inversion (parameter estimation) within a maximum likelihood framework. In this context, the PCE-based surrogate model enables one to (i) minimize the computational cost associated with the (forward and inverse) modeling procedures leading to uncertainty quantification and parameter estimation, and (ii) compute the full set of Sobol indices quantifying the contribution of each uncertain parameter to the variability of target state variables. Results are illustrated through the simulation of one-dimensional test cases. The analyses focuses on the calibration of model parameters through literature field cases. The quality of parameter estimates is then analyzed as a function of number, type and location of data.

Semiempirical Two-Dimensional Magnetohydrodynamic Model of the Solar Corona and Interplanetary Medium

NASA Technical Reports Server (NTRS)

Sittler, Edward C., Jr.; Guhathakurta, Madhulika

1999-01-01

We have developed a two-dimensional semiempirical MHD model of the solar corona and solar wind. The model uses empirically derived electron density profiles from white-light coronagraph data measured during the Skylub period and an empirically derived model of the magnetic field which is fitted to observed streamer topologies, which also come from the white-light coronagraph data The electron density model comes from that developed by Guhathakurta and coworkers. The electron density model is extended into interplanetary space by using electron densities derived from the Ulysses plasma instrument. The model also requires an estimate of the solar wind velocity as a function of heliographic latitude and radial component of the magnetic field at 1 AU, both of which can be provided by the Ulysses spacecraft. The model makes estimates as a function of radial distance and latitude of various fluid parameters of the plasma such as flow velocity V, effective temperature T(sub eff), and effective heat flux q(sub eff), which are derived from the equations of conservation of mass, momentum, and energy, respectively. The term effective indicates that wave contributions could be present. The model naturally provides the spiral pattern of the magnetic field far from the Sun and an estimate of the large-scale surface magnetic field at the Sun, which we estimate to be approx. 12 - 15 G. The magnetic field model shows that the large-scale surface magnetic field is dominated by an octupole term. The model is a steady state calculation which makes the assumption of azimuthal symmetry and solves the various conservation equations in the rotating frame of the Sun. The conservation equations are integrated along the magnetic field direction in the rotating frame of the Sun, thus providing a nearly self-consistent calculation of the fluid parameters. The model makes a minimum number of assumptions about the physics of the solar corona and solar wind and should provide a very accurate empirical description of the solar corona and solar wind Once estimates of mass density rho, flow velocity V, effective temperature T(sub eff), effective heat flux q(sub eff), and magnetic field B are computed from the model and waves are assumed unimportant, all other plasma parameters such as Mach number, Alfven speed, gyrofrequency, etc. can be derived as a function of radial distance and latitude from the Sun. The model can be used as a planning tool for such missions as Slar Probe and provide an empirical framework for theoretical models of the solar corona and solar wind The model will be used to construct a semiempirical MHD description of the steady state solar corona and solar wind using the SOHO Large Angle Spectrometric Coronagraph (LASCO) polarized brightness white-light coronagraph data, SOHO Extreme Ultraviolet Imaging Telescope data, and Ulysses plasma data.

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

Constraining cosmologies with fundamental constants - I. Quintessence and K-essence

NASA Astrophysics Data System (ADS)

Thompson, Rodger I.; Martins, C. J. A. P.; Vielzeuf, P. E.

