On the Effects of Gaps and Uses of Approximation Functions on the Time-Scale Signal Analysis: A Case Study Based on Space Geophysical Events

The presence of gaps is quite common in signals related to space science phenomena. Usually, this presence prevents the direct use of standard time-scale analysis because this analysis needs equally spaced data; it is affected by the time series borders (boundaries), and gaps can cause an increase of internal borders. Numerical approximations can be used to estimate the records whose entries are gaps. However, their use has limitations. In many practical cases, these approximations cannot faithfully reproduce the original signal behaviour. Alternatively, in this work, we compare an adapted wavelet technique (gaped wavelet transform), based on the continuous wavelet transform with Morlet wavelet analysing function, with two other standard approximation methods, namely, spline and Hermite cubic polynomials. This wavelet method does not require an approximation of the data on the gap positions, but it adapts the analysing wavelet function to deal with the gaps. To perform our comparisons, we use 120 magnetic field time series from a well-known space geophysical phenomena and we select and classify their gaps. Then, we analyse the influence of these methods in two time-scale tools. As conclusions, we observe that when the gaps are small (very few points sequentially missing), all the methods work well. However, with large gaps, the adapted wavelet method presents a better performance in the time-scale representation. Nevertheless, the cubic Hermite polynomial approximation is also an option when a reconstruction of the data is also needed, with the price of having a worse time-scale representation than the adapted wavelet method.     

A consistent LES/filtered-density function formulation for the simulation of turbulent flames with detailed chemistry

A hybrid large-Eddy simulation/filtered-density function (LES–FDF) methodology is formulated for simulating variable density turbulent reactive flows. An indirect feedback mechanism coupled with a consistency measure based on redundant density fields contained in the different solvers is used to construct a robust algorithm. Using this novel scheme, a partially premixed methane/air flame is simulated. To describe transport in composition space, a 16-species reduced chemistry mechanism is used along with the interaction-by-exchange with the mean (IEM) model. For the micro-mixing model, typically a constant ratio of scalar to mechanical time-scale is assumed. This parameter can have substantial variations and can strongly influence the combustion process. Here, a dynamic time-scale model is used to prescribe the mixing time-scale, which eliminates the time-scale ratio as a model constant. Two different flame configurations, namely, Sandia flames D and E are studied. Comparison of simulated radial profiles with experimental data show good agreement for both flames. The LES–FDF simulations accurately predict the increased extinction near the inlet and re-ignition further downstream. The conditional mean profiles show good agreement with experimental data for both flames.     

New Alfven continuum gaps and global modes induced by toroidal flow

Continuous magnetohydrodynamic (MHD) spectra in tokamaks with toroidal rotation are studied. In the corotating frame, the linear perturbations experience Coriolis and centrifugal effects. The latter create Alfven frequency gaps on rational surfaces resonant with the perturbations. New global eigenmodes are located inside these gaps. These modes may be used for MHD spectroscopy. In contrast to the usual gaps and toroidal Alfven eigenmodes, the new flow-induced gaps and global modes are in the low frequency range so that they will have important implications for stability as well.     

An ALE-based numerical technique for modeling sedimentary basin evolution featuring layer deformations and faults

In this paper we present a numerical tool to simulate dynamics of stratified sedimentary basins, i.e. depressions on the Earth’s surface filled by sediments. The basins are usually complicated by crustal deformations and faulting of the sediments. The balance equations, the non-Newtonian rheology of the sediments, and the depth-porosity compaction laws describe here a model of basin evolution. We propose numerical schemes for the basin boundary movement and for the fault tracking. In addition, a time splitting algorithm is employed to reduce the original model into some simpler mathematical problems. The numerical stability and the other features of the developed methodology are shown using simple test cases and some realistic configurations of sedimentary basins.     

Multi-scale plasma simulation by the interlocking of magnetohydrodynamic model and particle-in-cell kinetic model

Many kinds of simulation models have been developed to understand the complex plasma systems. However, these simulation models have been separately performed because the fundamental assumption of each model is different and restricts the physical processes in each spatial and temporal scales. On the other hand, it is well known that the interactions among the multiple scales may play crucial roles in the plasma phenomena (e.g. magnetic reconnection, collisionless shock), where the kinetic processes in the micro-scale may interact with the global structure in the fluid dynamics. To take self-consistently into account such multi-scale phenomena, we have developed a new simulation model by directly interlocking the fluid simulation of the magnetohyrdodynamics (MHD) model and the kinetic simulation of the particle-in-cell (PIC) model. The PIC domain is embedded in a small part of MHD domain. The both simulations are performed simultaneously in each domain and the bounded data are frequently exchanged each other to keep the consistency between the models. We have applied our new interlocked simulation to Alfvén wave propagation problem as a benchmark test and confirmed that the waves can propagate smoothly through the boundaries of each domain.     

