Stimuli Reduce the Dimensionality of Cortical Activity

PubMed Central

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models. PMID:26924968

Stimuli Reduce the Dimensionality of Cortical Activity.

PubMed

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

Normal forms for reduced stochastic climate models

PubMed Central

Majda, Andrew J.; Franzke, Christian; Crommelin, Daan

2009-01-01

The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high-dimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Here techniques from applied mathematics are utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. The use of a few Empirical Orthogonal Functions (EOFs) (also known as Principal Component Analysis, Karhunen–Loéve and Proper Orthogonal Decomposition) depending on observational data to span the low-frequency subspace requires the assessment of dyad interactions besides the more familiar triads in the interaction between the low- and high-frequency subspaces of the dynamics. It is shown below that the dyad and multiplicative triad interactions combine with the climatological linear operator interactions to simultaneously produce both strong nonlinear dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. For a single low-frequency variable the dyad interactions and climatological linear operator alone produce a normal form with CAM noise from advection of the large scales by the small scales and simultaneously strong cubic damping. These normal forms should prove useful for developing systematic strategies for the estimation of stochastic models from climate data. As an illustrative example the one-dimensional normal form is applied below to low-frequency patterns such as the North Atlantic Oscillation (NAO) in a climate model. The results here also illustrate the short comings of a recent linear scalar CAM noise model proposed elsewhere for low-frequency variability. PMID:19228943

Reducing the two-loop large-scale structure power spectrum to low-dimensional, radial integrals

DOE PAGES

Schmittfull, Marcel; Vlah, Zvonimir

2016-11-28

Modeling the large-scale structure of the universe on nonlinear scales has the potential to substantially increase the science return of upcoming surveys by increasing the number of modes available for model comparisons. One way to achieve this is to model nonlinear scales perturbatively. Unfortunately, this involves high-dimensional loop integrals that are cumbersome to evaluate. Here, trying to simplify this, we show how two-loop (next-to-next-to-leading order) corrections to the density power spectrum can be reduced to low-dimensional, radial integrals. Many of those can be evaluated with a one-dimensional fast Fourier transform, which is significantly faster than the five-dimensional Monte-Carlo integrals thatmore » are needed otherwise. The general idea of this fast fourier transform perturbation theory method is to switch between Fourier and position space to avoid convolutions and integrate over orientations, leaving only radial integrals. This reformulation is independent of the underlying shape of the initial linear density power spectrum and should easily accommodate features such as those from baryonic acoustic oscillations. We also discuss how to account for halo bias and redshift space distortions.« less

Electronic, Optical, and Thermal Properties of Reduced-Dimensional Semiconductors

NASA Astrophysics Data System (ADS)

Huang, Shouting

Reduced-dimensional materials have attracted tremendous attention because of their new physics and exotic properties, which are of great interests for fundamental science. More importantly, the manipulation and engineering of matter on an atomic scale yield promising applications for many fields including nanoelectronics, nanobiotechnology, environments, and renewable energy. Because of the unusual quantum confinement and enhanced surface effect of reduced-dimensional materials, traditional empirical models suffer from necessary but unreliable parameters extracted from previously-studied bulk materials. In this sense, quantitative, parameter-free approaches are highly useful for understanding properties of reduced-dimensional materials and, furthermore, predicting their novel applications. The first-principles density functional theory (DFT) is proven to be a reliable and convenient tool. In particular, recent progress in many-body perturbation theory (MBPT) makes it possible to calculate excited-state properties, e.g., quasiparticle (QP) band gap and optical excitations, by the first-principles approach based on DFT. Therefore, during my PhD study, I employed first-principles calculations based on DFT and MBPT to systematically study fundamental properties of typical reduced-dimensional semiconductors, i.e., the electronic structure, phonons, and optical excitations of core-shell nanowires (NWs) and graphene-like two-dimensional (2D) structures of current interests. First, I present first-principles studies on how to engineer band alignments of nano-sized radial heterojunctions, Si/Ge core-shell NWs. Our calculation reveals that band offsets in these one-dimensional (1D) nanostructures can be tailored by applying axial strain or varying core-shell sizes. In particular, the valence band offset can be efficiently tuned across a wide range and even be diminished via applied strain. Two mechanisms contribute to this tuning of band offsets. Furthermore, varying the

One-dimensional transport equation models for sound energy propagation in long spaces: theory.

PubMed

Jing, Yun; Larsen, Edward W; Xiang, Ning

2010-04-01

In this paper, a three-dimensional transport equation model is developed to describe the sound energy propagation in a long space. Then this model is reduced to a one-dimensional model by approximating the solution using the method of weighted residuals. The one-dimensional transport equation model directly describes the sound energy propagation in the "long" dimension and deals with the sound energy in the "short" dimensions by prescribed functions. Also, the one-dimensional model consists of a coupled set of N transport equations. Only N=1 and N=2 are discussed in this paper. For larger N, although the accuracy could be improved, the calculation time is expected to significantly increase, which diminishes the advantage of the model in terms of its computational efficiency.

Reduced-Order Model Based Feedback Control For Modified Hasegawa-Wakatani Model

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

Goumiri, I. R.; Rowley, C. W.; Ma, Z.

2013-01-28

In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modi ed Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in ow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then a modelbased feedback controller is designed for the reduced order model using linear quadratic regulators (LQR). Finally, a linear quadratic gaussian (LQG) controller, which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHWmore » equations to stabilize the equilibrium and suppress the transition to drift-wave induced turbulence.« less

On an algebraic structure of dimensionally reduced magical supergravity theories

NASA Astrophysics Data System (ADS)

Fukuchi, Shin; Mizoguchi, Shun'ya

2018-06-01

We study an algebraic structure of magical supergravities in three dimensions. We show that if the commutation relations among the generators of the quasi-conformal group in the super-Ehlers decomposition are in a particular form, then one can always find a parameterization of the group element in terms of various 3d bosonic fields that reproduces the 3d reduced Lagrangian of the corresponding magical supergravity. This provides a unified treatment of all the magical supergravity theories in finding explicit relations between the 3d dimensionally reduced Lagrangians and particular coset nonlinear sigma models. We also verify that the commutation relations of E 6 (+ 2), the quasi-conformal group for A = C, indeed satisfy this property, allowing the algebraic interpretation of the structure constants and scalar field functions as was done in the F 4 (+ 4) magical supergravity.

Sparse High Dimensional Models in Economics

PubMed Central

Fan, Jianqing; Lv, Jinchi; Qi, Lei

2010-01-01

This paper reviews the literature on sparse high dimensional models and discusses some applications in economics and finance. Recent developments of theory, methods, and implementations in penalized least squares and penalized likelihood methods are highlighted. These variable selection methods are proved to be effective in high dimensional sparse modeling. The limits of dimensionality that regularization methods can handle, the role of penalty functions, and their statistical properties are detailed. Some recent advances in ultra-high dimensional sparse modeling are also briefly discussed. PMID:22022635

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

PubMed

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

Sparsity enabled cluster reduced-order models for control

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

2018-01-01

Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

Reduced-order model based feedback control of the modified Hasegawa-Wakatani model

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

Goumiri, I. R.; Rowley, C. W.; Ma, Z.

2013-04-15

In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modified Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in flow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then, a model-based feedback controller is designed for the reduced order model using linear quadratic regulators. Finally, a linear quadratic Gaussian controller which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHW equations to stabilizemore » the equilibrium and suppress the transition to drift-wave induced turbulence.« less

One-dimensional model of inertial pumping

NASA Astrophysics Data System (ADS)

Kornilovitch, Pavel E.; Govyadinov, Alexander N.; Markel, David P.; Torniainen, Erik D.

2013-02-01

A one-dimensional model of inertial pumping is introduced and solved. The pump is driven by a high-pressure vapor bubble generated by a microheater positioned asymmetrically in a microchannel. The bubble is approximated as a short-term impulse delivered to the two fluidic columns inside the channel. Fluid dynamics is described by a Newton-like equation with a variable mass, but without the mass derivative term. Because of smaller inertia, the short column refills the channel faster and accumulates a larger mechanical momentum. After bubble collapse the total fluid momentum is nonzero, resulting in a net flow. Two different versions of the model are analyzed in detail, analytically and numerically. In the symmetrical model, the pressure at the channel-reservoir connection plane is assumed constant, whereas in the asymmetrical model it is reduced by a Bernoulli term. For low and intermediate vapor bubble pressures, both models predict the existence of an optimal microheater location. The predicted net flow in the asymmetrical model is smaller by a factor of about 2. For unphysically large vapor pressures, the asymmetrical model predicts saturation of the effect, while in the symmetrical model net flow increases indefinitely. Pumping is reduced by nonzero viscosity, but to a different degree depending on the microheater location.

One-dimensional model of inertial pumping.

PubMed

Kornilovitch, Pavel E; Govyadinov, Alexander N; Markel, David P; Torniainen, Erik D

2013-02-01

A one-dimensional model of inertial pumping is introduced and solved. The pump is driven by a high-pressure vapor bubble generated by a microheater positioned asymmetrically in a microchannel. The bubble is approximated as a short-term impulse delivered to the two fluidic columns inside the channel. Fluid dynamics is described by a Newton-like equation with a variable mass, but without the mass derivative term. Because of smaller inertia, the short column refills the channel faster and accumulates a larger mechanical momentum. After bubble collapse the total fluid momentum is nonzero, resulting in a net flow. Two different versions of the model are analyzed in detail, analytically and numerically. In the symmetrical model, the pressure at the channel-reservoir connection plane is assumed constant, whereas in the asymmetrical model it is reduced by a Bernoulli term. For low and intermediate vapor bubble pressures, both models predict the existence of an optimal microheater location. The predicted net flow in the asymmetrical model is smaller by a factor of about 2. For unphysically large vapor pressures, the asymmetrical model predicts saturation of the effect, while in the symmetrical model net flow increases indefinitely. Pumping is reduced by nonzero viscosity, but to a different degree depending on the microheater location.

Extra-dimensional models on the lattice

DOE PAGES

Knechtli, Francesco; Rinaldi, Enrico

2016-08-05

In this paper we summarize the ongoing effort to study extra-dimensional gauge theories with lattice simulations. In these models the Higgs field is identified with extra-dimensional components of the gauge field. The Higgs potential is generated by quantum corrections and is protected from divergences by the higher dimensional gauge symmetry. Dimensional reduction to four dimensions can occur through compactification or localization. Gauge-Higgs unification models are often studied using perturbation theory. Numerical lattice simulations are used to go beyond these perturbative expectations and to include nonperturbative effects. We describe the known perturbative predictions and their fate in the strongly-coupled regime formore » various extra-dimensional models.« less

Multiexponential models of (1+1)-dimensional dilaton gravity and Toda-Liouville integrable models

NASA Astrophysics Data System (ADS)

de Alfaro, V.; Filippov, A. T.

2010-01-01

We study general properties of a class of two-dimensional dilaton gravity (DG) theories with potentials containing several exponential terms. We isolate and thoroughly study a subclass of such theories in which the equations of motion reduce to Toda and Liouville equations. We show that the equation parameters must satisfy a certain constraint, which we find and solve for the most general multiexponential model. It follows from the constraint that integrable Toda equations in DG theories generally cannot appear without accompanying Liouville equations. The most difficult problem in the two-dimensional Toda-Liouville (TL) DG is to solve the energy and momentum constraints. We discuss this problem using the simplest examples and identify the main obstacles to solving it analytically. We then consider a subclass of integrable two-dimensional theories where scalar matter fields satisfy the Toda equations and the two-dimensional metric is trivial. We consider the simplest case in some detail. In this example, we show how to obtain the general solution. We also show how to simply derive wavelike solutions of general TL systems. In the DG theory, these solutions describe nonlinear waves coupled to gravity and also static states and cosmologies. For static states and cosmologies, we propose and study a more general one-dimensional TL model typically emerging in one-dimensional reductions of higher-dimensional gravity and supergravity theories. We especially attend to making the analytic structure of the solutions of the Toda equations as simple and transparent as possible.

Interaction phenomenon to dimensionally reduced p-gBKP equation

NASA Astrophysics Data System (ADS)

Zhang, Runfa; Bilige, Sudao; Bai, Yuexing; Lü, Jianqing; Gao, Xiaoqing

2018-02-01

Based on searching the combining of quadratic function and exponential (or hyperbolic cosine) function from the Hirota bilinear form of the dimensionally reduced p-gBKP equation, eight class of interaction solutions are derived via symbolic computation with Mathematica. The submergence phenomenon, presented to illustrate the dynamical features concerning these obtained solutions, is observed by three-dimensional plots and density plots with particular choices of the involved parameters between the exponential (or hyperbolic cosine) function and the quadratic function. It is proved that the interference between the two solitary waves is inelastic.

The problem of dimensional instability in airfoil models for cryogenic wind tunnels

NASA Technical Reports Server (NTRS)

Wigley, D. A.

1982-01-01

The problem of dimensional instability in airfoil models for cryogenic wind tunnels is discussed in terms of the various mechanisms that can be responsible. The interrelationship between metallurgical structure and possible dimensional instability in cryogenic usage is discussed for those steel alloys of most interest for wind tunnel model construction at this time. Other basic mechanisms responsible for setting up residual stress systems are discussed, together with ways in which their magnitude may be reduced by various elevated or low temperature thermal cycles. A standard specimen configuration is proposed for use in experimental investigations into the effects of machining, heat treatment, and other variables that influence the dimensional stability of the materials of interest. A brief classification of various materials in terms of their metallurgical structure and susceptability to dimensional instability is presented.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems

PubMed Central

Koumoutsakos, Petros

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

PubMed

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Chang, Siyuan; Luo, Haoxiang; Luo's lab Team

2016-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which is often needed in procedures such as optimization and parameter estimation. In this work, we study the performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin. Supported by the NSF.

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications

PubMed Central

Tao, Chenyang; Nichols, Thomas E.; Hua, Xue; Ching, Christopher R.K.; Rolls, Edmund T.; Thompson, Paul M.; Feng, Jianfeng

2017-01-01

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. PMID:27666385

A Standardized Generalized Dimensionality Discrepancy Measure and a Standardized Model-Based Covariance for Dimensionality Assessment for Multidimensional Models

ERIC Educational Resources Information Center

Levy, Roy; Xu, Yuning; Yel, Nedim; Svetina, Dubravka

2015-01-01

The standardized generalized dimensionality discrepancy measure and the standardized model-based covariance are introduced as tools to critique dimensionality assumptions in multidimensional item response models. These tools are grounded in a covariance theory perspective and associated connections between dimensionality and local independence.…

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.

PubMed

Song, Hongchao; Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k -nearest neighbor graphs- ( K -NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

PubMed Central

Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k-nearest neighbor graphs- (K-NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity. PMID:29270197

Hybrid reduced order modeling for assembly calculations

DOE PAGES

Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; ...

2015-08-14

While the accuracy of assembly calculations has greatly improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the usemore » of the reduced order modeling for a single physics code, such as a radiation transport calculation. This paper extends those works to coupled code systems as currently employed in assembly calculations. Finally, numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.« less

Model diagnostics in reduced-rank estimation

PubMed Central

Chen, Kun

2016-01-01

Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches. PMID:28003860

Model diagnostics in reduced-rank estimation.

PubMed

Chen, Kun

2016-01-01

Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches.

Concentration data and dimensionality in groundwater models: evaluation using inverse modelling

USGS Publications Warehouse

Barlebo, H.C.; Hill, M.C.; Rosbjerg, D.; Jensen, K.H.

1998-01-01

A three-dimensional inverse groundwater flow and transport model that fits hydraulic-head and concentration data simultaneously using nonlinear regression is presented and applied to a layered sand and silt groundwater system beneath the Grindsted Landfill in Denmark. The aquifer is composed of rather homogeneous hydrogeologic layers. Two issues common to groundwater flow and transport modelling are investigated: 1) The accuracy of simulated concentrations in the case of calibration with head data alone; and 2) The advantages and disadvantages of using a two-dimensional cross-sectional model instead of a three-dimensional model to simulate contaminant transport when the source is at the land surface. Results show that using only hydraulic heads in the nonlinear regression produces a simulated plume that is profoundly different from what is obtained in a calibration using both hydraulic-head and concentration data. The present study provides a well-documented example of the differences that can occur. Representing the system as a two-dimensional cross-section obviously omits some of the system dynamics. It was, however, possible to obtain a simulated plume cross-section that matched the actual plume cross-section well. The two-dimensional model execution times were about a seventh of those for the three-dimensional model, but some difficulties were encountered in representing the spatially variable source concentrations and less precise simulated concentrations were calculated by the two-dimensional model compared to the three-dimensional model. Summed up, the present study indicates that three dimensional modelling using both hydraulic heads and concentrations in the calibration should be preferred in the considered type of transport studies.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Progress Report on SAM Reduced-Order Model Development for Thermal Stratification and Mixing during Reactor Transients

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

Hu, R.

This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.

Advanced Fluid Reduced Order Models for Compressible Flow.

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

Tezaur, Irina Kalashnikova; Fike, Jeffrey A.; Carlberg, Kevin Thomas

This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly themore » POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.« less

A reduced theoretical model for estimating condensation effects in combustion-heated hypersonic tunnel

NASA Astrophysics Data System (ADS)

Lin, L.; Luo, X.; Qin, F.; Yang, J.

2018-03-01

As one of the combustion products of hydrocarbon fuels in a combustion-heated wind tunnel, water vapor may condense during the rapid expansion process, which will lead to a complex two-phase flow inside the wind tunnel and even change the design flow conditions at the nozzle exit. The coupling of the phase transition and the compressible flow makes the estimation of the condensation effects in such wind tunnels very difficult and time-consuming. In this work, a reduced theoretical model is developed to approximately compute the nozzle-exit conditions of a flow including real-gas and homogeneous condensation effects. Specifically, the conservation equations of the axisymmetric flow are first approximated in the quasi-one-dimensional way. Then, the complex process is split into two steps, i.e., a real-gas nozzle flow but excluding condensation, resulting in supersaturated nozzle-exit conditions, and a discontinuous jump at the end of the nozzle from the supersaturated state to a saturated state. Compared with two-dimensional numerical simulations implemented with a detailed condensation model, the reduced model predicts the flow parameters with good accuracy except for some deviations caused by the two-dimensional effect. Therefore, this reduced theoretical model can provide a fast, simple but also accurate estimation of the condensation effect in combustion-heated hypersonic tunnels.

Creating physically-based three-dimensional microstructures: Bridging phase-field and crystal plasticity models.

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

Lim, Hojun; Owen, Steven J.; Abdeljawad, Fadi F.

In order to better incorporate microstructures in continuum scale models, we use a novel finite element (FE) meshing technique to generate three-dimensional polycrystalline aggregates from a phase field grain growth model of grain microstructures. The proposed meshing technique creates hexahedral FE meshes that capture smooth interfaces between adjacent grains. Three dimensional realizations of grain microstructures from the phase field model are used in crystal plasticity-finite element (CP-FE) simulations of polycrystalline a -iron. We show that the interface conformal meshes significantly reduce artificial stress localizations in voxelated meshes that exhibit the so-called "wedding cake" interfaces. This framework provides a direct linkmore » between two mesoscale models - phase field and crystal plasticity - and for the first time allows mechanics simulations of polycrystalline materials using three-dimensional hexahedral finite element meshes with realistic topological features.« less

Dimensional reduction for a SIR type model

NASA Astrophysics Data System (ADS)

Cahyono, Edi; Soeharyadi, Yudi; Mukhsar

2018-03-01

Epidemic phenomena are often modeled in the form of dynamical systems. Such model has also been used to model spread of rumor, spread of extreme ideology, and dissemination of knowledge. Among the simplest is SIR (susceptible, infected and recovered) model, a model that consists of three compartments, and hence three variables. The variables are functions of time which represent the number of subpopulations, namely suspect, infected and recovery. The sum of the three is assumed to be constant. Hence, the model is actually two dimensional which sits in three-dimensional ambient space. This paper deals with the reduction of a SIR type model into two variables in two-dimensional ambient space to understand the geometry and dynamics better. The dynamics is studied, and the phase portrait is presented. The two dimensional model preserves the equilibrium and the stability. The model has been applied for knowledge dissemination, which has been the interest of knowledge management.

Development of a global aerosol model using a two-dimensional sectional method: 1. Model design

NASA Astrophysics Data System (ADS)

Matsui, H.

2017-08-01

This study develops an aerosol module, the Aerosol Two-dimensional bin module for foRmation and Aging Simulation version 2 (ATRAS2), and implements the module into a global climate model, Community Atmosphere Model. The ATRAS2 module uses a two-dimensional (2-D) sectional representation with 12 size bins for particles from 1 nm to 10 μm in dry diameter and 8 black carbon (BC) mixing state bins. The module can explicitly calculate the enhancement of absorption and cloud condensation nuclei activity of BC-containing particles by aging processes. The ATRAS2 module is an extension of a 2-D sectional aerosol module ATRAS used in our previous studies within a framework of a regional three-dimensional model. Compared with ATRAS, the computational cost of the aerosol module is reduced by more than a factor of 10 by simplifying the treatment of aerosol processes and 2-D sectional representation, while maintaining good accuracy of aerosol parameters in the simulations. Aerosol processes are simplified for condensation of sulfate, ammonium, and nitrate, organic aerosol formation, coagulation, and new particle formation processes, and box model simulations show that these simplifications do not substantially change the predicted aerosol number and mass concentrations and their mixing states. The 2-D sectional representation is simplified (the number of advected species is reduced) primarily by the treatment of chemical compositions using two interactive bin representations. The simplifications do not change the accuracy of global aerosol simulations. In part 2, comparisons with measurements and the results focused on aerosol processes such as BC aging processes are shown.

One-dimensional GIS-based model compared with a two-dimensional model in urban floods simulation.

PubMed

Lhomme, J; Bouvier, C; Mignot, E; Paquier, A

2006-01-01

A GIS-based one-dimensional flood simulation model is presented and applied to the centre of the city of Nîmes (Gard, France), for mapping flow depths or velocities in the streets network. The geometry of the one-dimensional elements is derived from the Digital Elevation Model (DEM). The flow is routed from one element to the next using the kinematic wave approximation. At the crossroads, the flows in the downstream branches are computed using a conceptual scheme. This scheme was previously designed to fit Y-shaped pipes junctions, and has been modified here to fit X-shaped crossroads. The results were compared with the results of a two-dimensional hydrodynamic model based on the full shallow water equations. The comparison shows that good agreements can be found in the steepest streets of the study zone, but differences may be important in the other streets. Some reasons that can explain the differences between the two models are given and some research possibilities are proposed.

Exploring load, velocity, and surface disorder dependence of friction with one-dimensional and two-dimensional models.

PubMed

Dagdeviren, Omur E

2018-08-03

The effect of surface disorder, load, and velocity on friction between a single asperity contact and a model surface is explored with one-dimensional and two-dimensional Prandtl-Tomlinson (PT) models. We show that there are fundamental physical differences between the predictions of one-dimensional and two-dimensional models. The one-dimensional model estimates a monotonic increase in friction and energy dissipation with load, velocity, and surface disorder. However, a two-dimensional PT model, which is expected to approximate a tip-sample system more realistically, reveals a non-monotonic trend, i.e. friction is inert to surface disorder and roughness in wearless friction regime. The two-dimensional model discloses that the surface disorder starts to dominate the friction and energy dissipation when the tip and the sample interact predominantly deep into the repulsive regime. Our numerical calculations address that tracking the minimum energy path and the slip-stick motion are two competing effects that determine the load, velocity, and surface disorder dependence of friction. In the two-dimensional model, the single asperity can follow the minimum energy path in wearless regime; however, with increasing load and sliding velocity, the slip-stick movement dominates the dynamic motion and results in an increase in friction by impeding tracing the minimum energy path. Contrary to the two-dimensional model, when the one-dimensional PT model is employed, the single asperity cannot escape to the minimum energy minimum due to constraint motion and reveals only a trivial dependence of friction on load, velocity, and surface disorder. Our computational analyses clarify the physical differences between the predictions of the one-dimensional and two-dimensional models and open new avenues for disordered surfaces for low energy dissipation applications in wearless friction regime.

Two-Dimensional Computational Model for Wave Rotor Flow Dynamics

NASA Technical Reports Server (NTRS)

Welch, Gerard E.

1996-01-01

A two-dimensional (theta,z) Navier-Stokes solver for multi-port wave rotor flow simulation is described. The finite-volume form of the unsteady thin-layer Navier-Stokes equations are integrated in time on multi-block grids that represent the stationary inlet and outlet ports and the moving rotor passages of the wave rotor. Computed results are compared with three-port wave rotor experimental data. The model is applied to predict the performance of a planned four-port wave rotor experiment. Two-dimensional flow features that reduce machine performance and influence rotor blade and duct wall thermal loads are identified. The performance impact of rounding the inlet port wall, to inhibit separation during passage gradual opening, is assessed.

Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

NASA Astrophysics Data System (ADS)

Qi, D.; Majda, A.

2017-12-01

A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with

Three-dimensional modeling of tea-shoots using images and models.

PubMed

Wang, Jian; Zeng, Xianyin; Liu, Jianbing

2011-01-01

In this paper, a method for three-dimensional modeling of tea-shoots with images and calculation models is introduced. The process is as follows: the tea shoots are photographed with a camera, color space conversion is conducted, using an improved algorithm that is based on color and regional growth to divide the tea shoots in the images, and the edges of the tea shoots extracted with the help of edge detection; after that, using the divided tea-shoot images, the three-dimensional coordinates of the tea shoots are worked out and the feature parameters extracted, matching and calculation conducted according to the model database, and finally the three-dimensional modeling of tea-shoots is completed. According to the experimental results, this method can avoid a lot of calculations and has better visual effects and, moreover, performs better in recovering the three-dimensional information of the tea shoots, thereby providing a new method for monitoring the growth of and non-destructive testing of tea shoots.

Assessment of reduced-order unscented Kalman filter for parameter identification in 1-dimensional blood flow models using experimental data.

PubMed

Caiazzo, A; Caforio, Federica; Montecinos, Gino; Muller, Lucas O; Blanco, Pablo J; Toro, Eluterio F

2016-10-25

This work presents a detailed investigation of a parameter estimation approach on the basis of the reduced-order unscented Kalman filter (ROUKF) in the context of 1-dimensional blood flow models. In particular, the main aims of this study are (1) to investigate the effects of using real measurements versus synthetic data for the estimation procedure (i.e., numerical results of the same in silico model, perturbed with noise) and (2) to identify potential difficulties and limitations of the approach in clinically realistic applications to assess the applicability of the filter to such setups. For these purposes, the present numerical study is based on a recently published in vitro model of the arterial network, for which experimental flow and pressure measurements are available at few selected locations. To mimic clinically relevant situations, we focus on the estimation of terminal resistances and arterial wall parameters related to vessel mechanics (Young's modulus and wall thickness) using few experimental observations (at most a single pressure or flow measurement per vessel). In all cases, we first perform a theoretical identifiability analysis on the basis of the generalized sensitivity function, comparing then the results owith the ROUKF, using either synthetic or experimental data, to results obtained using reference parameters and to available measurements. Copyright © 2016 John Wiley & Sons, Ltd.

Recovering a full dimensional quantum rate constant from a reduced dimensionality calculation: Application to the OH+CO{r_arrow}H+CO{sub 2} reaction

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

Dzegilenko, F.N.; Bowman, J.M.

1996-08-01

Two reduced dimensionality theories are used to calculate the thermal rate constant for the OH+CO{r_arrow}H+CO{sub 2} reaction. The standard theory employs energy-shift approximations to extract the full six degree-of-freedom quantum rate constant for this reaction from the previous two degree-of-freedom (2-DOF) quantum calculations of Hernandez and Clary [M.I. Hernandez and D.C. Clary, J. Chem. Phys. {bold 101}, 2779 (1994)]. Three extra bending modes and one extra {open_quote}{open_quote}spectator{close_quote}{close_quote} CO stretch mode are treated adiabatically in the harmonic fashion. The parameters of the exit channel transition state are used to evaluate the frequencies of those additional modes. A new reduced dimensionality theorymore » is also applied to this reaction. This theory explicitly addresses the finding from the 2-DOF calculations that the reaction proceeds mainly via complex formation. A J-shifting approximation has been used to take into account the initial states with non-zero values of total angular momentum in both reduced dimensionality theories. Cumulative reaction probabilities and thermal rate constants are calculated and compared with the previous quasiclassical and reduced dimensionality quantum calculations and with experiment. The rate constant from the new reduced dimensionality theory is between a factor of 5 and 100 times smaller than the statistical transition state theory result, and is in much better agreement with experiment. {copyright} {ital 1996 American Institute of Physics.}« less

Dynamic colloidal assembly pathways via low dimensional models

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

Yang, Yuguang; Bevan, Michael A., E-mail: mabevan@jhu.edu; Thyagarajan, Raghuram

2016-05-28

Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterizedmore » by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.« less

Continuum modeling of three-dimensional truss-like space structures

NASA Technical Reports Server (NTRS)

Nayfeh, A. H.; Hefzy, M. S.

1978-01-01

A mathematical and computational analysis capability has been developed for calculating the effective mechanical properties of three-dimensional periodic truss-like structures. Two models are studied in detail. The first, called the octetruss model, is a three-dimensional extension of a two-dimensional model, and the second is a cubic model. Symmetry considerations are employed as a first step to show that the specific octetruss model has four independent constants and that the cubic model has two. The actual values of these constants are determined by averaging the contributions of each rod element to the overall structure stiffness. The individual rod member contribution to the overall stiffness is obtained by a three-dimensional coordinate transformation. The analysis shows that the effective three-dimensional elastic properties of both models are relatively close to each other.

Simplified energy-balance model for pragmatic multi-dimensional device simulation

NASA Astrophysics Data System (ADS)

Chang, Duckhyun; Fossum, Jerry G.

1997-11-01

To pragmatically account for non-local carrier heating and hot-carrier effects such as velocity overshoot and impact ionization in multi-dimensional numerical device simulation, a new simplified energy-balance (SEB) model is developed and implemented in FLOODS[16] as a pragmatic option. In the SEB model, the energy-relaxation length is estimated from a pre-process drift-diffusion simulation using the carrier-velocity distribution predicted throughout the device domain, and is used without change in a subsequent simpler hydrodynamic (SHD) simulation. The new SEB model was verified by comparison of two-dimensional SHD and full HD DC simulations of a submicron MOSFET. The SHD simulations yield detailed distributions of carrier temperature, carrier velocity, and impact-ionization rate, which agree well with the full HD simulation results obtained with FLOODS. The most noteworthy feature of the new SEB/SHD model is its computational efficiency, which results from reduced Newton iteration counts caused by the enhanced linearity. Relative to full HD, SHD simulation times can be shorter by as much as an order of magnitude since larger voltage steps for DC sweeps and larger time steps for transient simulations can be used. The improved computational efficiency can enable pragmatic three-dimensional SHD device simulation as well, for which the SEB implementation would be straightforward as it is in FLOODS or any robust HD simulator.

Dynamo transition in low-dimensional models.

PubMed

Verma, Mahendra K; Lessinnes, Thomas; Carati, Daniele; Sarris, Ioannis; Kumar, Krishna; Singh, Meenakshi

2008-09-01

Two low-dimensional magnetohydrodynamic models containing three velocity and three magnetic modes are described. One of them (nonhelical model) has zero kinetic and current helicity, while the other model (helical) has nonzero kinetic and current helicity. The velocity modes are forced in both these models. These low-dimensional models exhibit a dynamo transition at a critical forcing amplitude that depends on the Prandtl number. In the nonhelical model, dynamo exists only for magnetic Prandtl number beyond 1, while the helical model exhibits dynamo for all magnetic Prandtl number. Although the model is far from reproducing all the possible features of dynamo mechanisms, its simplicity allows a very detailed study and the observed dynamo transition is shown to bear similarities with recent numerical and experimental results.

A Fourier dimensionality reduction model for big data interferometric imaging

NASA Astrophysics Data System (ADS)

Vijay Kartik, S.; Carrillo, Rafael E.; Thiran, Jean-Philippe; Wiaux, Yves

2017-06-01

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging methods to the big data setting of the next-generation telescopes. This article sheds new light on dimensionality reduction from the perspective of the compressed sensing theory and studies its interplay with imaging algorithms designed in the context of convex optimization. We propose a post-gridding linear data embedding to the space spanned by the left singular vectors of the measurement operator, providing a dimensionality reduction below image size. This embedding preserves the null space of the measurement operator and hence its sampling properties are also preserved in light of the compressed sensing theory. We show that this can be approximated by first computing the dirty image and then applying a weighted subsampled discrete Fourier transform to obtain the final reduced data vector. This Fourier dimensionality reduction model ensures a fast implementation of the full measurement operator, essential for any iterative image reconstruction method. The proposed reduction also preserves the independent and identically distributed Gaussian properties of the original measurement noise. For convex optimization-based imaging algorithms, this is key to justify the use of the standard ℓ2-norm as the data fidelity term. Our simulations confirm that this dimensionality reduction approach can be leveraged by convex optimization algorithms with no loss in imaging quality relative to reconstructing the image from the complete visibility data set. Reconstruction results in simulation settings with no direction dependent effects or calibration errors show promising performance of the proposed dimensionality reduction. Further tests on real data are planned as an extension of the current work. matlab code implementing the

Triple Resonance Solid State NMR Experiments with Reduced Dimensionality Evolution Periods

NASA Astrophysics Data System (ADS)

Astrof, Nathan S.; Lyon, Charles E.; Griffin, Robert G.

2001-10-01

Two solid state NMR triple resonance experiments which utilize the simultaneous incrementation of two chemical shift evolution periods to obtain a spectrum with reduced dimensionality are described. The CON CA experiment establishes the correlation of 13Ci-1 to 13Cαi and 15Ni by simultaneously encoding the 13COi-1 and 15Ni chemical shifts. The CAN COCA experiment establishes the correlation 13Cai and 15COi to 13Cαi-1 and 15Ni-1 within a single experiment by simultaneous encoding of the 13Cαi and 15Ni chemical shifts. This experiment establishes sequential amino acid correlations in close analogy to the solution state HNCA experiment. Reduced dimensionality 2D experiments are a practical alternative to recording multiple 3D data sets for the purpose of obtaining sequence-specific resonance assignments of peptides and proteins in the solid state.

Reduced order modeling of fluid/structure interaction.

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

Barone, Matthew Franklin; Kalashnikova, Irina; Segalman, Daniel Joseph

2009-11-01

This report describes work performed from October 2007 through September 2009 under the Sandia Laboratory Directed Research and Development project titled 'Reduced Order Modeling of Fluid/Structure Interaction.' This project addresses fundamental aspects of techniques for construction of predictive Reduced Order Models (ROMs). A ROM is defined as a model, derived from a sequence of high-fidelity simulations, that preserves the essential physics and predictive capability of the original simulations but at a much lower computational cost. Techniques are developed for construction of provably stable linear Galerkin projection ROMs for compressible fluid flow, including a method for enforcing boundary conditions that preservesmore » numerical stability. A convergence proof and error estimates are given for this class of ROM, and the method is demonstrated on a series of model problems. A reduced order method, based on the method of quadratic components, for solving the von Karman nonlinear plate equations is developed and tested. This method is applied to the problem of nonlinear limit cycle oscillations encountered when the plate interacts with an adjacent supersonic flow. A stability-preserving method for coupling the linear fluid ROM with the structural dynamics model for the elastic plate is constructed and tested. Methods for constructing efficient ROMs for nonlinear fluid equations are developed and tested on a one-dimensional convection-diffusion-reaction equation. These methods are combined with a symmetrization approach to construct a ROM technique for application to the compressible Navier-Stokes equations.« less

Modeling Three-Dimensional Flow in Confined Aquifers by Superposition of Both Two- and Three-Dimensional Analytic Functions

NASA Astrophysics Data System (ADS)

Haitjema, Henk M.

1985-10-01

A technique is presented to incorporate three-dimensional flow in a Dupuit-Forchheimer model. The method is based on superposition of approximate analytic solutions to both two- and three-dimensional flow features in a confined aquifer of infinite extent. Three-dimensional solutions are used in the domain of interest, while farfield conditions are represented by two-dimensional solutions. Approximate three- dimensional solutions have been derived for a partially penetrating well and a shallow creek. Each of these solutions satisfies the condition that no flow occurs across the confining layers of the aquifer. Because of this condition, the flow at some distance of a three-dimensional feature becomes nearly horizontal. Consequently, remotely from a three-dimensional feature, its three-dimensional solution is replaced by a corresponding two-dimensional one. The latter solution is trivial as compared to its three-dimensional counterpart, and its use greatly enhances the computational efficiency of the model. As an example, the flow is modeled between a partially penetrating well and a shallow creek that occur in a regional aquifer system.

Complex Langevin analysis of the spontaneous symmetry breaking in dimensionally reduced super Yang-Mills models

NASA Astrophysics Data System (ADS)

Anagnostopoulos, Konstantinos N.; Azuma, Takehiro; Ito, Yuta; Nishimura, Jun; Papadoudis, Stratos Kovalkov

2018-02-01

In recent years the complex Langevin method (CLM) has proven a powerful method in studying statistical systems which suffer from the sign problem. Here we show that it can also be applied to an important problem concerning why we live in four-dimensional spacetime. Our target system is the type IIB matrix model, which is conjectured to be a nonperturbative definition of type IIB superstring theory in ten dimensions. The fermion determinant of the model becomes complex upon Euclideanization, which causes a severe sign problem in its Monte Carlo studies. It is speculated that the phase of the fermion determinant actually induces the spontaneous breaking of the SO(10) rotational symmetry, which has direct consequences on the aforementioned question. In this paper, we apply the CLM to the 6D version of the type IIB matrix model and show clear evidence that the SO(6) symmetry is broken down to SO(3). Our results are consistent with those obtained previously by the Gaussian expansion method.