2013-01-01

Many cosmological models invoke rolling scalar fields to account for the observed acceleration of the expansion of the Universe. These theories generally include a potential V(φ) which is a function of the scalar field φ. Although V(φ) can be represented by a very diverse set of functions, recent work has shown that under some conditions, such as the slow-roll conditions, the equation of state parameter w is either independent of the form of V(φ) or part of family of solutions with only a few parameters. In realistic models of this type the scalar field couples to other sectors of the model leading to possibly observable changes in the fundamental constants such as the fine structure constant α and the proton to electron mass ratio μ. Although the current situation on a possible variance of α is complicated, there are firm limitations on the variance of μ in the early universe. This paper explores the limits this puts on the validity of various cosmologies that invoke rolling scalar fields. We find that the limit on the variation of μ puts significant constraints on the product of a cosmological parameter w + 1 and a new physics parameter ζ2μ, the coupling constant between μ and the rolling scalar field. Even when the cosmologies are restricted to very slow roll conditions either the value of ζμ must be at the lower end of or less than its expected values or the value of w + 1 must be restricted to values vanishingly close to 0. This implies that either the rolling scalar field is very weakly coupled to the electromagnetic field, small ζμ, very weakly coupled to gravity, (w + 1) ≈ 0 or both. These results stress that adherence to the measured invariance in μ is a very significant test of the validity of any proposed cosmology and any new physics it requires. The limits on the variation of μ also produces a significant tension with the reported changes in the value of α.

Inflationary universe in deformed phase space scenario

NASA Astrophysics Data System (ADS)

Rasouli, S. M. M.; Saba, Nasim; Farhoudi, Mehrdad; Marto, João; Moniz, P. V.

2018-06-01

We consider a noncommutative (NC) inflationary model with a homogeneous scalar field minimally coupled to gravity. The particular NC inflationary setting herein proposed, produces entirely new consequences as summarized in what follows. We first analyze the free field case and subsequently examine the situation where the scalar field is subjected to a polynomial and exponential potentials. We propose to use a canonical deformation between momenta, in a spatially flat Friedmann-Lemaî tre-Robertson-Walker (FLRW) universe, and while the Friedmann equation (Hamiltonian constraint) remains unaffected the Friedmann acceleration equation (and thus the Klein-Gordon equation) is modified by an extra term linear in the NC parameter. This concrete noncommutativity on the momenta allows interesting dynamics that other NC models seem not to allow. Let us be more precise. This extra term behaves as the sole explicit pressure that under the right circumstances implies a period of accelerated expansion of the universe. We find that in the absence of the scalar field potential, and in contrast with the commutative case, in which the scale factor always decelerates, we obtain an inflationary phase for small negative values of the NC parameter. Subsequently, the period of accelerated expansion is smoothly replaced by an appropriate deceleration phase providing an interesting model regarding the graceful exit problem in inflationary models. This last property is present either in the free field case or under the influence of the scalar field potentials considered here. Moreover, in the case of the free scalar field, we show that not only the horizon problem is solved but also there is some resemblance between the evolution equation of the scale factor associated to our model and that for the R2 (Starobinsky) inflationary model. Therefore, our herein NC model not only can be taken as an appropriate scenario to get a successful kinetic inflation, but also is a convenient setting to obtain inflationary universe possessing the graceful exit when scalar field potentials are present.

[Parameter sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model].

PubMed

He, Li-hong; Wang, Hai-yan; Lei, Xiang-dong

2016-02-01

Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.

Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information

DOE PAGES

Covey, Curt; Lucas, Donald D.; Tannahill, John; ...

2013-07-01

Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less

A general framework to test gravity using galaxy clusters - I. Modelling the dynamical mass of haloes in f(R) gravity

NASA Astrophysics Data System (ADS)

Mitchell, Myles A.; He, Jian-hua; Arnold, Christian; Li, Baojiu

2018-06-01

We propose a new framework for testing gravity using cluster observations, which aims to provide an unbiased constraint on modified gravity models from Sunyaev-Zel'dovich (SZ) and X-ray cluster counts and the cluster gas fraction, among other possible observables. Focusing on a popular f(R) model of gravity, we propose a novel procedure to recalibrate mass scaling relations from Λ cold dark matter (ΛCDM) to f(R) gravity for SZ and X-ray cluster observables. We find that the complicated modified gravity effects can be simply modelled as a dependence on a combination of the background scalar field and redshift, fR(z)/(1 + z), regardless of the f(R) model parameter. By employing a large suite of N-body simulations, we demonstrate that a theoretically derived tanh fitting formula is in excellent agreement with the dynamical mass enhancement of dark matter haloes for a large range of background field parameters and redshifts. Our framework is sufficiently flexible to allow for tests of other models and inclusion of further observables, and the one-parameter description of the dynamical mass enhancement can have important implications on the theoretical modelling of observables and on practical tests of gravity.

