Koopman decomposition of Burgers' equation: What can we learn?

NASA Astrophysics Data System (ADS)

Page, Jacob; Kerswell, Rich

2017-11-01

Burgers' equation is a well known 1D model of the Navier-Stokes equations and admits a selection of equilibria and travelling wave solutions. A series of Burgers' trajectories are examined with Dynamic Mode Decomposition (DMD) to probe the capability of the method to extract coherent structures from ``run-down'' simulations. The performance of the method depends critically on the choice of observable. We use the Cole-Hopf transformation to derive an observable which has linear, autonomous dynamics and for which the DMD modes overlap exactly with Koopman modes. This observable can accurately predict the flow evolution beyond the time window of the data used in the DMD, and in that sense outperforms other observables motivated by the nonlinearity in the governing equation. The linearizing observable also allows us to make informed decisions about often ambiguous choices in nonlinear problems, such as rank truncation and snapshot spacing. A number of rules of thumb for connecting DMD with the Koopman operator for nonlinear PDEs are distilled from the results. Related problems in low Reynolds number fluid turbulence are also discussed.

Reduced nonlinear prognostic model construction from high-dimensional data

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

Construction of a data-driven model of evolution operator using universal approximating functions can only be statistically justified when the dimension of its phase space is small enough, especially in the case of short time series. At the same time in many applications real-measured data is high-dimensional, e.g. it is space-distributed and multivariate in climate science. Therefore it is necessary to use efficient dimensionality reduction methods which are also able to capture key dynamical properties of the system from observed data. To address this problem we present a Bayesian approach to an evolution operator construction which incorporates two key reduction steps. First, the data is decomposed into a set of certain empirical modes, such as standard empirical orthogonal functions or recently suggested nonlinear dynamical modes (NDMs) [1], and the reduced space of corresponding principal components (PCs) is obtained. Then, the model of evolution operator for PCs is constructed which maps a number of states in the past to the current state. The second step is to reduce this time-extended space in the past using appropriate decomposition methods. Such a reduction allows us to capture only the most significant spatio-temporal couplings. The functional form of the evolution operator includes separately linear, nonlinear (based on artificial neural networks) and stochastic terms. Explicit separation of the linear term from the nonlinear one allows us to more easily interpret degree of nonlinearity as well as to deal better with smooth PCs which can naturally occur in the decompositions like NDM, as they provide a time scale separation. Results of application of the proposed method to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Spectral decomposition of nonlinear systems with memory

NASA Astrophysics Data System (ADS)

Svenkeson, Adam; Glaz, Bryan; Stanton, Samuel; West, Bruce J.

2016-02-01

We present an alternative approach to the analysis of nonlinear systems with long-term memory that is based on the Koopman operator and a Lévy transformation in time. Memory effects are considered to be the result of interactions between a system and its surrounding environment. The analysis leads to the decomposition of a nonlinear system with memory into modes whose temporal behavior is anomalous and lacks a characteristic scale. On average, the time evolution of a mode follows a Mittag-Leffler function, and the system can be described using the fractional calculus. The general theory is demonstrated on the fractional linear harmonic oscillator and the fractional nonlinear logistic equation. When analyzing data from an ill-defined (black-box) system, the spectral decomposition in terms of Mittag-Leffler functions that we propose may uncover inherent memory effects through identification of a small set of dynamically relevant structures that would otherwise be obscured by conventional spectral methods. Consequently, the theoretical concepts we present may be useful for developing more general methods for numerical modeling that are able to determine whether observables of a dynamical system are better represented by memoryless operators, or operators with long-term memory in time, when model details are unknown.

Genetic bases of fungal white rot wood decay predicted by phylogenomic analysis of correlated gene-phenotype evolution

Treesearch

László G. Nagy; Robert Riley; Philip J. Bergmann; Krisztina Krizsán; Francis M. Martin; Igor V. Grigoriev; Dan Cullen; David S. Hibbett

2016-01-01

Fungal decomposition of plant cell walls (PCW) is a complex process that has diverse industrial applications and huge impacts on the carbon cycle. White rot (WR) is a powerful mode of PCW decay in which lignin and carbohydrates are both degraded. Mechanistic studies of decay coupled with comparative genomic analyses have provided clues to the enzymatic components of WR...

Nonlinear evolution of the first mode supersonic oblique waves in compressible boundary layers. Part 1: Heated/cooled walls

NASA Technical Reports Server (NTRS)

Gajjar, J. S. B.

1993-01-01

The nonlinear stability of an oblique mode propagating in a two-dimensional compressible boundary layer is considered under the long wave-length approximation. The growth rate of the wave is assumed to be small so that the concept of unsteady nonlinear critical layers can be used. It is shown that the spatial/temporal evolution of the mode is governed by a pair of coupled unsteady nonlinear equations for the disturbance vorticity and density. Expressions for the linear growth rate show clearly the effects of wall heating and cooling and in particular how heating destabilizes the boundary layer for these long wavelength inviscid modes at O(1) Mach numbers. A generalized expression for the linear growth rate is obtained and is shown to compare very well for a range of frequencies and wave-angles at moderate Mach numbers with full numerical solutions of the linear stability problem. The numerical solution of the nonlinear unsteady critical layer problem using a novel method based on Fourier decomposition and Chebychev collocation is discussed and some results are presented.

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

Effectiveness of Modal Decomposition for Tapping Atomic Force Microscopy Microcantilevers in Liquid Environment.

PubMed

Kim, Il Kwang; Lee, Soo Il

2016-05-01

The modal decomposition of tapping mode atomic force microscopy microcantilevers in liquid environments was studied experimentally. Microcantilevers with different lengths and stiffnesses and two sample surfaces with different elastic moduli were used in the experiment. The response modes of the microcantilevers were extracted as proper orthogonal modes through proper orthogonal decomposition. Smooth orthogonal decomposition was used to estimate the resonance frequency directly. The effects of the tapping setpoint and the elastic modulus of the sample under test were examined in terms of their multi-mode responses with proper orthogonal modes, proper orthogonal values, smooth orthogonal modes and smooth orthogonal values. Regardless of the stiffness of the microcantilever under test, the first mode was dominant in tapping mode atomic force microscopy under normal operating conditions. However, at lower tapping setpoints, the flexible microcantilever showed modal distortion and noise near the tip when tapping on a hard sample. The stiff microcantilever had a higher mode effect on a soft sample at lower tapping setpoints. Modal decomposition for tapping mode atomic force microscopy can thus be used to estimate the characteristics of samples in liquid environments.

Spatio-Temporal Evolutions of Non-Orthogonal Equatorial Wave Modes Derived from Observations

NASA Astrophysics Data System (ADS)

Barton, C.; Cai, M.

2015-12-01

Equatorial waves have been studied extensively due to their importance to the tropical climate and weather systems. Historically, their activity is diagnosed mainly in the wavenumber-frequency domain. Recently, many studies have projected observational data onto parabolic cylinder functions (PCF), which represent the meridional structure of individual wave modes, to attain time-dependent spatial wave structures. In this study, we propose a methodology that seeks to identify individual wave modes in instantaneous fields of observations by determining their projections on PCF modes according to the equatorial wave theory. The new method has the benefit of yielding a closed system with a unique solution for all waves' spatial structures, including IG waves, for a given instantaneous observed field. We have applied our method to the ERA-Interim reanalysis dataset in the tropical stratosphere where the wave-mean flow interaction mechanism for the quasi-biennial oscillation (QBO) is well-understood. We have confirmed the continuous evolution of the selection mechanism for equatorial waves in the stratosphere from observations as predicted by the theory for the QBO. This also validates the proposed method for decomposition of observed tropical wave fields into non-orthogonal equatorial wave modes.

Mode Analyses of Gyrokinetic Simulations of Plasma Microturbulence

NASA Astrophysics Data System (ADS)

Hatch, David R.

This thesis presents analysis of the excitation and role of damped modes in gyrokinetic simulations of plasma microturbulence. In order to address this question, mode decompositions are used to analyze gyrokinetic simulation data. A mode decomposition can be constructed by projecting a nonlinearly evolved gyrokinetic distribution function onto a set of linear eigenmodes, or alternatively by constructing a proper orthogonal decomposition of the distribution function. POD decompositions are used to examine the role of damped modes in saturating ion temperature gradient driven turbulence. In order to identify the contribution of different modes to the energy sources and sinks, numerical diagnostics for a gyrokinetic energy quantity were developed for the GENE code. The use of these energy diagnostics in conjunction with POD mode decompositions demonstrates that ITG turbulence saturates largely through dissipation by damped modes at the same perpendicular spatial scales as those of the driving instabilities. This defines a picture of turbulent saturation that is very different from both traditional hydrodynamic scenarios and also many common theories for the saturation of plasma turbulence. POD mode decompositions are also used to examine the role of subdominant modes in causing magnetic stochasticity in electromagnetic gyrokinetic simulations. It is shown that the magnetic stochasticity, which appears to be ubiquitous in electromagnetic microturbulence, is caused largely by subdominant modes with tearing parity. The application of higher-order singular value decomposition (HOSVD) to the full distribution function from gyrokinetic simulations is presented. This is an effort to demonstrate the ability to characterize and extract insight from a very large, complex, and high-dimensional data-set - the 5-D (plus time) gyrokinetic distribution function.

Iterative filtering decomposition based on local spectral evolution kernel

PubMed Central

Wang, Yang; Wei, Guo-Wei; Yang, Siyang

2011-01-01

The synthesizing information, achieving understanding, and deriving insight from increasingly massive, time-varying, noisy and possibly conflicting data sets are some of most challenging tasks in the present information age. Traditional technologies, such as Fourier transform and wavelet multi-resolution analysis, are inadequate to handle all of the above-mentioned tasks. The empirical model decomposition (EMD) has emerged as a new powerful tool for resolving many challenging problems in data processing and analysis. Recently, an iterative filtering decomposition (IFD) has been introduced to address the stability and efficiency problems of the EMD. Another data analysis technique is the local spectral evolution kernel (LSEK), which provides a near prefect low pass filter with desirable time-frequency localizations. The present work utilizes the LSEK to further stabilize the IFD, and offers an efficient, flexible and robust scheme for information extraction, complexity reduction, and signal and image understanding. The performance of the present LSEK based IFD is intensively validated over a wide range of data processing tasks, including mode decomposition, analysis of time-varying data, information extraction from nonlinear dynamic systems, etc. The utility, robustness and usefulness of the proposed LESK based IFD are demonstrated via a large number of applications, such as the analysis of stock market data, the decomposition of ocean wave magnitudes, the understanding of physiologic signals and information recovery from noisy images. The performance of the proposed method is compared with that of existing methods in the literature. Our results indicate that the LSEK based IFD improves both the efficiency and the stability of conventional EMD algorithms. PMID:22350559

Modified complementary ensemble empirical mode decomposition and intrinsic mode functions evaluation index for high-speed train gearbox fault diagnosis

NASA Astrophysics Data System (ADS)

Chen, Dongyue; Lin, Jianhui; Li, Yanping

2018-06-01

Complementary ensemble empirical mode decomposition (CEEMD) has been developed for the mode-mixing problem in Empirical Mode Decomposition (EMD) method. Compared to the ensemble empirical mode decomposition (EEMD), the CEEMD method reduces residue noise in the signal reconstruction. Both CEEMD and EEMD need enough ensemble number to reduce the residue noise, and hence it would be too much computation cost. Moreover, the selection of intrinsic mode functions (IMFs) for further analysis usually depends on experience. A modified CEEMD method and IMFs evaluation index are proposed with the aim of reducing the computational cost and select IMFs automatically. A simulated signal and in-service high-speed train gearbox vibration signals are employed to validate the proposed method in this paper. The results demonstrate that the modified CEEMD can decompose the signal efficiently with less computation cost, and the IMFs evaluation index can select the meaningful IMFs automatically.

Trend extraction using empirical mode decomposition and statistical empirical mode decomposition: Case study: Kuala Lumpur stock market

NASA Astrophysics Data System (ADS)

Jaber, Abobaker M.

2014-12-01

Two nonparametric methods for prediction and modeling of financial time series signals are proposed. The proposed techniques are designed to handle non-stationary and non-linearity behave and to extract meaningful signals for reliable prediction. Due to Fourier Transform (FT), the methods select significant decomposed signals that will be employed for signal prediction. The proposed techniques developed by coupling Holt-winter method with Empirical Mode Decomposition (EMD) and it is Extending the scope of empirical mode decomposition by smoothing (SEMD). To show performance of proposed techniques, we analyze daily closed price of Kuala Lumpur stock market index.

Artifact removal from EEG data with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Efremova, Tatyana Yu.; Hramov, Alexander E.

2017-03-01

In the paper we propose the novel method for dealing with the physiological artifacts caused by intensive activity of facial and neck muscles and other movements in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We introduce the mathematical algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from movement artifacts and show high efficiency of the method.

Fast multidimensional ensemble empirical mode decomposition for the analysis of big spatio-temporal datasets.

PubMed

Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min

2016-04-13

In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. © 2016 The Authors.

Exploring the Common Dynamics of Homologous Proteins. Application to the Globin Family

PubMed Central

Maguid, Sandra; Fernandez-Alberti, Sebastian; Ferrelli, Leticia; Echave, Julian

2005-01-01

We present a procedure to explore the global dynamics shared between members of the same protein family. The method allows the comparison of patterns of vibrational motion obtained by Gaussian network model analysis. After the identification of collective coordinates that were conserved during evolution, we quantify the common dynamics within a family. Representative vectors that describe these dynamics are defined using a singular value decomposition approach. As a test case, the globin heme-binding family is considered. The two lowest normal modes are shown to be conserved within this family. Our results encourage the development of models for protein evolution that take into account the conservation of dynamical features. PMID:15749782

Coherent structures and turbulence evolution in magnetized non-neutral plasmas

NASA Astrophysics Data System (ADS)

Romé, M.; Chen, S.; Maero, G.

2018-01-01

The evolution of turbulence of a magnetized pure electron plasma confined in a Penning-Malmberg trap is investigated by means of a two-dimensional particle-in-cell numerical code. The transverse plasma dynamics is studied both in the case of free evolution and under the influence of non-axisymmetric, multipolar radio-frequency drives applied on the circular conducting boundary. In the latter case the radio-frequency fields are chosen in the frequency range of the low-order azimuthal (diocotron) modes of the plasma in order to investigate their effect on the insurgence of azimuthal instabilities and the formation and evolution of coherent structures, possibly preventing the relaxation to a fully-developed turbulent state. Different initial density distributions (rings and spirals) are considered, so that evolutions characterized by different levels of turbulence and intermittency are obtained. The time evolution of integral and spectral quantities of interest are computed using a multiresolution analysis based on a wavelet decomposition of density maps. Qualitative features of turbulent relaxation are found to be similar in conditions of both free and forced evolution, but the analysis allows one to highlight fine details of the flow beyond the self-similarity turbulence properties, so that the influence of the initial conditions and the effect of the external forcing can be distinguished. In particular, the presence of small inhomogeneities in the initial density configuration turns out to lead to quite different final states, especially in the presence of competing unstable diocotron modes characterized by similar growth rates.

Subgrid-scale physical parameterization in atmospheric modeling: How can we make it consistent?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-07-01

Approaches to subgrid-scale physical parameterization in atmospheric modeling are reviewed by taking turbulent combustion flow research as a point of reference. Three major general approaches are considered for its consistent development: moment, distribution density function (DDF), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in geophysics and engineering. The DDF (commonly called PDF) approach is intuitively appealing as it deals with a distribution of variables in subgrid scale in a more direct manner. Mode decomposition was originally applied by Aubry et al (1988 J. Fluid Mech. 192 115-73) in the context of wall boundary-layer turbulence. It is specifically designed to represent coherencies in compact manner by a low-dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (empirical orthogonal functions) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. Among those, wavelet is a particularly attractive alternative. The mass-flux formulation that is currently adopted in the majority of atmospheric models for parameterizing convection can also be considered a special case of mode decomposition, adopting segmentally constant modes for the expansion basis. This perspective further identifies a very basic but also general geometrical constraint imposed on the massflux formulation: the segmentally-constant approximation. Mode decomposition can, furthermore, be understood by analogy with a Galerkin method in numerically modeling. This analogy suggests that the subgrid parameterization may be re-interpreted as a type of mesh-refinement in numerical modeling. A link between the subgrid parameterization and downscaling problems is also pointed out.

Mode decomposition and Lagrangian structures of the flow dynamics in orbitally shaken bioreactors

NASA Astrophysics Data System (ADS)

Weheliye, Weheliye Hashi; Cagney, Neil; Rodriguez, Gregorio; Micheletti, Martina; Ducci, Andrea

2018-03-01

In this study, two mode decomposition techniques were applied and compared to assess the flow dynamics in an orbital shaken bioreactor (OSB) of cylindrical geometry and flat bottom: proper orthogonal decomposition and dynamic mode decomposition. Particle Image Velocimetry (PIV) experiments were carried out for different operating conditions including fluid height, h, and shaker rotational speed, N. A detailed flow analysis is provided for conditions when the fluid and vessel motions are in-phase (Fr = 0.23) and out-of-phase (Fr = 0.47). PIV measurements in vertical and horizontal planes were combined to reconstruct low order models of the full 3D flow and to determine its Finite-Time Lyapunov Exponent (FTLE) within OSBs. The combined results from the mode decomposition and the FTLE fields provide a useful insight into the flow dynamics and Lagrangian coherent structures in OSBs and offer a valuable tool to optimise bioprocess design in terms of mixing and cell suspension.

Comparison of two interpolation methods for empirical mode decomposition based evaluation of radiographic femur bone images.

PubMed

Udhayakumar, Ganesan; Sujatha, Chinnaswamy Manoharan; Ramakrishnan, Swaminathan

2013-01-01

Analysis of bone strength in radiographic images is an important component of estimation of bone quality in diseases such as osteoporosis. Conventional radiographic femur bone images are used to analyze its architecture using bi-dimensional empirical mode decomposition method. Surface interpolation of local maxima and minima points of an image is a crucial part of bi-dimensional empirical mode decomposition method and the choice of appropriate interpolation depends on specific structure of the problem. In this work, two interpolation methods of bi-dimensional empirical mode decomposition are analyzed to characterize the trabecular femur bone architecture of radiographic images. The trabecular bone regions of normal and osteoporotic femur bone images (N = 40) recorded under standard condition are used for this study. The compressive and tensile strength regions of the images are delineated using pre-processing procedures. The delineated images are decomposed into their corresponding intrinsic mode functions using interpolation methods such as Radial basis function multiquadratic and hierarchical b-spline techniques. Results show that bi-dimensional empirical mode decomposition analyses using both interpolations are able to represent architectural variations of femur bone radiographic images. As the strength of the bone depends on architectural variation in addition to bone mass, this study seems to be clinically useful.

Seasonal modulation of the 7Be solar neutrino rate in Borexino

NASA Astrophysics Data System (ADS)

Agostini, M.; Altenmüller, K.; Appel, S.; Atroshchenko, V.; Basilico, D.; Bellini, G.; Benziger, J.; Bick, D.; Bonfini, G.; Borodikhina, L.; Bravo, D.; Caccianiga, B.; Calaprice, F.; Caminata, A.; Caprioli, S.; Carlini, M.; Cavalcante, P.; Chepurnov, A.; Choi, K.; D'Angelo, D.; Davini, S.; Derbin, A.; Ding, X. F.; Di Noto, L.; Drachnev, I.; Fomenko, K.; Franco, D.; Froborg, F.; Gabriele, F.; Galbiati, C.; Ghiano, C.; Giammarchi, M.; Goeger-Neff, M.; Goretti, A.; Gromov, M.; Hagner, C.; Houdy, T.; Hungerford, E.; Ianni, Aldo; Ianni, Andrea; Jany, A.; Jeschke, D.; Kobychev, V.; Korablev, D.; Korga, G.; Kryn, D.; Laubenstein, M.; Lehnert, B.; Litvinovich, E.; Lombardi, F.; Lombardi, P.; Ludhova, L.; Lukyanchenko, G.; Machulin, I.; Manecki, S.; Manuzio, G.; Marcocci, S.; Martyn, J.; Meroni, E.; Meyer, M.; Miramonti, L.; Misiaszek, M.; Montuschi, M.; Muratova, V.; Neumair, B.; Oberauer, L.; Opitz, B.; Ortica, F.; Pallavicini, M.; Papp, L.; Pocar, A.; Ranucci, G.; Razeto, A.; Re, A.; Romani, A.; Roncin, R.; Rossi, N.; Schönert, S.; Semenov, D.; Shakina, P.; Skorokhvatov, M.; Smirnov, O.; Sotnikov, A.; Stokes, L. F. F.; Suvorov, Y.; Tartaglia, R.; Testera, G.; Thurn, J.; Toropova, M.; Unzhakov, E.; Vishneva, A.; Vogelaar, R. B.; von Feilitzsch, F.; Wang, H.; Weinz, S.; Wojcik, M.; Wurm, M.; Yokley, Z.; Zaimidoroga, O.; Zavatarelli, S.; Zuber, K.; Zuzel, G.; Borexino Collaboration

2017-06-01

We present the evidence for the seasonal modulation of the 7Be neutrino interaction rate with the Borexino detector at the Laboratori Nazionali del Gran Sasso in Italy. The period, amplitude, and phase of the observed time evolution of the signal are consistent with its solar origin, and the absence of an annual modulation is rejected at 99.99% C.L. The data are analyzed using three methods: the analytical fit to event rate, the Lomb-Scargle and the Empirical Mode Decomposition techniques, which all yield results in excellent agreement.

Photoinduced discommensuration of the commensurate charge-density wave phase in 1 T -Ta S2

NASA Astrophysics Data System (ADS)

Tanimura, Katsumi

2018-06-01

The dynamics induced by femtosecond-laser excitation of the commensurate phase of the charge-density wave (CDW) in 1 T -Ta S2 have been studied using both time-resolved electron diffraction and the time-resolved spectroscopy of coherent-phonon dynamics. Electron diffraction results show that the commensurate CDW phase is transformed into a new phase with CDW order that is similar to the nearly commensurate phase with threshold-type transition rates; the threshold excitation density of 0.2 per 13 Ta atoms is evaluated. Coherent-phonon spectroscopy results show that, together with the amplitude mode of CDW with a frequency of 2.41 THz, two other modes with frequencies of 2.34 and 2.07 THz are excited in the photoexcited commensurate CDW phase over a timescale of several tens of picoseconds after excitation. Spectroscopic, temporal, and excitation-intensity dependent characteristics of the three coherent phonons reveal that a photoinduced decomposition of the commensurate CDW order into an ensemble of domains with different CDW orders is induced before the CDW-phase transition occurs. The physics underlying the photoinduced decomposition and evolution into discommensurations responsible for the CDW-order transformation are discussed.

Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series

NASA Astrophysics Data System (ADS)

Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.

2017-12-01

Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.

Adaptive Filtration of Physiological Artifacts in EEG Signals in Humans Using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Grubov, V. V.; Runnova, A. E.; Hramov, A. E.

2018-05-01

A new method for adaptive filtration of experimental EEG signals in humans and for removal of different physiological artifacts has been proposed. The algorithm of the method includes empirical mode decomposition of EEG, determination of the number of empirical modes that are considered, analysis of the empirical modes and search for modes that contains artifacts, removal of these modes, and reconstruction of the EEG signal. The method was tested on experimental human EEG signals and demonstrated high efficiency in the removal of different types of physiological EEG artifacts.

Improvements to the construction of binary black hole initial data

NASA Astrophysics Data System (ADS)

Ossokine, Serguei; Foucart, Francois; Pfeiffer, Harald P.; Boyle, Michael; Szilágyi, Béla

2015-12-01

Construction of binary black hole initial data is a prerequisite for numerical evolutions of binary black holes. This paper reports improvements to the binary black hole initial data solver in the spectral Einstein code, to allow robust construction of initial data for mass-ratio above 10:1, and for dimensionless black hole spins above 0.9, while improving efficiency for lower mass-ratios and spins. We implement a more flexible domain decomposition, adaptive mesh refinement and an updated method for choosing free parameters. We also introduce a new method to control and eliminate residual linear momentum in initial data for precessing systems, and demonstrate that it eliminates gravitational mode mixing during the evolution. Finally, the new code is applied to construct initial data for hyperbolic scattering and for binaries with very small separation.

Nonlinear Waves in the Terrestrial Quasiparallel Foreshock.

PubMed

Hnat, B; Kolotkov, D Y; O'Connell, D; Nakariakov, V M; Rowlands, G

2016-12-02

We provide strongly conclusive evidence that the cubic nonlinearity plays an important part in the evolution of the large amplitude magnetic structures in the terrestrial foreshock. Large amplitude nonlinear wave trains at frequencies above the proton cyclotron frequency are identified after nonharmonic slow variations are filtered out by applying the empirical mode decomposition. Numerical solutions of the derivative nonlinear Schrödinger equation, predicted analytically by the use of a pseudopotential approach, are found to be consistent with the observed wave forms. The approximate phase speed of these nonlinear waves, indicated by the parameters of numerical solutions, is of the order of the local Alfvén speed. We suggest that the feedback of the large amplitude fluctuations on background plasma is reflected in the evolution of the pseudopotential.

Lamb Waves Decomposition and Mode Identification Using Matching Pursuit Method

DTIC Science & Technology

2009-01-01

Wigner - Ville distribution ( WVD ). However, WVD suffers from severe interferences, called cross-terms. Cross- terms are the area of a time-frequency...transform (STFT), wavelet transform, Wigner - Ville distribution , matching pursuit decomposition, etc. 1 Report Documentation Page Form ApprovedOMB No...MP decomposition using chirplet dictionary was applied to a simulated S0 mode Lamb wave shown previously in Figure 2a. Wigner - Ville distribution of

Application of empirical mode decomposition in removing fidgeting interference in doppler radar life signs monitoring devices.

PubMed

Mostafanezhad, Isar; Boric-Lubecke, Olga; Lubecke, Victor; Mandic, Danilo P

2009-01-01

Empirical Mode Decomposition has been shown effective in the analysis of non-stationary and non-linear signals. As an application in wireless life signs monitoring in this paper we use this method in conditioning the signals obtained from the Doppler device. Random physical movements, fidgeting, of the human subject during a measurement can fall on the same frequency of the heart or respiration rate and interfere with the measurement. It will be shown how Empirical Mode Decomposition can break the radar signal down into its components and help separate and remove the fidgeting interference.

Spatiotemporal evolution of the chlorophyll a trend in the North Atlantic Ocean.

PubMed

Zhang, Min; Zhang, Yuanling; Shu, Qi; Zhao, Chang; Wang, Gang; Wu, Zhaohua; Qiao, Fangli

2018-01-15

Analyses of the chlorophyll a concentration (chla) from satellite ocean color products have suggested the decadal-scale variability of chla linked to the climate change. The decadal-scale variability in chla is both spatially and temporally non-uniform. We need to understand the spatiotemporal evolution of chla in decadal or multi-decadal timescales to better evaluate its linkage to climate variability. Here, the spatiotemporal evolution of the chla trend in the North Atlantic Ocean for the period 1997-2016 is analyzed using the multidimensional ensemble empirical mode decomposition method. We find that this variable trend signal of chla shows a dipole pattern between the subpolar gyre and along the Gulf Stream path, and propagation along the opposite direction of the North Atlantic Current. This propagation signal has an overlapping variability of approximately twenty years. Our findings suggest that the spatiotemporal evolution of chla during the two most recent decades is part of the multidecadal variations and possibly regulated by the changes of Atlantic Meridional Overturning Circulation, whereas the mechanisms of such evolution patterns still need to be explored. Copyright © 2017 Elsevier B.V. All rights reserved.

A data-driven method to enhance vibration signal decomposition for rolling bearing fault analysis

NASA Astrophysics Data System (ADS)

Grasso, M.; Chatterton, S.; Pennacchi, P.; Colosimo, B. M.

2016-12-01

Health condition analysis and diagnostics of rotating machinery requires the capability of properly characterizing the information content of sensor signals in order to detect and identify possible fault features. Time-frequency analysis plays a fundamental role, as it allows determining both the existence and the causes of a fault. The separation of components belonging to different time-frequency scales, either associated to healthy or faulty conditions, represents a challenge that motivates the development of effective methodologies for multi-scale signal decomposition. In this framework, the Empirical Mode Decomposition (EMD) is a flexible tool, thanks to its data-driven and adaptive nature. However, the EMD usually yields an over-decomposition of the original signals into a large number of intrinsic mode functions (IMFs). The selection of most relevant IMFs is a challenging task, and the reference literature lacks automated methods to achieve a synthetic decomposition into few physically meaningful modes by avoiding the generation of spurious or meaningless modes. The paper proposes a novel automated approach aimed at generating a decomposition into a minimal number of relevant modes, called Combined Mode Functions (CMFs), each consisting in a sum of adjacent IMFs that share similar properties. The final number of CMFs is selected in a fully data driven way, leading to an enhanced characterization of the signal content without any information loss. A novel criterion to assess the dissimilarity between adjacent CMFs is proposed, based on probability density functions of frequency spectra. The method is suitable to analyze vibration signals that may be periodically acquired within the operating life of rotating machineries. A rolling element bearing fault analysis based on experimental data is presented to demonstrate the performances of the method and the provided benefits.

Lumley decomposition of turbulent boundary layer at high Reynolds numbers

NASA Astrophysics Data System (ADS)

Tutkun, Murat; George, William K.

2017-02-01

The decomposition proposed by Lumley in 1966 is applied to a high Reynolds number turbulent boundary layer. The experimental database was created by a hot-wire rake of 143 probes in the Laboratoire de Mécanique de Lille wind tunnel. The Reynolds numbers based on momentum thickness (Reθ) are 9800 and 19 100. Three-dimensional decomposition is performed, namely, proper orthogonal decomposition (POD) in the inhomogeneous and bounded wall-normal direction, Fourier decomposition in the homogeneous spanwise direction, and Fourier decomposition in time. The first POD modes in both cases carry nearly 50% of turbulence kinetic energy when the energy is integrated over Fourier dimensions. The eigenspectra always peak near zero frequency and most of the large scale, energy carrying features are found at the low end of the spectra. The spanwise Fourier mode which has the largest amount of energy is the first spanwise mode and its symmetrical pair. Pre-multiplied eigenspectra have only one distinct peak and it matches the secondary peak observed in the log-layer of pre-multiplied velocity spectra. Energy carrying modes obtained from the POD scale with outer scaling parameters. Full or partial reconstruction of turbulent velocity signal based only on energetic modes or non-energetic modes revealed the behaviour of urms in distinct regions across the boundary layer. When urms is based on energetic reconstruction, there exists (a) an exponential decay from near wall to log-layer, (b) a constant layer through the log-layer, and (c) another exponential decay in the outer region. The non-energetic reconstruction reveals that urms has (a) an exponential decay from the near-wall to the end of log-layer and (b) a constant layer in the outer region. Scaling of urms using the outer parameters is best when both energetic and non-energetic profiles are combined.

System and methods for determining masking signals for applying empirical mode decomposition (EMD) and for demodulating intrinsic mode functions obtained from application of EMD

DOEpatents

Senroy, Nilanjan [New Delhi, IN; Suryanarayanan, Siddharth [Littleton, CO

2011-03-15

A computer-implemented method of signal processing is provided. The method includes generating one or more masking signals based upon a computed Fourier transform of a received signal. The method further includes determining one or more intrinsic mode functions (IMFs) of the received signal by performing a masking-signal-based empirical mode decomposition (EMD) using the at least one masking signal.

Fast modal decomposition for optical fibers using digital holography.

PubMed

Lyu, Meng; Lin, Zhiquan; Li, Guowei; Situ, Guohai

2017-07-26

Eigenmode decomposition of the light field at the output end of optical fibers can provide fundamental insights into the nature of electromagnetic-wave propagation through the fibers. Here we present a fast and complete modal decomposition technique for step-index optical fibers. The proposed technique employs digital holography to measure the light field at the output end of the multimode optical fiber, and utilizes the modal orthonormal property of the basis modes to calculate the modal coefficients of each mode. Optical experiments were carried out to demonstrate the proposed decomposition technique, showing that this approach is fast, accurate and cost-effective.

New wrinkles on black hole perturbations: Numerical treatment of acoustic and gravitational waves

NASA Astrophysics Data System (ADS)

Tenyotkin, Valery

2009-06-01

This thesis develops two main topics. A full relativistic calculation of quasinormal modes of an acoustic black hole is carried out. The acoustic black hole is formed by a perfect, inviscid, relativistic, ideal gas that is spherically accreting onto a Schwarzschild black hole. The second major part is the calculation of sourceless vector (electromagnetic) and tensor (gravitational) covariant field evolution equations for perturbations on a Schwarzschild background using the relatively recent [Special characters omitted.] decomposition method. Scattering calculations are carried out in Schwarzschild coordinates for electromagnetic and gravitational cases as validation of the method and the derived equations.

Mechanical model for filament buckling and growth by phase ordering.

PubMed

Rey, Alejandro D; Abukhdeir, Nasser M

2008-02-05

A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.

Multi-focus image fusion based on window empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao

2017-09-01

In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.

An optimized time varying filtering based empirical mode decomposition method with grey wolf optimizer for machinery fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei

2018-03-01

A time varying filtering based empirical mode decomposition (EMD) (TVF-EMD) method was proposed recently to solve the mode mixing problem of EMD method. Compared with the classical EMD, TVF-EMD was proven to improve the frequency separation performance and be robust to noise interference. However, the decomposition parameters (i.e., bandwidth threshold and B-spline order) significantly affect the decomposition results of this method. In original TVF-EMD method, the parameter values are assigned in advance, which makes it difficult to achieve satisfactory analysis results. To solve this problem, this paper develops an optimized TVF-EMD method based on grey wolf optimizer (GWO) algorithm for fault diagnosis of rotating machinery. Firstly, a measurement index termed weighted kurtosis index is constructed by using kurtosis index and correlation coefficient. Subsequently, the optimal TVF-EMD parameters that match with the input signal can be obtained by GWO algorithm using the maximum weighted kurtosis index as objective function. Finally, fault features can be extracted by analyzing the sensitive intrinsic mode function (IMF) owning the maximum weighted kurtosis index. Simulations and comparisons highlight the performance of TVF-EMD method for signal decomposition, and meanwhile verify the fact that bandwidth threshold and B-spline order are critical to the decomposition results. Two case studies on rotating machinery fault diagnosis demonstrate the effectiveness and advantages of the proposed method.

Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

NASA Astrophysics Data System (ADS)

Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

2015-04-01

Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems. 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

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

NASA Astrophysics Data System (ADS)

Troshin, Victor; Seifert, Avraham

2018-01-01

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

Optimal Averages for Nonlinear Signal Decompositions - Another Alternative for Empirical Mode Decomposition

DTIC Science & Technology

2014-10-01

nonlinear and non-stationary signals. It aims at decomposing a signal, via an iterative sifting procedure, into several intrinsic mode functions ...stationary signals. It aims at decomposing a signal, via an iterative sifting procedure into several intrinsic mode functions (IMFs), and each of the... function , optimization. 1 Introduction It is well known that nonlinear and non-stationary signal analysis is important and difficult. His- torically

Approaches for Subgrid Parameterization: Does Scaling Help?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-04-01

Arguably the scaling behavior is a well-established fact in many geophysical systems. There are already many theoretical studies elucidating this issue. However, the scaling law is slow to be introduced in "operational" geophysical modelling, notably for weather forecast as well as climate projection models. The main purpose of this presentation is to ask why, and try to answer this question. As a reference point, the presentation reviews the three major approaches for traditional subgrid parameterization: moment, PDF (probability density function), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in the atmosphere and the oceans. The PDF approach is intuitively appealing as it directly deals with a distribution of variables in subgrid scale in a more direct manner. The third category, originally proposed by Aubry et al (1988) in context of the wall boundary-layer turbulence, is specifically designed to represent coherencies in compact manner by a low--dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (POD, or empirical orthogonal functions, EOF) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. The mass-flux formulation that is currently adopted in majority of atmospheric models for parameterizing convection can also be considered a special case of the mode decomposition, adopting the segmentally-constant modes for the expansion basis. The mode decomposition can, furthermore, be re-interpreted as a type of Galarkin approach for numerically modelling the subgrid-scale processes. Simple extrapolation of this re-interpretation further suggests us that the subgrid parameterization problem may be re-interpreted as a type of mesh-refinement problem in numerical modelling. We furthermore see a link between the subgrid parameterization and downscaling problems along this line. The mode decomposition approach would also be the best framework for linking between the traditional parameterizations and the scaling perspectives. However, by seeing the link more clearly, we also see strength and weakness of introducing the scaling perspectives into parameterizations. Any diagnosis under a mode decomposition would immediately reveal a power-law nature of the spectrum. However, exploiting this knowledge in operational parameterization would be a different story. It is symbolic to realize that POD studies have been focusing on representing the largest-scale coherency within a grid box under a high truncation. This problem is already hard enough. Looking at differently, the scaling law is a very concise manner for characterizing many subgrid-scale variabilities in systems. We may even argue that the scaling law can provide almost complete subgrid-scale information in order to construct a parameterization, but with a major missing link: its amplitude must be specified by an additional condition. The condition called "closure" in the parameterization problem, and known to be a tough problem. We should also realize that the studies of the scaling behavior tend to be statistical in the sense that it hardly provides complete information for constructing a parameterization: can we specify the coefficients of all the decomposition modes by a scaling law perfectly when the first few leading modes are specified? Arguably, the renormalization group (RNG) is a very powerful tool for reducing a system with a scaling behavior into a low dimension, say, under an appropriate mode decomposition procedure. However, RNG is analytical tool: it is extremely hard to apply it to real complex geophysical systems. It appears that it is still a long way to go for us before we can begin to exploit the scaling law in order to construct operational subgrid parameterizations in effective manner.

Image fusion method based on regional feature and improved bidimensional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Hu, Gang; Hu, Kai

2018-01-01

The decomposition of multiple source images using bidimensional empirical mode decomposition (BEMD) often produces mismatched bidimensional intrinsic mode functions, either by their number or their frequency, making image fusion difficult. A solution to this problem is proposed using a fixed number of iterations and a union operation in the sifting process. By combining the local regional features of the images, an image fusion method has been developed. First, the source images are decomposed using the proposed BEMD to produce the first intrinsic mode function (IMF) and residue component. Second, for the IMF component, a selection and weighted average strategy based on local area energy is used to obtain a high-frequency fusion component. Third, for the residue component, a selection and weighted average strategy based on local average gray difference is used to obtain a low-frequency fusion component. Finally, the fused image is obtained by applying the inverse BEMD transform. Experimental results show that the proposed algorithm provides superior performance over methods based on wavelet transform, line and column-based EMD, and complex empirical mode decomposition, both in terms of visual quality and objective evaluation criteria.

Transition from Direct to Inverse Cascade in Three-Dimensional Turbulence

NASA Astrophysics Data System (ADS)

Sahoo, Ganapati; Alexakis, Alexandros; Biferale, Luca

2017-11-01

We study a model system where the triadic interactions in Navier-Stokes equations are enhanced or suppressed in a controlled manner without affecting neither the total number of degrees of freedom nor the ideal invariants and without breaking any of the symmetries of original equations. Our numerical simulations are based on the helical decomposition of velocity Fourier modes. We introduced a parameter (0 <= λ <= 1) that controls the relative weight among homochiral and heterochiral triads in the nonlinear evolution. We show that by using this weighting protocol the turbulent evolution displays a sharp transition, for a critical value of the control parameter, from forward to backward energy transfer but still keeping the dynamics fully three dimensional, isotropic, and parity invariant. AtMath Collaboration of University of Helsinki and ERC Grant No. 339032 `NewTurb'.

Combined Molecular and Spin Dynamics Simulation of Lattice Vacancies in BCC Iron

NASA Astrophysics Data System (ADS)

Mudrick, Mark; Perera, Dilina; Eisenbach, Markus; Landau, David P.

Using an atomistic model that treats translational and spin degrees of freedom equally, combined molecular and spin dynamics simulations have been performed to study dynamic properties of BCC iron at varying levels of defect impurity. Atomic interactions are described by an empirical many-body potential, and spin interactions with a Heisenberg-like Hamiltonian with a coordinate dependent exchange interaction. Equations of motion are solved numerically using the second-order Suzuki-Trotter decomposition for the time evolution operator. We analyze the spatial and temporal correlation functions for atomic displacements and magnetic order to obtain the effect of vacancy defects on the phonon and magnon excitations. We show that vacancy clusters in the material cause splitting of the characteristic transverse spin-wave excitations, indicating the production of additional excitation modes. Additionally, we investigate the coupling of the atomic and magnetic modes. These modes become more distinct with increasing vacancy cluster size. This material is based upon work supported by the U.S. Department of Energy Office of Science Graduate Student Research (SCGSR) program.

Computationally efficient methods for modelling laser wakefield acceleration in the blowout regime

NASA Astrophysics Data System (ADS)

Cowan, B. M.; Kalmykov, S. Y.; Beck, A.; Davoine, X.; Bunkers, K.; Lifschitz, A. F.; Lefebvre, E.; Bruhwiler, D. L.; Shadwick, B. A.; Umstadter, D. P.; Umstadter

2012-08-01

Electron self-injection and acceleration until dephasing in the blowout regime is studied for a set of initial conditions typical of recent experiments with 100-terawatt-class lasers. Two different approaches to computationally efficient, fully explicit, 3D particle-in-cell modelling are examined. First, the Cartesian code vorpal (Nieter, C. and Cary, J. R. 2004 VORPAL: a versatile plasma simulation code. J. Comput. Phys. 196, 538) using a perfect-dispersion electromagnetic solver precisely describes the laser pulse and bubble dynamics, taking advantage of coarser resolution in the propagation direction, with a proportionally larger time step. Using third-order splines for macroparticles helps suppress the sampling noise while keeping the usage of computational resources modest. The second way to reduce the simulation load is using reduced-geometry codes. In our case, the quasi-cylindrical code calder-circ (Lifschitz, A. F. et al. 2009 Particle-in-cell modelling of laser-plasma interaction using Fourier decomposition. J. Comput. Phys. 228(5), 1803-1814) uses decomposition of fields and currents into a set of poloidal modes, while the macroparticles move in the Cartesian 3D space. Cylindrical symmetry of the interaction allows using just two modes, reducing the computational load to roughly that of a planar Cartesian simulation while preserving the 3D nature of the interaction. This significant economy of resources allows using fine resolution in the direction of propagation and a small time step, making numerical dispersion vanishingly small, together with a large number of particles per cell, enabling good particle statistics. Quantitative agreement of two simulations indicates that these are free of numerical artefacts. Both approaches thus retrieve the physically correct evolution of the plasma bubble, recovering the intrinsic connection of electron self-injection to the nonlinear optical evolution of the driver.

Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics

NASA Astrophysics Data System (ADS)

Baraldi, P.; Bonfanti, G.; Zio, E.

2018-03-01

The identification of the current degradation state of an industrial component and the prediction of its future evolution is a fundamental step for the development of condition-based and predictive maintenance approaches. The objective of the present work is to propose a general method for extracting a health indicator to measure the amount of component degradation from a set of signals measured during operation. The proposed method is based on the combined use of feature extraction techniques, such as Empirical Mode Decomposition and Auto-Associative Kernel Regression, and a multi-objective Binary Differential Evolution (BDE) algorithm for selecting the subset of features optimal for the definition of the health indicator. The objectives of the optimization are desired characteristics of the health indicator, such as monotonicity, trendability and prognosability. A case study is considered, concerning the prediction of the remaining useful life of turbofan engines. The obtained results confirm that the method is capable of extracting health indicators suitable for accurate prognostics.

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

Kolda, Tamara Gibson

We propose two new multilinear operators for expressing the matrix compositions that are needed in the Tucker and PARAFAC (CANDECOMP) decompositions. The first operator, which we call the Tucker operator, is shorthand for performing an n-mode matrix multiplication for every mode of a given tensor and can be employed to concisely express the Tucker decomposition. The second operator, which we call the Kruskal operator, is shorthand for the sum of the outer-products of the columns of N matrices and allows a divorce from a matricized representation and a very concise expression of the PARAFAC decomposition. We explore the properties ofmore » the Tucker and Kruskal operators independently of the related decompositions. Additionally, we provide a review of the matrix and tensor operations that are frequently used in the context of tensor decompositions.« less

Spatio-temporal evolutions of non-orthogonal equatorial wave modes derived from observations

NASA Astrophysics Data System (ADS)

Barton, Cory

Equatorial waves have been studied extensively due to their importance to the tropical climate and weather systems. Historically, their activity is diagnosed mainly in the wavenumber-frequency domain. Recently, many studies have projected observational data onto parabolic cylinder functions (PCFs), which represent the meridional structure of individual wave modes, to attain time-dependent spatial wave structures. The non-orthogonality of wave modes has yet posed a problem when attempting to separate data into wave fields where the waves project onto the same structure functions. We propose the development and application of a new methodology for equatorial wave expansion of instantaneous flows using the full equatorial wave spectrum. By creating a mapping from the meridional structure function amplitudes to the equatorial wave class amplitudes, we are able to diagnose instantaneous wave fields and determine their evolution. Because all meridional modes are shared by some subset of the wave classes, we require constraints on the wave class amplitudes to yield a closed system with a unique solution for all waves' spatial structures, including IG waves. A synthetic field is analyzed using this method to determine its accuracy for data of a single vertical mode. The wave class spectra diagnosed using this method successfully match the correct dispersion curves even if the incorrect depth is chosen for the spatial decomposition. In the case of more than one depth scale, waves with varying equivalent depth may be similarly identified using the dispersion curves. The primary vertical mode is the 200 m equivalent depth mode, which is that of the peak projection response. A distinct spectral power peak along the Kelvin wave dispersion curve for this value validates our choice of equivalent depth, although the possibility of depth varying with time and height is explored. The wave class spectra diagnosed assuming this depth scale mostly match their expected dispersion curves, showing that this method successfully partitions the wave spectra by calculating wave amplitudes in physical space. This is particularly striking because the time evolution, and therefore the frequency characteristics, is determined simply by a timeseries of independently-diagnosed instantaneous horizontal fields. We use the wave fields diagnosed by this method to study wave evolution in the context of the stratospheric QBO of zonal wind, confirming the continuous evolution of the selection mechanism for equatorial waves in the middle atmosphere. The amplitude cycle synchronized with the background zonal wind as predicted by QBO theory is present in the wave class fields even though the dynamics are not forced by the method itself. We have additionally identified a time-evolution of the zonal wavenumber spectrum responsible for the amplitude variability in physical space. Similar to the temporal characteristics, the vertical structures are also the result of a simple height cross-section through multiple independently-diagnosed levels.

Three dimensional empirical mode decomposition analysis apparatus, method and article manufacture

NASA Technical Reports Server (NTRS)

Gloersen, Per (Inventor)

2004-01-01

An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

Intramolecular energy transfer and mode-specific effects in unimolecular reactions of 1,2-difluoroethane

NASA Astrophysics Data System (ADS)

Raff, Lionel M.

1989-06-01

The unimolecular decomposition reactions of 1,2-difluoroethane upon mode-specific excitation to a total internal energy of 7.5 eV are investigated using classical trajectory methods and a previously formulated empirical potential-energy surface. The decomposition channels for 1,2-difluoroethane are, in order of importance, four-center HF elimination, C-C bond rupture, and hydrogen-atom dissociation. This order is found to be independent of the particular vibrational mode excited. Neither fluorine-atom nor F2 elimination reactions are ever observed even though these dissociation channels are energetically open. For four-center HF elimination, the average fraction of the total energy partitioned into internal HF motion varies between 0.115-0.181 depending upon the particular vibrational mode initially excited. The internal energy of the fluoroethylene product lies in the range 0.716-0.776. Comparison of the present results with those previously obtained for a random distribution of the initial 1,2-difluoroethane internal energy [J. Phys. Chem. 92, 5111 (1988)], shows that numerous mode-specific effects are present in these reactions in spite of the fact that intramolecular energy transfer rates for this system are 5.88-25.5 times faster than any of the unimolecular reaction rates. Mode-specific excitation always leads to a total decomposition rate significantly larger than that obtained for a random distribution of the internal energy. Excitation of different 1,2-difluoroethane vibrational modes is found to produce as much as a 51% change in the total decomposition rate. Mode-specific effects are also seen in the product energy partitioning. The rate coefficients for decomposition into the various channels are very sensitive to the particular mode excited. A comparison of the calculated mode-specific effects with the previously determined mode-to-mode energy transfer rate coefficients [J. Chem. Phys. 89, 5680 (1988)] shows that, to some extent, the presence of mode-specific chemistry is correlated with the magnitude of the energy transfer rate. However, the particular pathways for energy flow seem to be more important than the magnitude of the rate coefficients. It is suggested that the propensity for the energy to remain isolated in small subset of modes, such as the CH2F deformation modes or the rocking modes, is primarily responsible for the observation of mode-specific chemistry. The results clearly demonstrate that an intramolecular energy transfer rate that is fast relative to the unimolecular reaction rate is not a sufficient condition to ensure the absence of mode-specific chemical effects.

Quantization of Electromagnetic Fields in Cavities

NASA Technical Reports Server (NTRS)

Kakazu, Kiyotaka; Oshiro, Kazunori

1996-01-01

A quantization procedure for the electromagnetic field in a rectangular cavity with perfect conductor walls is presented, where a decomposition formula of the field plays an essential role. All vector mode functions are obtained by using the decomposition. After expanding the field in terms of the vector mode functions, we get the quantized electromagnetic Hamiltonian.

Randomized Dynamic Mode Decomposition

NASA Astrophysics Data System (ADS)

Erichson, N. Benjamin; Brunton, Steven L.; Kutz, J. Nathan

2017-11-01

The dynamic mode decomposition (DMD) is an equation-free, data-driven matrix decomposition that is capable of providing accurate reconstructions of spatio-temporal coherent structures arising in dynamical systems. We present randomized algorithms to compute the near-optimal low-rank dynamic mode decomposition for massive datasets. Randomized algorithms are simple, accurate and able to ease the computational challenges arising with `big data'. Moreover, randomized algorithms are amenable to modern parallel and distributed computing. The idea is to derive a smaller matrix from the high-dimensional input data matrix using randomness as a computational strategy. Then, the dynamic modes and eigenvalues are accurately learned from this smaller representation of the data, whereby the approximation quality can be controlled via oversampling and power iterations. Here, we present randomized DMD algorithms that are categorized by how many passes the algorithm takes through the data. Specifically, the single-pass randomized DMD does not require data to be stored for subsequent passes. Thus, it is possible to approximately decompose massive fluid flows (stored out of core memory, or not stored at all) using single-pass algorithms, which is infeasible with traditional DMD algorithms.

Nonlinear mode decomposition: A noise-robust, adaptive decomposition method

NASA Astrophysics Data System (ADS)

Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta

2015-09-01

The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

Structural system identification based on variational mode decomposition

NASA Astrophysics Data System (ADS)

Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

2018-03-01

In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

NASA Astrophysics Data System (ADS)

Kou, Jiaqing; Le Clainche, Soledad; Zhang, Weiwei

2018-01-01

This study proposes an improvement in the performance of reduced-order models (ROMs) based on dynamic mode decomposition to model the flow dynamics of the attractor from a transient solution. By combining higher order dynamic mode decomposition (HODMD) with an efficient mode selection criterion, the HODMD with criterion (HODMDc) ROM is able to identify dominant flow patterns with high accuracy. This helps us to develop a more parsimonious ROM structure, allowing better predictions of the attractor dynamics. The method is tested in the solution of a NACA0012 airfoil buffeting in a transonic flow, and its good performance in both the reconstruction of the original solution and the prediction of the permanent dynamics is shown. In addition, the robustness of the method has been successfully tested using different types of parameters, indicating that the proposed ROM approach is a tool promising for using in both numerical simulations and experimental data.

Dynamic mode decomposition for plasma diagnostics and validation.

PubMed

Taylor, Roy; Kutz, J Nathan; Morgan, Kyle; Nelson, Brian A

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Dynamic mode decomposition for plasma diagnostics and validation

NASA Astrophysics Data System (ADS)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2016-08-01

The main purpose of this work is to explore the usefulness of fractal descriptors estimated in multi-resolution domains to characterize biomedical digital image texture. In this regard, three multi-resolution techniques are considered: the well-known discrete wavelet transform (DWT) and the empirical mode decomposition (EMD), and; the newly introduced; variational mode decomposition mode (VMD). The original image is decomposed by the DWT, EMD, and VMD into different scales. Then, Fourier spectrum based fractal descriptors is estimated at specific scales and directions to characterize the image. The support vector machine (SVM) was used to perform supervised classification. The empirical study was applied to the problem of distinguishing between normal and abnormal brain magnetic resonance images (MRI) affected with Alzheimer disease (AD). Our results demonstrate that fractal descriptors estimated in VMD domain outperform those estimated in DWT and EMD domains; and also those directly estimated from the original image.

Adaptive DSPI phase denoising using mutual information and 2D variational mode decomposition

NASA Astrophysics Data System (ADS)

Xiao, Qiyang; Li, Jian; Wu, Sijin; Li, Weixian; Yang, Lianxiang; Dong, Mingli; Zeng, Zhoumo

2018-04-01

In digital speckle pattern interferometry (DSPI), noise interference leads to a low peak signal-to-noise ratio (PSNR) and measurement errors in the phase map. This paper proposes an adaptive DSPI phase denoising method based on two-dimensional variational mode decomposition (2D-VMD) and mutual information. Firstly, the DSPI phase map is subjected to 2D-VMD in order to obtain a series of band-limited intrinsic mode functions (BLIMFs). Then, on the basis of characteristics of the BLIMFs and in combination with mutual information, a self-adaptive denoising method is proposed to obtain noise-free components containing the primary phase information. The noise-free components are reconstructed to obtain the denoising DSPI phase map. Simulation and experimental results show that the proposed method can effectively reduce noise interference, giving a PSNR that is higher than that of two-dimensional empirical mode decomposition methods.

Orszag Tang vortex - Kinetic study of a turbulent plasma

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

Parashar, T. N.; Servidio, S.; Shay, M. A.