Two-dimensional lattice Boltzmann model for magnetohydrodynamics.

PubMed

Schaffenberger, Werner; Hanslmeier, Arnold

2002-10-01

We present a lattice Boltzmann model for the simulation of two-dimensional magnetohydro dynamic (MHD) flows. The model is an extension of a hydrodynamic lattice Boltzman model with 9 velocities on a square lattice resulting in a model with 17 velocities. Earlier lattice Boltzmann models for two-dimensional MHD used a bidirectional streaming rule. However, the use of such a bidirectional streaming rule is not necessary. In our model, the standard streaming rule is used, allowing smaller viscosities. To control the viscosity and the resistivity independently, a matrix collision operator is used. The model is then applied to the Hartmann flow, giving reasonable results.

Comparison of two-dimensional and quasi-one-dimensional scramjet models by the example of VAG experiment

NASA Astrophysics Data System (ADS)

Seleznev, R. K.

2017-02-01

In the paper two-dimensional and quasi-one dimensional models for scramjet combustion chamber are described. Comparison of the results of calculations for the two-dimensional and quasi-one dimensional code by the example of VAG experiment are presented.

Modeling and numerical simulations of growth and morphologies of three dimensional aggregated silver films

NASA Astrophysics Data System (ADS)

Davis, L. J.; Boggess, M.; Kodpuak, E.; Deutsch, M.

2012-11-01

We report on a model for the deposition of three dimensional, aggregated nanocrystalline silver films, and an efficient numerical simulation method developed for visualizing such structures. We compare our results to a model system comprising chemically deposited silver films with morphologies ranging from dilute, uniform distributions of nanoparticles to highly porous aggregated networks. Disordered silver films grown in solution on silica substrates are characterized using digital image analysis of high resolution scanning electron micrographs. While the latter technique provides little volume information, plane-projected (two dimensional) island structure and surface coverage may be reliably determined. Three parameters governing film growth are evaluated using these data and used as inputs for the deposition model, greatly reducing computing requirements while still providing direct access to the complete (bulk) structure of the films throughout the growth process. We also show how valuable three dimensional characteristics of the deposited materials can be extracted using the simulated structures.

Hybrid-dimensional modelling of two-phase flow through fractured porous media with enhanced matrix fracture transmission conditions

NASA Astrophysics Data System (ADS)

Brenner, Konstantin; Hennicker, Julian; Masson, Roland; Samier, Pierre

2018-03-01

In this work, we extend, to two-phase flow, the single-phase Darcy flow model proposed in [26], [12] in which the (d - 1)-dimensional flow in the fractures is coupled with the d-dimensional flow in the matrix. Three types of so called hybrid-dimensional two-phase Darcy flow models are proposed. They all account for fractures acting either as drains or as barriers, since they allow pressure jumps at the matrix-fracture interfaces. The models also permit to treat gravity dominated flow as well as discontinuous capillary pressure at the material interfaces. The three models differ by their transmission conditions at matrix fracture interfaces: while the first model accounts for the nonlinear two-phase Darcy flux conservations, the second and third ones are based on the linear single phase Darcy flux conservations combined with different approximations of the mobilities. We adapt the Vertex Approximate Gradient (VAG) scheme to this problem, in order to account for anisotropy and heterogeneity aspects as well as for applicability on general meshes. Several test cases are presented to compare our hybrid-dimensional models to the generic equi-dimensional model, in which fractures have the same dimension as the matrix, leading to deep insight about the quality of the proposed reduced models.

Three-Dimensional Electron Optics Model Developed for Traveling-Wave Tubes

NASA Technical Reports Server (NTRS)

Kory, Carol L.

2000-01-01

A three-dimensional traveling-wave tube (TWT) electron beam optics model including periodic permanent magnet (PPM) focusing has been developed at the NASA Glenn Research Center at Lewis Field. This accurate model allows a TWT designer to develop a focusing structure while reducing the expensive and time-consuming task of building the TWT and hot-testing it (with the electron beam). In addition, the model allows, for the first time, an investigation of the effect on TWT operation of the important azimuthally asymmetric features of the focusing stack. The TWT is a vacuum device that amplifies signals by transferring energy from an electron beam to a radiofrequency (RF) signal. A critically important component is the focusing structure, which keeps the electron beam from diverging and intercepting the RF slow wave circuit. Such an interception can result in excessive circuit heating and decreased efficiency, whereas excessive growth in the beam diameter can lead to backward wave oscillations and premature saturation, indicating a serious reduction in tube performance. The most commonly used focusing structure is the PPM stack, which consists of a sequence of cylindrical iron pole pieces and opposite-polarity magnets. Typically, two-dimensional electron optics codes are used in the design of magnetic focusing devices. In general, these codes track the beam from the gun downstream by solving equations of motion for the electron beam in static-electric and magnetic fields in an azimuthally symmetric structure. Because these two-dimensional codes cannot adequately simulate a number of important effects, the simulation code MAFIA (solution of Maxwell's equations by the Finite-Integration-Algorithm) was used at Glenn to develop a three-dimensional electron optics model. First, a PPM stack was modeled in three dimensions. Then, the fields obtained using the magnetostatic solver were loaded into a particle-in-cell solver where the fully three-dimensional behavior of the beam

CFD modeling of two-stage ignition in a rapid compression machine: Assessment of zero-dimensional approach

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

Mittal, Gaurav; Raju, Mandhapati P.; Sung, Chih-Jen

2010-07-15

In modeling rapid compression machine (RCM) experiments, zero-dimensional approach is commonly used along with an associated heat loss model. The adequacy of such approach has not been validated for hydrocarbon fuels. The existence of multi-dimensional effects inside an RCM due to the boundary layer, roll-up vortex, non-uniform heat release, and piston crevice could result in deviation from the zero-dimensional assumption, particularly for hydrocarbons exhibiting two-stage ignition and strong thermokinetic interactions. The objective of this investigation is to assess the adequacy of zero-dimensional approach in modeling RCM experiments under conditions of two-stage ignition and negative temperature coefficient (NTC) response. Computational fluidmore » dynamics simulations are conducted for n-heptane ignition in an RCM and the validity of zero-dimensional approach is assessed through comparisons over the entire NTC region. Results show that the zero-dimensional model based on the approach of 'adiabatic volume expansion' performs very well in adequately predicting the first-stage ignition delays, although quantitative discrepancy for the prediction of the total ignition delays and pressure rise in the first-stage ignition is noted even when the roll-up vortex is suppressed and a well-defined homogeneous core is retained within an RCM. Furthermore, the discrepancy is pressure dependent and decreases as compressed pressure is increased. Also, as ignition response becomes single-stage at higher compressed temperatures, discrepancy from the zero-dimensional simulations reduces. Despite of some quantitative discrepancy, the zero-dimensional modeling approach is deemed satisfactory from the viewpoint of the ignition delay simulation. (author)« less

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap.

PubMed

Spiwok, Vojtěch; Králová, Blanka

2011-12-14

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling. © 2011 American Institute of Physics

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Králová, Blanka

2011-12-01

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling.

A three-dimensional neural spheroid model for capillary-like network formation.

PubMed

Boutin, Molly E; Kramer, Liana L; Livi, Liane L; Brown, Tyler; Moore, Christopher; Hoffman-Kim, Diane

2018-04-01

In vitro three-dimensional neural spheroid models have an in vivo-like cell density, and have the potential to reduce animal usage and increase experimental throughput. The aim of this study was to establish a spheroid model to study the formation of capillary-like networks in a three-dimensional environment that incorporates both neuronal and glial cell types, and does not require exogenous vasculogenic growth factors. We created self-assembled, scaffold-free cellular spheroids using primary-derived postnatal rodent cortex as a cell source. The interactions between relevant neural cell types, basement membrane proteins, and endothelial cells were characterized by immunohistochemistry. Transmission electron microscopy was used to determine if endothelial network structures had lumens. Endothelial cells within cortical spheroids assembled into capillary-like networks with lumens. Networks were surrounded by basement membrane proteins, including laminin, fibronectin and collagen IV, as well as key neurovascular cell types. Existing in vitro models of the cortical neurovascular environment study monolayers of endothelial cells, either on transwell inserts or coating cellular spheroids. These models are not well suited to study vasculogenesis, a process hallmarked by endothelial cell cord formation and subsequent lumenization. The neural spheroid is a new model to study the formation of endothelial cell capillary-like structures in vitro within a high cell density three-dimensional environment that contains both neuronal and glial populations. This model can be applied to investigate vascular assembly in healthy or disease states, such as stroke, traumatic brain injury, or neurodegenerative disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Determining Reduced Order Models for Optimal Stochastic Reduced Order Models

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

Bonney, Matthew S.; Brake, Matthew R.W.

2015-08-01

The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better representmore » the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.« less

A Non Local Electron Heat Transport Model for Multi-Dimensional Fluid Codes

NASA Astrophysics Data System (ADS)

Schurtz, Guy

2000-10-01

Apparent inhibition of thermal heat flow is one of the most ancient problems in computational Inertial Fusion and flux-limited Spitzer-Harm conduction has been a mainstay in multi-dimensional hydrodynamic codes for more than 25 years. Theoretical investigation of the problem indicates that heat transport in laser produced plasmas has to be considered as a non local process. Various authors contributed to the non local theory and proposed convolution formulas designed for practical implementation in one-dimensional fluid codes. Though the theory, confirmed by kinetic calculations, actually predicts a reduced heat flux, it fails to explain the very small limiters required in two-dimensional simulations. Fokker-Planck simulations by Epperlein, Rickard and Bell [PRL 61, 2453 (1988)] demonstrated that non local effects could lead to a strong reduction of heat flow in two dimensions, even in situations where a one-dimensional analysis suggests that the heat flow is nearly classical. We developed at CEA/DAM a non local electron heat transport model suitable for implementation in our two-dimensional radiation hydrodynamic code FCI2. This model may be envisionned as the first step of an iterative solution of the Fokker-Planck equations; it takes the mathematical form of multigroup diffusion equations, the solution of which yields both the heat flux and the departure of the electron distribution function to the Maxwellian. Although direct implementation of the model is straightforward, formal solutions of it can be expressed in convolution form, exhibiting a three-dimensional tensor propagator. Reduction to one dimension retrieves the original formula of Luciani, Mora and Virmont [PRL 51, 1664 (1983)]. Intense magnetic fields may be generated by thermal effects in laser targets; these fields, as well as non local effects, will inhibit electron conduction. We present simulations where both effects are taken into account and shortly discuss the coupling strategy between them.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Bioengineered humanized livers as better three-dimensional drug testing model system.

PubMed

Vishwakarma, Sandeep Kumar; Bardia, Avinash; Lakkireddy, Chandrakala; Nagarapu, Raju; Habeeb, Md Aejaz; Khan, Aleem Ahmed

2018-01-27

To develop appropriate humanized three-dimensional ex-vivo model system for drug testing. Bioengineered humanized livers were developed in this study using human hepatic stem cells repopulation within the acellularized liver scaffolds which mimics with the natural organ anatomy and physiology. Six cytochrome P-450 probes were used to enable efficient identification of drug metabolism in bioengineered humanized livers. The drug metabolism study in bioengineered livers was evaluated to identify the absorption, distribution, metabolism, excretion and toxicity responses. The bioengineered humanized livers showed cellular and molecular characteristics of human livers. The bioengineered liver showed three-dimensional natural architecture with intact vasculature and extra-cellular matrix. Human hepatic cells were engrafted similar to the human liver. Drug metabolism studies provided a suitable platform alternative to available ex-vivo and in vivo models for identifying cellular and molecular dynamics of pharmacological drugs. The present study paves a way towards the development of suitable humanized preclinical model systems for pharmacological testing. This approach may reduce the cost and time duration of preclinical drug testing and further overcomes on the anatomical and physiological variations in xenogeneic systems.

Minimizers with Bounded Action for the High-Dimensional Frenkel-Kontorova Model

NASA Astrophysics Data System (ADS)

Miao, Xue-Qing; Wang, Ya-Nan; Qin, Wen-Xin

In Aubry-Mather theory for monotone twist maps or for one-dimensional Frenkel-Kontorova (FK) model with nearest neighbor interactions, each global minimizer (minimal energy configuration) is naturally Birkhoff. However, this is not true for the one-dimensional FK model with non-nearest neighbor interactions or for the high-dimensional FK model. In this paper, we study the Birkhoff property of minimizers with bounded action for the high-dimensional FK model.

Multi-Level Reduced Order Modeling Equipped with Probabilistic Error Bounds

NASA Astrophysics Data System (ADS)

Abdo, Mohammad Gamal Mohammad Mostafa

This thesis develops robust reduced order modeling (ROM) techniques to achieve the needed efficiency to render feasible the use of high fidelity tools for routine engineering analyses. Markedly different from the state-of-the-art ROM techniques, our work focuses only on techniques which can quantify the credibility of the reduction which can be measured with the reduction errors upper-bounded for the envisaged range of ROM model application. Our objective is two-fold. First, further developments of ROM techniques are proposed when conventional ROM techniques are too taxing to be computationally practical. This is achieved via a multi-level ROM methodology designed to take advantage of the multi-scale modeling strategy typically employed for computationally taxing models such as those associated with the modeling of nuclear reactor behavior. Second, the discrepancies between the original model and ROM model predictions over the full range of model application conditions are upper-bounded in a probabilistic sense with high probability. ROM techniques may be classified into two broad categories: surrogate construction techniques and dimensionality reduction techniques, with the latter being the primary focus of this work. We focus on dimensionality reduction, because it offers a rigorous approach by which reduction errors can be quantified via upper-bounds that are met in a probabilistic sense. Surrogate techniques typically rely on fitting a parametric model form to the original model at a number of training points, with the residual of the fit taken as a measure of the prediction accuracy of the surrogate. This approach, however, does not generally guarantee that the surrogate model predictions at points not included in the training process will be bound by the error estimated from the fitting residual. Dimensionality reduction techniques however employ a different philosophy to render the reduction, wherein randomized snapshots of the model variables, such as the

A reduced-dimensional model for near-wall transport in cardiovascular flows

PubMed Central

Hansen, Kirk B.

2015-01-01

Near-wall mass transport plays an important role in many cardiovascular processes, including the initiation of atherosclerosis, endothelial cell vasoregulation, and thrombogenesis. These problems are characterized by large Péclet and Schmidt numbers as well as a wide range of spatial and temporal scales, all of which impose computational difficulties. In this work, we develop an analytical relationship between the flow field and near-wall mass transport for high-Schmidt-number flows. This allows for the development of a wall-shear-stress-driven transport equation that lies on a codimension-one vessel-wall surface, significantly reducing computational cost in solving the transport problem. Separate versions of this equation are developed for the reaction-rate-limited and transport-limited cases, and numerical results in an idealized abdominal aortic aneurysm are compared to those obtained by solving the full transport equations over the entire domain. The reaction-rate-limited model matches the expected results well. The transport-limited model is accurate in the developed flow regions, but overpredicts wall flux at entry regions and reattachment points in the flow. PMID:26298313

Evaluating the effects of modeling errors for isolated finite three-dimensional targets

NASA Astrophysics Data System (ADS)

Henn, Mark-Alexander; Barnes, Bryan M.; Zhou, Hui

2017-10-01

Optical three-dimensional (3-D) nanostructure metrology utilizes a model-based metrology approach to determine critical dimensions (CDs) that are well below the inspection wavelength. Our project at the National Institute of Standards and Technology is evaluating how to attain key CD and shape parameters from engineered in-die capable metrology targets. More specifically, the quantities of interest are determined by varying the input parameters for a physical model until the simulations agree with the actual measurements within acceptable error bounds. As in most applications, establishing a reasonable balance between model accuracy and time efficiency is a complicated task. A well-established simplification is to model the intrinsically finite 3-D nanostructures as either periodic or infinite in one direction, reducing the computationally expensive 3-D simulations to usually less complex two-dimensional (2-D) problems. Systematic errors caused by this simplified model can directly influence the fitting of the model to the measurement data and are expected to become more apparent with decreasing lengths of the structures. We identify these effects using selected simulation results and present experimental setups, e.g., illumination numerical apertures and focal ranges, that can increase the validity of the 2-D approach.

Three-dimensional modeling of the plasma arc in arc welding

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

Xu, G.; Tsai, H. L.; Hu, J.

2008-11-15

Most previous three-dimensional modeling on gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) focuses on the weld pool dynamics and assumes the two-dimensional axisymmetric Gaussian distributions for plasma arc pressure and heat flux. In this article, a three-dimensional plasma arc model is developed, and the distributions of velocity, pressure, temperature, current density, and magnetic field of the plasma arc are calculated by solving the conservation equations of mass, momentum, and energy, as well as part of the Maxwell's equations. This three-dimensional model can be used to study the nonaxisymmetric plasma arc caused by external perturbations such asmore » an external magnetic field. It also provides more accurate boundary conditions when modeling the weld pool dynamics. The present work lays a foundation for true three-dimensional comprehensive modeling of GTAW and GMAW including the plasma arc, weld pool, and/or electrode.« less

Reduced-Order Models Based on POD-Tpwl for Compositional Subsurface Flow Simulation

NASA Astrophysics Data System (ADS)

Durlofsky, L. J.; He, J.; Jin, L. Z.

2014-12-01

A reduced-order modeling procedure applicable for compositional subsurface flow simulation will be described and applied. The technique combines trajectory piecewise linearization (TPWL) and proper orthogonal decomposition (POD) to provide highly efficient surrogate models. The method is based on a molar formulation (which uses pressure and overall component mole fractions as the primary variables) and is applicable for two-phase, multicomponent systems. The POD-TPWL procedure expresses new solutions in terms of linearizations around solution states generated and saved during previously simulated 'training' runs. High-dimensional states are projected into a low-dimensional subspace using POD. Thus, at each time step, only a low-dimensional linear system needs to be solved. Results will be presented for heterogeneous three-dimensional simulation models involving CO2 injection. Both enhanced oil recovery and carbon storage applications (with horizontal CO2 injectors) will be considered. Reasonably close agreement between full-order reference solutions and compositional POD-TPWL simulations will be demonstrated for 'test' runs in which the well controls differ from those used for training. Construction of the POD-TPWL model requires preprocessing overhead computations equivalent to about 3-4 full-order runs. Runtime speedups using POD-TPWL are, however, very significant - typically O(100-1000). The use of POD-TPWL for well control optimization will also be illustrated. For this application, some amount of retraining during the course of the optimization is required, which leads to smaller, but still significant, speedup factors.

Modeling change from large-scale high-dimensional spatio-temporal array data

NASA Astrophysics Data System (ADS)

Lu, Meng; Pebesma, Edzer

2014-05-01

The massive data that come from Earth observation satellite and other sensors provide significant information for modeling global change. At the same time, the high dimensionality of the data has brought challenges in data acquisition, management, effective querying and processing. In addition, the output of earth system modeling tends to be data intensive and needs methodologies for storing, validation, analyzing and visualization, e.g. as maps. An important proportion of earth system observations and simulated data can be represented as multi-dimensional array data, which has received increasingly attention in big data management and spatial-temporal analysis. Study cases will be developed in natural science such as climate change, hydrological modeling, sediment dynamics, from which the addressing of big data problems is necessary. Multi-dimensional array-based database management and analytics system such as Rasdaman, SciDB, and R will be applied to these cases. From these studies will hope to learn the strengths and weaknesses of these systems, how they might work together or how semantics of array operations differ, through addressing the problems associated with big data. Research questions include: • How can we reduce dimensions spatially and temporally, or thematically? • How can we extend existing GIS functions to work on multidimensional arrays? • How can we combine data sets of different dimensionality or different resolutions? • Can map algebra be extended to an intelligible array algebra? • What are effective semantics for array programming of dynamic data driven applications? • In which sense are space and time special, as dimensions, compared to other properties? • How can we make the analysis of multi-spectral, multi-temporal and multi-sensor earth observation data easy?

A three-dimensional model of Tangential YORP

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

Golubov, O.; Scheeres, D. J.; Krugly, Yu. N., E-mail: golubov@astron.kharkov.ua

2014-10-10

Tangential YORP, or TYORP, has recently been demonstrated to be an important factor in the evolution of an asteroid's rotation state. It is complementary to normal YORP, or NYORP, which used to be considered previously. While NYORP is produced by non-symmetry in the large-scale geometry of an asteroid, TYORP is due to heat conductivity in stones on the surface of the asteroid. To date, TYORP has been studied only in a simplified one-dimensional model, substituting stones with high long walls. This article for the first time considers TYORP in a realistic three-dimensional model, also including shadowing and self-illumination effects viamore » ray tracing. TYORP is simulated for spherical stones lying on regolith. The model includes only five free parameters and the dependence of the TYORP on each of them is studied. The TYORP torque appears to be smaller than previous estimates from the one-dimensional model, but is still comparable to the NYORP torques. These results can be used to estimate TYORP of different asteroids and also as a basis for more sophisticated models of TYORP.« less

A four-dimensional variational chemistry data assimilation scheme for Eulerian chemistry transport modeling

NASA Astrophysics Data System (ADS)

Eibern, Hendrik; Schmidt, Hauke

1999-08-01

The inverse problem of data assimilation of tropospheric trace gas observations into an Eulerian chemistry transport model has been solved by the four-dimensional variational technique including chemical reactions, transport, and diffusion. The University of Cologne European Air Pollution Dispersion Chemistry Transport Model 2 with the Regional Acid Deposition Model 2 gas phase mechanism is taken as the basis for developing a full four-dimensional variational data assimilation package, on the basis of the adjoint model version, which includes the adjoint operators of horizontal and vertical advection, implicit vertical diffusion, and the adjoint gas phase mechanism. To assess the potential and limitations of the technique without degrading the impact of nonperfect meteorological analyses and statistically not established error covariance estimates, artificial meteorological data and observations are used. The results are presented on the basis of a suite of experiments, where reduced records of artificial "observations" are provided to the assimilation procedure, while other "data" is retained for performance control of the analysis. The paper demonstrates that the four-dimensional variational technique is applicable for a comprehensive chemistry transport model in terms of computational and storage requirements on advanced parallel platforms. It is further shown that observed species can generally be analyzed, even if the "measurements" have unbiased random errors. More challenging experiments are presented, aiming to tax the skill of the method (1) by restricting available observations mostly to surface ozone observations for a limited assimilation interval of 6 hours and (2) by starting with poorly chosen first guess values. In this first such application to a three-dimensional chemistry transport model, success was also achieved in analyzing not only observed but also chemically closely related unobserved constituents.

Underwater striling engine design with modified one-dimensional model

NASA Astrophysics Data System (ADS)

Li, Daijin; Qin, Kan; Luo, Kai

2015-09-01

Stirling engines are regarded as an efficient and promising power system for underwater devices. Currently, many researches on one-dimensional model is used to evaluate thermodynamic performance of Stirling engine, but in which there are still some aspects which cannot be modeled with proper mathematical models such as mechanical loss or auxiliary power. In this paper, a four-cylinder double-acting Stirling engine for Unmanned Underwater Vehicles (UUVs) is discussed. And a one-dimensional model incorporated with empirical equations of mechanical loss and auxiliary power obtained from experiments is derived while referring to the Stirling engine computer model of National Aeronautics and Space Administration (NASA). The P-40 Stirling engine with sufficient testing results from NASA is utilized to validate the accuracy of this one-dimensional model. It shows that the maximum error of output power of theoretical analysis results is less than 18% over testing results, and the maximum error of input power is no more than 9%. Finally, a Stirling engine for UUVs is designed with Schmidt analysis method and the modified one-dimensional model, and the results indicate this designed engine is capable of showing desired output power.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation.

PubMed

Augustin, Moritz; Ladenbauer, Josef; Baumann, Fabian; Obermayer, Klaus

2017-06-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

PubMed Central

Baumann, Fabian; Obermayer, Klaus

2017-01-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for

One-Dimensional Modelling of Internal Ballistics

NASA Astrophysics Data System (ADS)

Monreal-González, G.; Otón-Martínez, R. A.; Velasco, F. J. S.; García-Cascáles, J. R.; Ramírez-Fernández, F. J.

2017-10-01

A one-dimensional model is introduced in this paper for problems of internal ballistics involving solid propellant combustion. First, the work presents the physical approach and equations adopted. Closure relationships accounting for the physical phenomena taking place during combustion (interfacial friction, interfacial heat transfer, combustion) are deeply discussed. Secondly, the numerical method proposed is presented. Finally, numerical results provided by this code (UXGun) are compared with results of experimental tests and with the outcome from a well-known zero-dimensional code. The model provides successful results in firing tests of artillery guns, predicting with good accuracy the maximum pressure in the chamber and muzzle velocity what highlights its capabilities as prediction/design tool for internal ballistics.

Physical lumping methods for developing linear reduced models for high speed propulsion systems

NASA Technical Reports Server (NTRS)

Immel, S. M.; Hartley, Tom T.; Deabreu-Garcia, J. Alex

1991-01-01

In gasdynamic systems, information travels in one direction for supersonic flow and in both directions for subsonic flow. A shock occurs at the transition from supersonic to subsonic flow. Thus, to simulate these systems, any simulation method implemented for the quasi-one-dimensional Euler equations must have the ability to capture the shock. In this paper, a technique combining both backward and central differencing is presented. The equations are subsequently linearized about an operating point and formulated into a linear state space model. After proper implementation of the boundary conditions, the model order is reduced from 123 to less than 10 using the Schur method of balancing. Simulations comparing frequency and step response of the reduced order model and the original system models are presented.

Comparisons between thermodynamic and one-dimensional combustion models of spark-ignition engines

NASA Technical Reports Server (NTRS)

Ramos, J. I.

1986-01-01

Results from a one-dimensional combustion model employing a constant eddy diffusivity and a one-step chemical reaction are compared with those of one-zone and two-zone thermodynamic models to study the flame propagation in a spark-ignition engine. One-dimensional model predictions are found to be very sensitive to the eddy diffusivity and reaction rate data. The average mixing temperature found using the one-zone thermodynamic model is higher than those of the two-zone and one-dimensional models during the compression stroke, and that of the one-dimensional model is higher than those predicted by both thermodynamic models during the expansion stroke. The one-dimensional model is shown to predict an accelerating flame even when the front approaches the cold cylinder wall.

Numerical Modeling of Three-Dimensional Confined Flows

NASA Technical Reports Server (NTRS)

Greywall, M. S.

1981-01-01

A three dimensional confined flow model is presented. The flow field is computed by calculating velocity and enthalpy along a set of streamlines. The finite difference equations are obtained by applying conservation principles to streamtubes constructed around the chosen streamlines. With appropriate substitutions for the body force terms, the approach computes three dimensional magnetohydrodynamic channel flows. A listing of a computer code, based on this approach is presented in FORTRAN IV language. The code computes three dimensional compressible viscous flow through a rectangular duct, with the duct cross section specified along the axis.

Dimensional models of personality: the five-factor model and the DSM-5

PubMed Central

Trull, Timothy J.; Widiger, Thomas A.

2013-01-01

It is evident that the classification of personality disorder is shifting toward a dimensional trait model and, more specifically, the five-factor model (FFM). The purpose of this paper is to provide an overview of the FFM of personality disorder. It will begin with a description of this dimensional model of normal and abnormal personality functioning, followed by a comparison with a proposal for future revisions to DSM-5 and a discussion of its potential advantages as an integrative hierarchical model of normal and abnormal personality structure. PMID:24174888

A two-state hysteresis model from high-dimensional friction

PubMed Central

Biswas, Saurabh; Chatterjee, Anindya

2015-01-01

In prior work (Biswas & Chatterjee 2014 Proc. R. Soc. A 470, 20130817 (doi:10.1098/rspa.2013.0817)), we developed a six-state hysteresis model from a high-dimensional frictional system. Here, we use a more intuitively appealing frictional system that resembles one studied earlier by Iwan. The basis functions now have simple analytical description. The number of states required decreases further, from six to the theoretical minimum of two. The number of fitted parameters is reduced by an order of magnitude, to just six. An explicit and faster numerical solution method is developed. Parameter fitting to match different specified hysteresis loops is demonstrated. In summary, a new two-state model of hysteresis is presented that is ready for practical implementation. Essential Matlab code is provided. PMID:26587279

Limit Properties of One Dimensional Periodic Hopping Model

NASA Astrophysics Data System (ADS)

Zhang, Yun-xin

2010-02-01

One dimensional periodic hopping model is useful to understand the motion of microscopic particles in thermal noise environment. In this research, by formal calculation and based on detailed balance, the explicit expressions of the limits of mean velocity and diffusion constant of this model as the number of internal mechanochemical sates tend to infinity are obtained. These results will be helpful to understand the limit of the one dimensional hopping model. At the same time, the work can be used to get more useful results in continuous form from the corresponding ones obtained by discrete models.

Linking a one-dimensional pesticide fate model to a three-dimensional groundwater model to simulate pollution risks of shallow and deep groundwater underlying fractured till.

PubMed

Stenemo, Fredrik; Jørgensen, Peter R; Jarvis, Nicholas

2005-09-01

The one-dimensional pesticide fate model MACRO was loose-linked to the three-dimensional discrete fracture/matrix diffusion model FRAC3DVS to describe transport of the pesticide mecoprop in a fractured moraine till and local sand aquifer (5-5.5 m depth) overlying a regional limestone aquifer (16 m depth) at Havdrup, Denmark. Alternative approaches to describe the upper boundary in the groundwater model were examined. Field-scale simulations were run to compare a uniform upper boundary condition with a spatially variable upper boundary derived from Monte-Carlo simulations with MACRO. Plot-scale simulations were run to investigate the influence of the temporal resolution of the upper boundary conditions for fluxes in the groundwater model and the effects of different assumptions concerning the macropore/fracture connectivity between the two models. The influence of within-field variability of leaching on simulated mecoprop concentrations in the local aquifer was relatively small. A fully transient simulation with FRAC3DVS gave 20 times larger leaching to the regional aquifer compared to the case with steady-state water flow, assuming full connectivity with respect to macropores/fractures across the boundary between the two models. For fully transient simulations 'disconnecting' the macropores/fractures at the interface between the two models reduced leaching by a factor 24. A fully connected, transient simulation with FRAC3DVS, with spatially uniform upper boundary fluxes derived from a MACRO simulation with 'effective' parameters is therefore recommended for assessing leaching risks to the regional aquifer, at this, and similar sites.

Low-Dimensional Model of a Cylinder Wake

NASA Astrophysics Data System (ADS)

Luchtenburg, Mark; Cohen, Kelly; Siegel, Stefan; McLaughlin, Tom

2003-11-01

In a two-dimensional cylinder wake, self-excited oscillations in the form of periodic shedding of vortices are observed above a critical Reynolds number of about 47. These flow-induced non-linear oscillations lead to some undesirable effects associated with unsteady pressures such as fluid-structure interactions. An effective way of suppressing the self-excited flow oscillations is by the incorporation of closed-loop flow control. In this effort, a low dimensional, proper orthogonal decomposition (POD) model is based on data obtained from direct numerical simulations of the Navier Stokes equations for the two dimensional circular cylinder wake at a Reynolds number of 100. Three different conditions are examined, namely, the unforced wake experiencing steady-state vortex shedding, the transient behavior of the unforced wake at the startup of the simulation, and transient response to open-loop harmonic forcing by translation. We discuss POD mode selection and the number of modes that need to be included in the low-dimensional model. It is found that the transient dynamics need to be represented by a coupled system that includes an aperiodic mean-flow mode, an aperiodic shift mode and the periodic von Karman modes. Finally, a least squares mapping method is introduced to develop the non-linear state equations. The predictive capability of the state equations demonstrates the ability of the above approach to model the transient dynamics of the wake.

COSMO-PAFOG: Three-dimensional fog forecasting with the high-resolution COSMO-model

NASA Astrophysics Data System (ADS)

Hacker, Maike; Bott, Andreas

2017-04-01

The presence of fog can have critical impact on shipping, aviation and road traffic increasing the risk of serious accidents. Besides these negative impacts of fog, in arid regions fog is explored as a supplementary source of water for human settlements. Thus the improvement of fog forecasts holds immense operational value. The aim of this study is the development of an efficient three-dimensional numerical fog forecast model based on a mesoscale weather prediction model for the application in the Namib region. The microphysical parametrization of the one-dimensional fog forecast model PAFOG (PArameterized FOG) is implemented in the three-dimensional nonhydrostatic mesoscale weather prediction model COSMO (COnsortium for Small-scale MOdeling) developed and maintained by the German Meteorological Service. Cloud water droplets are introduced in COSMO as prognostic variables, thus allowing a detailed description of droplet sedimentation. Furthermore, a visibility parametrization depending on the liquid water content and the droplet number concentration is implemented. The resulting fog forecast model COSMO-PAFOG is run with kilometer-scale horizontal resolution. In vertical direction, we use logarithmically equidistant layers with 45 of 80 layers in total located below 2000 m. Model results are compared to satellite observations and synoptic observations of the German Meteorological Service for a domain in the west of Germany, before the model is adapted to the geographical and climatological conditions in the Namib desert. COSMO-PAFOG is able to represent the horizontal structure of fog patches reasonably well. Especially small fog patches typical of radiation fog can be simulated in agreement with observations. Ground observations of temperature are also reproduced. Simulations without the PAFOG microphysics yield unrealistically high liquid water contents. This in turn reduces the radiative cooling of the ground, thus inhibiting nocturnal temperature decrease. The

Recurrence relations in one-dimensional Ising models.

PubMed

da Conceição, C M Silva; Maia, R N P

2017-09-01

The exact finite-size partition function for the nonhomogeneous one-dimensional (1D) Ising model is found through an approach using algebra operators. Specifically, in this paper we show that the partition function can be computed through a trace from a linear second-order recurrence relation with nonconstant coefficients in matrix form. A relation between the finite-size partition function and the generalized Lucas polynomials is found for the simple homogeneous model, thus establishing a recursive formula for the partition function. This is an important property and it might indicate the possible existence of recurrence relations in higher-dimensional Ising models. Moreover, assuming quenched disorder for the interactions within the model, the quenched averaged magnetic susceptibility displays a nontrivial behavior due to changes in the ferromagnetic concentration probability.

Full-dimensional and reduced-dimensional calculations of initial state-selected reaction probabilities studying the H + CH{sub 4} → H{sub 2} + CH{sub 3} reaction on a neural network PES

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

Welsch, Ralph, E-mail: rwelsch@uni-bielefeld.de; Manthe, Uwe, E-mail: uwe.manthe@uni-bielefeld.de

2015-02-14

Initial state-selected reaction probabilities of the H + CH{sub 4} → H{sub 2} + CH{sub 3} reaction are calculated in full and reduced dimensionality on a recent neural network potential [X. Xu, J. Chen, and D. H. Zhang, Chin. J. Chem. Phys. 27, 373 (2014)]. The quantum dynamics calculation employs the quantum transition state concept and the multi-layer multi-configurational time-dependent Hartree approach and rigorously studies the reaction for vanishing total angular momentum (J = 0). The calculations investigate the accuracy of the neutral network potential and study the effect resulting from a reduced-dimensional treatment. Very good agreement is found betweenmore » the present results obtained on the neural network potential and previous results obtained on a Shepard interpolated potential energy surface. The reduced-dimensional calculations only consider motion in eight degrees of freedom and retain the C{sub 3v} symmetry of the methyl fragment. Considering reaction starting from the vibrational ground state of methane, the reaction probabilities calculated in reduced dimensionality are moderately shifted in energy compared to the full-dimensional ones but otherwise agree rather well. Similar agreement is also found if reaction probabilities averaged over similar types of vibrational excitation of the methane reactant are considered. In contrast, significant differences between reduced and full-dimensional results are found for reaction probabilities starting specifically from symmetric stretching, asymmetric (f{sub 2}-symmetric) stretching, or e-symmetric bending excited states of methane.« less

A three-dimensional transport model for the middle atmosphere

NASA Technical Reports Server (NTRS)

Rasch, Philip J.; Tie, Xuexi; Boville, Byron A.; Williamson, David L.

1994-01-01

In this paper we describe fundamental properties of an 'off-line' three-dimensional transport model, that is, a model which uses prescribed rather than predicted winds. The model is currently used primarily for studying problems of the middle atmosphere because we have not (yet) incorporated a formulation for the convective transport of trace species, a prerequisite for many tropospheric problems. The off-line model is simpler and less expensive than a model which predicts the wind and mass evolution (an 'on-line' model), but it is more complex than the two-dimensional (2-D) zonally averaged transport models often used in the study of chemistry and transport in the middle atmosphere. It thus serves as a model of intermediate complexity and can fill a useful niche for the study of transport and chemistry. We compare simulations of four tracers, released in the lower stratosphere, in both the on- and off-line models to document the difference resulting from differences in modeling the same problem with this intermediate model. These differences identify the price to be paid in going to a cheaper and simpler calculation. The off-line model transports a tracer in three dimensions. For this reason, it requires fewer approximations than 2-D transport model, which must parameterize the effects of mixing by transient and zonally asymmetric wind features. We compare simulations of the off-line model with simulations of a 2-D model for two problems. First, we compare 2-D and three-dimensional (3-D) models by simulating the emission of an NO(x)-like tracer by a fleet of high-speed aircraft. The off-line model is then used to simulate the transport of C-14 and to contrast its simulation properties to that of the host of 2-D models which participated in an identical simulation in a recent NASA model intercomparison. The off-line model is shown to be somewhat sensitive to the sampling strategy for off-line winds. Simulations with daily averaged winds are in very good qualitative

Evaluation of the parameters affecting bone temperature during drilling using a three-dimensional dynamic elastoplastic finite element model.