Small traveling clusters in attractive and repulsive Hamiltonian mean-field models.

PubMed

Barré, Julien; Yamaguchi, Yoshiyuki Y

2009-03-01

Long-lasting small traveling clusters are studied in the Hamiltonian mean-field model by comparing between attractive and repulsive interactions. Nonlinear Landau damping theory predicts that a Gaussian momentum distribution on a spatially homogeneous background permits the existence of traveling clusters in the repulsive case, as in plasma systems, but not in the attractive case. Nevertheless, extending the analysis to a two-parameter family of momentum distributions of Fermi-Dirac type, we theoretically predict the existence of traveling clusters in the attractive case; these findings are confirmed by direct N -body numerical simulations. The parameter region with the traveling clusters is much reduced in the attractive case with respect to the repulsive case.

Decay properties and reaction dynamics of zirconium isotopes in the relativistic mean-field model

NASA Astrophysics Data System (ADS)

Panigrahi, M.; Panda, R. N.; Kumar, Bharat; Patra, S. K.

In the framework of relativistic mean-field theory, the ground state properties like binding energy, charge radius and quadrupole deformation parameter for various isotopes of zirconium from the valley of stability to drip-line region have been studied. The results are compared with the experimental data and we found reasonable agreement. The calculations are carried out for β-decay energy and β-decay half-life up to the drip-line. Total reaction and elastic differential cross-sections are also studied for few zirconium isotopes as projectiles with 12C as target, using different parameter sets namely NL3*, DD-ME2 and DD-PC1 in conjunction with Glauber model.

Improved methods for the measurement and analysis of stellar magnetic fields

NASA Technical Reports Server (NTRS)

Saar, Steven H.

1988-01-01

The paper presents several improved methods for the measurement of magnetic fields on cool stars which take into account simple radiative transfer effects and the exact Zeeman patterns. Using these methods, high-resolution, low-noise data can be fitted with theoretical line profiles to determine the mean magnetic field strength in stellar active regions and a model-dependent fraction of the stellar surface (filling factor) covered by these regions. Random errors in the derived field strength and filling factor are parameterized in terms of signal-to-noise ratio, wavelength, spectral resolution, stellar rotation rate, and the magnetic parameters themselves. Weak line blends, if left uncorrected, can have significant systematic effects on the derived magnetic parameters, and thus several methods are developed to compensate partially for them. The magnetic parameters determined by previous methods likely have systematic errors because of such line blends and because of line saturation effects. Other sources of systematic error are explored in detail. These sources of error currently make it difficult to determine the magnetic parameters of individual stars to better than about + or - 20 percent.

A database for propagation models

NASA Technical Reports Server (NTRS)

Kantak, Anil V.; Suwitra, Krisjani; Le, Choung

1993-01-01

The NASA Propagation Program supports academic research that models various propagation phenomena in the space research frequency bands. NASA supports such research via school and institutions prominent in the field. The products of such efforts are particularly useful for researchers in the field of propagation phenomena and telecommunications systems engineers. The systems engineer usually needs a few propagation parameter values for a system design. Published literature on the subject, such as the Cunsultative Committee for International Radio (CCIR) publications, may help somewhat, but often times, the parameter values given in such publications use a particular set of conditions which may not quite include the requirements of the system design. The systems engineer must resort to programming the propagation phenomena model of interest and to obtain the parameter values to be used in the project. Furthermore, the researcher in the propagation field must then program the propagation models either to substantiate the model or to generate a new model. The researcher or the systems engineer must either be a skillful computer programmer or hire a programmer, which of course increases the cost of the effort. An increase in cost due to the inevitable programming effort may seem particularly inappropriate if the data generated by the experiment is to be used to substantiate the already well-established models, or a slight variation thereof. To help researchers and the systems engineers, it was recommended by the participants of NASA Propagation Experimenters (NAPEX) 15 held in London, Ontario, Canada on 28-29 June 1991, that propagation software should be constructed which will contain models and prediction methods of most propagation phenomenon. Moreover, the software should be flexible enough for the user to make slight changes to the models without expending a substantial effort in programming.