Kinetic evolution of the Orszag-Tang vortex is studied using collisionless hybrid simulations based on particle in cell ions and fluid electrons. In magnetohydrodynamics (MHD) this configuration leads rapidly to broadband turbulence. An earlier study estimated the dissipation in the system. A comparison of MHD and hybrid simulations showed similar behavior at large scales but substantial differences at small scales. The hybrid magnetic energy spectrum shows a break at the scale where Hall term in the Ohm's law becomes important. The protons heat perpendicularly and most of the energy is dissipated through magnetic interactions. Here, the space time structure of themore » system is studied using frequency-wavenumber (k-omega) decomposition. No clear resonances appear, ruling out the cyclotron resonances as a likely candidate for the perpendicular heating. The only distinguishable wave modes present, which constitute a small percentage of total energy, are magnetosonic modes.« less

An Iterated Global Mascon Solution with Focus on Land Ice Mass Evolution

NASA Technical Reports Server (NTRS)

Luthcke, S. B.; Sabaka, T.; Rowlands, D. D.; Lemoine, F. G.; Loomis, B. D.; Boy, J. P.

2012-01-01

Land ice mass evolution is determined from a new GRACE global mascon solution. The solution is estimated directly from the reduction of the inter-satellite K-band range rate observations taking into account the full noise covariance, and formally iterating the solution. The new solution increases signal recovery while reducing the GRACE KBRR observation residuals. The mascons are estimated with 10-day and 1-arc-degree equal area sampling, applying anisotropic constraints for enhanced temporal and spatial resolution of the recovered land ice signal. The details of the solution are presented including error and resolution analysis. An Ensemble Empirical Mode Decomposition (EEMD) adaptive filter is applied to the mascon solution time series to compute timing of balance seasons and annual mass balances. The details and causes of the spatial and temporal variability of the land ice regions studied are discussed.

Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient.

PubMed

Li, Yuxing; Li, Yaan; Chen, Xiao; Yu, Jing

2017-12-26

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC). First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs) using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD); then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD) combined with CC compared to EMD denoising, ensemble EMD (EEMD) denoising, VMD denoising and cubic VMD (3VMD) denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

Adaptive Fourier decomposition based ECG denoising.

PubMed

Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming

2016-10-01

A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Explosive decomposition of hydrazine by rapid compression of a gas volume

NASA Technical Reports Server (NTRS)

Bunker, R. L.; Baker, D. L.; Lee, J. H. S.

1991-01-01

In the present investigation of the initiation mechanism and the explosion mode of hydrazine decomposition, a 20 cm-long column of liquid hydrazine was accelerated into a column of gaseous nitrogen, from which it was separated by a thin Teflon diaphragm, in a close-ended cylindrical chamber. Video data obtained reveal the formation of a froth generated by the acceleration of hydrazine into nitrogen at the liquid hydrazine-gaseous nitrogen interface. The explosive hydrazine decomposition had as its initiation mechanism the formation of a froth at a critical temperature; the explosion mode of hydrazine is a confined thermal runaway reaction.

Using dynamic mode decomposition for real-time background/foreground separation in video

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

Kutz, Jose Nathan; Grosek, Jacob; Brunton, Steven

The technique of dynamic mode decomposition (DMD) is disclosed herein for the purpose of robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. Foreground/background separation is achieved at the computational cost of just one singular value decomposition (SVD) and one linear equation solve, thus producing results orders of magnitude faster than robust principal component analysis (RPCA). Additional techniques, including techniques for analyzing the video for multi-resolution time-scale components, and techniques for reusing computations to allow processing of streaming video in real time, are also described herein.

TEMPORAL SIGNATURES OF AIR QUALITY OBSERVATIONS AND MODEL OUTPUTS: DO TIME SERIES DECOMPOSITION METHODS CAPTURE RELEVANT TIME SCALES?

EPA Science Inventory

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereb...

Analysis of Coherent Phonon Signals by Sparsity-promoting Dynamic Mode Decomposition

NASA Astrophysics Data System (ADS)

Murata, Shin; Aihara, Shingo; Tokuda, Satoru; Iwamitsu, Kazunori; Mizoguchi, Kohji; Akai, Ichiro; Okada, Masato

2018-05-01

We propose a method to decompose normal modes in a coherent phonon (CP) signal by sparsity-promoting dynamic mode decomposition. While the CP signals can be modeled as the sum of finite number of damped oscillators, the conventional method such as Fourier transform adopts continuous bases in a frequency domain. Thus, the uncertainty of frequency appears and it is difficult to estimate the initial phase. Moreover, measurement artifacts are imposed on the CP signal and deforms the Fourier spectrum. In contrast, the proposed method can separate the signal from the artifact precisely and can successfully estimate physical properties of the normal modes.

Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization

PubMed Central

Huang, Daizheng; Wu, Zhihui

2017-01-01

Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods. PMID:28222194

Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization.

PubMed

Huang, Daizheng; Wu, Zhihui

2017-01-01

Accurately predicting the trend of outpatient visits by mathematical modeling can help policy makers manage hospitals effectively, reasonably organize schedules for human resources and finances, and appropriately distribute hospital material resources. In this study, a hybrid method based on empirical mode decomposition and back-propagation artificial neural networks optimized by particle swarm optimization is developed to forecast outpatient visits on the basis of monthly numbers. The data outpatient visits are retrieved from January 2005 to December 2013 and first obtained as the original time series. Second, the original time series is decomposed into a finite and often small number of intrinsic mode functions by the empirical mode decomposition technique. Third, a three-layer back-propagation artificial neural network is constructed to forecast each intrinsic mode functions. To improve network performance and avoid falling into a local minimum, particle swarm optimization is employed to optimize the weights and thresholds of back-propagation artificial neural networks. Finally, the superposition of forecasting results of the intrinsic mode functions is regarded as the ultimate forecasting value. Simulation indicates that the proposed method attains a better performance index than the other four methods.

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

The Prominent Role of the Upstream Conditions on the Large-scale Motions of a Turbulent Channel Flow

NASA Astrophysics Data System (ADS)

Castillo, Luciano; Dharmarathne, Suranga; Tutkun, Murat; Hutchins, Nicholas

2017-11-01

In this study we investigate how upstream perturbations in a turbulent channel flow impact the downstream flow evolution, especially the large-scale motions. Direct numerical simulations were carried out at a friction Reynolds number, Reτ = 394 . Spanwise varying inlet blowing perturbations were imposed at 1 πh from the inlet. The flow field is decomposed into its constituent scales using proper orthogonal decomposition. The large-scale motions and the small-scale motions of the flow field are separated at a cut-off mode number, Mc. The cut-off mode number is defined as the number of the mode at which the fraction of energy recovered is 55 % . It is found that Reynolds stresses are increased due to blowing perturbations and large-scale motions are responsible for more than 70 % of the increase of the streamwise component of Reynolds normal stress. Surprisingly, 90 % of Reynolds shear stress is due to the energy augmentation of large-scale motions. It is shown that inlet perturbations impact the downstream flow by means of the LSM.

POD analysis of the instability mode of a low-speed streak in a laminar boundary layer

NASA Astrophysics Data System (ADS)

Deng, Si-Chao; Pan, Chong; Wang, Jin-Jun; Rinoshika, Akira

2017-12-01

The instability of one single low-speed streak in a zero-pressure-gradient laminar boundary layer is investigated experimentally via both hydrogen bubble visualization and planar particle image velocimetry (PIV) measurement. A single low-speed streak is generated and destabilized by the wake of an interference wire positioned normal to the wall and in the upstream. The downstream development of the streak includes secondary instability and self-reproduction process, which leads to the generation of two additional streaks appearing on either side of the primary one. A proper orthogonal decomposition (POD) analysis of PIV measured velocity field is used to identify the components of the streak instability in the POD mode space: for a sinuous/varicose type of POD mode, its basis functions present anti-symmetric/symmetric distributions about the streak centerline in the streamwise component, and the symmetry condition reverses in the spanwise component. It is further shown that sinuous mode dominates the turbulent kinematic energy (TKE) through the whole streak evolution process, the TKE content first increases along the streamwise direction to a saturation value and then decays slowly. In contrast, varicose mode exhibits a sustained growth of the TKE content, suggesting an increasing competition of varicose instability against sinuous instability.

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

PubMed Central

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

A four-stage hybrid model for hydrological time series forecasting.

PubMed

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

VELOCITY FIELD OF COMPRESSIBLE MAGNETOHYDRODYNAMIC TURBULENCE: WAVELET DECOMPOSITION AND MODE SCALINGS

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

Kowal, Grzegorz; Lazarian, A., E-mail: kowal@astro.wisc.ed, E-mail: lazarian@astro.wisc.ed

We study compressible magnetohydrodynamic turbulence, which holds the key to many astrophysical processes, including star formation and cosmic-ray propagation. To account for the variations of the magnetic field in the strongly turbulent fluid, we use wavelet decomposition of the turbulent velocity field into Alfven, slow, and fast modes, which presents an extension of the Cho and Lazarian decomposition approach based on Fourier transforms. The wavelets allow us to follow the variations of the local direction of the magnetic field and therefore improve the quality of the decomposition compared to the Fourier transforms, which are done in the mean field referencemore » frame. For each resulting component, we calculate the spectra and two-point statistics such as longitudinal and transverse structure functions as well as higher order intermittency statistics. In addition, we perform a Helmholtz- Hodge decomposition of the velocity field into incompressible and compressible parts and analyze these components. We find that the turbulence intermittency is different for different components, and we show that the intermittency statistics depend on whether the phenomenon was studied in the global reference frame related to the mean magnetic field or in the frame defined by the local magnetic field. The dependencies of the measures we obtained are different for different components of the velocity; for instance, we show that while the Alfven mode intermittency changes marginally with the Mach number, the intermittency of the fast mode is substantially affected by the change.« less

Palm vein recognition based on directional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei

2014-04-01

Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.

Single-Input and Multiple-Output Surface Acoustic Wave Sensing for Damage Quantification in Piezoelectric Sensors.

PubMed

Pamwani, Lavish; Habib, Anowarul; Melandsø, Frank; Ahluwalia, Balpreet Singh; Shelke, Amit

2018-06-22

The main aim of the paper is damage detection at the microscale in the anisotropic piezoelectric sensors using surface acoustic waves (SAWs). A novel technique based on the single input and multiple output of Rayleigh waves is proposed to detect the microscale cracks/flaws in the sensor. A convex-shaped interdigital transducer is fabricated for excitation of divergent SAWs in the sensor. An angularly shaped interdigital transducer (IDT) is fabricated at 0 degrees and ±20 degrees for sensing the convex shape evolution of SAWs. A precalibrated damage was introduced in the piezoelectric sensor material using a micro-indenter in the direction perpendicular to the pointing direction of the SAW. Damage detection algorithms based on empirical mode decomposition (EMD) and principal component analysis (PCA) are implemented to quantify the evolution of damage in piezoelectric sensor material. The evolution of the damage was quantified using a proposed condition indicator (CI) based on normalized Euclidean norm of the change in principal angles, corresponding to pristine and damaged states. The CI indicator provides a robust and accurate metric for detection and quantification of damage.

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

Two Dimensional Finite Element Based Magnetotelluric Inversion using Singular Value Decomposition Method on Transverse Electric Mode

NASA Astrophysics Data System (ADS)

Tjong, Tiffany; Yihaa’ Roodhiyah, Lisa; Nurhasan; Sutarno, Doddy

2018-04-01

In this work, an inversion scheme was performed using a vector finite element (VFE) based 2-D magnetotelluric (MT) forward modelling. We use an inversion scheme with Singular value decomposition (SVD) method toimprove the accuracy of MT inversion.The inversion scheme was applied to transverse electric (TE) mode of MT. SVD method was used in this inversion to decompose the Jacobian matrices. Singular values which obtained from the decomposition process were analyzed. This enabled us to determine the importance of data and therefore to define a threshold for truncation process. The truncation of singular value in inversion processcould improve the resulted model.

Microstructure Hierarchical Model of Competitive e+-Ps Trapping in Nanostructurized Substances: from Nanoparticle-Uniform to Nanoparticle-Biased Systems.

PubMed

Shpotyuk, Oleh; Ingram, Adam; Bujňáková, Zdenka; Baláž, Peter

2017-12-01

Microstructure hierarchical model considering the free-volume elements at the level of interacting crystallites (non-spherical approximation) and the agglomerates of these crystallites (spherical approximation) was developed to describe free-volume evolution in mechanochemically milled As 4 S 4 /ZnS composites employing positron annihilation spectroscopy in a lifetime measuring mode. Positron lifetime spectra were reconstructed from unconstrained three-term decomposition procedure and further subjected to parameterization using x3-x2-coupling decomposition algorithm. Intrinsic inhomogeneities due to coarse-grained As 4 S 4 and fine-grained ZnS nanoparticles were adequately described in terms of substitution trapping in positron and positronium (Ps) (bound positron-electron) states due to interfacial triple junctions between contacting particles and own free-volume defects in boundary compounds. Compositionally dependent nanostructurization in As 4 S 4 /ZnS nanocomposite system was imagined as conversion from o-Ps trapping sites to positron traps. The calculated trapping parameters that were shown could be useful to characterize adequately the nanospace filling in As 4 S 4 /ZnS composites.

Wavelet-bounded empirical mode decomposition for measured time series analysis

NASA Astrophysics Data System (ADS)

Moore, Keegan J.; Kurt, Mehmet; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2018-01-01

Empirical mode decomposition (EMD) is a powerful technique for separating the transient responses of nonlinear and nonstationary systems into finite sets of nearly orthogonal components, called intrinsic mode functions (IMFs), which represent the dynamics on different characteristic time scales. However, a deficiency of EMD is the mixing of two or more components in a single IMF, which can drastically affect the physical meaning of the empirical decomposition results. In this paper, we present a new approached based on EMD, designated as wavelet-bounded empirical mode decomposition (WBEMD), which is a closed-loop, optimization-based solution to the problem of mode mixing. The optimization routine relies on maximizing the isolation of an IMF around a characteristic frequency. This isolation is measured by fitting a bounding function around the IMF in the frequency domain and computing the area under this function. It follows that a large (small) area corresponds to a poorly (well) separated IMF. An optimization routine is developed based on this result with the objective of minimizing the bounding-function area and with the masking signal parameters serving as free parameters, such that a well-separated IMF is extracted. As examples of application of WBEMD we apply the proposed method, first to a stationary, two-component signal, and then to the numerically simulated response of a cantilever beam with an essentially nonlinear end attachment. We find that WBEMD vastly improves upon EMD and that the extracted sets of IMFs provide insight into the underlying physics of the response of each system.

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

PubMed Central

2018-01-01

Objective To study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects. Methods MfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1–35 Hz bandpass frequency filter (XDFT). The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8–15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability. Results Using the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8–15° eccentricity of the visual field). Conclusions Filtering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies. PMID:29677200

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

NASA Astrophysics Data System (ADS)

Kabanov, Dmitry I.; Kasimov, Aslan R.

2018-03-01

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

Computer implemented empirical mode decomposition method, apparatus, and article of manufacture for two-dimensional signals

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2001-01-01

A computer implemented method of processing two-dimensional physical signals includes five basic components and the associated presentation techniques of the results. The first component decomposes the two-dimensional signal into one-dimensional profiles. The second component is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF's) from each profile based on local extrema and/or curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the profiles. In the third component, the IMF's of each profile are then subjected to a Hilbert Transform. The fourth component collates the Hilbert transformed IMF's of the profiles to form a two-dimensional Hilbert Spectrum. A fifth component manipulates the IMF's by, for example, filtering the two-dimensional signal by reconstructing the two-dimensional signal from selected IMF(s).

Tissue artifact removal from respiratory signals based on empirical mode decomposition.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty

2013-05-01

On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal.

Decomposition-Based Failure Mode Identification Method for Risk-Free Design of Large Systems

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Stone, Robert B.; Roberts, Rory A.; Clancy, Daniel (Technical Monitor)

2002-01-01

When designing products, it is crucial to assure failure and risk-free operation in the intended operating environment. Failures are typically studied and eliminated as much as possible during the early stages of design. The few failures that go undetected result in unacceptable damage and losses in high-risk applications where public safety is of concern. Published NASA and NTSB accident reports point to a variety of components identified as sources of failures in the reported cases. In previous work, data from these reports were processed and placed in matrix form for all the system components and failure modes encountered, and then manipulated using matrix methods to determine similarities between the different components and failure modes. In this paper, these matrices are represented in the form of a linear combination of failures modes, mathematically formed using Principal Components Analysis (PCA) decomposition. The PCA decomposition results in a low-dimensionality representation of all failure modes and components of interest, represented in a transformed coordinate system. Such a representation opens the way for efficient pattern analysis and prediction of failure modes with highest potential risks on the final product, rather than making decisions based on the large space of component and failure mode data. The mathematics of the proposed method are explained first using a simple example problem. The method is then applied to component failure data gathered from helicopter, accident reports to demonstrate its potential.

Damage methodology approach on a composite panel based on a combination of Fringe Projection and 2D Digital Image Correlation

NASA Astrophysics Data System (ADS)

Felipe-Sesé, Luis; Díaz, Francisco A.

2018-02-01

The recent improvement in accessibility to high speed digital cameras has enabled three dimensional (3D) vibration measurements employing full-field optical techniques. Moreover, there is a need to develop a cost-effective and non-destructive testing method to quantify the severity of damages arising from impacts and thus, enhance the service life. This effect is more interesting in composite structures since possible internal damage has low external manifestation. Those possible damages have been previously studied experimentally by using vibration testing. Namely, those analyses were focused on variations in the modal frequencies or, more recently, mode shapes variations employing punctual accelerometers or vibrometers. In this paper it is presented an alternative method to investigate the severity of damage on a composite structure and how the damage affects to its integrity through the analysis of the full field modal behaviour. In this case, instead of punctual measurements, displacement maps are analysed by employing a combination of FP + 2D-DIC during vibration experiments in an industrial component. In addition, to analyse possible mode shape changes, differences between damaged and undamaged specimens are studied by employing a recent methodology based on Adaptive Image Decomposition (AGMD) procedure. It will be demonstrated that AGMD Image decomposition procedure, which decompose the displacement field into shape descriptors, is capable to detect and quantify the differences between mode shapes. As an application example, the proposed approach has been evaluated on two large industrial components (car bonnets) made of short-fibre reinforced composite. Specifically, the evolution of normalized AGMD shape descriptors has been evaluated for three different components with different damage levels. Results demonstrate the potential of the presented approach making it possible to measure the severity of a structural damage by evaluating the mode shape based in the analysis of its shape descriptors.

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

NASA Technical Reports Server (NTRS)

Ballabrera-Poy, J.; Busalacchi, A.; Murtugudde, R.

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model of Zebiak and Cane. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

Application of a Reduced Order Kalman Filter to Initialize a Coupled Atmosphere-Ocean Model: Impact on the Prediction of El Nino

NASA Technical Reports Server (NTRS)

Ballabrera-Poy, Joaquim; Busalacchi, Antonio J.; Murtugudde, Ragu

2000-01-01

A reduced order Kalman Filter, based on a simplification of the Singular Evolutive Extended Kalman (SEEK) filter equations, is used to assimilate observed fields of the surface wind stress, sea surface temperature and sea level into the nonlinear coupled ocean-atmosphere model. The SEEK filter projects the Kalman Filter equations onto a subspace defined by the eigenvalue decomposition of the error forecast matrix, allowing its application to high dimensional systems. The Zebiak and Cane model couples a linear reduced gravity ocean model with a single vertical mode atmospheric model of Zebiak. The compatibility between the simplified physics of the model and each observed variable is studied separately and together. The results show the ability of the model to represent the simultaneous value of the wind stress, SST and sea level, when the fields are limited to the latitude band 10 deg S - 10 deg N. In this first application of the Kalman Filter to a coupled ocean-atmosphere prediction model, the sea level fields are assimilated in terms of the Kelvin and Rossby modes of the thermocline depth anomaly. An estimation of the error of these modes is derived from the projection of an estimation of the sea level error over such modes. This method gives a value of 12 for the error of the Kelvin amplitude, and 6 m of error for the Rossby component of the thermocline depth. The ability of the method to reconstruct the state of the equatorial Pacific and predict its time evolution is demonstrated. The method is shown to be quite robust for predictions I up to six months, and able to predict the onset of the 1997 warm event fifteen months before its occurrence.

[EMD Time-Frequency Analysis of Raman Spectrum and NIR].

PubMed

Zhao, Xiao-yu; Fang, Yi-ming; Tan, Feng; Tong, Liang; Zhai, Zhe

2016-02-01

This paper analyzes the Raman spectrum and Near Infrared Spectrum (NIR) with time-frequency method. The empirical mode decomposition spectrum becomes intrinsic mode functions, which the proportion calculation reveals the Raman spectral energy is uniform distributed in each component, while the NIR's low order intrinsic mode functions only undertakes fewer primary spectroscopic effective information. Both the real spectrum and numerical experiments show that the empirical mode decomposition (EMD) regard Raman spectrum as the amplitude-modulated signal, which possessed with high frequency adsorption property; and EMD regards NIR as the frequency-modulated signal, which could be preferably realized high frequency narrow-band demodulation during first-order intrinsic mode functions. The first-order intrinsic mode functions Hilbert transform reveals that during the period of empirical mode decomposes Raman spectrum, modal aliasing happened. Through further analysis of corn leaf's NIR in time-frequency domain, after EMD, the first and second orders components of low energy are cut off, and reconstruct spectral signal by using the remaining intrinsic mode functions, the root-mean-square error is 1.001 1, and the correlation coefficient is 0.981 3, both of these two indexes indicated higher accuracy in re-construction; the decomposition trend term indicates the absorbency is ascending along with the decreasing to wave length in the near-infrared light wave band; and the Hilbert transform of characteristic modal component displays, 657 cm⁻¹ is the specific frequency by the corn leaf stress spectrum, which could be regarded as characteristic frequency for identification.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

Fluid dynamic propagation of initial baryon number perturbations on a Bjorken flow background

DOE PAGES

Floerchinger, Stefan; Martinez, Mauricio

2015-12-11

Baryon number density perturbations offer a possible route to experimentally measure baryon number susceptibilities and heat conductivity of the quark gluon plasma. We study the fluid dynamical evolution of local and event-by-event fluctuations of baryon number density, flow velocity, and energy density on top of a (generalized) Bjorken expansion. To that end we use a background-fluctuation splitting and a Bessel-Fourier decomposition for the fluctuating part of the fluid dynamical fields with respect to the azimuthal angle, the radius in the transverse plane, and rapidity. Here, we examine how the time evolution of linear perturbations depends on the equation of statemore » as well as on shear viscosity, bulk viscosity, and heat conductivity for modes with different azimuthal, radial, and rapidity wave numbers. Finally we discuss how this information is accessible to experiments in terms of the transverse and rapidity dependence of correlation functions for baryonic particles in high energy nuclear collisions.« less

POWERFUL RADIO EMISSION FROM LOW-MASS SUPERMASSIVE BLACK HOLES FAVORS DISK-LIKE BULGES

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

Wang, J.; Xu, Y.; Xu, D. W.

The origin of spin of low-mass supermassive black holes (SMBHs) is still a puzzle at present. We report here a study on the host galaxies of a sample of radio-selected nearby ( z < 0.05) Seyfert 2 galaxies with a BH mass of 10{sup 6–7} M{sub ⊙}. By modeling the SDSS r -band images of these galaxies through a two-dimensional bulge+disk decomposition, we identify a new dependence of SMBH's radio power on host bulge surface brightness profiles, in which more powerful radio emission comes from an SMBH associated with a more disk-like bulge. This result means low-mass and high-mass SMBHsmore » are spun up by two entirely different modes that correspond to two different evolutionary paths. A low-mass SMBH is spun up by a gas accretion with significant disk-like rotational dynamics of the host galaxy in the secular evolution, while a high-mass one by a BH–BH merger in the merger evolution.« less

Pi2 detection using Empirical Mode Decomposition (EMD)

NASA Astrophysics Data System (ADS)

Mieth, Johannes Z. D.; Frühauff, Dennis; Glassmeier, Karl-Heinz

2017-04-01

Empirical Mode Decomposition has been used as an alternative method to wavelet transformation to identify onset times of Pi2 pulsations in data sets of the Scandinavian Magnetometer Array (SMA). Pi2 pulsations are magnetohydrodynamic waves occurring during magnetospheric substorms. Almost always Pi2 are observed at substorm onset in mid to low latitudes on Earth's nightside. They are fed by magnetic energy release caused by dipolarization processes. Their periods lie between 40 to 150 seconds. Usually, Pi2 are detected using wavelet transformation. Here, Empirical Mode Decomposition (EMD) is presented as an alternative approach to the traditional procedure. EMD is a young signal decomposition method designed for nonlinear and non-stationary time series. It provides an adaptive, data driven, and complete decomposition of time series into slow and fast oscillations. An optimized version using Monte-Carlo-type noise assistance is used here. By displaying the results in a time-frequency space a characteristic frequency modulation is observed. This frequency modulation can be correlated with the onset of Pi2 pulsations. A basic algorithm to find the onset is presented. Finally, the results are compared to classical wavelet-based analysis. The use of different SMA stations furthermore allows the spatial analysis of Pi2 onset times. EMD mostly finds application in the fields of engineering and medicine. This work demonstrates the applicability of this method to geomagnetic time series.

Computer implemented empirical mode decomposition method, apparatus and article of manufacture

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

1999-01-01

A computer implemented physical signal analysis method is invented. This method includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

How to decompose arbitrary continuous-variable quantum operations.

PubMed

Sefi, Seckin; van Loock, Peter

2011-10-21

We present a general, systematic, and efficient method for decomposing any given exponential operator of bosonic mode operators, describing an arbitrary multimode Hamiltonian evolution, into a set of universal unitary gates. Although our approach is mainly oriented towards continuous-variable quantum computation, it may be used more generally whenever quantum states are to be transformed deterministically, e.g., in quantum control, discrete-variable quantum computation, or Hamiltonian simulation. We illustrate our scheme by presenting decompositions for various nonlinear Hamiltonians including quartic Kerr interactions. Finally, we conclude with two potential experiments utilizing offline-prepared optical cubic states and homodyne detections, in which quantum information is processed optically or in an atomic memory using quadratic light-atom interactions. © 2011 American Physical Society

Coherent mode decomposition using mixed Wigner functions of Hermite-Gaussian beams.

PubMed

Tanaka, Takashi

2017-04-15

A new method of coherent mode decomposition (CMD) is proposed that is based on a Wigner-function representation of Hermite-Gaussian beams. In contrast to the well-known method using the cross spectral density (CSD), it directly determines the mode functions and their weights without solving the eigenvalue problem. This facilitates the CMD of partially coherent light whose Wigner functions (and thus CSDs) are not separable, in which case the conventional CMD requires solving an eigenvalue problem with a large matrix and thus is numerically formidable. An example is shown regarding the CMD of synchrotron radiation, one of the most important applications of the proposed method.

Eliminating the zero spectrum in Fourier transform profilometry using empirical mode decomposition.

PubMed

Li, Sikun; Su, Xianyu; Chen, Wenjing; Xiang, Liqun

2009-05-01

Empirical mode decomposition is introduced into Fourier transform profilometry to extract the zero spectrum included in the deformed fringe pattern without the need for capturing two fringe patterns with pi phase difference. The fringe pattern is subsequently demodulated using a standard Fourier transform profilometry algorithm. With this method, the deformed fringe pattern is adaptively decomposed into a finite number of intrinsic mode functions that vary from high frequency to low frequency by means of an algorithm referred to as a sifting process. Then the zero spectrum is separated from the high-frequency components effectively. Experiments validate the feasibility of this method.

Experimental Modal Analysis and Dynamic Component Synthesis. Volume 3. Modal Parameter Estimation

DTIC Science & Technology

1987-12-01

residues as well as poles is achieved. A singular value decomposition method has been used to develop a complex mode indicator function ( CMIF )[70...which can be used to help determine the number of poles before the analysis. The CMIF is formed by performing a singular value decomposition of all of...servo systems which can include both low and high damping modes. "• CMIF can be used to indicate close or repeated eigenvalues before the parameter

Koopman Mode Decomposition Methods in Dynamic Stall: Reduced Order Modeling and Control

DTIC Science & Technology

2015-11-10

the flow phenomena by separating them into individual modes. The technique of Proper Orthogonal Decomposition (POD), see [ Holmes : 1998] is a popular...sampled values h(k), k = 0,…,2M-1, of the exponential sum 1. Solve the following linear system where 2. Compute all zeros zj  D, j = 1,…,M...of the Prony polynomial i.e., calculate all eigenvalues of the associated companion matrix and form fj = log zj for j = 1,…,M, where log is the

Structural Evolution of Silicon Oxynitride Fiber Reinforced Boron Nitride Matrix Composite at High Temperatures

NASA Astrophysics Data System (ADS)

Zou, Chunrong; Li, Bin; Zhang, Changrui; Wang, Siqing; Xie, Zhengfang; Shao, Changwei

2016-02-01

The structural evolution of a silicon oxynitride fiber reinforced boron nitride matrix (Si-N-Of/BN) wave-transparent composite at high temperatures was investigated. When heat treated at 1600 °C, the composite retained a favorable bending strength of 55.3 MPa while partially crystallizing to Si2N2O and h-BN from the as-received amorphous structure. The Si-N-O fibers still performed as effective reinforcements despite the presence of small pores due to fiber decomposition. Upon heat treatment at 1800 °C, the Si-N-O fibers already lost their reinforcing function and rough hollow microstructure formed within the fibers because of the accelerated decomposition. Further heating to 2000 °C led to the complete decomposition of the reinforcing fibers and only h-BN particles survived. The crystallization and decomposition behaviors of the composite at high temperatures are discussed.

High-order nonuniformly correlated beams

NASA Astrophysics Data System (ADS)

Wu, Dan; Wang, Fei; Cai, Yangjian

2018-02-01

We have introduced a class of partially coherent beams with spatially varying correlations named high-order nonuniformly correlated (HNUC) beams, as an extension of conventional nonuniformly correlated (NUC) beams. Such beams bring a new parameter (mode order) which is used to tailor the spatial coherence properties. The behavior of the spectral density of the HNUC beams on propagation has been investigated through numerical examples with the help of discrete model decomposition and fast Fourier transform (FFT) algorithm. Our results reveal that by selecting the mode order appropriately, the more sharpened intensity maxima can be achieved at a certain propagation distance compared to that of the NUC beams, and the lateral shift of the intensity maxima on propagation is closed related to the mode order. Furthermore, analytical expressions for the r.m.s width and the propagation factor of the HNUC beams on free-space propagation are derived by means of Wigner distribution function. The influence of initial beam parameters on the evolution of the r.m.s width and the propagation factor, and the relation between the r.m.s width and the occurring of the sharpened intensity maxima on propagation have been studied and discussed in detail.

Observation of photonic states dynamics in 3-D integrated Fourier circuits

NASA Astrophysics Data System (ADS)

Flamini, Fulvio; Viggianiello, Niko; Giordani, Taira; Bentivegna, Marco; Spagnolo, Nicolò; Crespi, Andrea; Corrielli, Giacomo; Osellame, Roberto; Martin-Delgado, Miguel Angel; Sciarrino, Fabio

2018-07-01

Entanglement is a fundamental resource at the basis of quantum-enhanced performances in several applications, such as quantum algorithms and quantum metrology. In these contexts, Fourier interferometers implement a relevant class of unitary evolutions which can be embedded in a large variety of protocols. For instance, in the single-particle regime it can be adopted to implement the quantum Fourier transform, while in the multi-particle scenario it can be employed to generate quantum states possessing useful entanglement for quantum phase estimation purposes, or as a tool to verify genuine multi-photon interference. In this article, we study experimentally the dynamics of single-photon and two-photon input states during the evolution provided by a 8-mode Fourier transformation, implemented by exploiting a three-dimensional architecture enabled by the femtosecond laser micromachining technology. In such a way, we fabricated three devices to study the evolution after each step of the decomposition. We observe that the probability distributions obey a step-by-step majorization relationship, where the quantum state occupies a progressively larger portion of the Hilbert space. Such behaviour can be related to the majorization principle, which has been conjectured as a necessary condition for quantum speedup.

Interannual coherent variability of SSTA and SSHA in the Tropical Indian Ocean

NASA Astrophysics Data System (ADS)

Feng, J. Q.

2012-01-01

Sea surface height derived from the multiple ocean satellite altimeter missions (TOPEX/Poseidon, Jason-1, ERS, Envisat et al.) and sea surface temperature from National Centers for Environmental Prediction (NCEP) over 1993-2008 are analyzed to investigate the coherent patterns between the interannual variability of the sea surface and subsurface in the Tropical Indian Ocean, by jointly adopting Singular Value Decomposition (SVD) and Extended Associate Pattern Analysis (EAPA) methods. Results show that there are two dominant coherent modes with the nearly same main period of about 3-5 yr, accounting for 86 % of the total covariance in all, but 90° phase difference between them. The primary pattern is characterized by a east-west dipole mode associated with the mature phase of ENSO, and the second presents a sandwich mode having one sign anomalies along Sumatra-Java coast and northeast of Madagascar, whilst an opposite sign between the two regions. The robust correlations of the sea surface height anomaly (SSHA) with sea surface temperature anomaly (SSTA) in the leading modes indicate a strong interaction between them, though the highest correlation coefficient appears with a time lag. And there may be some physical significance with respect to ocean dynamics implied in SSHA variability. Analyzing results show that the features of oceanic waves with basin scale, of which the Rossby wave is prominent, are apparent in the dominant modes. It is further demonstrated from the EAPA that the equatorial eastward Kelvin wave and off-equatorial westward Rossby wave as well as their reflection in the east and west boundary, respectively, are important dynamic mechanisms in the evolution of the two leading coherent patterns. Results of the present study suggest that the upper ocean thermal variations on the timescale of interannual coherent with the ocean dynamics in spatial structure and temporal evolution are mainly attributed to the ocean waves.

High-speed imaging of submerged jet: visualization analysis using proper orthogonality decomposition

NASA Astrophysics Data System (ADS)

Liu, Yingzheng; He, Chuangxin

2016-11-01

In the present study, the submerged jet at low Reynolds numbers was visualized using laser induced fluoresce and high-speed imaging in a water tank. Well-controlled calibration was made to determine linear dependency region of the fluoresce intensity on its concentration. Subsequently, the jet fluid issuing from a circular pipe was visualized using a high-speed camera. The animation sequence of the visualized jet flow field was supplied for the snapshot proper orthogonality decomposition (POD) analysis. Spatio-temporally varying structures superimposed in the unsteady fluid flow were identified, e.g., the axisymmetric mode and the helical mode, which were reflected from the dominant POD modes. The coefficients of the POD modes give strong indication of temporal and spectral features of the corresponding unsteady events. The reconstruction using the time-mean visualization and the selected POD modes was conducted to reveal the convective motion of the buried vortical structures. National Natural Science Foundation of China.

Determination of knock characteristics in spark ignition engines: an approach based on ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Li, Ning; Yang, Jianguo; Zhou, Rui; Liang, Caiping

2016-04-01

Knock is one of the major constraints to improve the performance and thermal efficiency of spark ignition (SI) engines. It can also result in severe permanent engine damage under certain operating conditions. Based on the ensemble empirical mode decomposition (EEMD), this paper proposes a new approach to determine the knock characteristics in SI engines. By adding a uniformly distributed and finite white Gaussian noise, the EEMD can preserve signal continuity in different scales and therefore alleviates the mode-mixing problem occurring in the classic empirical mode decomposition (EMD). The feasibilities of applying the EEMD to detect the knock signatures of a test SI engine via the pressure signal measured from combustion chamber and the vibration signal measured from cylinder head are investigated. Experimental results show that the EEMD-based method is able to detect the knock signatures from both the pressure signal and vibration signal, even in initial stage of knock. Finally, by comparing the application results with those obtained by short-time Fourier transform (STFT), Wigner-Ville distribution (WVD) and discrete wavelet transform (DWT), the superiority of the EEMD method in determining knock characteristics is demonstrated.

A Compound Fault Diagnosis for Rolling Bearings Method Based on Blind Source Separation and Ensemble Empirical Mode Decomposition

PubMed Central

Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

2014-01-01

A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals’ separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system. PMID:25289644

Analysis of turbulent synthetic jet by dynamic mode decomposition

NASA Astrophysics Data System (ADS)

Hyhlík, Tomáš; Netřebská, Hana; Devera, Jakub; Kalinay, Radomír

The article deals with the analysis of CFD results of the turbulent synthetic jet. The numerical simulation of Large Eddy Simulation (LES) using commercial solver ANSYS CFX has been performed. The unsteady flow field is studied from the point of view of identification of the moving vortex ring, which has been identified both on the snapshots of flow field using swirling-strength criterion and using the Dynamic Mode Decomposition (DMD) of five periods. It is shown that travelling vortex ring vanishes due to interaction with vortex structures in the synthesised turbulent jet. DMD modes with multiple of the basic frequency of synthetic jet, which are connected with travelling vortex structure, have largest DMD amplitudes.

Signal enhancement based on complex curvelet transform and complementary ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Dong, Lieqian; Wang, Deying; Zhang, Yimeng; Zhou, Datong

2017-09-01

Signal enhancement is a necessary step in seismic data processing. In this paper we utilize the complementary ensemble empirical mode decomposition (CEEMD) and complex curvelet transform (CCT) methods to separate signal from random noise further to improve the signal to noise (S/N) ratio. Firstly, the original data with noise is decomposed into a series of intrinsic mode function (IMF) profiles with the aid of CEEMD. Then the IMFs with noise are transformed into CCT domain. By choosing different thresholds which are based on the noise level difference of each IMF profile, the noise in original data can be suppressed. Finally, we illustrate the effectiveness of the approach by simulated and field datasets.

Modal characteristics of a simplified brake rotor model using semi-analytical Rayleigh Ritz method

NASA Astrophysics Data System (ADS)

Zhang, F.; Cheng, L.; Yam, L. H.; Zhou, L. M.

2006-10-01

Emphasis of this paper is given to the modal characteristics of a brake rotor which is utilized in automotive disc brake system. The brake rotor is modeled as a combined structure comprising an annular plate connected to a segment of cylindrical shell by distributed artificial springs. Modal analysis shows the existence of three types of modes for the combined structure, depending on the involvement of each substructure. A decomposition technique is proposed, allowing each mode of the combined structure to be decomposed into a linear combination of the individual substructure modes. It is shown that the decomposition coefficients provide a direct and systematic means to carry out modal classification and quantification.

Analysis of Self-Excited Combustion Instabilities Using Decomposition Techniques

DTIC Science & Technology

2016-07-05

are evaluated for the study of self-excited longitudinal combustion instabilities in laboratory-scaled single-element gas turbine and rocket...Air Force Base, California 93524 DOI: 10.2514/1.J054557 Proper orthogonal decomposition and dynamic mode decomposition are evaluated for the study of...instabilities. In addition, we also evaluate the capabilities of the methods to deal with data sets of different spatial extents and temporal resolution

Approaches to optimization of SS/TDMA time slot assignment. [satellite switched time division multiple access

NASA Technical Reports Server (NTRS)

Wade, T. O.

1984-01-01

Reduction techniques for traffic matrices are explored in some detail. These matrices arise in satellite switched time-division multiple access (SS/TDMA) techniques whereby switching of uplink and downlink beams is required to facilitate interconnectivity of beam zones. A traffic matrix is given to represent that traffic to be transmitted from n uplink beams to n downlink beams within a TDMA frame typically of 1 ms duration. The frame is divided into segments of time and during each segment a portion of the traffic is represented by a switching mode. This time slot assignment is characterized by a mode matrix in which there is not more than a single non-zero entry on each line (row or column) of the matrix. Investigation is confined to decomposition of an n x n traffic matrix by mode matrices with a requirement that the decomposition be 100 percent efficient or, equivalently, that the line(s) in the original traffic matrix whose sum is maximal (called critical line(s)) remain maximal as mode matrices are subtracted throughout the decomposition process. A method of decomposition of an n x n traffic matrix by mode matrices results in a number of steps that is bounded by n(2) - 2n + 2. It is shown that this upper bound exists for an n x n matrix wherein all the lines are maximal (called a quasi doubly stochastic (QDS) matrix) or for an n x n matrix that is completely arbitrary. That is, the fact that no method can exist with a lower upper bound is shown for both QDS and arbitrary matrices, in an elementary and straightforward manner.

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2004-01-01

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2002-01-01

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Computer implemented empirical mode decomposition method apparatus, and article of manufacture utilizing curvature extrema

NASA Technical Reports Server (NTRS)

Shen, Zheng (Inventor); Huang, Norden Eh (Inventor)

2003-01-01

A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

NASA Astrophysics Data System (ADS)

Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

2018-03-01

In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

Robust-mode analysis of hydrodynamic flows

NASA Astrophysics Data System (ADS)

Roy, Sukesh; Gord, James R.; Hua, Jia-Chen; Gunaratne, Gemunu H.

2017-04-01

The emergence of techniques to extract high-frequency high-resolution data introduces a new avenue for modal decomposition to assess the underlying dynamics, especially of complex flows. However, this task requires the differentiation of robust, repeatable flow constituents from noise and other irregular features of a flow. Traditional approaches involving low-pass filtering and principle components analysis have shortcomings. The approach outlined here, referred to as robust-mode analysis, is based on Koopman decomposition. Three applications to (a) a counter-rotating cellular flame state, (b) variations in financial markets, and (c) turbulent injector flows are provided.

Defect inspection using a time-domain mode decomposition technique

NASA Astrophysics Data System (ADS)

Zhu, Jinlong; Goddard, Lynford L.

2018-03-01

In this paper, we propose a technique called time-varying frequency scanning (TVFS) to meet the challenges in killer defect inspection. The proposed technique enables the dynamic monitoring of defects by checking the hopping in the instantaneous frequency data and the classification of defect types by comparing the difference in frequencies. The TVFS technique utilizes the bidimensional empirical mode decomposition (BEMD) method to separate the defect information from the sea of system errors. This significantly improve the signal-to-noise ratio (SNR) and moreover, it potentially enables reference-free defect inspection.

Data analysis using a combination of independent component analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lin, Shih-Lin; Tung, Pi-Cheng; Huang, Norden E.

2009-06-01

A combination of independent component analysis and empirical mode decomposition (ICA-EMD) is proposed in this paper to analyze low signal-to-noise ratio data. The advantages of ICA-EMD combination are these: ICA needs few sensory clues to separate the original source from unwanted noise and EMD can effectively separate the data into its constituting parts. The case studies reported here involve original sources contaminated by white Gaussian noise. The simulation results show that the ICA-EMD combination is an effective data analysis tool.

Fundamental Studies of Beta Phase Decomposition Modes in Titanium Alloys

DTIC Science & Technology

1989-01-31

and H. I. Aaronson, "The Carbon-Carbon Interaction Energy in Alpha Fe- C Alloys", Acta Met., in press. Raju V. Ramanujan , H. I. Aaronson and P. H. Leo...ACCESSIO% %. C 20332 61102F 2306 Al 11 TITLE (Include Security Classification) FUNDAMENTAL STUDIES OF BETA PHASE DECOMPOSITION MODES IN TITANIUM ALLOYS 12...SECUR1Tv CLASSiI-CAtION M) UNCLASSIFIED/UNLIMITED C SAME AS RPT C ] YfC ’SERS UNCLASSIFIED 22a NAME OF RESPONSIBLE INOI’JIDUAL 22b TELEPwONE (Include Area

Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting.

PubMed

Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M

2014-01-01

This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market

NASA Astrophysics Data System (ADS)

Cui, Ling-xiao; Long, Wen

2016-11-01

Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.

Integrated ensemble noise-reconstructed empirical mode decomposition for mechanical fault detection

NASA Astrophysics Data System (ADS)

Yuan, Jing; Ji, Feng; Gao, Yuan; Zhu, Jun; Wei, Chenjun; Zhou, Yu

2018-05-01

A new branch of fault detection is utilizing the noise such as enhancing, adding or estimating the noise so as to improve the signal-to-noise ratio (SNR) and extract the fault signatures. Hereinto, ensemble noise-reconstructed empirical mode decomposition (ENEMD) is a novel noise utilization method to ameliorate the mode mixing and denoised the intrinsic mode functions (IMFs). Despite the possibility of superior performance in detecting weak and multiple faults, the method still suffers from the major problems of the user-defined parameter and the powerless capability for a high SNR case. Hence, integrated ensemble noise-reconstructed empirical mode decomposition is proposed to overcome the drawbacks, improved by two noise estimation techniques for different SNRs as well as the noise estimation strategy. Independent from the artificial setup, the noise estimation by the minimax thresholding is improved for a low SNR case, which especially shows an outstanding interpretation for signature enhancement. For approximating the weak noise precisely, the noise estimation by the local reconfiguration using singular value decomposition (SVD) is proposed for a high SNR case, which is particularly powerful for reducing the mode mixing. Thereinto, the sliding window for projecting the phase space is optimally designed by the correlation minimization. Meanwhile, the reasonable singular order for the local reconfiguration to estimate the noise is determined by the inflection point of the increment trend of normalized singular entropy. Furthermore, the noise estimation strategy, i.e. the selection approaches of the two estimation techniques along with the critical case, is developed and discussed for different SNRs by means of the possible noise-only IMF family. The method is validated by the repeatable simulations to demonstrate the synthetical performance and especially confirm the capability of noise estimation. Finally, the method is applied to detect the local wear fault from a dual-axis stabilized platform and the gear crack from an operating electric locomotive to verify its effectiveness and feasibility.

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

A Comparison of the Raman Spectra and Crystal Chemistry of Norbergite and Clinohumite at High Pressure

NASA Astrophysics Data System (ADS)

Pease, A. M.; Gramsch, S. A.

2017-12-01

Humite group minerals n(Mg.Fe)2SiO4 - (Mg,Fe)(OH)2 have been suggested as possible candidates for water storage and transport in the mantle, and clinohumite in particular has been proposed as the source of ilmenite lamellae in Alpine ultrahigh pressure metamorphic terranes via its decomposition at high pressure and temperature. In this study, a comparison is made between the Raman spectra of norbergite (n = 1) and clinohumite (n = 4) up to 15 GPa to correlate the structural and vibrational properties of these two members of the group. All observed vibrational modes in the Raman spectra of both minerals increase in frequency with pressure, although the change in frequencies with pressure is much steeper in norbergite than for clinohumite. In norbergite, antisymmetric stretching modes of the SiO4 tetrahedra merge, but no such merging of modes occurs in clinohumite. In addition, the intensity of the antisymmetric stretching mode for clinohumite decreases dramatically in pressure compared to the intensity of the symmetric stretching mode. In the spectra of norbergite, these two modes retain their relative intensities with increasing pressure. The most striking difference between the spectra of norbergite and clinohumite is in the deformation modes of the brucite layer, which within the clinohumite structure retain their intensities with increasing pressure, while these modes are not observed in the spectra of norbergite. The nature of the Raman spectra and their evolution with pressure are correlated with the structural properties of the two minerals in terms of the interactions between olivine and brucite layers and the crystal chemistry of the humite group minerals.

Empirical mode decomposition-based facial pose estimation inside video sequences

NASA Astrophysics Data System (ADS)

Qing, Chunmei; Jiang, Jianmin; Yang, Zhijing

2010-03-01

We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions.

Dominant modal decomposition method

NASA Astrophysics Data System (ADS)

Dombovari, Zoltan

2017-03-01

The paper deals with the automatic decomposition of experimental frequency response functions (FRF's) of mechanical structures. The decomposition of FRF's is based on the Green function representation of free vibratory systems. After the determination of the impulse dynamic subspace, the system matrix is formulated and the poles are calculated directly. By means of the corresponding eigenvectors, the contribution of each element of the impulse dynamic subspace is determined and the sufficient decomposition of the corresponding FRF is carried out. With the presented dominant modal decomposition (DMD) method, the mode shapes, the modal participation vectors and the modal scaling factors are identified using the decomposed FRF's. Analytical example is presented along with experimental case studies taken from machine tool industry.

GPR random noise reduction using BPD and EMD

NASA Astrophysics Data System (ADS)

Ostoori, Roya; Goudarzi, Alireza; Oskooi, Behrooz

2018-04-01

Ground-penetrating radar (GPR) exploration is a new high-frequency technology that explores near-surface objects and structures accurately. The high-frequency antenna of the GPR system makes it a high-resolution method compared to other geophysical methods. The frequency range of recorded GPR is so wide that random noise recording is inevitable due to acquisition. This kind of noise comes from unknown sources and its correlation to the adjacent traces is nearly zero. This characteristic of random noise along with the higher accuracy of GPR system makes denoising very important for interpretable results. The main objective of this paper is to reduce GPR random noise based on pursuing denoising using empirical mode decomposition. Our results showed that empirical mode decomposition in combination with basis pursuit denoising (BPD) provides satisfactory outputs due to the sifting process compared to the time-domain implementation of the BPD method on both synthetic and real examples. Our results demonstrate that because of the high computational costs, the BPD-empirical mode decomposition technique should only be used for heavily noisy signals.

Dynamic correlations at different time-scales with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Nava, Noemi; Di Matteo, T.; Aste, Tomaso

2018-07-01

We introduce a simple approach which combines Empirical Mode Decomposition (EMD) and Pearson's cross-correlations over rolling windows to quantify dynamic dependency at different time scales. The EMD is a tool to separate time series into implicit components which oscillate at different time-scales. We apply this decomposition to intraday time series of the following three financial indices: the S&P 500 (USA), the IPC (Mexico) and the VIX (volatility index USA), obtaining time-varying multidimensional cross-correlations at different time-scales. The correlations computed over a rolling window are compared across the three indices, across the components at different time-scales and across different time lags. We uncover a rich heterogeneity of interactions, which depends on the time-scale and has important lead-lag relations that could have practical use for portfolio management, risk estimation and investment decisions.

A hybrid filtering method based on a novel empirical mode decomposition for friction signals

NASA Astrophysics Data System (ADS)

Li, Chengwei; Zhan, Liwei

2015-12-01

During a measurement, the measured signal usually contains noise. To remove the noise and preserve the important feature of the signal, we introduce a hybrid filtering method that uses a new intrinsic mode function (NIMF) and a modified Hausdorff distance. The NIMF is defined as the difference between the noisy signal and each intrinsic mode function (IMF), which is obtained by empirical mode decomposition (EMD), ensemble EMD, complementary ensemble EMD, or complete ensemble EMD with adaptive noise (CEEMDAN). The relevant mode selecting is based on the similarity between the first NIMF and the rest of the NIMFs. With this filtering method, the EMD and improved versions are used to filter the simulation and friction signals. The friction signal between an airplane tire and the runaway is recorded during a simulated airplane touchdown and features spikes of various amplitudes and noise. The filtering effectiveness of the four hybrid filtering methods are compared and discussed. The results show that the filtering method based on CEEMDAN outperforms other signal filtering methods.

Long memory in international financial markets trends and short movements during 2008 financial crisis based on variational mode decomposition and detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2015-11-01

The purpose of this study is to investigate long-range dependence in trend and short variation of stock market price and return series before, during, and after 2008 financial crisis. Variational mode decomposition (VMD), a newly introduced technique for signal processing, is adopted to decompose stock market data into a finite set of modes so as to obtain long term trends and short term movements of stock market data. Then, the detrended fluctuation analysis (DFA) and range scale (R/S) analysis are used to estimate Hurst exponent in each variational mode obtained from VMD. For both price and return series, the empirical results from twelve international stock markets show evidence that long term trends are persistent, whilst short term variations are anti-persistent before, during, and after 2008 financial crisis.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN.

PubMed

Liu, Chang; Cheng, Gang; Chen, Xihui; Pang, Yusong

2018-05-11

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN

PubMed Central

Cheng, Gang; Chen, Xihui

2018-01-01

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears. PMID:29751671

Evaluating imaging quality between different ghost imaging systems based on the coherent-mode representation

NASA Astrophysics Data System (ADS)

Shen, Qian; Bai, Yanfeng; Shi, Xiaohui; Nan, Suqin; Qu, Lijie; Li, Hengxing; Fu, Xiquan

2017-07-01

The difference in imaging quality between different ghost imaging schemes is studied by using coherent-mode representation of partially coherent fields. It is shown that the difference mainly relies on the distribution changes of the decomposition coefficients of the object imaged when the light source is fixed. For a new-designed imaging scheme, we only need to give the distribution of the decomposition coefficients and compare them with that of the existing imaging system, thus one can predict imaging quality. By choosing several typical ghost imaging systems, we theoretically and experimentally verify our results.

Empirical mode decomposition for analyzing acoustical signals

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2005-01-01

The present invention discloses a computer implemented signal analysis method through the Hilbert-Huang Transformation (HHT) for analyzing acoustical signals, which are assumed to be nonlinear and nonstationary. The Empirical Decomposition Method (EMD) and the Hilbert Spectral Analysis (HSA) are used to obtain the HHT. Essentially, the acoustical signal will be decomposed into the Intrinsic Mode Function Components (IMFs). Once the invention decomposes the acoustic signal into its constituting components, all operations such as analyzing, identifying, and removing unwanted signals can be performed on these components. Upon transforming the IMFs into Hilbert spectrum, the acoustical signal may be compared with other acoustical signals.

IR spectral assignments for the hydrated excess proton in liquid water.

PubMed

Biswas, Rajib; Carpenter, William; Fournier, Joseph A; Voth, Gregory A; Tokmakoff, Andrei

2017-04-21

The local environmental sensitivity of infrared (IR) spectroscopy to a hydrogen-bonding structure makes it a powerful tool for investigating the structure and dynamics of excess protons in water. Although of significant interest, the line broadening that results from the ultrafast evolution of different solvated proton-water structures makes the assignment of liquid-phase IR spectra a challenging task. In this work, we apply a normal mode analysis using density functional theory of thousands of proton-water clusters taken from reactive molecular dynamics trajectories of the latest generation multistate empirical valence bond proton model (MS-EVB 3.2). These calculations are used to obtain a vibrational density of states and IR spectral density, which are decomposed on the basis of solvated proton structure and the frequency dependent mode character. Decompositions are presented on the basis of the proton sharing parameter δ, often used to distinguish Eigen and Zundel species, the stretch and bend character of the modes, the mode delocalization, and the vibrational mode symmetry. We find there is a wide distribution of vibrational frequencies spanning 1200-3000 cm -1 for every local proton configuration, with the region 2000-2600 cm -1 being mostly governed by the distorted Eigen-like configuration. We find a continuous red shift of the special-pair O⋯H + ⋯O stretching frequency, and an increase in the flanking water bending intensity with decreasing δ. Also, we find that the flanking water stretch mode of the Zundel-like species is strongly mixed with the flanking water bend, and the special pair proton oscillation band is strongly coupled with the bend modes of the central H 5 O2+moiety.