Analytical studies on the evolution processes of rarefied deuterium plasma shell Z-pinch by PIC and MHD simulations

In this paper, we analytically explore the magnetic field and mass density evolutions obtained in particle-in-cell(PIC)and magnetohydrodynamics(MHD) simulations of a rarefied deuterium shell Z-pinch and compare those results, and also we study the effects of artificially increased Spitzer resistivity on the magnetic field evolution and Z-pinch dynamic process in the MHD simulation. There are significant differences between the profiles of mass density in the PIC and MHD simulations before 45 ns of the Z-pinch in this study. However, after the shock formation in the PIC simulation,the mass density profile is similar to that in the MHD simulation in the case of using multiplier 2 to modify the Spitzer resistivity. Compared with the magnetic field profiles of the PIC simulation of the shell, the magnetic field diffusion has still not been sufficiently revealed in the MHD simulation even though their convergence ratios become the same by using larger multipliers in the resistivity. The MHD simulation results suggest that the magnetic field diffusion is greatly enhanced by increasing the Spitzer resistivity used, which, however, causes the implosion characteristic to change from shock compression to weak shock, even shockless evolution, and expedites the expansion of the shell. Too large a multiplier is not suggested to be used to modify the resistivity in some Z-pinch applications, such as the Z-pinch driven inertial confinement fusion(ICF) in a dynamic hohlraum. Two-fluid or Hall MHD model, even the PIC/fluid hybrid simulation would be considered as a suitable physical model when there exist the plasma regions with very low density in the simulated domain.     

Multi-scale plasma simulation by the interlocking of magnetohydrodynamic model and particle-in-cell kinetic model

Many kinds of simulation models have been developed to understand the complex plasma systems. However, these simulation models have been separately performed because the fundamental assumption of each model is different and restricts the physical processes in each spatial and temporal scales. On the other hand, it is well known that the interactions among the multiple scales may play crucial roles in the plasma phenomena (e.g. magnetic reconnection, collisionless shock), where the kinetic processes in the micro-scale may interact with the global structure in the fluid dynamics. To take self-consistently into account such multi-scale phenomena, we have developed a new simulation model by directly interlocking the fluid simulation of the magnetohyrdodynamics (MHD) model and the kinetic simulation of the particle-in-cell (PIC) model. The PIC domain is embedded in a small part of MHD domain. The both simulations are performed simultaneously in each domain and the bounded data are frequently exchanged each other to keep the consistency between the models. We have applied our new interlocked simulation to Alfvén wave propagation problem as a benchmark test and confirmed that the waves can propagate smoothly through the boundaries of each domain.     

Central discontinuous Galerkin methods for ideal MHD equations with the exactly divergence-free magnetic field

In this paper, central discontinuous Galerkin methods are developed for solving ideal magnetohydrodynamic (MHD) equations. The methods are based on the original central discontinuous Galerkin methods designed for hyperbolic conservation laws on overlapping meshes, and use different discretization for magnetic induction equations. The resulting schemes carry many features of standard central discontinuous Galerkin methods such as high order accuracy and being free of exact or approximate Riemann solvers. And more importantly, the numerical magnetic field is exactly divergence-free. Such property, desired in reliable simulations of MHD equations, is achieved by first approximating the normal component of the magnetic field through discretizing induction equations on the mesh skeleton, namely, the element interfaces. And then it is followed by an element-by-element divergence-free reconstruction with the matching accuracy. Numerical examples are presented to demonstrate the high order accuracy and the robustness of the schemes.     

Probabilistic sequence alignments: realistic models with efficient algorithms

Alignment algorithms usually rely on simplified models of gaps for computational efficiency. Based on correspondences between alignments and structural models for nucleic acids, and using methods from statistical mechanics, we show that alignments with realistic laws for gaps can be computed with fast algorithms. Improved performances of probabilistic alignments with realistic models of gaps are illustrated. By contrast with optimization-based alignments, such improvements with realistic laws are not observed. General perspectives for biological and physical modelings are mentioned.     