A sensitivity analysis of a surface energy balance model to LAI (Leaf Area Index)

NASA Astrophysics Data System (ADS)

Maltese, A.; Cannarozzo, M.; Capodici, F.; La Loggia, G.; Santangelo, T.

2008-10-01

The LAI is a key parameter in hydrological processes, especially in the physically based distribution models. It is a critical ecosystem attribute since physiological processes such as photosynthesis, transpiration and evaporation depend on it. The diffusion of water vapor, momentum, heat and light through the canopy is regulated by the distribution and density of the leaves, branches, twigs and stems. The LAI influences the sensible heat flux H in the surface energy balance single source models through the calculation of the roughness length and of the displacement height. The aerodynamic resistance between the soil and within-canopy source height is a function of the LAI through the roughness length. This research carried out a sensitivity analysis of some of the most important parameters of surface energy balance models to the LAI time variation, in order to take into account the effects of the LAI variation with the phenological period. Finally empirical retrieved relationships between field spectroradiometric data and the field LAI measured via a light-sensitive instrument are presented for a cereal field.

A dissipative random velocity field for fully developed fluid turbulence

NASA Astrophysics Data System (ADS)

Chevillard, Laurent; Pereira, Rodrigo; Garban, Christophe

2016-11-01

We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent flow. A key step in the construction of this model is the introduction of some aspects of the vorticity stretching mechanism that governs the dynamics of fluid particles along their trajectory. An additional further phenomenological step aimed at including the long range correlated nature of turbulence makes this model depending on a single free parameter that can be estimated from experimental measurements. We confirm the realism of the model regarding the geometry of the velocity gradient tensor, the power-law behaviour of the moments of velocity increments, including the intermittent corrections, and the existence of energy transfers across scales. We quantify the dependence of these basic properties of turbulent flows on the free parameter and derive analytically the spectrum of exponents of the structure functions in a simplified non dissipative case. A perturbative expansion shows that energy transfers indeed take place, justifying the dissipative nature of this random field.

Constitutive models for the Etchegoin Sands, Belridge Diatomite, and overburden formations at the Lost Hills oil field, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

FOSSUM,ARLO F.; FREDRICH,JOANNE T.

2000-04-01

This report documents the development of constitutive material models for the overburden formations, reservoir formations, and underlying strata at the Lost Hills oil field located about 45 miles northwest of Bakersfield in Kern County, California. Triaxial rock mechanics tests were performed on specimens prepared from cores recovered from the Lost Hills field, and included measurements of axial and radial stresses and strains under different load paths. The tested intervals comprise diatomaceous sands of the Etchegoin Formation and several diatomite types of the Belridge Diatomite Member of the Monterey Formation, including cycles both above and below the diagenetic phase boundary betweenmore » opal-A and opal-CT. The laboratory data are used to drive constitutive parameters for the Extended Sandler-Rubin (ESR) cap model that is implemented in Sandia's structural mechanics finite element code JAS3D. Available data in the literature are also used to derive ESR shear failure parameters for overburden formations. The material models are being used in large-scale three-dimensional geomechanical simulations of the reservoir behavior during primary and secondary recovery.« less

Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates

NASA Astrophysics Data System (ADS)

Small, Meagan C.; Aytenfisu, Asaminew H.; Lin, Fang-Yu; He, Xibing; MacKerell, Alexander D.

2017-04-01

The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars ( d-allose and d-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars d-allose and d-psicose, thereby extending the available biomolecules in the Drude polarizable FF.

Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates.

PubMed

Small, Meagan C; Aytenfisu, Asaminew H; Lin, Fang-Yu; He, Xibing; MacKerell, Alexander D

2017-04-01

The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars (D-allose and D-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars D-allose and D-psicose, thereby extending the available biomolecules in the Drude polarizable FF.