IR spectral assignments for the hydrated excess proton in liquid water

NASA Astrophysics Data System (ADS)

Biswas, Rajib; Carpenter, William; Fournier, Joseph A.; Voth, Gregory A.; Tokmakoff, Andrei

2017-04-01

The local environmental sensitivity of infrared (IR) spectroscopy to a hydrogen-bonding structure makes it a powerful tool for investigating the structure and dynamics of excess protons in water. Although of significant interest, the line broadening that results from the ultrafast evolution of different solvated proton-water structures makes the assignment of liquid-phase IR spectra a challenging task. In this work, we apply a normal mode analysis using density functional theory of thousands of proton-water clusters taken from reactive molecular dynamics trajectories of the latest generation multistate empirical valence bond proton model (MS-EVB 3.2). These calculations are used to obtain a vibrational density of states and IR spectral density, which are decomposed on the basis of solvated proton structure and the frequency dependent mode character. Decompositions are presented on the basis of the proton sharing parameter δ, often used to distinguish Eigen and Zundel species, the stretch and bend character of the modes, the mode delocalization, and the vibrational mode symmetry. We find there is a wide distribution of vibrational frequencies spanning 1200-3000 cm-1 for every local proton configuration, with the region 2000-2600 cm-1 being mostly governed by the distorted Eigen-like configuration. We find a continuous red shift of the special-pair O⋯H+⋯O stretching frequency, and an increase in the flanking water bending intensity with decreasing δ. Also, we find that the flanking water stretch mode of the Zundel-like species is strongly mixed with the flanking water bend, and the special pair proton oscillation band is strongly coupled with the bend modes of the central H5+O2 moiety.

Thermal decomposition reactions of cotton fabric treated with piperazine-phosphonates derivatives as a flame retardant

USDA-ARS?s Scientific Manuscript database

There has been a great scientific interest in exploring the great potential of the piperazine-phosphonates in flame retardant (FR) application on cotton fabric by investigating the thermal decomposition of cotton fabric treated with them. This research tries to understand the mode of action of the t...

Investigation of shock-induced chemical decomposition of sensitized nitromethane through time-resolved Raman spectroscopy

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

Pangilinan, G.I.; Constantinou, C.P.; Gruzdkov, Y.A.

1996-07-01

Molecular processes associated with shock induced chemical decomposition of a mixture of nitromethane with ethylenediamine (0.1 wt%) are examined using time-resolved, Raman scattering. When shocked by stepwise loading to 14.2 GPa pressure, changes in the nitromethane vibrational modes and the spectral background characterize the onset of reaction. The CN stretch mode softens and disappears even as the NO{sub 2} and CH{sub 3} stretch modes, though modified, retain their identities. The shape and intensity of the spectral background also shows changes characteristic of reaction. Changes in the background, which are observed even at lower peak pressures of 11.4 GPa, are assignedmore » to luminescence from reaction intermediates. The implications of these results to various molecular models of sensitization are discussed.« less

Moisture can be the dominant environmental parameter governing cadaver decomposition in soil.

PubMed

Carter, David O; Yellowlees, David; Tibbett, Mark

2010-07-15

Forensic taphonomy involves the use of decomposition to estimate postmortem interval (PMI) or locate clandestine graves. Yet, cadaver decomposition remains poorly understood, particularly following burial in soil. Presently, we do not know how most edaphic and environmental parameters, including soil moisture, influence the breakdown of cadavers following burial and alter the processes that are used to estimate PMI and locate clandestine graves. To address this, we buried juvenile rat (Rattus rattus) cadavers (approximately 18 g wet weight) in three contrasting soils from tropical savanna ecosystems located in Pallarenda (sand), Wambiana (medium clay), or Yabulu (loamy sand), Queensland, Australia. These soils were sieved (2mm), weighed (500 g dry weight), calibrated to a matric potential of -0.01 megapascals (MPa), -0.05 MPa, or -0.3 MPa (wettest to driest) and incubated at 22 degrees C. Measurements of cadaver decomposition included cadaver mass loss, carbon dioxide-carbon (CO(2)-C) evolution, microbial biomass carbon (MBC), protease activity, phosphodiesterase activity, ninhydrin-reactive nitrogen (NRN) and soil pH. Cadaver burial resulted in a significant increase in CO(2)-C evolution, MBC, enzyme activities, NRN and soil pH. Cadaver decomposition in loamy sand and sandy soil was greater at lower matric potentials (wetter soil). However, optimal matric potential for cadaver decomposition in medium clay was exceeded, which resulted in a slower rate of cadaver decomposition in the wettest soil. Slower cadaver decomposition was also observed at high matric potential (-0.3 MPa). Furthermore, wet sandy soil was associated with greater cadaver decomposition than wet fine-textured soil. We conclude that gravesoil moisture content can modify the relationship between temperature and cadaver decomposition and that soil microorganisms can play a significant role in cadaver breakdown. We also conclude that soil NRN is a more reliable indicator of gravesoil than soil pH. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Dynamics of controllably induced bruises assessed by diffuse reflectance spectroscopy and pulsed photothermal radiometry

NASA Astrophysics Data System (ADS)

Marin, Ana; Milanič, Matija; Verdel, Nina; Vidovič, Luka; Majaron, Boris

2018-02-01

Combination of diffuse reflectance spectroscopy (DRS) and pulsed photothermal radiometry (PPTR) was recently successfully used to study evolution of accidental traumatic bruises. Yet, accidental bruises introduce many unknowns into the evolution analysis and thus a more controllable and repeatable approach for bruising is desired. In this study, evolution of bruises induced by aluminum projectiles of known mass and velocity were studied by DRS and PPTR. Bruises were induced on volar forearm skin of two healthy volunteers. Inverse Monte Carlo including four-layer skin model, was used to analyze the DRS and PPTR data to determine skin chromophores, their concentrations and depths. For bruise analysis, a bruise model was constructed and evolved according to hemoglobin diffusion kinetics. Bruise analysis of PPTR signals yielded bruise evolution parameters, most importantly hemoglobin diffusion constant, hemoglobin decomposition time and blood pool depth. The study results show that chronological tracking of hemoglobin decomposition can be assessed by the combined DRS and PPTR technique on induced bruise. Parameters of individual bruises were compared and two trends in chronological behavior of hemoglobin decomposition time discerned. Changes in bruise diffuse reflectance spectra were noted. Induced bruise parameters, however, still showed some scatter and thus further research is needed to reduce bruise variability.

LLNL demonstration of liquid gun propellant destruction in a 0.1 gallon per minute scale reactor

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

Cena, R.J.; Thorsness, C.B.; Coburn, T.T.

1994-06-01

The Lawrence Livermore National Laboratory (LLNL) has built and operated a pilot plant for processing oil shale using recirculating hot solids. This pilot plant, was adapted in 1993 to demonstrate the feasibility of decomposing a liquid gun propellant (LGP), LP XM46, a mixture of 76% HAN (NH{sub 3}OHNO{sub 3}) and 24% TEAN (HOCH{sub 2}CH{sub 2}){sub 3} NHNO{sub 3} diluted 1:3 in water. In the Livermore process, the LPG is thermally treated in a moving packed bed of ceramic spheres, where TEAN and HAN decompose, forming a suite of gases including: methane, carbon monoxide, oxygen, nitrogen oxides, ammonia and molecular nitrogen.more » The ceramic spheres are circulated and heated, providing the energy required for thermal decomposition. The authors performed an extended one day (8 hour) test of the solids recirculation system, with continuous injection of approximately 0.1 gal/min of LGP, diluted 1:3 in water, for a period of eight hours. The apparatus operated smoothly over the course of the eight hour run during which 144 kg of solution was processed, containing 36 kg of LGP. Continuous on-line gas analysis was invaluable in tracking the progress of the experiment and quantifying the decomposition products. The reactor was operated in two modes, a {open_quotes}Pyrolysis{close_quotes} mode, where decomposition products were removed from the moving bed reactor exit, passing through condensers to a flare, and in a {open_quotes}Combustion{close_quotes} mode, where the products were oxidized in air lift pipe prior to exiting the system. In the {open_quotes}Pyrolysis{close_quotes} mode, driver gases were recycled producing a small, concentrated stream of decomposition products. In the {open_quotes}Combustion mode{close_quotes}, the driver gases were not recycled, resulting in 40 times higher gas flow rates and correspondingly lower concentrations of nitrogen bearing gases.« less

Modeling for Matrix Multicracking Evolution of Cross-ply Ceramic-Matrix Composites Using Energy Balance Approach

NASA Astrophysics Data System (ADS)

Longbiao, Li

2015-12-01

The matrix multicracking evolution of cross-ply ceramic-matrix composites (CMCs) has been investigated using energy balance approach. The multicracking of cross-ply CMCs was classified into five modes, i.e., (1) mode 1: transverse multicracking; (2) mode 2: transverse multicracking and matrix multicracking with perfect fiber/matrix interface bonding; (3) mode 3: transverse multicracking and matrix multicracking with fiber/matrix interface debonding; (4) mode 4: matrix multicracking with perfect fiber/matrix interface bonding; and (5) mode 5: matrix multicracking with fiber/matrix interface debonding. The stress distributions of four cracking modes, i.e., mode 1, mode 2, mode 3 and mode 5, are analysed using shear-lag model. The matrix multicracking evolution of mode 1, mode 2, mode 3 and mode 5, has been determined using energy balance approach. The effects of ply thickness and fiber volume fraction on matrix multicracking evolution of cross-ply CMCs have been investigated.

A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain-computer interface

NASA Astrophysics Data System (ADS)

Chen, Yi-Feng; Atal, Kiran; Xie, Sheng-Quan; Liu, Quan

2017-08-01

Objective. Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications. Approach. Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts. This paper presents an improved method to detect the frequency component associated with SSVEP using multivariate empirical mode decomposition (MEMD) and CCA (MEMD-CCA). EEG signals from nine healthy volunteers were recorded to evaluate the performance of the proposed method for SSVEP recognition. Main results. We compared our method with CCA and temporally local multivariate synchronization index (TMSI). The results suggest that the MEMD-CCA achieved significantly higher accuracy in contrast to standard CCA and TMSI. It gave the improvements of 1.34%, 3.11%, 3.33%, 10.45%, 15.78%, 18.45%, 15.00% and 14.22% on average over CCA at time windows from 0.5 s to 5 s and 0.55%, 1.56%, 7.78%, 14.67%, 13.67%, 7.33% and 7.78% over TMSI from 0.75 s to 5 s. The method outperformed the filter-based decomposition (FB), empirical mode decomposition (EMD) and wavelet decomposition (WT) based CCA for SSVEP recognition. Significance. The results demonstrate the ability of our proposed MEMD-CCA to improve the performance of SSVEP-based BCI.

Protein sectors: evolutionary units of three-dimensional structure

PubMed Central

Halabi, Najeeb; Rivoire, Olivier; Leibler, Stanislas; Ranganathan, Rama

2011-01-01

Proteins display a hierarchy of structural features at primary, secondary, tertiary, and higher-order levels, an organization that guides our current understanding of their biological properties and evolutionary origins. Here, we reveal a structural organization distinct from this traditional hierarchy by statistical analysis of correlated evolution between amino acids. Applied to the S1A serine proteases, the analysis indicates a decomposition of the protein into three quasi-independent groups of correlated amino acids that we term “protein sectors”. Each sector is physically connected in the tertiary structure, has a distinct functional role, and constitutes an independent mode of sequence divergence in the protein family. Functionally relevant sectors are evident in other protein families as well, suggesting that they may be general features of proteins. We propose that sectors represent a structural organization of proteins that reflects their evolutionary histories. PMID:19703402

Analogs of solid nanoparticles as precursors of aromatic hydrocarbons

NASA Astrophysics Data System (ADS)

Gadallah, K. A. K.; Mutschke, H.; Jäger, C.

2013-06-01

Context. Aromatic =CH and C=C vibrational bands have been observed within shocked interstellar regions, indicating the presence of aromatic emission carriers such as PAHs, which may have been created from adjacent molecular cloud material by interaction with a shock front. Aims: We investigate the evolution of the aromatic =CH and C=C vibrational modes at 3.3 and 6.2 μm wavelength in heated HAC materials, PAHs and mixed PAHs and HACs, respectively, aiming at an explanation of the evolution of carbonaceous dust grains in the shocked regions. Methods: Materials used in these analogs (HAC and PAH materials) were prepared by the laser ablation and the laser pyrolysis methods, respectively. The transmission electron microscopy (TEM) in high-resolution mode was used as an analytical technique to characterize the aromatic layers in HACs. Spectroscopic analysis was prformed in the mid-IR range. Results: A remarkable destruction of aliphatic structures in HACs has been observed with the thermal processing, while aromatic structures become dominating by increasing the diameters of the graphene layers. The aromatic bands at 3.3 and 6.2 μm, observed in the laboratory spectra of PAHs and of the combination of the PAHs and HAC materials, are also clearly observed in the spectrum of the heated HACs. These bands agree with those of aromatic bands observed in astronomical observations. Conclusions: Aromatization of HACs could be a pre-stage in the decomposition process of hydrocarbons that form PAH-clusters in such hot interstellar medium.

Structure identification within a transitioning swept-wing boundary layer

NASA Astrophysics Data System (ADS)

Chapman, Keith Lance

1997-08-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use linear stochastic estimation (LSE) and proper orthogonal decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Structure Identification Within a Transitioning Swept-Wing Boundary Layer

NASA Technical Reports Server (NTRS)

Chapman, Keith; Glauser, Mark

1996-01-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use Linear Stochastic Estimation (LSE) and Proper Orthogonal Decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

NASA Astrophysics Data System (ADS)

Hsiao, Y. R.; Tsai, C.

2017-12-01

As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition.

PubMed

Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E

2016-07-15

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.

A technique for plasma velocity-space cross-correlation

NASA Astrophysics Data System (ADS)

Mattingly, Sean; Skiff, Fred

2018-05-01

An advance in experimental plasma diagnostics is presented and used to make the first measurement of a plasma velocity-space cross-correlation matrix. The velocity space correlation function can detect collective fluctuations of plasmas through a localized measurement. An empirical decomposition, singular value decomposition, is applied to this Hermitian matrix in order to obtain the plasma fluctuation eigenmode structure on the ion distribution function. A basic theory is introduced and compared to the modes obtained by the experiment. A full characterization of these modes is left for future work, but an outline of this endeavor is provided. Finally, the requirements for this experimental technique in other plasma regimes are discussed.

A New Approach of evaluating the damage in simply-supported reinforced concrete beam by Local mean decomposition (LMD)

NASA Astrophysics Data System (ADS)

Zhang, Xuebing; Liu, Ning; Xi, Jiaxin; Zhang, Yunqi; Zhang, Wenchun; Yang, Peipei

2017-08-01

How to analyze the nonstationary response signals and obtain vibration characters is extremely important in the vibration-based structural diagnosis methods. In this work, we introduce a more reasonable time-frequency decomposition method termed local mean decomposition (LMD) to instead the widely-used empirical mode decomposition (EMD). By employing the LMD method, one can derive a group of component signals, each of which is more stationary, and then analyze the vibration state and make the assessment of structural damage of a construction or building. We illustrated the effectiveness of LMD by a synthetic data and an experimental data recorded in a simply-supported reinforced concrete beam. Then based on the decomposition results, an elementary method of damage diagnosis was proposed.

Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

2013-12-01

The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Bian, Songhan

2017-05-01

In this paper, we apply the empirical mode decomposition (EMD) method to the recurrence plot (RP) and recurrence quantification analysis (RQA), to evaluate the frequency- and time-evolving dynamics of the traffic flow. Based on the cumulative intrinsic mode functions extracted by the EMD, the frequency-evolving RP regarding different oscillation of modes suggests that apparent dynamics of the data considered are mainly dominated by its components of medium- and low-frequencies while severely affected by fast oscillated noises contained in the signal. Noises are then eliminated to analyze the intrinsic dynamics and consequently, the denoised time-evolving RQA diversely characterizes the properties of the signal and marks crucial points more accurately where white bands in the RP occur, whereas a strongly qualitative agreement exists between all the non-denoised RQA measures. Generally, the EMD combining with the recurrence analysis sheds more reliable, abundant and inherent lights into the traffic flow, which is meaningful to the empirical analysis of complex systems.

Identification of flow structures in fully developed canonical and wavy channels by means of modal decomposition techniques

NASA Astrophysics Data System (ADS)

Ghebali, Sacha; Garicano-Mena, Jesús; Ferrer, Esteban; Valero, Eusebio

2018-04-01

A Dynamic Mode Decomposition (DMD) of Direct Numerical Simulations (DNS) of fully developed channel flows is undertaken in order to study the main differences in flow features between a plane-channel flow and a passively “controlled” flow wherein the mean friction was reduced relative to the baseline by modifying the geometry in order to generate a streamwise-periodic spanwise pressure gradient, as is the case for an oblique wavy wall. The present analysis reports POD and DMD modes for the plane channel, jointly with the application of a sparsity-promoting method, as well as a reconstruction of the Reynolds shear stress with the dynamic modes. Additionally, a dynamic link between the streamwise velocity fluctuations and the friction on the wall is sought by means of a composite approach both in the plane and wavy cases. One of the DMD modes associated with the wavy-wall friction exhibits a meandering motion which was hardly identifiable on the instantaneous friction fluctuations.

Heterogeneous decomposition of silane in a fixed bed reactor

NASA Technical Reports Server (NTRS)

Iya, S. K.; Flagella, R. N.; Dipaolo, F. S.

1982-01-01

Heterogeneous decomposition of silane in a fluidized bed offers an attractive route for the low-cost production of silicon for photovoltaic application. To obtain design data for a fluid bed silane pyrolysis reactor, deposition experiments were conducted in a small-scale fixed bed apparatus. Data on the decomposition mode, plating rate, and deposition morphology were obtained in the temperature range 600-900 C. Conditions favorable for heterogeneous decomposition with good deposition morphology were identified. The kinetic rate data showed the reaction to be first order with an activation energy of 38.8 kcal/mol, which agrees well with work done by others. The results are promising for the development of an economically attractive fluid bed process.

Effect of Systematic Control of Pd Thickness and Annealing Temperature on the Fabrication and Evolution of Palladium Nanostructures on Si (111) via the Solid State Dewetting.

PubMed

Kunwar, Sundar; Pandey, Puran; Sui, Mao; Zhang, Quanzhen; Li, Ming-Yu; Lee, Jihoon

2017-12-01

Si-based optoelectronic devices embedded with metallic nanoparticles (NPs) have demonstrated the NP shape, size, spacing, and crystallinity dependent on light absorption and emission induced by the localized surface plasmon resonance. In this work, we demonstrate various sizes and configurations of palladium (Pd) nanostructures on Si (111) by the systematic thermal annealing with the variation of Pd thickness and annealing temperature. The evolution of Pd nanostructures are systematically controlled by the dewetting of thin film by means of the surface diffusion in conjunction with the surface and interface energy minimization and Volmer-Weber growth model. Depending on the control of deposition amount ranging between 0.5 and 100 nm at various annealing temperatures, four distinctive regimes of Pd nanostructures are demonstrated: (i) small pits and grain formation, (ii) nucleation and growth of NPs, (iii) lateral evolution of NPs, and (iv) merged nanostructures. In addition, by the control of annealing between 300 and 800 °C, the Pd nanostructures show the evolution of small pits and grains, isolated NPs, and finally, Pd NP-assisted nanohole formation along with the Si decomposition and Pd-Si inter-diffusion. The Raman analysis showed the discrepancies on phonon modes of Si (111) such that the decreased peak intensity with left shift after the fabrication of Pd nanostructures. Furthermore, the UV-VIS-NIR reflectance spectra revealed the existence of surface morphology dependent on absorption, scattering, and reflectance properties.

Effect of Systematic Control of Pd Thickness and Annealing Temperature on the Fabrication and Evolution of Palladium Nanostructures on Si (111) via the Solid State Dewetting

NASA Astrophysics Data System (ADS)

Kunwar, Sundar; Pandey, Puran; Sui, Mao; Zhang, Quanzhen; Li, Ming-Yu; Lee, Jihoon

2017-05-01

Si-based optoelectronic devices embedded with metallic nanoparticles (NPs) have demonstrated the NP shape, size, spacing, and crystallinity dependent on light absorption and emission induced by the localized surface plasmon resonance. In this work, we demonstrate various sizes and configurations of palladium (Pd) nanostructures on Si (111) by the systematic thermal annealing with the variation of Pd thickness and annealing temperature. The evolution of Pd nanostructures are systematically controlled by the dewetting of thin film by means of the surface diffusion in conjunction with the surface and interface energy minimization and Volmer-Weber growth model. Depending on the control of deposition amount ranging between 0.5 and 100 nm at various annealing temperatures, four distinctive regimes of Pd nanostructures are demonstrated: (i) small pits and grain formation, (ii) nucleation and growth of NPs, (iii) lateral evolution of NPs, and (iv) merged nanostructures. In addition, by the control of annealing between 300 and 800 °C, the Pd nanostructures show the evolution of small pits and grains, isolated NPs, and finally, Pd NP-assisted nanohole formation along with the Si decomposition and Pd-Si inter-diffusion. The Raman analysis showed the discrepancies on phonon modes of Si (111) such that the decreased peak intensity with left shift after the fabrication of Pd nanostructures. Furthermore, the UV-VIS-NIR reflectance spectra revealed the existence of surface morphology dependent on absorption, scattering, and reflectance properties.

Constraint damping for the Z4c formulation of general relativity

NASA Astrophysics Data System (ADS)

Weyhausen, Andreas; Bernuzzi, Sebastiano; Hilditch, David

2012-01-01

One possibility for avoiding constraint violation in numerical relativity simulations adopting free-evolution schemes is to modify the continuum evolution equations so that constraint violations are damped away. Gundlach et al. demonstrated that such a scheme damps low-amplitude, high-frequency constraint-violating modes exponentially for the Z4 formulation of general relativity. Here we analyze the effect of the damping scheme in numerical applications on a conformal decomposition of Z4. After reproducing the theoretically predicted damping rates of constraint violations in the linear regime, we explore numerical solutions not covered by the theoretical analysis. In particular we examine the effect of the damping scheme on low-frequency and on high-amplitude perturbations of flat spacetime as well and on the long-term dynamics of puncture and compact star initial data in the context of spherical symmetry. We find that the damping scheme is effective provided that the constraint violation is resolved on the numerical grid. On grid noise the combination of artificial dissipation and damping helps to suppress constraint violations. We find that care must be taken in choosing the damping parameter in simulations of puncture black holes. Otherwise the damping scheme can cause undesirable growth of the constraints, and even qualitatively incorrect evolutions. In the numerical evolution of a compact static star we find that the choice of the damping parameter is even more delicate, but may lead to a small decrease of constraint violation. For a large range of values it results in unphysical behavior.

Deconvolution of reacting-flow dynamics using proper orthogonal and dynamic mode decompositions

NASA Astrophysics Data System (ADS)

Roy, Sukesh; Hua, Jia-Chen; Barnhill, Will; Gunaratne, Gemunu H.; Gord, James R.

2015-01-01

Analytical and computational studies of reacting flows are extremely challenging due in part to nonlinearities of the underlying system of equations and long-range coupling mediated by heat and pressure fluctuations. However, many dynamical features of the flow can be inferred through low-order models if the flow constituents (e.g., eddies or vortices) and their symmetries, as well as the interactions among constituents, are established. Modal decompositions of high-frequency, high-resolution imaging, such as measurements of species-concentration fields through planar laser-induced florescence and of velocity fields through particle-image velocimetry, are the first step in the process. A methodology is introduced for deducing the flow constituents and their dynamics following modal decomposition. Proper orthogonal (POD) and dynamic mode (DMD) decompositions of two classes of problems are performed and their strengths compared. The first problem involves a cellular state generated in a flat circular flame front through symmetry breaking. The state contains two rings of cells that rotate clockwise at different rates. Both POD and DMD can be used to deconvolve the state into the two rings. In POD the contribution of each mode to the flow is quantified using the energy. Each DMD mode can be associated with an energy as well as a unique complex growth rate. Dynamic modes with the same spatial symmetry but different growth rates are found to be combined into a single POD mode. Thus, a flow can be approximated by a smaller number of POD modes. On the other hand, DMD provides a more detailed resolution of the dynamics. Two classes of reacting flows behind symmetric bluff bodies are also analyzed. In the first, symmetric pairs of vortices are released periodically from the two ends of the bluff body. The second flow contains von Karman vortices also, with a vortex being shed from one end of the bluff body followed by a second shedding from the opposite end. The way in which DMD can be used to deconvolve the second flow into symmetric and von Karman vortices is demonstrated. The analyses performed illustrate two distinct advantages of DMD: (1) Unlike proper orthogonal modes, each dynamic mode is associated with a unique complex growth rate. By comparing DMD spectra from multiple nominally identical experiments, it is possible to identify "reproducible" modes in a flow. We also find that although most high-energy modes are reproducible, some are not common between experimental realizations; in the examples considered, energy fails to differentiate between reproducible and nonreproducible modes. Consequently, it may not be possible to differentiate reproducible and nonreproducible modes in POD. (2) Time-dependent coefficients of dynamic modes are complex. Even in noisy experimental data, the dynamics of the phase of these coefficients (but not their magnitude) are highly regular. The phase represents the angular position of a rotating ring of cells and quantifies the downstream displacement of vortices in reacting flows. Thus, it is suggested that the dynamical characterizations of complex flows are best made through the phase dynamics of reproducible DMD modes.

Low-frequency Raman scattering in a Xe hydrate.

PubMed

Adichtchev, S V; Belosludov, V R; Ildyakov, A V; Malinovsky, V K; Manakov, A Yu; Subbotin, O S; Surovtsev, N V

2013-09-12

The physics of gas hydrates are rich in interesting phenomena such as anomalies for thermal conductivity, self-preservation effects for decomposition, and others. Some of these phenomena are presumably attributed to the resonance interaction of the rattling motions of guest molecules or atoms with the lattice modes. This can be expected to induce some specific features in the low-frequency (THz) vibrational response. Here we present results for low-frequency Raman scattering in a Xe hydrate, supported by numerical calculations of vibrational density of states. A number of narrow lines, located in the range from 18 to 90 cm(-1), were found in the Raman spectrum. Numerical calculations confirm that these lines correspond to resonance modes of the Xe hydrate. Also, low-frequency Raman scattering was studied during gas hydrate decomposition, and two scenarios were observed. The first one is the direct decomposition of the Xe hydrate to water and gas. The second one is the hydrate decomposition to ice and gas with subsequent melting of ice. In the latter case, a transient low-frequency Raman band is observed, which is associated with low-frequency bands (e.g., boson peak) of disordered solids.

Complete ensemble local mean decomposition with adaptive noise and its application to fault diagnosis for rolling bearings

NASA Astrophysics Data System (ADS)

Wang, Lei; Liu, Zhiwen; Miao, Qiang; Zhang, Xin

2018-06-01

Mode mixing resulting from intermittent signals is an annoying problem associated with the local mean decomposition (LMD) method. Based on noise-assisted approach, ensemble local mean decomposition (ELMD) method alleviates the mode mixing issue of LMD to some degree. However, the product functions (PFs) produced by ELMD often contain considerable residual noise, and thus a relatively large number of ensemble trials are required to eliminate the residual noise. Furthermore, since different realizations of Gaussian white noise are added to the original signal, different trials may generate different number of PFs, making it difficult to take ensemble mean. In this paper, a novel method is proposed called complete ensemble local mean decomposition with adaptive noise (CELMDAN) to solve these two problems. The method adds a particular and adaptive noise at every decomposition stage for each trial. Moreover, a unique residue is obtained after separating each PF, and the obtained residue is used as input for the next stage. Two simulated signals are analyzed to illustrate the advantages of CELMDAN in comparison to ELMD and CEEMDAN. To further demonstrate the efficiency of CELMDAN, the method is applied to diagnose faults for rolling bearings in an experimental case and an engineering case. The diagnosis results indicate that CELMDAN can extract more fault characteristic information with less interference than ELMD.

The spinodal decomposition in 17-4PH stainless steel subjected to long-term aging at 350 deg. C

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

Wang Jun; Zou Hong; Li Cong

2008-05-15

The influence of aging time on the microstructure evolution of 17-4 PH martensitic stainless steel was studied by transmission electron microscopy (TEM). Results showed that the martensite decomposed by a spinodal decomposition mechanism after the alloy was subjected to long-term aging at 350 deg. C. The fine scale spinodal decomposition of {alpha}-ferrite brought about a Cr-enriched bright stripe and a Fe-enriched dark stripe, i.e., {alpha}' and {alpha} phases, separately, which were perpendicular to the grain boundary. The spinodal decomposition started at the grain boundary. Then with prolonged aging time, the decomposition microstructure expanded from the grain boundary to interior. Themore » wavelength of the spinodally decomposed microstructure changed little with extended aging time.« less

Automated Identification of MHD Mode Bifurcation and Locking in Tokamaks

NASA Astrophysics Data System (ADS)

Riquezes, J. D.; Sabbagh, S. A.; Park, Y. S.; Bell, R. E.; Morton, L. A.

2017-10-01

Disruption avoidance is critical in reactor-scale tokamaks such as ITER to maintain steady plasma operation and avoid damage to device components. A key physical event chain that leads to disruptions is the appearance of rotating MHD modes, their slowing by resonant field drag mechanisms, and their locking. An algorithm has been developed that automatically detects bifurcation of the mode toroidal rotation frequency due to loss of torque balance under resonant braking, and mode locking for a set of shots using spectral decomposition. The present research examines data from NSTX, NSTX-U and KSTAR plasmas which differ significantly in aspect ratio (ranging from A = 1.3 - 3.5). The research aims to examine and compare the effectiveness of different algorithms for toroidal mode number discrimination, such as phase matching and singular value decomposition approaches, and to examine potential differences related to machine aspect ratio (e.g. mode eigenfunction shape variation). Simple theoretical models will be compared to the dynamics found. Main goals are to detect or potentially forecast the event chain early during a discharge. This would serve as a cue to engage active mode control or a controlled plasma shutdown. Supported by US DOE Contracts DE-SC0016614 and DE-AC02-09CH11466.

Structural Evolution Following Spinodal Decomposition of the Pseudoternary Compound (Pb0.3Sn0.1Ge0.6)Te

NASA Astrophysics Data System (ADS)

Dado, Boaz; Gelbstein, Yaniv; Mogilansky, Dimitri; Ezersky, Vladimir; Dariel, Moshe P.

2010-09-01

Pseudoternary (Ge,Sn,Pb)Te compounds display favorable thermoelectric properties. Spinodal decomposition in the quasiternary (Ge,Sn,Pb)Te system is at the origin of a wide solubility gap at low Sn concentrations. The structural evolution of the spinodal decomposition was investigated as a function of aging time at 500°C, using x-ray diffraction, electron microscopy, and scanning electron microscopy. The evolution of the structure at 500°C consists initially of a short diffusion-controlled demixing stage into Pb- and Ge-rich coherent areas, with compositions corresponding to the inflection points of the free-energy curve. The Pb-rich areas adopt configurations associated with the directions of the soft elastic moduli of the cubic compound. Both the Pb- and Ge-rich areas are supersaturated and undergo in a second stage a nucleation and growth process and give rise to a biphased structure with equilibrium compositions corresponding to the boundaries of the miscibility gap. The resulting Pb-rich areas display a relatively stable microstructure suggesting the presence of long-range interactions between the Pb-rich precipitates in the Ge-rich matrix.

Competition and evolution of dielectric waveguide mode and plasmonic waveguide mode

NASA Astrophysics Data System (ADS)

Yuan, Sheng-Nan; Fang, Yun-Tuan

2017-10-01

In order to study the coupling and evolution law of the waveguide mode and two plasmonic surface modes, we construct a line defect waveguide based on hexagonal honeycomb plasmonic photonic crystal. Through adjusting the radius of the edge dielectric rods, the competition and evolution behaviors occur between dielectric waveguide mode and plasmonic waveguide mode. There are three status: only plasmonic waveguide modes occur for rA < 0.09a; only dielectric waveguide modes occur for rA > 0.25a; two kinds of modes coexist for 0.09a < rA < 0.25a. The plasmonic waveguide mode has advantages in achieving slow light.

A projection method for low speed flows

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

Colella, P.; Pao, K.

The authors propose a decomposition applicable to low speed, inviscid flows of all Mach numbers less than 1. By using the Hodge decomposition, they may write the velocity field as the sum of a divergence-free vector field and a gradient of a scalar function. Evolution equations for these parts are presented. A numerical procedure based on this decomposition is designed, using projection methods for solving the incompressible variables and a backward-Euler method for solving the potential variables. Numerical experiments are included to illustrate various aspects of the algorithm.

Heave and Flow: Understanding the role of resonance and shape evolution for heaving flexible panels

NASA Astrophysics Data System (ADS)

Hoover, Alexander; Cortez, Ricardo; Tytell, Eric; Fauci, Lisa

2017-11-01

Many animals that swim or fly use their body to accelerate the fluid around them, transferring momentum from their bodies to the surrounding fluid. The emergent kinematics from this transfer are a result of the coupling between the fluid and the material properties of the body. Here we present a computational study of a 3-dimensional flexible panel that is heaved at its leading edge in an incompressible, viscous fluid. These high-fidelity numerical simulations enable us to examine the role of resonance, fluid forces, and panel deformations have on swimming performance. Varying both the passive material properties and the heaving frequency of the panel, we find peaks in trailing edge amplitude and forward swimming speed are determined by a dimensionless quantity, the effective flexibility. Modal decompositions of panel deflections reveal that the strength of each mode is related to the effective flexibility and peaks in the swimming speed and trailing edge amplitude correspond to peaks in the contributions of different modes. Panels of different material properties but with similar effective flexibilities have modal contributions that evolve similarly over the phase of the heaving cycle and agreement in dominant vortex structures generated by the panel. NSF RTG 1043626.

Simulation of Vortex Structure in Supersonic Free Shear Layer Using Pse Method

NASA Astrophysics Data System (ADS)

Guo, Xin; Wang, Qiang

The method of parabolized stability equations (PSE) are applied in the analysis of nonlinear stability and the simulation of flow structure in supersonic free shear layer. High accuracy numerical techniques including self-similar basic flow, high order differential method, appropriate transformation and decomposition of nonlinear terms are adopted and developed to solve the PSE effectively for free shear layer. The spatial evolving unstable waves which dominate the flow structure are investigated through nonlinear coupling spatial marching methods. The nonlinear interactions between harmonic waves are further analyzed and instantaneous flow field are obtained by adding the harmonic waves into basic flow. Relevant data agree well with that of DNS. The results demonstrate that T-S wave does not keeping growing exponential as the linear evolution, the energy transfer to high order harmonic modes and finally all harmonic modes get saturation due to the nonlinear interaction; Mean flow distortion is produced by the nonlinear interaction between the harmonic and its conjugate harmonic, makes great change to the average flow and increases the thickness of shear layer; PSE methods can well capture the large scale nonlinear flow structure in the supersonic free shear layer such as vortex roll-up, vortex pairing and nonlinear saturation.

Efficient solution of the Wigner-Liouville equation using a spectral decomposition of the force field

NASA Astrophysics Data System (ADS)

Van de Put, Maarten L.; Sorée, Bart; Magnus, Wim

2017-12-01

The Wigner-Liouville equation is reformulated using a spectral decomposition of the classical force field instead of the potential energy. The latter is shown to simplify the Wigner-Liouville kernel both conceptually and numerically as the spectral force Wigner-Liouville equation avoids the numerical evaluation of the highly oscillatory Wigner kernel which is nonlocal in both position and momentum. The quantum mechanical evolution is instead governed by a term local in space and non-local in momentum, where the non-locality in momentum has only a limited range. An interpretation of the time evolution in terms of two processes is presented; a classical evolution under the influence of the averaged driving field, and a probability-preserving quantum-mechanical generation and annihilation term. Using the inherent stability and reduced complexity, a direct deterministic numerical implementation using Chebyshev and Fourier pseudo-spectral methods is detailed. For the purpose of illustration, we present results for the time-evolution of a one-dimensional resonant tunneling diode driven out of equilibrium.

Ensemble empirical mode decomposition based fluorescence spectral noise reduction for low concentration PAHs

NASA Astrophysics Data System (ADS)

Wang, Shu-tao; Yang, Xue-ying; Kong, De-ming; Wang, Yu-tian

2017-11-01

A new noise reduction method based on ensemble empirical mode decomposition (EEMD) is proposed to improve the detection effect for fluorescence spectra. Polycyclic aromatic hydrocarbons (PAHs) pollutants, as a kind of important current environmental pollution source, are highly oncogenic. Using the fluorescence spectroscopy method, the PAHs pollutants can be detected. However, instrument will produce noise in the experiment. Weak fluorescent signals can be affected by noise, so we propose a way to denoise and improve the detection effect. Firstly, we use fluorescence spectrometer to detect PAHs to obtain fluorescence spectra. Subsequently, noises are reduced by EEMD algorithm. Finally, the experiment results show the proposed method is feasible.

Visualization of transient phenomena during the interaction of pulsed CO2 laser radiation with matter

NASA Astrophysics Data System (ADS)

Schmitt, R.; Hugenschmidt, Manfred

1996-05-01

Carbon-dioxide-lasers operating in the pulsed mode with energy densities up to several tens of J/cm2 and peak power densities in the multi-MW/cm2-range may cause fast heating and melting. Eventually quasi-explosive ejection, decomposition or vaporization of material can be observed. Surface plasmas are strongly influencing the energy transfer from the laser radiation field to any target. For optically transparent plastics, such as PMMA for example, only slowly expanding plasmas (LSC-waves) are ignited at fluences around 20 J/cm2, with a low level of self-luminosity. High brightness, supersonically expanding plasma jets (LSD-waves) are generated at the same fluences on glasses. Similar conditions were found for metals as well. From recordings with a high speed CCD-camera, interesting features concerning the initial plasma phases and temporal evolution were deduced. Additionally, information was obtained concerning the quasi explosive ejection of material for PMMA.

A spatiotemporal analysis of U.S. station temperature trends over the last century

NASA Astrophysics Data System (ADS)

Capparelli, V.; Franzke, C.; Vecchio, A.; Freeman, M. P.; Watkins, N. W.; Carbone, V.

2013-07-01

This study presents a nonlinear spatiotemporal analysis of 1167 station temperature records from the United States Historical Climatology Network covering the period from 1898 through 2008. We use the empirical mode decomposition method to extract the generally nonlinear trends of each station. The statistical significance of each trend is assessed against three null models of the background climate variability, represented by stochastic processes of increasing temporal correlation length. We find strong evidence that more than 50% of all stations experienced a significant trend over the last century with respect to all three null models. A spatiotemporal analysis reveals a significant cooling trend in the South-East and significant warming trends in the rest of the contiguous U.S. It also shows that the warming trend appears to have migrated equatorward. This shows the complex spatiotemporal evolution of climate change at local scales.

Probing Thermomechanics at the Nanoscale: Impulsively Excited Pseudosurface Acoustic Waves in Hypersonic Phononic Crystals

PubMed Central

2011-01-01

High-frequency surface acoustic waves can be generated by ultrafast laser excitation of nanoscale patterned surfaces. Here we study this phenomenon in the hypersonic frequency limit. By modeling the thermomechanics from first-principles, we calculate the system’s initial heat-driven impulsive response and follow its time evolution. A scheme is introduced to quantitatively access frequencies and lifetimes of the composite system’s excited eigenmodes. A spectral decomposition of the calculated response on the eigemodes of the system reveals asymmetric resonances that result from the coupling between surface and bulk acoustic modes. This finding allows evaluation of impulsively excited pseudosurface acoustic wave frequencies and lifetimes and expands our understanding of the scattering of surface waves in mesoscale metamaterials. The model is successfully benchmarked against time-resolved optical diffraction measurements performed on one-dimensional and two-dimensional surface phononic crystals, probed using light at extreme ultraviolet and near-infrared wavelengths. PMID:21910426

Multi-faults decoupling on turbo-expander using differential-based ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Li, Hongguang; Li, Ming; Li, Cheng; Li, Fucai; Meng, Guang

2017-09-01

This paper dedicates on the multi-faults decoupling of turbo-expander rotor system using Differential-based Ensemble Empirical Mode Decomposition (DEEMD). DEEMD is an improved version of DEMD to resolve the imperfection of mode mixing. The nonlinear behaviors of the turbo-expander considering temperature gradient with crack, rub-impact and pedestal looseness faults are investigated respectively, so that the baseline for the multi-faults decoupling can be established. DEEMD is then utilized on the vibration signals of the rotor system with coupling faults acquired by numerical simulation, and the results indicate that DEEMD can successfully decouple the coupling faults, which is more efficient than EEMD. DEEMD is also applied on the vibration signal of the misalignment coupling with rub-impact fault obtained during the adjustment of the experimental system. The conclusion shows that DEEMD can decompose the practical multi-faults signal and the industrial prospect of DEEMD is verified as well.

Decomposition Technique for Remaining Useful Life Prediction

NASA Technical Reports Server (NTRS)

Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor); Saxena, Abhinav (Inventor); Celaya, Jose R. (Inventor)

2014-01-01

The prognostic tool disclosed here decomposes the problem of estimating the remaining useful life (RUL) of a component or sub-system into two separate regression problems: the feature-to-damage mapping and the operational conditions-to-damage-rate mapping. These maps are initially generated in off-line mode. One or more regression algorithms are used to generate each of these maps from measurements (and features derived from these), operational conditions, and ground truth information. This decomposition technique allows for the explicit quantification and management of different sources of uncertainty present in the process. Next, the maps are used in an on-line mode where run-time data (sensor measurements and operational conditions) are used in conjunction with the maps generated in off-line mode to estimate both current damage state as well as future damage accumulation. Remaining life is computed by subtracting the instance when the extrapolated damage reaches the failure threshold from the instance when the prediction is made.

Tourism forecasting using modified empirical mode decomposition and group method of data handling

NASA Astrophysics Data System (ADS)

Yahya, N. A.; Samsudin, R.; Shabri, A.

2017-09-01

In this study, a hybrid model using modified Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) model is proposed for tourism forecasting. This approach reconstructs intrinsic mode functions (IMFs) produced by EMD using trial and error method. The new component and the remaining IMFs is then predicted respectively using GMDH model. Finally, the forecasted results for each component are aggregated to construct an ensemble forecast. The data used in this experiment are monthly time series data of tourist arrivals from China, Thailand and India to Malaysia from year 2000 to 2016. The performance of the model is evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) where conventional GMDH model and EMD-GMDH model are used as benchmark models. Empirical results proved that the proposed model performed better forecasts than the benchmarked models.

An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG.

PubMed

Orosco, Lorena; Laciar, Eric; Correa, Agustina Garces; Torres, Abel; Graffigna, Juan P

2009-01-01

Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates the energy of each IMF and performs the detection based on an energy threshold and a minimum duration decision. The algorithm was tested in 9 invasive EEG records provided and validated by the Epilepsy Center of the University Hospital of Freiburg. In 90 segments analyzed (39 with epileptic seizures) the sensitivity and specificity obtained with the method were of 56.41% and 75.86% respectively. It could be concluded that EMD is a promissory method for epileptic seizure detection in EEG records.

Fringe-projection profilometry based on two-dimensional empirical mode decomposition.

PubMed

Zheng, Suzhen; Cao, Yiping

2013-11-01

In 3D shape measurement, because deformed fringes often contain low-frequency information degraded with random noise and background intensity information, a new fringe-projection profilometry is proposed based on 2D empirical mode decomposition (2D-EMD). The fringe pattern is first decomposed into numbers of intrinsic mode functions by 2D-EMD. Because the method has partial noise reduction, the background components can be removed to obtain the fundamental components needed to perform Hilbert transformation to retrieve the phase information. The 2D-EMD can effectively extract the modulation phase of a single direction fringe and an inclined fringe pattern because it is a full 2D analysis method and considers the relationship between adjacent lines of a fringe patterns. In addition, as the method does not add noise repeatedly, as does ensemble EMD, the data processing time is shortened. Computer simulations and experiments prove the feasibility of this method.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

PubMed

Sun, Yanfeng; Gao, Junbin; Hong, Xia; Mishra, Bamdev; Yin, Baocai

2016-03-01

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

Telephone-quality pathological speech classification using empirical mode decomposition.

PubMed

Kaleem, M F; Ghoraani, B; Guergachi, A; Krishnan, S

2011-01-01

This paper presents a computationally simple and effective methodology based on empirical mode decomposition (EMD) for classification of telephone quality normal and pathological speech signals. EMD is used to decompose continuous normal and pathological speech signals into intrinsic mode functions, which are analyzed to extract physically meaningful and unique temporal and spectral features. Using continuous speech samples from a database of 51 normal and 161 pathological speakers, which has been modified to simulate telephone quality speech under different levels of noise, a linear classifier is used with the feature vector thus obtained to obtain a high classification accuracy, thereby demonstrating the effectiveness of the methodology. The classification accuracy reported in this paper (89.7% for signal-to-noise ratio 30 dB) is a significant improvement over previously reported results for the same task, and demonstrates the utility of our methodology for cost-effective remote voice pathology assessment over telephone channels.

Forecasting stochastic neural network based on financial empirical mode decomposition.

PubMed

Wang, Jie; Wang, Jun

2017-06-01

In an attempt to improve the forecasting accuracy of stock price fluctuations, a new one-step-ahead model is developed in this paper which combines empirical mode decomposition (EMD) with stochastic time strength neural network (STNN). The EMD is a processing technique introduced to extract all the oscillatory modes embedded in a series, and the STNN model is established for considering the weight of occurrence time of the historical data. The linear regression performs the predictive availability of the proposed model, and the effectiveness of EMD-STNN is revealed clearly through comparing the predicted results with the traditional models. Moreover, a new evaluated method (q-order multiscale complexity invariant distance) is applied to measure the predicted results of real stock index series, and the empirical results show that the proposed model indeed displays a good performance in forecasting stock market fluctuations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using a Hands-On Hydrogen Peroxide Decomposition Activity to Teach Catalysis Concepts to K-12 Students

ERIC Educational Resources Information Center

Cybulskis, Viktor J.; Ribeiro, Fabio H.; Gounder, Rajamani

2016-01-01

A versatile and transportable laboratory apparatus was developed for middle and high school (6th-12th grade) students as part of a hands-on outreach activity to estimate catalytic rates of hydrogen peroxide decomposition from oxygen evolution rates measured by using a volumetric displacement method. The apparatus was constructed with inherent…

An evaluation: The potential of discarded tires as a source of fuel

NASA Technical Reports Server (NTRS)

Collins, L. W.; Downs, W. R.; Gibson, E. K.; Moore, G. W.

1974-01-01

The destructive distillation of rubber tire samples was studied by thermogravimetry, differential scanning calorimetry, combustion calorimetry, and mass spectroscopy. The decomposition reaction was found to be exothermic and produced a mass loss of 65 percent. The gas evolution curves that were obtained indicate that a variety of organic materials are evolved simultaneously during the decomposition of the rubber polymer.

Phase-field modeling of diffusional phase behaviors of solid surfaces: A case study of phase-separating Li XFePO 4 electrode particles

DOE PAGES

Heo, Tae Wook; Chen, Long-Qing; Wood, Brandon C.

2015-04-08

In this paper, we present a comprehensive phase-field model for simulating diffusion-mediated kinetic phase behaviors near the surface of a solid particle. The model incorporates elastic inhomogeneity and anisotropy, diffusion mobility anisotropy, interfacial energy anisotropy, and Cahn–Hilliard diffusion kinetics. The free energy density function is formulated based on the regular solution model taking into account the possible solute-surface interaction near the surface. The coherency strain energy is computed using the Fourier-spectral iterative-perturbation method due to the strong elastic inhomogeneity with a zero surface traction boundary condition. Employing a phase-separating Li XFePO 4 electrode particle for Li-ion batteries as a modelmore » system, we perform parametric three-dimensional computer simulations. The model permits the observation of surface phase behaviors that are different from the bulk counterpart. For instance, it reproduces the theoretically well-established surface modes of spinodal decomposition of an unstable solid solution: the surface mode of coherent spinodal decomposition and the surface-directed spinodal decomposition mode. We systematically investigate the influences of major factors on the kinetic surface phase behaviors during the diffusional process. Finally, our simulation study provides insights for tailoring the internal phase microstructure of a particle by controlling the surface phase morphology.« less

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

NASA Technical Reports Server (NTRS)

Huang, Norden E.

1999-01-01

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Identification of significant intrinsic mode functions for the diagnosis of induction motor fault.

PubMed

Cho, Sangjin; Shahriar, Md Rifat; Chong, Uipil

2014-08-01

For the analysis of non-stationary signals generated by a non-linear process like fault of an induction motor, empirical mode decomposition (EMD) is the best choice as it decomposes the signal into its natural oscillatory modes known as intrinsic mode functions (IMFs). However, some of these oscillatory modes obtained from a fault signal are not significant as they do not bear any fault signature and can cause misclassification of the fault instance. To solve this issue, a novel IMF selection algorithm is proposed in this work.

Analysis of the SFR-M∗ plane at z < 3: single fitting versus multi-Gaussian decomposition

NASA Astrophysics Data System (ADS)

Bisigello, L.; Caputi, K. I.; Grogin, N.; Koekemoer, A.

2018-01-01

The analysis of galaxies on the star formation rate-stellar mass (SFR-M∗) plane is a powerful diagnostic for galaxy evolution at different cosmic times. We consider a sample of 24 463 galaxies from the CANDELS/GOODS-S survey to conduct a detailed analysis of the SFR-M∗ relation at redshifts re than three dex in stellar mass. To obtain SFR estimates, we utilise mid- and far-IR photometry when available, and rest-UV fluxes for all the other galaxies. We perform our analysis in different redshift bins, with two different methods: 1) a linear regression fitting of all star-forming galaxies, defined as those with specific SFRs log 10(sSFR/ yr-1) > -9.8, similarly to what is typically done in the literature; 2) a multi-Gaussian decomposition to identify the galaxy main sequence (MS), the starburst sequence and the quenched galaxy cloud. We find that the MS slope becomes flatter when higher stellar mass cuts are adopted, and that the apparent slope change observed at high masses depends on the SFR estimation method. In addition, the multi-Gaussian decomposition reveals the presence of a starburst population which increases towards low stellar masses and high redshifts. We find that starbursts make up 5% of all galaxies at z = 0.5-1.0, while they account for 16% of galaxies at 2

Acoustics flow analysis in circular duct using sound intensity and dynamic mode decomposition

NASA Astrophysics Data System (ADS)

Weyna, S.

2014-08-01

Sound intensity generation in hard-walled duct with acoustic flow (no mean-flow) is treated experimentally and shown graphically. In paper, numerous methods of visualization illustrating the vortex flow (2D, 3D) can graphically explain diffraction and scattering phenomena occurring inside the duct and around open end area. Sound intensity investigation in annular duct gives a physical picture of sound waves in any duct mode. In the paper, modal energy analysis are discussed with particular reference to acoustics acoustic orthogonal decomposition (AOD). The image of sound intensity fields before and above "cut-off" frequency region are found to compare acoustic modes which might resonate in duct. The experimental results show also the effects of axial and swirling flow. However acoustic field is extremely complicated, because pressures in non-propagating (cut-off) modes cooperate with the particle velocities in propagating modes, and vice versa. Measurement in cylindrical duct demonstrates also the cut-off phenomenon and the effect of reflection from open end. The aim of experimental study was to obtain information on low Mach number flows in ducts in order to improve physical understanding and validate theoretical CFD and CAA models that still may be improved.

Endothermic decompositions of inorganic monocrystalline thin plates. II. Displacement rate modulation of the reaction front

NASA Astrophysics Data System (ADS)

Bertrand, G.; Comperat, M.; Lallemant, M.

1980-09-01

Copper sulfate pentahydrate dehydration into trihydrate was investigated using monocrystalline platelets with (110) crystallographic orientation. Temperature and pressure conditions were selected so as to obtain elliptical trihydrate domains. The study deals with the evolution, vs time, of elliptical domain dimensions and the evolution, vs water vapor pressure, of the {D}/{d} ratio of ellipse axes and on the other hand of the interface displacement rate along a given direction. The phenomena observed are not basically different from those yielded by the overall kinetic study of the solid sample. Their magnitude, however, is modulated depending on displacement direction. The results are analyzed within the scope of our study of endothermic decomposition of solids.

On the solutions of fractional order of evolution equations

NASA Astrophysics Data System (ADS)

Morales-Delgado, V. F.; Taneco-Hernández, M. A.; Gómez-Aguilar, J. F.

2017-01-01

In this paper we present a discussion of generalized Cauchy problems in a diffusion wave process, we consider bi-fractional-order evolution equations in the Riemann-Liouville, Liouville-Caputo, and Caputo-Fabrizio sense. Through Fourier transforms and Laplace transform we derive closed-form solutions to the Cauchy problems mentioned above. Similarly, we establish fundamental solutions. Finally, we give an application of the above results to the determination of decompositions of Dirac type for bi-fractional-order equations and write a formula for the moments for the fractional vibration of a beam equation. This type of decomposition allows us to speak of internal degrees of freedom in the vibration of a beam equation.