PubMed

Chen, Yung-Chuan; Tu, Yuan-Kun; Zhuang, Jun-Yan; Tsai, Yi-Jung; Yen, Cheng-Yo; Hsiao, Chih-Kun

2017-11-01

A three-dimensional dynamic elastoplastic finite element model was constructed and experimentally validated and was used to investigate the parameters which influence bone temperature during drilling, including the drill speed, feeding force, drill bit diameter, and bone density. Results showed the proposed three-dimensional dynamic elastoplastic finite element model can effectively simulate the temperature elevation during bone drilling. The bone temperature rise decreased with an increase in feeding force and drill speed, however, increased with the diameter of drill bit or bone density. The temperature distribution is significantly affected by the drilling duration; a lower drilling speed reduced the exposure duration, decreases the region of the thermally affected zone. The constructed model could be applied for analyzing the influence parameters during bone drilling to reduce the risk of thermal necrosis. It may provide important information for the design of drill bits and surgical drilling powers.

Dimensional reduction of the Standard Model coupled to a new singlet scalar field

NASA Astrophysics Data System (ADS)

Brauner, Tomáš; Tenkanen, Tuomas V. I.; Tranberg, Anders; Vuorinen, Aleksi; Weir, David J.

2017-03-01

We derive an effective dimensionally reduced theory for the Standard Model augmented by a real singlet scalar. We treat the singlet as a superheavy field and integrate it out, leaving an effective theory involving only the Higgs and SU(2) L × U(1) Y gauge fields, identical to the one studied previously for the Standard Model. This opens up the possibility of efficiently computing the order and strength of the electroweak phase transition, numerically and nonperturbatively, in this extension of the Standard Model. Understanding the phase diagram is crucial for models of electroweak baryogenesis and for studying the production of gravitational waves at thermal phase transitions.

Quasi-exact solvability and entropies of the one-dimensional regularised Calogero model

NASA Astrophysics Data System (ADS)

Pont, Federico M.; Osenda, Omar; Serra, Pablo

2018-05-01

The Calogero model can be regularised through the introduction of a cutoff parameter which removes the divergence in the interaction term. In this work we show that the one-dimensional two-particle regularised Calogero model is quasi-exactly solvable and that for certain values of the Hamiltonian parameters the eigenfunctions can be written in terms of Heun’s confluent polynomials. These eigenfunctions are such that the reduced density matrix of the two-particle density operator can be obtained exactly as well as its entanglement spectrum. We found that the number of non-zero eigenvalues of the reduced density matrix is finite in these cases. The limits for the cutoff distance going to zero (Calogero) and infinity are analysed and all the previously obtained results for the Calogero model are reproduced. Once the exact eigenfunctions are obtained, the exact von Neumann and Rényi entanglement entropies are studied to characterise the physical traits of the model. The quasi-exactly solvable character of the model is assessed studying the numerically calculated Rényi entropy and entanglement spectrum for the whole parameter space.

A methodology for reduced order modeling and calibration of the upper atmosphere

NASA Astrophysics Data System (ADS)

Mehta, Piyush M.; Linares, Richard

2017-10-01

Atmospheric drag is the largest source of uncertainty in accurately predicting the orbit of satellites in low Earth orbit (LEO). Accurately predicting drag for objects that traverse LEO is critical to space situational awareness. Atmospheric models used for orbital drag calculations can be characterized either as empirical or physics-based (first principles based). Empirical models are fast to evaluate but offer limited real-time predictive/forecasting ability, while physics based models offer greater predictive/forecasting ability but require dedicated parallel computational resources. Also, calibration with accurate data is required for either type of models. This paper presents a new methodology based on proper orthogonal decomposition toward development of a quasi-physical, predictive, reduced order model that combines the speed of empirical and the predictive/forecasting capabilities of physics-based models. The methodology is developed to reduce the high dimensionality of physics-based models while maintaining its capabilities. We develop the methodology using the Naval Research Lab's Mass Spectrometer Incoherent Scatter model and show that the diurnal and seasonal variations can be captured using a small number of modes and parameters. We also present calibration of the reduced order model using the CHAMP and GRACE accelerometer-derived densities. Results show that the method performs well for modeling and calibration of the upper atmosphere.

A computationally fast, reduced model for simulating landslide dynamics and tsunamis generated by landslides in natural terrains

NASA Astrophysics Data System (ADS)

Mohammed, F.

2016-12-01

Landslide hazards such as fast-moving debris flows, slow-moving landslides, and other mass flows cause numerous fatalities, injuries, and damage. Landslide occurrences in fjords, bays, and lakes can additionally generate tsunamis with locally extremely high wave heights and runups. Two-dimensional depth-averaged models can successfully simulate the entire lifecycle of the three-dimensional landslide dynamics and tsunami propagation efficiently and accurately with the appropriate assumptions. Landslide rheology is defined using viscous fluids, visco-plastic fluids, and granular material to account for the possible landslide source materials. Saturated and unsaturated rheologies are further included to simulate debris flow, debris avalanches, mudflows, and rockslides respectively. The models are obtained by reducing the fully three-dimensional Navier-Stokes equations with the internal rheological definition of the landslide material, the water body, and appropriate scaling assumptions to obtain the depth-averaged two-dimensional models. The landslide and tsunami models are coupled to include the interaction between the landslide and the water body for tsunami generation. The reduced models are solved numerically with a fast semi-implicit finite-volume, shock-capturing based algorithm. The well-balanced, positivity preserving algorithm accurately accounts for wet-dry interface transition for the landslide runout, landslide-water body interface, and the tsunami wave flooding on land. The models are implemented as a General-Purpose computing on Graphics Processing Unit-based (GPGPU) suite of models, either coupled or run independently within the suite. The GPGPU implementation provides up to 1000 times speedup over a CPU-based serial computation. This enables simulations of multiple scenarios of hazard realizations that provides a basis for a probabilistic hazard assessment. The models have been successfully validated against experiments, past studies, and field data

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Reduced Order Modeling in General Relativity

NASA Astrophysics Data System (ADS)

Tiglio, Manuel

2014-03-01

Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).

Exact solution of a one-dimensional model of strained epitaxy on a periodically modulated substrate

NASA Astrophysics Data System (ADS)

Tokar, V. I.; Dreyssé, H.

2005-03-01

We consider a one-dimensional lattice gas model of strained epitaxy with the elastic strain accounted for through a finite number of cluster interactions comprising contiguous atomic chains. Interactions of this type arise in the models of strained epitaxy based on the Frenkel-Kontorova model. Furthermore, the deposited atoms interact with the substrate via an arbitrary periodic potential of period L . This model is solved exactly with the use of an appropriately adopted technique developed recently in the theory of protein folding. The advantage of the proposed approach over the standard transfer-matrix method is that it reduces the problem to finding the largest eigenvalue of a matrix of size L instead of 2L-1 , which is vital in the case of nanostructures where L may measure in hundreds of interatomic distances. Our major conclusion is that the substrate modulation always facilitates the size calibration of self-assembled nanoparticles in one- and two-dimensional systems.

Zero dimensional model of atmospheric SMD discharge and afterglow in humid air

NASA Astrophysics Data System (ADS)

Smith, Ryan; Kemaneci, Efe; Offerhaus, Bjoern; Stapelmann, Katharina; Peter Brinkmann, Ralph

2016-09-01

A novel mesh-like Surface Micro Discharge (SMD) device designed for surface wound treatment is simulated by multiple time-scaled zero-dimensional models. The chemical dynamics of the discharge are resolved in time at atmospheric pressure in humid conditions. Simulated are the particle densities of electrons, 26 ionic species, and 26 reactive neutral species including: O3, NO, and HNO3. The total of 53 described species are constrained by 624 reactions within the simulated plasma discharge volume. The neutral species are allowed to diffuse into a diffusive gas regime which is of primary interest. Two interdependent zero-dimensional models separated by nine orders of magnitude in temporal resolution are used to accomplish this; thereby reducing the computational load. Through variation of control parameters such as: ignition frequency, deposited power density, duty cycle, humidity level, and N2 content, the ideal operation conditions for the SMD device can be predicted. The described model has been verified by matching simulation parameters and comparing results to that of previous works. Current operating conditions of the experimental mesh-like SMD were matched and results are compared to the simulations. Work supported by SFB TR 87.

Three-Dimensional Direct Numerical Simulation of Methane-Air Turbulent Premixed Flames with Reduced Kinetic Mechanism

NASA Astrophysics Data System (ADS)

Tanahashi, Mamoru; Kikuta, Satoshi; Miyauchi, Toshio

2004-11-01

Three-dimensional DNS of methane-air turbulent premixed flames have been conducted to investigate local extinction mechanism of turbulent premixed flames. A reduced kinetic mechanism (MeCH-19), which is created from GRI-Mech. 2.11 and includes 23 reactive species and 19 step reactions, are used to simulate CH_4-O_2-N2 reaction in turbulence. The effectiveness of this reduced kinetic mechanism has been conformed by preliminary two-dimensional DNS with the reduced kinetic mechanism and two detailed kinetic mechanisms; GRI-Mech. 2.11 and Miller & Bowman. Flame structures of methane-air turbulent premixed flames are compared with those of hydrogen-air turbulent premixed flames which have been obtained by 3D-DNS with a detailed kinetic mechanism in our previous study. Local extinctions occur in methane-air turbulent premixed flames, whereas no extinction is observed for hydrogen-air flames in nearly same turbulence condition. The local extinction mechanism is discussed based on eddy/flame interaction in small scales.

THREE-DIMENSIONAL MODEL FOR HYPERTHERMIA CALCULATIONS

EPA Science Inventory

Realistic three-dimensional models that predict temperature distributions with a high degree of spatial resolution in bodies exposed to electromagnetic (EM) fields are required in the application of hyperthermia for cancer treatment. To ascertain the thermophysiologic response of...

VALIDITY OF A TWO-DIMENSIONAL MODEL FOR VARIABLE-DENSITY HYDRODYNAMIC CIRCULATION

EPA Science Inventory

A three-dimensional model of temperatures and currents has been formulated to assist in the analysis and interpretation of the dynamics of stratified lakes. In this model, nonlinear eddy coefficients for viscosity and conductivities are included. A two-dimensional model (one vert...

Three-dimensional finite element modelling of muscle forces during mastication.

PubMed

Röhrle, Oliver; Pullan, Andrew J

2007-01-01

This paper presents a three-dimensional finite element model of human mastication. Specifically, an anatomically realistic model of the masseter muscles and associated bones is used to investigate the dynamics of chewing. A motion capture system is used to track the jaw motion of a subject chewing standard foods. The three-dimensional nonlinear deformation of the masseter muscles are calculated via the finite element method, using the jaw motion data as boundary conditions. Motion-driven muscle activation patterns and a transversely isotropic material law, defined in a muscle-fibre coordinate system, are used in the calculations. Time-force relationships are presented and analysed with respect to different tasks during mastication, e.g. opening, closing, and biting, and are also compared to a more traditional one-dimensional model. The results strongly suggest that, due to the complex arrangement of muscle force directions, modelling skeletal muscles as conventional one-dimensional lines of action might introduce a significant source of error.

Office-Based Three-Dimensional Printing Workflow for Craniomaxillofacial Fracture Repair.

PubMed

Elegbede, Adekunle; Diaconu, Silviu C; McNichols, Colton H L; Seu, Michelle; Rasko, Yvonne M; Grant, Michael P; Nam, Arthur J

2018-03-08

Three-dimensional printing of patient-specific models is being used in various aspects of craniomaxillofacial reconstruction. Printing is typically outsourced to off-site vendors, with the main disadvantages being increased costs and time for production. Office-based 3-dimensional printing has been proposed as a means to reduce costs and delays, but remains largely underused because of the perception among surgeons that it is futuristic, highly technical, and prohibitively expensive. The goal of this report is to demonstrate the feasibility and ease of incorporating in-office 3-dimensional printing into the standard workflow for facial fracture repair.Patients with complex mandible fractures requiring open repair were identified. Open-source software was used to create virtual 3-dimensional skeletal models of the, initial injury pattern, and then the ideally reduced fractures based on preoperative computed tomography (CT) scan images. The virtual 3-dimensional skeletal models were then printed in our office using a commercially available 3-dimensional printer and bioplastic filament. The 3-dimensional skeletal models were used as templates to bend and shape titanium plates that were subsequently used for intraoperative fixation.Average print time was 6 hours. Excluding the 1-time cost of the 3-dimensional printer of $2500, roughly the cost of a single commercially produced model, the average material cost to print 1 model mandible was $4.30. Postoperative CT imaging demonstrated precise, predicted reduction in all patients.Office-based 3-dimensional printing of skeletal models can be routinely used in repair of facial fractures in an efficient and cost-effective manner.

Particle orbits in two-dimensional equilibrium models for the magnetotail

NASA Technical Reports Server (NTRS)

Karimabadi, H.; Pritchett, P. L.; Coroniti, F. V.

1990-01-01

Assuming that there exist an equilibrium state for the magnetotail, particle orbits are investigated in two-dimensional kinetic equilibrium models for the magnetotail. Particle orbits in the equilibrium field are compared with those calculated earlier with one-dimensional models, where the main component of the magnetic field (Bx) was approximated as either a hyperbolic tangent or a linear function of z with the normal field (Bz) assumed to be a constant. It was found that the particle orbits calculated with the two types of models are significantly different, mainly due to the neglect of the variation of Bx with x in the one-dimensional fields.

Analysis of the Three-Dimensional Vector FAÇADE Model Created from Photogrammetric Data

NASA Astrophysics Data System (ADS)

Kamnev, I. S.; Seredovich, V. A.

2017-12-01

The results of the accuracy assessment analysis for creation of a three-dimensional vector model of building façade are described. In the framework of the analysis, analytical comparison of three-dimensional vector façade models created by photogrammetric and terrestrial laser scanning data has been done. The three-dimensional model built from TLS point clouds was taken as the reference one. In the course of the experiment, the three-dimensional model to be analyzed was superimposed on the reference one, the coordinates were measured and deviations between the same model points were determined. The accuracy estimation of the three-dimensional model obtained by using non-metric digital camera images was carried out. Identified façade surface areas with the maximum deviations were revealed.

Existence of global weak solution for a reduced gravity two and a half layer model

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

Guo, Zhenhua, E-mail: zhenhua.guo.math@gmail.com; Li, Zilai, E-mail: lizilai0917@163.com; Yao, Lei, E-mail: yaolei1056@hotmail.com

2013-12-15

We investigate the existence of global weak solution to a reduced gravity two and a half layer model in one-dimensional bounded spatial domain or periodic domain. Also, we show that any possible vacuum state has to vanish within finite time, then the weak solution becomes a unique strong one.

One-Dimensional Harmonic Model for Biomolecules

PubMed Central

Krizan, John E.

1973-01-01

Following in spirit a paper by Rosen, we propose a one-dimensional harmonic model for biomolecules. Energy bands with gaps of the order of semi-conductor gaps are found. The method is discussed for general symmetric and periodic potential functions. PMID:4709518

Exact solution of three-dimensional transport problems using one-dimensional models. [in semiconductor devices

NASA Technical Reports Server (NTRS)

Misiakos, K.; Lindholm, F. A.

1986-01-01

Several parameters of certain three-dimensional semiconductor devices including diodes, transistors, and solar cells can be determined without solving the actual boundary-value problem. The recombination current, transit time, and open-circuit voltage of planar diodes are emphasized here. The resulting analytical expressions enable determination of the surface recombination velocity of shallow planar diodes. The method involves introducing corresponding one-dimensional models having the same values of these parameters.

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1994-10-15

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1993-12-31

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

PubMed

Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain

2015-10-01

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.

Particle-in-a-box model of one-dimensional excitons in conjugated polymers

NASA Astrophysics Data System (ADS)

Pedersen, Thomas G.; Johansen, Per M.; Pedersen, Henrik C.

2000-04-01

A simple two-particle model of excitons in conjugated polymers is proposed as an alternative to usual highly computationally demanding quantum chemical methods. In the two-particle model, the exciton is described as an electron-hole pair interacting via Coulomb forces and confined to the polymer backbone by rigid walls. Furthermore, by integrating out the transverse part, the two-particle equation is reduced to one-dimensional form. It is demonstrated how essentially exact solutions are obtained in the cases of short and long conjugation length, respectively. From a linear combination of these cases an approximate solution for the general case is obtained. As an application of the model the influence of a static electric field on the electron-hole overlap integral and exciton energy is considered.

An Energy Model of Place Cell Network in Three Dimensional Space.

PubMed

Wang, Yihong; Xu, Xuying; Wang, Rubin

2018-01-01

Place cells are important elements in the spatial representation system of the brain. A considerable amount of experimental data and classical models are achieved in this area. However, an important question has not been addressed, which is how the three dimensional space is represented by the place cells. This question is preliminarily surveyed by energy coding method in this research. Energy coding method argues that neural information can be expressed by neural energy and it is convenient to model and compute for neural systems due to the global and linearly addable properties of neural energy. Nevertheless, the models of functional neural networks based on energy coding method have not been established. In this work, we construct a place cell network model to represent three dimensional space on an energy level. Then we define the place field and place field center and test the locating performance in three dimensional space. The results imply that the model successfully simulates the basic properties of place cells. The individual place cell obtains unique spatial selectivity. The place fields in three dimensional space vary in size and energy consumption. Furthermore, the locating error is limited to a certain level and the simulated place field agrees to the experimental results. In conclusion, this is an effective model to represent three dimensional space by energy method. The research verifies the energy efficiency principle of the brain during the neural coding for three dimensional spatial information. It is the first step to complete the three dimensional spatial representing system of the brain, and helps us further understand how the energy efficiency principle directs the locating, navigating, and path planning function of the brain.

One-dimensional biomass fast pyrolysis model with reaction kinetics integrated in an Aspen Plus Biorefinery Process Model

DOE PAGES

Humbird, David; Trendewicz, Anna; Braun, Robert; ...

2017-01-12

A biomass fast pyrolysis reactor model with detailed reaction kinetics and one-dimensional fluid dynamics was implemented in an equation-oriented modeling environment (Aspen Custom Modeler). Portions of this work were detailed in previous publications; further modifications have been made here to improve stability and reduce execution time of the model to make it compatible for use in large process flowsheets. The detailed reactor model was integrated into a larger process simulation in Aspen Plus and was stable for different feedstocks over a range of reactor temperatures. Sample results are presented that indicate general agreement with experimental results, but with higher gasmore » losses caused by stripping of the bio-oil by the fluidizing gas in the simulated absorber/condenser. Lastly, this integrated modeling approach can be extended to other well-defined, predictive reactor models for fast pyrolysis, catalytic fast pyrolysis, as well as other processes.« less

One-dimensional biomass fast pyrolysis model with reaction kinetics integrated in an Aspen Plus Biorefinery Process Model

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

Humbird, David; Trendewicz, Anna; Braun, Robert

A biomass fast pyrolysis reactor model with detailed reaction kinetics and one-dimensional fluid dynamics was implemented in an equation-oriented modeling environment (Aspen Custom Modeler). Portions of this work were detailed in previous publications; further modifications have been made here to improve stability and reduce execution time of the model to make it compatible for use in large process flowsheets. The detailed reactor model was integrated into a larger process simulation in Aspen Plus and was stable for different feedstocks over a range of reactor temperatures. Sample results are presented that indicate general agreement with experimental results, but with higher gasmore » losses caused by stripping of the bio-oil by the fluidizing gas in the simulated absorber/condenser. Lastly, this integrated modeling approach can be extended to other well-defined, predictive reactor models for fast pyrolysis, catalytic fast pyrolysis, as well as other processes.« less

Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.

PubMed

Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela

2016-12-01

Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.

Supersymmetric gauged matrix models from dimensional reduction on a sphere

NASA Astrophysics Data System (ADS)

Closset, Cyril; Ghim, Dongwook; Seong, Rak-Kyeong

2018-05-01

It was recently proposed that N = 1 supersymmetric gauged matrix models have a duality of order four — that is, a quadrality — reminiscent of infrared dualities of SQCD theories in higher dimensions. In this note, we show that the zero-dimensional quadrality proposal can be inferred from the two-dimensional Gadde-Gukov-Putrov triality. We consider two-dimensional N = (0, 2) SQCD compactified on a sphere with the half-topological twist. For a convenient choice of R-charge, the zero-mode sector on the sphere gives rise to a simple N = 1 gauged matrix model. Triality on the sphere then implies a triality relation for the supersymmetric matrix model, which can be completed to the full quadrality.

In vitro three-dimensional aortic vasculature modeling based on sensor fusion between intravascular ultrasound and magnetic tracker.

PubMed

Shi, Chaoyang; Tercero, Carlos; Ikeda, Seiichi; Ooe, Katsutoshi; Fukuda, Toshio; Komori, Kimihiro; Yamamoto, Kiyohito

2012-09-01

It is desirable to reduce aortic stent graft installation time and the amount of contrast media used for this process. Guidance with augmented reality can achieve this by facilitating alignment of the stent graft with the renal and mesenteric arteries. For this purpose, a sensor fusion is proposed between intravascular ultrasound (IVUS) and magnetic trackers to construct three-dimensional virtual reality models of the blood vessels, as well as improvements to the gradient vector flow snake for boundary detection in ultrasound images. In vitro vasculature imaging experiments were done with hybrid probe and silicone models of the vasculature. The dispersion of samples for the magnetic tracker in the hybrid probe increased less than 1 mm when the IVUS was activated. Three-dimensional models of the descending thoracic aorta, with cross-section radius average error of 0.94 mm, were built from the data fusion. The development of this technology will enable reduction in the amount of contrast media required for in vivo and real-time three-dimensional blood vessel imaging. Copyright © 2012 John Wiley & Sons, Ltd.

Computational technique and performance of Transient Inundation Model for Rivers--2 Dimensional (TRIM2RD) : a depth-averaged two-dimensional flow model

USGS Publications Warehouse

Fulford, Janice M.

2003-01-01

A numerical computer model, Transient Inundation Model for Rivers -- 2 Dimensional (TrimR2D), that solves the two-dimensional depth-averaged flow equations is documented and discussed. The model uses a semi-implicit, semi-Lagrangian finite-difference method. It is a variant of the Trim model and has been used successfully in estuarine environments such as San Francisco Bay. The abilities of the model are documented for three scenarios: uniform depth flows, laboratory dam-break flows, and large-scale riverine flows. The model can start computations from a ?dry? bed and converge to accurate solutions. Inflows are expressed as source terms, which limits the use of the model to sufficiently long reaches where the flow reaches equilibrium with the channel. The data sets used by the investigation demonstrate that the model accurately propagates flood waves through long river reaches and simulates dam breaks with abrupt water-surface changes.

Fractional calculus phenomenology in two-dimensional plasma models

NASA Astrophysics Data System (ADS)

Gustafson, Kyle; Del Castillo Negrete, Diego; Dorland, Bill

2006-10-01

Transport processes in confined plasmas for fusion experiments, such as ITER, are not well-understood at the basic level of fully nonlinear, three-dimensional kinetic physics. Turbulent transport is invoked to describe the observed levels in tokamaks, which are orders of magnitude greater than the theoretical predictions. Recent results show the ability of a non-diffusive transport model to describe numerical observations of turbulent transport. For example, resistive MHD modeling of tracer particle transport in pressure-gradient driven turbulence for a three-dimensional plasma reveals that the superdiffusive (2̂˜t^α where α> 1) radial transport in this system is described quantitatively by a fractional diffusion equation Fractional calculus is a generalization involving integro-differential operators, which naturally describe non-local behaviors. Our previous work showed the quantitative agreement of special fractional diffusion equation solutions with numerical tracer particle flows in time-dependent linearized dynamics of the Hasegawa-Mima equation (for poloidal transport in a two-dimensional cold-ion plasma). In pursuit of a fractional diffusion model for transport in a gyrokinetic plasma, we now present numerical results from tracer particle transport in the nonlinear Hasegawa-Mima equation and a planar gyrokinetic model. Finite Larmor radius effects will be discussed. D. del Castillo Negrete, et al, Phys. Rev. Lett. 94, 065003 (2005).

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

A one-dimensional model for gas-solid heat transfer in pneumatic conveying

NASA Astrophysics Data System (ADS)

Smajstrla, Kody Wayne

A one-dimensional ODE model reduced from a two-fluid model of a higher dimensional order is developed to study dilute, two-phase (air and solid particles) flows with heat transfer in a horizontal pneumatic conveying pipe. Instead of using constant air properties (e.g., density, viscosity, thermal conductivity) evaluated at the initial flow temperature and pressure, this model uses an iteration approach to couple the air properties with flow pressure and temperature. Multiple studies comparing the use of constant or variable air density, viscosity, and thermal conductivity are conducted to study the impact of the changing properties to system performance. The results show that the fully constant property calculation will overestimate the results of the fully variable calculation by 11.4%, while the constant density with variable viscosity and thermal conductivity calculation resulted in an 8.7% overestimation, the constant viscosity with variable density and thermal conductivity overestimated by 2.7%, and the constant thermal conductivity with variable density and viscosity calculation resulted in a 1.2% underestimation. These results demonstrate that gas properties varying with gas temperature can have a significant impact on a conveying system and that the varying density accounts for the majority of that impact. The accuracy of the model is also validated by comparing the simulation results to the experimental values found in the literature.

Three-dimensional cell culture models for investigating human viruses.

PubMed

He, Bing; Chen, Guomin; Zeng, Yi

2016-10-01

Three-dimensional (3D) culture models are physiologically relevant, as they provide reproducible results, experimental flexibility and can be adapted for high-throughput experiments. Moreover, these models bridge the gap between traditional two-dimensional (2D) monolayer cultures and animal models. 3D culture systems have significantly advanced basic cell science and tissue engineering, especially in the fields of cell biology and physiology, stem cell research, regenerative medicine, cancer research, drug discovery, and gene and protein expression studies. In addition, 3D models can provide unique insight into bacteriology, virology, parasitology and host-pathogen interactions. This review summarizes and analyzes recent progress in human virological research with 3D cell culture models. We discuss viral growth, replication, proliferation, infection, virus-host interactions and antiviral drugs in 3D culture models.

Modelling Parsing Constraints with High-Dimensional Context Space.

ERIC Educational Resources Information Center

Burgess, Curt; Lund, Kevin

1997-01-01

Presents a model of high-dimensional context space, the Hyperspace Analogue to Language (HAL), with a series of simulations modelling human empirical results. Proposes that HAL's context space can be used to provide a basic categorization of semantic and grammatical concepts; model certain aspects of morphological ambiguity in verbs; and provide…

Three Dimensional Modeling of Breaking

DTIC Science & Technology

2005-09-30

Three Dimensional Modeling of Breaking Robert A. Dalrymple Dept of Civil Engineering The Johns Hopkins University 3400 North Charles Street...University,Dept of Civil Engineering,3400 North Charles Street,Baltimore,MD,21218 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING...R.A. Dalrymple, A.J.C. Crespo, and D. Cerquiero, "Uso de la Tecnica SPH para el Estudio de la Interaccion entre Olas y Estructuras," Ingenieria del

Micropolar continuum modelling of bi-dimensional tetrachiral lattices

PubMed Central

Chen, Y.; Liu, X. N.; Hu, G. K.; Sun, Q. P.; Zheng, Q. S.

2014-01-01

The in-plane behaviour of tetrachiral lattices should be characterized by bi-dimensional orthotropic material owing to the existence of two orthogonal axes of rotational symmetry. Moreover, the constitutive model must also represent the chirality inherent in the lattices. To this end, a bi-dimensional orthotropic chiral micropolar model is developed based on the theory of irreducible orthogonal tensor decomposition. The obtained constitutive tensors display a hierarchy structure depending on the symmetry of the underlying microstructure. Eight additional material constants, in addition to five for the hemitropic case, are introduced to characterize the anisotropy under Z2 invariance. The developed continuum model is then applied to a tetrachiral lattice, and the material constants of the continuum model are analytically derived by a homogenization process. By comparing with numerical simulations for the discrete lattice, it is found that the proposed continuum model can correctly characterize the static and wave properties of the tetrachiral lattice. PMID:24808754

One-dimensional nonlinear elastodynamic models and their local conservation laws with applications to biological membranes.

PubMed

Cheviakov, A F; Ganghoffer, J-F

2016-05-01

The framework of incompressible nonlinear hyperelasticity and viscoelasticity is applied to the derivation of one-dimensional models of nonlinear wave propagation in fiber-reinforced elastic solids. Equivalence transformations are used to simplify the resulting wave equations and to reduce the number of parameters. Local conservation laws and global conserved quantities of the models are systematically computed and discussed, along with other related mathematical properties. Sample numerical solutions are presented. The models considered in the paper are appropriate for the mathematical description of certain aspects of the behavior of biological membranes and similar structures. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comparison of two- and three-dimensional stochastic models of regional solute movement

USGS Publications Warehouse

Shapiro, A.M.; Cvetkovic, V.D.

1990-01-01

Recent models of solute movement in porous media that are based on a stochastic description of the porous medium properties have been dedicated primarily to a three-dimensional interpretation of solute movement. In many practical problems, however, it is more convenient and consistent with measuring techniques to consider flow and solute transport as an areal, two-dimensional phenomenon. The physics of solute movement, however, is dependent on the three-dimensional heterogeneity in the formation. A comparison of two- and three-dimensional stochastic interpretations of solute movement in a porous medium having a statistically isotropic hydraulic conductivity field is investigated. To provide an equitable comparison between the two- and three-dimensional analyses, the stochastic properties of the transmissivity are defined in terms of the stochastic properties of the hydraulic conductivity. The variance of the transmissivity is shown to be significantly reduced in comparison to that of the hydraulic conductivity, and the transmissivity is spatially correlated over larger distances. These factors influence the two-dimensional interpretations of solute movement by underestimating the longitudinal and transverse growth of the solute plume in comparison to its description as a three-dimensional phenomenon. Although this analysis is based on small perturbation approximations and the special case of a statistically isotropic hydraulic conductivity field, it casts doubt on the use of a stochastic interpretation of the transmissivity in describing regional scale movement. However, by assuming the transmissivity to be the vertical integration of the hydraulic conductivity field at a given position, the stochastic properties of the hydraulic conductivity can be estimated from the stochastic properties of the transmissivity and applied to obtain a more accurate interpretation of solute movement. ?? 1990 Kluwer Academic Publishers.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

PubMed

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

Integration of Local Observations into the One Dimensional Fog Model PAFOG

NASA Astrophysics Data System (ADS)

Thoma, Christina; Schneider, Werner; Masbou, Matthieu; Bott, Andreas

2012-05-01

The numerical prediction of fog requires a very high vertical resolution of the atmosphere. Owing to a prohibitive computational effort of high resolution three dimensional models, operational fog forecast is usually done by means of one dimensional fog models. An important condition for a successful fog forecast with one dimensional models consists of the proper integration of observational data into the numerical simulations. The goal of the present study is to introduce new methods for the consideration of these data in the one dimensional radiation fog model PAFOG. First, it will be shown how PAFOG may be initialized with observed visibilities. Second, a nudging scheme will be presented for the inclusion of measured temperature and humidity profiles in the PAFOG simulations. The new features of PAFOG have been tested by comparing the model results with observations of the German Meteorological Service. A case study will be presented that reveals the importance of including local observations in the model calculations. Numerical results obtained with the modified PAFOG model show a distinct improvement of fog forecasts regarding the times of fog formation, dissipation as well as the vertical extent of the investigated fog events. However, model results also reveal that a further improvement of PAFOG might be possible if several empirical model parameters are optimized. This tuning can only be realized by comprehensive comparisons of model simulations with corresponding fog observations.

Current status of one- and two-dimensional numerical models: Successes and limitations

NASA Technical Reports Server (NTRS)

Schwartz, R. J.; Gray, J. L.; Lundstrom, M. S.

1985-01-01

The capabilities of one and two-dimensional numerical solar cell modeling programs (SCAP1D and SCAP2D) are described. The occasions when a two-dimensional model is required are discussed. The application of the models to design, analysis, and prediction are presented along with a discussion of problem areas for solar cell modeling.

Development and Validation of a 3-Dimensional CFB Furnace Model

NASA Astrophysics Data System (ADS)

Vepsäläinen, Arl; Myöhänen, Karl; Hyppäneni, Timo; Leino, Timo; Tourunen, Antti

At Foster Wheeler, a three-dimensional CFB furnace model is essential part of knowledge development of CFB furnace process regarding solid mixing, combustion, emission formation and heat transfer. Results of laboratory and pilot scale phenomenon research are utilized in development of sub-models. Analyses of field-test results in industrial-scale CFB boilers including furnace profile measurements are simultaneously carried out with development of 3-dimensional process modeling, which provides a chain of knowledge that is utilized as feedback for phenomenon research. Knowledge gathered by model validation studies and up-to-date parameter databases are utilized in performance prediction and design development of CFB boiler furnaces. This paper reports recent development steps related to modeling of combustion and formation of char and volatiles of various fuel types in CFB conditions. Also a new model for predicting the formation of nitrogen oxides is presented. Validation of mixing and combustion parameters for solids and gases are based on test balances at several large-scale CFB boilers combusting coal, peat and bio-fuels. Field-tests including lateral and vertical furnace profile measurements and characterization of solid materials provides a window for characterization of fuel specific mixing and combustion behavior in CFB furnace at different loads and operation conditions. Measured horizontal gas profiles are projection of balance between fuel mixing and reactions at lower part of furnace and are used together with both lateral temperature profiles at bed and upper parts of furnace for determination of solid mixing and combustion model parameters. Modeling of char and volatile based formation of NO profiles is followed by analysis of oxidizing and reducing regions formed due lower furnace design and mixing characteristics of fuel and combustion airs effecting to formation ofNO furnace profile by reduction and volatile-nitrogen reactions. This paper presents

Development and validation of a two-dimensional fast-response flood estimation model

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

Judi, David R; Mcpherson, Timothy N; Burian, Steven J

2009-01-01

A finite difference formulation of the shallow water equations using an upwind differencing method was developed maintaining computational efficiency and accuracy such that it can be used as a fast-response flood estimation tool. The model was validated using both laboratory controlled experiments and an actual dam breach. Through the laboratory experiments, the model was shown to give good estimations of depth and velocity when compared to the measured data, as well as when compared to a more complex two-dimensional model. Additionally, the model was compared to high water mark data obtained from the failure of the Taum Sauk dam. Themore » simulated inundation extent agreed well with the observed extent, with the most notable differences resulting from the inability to model sediment transport. The results of these validation studies complex two-dimensional model. Additionally, the model was compared to high water mark data obtained from the failure of the Taum Sauk dam. The simulated inundation extent agreed well with the observed extent, with the most notable differences resulting from the inability to model sediment transport. The results of these validation studies show that a relatively numerical scheme used to solve the complete shallow water equations can be used to accurately estimate flood inundation. Future work will focus on further reducing the computation time needed to provide flood inundation estimates for fast-response analyses. This will be accomplished through the efficient use of multi-core, multi-processor computers coupled with an efficient domain-tracking algorithm, as well as an understanding of the impacts of grid resolution on model results.« less

Two-Dimensional Porous Electrode Model for Capacitive Deionization

DOE PAGES

Hemmatifar, Ali; Stadermann, Michael; Santiago, Juan G.

2015-10-28

Here, ion transport in porous conductive materials is of great importance in a variety of electrochemical systems including batteries and supercapacitors. We here analyze the coupling of flow and charge transport and charge capacitance in capacitive deionization (CDI). In CDI, a pair of porous carbon electrodes is employed to electrostatically retain and remove ionic species from aqueous solutions. We here develop and solve a novel unsteady two-dimensional model for capturing the ion adsorption/desorption dynamics in a flow-between CDI system. We use this model to study the complex, nonlinear coupling between electromigration, diffusion, and advection of ions. We also fabricated amore » laboratory-scale CDI cell which we use to measure the near-equilibrium, cumulative adsorbed salt, and electric charge as a function of applied external voltage. We use these integral measures to validate and calibrate this model. We further present a detailed computational study of the spatiotemporal adsorption/desorption dynamics under constant voltage and constant flow conditions. We show results for low (20 mM KCl) and relatively high (200 mM KCl) inlet ion concentrations and identify effects of ion starvation on desalination. We show that in both cases electromigrative transport eventually becomes negligible and diffusive ion transport reduces the desalination rate.« less

A two-dimensional kinematic dynamo model of the ionospheric magnetic field at Venus

NASA Technical Reports Server (NTRS)

Cravens, T. E.; Wu, D.; Shinagawa, H.

1990-01-01

The results of a high-resolution, two-dimensional, time dependent, kinematic dynamo model of the ionospheric magnetic field of Venus are presented. Various one-dimensional models are considered and the two-dimensional model is then detailed. In this model, the two-dimensional magnetic induction equation, the magnetic diffusion-convection equation, is numerically solved using specified plasma velocities. Origins of the vertical velocity profile and of the horizontal velocities are discussed. It is argued that the basic features of the vertical magnetic field profile remain unaltered by horizontal flow effects and also that horizontal plasma flow can strongly affect the magnetic field for altitudes above 300 km.

Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

DOE PAGES

Carlberg, Kevin T.

2014-11-05

Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operationsmore » or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.« less

Reduced-Dimensionality Semiclassical Transition State Theory: Application to Hydrogen Atom Abstraction and Exchange Reactions of Hydrocarbons.

PubMed

Greene, Samuel M; Shan, Xiao; Clary, David C

2015-12-17

Quantum mechanical methods for calculating rate constants are often intractable for reactions involving many atoms. Semiclassical transition state theory (SCTST) offers computational advantages over these methods but nonetheless scales exponentially with the number of degrees of freedom (DOFs) of the system. Here we present a method with more favorable scaling, reduced-dimensionality SCTST (RD SCTST), that treats only a subset of DOFs of the system explicitly. We apply it to three H abstraction and exchange reactions for which two-dimensional potential energy surfaces (PESs) have previously been constructed and evaluated using RD quantum scattering calculations. We differentiated these PESs to calculate harmonic frequencies and anharmonic constants, which were then used to calculate cumulative reaction probabilities and rate constants by RD SCTST. This method yielded rate constants in good agreement with quantum scattering results. Notably, it performed well for a heavy-light-heavy reaction, even though it does not explicitly account for corner-cutting effects. Recent extensions to SCTST that improve its treatment of deep tunneling were also evaluated within the reduced-dimensionality framework. The success of RD SCTST in this study suggests its potential applicability to larger systems.