Drude Polarizable Force Field for Aliphatic Ketones and Aldehydes, and their Associated Acyclic Carbohydrates

PubMed Central

Small, Meagan C.; Aytenfisu, Asaminew H.; Lin, Fang-Yu; He, Xibing; MacKerell, Alexander D.

2017-01-01

The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars (D-allose and D-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars D-allose and D-psicose, thereby extending the available biomolecules in the Drude polarizable FF. PMID:28190218

Microwave remote sensing and radar polarization signatures of natural fields

NASA Technical Reports Server (NTRS)

Mo, Tsan

1989-01-01

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

Implementation and comparative analysis of the optimisations produced by evolutionary algorithms for the parameter extraction of PSP MOSFET model

NASA Astrophysics Data System (ADS)

Hadia, Sarman K.; Thakker, R. A.; Bhatt, Kirit R.

2016-05-01

The study proposes an application of evolutionary algorithms, specifically an artificial bee colony (ABC), variant ABC and particle swarm optimisation (PSO), to extract the parameters of metal oxide semiconductor field effect transistor (MOSFET) model. These algorithms are applied for the MOSFET parameter extraction problem using a Pennsylvania surface potential model. MOSFET parameter extraction procedures involve reducing the error between measured and modelled data. This study shows that ABC algorithm optimises the parameter values based on intelligent activities of honey bee swarms. Some modifications have also been applied to the basic ABC algorithm. Particle swarm optimisation is a population-based stochastic optimisation method that is based on bird flocking activities. The performances of these algorithms are compared with respect to the quality of the solutions. The simulation results of this study show that the PSO algorithm performs better than the variant ABC and basic ABC algorithm for the parameter extraction of the MOSFET model; also the implementation of the ABC algorithm is shown to be simpler than that of the PSO algorithm.

Do all leaf photosynthesis parameters of rice acclimate to elevated CO2 , elevated temperature, and their combination, in FACE environments?

PubMed

Cai, Chuang; Li, Gang; Yang, Hailong; Yang, Jiaheng; Liu, Hong; Struik, Paul C; Luo, Weihong; Yin, Xinyou; Di, Lijun; Guo, Xuanhe; Jiang, Wenyu; Si, Chuanfei; Pan, Genxing; Zhu, Jianguo

2018-04-01

Leaf photosynthesis of crops acclimates to elevated CO 2 and temperature, but studies quantifying responses of leaf photosynthetic parameters to combined CO 2 and temperature increases under field conditions are scarce. We measured leaf photosynthesis of rice cultivars Changyou 5 and Nanjing 9108 grown in two free-air CO 2 enrichment (FACE) systems, respectively, installed in paddy fields. Each FACE system had four combinations of two levels of CO 2 (ambient and enriched) and two levels of canopy temperature (no warming and warmed by 1.0-2.0°C). Parameters of the C 3 photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model), and of a stomatal conductance (g s ) model were estimated for the four conditions. Most photosynthetic parameters acclimated to elevated CO 2 , elevated temperature, and their combination. The combination of elevated CO 2 and temperature changed the functional relationships between biochemical parameters and leaf nitrogen content for Changyou 5. The g s model significantly underestimated g s under the combination of elevated CO 2 and temperature by 19% for Changyou 5 and by 10% for Nanjing 9108 if no acclimation was assumed. However, our further analysis applying the coupled g s -FvCB model to an independent, previously published FACE experiment showed that including such an acclimation response of g s hardly improved prediction of leaf photosynthesis under the four combinations of CO 2 and temperature. Therefore, the typical procedure that crop models using the FvCB and g s models are parameterized from plants grown under current ambient conditions may not result in critical errors in projecting productivity of paddy rice under future global change. © 2017 John Wiley & Sons Ltd.

Supergravity backgrounds for deformations of AdS n × S n supercoset string models

DOE PAGES

Lunin, O.; Roiban, R.; Tseytlin, A. A.