Variability modes of precipitation along a Central Mediterranean area and their relations with ENSO, NAO, and other climatic patterns

NASA Astrophysics Data System (ADS)

Kalimeris, Anastasios; Ranieri, Ezio; Founda, Dimitra; Norrant, Caroline

2017-12-01

This study analyses a century-long set of precipitation time series in the Central Mediterranean (encompassing the Greek Ionian and the Italian Puglia regions) and investigates the statistically significant modes of the interannual precipitation variability using efficient methods of spectral decomposition. The statistical relations and the possible physical couplings between the detected modes and the global or hemispheric patterns of climatic variability (the El Niño Southern Oscillation or ENSO, the North Atlantic Oscillation or NAO, the East Atlantic or EA, the Scandinavian or SCAND, and others) were examined in the time-frequency domain and low-order synchronization events were sought. Significant modes of precipitation variability were detected in the Taranto Gulf and the southern part of the Greek Ionian region at the sub-decadal scales (mostly driven by the SCAND pattern) and particularly at the decadal and quasi-decadal scales, where strong relations found with the ENSO activity (under complex implications of EA and NAO) prior to the 1930s or after the early-1970s. The precipitation variations in the Adriatic stations of Puglia are dominated by significant bi-decadal modes which found to be coherent with the ENSO activity and also weakly related with the Atlantic Ocean sea surface temperature intrinsic variability. Additionally, important discontinuities characterize the evolution of precipitation in certain stations of the Taranto Gulf and the Greek Ionian region during the early-1960s and particularly during the early-1970s, followed by significant reductions in the mean annual precipitation. These discontinuities seem to be associated with regional effects of NAO and SCAND, probably combined with the impact of the 1970s climatic shift in the Pacific and the ENSO variability.

Unsteady Shear Disturbances Within a Two Dimensional Stratified Flow

NASA Technical Reports Server (NTRS)

Yokota, Jeffrey W.

1992-01-01

The origin and evolution of shear disturbances within a stratified, inviscid, incompressible flow are investigated numerically by a Clebsch/Weber decomposition based scheme. In contrast to homogeneous flows, within which vorticity can be redistributed but not generated, the presence of a density stratification can render an otherwise irrotational flow vortical. In this work, a kinematic decomposition of the unsteady Euler equations separates the unsteady velocity field into rotational and irrotational components. The subsequent evolution of these components is used to study the influence various velocity disturbances have on both stratified and homogeneous flows. In particular, the flow within a two-dimensional channel is used to investigate the evolution of rotational disturbances, generated or convected, downstream from an unsteady inflow condition. Contrasting simulations of both stratified and homogeneous flows are used to distinguish between redistributed inflow vorticity and that which is generated by a density stratification.

Partial differential equation-based approach for empirical mode decomposition: application on image analysis.

PubMed

Niang, Oumar; Thioune, Abdoulaye; El Gueirea, Mouhamed Cheikh; Deléchelle, Eric; Lemoine, Jacques

2012-09-01

The major problem with the empirical mode decomposition (EMD) algorithm is its lack of a theoretical framework. So, it is difficult to characterize and evaluate this approach. In this paper, we propose, in the 2-D case, the use of an alternative implementation to the algorithmic definition of the so-called "sifting process" used in the original Huang's EMD method. This approach, especially based on partial differential equations (PDEs), was presented by Niang in previous works, in 2005 and 2007, and relies on a nonlinear diffusion-based filtering process to solve the mean envelope estimation problem. In the 1-D case, the efficiency of the PDE-based method, compared to the original EMD algorithmic version, was also illustrated in a recent paper. Recently, several 2-D extensions of the EMD method have been proposed. Despite some effort, 2-D versions for EMD appear poorly performing and are very time consuming. So in this paper, an extension to the 2-D space of the PDE-based approach is extensively described. This approach has been applied in cases of both signal and image decomposition. The obtained results confirm the usefulness of the new PDE-based sifting process for the decomposition of various kinds of data. Some results have been provided in the case of image decomposition. The effectiveness of the approach encourages its use in a number of signal and image applications such as denoising, detrending, or texture analysis.

Multiscale Processes of Hurricane Sandy (2012) as Revealed by the CAMVis-MAP

NASA Astrophysics Data System (ADS)

Shen, B.; Li, J. F.; Cheung, S.

2013-12-01

In late October 2012, Storm Sandy made landfall near Brigantine, New Jersey, devastating surrounding areas and causing tremendous economic loss and hundreds of fatalities (Blake et al., 2013). An estimated damage of $50 billion made Sandy become the second costliest tropical cyclone (TC) in US history, surpassed only by Hurricane Katrina (2005). Central questions to be addressed include (1) to what extent the lead time of severe storm prediction such as Sandy can be extended (e.g., Emanuel 2012); and (2) whether and how advanced global model, supercomputing technology and numerical algorithm can help effectively illustrate the complicated physical processes that are associated with the evolution of the storms. In this study, the predictability of Sandy is addressed with a focus on short-term (or extended-range) genesis prediction as the first step toward the goal of understanding the relationship between extreme events, such as Sandy, and the current climate. The newly deployed Coupled Advanced global mesoscale Modeling (GMM) and concurrent Visualization (CAMVis) system is used for this study. We will show remarkable simulations of Hurricane Sandy with the GMM, including realistic 7-day track and intensity forecast and genesis predictions with a lead time of up to 6 days (e.g., Shen et al., 2013, GRL, submitted). We then discuss the enabling role of the high-resolution 4-D (time-X-Y-Z) visualizations in illustrating TC's transient dynamics and its interaction with tropical waves. In addition, we have finished the parallel implementation of the ensemble empirical mode decomposition (PEEMD, Cheung et al., 2013, AGU13, submitted) method that will be soon integrated into the multiscale analysis package (MAP) for the analysis of tropical weather systems such as TCs and tropical waves. While the original EEMD has previously shown superior performance in decomposition of nonlinear (local) and non-stationary data into different intrinsic modes which stay within the natural filter period windows, the PEEMD achieves a speedup of over 100 times as compared to the original EEMD. The advanced GMM, 4D visualizations and PEEMD method are being used to examine the multiscale processes of Sandy and its environmental flows that may contribute to the extended lead-time predictability of Hurricane Sandy. Figure 1: Evolution of Hurricane Sandy (2012) as revealed by the advanced visualization.

Broadband and fabrication-tolerant on-chip scalable mode-division multiplexing based on mode-evolution counter-tapered couplers.

PubMed

Wang, Jing; Xuan, Yi; Qi, Minghao; Huang, Haiyang; Li, You; Li, Ming; Chen, Xin; Sheng, Zhen; Wu, Aimin; Li, Wei; Wang, Xi; Zou, Shichang; Gan, Fuwan

2015-05-01

A broadband and fabrication-tolerant on-chip scalable mode-division multiplexing (MDM) scheme based on mode-evolution counter-tapered couplers is designed and experimentally demonstrated on a silicon-on-insulator (SOI) platform. Due to the broadband advantage offered by mode evolution, the two-mode MDM link exhibits a very large, -1  dB bandwidth of >180  nm, which is considerably larger than most of the previously reported MDM links whether they are based on mode-interference or evolution. In addition, the performance metrics remain stable for large-device width deviations from the designed valued by -60  nm to 40 nm, and for temperature variations from -25°C to 75°C. This MDM scheme can be readily extended to higher-order mode multiplexing and a three-mode MDM link is measured with less than -10  dB crosstalk from 1.46 to 1.64 μm wavelength range.

Gas evolution from cathode materials: A pathway to solvent decomposition concomitant to SEI formation.

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

Browning, Katie L; Baggetto, Loic; Unocic, Raymond R

This work reports a method to explore the catalytic reactivity of electrode surfaces towards the decomposition of carbonate solvents [ethylene carbonate (EC), dimethyl carbonate (DMC), and EC/DMC]. We show that the decomposition of a 1:1 wt% EC/DMC mixture is accelerated over certain commercially available LiCoO2 materials resulting in the formation of CO2 while over pure EC or DMC the reaction is much slower or negligible. The solubility of the produced CO2 in carbonate solvents is high (0.025 grams/mL) which masks the effect of electrolyte decomposition during storage or use. The origin of this decomposition is not clear but it ismore » expected to be present on other cathode materials and may affect the analysis of SEI products as well as the safety of Li-ion batteries.« less

Direct observation of nanowire growth and decomposition.

PubMed

Rackauskas, Simas; Shandakov, Sergey D; Jiang, Hua; Wagner, Jakob B; Nasibulin, Albert G

2017-09-26

Fundamental concepts of the crystal formation suggest that the growth and decomposition are determined by simultaneous embedding and removal of the atoms. Apparently, by changing the crystal formation conditions one can switch the regimes from the growth to decomposition. To the best of our knowledge, so far this has been only postulated, but never observed at the atomic level. By means of in situ environmental transmission electron microscopy we monitored and examined the atomic layer transformation at the conditions of the crystal growth and its decomposition using CuO nanowires selected as a model object. The atomic layer growth/decomposition was studied by varying an O 2 partial pressure. Three distinct regimes of the atomic layer evolution were experimentally observed: growth, transition and decomposition. The transition regime, at which atomic layer growth/decomposition switch takes place, is characterised by random nucleation of the atomic layers on the growing {111} surface. The decomposition starts on the side of the nanowire by removing the atomic layers without altering the overall crystal structure, which besides the fundamental importance offers new possibilities for the nanowire manipulation. Understanding of the crystal growth kinetics and nucleation at the atomic level is essential for the precise control of 1D crystal formation.

Mode evolution in polarization maintain few mode fibers and applications in mode-division-multiplexing systems

NASA Astrophysics Data System (ADS)

Li, Yan; Zeng, Xinglin; Mo, Qi; Li, Wei; Liu, Zhijian; Wu, Jian

2016-10-01

In few-mode polarization-maintaining-fiber (FM-PMF), the effective-index splitting exists not only between orthogonally polarization state but also between degenerated modes within a high-order mode group. Hence besides the polarization state evolution, the mode patterns in each LP set are need to be analyzed. In this letter, the completed firstorder mode (LP11 mode) evolution in PM-FMF is analyzed and represented by analogous Jones vector and Poincarésphere respectively. Furthermore, with Jones matrix analysis, the modal dynamics in FM-PMFs is conveniently analyzed. The conclusions are used to propose a PM-FMF based LP11 mode rotator and an PM-FMF based OAM generator. Both simulation and experiments are conducted to investigate performance of the two devices.

Genetic Bases of Fungal White Rot Wood Decay Predicted by Phylogenomic Analysis of Correlated Gene-Phenotype Evolution.

PubMed

Nagy, László G; Riley, Robert; Bergmann, Philip J; Krizsán, Krisztina; Martin, Francis M; Grigoriev, Igor V; Cullen, Dan; Hibbett, David S

2017-01-01

Fungal decomposition of plant cell walls (PCW) is a complex process that has diverse industrial applications and huge impacts on the carbon cycle. White rot (WR) is a powerful mode of PCW decay in which lignin and carbohydrates are both degraded. Mechanistic studies of decay coupled with comparative genomic analyses have provided clues to the enzymatic components of WR systems and their evolutionary origins, but the complete suite of genes necessary for WR remains undetermined. Here, we use phylogenomic comparative methods, which we validate through simulations, to identify shifts in gene family diversification rates that are correlated with evolution of WR, using data from 62 fungal genomes. We detected 409 gene families that appear to be evolutionarily correlated with WR. The identified gene families encode well-characterized decay enzymes, e.g., fungal class II peroxidases and cellobiohydrolases, and enzymes involved in import and detoxification pathways, as well as 73 gene families that have no functional annotation. About 310 of the 409 identified gene families are present in the genome of the model WR fungus Phanerochaete chrysosporium and 192 of these (62%) have been shown to be upregulated under ligninolytic culture conditions, which corroborates the phylogeny-based functional inferences. These results illuminate the complexity of WR and suggest that its evolution has involved a general elaboration of the decay apparatus, including numerous gene families with as-yet unknown exact functions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Linear optics only allows every possible quantum operation for one photon or one port

NASA Astrophysics Data System (ADS)

Moyano-Fernández, Julio José; Garcia-Escartin, Juan Carlos

2017-01-01

We study the evolution of the quantum state of n photons in m different modes when they go through a lossless linear optical system. We show that there are quantum evolution operators U that cannot be built with linear optics alone unless the number of photons or the number of modes is equal to one. The evolution for single photons can be controlled with the known realization of any unitary proved by Reck, Zeilinger, Bernstein and Bertani. The evolution for a single mode corresponds to the trivial evolution in a phase shifter. We analyze these two cases and prove that any other combination of the number of photons and modes produces a Hilbert state too large for the linear optics system to give any desired evolution.

Evolution of the f-mode instability in neutron stars and gravitational wave detectability

NASA Astrophysics Data System (ADS)

Passamonti, A.; Gaertig, E.; Kokkotas, K. D.; Doneva, D.

2013-04-01

We study the dynamical evolution of the gravitational-wave driven instability of the f mode in rapidly rotating relativistic stars. With an approach based on linear perturbation theory we describe the evolution of the mode amplitude and follow the trajectory of a newborn neutron star through its instability window. The influence on the f-mode instability of the magnetic field and the presence of an unstable r mode is also considered. Two different configurations are studied in more detail, an N=1 polytrope with a typical mass and radius and a more massive polytropic N=0.62 model with gravitational mass M=1.98M⊙. We study several evolutions with different initial rotation rates and temperature and determine the gravitational waves radiated during the instability. In more massive models, an unstable f mode with a saturation energy of about 10-6M⊙c2 may generate a gravitational wave signal which can be detected by the Advanced LIGO/Virgo detector from the Virgo cluster. The magnetic field affects the evolution and then the detectability of the gravitational radiation when its strength is higher than 1012G, while the effects of an unstable r mode become dominant when this mode reaches the maximum saturation value allowed by nonlinear mode couplings. However, the relative saturation amplitude of the f and r modes must be known more accurately in order to provide a definitive answer to this issue. From the thermal evolution we find also that the heat generated by shear viscosity during the saturation phase completely balances the neutrinos’ cooling and prevents the star from entering the regime of mutual friction. The evolution time of the instability is therefore longer and the star loses significantly larger amounts of angular momentum via gravitational waves.

Identification of sudden stiffness changes in the acceleration response of a bridge to moving loads using ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Aied, H.; González, A.; Cantero, D.

2016-01-01

The growth of heavy traffic together with aggressive environmental loads poses a threat to the safety of an aging bridge stock. Often, damage is only detected via visual inspection at a point when repairing costs can be quite significant. Ideally, bridge managers would want to identify a stiffness change as soon as possible, i.e., as it is occurring, to plan for prompt measures before reaching a prohibitive cost. Recent developments in signal processing techniques such as wavelet analysis and empirical mode decomposition (EMD) have aimed to address this need by identifying a stiffness change from a localised feature in the structural response to traffic. However, the effectiveness of these techniques is limited by the roughness of the road profile, the vehicle speed and the noise level. In this paper, ensemble empirical mode decomposition (EEMD) is applied by the first time to the acceleration response of a bridge model to a moving load with the purpose of capturing sudden stiffness changes. EEMD is more adaptive and appears to be better suited to non-linear signals than wavelets, and it reduces the mode mixing problem present in EMD. EEMD is tested in a variety of theoretical 3D vehicle-bridge interaction scenarios. Stiffness changes are successfully identified, even for small affected regions, relatively poor profiles, high vehicle speeds and significant noise. The latter is due to the ability of EEMD to separate high frequency components associated to sudden stiffness changes from other frequency components associated to the vehicle-bridge interaction system.

CFD modeling of space-time evolution of fast pyrolysis products in a bench-scale fluidized-bed reactor

USDA-ARS?s Scientific Manuscript database

A model for the evolution of pyrolysis products in a fluidized bed has been developed. In this study the unsteady constitutive transport equations for inert gas flow and decomposition kinetics were modeled using the commercial computational fluid dynamics (CFD) software FLUENT-12. The model system d...

Quantitative investigation into the influence of temperature on carbide and austenite evolution during partitioning of a quenched and partitioned steel

DOE PAGES

Pierce, Dean T.; Coughlin, D. R.; Williamson, Don L.; ...

2016-05-03

Here, the influence of partitioning temperature on microstructural evolution during quenching and partitioning was investigated in a 0.38C-1.54Mn-1.48Si wt.% steel using Mössbauer spectroscopy and transmission electron microscopy. η-carbide formation occurs in the martensite during the quenching, holding, and partitioning steps. More effective carbon partitioning from martensite to austenite was observed at 450 than 400°C, resulting in lower martensite carbon contents, less carbide formation, and greater retained austenite amounts for short partitioning times. Conversely, greater austenite decomposition occurs at 450°C for longer partitioning times. Lastly, cementite forms during austenite decomposition and in the martensite for longer partitioning times at 450°C.

Iterative variational mode decomposition based automated detection of glaucoma using fundus images.

PubMed

Maheshwari, Shishir; Pachori, Ram Bilas; Kanhangad, Vivek; Bhandary, Sulatha V; Acharya, U Rajendra

2017-09-01

Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition. Various features namely, Kapoor entropy, Renyi entropy, Yager entropy, and fractal dimensions are extracted from VMD components. ReliefF algorithm is used to select the discriminatory features and these features are then fed to the least squares support vector machine (LS-SVM) for classification. Our proposed method achieved classification accuracies of 95.19% and 94.79% using three-fold and ten-fold cross-validation strategies, respectively. This system can aid the ophthalmologists in confirming their manual reading of classes (glaucoma or normal) using fundus images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Speech rhythm analysis with decomposition of the amplitude envelope: characterizing rhythmic patterns within and across languages.

PubMed

Tilsen, Sam; Arvaniti, Amalia

2013-07-01

This study presents a method for analyzing speech rhythm using empirical mode decomposition of the speech amplitude envelope, which allows for extraction and quantification of syllabic- and supra-syllabic time-scale components of the envelope. The method of empirical mode decomposition of a vocalic energy amplitude envelope is illustrated in detail, and several types of rhythm metrics derived from this method are presented. Spontaneous speech extracted from the Buckeye Corpus is used to assess the effect of utterance length on metrics, and it is shown how metrics representing variability in the supra-syllabic time-scale components of the envelope can be used to identify stretches of speech with targeted rhythmic characteristics. Furthermore, the envelope-based metrics are used to characterize cross-linguistic differences in speech rhythm in the UC San Diego Speech Lab corpus of English, German, Greek, Italian, Korean, and Spanish speech elicited in read sentences, read passages, and spontaneous speech. The envelope-based metrics exhibit significant effects of language and elicitation method that argue for a nuanced view of cross-linguistic rhythm patterns.

A data-driven decomposition approach to model aerodynamic forces on flapping airfoils

NASA Astrophysics Data System (ADS)

Raiola, Marco; Discetti, Stefano; Ianiro, Andrea

2017-11-01

In this work, we exploit a data-driven decomposition of experimental data from a flapping airfoil experiment with the aim of isolating the main contributions to the aerodynamic force and obtaining a phenomenological model. Experiments are carried out on a NACA 0012 airfoil in forward flight with both heaving and pitching motion. Velocity measurements of the near field are carried out with Planar PIV while force measurements are performed with a load cell. The phase-averaged velocity fields are transformed into the wing-fixed reference frame, allowing for a description of the field in a domain with fixed boundaries. The decomposition of the flow field is performed by means of the POD applied on the velocity fluctuations and then extended to the phase-averaged force data by means of the Extended POD approach. This choice is justified by the simple consideration that aerodynamic forces determine the largest contributions to the energetic balance in the flow field. Only the first 6 modes have a relevant contribution to the force. A clear relationship can be drawn between the force and the flow field modes. Moreover, the force modes are closely related (yet slightly different) to the contributions of the classic potential models in literature, allowing for their correction. This work has been supported by the Spanish MINECO under Grant TRA2013-41103-P.

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis

NASA Astrophysics Data System (ADS)

Jiang, Fan; Zhu, Zhencai; Li, Wei; Zhou, Gongbo; Chen, Guoan

2014-07-01

Accurately identifying faults in rotor-bearing systems by analyzing vibration signals, which are nonlinear and nonstationary, is challenging. To address this issue, a new approach based on ensemble empirical mode decomposition (EEMD) and self-zero space projection analysis is proposed in this paper. This method seeks to identify faults appearing in a rotor-bearing system using simple algebraic calculations and projection analyses. First, EEMD is applied to decompose the collected vibration signals into a set of intrinsic mode functions (IMFs) for features. Second, these extracted features under various mechanical health conditions are used to design a self-zero space matrix according to space projection analysis. Finally, the so-called projection indicators are calculated to identify the rotor-bearing system's faults with simple decision logic. Experiments are implemented to test the reliability and effectiveness of the proposed approach. The results show that this approach can accurately identify faults in rotor-bearing systems.

The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

PubMed

Wang, Gang; Teng, Chaolin; Li, Kuo; Zhang, Zhonglin; Yan, Xiangguo

2016-09-01

The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

PubMed

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

[A Feature Extraction Method for Brain Computer Interface Based on Multivariate Empirical Mode Decomposition].

PubMed

Wang, Jinjia; Liu, Yuan

2015-04-01

This paper presents a feature extraction method based on multivariate empirical mode decomposition (MEMD) combining with the power spectrum feature, and the method aims at the non-stationary electroencephalogram (EEG) or magnetoencephalogram (MEG) signal in brain-computer interface (BCI) system. Firstly, we utilized MEMD algorithm to decompose multichannel brain signals into a series of multiple intrinsic mode function (IMF), which was proximate stationary and with multi-scale. Then we extracted and reduced the power characteristic from each IMF to a lower dimensions using principal component analysis (PCA). Finally, we classified the motor imagery tasks by linear discriminant analysis classifier. The experimental verification showed that the correct recognition rates of the two-class and four-class tasks of the BCI competition III and competition IV reached 92.0% and 46.2%, respectively, which were superior to the winner of the BCI competition. The experimental proved that the proposed method was reasonably effective and stable and it would provide a new way for feature extraction.

Response of rotation-translation blocked proteins using Langevin dynamics on a locally harmonic landscape.

PubMed

Manson, Anthony C; Coalson, Rob D

2012-10-11

Langevin dynamics is used to compute the time evolution of the nonequilibrium motion of the atomic coordinates of a protein in response to ligand dissociation. The protein potential energy surface (PES) is approximated by a harmonic basin about the minimum of the unliganded state. Upon ligand dissociation, the protein undergoes relaxation from the bound to the unbound state. A coarse graining scheme based on rotation translation blocks (RTB) is applied to the relaxation of the two domain iron transport protein, ferric binding protein. This scheme provides a natural and efficient way to freeze out the small amplitude, high frequency motions within each rigid fragment, thereby allowing for the number of dynamical degrees of freedom to be reduced. The results obtained from all flexible atom (constraint free) dynamics are compared to those obtained using RTB-Langevin dynamics. To assess the impact of the assumed rigid fragment clustering on the temporal relaxation dynamics of the protein molecule, three distinct rigid block decompositions were generated and their responses compared. Each of the decompositions was a variant of the one-block-per-residue grouping, with their force and friction matrices being derived from their fully flexible counterpart. Monitoring the time evolution of the distance separating a selected pair of amino acids, the response curves of the blocked decompositions were similar in shape to each other and to the control system in which all atomic degrees of freedom are fully independent. The similar shape of the blocked responses showed that the variations in grouping had only a minor impact on the kinematics. Compared with the all atom responses, however, the blocked responses were faster as a result of the instantaneous transmission of force throughout each rigid block. This occurred because rigid blocking does not permit any intrablock deformation that could store or divert energy. It was found, however, that this accelerated response could be successfully corrected by scaling each eigenvalue in the appropriate propagation matrix by the least-squares fitted slope of the blocked vs nonblocked eigenvalue spectra. The RTB responses for each test system were dominated by small eigenvalue overdamped Langevin modes. The large eigenvalue members of each response dissipated within the first 5 ps, after which the long time response was dominated by a modest set of low energy, overdamped normal modes, that were characterized by highly cooperative, functionally relevant displacements. The response assuming that the system is in the overdamped limit was compared to the full phase space Langevin dynamics results. The responses after the first 5 ps were nearly identical, confirming that the inertial components were significant only in the initial stages of the relaxation. Since the propagator matrix in the overdamped formulation is real-symmetric and does not require the inertial component in the propagator, the computation time and memory footprint was reduced by 1 order of magnitude.

Low-Temperature Aging Characteristics of Type 316L Stainless Steel Welds: Dependence on Solidification Mode

NASA Astrophysics Data System (ADS)

Abe, Hiroshi; Watanabe, Yutaka

2008-06-01

Thermal aging embrittlement of light water reactor (LWR) components made of stainless steel cast has been recognized as a potential degradation issue, and careful attention has been paid to it. Although welds of austenitic stainless steels have γ-δ duplex microstructure, which is similar to that of the stainless steel cast, examination of the thermal aging characteristics of the stainless steel welds is very limited. In this investigation, two types of type 316L stainless steel weld metal with different solidification modes were prepared using two kinds of filler metals having tailored Ni equivalent and Cr equivalent. Differences between the two weld metals in the morphology of microstructure, in the composition of δ-ferrite, and in hardening behaviors with isothermal aging at 335 °C have been investigated. The hardness of the ferrite phase has increased with aging time, while the hardness of austenite phase has stayed the same. The mottled aspect has been observed in δ-ferrite of aged samples by transmission electron microscopy (TEM) observation. These characteristics suggest that spinodal decomposition has occurred in δ-ferrite by aging at 335 °C. The age-hardening rate of δ-ferrite was faster for the primary austenite solidification mode (AF mode) sample than the primary ferrite solidification mode (FA mode) sample in the initial stage of the aging up to 2000 hours. It has been suggested that the solidification mode can affect the kinetics of spinodal decomposition.

Multi-scale fluctuation analysis of precipitation in Beijing by Extreme-point Symmetric Mode Decomposition

NASA Astrophysics Data System (ADS)

Li, Jiqing; Duan, Zhipeng; Huang, Jing

2018-06-01

With the aggravation of the global climate change, the shortage of water resources in China is becoming more and more serious. Using reasonable methods to study changes in precipitation is very important for planning and management of water resources. Based on the time series of precipitation in Beijing from 1951 to 2015, the multi-scale features of precipitation are analyzed by the Extreme-point Symmetric Mode Decomposition (ESMD) method to forecast the precipitation shift. The results show that the precipitation series have periodic changes of 2.6, 4.3, 14 and 21.7 years, and the variance contribution rate of each modal component shows that the inter-annual variation dominates the precipitation in Beijing. It is predicted that precipitation in Beijing will continue to decrease in the near future.

A novel approach for baseline correction in 1H-MRS signals based on ensemble empirical mode decomposition.

PubMed

Parto Dezfouli, Mohammad Ali; Dezfouli, Mohsen Parto; Rad, Hamidreza Saligheh

2014-01-01

Proton magnetic resonance spectroscopy ((1)H-MRS) is a non-invasive diagnostic tool for measuring biochemical changes in the human body. Acquired (1)H-MRS signals may be corrupted due to a wideband baseline signal generated by macromolecules. Recently, several methods have been developed for the correction of such baseline signals, however most of them are not able to estimate baseline in complex overlapped signal. In this study, a novel automatic baseline correction method is proposed for (1)H-MRS spectra based on ensemble empirical mode decomposition (EEMD). This investigation was applied on both the simulated data and the in-vivo (1)H-MRS of human brain signals. Results justify the efficiency of the proposed method to remove the baseline from (1)H-MRS signals.

Temporal structure of neuronal population oscillations with empirical model decomposition

NASA Astrophysics Data System (ADS)

Li, Xiaoli

2006-08-01

Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

The Thermal Decomposition of Some Organic Lead Compounds

DTIC Science & Technology

1957-11-01

either of salicylic anhydride or of its pyrolysis fragments which are reported to be a mixture of carbon dioxide , phenol and phenyl salicylate. Other...7) have studied the decomposition of the mono-salicylate in vacuo at 400°C. and have found that one molecule of carbon dioxide is evolved per...of lead nitrate and nitrosalicylic acid, though seme of the latter is decarboxylated with evolution of carbon dioxide . These points are considered

Theoretical study of mode evolution in active long tapered multimode fiber.

PubMed

Shi, Chen; Wang, Xiaolin; Zhou, Pu; Xu, Xiaojun; Lu, Qisheng

2016-08-22

A concise and effective model based on coupled mode theory to describe mode evolution in long tapered active fiber is presented in this manuscript. The mode coupling due to variation of core radius and slight perturbation have been analyzed and local gain with transverse spatial hole burning (TSHB) effect, loss and curvature have been taken into consideration in our model. On the base of this model, the mode evolution behaviors under different factors have been numerically investigated. Our model and results can provide instructive suggestions when designing long tapered fiber based laser and amplifiers.

Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks

PubMed Central

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806

Decomposition-based multiobjective evolutionary algorithm for community detection in dynamic social networks.

PubMed

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.

Algorithm for Stabilizing a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

Frequency-domain algorithm for the Lorenz-gauge gravitational self-force

NASA Astrophysics Data System (ADS)

Akcay, Sarp; Warburton, Niels; Barack, Leor

2013-11-01

State-of-the-art computations of the gravitational self-force (GSF) on massive particles in black hole spacetimes involve numerical evolution of the metric perturbation equations in the time domain, which is computationally very costly. We present here a new strategy based on a frequency-domain treatment of the perturbation equations, which offers considerable computational saving. The essential ingredients of our method are (i) a Fourier-harmonic decomposition of the Lorenz-gauge metric perturbation equations and a numerical solution of the resulting coupled set of ordinary equations with suitable boundary conditions; (ii) a generalized version of the method of extended homogeneous solutions [L. Barack, A. Ori, and N. Sago, Phys. Rev. D 78, 084021 (2008)] used to circumvent the Gibbs phenomenon that would otherwise hamper the convergence of the Fourier mode sum at the particle’s location; (iii) standard mode-sum regularization, which finally yields the physical GSF as a sum over regularized modal contributions. We present a working code that implements this strategy to calculate the Lorenz-gauge GSF along eccentric geodesic orbits around a Schwarzschild black hole. The code is far more efficient than existing time-domain methods; the gain in computation speed (at a given precision) is about an order of magnitude at an eccentricity of 0.2, and up to 3 orders of magnitude for circular or nearly circular orbits. This increased efficiency was crucial in enabling the recently reported calculation of the long-term orbital evolution of an extreme mass ratio inspiral [N. Warburton, S. Akcay, L. Barack, J. R. Gair, and N. Sago, Phys. Rev. D 85, 061501(R) (2012)]. Here we provide full technical details of our method to complement the above report.

A Novel Approach to Resonant Absorption of the Fast Magnetohydrodynamic Eigenmodes of a Coronal Arcade

NASA Astrophysics Data System (ADS)

Hindman, Bradley W.; Jain, Rekha

2018-05-01

The arched field lines forming coronal arcades are often observed to undulate as magnetohydrodynamic waves propagate both across and along the magnetic field. These waves are most likely a combination of resonantly coupled fast magnetoacoustic waves and Alfvén waves. The coupling results in resonant absorption of the fast waves, converting fast wave energy into Alfvén waves. The fast eigenmodes of the arcade have proven difficult to compute or derive analytically, largely because of the mathematical complexity that the coupling introduces. When a traditional spectral decomposition is employed, the discrete spectrum associated with the fast eigenmodes is often subsumed into the continuous Alfvén spectrum. Thus fast eigenmodes become collective modes or quasi-modes. Here we present a spectral decomposition that treats the eigenmodes as having real frequencies but complex wavenumbers. Using this procedure we derive dispersion relations, spatial damping rates, and eigenfunctions for the resonant, fast eigenmodes of the arcade. We demonstrate that resonant absorption introduces a fast mode that would not exist otherwise. This new mode is heavily damped by resonant absorption, travelling only a few wavelengths before losing most of its energy.

Variational mode decomposition based approach for accurate classification of color fundus images with hemorrhages

NASA Astrophysics Data System (ADS)

Lahmiri, Salim; Shmuel, Amir

2017-11-01

Diabetic retinopathy is a disease that can cause a loss of vision. An early and accurate diagnosis helps to improve treatment of the disease and prognosis. One of the earliest characteristics of diabetic retinopathy is the appearance of retinal hemorrhages. The purpose of this study is to design a fully automated system for the detection of hemorrhages in a retinal image. In the first stage of our proposed system, a retinal image is processed with variational mode decomposition (VMD) to obtain the first variational mode, which captures the high frequency components of the original image. In the second stage, four texture descriptors are extracted from the first variational mode. Finally, a classifier trained with all computed texture descriptors is used to distinguish between images of healthy and unhealthy retinas with hemorrhages. Experimental results showed evidence of the effectiveness of the proposed system for detection of hemorrhages in the retina, since a perfect detection rate was achieved. Our proposed system for detecting diabetic retinopathy is simple and easy to implement. It requires only short processing time, and it yields higher accuracy in comparison with previously proposed methods for detecting diabetic retinopathy.

Reduced quantum dynamics with arbitrary bath spectral densities: hierarchical equations of motion based on several different bath decomposition schemes.

PubMed

Liu, Hao; Zhu, Lili; Bai, Shuming; Shi, Qiang

2014-04-07

We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly in the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.

Reduced quantum dynamics with arbitrary bath spectral densities: Hierarchical equations of motion based on several different bath decomposition schemes

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

Liu, Hao; Zhu, Lili; Bai, Shuming

2014-04-07

We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly inmore » the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.« less

Fault detection, isolation, and diagnosis of self-validating multifunctional sensors.

PubMed

Yang, Jing-Li; Chen, Yin-Sheng; Zhang, Li-Li; Sun, Zhen

2016-06-01

A novel fault detection, isolation, and diagnosis (FDID) strategy for self-validating multifunctional sensors is presented in this paper. The sparse non-negative matrix factorization-based method can effectively detect faults by using the squared prediction error (SPE) statistic, and the variables contribution plots based on SPE statistic can help to locate and isolate the faulty sensitive units. The complete ensemble empirical mode decomposition is employed to decompose the fault signals to a series of intrinsic mode functions (IMFs) and a residual. The sample entropy (SampEn)-weighted energy values of each IMFs and the residual are estimated to represent the characteristics of the fault signals. Multi-class support vector machine is introduced to identify the fault mode with the purpose of diagnosing status of the faulty sensitive units. The performance of the proposed strategy is compared with other fault detection strategies such as principal component analysis, independent component analysis, and fault diagnosis strategies such as empirical mode decomposition coupled with support vector machine. The proposed strategy is fully evaluated in a real self-validating multifunctional sensors experimental system, and the experimental results demonstrate that the proposed strategy provides an excellent solution to the FDID research topic of self-validating multifunctional sensors.

PHYSICS OF NON-GAUSSIAN FIELDS AND THE COSMOLOGICAL GENUS STATISTIC

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

James, J. Berian, E-mail: berian@berkeley.edu

2012-05-20

We report a technique to calculate the impact of distinct physical processes inducing non-Gaussianity on the cosmological density field. A natural decomposition of the cosmic genus statistic into an orthogonal polynomial sequence allows complete expression of the scale-dependent evolution of the topology of large-scale structure, in which effects including galaxy bias, nonlinear gravitational evolution, and primordial non-Gaussianity may be delineated. The relationship of this decomposition to previous methods for analyzing the genus statistic is briefly considered and the following applications are made: (1) the expression of certain systematics affecting topological measurements, (2) the quantification of broad deformations from Gaussianity thatmore » appear in the genus statistic as measured in the Horizon Run simulation, and (3) the study of the evolution of the genus curve for simulations with primordial non-Gaussianity. These advances improve the treatment of flux-limited galaxy catalogs for use with this measurement and further the use of the genus statistic as a tool for exploring non-Gaussianity.« less

Microstructural Evolution and Phase Formation in 2nd-Generation Refractory-Based High Entropy Alloys

PubMed Central

Eshed, Eyal; Larianovsky, Natalya; Kovalevsky, Alexey; Popov, Vladimir; Gorbachev, Igor; Popov, Vladimir; Katz-Demyanetz, Alexander

2018-01-01

Refractory-based high entropy alloys (HEAs) of the 2nd-generation type are new intensively-studied materials with a high potential for structural high-temperature applications. This paper presents investigation results on microstructural evolution and phase formation in as-cast and subsequently heat-treated HEAs at various temperature-time regimes. Microstructural examination was performed by means of scanning electron microscopy (SEM) combined with the energy dispersive spectroscopy (EDS) mode of electron probe microanalysis (EPMA) and qualitative X-ray diffraction (XRD). The primary evolutionary trend observed was the tendency of Zr to gradually segregate as the temperature rises, while all the other elements eventually dissolve in the BCC solid solution phase once the onset of Laves phase complex decomposition is reached. The performed thermodynamic modelling was based on the Calculation of Phase Diagrams method (CALPHAD). The BCC A2 solid solution phase is predicted by the model to contain increasing amounts of Cr as the temperature rises, which is in perfect agreement with the actual results obtained by SEM. However, the model was not able to predict the existence of the Zr-rich phase or the tendency of Zr to segregate and form its own solid solution—most likely as a result of the Zr segregation trend not being an equilibrium phenomenon. PMID:29360763

Unravelling Diurnal Asymmetry of Surface Temperature in Different Climate Zones.

PubMed

Vinnarasi, R; Dhanya, C T; Chakravorty, Aniket; AghaKouchak, Amir

2017-08-04

Understanding the evolution of Diurnal Temperature Range (DTR), which has contradicting global and regional trends, is crucial because it influences environmental and human health. Here, we analyse the regional evolution of DTR trend over different climatic zones in India using a non-stationary approach known as the Multidimensional Ensemble Empirical Mode Decomposition (MEEMD) method, to explore the generalized influence of regional climate on DTR, if any. We report a 0.36 °C increase in overall mean of DTR till 1980, however, the rate has declined since then. Further, arid deserts and warm-temperate grasslands exhibit negative DTR trends, while the west coast and sub-tropical forest in the north-east show positive trends. This transition predominantly begins with a 0.5 °C increase from the west coast and spreads with an increase of 0.25 °C per decade. These changes are more pronounced during winter and post-monsoon, especially in the arid desert and warm-temperate grasslands, the DTR decreased up to 2 °C, where the rate of increase in minimum temperature is higher than the maximum temperature. We conclude that both maximum and minimum temperature increase in response to the global climate change, however, their rates of increase are highly local and depend on the underlying climatic zone.

Optical diagnosis of cervical cancer by intrinsic mode functions

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Pratiher, Sawon; Pratiher, Souvik; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-03-01

In this paper, we make use of the empirical mode decomposition (EMD) to discriminate the cervical cancer tissues from normal ones based on elastic scattering spectroscopy. The phase space has been reconstructed through decomposing the optical signal into a finite set of bandlimited signals known as intrinsic mode functions (IMFs). It has been shown that the area measure of the analytic IMFs provides a good discrimination performance. Simulation results validate the efficacy of the IMFs followed by SVM based classification.

Handling Qualities of Large Flexible Aircraft. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Poopaka, S.

1980-01-01

The effects on handling qualities of elastic modes interaction with the rigid body dynamics of a large flexible aircraft are studied by a mathematical computer simulation. An analytical method to predict the pilot ratings when there is a severe modes interactions is developed. This is done by extending the optimal control model of the human pilot response to include the mode decomposition mechanism into the model. The handling qualities are determined for a longitudinal tracking task using a large flexible aircraft with parametric variations in the undamped natural frequencies of the two lowest frequency, symmetric elastic modes made to induce varying amounts of mode interaction.

Raman intensity and vibrational modes of armchair CNTs

NASA Astrophysics Data System (ADS)

Hur, Jaewoong; Stuart, Steven J.

2017-07-01

Raman intensity changes and frequency patterns have been studied using the various armchair (n, n) to understand the variations of bond polarizability, in regard to changing diameters, lengths, and the number of atoms in the (n, n). The Raman intensity trends of the (n, n) are validated by those of Cn isomers. For frequency trends, similar frequency patterns and frequency inward shifts for the (n, n) are characterized. Also, VDOS trends of the (n, n) expressing Raman modes are interpreted. The decomposition of vibrational modes in the (n, n) into radial, longitudinal, and tangential mode is beneficially used to recognize the distinct characteristics of vibrational modes.

Multifractal Detrended Fluctuation Analysis of Regional Precipitation Sequences Based on the CEEMDAN-WPT

NASA Astrophysics Data System (ADS)

Liu, Dong; Cheng, Chen; Fu, Qiang; Liu, Chunlei; Li, Mo; Faiz, Muhammad Abrar; Li, Tianxiao; Khan, Muhammad Imran; Cui, Song

2018-03-01

In this paper, the complete ensemble empirical mode decomposition with the adaptive noise (CEEMDAN) algorithm is introduced into the complexity research of precipitation systems to improve the traditional complexity measure method specific to the mode mixing of the Empirical Mode Decomposition (EMD) and incomplete decomposition of the ensemble empirical mode decomposition (EEMD). We combined the CEEMDAN with the wavelet packet transform (WPT) and multifractal detrended fluctuation analysis (MF-DFA) to create the CEEMDAN-WPT-MFDFA, and used it to measure the complexity of the monthly precipitation sequence of 12 sub-regions in Harbin, Heilongjiang Province, China. The results show that there are significant differences in the monthly precipitation complexity of each sub-region in Harbin. The complexity of the northwest area of Harbin is the lowest and its predictability is the best. The complexity and predictability of the middle and Midwest areas of Harbin are about average. The complexity of the southeast area of Harbin is higher than that of the northwest, middle, and Midwest areas of Harbin and its predictability is worse. The complexity of Shuangcheng is the highest and its predictability is the worst of all the studied sub-regions. We used terrain and human activity as factors to analyze the causes of the complexity of the local precipitation. The results showed that the correlations between the precipitation complexity and terrain are obvious, and the correlations between the precipitation complexity and human influence factors vary. The distribution of the precipitation complexity in this area may be generated by the superposition effect of human activities and natural factors such as terrain, general atmospheric circulation, land and sea location, and ocean currents. To evaluate the stability of the algorithm, the CEEMDAN-WPT-MFDFA was compared with the equal probability coarse graining LZC algorithm, fuzzy entropy, and wavelet entropy. The results show that the CEEMDAN-WPT-MFDFA was more stable than 3 contrast methods under the influence of white noise and colored noise, which proves that the CEEMDAN-WPT-MFDFA has a strong robustness under the influence of noise.

New insights into thermal decomposition of polycyclic aromatic hydrocarbon oxyradicals.

PubMed

Liu, Peng; Lin, He; Yang, Yang; Shao, Can; Gu, Chen; Huang, Zhen

2014-12-04

Thermal decompositions of polycyclic aromatic hydrocarbon (PAH) oxyradicals on various surface sites including five-membered ring, free-edge, zigzag, and armchair have been systematically investigated by using ab initio density functional theory B3LYP/6-311+G(d,p) basis set. The calculation based on Hückel theory indicates that PAHs (3H-cydopenta[a]anthracene oxyradical) with oxyradicals on a five-membered ring site have high chemical reactivity. The rate coefficients of PAH oxyradical decomposition were evaluated by using Rice-Ramsperger-Kassel-Marcus theory and solving the master equations in the temperature range of 1500-2500 K and the pressure range of 0.1-10 atm. The kinetic calculations revealed that the rate coefficients of PAH oxyradical decomposition are temperature-, pressure-, and surface site-dependent, and the oxyradical on a five-membered ring is easier to decompose than that on a six-membered ring. Four-membered rings were found in decomposition of the five-membered ring, and a new reaction channel of PAH evolution involving four-membered rings is recommended.

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

Animal evolution, bioturbation, and the sulfate concentration of the oceans

PubMed Central

Canfield, Donald E.; Farquhar, James

2009-01-01

As recognized already by Charles Darwin, animals are geobiological agents. Darwin observed that worms aerate and mix soils on a massive scale, aiding in the decomposition of soil organic matter. A similar statement can be made about marine benthic animals. This mixing, also known as bioturbation, not only aides in the decomposition of sedimentary organic material, but as contended here, it has also significantly influenced the chemistry of seawater. In particular, it is proposed that sediment mixing by bioturbating organisms resulted in a severalfold increase in seawater sulfate concentration. For this reason, the evolution of bioturbation is linked to the significant deposition of sulfate evaporate minerals, which is largely a phenomena of the Phanerozoic, the last 542 million years and the time over which animals rose to prominence. PMID:19451639

Animal evolution, bioturbation, and the sulfate concentration of the oceans.

PubMed

Canfield, Donald E; Farquhar, James

2009-05-19

As recognized already by Charles Darwin, animals are geobiological agents. Darwin observed that worms aerate and mix soils on a massive scale, aiding in the decomposition of soil organic matter. A similar statement can be made about marine benthic animals. This mixing, also known as bioturbation, not only aides in the decomposition of sedimentary organic material, but as contended here, it has also significantly influenced the chemistry of seawater. In particular, it is proposed that sediment mixing by bioturbating organisms resulted in a severalfold increase in seawater sulfate concentration. For this reason, the evolution of bioturbation is linked to the significant deposition of sulfate evaporate minerals, which is largely a phenomena of the Phanerozoic, the last 542 million years and the time over which animals rose to prominence.

Oxygen Mass Flow Rate Generated for Monitoring Hydrogen Peroxide Stability

NASA Technical Reports Server (NTRS)

Ross, H. Richard

2002-01-01

Recent interest in propellants with non-toxic reaction products has led to a resurgence of interest in hydrogen peroxide for various propellant applications. Because peroxide is sensitive to contaminants, material interactions, stability and storage issues, monitoring decomposition rates is important. Stennis Space Center (SSC) uses thermocouples to monitor bulk fluid temperature (heat evolution) to determine reaction rates. Unfortunately, large temperature rises are required to offset the heat lost into the surrounding fluid. Also, tank penetration to accomodate a thermocouple can entail modification of a tank or line and act as a source of contamination. The paper evaluates a method for monitoring oxygen evolution as a means to determine peroxide stability. Oxygen generation is not only directly related to peroxide decomposition, but occurs immediately. Measuring peroxide temperature to monitor peroxide stability has significant limitations. The bulk decomposition of 1% / week in a large volume tank can produce in excess of 30 cc / min. This oxygen flow rate corresponds to an equivalent temperature rise of approximately 14 millidegrees C, which is difficult to measure reliably. Thus, if heat transfer were included, there would be no temperature rise. Temperature changes from the surrounding environment and heat lost to the peroxide will also mask potential problems. The use of oxygen flow measurements provides an ultra sensitive technique for monitoring reaction events and will provide an earlier indication of an abnormal decomposition when compared to measuring temperature rise.

International journal of computational fluid dynamics real-time prediction of unsteady flow based on POD reduced-order model and particle filter

NASA Astrophysics Data System (ADS)

Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru

2016-04-01

An integrated method consisting of a proper orthogonal decomposition (POD)-based reduced-order model (ROM) and a particle filter (PF) is proposed for real-time prediction of an unsteady flow field. The proposed method is validated using identical twin experiments of an unsteady flow field around a circular cylinder for Reynolds numbers of 100 and 1000. In this study, a PF is employed (ROM-PF) to modify the temporal coefficient of the ROM based on observation data because the prediction capability of the ROM alone is limited due to the stability issue. The proposed method reproduces the unsteady flow field several orders faster than a reference numerical simulation based on Navier-Stokes equations. Furthermore, the effects of parameters, related to observation and simulation, on the prediction accuracy are studied. Most of the energy modes of the unsteady flow field are captured, and it is possible to stably predict the long-term evolution with ROM-PF.

Higher-order stochastic differential equations and the positive Wigner function

NASA Astrophysics Data System (ADS)

Drummond, P. D.

2017-12-01

General higher-order stochastic processes that correspond to any diffusion-type tensor of higher than second order are obtained. The relationship of multivariate higher-order stochastic differential equations with tensor decomposition theory and tensor rank is explained. Techniques for generating the requisite complex higher-order noise are proved to exist either using polar coordinates and γ distributions, or from products of Gaussian variates. This method is shown to allow the calculation of the dynamics of the Wigner function, after it is extended to a complex phase space. The results are illustrated physically through dynamical calculations of the positive Wigner distribution for three-mode parametric downconversion, widely used in quantum optics. The approach eliminates paradoxes arising from truncation of the higher derivative terms in Wigner function time evolution. Anomalous results of negative populations and vacuum scattering found in truncated Wigner quantum simulations in quantum optics and Bose-Einstein condensate dynamics are shown not to occur with this type of stochastic theory.

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Growth, structural, optical, thermal and dielectric properties of lanthanum chloride—thiourea—L tartaric acid coordinated complex

NASA Astrophysics Data System (ADS)

Slathia, Goldy; Bamzai, K. K.

2017-11-01

Lanthanum chloride—thiourea—l tartaric acid coordinated complex was grown in the form of single crystal by slow evaporation of supersaturated solutions at room temperature. This coordinated complex crystallizes in orthorhombic crystal system having space group P nma. The crystallinity and purity was tested by powder x-ray diffraction. Fourier transform infra red and Raman spectroscopy analysis provide the evidences on structure and mode of coordination. The scanning electron microscopy (SEM) analysis shows the morphology evolution as brought by the increase in composition of lanthanum chloride. The band transitions due to C=O and C=S chromophores remain active in grown complexes and are recorded in the UV-vis optical spectrum. The thermal effects such as dehydration, melting and decomposition were observed by the thermogravimetric and differential thermo analytical (TGA/DTA) analysis. Electrical properties were studied by dielectric analysis in frequency range 100-30 MHz at various temperatures. Increase in values of dielectric constant was observed with change in lanthanum concentration in the coordinated complex.

Hydrogen production by photoelectrolytic decomposition of H2O using solar energy

NASA Technical Reports Server (NTRS)

Rauh, R. D.; Alkaitis, S. A.; Buzby, J. M.; Schiff, R.

1980-01-01

Photoelectrochemical systems for the efficient decomposition of water are discussed. Semiconducting d band oxides which would yield the combination of stability, low electron affinity, and moderate band gap essential for an efficient photoanode are sought. The materials PdO and Fe-xRhxO3 appear most likely. Oxygen evolution yields may also be improved by mediation of high energy oxidizing agents, such as CO3(-). Examination of several p type semiconductors as photocathodes revealed remarkable stability for p-GaAs, and also indicated p-CdTe as a stable H2 photoelectrode. Several potentially economical schemes for photoelectrochemical decomposition of water were examined, including photoelectrochemical diodes and two stage, four photon processes.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

Stability evaluation of short-circuiting gas metal arc welding based on ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Huang, Yong; Wang, Kehong; Zhou, Zhilan; Zhou, Xiaoxiao; Fang, Jimi

2017-03-01

The arc of gas metal arc welding (GMAW) contains abundant information about its stability and droplet transition, which can be effectively characterized by extracting the arc electrical signals. In this study, ensemble empirical mode decomposition (EEMD) was used to evaluate the stability of electrical current signals. The welding electrical signals were first decomposed by EEMD, and then transformed to a Hilbert-Huang spectrum and a marginal spectrum. The marginal spectrum is an approximate distribution of amplitude with frequency of signals, and can be described by a marginal index. Analysis of various welding process parameters showed that the marginal index of current signals increased when the welding process was more stable, and vice versa. Thus EEMD combined with the marginal index can effectively uncover the stability and droplet transition of GMAW.

Fourier imaging of non-linear structure formation

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

Brandbyge, Jacob; Hannestad, Steen, E-mail: jacobb@phys.au.dk, E-mail: sth@phys.au.dk

We perform a Fourier space decomposition of the dynamics of non-linear cosmological structure formation in ΛCDM models. From N -body simulations involving only cold dark matter we calculate 3-dimensional non-linear density, velocity divergence and vorticity Fourier realizations, and use these to calculate the fully non-linear mode coupling integrals in the corresponding fluid equations. Our approach allows for a reconstruction of the amount of mode coupling between any two wavenumbers as a function of redshift. With our Fourier decomposition method we identify the transfer of power from larger to smaller scales, the stable clustering regime, the scale where vorticity becomes important,more » and the suppression of the non-linear divergence power spectrum as compared to linear theory. Our results can be used to improve and calibrate semi-analytical structure formation models.« less

Phase transformations of siderite ore by the thermomagnetic analysis data

NASA Astrophysics Data System (ADS)

Ponomar, V. P.; Dudchenko, N. O.; Brik, A. B.

2017-02-01

Thermal decomposition of Bakal siderite ore (that consists of magnesium siderite and ankerite traces) was investigated by thermomagnetic analysis. Thermomagnetic analysis was carried-out using laboratory-built facility that allows automatic registration of sample magnetization with the temperature (heating/cooling rate was 65°/min, maximum temperature 650 °C) at low- and high-oxygen content. Curie temperature gradually decreases with each next cycles of heating/cooling at low-oxygen content. Curie temperature decrease after 2nd cycle of heating/cooling at high-oxygen content and do not change with next cycles. Final Curie temperature for both modes was 320 °C. Saturation magnetization of obtained samples increases up to 20 Am2/kg. The final product of phase transformation at both modes was magnesioferrite. It was shown that intermediate phase of thermal decomposition of Bakal siderite ore was magnesiowustite.

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine.

PubMed

Wahba, Maram A; Ashour, Amira S; Napoleon, Sameh A; Abd Elnaby, Mustafa M; Guo, Yanhui

2017-12-01

Basal cell carcinoma is one of the most common malignant skin lesions. Automated lesion identification and classification using image processing techniques is highly required to reduce the diagnosis errors. In this study, a novel technique is applied to classify skin lesion images into two classes, namely the malignant Basal cell carcinoma and the benign nevus. A hybrid combination of bi-dimensional empirical mode decomposition and gray-level difference method features is proposed after hair removal. The combined features are further classified using quadratic support vector machine (Q-SVM). The proposed system has achieved outstanding performance of 100% accuracy, sensitivity and specificity compared to other support vector machine procedures as well as with different extracted features. Basal Cell Carcinoma is effectively classified using Q-SVM with the proposed combined features.

Adaptive multi-step Full Waveform Inversion based on Waveform Mode Decomposition

NASA Astrophysics Data System (ADS)

Hu, Yong; Han, Liguo; Xu, Zhuo; Zhang, Fengjiao; Zeng, Jingwen

2017-04-01

Full Waveform Inversion (FWI) can be used to build high resolution velocity models, but there are still many challenges in seismic field data processing. The most difficult problem is about how to recover long-wavelength components of subsurface velocity models when seismic data is lacking of low frequency information and without long-offsets. To solve this problem, we propose to use Waveform Mode Decomposition (WMD) method to reconstruct low frequency information for FWI to obtain a smooth model, so that the initial model dependence of FWI can be reduced. In this paper, we use adjoint-state method to calculate the gradient for Waveform Mode Decomposition Full Waveform Inversion (WMDFWI). Through the illustrative numerical examples, we proved that the low frequency which is reconstructed by WMD method is very reliable. WMDFWI in combination with the adaptive multi-step inversion strategy can obtain more faithful and accurate final inversion results. Numerical examples show that even if the initial velocity model is far from the true model and lacking of low frequency information, we still can obtain good inversion results with WMD method. From numerical examples of anti-noise test, we see that the adaptive multi-step inversion strategy for WMDFWI has strong ability to resist Gaussian noise. WMD method is promising to be able to implement for the land seismic FWI, because it can reconstruct the low frequency information, lower the dominant frequency in the adjoint source, and has a strong ability to resist noise.