A new approach for assimilation of two-dimensional radar precipitation in a high resolution NWP model

NASA Astrophysics Data System (ADS)

Korsholm, Ulrik; Petersen, Claus; Hansen Sass, Bent; Woetman, Niels; Getreuer Jensen, David; Olsen, Bjarke Tobias; GIll, Rasphal; Vedel, Henrik

2014-05-01

The DMI nowcasting system has been running in a pre-operational state for the past year. The system consists of hourly simulations with the High Resolution Limited Area weather model combined with surface and three-dimensional variational assimilation at each restart and nudging of satellite cloud products and radar precipitation. Nudging of a two-dimensional radar reflectivity CAPPI product is achieved using a new method where low level horizontal divergence is nudged towards pseudo observations. Pseudo observations are calculated based on an assumed relation between divergence and precipitation rate and the strength of the nudging is proportional to the offset between observed and modelled precipitation leading to increased moisture convergence below cloud base if there is an under-production of precipitation relative to the CAPPI product. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values. In this talk results will be discussed based on calculation of the fractions skill score in cases with heavy precipitation over Denmark. Furthermore, results from simulations combining reflectivity nudging and extrapolation of reflectivity will be shown. Results indicate that the new method leads to fast adjustment of the dynamical state of the model to facilitate precipitation release when the model precipitation intensity is too low. Removal of precipitation is also shown to be of importance and strong improvements were found in the position of the precipitation systems. Bias is reduced for low and extreme precipitation rates.

A one-dimensional model of subsurface hillslope flow

Treesearch

Jason C. Fisher

1997-01-01

Abstract - A one-dimensional, finite difference model of saturated subsurface flow within a hillslope was developed. The model uses rainfall, elevation data, a hydraulic conductivity, and a storage coefficient to predict the saturated thickness in time and space. The model was tested against piezometric data collected in a swale located in the headwaters of the North...

Analysis, simulation and visualization of 1D tapping via reduced dynamical models

NASA Astrophysics Data System (ADS)

Blackmore, Denis; Rosato, Anthony; Tricoche, Xavier; Urban, Kevin; Zou, Luo

2014-04-01

A low-dimensional center-of-mass dynamical model is devised as a simplified means of approximately predicting some important aspects of the motion of a vertical column comprised of a large number of particles subjected to gravity and periodic vertical tapping. This model is investigated first as a continuous dynamical system using analytical, simulation and visualization techniques. Then, by employing an approach analogous to that used to approximate the dynamics of a bouncing ball on an oscillating flat plate, it is modeled as a discrete dynamical system and analyzed to determine bifurcations and transitions to chaotic motion along with other properties. The predictions of the analysis are then compared-primarily qualitatively-with visualization and simulation results of the reduced continuous model, and ultimately with simulations of the complete system dynamics.

Three dimensional geometric modeling of processing-tomatoes

USDA-ARS?s Scientific Manuscript database

Characterizing tomato geometries with different shapes and sizes would facilitate the design of tomato processing equipments and promote computer-based engineering simulations. This research sought to develop a three-dimensional geometric model that can describe the morphological attributes of proce...

Applications of three-dimensional modeling in electromagnetic exploration

NASA Astrophysics Data System (ADS)

Pellerin, Louise Donna

Numerical modeling is used in geophysical exploration to understand physical mechanisms of a geophysical method, compare different exploration techniques, and interpret field data. Exploring the physics of a geophysical response enhances the geophysicist's insight, resulting in better survey design and interpretation. Comparing exploration methods numerically can eliminate the use of a technique that cannot resolve the exploration target. Interpreting field data to determine the structure of the earth is the ultimate goal of the exploration geophysicist. Applications of three-dimensional (3-D) electromagnetic (EM) modeling in mining, geothermal and environmental exploration demonstrate the importance of numerical modeling as a geophysical tool. Detection of a confined, conductive target with a vertical electric source (VES) can be an effective technique if properly used. The vertical magnetic field response is due solely to multi-dimensional structures, and current channeling is the dominant mechanism. A VES is deployed in a bore hole, hence the orientation of the hole is critical to the response. A deviation of more than a degree from the vertical can result in a host response that overwhelms the target response. Only the in-phase response at low frequencies can be corrected to a purely vertical response. The geothermal system studied consists of a near-surface clay cap and a deep reservoir. The magnetotelluric (MT), controlled-source audio magnetotelluric (CSAMT), long-offset time-domain electromagnetic (LOTEM) and central-loop transient electromagnetic (TEM) methods are appraised for their ability to detect the reservoir and delineate the cap. The reservoir anomaly is supported by boundary charges and therefore is detectable only with deep sounding electric field measurement MT and LOTEM. The cap is easily delineated with all techniques. For interpretation I developed an approximate 3-D inversion that refines a 1-D interpretation by removing lateral distortions

Equation of State of the Two-Dimensional Hubbard Model

NASA Astrophysics Data System (ADS)

Cocchi, Eugenio; Miller, Luke A.; Drewes, Jan H.; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael

2016-04-01

The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0 ≲U /t ≲20 and temperatures, down to kBT /t =0.63 (2 ) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.

SABRINA: an interactive three-dimensional geometry-mnodeling program for MCNP

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

West, J.T. III

SABRINA is a fully interactive three-dimensional geometry-modeling program for MCNP, a Los Alamos Monte Carlo code for neutron and photon transport. In SABRINA, a user constructs either body geometry or surface geometry models and debugs spatial descriptions for the resulting objects. This enhanced capability significantly reduces effort in constructing and debugging complicated three-dimensional geometry models for Monte Carlo analysis. 2 refs., 33 figs.

A one-dimensional with three-dimensional velocity space hybrid-PIC model of the discharge plasma in a Hall thruster

NASA Astrophysics Data System (ADS)

Shashkov, Andrey; Lovtsov, Alexander; Tomilin, Dmitry

2017-04-01

According to present knowledge, countless numerical simulations of the discharge plasma in Hall thrusters were conducted. However, on the one hand, adequate two-dimensional (2D) models require a lot of time to carry out numerical research of the breathing mode oscillations or the discharge structure. On the other hand, existing one-dimensional (1D) models are usually too simplistic and do not take into consideration such important phenomena as neutral-wall collisions, magnetic field induced by Hall current and double, secondary, and stepwise ionizations together. In this paper a one-dimensional with three-dimensional velocity space (1D3V) hybrid-PIC model is presented. The model is able to incorporate all the phenomena mentioned above. A new method of neutral-wall collisions simulation in described space was developed and validated. Simulation results obtained for KM-88 and KM-60 thrusters are in a good agreement with experimental data. The Bohm collision coefficient was the same for both thrusters. Neutral-wall collisions, doubly charged ions, and induced magnetic field were proved to stabilize the breathing mode oscillations in a Hall thruster under some circumstances.

Rigorous Model Reduction for a Damped-Forced Nonlinear Beam Model: An Infinite-Dimensional Analysis

NASA Astrophysics Data System (ADS)

Kogelbauer, Florian; Haller, George

2018-06-01

We use invariant manifold results on Banach spaces to conclude the existence of spectral submanifolds (SSMs) in a class of nonlinear, externally forced beam oscillations. SSMs are the smoothest nonlinear extensions of spectral subspaces of the linearized beam equation. Reduction in the governing PDE to SSMs provides an explicit low-dimensional model which captures the correct asymptotics of the full, infinite-dimensional dynamics. Our approach is general enough to admit extensions to other types of continuum vibrations. The model-reduction procedure we employ also gives guidelines for a mathematically self-consistent modeling of damping in PDEs describing structural vibrations.

THREE-DIMENSIONAL NAPL FATE AND TRANSPORT MODEL

EPA Science Inventory

We have added several new and significant capabilities to UTCHEM to make it into a general-purpose NAPL simulator. The simulator is now capable of modeling transient and steady-state three-dimensional flow and mass transport in the groundwater (saturated) and vadose (unsaturated...

Lift, Drag, and Pressure Distribution Effects Accompanying Drag-Reducing Polymer Injection on Two-Dimensional Hydrofoil

DTIC Science & Technology

1975-10-01

associated with drag- reducing polymers since Wu’s discovery of pump effects in 1969(16) Some of the research has involved tests on propellers finite span...AD-A022 433 LIFT, DRAG, AND PRESSURE DISTRIBUTION EFFECTS ACCOMPANYING DRAG- REDUCING POLYMER INJECTION ON TWO-DIMENSIONAL HYDROFOIL Daniel H. Fruman...et al Hydronautits, IncorponAted "Prepared f’or: Office of Naval Research October 197’ .!. S.IIE KA NTO CmaY - t 093103 A pprove!- for p~thic relpsa

A two-dimensional particle-in-cell model of a dusty plasma

NASA Technical Reports Server (NTRS)

Young, B.; Cravens, T. E.; Armstrong, T. P.; Friauf, R. J.

1994-01-01

Dusty plasmas are present in comets, in the ring systems of the outer planets, and in the interstellar medium. A two-dimensional particle-in-cell (PIC) model of a dusty plasma is presented in this paper. The PIC code is best suited for modeling the plasma-dust interaction for large grains, with diameters of the order of a centimeter. We have modeled the charging process for an individual dust grain and the associated potential pattern in the surrounding plasma. We have also considered the case of a large number of grains in a plasma, with intergrain separations of the order of the Debye length, and have shown that the plasma becomes depleted and the charge on a dust grain is reduced, as other workers in this field have predicted (cf. C. K. Goertz, 1989). We examine the electron and ion distribution functions in the vicinity of a charged grain and demonstrate that the ions near a grain have clearly been accelerated by the electrostatic potential.

DOA estimation of noncircular signals for coprime linear array via locally reduced-dimensional Capon

NASA Astrophysics Data System (ADS)

Zhai, Hui; Zhang, Xiaofei; Zheng, Wang

2018-05-01

We investigate the issue of direction of arrival (DOA) estimation of noncircular signals for coprime linear array (CLA). The noncircular property enhances the degree of freedom and improves angle estimation performance, but it leads to a more complex angle ambiguity problem. To eliminate ambiguity, we theoretically prove that the actual DOAs of noncircular signals can be uniquely estimated by finding the coincide results from the two decomposed subarrays based on the coprimeness. We propose a locally reduced-dimensional (RD) Capon algorithm for DOA estimation of noncircular signals for CLA. The RD processing is used in the proposed algorithm to avoid two dimensional (2D) spectral peak search, and coprimeness is employed to avoid the global spectral peak search. The proposed algorithm requires one-dimensional locally spectral peak search, and it has very low computational complexity. Furthermore, the proposed algorithm needs no prior knowledge of the number of sources. We also derive the Crámer-Rao bound of DOA estimation of noncircular signals in CLA. Numerical simulation results demonstrate the effectiveness and superiority of the algorithm.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

PubMed Central

Xing, W. W.; Triantafyllidis, V.

2017-01-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

Modeling of thin-walled structures interacting with acoustic media as constrained two-dimensional continua

NASA Astrophysics Data System (ADS)

Rabinskiy, L. N.; Zhavoronok, S. I.

2018-04-01

The transient interaction of acoustic media and elastic shells is considered on the basis of the transition function approach. The three-dimensional hyperbolic initial boundary-value problem is reduced to a two-dimensional problem of shell theory with integral operators approximating the acoustic medium effect on the shell dynamics. The kernels of these integral operators are determined by the elementary solution of the problem of acoustic waves diffraction at a rigid obstacle with the same boundary shape as the wetted shell surface. The closed-form elementary solution for arbitrary convex obstacles can be obtained at the initial interaction stages on the background of the so-called “thin layer hypothesis”. Thus, the shell–wave interaction model defined by integro-differential dynamic equations with analytically determined kernels of integral operators becomes hence two-dimensional but nonlocal in time. On the other hand, the initial interaction stage results in localized dynamic loadings and consequently in complex strain and stress states that require higher-order shell theories. Here the modified theory of I.N.Vekua–A.A.Amosov-type is formulated in terms of analytical continuum dynamics. The shell model is constructed on a two-dimensional manifold within a set of field variables, Lagrangian density, and constraint equations following from the boundary conditions “shifted” from the shell faces to its base surface. Such an approach allows one to construct consistent low-order shell models within a unified formal hierarchy. The equations of the N th-order shell theory are singularly perturbed and contain second-order partial derivatives with respect to time and surface coordinates whereas the numerical integration of systems of first-order equations is more efficient. Such systems can be obtained as Hamilton–de Donder–Weyl-type equations for the Lagrangian dynamical system. The Hamiltonian formulation of the elementary N th-order shell theory is

Statistical mechanics of shell models for two-dimensional turbulence

NASA Astrophysics Data System (ADS)

Aurell, E.; Boffetta, G.; Crisanti, A.; Frick, P.; Paladin, G.; Vulpiani, A.

1994-12-01

We study shell models that conserve the analogs of energy and enstrophy and hence are designed to mimic fluid turbulence in two-dimensions (2D). The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach to two-dimensional ideal hydrodynamics of Onsager [Nuovo Cimento Suppl. 6, 279 (1949)], Hopf [J. Rat. Mech. Anal. 1, 87 (1952)], and Lee [Q. Appl. Math. 10, 69 (1952)]. In the presence of forcing and dissipation we observe a forward flux of enstrophy and a backward flux of energy. These fluxes can be understood as mean diffusive drifts from a source to two sinks in a system which is close to local equilibrium with Lagrange multipliers (``shell temperatures'') changing slowly with scale. This is clear evidence that the simplest shell models are not adequate to reproduce the main features of two-dimensional turbulence. The dimensional predictions on the power spectra from a supposed forward cascade of enstrophy and from one branch of the formal statistical equilibrium coincide in these shell models in contrast to the corresponding predictions for the Navier-Stokes and Euler equations in 2D. This coincidence has previously led to the mistaken conclusion that shell models exhibit a forward cascade of enstrophy. We also study the dynamical properties of the models and the growth of perturbations.

A semi-implicit finite difference model for three-dimensional tidal circulation,

USGS Publications Warehouse

Casulli, V.; Cheng, R.T.

1992-01-01

A semi-implicit finite difference formulation for the numerical solution of three-dimensional tidal circulation is presented. The governing equations are the three-dimensional Reynolds equations in which the pressure is assumed to be hydrostatic. A minimal degree of implicitness has been introduced in the finite difference formula so that in the absence of horizontal viscosity the resulting algorithm is unconditionally stable at a minimal computational cost. When only one vertical layer is specified this method reduces, as a particular case, to a semi-implicit scheme for the solutions of the corresponding two-dimensional shallow water equations. The resulting two- and three-dimensional algorithm is fast, accurate and mass conservative. This formulation includes the simulation of flooding and drying of tidal flats, and is fully vectorizable for an efficient implementation on modern vector computers.

Modeling self-excited combustion instabilities using a combination of two- and three-dimensional simulations

NASA Astrophysics Data System (ADS)

Harvazinski, Matthew Evan

observed in experiments. All fuel rich simulations used a single step global reaction for the chemical kinetic model. A fuel lean operating condition is also studied and has a lower level of instability. The two-dimensional results are unable to provide good agreement with experimental results unless a more expensive four-step chemical kinetic model is used. The three-dimensional simulation is able to predict the harmonic behavior but fails to capture the amplitude of the instability observed in the companion experiment, instead predicting lower amplitude oscillations. A detailed analysis of the three-dimensional results on a single cycle shows that the periodic heat release commonly associated with combustion instability can be interpreted to be a result of the time lag between the instant the fuel is injected and when it is burned. The time lag is due to two mechanisms. First, methane present near the backstep can become trapped and transported inside shed vortices to the point of combustion. The second aspect of the time lag arises due to the interaction of the fuel with upstream-running pressure waves. As the wave moves past the injection point the flow is temporarily disrupted, reducing the fuel flow into the combustor. A comparison between the fuel lean and fuel rich cases shows several differences. Whereas both cases can produce instability, the fuel-rich case is measurably more unstable. Using the tools developed differences in the location of the damping, and driving regions are evident. By moving the peak driving area upstream of the damping region the level of instability is lower in the fuel lean case. The location of the mean heat release is also important; locating the mean heat release adjacent to the vortex impingement point a higher level of instability is observed for the fuel rich case. This research shows that DES instability modeling has the ability to be a valuable tool in the study of combustion instability. The lower grid size requirement makes the

Data-Adaptive Bias-Reduced Doubly Robust Estimation.

PubMed

Vermeulen, Karel; Vansteelandt, Stijn

2016-05-01

Doubly robust estimators have now been proposed for a variety of target parameters in the causal inference and missing data literature. These consistently estimate the parameter of interest under a semiparametric model when one of two nuisance working models is correctly specified, regardless of which. The recently proposed bias-reduced doubly robust estimation procedure aims to partially retain this robustness in more realistic settings where both working models are misspecified. These so-called bias-reduced doubly robust estimators make use of special (finite-dimensional) nuisance parameter estimators that are designed to locally minimize the squared asymptotic bias of the doubly robust estimator in certain directions of these finite-dimensional nuisance parameters under misspecification of both parametric working models. In this article, we extend this idea to incorporate the use of data-adaptive estimators (infinite-dimensional nuisance parameters), by exploiting the bias reduction estimation principle in the direction of only one nuisance parameter. We additionally provide an asymptotic linearity theorem which gives the influence function of the proposed doubly robust estimator under correct specification of a parametric nuisance working model for the missingness mechanism/propensity score but a possibly misspecified (finite- or infinite-dimensional) outcome working model. Simulation studies confirm the desirable finite-sample performance of the proposed estimators relative to a variety of other doubly robust estimators.

Diffusion in higher dimensional SYK model with complex fermions

NASA Astrophysics Data System (ADS)

Cai, Wenhe; Ge, Xian-Hui; Yang, Guo-Hong

2018-01-01

We construct a new higher dimensional SYK model with complex fermions on bipartite lattices. As an extension of the original zero-dimensional SYK model, we focus on the one-dimension case, and similar Hamiltonian can be obtained in higher dimensions. This model has a conserved U(1) fermion number Q and a conjugate chemical potential μ. We evaluate the thermal and charge diffusion constants via large q expansion at low temperature limit. The results show that the diffusivity depends on the ratio of free Majorana fermions to Majorana fermions with SYK interactions. The transport properties and the butterfly velocity are accordingly calculated at low temperature. The specific heat and the thermal conductivity are proportional to the temperature. The electrical resistivity also has a linear temperature dependence term.

Modeling the defrost process in complex geometries - Part 1: Development of a one-dimensional defrost model

NASA Astrophysics Data System (ADS)

van Buren, Simon; Hertle, Ellen; Figueiredo, Patric; Kneer, Reinhold; Rohlfs, Wilko

2017-11-01

Frost formation is a common, often undesired phenomenon in heat exchanges such as air coolers. Thus, air coolers have to be defrosted periodically, causing significant energy consumption. For the design and optimization, prediction of defrosting by a CFD tool is desired. This paper presents a one-dimensional transient model approach suitable to be used as a zero-dimensional wall-function in CFD for modeling the defrost process at the fin and tube interfaces. In accordance to previous work a multi stage defrost model is introduced (e.g. [1, 2]). In the first instance the multi stage model is implemented and validated using MATLAB. The defrost process of a one-dimensional frost segment is investigated. Fixed boundary conditions are provided at the frost interfaces. The simulation results verify the plausibility of the designed model. The evaluation of the simulated defrost process shows the expected convergent behavior of the three-stage sequence.

Discrete-to-continuum modelling of weakly interacting incommensurate two-dimensional lattices.

PubMed

Español, Malena I; Golovaty, Dmitry; Wilber, J Patrick

2018-01-01

In this paper, we derive a continuum variational model for a two-dimensional deformable lattice of atoms interacting with a two-dimensional rigid lattice. The starting point is a discrete atomistic model for the two lattices which are assumed to have slightly different lattice parameters and, possibly, a small relative rotation. This is a prototypical example of a three-dimensional system consisting of a graphene sheet suspended over a substrate. We use a discrete-to-continuum procedure to obtain the continuum model which recovers both qualitatively and quantitatively the behaviour observed in the corresponding discrete model. The continuum model predicts that the deformable lattice develops a network of domain walls characterized by large shearing, stretching and bending deformation that accommodates the misalignment and/or mismatch between the deformable and rigid lattices. Two integer-valued parameters, which can be identified with the components of a Burgers vector, describe the mismatch between the lattices and determine the geometry and the details of the deformation associated with the domain walls.

Model of a Negatively Curved Two-Dimensional Space.

ERIC Educational Resources Information Center

Eckroth, Charles A.

1995-01-01

Describes the construction of models of two-dimensional surfaces with negative curvature that are used to illustrate differences in the triangle sum rule for the various Big Bang Theories of the universe. (JRH)

Fast prediction and evaluation of eccentric inspirals using reduced-order models

NASA Astrophysics Data System (ADS)

Barta, Dániel; Vasúth, Mátyás

2018-06-01

A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.

Chaotic oscillator containing memcapacitor and meminductor and its dimensionality reduction analysis.

PubMed

Yuan, Fang; Wang, Guangyi; Wang, Xiaowei

2017-03-01

In this paper, smooth curve models of meminductor and memcapacitor are designed, which are generalized from a memristor. Based on these models, a new five-dimensional chaotic oscillator that contains a meminductor and memcapacitor is proposed. By dimensionality reducing, this five-dimensional system can be transformed into a three-dimensional system. The main work of this paper is to give the comparisons between the five-dimensional system and its dimensionality reduction model. To investigate dynamics behaviors of the two systems, equilibrium points and stabilities are analyzed. And the bifurcation diagrams and Lyapunov exponent spectrums are used to explore their properties. In addition, digital signal processing technologies are used to realize this chaotic oscillator, and chaotic sequences are generated by the experimental device, which can be used in encryption applications.

Physically-Based Reduced Order Modelling of a Uni-Axial Polysilicon MEMS Accelerometer

PubMed Central

Ghisi, Aldo; Mariani, Stefano; Corigliano, Alberto; Zerbini, Sarah

2012-01-01

In this paper, the mechanical response of a commercial off-the-shelf, uni-axial polysilicon MEMS accelerometer subject to drops is numerically investigated. To speed up the calculations, a simplified physically-based (beams and plate), two degrees of freedom model of the movable parts of the sensor is adopted. The capability and the accuracy of the model are assessed against three-dimensional finite element simulations, and against outcomes of experiments on instrumented samples. It is shown that the reduced order model provides accurate outcomes as for the system dynamics. To also get rather accurate results in terms of stress fields within regions that are prone to fail upon high-g shocks, a correction factor is proposed by accounting for the local stress amplification induced by re-entrant corners. PMID:23202031

Three-dimensional ``Mercedes-Benz'' model for water

NASA Astrophysics Data System (ADS)

Dias, Cristiano L.; Ala-Nissila, Tapio; Grant, Martin; Karttunen, Mikko

2009-08-01

In this paper we introduce a three-dimensional version of the Mercedes-Benz model to describe water molecules. In this model van der Waals interactions and hydrogen bonds are given explicitly through a Lennard-Jones potential and a Gaussian orientation-dependent terms, respectively. At low temperature the model freezes forming Ice-I and it reproduces the main peaks of the experimental radial distribution function of water. In addition to these structural properties, the model also captures the thermodynamical anomalies of water: The anomalous density profile, the negative thermal expansivity, the large heat capacity, and the minimum in the isothermal compressibility.

Three-dimensional "Mercedes-Benz" model for water.

PubMed

Dias, Cristiano L; Ala-Nissila, Tapio; Grant, Martin; Karttunen, Mikko

2009-08-07

In this paper we introduce a three-dimensional version of the Mercedes-Benz model to describe water molecules. In this model van der Waals interactions and hydrogen bonds are given explicitly through a Lennard-Jones potential and a Gaussian orientation-dependent terms, respectively. At low temperature the model freezes forming Ice-I and it reproduces the main peaks of the experimental radial distribution function of water. In addition to these structural properties, the model also captures the thermodynamical anomalies of water: The anomalous density profile, the negative thermal expansivity, the large heat capacity, and the minimum in the isothermal compressibility.

An algebraic turbulence model for three-dimensional viscous flows

NASA Technical Reports Server (NTRS)

Chima, R. V.; Giel, P. W.; Boyle, R. J.

1993-01-01

An algebraic turbulence model is proposed for use with three-dimensional Navier-Stokes analyses. It incorporates features of both the Baldwin-Lomax and Cebeci-Smith models. The Baldwin-Lomax model uses the maximum of a function f(y) to determine length and velocity scales. An analysis of the Baldwin-Lomax model shows that f(y) can have a spurious maximum close to the wall, causing numerical problems and non-physical results. The proposed model uses integral relations to determine delta(*) u(sub e) and delta used in the Cebeci-Smith mode. It eliminates a constant in the Baldwin-Lomax model and determines the two remaining constants by comparison to the Cebeci-Smith formulation. Pressure gradient effects, a new wake model, and the implementation of these features in a three-dimensional Navier-Stokes code are also described. Results are shown for a flat plate boundary layer, an annular turbine cascade, and endwall heat transfer in a linear turbine cascade. The heat transfer results agree well with experimental data which shows large variations in endwall Stanton number contours with Reynolds number.

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

NASA Astrophysics Data System (ADS)

Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

2018-04-01

In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

The Long Decay Model of One-Dimensional Projectile Motion

ERIC Educational Resources Information Center

Lattery, Mark Joseph

2008-01-01

This article introduces a research study on student model formation and development in introductory mechanics. As a point of entry, I present a detailed analysis of the Long Decay Model of one-dimensional projectile motion. This model has been articulated by Galileo ("in De Motu") and by contemporary students. Implications for instruction are…

Reduced-order modeling for hyperthermia control.

PubMed

Potocki, J K; Tharp, H S

1992-12-01

This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS). These thermal state space models are reduced using the balanced realization technique, and an order reduction criterion is tabulated. Results show that a drastic reduction in model dimension can be achieved using the balanced realization. The reduced-order model is then used to design a reduced-order optimal servomechanism controller for a two-scan input, two thermocouple output tissue model. In addition, a full-order optimal servomechanism controller is designed for comparison and validation purposes. These two controllers are applied to a variety of perturbed tissue thermal models to test the robust nature of the reduced-order controller. A comparison of the two controllers validates the use of open-loop balanced reduced-order models in the design of MIMO hyperthermia controllers.

Analytical model for three-dimensional Mercedes-Benz water molecules.

PubMed

Urbic, T

2012-06-01

We developed a statistical model which describes the thermal and volumetric properties of water-like molecules. A molecule is presented as a three-dimensional sphere with four hydrogen-bonding arms. Each water molecule interacts with its neighboring waters through a van der Waals interaction and an orientation-dependent hydrogen-bonding interaction. This model, which is largely analytical, is a variant of a model developed before for a two-dimensional Mercedes-Benz model of water. We explored properties such as molar volume, density, heat capacity, thermal expansion coefficient, and isothermal compressibility as a function of temperature and pressure. We found that the volumetric and thermal properties follow the same trends with temperature as in real water and are in good general agreement with Monte Carlo simulations, including the density anomaly, the minimum in the isothermal compressibility, and the decreased number of hydrogen bonds upon increasing the temperature.

Analytical model for three-dimensional Mercedes-Benz water molecules

NASA Astrophysics Data System (ADS)

Urbic, T.

2012-06-01

We developed a statistical model which describes the thermal and volumetric properties of water-like molecules. A molecule is presented as a three-dimensional sphere with four hydrogen-bonding arms. Each water molecule interacts with its neighboring waters through a van der Waals interaction and an orientation-dependent hydrogen-bonding interaction. This model, which is largely analytical, is a variant of a model developed before for a two-dimensional Mercedes-Benz model of water. We explored properties such as molar volume, density, heat capacity, thermal expansion coefficient, and isothermal compressibility as a function of temperature and pressure. We found that the volumetric and thermal properties follow the same trends with temperature as in real water and are in good general agreement with Monte Carlo simulations, including the density anomaly, the minimum in the isothermal compressibility, and the decreased number of hydrogen bonds upon increasing the temperature.

Analytical model for three-dimensional Mercedes-Benz water molecules

PubMed Central

Urbic, T.

2013-01-01

We developed a statistical model which describes the thermal and volumetric properties of water-like molecules. A molecule is presented as a three-dimensional sphere with four hydrogen-bonding arms. Each water molecule interacts with its neighboring waters through a van der Waals interaction and an orientation-dependent hydrogen-bonding interaction. This model, which is largely analytical, is a variant of a model developed before for a two-dimensional Mercedes-Benz model of water. We explored properties such as molar volume, density, heat capacity, thermal expansion coefficient, and isothermal compressibility as a function of temperature and pressure. We found that the volumetric and thermal properties follow the same trends with temperature as in real water and are in good general agreement with Monte Carlo simulations, including the density anomaly, the minimum in the isothermal compressibility, and the decreased number of hydrogen bonds upon increasing the temperature. PMID:23005100

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

NASA Astrophysics Data System (ADS)

Khawli, Toufik Al; Gebhardt, Sascha; Eppelt, Urs; Hermanns, Torsten; Kuhlen, Torsten; Schulz, Wolfgang

2016-06-01

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

Predicting RNA folding thermodynamics with a reduced chain representation model

PubMed Central

CAO, SONG; CHEN, SHI-JIE

2005-01-01

Based on the virtual bond representation for the nucleotide backbone, we develop a reduced conformational model for RNA. We use the experimentally measured atomic coordinates to model the helices and use the self-avoiding walks in a diamond lattice to model the loop conformations. The atomic coordinates of the helices and the lattice representation for the loops are matched at the loop–helix junction, where steric viability is accounted for. Unlike the previous simplified lattice-based models, the present virtual bond model can account for the atomic details of realistic three-dimensional RNA structures. Based on the model, we develop a statistical mechanical theory for RNA folding energy landscapes and folding thermodynamics. Tests against experiments show that the theory can give much more improved predictions for the native structures, the thermal denaturation curves, and the equilibrium folding/unfolding pathways than the previous models. The application of the model to the P5abc region of Tetrahymena group I ribozyme reveals the misfolded intermediates as well as the native-like intermediates in the equilibrium folding process. Moreover, based on the free energy landscape analysis for each and every loop mutation, the model predicts five lethal mutations that can completely alter the free energy landscape and the folding stability of the molecule. PMID:16251382

Three dimensional global modeling of atmospheric CO2

NASA Technical Reports Server (NTRS)

Fung, I.; Hansen, J.; Rind, D.

1983-01-01

A model was developed to study the prospects of extracting information on carbon dioxide sources and sinks from observed CO2 variations. The approach uses a three dimensional global transport model, based on winds from a 3-D general circulation model (GCM), to advect CO2 noninteractively, i.e., as a tracer, with specified sources and sinks of CO2 at the surface. The 3-D model employed is identified and biosphere, ocean and fossil fuel sources and sinks are discussed. Some preliminary model results are presented.

Modeling the pyrolysis study of non-charring polymers under reduced pressure environments

NASA Astrophysics Data System (ADS)

Zong, Ruowen; Kang, Ruxue; Hu, Yanghui; Zhi, Youran

2018-04-01

In order to study the pyrolysis of non-charring polymers under reduced pressure environments, a series of experiments based on black acrylonitrile butadiene styrene (ABS) was conducted in a reduced pressure chamber under different external heat fluxes. The temperatures of the top surface and the bottom of the sample and the mass loss during the whole process were measured in real time. A one-dimensional numerical model was developed to predict the top surface and the bottom surface temperatures of ABS during the pyrolysis at different reduced pressures and external heat fluxes, and the model was validated by the experimental data. The results of the study indicate that the profiles of the top surface and the bottom surface temperatures are different at different pressures and heat fluxes. The temperature and the mass loss rate of the sample under a lower heat flux decreased significantly as the pressure was increased. However, under a higher heat flux, the temperature and the mass loss rate showed little sensitivity to the pressure. The simulated results fitted the experimental results better at the higher heat flux than at the lower heat flux.

Two dimensional analytical model for a reconfigurable field effect transistor

NASA Astrophysics Data System (ADS)

Ranjith, R.; Jayachandran, Remya; Suja, K. J.; Komaragiri, Rama S.

2018-02-01

This paper presents two-dimensional potential and current models for a reconfigurable field effect transistor (RFET). Two potential models which describe subthreshold and above-threshold channel potentials are developed by solving two-dimensional (2D) Poisson's equation. In the first potential model, 2D Poisson's equation is solved by considering constant/zero charge density in the channel region of the device to get the subthreshold potential characteristics. In the second model, accumulation charge density is considered to get above-threshold potential characteristics of the device. The proposed models are applicable for the device having lightly doped or intrinsic channel. While obtaining the mathematical model, whole body area is divided into two regions: gated region and un-gated region. The analytical models are compared with technology computer-aided design (TCAD) simulation results and are in complete agreement for different lengths of the gated regions as well as at various supply voltage levels.

A stabilized MFE reduced-order extrapolation model based on POD for the 2D unsteady conduction-convection problem.

PubMed

Xia, Hong; Luo, Zhendong

2017-01-01

In this study, we devote ourselves to establishing a stabilized mixed finite element (MFE) reduced-order extrapolation (SMFEROE) model holding seldom unknowns for the two-dimensional (2D) unsteady conduction-convection problem via the proper orthogonal decomposition (POD) technique, analyzing the existence and uniqueness and the stability as well as the convergence of the SMFEROE solutions and validating the correctness and dependability of the SMFEROE model by means of numerical simulations.

Trans-dimensional inversion of microtremor array dispersion data with hierarchical autoregressive error models

NASA Astrophysics Data System (ADS)

Dettmer, Jan; Molnar, Sheri; Steininger, Gavin; Dosso, Stan E.; Cassidy, John F.

2012-02-01

This paper applies a general trans-dimensional Bayesian inference methodology and hierarchical autoregressive data-error models to the inversion of microtremor array dispersion data for shear wave velocity (vs) structure. This approach accounts for the limited knowledge of the optimal earth model parametrization (e.g. the number of layers in the vs profile) and of the data-error statistics in the resulting vs parameter uncertainty estimates. The assumed earth model parametrization influences estimates of parameter values and uncertainties due to different parametrizations leading to different ranges of data predictions. The support of the data for a particular model is often non-unique and several parametrizations may be supported. A trans-dimensional formulation accounts for this non-uniqueness by including a model-indexing parameter as an unknown so that groups of models (identified by the indexing parameter) are considered in the results. The earth model is parametrized in terms of a partition model with interfaces given over a depth-range of interest. In this work, the number of interfaces (layers) in the partition model represents the trans-dimensional model indexing. In addition, serial data-error correlations are addressed by augmenting the geophysical forward model with a hierarchical autoregressive error model that can account for a wide range of error processes with a small number of parameters. Hence, the limited knowledge about the true statistical distribution of data errors is also accounted for in the earth model parameter estimates, resulting in more realistic uncertainties and parameter values. Hierarchical autoregressive error models do not rely on point estimates of the model vector to estimate data-error statistics, and have no requirement for computing the inverse or determinant of a data-error covariance matrix. This approach is particularly useful for trans-dimensional inverse problems, as point estimates may not be representative of the

Model's sparse representation based on reduced mixed GMsFE basis methods

NASA Astrophysics Data System (ADS)

Jiang, Lijian; Li, Qiuqi

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random porous

Model's sparse representation based on reduced mixed GMsFE basis methods

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a largemore » number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in random

Three-Dimensional Computer-Assisted Two-Layer Elastic Models of the Face.

PubMed

Ueda, Koichi; Shigemura, Yuka; Otsuki, Yuki; Fuse, Asuka; Mitsuno, Daisuke

2017-11-01

To make three-dimensional computer-assisted elastic models for the face, we decided on five requirements: (1) an elastic texture like skin and subcutaneous tissue; (2) the ability to take pen marking for incisions; (3) the ability to be cut with a surgical knife; (4) the ability to keep stitches in place for a long time; and (5) a layered structure. After testing many elastic solvents, we have made realistic three-dimensional computer-assisted two-layer elastic models of the face and cleft lip from the computed tomographic and magnetic resonance imaging stereolithographic data. The surface layer is made of polyurethane and the inner layer is silicone. Using this elastic model, we taught residents and young doctors how to make several typical local flaps and to perform cheiloplasty. They could experience realistic simulated surgery and understand three-dimensional movement of the flaps.

Two-dimensional habitat modeling in the Yellowstone/Upper Missouri River system

USGS Publications Warehouse

Waddle, T. J.; Bovee, K.D.; Bowen, Z.H.

1997-01-01

This study is being conducted to provide the aquatic biology component of a decision support system being developed by the U.S. Bureau of Reclamation. In an attempt to capture the habitat needs of Great Plains fish communities we are looking beyond previous habitat modeling methods. Traditional habitat modeling approaches have relied on one-dimensional hydraulic models and lumped compositional habitat metrics to describe aquatic habitat. A broader range of habitat descriptors is available when both composition and configuration of habitats is considered. Habitat metrics that consider both composition and configuration can be adapted from terrestrial biology. These metrics are most conveniently accessed with spatially explicit descriptors of the physical variables driving habitat composition. Two-dimensional hydrodynamic models have advanced to the point that they may provide the spatially explicit description of physical parameters needed to address this problem. This paper reports progress to date on applying two-dimensional hydraulic and habitat models on the Yellowstone and Missouri Rivers and uses examples from the Yellowstone River to illustrate the configurational metrics as a new tool for assessing riverine habitats.

Exactly solvable model of the two-dimensional electrical double layer.