2014-12-11

We considermore » type IIB supergravity backgrounds corresponding to the deformed AdS n × S n × T 10 - 2 n supercoset string models of the type constructed in arXiv:1309.5850[2] which depend on one deformation parameter κ. In AdS 2 × S 2 case we find that the deformed metric can be extended to a full supergravity solution with non-trivial dilaton, RR scalar and RR 5-form strength. The solution depends on a free parameter a that should be chosen as a particular function of κ to correspond to the deformed supercoset model. In AdS 3 × S 3 case the full solution supported by the dilaton, RR scalar and RR 3-form strength exists only in the two special cases, a = 0 and a = 1 . We conjecture that there may be a more general one-parameter solution supported by several RR fields that for particular a = a ( κ ) corresponds to the supercoset model. In the most complicated deformed AdS 5 × S 5 case we were able to find only the expressions for the dilaton and the RR scalar. The full solution is likely to be supported by a combination of the 5-form and 3-form field strengths. We comment on the singularity structure of the resulting metric and exact dilaton field.« less

Supergravity backgrounds for deformations of AdS n × S n supercoset string models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lunin, O.; Roiban, R.; Tseytlin, A. A.

We considermore » type IIB supergravity backgrounds corresponding to the deformed AdS n × S n × T 10 - 2 n supercoset string models of the type constructed in arXiv:1309.5850[2] which depend on one deformation parameter κ. In AdS 2 × S 2 case we find that the deformed metric can be extended to a full supergravity solution with non-trivial dilaton, RR scalar and RR 5-form strength. The solution depends on a free parameter a that should be chosen as a particular function of κ to correspond to the deformed supercoset model. In AdS 3 × S 3 case the full solution supported by the dilaton, RR scalar and RR 3-form strength exists only in the two special cases, a = 0 and a = 1 . We conjecture that there may be a more general one-parameter solution supported by several RR fields that for particular a = a ( κ ) corresponds to the supercoset model. In the most complicated deformed AdS 5 × S 5 case we were able to find only the expressions for the dilaton and the RR scalar. The full solution is likely to be supported by a combination of the 5-form and 3-form field strengths. We comment on the singularity structure of the resulting metric and exact dilaton field.« less

Characterizations of pumping-induced land subsidence in coastal aquifers - model development and field-scale implementations

NASA Astrophysics Data System (ADS)

Ni, C.; Huang, Y.; Lu, C.

2012-12-01

The pumping-induced land subsidence events are typically founded in coastal aquifers in Taiwan especially in the areas of lower alluvial fans. Previous investigations have recognized the irreversible situation for an aquifer deformation even if the pumped water is significantly reduced or stopped. Long-term monitoring projects on land subsidence in Choshui alluvial fan in central Taiwan have improved the understanding of the deformations in the aquifer system. To characterization the detailed land subsidence mechanism, this study develops an inverse numerical model to estimate the deformation parameters such as the specific storage (Ss) and vertical hydraulic conductivity (Kv) for interbeds. Similar to the concept of Hydraulic tomography survey (HTS), the developed model employs the iterative cokriging estimator to improve the accuracy of estimating deformation parameters. A one-dimensional numerical example is employed to assess the accuracy of the developed inverse model. The developed model is then applied to field-scale data from compaction monitoring wells (CMW) installed in the lower Choshui River fan. Results of the synthetic example show that the developed inverse model can reproduce well the predefined geologic features of the synthetic aquifer. The model provides better estimations of Kv patterns and magnitudes. Slightly less detail of the Ss was obtained due to the insensitivity of transient stresses for specified sampling times. Without prior information from field measurements, the developed model associated with deformation measurements form CMW can estimate Kv and Ss fields with great spatial resolution.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

Saturn systems holddown acoustic efficiency and normalized acoustic power spectrum.

NASA Technical Reports Server (NTRS)

Gilbert, D. W.