Surface Chemistry of CWAs for Decon Enabling Sciences

DTIC Science & Technology

2014-11-04

representing the formation of a hydrogen-bonded mode. Characteristic modes of the sarin molecule itself are also observed. These experimental results show...Triangle Park, NC 27709-2211 surface science, CWA, uptake, decomposition, decontamination, filtration , XPS, FTIR, TPD, MS, UHV REPORT DOCUMENTATION PAGE 11...Karwacki, Team Leader CBR Filtration Research and Technology Directorate at ECBC. Through this collaboration, we have established a facility for the study

Optimal Multi-scale Demand-side Management for Continuous Power-Intensive Processes

NASA Astrophysics Data System (ADS)

Mitra, Sumit

With the advent of deregulation in electricity markets and an increasing share of intermittent power generation sources, the profitability of industrial consumers that operate power-intensive processes has become directly linked to the variability in energy prices. Thus, for industrial consumers that are able to adjust to the fluctuations, time-sensitive electricity prices (as part of so-called Demand-Side Management (DSM) in the smart grid) offer potential economical incentives. In this thesis, we introduce optimization models and decomposition strategies for the multi-scale Demand-Side Management of continuous power-intensive processes. On an operational level, we derive a mode formulation for scheduling under time-sensitive electricity prices. The formulation is applied to air separation plants and cement plants to minimize the operating cost. We also describe how a mode formulation can be used for industrial combined heat and power plants that are co-located at integrated chemical sites to increase operating profit by adjusting their steam and electricity production according to their inherent flexibility. Furthermore, a robust optimization formulation is developed to address the uncertainty in electricity prices by accounting for correlations and multiple ranges in the realization of the random variables. On a strategic level, we introduce a multi-scale model that provides an understanding of the value of flexibility of the current plant configuration and the value of additional flexibility in terms of retrofits for Demand-Side Management under product demand uncertainty. The integration of multiple time scales leads to large-scale two-stage stochastic programming problems, for which we need to apply decomposition strategies in order to obtain a good solution within a reasonable amount of time. Hence, we describe two decomposition schemes that can be applied to solve two-stage stochastic programming problems: First, a hybrid bi-level decomposition scheme with novel Lagrangean-type and subset-type cuts to strengthen the relaxation. Second, an enhanced cross-decomposition scheme that integrates Benders decomposition and Lagrangean decomposition on a scenario basis. To demonstrate the effectiveness of our developed methodology, we provide several industrial case studies throughout the thesis.

Solar rotational modulations of spectral irradiance and correlations with the variability of total solar irradiance

NASA Astrophysics Data System (ADS)

Lee, Jae N.; Cahalan, Robert F.; Wu, Dong L.

2016-09-01

Aims: We characterize the solar rotational modulations of spectral solar irradiance (SSI) and compare them with the corresponding changes of total solar irradiance (TSI). Solar rotational modulations of TSI and SSI at wavelengths between 120 and 1600 nm are identified over one hundred Carrington rotational cycles during 2003-2013. Methods: The SORCE (Solar Radiation and Climate Experiment) and TIMED (Thermosphere Ionosphere Mesosphere Energetics and Dynamics)/SEE (Solar EUV Experiment) measured and SATIRE-S modeled solar irradiances are analyzed using the EEMD (Ensemble Empirical Mode Decomposition) method to determine the phase and amplitude of 27-day solar rotational variation in TSI and SSI. Results: The mode decomposition clearly identifies 27-day solar rotational variations in SSI between 120 and 1600 nm, and there is a robust wavelength dependence in the phase of the rotational mode relative to that of TSI. The rotational modes of visible (VIS) and near infrared (NIR) are in phase with the mode of TSI, but the phase of the rotational mode of ultraviolet (UV) exhibits differences from that of TSI. While it is questionable that the VIS to NIR portion of the solar spectrum has yet been observed with sufficient accuracy and precision to determine the 11-year solar cycle variations, the temporal variations over one hundred cycles of 27-day solar rotation, independent of the two solar cycles in which they are embedded, show distinct solar rotational modulations at each wavelength.

Solar Rotational Modulations of Spectral Irradiance and Correlations with the Variability of Total Solar Irradiance

NASA Technical Reports Server (NTRS)

Lee, Jae N.; Cahalan, Robert F.; Wu, Dong L.

2016-01-01

Aims: We characterize the solar rotational modulations of spectral solar irradiance (SSI) and compare them with the corresponding changes of total solar irradiance (TSI). Solar rotational modulations of TSI and SSI at wavelengths between 120 and 1600 nm are identified over one hundred Carrington rotational cycles during 2003-2013. Methods: The SORCE (Solar Radiation and Climate Experiment) and TIMED (Thermosphere Ionosphere Mesosphere Energetics and Dynamics)/SEE (Solar EUV Experiment) measured and SATIRE-S modeled solar irradiances are analyzed using the EEMD (Ensemble Empirical Mode Decomposition) method to determine the phase and amplitude of 27-day solar rotational variation in TSI and SSI. Results: The mode decomposition clearly identifies 27-day solar rotational variations in SSI between 120 and 1600 nm, and there is a robust wavelength dependence in the phase of the rotational mode relative to that of TSI. The rotational modes of visible (VIS) and near infrared (NIR) are in phase with the mode of TSI, but the phase of the rotational mode of ultraviolet (UV) exhibits differences from that of TSI. While it is questionable that the VIS to NIR portion of the solar spectrum has yet been observed with sufficient accuracy and precision to determine the 11-year solar cycle variations, the temporal variations over one hundred cycles of 27-day solar rotation, independent of the two solar cycles in which they are embedded, show distinct solar rotational modulations at each wavelength.

Fast flux module detection using matroid theory.

PubMed

Reimers, Arne C; Bruggeman, Frank J; Olivier, Brett G; Stougie, Leen

2015-05-01

Flux balance analysis (FBA) is one of the most often applied methods on genome-scale metabolic networks. Although FBA uniquely determines the optimal yield, the pathway that achieves this is usually not unique. The analysis of the optimal-yield flux space has been an open challenge. Flux variability analysis is only capturing some properties of the flux space, while elementary mode analysis is intractable due to the enormous number of elementary modes. However, it has been found by Kelk et al. (2012) that the space of optimal-yield fluxes decomposes into flux modules. These decompositions allow a much easier but still comprehensive analysis of the optimal-yield flux space. Using the mathematical definition of module introduced by Müller and Bockmayr (2013b), we discovered useful connections to matroid theory, through which efficient algorithms enable us to compute the decomposition into modules in a few seconds for genome-scale networks. Using that every module can be represented by one reaction that represents its function, in this article, we also present a method that uses this decomposition to visualize the interplay of modules. We expect the new method to replace flux variability analysis in the pipelines for metabolic networks.

Three-pattern decomposition of global atmospheric circulation: part II—dynamical equations of horizontal, meridional and zonal circulations

NASA Astrophysics Data System (ADS)

Hu, Shujuan; Cheng, Jianbo; Xu, Ming; Chou, Jifan

2018-04-01

The three-pattern decomposition of global atmospheric circulation (TPDGAC) partitions three-dimensional (3D) atmospheric circulation into horizontal, meridional and zonal components to study the 3D structures of global atmospheric circulation. This paper incorporates the three-pattern decomposition model (TPDM) into primitive equations of atmospheric dynamics and establishes a new set of dynamical equations of the horizontal, meridional and zonal circulations in which the operator properties are studied and energy conservation laws are preserved, as in the primitive equations. The physical significance of the newly established equations is demonstrated. Our findings reveal that the new equations are essentially the 3D vorticity equations of atmosphere and that the time evolution rules of the horizontal, meridional and zonal circulations can be described from the perspective of 3D vorticity evolution. The new set of dynamical equations includes decomposed expressions that can be used to explore the source terms of large-scale atmospheric circulation variations. A simplified model is presented to demonstrate the potential applications of the new equations for studying the dynamics of the Rossby, Hadley and Walker circulations. The model shows that the horizontal air temperature anomaly gradient (ATAG) induces changes in meridional and zonal circulations and promotes the baroclinic evolution of the horizontal circulation. The simplified model also indicates that the absolute vorticity of the horizontal circulation is not conserved, and its changes can be described by changes in the vertical vorticities of the meridional and zonal circulations. Moreover, the thermodynamic equation shows that the induced meridional and zonal circulations and advection transport by the horizontal circulation in turn cause a redistribution of the air temperature. The simplified model reveals the fundamental rules between the evolution of the air temperature and the horizontal, meridional and zonal components of global atmospheric circulation.

Domain decomposition: A bridge between nature and parallel computers

NASA Technical Reports Server (NTRS)

Keyes, David E.

1992-01-01

Domain decomposition is an intuitive organizing principle for a partial differential equation (PDE) computation, both physically and architecturally. However, its significance extends beyond the readily apparent issues of geometry and discretization, on one hand, and of modular software and distributed hardware, on the other. Engineering and computer science aspects are bridged by an old but recently enriched mathematical theory that offers the subject not only unity, but also tools for analysis and generalization. Domain decomposition induces function-space and operator decompositions with valuable properties. Function-space bases and operator splittings that are not derived from domain decompositions generally lack one or more of these properties. The evolution of domain decomposition methods for elliptically dominated problems has linked two major algorithmic developments of the last 15 years: multilevel and Krylov methods. Domain decomposition methods may be considered descendants of both classes with an inheritance from each: they are nearly optimal and at the same time efficiently parallelizable. Many computationally driven application areas are ripe for these developments. A progression is made from a mathematically informal motivation for domain decomposition methods to a specific focus on fluid dynamics applications. To be introductory rather than comprehensive, simple examples are provided while convergence proofs and algorithmic details are left to the original references; however, an attempt is made to convey their most salient features, especially where this leads to algorithmic insight.

Thermal Decomposition Mechanism of CL-20 at Different Temperatures by ReaxFF Reactive Molecular Dynamics Simulations.

PubMed

Wang, Fuping; Chen, Lang; Geng, Deshen; Wu, Junying; Lu, Jianying; Wang, Chen

2018-04-26

Hexanitrohexaazaisowurtzitane (CL-20) has a high detonation velocity and pressure, but its sensitivity is also high, which somewhat limits its applications. Therefore, it is important to understand the mechanism and characteristics of thermal decomposition of CL-20. In this study, a ε-CL-20 supercell was constructed and ReaxFF-lg reactive molecular dynamics simulations were performed to investigate thermal decomposition of ε-CL-20 at various temperatures (2000, 2500, 2750, 3000, 3250, and 3500 K). The mechanism of thermal decomposition of CL-20 was analyzed from the aspects of potential energy evolution, the primary reactions, and the intermediate and final product species. The effect of temperature on thermal decomposition of CL-20 is also discussed. The initial reaction path of thermal decomposition of CL-20 is N-NO 2 cleavage to form NO 2 , followed by C-N cleavage, leading to the destruction of the cage structure. A small number of clusters appear in the early reactions and disappear at the end of the reactions. The initial reaction path of CL-20 decomposition is the same at different temperatures. However, as the temperature increases, the decomposition rate of CL-20 increases and the cage structure is destroyed earlier. The temperature greatly affects the rate constants of H 2 O and N 2 , but it has little effect on the rate constants of CO 2 and H 2 .

Transfer of Asymmetry between Proteinogenic Amino Acids under Harsh Conditions

NASA Astrophysics Data System (ADS)

Tarasevych, Arkadii V.; Vives, Thomas; Snytnikov, Valeriy N.; Guillemin, Jean-Claude

2017-09-01

The heating above 400 °C of serine, cysteine, selenocysteine and threonine leads to a complete decomposition of the amino acids and to the formation in low yields of alanine for the three formers and of 2-aminobutyric acid for the latter. At higher temperature, this amino acid is observed only when sublimable α-alkyl-α-amino acids are present, and with an enantiomeric excess dependent on several parameters. Enantiopure or enantioenriched Ser, Cys, Sel or Thr is not able to transmit its enantiomeric excess to the amino acid formed during its decomposition. The presence during the sublimation-decomposition of enantioenriched valine or isoleucine leads to the enantioenrichment of all sublimable amino acids independently of the presence of many decomposition products coming from the unstable derivative. All these studies give information on a potentially prebiotic key-reaction of abiotic transformations between α-amino acids and their evolution to homochirality.

Singular value decomposition metrics show limitations of detector design in diffuse fluorescence tomography

PubMed Central

Leblond, Frederic; Tichauer, Kenneth M.; Pogue, Brian W.

2010-01-01

The spatial resolution and recovered contrast of images reconstructed from diffuse fluorescence tomography data are limited by the high scattering properties of light propagation in biological tissue. As a result, the image reconstruction process can be exceedingly vulnerable to inaccurate prior knowledge of tissue optical properties and stochastic noise. In light of these limitations, the optimal source-detector geometry for a fluorescence tomography system is non-trivial, requiring analytical methods to guide design. Analysis of the singular value decomposition of the matrix to be inverted for image reconstruction is one potential approach, providing key quantitative metrics, such as singular image mode spatial resolution and singular data mode frequency as a function of singular mode. In the present study, these metrics are used to analyze the effects of different sources of noise and model errors as related to image quality in the form of spatial resolution and contrast recovery. The image quality is demonstrated to be inherently noise-limited even when detection geometries were increased in complexity to allow maximal tissue sampling, suggesting that detection noise characteristics outweigh detection geometry for achieving optimal reconstructions. PMID:21258566

Investigation of Kelvin wave periods during Hai-Tang typhoon using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Kishore, P.; Jayalakshmi, J.; Lin, Pay-Liam; Velicogna, Isabella; Sutterley, Tyler C.; Ciracì, Enrico; Mohajerani, Yara; Kumar, S. Balaji

2017-11-01

Equatorial Kelvin waves (KWs) are fundamental components of the tropical climate system. In this study, we investigate Kelvin waves (KWs) during the Hai-Tang typhoon of 2005 using Empirical Mode Decomposition (EMD) of regional precipitation, zonal and meridional winds. For the analysis, we use daily precipitation datasets from the Global Precipitation Climatology Project (GPCP) and wind datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-analysis (ERA-Interim). As an additional measurement, we use in-situ precipitation datasets from rain-gauges over the Taiwan region. The maximum accumulated precipitation was approximately 2400 mm during the period July 17-21, 2005 over the southwestern region of Taiwan. The spectral analysis using the wind speed at 950 hPa found in the 2nd, 3rd, and 4th intrinsic mode functions (IMFs) reveals prevailing Kelvin wave periods of ∼3 days, ∼4-6 days, and ∼6-10 days, respectively. From our analysis of precipitation datasets, we found the Kelvin waves oscillated with periods between ∼8 and 20 days.

Investigation of KDP crystal surface based on an improved bidimensional empirical mode decomposition method

NASA Astrophysics Data System (ADS)

Lu, Lei; Yan, Jihong; Chen, Wanqun; An, Shi

2018-03-01

This paper proposed a novel spatial frequency analysis method for the investigation of potassium dihydrogen phosphate (KDP) crystal surface based on an improved bidimensional empirical mode decomposition (BEMD) method. Aiming to eliminate end effects of the BEMD method and improve the intrinsic mode functions (IMFs) for the efficient identification of texture features, a denoising process was embedded in the sifting iteration of BEMD method. With removing redundant information in decomposed sub-components of KDP crystal surface, middle spatial frequencies of the cutting and feeding processes were identified. Comparative study with the power spectral density method, two-dimensional wavelet transform (2D-WT), as well as the traditional BEMD method, demonstrated that the method developed in this paper can efficiently extract texture features and reveal gradient development of KDP crystal surface. Furthermore, the proposed method was a self-adaptive data driven technique without prior knowledge, which overcame shortcomings of the 2D-WT model such as the parameters selection. Additionally, the proposed method was a promising tool for the application of online monitoring and optimal control of precision machining process.

Transmission and reflection of terahertz plasmons in two-dimensional plasmonic devices

DOE PAGES

Sydoruk, Oleksiy; Choonee, Kaushal; Dyer, Gregory Conrad

2015-03-10

We found that plasmons in two-dimensional semiconductor devices will be reflected by discontinuities, notably, junctions between gated and non-gated electron channels. The transmitted and reflected plasmons can form spatially- and frequency-varying signals, and their understanding is important for the design of terahertz detectors, oscillators, and plasmonic crystals. Using mode decomposition, we studied terahertz plasmons incident on a junction between a gated and a nongated channel. The plasmon reflection and transmission coefficients were found numerically and analytically and studied between 0.3 and 1 THz for a range of electron densities. At higher frequencies, we could describe the plasmons by a simplifiedmore » model of channels in homogeneous dielectrics, for which the analytical approximations were accurate. At low frequencies, however, the full geometry and mode spectrum had to be taken into account. Moreover, the results agreed with simulations by the finite-element method. As a result, mode decomposition thus proved to be a powerful method for plasmonic devices, combining the rigor of complete solutions of Maxwell's equations with the convenience of analytical expressions.« less

Surface reaction modification: The effect of structured overlayers of sulfur on the kinetics and mechanism of the decomposition of formic acid on Pt(111)

NASA Astrophysics Data System (ADS)

Abbas, N.; Madix, R. J.

The reaction of formic acid (DCOOH) on Pt(111), Pt(111)-(2×2)S and Pt(111)-(√3×√3)R30°S surfaces was examined by temperature programmed reaction spectroscopy. On the clean surface formic acid decomposed to yield primarily carbon dioxide and the hydrogenic species (H 2, HD and D 2) at low coverages. Although the formation of water and carbon monoxide via a dehydration reaction was observed at these coverages, the yield of these products was small when compared to the other products of reaction. The evolution of CO 2 at low temperature was ascribed to the decomposition of the formate intermediate. In the presence of sulfur the amount of molecularly adsorbed formic acid decreased up to a factor of three on the (√3×√3)R30°S surface, and a decline in the reactivity of over an order of magnitude was also observed. The only products formed were the hydrogenic species and carbon dioxide. The absence of carbon monoxide indicated that the dehydration pathway was blocked by sulfur. In addition to the low temperature CO 2 peak a high temperature CO 2-producing path was also evident. It was inferred from both the stoichiometry and the coincident evolution of D 2 and CO 2 in the high temperature states that these products also evolved due to the decomposition of the formate intermediate. On increasing the sulfur coverage to one-third monolayer this intermediate was further stabilized, and a predominance of the decomposition via the high temperature path was observed. Stability of the formate intermediate was attributed to inhibition of the decomposition reaction by sulfur atoms. The activation energy for formate decomposition increased from 15 kcal/gmole on the clean surface to 24.3 kcal/gmol on the (√3×√3)R30°S overlayer.

The tempo and mode of evolution: body sizes of island mammals.

PubMed

Raia, Pasquale; Meiri, Shai

2011-07-01

The tempo and mode of body size evolution on islands are believed to be well known. It is thought that body size evolves relatively quickly on islands toward the mammalian modal value, thus generating extreme cases of size evolution and the island rule. Here, we tested both theories in a phylogenetically explicit context, by using two different species-level mammalian phylogenetic hypotheses limited to sister clades dichotomizing into an exclusively insular and an exclusively mainland daughter nodes. Taken as a whole, mammals were found to show a largely punctuational mode of size evolution. We found that, accounting for this, and regardless of the phylogeny used, size evolution on islands is no faster than on the continents. We compared different selection regimes using a set of Ornstein-Uhlenbeck models to examine the effects of insularity of the mode of evolution. The models strongly supported clade-specific selection regimes. Under this regime, however, an evolutionary model allowing insular species to evolve differently from their mainland relatives performs worse than a model that ignores insularity as a factor. Thus, insular taxa do not experience statistically different selection from their mainland relatives. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Causality analysis of leading singular value decomposition modes identifies rotor as the dominant driving normal mode in fibrillation

NASA Astrophysics Data System (ADS)

Biton, Yaacov; Rabinovitch, Avinoam; Braunstein, Doron; Aviram, Ira; Campbell, Katherine; Mironov, Sergey; Herron, Todd; Jalife, José; Berenfeld, Omer

2018-01-01

Cardiac fibrillation is a major clinical and societal burden. Rotors may drive fibrillation in many cases, but their role and patterns are often masked by complex propagation. We used Singular Value Decomposition (SVD), which ranks patterns of activation hierarchically, together with Wiener-Granger causality analysis (WGCA), which analyses direction of information among observations, to investigate the role of rotors in cardiac fibrillation. We hypothesized that combining SVD analysis with WGCA should reveal whether rotor activity is the dominant driving force of fibrillation even in cases of high complexity. Optical mapping experiments were conducted in neonatal rat cardiomyocyte monolayers (diameter, 35 mm), which were genetically modified to overexpress the delayed rectifier K+ channel IKr only in one half of the monolayer. Such monolayers have been shown previously to sustain fast rotors confined to the IKr overexpressing half and driving fibrillatory-like activity in the other half. SVD analysis of the optical mapping movies revealed a hierarchical pattern in which the primary modes corresponded to rotor activity in the IKr overexpressing region and the secondary modes corresponded to fibrillatory activity elsewhere. We then applied WGCA to evaluate the directionality of influence between modes in the entire monolayer using clear and noisy movies of activity. We demonstrated that the rotor modes influence the secondary fibrillatory modes, but influence was detected also in the opposite direction. To more specifically delineate the role of the rotor in fibrillation, we decomposed separately the respective SVD modes of the rotor and fibrillatory domains. In this case, WGCA yielded more information from the rotor to the fibrillatory domains than in the opposite direction. In conclusion, SVD analysis reveals that rotors can be the dominant modes of an experimental model of fibrillation. Wiener-Granger causality on modes of the rotor domains confirms their preferential driving influence on fibrillatory modes.

Intelligent diagnosis of short hydraulic signal based on improved EEMD and SVM with few low-dimensional training samples

NASA Astrophysics Data System (ADS)

Zhang, Meijun; Tang, Jian; Zhang, Xiaoming; Zhang, Jiaojiao

2016-03-01

The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors, however the characteristics of the signal need to be extracted accurately. Although the existing EMD(empirical mode decomposition) and EEMD(ensemble empirical mode decomposition) are suitable for processing non-stationary and non-linear signals, but when a short signal, such as a hydraulic impact signal, is concerned, their decomposition accuracy become very poor. An improve EEMD is proposed specifically for short hydraulic impact signals. The improvements of this new EEMD are mainly reflected in four aspects, including self-adaptive de-noising based on EEMD, signal extension based on SVM(support vector machine), extreme center fitting based on cubic spline interpolation, and pseudo component exclusion based on cross-correlation analysis. After the energy eigenvector is extracted from the result of the improved EEMD, the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied. At last, the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods, and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high. The improved EEMD is very propitious for the decomposition of short signal, such as hydraulic impact signal, and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.

Intracavity vortex beam generation

NASA Astrophysics Data System (ADS)

Naidoo, Darryl; Aït-Ameur, Kamel; Forbes, Andrew

2011-10-01

In this paper we explore vortex beams and in particular the generation of single LG0l modes and superpositions thereof. Vortex beams carry orbital angular momentum (OAM) and this intrinsic property makes them prevalent in transferring this OAM to matter and to be used in quantum information processing. We explore an extra-cavity and intra-cavity approach in LG0l mode generation respectively. The outputs of a Porro-prism resonator are represented by "petals" and we show that through a full modal decomposition, the "petal" fields are a superposition of two LG0l modes.

Numerical Schemes and Computational Studies for Dynamically Orthogonal Equations (Multidisciplinary Simulation, Estimation, and Assimilation Systems: Reports in Ocean Science and Engineering)

DTIC Science & Technology

2011-08-01

heat transfers [49, 52]. However, the DO method has not yet been applied to Boussinesq flows, and the numerical challenges of the DO decomposition for...used a PCE scheme to study mixing in a two-dimensional (2D) microchannel and improved the efficiency of their solution scheme by decoupling the...to several Navier-Stokes flows and their stochastic dynamics has been studied, including mean-mode and mode-mode energy transfers for 2D flows and

Vibrational Softening of a Protein on Ligand Binding

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

Balog, Erica; Perahia, David; Smith, Jeremy C

2011-01-01

Neutron scattering experiments have demonstrated that binding of the cancer drug methotrexate softens the low-frequency vibrations of its target protein, dihydrofolate reductase (DHFR). Here, this softening is fully reproduced using atomic detail normal-mode analysis. Decomposition of the vibrational density of states demonstrates that the largest contributions arise from structural elements of DHFR critical to stability and function. Mode-projection analysis reveals an increase of the breathing-like character of the affected vibrational modes consistent with the experimentally observed increased adiabatic compressibility of the protein on complexation.

Noncatalytic hydrazine thruster development - 0.050 to 5.0 pounds thrust

NASA Technical Reports Server (NTRS)

Murch, C. K.; Sackheim, R. L.; Kuenzly, J. D.; Callens, R. A.

1976-01-01

Noncatalytic (thermal-decompositon) hydrazine thrusters can operate in both the pulsing and steady-state modes to meet the propulsive requirements of long-life spacecraft. The thermal decomposition mode yields higher specific impulse than is characteristic of catalytic thrusters at similar thrust levels. This performance gain is the result of higher temperature operation and a lower fraction of ammonia dissociation. Some life limiting factors of catalytic thrusters are eliminated.

Measuring the magnetic field of a trans-equatorial loop system using coronal seismology

NASA Astrophysics Data System (ADS)

Long, D. M.; Valori, G.; Pérez-Suárez, D.; Morton, R. J.; Vásquez, A. M.

2017-07-01

Context. EIT waves are freely-propagating global pulses in the low corona which are strongly associated with the initial evolution of coronal mass ejections (CMEs). They are thought to be large-amplitude, fast-mode magnetohydrodynamic waves initially driven by the rapid expansion of a CME in the low corona. Aims: An EIT wave was observed on 6 July 2012 to impact an adjacent trans-equatorial loop system which then exhibited a decaying oscillation as it returned to rest. Observations of the loop oscillations were used to estimate the magnetic field strength of the loop system by studying the decaying oscillation of the loop, measuring the propagation of ubiquitous transverse waves in the loop and extrapolating the magnetic field from observed magnetograms. Methods: Observations from the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory (SDO/AIA) and the Coronal Multi-channel Polarimeter (CoMP) were used to study the event. An Empirical Mode Decomposition analysis was used to characterise the oscillation of the loop system in CoMP Doppler velocity and line width and in AIA intensity. Results: The loop system was shown to oscillate in the 2nd harmonic mode rather than at the fundamental frequency, with the seismological analysis returning an estimated magnetic field strength of ≈ 5.5 ± 1.5 G. This compares to the magnetic field strength estimates of ≈1-9 G and ≈3-9 G found using the measurements of transverse wave propagation and magnetic field extrapolation respectively. A movie associated to Figs. 1 and 2 is available at http://www.aanda.org

Exploring Galaxy Formation and Evolution via Structural Decomposition

NASA Astrophysics Data System (ADS)

Kelvin, Lee; Driver, Simon; Robotham, Aaron; Hill, David; Cameron, Ewan

2010-06-01

The Galaxy And Mass Assembly (GAMA) structural decomposition pipeline (GAMA-SIGMA Structural Investigation of Galaxies via Model Analysis) will provide multi-component information for a sample of ~12,000 galaxies across 9 bands ranging from near-UV to near-IR. This will allow the relationship between structural properties and broadband, optical-to-near-IR, spectral energy distributions of bulge, bar, and disk components to be explored, revealing clues as to the history of baryonic mass assembly within a hierarchical clustering framework. Data is initially taken from the SDSS & UKIDSS-LAS surveys to test the robustness of our automated decomposition pipeline. This will eventually be replaced with the forthcoming higher-resolution VST & VISTA surveys data, expanding the sample to ~30,000 galaxies.

Determination of the mode composition of long-wave disturbances in a supersonic flow in a hotshot wind tunnel

NASA Astrophysics Data System (ADS)

Tsyryulnikov, I. S.; Kirilovskiy, S. V.; Poplavskaya, T. V.

2016-10-01

In this paper, we describe a new method of mode decomposition of disturbances on the basis of specific features of interaction of long-wave free-stream disturbances with the shock wave and knowing the trends of changing of the conversion factors of various disturbance modes due to variations of the shock wave incidence angle. The range of admissible root-mean-square amplitudes of oscillations of vortex, entropy, and acoustic modes in the free stream generated in IT-302M was obtained by using the pressure fluctuations measured on the model surface and the calculated conversion factors.

Simulation of transverse modes with their intrinsic Landau damping for bunched beams in the presence of space charge

DOE PAGES

Macridin, Alexandru; Burov, Alexey; Stern, Eric; ...

2015-07-22

Transverse dipole modes in bunches with space charge are simulated using the synergia accelerator modeling package and analyzed with dynamic mode decomposition. The properties of the first three space charge modes, including their shape, damping rates, and tune shifts are described over the entire range of space charge strength. As a result, the intrinsic Landau damping predicted and estimated in 2009 by one of the authors is confirmed with a reasonable scaling factor of ≃2.4. For the KV distribution, very good agreement with PATRIC simulations performed by Kornilov and Boine-Frankenheim is obtained.

On Unified Mode in Grid Mounted Round Jets

NASA Astrophysics Data System (ADS)

Parimalanathan, Senthil Kumar; T, Sundararajan; v, Raghavan

2015-11-01

The turbulence evolution in a free round jet is strongly affected by its initial conditions. Since the transition to turbulence is moderated by instability modes, the initial conditions seem to play a major role in altering the dynamics of these modes. In the present investigation, grids of different configurations are placed at the jet nozzle exit and the flow field characterization is carried out using a bi-component hot-wire anemometer. The instability modes has been obtained by analyzing the velocity spectral data. Free jets are characterized by the presence of two instability modes, viz., the preferred mode and the shear mode. The preferred mode corresponds to the most amplified oscillations along the jet centerline, while the shear modes are due to the dynamic evolution of vortical structures in the jet shear layer. The presence of grid clearly alters the jet structure, and plays a major role in altering the shear layer mode in particular. In fact, it is observed that close to the nozzle exit, the presence of grids deviate the streamlines inwards around the edge due to the momentum difference between the jet central core and the boundary layer region near the wall. This result in a single unified mode, where there is no distinct preferred or shear mode. This phenomena is more dominant in case of the grids having higher blockage ratio with small grid opening. In the present study, investigation of the physics behind the evolution of unified mode and how the grids affect the overall turbulent flow field evolution has been reported. Experimental Fluid Mechanics.

Flash pyrolysis of coal, coal maceral, and coal-derived pyrite with on-line characterization of volatile sulfur compounds

USGS Publications Warehouse

Chou, I.-Ming; Lake, M.A.; Griffin, R.A.

1988-01-01

A Pyroprobe flash pyrolysis-gas chromatograph equipped with a flame photometric detector was used to study volatile sulfur compounds produced during the thermal decomposition of Illinois coal, coal macerals and coal-derived pyrite. Maximum evolution of volatile organic sulfur compounds from all coal samples occurred at a temperature of approximately 700??C. At this temperature, the evolution of thiophene, its alkyl isomers, and short-chain dialkyl sulfide compounds relative to the evolution of benzothiophene and dibenzothiophene compounds was greater from coal high in organic sulfur than from coal low in organic sulfur. The variation in the evolution of sulfur compounds observed for three separate coal macerals (exinite, vitrinite, and inertinite) was similar to that observed for whole coal samples. However, the variation trend for the macerals was much more pronounced. Decomposition of coal-derived pyrite with the evolution of elemental sulfur was detected at a temperature greater than 700??C. The results of this study indicated that the gas chromotographic profile of the volatile sulfur compounds produced during flash pyrolysis of coals and coal macerals varied as a function of the amount of organic sulfur that occurred in the samples. Characterization of these volatile sulfur compounds provides a better understanding of the behavior of sulfur in coal during the thermolysis process, which could be incorporated in the design for coal cleaning using flash pyrolysis techniques. ?? 1988.

Numerical simulation of interaction of long-wave disturbances with a shock wave on a wedge for the problem of mode decomposition of supersonic flow oscillations

NASA Astrophysics Data System (ADS)

Kirilovskiy, S. V.; Poplavskaya, T. V.; Tsyryulnikov, I. S.

2016-10-01

This work is aimed at obtaining conversion factors of free stream disturbances from shock wave angle φ, angle of acoustic disturbances distribution θ and Mach number M∞ by solving a problem of interaction of long-wave (with the wavelength λ greater than the model length) free-stream disturbances with a shock wave formed in a supersonic flow around the wedge. Conversion factors at x/λ=0.2 as a ration between amplitude of pressure pulsations on the wedge surface and free stream disturbances amplitude were obtained. Factors of conversion were described by the dependence on angle θ of disturbances distribution, shock wave angle φ and Mach number M∞. These dependences are necessary for solving the problem of mode decomposition of disturbances in supersonic flows in wind tunnels.

Bi-dimensional empirical mode decomposition based fringe-like pattern suppression in polarization interference imaging spectrometer

NASA Astrophysics Data System (ADS)

Ren, Wenyi; Cao, Qizhi; Wu, Dan; Jiang, Jiangang; Yang, Guoan; Xie, Yingge; Wang, Guodong; Zhang, Sheqi

2018-01-01

Many observers using interference imaging spectrometer were plagued by the fringe-like pattern(FP) that occurs for optical wavelengths in red and near-infrared region. It brings us more difficulties in the data processing such as the spectrum calibration, information retrieval, and so on. An adaptive method based on the bi-dimensional empirical mode decomposition was developed to suppress the nonlinear FP in polarization interference imaging spectrometer. The FP and corrected interferogram were separated effectively. Meanwhile, the stripes introduced by CCD mosaic was suppressed. The nonlinear interferogram background removal and the spectrum distortion correction were implemented as well. It provides us an alternative method to adaptively suppress the nonlinear FP without prior experimental data and knowledge. This approach potentially is a powerful tool in the fields of Fourier transform spectroscopy, holographic imaging, optical measurement based on moire fringe, etc.

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Cheung, Samson; Li, Jui-Lin F.; Wu, Yu-ling

2013-01-01

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

Estimation of pulse rate from ambulatory PPG using ensemble empirical mode decomposition and adaptive thresholding.

PubMed

Pittara, Melpo; Theocharides, Theocharis; Orphanidou, Christina

2017-07-01

A new method for deriving pulse rate from PPG obtained from ambulatory patients is presented. The method employs Ensemble Empirical Mode Decomposition to identify the pulsatile component from noise-corrupted PPG, and then uses a set of physiologically-relevant rules followed by adaptive thresholding, in order to estimate the pulse rate in the presence of noise. The method was optimized and validated using 63 hours of data obtained from ambulatory hospital patients. The F1 score obtained with respect to expertly annotated data was 0.857 and the mean absolute errors of estimated pulse rates with respect to heart rates obtained from ECG collected in parallel were 1.72 bpm for "good" quality PPG and 4.49 bpm for "bad" quality PPG. Both errors are within the clinically acceptable margin-of-error for pulse rate/heart rate measurements, showing the promise of the proposed approach for inclusion in next generation wearable sensors.

Gyroscope-driven mouse pointer with an EMOTIV® EEG headset and data analysis based on Empirical Mode Decomposition.

PubMed

Rosas-Cholula, Gerardo; Ramirez-Cortes, Juan Manuel; Alarcon-Aquino, Vicente; Gomez-Gil, Pilar; Rangel-Magdaleno, Jose de Jesus; Reyes-Garcia, Carlos

2013-08-14

This paper presents a project on the development of a cursor control emulating the typical operations of a computer-mouse, using gyroscope and eye-blinking electromyographic signals which are obtained through a commercial 16-electrode wireless headset, recently released by Emotiv. The cursor position is controlled using information from a gyroscope included in the headset. The clicks are generated through the user's blinking with an adequate detection procedure based on the spectral-like technique called Empirical Mode Decomposition (EMD). EMD is proposed as a simple and quick computational tool, yet effective, aimed to artifact reduction from head movements as well as a method to detect blinking signals for mouse control. Kalman filter is used as state estimator for mouse position control and jitter removal. The detection rate obtained in average was 94.9%. Experimental setup and some obtained results are presented.

Gyroscope-Driven Mouse Pointer with an EMOTIV® EEG Headset and Data Analysis Based on Empirical Mode Decomposition

PubMed Central

Rosas-Cholula, Gerardo; Ramirez-Cortes, Juan Manuel; Alarcon-Aquino, Vicente; Gomez-Gil, Pilar; Rangel-Magdaleno, Jose de Jesus; Reyes-Garcia, Carlos

2013-01-01

This paper presents a project on the development of a cursor control emulating the typical operations of a computer-mouse, using gyroscope and eye-blinking electromyographic signals which are obtained through a commercial 16-electrode wireless headset, recently released by Emotiv. The cursor position is controlled using information from a gyroscope included in the headset. The clicks are generated through the user's blinking with an adequate detection procedure based on the spectral-like technique called Empirical Mode Decomposition (EMD). EMD is proposed as a simple and quick computational tool, yet effective, aimed to artifact reduction from head movements as well as a method to detect blinking signals for mouse control. Kalman filter is used as state estimator for mouse position control and jitter removal. The detection rate obtained in average was 94.9%. Experimental setup and some obtained results are presented. PMID:23948873

Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications.

PubMed

Hemakom, Apit; Goverdovsky, Valentin; Looney, David; Mandic, Danilo P

2016-04-13

An extension to multivariate empirical mode decomposition (MEMD), termed adaptive-projection intrinsically transformed MEMD (APIT-MEMD), is proposed to cater for power imbalances and inter-channel correlations in real-world multichannel data. It is shown that the APIT-MEMD exhibits similar or better performance than MEMD for a large number of projection vectors, whereas it outperforms MEMD for the critical case of a small number of projection vectors within the sifting algorithm. We also employ the noise-assisted APIT-MEMD within our proposed intrinsic multiscale analysis framework and illustrate the advantages of such an approach in notoriously noise-dominated cooperative brain-computer interface (BCI) based on the steady-state visual evoked potentials and the P300 responses. Finally, we show that for a joint cognitive BCI task, the proposed intrinsic multiscale analysis framework improves system performance in terms of the information transfer rate. © 2016 The Author(s).

Towards estimation of respiratory muscle effort with respiratory inductance plethysmography signals and complementary ensemble empirical mode decomposition.

PubMed

Chen, Ya-Chen; Hsiao, Tzu-Chien

2018-07-01

Respiratory inductance plethysmography (RIP) sensor is an inexpensive, non-invasive, easy-to-use transducer for collecting respiratory movement data. Studies have reported that the RIP signal's amplitude and frequency can be used to discriminate respiratory diseases. However, with the conventional approach of RIP data analysis, respiratory muscle effort cannot be estimated. In this paper, the estimation of the respiratory muscle effort through RIP signal was proposed. A complementary ensemble empirical mode decomposition method was used, to extract hidden signals from the RIP signals based on the frequency bands of the activities of different respiratory muscles. To validate the proposed method, an experiment to collect subjects' RIP signal under thoracic breathing (TB) and abdominal breathing (AB) was conducted. The experimental results for both the TB and AB indicate that the proposed method can be used to loosely estimate the activities of thoracic muscles, abdominal muscles, and diaphragm. Graphical abstract ᅟ.

The evolution of reproductive diversity in Afrobatrachia: A phylogenetic comparative analysis of an extensive radiation of African frogs.

PubMed

Portik, Daniel M; Blackburn, David C

2016-09-01

The reproductive modes of anurans (frogs and toads) are the most diverse of terrestrial vertebrates, and a major challenge is identifying selective factors that promote the evolution or retention of reproductive modes across clades. Terrestrialized anuran breeding strategies have evolved repeatedly from the plesiomorphic fully aquatic reproductive mode, a process thought to occur through intermediate reproductive stages. Several selective forces have been proposed for the evolution of terrestrialized reproductive traits, but factors such as water systems and co-evolution with ecomorphologies have not been investigated. We examined these topics in a comparative phylogenetic framework using Afrobatrachian frogs, an ecologically and reproductively diverse clade representing more than half of the total frog diversity found in Africa (∼400 species). We infer direct development has evolved twice independently from terrestrialized reproductive modes involving subterranean or terrestrial oviposition, supporting evolution through intermediate stages. We also detect associations between specific ecomorphologies and oviposition sites, and demonstrate arboreal species exhibit an overall shift toward using lentic water systems for breeding. These results indicate that changes in microhabitat use associated with ecomorphology, which allow access to novel sites for reproductive behavior, oviposition, or larval development, may also promote reproductive mode diversity in anurans. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Nonlinear Evolution of Counter-Propagating Whistler Mode Waves Excited by Anisotropic Electrons Within the Equatorial Source Region: 1-D PIC Simulations

NASA Astrophysics Data System (ADS)

Chen, Huayue; Gao, Xinliang; Lu, Quanming; Sun, Jicheng; Wang, Shui

2018-02-01

Nonlinear physical processes related to whistler mode waves are attracting more and more attention for their significant role in reshaping whistler mode spectra in the Earth's magnetosphere. Using a 1-D particle-in-cell simulation model, we have investigated the nonlinear evolution of parallel counter-propagating whistler mode waves excited by anisotropic electrons within the equatorial source region. In our simulations, after the linear phase of whistler mode instability, the strong electrostatic standing structures along the background magnetic field will be formed, resulting from the coupling between excited counter-propagating whistler mode waves. The wave numbers of electrostatic standing structures are about twice those of whistler mode waves generated by anisotropic hot electrons. Moreover, these electrostatic standing structures can further be coupled with either parallel or antiparallel propagating whistler mode waves to excite high-k modes in this plasma system. Compared with excited whistler mode waves, these high-k modes typically have 3 times wave number, same frequency, and about 2 orders of magnitude smaller amplitude. Our study may provide a fresh view on the evolution of whistler mode waves within their equatorial source regions in the Earth's magnetosphere.

Simulation of Decomposition Kinetics of Supercooled Austenite in Powder Steel

NASA Astrophysics Data System (ADS)

Tsyganova, M. S.; Ivashko, A. G.; Polyshuk, I. N.; Nabatov, R. I.; Tsyganova, A. I.

2017-10-01

To approve heat treatment of steel modes, quantitative data on austenite decomposition are required. Gaining these data experimentally appears to be extremely complicated. In present work, few approaches to simulate the phase transformation process are proposed considering structure characteristics of powder steels. Results of comparative analysis of these approaches are also given. Predicting the transformation kinetics by simulation is verified for PK40N2M (0.38% C, 2.10% Ni, 0.40% Mo) steel with 3% porosity and PK80 (0.80% C) steel with different porosity using published experimental data.

A New View of Earthquake Ground Motion Data: The Hilbert Spectral Analysis

NASA Technical Reports Server (NTRS)

Huang, Norden; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

A brief description of the newly developed Empirical Mode Decomposition (ENID) and Hilbert Spectral Analysis (HSA) method will be given. The decomposition is adaptive and can be applied to both nonlinear and nonstationary data. Example of the method applied to a sample earthquake record will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Natural periodicities and Northern Hemisphere-Southern Hemisphere connection of temperature changes during the last glacial period: EPICA and NGRIP data sets revisited

NASA Astrophysics Data System (ADS)

Alberti, Tommaso; Lepreti, Fabio; Vecchio, Antonio; Bevacqua, Emanuele; Capparelli, Vincenzo; Carbone, Vincenzo

2015-04-01

We investigate both the European Project for Ice Coring in Antarctica Dronning Maud Land (EDML) and North Greenland Ice-Core Project (NGRIP) δ18O data sets to study both the time evolution of the so-called Dansgaard-Oeschger events and the dynamics at longer timescales during the last glacial period, considering the interval 20 - 120 kyr B.P., since this is the interval in which significant temperature changes, that are the focus of the present work, are observed. To identify the main periodicities and their amplitudes, we applied the Empirical Mode Decomposition (EMD), a technique designed to investigate non-stationary data, by which both the δ18O time series are decomposed into a finite number m of oscillating intrinsic mode functions (IMFs) as 18 mΣ-1 δ O = Cj(t)+ rm(t) j=0 (1) where Cj(t) are the IMFs and rm(t) is a residue which provides the mean trend. We extract the proper modes of both the data sets confirming that natural cycles of abrupt climate changes exist and their occurrence cannot be due to random fluctuations in time. It is shown that the time behavior at the typical timescales of Dansgaard-Oeschger events is captured through signal reconstructions obtained by summing five EMD modes for NGRIP and four EMD modes for EDML. The reconstructions obtained by summing the successive modes can be used to describe the climate evolution at longer timescales, characterized by intervals in which Dansgaard-Oeschger events happen and intervals when these are not observed. Using EMD signal reconstructions and a simple model based on the one-dimensional Langevin equation, it is argued that the occurrence of a Dansgaard-Oeschger event can be described as an excitation of the climate system within the same state, while the longer timescale behavior appears to be due to transitions between different climate states. Finally, on the basis of a cross correlation analysis performed to investigate the North-South asynchrony, it is found that the clearest correlation occurs between the long-scale reconstructions at a lag of ≃ 3.05 kyr, which supports the view according to which the Antarctic climate changes lead that of Greenland, but on a longer time-scale than previously reported. The novelty introduced by this work is represented by the fact that we use EMD reconstructions to investigate the climate dynamics at different timescales and to highlight the behaviour of the climate system in order to describe transitions between two different stable states. We also suggest that the results of correlation analysis could be explained in the framework of seesaw models but building up a model which take into account our EMD filtered long timescales series. The results presented could be also useful for theoretical modeling of the climate evolution in order to study which kind of mechanisms are involved and to clarify the role of the ocean into coupling mechanism between the two hemispheres.

Natural periodicities and Northern Hemisphere-Southern Hemisphere connection of temperature changes during the last glacial period: EPICA and NGRIP data sets revisited

NASA Astrophysics Data System (ADS)

Alberti, Tommaso; Lepreti, Fabio; Vecchio, Antonio; Carbone, Vincenzo

2016-04-01

We investigate both the European Project for Ice Coring in Antarctica Dronning Maud Land (EDML) and North Greenland Ice-Core Project (NGRIP) δ18O data sets to study both the time evolution of the so-called Dansgaard-Oeschger events and the dynamics at longer timescales during the last glacial period, considering the interval 20 - 120 kyr B.P., since this is the interval in which significant temperature changes, that are the focus of the present work, are observed. To identify the main periodicities and their amplitudes, we applied the Empirical Mode Decomposition (EMD), a technique designed to investigate non-stationary data, by which both the δ18O time series are decomposed into a finite number m of oscillating intrinsic mode functions (IMFs) as 18 m∑-1 δ O = Cj(t)+ rm(t) j=0 (1) where Cj(t) are the IMFs and rm(t) is a residue which provides the mean trend. We extract the proper modes of both the data sets confirming that natural cycles of abrupt climate changes exist and their occurrence cannot be due to random fluctuations in time. It is shown that the time behavior at the typical timescales of Dansgaard-Oeschger events is captured through signal reconstructions obtained by summing five EMD modes for NGRIP and four EMD modes for EDML. The reconstructions obtained by summing the successive modes can be used to describe the climate evolution at longer timescales, characterized by intervals in which Dansgaard-Oeschger events happen and intervals when these are not observed. Using EMD signal reconstructions and a simple model based on the one-dimensional Langevin equation, it is argued that the occurrence of a Dansgaard-Oeschger event can be described as an excitation of the climate system within the same state, while the longer timescale behavior appears to be due to transitions between different climate states. Finally, on the basis of a cross correlation analysis performed to investigate the North-South asynchrony, it is found that the clearest correlation occurs between the long-scale reconstructions at a lag of ≃ 3.05 kyr, which supports the view according to which the Antarctic climate changes lead that of Greenland, but on a longer time-scale than previously reported. The novelty introduced by this work is represented by the fact that we use EMD reconstructions to investigate the climate dynamics at different timescales and to highlight the behaviour of the climate system in order to describe transitions between two different stable states. We also suggest that the results of correlation analysis could be explained in the framework of seesaw models but building up a model which take into account our EMD filtered long timescales series. The results presented could be also useful for theoretical modeling of the climate evolution in order to study which kind of mechanisms are involved and to clarify the role of the ocean into coupling mechanism between the two hemispheres.

Ensemble Empirical Mode Decomposition based methodology for ultrasonic testing of coarse grain austenitic stainless steels.

PubMed

Sharma, Govind K; Kumar, Anish; Jayakumar, T; Purnachandra Rao, B; Mariyappa, N

2015-03-01

A signal processing methodology is proposed in this paper for effective reconstruction of ultrasonic signals in coarse grained high scattering austenitic stainless steel. The proposed methodology is comprised of the Ensemble Empirical Mode Decomposition (EEMD) processing of ultrasonic signals and application of signal minimisation algorithm on selected Intrinsic Mode Functions (IMFs) obtained by EEMD. The methodology is applied to ultrasonic signals obtained from austenitic stainless steel specimens of different grain size, with and without defects. The influence of probe frequency and data length of a signal on EEMD decomposition is also investigated. For a particular sampling rate and probe frequency, the same range of IMFs can be used to reconstruct the ultrasonic signal, irrespective of the grain size in the range of 30-210 μm investigated in this study. This methodology is successfully employed for detection of defects in a 50mm thick coarse grain austenitic stainless steel specimens. Signal to noise ratio improvement of better than 15 dB is observed for the ultrasonic signal obtained from a 25 mm deep flat bottom hole in 200 μm grain size specimen. For ultrasonic signals obtained from defects at different depths, a minimum of 7 dB extra enhancement in SNR is achieved as compared to the sum of selected IMF approach. The application of minimisation algorithm with EEMD processed signal in the proposed methodology proves to be effective for adaptive signal reconstruction with improved signal to noise ratio. This methodology was further employed for successful imaging of defects in a B-scan. Copyright © 2014. Published by Elsevier B.V.

RIO: a new computational framework for accurate initial data of binary black holes

NASA Astrophysics Data System (ADS)

Barreto, W.; Clemente, P. C. M.; de Oliveira, H. P.; Rodriguez-Mueller, B.

2018-06-01

We present a computational framework ( Rio) in the ADM 3+1 approach for numerical relativity. This work enables us to carry out high resolution calculations for initial data of two arbitrary black holes. We use the transverse conformal treatment, the Bowen-York and the puncture methods. For the numerical solution of the Hamiltonian constraint we use the domain decomposition and the spectral decomposition of Galerkin-Collocation. The nonlinear numerical code solves the set of equations for the spectral modes using the standard Newton-Raphson method, LU decomposition and Gaussian quadratures. We show the convergence of the Rio code. This code allows for easy deployment of large calculations. We show how the spin of one of the black holes is manifest in the conformal factor.

NASREN: Standard reference model for telerobot control

NASA Technical Reports Server (NTRS)

Albus, J. S.; Lumia, R.; Mccain, H.

1987-01-01

A hierarchical architecture is described which supports space station telerobots in a variety of modes. The system is divided into three hierarchies: task decomposition, world model, and sensory processing. Goals at each level of the task dedomposition heirarchy are divided both spatially and temporally into simpler commands for the next lower level. This decomposition is repreated until, at the lowest level, the drive signals to the robot actuators are generated. To accomplish its goals, task decomposition modules must often use information stored it the world model. The purpose of the sensory system is to update the world model as rapidly as possible to keep the model in registration with the physical world. The architecture of the entire control system hierarch is described and how it can be applied to space telerobot applications.

Efficient dehydrogenation of formic acid using Al12N12 nanocage: A DFT study

NASA Astrophysics Data System (ADS)

Esrafili, Mehdi D.; Nurazar, Roghaye

2014-11-01

We have studied the adsorption and decomposition of formic acid (HCOOH) on the surface of Al12N12 fullerene-like nanocage using density functional theory. Different adsorption modes were found for HCOOH on the Al12N12, i.e. molecular and dissociative monodentate or bidentate adsorption. Three reaction pathways were proposed to understand gas-phase HCOOH decomposition on the Al12N12 nanocage. Our results reveal that for the decomposition of HCOOH into CO2 and H2, the most favorable pathway should be the Csbnd H bond activation reaction. The reaction energies and the activation barriers obtained here suggest that for the dissociative adsorption configuration on the Al12N12 surface, the rate-determining step is the Csbnd H bond breaking.

CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system

NASA Astrophysics Data System (ADS)

Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao

2016-09-01

Hydrological forecasting is complicated by flow regime alterations in a coupled socio-hydrologic system, encountering increasingly non-stationary, nonlinear and irregular changes, which make decision support difficult for future water resources management. Currently, many hybrid data-driven models, based on the decomposition-prediction-reconstruction principle, have been developed to improve the ability to make predictions of annual streamflow. However, there exist many problems that require further investigation, the chief among which is the direction of trend components decomposed from annual streamflow series and is always difficult to ascertain. In this paper, a hybrid data-driven model was proposed to capture this issue, which combined empirical mode decomposition (EMD), radial basis function neural networks (RBFNN), and external forces (EF) variable, also called the CEREF model. The hybrid model employed EMD for decomposition and RBFNN for intrinsic mode function (IMF) forecasting, and determined future trend component directions by regression with EF as basin water demand representing the social component in the socio-hydrologic system. The Wuding River basin was considered for the case study, and two standard statistical measures, root mean squared error (RMSE) and mean absolute error (MAE), were used to evaluate the performance of CEREF model and compare with other models: the autoregressive (AR), RBFNN and EMD-RBFNN. Results indicated that the CEREF model had lower RMSE and MAE statistics, 42.8% and 7.6%, respectively, than did other models, and provided a superior alternative for forecasting annual runoff in the Wuding River basin. Moreover, the CEREF model can enlarge the effective intervals of streamflow forecasting compared to the EMD-RBFNN model by introducing the water demand planned by the government department to improve long-term prediction accuracy. In addition, we considered the high-frequency component, a frequent subject of concern in EMD-based forecasting, and results showed that removing high-frequency component is an effective measure to improve forecasting precision and is suggested for use with the CEREF model for better performance. Finally, the study concluded that the CEREF model can be used to forecast non-stationary annual streamflow change as a co-evolution of hydrologic and social systems with better accuracy. Also, the modification about removing high-frequency can further improve the performance of the CEREF model. It should be noted that the CEREF model is beneficial for data-driven hydrologic forecasting in complex socio-hydrologic systems, and as a simple data-driven socio-hydrologic forecasting model, deserves more attention.