Probabilistic parameter estimation in a 2-step chemical kinetics model for n-dodecane jet autoignition

This paper demonstrates the development of a simple chemical kinetics model designed for autoignition of n-dodecane in air using Bayesian inference with a model-error representation. The model error, i.e. intrinsic discrepancy from a high-fidelity benchmark model, is represented by allowing additional variability in selected parameters. Subsequently, we quantify predictive uncertainties in the results of autoignition simulations of homogeneous reactors at realistic diesel engine conditions. We demonstrate that these predictive error bars capture model error as well. The uncertainty propagation is performed using non-intrusive spectral projection that can also be used in principle with larger scale computations, such as large eddy simulation. While the present calibration is performed to match a skeletal mechanism, it can be done with equal success using experimental data only (e.g. shock-tube measurements). Since our method captures the error associated with structural model simplifications, we believe that the optimised model could then lead to better qualified predictions of autoignition delay time in high-fidelity large eddy simulations than the existing detailed mechanisms. This methodology provides a way to reduce the cost of reaction kinetics in simulations systematically, while quantifying the accuracy of predictions of important target quantities.     

Fast ion induced shearing of 2D Alfvén eigenmodes measured by electron cyclotron emission imaging

Two-dimensional images of electron temperature perturbations are obtained with electron cyclotron emission imaging (ECEI) on the DIII-D tokamak and compared to Alfvén eigenmode structures obtained by numerical modeling using both ideal MHD and hybrid MHD-gyrofluid codes. While many features of the observations are found to be in excellent agreement with simulations using an ideal MHD code (NOVA), other characteristics distinctly reveal the influence of fast ions on the mode structures. These features are found to be well described by the nonperturbative hybrid MHD-gyrofluid model TAEFL.     

Review of implicit methods for the magnetohydrodynamic description of magnetically confined plasmas

Implicit algorithms are essential for predicting the slow growth and saturation of global instabilities in today’s magnetically confined fusion plasma experiments. Present day algorithms for obtaining implicit solutions to the magnetohydrodynamic (MHD) equations for highly magnetized plasma have their roots in algorithms used in the 1960s and 1970s. However, today’s computers and modern linear and non-linear solver techniques make practical much more comprehensive implicit algorithms than were previously possible. Combining these advanced implicit algorithms with highly accurate spatial representations of the vector fields describing the plasma flow and magnetic fields and with improved methods of calculating anisotropic thermal conduction now makes possible simulations of fusion experiments using realistic values of plasma parameters and actual configuration geometry. This article is a review of these developments.     

Heterogeneous diffusion in a reversible gel

We introduce a microscopically realistic model of a physical gel and use computer simulations to study its static and dynamic properties at thermal equilibrium. The phase diagram comprises a sol phase, a coexistence region ending at a critical point, a gelation line determined by geometric percolation, and an equilibrium gel phase unrelated to phase separation. The global structure of the gel is homogeneous, but the stress is only supported by a fractal network. The gel dynamics is highly heterogeneous and we propose a theoretical model to quantitatively describe dynamic heterogeneity in gels. We elucidate several differences between the dynamics of gels and that of glass formers.     

Anomalous flow deflection at earth's low-Alfvén-Mach-Number bow shock

Earth's magnetosphere is an obstacle to the supersonic solar wind and the bow shock is formed in the front side of it. In ordinary hydrodynamics, the flow decelerated at the shock is diverted around the obstacle symmetrically about the Earth-Sun line, which is indeed observed in the magnetosheath most of the time. Here we show a case under a very low-density solar wind in which duskward flow was observed in the dawnside magnetosheath. A Rankine-Hugoniot test shows that the magnetic effect is crucial for this "wrong flow" to appear. A full three-dimensional magnetohydrodynamics (MHD) simulation of the situation confirming this interpretation and earlier simulations is also performed. It is illustrated that in addition to the "wrong flow" feature, various peculiar characteristics appear in the global picture of the MHD flow interaction with the obstacle.     

A large eddy lattice Boltzmann simulation of magnetohydrodynamic turbulence

Large eddy simulations (LES) of a lattice Boltzmann magnetohydrodynamic (LB-MHD) model are performed for the unstable magnetized Kelvin–Helmholtz jet instability. This algorithm is an extension of Ansumali et al. [1] to MHD in which one performs first an expansion in the filter width on the kinetic equations followed by the usual low Knudsen number expansion. These two perturbation operations do not commute. Closure is achieved by invoking the physical constraint that subgrid effects occur at transport time scales. The simulations are in very good agreement with direct numerical simulations.     