PubMed

Samaj, L; Bajnok, Z

2005-12-01

We consider equilibrium statistical mechanics of a simplified model for the ideal conductor electrode in an interface contact with a classical semi-infinite electrolyte, modeled by the two-dimensional Coulomb gas of pointlike unit charges in the stability-against-collapse regime of reduced inverse temperatures 0< or = beta < 2. If there is a potential difference between the bulk interior of the electrolyte and the grounded electrode, the electrolyte region close to the electrode (known as the electrical double layer) carries some nonzero surface charge density. The model is mappable onto an integrable semi-infinite sine-Gordon theory with Dirichlet boundary conditions. The exact form-factor and boundary state information gained from the mapping provide asymptotic forms of the charge and number density profiles of electrolyte particles at large distances from the interface. The result for the asymptotic behavior of the induced electric potential, related to the charge density via the Poisson equation, confirms the validity of the concept of renormalized charge and the corresponding saturation hypothesis. It is documented on the nonperturbative result for the asymptotic density profile at a strictly nonzero beta that the Debye-Hückel beta-->0 limit is a delicate issue.

Role of a computer-generated three-dimensional laryngeal model in anatomy teaching for advanced learners.

PubMed

Tan, S; Hu, A; Wilson, T; Ladak, H; Haase, P; Fung, K

2012-04-01

(1) To investigate the efficacy of a computer-generated three-dimensional laryngeal model for laryngeal anatomy teaching; (2) to explore the relationship between students' spatial ability and acquisition of anatomical knowledge; and (3) to assess participants' opinion of the computerised model. Forty junior doctors were randomised to undertake laryngeal anatomy study supplemented by either a three-dimensional computer model or two-dimensional images. Outcome measurements comprised a laryngeal anatomy test, the modified Vandenberg and Kuse mental rotation test, and an opinion survey. Mean scores ± standard deviations for the anatomy test were 15.7 ± 2.0 for the 'three dimensions' group and 15.5 ± 2.3 for the 'standard' group (p = 0.7222). Pearson's correlation between the rotation test scores and the scores for the spatial ability questions in the anatomy test was 0.4791 (p = 0.086, n = 29). Opinion survey answers revealed significant differences in respondents' perceptions of the clarity and 'user friendliness' of, and their preferences for, the three-dimensional model as regards anatomical study. The three-dimensional computer model was equivalent to standard two-dimensional images, for the purpose of laryngeal anatomy teaching. There was no association between students' spatial ability and functional anatomy learning. However, students preferred to use the three-dimensional model.

Strategies to reduce the complexity of hydrologic data assimilation for high-dimensional models

NASA Astrophysics Data System (ADS)

Hernandez, F.; Liang, X.

2017-12-01

Probabilistic forecasts in the geosciences offer invaluable information by allowing to estimate the uncertainty of predicted conditions (including threats like floods and droughts). However, while forecast systems based on modern data assimilation algorithms are capable of producing multi-variate probability distributions of future conditions, the computational resources required to fully characterize the dependencies between the model's state variables render their applicability impractical for high-resolution cases. This occurs because of the quadratic space complexity of storing the covariance matrices that encode these dependencies and the cubic time complexity of performing inference operations with them. In this work we introduce two complementary strategies to reduce the size of the covariance matrices that are at the heart of Bayesian assimilation methods—like some variants of (ensemble) Kalman filters and of particle filters—and variational methods. The first strategy involves the optimized grouping of state variables by clustering individual cells of the model into "super-cells." A dynamic fuzzy clustering approach is used to take into account the states (e.g., soil moisture) and forcings (e.g., precipitation) of each cell at each time step. The second strategy consists in finding a compressed representation of the covariance matrix that still encodes the most relevant information but that can be more efficiently stored and processed. A learning and a belief-propagation inference algorithm are developed to take advantage of this modified low-rank representation. The two proposed strategies are incorporated into OPTIMISTS, a state-of-the-art hybrid Bayesian/variational data assimilation algorithm, and comparative streamflow forecasting tests are performed using two watersheds modeled with the Distributed Hydrology Soil Vegetation Model (DHSVM). Contrasts are made between the efficiency gains and forecast accuracy losses of each strategy used in

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

NASA Astrophysics Data System (ADS)

Pevný, Tomáš; Filler, Tomáš; Bas, Patrick

This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to "preserve" the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.

Three-dimensional ray-tracing model for the study of advanced refractive errors in keratoconus.

PubMed

Schedin, Staffan; Hallberg, Per; Behndig, Anders

2016-01-20

We propose a numerical three-dimensional (3D) ray-tracing model for the analysis of advanced corneal refractive errors. The 3D modeling was based on measured corneal elevation data by means of Scheimpflug photography. A mathematical description of the measured corneal surfaces from a keratoconus (KC) patient was used for the 3D ray tracing, based on Snell's law of refraction. A model of a commercial intraocular lens (IOL) was included in the analysis. By modifying the posterior IOL surface, it was shown that the imaging quality could be significantly improved. The RMS values were reduced by approximately 50% close to the retina, both for on- and off-axis geometries. The 3D ray-tracing model can constitute a basis for simulation of customized IOLs that are able to correct the advanced, irregular refractive errors in KC.

Selected topics in high energy physics: Flavon, neutrino and extra-dimensional models

NASA Astrophysics Data System (ADS)

Dorsner, Ilja

There is already significant evidence, both experimental and theoretical, that the Standard Model of elementary particle physics is just another effective physical theory. Thus, it is crucial (a) to anticipate the experiments in search for signatures of the physics beyond the Standard Model, and (b) whether some theoretically preferred structure can reproduce the low-energy signature of the Standard Model. This work pursues these two directions by investigating various extensions of the Standard Model. One of them is a simple flavon model that accommodates the observed hierarchy of the charged fermion masses and mixings. We show that flavor changing and CP violating signatures of this model are equally near the present experimental limits. We find that, for a significant range of parameters, mu-e conversion can be the most sensitive place to look for such signatures. We then propose two variants of an SO(10) model in five-dimensional framework. The first variant demonstrates that one can embed a four-dimensional flipped SU(5) model into a five-dimensional SO(10) model. This allows one to maintain the advantages of flipped SU(5) while avoiding its well-known drawbacks. The second variant shows that exact unification of the gauge couplings is possible even in the higher dimensional setting. This unification yields low-energy values of the gauge couplings that are in a perfect agreement with experimental values. We show that the corrections to the usual four-dimensional running, due to the Kaluza-Klein towers of states, can be unambiguously and systematically evaluated. We also consider the various main types of models of neutrino masses and mixings from the point of view of how naturally they give the large mixing angle MSW solution to the solar neutrino problem. Special attention is given to one particular "lopsided" SU(5) model, which is then analyzed in a completely statistical manner. We suggest that this sort of statistical analysis should be applicable to other

On numerical modeling of one-dimensional geothermal histories

USGS Publications Warehouse

Haugerud, R.A.

1989-01-01

Numerical models of one-dimensional geothermal histories are one way of understanding the relations between tectonics and transient thermal structure in the crust. Such models can be powerful tools for interpreting geochronologic and thermobarometric data. A flexible program to calculate these models on a microcomputer is available and examples of its use are presented. Potential problems with this approach include the simplifying assumptions that are made, limitations of the numerical techniques, and the neglect of convective heat transfer. ?? 1989.

An Overview of Software for Conducting Dimensionality Assessment in Multidimensional Models

ERIC Educational Resources Information Center

Svetina, Dubravka; Levy, Roy

2012-01-01

An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…

The innovative concept of three-dimensional hybrid receptor modeling

NASA Astrophysics Data System (ADS)

Stojić, A.; Stanišić Stojić, S.

2017-09-01

The aim of this study was to improve the current understanding of air pollution transport processes at regional and long-range scale. For this purpose, three-dimensional (3D) potential source contribution function and concentration weighted trajectory models, as well as new hybrid receptor model, concentration weighted boundary layer (CWBL), which uses a two-dimensional grid and a planetary boundary layer height as a frame of reference, are presented. The refined approach to hybrid receptor modeling has two advantages. At first, it considers whether each trajectory endpoint meets the inclusion criteria based on planetary boundary layer height, which is expected to provide a more realistic representation of the spatial distribution of emission sources and pollutant transport pathways. Secondly, it includes pollutant time series preprocessing to make hybrid receptor models more applicable for suburban and urban locations. The 3D hybrid receptor models presented herein are designed to identify altitude distribution of potential sources, whereas CWBL can be used for analyzing the vertical distribution of pollutant concentrations along the transport pathway.

3-dimensional orthodontics visualization system with dental study models and orthopantomograms

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ong, S. H.; Foong, K. W. C.; Dhar, T.

2005-04-01

The aim of this study is to develop a system that provides 3-dimensional visualization of orthodontic treatments. Dental plaster models and corresponding orthopantomogram (dental panoramic tomogram) are first digitized and fed into the system. A semi-auto segmentation technique is applied to the plaster models to detect the dental arches, tooth interstices and gum margins, which are used to extract individual crown models. 3-dimensional representation of roots, generated by deforming generic tooth models with orthopantomogram using radial basis functions, is attached to corresponding crowns to enable visualization of complete teeth. An optional algorithm to close the gaps between deformed roots and actual crowns by using multi-quadratic radial basis functions is also presented, which is capable of generating smooth mesh representation of complete 3-dimensional teeth. User interface is carefully designed to achieve a flexible system with as much user friendliness as possible. Manual calibration and correction is possible throughout the data processing steps to compensate occasional misbehaviors of automatic procedures. By allowing the users to move and re-arrange individual teeth (with their roots) on a full dentition, this orthodontic visualization system provides an easy and accurate way of simulation and planning of orthodontic treatment. Its capability of presenting 3-dimensional root information with only study models and orthopantomogram is especially useful for patients who do not undergo CT scanning, which is not a routine procedure in most orthodontic cases.

Dimensional modeling: beyond data processing constraints.

PubMed

Bunardzic, A

1995-01-01

in the relational databases normalized to their 3rd normal form. Object-oriented approach insists on the importance of the common sense component of the data processing activities. But, particularly interesting, is the approach that advocates the necessity of 'flattening' the structure of the business models as we know them today. This discipline is called Dimensional Modeling and it enables users to form multidimensional views of the relevant facts which are stored in a 'flat' (non-structured), easy-to-comprehend and easy-to-access database. When using dimensional modeling, we relax many of the axioms inherent in a relational model. We focus on the knowledge of the relevant facts which are reflecting the business operations and are the real basis for the decision support and business analysis. At the core of the dimensional modeling are fact tables that contain the non-discrete, additive data. To determine the level of aggregation of these facts, we use granularity tables that specify the resolution, or the level/detail, that the user is allowed to entertain. The third component is dimension tables that embody the knowledge of the constraints to be used to form the views.

A THREE-DIMENSIONAL BABCOCK-LEIGHTON SOLAR DYNAMO MODEL

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

Miesch, Mark S.; Dikpati, Mausumi, E-mail: miesch@ucar.edu

We present a three-dimensional (3D) kinematic solar dynamo model in which poloidal field is generated by the emergence and dispersal of tilted sunspot pairs (more generally bipolar magnetic regions, or BMRs). The axisymmetric component of this model functions similarly to previous 2.5 dimensional (2.5D, axisymmetric) Babcock-Leighton (BL) dynamo models that employ a double-ring prescription for poloidal field generation but we generalize this prescription into a 3D flux emergence algorithm that places BMRs on the surface in response to the dynamo-generated toroidal field. In this way, the model can be regarded as a unification of BL dynamo models (2.5D in radius/latitude)more » and surface flux transport models (2.5D in latitude/longitude) into a more self-consistent framework that builds on the successes of each while capturing the full 3D structure of the evolving magnetic field. The model reproduces some basic features of the solar cycle including an 11 yr periodicity, equatorward migration of toroidal flux in the deep convection zone, and poleward propagation of poloidal flux at the surface. The poleward-propagating surface flux originates as trailing flux in BMRs, migrates poleward in multiple non-axisymmetric streams (made axisymmetric by differential rotation and turbulent diffusion), and eventually reverses the polar field, thus sustaining the dynamo. In this Letter we briefly describe the model, initial results, and future plans.« less

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Implicit Three-Dimensional Geo-Modelling Based on HRBF Surface

NASA Astrophysics Data System (ADS)

Gou, J.; Zhou, W.; Wu, L.

2016-10-01

Three-dimensional (3D) geological models are important representations of the results of regional geological surveys. However, the process of constructing 3D geological models from two-dimensional (2D) geological elements remains difficult and time-consuming. This paper proposes a method of migrating from 2D elements to 3D models. First, the geological interfaces were constructed using the Hermite Radial Basis Function (HRBF) to interpolate the boundaries and attitude data. Then, the subsurface geological bodies were extracted from the spatial map area using the Boolean method between the HRBF surface and the fundamental body. Finally, the top surfaces of the geological bodies were constructed by coupling the geological boundaries to digital elevation models. Based on this workflow, a prototype system was developed, and typical geological structures (e.g., folds, faults, and strata) were simulated. Geological modes were constructed through this workflow based on realistic regional geological survey data. For extended applications in 3D modelling of other kinds of geo-objects, mining ore body models and urban geotechnical engineering stratum models were constructed by this method from drill-hole data. The model construction process was rapid, and the resulting models accorded with the constraints of the original data.

Two-dimensional Anderson-Hubbard model in the DMFT + {Sigma} approximation

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

Kuchinskii, E. Z., E-mail: kuchinsk@iep.uran.ru; Kuleeva, N. A.; Nekrasov, I. A.

The density of states, the dynamic (optical) conductivity, and the phase diagram of the paramagnetic two-dimensional Anderson-Hubbard model with strong correlations and disorder are analyzed within the generalized dynamical mean field theory (DMFT + {Sigma} approximation). Strong correlations are accounted by the DMFT, while disorder is taken into account via the appropriate generalization of the self-consistent theory of localization. We consider the two-dimensional system with the rectangular 'bare' density of states (DOS). The DMFT effective single-impurity problem is solved by numerical renormalization group (NRG). The 'correlated metal,' Mott insulator, and correlated Anderson insulator phases are identified from the evolution ofmore » the density of states, optical conductivity, and localization length, demonstrating both Mott-Hubbard and Anderson metal-insulator transitions in two-dimensional systems of finite size, allowing us to construct the complete zero-temperature phase diagram of the paramagnetic Anderson-Hubbard model. The localization length in our approximation is practically independent of the strength of Hubbard correlations. But the divergence of the localization length in a finite-size two-dimensional system at small disorder signifies the existence of an effective Anderson transition.« less

Two-dimensional Mathematical Model of Oil-bearing Materials in Extrusion-type Transportation over Rectangular Screw Core

NASA Astrophysics Data System (ADS)

Gukasyan, A. V.; Koshevoy, E. P.; Kosachev, V. S.

2018-05-01

A comparative analysis of alternative models for plastic flow in extrusive transportation of oil-bearing materials was conducted; the research was directed at determining the function describing the screw core throughput capacity of the press (extruder). Transition from a one-dimensional model to a two-dimensional model significantly improves the mathematical model and allows using two-dimensional rheological models determining the throughput of the screw core.

Verification and transfer of thermal pollution model. Volume 5: Verification of 2-dimensional numerical model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Nwadike, E. V.

1982-01-01

The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorate (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter. These models allow computation of time dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions.

Two-dimensional plasmons in the random impedance network model of disordered thin film nanocomposites

NASA Astrophysics Data System (ADS)

Olekhno, N. A.; Beltukov, Y. M.

2018-05-01

Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric nanocomposites. Two-dimensional networks are applied when considering thin films despite the fact that such networks correspond to the two-dimensional electrodynamics [Clerc et al., J. Phys. A 29, 4781 (1996), 10.1088/0305-4470/29/16/006]. In the present work, we propose a model of two-dimensional systems with the three-dimensional Coulomb interaction and show that this model is equivalent to the planar network with long-range capacitive links between distant sites. In the case of a metallic film, we obtain the well-known dispersion of two-dimensional plasmons ω ∝√{k } . We study the evolution of resonances with a decrease in the metal filling factor within the framework of the proposed model. In the subcritical region with the metal filling p lower than the percolation threshold pc, we observe a gap with Lifshitz tails in the spectral density of states (DOS). In the supercritical region p >pc , the DOS demonstrates a crossover between plane-wave two-dimensional plasmons and resonances of finite clusters.

Verification and transfer of thermal pollution model. Volume 6: User's manual for 1-dimensional numerical model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Nwadike, E. V.

1982-01-01

The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter.

Two-Dimensional Versus Three-Dimensional Conceptualization in Astronomy Education

NASA Astrophysics Data System (ADS)

Reynolds, Michael David

Numerous science conceptual issues are naturally three-dimensional. Classroom presentations are often two -dimensional or at best multidimensional. Several astronomy topics are of this nature, e. g. mechanics of the phases of the moon. Textbooks present this three-dimensional topic in two-dimensions; such is often the case in the classroom. This study was conducted to examine conceptions exhibited by pairs of like-sex 11th grade standard physics students as they modeled the lunar phases. Student pairs, 13 male and 13 female, were randomly selected and assigned. Pairing comes closer to classroom emulation, minimizes needs for direct probes, and pair discussion is more likely to display variety and depth. Four hypotheses were addressed: (1) Participants who model three-dimensionally will more likely achieve a higher explanation score. (2) Students who experienced more earth or physical science exposure will more likely model three-dimensionally. (3) Pairs that exhibit a strong science or mathematics preference will more likely model three-dimensionally. (4) Males will model in three dimensions more than females. Students provided background information, including science course exposure and subject preference. Each pair laid out a 16-card set representing two complete lunar phase changes. The pair was asked to explain why the phases occur. Materials were provided for use, including disks, spheres, paper and pen, and flashlight. Activities were videotaped for later evaluation. Statistics of choice was a correlation determination between course preference and model type and ANOVA for the other hypotheses. It was determined that pairs who modeled three -dimensionally achieved a higher score on their phases mechanics explanation at p <.05 level. Pairs with earth science or physical science exposure, those who prefer science or mathematics, and male participants were not more likely to model three-dimensionally. Possible reasons for lack of significance was small sample

Fermion masses and mixing in general warped extra dimensional models

NASA Astrophysics Data System (ADS)

Frank, Mariana; Hamzaoui, Cherif; Pourtolami, Nima; Toharia, Manuel

2015-06-01

We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave functions to small flavor breaking effects yield hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the five-dimensional neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is more successful in generalized warped scenarios where the metric background solution is different than five-dimensional anti-de Sitter (AdS5 ). We study these features in two simple frameworks, flavor complimentarity and flavor democracy, which provide specific predictions and correlations between quarks and leptons, testable as more precise data in the neutrino sector becomes available.

An introduction to three-dimensional climate modeling

NASA Technical Reports Server (NTRS)

Washington, W. M.; Parkinson, C. L.

1986-01-01

The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

PubMed Central

Xiao, Fu; Yang, Yang; Wang, Ruchuan; Sun, Lijuan

2014-01-01

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes' radius is deduced; also the minimum number of sensor nodes to maintain network area's full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme. PMID:25045747

Scientific data interpolation with low dimensional manifold model

NASA Astrophysics Data System (ADS)

Zhu, Wei; Wang, Bao; Barnard, Richard; Hauck, Cory D.; Jenko, Frank; Osher, Stanley

2018-01-01

We propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace-Beltrami operator in the Euler-Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on data compression and interpolation from both regular and irregular samplings.

Four-dimensional world-wide atmospheric models (surface to 25 km altitude)

NASA Technical Reports Server (NTRS)

Spiegler, D. B.; Fowler, M. G.

1972-01-01

Four-dimensional atmospheric models previously developed for use as input to atmospheric attenuation models are evaluated to determine where refinements are warranted. The models are refined where appropriate. A computerized technique is developed that has the unique capability of extracting mean monthly and daily variance profiles of moisture, temperature, density and pressure at 1 km intervals to the height of 25 km for any location on the globe. This capability could be very useful to planners of remote sensing of earth resources missions in that the profiles may be used as input to the attenuation models that predict the expected degradation of the sensor data. Recommendations are given for procedures to use the four-dimensional models in computer mission simulations and for the approach to combining the information provided by the 4-D models with that given by the global models.

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

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

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less

Biomechanical factors associated with mandibular cantilevers: analysis with three-dimensional finite element models.

PubMed

Gonda, Tomoya; Yasuda, Daiisa; Ikebe, Kazunori; Maeda, Yoshinobu

2014-01-01

Although the risks of using a cantilever to treat missing teeth have been described, the mechanisms remain unclear. This study aimed to reveal these mechanisms from a biomechanical perspective. The effects of various implant sites, number of implants, and superstructural connections on stress distribution in the marginal bone were analyzed with three-dimensional finite element models based on mandibular computed tomography data. Forces from the masseter, temporalis, and internal pterygoid were applied as vectors. Two three-dimensional finite element models were created with the edentulous mandible showing severe and relatively modest residual ridge resorption. Cantilevers of the premolar and molar were simulated in the superstructures in the models. The following conditions were also included as factors in the models to investigate changes: poor bone quality, shortened dental arch, posterior occlusion, lateral occlusion, double force of the masseter, and short implant. Multiple linear regression analysis with a forced-entry method was performed with stress values as the objective variable and the factors as the explanatory variable. When bone mass was high, stress around the implant caused by differences in implantation sites was reduced. When bone mass was low, the presence of a cantilever was a possible risk factor. The stress around the implant increased significantly if bone quality was poor or if increased force (eg, bruxism) was applied. The addition of a cantilever to the superstructure increased stress around implants. When large muscle forces were applied to a superstructure with cantilevers or if bone quality was poor, stress around the implants increased.

Evaluation of Floodplain Modifications to Reduce the Effect of Floods Using a Two-Dimensional Hydrodynamic Model of the Flint River at Albany, Georgia

USGS Publications Warehouse

Musser, Jonathan W.

2008-01-01

Potential flow characteristics of future flooding along a 4.8-mile reach of the Flint River in Albany, Georgia, were simulated using recent digital-elevation-model data and the U.S. Geological Survey finite-element surface-water modeling system for two-dimensional flow in the horizontal plane (FESWMS-2DH). The model was run at four water-surface altitudes at the Flint River at Albany streamgage (02352500): 181.5-foot (ft) altitude with a flow of 61,100 cubic feet per second (ft3/s), 184.5-ft altitude with a flow of 75,400 ft3/s, 187.5-ft altitude with a flow of 91,700 ft3/s, and 192.5-ft altitude with a flow of 123,000 ft3/s. The model was run to measure changes in inundated areas and water-surface altitudes for eight scenarios of possible modifications to the 4.8-mile reach on the Flint River. The eight scenarios include removing a human-made peninsula located downstream from Oglethorpe Boulevard, increasing the opening under the Oakridge Drive bridge, adding culverts to the east Oakridge Drive bridge approach, adding culverts to the east and west Oakridge Drive bridge approaches, adding an overflow across the oxbow north of Oakridge Drive, making the overflow into a channel, removing the Oakridge Drive bridge, and adding a combination of an oxbow overflow and culverts on both Oakridge Drive bridge approaches. The modeled inundation and water-surface altitude changes were mapped for use in evaluating the river modifications. The most effective scenario at reducing inundated area was the combination scenario. At the 187.5-ft altitude, the inundated area decreased from 4.24 square miles to 4.00 square miles. The remove-peninsula scenario was the least effective with a reduction in inundated area of less than 0.01 square miles. In all scenarios, the inundated area reduction increased with water-surface altitude, peaking at the 187.5-ft altitude. The inundated area reduction then decreased at the gage altitude of 192.5 ft.

[Research progress of three-dimensional digital model for repair and reconstruction of knee joint].

PubMed

Tong, Lu; Li, Yanlin; Hu, Meng

2013-01-01

To review recent advance in the application and research of three-dimensional digital knee model. The recent original articles about three-dimensional digital knee model were extensively reviewed and analyzed. The digital three-dimensional knee model can simulate the knee complex anatomical structure very well. Based on this, there are some developments of new software and techniques, and good clinical results are achieved. With the development of computer techniques and software, the knee repair and reconstruction procedure has been improved, the operation will be more simple and its accuracy will be further improved.

HR Del REMNANT ANATOMY USING TWO-DIMENSIONAL SPECTRAL DATA AND THREE-DIMENSIONAL PHOTOIONIZATION SHELL MODELS

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

Moraes, Manoel; Diaz, Marcos

2009-12-15

The HR Del nova remnant was observed with the IFU-GMOS at Gemini North. The spatially resolved spectral data cube was used in the kinematic, morphological, and abundance analysis of the ejecta. The line maps show a very clumpy shell with two main symmetric structures. The first one is the outer part of the shell seen in H{alpha}, which forms two rings projected in the sky plane. These ring structures correspond to a closed hourglass shape, first proposed by Harman and O'Brien. The equatorial emission enhancement is caused by the superimposed hourglass structures in the line of sight. The second structuremore » seen only in the [O III] and [N II] maps is located along the polar directions inside the hourglass structure. Abundance gradients between the polar caps and equatorial region were not found. However, the outer part of the shell seems to be less abundant in oxygen and nitrogen than the inner regions. Detailed 2.5-dimensional photoionization modeling of the three-dimensional shell was performed using the mass distribution inferred from the observations and the presence of mass clumps. The resulting model grids are used to constrain the physical properties of the shell as well as the central ionizing source. A sequence of three-dimensional clumpy models including a disk-shaped ionization source is able to reproduce the ionization gradients between polar and equatorial regions of the shell. Differences between shell axial ratios in different lines can also be explained by aspherical illumination. A total shell mass of 9 x 10{sup -4} M {sub sun} is derived from these models. We estimate that 50%-70% of the shell mass is contained in neutral clumps with density contrast up to a factor of 30.« less

Special Holonomy and Two-Dimensional Supersymmetric Sigma-Models

NASA Astrophysics Data System (ADS)

Stojevic, Vid

2006-11-01

Two-dimensional sigma-models describing superstrings propagating on manifolds of special holonomy are characterized by symmetries related to covariantly constant forms that these manifolds hold, which are generally non-linear and close in a field dependent sense. The thesis explores various aspects of the special holonomy symmetries.

Use of upscaled elevation and surface roughness data in two-dimensional surface water models

USGS Publications Warehouse

Hughes, J.D.; Decker, J.D.; Langevin, C.D.

2011-01-01

In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton–Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.

Kaluza-Klein cosmology from five-dimensional Lovelock-Cartan theory

NASA Astrophysics Data System (ADS)

Castillo-Felisola, Oscar; Corral, Cristóbal; del Pino, Simón; Ramírez, Francisca

2016-12-01

We study the Kaluza-Klein dimensional reduction of the Lovelock-Cartan theory in five-dimensional spacetime, with a compact dimension of S1 topology. We find cosmological solutions of the Friedmann-Robertson-Walker class in the reduced spacetime. The torsion and the fields arising from the dimensional reduction induce a nonvanishing energy-momentum tensor in four dimensions. We find solutions describing expanding, contracting, and bouncing universes. The model shows a dynamical compactification of the extra dimension in some regions of the parameter space.

Programmers manual for a one-dimensional Lagrangian transport model

USGS Publications Warehouse

Schoellhamer, D.H.; Jobson, H.E.

1986-01-01

A one-dimensional Lagrangian transport model for simulating water-quality constituents such as temperature, dissolved oxygen , and suspended sediment in rivers is presented in this Programmers Manual. Lagrangian transport modeling techniques, the model 's subroutines, and the user-written decay-coefficient subroutine are discussed in detail. Appendices list the program codes. The Programmers Manual is intended for the model user who needs to modify code either to adapt the model to a particular need or to use reaction kinetics not provided with the model. (Author 's abstract)

Gravitational lensing by a smoothly variable three-dimensional mass distribution

NASA Technical Reports Server (NTRS)

Lee, Man Hoi; Paczynski, Bohdan

1990-01-01

A smooth three-dimensional mass distribution is approximated by a model with multiple thin screens, with surface mass density varying smoothly on each screen. It is found that 16 screens are sufficient for a good approximation of the three-dimensional distribution of matter. It is also found that in this multiscreen model the distribution of amplifications of single images is dominated by the convergence due to matter within the beam. The shear caused by matter outside the beam has no significant effect. This finding considerably simplifies the modeling of lensing by a smooth three-dimensional mass distribution by effectively reducing the problem to one dimension, as it is sufficient to know the mass distribution along a straight light ray.

Two-dimensional airflow modeling underpredicts the wind velocity over dunes

PubMed Central

Michelsen, Britt; Strobl, Severin; Parteli, Eric J. R.; Pöschel, Thorsten

2015-01-01

We investigate the average turbulent wind field over a barchan dune by means of Computational Fluid Dynamics. We find that the fractional speed-up ratio of the wind velocity over the three-dimensional barchan shape differs from the one obtained from two-dimensional calculations of the airflow over the longitudinal cut along the dune’s symmetry axis — that is, over the equivalent transverse dune of same size. This finding suggests that the modeling of the airflow over the central slice of barchan dunes is insufficient for the purpose of the quantitative description of barchan dune dynamics as three-dimensional flow effects cannot be neglected. PMID:26572966

Loop models, modular invariance, and three-dimensional bosonization

NASA Astrophysics Data System (ADS)

Goldman, Hart; Fradkin, Eduardo

2018-05-01

We consider a family of quantum loop models in 2+1 spacetime dimensions with marginally long-ranged and statistical interactions mediated by a U (1 ) gauge field, both purely in 2+1 dimensions and on a surface in a (3+1)-dimensional bulk system. In the absence of fractional spin, these theories have been shown to be self-dual under particle-vortex duality and shifts of the statistical angle of the loops by 2 π , which form a subgroup of the modular group, PSL (2 ,Z ) . We show that careful consideration of fractional spin in these theories completely breaks their statistical periodicity and describe how this occurs, resolving a disagreement with the conformal field theories they appear to approach at criticality. We show explicitly that incorporation of fractional spin leads to loop model dualities which parallel the recent web of (2+1)-dimensional field theory dualities, providing a nontrivial check on its validity.

Preoperative planning and real-time assisted navigation by three-dimensional individual digital model in partial nephrectomy with three-dimensional laparoscopic system.

PubMed

Wang, Dongwen; Zhang, Bin; Yuan, Xiaobin; Zhang, Xuhui; Liu, Chen

2015-09-01

To evaluate the feasibility and effectiveness of preoperative planning and real-time assisted surgical navigation for three-dimensional laparoscopic partial nephrectomy under the guidance of three-dimensional individual digital model (3D-IDM) created using three-dimensional medical image reconstructing and guiding system (3D-MIRGS). Between May 2012 and February 2014, 44 patients with cT1 renal tumors underwent retroperitoneal laparoscopic partial nephrectomy (LPN) using a three-dimensional laparoscopic system. The 3D-IDMs were created using the 3D-MIRGS in 21 patients (3D-MIRGS group) between February 2013 and February 2014. After preoperative planning, operations were real-time assisted using composite 3D-IDMs, which were fused with two-dimensional retrolaparoscopic images. The remaining 23 patients underwent surgery without 3D-MIRGS between May 2012 and February 2013; 14 of these patients were selected as a control group. Preoperative aspects and dimensions used for an anatomical score, "radius; exophytic/endophytic; nearness; anterior/posterior; location" nephrometry score, tumor size, operative time (OT), segmental renal artery clamping (SRAC) time, estimated blood loss (EBL), postoperative hospitalization, the preoperative serum creatinine level and ipsilateral glomerular filtration rate (GFR), as well as postoperative 6-month data were compared between groups. All the SRAC procedures were technically successful, and each targeted tumor was excised completely; final pathological margin results were negative. The OT was shorter (159.0 vs. 193.2 min; p < 0.001), and EBL (148.1 vs. 176.1 mL; p < 0.001) was reduced in the 3D-MIRGS group compared with controls. No statistically significant differences in SRAC time or postoperative hospitalization were found between the groups. Neither group showed any statistically significant increases in serum creatinine level or decreases in ipsilateral GFR postoperatively. Preoperative planning and real-time assisted surgical

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.

Exact results for quench dynamics and defect production in a two-dimensional model.

PubMed

Sengupta, K; Sen, Diptiman; Mondal, Shreyoshi

2008-02-22

We show that for a d-dimensional model in which a quench with a rate tau(-1) takes the system across a (d-m)-dimensional critical surface, the defect density scales as n approximately 1/tau(mnu/(znu+1)), where nu and z are the correlation length and dynamical critical exponents characterizing the critical surface. We explicitly demonstrate that the Kitaev model provides an example of such a scaling with d = 2 and m = nu = z = 1. We also provide the first example of an exact calculation of some multispin correlation functions for a two-dimensional model that can be used to determine the correlation between the defects. We suggest possible experiments to test our theory.

Variational model for one-dimensional quantum magnets

NASA Astrophysics Data System (ADS)

Kudasov, Yu. B.; Kozabaranov, R. V.

2018-04-01

A new variational technique for investigation of the ground state and correlation functions in 1D quantum magnets is proposed. A spin Hamiltonian is reduced to a fermionic representation by the Jordan-Wigner transformation. The ground state is described by a new non-local trial wave function, and the total energy is calculated in an analytic form as a function of two variational parameters. This approach is demonstrated with an example of the XXZ-chain of spin-1/2 under a staggered magnetic field. Generalizations and applications of the variational technique for low-dimensional magnetic systems are discussed.

Predicted macroinvertebrate response to water diversion from a montane stream using two-dimensional hydrodynamic models and zero flow approximation

USGS Publications Warehouse

Holmquist, Jeffrey G.; Waddle, Terry J.

2013-01-01

We used two-dimensional hydrodynamic models for the assessment of water diversion effects on benthic macroinvertebrates and associated habitat in a montane stream in Yosemite National Park, Sierra Nevada Mountains, CA, USA. We sampled the macroinvertebrate assemblage via Surber sampling, recorded detailed measurements of bed topography and flow, and coupled a two-dimensional hydrodynamic model with macroinvertebrate indicators to assess habitat across a range of low flows in 2010 and representative past years. We also made zero flow approximations to assess response of fauna to extreme conditions. The fauna of this montane reach had a higher percentage of Ephemeroptera, Plecoptera, and Trichoptera (%EPT) than might be expected given the relatively low faunal diversity of the study reach. The modeled responses of wetted area and area-weighted macroinvertebrate metrics to decreasing discharge indicated precipitous declines in metrics as flows approached zero. Changes in area-weighted metrics closely approximated patterns observed for wetted area, i.e., area-weighted invertebrate metrics contributed relatively little additional information above that yielded by wetted area alone. Loss of habitat area in this montane stream appears to be a greater threat than reductions in velocity and depth or changes in substrate, and the modeled patterns observed across years support this conclusion. Our models suggest that step function losses of wetted area may begin when discharge in the Merced falls to 0.02 m3/s; proportionally reducing diversions when this threshold is reached will likely reduce impacts in low flow years.

Synthesis and identification of three-dimensional faces from image(s) and three-dimensional generic models

NASA Astrophysics Data System (ADS)

Liu, Zexi; Cohen, Fernand

2017-11-01

We describe an approach for synthesizing a three-dimensional (3-D) face structure from an image or images of a human face taken at a priori unknown poses using gender and ethnicity specific 3-D generic models. The synthesis process starts with a generic model, which is personalized as images of the person become available using preselected landmark points that are tessellated to form a high-resolution triangular mesh. From a single image, two of the three coordinates of the model are reconstructed in accordance with the given image of the person, while the third coordinate is sampled from the generic model, and the appearance is made in accordance with the image. With multiple images, all coordinates and appearance are reconstructed in accordance with the observed images. This method allows for accurate pose estimation as well as face identification in 3-D rendering of a difficult two-dimensional (2-D) face recognition problem into a much simpler 3-D surface matching problem. The estimation of the unknown pose is achieved using the Levenberg-Marquardt optimization process. Encouraging experimental results are obtained in a controlled environment with high-resolution images under a good illumination condition, as well as for images taken in an uncontrolled environment under arbitrary illumination with low-resolution cameras.

Creating three-dimensional tooth models from tomographic images.

PubMed

Lima da Silva, Isaac Newton; Barbosa, Gustavo Frainer; Soares, Rodrigo Borowski Grecco; Beltrao, Maria Cecilia Gomes; Spohr, Ana Maria; Mota, Eduardo Golcalves; Oshima, Hugo Mitsuo Silva; Burnett, Luiz Henrique

2008-01-01

The use of Finite Element Analysis (FEA) is becoming very frequent in Dentistry. However, most of the three-dimensional models presented by the literature for teeth are limited in terms of geometry. Discrepancy in shape and dimensions can cause wrong results to occur. Sharp cusps and faceted contour can produce stress concentrations, which are incoherent with the reality. The aim of this study was the processing of tomographic images in order to develop an advanced three-dimensional reconstruction of the anatomy of a molar tooth and the integration of the resulting solid with commercially available CAD/CAE software. Computed tomographic images were obtained from 0.5 mm thick slices of mandibular molar and transferred to commercial cad software. Once the point cloud data have been generated, the work on these points started to get to the solid model of the tooth with Pro/Engineer software. The obtained tooth model showed very accurate shape and dimensions, as it was obtained from real tooth data with error of 0.0 to -0.8 mm. The methodology presented was efficient for creating a biomodel of a tooth from tomographic images that realistically represented its anatomy.

Three-dimensional ring current decay model

NASA Technical Reports Server (NTRS)

Fok, Mei-Ching; Moore, Thomas E.; Kozyra, Janet U.; Ho, George C.; Hamilton, Douglas C.