Acoustic wave propagation and intensity fluctuations in shallow water 2006 experiment

NASA Astrophysics Data System (ADS)

Luo, Jing

Fluctuations of low frequency sound propagation in the presence of nonlinear internal waves during the Shallow Water 2006 experiment are analyzed. Acoustic waves and environmental data including on-board ship radar images were collected simultaneously before, during, and after a strong internal solitary wave packet passed through a source-receiver acoustic track. Analysis of the acoustic wave signals shows temporal intensity fluctuations. These fluctuations are affected by the passing internal wave and agrees well with the theory of the horizontal refraction of acoustic wave propagation in shallow water. The intensity focusing and defocusing that occurs in a fixed source-receiver configuration while internal wave packet approaches and passes the acoustic track is addressed in this thesis. Acoustic ray-mode theory is used to explain the modal evolution of broadband acoustic waves propagating in a shallow water waveguide in the presence of internal waves. Acoustic modal behavior is obtained from the data through modal decomposition algorithms applied to data collected by a vertical line array of hydrophones. Strong interference patterns are observed in the acoustic data, whose main cause is identified as the horizontal refraction referred to as the horizontal Lloyd mirror effect. To analyze this interference pattern, combined Parabolic Equation model and Vertical-mode horizontal-ray model are utilized. A semi-analytic formula for estimating the horizontal Lloyd mirror effect is developed.

Classification of Features of Pavement Profiles Using Empirical Mode Decomposition

DOT National Transportation Integrated Search

2014-12-01

The Long-Term Pavement Performance (LTPP) database contains surface profile data for numerous pavements that are used mainly for computing International Roughness Index (IRI).(2) In order to obtain more information from these surface profiles, a Hilb...

Seismic random noise attenuation method based on empirical mode decomposition of Hausdorff dimension

NASA Astrophysics Data System (ADS)

Yan, Z.; Luan, X.

2017-12-01

Introduction Empirical mode decomposition (EMD) is a noise suppression algorithm by using wave field separation, which is based on the scale differences between effective signal and noise. However, since the complexity of the real seismic wave field results in serious aliasing modes, it is not ideal and effective to denoise with this method alone. Based on the multi-scale decomposition characteristics of the signal EMD algorithm, combining with Hausdorff dimension constraints, we propose a new method for seismic random noise attenuation. First of all, We apply EMD algorithm adaptive decomposition of seismic data and obtain a series of intrinsic mode function (IMF)with different scales. Based on the difference of Hausdorff dimension between effectively signals and random noise, we identify IMF component mixed with random noise. Then we use threshold correlation filtering process to separate the valid signal and random noise effectively. Compared with traditional EMD method, the results show that the new method of seismic random noise attenuation has a better suppression effect. The implementation process The EMD algorithm is used to decompose seismic signals into IMF sets and analyze its spectrum. Since most of the random noise is high frequency noise, the IMF sets can be divided into three categories: the first category is the effective wave composition of the larger scale; the second category is the noise part of the smaller scale; the third category is the IMF component containing random noise. Then, the third kind of IMF component is processed by the Hausdorff dimension algorithm, and the appropriate time window size, initial step and increment amount are selected to calculate the Hausdorff instantaneous dimension of each component. The dimension of the random noise is between 1.0 and 1.05, while the dimension of the effective wave is between 1.05 and 2.0. On the basis of the previous steps, according to the dimension difference between the random noise and effective signal, we extracted the sample points, whose fractal dimension value is less than or equal to 1.05 for the each IMF components, to separate the residual noise. Using the IMF components after dimension filtering processing and the effective wave IMF components after the first selection for reconstruction, we can obtained the results of de-noising.

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition

PubMed Central

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-01-01

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijiang stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five models. The scatterplots of the predicted results of the six models versus the original daily LST data series show that the hybrid EEMD-LSTM model is superior to the other five models. It is concluded that the proposed hybrid EEMD-LSTM model in this study is a suitable tool for temperature forecasting. PMID:29883381

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.

PubMed

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-05-21

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five models. The scatterplots of the predicted results of the six models versus the original daily LST data series show that the hybrid EEMD-LSTM model is superior to the other five models. It is concluded that the proposed hybrid EEMD-LSTM model in this study is a suitable tool for temperature forecasting.

A Raman spectroscopic determination of the kinetics of decomposition of ammonium chromate (NH 4) 2CrO 4

NASA Astrophysics Data System (ADS)

De Waal, D.; Heyns, A. M.; Range, K.-J.

1989-06-01

Raman spectroscopy was used as a method in the kinetic investigation of the thermal decomposition of solid (NH 4) 2CrO 4. Time-dependent measurements of the intensity of the totally symmetric stretching CrO mode of (NH 4) 2CrO 4 have been made between 343 and 363 K. A short initial acceleratory period is observed at lower temperatures and the decomposition reaction decelerates after the maximum decomposition rate has been reached at all temperatures. These results can be interpreted in terms of the Avrami-Erofe'ev law 1 - (χ r) {1}/{2} = kt , where χr is the fraction of reactant at time t. At 358 K, k is equal to 1.76 ± 0.01 × 10 -3 sec -1 for microcrystals and for powdered samples. Activation energies of 97 ± 10 and 49 ± 0.9 kJ mole -1 have been calculated for microcrystalline and powdered samples, respectively.

On the identification of normal modes of oscillation from observations of the solar periphery

NASA Technical Reports Server (NTRS)

Gough, D. D.; Latour, J.

1984-01-01

The decomposition of solar oscillations into their constituent normal modes requires a knowledge of both the spatial and temporal variation of the perturbation to the Sun's surface. The task is especially difficult when only limited spatial information is available. Observations of the limb darkening function, for example, are probably sensitive to too large a number of modes to permit most of the modes to be identified in a power spectrum of measurements at only a few points on the limb, unless the results are combined with other data. A procedure was considered by which the contributions from quite small groups of modes to spatially well resolved data obtained at any instant can be extracted from the remaining modes. Combining these results with frequency information then permits the modes to be identified, at least if their frequencies are low enough to ensure that modes of high degree do not contribute substantially to the signal.

A roadmap for bridging basic and applied research in forensic entomology.

PubMed

Tomberlin, J K; Mohr, R; Benbow, M E; Tarone, A M; VanLaerhoven, S

2011-01-01

The National Research Council issued a report in 2009 that heavily criticized the forensic sciences. The report made several recommendations that if addressed would allow the forensic sciences to develop a stronger scientific foundation. We suggest a roadmap for decomposition ecology and forensic entomology hinging on a framework built on basic research concepts in ecology, evolution, and genetics. Unifying both basic and applied research fields under a common umbrella of terminology and structure would facilitate communication in the field and the production of scientific results. It would also help to identify novel research areas leading to a better understanding of principal underpinnings governing ecosystem structure, function, and evolution while increasing the accuracy of and ability to interpret entomological evidence collected from crime scenes. By following the proposed roadmap, a bridge can be built between basic and applied decomposition ecology research, culminating in science that could withstand the rigors of emerging legal and cultural expectations.

Pt deposited TiO2 catalyst fabricated by thermal decomposition of titanium complex for solar hydrogen production

NASA Astrophysics Data System (ADS)

Truong, Quang Duc; Le, Thanh Son; Ling, Yong-Chien

2014-12-01

C, N codoped TiO2 catalyst has been synthesized by thermal decomposition of a novel water-soluble titanium complex. The structure, morphology, and optical properties of the synthesized TiO2 catalyst were characterized by X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, and UV-vis diffuse reflectance spectroscopy. The photocatalytic activity of the Pt deposited TiO2 catalysts synthesized at different temperatures was evaluated by means of hydrogen evolution reaction under both UV-vis and visible light irradiation. The investigation results reveal that the photocatalytic H2 evolution rate strongly depended on the crystalline grain size as well as specific surface area of the synthesized catalyst. Our studies successfully demonstrate a simple method for the synthesis of visible-light responsive Pt deposited TiO2 catalyst for solar hydrogen production.

Interannual Variability and Trends of Extratropical Ozone. Part 1; Northern Hemisphere

NASA Technical Reports Server (NTRS)

Yung, Yuk L.

2008-01-01

The authors apply principal component analysis (PCA) to the extratropical total column ozone from the combined merged ozone data product and the European Centre for Medium-Range Weather Forecasts assimilated ozone from January 1979 to August 2002. The interannual variability (IAV) of extratropical O-3 in the Northern Hemisphere (NH) is characterized by four main modes. Attributable to dominant dynamical effects, these four modes account for nearly 60% of the total ozone variance in the NH. The patterns of variability are distinctly different from those derived for total O-3 in the tropics. To relate the derived patterns of O-3 to atmospheric dynamics, similar decompositions are performed for the 30 100-Wa geopotential thickness. The results reveal intimate connections between the IAV of total ozone and the atmospheric circulation. The first two leading modes are nearly zonally symmetric and represent the connections to the annular modes and the quasi-biennial oscillation. The other two modes exhibit in-quadrature, wavenumber-1 structures that, when combined, describe the displacement of the polar vortices in response to planetary waves. In the NH, the extrema of these combined modes have preferred locations that suggest fixed topographical and land-sea thermal forcing of the involved planetary waves. Similar spatial patterns and trends in extratropical column ozone are simulated by the Goddard Earth Observation System chemistryclimate model (GEOS-CCM). The decreasing O-3 trend is captured in the first mode. The largest trend occurs at the North Pole, with values similar to-1 Dobson Unit (DU) yr(-1). There is almost no trend in tropical O-3. The trends derived from PCA are confirmed using a completely independent method, empirical mode decomposition, for zonally averaged O-3 data. The O-3 trend is also captured by mode 1 in the GEOS-CCM, but the decrease is substantially larger than that in the real atmosphere.

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

PubMed

Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

2015-01-01

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

Data-adaptive harmonic spectra and multilayer Stuart-Landau models

NASA Astrophysics Data System (ADS)

Chekroun, Mickaël D.; Kondrashov, Dmitri

2017-09-01

Harmonic decompositions of multivariate time series are considered for which we adopt an integral operator approach with periodic semigroup kernels. Spectral decomposition theorems are derived that cover the important cases of two-time statistics drawn from a mixing invariant measure. The corresponding eigenvalues can be grouped per Fourier frequency and are actually given, at each frequency, as the singular values of a cross-spectral matrix depending on the data. These eigenvalues obey, furthermore, a variational principle that allows us to define naturally a multidimensional power spectrum. The eigenmodes, as far as they are concerned, exhibit a data-adaptive character manifested in their phase which allows us in turn to define a multidimensional phase spectrum. The resulting data-adaptive harmonic (DAH) modes allow for reducing the data-driven modeling effort to elemental models stacked per frequency, only coupled at different frequencies by the same noise realization. In particular, the DAH decomposition extracts time-dependent coefficients stacked by Fourier frequency which can be efficiently modeled—provided the decay of temporal correlations is sufficiently well-resolved—within a class of multilayer stochastic models (MSMs) tailored here on stochastic Stuart-Landau oscillators. Applications to the Lorenz 96 model and to a stochastic heat equation driven by a space-time white noise are considered. In both cases, the DAH decomposition allows for an extraction of spatio-temporal modes revealing key features of the dynamics in the embedded phase space. The multilayer Stuart-Landau models (MSLMs) are shown to successfully model the typical patterns of the corresponding time-evolving fields, as well as their statistics of occurrence.

Hydrogen Peroxide - Material Compatibility Studied by Microcalorimetry

NASA Technical Reports Server (NTRS)

Homung, Steven D.; Davis, Dennis D.; Baker, David; Popp, Christopher G.

2003-01-01

Environmental and toxicity concerns with current hypergolic propellants have led to a renewed interest in propellant grade hydrogen peroxide (HP) for propellant applications. Storability and stability has always been an issue with HP. Contamination or contact of HP with metallic surfaces may cause decomposition, which can result in the evolution of heat and gas leading to increased pressure or thermal hazards. The NASA Johnson Space Center White Sands Test Facility has developed a technique to monitor the decompositions of hydrogen peroxide at temperatures ranging from 25 to 60 C. Using isothermal microcalorimetry we have measured decomposition rates at the picomole/s/g level showing the catalytic effects of materials of construction. In this paper we will present the results of testing with Class 1 and 2 materials in 90 percent hydrogen peroxide.

Thermochemical characterization of polymers for improved fire safety

NASA Technical Reports Server (NTRS)

Lerner, N. R.

1977-01-01

Apparatus has been constructed for studying the thermal decomposition of polymers as a function of temperature. Such data is needed to evaluate the toxic threat presented by polymeric materials under fire conditions such as the smoldering fire of the type that occurs in closed areas such as coat closets in which anaerobic decomposition of polymers occurs. The apparatus allows the products of thermal decomposition to be collected and analyzed by infrared spectrometry and mass spectrometry. Data obtained from dog hair, an aromatic polyamide, polyphenylene sulfide, and polybenzimidazole are presented. It was found that significant amounts of toxic gas were evolved from dog hair at temperatures as low as 250 C, while temperatures in excess of 500 C were necessary in order for the evolution of toxic gas from the aromatic polymers to become significant.

Comparative Genomics of Early-Diverging Mushroom-Forming Fungi Provides Insights into the Origins of Lignocellulose Decay Capabilities.

PubMed

Nagy, László G; Riley, Robert; Tritt, Andrew; Adam, Catherine; Daum, Chris; Floudas, Dimitrios; Sun, Hui; Yadav, Jagjit S; Pangilinan, Jasmyn; Larsson, Karl-Henrik; Matsuura, Kenji; Barry, Kerrie; Labutti, Kurt; Kuo, Rita; Ohm, Robin A; Bhattacharya, Sukanta S; Shirouzu, Takashi; Yoshinaga, Yuko; Martin, Francis M; Grigoriev, Igor V; Hibbett, David S

2016-04-01

Evolution of lignocellulose decomposition was one of the most ecologically important innovations in fungi. White-rot fungi in the Agaricomycetes (mushrooms and relatives) are the most effective microorganisms in degrading both cellulose and lignin components of woody plant cell walls (PCW). However, the precise evolutionary origins of lignocellulose decomposition are poorly understood, largely because certain early-diverging clades of Agaricomycetes and its sister group, the Dacrymycetes, have yet to be sampled, or have been undersampled, in comparative genomic studies. Here, we present new genome sequences of ten saprotrophic fungi, including members of the Dacrymycetes and early-diverging clades of Agaricomycetes (Cantharellales, Sebacinales, Auriculariales, and Trechisporales), which we use to refine the origins and evolutionary history of the enzymatic toolkit of lignocellulose decomposition. We reconstructed the origin of ligninolytic enzymes, focusing on class II peroxidases (AA2), as well as enzymes that attack crystalline cellulose. Despite previous reports of white rot appearing as early as the Dacrymycetes, our results suggest that white-rot fungi evolved later in the Agaricomycetes, with the first class II peroxidases reconstructed in the ancestor of the Auriculariales and residual Agaricomycetes. The exemplars of the most ancient clades of Agaricomycetes that we sampled all lack class II peroxidases, and are thus concluded to use a combination of plesiomorphic and derived PCW degrading enzymes that predate the evolution of white rot. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dynamic characterization of a damaged beam using empirical mode decomposition and Hilbert spectrum method

NASA Astrophysics Data System (ADS)

Chang, Chih-Chen; Poon, Chun-Wing

2004-07-01

Recently, the empirical mode decomposition (EMD) in combination with the Hilbert spectrum method has been proposed to identify the dynamic characteristics of linear structures. In this study, this EMD and Hilbert spectrum method is used to analyze the dynamic characteristics of a damaged reinforced concrete (RC) beam in the laboratory. The RC beam is 4m long with a cross section of 200mm X 250mm. The beam is sequentially subjected to a concentrated load of different magnitudes at the mid-span to produce different degrees of damage. An impact load is applied around the mid-span to excite the beam. Responses of the beam are recorded by four accelerometers. Results indicate that the EMD and Hilbert spectrum method can reveal the variation of the dynamic characteristics in the time domain. These results are also compared with those obtained using the Fourier analysis. In general, it is found that the two sets of results correlate quite well in terms of mode counts and frequency values. Some differences, however, can be seen in the damping values, which perhaps can be attributed to the linear assumption of the Fourier transform.

Steepest Ascent Low/Non-Low-Frequency Ratio in Empirical Mode Decomposition to Separate Deterministic and Stochastic Velocities From a Single Lagrangian Drifter

NASA Astrophysics Data System (ADS)

Chu, Peter C.

2018-03-01

SOund Fixing And Ranging (RAFOS) floats deployed by the Naval Postgraduate School (NPS) in the California Current system from 1992 to 2001 at depth between 150 and 600 m (http://www.oc.nps.edu/npsRAFOS/) are used to study 2-D turbulent characteristics. Each drifter trajectory is adaptively decomposed using the empirical mode decomposition (EMD) into a series of intrinsic mode functions (IMFs) with corresponding specific scale for each IMF. A new steepest ascent low/non-low-frequency ratio is proposed in this paper to separate a Lagrangian trajectory into low-frequency (nondiffusive, i.e., deterministic) and high-frequency (diffusive, i.e., stochastic) components. The 2-D turbulent (or called eddy) diffusion coefficients are calculated on the base of the classical turbulent diffusion with mixing length theory from stochastic component of a single drifter. Statistical characteristics of the calculated 2-D turbulence length scale, strength, and diffusion coefficients from the NPS RAFOS data are presented with the mean values (over the whole drifters) of the 2-D diffusion coefficients comparable to the commonly used diffusivity tensor method.

Pseudo-fault signal assisted EMD for fault detection and isolation in rotating machines

NASA Astrophysics Data System (ADS)

Singh, Dheeraj Sharan; Zhao, Qing

2016-12-01

This paper presents a novel data driven technique for the detection and isolation of faults, which generate impacts in a rotating equipment. The technique is built upon the principles of empirical mode decomposition (EMD), envelope analysis and pseudo-fault signal for fault separation. Firstly, the most dominant intrinsic mode function (IMF) is identified using EMD of a raw signal, which contains all the necessary information about the faults. The envelope of this IMF is often modulated with multiple vibration sources and noise. A second level decomposition is performed by applying pseudo-fault signal (PFS) assisted EMD on the envelope. A pseudo-fault signal is constructed based on the known fault characteristic frequency of the particular machine. The objective of using external (pseudo-fault) signal is to isolate different fault frequencies, present in the envelope . The pseudo-fault signal serves dual purposes: (i) it solves the mode mixing problem inherent in EMD, (ii) it isolates and quantifies a particular fault frequency component. The proposed technique is suitable for real-time implementation, which has also been validated on simulated fault and experimental data corresponding to a bearing and a gear-box set-up, respectively.

A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network

PubMed Central

Xu, Jing; Wang, Zhongbin; Tan, Chao; Si, Lei; Liu, Xinhua

2015-01-01

In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD) and Probabilistic Neural Network (PNN) is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF) components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method. PMID:26528985

Spatial Distribution of Resonance in the Velocity Field for Transonic Flow over a Rectangular Cavity

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

Beresh, Steven J.; Wagner, Justin L.; Casper, Katya M.

Pulse-burst particle image velocimetry (PIV) has been used to acquire time-resolved data at 37.5 kHz of the flow over a finite-width rectangular cavity at Mach 0.8. Power spectra of the PIV data reveal four resonance modes that match the frequencies detected simultaneously using high-frequency wall pressure sensors but whose magnitudes exhibit spatial dependence throughout the cavity. Spatio-temporal cross-correlations of velocity to pressure were calculated after bandpass filtering for specific resonance frequencies. Cross-correlation magnitudes express the distribution of resonance energy, revealing local maxima and minima at the edges of the shear layer attributable to wave interference between downstream- and upstream-propagating disturbances.more » Turbulence intensities were calculated using a triple decomposition and are greatest in the core of the shear layer for higher modes, where resonant energies ordinarily are lower. Most of the energy for the lowest mode lies in the recirculation region and results principally from turbulence rather than resonance. Together, the velocity-pressure cross-correlations and the triple-decomposition turbulence intensities explain the sources of energy identified in the spatial distributions of power spectra amplitudes.« less

Spatial Distribution of Resonance in the Velocity Field for Transonic Flow over a Rectangular Cavity

DOE PAGES

Beresh, Steven J.; Wagner, Justin L.; Casper, Katya M.; ...

2017-07-27

Pulse-burst particle image velocimetry (PIV) has been used to acquire time-resolved data at 37.5 kHz of the flow over a finite-width rectangular cavity at Mach 0.8. Power spectra of the PIV data reveal four resonance modes that match the frequencies detected simultaneously using high-frequency wall pressure sensors but whose magnitudes exhibit spatial dependence throughout the cavity. Spatio-temporal cross-correlations of velocity to pressure were calculated after bandpass filtering for specific resonance frequencies. Cross-correlation magnitudes express the distribution of resonance energy, revealing local maxima and minima at the edges of the shear layer attributable to wave interference between downstream- and upstream-propagating disturbances.more » Turbulence intensities were calculated using a triple decomposition and are greatest in the core of the shear layer for higher modes, where resonant energies ordinarily are lower. Most of the energy for the lowest mode lies in the recirculation region and results principally from turbulence rather than resonance. Together, the velocity-pressure cross-correlations and the triple-decomposition turbulence intensities explain the sources of energy identified in the spatial distributions of power spectra amplitudes.« less

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

NASA Astrophysics Data System (ADS)

E, Jianwei; Bao, Yanling; Ye, Jimin

2017-10-01

As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

Defects diagnosis in laser brazing using near-infrared signals based on empirical mode decomposition

NASA Astrophysics Data System (ADS)

Cheng, Liyong; Mi, Gaoyang; Li, Shuo; Wang, Chunming; Hu, Xiyuan

2018-03-01

Real-time monitoring of laser welding plays a very important role in the modern automated production and online defects diagnosis is necessary to be implemented. In this study, the status of laser brazing was monitored in real time using an infrared photoelectric sensor. Four kinds of braze seams (including healthy weld, unfilled weld, hole weld and rough surface weld) along with corresponding near-infrared signals were obtained. Further, a new method called Empirical Mode Decomposition (EMD) was proposed to analyze the near-infrared signals. The results showed that the EMD method had a good performance in eliminating the noise on the near-infrared signals. And then, the correlation coefficient was developed for selecting the Intrinsic Mode Function (IMF) more sensitive to the weld defects. A more accurate signal was reconstructed with the selected IMF components. Simultaneously, the spectrum of selected IMF components was solved using fast Fourier transform, and the frequency characteristics were clearly revealed. The frequency energy of different frequency bands was computed to diagnose the defects. There was a significant difference in four types of weld defects. This approach has been proved to be an effective and efficient method for monitoring laser brazing defects.

Dynamic mode decomposition of Fontan hemodynamics in an idealized total cavopulmonary connection

NASA Astrophysics Data System (ADS)

Delorme, Yann T.; Kerlo, Anna-Elodie M.; Anupindi, Kameswararao; Rodefeld, Mark D.; Frankel, Steven H.

2014-08-01

Univentricular heart disease is the leading cause of death from any birth defect in the first year of life. Typically, patients have to undergo three open heart surgical procedures within the first few years of their lives to eventually directly connect the superior and inferior vena cavae to the left and right pulmonary arteries forming the total cavopulmonary connection (TCPC). The end result is a weak circulation where the single working ventricle pumps oxygenated blood to the body and de-oxygenated blood flows passively through the TCPC into the lungs. The fluid dynamics of the TCPC junction involve confined impinging jets resulting in a highly unstable flow, significant mechanical energy dissipation and undesirable pressure loss. Understanding and predicting such flows is important for improving the surgical procedure and for the design of mechanical cavopulmonary assist devices. In this study, dynamic mode decomposition (DMD) is used to analyze previously obtained stereoscopic particle imaging velocimetry (SPIV) data and large eddy simulation (LES) results for an idealized TCPC. Analysis of the DMD modes from the SPIV and LES serves to both highlight the unsteady vortical dynamics and the qualitative agreement between measurements and simulations.

Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysis.

PubMed

Demerdash, Omar N A; Mitchell, Julie C

2012-07-01

Normal mode analysis has emerged as a useful technique for investigating protein motions on long time scales. This is largely due to the advent of coarse-graining techniques, particularly Hooke's Law-based potentials and the rotational-translational blocking (RTB) method for reducing the size of the force-constant matrix, the Hessian. Here we present a new method for domain decomposition for use in RTB that is based on hierarchical clustering of atomic density gradients, which we call Density-Cluster RTB (DCRTB). The method reduces the number of degrees of freedom by 85-90% compared with the standard blocking approaches. We compared the normal modes from DCRTB against standard RTB using 1-4 residues in sequence in a single block, with good agreement between the two methods. We also show that Density-Cluster RTB and standard RTB perform well in capturing the experimentally determined direction of conformational change. Significantly, we report superior correlation of DCRTB with B-factors compared with 1-4 residue per block RTB. Finally, we show significant reduction in computational cost for Density-Cluster RTB that is nearly 100-fold for many examples. Copyright © 2012 Wiley Periodicals, Inc.

Pathological speech signal analysis and classification using empirical mode decomposition.

PubMed

Kaleem, Muhammad; Ghoraani, Behnaz; Guergachi, Aziz; Krishnan, Sridhar

2013-07-01

Automated classification of normal and pathological speech signals can provide an objective and accurate mechanism for pathological speech diagnosis, and is an active area of research. A large part of this research is based on analysis of acoustic measures extracted from sustained vowels. However, sustained vowels do not reflect real-world attributes of voice as effectively as continuous speech, which can take into account important attributes of speech such as rapid voice onset and termination, changes in voice frequency and amplitude, and sudden discontinuities in speech. This paper presents a methodology based on empirical mode decomposition (EMD) for classification of continuous normal and pathological speech signals obtained from a well-known database. EMD is used to decompose randomly chosen portions of speech signals into intrinsic mode functions, which are then analyzed to extract meaningful temporal and spectral features, including true instantaneous features which can capture discriminative information in signals hidden at local time-scales. A total of six features are extracted, and a linear classifier is used with the feature vector to classify continuous speech portions obtained from a database consisting of 51 normal and 161 pathological speakers. A classification accuracy of 95.7 % is obtained, thus demonstrating the effectiveness of the methodology.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Q-3D: Imaging Spectroscopy of Quasar Hosts with JWST Analyzed with a Powerful New PSF Decomposition and Spectral Analysis Package

NASA Astrophysics Data System (ADS)

Wylezalek, Dominika; Veilleux, Sylvain; Zakamska, Nadia; Barrera-Ballesteros, J.; Luetzgendorf, N.; Nesvadba, N.; Rupke, D.; Sun, A.

2017-11-01

In the last few years, optical and near-IR IFU observations from the ground have revolutionized extragalactic astronomy. The unprecedented infrared sensitivity, spatial resolution, and spectral coverage of the JWST IFUs will ensure high demand from the community. For a wide range of extragalactic phenomena (e.g. quasars, starbursts, supernovae, gamma ray bursts, tidal disruption events) and beyond (e.g. nebulae, debris disks around bright stars), PSF contamination will be an issue when studying the underlying extended emission. We propose to provide the community with a PSF decomposition and spectral analysis package for high dynamic range JWST IFU observations allowing the user to create science-ready maps of relevant spectral features. Luminous quasars, with their bright central source (quasar) and extended emission (host galaxy), are excellent test cases for this software. Quasars are also of high scientific interest in their own right as they are widely considered to be the main driver in regulating massive galaxy growth. JWST will revolutionize our understanding of black hole-galaxy co-evolution by allowing us to probe the stellar, gas, and dust components of nearby and distant galaxies, spatially and spectrally. We propose to use the IFU capabilities of NIRSpec and MIRI to study the impact of three carefully selected luminous quasars on their hosts. Our program will provide (1) a scientific dataset of broad interest that will serve as a pathfinder for JWST science investigations in IFU mode and (2) a powerful new data analysis tool that will enable frontier science for a wide swath of astrophysical research.

Temporal and Spatial Evolution Characteristics of Disturbance Wave in a Hypersonic Boundary Layer due to Single-Frequency Entropy Disturbance

PubMed Central

Lv, Hongqing; Shi, Jianqiang

2014-01-01

By using a high-order accurate finite difference scheme, direct numerical simulation of hypersonic flow over an 8° half-wedge-angle blunt wedge under freestream single-frequency entropy disturbance is conducted; the generation and the temporal and spatial nonlinear evolution of boundary layer disturbance waves are investigated. Results show that, under the freestream single-frequency entropy disturbance, the entropy state of boundary layer is changed sharply and the disturbance waves within a certain frequency range are induced in the boundary layer. Furthermore, the amplitudes of disturbance waves in the period phase are larger than that in the response phase and ablation phase and the frequency range in the boundary layer in the period phase is narrower than that in these two phases. In addition, the mode competition, dominant mode transformation, and disturbance energy transfer exist among different modes both in temporal and in spatial evolution. The mode competition changes the characteristics of nonlinear evolution of the unstable waves in the boundary layer. The development of the most unstable mode along streamwise relies more on the motivation of disturbance waves in the upstream than that of other modes on this motivation. PMID:25143983

Temporal and spatial evolution characteristics of disturbance wave in a hypersonic boundary layer due to single-frequency entropy disturbance.

PubMed

Wang, Zhenqing; Tang, Xiaojun; Lv, Hongqing; Shi, Jianqiang

2014-01-01

By using a high-order accurate finite difference scheme, direct numerical simulation of hypersonic flow over an 8° half-wedge-angle blunt wedge under freestream single-frequency entropy disturbance is conducted; the generation and the temporal and spatial nonlinear evolution of boundary layer disturbance waves are investigated. Results show that, under the freestream single-frequency entropy disturbance, the entropy state of boundary layer is changed sharply and the disturbance waves within a certain frequency range are induced in the boundary layer. Furthermore, the amplitudes of disturbance waves in the period phase are larger than that in the response phase and ablation phase and the frequency range in the boundary layer in the period phase is narrower than that in these two phases. In addition, the mode competition, dominant mode transformation, and disturbance energy transfer exist among different modes both in temporal and in spatial evolution. The mode competition changes the characteristics of nonlinear evolution of the unstable waves in the boundary layer. The development of the most unstable mode along streamwise relies more on the motivation of disturbance waves in the upstream than that of other modes on this motivation.

Sampling considerations for modal analysis with damping

NASA Astrophysics Data System (ADS)

Park, Jae Young; Wakin, Michael B.; Gilbert, Anna C.

2015-03-01

Structural health monitoring (SHM) systems are critical for monitoring aging infrastructure (such as buildings or bridges) in a cost-effective manner. Wireless sensor networks that sample vibration data over time are particularly appealing for SHM applications due to their flexibility and low cost. However, in order to extend the battery life of wireless sensor nodes, it is essential to minimize the amount of vibration data these sensors must collect and transmit. In recent work, we have studied the performance of the Singular Value Decomposition (SVD) applied to the collection of data and provided new finite sample analysis characterizing conditions under which this simple technique{also known as the Proper Orthogonal Decomposition (POD){can correctly estimate the mode shapes of the structure. Specifically, we provided theoretical guarantees on the number and duration of samples required in order to estimate a structure's mode shapes to a desired level of accuracy. In that previous work, however, we considered simplified Multiple-Degree-Of-Freedom (MDOF) systems with no damping. In this paper we consider MDOF systems with proportional damping and show that, with sufficiently light damping, the POD can continue to provide accurate estimates of a structure's mode shapes. We support our discussion with new analytical insight and experimental demonstrations. In particular, we study the tradeoffs between the level of damping, the sampling rate and duration, and the accuracy to which the structure's mode shapes can be estimated.

Joint inversion of fundamental and higher mode Rayleigh waves

USGS Publications Warehouse

Luo, Y.-H.; Xia, J.-H.; Liu, J.-P.; Liu, Q.-S.

2008-01-01

In this paper, we analyze the characteristics of the phase velocity of fundamental and higher mode Rayleigh waves in a six-layer earth model. The results show that fundamental mode is more sensitive to the shear velocities of shallow layers (< 7 m) and concentrated in a very narrow band (around 18 Hz) while higher modes are more sensitive to the parameters of relatively deeper layers and distributed over a wider frequency band. These properties provide a foundation of using a multi-mode joint inversion to define S-wave velocity. Inversion results of both synthetic data and a real-world example demonstrate that joint inversion with the damped least squares method and the SVD (Singular Value Decomposition) technique to invert Rayleigh waves of fundamental and higher modes can effectively reduce the ambiguity and improve the accuracy of inverted S-wave velocities.

[Progress in Raman spectroscopic measurement of methane hydrate].

PubMed

Xu, Feng; Zhu, Li-hua; Wu, Qiang; Xu, Long-jun

2009-09-01

Complex thermodynamics and kinetics problems are involved in the methane hydrate formation and decomposition, and these problems are crucial to understanding the mechanisms of hydrate formation and hydrate decomposition. However, it was difficult to accurately obtain such information due to the difficulty of measurement since methane hydrate is only stable under low temperature and high pressure condition, and until recent years, methane hydrate has been measured in situ using Raman spectroscopy. Raman spectroscopy, a non-destructive and non-invasive technique, is used to study vibrational modes of molecules. Studies of methane hydrate using Raman spectroscopy have been developed over the last decade. The Raman spectra of CH4 in vapor phase and in hydrate phase are presented in this paper. The progress in the research on methane hydrate formation thermodynamics, formation kinetics, decomposition kinetics and decomposition mechanism based on Raman spectroscopic measurements in the laboratory and deep sea are reviewed. Formation thermodynamic studies, including in situ observation of formation condition of methane hydrate, analysis of structure, and determination of hydrate cage occupancy and hydration numbers by using Raman spectroscopy, are emphasized. In the aspect of formation kinetics, research on variation in hydrate cage amount and methane concentration in water during the growth of hydrate using Raman spectroscopy is also introduced. For the methane hydrate decomposition, the investigation associated with decomposition mechanism, the mutative law of cage occupancy ratio and the formulation of decomposition rate in porous media are described. The important aspects for future hydrate research based on Raman spectroscopy are discussed.

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

An operational modal analysis method in frequency and spatial domain

NASA Astrophysics Data System (ADS)

Wang, Tong; Zhang, Lingmi; Tamura, Yukio

2005-12-01

A frequency and spatial domain decomposition method (FSDD) for operational modal analysis (OMA) is presented in this paper, which is an extension of the complex mode indicator function (CMIF) method for experimental modal analysis (EMA). The theoretical background of the FSDD method is clarified. Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density (PSD) is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

NOx formation in apokamp-type atmospheric pressure plasma jets in air initiated by a pulse-repetitive discharge

NASA Astrophysics Data System (ADS)

Sosnin, Eduard A.; Didenko, Maria V.; Panarin, Victor A.; Skakun, Victor S.; Tarasenko, Victor F.; Liu, Dongping P.; Song, Ying

2018-04-01

The decomposition products of atmospheric pressure plasma of repetitive pulsed discharge in apokamp and corona modes were determined by optical and chemical methods. It is shown, that the decomposition products contain mainly nitrogen oxides NOx. A brief review of the plasma- and thermochemical reactions in the pulsed discharges was made. The review and experimental data allow us to explain the reactive oxygen species formation mechanisms in a potential discharge channel with apokamp. The possible applications of this plasma source for treatment of seeds of agricultural crops are discussed.

Dynamic Factorization in Large-Scale Optimization

DTIC Science & Technology

1993-03-12

variable production charges, distribution via multiple modes, taxes, duties and duty drawback, and inventory charges. See Harrison, Arntzen , and Brown...Decomposition," presented at CORS/TIMS/ORSA meeting, Vancouver. British Columbia, Canada, May. Harrison, T. P., Arntzen , B. C., and Brown, G. G. 1992

Micromechanical Sensor for the Spectral Decomposition of Acoustic Signals

DTIC Science & Technology

2012-02-01

8 Figure 2.2: Reverse Ballistic Air Gun ................................................................................. 9 Figure 2.3: A MEMS...Schematic of the Sensor including Sensor-to-Sensor Parasitic .................... 177 Figure 5.9: Schematic of Laser Machined Sensor...178 Figure 5.10: Laser Machined Sensor Mode 1

Reflection of Lamb waves obliquely incident on the free edge of a plate.

PubMed

Santhanam, Sridhar; Demirli, Ramazan

2013-01-01

The reflection of obliquely incident symmetric and anti-symmetric Lamb wave modes at the edge of a plate is studied. Both in-plane and Shear-Horizontal (SH) reflected wave modes are spawned by an obliquely incident in-plane Lamb wave mode. Energy reflection coefficients are calculated for the reflected wave modes as a function of frequency and angle of incidence. This is done by using the method of orthogonal mode decomposition and by enforcing traction free conditions at the plate edge using the method of collocation. A PZT sensor network, affixed to an Aluminum plate, is used to experimentally verify the predictions of the analysis. Experimental results provide support for the analytically determined results. Copyright © 2012 Elsevier B.V. All rights reserved.

On the effects of higher convection modes on the thermal evolution of small planetary bodies

NASA Technical Reports Server (NTRS)

Arkani-Hamed, J.

1979-01-01

The effects of higher modes of convection on the thermal evolution of a small planetary body is investigated. Three sets of models are designed to specify an initially cold and differentiated, an initially hot and differentiated, and an initially cold and undifferentiated Moon-type body. The strong temperature dependence of viscosity enhances the thickening of lithosphere so that a lithosphere of about 400 km thickness is developed within the first billion years of the evolution of a Moon-type body. The thermally isolating effect of such a lithosphere hampers the heat flux out of the body and increases the temperature of the interior, causing the solid-state convection to occur with high velocity so that even the lower modes of convection can maintain an adiabatic temperature gradient there. It is demonstrated that the effect of solid-state convection on the thermal evolution of the models may be adequately determined by a combination of convection modes up to the third or the fourth order harmonic. The inclusion of higher modes does not affect the results significantly.

Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data.

PubMed

Vera, J Fernando; Macías, Rodrigo

2017-06-01

One of the main problems in cluster analysis is that of determining the number of groups in the data. In general, the approach taken depends on the cluster method used. For K-means, some of the most widely employed criteria are formulated in terms of the decomposition of the total point scatter, regarding a two-mode data set of N points in p dimensions, which are optimally arranged into K classes. This paper addresses the formulation of criteria to determine the number of clusters, in the general situation in which the available information for clustering is a one-mode [Formula: see text] dissimilarity matrix describing the objects. In this framework, p and the coordinates of points are usually unknown, and the application of criteria originally formulated for two-mode data sets is dependent on their possible reformulation in the one-mode situation. The decomposition of the variability of the clustered objects is proposed in terms of the corresponding block-shaped partition of the dissimilarity matrix. Within-block and between-block dispersion values for the partitioned dissimilarity matrix are derived, and variance-based criteria are subsequently formulated in order to determine the number of groups in the data. A Monte Carlo experiment was carried out to study the performance of the proposed criteria. For simulated clustered points in p dimensions, greater efficiency in recovering the number of clusters is obtained when the criteria are calculated from the related Euclidean distances instead of the known two-mode data set, in general, for unequal-sized clusters and for low dimensionality situations. For simulated dissimilarity data sets, the proposed criteria always outperform the results obtained when these criteria are calculated from their original formulation, using dissimilarities instead of distances.

Three distinct modes of intron dynamics in the evolution of eukaryotes.

PubMed

Carmel, Liran; Wolf, Yuri I; Rogozin, Igor B; Koonin, Eugene V

2007-07-01

Several contrasting scenarios have been proposed for the origin and evolution of spliceosomal introns, a hallmark of eukaryotic genes. A comprehensive probabilistic model to obtain a definitive reconstruction of intron evolution was developed and applied to 391 sets of conserved genes from 19 eukaryotic species. It is inferred that a relatively high intron density was reached early, i.e., the last common ancestor of eukaryotes contained >2.15 introns/kilobase, and the last common ancestor of multicellular life forms harbored approximately 3.4 introns/kilobase, a greater intron density than in most of the extant fungi and in some animals. The rates of intron gain and intron loss appear to have been dropping during the last approximately 1.3 billion years, with the decline in the gain rate being much steeper. Eukaryotic lineages exhibit three distinct modes of evolution of the intron-exon structure. The primary, balanced mode, apparently, operates in all lineages. In this mode, intron gain and loss are strongly and positively correlated, in contrast to previous reports on inverse correlation between these processes. The second mode involves an elevated rate of intron loss and is prevalent in several lineages, such as fungi and insects. The third mode, characterized by elevated rate of intron gain, is seen only in deep branches of the tree, indicating that bursts of intron invasion occurred at key points in eukaryotic evolution, such as the origin of animals. Intron dynamics could depend on multiple mechanisms, and in the balanced mode, gain and loss of introns might share common mechanistic features.

Mars mission effects on Space Station evolution

NASA Technical Reports Server (NTRS)

Askins, Barbara S.; Cook, Stephen G.

1989-01-01

The permanently manned Space Station scheduled to be operational in low earth by the mid 1990's, will provide accommodations for science, applications, technology, and commercial users, and will develop enabling capabilities for future missions. A major aspect of the baseline Space Station design is that provisions for evolution to greater capabilities are included in the systems and subsystems designs. User requirements are the basis for conceptual evolution modes or infrastructure to support the paths. Four such modes are discussed in support of a Human to Mars mission, along with some of the near term actions protecting the future of supporting Mars missions on the Space Station. The evolution modes include crew and payload transfer, storage, checkout, assembly, maintenance, repair, and fueling.

Formation of oligomeric alkenylperoxides during the oxidation of unsaturated fatty acids: an electrospray ionization tandem mass spectrometry study.

PubMed

Villaverde, Juan José; Santos, Sónia A O; Maciel, Elisabete; Simões, Mário M Q; Pascoal Neto, Carlos; Domingues, M Rosário M; Silvestre, Armando J D

2012-02-01

This study reports the identification of oligomeric alkenylperoxides by electrospray ionization mass spectrometry (ESI-MS) and tandem mass spectrometry (ESI-MS(2)), during the oxidation of oleic, linoleic and linolenic acids with Fenton's (Fe(2+)/H(2)O(2)) and Fe(2+)/O(2) systems. The reactions were followed by ferrous oxidation-xylenol orange method together with GC-MS and GC-FID, allowing to observe that both oxidation systems are different in terms of hydroperoxide evolution, probably due to the presence of different intermediate reactive species: perferryl ion and OH(·) radical responsible for the decomposition of lipid hydroperoxides and formation of new compounds. The analysis of ESI-MS in the negative mode, obtained after oxidation of each fatty acid, confirmed the presence of the monomeric oxidation products together with other compounds at high mass region above m/z 550. These new ions were attributed to oligomeric structures, identified by the fragmentation pathways observed in the tandem mass spectra. Copyright © 2012 John Wiley & Sons, Ltd.

High-Speed Boundary-Layer Transition: Study of Stationary Crossflow Using Spectral Analysis

NASA Astrophysics Data System (ADS)

McGuire, Patrick Joseph

Crossflow instability is primary cause of boundary-layer transition on swept wings used in high-speed applications. Delaying the downstream location of transition would drastically reduce the viscous drag over the wing surface, and subsequently improves the overall aircraft efficiency. By studying the development of instability growth rates and how they interact with the surroundings, researchers can control the crossflow transition location. Experiments on the 35° swept-wing model were performed in the NASA Langley 20-Inch Supersonic Wind Tunnel with Mach 2.0 flow conditions and 20 μm tall discrete roughness elements (DRE) with varying spacing placed along the leading edge. Fluorene was used as the sublimating chemical in the surface flow visualization technique to observe the transition front and stationary crossflow vortex patterns in the laminar flow region. Spatial spectral decomposition was completed on high-resolution images of sublimating chemical runs using a newly developed image processing technique. Streamwise evolution of the vortex track wavelengths within the laminar boundary-layer region was observed. The spectral information was averaged to produce dominant modes present throughout the laminar region.

Swirl ratio effects on tornado-like vortices

NASA Astrophysics Data System (ADS)

Hashemi-Tari, Pooyan; Gurka, Roi; Hangen, Horia

2007-11-01

The effect of swirl ratio on the flow field for a tornado-like vortex simulator (TVS) is investigated. Different swirl ratios are obtained by changing the geometry and tangential velocity which determine the vortex evolution. Flow visualizations, surface pressure and Particle Image Velocimetry (PIV) measurements are performed in a small TVS for swirl ratios S between 0 and 1. The PIV data was acquired for two orthogonal planes: normal and parallel to the solid boundary at several height locations. The ratio between the angular momentum and the radial momentum which characterize the swirl ratio is investigated. Statistical analysis to the turbulent field is performed by mean and rms profiles of the velocity, stresses and vorticity are presented. A Proper Orthogonal Decomposition (POD) is performed on the vorticity field. The results are used to: (i) provide a relation between these 3 sets of qualitative and quantitative measurements and the swirl ratio in an attempt to relate the fluid dynamics parameters to the forensic, Fujita scale, and (ii) understand the spatio-temporal distribution of the most energetic POD modes in a tornado-like vortex.

A reconstruction of sexual modes throughout animal evolution.

PubMed

Sasson, Daniel A; Ryan, Joseph F

2017-12-06

Although most extant animals have separate sexes, simultaneous hermaphrodites can be found in lineages throughout the animal kingdom. However, the sexual modes of key ancestral nodes including the last common ancestor (LCA) of all animals remain unclear. Without these data, it is difficult to infer the reproductive-state transitions that occurred early in animal evolution, and thus a broad understanding of the evolution of animal reproduction remains elusive. In this study, we use a composite phylogeny from four previously published studies, two alternative topologies (ctenophores or sponges as sister to the rest of animals), and multiple phylogenetic approaches to conduct the most extensive analysis to date of the evolution of animal sexual modes. Our analyses clarify the sexual mode of many ancestral animal nodes and allow for sound inferences of modal transitions that have occurred in animal history. Our results also indicate that the transition from separate sexes to hermaphroditism has been more common in animal history than the reverse. These results provide the most complete view of the evolution of animal sexual modes to date and provide a framework for future inquiries into the correlation of these transitions with genes, behaviors, and physiology. These results also suggest that mutations promoting hermaphroditism have historically been more likely to invade gonochoristic populations than vice versa.

The evolution of reproductive diversity in Afrobatrachia: A phylogenetic comparative analysis of an extensive radiation of African frogs

PubMed Central

Portik, Daniel M.; Blackburn, David C.

2016-01-01

The reproductive modes of anurans (frogs and toads) are the most diverse of terrestrial vertebrates, and a major challenge is identifying selective factors that promote the evolution or retention of reproductive modes across clades. Terrestrialized anuran breeding strategies have evolved repeatedly from the plesiomorphic fully aquatic reproductive mode, a process thought to occur through intermediate reproductive stages. Several selective forces have been proposed for the evolution of terrestrialized reproductive traits, but factors such as water systems and co‐evolution with ecomorphologies have not been investigated. We examined these topics in a comparative phylogenetic framework using Afrobatrachian frogs, an ecologically and reproductively diverse clade representing more than half of the total frog diversity found in Africa (∼400 species). We infer direct development has evolved twice independently from terrestrialized reproductive modes involving subterranean or terrestrial oviposition, supporting evolution through intermediate stages. We also detect associations between specific ecomorphologies and oviposition sites, and demonstrate arboreal species exhibit an overall shift toward using lentic water systems for breeding. These results indicate that changes in microhabitat use associated with ecomorphology, which allow access to novel sites for reproductive behavior, oviposition, or larval development, may also promote reproductive mode diversity in anurans. PMID:27402182

Nonlinear Wave Propagation

DTIC Science & Technology

2009-02-12

describes the mode- locking and dynamics of solitons . A characteristic of short pulse lasers is the carrier-envelope phase (CEP) slip which is the change in...and evolution of pulses in mode- locked lasers that are operating in the soliton regime. To describe our research in more detail, we fix typical...solutions with mode- locking evolution. Otherwise the solitons are found to be unstable; either dispersing to radiation or evolving into nonlocalized

Evolution of the bi-stable wake of a square-back automotive shape

NASA Astrophysics Data System (ADS)

Pavia, Giancarlo; Passmore, Martin; Sardu, Costantino

2018-01-01

Square-back shapes are popular in the automotive market for their high level of practicality. These geometries, however, are usually characterised by high drag and their wake dynamics present aspects, such as the coexistence of a long-time bi-stable behaviour and short-time global fluctuating modes that are not fully understood. In the present paper, the unsteady behaviour of the wake of a generic square-back car geometry is characterised with an emphasis on identifying the causal relationship between the different dynamic modes in the wake. The study is experimental, consisting of balance, pressure, and stereoscopic PIV measurements. Applying wavelet and cross-wavelet transforms to the balance data, a quasi-steady correlation is demonstrated between the forces and bi-stable modes. This is investigated by applying proper orthogonal decomposition to the pressure and velocity data sets and a new structure is proposed for each bi-stable state, consisting of a hairpin vortex that originates from one of the two model's vertical trailing edges and bends towards the opposite side as it merges into a single streamwise vortex downstream. The wake pumping motion is also identified and for the first time linked with the motion of the bi-stable vortical structure in the streamwise direction, resulting in out-of-phase pressure variations between the two vertical halves of the model base. A phase-averaged low-order model is also proposed that provides a comprehensive description of the mechanisms of the switch between the bi-stable states. It is demonstrated that, during the switch, the wake becomes laterally symmetric and, at this point, the level of interaction between the recirculating structures and the base reaches a minimum, yielding, for this geometry, a 7% reduction of the base drag compared to the time-averaged result.

THE DYNAMICS OF THE SOLAR MAGNETIC FIELD: POLARITY REVERSALS, BUTTERFLY DIAGRAM, AND QUASI-BIENNIAL OSCILLATIONS

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

Vecchio, A.; Meduri, D.; Carbone, V.

2012-04-10

The spatio-temporal dynamics of the solar magnetic field has been investigated by using NSO/Kitt Peak magnetic synoptic maps covering the period 1976 August-2003 September. The field radial component, for each heliographic latitude, has been decomposed in intrinsic mode functions through the Empirical Mode Decomposition in order to investigate the time evolution of the various characteristic oscillating modes at different latitudes. The same technique has also been applied on synoptic maps of the meridional and east-west components, which were derived from the observed line-of-sight projection of the field by using the differential rotation. Results obtained for the {approx}22 yr cycle, relatedmore » to the polarity inversions of the large-scale dipolar field, show an antisymmetric behavior with respect to the equator in all the field components and a marked poleward flux migration in the radial and meridional components (from about -35 Degree-Sign and +35 Degree-Sign in the southern and northern hemispheres, respectively). The quasi-biennial oscillations (QBOs) are also identified as a fundamental timescale of variability of the magnetic field and associated with poleward magnetic flux migration from low latitudes around the maximum and descending phase of the solar cycle. Moreover, signs of an equatorward drift, at a {approx}2 yr rate, seem to appear in the radial and toroidal components. Hence, the QBO patterns suggest a link to a dynamo action. Finally, the high-frequency component of the magnetic field, at timescales less than 1 yr, provides the most energetic contribution and it is associated with the outbreaks of the bipolar regions on the solar surface.« less

Parameterizing Coefficients of a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

A method of parameterizing the coefficients of a dynamical system based of a proper orthogonal decomposition (POD) representing the flow dynamics of a viscous fluid has been introduced. (A brief description of POD is presented in the immediately preceding article.) The present parameterization method is intended to enable construction of the dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers. The need for this or a similar method arises as follows: A procedure that includes direct numerical simulation followed by POD, followed by Galerkin projection to a dynamical system has been proven to enable representation of flow dynamics by a low-dimensional model at the Reynolds number of the simulation. However, a more difficult task is to obtain models that are valid over a range of Reynolds numbers. Extrapolation of low-dimensional models by use of straightforward Reynolds-number-based parameter continuation has proven to be inadequate for successful prediction of flows. A key part of the problem of constructing a dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers is the problem of understanding and providing for the variation of the coefficients of the dynamical system with the Reynolds number. Prior methods do not enable capture of temporal dynamics over ranges of Reynolds numbers in low-dimensional models, and are not even satisfactory when large numbers of modes are used. The basic idea of the present method is to solve the problem through a suitable parameterization of the coefficients of the dynamical system. The parameterization computations involve utilization of the transfer of kinetic energy between modes as a function of Reynolds number. The thus-parameterized dynamical system accurately predicts the flow dynamics and is applicable to a range of flow problems in the dynamical regime around the Hopf bifurcation. Parameter-continuation software can be used on the parameterized dynamical system to derive a bifurcation diagram that accurately predicts the temporal flow behavior.

Empirical Investigation of Critical Transitions in Paleoclimate

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.

2016-12-01

In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1

Modal Identification of Tsing MA Bridge by Using Improved Eigensystem Realization Algorithm

NASA Astrophysics Data System (ADS)

QIN, Q.; LI, H. B.; QIAN, L. Z.; LAU, C.-K.

2001-10-01

This paper presents the results of research work on modal identification of Tsing Ma bridge ambient testing data by using an improved eigensystem realization algorithm. The testing was carried out before the bridge was open to traffic and after the completion of surfacing. Without traffic load, ambient excitations were much less intensive, and the bridge responses to such ambient excitation were also less intensive. Consequently, the bridge responses were significantly influenced by the random movement of heavy construction vehicles on the deck. To cut off noises in the testing data and make the ambient signals more stationary, the Chebyshev digital filter was used instead of the digital filter with a Hanning window. Random decrement (RD) functions were built to convert the ambient responses to free vibrations. An improved eigensystem realization algorithm was employed to improve the accuracy and the efficiency of modal identification. It uses cross-correlation functions ofRD functions to form the Hankel matrix instead of RD functions themselves and uses eigenvalue decomposition instead of singular value decomposition. The data for response accelerations were acquired group by group because of limited number of high-quality accelerometers and channels of data loggers available. The modes were identified group by group and then assembled by using response accelerations acquired at reference points to form modes of the complete bridge. Seventy-nine modes of the Tsing Ma bridge were identified, including five complex modes formed in accordance with unevenly distributed damping in the bridge. The identified modes in time domain were then compared with those identified in frequency domain and finite element analytical results.