1972-01-01

Saturn systems field acoustic data are used to derive mid- and far-field prediction parameters for rocket engine noise. The data were obtained during Saturn vehicle launches at the Kennedy Space Center. The data base is a sorted set of acoustic data measured during the period 1961 through 1971 for Saturn system launches SA-1 through AS-509. The model assumes hemispherical radiation from a simple source located at the intersection of the longitudinal axis of each booster and the engine exit plane. The model parameters are evaluated only during vehicle holddown. The acoustic normalized power spectrum and efficiency for each system are isolated as a composite from the data using linear numerical methods. The specific definitions of each allows separation. The resulting power spectra are nondimensionalized as a function of rocket engine parameters. The nondimensional Saturn system acoustic spectrum and efficiencies are compared as a function of Strouhal number with power spectra from other systems.

Effect of reaction control system jet-flow field interactions on a 0.015 scale model space shuttle orbiter aerodynamic characteristics

NASA Technical Reports Server (NTRS)

Monta, W. J.; Rausch, J. R.

1973-01-01

The effects of the reaction control system (RCS) jet-flow field interactions on the space shuttle orbiter system during entry are discussed. The primary objective of the test program was to obtain data for the shuttle orbiter configuration to determine control amplification factors resulting from jet interaction between the RCS plumes and the external flow over the vehicle. A secondary objective was to provide data for comparison and improvement of analytic jet interaction prediction techniques. The test program was divided into two phases; (1) force and moment measurements were made with and without RCS blowing, investigating environment parameters (R sub e, Alpha, Beta), RCS plume parameters (Jet pressure ratio, momentum ratio and thrust level), and geometry parameters (RCS pod locations) on the orbiter model, (2) oil flow visualization tests were conducted on a dummy balance at the end of the test.

How to deal with the high condition number of the noise covariance matrix of gravity field functionals synthesised from a satellite-only global gravity field model?

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-03-01

The posed question arises for instance in regional gravity field modelling using weighted least-squares techniques if the gravity field functionals are synthesised from the spherical harmonic coefficients of a satellite-only global gravity model (GGM), and are used as one of the noisy datasets. The associated noise covariance matrix, appeared to be extremely ill-conditioned with a singular value spectrum that decayed gradually to zero without any noticeable gap. We analysed three methods to deal with the ill-conditioned noise covariance matrix: Tihonov regularisation of the noise covariance matrix in combination with the standard formula for the weighted least-squares estimator, a formula of the weighted least-squares estimator, which does not involve the inverse noise covariance matrix, and an estimator based on Rao's unified theory of least-squares. Our analysis was based on a numerical experiment involving a set of height anomalies synthesised from the GGM GOCO05s, which is provided with a full noise covariance matrix. We showed that the three estimators perform similar, provided that the two regularisation parameters each method knows were chosen properly. As standard regularisation parameter choice rules do not apply here, we suggested a new parameter choice rule, and demonstrated its performance. Using this rule, we found that the differences between the three least-squares estimates were within noise. For the standard formulation of the weighted least-squares estimator with regularised noise covariance matrix, this required an exceptionally strong regularisation, much larger than one expected from the condition number of the noise covariance matrix. The preferred method is the inversion-free formulation of the weighted least-squares estimator, because of its simplicity with respect to the choice of the two regularisation parameters.

Two-field axion-monodromy hybrid inflation model: Dante's Waterfall

NASA Astrophysics Data System (ADS)

Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen

2015-02-01

We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.

Mitigating stimulated scattering processes in gas-filled Hohlraums via external magnetic fields

NASA Astrophysics Data System (ADS)

Gong, Tao; Zheng, Jian; Li, Zhichao; Ding, Yongkun; Yang, Dong; Hu, Guangyue; Zhao, Bin

2015-09-01

A simple model, based on energy and pressure equilibrium, is proposed to deal with the effect of external magnetic fields on the plasma parameters inside the laser path, which shows that the electron temperature can be significantly enhanced as the intensity of the external magnetic fields increases. With the combination of this model and a 1D three-wave coupling code, the effect of external magnetic fields on the reflectivities of stimulated scattering processes is studied. The results indicate that a magnetic field with an intensity of tens of Tesla can decrease the reflectivities of stimulated scattering processes by several orders of magnitude.