1995-01-01

This work is an extension of a previous ring current decay model. In the previous work, a two-dimensional kinetic model was constructed to study the temporal variations of the equatorially mirroring ring current ions, considering charge exchange and Coulomb drag losses along drift paths in a magnetic dipole field. In this work, particles with arbitrary pitch angle are considered. By bounce averaging the kinetic equation of the phase space density, information along magnetic field lines can be inferred from the equator. The three-dimensional model is used to simulate the recovery phase of a model great magnetic storm, similar to that which occurred in early February 1986. The initial distribution of ring current ions (at the minimum Dst) is extrapolated to all local times from AMPTE/CCE spacecraft observations on the dawnside and duskside of the inner magnetosphere spanning the L value range L = 2.25 to 6.75. Observations by AMPTE/CCE of ring current distributions over subsequent orbits during the storm recovery phase are compared to model outputs. In general, the calculated ion fluxes are consistent with observations, except for H(+) fluxes at tens of keV, which are always overestimated. A newly invented visualization idea, designated as a chromogram, is used to display the spatial and energy dependence of the ring current ion differential flux. Important features of storm time ring current, such as day-night asymmetry during injection and drift hole on the dayside at low energies (less than 10 keV), are manifested in the chromogram representation. The pitch angle distribution is well fit by the function, J(sub o)(1 + Ay(sup n)), where y is sine of the equatorial pitch angle. The evolution of the index n is a combined effect of charge exchange loss and particle drift. At low energies (less than 30 keV), both drift dispersion and charge exchange are important in determining n.

A numerical code for a three-dimensional magnetospheric MHD equilibrium model

NASA Technical Reports Server (NTRS)

Voigt, G.-H.

1992-01-01

Two dimensional and three dimensional MHD equilibrium models were begun for Earth's magnetosphere. The original proposal was motivated by realizing that global, purely data based models of Earth's magnetosphere are inadequate for studying the underlying plasma physical principles according to which the magnetosphere evolves on the quasi-static convection time scale. Complex numerical grid generation schemes were established for a 3-D Poisson solver, and a robust Grad-Shafranov solver was coded for high beta MHD equilibria. Thus, the effects were calculated of both the magnetopause geometry and boundary conditions on the magnetotail current distribution.

A Reduced Order Model of the Linearized Incompressible Navier-Strokes Equations for the Sensor/Actuator Placement Problem

NASA Technical Reports Server (NTRS)

Allan, Brian G.

2000-01-01

A reduced order modeling approach of the Navier-Stokes equations is presented for the design of a distributed optimal feedback kernel. This approach is based oil a Krylov subspace method where significant modes of the flow are captured in the model This model is then used in all optimal feedback control design where sensing and actuation is performed oil tile entire flow field. This control design approach yields all optimal feedback kernel which provides insight into the placement of sensors and actuators in the flow field. As all evaluation of this approach, a two-dimensional shear layer and driven cavity flow are investigated.

Verification and transfer of thermal pollution model. Volume 4: User's manual for three-dimensional rigid-lid model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Nwadike, E. V.; Sinha, S. E.

1982-01-01

The theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model are described. Model verification at two sites, a separate user's manual for each model are included. The 3-D model has two forms: free surface and rigid lid. The former allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth, estuaries and coastal regions. The latter is suited for small surface wave heights compared to depth because surface elevation was removed as a parameter. These models allow computation of time dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions. The free surface model also provides surface height variations with time.

Role of dimensionality in Axelrod's model for the dissemination of culture

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San

2003-09-01

We analyze a model of social interaction in one- and two-dimensional lattices for a moderate number of features. We introduce an order parameter as a function of the overlap between neighboring sites. In a one-dimensional chain, we observe that the dynamics is consistent with a second-order transition, where the order parameter changes continuously and the average domain diverges at the transition point. However, in a two-dimensional lattice the order parameter is discontinuous at the transition point characteristic of a first-order transition between an ordered and a disordered state.

Investigation of biogeophysical feedback on the African climate using a two-dimensional model

NASA Technical Reports Server (NTRS)

Xue, Yongkang; Liou, Kuo-Nan; Kasahara, Akira

1990-01-01

A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.

A three-dimensional spin-diffusion model for micromagnetics

PubMed Central

Abert, Claas; Ruggeri, Michele; Bruckner, Florian; Vogler, Christoph; Hrkac, Gino; Praetorius, Dirk; Suess, Dieter

2015-01-01

We solve a time-dependent three-dimensional spin-diffusion model coupled to the Landau-Lifshitz-Gilbert equation numerically. The presented model is validated by comparison to two established spin-torque models: The model of Slonzewski that describes spin-torque in multi-layer structures in the presence of a fixed layer and the model of Zhang and Li that describes current driven domain-wall motion. It is shown that both models are incorporated by the spin-diffusion description, i.e., the nonlocal effects of the Slonzewski model are captured as well as the spin-accumulation due to magnetization gradients as described by the model of Zhang and Li. Moreover, the presented method is able to resolve the time dependency of the spin-accumulation. PMID:26442796

Scientific data interpolation with low dimensional manifold model

DOE PAGES

Zhu, Wei; Wang, Bao; Barnard, Richard C.; ...

2017-09-28

Here, we propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace–Beltrami operator in the Euler–Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on datamore » compression and interpolation from both regular and irregular samplings.« less

Scientific data interpolation with low dimensional manifold model

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

Zhu, Wei; Wang, Bao; Barnard, Richard C.

Here, we propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace–Beltrami operator in the Euler–Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on datamore » compression and interpolation from both regular and irregular samplings.« less

Numerical investigation of fluid mud motion using a three-dimensional hydrodynamic and two-dimensional fluid mud coupling model

NASA Astrophysics Data System (ADS)

Yang, Xiaochen; Zhang, Qinghe; Hao, Linnan

2015-03-01

A water-fluid mud coupling model is developed based on the unstructured grid finite volume coastal ocean model (FVCOM) to investigate the fluid mud motion. The hydrodynamics and sediment transport of the overlying water column are solved using the original three-dimensional ocean model. A horizontal two-dimensional fluid mud model is integrated into the FVCOM model to simulate the underlying fluid mud flow. The fluid mud interacts with the water column through the sediment flux, current, and shear stress. The friction factor between the fluid mud and the bed, which is traditionally determined empirically, is derived with the assumption that the vertical distribution of shear stress below the yield surface of fluid mud is identical to that of uniform laminar flow of Newtonian fluid in the open channel. The model is validated by experimental data and reasonable agreement is found. Compared with numerical cases with fixed friction factors, the results simulated with the derived friction factor exhibit the best agreement with the experiment, which demonstrates the necessity of the derivation of the friction factor.

Estimating habitat volume of living resources using three-dimensional circulation and biogeochemical models

NASA Astrophysics Data System (ADS)

Smith, Katharine A.; Schlag, Zachary; North, Elizabeth W.

2018-07-01

Coupled three-dimensional circulation and biogeochemical models predict changes in water properties that can be used to define fish habitat, including physiologically important parameters such as temperature, salinity, and dissolved oxygen. However, methods for calculating the volume of habitat defined by the intersection of multiple water properties are not well established for coupled three-dimensional models. The objectives of this research were to examine multiple methods for calculating habitat volume from three-dimensional model predictions, select the most robust approach, and provide an example application of the technique. Three methods were assessed: the "Step," "Ruled Surface", and "Pentahedron" methods, the latter of which was developed as part of this research. Results indicate that the analytical Pentahedron method is exact, computationally efficient, and preserves continuity in water properties between adjacent grid cells. As an example application, the Pentahedron method was implemented within the Habitat Volume Model (HabVol) using output from a circulation model with an Arakawa C-grid and physiological tolerances of juvenile striped bass (Morone saxatilis). This application demonstrates that the analytical Pentahedron method can be successfully applied to calculate habitat volume using output from coupled three-dimensional circulation and biogeochemical models, and it indicates that the Pentahedron method has wide application to aquatic and marine systems for which these models exist and physiological tolerances of organisms are known.

Construction and validation of a three-dimensional finite element model of degenerative scoliosis.

PubMed

Zheng, Jie; Yang, Yonghong; Lou, Shuliang; Zhang, Dongsheng; Liao, Shenghui

2015-12-24

With the aging of the population, degenerative scoliosis (DS) incidence rate is increasing. In recent years, increasing research on this topic has been carried out, yet biomechanical research on the subject is seldom seen and in vitro biomechanical model of DS nearly cannot be available. The objective of this study was to develop and validate a complete three-dimensional finite element model of DS in order to build the digital platform for further biomechanical study. A 55-year-old female DS patient (Suer Pan, ID number was P141986) was selected for this study. This study was performed in accordance with the ethical standards of Declaration of Helsinki and its amendments and was approved by the local ethics committee (117 hospital of PLA ethics committee). Spiral computed tomography (CT) scanning was conducted on the patient's lumbar spine from the T12 to S1. CT images were then imported into a finite element modeling system. A three-dimensional solid model was then formed from segmentation of the CT scan. The three-dimensional model of each vertebra was then meshed, and material properties were assigned to each element according to the pathological characteristics of DS. Loads and boundary conditions were then applied in such a manner as to simulate in vitro biomechanical experiments conducted on lumbar segments. The results of the model were then compared with experimental results in order to validate the model. An integral three-dimensional finite element model of DS was built successfully, consisting of 113,682 solid elements, 686 cable elements, 33,329 shell elements, 4968 target elements, 4968 contact elements, totaling 157,635 elements, and 197,374 nodes. The model accurately described the physical features of DS and was geometrically similar to the object of study. The results of analysis with the finite element model agreed closely with in vitro experiments, validating the accuracy of the model. The three-dimensional finite element model of DS built in

Inverse finite-size scaling for high-dimensional significance analysis

NASA Astrophysics Data System (ADS)

Xu, Yingying; Puranen, Santeri; Corander, Jukka; Kabashima, Yoshiyuki

2018-06-01

We propose an efficient procedure for significance determination in high-dimensional dependence learning based on surrogate data testing, termed inverse finite-size scaling (IFSS). The IFSS method is based on our discovery of a universal scaling property of random matrices which enables inference about signal behavior from much smaller scale surrogate data than the dimensionality of the original data. As a motivating example, we demonstrate the procedure for ultra-high-dimensional Potts models with order of 1010 parameters. IFSS reduces the computational effort of the data-testing procedure by several orders of magnitude, making it very efficient for practical purposes. This approach thus holds considerable potential for generalization to other types of complex models.

Development of a three dimensional numerical water quality model for continental shelf applications

NASA Technical Reports Server (NTRS)

Spaulding, M.; Hunter, D.

1975-01-01

A model to predict the distribution of water quality parameters in three dimensions was developed. The mass transport equation was solved using a non-dimensional vertical axis and an alternating-direction-implicit finite difference technique. The reaction kinetics of the constituents were incorporated into a matrix method which permits computation of the interactions of multiple constituents. Methods for the computation of dispersion coefficients and coliform bacteria decay rates were determined. Numerical investigations of dispersive and dissipative effects showed that the three-dimensional model performs as predicted by analysis of simpler cases. The model was then applied to a two dimensional vertically averaged tidal dynamics model for the Providence River. It was also extended to a steady state application by replacing the time step with an iteration sequence. This modification was verified by comparison to analytical solutions and applied to a river confluence situation.

Three-Dimensional, Transgenic Cell Models to Quantify Space Genotoxic Effects

NASA Technical Reports Server (NTRS)

Gonda, S. R.; Sognier, M. A.; Wu, H.; Pingerelli, P. L.; Glickman, B. W.; Dawson, David L. (Technical Monitor)

1999-01-01

The space environment contains radiation and chemical agents known to be mutagenic and carcinogenic to humans. Additionally, microgravity is a complicating factor that may modify or synergize induced genotoxic effects. Most in vitro models fail to use human cells (making risk extrapolation to humans more difficult), overlook the dynamic effect of tissue intercellular interactions on genotoxic damage, and lack the sensitivity required to measure low-dose effects. Currently a need exists for a model test system that simulates cellular interactions present in tissue, and can be used to quantify genotoxic damage induced by low levels of radiation and chemicals, and extrapolate assessed risk to humans. A state-of-the-art, three-dimensional, multicellular tissue equivalent cell culture model will be presented. It consists of mammalian cells genetically engineered to contain multiple copies of defined target genes for genotoxic assessment,. NASA-designed bioreactors were used to coculture mammalian cells into spheroids, The cells used were human mammary epithelial cells (H184135) and Stratagene's (Austin, Texas) Big Blue(TM) Rat 2 lambda fibroblasts. The fibroblasts were genetically engineered to contain -a high-density target gene for mutagenesis (60 copies of lacl/LacZ per cell). Tissue equivalent spheroids were routinely produced by inoculation of 2 to 7 X 10(exp 5) fibroblasts with Cytodex 3 beads (150 micrometers in diameter). at a 20:1 cell:bead ratio, into 50-ml HARV bioreactors (Synthecon, Inc.). Fibroblasts were cultured for 5 days, an equivalent number of epithelial cells added, and the fibroblast/epithelial cell coculture continued for 21 days. Three-dimensional spheroids with diameters ranging from 400 to 600 micrometers were obtained. Histological and immunohistochemical Characterization revealed i) both cell types present in the spheroids, with fibroblasts located primarily in the center, surrounded by epithelial cells; ii) synthesis of extracellular matrix

Low-dimensional manifold of actin polymerization dynamics

NASA Astrophysics Data System (ADS)

Floyd, Carlos; Jarzynski, Christopher; Papoian, Garegin

2017-12-01

Actin filaments are critical components of the eukaryotic cytoskeleton, playing important roles in a number of cellular functions, such as cell migration, organelle transport, and mechanosensation. They are helical polymers with a well-defined polarity, composed of globular subunits that bind nucleotides in one of three hydrolysis states (ATP, ADP-Pi, or ADP). Mean-field models of the dynamics of actin polymerization have succeeded in, among other things, determining the nucleotide profile of an average filament and resolving the mechanisms of accessory proteins. However, these models require numerical solution of a high-dimensional system of nonlinear ordinary differential equations. By truncating a set of recursion equations, the Brooks-Carlsson (BC) model reduces dimensionality to 11, but it still remains nonlinear and does not admit an analytical solution, hence, significantly hindering understanding of its resulting dynamics. In this work, by taking advantage of the fast timescales of the hydrolysis states of the filament tips, we propose two model reduction schemes: the quasi steady-state approximation model is five-dimensional and nonlinear, whereas the constant tip (CT) model is five-dimensional and linear, resulting from the approximation that the tip states are not dynamic variables. We provide an exact solution of the CT model and use it to shed light on the dynamical behaviors of the full BC model, highlighting the relative ordering of the timescales of various collective processes, and explaining some unusual dependence of the steady-state behavior on initial conditions.

Verification and transfer of thermal pollution model. Volume 2: User's manual for 3-dimensional free-surface model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Tuann, S. Y.; Lee, C. R.

1982-01-01

The six-volume report: describes the theory of a three-dimensional (3-D) mathematical thermal discharge model and a related one-dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth. These models allow computation of time-dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions.

Verification and transfer of thermal pollution model. Volume 3: Verification of 3-dimensional rigid-lid model

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Nwadike, E. V.; Sinha, S. K.

1982-01-01

The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter. These models allow computation of time-dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions. The free-surface model also provides surface height variations with time.

Adaptation of an articulated fetal skeleton model to three-dimensional fetal image data

NASA Astrophysics Data System (ADS)

Klinder, Tobias; Wendland, Hannes; Wachter-Stehle, Irina; Roundhill, David; Lorenz, Cristian

2015-03-01

The automatic interpretation of three-dimensional fetal images poses specific challenges compared to other three-dimensional diagnostic data, especially since the orientation of the fetus in the uterus and the position of the extremities is highly variable. In this paper, we present a comprehensive articulated model of the fetal skeleton and the adaptation of the articulation for pose estimation in three-dimensional fetal images. The model is composed out of rigid bodies where the articulations are represented as rigid body transformations. Given a set of target landmarks, the model constellation can be estimated by optimization of the pose parameters. Experiments are carried out on 3D fetal MRI data yielding an average error per case of 12.03+/-3.36 mm between target and estimated landmark positions.

Two-Dimensional Quantum Model of a Nanotransistor

NASA Technical Reports Server (NTRS)

Govindan, T. R.; Biegel, B.; Svizhenko, A.; Anantram, M. P.

2009-01-01

A mathematical model, and software to implement the model, have been devised to enable numerical simulation of the transport of electric charge in, and the resulting electrical performance characteristics of, a nanotransistor [in particular, a metal oxide/semiconductor field-effect transistor (MOSFET) having a channel length of the order of tens of nanometers] in which the overall device geometry, including the doping profiles and the injection of charge from the source, gate, and drain contacts, are approximated as being two-dimensional. The model and software constitute a computational framework for quantitatively exploring such device-physics issues as those of source-drain and gate leakage currents, drain-induced barrier lowering, and threshold voltage shift due to quantization. The model and software can also be used as means of studying the accuracy of quantum corrections to other semiclassical models.

Development of Unsteady Aerodynamic and Aeroelastic Reduced-Order Models Using the FUN3D Code

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Vatsa, Veer N.; Biedron, Robert T.

2009-01-01

Recent significant improvements to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) are implemented into the FUN3D unstructured flow solver. These improvements include the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system via a single CFD solution, minimization of the error between the full CFD and the ROM unsteady aero- dynamic solution, and computation of a root locus plot of the aeroelastic ROM. Results are presented for a viscous version of the two-dimensional Benchmark Active Controls Technology (BACT) model and an inviscid version of the AGARD 445.6 aeroelastic wing using the FUN3D code.

Continued development and validation of the AER two-dimensional interactive model

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Sze, N. D.; Shia, R. L.; Mackay, M.; Weisenstein, D. K.; Zhou, S. T.

1996-01-01

Results from two-dimensional chemistry-transport models have been used to predict the future behavior of ozone in the stratosphere. Since the transport circulation, temperature, and aerosol surface area are fixed in these models, they cannot account for the effects of changes in these quantities, which could be modified because of ozone redistribution and/or other changes in the troposphere associated with climate changes. Interactive two-dimensional models, which calculate the transport circulation and temperature along with concentrations of the chemical species, could provide answers to complement the results from three-dimension model calculations. In this project, we performed the following tasks in pursuit of the respective goals: (1) We continued to refine the 2-D chemistry-transport model; (2) We developed a microphysics model to calculate the aerosol loading and its size distribution; (3) The treatment of physics in the AER 2-D interactive model were refined in the following areas--the heating rate in the troposphere, and wave-forcing from propagation of planetary waves.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

(N+1)-dimensional fractional reduced differential transform method for fractional order partial differential equations

NASA Astrophysics Data System (ADS)

Arshad, Muhammad; Lu, Dianchen; Wang, Jun

2017-07-01

In this paper, we pursue the general form of the fractional reduced differential transform method (DTM) to (N+1)-dimensional case, so that fractional order partial differential equations (PDEs) can be resolved effectively. The most distinct aspect of this method is that no prescribed assumptions are required, and the huge computational exertion is reduced and round-off errors are also evaded. We utilize the proposed scheme on some initial value problems and approximate numerical solutions of linear and nonlinear time fractional PDEs are obtained, which shows that the method is highly accurate and simple to apply. The proposed technique is thus an influential technique for solving the fractional PDEs and fractional order problems occurring in the field of engineering, physics etc. Numerical results are obtained for verification and demonstration purpose by using Mathematica software.

N = 1 supersymmetric indices and the four-dimensional A-model

NASA Astrophysics Data System (ADS)

Closset, Cyril; Kim, Heeyeon; Willett, Brian

2017-08-01

We compute the supersymmetric partition function of N = 1 supersymmetric gauge theories with an R-symmetry on M_4\\cong M_{g,p}× {S}^1 , a principal elliptic fiber bundle of degree p over a genus- g Riemann surface, Σ g . Equivalently, we compute the generalized supersymmetric index I_{M}{_{g,p}, with the supersymmetric three-manifold M_{g,p} as the spatial slice. The ordinary N = 1 supersymmetric index on the round three-sphere is recovered as a special case. We approach this computation from the point of view of a topological A-model for the abelianized gauge fields on the base Σ g . This A-model — or A-twisted two-dimensional N = (2 , 2) gauge theory — encodes all the information about the generalized indices, which are viewed as expectations values of some canonically-defined surface defects wrapped on T 2 inside Σ g × T 2. Being defined by compactification on the torus, the A-model also enjoys natural modular properties, governed by the four-dimensional 't Hooft anomalies. As an application of our results, we provide new tests of Seiberg duality. We also present a new evaluation formula for the three-sphere index as a sum over two-dimensional vacua.

Theory and application of a three-dimensional model of the human spine.

PubMed

Belytschko, T; Schwer, L; Privitzer, E

1978-01-01

A three-dimensional, discrete model of the human spine, torso, and head was developed for the purpose of evaluating mechanical response in pilot ejection. However, it was developed in sufficient generality to be applicable to other body response problems, such as occupant response in aircraft crash and arbitrary loads on the head-spine system. The anatomy is modelled by a collection of rigid bodies, which represent skeletal segments such as the vertebrae, pelvis, head, and ribs, interconnected by deformable elements, which represent ligaments, cargilagenous joints, viscera and connective tissues. Results are presented for several conditions: different rates of onset, ejection at angles, preejection alignment, and eccentric head loadings. It is shown that slow rates of onset and angling the seat reduce both the peak axial loads and bending moments. In the presence of eccentric head masses, such as helmet-mounted devices, the reflected flexural wave is shown to be the key injury mechanism.

Finding of Correction Factor and Dimensional Error in Bio-AM Model by FDM Technique

NASA Astrophysics Data System (ADS)

Manmadhachary, Aiamunoori; Ravi Kumar, Yennam; Krishnanand, Lanka

2018-06-01

Additive Manufacturing (AM) is the swift manufacturing process, in which input data can be provided from various sources like 3-Dimensional (3D) Computer Aided Design (CAD), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and 3D scanner data. From the CT/MRI data can be manufacture Biomedical Additive Manufacturing (Bio-AM) models. The Bio-AM model gives a better lead on preplanning of oral and maxillofacial surgery. However manufacturing of the accurate Bio-AM model is one of the unsolved problems. The current paper demonstrates error between the Standard Triangle Language (STL) model to Bio-AM model of dry mandible and found correction factor in Bio-AM model with Fused Deposition Modelling (FDM) technique. In the present work dry mandible CT images are acquired by CT scanner and supplied into a 3D CAD model in the form of STL model. Further the data is sent to FDM machine for fabrication of Bio-AM model. The difference between Bio-AM to STL model dimensions is considered as dimensional error and the ratio of STL to Bio-AM model dimensions considered as a correction factor. This correction factor helps to fabricate the AM model with accurate dimensions of the patient anatomy. These true dimensional Bio-AM models increasing the safety and accuracy in pre-planning of oral and maxillofacial surgery. The correction factor for Dimension SST 768 FDM AM machine is 1.003 and dimensional error is limited to 0.3 %.

Finding of Correction Factor and Dimensional Error in Bio-AM Model by FDM Technique

NASA Astrophysics Data System (ADS)

Manmadhachary, Aiamunoori; Ravi Kumar, Yennam; Krishnanand, Lanka

2016-06-01

Additive Manufacturing (AM) is the swift manufacturing process, in which input data can be provided from various sources like 3-Dimensional (3D) Computer Aided Design (CAD), Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and 3D scanner data. From the CT/MRI data can be manufacture Biomedical Additive Manufacturing (Bio-AM) models. The Bio-AM model gives a better lead on preplanning of oral and maxillofacial surgery. However manufacturing of the accurate Bio-AM model is one of the unsolved problems. The current paper demonstrates error between the Standard Triangle Language (STL) model to Bio-AM model of dry mandible and found correction factor in Bio-AM model with Fused Deposition Modelling (FDM) technique. In the present work dry mandible CT images are acquired by CT scanner and supplied into a 3D CAD model in the form of STL model. Further the data is sent to FDM machine for fabrication of Bio-AM model. The difference between Bio-AM to STL model dimensions is considered as dimensional error and the ratio of STL to Bio-AM model dimensions considered as a correction factor. This correction factor helps to fabricate the AM model with accurate dimensions of the patient anatomy. These true dimensional Bio-AM models increasing the safety and accuracy in pre-planning of oral and maxillofacial surgery. The correction factor for Dimension SST 768 FDM AM machine is 1.003 and dimensional error is limited to 0.3 %.

Spectroscopic properties of a two-dimensional time-dependent Cepheid model. I. Description and validation of the model

NASA Astrophysics Data System (ADS)

Vasilyev, V.; Ludwig, H.-G.; Freytag, B.; Lemasle, B.; Marconi, M.

2017-10-01

Context. Standard spectroscopic analyses of Cepheid variables are based on hydrostatic one-dimensional model atmospheres, with convection treated using various formulations of mixing-length theory. Aims: This paper aims to carry out an investigation of the validity of the quasi-static approximation in the context of pulsating stars. We check the adequacy of a two-dimensional time-dependent model of a Cepheid-like variable with focus on its spectroscopic properties. Methods: With the radiation-hydrodynamics code CO5BOLD, we construct a two-dimensional time-dependent envelope model of a Cepheid with Teff = 5600 K, log g = 2.0, solar metallicity, and a 2.8-day pulsation period. Subsequently, we perform extensive spectral syntheses of a set of artificial iron lines in local thermodynamic equilibrium. The set of lines allows us to systematically study effects of line strength, ionization stage, and excitation potential. Results: We evaluate the microturbulent velocity, line asymmetry, projection factor, and Doppler shifts. The microturbulent velocity, averaged over all lines, depends on the pulsational phase and varies between 1.5 and 2.7 km s-1. The derived projection factor lies between 1.23 and 1.27, which agrees with observational results. The mean Doppler shift is non-zero and negative, -1 km s-1, after averaging over several full periods and lines. This residual line-of-sight velocity (related to the "K-term") is primarily caused by horizontal inhomogeneities, and consequently we interpret it as the familiar convective blueshift ubiquitously present in non-pulsating late-type stars. Limited statistics prevent firm conclusions on the line asymmetries. Conclusions: Our two-dimensional model provides a reasonably accurate representation of the spectroscopic properties of a short-period Cepheid-like variable star. Some properties are primarily controlled by convective inhomogeneities rather than by the Cepheid-defining pulsations. Extended multi-dimensional modelling

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Modeling of the financial market using the two-dimensional anisotropic Ising model

NASA Astrophysics Data System (ADS)

Lima, L. S.

2017-09-01

We have used the two-dimensional classical anisotropic Ising model in an external field and with an ion single anisotropy term as a mathematical model for the price dynamics of the financial market. The model presented allows us to test within the same framework the comparative explanatory power of rational agents versus irrational agents with respect to the facts of financial markets. We have obtained the mean price in terms of the strong of the site anisotropy term Δ which reinforces the sensitivity of the agent's sentiment to external news.

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Three-Dimensional Modeling May Improve Surgical Education and Clinical Practice.

PubMed

Jones, Daniel B; Sung, Robert; Weinberg, Crispin; Korelitz, Theodore; Andrews, Robert

2016-04-01

Three-dimensional (3D) printing has been used in the manufacturing industry for rapid prototyping and product testing. The aim of our study was to assess the feasibility of creating anatomical 3D models from a digital image using 3D printers. Furthermore, we sought face validity of models and explored potential opportunities for using 3D printing to enhance surgical education and clinical practice. Computed tomography and magnetic resonance images were reviewed, converted to computer models, and printed by stereolithography to create near exact replicas of human organs. Medical students and surgeons provided feedback via survey at the 2014 Surgical Education Week conference. There were 51 respondents, and 95.8% wanted these models for their patients. Cost was a concern, but 82.6% found value in these models at a price less than $500. All respondents thought the models would be useful for integration into the medical school curriculum. Three-dimensional printing is a potentially disruptive technology to improve both surgical education and clinical practice. As the technology matures and cost decreases, we envision 3D models being increasingly used in surgery. © The Author(s) 2015.

Data-driven reduced order models for effective yield strength and partitioning of strain in multiphase materials

NASA Astrophysics Data System (ADS)

Latypov, Marat I.; Kalidindi, Surya R.

2017-10-01

There is a critical need for the development and verification of practically useful multiscale modeling strategies for simulating the mechanical response of multiphase metallic materials with heterogeneous microstructures. In this contribution, we present data-driven reduced order models for effective yield strength and strain partitioning in such microstructures. These models are built employing the recently developed framework of Materials Knowledge Systems that employ 2-point spatial correlations (or 2-point statistics) for the quantification of the heterostructures and principal component analyses for their low-dimensional representation. The models are calibrated to a large collection of finite element (FE) results obtained for a diverse range of microstructures with various sizes, shapes, and volume fractions of the phases. The performance of the models is evaluated by comparing the predictions of yield strength and strain partitioning in two-phase materials with the corresponding predictions from a classical self-consistent model as well as results of full-field FE simulations. The reduced-order models developed in this work show an excellent combination of accuracy and computational efficiency, and therefore present an important advance towards computationally efficient microstructure-sensitive multiscale modeling frameworks.

Development of Comprehensive Reduced Kinetic Models for Supersonic Reacting Shear Layer Simulations

NASA Technical Reports Server (NTRS)

Zambon, A. C.; Chelliah, H. K.; Drummond, J. P.

2006-01-01

Large-scale simulations of multi-dimensional unsteady turbulent reacting flows with detailed chemistry and transport can be computationally extremely intensive even on distributed computing architectures. With the development of suitable reduced chemical kinetic models, the number of scalar variables to be integrated can be decreased, leading to a significant reduction in the computational time required for the simulation with limited loss of accuracy in the results. A general MATLAB-based automated mechanism reduction procedure is presented to reduce any complex starting mechanism (detailed or skeletal) with minimal human intervention. Based on the application of the quasi steady-state (QSS) approximation for certain chemical species and on the elimination of the fast reaction rates in the mechanism, several comprehensive reduced models, capable of handling different fuels such as C2H4, CH4 and H2, have been developed and thoroughly tested for several combustion problems (ignition, propagation and extinction) and physical conditions (reactant compositions, temperatures, and pressures). A key feature of the present reduction procedure is the explicit solution of the concentrations of the QSS species, needed for the evaluation of the elementary reaction rates. In contrast, previous approaches relied on an implicit solution due to the strong coupling between QSS species, requiring computationally expensive inner iterations. A novel algorithm, based on the definition of a QSS species coupling matrix, is presented to (i) introduce appropriate truncations to the QSS algebraic relations and (ii) identify the optimal sequence for the explicit solution of the concentration of the QSS species. With the automatic generation of the relevant source code, the resulting reduced models can be readily implemented into numerical codes.

Three-Dimensional Blood-Brain Barrier Model for in vitro Studies of Neurovascular Pathology

NASA Astrophysics Data System (ADS)

Cho, Hansang; Seo, Ji Hae; Wong, Keith H. K.; Terasaki, Yasukazu; Park, Joseph; Bong, Kiwan; Arai, Ken; Lo, Eng H.; Irimia, Daniel

2015-10-01

Blood-brain barrier (BBB) pathology leads to neurovascular disorders and is an important target for therapies. However, the study of BBB pathology is difficult in the absence of models that are simple and relevant. In vivo animal models are highly relevant, however they are hampered by complex, multi-cellular interactions that are difficult to decouple. In vitro models of BBB are simpler, however they have limited functionality and relevance to disease processes. To address these limitations, we developed a 3-dimensional (3D) model of BBB on a microfluidic platform. We verified the tightness of the BBB by showing its ability to reduce the leakage of dyes and to block the transmigration of immune cells towards chemoattractants. Moreover, we verified the localization at endothelial cell boundaries of ZO-1 and VE-Cadherin, two components of tight and adherens junctions. To validate the functionality of the BBB model, we probed its disruption by neuro-inflammation mediators and ischemic conditions and measured the protective function of antioxidant and ROCK-inhibitor treatments. Overall, our 3D BBB model provides a robust platform, adequate for detailed functional studies of BBB and for the screening of BBB-targeting drugs in neurological diseases.

Retention modelling of polychlorinated biphenyls in comprehensive two-dimensional gas chromatography.

PubMed

D'Archivio, Angelo Antonio; Incani, Angela; Ruggieri, Fabrizio

2011-01-01

In this paper, we use a quantitative structure-retention relationship (QSRR) method to predict the retention times of polychlorinated biphenyls (PCBs) in comprehensive two-dimensional gas chromatography (GC×GC). We analyse the GC×GC retention data taken from the literature by comparing predictive capability of different regression methods. The various models are generated using 70 out of 209 PCB congeners in the calibration stage, while their predictive performance is evaluated on the remaining 139 compounds. The two-dimensional chromatogram is initially estimated by separately modelling retention times of PCBs in the first and in the second column ((1) t (R) and (2) t (R), respectively). In particular, multilinear regression (MLR) combined with genetic algorithm (GA) variable selection is performed to extract two small subsets of predictors for (1) t (R) and (2) t (R) from a large set of theoretical molecular descriptors provided by the popular software Dragon, which after removal of highly correlated or almost constant variables consists of 237 structure-related quantities. Based on GA-MLR analysis, a four-dimensional and a five-dimensional relationship modelling (1) t (R) and (2) t (R), respectively, are identified. Single-response partial least square (PLS-1) regression is alternatively applied to independently model (1) t (R) and (2) t (R) without the need for preliminary GA variable selection. Further, we explore the possibility of predicting the two-dimensional chromatogram of PCBs in a single calibration procedure by using a two-response PLS (PLS-2) model or a feed-forward artificial neural network (ANN) with two output neurons. In the first case, regression is carried out on the full set of 237 descriptors, while the variables previously selected by GA-MLR are initially considered as ANN inputs and subjected to a sensitivity analysis to remove the redundant ones. Results show PLS-1 regression exhibits a noticeably better descriptive and predictive

Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2017-10-01

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space. Copyright © 2017 Elsevier B.V. All rights reserved.

Judgment Research and the Dimensional Model of Personality

ERIC Educational Resources Information Center

Garb, Howard N.

2008-01-01

Comments on the original article "Plate tectonics in the classification of personality disorder: Shifting to a dimensional model," by T. A. Widiger and T. J. Trull. The purpose of this comment is to address (a) whether psychologists know how personality traits are currently assessed by clinicians and (b) the reliability and validity of those…

ALGE3D: A Three-Dimensional Transport Model

NASA Astrophysics Data System (ADS)

Maze, G. M.

2017-12-01

Of the top 10 most populated US cities from a 2015 US Census Bureau estimate, 7 of the cities are situated near the ocean, a bay, or on one of the Great Lakes. A contamination of the water ways in the United States could be devastating to the economy (through tourism and industries such as fishing), public health (from direct contact, or contaminated drinking water), and in some cases even infrastructure (water treatment plants). Current national response models employed by emergency response agencies have well developed models to simulate the effects of hazardous contaminants in riverine systems that are primarily driven by one-dimensional flows; however in more complex systems, such as tidal estuaries, bays, or lakes, a more complex model is needed. While many models exist, none are capable of quick deployment in emergency situations that could contain a variety of release situations including a mixture of both particulate and dissolved chemicals in a complex flow area. ALGE3D, developed at the Department of Energy's (DOE) Savannah River National Laboratory (SRNL), is a three-dimensional hydrodynamic code which solves the momentum, mass, and energy conservation equations to predict the movement and dissipation of thermal or dissolved chemical plumes discharged into cooling lakes, rivers, and estuaries. ALGE3D is capable of modeling very complex flows, including areas with tidal flows which include wetting and drying of land. Recent upgrades have increased the capabilities including the transport of particulate tracers, allowing for more complete modeling of the transport of pollutants. In addition the model is capable of coupling with a one-dimension riverine transport model or a two-dimension atmospheric deposition model in the event that a contamination event occurs upstream or upwind of the water body.

(2 + 1)-dimensional interacting model of two massless spin-2 fields as a bi-gravity model

NASA Astrophysics Data System (ADS)

Hoseinzadeh, S.; Rezaei-Aghdam, A.

2018-06-01

We propose a new group-theoretical (Chern-Simons) formulation for the bi-metric theory of gravity in (2 + 1)-dimensional spacetime which describe two interacting massless spin-2 fields. Our model has been formulated in terms of two dreibeins rather than two metrics. We obtain our Chern-Simons gravity model by gauging mixed AdS-AdS Lie algebra and show that it has a two dimensional conformal field theory (CFT) at the boundary of the anti de Sitter (AdS) solution. We show that the central charge of the dual CFT is proportional to the mass of the AdS solution. We also study cosmological implications of our massless bi-gravity model.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

PubMed

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

Horizontal mixing coefficients for two-dimensional chemical models calculated from National Meteorological Center Data

NASA Technical Reports Server (NTRS)

Newman, P. A.; Schoeberl, M. R.; Plumb, R. A.

1986-01-01

Calculations of the two-dimensional, species-independent mixing coefficients for two-dimensional chemical models for the troposphere and stratosphere are performed using quasi-geostrophic potential vorticity fluxes and gradients from 4 years of National Meteorological Center data for the four seasons in both hemispheres. Results show that the horizontal mixing coefficient values for the winter lower stratosphere are broadly consistent with those currently employed in two-dimensional models, but the horizontal mixing coefficient values in the northern winter upper stratosphere are much larger than those usually used.

a Speculative Study on Negative-Dimensional Potential and Wave Problems by Implicit Calculus Modeling Approach

NASA Astrophysics Data System (ADS)

Chen, Wen; Wang, Fajie

Based on the implicit calculus equation modeling approach, this paper proposes a speculative concept of the potential and wave operators on negative dimensionality. Unlike the standard partial differential equation (PDE) modeling, the implicit calculus modeling approach does not require the explicit expression of the PDE governing equation. Instead the fundamental solution of physical problem is used to implicitly define the differential operator and to implement simulation in conjunction with the appropriate boundary conditions. In this study, we conjecture an extension of the fundamental solution of the standard Laplace and Helmholtz equations to negative dimensionality. And then by using the singular boundary method, a recent boundary discretization technique, we investigate the potential and wave problems using the fundamental solution on negative dimensionality. Numerical experiments reveal that the physics behaviors on negative dimensionality may differ on positive dimensionality. This speculative study might open an unexplored territory in research.