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

Nonlinear evolution of Mack modes in a hypersonic boundary layer

NASA Astrophysics Data System (ADS)

Chokani, Ndaona

2005-01-01

In hypersonic boundary layer flows the nonlinear disturbance evolution occurs relatively slowly over a very long length scale and has a profound effect on boundary layer transition. In the case of low-level freestream disturbances and negligible surface roughness, the transition is due to the modal growth of exponentially growing Mack modes that are destabilized by wall cooling. Cross-bicoherence measurements, derived from hot-wire data acquired in a quiet hypersonic tunnel, are used to identify and quantify phase-locked, quadratic sum and difference interactions involving the Mack modes. In the early stages of the nonlinear disturbance evolution, cross-bicoherence measurements indicate that the energy exchange between the Mack mode and the mean flow first occurs to broaden the sidebands; this is immediately followed by a sum interaction of the Mack mode to generate the first harmonic. In the next stages of the nonlinear disturbance evolution, there is a difference interaction of the first harmonic, which is also thought to contribute to the mean flow distortion. This difference interaction, in the latter stages, is also accompanied by a difference interaction between Mack mode and first harmonic, and a sum interaction, which forces the second harmonic. Analysis using the digital complex demodulation technique, shows that the low-frequency, phase-locked interaction that is identified in the cross bicoherence when the Mack mode and first harmonic have large amplitudes, arises due to the amplitude modulation of Mack mode and first harmonic.

Dynamic Factorization in Large-Scale Optimization

DTIC Science & Technology

1994-01-01

and variable production charges, distribution via multiple modes, taxes, duties and duty draw- back, and inventory charges. See Harrison, Arntzen and...34 Capital allocation and project selection via decomposition:’ presented at CORS/TIMS/ORSA meeting. Vancouver. Be ( 1989). T.P. Harrison. B.C. Arntzen and

Empirical mode decomposition of the ECG signal for noise removal

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Alam, Mohammad

2011-04-01

Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.

A structural design decomposition method utilizing substructuring

NASA Technical Reports Server (NTRS)

Scotti, Stephen J.

1994-01-01

A new method of design decomposition for structural analysis and optimization is described. For this method, the structure is divided into substructures where each substructure has its structural response described by a structural-response subproblem, and its structural sizing determined from a structural-sizing subproblem. The structural responses of substructures that have rigid body modes when separated from the remainder of the structure are further decomposed into displacements that have no rigid body components, and a set of rigid body modes. The structural-response subproblems are linked together through forces determined within a structural-sizing coordination subproblem which also determines the magnitude of any rigid body displacements. Structural-sizing subproblems having constraints local to the substructures are linked together through penalty terms that are determined by a structural-sizing coordination subproblem. All the substructure structural-response subproblems are totally decoupled from each other, as are all the substructure structural-sizing subproblems, thus there is significant potential for use of parallel solution methods for these subproblems.

Turbulent Statistics From Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2013-01-01

Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.

Turbulent Statistics from Time-Resolved PIV Measurements of a Jet Using Empirical Mode Decomposition

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2012-01-01

Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.

Detection of the ice assertion on aircraft using empirical mode decomposition enhanced by multi-objective optimization

NASA Astrophysics Data System (ADS)

Bagherzadeh, Seyed Amin; Asadi, Davood

2017-05-01

In search of a precise method for analyzing nonlinear and non-stationary flight data of an aircraft in the icing condition, an Empirical Mode Decomposition (EMD) algorithm enhanced by multi-objective optimization is introduced. In the proposed method, dissimilar IMF definitions are considered by the Genetic Algorithm (GA) in order to find the best decision parameters of the signal trend. To resolve disadvantages of the classical algorithm caused by the envelope concept, the signal trend is estimated directly in the proposed method. Furthermore, in order to simplify the performance and understanding of the EMD algorithm, the proposed method obviates the need for a repeated sifting process. The proposed enhanced EMD algorithm is verified by some benchmark signals. Afterwards, the enhanced algorithm is applied to simulated flight data in the icing condition in order to detect the ice assertion on the aircraft. The results demonstrate the effectiveness of the proposed EMD algorithm in aircraft ice detection by providing a figure of merit for the icing severity.

Fluorescence background removal method for biological Raman spectroscopy based on empirical mode decomposition.

PubMed

Leon-Bejarano, Maritza; Dorantes-Mendez, Guadalupe; Ramirez-Elias, Miguel; Mendez, Martin O; Alba, Alfonso; Rodriguez-Leyva, Ildefonso; Jimenez, M

2016-08-01

Raman spectroscopy of biological tissue presents fluorescence background, an undesirable effect that generates false Raman intensities. This paper proposes the application of the Empirical Mode Decomposition (EMD) method to baseline correction. EMD is a suitable approach since it is an adaptive signal processing method for nonlinear and non-stationary signal analysis that does not require parameters selection such as polynomial methods. EMD performance was assessed through synthetic Raman spectra with different signal to noise ratio (SNR). The correlation coefficient between synthetic Raman spectra and the recovered one after EMD denoising was higher than 0.92. Additionally, twenty Raman spectra from skin were used to evaluate EMD performance and the results were compared with Vancouver Raman algorithm (VRA). The comparison resulted in a mean square error (MSE) of 0.001554. High correlation coefficient using synthetic spectra and low MSE in the comparison between EMD and VRA suggest that EMD could be an effective method to remove fluorescence background in biological Raman spectra.

An integrated condition-monitoring method for a milling process using reduced decomposition features

NASA Astrophysics Data System (ADS)

Liu, Jie; Wu, Bo; Wang, Yan; Hu, Youmin

2017-08-01

Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification.

A New Strategy for ECG Baseline Wander Elimination Using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Shahbakhti, Mohammad; Bagheri, Hamed; Shekarchi, Babak; Mohammadi, Somayeh; Naji, Mohsen

2016-06-01

Electrocardiogram (ECG) signals might be affected by various artifacts and noises that have biological and external sources. Baseline wander (BW) is a low-frequency artifact that may be caused by breathing, body movements and loose sensor contact. In this paper, a novel method based on empirical mode decomposition (EMD) for removal of baseline noise from ECG is presented. When compared to other EMD-based methods, the novelty of this research is to reach the optimized number of decomposed levels for ECG BW de-noising using mean power frequency (MPF), while the reduction of processing time is considered. To evaluate the performance of the proposed method, a fifth-order Butterworth high pass filtering (BHPF) with cut-off frequency at 0.5Hz and wavelet approach are applied. Three performance indices, signal-to-noise ratio (SNR), mean square error (MSE) and correlation coefficient (CC), between pure and filtered signals have been utilized for qualification of presented techniques. Results suggest that the EMD-based method outperforms the other filtering method.

Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB.

PubMed

Li, Qinwei; Xiao, Xia; Wang, Liang; Song, Hang; Kono, Hayato; Liu, Peifang; Lu, Hong; Kikkawa, Takamaro

2015-10-01

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.

Two-step relaxation mode analysis with multiple evolution times applied to all-atom molecular dynamics protein simulation.

PubMed

Karasawa, N; Mitsutake, A; Takano, H

2017-12-01

Proteins implement their functionalities when folded into specific three-dimensional structures, and their functions are related to the protein structures and dynamics. Previously, we applied a relaxation mode analysis (RMA) method to protein systems; this method approximately estimates the slow relaxation modes and times via simulation and enables investigation of the dynamic properties underlying the protein structural fluctuations. Recently, two-step RMA with multiple evolution times has been proposed and applied to a slightly complex homopolymer system, i.e., a single [n]polycatenane. This method can be applied to more complex heteropolymer systems, i.e., protein systems, to estimate the relaxation modes and times more accurately. In two-step RMA, we first perform RMA and obtain rough estimates of the relaxation modes and times. Then, we apply RMA with multiple evolution times to a small number of the slowest relaxation modes obtained in the previous calculation. Herein, we apply this method to the results of principal component analysis (PCA). First, PCA is applied to a 2-μs molecular dynamics simulation of hen egg-white lysozyme in aqueous solution. Then, the two-step RMA method with multiple evolution times is applied to the obtained principal components. The slow relaxation modes and corresponding relaxation times for the principal components are much improved by the second RMA.

Two-step relaxation mode analysis with multiple evolution times applied to all-atom molecular dynamics protein simulation

NASA Astrophysics Data System (ADS)

Karasawa, N.; Mitsutake, A.; Takano, H.

2017-12-01

Proteins implement their functionalities when folded into specific three-dimensional structures, and their functions are related to the protein structures and dynamics. Previously, we applied a relaxation mode analysis (RMA) method to protein systems; this method approximately estimates the slow relaxation modes and times via simulation and enables investigation of the dynamic properties underlying the protein structural fluctuations. Recently, two-step RMA with multiple evolution times has been proposed and applied to a slightly complex homopolymer system, i.e., a single [n ] polycatenane. This method can be applied to more complex heteropolymer systems, i.e., protein systems, to estimate the relaxation modes and times more accurately. In two-step RMA, we first perform RMA and obtain rough estimates of the relaxation modes and times. Then, we apply RMA with multiple evolution times to a small number of the slowest relaxation modes obtained in the previous calculation. Herein, we apply this method to the results of principal component analysis (PCA). First, PCA is applied to a 2-μ s molecular dynamics simulation of hen egg-white lysozyme in aqueous solution. Then, the two-step RMA method with multiple evolution times is applied to the obtained principal components. The slow relaxation modes and corresponding relaxation times for the principal components are much improved by the second RMA.

Improving EMG based classification of basic hand movements using EMD.

PubMed

Sapsanis, Christos; Georgoulas, George; Tzes, Anthony; Lymberopoulos, Dimitrios

2013-01-01

This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

Ghost microscope imaging system from the perspective of coherent-mode representation

NASA Astrophysics Data System (ADS)

Shen, Qian; Bai, Yanfeng; Shi, Xiaohui; Nan, Suqin; Qu, Lijie; Li, Hengxing; Fu, Xiquan

2018-03-01

The coherent-mode representation theory of partially coherent fields is firstly used to analyze a two-arm ghost microscope imaging system. It is shown that imaging quality of the generated images depend crucially on the distribution of the decomposition coefficients of the object imaged when the light source is fixed. This theory is also suitable for demonstrating the effects from the distance the object is moved away from the original plane on imaging quality. Our results are verified theoretically and experimentally.

General Monte Carlo reliability simulation code including common mode failures and HARP fault/error-handling

NASA Technical Reports Server (NTRS)

Platt, M. E.; Lewis, E. E.; Boehm, F.

1991-01-01

A Monte Carlo Fortran computer program was developed that uses two variance reduction techniques for computing system reliability applicable to solving very large highly reliable fault-tolerant systems. The program is consistent with the hybrid automated reliability predictor (HARP) code which employs behavioral decomposition and complex fault-error handling models. This new capability is called MC-HARP which efficiently solves reliability models with non-constant failures rates (Weibull). Common mode failure modeling is also a specialty.

Analyzing nonstationary financial time series via hilbert-huang transform (HHT)

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2008-01-01

An apparatus, computer program product and method of analyzing non-stationary time varying phenomena. A representation of a non-stationary time varying phenomenon is recursively sifted using Empirical Mode Decomposition (EMD) to extract intrinsic mode functions (IMFs). The representation is filtered to extract intrinsic trends by combining a number of IMFs. The intrinsic trend is inherent in the data and identifies an IMF indicating the variability of the phenomena. The trend also may be used to detrend the data.

Effects of resonant magnetic perturbation on the triggering and the evolution of double-tearing mode

NASA Astrophysics Data System (ADS)

Wang, L.; Lin, W. B.; Wang, X. Q.

2018-02-01

The effects of resonant magnetic perturbation on the triggering and the evolution of the double-tearing mode are investigated by using nonlinear magnetohydrodynamics simulations in a slab geometry. It is found that the double-tearing mode can be destabilized by boundary magnetic perturbation. Moreover, the mode has three typical development stages before it reaches saturation: the linear stable stage, the linear-growth stage, and the exponential-growth stage. The onset and growth of the double-tearing mode significantly depend on the boundary magnetic perturbations, particularly in the early development stage of the mode. The influences of the magnetic perturbation amplitude on the mode for different separations of the two rational surfaces are also discussed.

Dynamic Data-Driven Reduced-Order Models of Macroscale Quantities for the Prediction of Equilibrium System State for Multiphase Porous Medium Systems

NASA Astrophysics Data System (ADS)

Talbot, C.; McClure, J. E.; Armstrong, R. T.; Mostaghimi, P.; Hu, Y.; Miller, C. T.

2017-12-01

Microscale simulation of multiphase flow in realistic, highly-resolved porous medium systems of a sufficient size to support macroscale evaluation is computationally demanding. Such approaches can, however, reveal the dynamic, steady, and equilibrium states of a system. We evaluate methods to utilize dynamic data to reduce the cost associated with modeling a steady or equilibrium state. We construct data-driven models using extensions to dynamic mode decomposition (DMD) and its connections to Koopman Operator Theory. DMD and its variants comprise a class of equation-free methods for dimensionality reduction of time-dependent nonlinear dynamical systems. DMD furnishes an explicit reduced representation of system states in terms of spatiotemporally varying modes with time-dependent oscillation frequencies and amplitudes. We use DMD to predict the steady and equilibrium macroscale state of a realistic two-fluid porous medium system imaged using micro-computed tomography (µCT) and simulated using the lattice Boltzmann method (LBM). We apply Koopman DMD to direct numerical simulation data resulting from simulations of multiphase fluid flow through a 1440x1440x4320 section of a full 1600x1600x5280 realization of imaged sandstone. We determine a representative set of system observables via dimensionality reduction techniques including linear and kernel principal component analysis. We demonstrate how this subset of macroscale quantities furnishes a representation of the time-evolution of the system in terms of dynamic modes, and discuss the selection of a subset of DMD modes yielding the optimal reduced model, as well as the time-dependence of the error in the predicted equilibrium value of each macroscale quantity. Finally, we describe how the above procedure, modified to incorporate methods from compressed sensing and random projection techniques, may be used in an online fashion to facilitate adaptive time-stepping and parsimonious storage of system states over time.

Partial differential equation transform — Variational formulation and Fourier analysis

PubMed Central

Wang, Yang; Wei, Guo-Wei; Yang, Siyang

2011-01-01

Nonlinear partial differential equation (PDE) models are established approaches for image/signal processing, data analysis and surface construction. Most previous geometric PDEs are utilized as low-pass filters which give rise to image trend information. In an earlier work, we introduced mode decomposition evolution equations (MoDEEs), which behave like high-pass filters and are able to systematically provide intrinsic mode functions (IMFs) of signals and images. Due to their tunable time-frequency localization and perfect reconstruction, the operation of MoDEEs is called a PDE transform. By appropriate selection of PDE transform parameters, we can tune IMFs into trends, edges, textures, noise etc., which can be further utilized in the secondary processing for various purposes. This work introduces the variational formulation, performs the Fourier analysis, and conducts biomedical and biological applications of the proposed PDE transform. The variational formulation offers an algorithm to incorporate two image functions and two sets of low-pass PDE operators in the total energy functional. Two low-pass PDE operators have different signs, leading to energy disparity, while a coupling term, acting as a relative fidelity of two image functions, is introduced to reduce the disparity of two energy components. We construct variational PDE transforms by using Euler-Lagrange equation and artificial time propagation. Fourier analysis of a simplified PDE transform is presented to shed light on the filter properties of high order PDE transforms. Such an analysis also offers insight on the parameter selection of the PDE transform. The proposed PDE transform algorithm is validated by numerous benchmark tests. In one selected challenging example, we illustrate the ability of PDE transform to separate two adjacent frequencies of sin(x) and sin(1.1x). Such an ability is due to PDE transform’s controllable frequency localization obtained by adjusting the order of PDEs. The frequency selection is achieved either by diffusion coefficients or by propagation time. Finally, we explore a large number of practical applications to further demonstrate the utility of proposed PDE transform. PMID:22207904

Localized motion in random matrix decomposition of complex financial systems

NASA Astrophysics Data System (ADS)

Jiang, Xiong-Fei; Zheng, Bo; Ren, Fei; Qiu, Tian

2017-04-01

With the random matrix theory, we decompose the multi-dimensional time series of complex financial systems into a set of orthogonal eigenmode functions, which are classified into the market mode, sector mode, and random mode. In particular, the localized motion generated by the business sectors, plays an important role in financial systems. Both the business sectors and their impact on the stock market are identified from the localized motion. We clarify that the localized motion induces different characteristics of the time correlations for the stock-market index and individual stocks. With a variation of a two-factor model, we reproduce the return-volatility correlations of the eigenmodes.

Reconstructing multi-mode networks from multivariate time series

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Yang, Yu-Xuan; Dang, Wei-Dong; Cai, Qing; Wang, Zhen; Marwan, Norbert; Boccaletti, Stefano; Kurths, Jürgen

2017-09-01

Unveiling the dynamics hidden in multivariate time series is a task of the utmost importance in a broad variety of areas in physics. We here propose a method that leads to the construction of a novel functional network, a multi-mode weighted graph combined with an empirical mode decomposition, and to the realization of multi-information fusion of multivariate time series. The method is illustrated in a couple of successful applications (a multi-phase flow and an epileptic electro-encephalogram), which demonstrate its powerfulness in revealing the dynamical behaviors underlying the transitions of different flow patterns, and enabling to differentiate brain states of seizure and non-seizure.

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

PubMed Central

Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

2015-01-01

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

Design of a linear projector for use with the normal modes of the GLAS 4th order GCM

NASA Technical Reports Server (NTRS)

Bloom, S. C.

1984-01-01

The design of a linear projector for use with the normal modes of a model of atmospheric circulation is discussed. A central element in any normal mode initialization scheme is the process by which a set of data fields - winds, temperatures or geopotentials, and surface pressures - are expressed ("projected') in terms of the coefficients of a model's normal modes. This process is completely analogous to the Fourier decomposition of a single field (indeed a FFT applied in the zonal direction is a part of the process). Complete separability in all three spatial dimensions is assumed. The basis functions for the modal expansion are given. An important feature of the normal modes is their coupling of the structures of different fields, thus a coefficient in a normal mode expansion would contain both mass and momentum information.

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

PubMed

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

Density functional theory study of HfCl4, ZrCl4, and Al(CH3)3 decomposition on hydroxylated SiO2: Initial stage of high-k atomic layer deposition

NASA Astrophysics Data System (ADS)

Jeloaica, L.; Estève, A.; Djafari Rouhani, M.; Estève, D.

2003-07-01

The initial stage of atomic layer deposition of HfO2, ZrO2, and Al2O3 high-k films, i.e., the decomposition of HfCl4, ZrCl4, and Al(CH3)3 precursor molecules on an OH-terminated SiO2 surface, is investigated within density functional theory. The energy barriers are determined using artificial activation of vibrational normal modes. For all precursors, reaction proceeds through the formation of intermediate complexes that have equivalent formation energies (˜-0.45 eV), and results in HCl and CH4 formation with activation energies of 0.88, 0.91, and 1.04 eV for Hf, Zr, and Al based precursors, respectively. The reaction product of Al(CH3)3 decomposition is found to be more stable (by -1.45 eV) than the chemisorbed intermediate complex compared to the endothermic decomposition of HfCl4 and ZrCl4 chemisorbed precursors (0.26 and 0.29 eV, respectively).

Preparation, non-isothermal decomposition kinetics, heat capacity and adiabatic time-to-explosion of NTOxDNAZ.

PubMed

Ma, Haixia; Yan, Biao; Li, Zhaona; Guan, Yulei; Song, Jirong; Xu, Kangzhen; Hu, Rongzu

2009-09-30

NTOxDNAZ was prepared by mixing 3,3-dinitroazetidine (DNAZ) and 3-nitro-1,2,4-triazol-5-one (NTO) in ethanol solution. The thermal behavior of the title compound was studied under a non-isothermal condition by DSC and TG/DTG methods. The kinetic parameters were obtained from analysis of the DSC and TG/DTG curves by Kissinger method, Ozawa method, the differential method and the integral method. The main exothermic decomposition reaction mechanism of NTOxDNAZ is classified as chemical reaction, and the kinetic parameters of the reaction are E(a)=149.68 kJ mol(-1) and A=10(15.81)s(-1). The specific heat capacity of the title compound was determined with continuous C(p) mode of microcalorimeter. The standard mole specific heat capacity of NTOxDNAZ was 352.56 J mol(-1)K(-1) in 298.15K. Using the relationship between C(p) and T and the thermal decomposition parameters, the time of the thermal decomposition from initialization to thermal explosion (adiabatic time-to-explosion) was obtained.

On the identification of normal modes of oscillation from observations of the solar periphery

NASA Technical Reports Server (NTRS)

Gough, D. O.; Latour, J.

1984-01-01

The decomposition of solar oscillations into their constituent normal modes requires a knowledge of both the spatial and temporal variation of the perturbation to the sun's surface. The task can be especially difficult when only limited spatial information is available. Observations of the limb-darkening function, for example, are probably sensitive to too large a number of modes to permit most of the modes to be identified in a power spectrum of measurements at only a few points on the limb, unless the results are combined with other data. In this paper a procedure is considered by which the contributions from quite small groups of modes to spatially well resolved data obtained at any instant can be extracted from the remaining modes. Combining these results with frequency information then permits the modes to be identified, at least if their frequencies are low enough to ensure that modes of high degree do not contribute substantially to the signal.

Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

PubMed Central

Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

2016-01-01

Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements. PMID:27007388

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

Miller, David C.; Kempe, Michael D.; Muller, Matthew T.

We examined the durability of polymeric encapsulation materials using outdoor exposure at the nominal geometric concentration of 500 suns. The results for 36-month cumulative field deployment are presented for materials including: poly(ethylene-co-vinyl acetate), (EVA); polyvinyl butyral (PVB); ionomer; polyethylene/polyoctene copolymer (PO); thermoplastic polyurethane (TPU); poly(dimethylsiloxane) (PDMS); poly(diphenyl dimethyl siloxane) (PDPDMS); and poly(phenyl-methyl siloxane) (PPMS). Measurements of the field conditions including ambient temperature and ultraviolet (UV) dose were recorded at the test site during the experiment. Our measurements for the experiment included optical transmittance (with subsequent analysis of solar-weighted transmittance, UV cut-off wavelength, and yellowness index), mass, visual photography, photoelastic imaging,more » and fluorescence spectroscopy. While the results to date for EVA are presented and discussed, examination here focuses more on the siloxane materials. A specimen recently observed to fail by thermal decomposition is discussed in terms of the implementation of the experiment as well as its fluorescence signature, which was observed to become more pronounced with age. Modulated thermogravimetry (allowing determination of the activation energy of thermal decomposition) was performed on a subset of the siloxanes to quantify the propensity for decomposition at elevated temperatures. Supplemental, Pt-catalyst- and primer-solutions as well as peroxide-cured PDMS specimens were examined to assess the source of the luminescence. Furthermore, our results, including the change in optical transmittance, observed failure modes, and subsequent analyses of the failure modes are described in the conclusions.« less

Scalar self-force for highly eccentric equatorial orbits in Kerr spacetime

NASA Astrophysics Data System (ADS)

Thornburg, Jonathan; Wardell, Barry

2017-04-01

If a small "particle" of mass μ M (with μ ≪1 ) orbits a black hole of mass M , the leading-order radiation-reaction effect is an O (μ2) "self-force" acting on the particle, with a corresponding O (μ ) "self-acceleration" of the particle away from a geodesic. Such "extreme-mass-ratio inspiral" systems are likely to be important gravitational-wave sources for future space-based gravitational-wave detectors. Here we consider the "toy model" problem of computing the self-force for a scalar-field particle on a bound eccentric orbit in Kerr spacetime. We use the Barack-Golbourn-Vega-Detweiler effective-source regularization with a 4th-order puncture field, followed by an ei m ϕ ("m -mode") Fourier decomposition and a separate time-domain numerical evolution in 2 +1 dimensions for each m . We introduce a finite worldtube that surrounds the particle worldline and define our evolution equations in a piecewise manner so that the effective source is only used within the worldtube. Viewed as a spatial region, the worldtube moves to follow the particle's orbital motion. We use slices of constant Boyer-Lindquist time in the region of the particle's motion, deformed to be asymptotically hyperboloidal and compactified near the horizon and J+ . Our numerical evolution uses Berger-Oliger mesh refinement with 4th-order finite differencing in space and time. Our computational scheme allows computation for highly eccentric orbits and should be generalizable to orbital evolution in the future. Our present implementation is restricted to equatorial geodesic orbits, but this restriction is not fundamental. We present numerical results for a number of test cases with orbital eccentricities as high as 0.98. In some cases we find large oscillations ("wiggles") in the self-force on the outgoing leg of the orbit shortly after periastron passage; these appear to be caused by the passage of the orbit through the strong-field region close to the background Kerr black hole.

Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses

NASA Astrophysics Data System (ADS)

Le, Thien-Phu

2017-10-01

The frequency-scale domain decomposition technique has recently been proposed for operational modal analysis. The technique is based on the Cauchy mother wavelet. In this paper, the approach is extended to the Morlet mother wavelet, which is very popular in signal processing due to its superior time-frequency localization. Based on the regressive form and an appropriate norm of the Morlet mother wavelet, the continuous wavelet transform of the power spectral density of ambient responses enables modes in the frequency-scale domain to be highlighted. Analytical developments first demonstrate the link between modal parameters and the local maxima of the continuous wavelet transform modulus. The link formula is then used as the foundation of the proposed modal identification method. Its practical procedure, combined with the singular value decomposition algorithm, is presented step by step. The proposition is finally verified using numerical examples and a laboratory test.

Patient-Specific Seizure Detection in Long-Term EEG Using Signal-Derived Empirical Mode Decomposition (EMD)-based Dictionary Approach.

PubMed

Kaleem, Muhammad; Gurve, Dharmendra; Guergachi, Aziz; Krishnan, Sridhar

2018-06-25

The objective of the work described in this paper is development of a computationally efficient methodology for patient-specific automatic seizure detection in long-term multi-channel EEG recordings. Approach: A novel patient-specific seizure detection approach based on signal-derived Empirical Mode Decomposition (EMD)-based dictionary approach is proposed. For this purpose, we use an empirical framework for EMD-based dictionary creation and learning, inspired by traditional dictionary learning methods, in which the EMD-based dictionary is learned from the multi-channel EEG data being analyzed for automatic seizure detection. We present the algorithm for dictionary creation and learning, whose purpose is to learn dictionaries with a small number of atoms. Using training signals belonging to seizure and non-seizure classes, an initial dictionary, termed as the raw dictionary, is formed. The atoms of the raw dictionary are composed of intrinsic mode functions obtained after decomposition of the training signals using the empirical mode decomposition algorithm. The raw dictionary is then trained using a learning algorithm, resulting in a substantial decrease in the number of atoms in the trained dictionary. The trained dictionary is then used for automatic seizure detection, such that coefficients of orthogonal projections of test signals against the trained dictionary form the features used for classification of test signals into seizure and non-seizure classes. Thus no hand-engineered features have to be extracted from the data as in traditional seizure detection approaches. Main results: The performance of the proposed approach is validated using the CHB-MIT benchmark database, and averaged accuracy, sensitivity and specificity values of 92.9%, 94.3% and 91.5%, respectively, are obtained using support vector machine classifier and five-fold cross-validation method. These results are compared with other approaches using the same database, and the suitability of the approach for seizure detection in long-term multi-channel EEG recordings is discussed. Significance: The proposed approach describes a computationally efficient method for automatic seizure detection in long-term multi-channel EEG recordings. The method does not rely on hand-engineered features, as are required in traditional approaches. Furthermore, the approach is suitable for scenarios where the dictionary once formed and trained can be used for automatic seizure detection of newly recorded data, making the approach suitable for long-term multi-channel EEG recordings. © 2018 IOP Publishing Ltd.

Laser augmented decomposition. II. D/sub 3/BPF/sub 3/. [Deuterium effects

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

Chien, K.R.; Bauer, S.H.

1976-06-17

The study of the accelerated decomposition of H/sub 3/BPF/sub 3/ induced by laser radiation (930-950 cm/sup -1/ was extended to the fully deuterated species. While in all essential respects the kinetics of the ir photolysis for the two compounds are identical, the few differences which were uncovered proved crucial in pointing to interesting features of the mechanism. These verified predictions were based on a normal mode analysis for the distribution of potential energy among the internal coordinates. For the laser augmented decomposition, E/sub a//sup L/ = 3.5 +- 1 kcal/mol, compared with E/sub a//sup th/ = 29.3 kcal/mol for themore » thermal process. The quantum efficiency is low, approximately 4 x 10/sup 4/ photons/molecule decomposed. The rates of decomposition depend on the isotopic content and are sensitively dependent on the frequency of the irradiating line. For example, with P(24) large fractionation ratios were found for D/sub 3/BPF/sub 3/ vs. H/sub 3/BPF/sub 3/, and small differences for D/sub 3//sup 11/BPF/sub 3/ vs. D/sub 3//sup 10/BPF/sub 3/. The levels of decomposition induced by the sequential three-photon absorption have been semiquantitatively accounted for.« less

Principal Component Relaxation Mode Analysis of an All-Atom Molecular Dynamics Simulation of Human Lysozyme

NASA Astrophysics Data System (ADS)

Nagai, Toshiki; Mitsutake, Ayori; Takano, Hiroshi

2013-02-01

A new relaxation mode analysis method, which is referred to as the principal component relaxation mode analysis method, has been proposed to handle a large number of degrees of freedom of protein systems. In this method, principal component analysis is carried out first and then relaxation mode analysis is applied to a small number of principal components with large fluctuations. To reduce the contribution of fast relaxation modes in these principal components efficiently, we have also proposed a relaxation mode analysis method using multiple evolution times. The principal component relaxation mode analysis method using two evolution times has been applied to an all-atom molecular dynamics simulation of human lysozyme in aqueous solution. Slow relaxation modes and corresponding relaxation times have been appropriately estimated, demonstrating that the method is applicable to protein systems.

Crack classification and evolution in anisotropic shale during cyclic loading tests by acoustic emission

NASA Astrophysics Data System (ADS)

Wang, Miaomiao; Tan, Chengxuan; Meng, Jing; Yang, Baicun; Li, Yuan

2017-08-01

Characterization and evolution of the cracking mode in shale formation is significant, as fracture networks are an important element in shale gas exploitation. In this study we determine the crack modes and evolution in anisotropic shale under cyclic loading using the acoustic emission (AE) parameter-analysis method based on the average frequency and RA (rise-time/amplitude) value. Shale specimens with bedding-plane orientations parallel and perpendicular to the axial loading direction were subjected to loading cycles with increasing peak values until failure occurred. When the loading was parallel to the bedding plane, most of the cracks at failure were shear cracks, while tensile cracks were dominant in the specimens that were loaded normal to the bedding direction. The evolution of the crack mode in the shale specimens observed in the loading-unloading sequence except for the first cycle can be divided into three stages: (I) no or several cracks (AE events) form as a result of the Kaiser effect, (II) tensile and shear cracks increase steadily at nearly equal proportions, (III) tensile cracks and shear cracks increase abruptly, with more cracks forming in one mode than in the other. As the dominant crack motion is influenced by the bedding, the failure mechanism is discussed based on the evolution of the different crack modes. Our conclusions can increase our understanding of the formation mechanism of fracture networks in the field.

Gradual plasmon evolution and huge infrared near-field enhancement of metallic bridged nanoparticle dimers.

PubMed

Huang, Yu; Ma, Lingwei; Hou, Mengjing; Xie, Zheng; Zhang, Zhengjun

2016-01-28

By three-dimensional (3D) finite element method (FEM) plasmon mapping, gradual plasmon evolutions of both bonding dipole plasmon (BDP) and charge transfer plasmon (CTP) modes are visualized. In particular, the evolved BDP mode provides a physical insight into the rapid degeneration of electromagnetic hot spots in practical applications, while the rising CTP mode enables a huge near-field enhancement for potential plasmonic devices at infrared wavelengths.

FIBER AND INTEGRAL OPTICS: Mode composition of radiation in graded-index waveguides with random microbending of the axis

NASA Astrophysics Data System (ADS)

Valyaev, A. B.; Krivoshlykov, S. G.

1989-06-01

It is shown that the problem of investigating the mode composition of a partly coherent radiation beam in a randomly inhomogeneous medium can be reduced to a study of evolution of the energy of individual modes and of the coefficients of correlations between the modes. General expressions are obtained for the coupling coefficients of modes in a parabolic waveguide with a random microbending of the axis and an analysis is made of their evolution as a function of the excitation conditions. An estimate is obtained of the distance in which a steady-state energy distribution between the modes is established. Explicit expressions are obtained for the correlation function in the case when a waveguide is excited by off-axial Gaussian beams or Gauss-Hermite modes.

A model-reduction approach in micromechanics of materials preserving the variational structure of constitutive relations

NASA Astrophysics Data System (ADS)

Michel, Jean-Claude; Suquet, Pierre

2016-05-01

In 2003 the authors proposed a model-reduction technique, called the Nonuniform Transformation Field Analysis (NTFA), based on a decomposition of the local fields of internal variables on a reduced basis of modes, to analyze the effective response of composite materials. The present study extends and improves on this approach in different directions. It is first shown that when the constitutive relations of the constituents derive from two potentials, this structure is passed to the NTFA model. Another structure-preserving model, the hybrid NTFA model of Fritzen and Leuschner, is analyzed and found to differ (slightly) from the primal NTFA model (it does not exhibit the same variational upper bound character). To avoid the "on-line" computation of local fields required by the hybrid model, new reduced evolution equations for the reduced variables are proposed, based on an expansion to second order (TSO) of the potential of the hybrid model. The coarse dynamics can then be entirely expressed in terms of quantities which can be pre-computed once for all. Roughly speaking, these pre-computed quantities depend only on the average and fluctuations per phase of the modes and of the associated stress fields. The accuracy of the new NTFA-TSO model is assessed by comparison with full-field simulations. The acceleration provided by the new coarse dynamics over the full-field computations (and over the hybrid model) is then spectacular, larger by three orders of magnitude than the acceleration due to the sole reduction of unknowns.

Interannual hydroclimatic variability and the 2009-2011 extreme ENSO phases in Colombia: from Andean glaciers to Caribbean lowlands

NASA Astrophysics Data System (ADS)

Bedoya-Soto, Juan Mauricio; Poveda, Germán; Trenberth, Kevin E.; Vélez-Upegui, Jorge Julián

2018-03-01

During 2009-2011, Colombia experienced extreme hydroclimatic events associated with the extreme phases of El Niño-Southern Oscillation (ENSO). Here, we study the dynamics of diverse land-atmosphere phenomena involved in such anomalous events at continental, regional, and local scales. Standardized anomalies of precipitation, 2-m temperature, total column water (TCW), volumetric soil water (VSW), temperature at 925 hPa, surface sensible heat (SSH), latent heat (SLH), evaporation (EVP), and liquid water equivalent thickness (LWET) are analyzed to assess atmosphere-land controls and relationships over tropical South America (TropSA) during 1986-2013 (long term) and 2009-2011 (ENSO extreme phases). An assessment of the interannual covariability between precipitation and 2-m temperature is performed using singular value decomposition (SVD) to identify the dominant spatiotemporal modes of hydroclimatic variability over the region's largest river basins (Amazon, Orinoco, Tocantins, Magdalena-Cauca, and Essequibo). ENSO, its evolution in time, and strong and consistent spatial structures emerge as the dominant mode of variability. In situ anomalies during both extreme phases of ENSO 2009-2011 over the Magdalena-Cauca River basins are linked at the continental scale. The ENSO-driven hydroclimatic effects extend from the diurnal cycle to interannual timescales, as reflected in temperature data from tropical glaciers and the rain-snow boundary in the highest peaks of the Central Andes of Colombia to river levels along the Caribbean lowlands of the Magdalena-Cauca River basin.

Completed Ensemble Empirical Mode Decomposition: a Robust Signal Processing Tool to Identify Sequence Strata

NASA Astrophysics Data System (ADS)

Purba, H.; Musu, J. T.; Diria, S. A.; Permono, W.; Sadjati, O.; Sopandi, I.; Ruzi, F.

2018-03-01

Well logging data provide many geological information and its trends resemble nonlinear or non-stationary signals. As long well log data recorded, there will be external factors can interfere or influence its signal resolution. A sensitive signal analysis is required to improve the accuracy of logging interpretation which it becomes an important thing to determine sequence stratigraphy. Complete Ensemble Empirical Mode Decomposition (CEEMD) is one of nonlinear and non-stationary signal analysis method which decomposes complex signal into a series of intrinsic mode function (IMF). Gamma Ray and Spontaneous Potential well log parameters decomposed into IMF-1 up to IMF-10 and each of its combination and correlation makes physical meaning identification. It identifies the stratigraphy and cycle sequence and provides an effective signal treatment method for sequence interface. This method was applied to BRK- 30 and BRK-13 well logging data. The result shows that the combination of IMF-5, IMF-6, and IMF-7 pattern represent short-term and middle-term while IMF-9 and IMF-10 represent the long-term sedimentation which describe distal front and delta front facies, and inter-distributary mouth bar facies, respectively. Thus, CEEMD clearly can determine the different sedimentary layer interface and better identification of the cycle of stratigraphic base level.

Experimental validation of a structural damage detection method based on marginal Hilbert spectrum

NASA Astrophysics Data System (ADS)

Banerji, Srishti; Roy, Timir B.; Sabamehr, Ardalan; Bagchi, Ashutosh

2017-04-01

Structural Health Monitoring (SHM) using dynamic characteristics of structures is crucial for early damage detection. Damage detection can be performed by capturing and assessing structural responses. Instrumented structures are monitored by analyzing the responses recorded by deployed sensors in the form of signals. Signal processing is an important tool for the processing of the collected data to diagnose anomalies in structural behavior. The vibration signature of the structure varies with damage. In order to attain effective damage detection, preservation of non-linear and non-stationary features of real structural responses is important. Decomposition of the signals into Intrinsic Mode Functions (IMF) by Empirical Mode Decomposition (EMD) and application of Hilbert-Huang Transform (HHT) addresses the time-varying instantaneous properties of the structural response. The energy distribution among different vibration modes of the intact and damaged structure depicted by Marginal Hilbert Spectrum (MHS) detects location and severity of the damage. The present work investigates damage detection analytically and experimentally by employing MHS. The testing of this methodology for different damage scenarios of a frame structure resulted in its accurate damage identification. The sensitivity of Hilbert Spectral Analysis (HSA) is assessed with varying frequencies and damage locations by means of calculating Damage Indices (DI) from the Hilbert spectrum curves of the undamaged and damaged structures.

Analysis of microvascular perfusion with multi-dimensional complete ensemble empirical mode decomposition with adaptive noise algorithm: Processing of laser speckle contrast images recorded in healthy subjects, at rest and during acetylcholine stimulation.

PubMed

Humeau-Heurtier, Anne; Marche, Pauline; Dubois, Severine; Mahe, Guillaume

2015-01-01

Laser speckle contrast imaging (LSCI) is a full-field imaging modality to monitor microvascular blood flow. It is able to give images with high temporal and spatial resolutions. However, when the skin is studied, the interpretation of the bidimensional data may be difficult. This is why an averaging of the perfusion values in regions of interest is often performed and the result is followed in time, reducing the data to monodimensional time series. In order to avoid such a procedure (that leads to a loss of the spatial resolution), we propose to extract patterns from LSCI data and to compare these patterns for two physiological states in healthy subjects: at rest and at the peak of acetylcholine-induced perfusion peak. For this purpose, the recent multi-dimensional complete ensemble empirical mode decomposition with adaptive noise (MCEEMDAN) algorithm is applied to LSCI data. The results show that the intrinsic mode functions and residue given by MCEEMDAN show different patterns for the two physiological states. The images, as bidimensional data, can therefore be processed to reveal microvascular perfusion patterns, hidden in the images themselves. This work is therefore a feasibility study before analyzing data in patients with microvascular dysfunctions.

Machinery Bearing Fault Diagnosis Using Variational Mode Decomposition and Support Vector Machine as a Classifier

NASA Astrophysics Data System (ADS)

Rama Krishna, K.; Ramachandran, K. I.

2018-02-01

Crack propagation is a major cause of failure in rotating machines. It adversely affects the productivity, safety, and the machining quality. Hence, detecting the crack’s severity accurately is imperative for the predictive maintenance of such machines. Fault diagnosis is an established concept in identifying the faults, for observing the non-linear behaviour of the vibration signals at various operating conditions. In this work, we find the classification efficiencies for both original and the reconstructed vibrational signals. The reconstructed signals are obtained using Variational Mode Decomposition (VMD), by splitting the original signal into three intrinsic mode functional components and framing them accordingly. Feature extraction, feature selection and feature classification are the three phases in obtaining the classification efficiencies. All the statistical features from the original signals and reconstructed signals are found out in feature extraction process individually. A few statistical parameters are selected in feature selection process and are classified using the SVM classifier. The obtained results show the best parameters and appropriate kernel in SVM classifier for detecting the faults in bearings. Hence, we conclude that better results were obtained by VMD and SVM process over normal process using SVM. This is owing to denoising and filtering the raw vibrational signals.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

PubMed

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-07-07

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition

PubMed Central

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-01-01

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method. PMID:26198231

High and low frequency unfolded partial least squares regression based on empirical mode decomposition for quantitative analysis of fuel oil samples.

PubMed

Bian, Xihui; Li, Shujuan; Lin, Ligang; Tan, Xiaoyao; Fan, Qingjie; Li, Ming

2016-06-21

Accurate prediction of the model is fundamental to the successful analysis of complex samples. To utilize abundant information embedded over frequency and time domains, a novel regression model is presented for quantitative analysis of hydrocarbon contents in the fuel oil samples. The proposed method named as high and low frequency unfolded PLSR (HLUPLSR), which integrates empirical mode decomposition (EMD) and unfolded strategy with partial least squares regression (PLSR). In the proposed method, the original signals are firstly decomposed into a finite number of intrinsic mode functions (IMFs) and a residue by EMD. Secondly, the former high frequency IMFs are summed as a high frequency matrix and the latter IMFs and residue are summed as a low frequency matrix. Finally, the two matrices are unfolded to an extended matrix in variable dimension, and then the PLSR model is built between the extended matrix and the target values. Coupled with Ultraviolet (UV) spectroscopy, HLUPLSR has been applied to determine hydrocarbon contents of light gas oil and diesel fuels samples. Comparing with single PLSR and other signal processing techniques, the proposed method shows superiority in prediction ability and better model interpretation. Therefore, HLUPLSR method provides a promising tool for quantitative analysis of complex samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust multitask learning with three-dimensional empirical mode decomposition-based features for hyperspectral classification

NASA Astrophysics Data System (ADS)

He, Zhi; Liu, Lin

2016-11-01

Empirical mode decomposition (EMD) and its variants have recently been applied for hyperspectral image (HSI) classification due to their ability to extract useful features from the original HSI. However, it remains a challenging task to effectively exploit the spectral-spatial information by the traditional vector or image-based methods. In this paper, a three-dimensional (3D) extension of EMD (3D-EMD) is proposed to naturally treat the HSI as a cube and decompose the HSI into varying oscillations (i.e. 3D intrinsic mode functions (3D-IMFs)). To achieve fast 3D-EMD implementation, 3D Delaunay triangulation (3D-DT) is utilized to determine the distances of extrema, while separable filters are adopted to generate the envelopes. Taking the extracted 3D-IMFs as features of different tasks, robust multitask learning (RMTL) is further proposed for HSI classification. In RMTL, pairs of low-rank and sparse structures are formulated by trace-norm and l1,2 -norm to capture task relatedness and specificity, respectively. Moreover, the optimization problems of RMTL can be efficiently solved by the inexact augmented Lagrangian method (IALM). Compared with several state-of-the-art feature extraction and classification methods, the experimental results conducted on three benchmark data sets demonstrate the superiority of the proposed methods.

A Combined Methodology to Eliminate Artifacts in Multichannel Electrogastrogram Based on Independent Component Analysis and Ensemble Empirical Mode Decomposition.

PubMed

Sengottuvel, S; Khan, Pathan Fayaz; Mariyappa, N; Patel, Rajesh; Saipriya, S; Gireesan, K

2018-06-01

Cutaneous measurements of electrogastrogram (EGG) signals are heavily contaminated by artifacts due to cardiac activity, breathing, motion artifacts, and electrode drifts whose effective elimination remains an open problem. A common methodology is proposed by combining independent component analysis (ICA) and ensemble empirical mode decomposition (EEMD) to denoise gastric slow-wave signals in multichannel EGG data. Sixteen electrodes are fixed over the upper abdomen to measure the EGG signals under three gastric conditions, namely, preprandial, postprandial immediately, and postprandial 2 h after food for three healthy subjects and a subject with a gastric disorder. Instantaneous frequencies of intrinsic mode functions that are obtained by applying the EEMD technique are analyzed to individually identify and remove each of the artifacts. A critical investigation on the proposed ICA-EEMD method reveals its ability to provide a higher attenuation of artifacts and lower distortion than those obtained by the ICA-EMD method and conventional techniques, like bandpass and adaptive filtering. Characteristic changes in the slow-wave frequencies across the three gastric conditions could be determined from the denoised signals for all the cases. The results therefore encourage the use of the EEMD-based technique for denoising gastric signals to be used in clinical practice.

Effect of aging temperature on phase decomposition and mechanical properties in cast duplex stainless steels

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

Mburu, Sarah; Kolli, R. Prakash; Perea, Daniel E.

The microstructure and mechanical properties in unaged and thermally aged (at 280 °C, 320 °C, 360 °C, and 400 °C to 4300 h) CF–3 and CF–8 cast duplex stainless steels (CDSS) are investigated. The unaged CF–8 steel has Cr-rich M 23C 6 carbides located at the δ–ferrite/γ–austenite heterophase interfaces that were not observed in the CF–3 steel and this corresponds to a difference in mechanical properties. Both unaged steels exhibit incipient spinodal decomposition into Fe-rich α–domains and Cr-rich α’–domains. During aging, spinodal decomposition progresses and the mean wavelength (MW) and mean amplitude (MA) of the compositional fluctuations increase as amore » function of aging temperature. Additionally, G–phase precipitates form between the spinodal decomposition domains in CF–3 at 360 °C and 400 °C and in CF–8 at 400 °C. Finally, the microstructural evolution is correlated to changes in mechanical properties.« less

Effect of aging temperature on phase decomposition and mechanical properties in cast duplex stainless steels

DOE PAGES

Mburu, Sarah; Kolli, R. Prakash; Perea, Daniel E.; ...

2017-03-06

The microstructure and mechanical properties in unaged and thermally aged (at 280 °C, 320 °C, 360 °C, and 400 °C to 4300 h) CF–3 and CF–8 cast duplex stainless steels (CDSS) are investigated. The unaged CF–8 steel has Cr-rich M 23C 6 carbides located at the δ–ferrite/γ–austenite heterophase interfaces that were not observed in the CF–3 steel and this corresponds to a difference in mechanical properties. Both unaged steels exhibit incipient spinodal decomposition into Fe-rich α–domains and Cr-rich α’–domains. During aging, spinodal decomposition progresses and the mean wavelength (MW) and mean amplitude (MA) of the compositional fluctuations increase as amore » function of aging temperature. Additionally, G–phase precipitates form between the spinodal decomposition domains in CF–3 at 360 °C and 400 °C and in CF–8 at 400 °C. Finally, the microstructural evolution is correlated to changes in mechanical properties.« less

Effect of aging temperature on phase decomposition and mechanical properties in cast duplex stainless steels

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

Mburu, Sarah; Kolli, R. Prakash; Perea, Daniel E.

The microstructure and mechanical properties in unaged and thermally aged (at 280 oC, 320 oC, 360 oC, and 400 oC to 4300 h) CF–3 and CF–8 cast duplex stainless steels (CDSS) are investigated. The unaged CF–8 steel has Cr-rich M23C6 carbides located at the δ–ferrite/γ– austenite heterophase interfaces that were not observed in the CF–3 steel and this corresponds to a difference in mechanical properties. Both unaged steels exhibit incipient spinodal decomposition into Fe-rich α–domains and Cr-rich α’–domains. During aging, spinodal decomposition progresses and the mean wavelength (MW) and mean amplitude (MA) of the compositional fluctuations increase as a functionmore » of aging temperature. Additionally, G–phase precipitates form between the spinodal decomposition domains in CF–3 at 360 oC and 400 oC and in CF–8 at 400 oC. The microstructural evolution is correlated to changes in mechanical properties.« less

Continuous-variable gate decomposition for the Bose-Hubbard model

NASA Astrophysics Data System (ADS)

Kalajdzievski, Timjan; Weedbrook, Christian; Rebentrost, Patrick

2018-06-01

In this work, we decompose the time evolution of the Bose-Hubbard model into a sequence of logic gates that can be implemented on a continuous-variable photonic quantum computer. We examine the structure of the circuit that represents this time evolution for one-dimensional and two-dimensional lattices. The elementary gates needed for the implementation are counted as a function of lattice size. We also include the contribution of the leading dipole interaction term which may be added to the Hamiltonian and its corresponding circuit.

Methyl group transfer upon gas phase decomposition of protonated methyl benzoate and similar compounds.

PubMed

Frański, Rafał; Gierczyk, Błażej; Zalas, Maciej; Jankowski, Wojciech; Hoffmann, Marcin

2018-05-01

Gas phase decompositions of protonated methyl benzoate and its conjugates have been studied by using electrospray ionization-collision induced dissociation-tandem mass spectrometry. Loss of CO 2 molecule, thus transfer of methyl group, has been observed. In order to better understand this process, the theoretical calculations have been performed. For methyl benzoate conjugates, it has been found that position of substituent affects the loss of CO 2 molecule, not the electron donor/withdrawing properties of the substituent. Therefore, electrospray ionization-mass spectrometry in positive ion mode may be useful for differentiation of isomers of methyl benzoate conjugates. Copyright © 2018 John Wiley & Sons, Ltd.

Signatures of extra dimensions in gravitational waves from black hole quasinormal modes

NASA Astrophysics Data System (ADS)

Chakraborty, Sumanta; Chakravarti, Kabir; Bose, Sukanta; SenGupta, Soumitra

2018-05-01

In this work, we have derived the evolution equation for gravitational perturbation in four-dimensional spacetime in the presence of a spatial extra dimension. The evolution equation is derived by perturbing the effective gravitational field equations on the four-dimensional spacetime, which inherits nontrivial higher-dimensional effects. Note that this is different from the perturbation of the five-dimensional gravitational field equations that exist in the literature and possess quantitatively new features. The gravitational perturbation has further been decomposed into a purely four-dimensional part and another piece that depends on extra dimensions. The four-dimensional gravitational perturbation now admits massive propagating degrees of freedom, owing to the existence of higher dimensions. We have also studied the influence of these massive propagating modes on the quasinormal mode frequencies, signaling the higher-dimensional nature of the spacetime, and have contrasted these massive modes with the massless modes in general relativity. Surprisingly, it turns out that the massive modes experience damping much smaller than that of the massless modes in general relativity and may even dominate over and above the general relativity contribution if one observes the ringdown phase of a black hole merger event at sufficiently late times. Furthermore, the whole analytical framework has been supplemented by the fully numerical Cauchy evolution problem, as well. In this context, we have shown that, except for minute details, the overall features of the gravitational perturbations are captured both in the Cauchy evolution as well as in the analysis of quasinormal modes. The implications on observations of black holes with LIGO and proposed space missions such as LISA are also discussed.

Power-induced evolution and increased dimensionality of nonlinear modes in reorientational soft matter.

PubMed

Laudyn, Urszula A; Jung, Paweł S; Zegadło, Krzysztof B; Karpierz, Miroslaw A; Assanto, Gaetano

2014-11-15

We demonstrate the evolution of higher order one-dimensional guided modes into two-dimensional solitary waves in a reorientational medium. The observations, carried out at two different wavelengths in chiral nematic liquid crystals, are in good agreement with a simple nonlocal nonlinear model.

Antarctica, Greenland and Gulf of Alaska Land-ice Evolution from an Iterated GRACE Global Mascon Solution

NASA Technical Reports Server (NTRS)

Luthcke, Scott B.; Sabaka, T. J.; Loomis, B. D.; Arendt, A. A.; McCarthy, J. J.; Camp, J.

2013-01-01

We have determined the ice mass evolution of the Antarctica and Greenland ice sheets (AIS and GIS) and Gulf of Alaska (GOA) glaciers from a new GRACE global solution of equal-area surface mass concentration parcels (mascons) in equivalent height of water. The mascons were estimated directly from the reduction of the inter-satellite K-band range-rate (KBRR) observations, taking into account the full noise covariance, and formally iterating the solution. The new solution increases signal recovery while reducing the GRACE KBRR observation residuals. The mascons were estimated with 10 day and 1 arc degree equal-area sampling, applying anisotropic constraints. An ensemble empirical mode decomposition adaptive filter was applied to the mascon time series to compute annual mass balances. The details and causes of the spatial and temporal variability of the land-ice regions studied are discussed. The estimated mass trend over the total GIS, AIS and GOA glaciers for the time period 1 December 2003 to 1 December 2010 is -380 plus or minus 31 Gt a(exp -1), equivalent to -1.05 plus or minus 0.09 mma(exp -1) sea-level rise. Over the same time period we estimate the mass acceleration to be -41 plus or minus 27 Gt a(exp -2), equivalent to a 0.11 plus or minus 0.08 mm a(exp -2) rate of change in sea level. The trends and accelerations are dependent on significant seasonal and annual balance anomalies.

Antarctica, Greenland and Gulf of Alaska Land-Ice Evolution from an Iterated GRACE Global Mascon Solution

NASA Technical Reports Server (NTRS)

Luthcke, Scott B.; Sabaka, T. J.; Loomis, B. D.; Arendt, A. A.; McCarthy, J. J.; Camp, J.