Global magnetohydrodynamic simulations of the magnetosphere

The authors demonstrate the use of a global MHD (magnetohydrodynamic) simulations to study the magnetospheric configuration by reviewing some of the results obtained from the Ogino model. The authors start by considering the steady-state configuration of the magnetosphere in the absence of an IMF (interplanetary magnetic field), and then demonstrate how that configuration is changed when a northward or southward IMF is introduced. It is noted that the magnetosphere is very dynamic and since global MHD simulations are intrinsically time-dependent, they offer the possibility of modeling the time-sequence of events in the magnetosphere. Finally results of a calculation in which a magnetospheric substorm is modeled are presented     

Practical global oceanic state estimation

The problem of oceanographic state estimation, by means of an ocean general circulation model (GCM) and a multitude of observations, is described and contrasted with the meteorological process of data assimilation. In practice, all such methods reduce, on the computer, to forms of least-squares. The global oceanographic problem is at the present time focussed primarily on smoothing, rather than forecasting, and the data types are unlike meteorological ones. As formulated in the consortium Estimating the Circulation and Climate of the Ocean (ECCO), an automatic differentiation tool is used to calculate the so-called adjoint code of the GCM, and the method of Lagrange multipliers used to render the problem one of unconstrained least-squares minimization. Major problems today lie less with the numerical algorithms (least-squares problems can be solved by many means) than with the issues of data and model error. Results of ongoing calculations covering the period of the World Ocean Circulation Experiment, and including among other data, satellite altimetry from TOPEX/POSEIDON, Jason-1, ERS- 1/2, ENVISAT, and GFO, a global array of profiling floats from the Argo program, and satellite gravity data from the GRACE mission, suggest that the solutions are now useful for scientific purposes. Both methodology and applications are developing in a number of different directions.     

Detection of global and local parameter variations using nonlinear feedback auxiliary signals and system augmentation

Recently, system augmentation has been combined with nonlinear feedback auxiliary signals to provide sensitivity enhancement in both linear and nonlinear systems. Augmented systems are higher dimensional linear systems that follow trajectories of a nonlinear system one at a time. These augmented systems are subject to a specialized augmented forcing which enforces the augmented system to exactly reproduce the trajectory of the nonlinear system when projected onto the lower dimensional (physical) system. Augmented systems have additional benefits outside of handling nonlinear systems, which makes them more desirable than regular linear systems for sensitivity enhancing control. One of the key advantages of augmented systems is the complete control over the augmented degrees of freedom, and the additional sensor-type knowledge from the augmented variables. These sensing and actuation features are very useful when only few physical actuators and sensors can be placed. Such restrictions are common in most applications, and they severely limit the usefulness of traditional linear sensitivity enhancing feedback approaches. Another benefit of the augmentation is that the control exerted on the augmented degrees of freedom does not require any physical energy, rather it is just signal processing. In this work, these benefits are refined to improve the robustness of detection using sensitivity enhancement. Also, the benefits of system augmentation are explored by using few actuators and sensors. An optimization algorithm is employed not only to maximize the sensitivity of resonant frequencies to added mass at particular locations, but also to detect uniform changes in mass and stiffness. In addition to increased sensitivity for both global and local parameter changes, a study of increasing the sensitivity of local changes, while decreasing the sensitivity of global changes is conducted. Additionally, a methodology is presented to accurately extract augmented frequencies from displacement and forcing data corrupted by noise. Numerical simulations of cantilevered beams are used to validate the approach and discuss the effects of noise.     

Advanced simulation of conductance histograms validated through channel-sensitive experiments on indium nanojunctions

We demonstrate a self-contained methodology for predicting conductance histograms of atomic and molecular junctions. Fast classical molecular-dynamics simulations are combined with accurate density functional theory calculations predicting both quantum transport properties and molecular-dynamics force field parameters. The methodology is confronted with experiments on atomic-sized indium nanojunctions. Beside conductance histograms the distribution of individual channel transmission eigenvalues is also determined by fitting the superconducting subgap features in the I-V curves. The remarkable agreement in the evolution of the channel transmissions demonstrates that the simulated ruptures are able to reproduce a realistic statistical ensemble of contact configurations, whereas simulations on selected ideal geometries show strong deviations from the experimental observations.     

一个新的用于不可压磁流体动力学的格子波尔兹曼模型

绝大多数现有的格子波尔兹曼磁流体动力学模型其实是用可压缩方法来模拟不可压磁流体。而这些可压缩效应在数值模拟中往往会带来意想不到的误差。在这篇文章中，我们提出了一个全新的可用于的不可压格子波尔兹曼磁流体动力学模型，并且进行了哈特曼流的数值模拟。模拟结果与哈特曼流的解析解非常吻合。这个方法需要一个假设条件来消除误差。我们做了大量的数值试验，并且与Dellar教授的模型进行了详细的分析与比较。