REGULARIZATION FOR COX'S PROPORTIONAL HAZARDS MODEL WITH NP-DIMENSIONALITY.

PubMed

Bradic, Jelena; Fan, Jianqing; Jiang, Jiancheng

2011-01-01

High throughput genetic sequencing arrays with thousands of measurements per sample and a great amount of related censored clinical data have increased demanding need for better measurement specific model selection. In this paper we establish strong oracle properties of non-concave penalized methods for non-polynomial (NP) dimensional data with censoring in the framework of Cox's proportional hazards model. A class of folded-concave penalties are employed and both LASSO and SCAD are discussed specifically. We unveil the question under which dimensionality and correlation restrictions can an oracle estimator be constructed and grasped. It is demonstrated that non-concave penalties lead to significant reduction of the "irrepresentable condition" needed for LASSO model selection consistency. The large deviation result for martingales, bearing interests of its own, is developed for characterizing the strong oracle property. Moreover, the non-concave regularized estimator, is shown to achieve asymptotically the information bound of the oracle estimator. A coordinate-wise algorithm is developed for finding the grid of solution paths for penalized hazard regression problems, and its performance is evaluated on simulated and gene association study examples.

Two-dimensional Ising model on random lattices with constant coordination number

NASA Astrophysics Data System (ADS)

Schrauth, Manuel; Richter, Julian A. J.; Portela, Jefferson S. E.

2018-02-01

We study the two-dimensional Ising model on networks with quenched topological (connectivity) disorder. In particular, we construct random lattices of constant coordination number and perform large-scale Monte Carlo simulations in order to obtain critical exponents using finite-size scaling relations. We find disorder-dependent effective critical exponents, similar to diluted models, showing thus no clear universal behavior. Considering the very recent results for the two-dimensional Ising model on proximity graphs and the coordination number correlation analysis suggested by Barghathi and Vojta [Phys. Rev. Lett. 113, 120602 (2014), 10.1103/PhysRevLett.113.120602], our results indicate that the planarity and connectedness of the lattice play an important role on deciding whether the phase transition is stable against quenched topological disorder.

Three-dimensional light-tissue interaction models for bioluminescence tomography

NASA Astrophysics Data System (ADS)

Côté, D.; Allard, M.; Henkelman, R. M.; Vitkin, I. A.

2005-09-01

Many diagnostic and therapeutic approaches in medical physics today take advantage of the unique properties of light and its interaction with tissues. Because light scatters in tissue, our ability to develop these techniques depends critically on our knowledge of the distribution of light in tissue. Solutions to the diffusion equation can provide such information, but often lack the flexibility required for more general problems that involve, for instance, inhomogeneous optical properties, light polarization, arbitrary three-dimensional geometries, or arbitrary scattering. Monte Carlo techniques, which statistically sample the light distribution in tissue, offer a better alternative to analytical models. First, we discuss our implementation of a validated three-dimensional polarization-sensitive Monte Carlo algorithm and demonstrate its generality with respect to the geometry and scattering models it can treat. Second, we apply our model to bioluminescence tomography. After appropriate genetic modifications to cell lines, bioluminescence can be used as an indicator of cell activity, and is often used to study tumour growth and treatment in animal models. However, the amount of light escaping the animal is strongly dependent on the position and size of the tumour. Using forward models and structural data from magnetic resonance imaging, we show how the models can help to determine the location and size of tumour made of bioluminescent cancer cells in the brain of a mouse.

Three-Dimensional Transgenic Cell Models to Quantify Space Genotoxic Effects

NASA Technical Reports Server (NTRS)

Gonda, S.; Wu, H.; Pingerelli, P.; Glickman, B.

2000-01-01

In this paper we describe a three-dimensional, multicellular tissue-equivalent model, produced in NASA-designed, rotating wall bioreactors using mammalian cells engineered for genomic containment of mUltiple copies of defined target genes for genotoxic assessment. The Rat 2(lambda) fibroblasts (Stratagene, Inc.) were genetically engineered to contain high-density target genes for mutagenesis. Stable three-dimensional, multicellular spheroids were formed when human mammary epithelial cells and Rat 2(lambda) fibroblasts were cocultured on Cytodex 3 Beads in a rotating wall bioreactor. The utility of this spheroidal model for genotoxic assessment was indicated by a linear dose response curve and by results of gene sequence analysis of mutant clones from 400micron diameter spheroids following low-dose, high-energy, neon radiation exposure

A THREE-DIMENSIONAL MODEL ASSESSMENT OF THE GLOBAL DISTRIBUTION OF HEXACHLOROBENZENE

EPA Science Inventory

The distributions of persistent organic pollutants (POPs) in the global environment have been studied typically with box/fugacity models with simplified treatments of atmospheric transport processes1. Such models are incapable of simulating the complex three-dimensional mechanis...

Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks.

PubMed

Xue, Hongqi; Wu, Shuang; Wu, Yichao; Ramirez Idarraga, Juan C; Wu, Hulin

2018-05-02

Mechanism-driven low-dimensional ordinary differential equation (ODE) models are often used to model viral dynamics at cellular levels and epidemics of infectious diseases. However, low-dimensional mechanism-based ODE models are limited for modeling infectious diseases at molecular levels such as transcriptomic or proteomic levels, which is critical to understand pathogenesis of diseases. Although linear ODE models have been proposed for gene regulatory networks (GRNs), nonlinear regulations are common in GRNs. The reconstruction of large-scale nonlinear networks from time-course gene expression data remains an unresolved issue. Here, we use high-dimensional nonlinear additive ODEs to model GRNs and propose a 4-step procedure to efficiently perform variable selection for nonlinear ODEs. To tackle the challenge of high dimensionality, we couple the 2-stage smoothing-based estimation method for ODEs and a nonlinear independence screening method to perform variable selection for the nonlinear ODE models. We have shown that our method possesses the sure screening property and it can handle problems with non-polynomial dimensionality. Numerical performance of the proposed method is illustrated with simulated data and a real data example for identifying the dynamic GRN of Saccharomyces cerevisiae. Copyright © 2018 John Wiley & Sons, Ltd.

Escherichia coli growth under modeled reduced gravity

NASA Technical Reports Server (NTRS)

Baker, Paul W.; Meyer, Michelle L.; Leff, Laura G.

2004-01-01

Bacteria exhibit varying responses to modeled reduced gravity that can be simulated by clino-rotation. When Escherichia coli was subjected to different rotation speeds during clino-rotation, significant differences between modeled reduced gravity and normal gravity controls were observed only at higher speeds (30-50 rpm). There was no apparent affect of removing samples on the results obtained. When E. coli was grown in minimal medium (at 40 rpm), cell size was not affected by modeled reduced gravity and there were few differences in cell numbers. However, in higher nutrient conditions (i.e., dilute nutrient broth), total cell numbers were higher and cells were smaller under reduced gravity compared to normal gravity controls. Overall, the responses to modeled reduced gravity varied with nutrient conditions; larger surface to volume ratios may help compensate for the zone of nutrient depletion around the cells under modeled reduced gravity.

Three-dimensional face model reproduction method using multiview images

NASA Astrophysics Data System (ADS)

Nagashima, Yoshio; Agawa, Hiroshi; Kishino, Fumio

1991-11-01

This paper describes a method of reproducing three-dimensional face models using multi-view images for a virtual space teleconferencing system that achieves a realistic visual presence for teleconferencing. The goal of this research, as an integral component of a virtual space teleconferencing system, is to generate a three-dimensional face model from facial images, synthesize images of the model virtually viewed from different angles, and with natural shadow to suit the lighting conditions of the virtual space. The proposed method is as follows: first, front and side view images of the human face are taken by TV cameras. The 3D data of facial feature points are obtained from front- and side-views by an image processing technique based on the color, shape, and correlation of face components. Using these 3D data, the prepared base face models, representing typical Japanese male and female faces, are modified to approximate the input facial image. The personal face model, representing the individual character, is then reproduced. Next, an oblique view image is taken by TV camera. The feature points of the oblique view image are extracted using the same image processing technique. A more precise personal model is reproduced by fitting the boundary of the personal face model to the boundary of the oblique view image. The modified boundary of the personal face model is determined by using face direction, namely rotation angle, which is detected based on the extracted feature points. After the 3D model is established, the new images are synthesized by mapping facial texture onto the model.

Three-dimensional modeling of plasma edge transport and divertor fluxes during application of resonant magnetic perturbations on ITER

NASA Astrophysics Data System (ADS)

Schmitz, O.; Becoulet, M.; Cahyna, P.; Evans, T. E.; Feng, Y.; Frerichs, H.; Loarte, A.; Pitts, R. A.; Reiser, D.; Fenstermacher, M. E.; Harting, D.; Kirschner, A.; Kukushkin, A.; Lunt, T.; Saibene, G.; Reiter, D.; Samm, U.; Wiesen, S.

2016-06-01

Results from three-dimensional modeling of plasma edge transport and plasma-wall interactions during application of resonant magnetic perturbation (RMP) fields for control of edge-localized modes in the ITER standard 15 MA Q  =  10 H-mode are presented. The full 3D plasma fluid and kinetic neutral transport code EMC3-EIRENE is used for the modeling. Four characteristic perturbed magnetic topologies are considered and discussed with reference to the axisymmetric case without RMP fields. Two perturbation field amplitudes at full and half of the ITER ELM control coil current capability using the vacuum approximation are compared to a case including a strongly screening plasma response. In addition, a vacuum field case at high q 95  =  4.2 featuring increased magnetic shear has been modeled. Formation of a three-dimensional plasma boundary is seen for all four perturbed magnetic topologies. The resonant field amplitudes and the effective radial magnetic field at the separatrix define the shape and extension of the 3D plasma boundary. Opening of the magnetic field lines from inside the separatrix establishes scrape-off layer-like channels of direct parallel particle and heat flux towards the divertor yielding a reduction of the main plasma thermal and particle confinement. This impact on confinement is most accentuated at full RMP current and is strongly reduced when screened RMP fields are considered, as well as for the reduced coil current cases. The divertor fluxes are redirected into a three-dimensional pattern of helical magnetic footprints on the divertor target tiles. At maximum perturbation strength, these fingers stretch out as far as 60 cm across the divertor targets, yielding heat flux spreading and the reduction of peak heat fluxes by 30%. However, at the same time substantial and highly localized heat fluxes reach divertor areas well outside of the axisymmetric heat flux decay profile. Reduced RMP amplitudes due to screening or reduced RMP

Three-dimensional radiation transfer modeling in a dicotyledon leaf

NASA Astrophysics Data System (ADS)

Govaerts, Yves M.; Jacquemoud, Stéphane; Verstraete, Michel M.; Ustin, Susan L.

1996-11-01

The propagation of light in a typical dicotyledon leaf is investigated with a new Monte Carlo ray-tracing model. The three-dimensional internal cellular structure of the various leaf tissues, including the epidermis, the palisade parenchyma, and the spongy mesophyll, is explicitly described. Cells of different tissues are assigned appropriate morphologies and contain realistic amounts of water and chlorophyll. Each cell constituent is characterized by an index of refraction and an absorption coefficient. The objective of this study is to investigate how the internal three-dimensional structure of the tissues and the optical properties of cell constituents control the reflectance and transmittance of the leaf. Model results compare favorably with laboratory observations. The influence of the roughness of the epidermis on the reflection and absorption of light is investigated, and simulation results confirm that convex cells in the epidermis focus light on the palisade parenchyma and increase the absorption of radiation.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied. PMID:22661790

Application of N-Doped Three-Dimensional Reduced Graphene Oxide Aerogel to Thin Film Loudspeaker.

PubMed

Kim, Choong Sun; Lee, Kyung Eun; Lee, Jung-Min; Kim, Sang Ouk; Cho, Byung Jin; Choi, Jung-Woo

2016-08-31

We built a thermoacoustic loudspeaker employing N-doped three-dimensional reduced graphene oxide aerogel (N-rGOA) based on a simple template-free fabrication method. A two-step fabrication process, which includes freeze-drying and reduction/doping, was used to realize a three-dimensional, freestanding, and porous graphene-based loudspeaker, whose macroscopic structure can be easily modulated. The simplified fabrication process also allows the control of structural properties of the N-rGOAs, including density and area. Taking advantage of the facile fabrication process, we fabricated and analyzed thermoacoustic loudspeakers with different structural properties. The anlayses showed that a N-rGOA with lower density and larger area can produce a higher sound pressure level (SPL). Furthermore, the resistance of the proposed loudspeaker can be easily controlled through heteroatom doping, thereby helping to generate higher SPL per unit driving voltage. Our success in constructing an array of optimized N-rGOAs able to withstand input power as high as 40 W demonstrates that a practical thermoacoustic loudspeaker can be fabricated using the proposed mass-producible solution-based process.

Three-dimensional vortex-induced vibrations of supported pipes conveying fluid based on wake oscillator models

NASA Astrophysics Data System (ADS)

Wang, L.; Jiang, T. L.; Dai, H. L.; Ni, Q.

2018-05-01

The present study develops a new three-dimensional nonlinear model for investigating vortex-induced vibrations (VIV) of flexible pipes conveying internal fluid flow. The unsteady hydrodynamic forces associated with the wake dynamics are modeled by two distributed van der Pol wake oscillators. In particular, the nonlinear partial differential equations of motion of the pipe and the wake are derived, taking into account the coupling between the structure and the fluid. The nonlinear equations of motion for the coupled system are then discretized by means of the Galerkin technique, resulting in a high-dimensional reduced-order model of the system. It is shown that the natural frequencies for in-plane and out-of-plane motions of the pipe may be different at high internal flow velocities beyond the threshold of buckling instability. The orientation angle of the postbuckling configuration is time-varying due to the disturbance of hydrodynamic forces, thus yielding sometimes unexpected results. For a buckled pipe with relatively low cross-flow velocity, interestingly, examining the nonlinear dynamics of the pipe indicates that the combined effects of the cross-flow-induced resonance of the in-plane first mode and the internal-flow-induced buckling on the IL and CF oscillation amplitudes may be significant. For higher cross-flow velocities, however, the effect of internal fluid flow on the nonlinear VIV responses of the pipe is not pronounced.

[Three-dimensional morphological modeling and visualization of wheat root system].

PubMed

Tan, Feng; Tang, Liang; Hu, Jun-Cheng; Jiang, Hai-Yan; Cao, Wei-Xing; Zhu, Yan

2011-01-01

Crop three-dimensional (3D) morphological modeling and visualization is an important part of digital plant study. This paper aimed to develop a 3D morphological model of wheat root system based on the parameters of wheat root morphological features, and to realize the visualization of wheat root growth. According to the framework of visualization technology for wheat root growth, a 3D visualization model of wheat root axis, including root axis growth model, branch geometric model, and root axis curve model, was developed firstly. Then, by integrating root topology, the corresponding pixel was determined, and the whole wheat root system was three-dimensionally re-constructed by using the morphological feature parameters in the root morphological model. Finally, based on the platform of OpenGL, and by integrating the technologies of texture mapping, lighting rendering, and collision detection, the 3D visualization of wheat root growth was realized. The 3D output of wheat root system from the model was vivid, which could realize the 3D root system visualization of different wheat cultivars under different water regimes and nitrogen application rates. This study could lay a technical foundation for further development of an integral visualization system of wheat plant.

Three-dimensional Myoblast Aggregates--Effects of Modeled Microgravity

NASA Technical Reports Server (NTRS)

Byerly, Diane; Sognier, M. A.; Marquette, M. L.

2006-01-01

The overall objective of these studies is to elucidate the molecular and cellular alterations that contribute to muscle atrophy in astronauts caused by exposure to microgravity conditions in space. To accomplish this, a three-dimensional model test system was developed using mouse myoblast cells (C2C12). Myoblast cells were grown as three-dimensional aggregates (without scaffolding or other solid support structures) in both modeled microgravity (Rotary Cell Culture System, Synthecon, Inc.) and at unit gravity in coated Petri dishes. Evaluation of H&E stained thin sections of the aggregates revealed the absence of any necrosis. Confocal microscopy evaluations of cells stained with the Live/Dead assay (Molecular Probes) confirmed that viable cells were present throughout the aggregates with an average of only three dead cells observed per aggregate. Preliminary results from gene array analysis (Affymetrix chip U74Av2) showed that approximately 14% of the genes were down regulated (decreased more than 3 fold) and 4% were upregulated in cells exposed to modeled microgravity for 12 hours compared to unit gravity controls. Additional studies using fluorescent phallacidin revealed a decrease in F-actin in the cells exposed to modeled microgravity compared to unit gravity. Myoblast cells grown as aggregates in modeled microgravity exhibited spontaneous differentiation into syncitia while no differentiation was seen in the unit gravity controls. These studies show that 1)the model test system developed is suitable for assessing cellular and molecular alterations in myoblasts; 2) gene expression alterations occur rapidly (within 12 hours) following exposure to modeled microgravity; and 3) modeled microgravity conditions stimulated myoblast cell differentiation. Achieving a greater understanding of the molecular alterations leading to muscle atrophy will eventually enable the development of cell-based countermeasures, which may be valuable for treatment of muscle diseases on

High dimensional linear regression models under long memory dependence and measurement error

NASA Astrophysics Data System (ADS)

Kaul, Abhishek

This dissertation consists of three chapters. The first chapter introduces the models under consideration and motivates problems of interest. A brief literature review is also provided in this chapter. The second chapter investigates the properties of Lasso under long range dependent model errors. Lasso is a computationally efficient approach to model selection and estimation, and its properties are well studied when the regression errors are independent and identically distributed. We study the case, where the regression errors form a long memory moving average process. We establish a finite sample oracle inequality for the Lasso solution. We then show the asymptotic sign consistency in this setup. These results are established in the high dimensional setup (p> n) where p can be increasing exponentially with n. Finally, we show the consistency, n½ --d-consistency of Lasso, along with the oracle property of adaptive Lasso, in the case where p is fixed. Here d is the memory parameter of the stationary error sequence. The performance of Lasso is also analysed in the present setup with a simulation study. The third chapter proposes and investigates the properties of a penalized quantile based estimator for measurement error models. Standard formulations of prediction problems in high dimension regression models assume the availability of fully observed covariates and sub-Gaussian and homogeneous model errors. This makes these methods inapplicable to measurement errors models where covariates are unobservable and observations are possibly non sub-Gaussian and heterogeneous. We propose weighted penalized corrected quantile estimators for the regression parameter vector in linear regression models with additive measurement errors, where unobservable covariates are nonrandom. The proposed estimators forgo the need for the above mentioned model assumptions. We study these estimators in both the fixed dimension and high dimensional sparse setups, in the latter setup, the

Galactic Cosmic-ray Transport in the Global Heliosphere: A Four-Dimensional Stochastic Model

NASA Astrophysics Data System (ADS)

Florinski, V.

2009-04-01

We study galactic cosmic-ray transport in the outer heliosphere and heliosheath using a newly developed transport model based on stochastic integration of the phase-space trajectories of Parker's equation. The model employs backward integration of the diffusion-convection transport equation using Ito calculus and is four-dimensional in space+momentum. We apply the model to the problem of galactic proton transport in the heliosphere during a negative solar minimum. Model results are compared with the Voyager measurements of galactic proton radial gradients and spectra in the heliosheath. We show that the heliosheath is not as efficient in diverting cosmic rays during solar minima as predicted by earlier two-dimensional models.

[Three dimensional finite element model of a modified posterior cervical single open-door laminoplasty].

PubMed

Wang, Q; Yang, Y; Fei, Q; Li, D; Li, J J; Meng, H; Su, N; Fan, Z H; Wang, B Q

2017-06-06

Objective: To build a three-dimensional finite element models of a modified posterior cervical single open-door laminoplasty with short-segmental lateral mass screws fusion. Methods: The C(2)-C(7) segmental data were obtained from computed tomography (CT) scans of a male patient with cervical spondylotic myelopathy and spinal stenosis.Three-dimensional finite element models of a modified cervical single open-door laminoplasty (before and after surgery) were constructed by the combination of software package MIMICS, Geomagic and ABAQUS.The models were composed of bony vertebrae, articulating facets, intervertebral disc and associated ligaments.The loads of moments 1.5Nm at different directions (flexion, extension, lateral bending and axial rotation)were applied at preoperative model to calculate intersegmental ranges of motion.The results were compared with the previous studies to verify the validation of the models. Results: Three-dimensional finite element models of the modified cervical single open- door laminoplasty had 102258 elements (preoperative model) and 161 892 elements (postoperative model) respectively, including C(2-7) six bony vertebraes, C(2-3)-C(6-7) five intervertebral disc, main ligaments and lateral mass screws.The intersegmental responses at the preoperative model under the loads of moments 1.5 Nm at different directions were similar to the previous published data. Conclusion: Three-dimensional finite element models of the modified cervical single open- door laminoplasty were successfully established and had a good biological fidelity, which can be used for further study.

Validating two-dimensional leadership models on three-dimensionally structured fish schools

PubMed Central

Nagy, Máté; Holbrook, Robert I.; Biro, Dora; Burt de Perera, Theresa

2017-01-01

Identifying leader–follower interactions is crucial for understanding how a group decides where or when to move, and how this information is transferred between members. Although many animal groups have a three-dimensional structure, previous studies investigating leader–follower interactions have often ignored vertical information. This raises the question of whether commonly used two-dimensional leader–follower analyses can be used justifiably on groups that interact in three dimensions. To address this, we quantified the individual movements of banded tetra fish (Astyanax mexicanus) within shoals by computing the three-dimensional trajectories of all individuals using a stereo-camera technique. We used these data firstly to identify and compare leader–follower interactions in two and three dimensions, and secondly to analyse leadership with respect to an individual's spatial position in three dimensions. We show that for 95% of all pairwise interactions leadership identified through two-dimensional analysis matches that identified through three-dimensional analysis, and we reveal that fish attend to the same shoalmates for vertical information as they do for horizontal information. Our results therefore highlight that three-dimensional analyses are not always required to identify leader–follower relationships in species that move freely in three dimensions. We discuss our results in terms of the importance of taking species' sensory capacities into account when studying interaction networks within groups. PMID:28280582

Helicity moduli of three-dimensional dilute XY models

NASA Astrophysics Data System (ADS)

Garg, Anupam; Pandit, Rahul; Solla, Sara A.; Ebner, C.

1984-07-01

The helicity moduli of various dilute, classical XY models on three-dimensional lattices are studied with a view to understanding some aspects of the superfluidity of 4He in Vycor glass. A spinwave calculation is used to obtain the low-temperature helicity modulus of a regularly-diluted XY model. A similar calculation is performed for the randomly bond-diluted and site-diluted XY models in the limit of low dilution. A Monte Carlo simulation is used to obtain the helicity modulus of the randomly bond-diluted XY model over a wide range of temperature and dilution. It is found that the randomly diluted models do agree and the regularly diluted model does not agree with certain experimentally found features of the variation in superfluid fraction with coverage of 4He in Vycor glass.

A perspective on bridging scales and design of models using low-dimensional manifolds and data-driven model inference

PubMed Central

Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David

2016-01-01

Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698038

Evaluation of one dimensional analytical models for vegetation canopies

NASA Technical Reports Server (NTRS)

Goel, Narendra S.; Kuusk, Andres

1992-01-01

The SAIL model for one-dimensional homogeneous vegetation canopies has been modified to include the specular reflectance and hot spot effects. This modified model and the Nilson-Kuusk model are evaluated by comparing the reflectances given by them against those given by a radiosity-based computer model, Diana, for a set of canopies, characterized by different leaf area index (LAI) and leaf angle distribution (LAD). It is shown that for homogeneous canopies, the analytical models are generally quite accurate in the visible region, but not in the infrared region. For architecturally realistic heterogeneous canopies of the type found in nature, these models fall short. These shortcomings are quantified.

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

PubMed Central

Cowley, Benjamin R.; Doiron, Brent; Kohn, Adam

2016-01-01

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure. PMID:27926936

Three-dimensional discrete-time Lotka-Volterra models with an application to industrial clusters

NASA Astrophysics Data System (ADS)

Bischi, G. I.; Tramontana, F.

2010-10-01

We consider a three-dimensional discrete dynamical system that describes an application to economics of a generalization of the Lotka-Volterra prey-predator model. The dynamic model proposed is used to describe the interactions among industrial clusters (or districts), following a suggestion given by [23]. After studying some local and global properties and bifurcations in bidimensional Lotka-Volterra maps, by numerical explorations we show how some of them can be extended to their three-dimensional counterparts, even if their analytic and geometric characterization becomes much more difficult and challenging. We also show a global bifurcation of the three-dimensional system that has no two-dimensional analogue. Besides the particular economic application considered, the study of the discrete version of Lotka-Volterra dynamical systems turns out to be a quite rich and interesting topic by itself, i.e. from a purely mathematical point of view.

Modeling the effect of mood on dimensional attention during categorization.

PubMed

Zivot, Matthew T; Cohen, Andrew L; Kapucu, Aycan

2013-08-01

Classification is a flexible process that can be affected by mood. The goal of this paper is to evaluate the idea that mood may modulate categorization behavior through an attentional weighting mechanism in which mood changes the attention afforded to different stimulus dimensions. In two experiments, participants learn and are tested on categories while in a calm or sad mood. In Experiment 1, sad participants are faster to learn one- and two-dimensional category structures, but show no advantage on a three-dimensional category structure. In Experiment 2, the generalized context model of categorization is used to measure dimensional weighting. The results suggest that sad participants have a narrower focus of attention, but that the narrowing tends to be on diagnostic dimensions. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Model-Free Conditional Independence Feature Screening For Ultrahigh Dimensional Data.

PubMed

Wang, Luheng; Liu, Jingyuan; Li, Yong; Li, Runze

2017-03-01

Feature screening plays an important role in ultrahigh dimensional data analysis. This paper is concerned with conditional feature screening when one is interested in detecting the association between the response and ultrahigh dimensional predictors (e.g., genetic makers) given a low-dimensional exposure variable (such as clinical variables or environmental variables). To this end, we first propose a new index to measure conditional independence, and further develop a conditional screening procedure based on the newly proposed index. We systematically study the theoretical property of the proposed procedure and establish the sure screening and ranking consistency properties under some very mild conditions. The newly proposed screening procedure enjoys some appealing properties. (a) It is model-free in that its implementation does not require a specification on the model structure; (b) it is robust to heavy-tailed distributions or outliers in both directions of response and predictors; and (c) it can deal with both feature screening and the conditional screening in a unified way. We study the finite sample performance of the proposed procedure by Monte Carlo simulations and further illustrate the proposed method through two real data examples.

Three-dimensional modeling of flexible pavements : executive summary, August 2001.

DOT National Transportation Integrated Search

2001-08-01

A linear viscoelastic model has been incorporated into a three-dimensional finite element program for analysis of flexible pavements. Linear and quadratic versions of hexahedral elements and quadrilateral axisymmetrix elements are provided. Dynamic p...

Three dimensional modeling of flexible pavements : final report, March 2002.

DOT National Transportation Integrated Search

2001-08-01

A linear viscoelastic model has been incorporated into a three-dimensional finite element program for analysis of flexible pavements. Linear and quadratic versions of hexahedral elements and quadrilateral axisymmetrix elements are provided. Dynamic p...

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

NASA Astrophysics Data System (ADS)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Innovation Rather than Improvement: A Solvable High-Dimensional Model Highlights the Limitations of Scalar Fitness

NASA Astrophysics Data System (ADS)

Tikhonov, Mikhail; Monasson, Remi

2018-01-01

Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.

Incorporating 3-dimensional models in online articles.

PubMed

Cevidanes, Lucia H S; Ruellas, Antonio C O; Jomier, Julien; Nguyen, Tung; Pieper, Steve; Budin, Francois; Styner, Martin; Paniagua, Beatriz

2015-05-01

The aims of this article are to introduce the capability to view and interact with 3-dimensional (3D) surface models in online publications, and to describe how to prepare surface models for such online 3D visualizations. Three-dimensional image analysis methods include image acquisition, construction of surface models, registration in a common coordinate system, visualization of overlays, and quantification of changes. Cone-beam computed tomography scans were acquired as volumetric images that can be visualized as 3D projected images or used to construct polygonal meshes or surfaces of specific anatomic structures of interest. The anatomic structures of interest in the scans can be labeled with color (3D volumetric label maps), and then the scans are registered in a common coordinate system using a target region as the reference. The registered 3D volumetric label maps can be saved in .obj, .ply, .stl, or .vtk file formats and used for overlays, quantification of differences in each of the 3 planes of space, or color-coded graphic displays of 3D surface distances. All registered 3D surface models in this study were saved in .vtk file format and loaded in the Elsevier 3D viewer. In this study, we describe possible ways to visualize the surface models constructed from cone-beam computed tomography images using 2D and 3D figures. The 3D surface models are available in the article's online version for viewing and downloading using the reader's software of choice. These 3D graphic displays are represented in the print version as 2D snapshots. Overlays and color-coded distance maps can be displayed using the reader's software of choice, allowing graphic assessment of the location and direction of changes or morphologic differences relative to the structure of reference. The interpretation of 3D overlays and quantitative color-coded maps requires basic knowledge of 3D image analysis. When submitting manuscripts, authors can now upload 3D models that will allow readers to

Multi-Dimensional Calibration of Impact Dynamic Models

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.; Annett, Martin S.; Jackson, Karen E.

2011-01-01

NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data.

Limitations to the use of two-dimensional thermal modeling of a nuclear waste repository

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

Davis, B.W.

1979-01-04

Thermal modeling of a nuclear waste repository is basic to most waste management predictive models. It is important that the modeling techniques accurately determine the time-dependent temperature distribution of the waste emplacement media. Recent modeling studies show that the time-dependent temperature distribution can be accurately modeled in the far-field using a 2-dimensional (2-D) planar numerical model; however, the near-field cannot be modeled accurately enough by either 2-D axisymmetric or 2-D planar numerical models for repositories in salt. The accuracy limits of 2-D modeling were defined by comparing results from 3-dimensional (3-D) TRUMP modeling with results from both 2-D axisymmetric andmore » 2-D planar. Both TRUMP and ADINAT were employed as modeling tools. Two-dimensional results from the finite element code, ADINAT were compared with 2-D results from the finite difference code, TRUMP; they showed almost perfect correspondence in the far-field. This result adds substantially to confidence in future use of ADINAT and its companion stress code ADINA for thermal stress analysis. ADINAT was found to be somewhat sensitive to time step and mesh aspect ratio. 13 figures, 4 tables.« less

One-dimensional bubble model of pulsed discharge in water

NASA Astrophysics Data System (ADS)

Lu, XinPei

2007-09-01

In this paper, a one-dimensional bubble model of pulsed discharge in water is presented. With a total input energy of 0.63J, the simulation results show that when the bubble collapses at the center of the bubble, the plasma pressure oscillates strongly. It oscillates between 800 and 1150atm with an oscillation frequency of about 6.9MHz, while at r =R/2 (R: bubble radius), the gas velocity oscillates intensely at the same frequency. It oscillates between -235 and 229m/s when the bubble radius reaches its minimum. But it does not oscillate at r =R because of the inertia of the surrounding water. The bubble collapses and reexpands with almost the same speed as that of the zero-dimensional (0D) model. This further confirms why the shock wave pressure from the 0D mode has a good agreement with the experimental results since the shock wave pressure is only determined by the bubble wall velocity v(R ).

Two-Dimensional Mathematical Modeling of the Pack Carburizing Process

NASA Astrophysics Data System (ADS)

Sarkar, S.; Gupta, G. S.

2008-10-01

Pack carburization is the oldest method among the case-hardening treatments, and sufficient attempts have not been made to understand this process in terms of heat and mass transfer, effect of alloying elements, dimensions of the sample, etc. Thus, a two-dimensional mathematical model in cylindrical coordinate is developed for simulating the pack carburization process for chromium-bearing steel in this study. Heat and mass balance equations are solved simultaneously, where the surface temperature of the sample varies with time, but the carbon potential at the surface during the process remains constant. The fully implicit finite volume technique is used to solve the governing equations. Good agreement has been found between the predicted and published data. The effect of temperature, carburizing time, dimensions of the sample, etc. on the pack carburizing process shows some interesting results. It is found that the two-dimensional model gives better insight into understanding the carburizing process.

A three-dimensional model to assess the effect of ankle joint axis misalignments in ankle-foot orthoses.

PubMed

Fatone, Stefania; Johnson, William Brett; Tucker, Kerice

2016-04-01

Misalignment of an articulated ankle-foot orthosis joint axis with the anatomic joint axis may lead to discomfort, alterations in gait, and tissue damage. Theoretical, two-dimensional models describe the consequences of misalignments, but cannot capture the three-dimensional behavior of ankle-foot orthosis use. The purpose of this project was to develop a model to describe the effects of ankle-foot orthosis ankle joint misalignment in three dimensions. Computational simulation. Three-dimensional scans of a leg and ankle-foot orthosis were incorporated into a link segment model where the ankle-foot orthosis joint axis could be misaligned with the anatomic ankle joint axis. The leg/ankle-foot orthosis interface was modeled as a network of nodes connected by springs to estimate interface pressure. Motion between the leg and ankle-foot orthosis was calculated as the ankle joint moved through a gait cycle. While the three-dimensional model corroborated predictions of the previously published two-dimensional model that misalignments in the anterior -posterior direction would result in greater relative motion compared to misalignments in the proximal -distal direction, it provided greater insight showing that misalignments have asymmetrical effects. The three-dimensional model has been incorporated into a freely available computer program to assist others in understanding the consequences of joint misalignments. Models and simulations can be used to gain insight into functioning of systems of interest. We have developed a three-dimensional model to assess the effect of ankle joint axis misalignments in ankle-foot orthoses. The model has been incorporated into a freely available computer program to assist understanding of trainees and others interested in orthotics. © The International Society for Prosthetics and Orthotics 2014.

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

NASA Astrophysics Data System (ADS)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

Reduced Order Modeling Incompressible Flows

NASA Technical Reports Server (NTRS)

Helenbrook, B. T.

2010-01-01

The details: a) Need stable numerical methods; b) Round off error can be considerable; c) Not convinced modes are correct for incompressible flow. Nonetheless, can derive compact and accurate reduced-order models. Can be used to generate actuator models or full flow-field models

Three-dimensional Model of Tissue and Heavy Ions Effects

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; Sundaresan, Alamelu; Huff, Janice L.; Cucinotta, Francis A.

2007-01-01

A three-dimensional tissue model was incorporated into a new Monte Carlo algorithm that simulates passage of heavy ions in a tissue box . The tissue box was given as a realistic model of tissue based on confocal microscopy images. The action of heavy ions on the cellular matrix for 2- or 3-dimensional cases was simulated. Cells were modeled as a cell culture monolayer in one example, where the data were taken directly from microscopy (2-d cell matrix), and as a multi-layer obtained from confocal microscopy (3-d case). Image segmentation was used to identify cells with precise areas/volumes in an irradiated cell culture monolayer, and slices of tissue with many cell layers. The cells were then inserted into the model box of the simulated physical space pixel by pixel. In the case of modeled tissues (3-d), the tissue box had periodic boundary conditions imposed, which extrapolates the technique to macroscopic volumes of tissue. For the real tissue (3-d), specific spatial patterns for cell apoptosis and necrosis are expected. The cell patterns were modeled based on action cross sections for apoptosis and necrosis estimated from current experimental data. A spatial correlation function indicating a higher spatial concentration of damaged cells from heavy ions relative to the low-LET radiation cell damage pattern is presented. The spatial correlation effects among necrotic cells can help studying microlesions in organs, and probable effects of directionality of heavy ion radiation on epithelium and endothelium.

Three-Dimensional Model of Heat and Mass Transfer in Fractured Rocks to Estimate Environmental Conditions Along Heated Drifts

NASA Astrophysics Data System (ADS)

Fedors, R. W.; Painter, S. L.

2004-12-01

Temperature gradients along the thermally-perturbed drifts of the potential high-level waste repository at Yucca Mountain, Nevada, will drive natural convection and associated heat and mass transfer along drifts. A three-dimensional, dual-permeability, thermohydrological model of heat and mass transfer was used to estimate the magnitude of temperature gradients along a drift. Temperature conditions along heated drifts are needed to support estimates of repository-edge cooling and as input to computational fluid dynamics modeling of in-drift axial convection and the cold-trap process. Assumptions associated with abstracted heat transfer models and two-dimensional thermohydrological models weakly coupled to mountain-scale thermal models can readily be tested using the three-dimensional thermohydrological model. Although computationally expensive, the fully coupled three-dimensional thermohydrological model is able to incorporate lateral heat transfer, including host rock processes of conduction, convection in gas phase, advection in liquid phase, and latent-heat transfer. Results from the three-dimensional thermohydrological model showed that weakly coupling three-dimensional thermal and two-dimensional thermohydrological models lead to underestimates of temperatures and underestimates of temperature gradients over large portions of the drift. The representative host rock thermal conductivity needed for abstracted heat transfer models are overestimated using the weakly coupled models. If axial flow patterns over large portions of drifts are not impeded by the strong cross-sectional flow patterns imparted by the heat rising directly off the waste package, condensation from the cold-trap process will not be limited to the extreme ends of each drift. Based on the three-dimensional thermohydrological model, axial temperature gradients occur sooner over a larger portion of the drift, though high gradients nearest the edge of the potential repository are dampened. This

Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

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

Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

Modeling of Unsteady Three-dimensional Flows in Multistage Machines

NASA Technical Reports Server (NTRS)

Hall, Kenneth C.; Pratt, Edmund T., Jr.; Kurkov, Anatole (Technical Monitor)

2003-01-01

Despite many years of development, the accurate and reliable prediction of unsteady aerodynamic forces acting on turbomachinery blades remains less than satisfactory, especially when viewed next to the great success investigators have had in predicting steady flows. Hall and Silkowski (1997) have proposed that one of the main reasons for the discrepancy between theory and experiment and/or industrial experience is that many of the current unsteady aerodynamic theories model a single blade row in an infinitely long duct, ignoring potentially important multistage effects. However, unsteady flows are made up of acoustic, vortical, and entropic waves. These waves provide a mechanism for the rotors and stators of multistage machines to communicate with one another. In other words, wave behavior makes unsteady flows fundamentally a multistage (and three-dimensional) phenomenon. In this research program, we have has as goals (1) the development of computationally efficient computer models of the unsteady aerodynamic response of blade rows embedded in a multistage machine (these models will ultimately be capable of analyzing three-dimensional viscous transonic flows), and (2) the use of these computer codes to study a number of important multistage phenomena.

An Adaptive ANOVA-based PCKF for High-Dimensional Nonlinear Inverse Modeling

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

LI, Weixuan; Lin, Guang; Zhang, Dongxiao

2014-02-01

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect—except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos bases in the expansion helps to capture uncertainty more accurately but increases computational cost. Bases selection is particularly importantmore » for high-dimensional stochastic problems because the number of polynomial chaos bases required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE bases are pre-set based on users’ experience. Also, for sequential data assimilation problems, the bases kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE bases for different problems and automatically adjusts the number of bases in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm is tested with different examples and demonstrated great effectiveness in comparison with non-adaptive PCKF and En

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

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

Li, Weixuan, E-mail: weixuan.li@usc.edu; Lin, Guang, E-mail: guang.lin@pnnl.gov; Zhang, Dongxiao, E-mail: dxz@pku.edu.cn

2014-02-01

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect—except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functionsmore » is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and

Measurement of the Equation of State of the Two-Dimensional Hubbard Model

NASA Astrophysics Data System (ADS)

Miller, Luke; Cocchi, Eugenio; Drewes, Jan; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael

2016-05-01

The subtle interplay between kinetic energy, interactions and dimensionality challenges our comprehension of strongly-correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions, 0 <= U / t <= 20 , and temperatures, down to kB T / t = 0 . 63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities and double occupancies over the whole doping range, and hence our results constitute benchmarks for state-of-the-art theoretical approaches.

Three-Dimensional Printing of a Scalable Molecular Model and Orbital Kit for Organic Chemistry Teaching and Learning

ERIC Educational Resources Information Center

Penny, Matthew R.; Cao, Zi Jing; Patel, Bhaven; dos Santos, Bruno Sil; Asquith, Christopher R. M.; Szulc, Blanka R.; Rao, Zenobia X.; Muwaffak, Zaid; Malkinson, John P.; Hilton, Stephen T.

2017-01-01

Three-dimensional (3D) chemical models are a well-established learning tool used to enhance the understanding of chemical structures by converting two-dimensional paper or screen outputs into realistic three-dimensional objects. While commercial atom model kits are readily available, there is a surprising lack of large molecular and orbital models…

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Two-dimensional random surface model for asperity-contact in elastohydrodynamic lubrication

NASA Technical Reports Server (NTRS)

Coy, J. J.; Sidik, S. M.

1979-01-01

Relations for the asperity-contact time function during elastohydrodynamic lubrication of a ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces are used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately four to five. This thickness ratio is several times large than reported in the literature where one-dimensional random surface models were used. It is shown that low pass filtering of the statistical records will bring agreement between the present results and those in the literature.

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.

Three-dimensional virtual surgery models for percutaneous coronary intervention (PCI) optimization strategies

NASA Astrophysics Data System (ADS)

Wang, Hujun; Liu, Jinghua; Zheng, Xu; Rong, Xiaohui; Zheng, Xuwei; Peng, Hongyu; Silber-Li, Zhanghua; Li, Mujun; Liu, Liyu

2015-06-01

Percutaneous coronary intervention (PCI), especially coronary stent implantation, has been shown to be an effective treatment for coronary artery disease. However, in-stent restenosis is one of the longstanding unsolvable problems following PCI. Although stents implanted inside narrowed vessels recover normal flux of blood flows, they instantaneously change the wall shear stress (WSS) distribution on the vessel surface. Improper stent implantation positions bring high possibilities of restenosis as it enlarges the low WSS regions and subsequently stimulates more epithelial cell outgrowth on vessel walls. To optimize the stent position for lowering the risk of restenosis, we successfully established a digital three-dimensional (3-D) model based on a real clinical coronary artery and analysed the optimal stenting strategies by computational simulation. Via microfabrication and 3-D printing technology, the digital model was also converted into in vitro microfluidic models with 3-D micro channels. Simultaneously, physicians placed real stents inside them; i.e., they performed “virtual surgeries”. The hydrodynamic experimental results showed that the microfluidic models highly inosculated the simulations. Therefore, our study not only demonstrated that the half-cross stenting strategy could maximally reduce restenosis risks but also indicated that 3-D printing combined with clinical image reconstruction is a promising method for future angiocardiopathy research.

Mixed-order phase transition in a one-dimensional model.

PubMed

Bar, Amir; Mukamel, David

2014-01-10

We introduce and analyze an exactly soluble one-dimensional Ising model with long range interactions that exhibits a mixed-order transition, namely a phase transition in which the order parameter is discontinuous as in first order transitions while the correlation length diverges as in second order transitions. Such transitions are known to appear in a diverse classes of models that are seemingly unrelated. The model we present serves as a link between two classes of models that exhibit a mixed-order transition in one dimension, namely, spin models with a coupling constant that decays as the inverse distance squared and models of depinning transitions, thus making a step towards a unifying framework.

Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned…

Identification of Reduced-Order Thermal Therapy Models Using Thermal MR Images: Theory and Validation

PubMed Central

2013-01-01

In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate. PMID:22531754

Identification of reduced-order thermal therapy models using thermal MR images: theory and validation.

PubMed

Niu, Ran; Skliar, Mikhail

2012-07-01

In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate.

Multi-dimensional modelling of gas turbine combustion using a flame sheet model in KIVA II

NASA Technical Reports Server (NTRS)

Cheng, W. K.; Lai, M.-C.; Chue, T.-H.

1991-01-01

A flame sheet model for heat release is incorporated into a multi-dimensional fluid mechanical simulation for gas turbine application. The model assumes that the chemical reaction takes place in thin sheets compared to the length scale of mixing, which is valid for the primary combustion zone in a gas turbine combustor. In this paper, the details of the model are described and computational results are discussed.

Integral formulae of the canonical correlation functions for the one dimensional transverse Ising model

NASA Astrophysics Data System (ADS)

Inoue, Makoto

2017-12-01

Some new formulae of the canonical correlation functions for the one dimensional quantum transverse Ising model are found by the ST-transformation method using a Morita's sum rule and its extensions for the two dimensional classical Ising model. As a consequence we obtain a time-independent term of the dynamical correlation functions. Differences of quantum version and classical version of these formulae are also discussed.

A three-dimensional ring current decay model

NASA Technical Reports Server (NTRS)

Fok, Mei-Ching; Moore, Thomas E.; Kozyra, Janet U.; Ho, George C.; Hamilton, Douglas C.

1994-01-01

This work is an extension of a previous ring current decay model. In the previous work, a two-dimensional kinetic model was constructed to study the temporal variations of the equatorially mirroring ring current ions, considering charge exchange and Coulomb drag losses along drift paths in a magnetic dipole field. In this work, particles with arbitrary pitch angle are considered. By bounce averaging the kinetic equation of the phase space density, information along magnetic field lines can be inferred from the equator. The three-dimensional model is used to simulate the recovery phase of a model great magnetic storm, similar to that which occurred in early February 1986. The initial distribution of ring current ions (at the minimum Dst) is extrapolated to all local times from AMPTE/CCE spacecraft observations on the dawn and dusk sides of the inner magnetosphere spanning the L value range L = 2.25 to 6.75. Observations by AMPTE/CCE of ring current distributions over subsequent orbits during the storm recovery phase are compared to model outputs. In general, the calculated ion fluxes are consistent with observations, except for H+ fluxes at tens of keV, which are always over-estimated. A newly-invented visualization idea, designated as a chromogram, is used to display the spatial and energy dependence of the ring current ion differential flux. Important features of storm-time ring current, such as day-night asymmetry during injection and drift hole on the dayside at low energies (less than 10 keV), are manifested in the chromogram representation. The pitch angle distribution is well fit by the function, j(sub o)(1+Ay(exp n)), where y is sine of the equatorial pitch angle. The evolution of the index n is a combined effect of charge exchange loss and particle drift. At low energies (less than 30 keV), both drift dispersion and charge exchange are important in determining n.

Evaluation of a two-dimensional numerical model for air quality simulation in a street canyon

NASA Astrophysics Data System (ADS)

Okamoto, Shin `Ichi; Lin, Fu Chi; Yamada, Hiroaki; Shiozawa, Kiyoshige

For many urban areas, the most severe air pollution caused by automobile emissions appears along a road surrounded by tall buildings: the so=called street canyon. A practical two-dimensional numerical model has been developed to be applied to this kind of road structure. This model contains two submodels: a wind-field model and a diffusion model based on a Monte Carlo particle scheme. In order to evaluate the predictive performance of this model, an air quality simulation was carried out at three trunk roads in the Tokyo metropolitan area: Nishi-Shimbashi, Aoyama and Kanda-Nishikicho (using SF 6 as a tracer and NO x measurement). Since this model has two-dimensional properties and cannot be used for the parallel wind condition, the perpendicular wind condition was selected for the simulation. The correlation coefficients for the SF 6 and NO x data in Aoyama were 0.67 and 0.62, respectively. When predictive performance of this model is compared with other models, this model is comparable to the SRI model, and superior to the APPS three-dimensional numerical model.

An incompressible two-dimensional multiphase particle-in-cell model for dense particle flows

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

Snider, D.M.; O`Rourke, P.J.; Andrews, M.J.

1997-06-01

A two-dimensional, incompressible, multiphase particle-in-cell (MP-PIC) method is presented for dense particle flows. The numerical technique solves the governing equations of the fluid phase using a continuum model and those of the particle phase using a Lagrangian model. Difficulties associated with calculating interparticle interactions for dense particle flows with volume fractions above 5% have been eliminated by mapping particle properties to a Eulerian grid and then mapping back computed stress tensors to particle positions. This approach utilizes the best of Eulerian/Eulerian continuum models and Eulerian/Lagrangian discrete models. The solution scheme allows for distributions of types, sizes, and density of particles,more » with no numerical diffusion from the Lagrangian particle calculations. The computational method is implicit with respect to pressure, velocity, and volume fraction in the continuum solution thus avoiding courant limits on computational time advancement. MP-PIC simulations are compared with one-dimensional problems that have analytical solutions and with two-dimensional problems for which there are experimental data.« less

Local entanglement entropy of fermions as a marker of quantum phase transition in the one-dimensional Hubbard model

NASA Astrophysics Data System (ADS)

Cha, Min-Chul; Chung, Myung-Hoon

2018-05-01

We study quantum phase transition of interacting fermions by measuring the local entanglement entropy in the one-dimensional Hubbard model. The reduced density matrices for blocks of a few sites are constructed from the ground state wave function in infinite systems by adopting the matrix product state representation where time-evolving block decimations are performed to obtain the lowest energy states. The local entanglement entropy, constructed from the reduced density matrices, as a function of the chemical potential shows clear signatures of the Mott transition. The value of the central charge, numerically determined from the universal properties of the local entanglement entropy, confirms that the transition is caused by the suppression of the charge degrees of freedom.

Three-dimensional lattice Boltzmann model for compressible flows.

PubMed

Sun, Chenghai; Hsu, Andrew T

2003-07-01

A three-dimensional compressible lattice Boltzmann model is formulated on a cubic lattice. A very large particle-velocity set is incorporated in order to enable a greater variation in the mean velocity. Meanwhile, the support set of the equilibrium distribution has only six directions. Therefore, this model can efficiently handle flows over a wide range of Mach numbers and capture shock waves. Due to the simple form of the equilibrium distribution, the fourth-order velocity tensors are not involved in the formulation. Unlike the standard lattice Boltzmann model, no special treatment is required for the homogeneity of fourth-order velocity tensors on square lattices. The Navier-Stokes equations were recovered, using the Chapman-Enskog method from the Bhatnagar-Gross-Krook (BGK) lattice Boltzmann equation. The second-order discretization error of the fluctuation velocity in the macroscopic conservation equation was eliminated by means of a modified collision invariant. The model is suitable for both viscous and inviscid compressible flows with or without shocks. Since the present scheme deals only with the equilibrium distribution that depends only on fluid density, velocity, and internal energy, boundary conditions on curved wall are easily implemented by an extrapolation of macroscopic variables. To verify the scheme for inviscid flows, we have successfully simulated a three-dimensional shock-wave propagation in a box and a normal shock of Mach number 10 over a wedge. As an application to viscous flows, we have simulated a flat plate boundary layer flow, flow over a cylinder, and a transonic flow over a NACA0012 airfoil cascade.

A multi scale multi-dimensional thermo electrochemical modelling of high capacity lithium-ion cells

NASA Astrophysics Data System (ADS)

Tourani, Abbas; White, Peter; Ivey, Paul

2014-06-01

Lithium iron phosphate (LFP) and lithium manganese oxide (LMO) are competitive and complementary to each other as cathode materials for lithium-ion batteries, especially for use in electric vehicles. A multi scale multi-dimensional physic-based model is proposed in this paper to study the thermal behaviour of the two lithium-ion chemistries. The model consists of two sub models, a one dimensional (1D) electrochemical sub model and a two dimensional (2D) thermo-electric sub model, which are coupled and solved concurrently. The 1D model predicts the heat generation rate (Qh) and voltage (V) of the battery cell through different load cycles. The 2D model of the battery cell accounts for temperature distribution and current distribution across the surface of the battery cell. The two cells are examined experimentally through 90 h load cycles including high/low charge/discharge rates. The experimental results are compared with the model results and they are in good agreement. The presented results in this paper verify the cells temperature behaviour at different operating conditions which will lead to the design of a cost effective thermal management system for the battery pack.

[Analysis of a three-dimensional finite element model of atlas and axis complex fracture].

PubMed

Tang, X M; Liu, C; Huang, K; Zhu, G T; Sun, H L; Dai, J; Tian, J W

2018-05-22

Objective: To explored the clinical application of the three-dimensional finite element model of atlantoaxial complex fracture. Methods: A three-dimensional finite element model of cervical spine (FEM/intact) was established by software of Abaqus6.12.On the basis of this model, a three-dimensional finite element model of four types of atlantoaxial complex fracture was established: C(1) fracture (Jefferson)+ C(2) fracture (type Ⅱfracture), Jefferson+ C(2) fracture(type Ⅲfracture), Jefferson+ C(2) fracture(Hangman), Jefferson+ stable C(2) fracture (FEM/fracture). The range of motion under flexion, extension, lateral bending and axial rotation were measured and compared with the model of cervical spine. Results: The three-dimensional finite element model of four types of atlantoaxial complex fracture had the same similarity and profile.The range of motion (ROM) of different segments had different changes.Compared with those in the normal model, the ROM of C(0/1) and C(1/2) in C(1) combined Ⅱ odontoid fracture model in flexion/extension, lateral bending and rotation increased by 57.45%, 29.34%, 48.09% and 95.49%, 88.52%, 36.71%, respectively.The ROM of C(0/1) and C(1/2) in C(1) combined Ⅲodontoid fracture model in flexion/extension, lateral bending and rotation increased by 47.01%, 27.30%, 45.31% and 90.38%, 27.30%, 30.0%.The ROM of C(0/1) and C(1/2) in C(1) combined Hangman fracture model in flexion/extension, lateral bending and rotation increased by 32.68%, 79.34%, 77.62% and 60.53%, 81.20%, 21.48%, respectively.The ROM of C(0/1) and C(1/2) in C(1) combined axis fracture model in flexion/extension, lateral bending and rotation increased by 15.00%, 29.30%, 8.47% and 37.87%, 75.57%, 8.30%, respectively. Conclusions: The three-dimensional finite element model can be used to simulate the biomechanics of atlantoaxial complex fracture.The ROM of atlantoaxial complex fracture is larger than nomal model, which indicates that surgical treatment should be performed.

Validation and application of a two-dimensional model to simulate soil salt transport under mulched drip irrigation

NASA Astrophysics Data System (ADS)

Jiao, Huiqing; Zhao, Chengyi; Sheng, Yu; Chen, Yan; Shi, Jianchu; Li, Baoguo

2017-04-01

Water shortage and soil salinization increasingly become the main constraints for sustainable development of agriculture in Southern Xinjiang, China. Mulched drip irrigation, as a high-efficient water-saving irrigation method, has been widely applied in Southern Xinjiang for cotton production. In order to analyze the reasonability of describing the three-dimensional soil water and salt transport processes under mulched drip irrigation with a relatively simple two-dimensional model, a field experiment was conducted from 2007 to 2015 at Aksu of Southern Xinjiang, and soil water and salt transport processes were simulated through the three-dimensional and two-dimensional models based on COMSOL. Obvious differences were found between three-dimensional and two-dimensional simulations for soil water flow within the early 12 h of irrigation event and for soil salt transport in the area within 15 cm away from drip tubes during the whole irrigation event. The soil water and salt contents simulated by the two-dimensional model, however, agreed well with the mean values between two adjacent emitters simulated by the three-dimensional model, and also coincided with the measurements as corresponding RMSE less than 0.037 cm3 cm-3 and 1.80 g kg-1, indicating that the two-dimensional model was reliable for field irrigation management. Subsequently, the two-dimensional model was applied to simulate the dynamics of soil salinity for five numerical situations and for a widely adopted irrigation pattern in Southern Xinjiang (about 350 mm through mulched drip irrigation during growing season of cotton and total 400 mm through flooding irrigations before sowing and after harvesting). The simulation results indicated that the contribution of transpiration to salt accumulation in root layer was about 75% under mulched drip irrigation. Moreover, flooding irrigations before sowing and after harvesting were of great importance for salt leaching of arable layer, especially in bare strip where

Checking Dimensionality in Item Response Models with Principal Component Analysis on Standardized Residuals

ERIC Educational Resources Information Center

Chou, Yeh-Tai; Wang, Wen-Chung

2010-01-01

Dimensionality is an important assumption in item response theory (IRT). Principal component analysis on standardized residuals has been used to check dimensionality, especially under the family of Rasch models. It has been suggested that an eigenvalue greater than 1.5 for the first eigenvalue signifies a violation of unidimensionality when there…

Uncertainty propagation by using spectral methods: A practical application to a two-dimensional turbulence fluid model

NASA Astrophysics Data System (ADS)

Riva, Fabio; Milanese, Lucio; Ricci, Paolo

2017-10-01

To reduce the computational cost of the uncertainty propagation analysis, which is used to study the impact of input parameter variations on the results of a simulation, a general and simple to apply methodology based on decomposing the solution to the model equations in terms of Chebyshev polynomials is discussed. This methodology, based on the work by Scheffel [Am. J. Comput. Math. 2, 173-193 (2012)], approximates the model equation solution with a semi-analytic expression that depends explicitly on time, spatial coordinates, and input parameters. By employing a weighted residual method, a set of nonlinear algebraic equations for the coefficients appearing in the Chebyshev decomposition is then obtained. The methodology is applied to a two-dimensional Braginskii model used to simulate plasma turbulence in basic plasma physics experiments and in the scrape-off layer of tokamaks, in order to study the impact on the simulation results of the input parameter that describes the parallel losses. The uncertainty that characterizes the time-averaged density gradient lengths, time-averaged densities, and fluctuation density level are evaluated. A reasonable estimate of the uncertainty of these distributions can be obtained with a single reduced-cost simulation.

Reduced-Order Modeling of 3D Rayleigh-Benard Turbulent Convection

NASA Astrophysics Data System (ADS)

Hassanzadeh, Pedram; Grover, Piyush; Nabi, Saleh

2017-11-01

Accurate Reduced-Order Models (ROMs) of turbulent geophysical flows have broad applications in science and engineering; for example, to study the climate system or to perform real-time flow control/optimization in energy systems. Here we focus on 3D Rayleigh-Benard turbulent convection at the Rayleigh number of 106 as a prototype for turbulent geophysical flows, which are dominantly buoyancy driven. The purpose of the study is to evaluate and improve the performance of different model reduction techniques using this setting. One-dimensional ROMs for horizontally averaged temperature are calculated using several methods. Specifically, the Linear Response Function (LRF) of the system is calculated from a large DNS dataset using Dynamic Mode Decomposition (DMD) and Fluctuation-Dissipation Theorem (FDT). The LRF is also calculated using the Green's function method of Hassanzadeh and Kuang (2016, J. Atmos. Sci.), which is based on using numerous forced DNS runs. The performance of these LRFs in estimating the system's response to weak external forcings or controlling the time-mean flow are compared and contrasted. The spectral properties of the LRFs and the scaling of the accuracy with the length of the dataset (for the data-driven methods) are also discussed.

One-dimensional and two-dimensional hydrodynamic modelling derived flow properties: Impacts on aquatic habitat quality predictions

Treesearch

Rohan Benjankar; Daniele Tonina; James McKean

2014-01-01

Studies of the effects of hydrodynamic model dimensionality on simulated flow properties and derived quantities such as aquatic habitat quality are limited. It is important to close this knowledge gap especially now that entire river networks can be mapped at the microhabitat scale due to the advent of point-cloud techniques. This study compares flow properties, such...

Recent Progress in GW-based Methods for Excited-State Calculations of Reduced Dimensional Systems

NASA Astrophysics Data System (ADS)

da Jornada, Felipe H.

2015-03-01

Ab initio calculations of excited-state phenomena within the GW and GW-Bethe-Salpeter equation (GW-BSE) approaches allow one to accurately study the electronic and optical properties of various materials, including systems with reduced dimensionality. However, several challenges arise when dealing with complicated nanostructures where the electronic screening is strongly spatially and directionally dependent. In this talk, we discuss some recent developments to address these issues. First, we turn to the slow convergence of quasiparticle energies and exciton binding energies with respect to k-point sampling. This is very effectively dealt with using a new hybrid sampling scheme, which results in savings of several orders of magnitude in computation time. A new ab initio method is also developed to incorporate substrate screening into GW and GW-BSE calculations. These two methods have been applied to mono- and few-layer MoSe2, and yielded strong environmental dependent behaviors in good agreement with experiment. Other issues that arise in confined systems and materials with reduced dimensionality, such as the effect of the Tamm-Dancoff approximation to GW-BSE, and the calculation of non-radiative exciton lifetime, are also addressed. These developments have been efficiently implemented and successfully applied to real systems in an ab initio framework using the BerkeleyGW package. I would like to acknowledge collaborations with Diana Y. Qiu, Steven G. Louie, Meiyue Shao, Chao Yang, and the experimental groups of M. Crommie and F. Wang. This work was supported by Department of Energy under Contract No. DE-AC02-05CH11231 and by National Science Foundation under Grant No. DMR10-1006184.

A Framework for Dimensionality Assessment for Multidimensional Item Response Models

ERIC Educational Resources Information Center

Svetina, Dubravka; Levy, Roy

2014-01-01

A framework is introduced for considering dimensionality assessment procedures for multidimensional item response models. The framework characterizes procedures in terms of their confirmatory or exploratory approach, parametric or nonparametric assumptions, and applicability to dichotomous, polytomous, and missing data. Popular and emerging…

Three dimensional δf simulations of beams in the SSC

NASA Astrophysics Data System (ADS)

Koga, J.; Tajima, T.; Machida, S.

1993-12-01

A three dimensional δf strong-strong algorithm has been developed to apply to the study of such effects as space charge and beam-beam interaction phenomena in the Superconducting Super Collider (SSC). The algorithm is obtained from the merging of the particle tracking code Simpsons used for 3 dimensional space charge effects and a δf code. The δf method is used to follow the evolution of the non-gaussian part of the beam distribution. The advantages of this method are twofold. First, the Simpsons code utilizes a realistic accelerator model including synchrotron oscillations and energy ramping in 6 dimensional phase space with electromagnetic fields of the beams calculated using a realistic 3 dimensional field solver. Second, the beams are evolving in the fully self-consistent strong-strong sense with finite particle fluctuation noise is greatly reduced as opposed to the weak-strong models where one beam is fixed.

Quasi-one-dimensional Hall physics in the Harper–Hofstadter–Mott model

NASA Astrophysics Data System (ADS)

Kozarski, Filip; Hügel, Dario; Pollet, Lode

2018-04-01

We study the ground-state phase diagram of the strongly interacting Harper–Hofstadter–Mott model at quarter flux on a quasi-one-dimensional lattice consisting of a single magnetic flux quantum in y-direction. In addition to superfluid phases with various density patterns, the ground-state phase diagram features quasi-one-dimensional analogs of fractional quantum Hall phases at fillings ν = 1/2 and 3/2, where the latter is only found thanks to the hopping anisotropy and the quasi-one-dimensional geometry. At integer fillings—where in the full two-dimensional system the ground-state is expected to be gapless—we observe gapped non-degenerate ground-states: at ν = 1 it shows an odd ‘fermionic’ Hall conductance, while the Hall response at ν = 2 consists of the transverse transport of a single particle–hole pair, resulting in a net zero Hall conductance. The results are obtained by exact diagonalization and in the reciprocal mean-field approximation.

One-dimensional Turbulence Models of Type I X-ray Bursts

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

Hou, Chen

Type I X-ray bursts are caused by thermonuclear explosions occurring on the surface of an accreting neutron star in a binary star system. Observations and simulations of these phenomena are of great importance for understanding the fundamental properties of neutron stars and dense matter because the equation of state for cold dense matter can be constrained by the mass-radius relationship of neutron stars. During the bursts, turbulence plays a key role in mixing the fuels and driving the unstable nuclear burning process. This dissertation presents one-dimensional models of photospheric radius expansion bursts with a new approach to simulate turbulent advection.more » Compared with the traditional mixing length theory, the one-dimensional turbulence (ODT) model represents turbulent motions by a sequence of maps that are generated according to a stochastic process. The light curves I obtained with the ODT models are in good agreement with those of the KEPLER model in which the mixing length theory and various diffusive processes are applied. The abundance comparison, however, indicates that the differences in turbulent regions and turbulent diffusivities result in more 12C survival during the bursts in the ODT models, which can make a difference in the superbursts phenomena triggered by unstable carbon burning.« less

Phase Diagrams of Three-Dimensional Anderson and Quantum Percolation Models Using Deep Three-Dimensional Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Mano, Tomohiro; Ohtsuki, Tomi

2017-11-01

The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization-localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. 85, 123706 (2016), 86, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural network. However, in contrast to previous papers in which 2D image recognition was used, we applied 3D image recognition to analyze entire 3D wave functions. We show that a full phase diagram of the disorder-energy plane is obtained once the 3D convolutional neural network has been trained at the band center. We further demonstrate that the full phase diagram for 3D quantum bond and site percolations can be drawn by training the 3D Anderson model at the band center.

Small-angle X-ray scattering tensor tomography: model of the three-dimensional reciprocal-space map, reconstruction algorithm and angular sampling requirements.

PubMed

Liebi, Marianne; Georgiadis, Marios; Kohlbrecher, Joachim; Holler, Mirko; Raabe, Jörg; Usov, Ivan; Menzel, Andreas; Schneider, Philipp; Bunk, Oliver; Guizar-Sicairos, Manuel

2018-01-01

Small-angle X-ray scattering tensor tomography, which allows reconstruction of the local three-dimensional reciprocal-space map within a three-dimensional sample as introduced by Liebi et al. [Nature (2015), 527, 349-352], is described in more detail with regard to the mathematical framework and the optimization algorithm. For the case of trabecular bone samples from vertebrae it is shown that the model of the three-dimensional reciprocal-space map using spherical harmonics can adequately describe the measured data. The method enables the determination of nanostructure orientation and degree of orientation as demonstrated previously in a single momentum transfer q range. This article presents a reconstruction of the complete reciprocal-space map for the case of bone over extended ranges of q. In addition, it is shown that uniform angular sampling and advanced regularization strategies help to reduce the amount of data required.

Discrete elastic model for two-dimensional melting.

PubMed

Lansac, Yves; Glaser, Matthew A; Clark, Noel A

2006-04-01

We present a network model for the study of melting and liquid structure in two dimensions, the first in which the presence and energy of topological defects (dislocations and disclinations) and of geometrical defects (elemental voids) can be independently controlled. Interparticle interaction is via harmonic springs and control is achieved by Monte Carlo moves which springs can either be orientationally "flipped" between particles to generate topological defects, or can be "popped" in force-free shape, to generate geometrical defects. With the geometrical defects suppressed the transition to the liquid phase occurs via disclination unbinding, as described by the Kosterlitz-Thouless-Halperin-Nelson-Young model and found in soft potential two-dimensional (2D) systems, such as the dipole-dipole potential [H. H. von Grünberg, Phys. Rev. Lett. 93, 255703 (2004)]. By contrast, with topological defects suppressed, a disordering transition, the Glaser-Clark condensation of geometrical defects [M. A. Glaser and N. A. Clark, Adv. Chem. Phys. 83, 543 (1993); M. A. Glaser, (Springer-Verlag, Berlin, 1990), Vol. 52, p. 141], produces a state that accurately characterizes the local liquid structure and first-order melting observed in hard-potential 2D systems, such as hard disk and the Weeks-Chandler-Andersen (WCA) potentials (M. A. Glaser and co-workers, see above). Thus both the geometrical and topological defect systems play a role in melting. The present work introduces a system in which the relative roles of topological and geometrical defects and their interactions can be explored. We perform Monte Carlo simulations of this model in the isobaric-isothermal ensemble, and present the phase diagram as well as various thermodynamic, statistical, and structural quantities as a function of the relative populations of geometrical and topological defects. The model exhibits a rich phase behavior including hexagonal and square crystals, expanded crystal, dodecagonal quasicrystal

Sensitivity experiments with a one-dimensional coupled plume - iceflow model

NASA Astrophysics Data System (ADS)

Beckmann, Johanna; Perette, Mahé; Alexander, David; Calov, Reinhard; Ganopolski, Andrey

2016-04-01

Over the last few decades Greenland Ice sheet mass balance has become increasingly negative, caused by enhanced surface melting and speedup of the marine-terminating outlet glaciers at the ice sheet margins. Glaciers speedup has been related, among other factors, to enhanced submarine melting, which in turn is caused by warming of the surrounding ocean and less obviously, by increased subglacial discharge. While ice-ocean processes potentially play an important role in recent and future mass balance changes of the Greenland Ice Sheet, their physical understanding remains poorly understood. In this work we performed numerical experiments with a one-dimensional plume model coupled to a one-dimensional iceflow model. First we investigated the sensitivity of submarine melt rate to changes in ocean properties (ocean temperature and salinity), to the amount of subglacial discharge and to the glacier's tongue geometry itself. A second set of experiments investigates the response of the coupled model, i.e. the dynamical response of the outlet glacier to altered submarine melt, which results in new glacier geometry and updated melt rates.

Integrability and chemical potential in the (3 + 1)-dimensional Skyrme model

NASA Astrophysics Data System (ADS)

Alvarez, P. D.; Canfora, F.; Dimakis, N.; Paliathanasis, A.

2017-10-01

Using a remarkable mapping from the original (3 + 1)dimensional Skyrme model to the Sine-Gordon model, we construct the first analytic examples of Skyrmions as well as of Skyrmions-anti-Skyrmions bound states within a finite box in 3 + 1 dimensional flat space-time. An analytic upper bound on the number of these Skyrmions-anti-Skyrmions bound states is derived. We compute the critical isospin chemical potential beyond which these Skyrmions cease to exist. With these tools, we also construct topologically protected time-crystals: time-periodic configurations whose time-dependence is protected by their non-trivial winding number. These are striking realizations of the ideas of Shapere and Wilczek. The critical isospin chemical potential for these time-crystals is determined.

A one-dimensional model of solid-earth electrical resistivity beneath Florida

USGS Publications Warehouse

Blum, Cletus; Love, Jeffrey J.; Pedrie, Kolby; Bedrosian, Paul A.; Rigler, E. Joshua

2015-11-19

An estimated one-dimensional layered model of electrical resistivity beneath Florida was developed from published geological and geophysical information. The resistivity of each layer is represented by plausible upper and lower bounds as well as a geometric mean resistivity. Corresponding impedance transfer functions, Schmucker-Weidelt transfer functions, apparent resistivity, and phase responses are calculated for inducing geomagnetic frequencies ranging from 10−5 to 100 hertz. The resulting one-dimensional model and response functions can be used to make general estimates of time-varying electric fields associated with geomagnetic storms such as might represent induction hazards for electric-power grid operation. The plausible upper- and lower-bound resistivity structures show the uncertainty, giving a wide range of plausible time-varying electric fields.

Modeling of a piezoelectric/piezomagnetic nano energy harvester based on two dimensional theory

NASA Astrophysics Data System (ADS)

Yan, Zhi

2018-01-01

This work presents a two dimensional theory for a piezoelectric/piezomagnetic bilayer nanoplate in coupled extensional and flexural vibrations with both flexoelectric and surface effects. The magneto-electro-elastic (MEE) coupling equations are derived from three-dimensional equations and Kirchhoff plate theory. Based on the developed theory, a piezoelectric/piezomagnetic nano energy harvester is proposed, which can generate electricity under time-harmonic applied magnetic field. The approximate solutions for the mechanical responses and voltage of the energy harvester are obtained using the weighted residual method. Results show that the properties of the proposed energy harvester are size-dependent due to the flexoelectric and surface effects, and such effects are more pronounced when the bilayer thickness is reduced to dozens of nanometers. It is also found that the magnetoelectric coupling coefficient and power density of the energy harvester are sensitive to the load resistance, the thickness fraction of the piezoelectric or the piezomagnetic layer and damping ratios. Moreover, results indicate that the flexoelectric effect could be made use to build a dielectric/piezomagnetic nano energy harvester. This work provides modeling techniques and numerical methods for investigating the size-dependent properties of MEE nanoplate-based energy harvester and could be helpful for designing nano energy harvesters using the principle of flexoelectricity.

Reducing variation in decomposition odour profiling using comprehensive two-dimensional gas chromatography.

PubMed

Perrault, Katelynn A; Stefanuto, Pierre-Hugues; Stuart, Barbara H; Rai, Tapan; Focant, Jean-François; Forbes, Shari L

2015-01-01

Challenges in decomposition odour profiling have led to variation in the documented odour profile by different research groups worldwide. Background subtraction and use of controls are important considerations given the variation introduced by decomposition studies conducted in different geographical environments. The collection of volatile organic compounds (VOCs) from soil beneath decomposing remains is challenging due to the high levels of inherent soil VOCs, further confounded by the use of highly sensitive instrumentation. This study presents a method that provides suitable chromatographic resolution for profiling decomposition odour in soil by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry using appropriate controls and field blanks. Logarithmic transformation and t-testing of compounds permitted the generation of a compound list of decomposition VOCs in soil. Principal component analysis demonstrated the improved discrimination between experimental and control soil, verifying the value of the data handling method. Data handling procedures have not been well documented in this field and standardisation would thereby reduce misidentification of VOCs present in the surrounding environment as decomposition byproducts. Uniformity of data handling and instrumental procedures will reduce analytical variation, increasing confidence in the future when investigating the effect of taphonomic variables on the decomposition VOC profile. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Three dimensional modeling of rigid pavement : executive summary, February 1995.

DOT National Transportation Integrated Search

1995-02-17

A finite-element program has been developed to model the response of rigid pavement to both static loads and temperature changes. The program is fully three-dimensional and incorporates not only the common twenty-node brick element but also a thin in...

Three-dimensional modeling of rigid pavement : final report, September 1995.

DOT National Transportation Integrated Search

1995-02-17

A finite-element program has been developed to model the response of rigid pavement to both static loads and temperature changes. The program is fully three-dimensional and incorporates not only the common twenty-node brick element but also a thin in...

Slab1.0: A three-dimensional model of global subduction zone geometries

NASA Astrophysics Data System (ADS)

Hayes, Gavin P.; Wald, David J.; Johnson, Rebecca L.

2012-01-01

We describe and present a new model of global subduction zone geometries, called Slab1.0. An extension of previous efforts to constrain the two-dimensional non-planar geometry of subduction zones around the focus of large earthquakes, Slab1.0 describes the detailed, non-planar, three-dimensional geometry of approximately 85% of subduction zones worldwide. While the model focuses on the detailed form of each slab from their trenches through the seismogenic zone, where it combines data sets from active source and passive seismology, it also continues to the limits of their seismic extent in the upper-mid mantle, providing a uniform approach to the definition of the entire seismically active slab geometry. Examples are shown for two well-constrained global locations; models for many other regions are available and can be freely downloaded in several formats from our new Slab1.0 website, http://on.doi.gov/d9ARbS. We describe improvements in our two-dimensional geometry constraint inversion, including the use of `average' active source seismic data profiles in the shallow trench regions where data are otherwise lacking, derived from the interpolation between other active source seismic data along-strike in the same subduction zone. We include several analyses of the uncertainty and robustness of our three-dimensional interpolation methods. In addition, we use the filtered, subduction-related earthquake data sets compiled to build Slab1.0 in a reassessment of previous analyses of the deep limit of the thrust interface seismogenic zone for all subduction zones included in our global model thus far, concluding that the width of these seismogenic zones is on average 30% larger than previous studies have suggested.

KRISSY: user's guide to modeling three-dimensional wind flow in complex terrain

Treesearch

Michael A. Fosberg; Michael L. Sestak

1986-01-01

KRISSY is a computer model for generating three-dimensional wind flows in complex terrain from data that were not or perhaps cannot be collected. The model is written in FORTRAN IV This guide describes data requirements, modeling, and output from an applications viewpoint rather than that of programming or theoretical modeling. KRISSY is designed to minimize...

Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy

NASA Astrophysics Data System (ADS)

Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li

2018-03-01

In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.