2013-01-01

We have determined the ice mass evolution of the Antarctica and Greenland ice sheets (AIS and GIS) and Gulf of Alaska (GOA) glaciers from a new GRACE global solution of equal-area surface mass concentration parcels (mascons) in equivalent height of water. The mascons were estimated directly from the reduction of the inter-satellite K-band range-rate (KBRR) observations, taking into account the full noise covariance, and formally iterating the solution. The new solution increases signal recovery while reducing the GRACE KBRR observation residuals. The mascons were estimated with 10 day and 1 arc degree equal-area sampling, applying anisotropic constraints. An ensemble empirical mode decomposition adaptive filter was applied to the mascon time series to compute annual mass balances. The details and causes of the spatial and temporal variability of the land-ice regions studied are discussed. The estimated mass trend over the total GIS, AIS and GOA glaciers for the time period 1 December 2003 to 1 December 2010 is -380 plus or minus 31 Gt a(exp -1), equivalent to -1.05 plus or minus 0.09 mma(exp -1) sea-level rise. Over the same time period we estimate the mass acceleration to be -41 plus or minus 27 Gt a(exp -2), equivalent to a 0.11 plus or minus 0.08 mm a(exp -2) rate of change in sea level. The trends and accelerations are dependent on significant seasonal and annual balance anomalies.

Wave Phenomena in an Acoustic Resonant Chamber

ERIC Educational Resources Information Center

Smith, Mary E.; And Others

1974-01-01

Discusses the design and operation of a high Q acoustical resonant chamber which can be used to demonstrate wave phenomena such as three-dimensional normal modes, Q values, densities of states, changes in the speed of sound, Fourier decomposition, damped harmonic oscillations, sound-absorbing properties, and perturbation and scattering problems.…

Sea surface temperature variation linked to elemental mercury concentrations measured on Mauna Loa

EPA Science Inventory

The Hg0 time series recorded at the Mauna Loa Observatory (MLO) in Hawaii between 2002 and 2009 has been analyzed using Empirical Mode Decomposition. This technique has been used in numerous contexts in order to identify periodical variations in time series data. The periodicitie...

Compatibility Studies of Hydrogen Peroxide and a New Hypergolic Fuel Blend

NASA Technical Reports Server (NTRS)

Baldridge, Jennifer; Villegas, Yvonne

2002-01-01

Several preliminary materials compatibility studies have been conducted to determine the practicality of a new hypergolic fuel system. Hypergolic fuel ignites spontaneously as the oxidizer decomposes and releases energy in the presence of the fuel. The bipropellant system tested consists of high-test hydrogen peroxide (HTP) and a liquid fuel blend consisting of a hydrocarbon fuel, an ignition enhancer and a transition metal catalyst. In order for further testing of the new fuel blend to take place, some basic materials compatibility and HTP decomposition studies must be accomplished. The thermal decomposition rate of HTP was tested using gas evolution and isothermal microcalorimetry (IMC). Materials were analyzed for compatibility with hydrogen peroxide including a study of the affect welding has on stainless steel elemental composition and its relation to HTP decomposition. Compatibility studies of valve materials in the fuel blend were performed to determine the corrosion resistance of the materials.

A parallel domain decomposition-based implicit method for the Cahn–Hilliard–Cook phase-field equation in 3D

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

Zheng, Xiang; Yang, Chao; State Key Laboratory of Computer Science, Chinese Academy of Sciences, Beijing 100190

2015-03-15

We present a numerical algorithm for simulating the spinodal decomposition described by the three dimensional Cahn–Hilliard–Cook (CHC) equation, which is a fourth-order stochastic partial differential equation with a noise term. The equation is discretized in space and time based on a fully implicit, cell-centered finite difference scheme, with an adaptive time-stepping strategy designed to accelerate the progress to equilibrium. At each time step, a parallel Newton–Krylov–Schwarz algorithm is used to solve the nonlinear system. We discuss various numerical and computational challenges associated with the method. The numerical scheme is validated by a comparison with an explicit scheme of high accuracymore » (and unreasonably high cost). We present steady state solutions of the CHC equation in two and three dimensions. The effect of the thermal fluctuation on the spinodal decomposition process is studied. We show that the existence of the thermal fluctuation accelerates the spinodal decomposition process and that the final steady morphology is sensitive to the stochastic noise. We also show the evolution of the energies and statistical moments. In terms of the parallel performance, it is found that the implicit domain decomposition approach scales well on supercomputers with a large number of processors.« less

Multiplexing of spatial modes in the mid-IR region

NASA Astrophysics Data System (ADS)

Gailele, Lucas; Maweza, Loyiso; Dudley, Angela; Ndagano, Bienvenu; Rosales-Guzman, Carmelo; Forbes, Andrew

2017-02-01

Traditional optical communication systems optimize multiplexing in polarization and wavelength both trans- mitted in fiber and free-space to attain high bandwidth data communication. Yet despite these technologies, we are expected to reach a bandwidth ceiling in the near future. Communications using orbital angular momentum (OAM) carrying modes offers infinite dimensional states, providing means to increase link capacity by multiplexing spatially overlapping modes in both the azimuthal and radial degrees of freedom. OAM modes are multiplexed and de-multiplexed by the use of spatial light modulators (SLM). Implementation of complex amplitude modulation is employed on laser beams phase and amplitude to generate Laguerre-Gaussian (LG) modes. Modal decomposition is employed to detect these modes due to their orthogonality as they propagate in space. We demonstrate data transfer by sending images as a proof-of concept in a lab-based scheme. We demonstrate the creation and detection of OAM modes in the mid-IR region as a precursor to a mid-IR free-space communication link.

EMD self-adaptive selecting relevant modes algorithm for FBG spectrum signal

NASA Astrophysics Data System (ADS)

Chen, Yong; Wu, Chun-ting; Liu, Huan-lin

2017-07-01

Noise may reduce the demodulation accuracy of fiber Bragg grating (FBG) sensing signal so as to affect the quality of sensing detection. Thus, the recovery of a signal from observed noisy data is necessary. In this paper, a precise self-adaptive algorithm of selecting relevant modes is proposed to remove the noise of signal. Empirical mode decomposition (EMD) is first used to decompose a signal into a set of modes. The pseudo modes cancellation is introduced to identify and eliminate false modes, and then the Mutual Information (MI) of partial modes is calculated. MI is used to estimate the critical point of high and low frequency components. Simulation results show that the proposed algorithm estimates the critical point more accurately than the traditional algorithms for FBG spectral signal. While, compared to the similar algorithms, the signal noise ratio of the signal can be improved more than 10 dB after processing by the proposed algorithm, and correlation coefficient can be increased by 0.5, so it demonstrates better de-noising effect.

Modelling of hyperconcentrated flood and channel evolution in a braided reach using a dynamically coupled one-dimensional approach

NASA Astrophysics Data System (ADS)

Xia, Junqiang; Zhang, Xiaolei; Wang, Zenghui; Li, Jie; Zhou, Meirong

2018-06-01

Hyperconcentrated sediment-laden floods often occur in a braided reach of the Lower Yellow River, usually leading to significant channel evolution. A one-dimensional (1D) morphodynamic model using a dynamically coupled solution approach is developed to simulate hyperconcentrated flood and channel evolution in the braided reach with an extremely irregular cross-sectional geometry. In the model, the improved equations for hydrodynamics account for the effects of sediment concentration and bed evolution, which are coupled with the equations of non-equilibrium sediment transport and bed evolution. The model was validated using measurements from the 1977 and 2004 hyperconcentrated floods. Furthermore, the effects were investigated of different cross-sectional spacings and allocation modes of channel deformation area on the model results. It was found that a suitable cross-sectional distance of less than 3 km should be adopted when simulating hyperconcentrated floods, and the results using the uniform allocation mode can agree better with measurements than other two allocation modes.

A preprocessing strategy for helioseismic inversions

NASA Astrophysics Data System (ADS)

Christensen-Dalsgaard, J.; Thompson, M. J.

1993-05-01

Helioseismic inversion in general involves considerable computational expense, due to the large number of modes that is typically considered. This is true in particular of the widely used optimally localized averages (OLA) inversion methods, which require the inversion of one or more matrices whose order is the number of modes in the set. However, the number of practically independent pieces of information that a large helioseismic mode set contains is very much less than the number of modes, suggesting that the set might first be reduced before the expensive inversion is performed. We demonstrate with a model problem that by first performing a singular value decomposition the original problem may be transformed into a much smaller one, reducing considerably the cost of the OLA inversion and with no significant loss of information.

Nonlinear evolution of three-dimensional instabilities of thin and thick electron scale current sheets: Plasmoid formation and current filamentation

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

Jain, Neeraj; Büchner, Jörg; Max Planck Institute for Solar System Research, Justus-Von-Liebig-Weg-3, Göttingen

Nonlinear evolution of three dimensional electron shear flow instabilities of an electron current sheet (ECS) is studied using electron-magnetohydrodynamic simulations. The dependence of the evolution on current sheet thickness is examined. For thin current sheets (half thickness =d{sub e}=c/ω{sub pe}), tearing mode instability dominates. In its nonlinear evolution, it leads to the formation of oblique current channels. Magnetic field lines form 3-D magnetic spirals. Even in the absence of initial guide field, the out-of-reconnection-plane magnetic field generated by the tearing instability itself may play the role of guide field in the growth of secondary finite-guide-field instabilities. For thicker current sheetsmore » (half thickness ∼5 d{sub e}), both tearing and non-tearing modes grow. Due to the non-tearing mode, current sheet becomes corrugated in the beginning of the evolution. In this case, tearing mode lets the magnetic field reconnect in the corrugated ECS. Later thick ECS develops filamentary structures and turbulence in which reconnection occurs. This evolution of thick ECS provides an example of reconnection in self-generated turbulence. The power spectra for both the thin and thick current sheets are anisotropic with respect to the electron flow direction. The cascade towards shorter scales occurs preferentially in the direction perpendicular to the electron flow.« less

Morphological diversity and evolution of egg and clutch structure in amphibians

USGS Publications Warehouse

Altig, Ronald; McDiarmid, Roy W.

2007-01-01

The first part of this synthesis summarizes the morphology of the jelly layers surrounding an amphibian ovum. We propose a standard terminology and discuss the evolution of jelly layers. The second part reviews the morphological diversity and arrangement of deposited eggs?the ovipositional mode; we recognize 5 morphological classes including 14 modes. We discuss some of the oviductal, ovipositional, and postovipositional events that contribute to these morphologies. We have incorporated data from taxa from throughout the world but recognize that other types will be discovered that may modify understanding of these modes. Finally, we discuss the evolutionary context of the diversity of clutch structure and present a first estimate of its evolution.

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric Model Order Reduction

PubMed Central

Paul, Sarbajit; Chang, Junghwan

2017-01-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension. PMID:28671580

A general solution strategy of modified power method for higher mode solutions

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

Zhang, Peng; Lee, Hyunsuk; Lee, Deokjung, E-mail: deokjung@unist.ac.kr

2016-01-15

A general solution strategy of the modified power iteration method for calculating higher eigenmodes has been developed and applied in continuous energy Monte Carlo simulation. The new approach adopts four features: 1) the eigen decomposition of transfer matrix, 2) weight cancellation for higher modes, 3) population control with higher mode weights, and 4) stabilization technique of statistical fluctuations using multi-cycle accumulations. The numerical tests of neutron transport eigenvalue problems successfully demonstrate that the new strategy can significantly accelerate the fission source convergence with stable convergence behavior while obtaining multiple higher eigenmodes at the same time. The advantages of the newmore » strategy can be summarized as 1) the replacement of the cumbersome solution step of high order polynomial equations required by Booth's original method with the simple matrix eigen decomposition, 2) faster fission source convergence in inactive cycles, 3) more stable behaviors in both inactive and active cycles, and 4) smaller variances in active cycles. Advantages 3 and 4 can be attributed to the lower sensitivity of the new strategy to statistical fluctuations due to the multi-cycle accumulations. The application of the modified power method to continuous energy Monte Carlo simulation and the higher eigenmodes up to 4th order are reported for the first time in this paper. -- Graphical abstract: -- Highlights: •Modified power method is applied to continuous energy Monte Carlo simulation. •Transfer matrix is introduced to generalize the modified power method. •All mode based population control is applied to get the higher eigenmodes. •Statistic fluctuation can be greatly reduced using accumulated tally results. •Fission source convergence is accelerated with higher mode solutions.« less

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric model order reduction.

PubMed

Paul, Sarbajit; Chang, Junghwan

2017-07-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.

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

Pierce, Dean T.; Coughlin, D. R.; Williamson, Don L.

Here, the influence of partitioning temperature on microstructural evolution during quenching and partitioning was investigated in a 0.38C-1.54Mn-1.48Si wt.% steel using Mössbauer spectroscopy and transmission electron microscopy. η-carbide formation occurs in the martensite during the quenching, holding, and partitioning steps. More effective carbon partitioning from martensite to austenite was observed at 450 than 400°C, resulting in lower martensite carbon contents, less carbide formation, and greater retained austenite amounts for short partitioning times. Conversely, greater austenite decomposition occurs at 450°C for longer partitioning times. Lastly, cementite forms during austenite decomposition and in the martensite for longer partitioning times at 450°C.

Probing longitudinal modes evolution of a InGaN green laser diode

NASA Astrophysics Data System (ADS)

Chen, Yi-Hsi; Lin, Wei-Chen; Chen, Hong-Zui; Shy, Jow-Tsong; Chui, Hsiang-Chen

2018-06-01

This study aims to investigate the longitudinal mode evolution of a InGaN green laser diode. A spectrometer with a 3-pm resolution was employed to obtain the emission spectra of a green laser diode, at a wavelength of around 520 nm, as a function of applied current and temperature. The spectral behavior of the laser modes with applied current was investigated. Right above the lasing threshold, the green diode laser emitted single longitudinal mode output. With increasing applied current, the number of the longitudinal modes increased. Up to ten lasing modes oscillated within the entire gain profile when the applied currents were tuned to 2.2Ith. Subsequently, a multi-Lorentzian profile model was adopted to analyze the spectra and observe how the modes evolved with temperature and applied current.

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

Stellar convection 2: A multi-mode numerical solution for convection in spheres

NASA Technical Reports Server (NTRS)

Marcus, P. S.

1979-01-01

The convective flow of a self gravitating sphere of Boussinesq fluid for small Reynolds and Peclet numbers is numerically determined. The decomposition of the equations of motion into modes is reviewed and a relaxation method is developed and presented to compute the solutions to these equations. The stable equilibrium flow for a Rayleigh number of 10 to the 4th power and a Prandtl number of 10 is determined. The 2 and 3 dimensional spectra of the kinetic and thermal energies and the convective flux as a function of wavelengths are calculated in terms of modes. The anisotropy of the flow as a function of wavelength is defined.

A combined cICA-EEMD analysis of EEG recordings from depressed or schizophrenic patients during olfactory stimulation

NASA Astrophysics Data System (ADS)

Götz, Th; Stadler, L.; Fraunhofer, G.; Tomé, A. M.; Hausner, H.; Lang, E. W.

2017-02-01

Objective. We propose a combination of a constrained independent component analysis (cICA) with an ensemble empirical mode decomposition (EEMD) to analyze electroencephalographic recordings from depressed or schizophrenic subjects during olfactory stimulation. Approach. EEMD serves to extract intrinsic modes (IMFs) underlying the recorded EEG time. The latter then serve as reference signals to extract the most similar underlying independent component within a constrained ICA. The extracted modes are further analyzed considering their power spectra. Main results. The analysis of the extracted modes reveals clear differences in the related power spectra between the disease characteristics of depressed and schizophrenic patients. Such differences appear in the high frequency γ-band in the intrinsic modes, but also in much more detail in the low frequency range in the α-, θ- and δ-bands. Significance. The proposed method provides various means to discriminate both disease pictures in a clinical environment.

A guided wave dispersion compensation method based on compressed sensing

NASA Astrophysics Data System (ADS)

Xu, Cai-bin; Yang, Zhi-bo; Chen, Xue-feng; Tian, Shao-hua; Xie, Yong

2018-03-01

The ultrasonic guided wave has emerged as a promising tool for structural health monitoring (SHM) and nondestructive testing (NDT) due to their capability to propagate over long distances with minimal loss and sensitivity to both surface and subsurface defects. The dispersion effect degrades the temporal and spatial resolution of guided waves. A novel ultrasonic guided wave processing method for both single mode and multi-mode guided waves dispersion compensation is proposed in this work based on compressed sensing, in which a dispersion signal dictionary is built by utilizing the dispersion curves of the guided wave modes in order to sparsely decompose the recorded dispersive guided waves. Dispersion-compensated guided waves are obtained by utilizing a non-dispersion signal dictionary and the results of sparse decomposition. Numerical simulations and experiments are implemented to verify the effectiveness of the developed method for both single mode and multi-mode guided waves.

Entanglement and purity of two-mode Gaussian states in noisy channels

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

Serafini, Alessio; Illuminati, Fabrizio; De Siena, Silvio

2004-02-01

We study the evolution of purity, entanglement, and total correlations of general two-mode continuous variable Gaussian states in arbitrary uncorrelated Gaussian environments. The time evolution of purity, von Neumann entropy, logarithmic negativity, and mutual information is analyzed for a wide range of initial conditions. In general, we find that a local squeezing of the bath leads to a faster degradation of purity and entanglement, while it can help to preserve the mutual information between the modes.

Between-Region Genetic Divergence Reflects the Mode and Tempo of Tumor Evolution

PubMed Central

Sun, Ruping; Hu, Zheng; Sottoriva, Andrea; Graham, Trevor A.; Harpak, Arbel; Ma, Zhicheng; Fischer, Jared M.; Shibata, Darryl; Curtis, Christina

2017-01-01

Given the implications of tumor dynamics for precision medicine, there is a need to systematically characterize the mode of evolution across diverse solid tumor types. In particular, methods to infer the role of natural selection within established human tumors are lacking. By simulating spatial tumor growth under different evolutionary modes and examining patterns of between-region subclonal genetic divergence from multi-region sequencing (MRS) data, we demonstrate that it is feasible to distinguish tumors driven by strong positive subclonal selection from those evolving neutrally or under weak selection, as the latter fail to dramatically alter subclonal composition. We developed a classifier based on measures of between-region subclonal genetic divergence and projected patient data into model space, revealing different modes of evolution both within and between solid tumor types. Our findings have broad implications for how human tumors progress, accumulate intra-tumor heterogeneity, and ultimately how they may be more effectively treated. PMID:28581503

The effect of a dominant initial single mode on the Kelvin–Helmholtz instability evolution: New insights on previous experimental results

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

Shimony, Assaf; Shvarts, Dov; Malamud, Guy

2016-04-12

This paper brings new insights on an experiment, measuring the Kelvin–Helmholtz (KH) instability evolution, performed on the OMEGA-60 laser facility. Experimental radiographs show that the initial seed perturbations in the experiment are of multimode spectrum with a dominant single-mode of 16 μm wavelength. In single-mode-dominated KH instability flows, the mixing zone (MZ) width saturates to a constant value comparable to the wavelength. However, the experimental MZ width at late times has exceeded 100 μm, an order of magnitude larger. In this work, we use numerical simulations and a statistical model in order to investigate the vortex dynamics of the KHmore » instability for the experimental initial spectrum. Here, we conclude that the KH instability evolution in the experiment is dominated by multimode, vortex-merger dynamics, overcoming the dominant initial mode.« less

Restricted Modal Analysis Applied to Internal Annular Combustor Autospectra and Cross-Spectra Measurements

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2007-01-01

A treatment of the modal decomposition of the pressure field in a combustor as determined by two pressure time history measurements is developed herein. It is applied to a Pratt and Whitney PW4098 engine combustor over a range of operating conditions. For modes other than the plane wave the assumption is made that there are distinct frequency bands in which the individual modes, including the plane wave mode, overlap such that if circumferential mode m and circumferential mode m-1 are present then circumferential mode m-2 is not. In the analysis used herein at frequencies above the first cutoff mode frequency, only pairs of circumferential modes are individually present at each frequency. Consequently, this is a restricted modal analysis. As part of the analysis one specifies mode cut-on frequencies. This creates a set of frequencies that each mode spans. One finding was the successful use of the same modal span frequencies over a range of operating conditions for this particular engine. This suggests that for this case the cut-on frequencies are in proximity at each operating condition. Consequently, the combustion noise spectrum related to the circumferential modes might not change much with operating condition.

Nonperturbative Treatment of non-Markovian Dynamics of Open Quantum Systems

NASA Astrophysics Data System (ADS)

Tamascelli, D.; Smirne, A.; Huelga, S. F.; Plenio, M. B.

2018-01-01

We identify the conditions that guarantee equivalence of the reduced dynamics of an open quantum system (OQS) for two different types of environments—one a continuous bosonic environment leading to a unitary system-environment evolution and the other a discrete-mode bosonic environment resulting in a system-mode (nonunitary) Lindbladian evolution. Assuming initial Gaussian states for the environments, we prove that the two OQS dynamics are equivalent if both the expectation values and two-time correlation functions of the environmental interaction operators are the same at all times for the two configurations. Since the numerical and analytical description of a discrete-mode environment undergoing a Lindbladian evolution is significantly more efficient than that of a continuous bosonic environment in a unitary evolution, our result represents a powerful, nonperturbative tool to describe complex and possibly highly non-Markovian dynamics. As a special application, we recover and generalize the well-known pseudomodes approach to open-system dynamics.

Texture evolution and their effects on the mechanical properties of duplex Mg-Li alloy

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

Zou, Yun; Zhang, Lehao; Wang, Hongtao

Texture evolution is strongly dependent on the deformation mode during thermo-mechanical treatments. In this paper, we report the texture evolution in a duplex Mg-Li alloy. The results provide an evidence of deformation mode transition in the hexagonal-close-packed (hcp) alpha phase with various thickness reductions. The activation sequence of deformation modes is basal slip first, and then pyramidal slip during hot-rolling to a thickness reduction of 40%. The relative activity of slip decreases with further thickness reduction. After annealing, basal texture is strengthened and pyramidal component disappears due to static recrystallization and grain growth. The microstructure, specifically texture evolution in bothmore » hcp alpha and body-centered cubic (bcc) beta phase and their effects on mechanical properties are quantitatively analyzed and assessed. (C) 2016 Elsevier B.V. All rights reserved.« less

Texture evolution and their effects on the mechanical properties of duplex Mg-Li alloy

DOE PAGES

Zou, Yun; Zhang, Lehao; Wang, Hongtao; ...

2016-01-27

Texture evolution is strongly dependent on the deformation mode during thermo-mechanical treatments. In this paper, we report the texture evolution in a duplex Mg-Li alloy. The results provide an evidence of deformation mode transition in the hexagonal-close-packed (hcp) alpha phase with various thickness reductions. The activation sequence of deformation modes is basal slip first, and then pyramidal slip during hot-rolling to a thickness reduction of 40%. The relative activity of slip decreases with further thickness reduction. After annealing, basal texture is strengthened and pyramidal component disappears due to static recrystallization and grain growth. The microstructure, specifically texture evolution in bothmore » hcp alpha and body-centered cubic (bcc) beta phase and their effects on mechanical properties are quantitatively analyzed and assessed. (C) 2016 Elsevier B.V. All rights reserved.« less

Non-modal analysis of the diocotron instability: Cylindrical geometry

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

Mikhailenko, V. V.; Lee, Hae June; Mikhailenko, V. S.

2013-04-15

The temporal evolution of the linear diocotron instability of the cylindrical annular plasma column is investigated by employing the extension of the shearing modes methodology to the cylindrical geometry. It was obtained that the spatial time-dependent distortion of the electron density initial perturbations by shear flows leads to the non-modal evolution of the potential, which was referred to as the manifestation of the continuous spectrum. The evolution process leads toward the convergence to the phase-locking configuration of the mutually growing normal modes.

A neural network-based method for spectral distortion correction in photon counting x-ray CT

NASA Astrophysics Data System (ADS)

Touch, Mengheng; Clark, Darin P.; Barber, William; Badea, Cristian T.

2016-08-01

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables both 4 energy bins acquisition, as well as full-spectrum mode in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical effects in the detector and can be very noisy due to photon starvation in narrow energy bins. To address spectral distortions, we propose and demonstrate a novel artificial neural network (ANN)-based spectral distortion correction mechanism, which learns to undo the distortion in spectral CT, resulting in improved material decomposition accuracy. To address noise, post-reconstruction denoising based on bilateral filtration, which jointly enforces intensity gradient sparsity between spectral samples, is used to further improve the robustness of ANN training and material decomposition accuracy. Our ANN-based distortion correction method is calibrated using 3D-printed phantoms and a model of our spectral CT system. To enable realistic simulations and validation of our method, we first modeled the spectral distortions using experimental data acquired from 109Cd and 133Ba radioactive sources measured with our PCXD. Next, we trained an ANN to learn the relationship between the distorted spectral CT projections and the ideal, distortion-free projections in a calibration step. This required knowledge of the ground truth, distortion-free spectral CT projections, which were obtained by simulating a spectral CT scan of the digital version of a 3D-printed phantom. Once the training was completed, the trained ANN was used to perform distortion correction on any subsequent scans of the same system with the same parameters. We used joint bilateral filtration to perform noise reduction by jointly enforcing intensity gradient sparsity between the reconstructed images for each energy bin. Following reconstruction and denoising, the CT data was spectrally decomposed using the photoelectric effect, Compton scattering, and a K-edge material (i.e. iodine). The ANN-based distortion correction approach was tested using both simulations and experimental data acquired in phantoms and a mouse with our PCXD-based micro-CT system for 4 bins and full-spectrum acquisition modes. The iodine detectability and decomposition accuracy were assessed using the contrast-to-noise ratio and relative error in iodine concentration estimation metrics in images with and without distortion correction. In simulation, the material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with 50% and 20% reductions in material concentration measurement error in full-spectrum and 4 energy bins cases, respectively. Overall, experimental data confirms that full-spectrum mode provides superior results to 4-energy mode when the distortion corrections are applied. The material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with as much as a 41% reduction in material concentration measurement error for full-spectrum mode, while also bringing the iodine detectability to 4-6 mg ml-1. Distortion correction also improved the 4 bins mode data, but to a lesser extent. The results demonstrate the experimental feasibility and potential advantages of ANN-based distortion correction and joint bilateral filtration-based denoising for accurate K-edge imaging with a PCXD. Given the computational efficiency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.

Cell-selfish modes of evolution and mutations directed after transcriptional bypass.

PubMed

Holmquist, Gerald P

2002-12-29

During transcription, prokaryotic and eukaryotic RNA polymerases bypass and misread (transcriptional mutagenesis) several classes of DNA lesions. For example, misreading of 8-OH-dG generates mRNAs containing G to T transversions. After translation, if the mutant protein briefly allowed the cell a growth-DNA replication advantage, then precocious DNA replication would bypass that unrepaired 8-OH-dG and misinsert dA opposite the directing DNA lesion with a higher probability than would be experienced for 8-OH-G lesions at other positions in otherwise identical neighboring cells. Such retromutations would have been tested for their imparted growth advantage as mRNA before they became heritable DNA mutations. The logical properties of a mode of evolution that utilizes directed-retromutagenesis were compared one by one with those of the standard neo-Darwinian mode. The retromutagenesis mode, while minimizing mutational load, is cell-selfish; fitness is for an immediate growth advantage rather than future reproductive potential. In prokaryotes, an evolutionary mode that involves standard Darwinian fitness testing of novel alleles in the genetic background of origin followed by clonal expansion also favors cell-selfish allele combinations when linkage disequilibrium is practiced. For metazoa and plants to have evolved organized tissues, cell-selfish modes of evolution represent systems-poisons that must be totally suppressed. The feedback loops that allow evolution to be cell-serving in prokaryotes are actively blocked in eukaryotes by traits that restrict fitness to future reproductive potential. These traits include (i) delay of fitness testing until after the mutation is made permanently heritable, (ii) diploidy to further delay fitness testing, (iii) segregation of somatic lines from germ lines, (iv) testing of novel alleles against randomized allele combinations constructed by obligate sex, and (v) obligate genetic death to insure that that the most basic systems unit of selfish allele combinatorial uniqueness is the species instead of the cell. The analyses indicate that modes of evolution in addition to our neo-Darwinian one could have existed utilizing known molecular mechanisms. The evolution of multicellularity was as much the discarding of old cell-selfish habits as the acquisition of new altruistic ones.

Diversity of moderate El Niño events evolution: role of air-sea interactions in the eastern tropical Pacific

NASA Astrophysics Data System (ADS)

Dewitte, Boris; Takahashi, Ken

2017-12-01

In this paper we investigate the evolution of moderate El Niño events during their developing phase with the objective to understand why some of them did not evolve as extreme events despite favourable conditions for the non-linear amplification of the Bjerknes feedback (i.e. warm SST in Austral winter in the eastern equatorial Pacific). Among the moderate events, two classes are considered consisting in the Eastern Pacific (EP) El Niño events and Central Pacific (CP) events. We first show that the observed SST variability across moderate El Niño events (i.e. inter-event variability) is largest in the far eastern Pacific (east of 130°W) in the Austral winter prior to their peak, which is associated to either significant warm anomaly (moderate EP El Niño) or an anomaly between weak warm and cold (moderate CP El Niño) as reveals by the EOF analysis of the SST anomaly evolution during the development phase of El Niño across the El Niño years. Singular value decomposition (SVD) analysis of SST and wind stress anomalies across the El Niño years further indicates that the inter-event SST variability is associated with an air-sea mode explaining 31% of the covariance between SST and wind stress. The associated SST pattern consists in SST anomalies developing along the coast of Ecuador in Austral fall and expanding westward as far as 130°W in Austral winter. The associated wind stress pattern features westerlies (easterlies) west of 130°W along the equator peaking around June-August for EP (CP) El Niño events. This air-sea mode is interpreted as resulting from a developing seasonal Bjerknes feedback for EP El Niño events since it is shown to be associated to a Kelvin wave response at its peak phase. However equatorial easterlies east of 130°W emerge in September that counters the growing SST anomalies associated to the air-sea mode. These have been particularly active during both the 1972 and the 2015 El Niño events. It is shown that the easterlies are connected to an off-equatorial southerly wind off the coast of Peru and Ecuador. The southerly wind is a response to the coastal SST anomalies off Peru developing from Austral fall. Implications of our results for the understanding of the seasonal ENSO dynamics and diversity are discussed in the light of the analysis of two global climate models simulating realistically ENSO diversity (GFDL_CM2.1 and CESM).

Durability of Polymeric Encapsulation Materials for a PMMA/glass Concentrator Photovoltaic System

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

Miller, David C.; Kempe, Michael D.; Muller, Matthew T

2014-04-08

The durability of polymeric encapsulation materials was examined using outdoor exposure at the nominal geometric concentration of 500 suns. The results for 36 months cumulative field deployment are presented for materials including: poly(ethylene-co-vinyl acetate), (EVA); polyvinyl butyral (PVB); ionomer; polyethylene/ polyoctene copolymer (PO); thermoplastic polyurethane (TPU); poly(dimethylsiloxane) (PDMS); poly(diphenyl dimethyl siloxane) (PDPDMS); and poly(phenyl-methyl siloxane) (PPMS). Measurements of the field conditions including ambient temperature and ultraviolet (UV) dose were recorded at the test site during the experiment. Measurements for the experiment included optical transmittance (with subsequent analysis of solar-weighted transmittance, UV cut-off wavelength, and yellowness index), mass, visual photography, photoelasticmore » imaging, and fluorescence spectroscopy. While the results to date for EVA are presented and discussed, examination here focuses more on the siloxane materials. A specimen recently observed to fail by thermal decomposition is discussed in terms of the implementation of the experiment as well as its fluorescence signature, which was observed to become more pronounced with age. Modulated thermogravimetry (allowing determination of the activation energy of thermal decomposition) was performed on a subset of the siloxanes to quantify the propensity for decomposition at elevated temperatures. Supplemental, Pt-catalyst- and primer-solutions as well as peroxide-cured PDMS specimens were examined to assess the source of the luminescence. The results of the study including the change in optical transmittance, observed failure modes, and subsequent analyses of the failure modes are described in the conclusions.« less

Fault feature analysis of cracked gear based on LOD and analytical-FE method

NASA Astrophysics Data System (ADS)

Wu, Jiateng; Yang, Yu; Yang, Xingkai; Cheng, Junsheng

2018-01-01

At present, there are two main ideas for gear fault diagnosis. One is the model-based gear dynamic analysis; the other is signal-based gear vibration diagnosis. In this paper, a method for fault feature analysis of gear crack is presented, which combines the advantages of dynamic modeling and signal processing. Firstly, a new time-frequency analysis method called local oscillatory-characteristic decomposition (LOD) is proposed, which has the attractive feature of extracting fault characteristic efficiently and accurately. Secondly, an analytical-finite element (analytical-FE) method which is called assist-stress intensity factor (assist-SIF) gear contact model, is put forward to calculate the time-varying mesh stiffness (TVMS) under different crack states. Based on the dynamic model of the gear system with 6 degrees of freedom, the dynamic simulation response was obtained for different tooth crack depths. For the dynamic model, the corresponding relation between the characteristic parameters and the degree of the tooth crack is established under a specific condition. On the basis of the methods mentioned above, a novel gear tooth root crack diagnosis method which combines the LOD with the analytical-FE is proposed. Furthermore, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) are contrasted with the LOD by gear crack fault vibration signals. The analysis results indicate that the proposed method performs effectively and feasibility for the tooth crack stiffness calculation and the gear tooth crack fault diagnosis.

Comparison of methods for extracting annual cycle with changing amplitude in climate science

NASA Astrophysics Data System (ADS)

Deng, Q.; Fu, Z.

2017-12-01

Changes of annual cycle gains a growing concern recently. The basic hypothesis regards annual cycle as constant. Climatology mean within a time period is usually used to depict the annual cycle. Obviously this hypothesis contradicts with the fact that annual cycle is changing every year. For the lack of a unified definition about annual cycle, the approaches adopted in extracting annual cycle are various and may lead to different results. The precision and validity of these methods need to be examined. In this work we numerical experiments with known monofrequent annual cycle are set to evaluate five popular extracting methods: fitting sinusoids, complex demodulation, Ensemble Empirical Mode Decomposition (EEMD), Nonlinear Mode Decomposition (NMD) and Seasonal trend decomposition procedure based on loess (STL). Three different types of changing amplitude will be generated: steady, linear increasing and nonlinearly varying. Comparing the annual cycle extracted by these methods with the generated annual cycle, we find that (1) NMD performs best in depicting annual cycle itself and its amplitude change, (2) fitting sinusoids, complex demodulation and EEMD methods are more sensitive to long-term memory(LTM) of generated time series thus lead to overfitting annual cycle and too noisy amplitude, oppositely the result of STL underestimate the amplitude variation (3)all of them can present the amplitude trend correctly in long-time scale but the errors on account of noise and LTM are common in some methods over short time scales.

Durability of polymeric encapsulation materials in a PMMA/glass concentrator photovoltaic system

DOE PAGES

Miller, David C.; Kempe, Michael D.; Muller, Matthew T.; ...

2016-07-13

We examined the durability of polymeric encapsulation materials using outdoor exposure at the nominal geometric concentration of 500 suns. The results for 36-month cumulative field deployment are presented for materials including: poly(ethylene-co-vinyl acetate), (EVA); polyvinyl butyral (PVB); ionomer; polyethylene/polyoctene copolymer (PO); thermoplastic polyurethane (TPU); poly(dimethylsiloxane) (PDMS); poly(diphenyl dimethyl siloxane) (PDPDMS); and poly(phenyl-methyl siloxane) (PPMS). Measurements of the field conditions including ambient temperature and ultraviolet (UV) dose were recorded at the test site during the experiment. Our measurements for the experiment included optical transmittance (with subsequent analysis of solar-weighted transmittance, UV cut-off wavelength, and yellowness index), mass, visual photography, photoelastic imaging,more » and fluorescence spectroscopy. While the results to date for EVA are presented and discussed, examination here focuses more on the siloxane materials. A specimen recently observed to fail by thermal decomposition is discussed in terms of the implementation of the experiment as well as its fluorescence signature, which was observed to become more pronounced with age. Modulated thermogravimetry (allowing determination of the activation energy of thermal decomposition) was performed on a subset of the siloxanes to quantify the propensity for decomposition at elevated temperatures. Supplemental, Pt-catalyst- and primer-solutions as well as peroxide-cured PDMS specimens were examined to assess the source of the luminescence. Furthermore, our results, including the change in optical transmittance, observed failure modes, and subsequent analyses of the failure modes are described in the conclusions.« less

Restricted Acoustic Modal Analysis Applied to Internal Combustor Spectra and Cross-Spectra Measurements

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2006-01-01

A treatment of the modal decomposition of the pressure field in a combustor as determined by two Kulite pressure measurements is developed herein. It is applied to a Pratt & Whitney PW4098 engine combustor over a range of operating conditions. For modes other than the plane wave the new part of the treatment is the assumption that there are distinct frequency bands in which the individual modes, including the plane wave mode, overlap such that if circumferential mode m and circumferential mode m-1 are present than circumferential mode m 2 is not. Consequently, in the analysis used herein at frequencies above the first cut-off mode frequency, only pairs of circumferential modes are individually present at each frequency. Consequently, this is a restricted modal analysis. A new result is that the successful use of the same modal span frequencies over a range of operating conditions for this particular engine suggests that the temperature, T, and the velocity, v, of the flow at each operating condition are related by c(sup 2)-v(sup 2) = a constant where c is the speed of sound.

COMPRESSIBLE RELATIVISTIC MAGNETOHYDRODYNAMIC TURBULENCE IN MAGNETICALLY DOMINATED PLASMAS AND IMPLICATIONS FOR A STRONG-COUPLING REGIME

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

Takamoto, Makoto; Lazarian, Alexandre, E-mail: mtakamoto@eps.s.u-tokyo.ac.jp, E-mail: alazarian@facstaff.wisc.edu

2016-11-10

In this Letter, we report compressible mode effects on relativistic magnetohydrodynamic (RMHD) turbulence in Poynting-dominated plasmas using three-dimensional numerical simulations. We decomposed fluctuations in the turbulence into 3 MHD modes (fast, slow, and Alfvén) following the procedure of mode decomposition in Cho and Lazarian, and analyzed their energy spectra and structure functions separately. We also analyzed the ratio of compressible mode to Alfvén mode energy with respect to its Mach number. We found the ratio of compressible mode increases not only with the Alfvén Mach number, but also with the background magnetization, which indicates a strong coupling between the fastmore » and Alfvén modes. It also signifies the appearance of a new regime of RMHD turbulence in Poynting-dominated plasmas where the fast and Alfvén modes are strongly coupled and, unlike the non-relativistic MHD regime, cannot be treated separately. This finding will affect particle acceleration efficiency obtained by assuming Alfvénic critical-balance turbulence and can change the resulting photon spectra emitted by non-thermal electrons.« less

Synthesis and catalytic activity of the metastable phase of gold phosphide

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

Fernando, Deshani; Nigro, Toni A.E.; Dyer, I.D.

Recently, transition metal phosphides have found new applications as catalysts for the hydrogen evolution reaction that has generated an impetus to synthesize these materials at the nanoscale. In this work, Au{sub 2}P{sub 3} was synthesized utilizing the high temperature decomposition of tri-n-octylphosphine as a source of elemental phosphorous. Gold nanorods were used as morphological templates with the aim of controlling the shape and size of the resulting gold phosphide particles. We demonstrate that the surface capping ligand of the gold nanoparticle precursors can influence the purity and extent to which the gold phosphide phase will form. Gold nanorods functionalized withmore » 1-dodecanethiol undergo digestive ripening to produce discrete spherical particles that exhibit reduced reactivity towards phosphorous, resulting in low yields of the gold phosphide. In contrast, gold phosphide was obtained as a phase pure product when cetyltrimethylammonium bromide functionalized gold nanorods are used instead. The Au{sub 2}P{sub 3} nanoparticles exhibited higher activity than polycrystalline gold towards the hydrogen evolution reaction. - Graphical abstract: Au{sub 2}P{sub 3} was synthesized utilizing the high temperature decomposition of tri-n-octylphosphine as a source of elemental phosphorous and gold nanoparticles as reactants. We demonstrate that the surface capping ligand of the gold nanoparticle precursors influence the purity and extent to which the Au{sub 2}P{sub 3} phase will form. Gold nanorods functionalized with 1-dodecanethiol undergo digestive ripening to produce discrete spherical particles that exhibit reduced reactivity towards phosphorous, resulting in low yields of the gold phosphide. In contrast, gold phosphide was obtained as a phase pure product when cetyltrimethylammonium bromide functionalized gold nanoparticles are used instead. The Au{sub 2}P{sub 3} nanoparticles exhibited higher activity than polycrystalline gold towards the hydrogen evolution reaction. - Highlights: • The surface chemistry of gold affects the synthetic yields of Au{sub 2}P{sub 3}. • Imaging of Au{sub 2}P{sub 3} with transmission electron microscopy results in decomposition. • Au{sub 2}P{sub 3} nanoparticles exhibit activity towards the hydrogen evolution reaction.« less

A new EEMD-based scheme for detection of insect damaged wheat kernels using impact acoustics

USDA-ARS?s Scientific Manuscript database

Internally feeding insects inside wheat kernels cause significant, but unseen economic damage to stored grain. In this paper, a new scheme based on ensemble empirical mode decomposition (EEMD) using impact acoustics is proposed for detection of insect-damaged wheat kernels, based on its capability t...

Acceleration Response Mode Decomposition for Quantifying Wave Impact Load in High-Speed Planing Craft

DTIC Science & Technology

2014-04-01

Chicago , San Francisco, 1996 6. Savitsky, Daniel and Brown, P.W., “Procedures for Hydrodynamic Evaluation of Planing Hulls in Smooth and Rough Water...20593-7356 Attn: David Shepard United States Coast Guard RDT&E Division 2100 Second Street, SW STOP 7111 Washington, DC 20593-7111 Attn: Frank

Seismic facies analysis based on self-organizing map and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Du, Hao-kun; Cao, Jun-xing; Xue, Ya-juan; Wang, Xing-jian

2015-01-01

Seismic facies analysis plays an important role in seismic interpretation and reservoir model building by offering an effective way to identify the changes in geofacies inter wells. The selections of input seismic attributes and their time window have an obvious effect on the validity of classification and require iterative experimentation and prior knowledge. In general, it is sensitive to noise when waveform serves as the input data to cluster analysis, especially with a narrow window. To conquer this limitation, the Empirical Mode Decomposition (EMD) method is introduced into waveform classification based on SOM. We first de-noise the seismic data using EMD and then cluster the data using 1D grid SOM. The main advantages of this method are resolution enhancement and noise reduction. 3D seismic data from the western Sichuan basin, China, are collected for validation. The application results show that seismic facies analysis can be improved and better help the interpretation. The powerful tolerance for noise makes the proposed method to be a better seismic facies analysis tool than classical 1D grid SOM method, especially for waveform cluster with a narrow window.

Structural modal parameter identification using local mean decomposition

NASA Astrophysics Data System (ADS)

Keyhani, Ali; Mohammadi, Saeed

2018-02-01

Modal parameter identification is the first step in structural health monitoring of existing structures. Already, many powerful methods have been proposed for this concept and each method has some benefits and shortcomings. In this study, a new method based on local mean decomposition is proposed for modal identification of civil structures from free or ambient vibration measurements. The ability of the proposed method was investigated using some numerical studies and the results compared with those obtained from the Hilbert-Huang transform (HHT). As a major advantage, the proposed method can extract natural frequencies and damping ratios of all active modes from only one measurement. The accuracy of the identified modes depends on their participation in the measured responses. Nevertheless, the identified natural frequencies have reasonable accuracy in both cases of free and ambient vibration measurements, even in the presence of noise. The instantaneous phase angle and the natural logarithm of instantaneous amplitude curves obtained from the proposed method have more linearity rather than those from the HHT algorithm. Also, the end effect is more restricted for the proposed method.

Prediction of S-wave velocity using complete ensemble empirical mode decomposition and neural networks

NASA Astrophysics Data System (ADS)

Gaci, Said; Hachay, Olga; Zaourar, Naima

2017-04-01

One of the key elements in hydrocarbon reservoirs characterization is the S-wave velocity (Vs). Since the traditional estimating methods often fail to accurately predict this physical parameter, a new approach that takes into account its non-stationary and non-linear properties is needed. In this view, a prediction model based on complete ensemble empirical mode decomposition (CEEMD) and a multiple layer perceptron artificial neural network (MLP ANN) is suggested to compute Vs from P-wave velocity (Vp). Using a fine-to-coarse reconstruction algorithm based on CEEMD, the Vp log data is decomposed into a high frequency (HF) component, a low frequency (LF) component and a trend component. Then, different combinations of these components are used as inputs of the MLP ANN algorithm for estimating Vs log. Applications on well logs taken from different geological settings illustrate that the predicted Vs values using MLP ANN with the combinations of HF, LF and trend in inputs are more accurate than those obtained with the traditional estimating methods. Keywords: S-wave velocity, CEEMD, multilayer perceptron neural networks.

Geometric decompositions of collective motion

NASA Astrophysics Data System (ADS)

Mischiati, Matteo; Krishnaprasad, P. S.

2017-04-01

Collective motion in nature is a captivating phenomenon. Revealing the underlying mechanisms, which are of biological and theoretical interest, will require empirical data, modelling and analysis techniques. Here, we contribute a geometric viewpoint, yielding a novel method of analysing movement. Snapshots of collective motion are portrayed as tangent vectors on configuration space, with length determined by the total kinetic energy. Using the geometry of fibre bundles and connections, this portrait is split into orthogonal components each tangential to a lower dimensional manifold derived from configuration space. The resulting decomposition, when interleaved with classical shape space construction, is categorized into a family of kinematic modes-including rigid translations, rigid rotations, inertia tensor transformations, expansions and compressions. Snapshots of empirical data from natural collectives can be allocated to these modes and weighted by fractions of total kinetic energy. Such quantitative measures can provide insight into the variation of the driving goals of a collective, as illustrated by applying these methods to a publicly available dataset of pigeon flocking. The geometric framework may also be profitably employed in the control of artificial systems of interacting agents such as robots.

Changes in the Amplitude and Phase of the Annual Cycle: quantifying from surface wind series in China

NASA Astrophysics Data System (ADS)

Feng, Tao

2013-04-01

Climate change is not only reflected in the changes in annual means of climate variables but also in the changes in their annual cycles (seasonality), especially in the regions outside the tropics. Changes in the timing of seasons, especially the wind season, have gained much attention worldwide in recent decade or so. We introduce long-range correlated surrogate data to Ensemble Empirical Mode Decomposition method, which represent the statistic characteristics of data better than white noise. The new method we named Ensemble Empirical Mode Decomposition with Long-range Correlated noise (EEMD-LRC) and applied to 600 station wind speed records. This new method is applied to investigate the trend in the amplitude of the annual cycle of China's daily mean surface wind speed for the period 1971-2005. The amplitude of seasonal variation decrease significantly in the past half century over China, which can be well explained by Annual Cycle component from EEMD-LRC. Furthermore, the phase change of annual cycle lead to strongly shorten of wind season in spring, and corresponding with strong windy day frequency change over Northern China.

A low dimensional dynamical system for the wall layer

NASA Technical Reports Server (NTRS)

Aubry, N.; Keefe, L. R.

1987-01-01

Low dimensional dynamical systems which model a fully developed turbulent wall layer were derived.The model is based on the optimally fast convergent proper orthogonal decomposition, or Karhunen-Loeve expansion. This decomposition provides a set of eigenfunctions which are derived from the autocorrelation tensor at zero time lag. Via Galerkin projection, low dimensional sets of ordinary differential equations in time, for the coefficients of the expansion, were derived from the Navier-Stokes equations. The energy loss to the unresolved modes was modeled by an eddy viscosity representation, analogous to Heisenberg's spectral model. A set of eigenfunctions and eigenvalues were obtained from direct numerical simulation of a plane channel at a Reynolds number of 6600, based on the mean centerline velocity and the channel width flow and compared with previous work done by Herzog. Using the new eigenvalues and eigenfunctions, a new ten dimensional set of ordinary differential equations were derived using five non-zero cross-stream Fourier modes with a periodic length of 377 wall units. The dynamical system was integrated for a range of the eddy viscosity prameter alpha. This work is encouraging.

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview

NASA Astrophysics Data System (ADS)

Han, G.; Lin, B.; Xu, Z.

2017-03-01

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

PubMed

Ferdinando, Hany; Seppanen, Tapio; Alasaarela, Esko

2017-07-01

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.

Cost decomposition of linear systems with application to model reduction

NASA Technical Reports Server (NTRS)

Skelton, R. E.

1980-01-01

A means is provided to assess the value or 'cst' of each component of a large scale system, when the total cost is a quadratic function. Such a 'cost decomposition' of the system has several important uses. When the components represent physical subsystems which can fail, the 'component cost' is useful in failure mode analysis. When the components represent mathematical equations which may be truncated, the 'component cost' becomes a criterion for model truncation. In this latter event component costs provide a mechanism by which the specific control objectives dictate which components should be retained in the model reduction process. This information can be valuable in model reduction and decentralized control problems.

Hybrid empirical mode decomposition- ARIMA for forecasting exchange rates

NASA Astrophysics Data System (ADS)

Abadan, Siti Sarah; Shabri, Ani; Ismail, Shuhaida

2015-02-01

This paper studied the forecasting of monthly Malaysian Ringgit (MYR)/ United State Dollar (USD) exchange rates using the hybrid of two methods which are the empirical model decomposition (EMD) and the autoregressive integrated moving average (ARIMA). MYR is pegged to USD during the Asian financial crisis causing the exchange rates are fixed to 3.800 from 2nd of September 1998 until 21st of July 2005. Thus, the chosen data in this paper is the post-July 2005 data, starting from August 2005 to July 2010. The comparative study using root mean square error (RMSE) and mean absolute error (MAE) showed that the EMD-ARIMA outperformed the single-ARIMA and the random walk benchmark model.

Galerkin-collocation domain decomposition method for arbitrary binary black holes

NASA Astrophysics Data System (ADS)

Barreto, W.; Clemente, P. C. M.; de Oliveira, H. P.; Rodriguez-Mueller, B.

2018-05-01

We present a new computational framework for the Galerkin-collocation method for double domain in the context of ADM 3 +1 approach in numerical relativity. This work enables us to perform high resolution calculations for initial sets of two arbitrary black holes. We use the Bowen-York method for binary systems and the puncture method to solve the Hamiltonian constraint. The nonlinear numerical code solves the set of equations for the spectral modes using the standard Newton-Raphson method, LU decomposition and Gaussian quadratures. We show convergence of our code for the conformal factor and the ADM mass. Thus, we display features of the conformal factor for different masses, spins and linear momenta.

Mechanistic and Kinetic Analysis of Na2SO4-Modified Laterite Decomposition by Thermogravimetry Coupled with Mass Spectrometry

PubMed Central

Yang, Song; Du, Wenguang; Shi, Pengzheng; Shangguan, Ju; Liu, Shoujun; Zhou, Changhai; Chen, Peng; Zhang, Qian; Fan, Huiling

2016-01-01

Nickel laterites cannot be effectively used in physical methods because of their poor crystallinity and fine grain size. Na2SO4 is the most efficient additive for grade enrichment and Ni recovery. However, how Na2SO4 affects the selective reduction of laterite ores has not been clearly investigated. This study investigated the decomposition of laterite with and without the addition of Na2SO4 in an argon atmosphere using thermogravimetry coupled with mass spectrometry (TG-MS). Approximately 25 mg of samples with 20 wt% Na2SO4 was pyrolyzed under a 100 ml/min Ar flow at a heating rate of 10°C/min from room temperature to 1300°C. The kinetic study was based on derivative thermogravimetric (DTG) curves. The evolution of the pyrolysis gas composition was detected by mass spectrometry, and the decomposition products were analyzed by X-ray diffraction (XRD). The decomposition behavior of laterite with the addition of Na2SO4 was similar to that of pure laterite below 800°C during the first three stages. However, in the fourth stage, the dolomite decomposed at 897°C, which is approximately 200°C lower than the decomposition of pure laterite. In the last stage, the laterite decomposed and emitted SO2 in the presence of Na2SO4 with an activation energy of 91.37 kJ/mol. The decomposition of laterite with and without the addition of Na2SO4 can be described by one first-order reaction. Moreover, the use of Na2SO4 as the modification agent can reduce the activation energy of laterite decomposition; thus, the reaction rate can be accelerated, and the reaction temperature can be markedly reduced. PMID:27333072

A review of plutonium oxalate decomposition reactions and effects of decomposition temperature on the surface area of the plutonium dioxide product

NASA Astrophysics Data System (ADS)

Orr, R. M.; Sims, H. E.; Taylor, R. J.

2015-10-01

Plutonium (IV) and (III) ions in nitric acid solution readily form insoluble precipitates with oxalic acid. The plutonium oxalates are then easily thermally decomposed to form plutonium dioxide powder. This simple process forms the basis of current industrial conversion or 'finishing' processes that are used in commercial scale reprocessing plants. It is also widely used in analytical or laboratory scale operations and for waste residues treatment. However, the mechanisms of the thermal decompositions in both air and inert atmospheres have been the subject of various studies over several decades. The nature of intermediate phases is of fundamental interest whilst understanding the evolution of gases at different temperatures is relevant to process control. The thermal decomposition is also used to control a number of powder properties of the PuO2 product that are important to either long term storage or mixed oxide fuel manufacturing. These properties are the surface area, residual carbon impurities and adsorbed volatile species whereas the morphology and particle size distribution are functions of the precipitation process. Available data and experience regarding the thermal and radiation-induced decompositions of plutonium oxalate to oxide are reviewed. The mechanisms of the thermal decompositions are considered with a particular focus on the likely redox chemistry involved. Also, whilst it is well known that the surface area is dependent on calcination temperature, there is a wide variation in the published data and so new correlations have been derived. Better understanding of plutonium (III) and (IV) oxalate decompositions will assist the development of more proliferation resistant actinide co-conversion processes that are needed for advanced reprocessing in future closed nuclear fuel cycles.

An equivalent domain integral method for three-dimensional mixed-mode fracture problems

NASA Technical Reports Server (NTRS)

Shivakumar, K. N.; Raju, I. S.

1991-01-01

A general formulation of the equivalent domain integral (EDI) method for mixed mode fracture problems in cracked solids is presented. The method is discussed in the context of a 3-D finite element analysis. The J integral consists of two parts: the volume integral of the crack front potential over a torus enclosing the crack front and the crack surface integral due to the crack front potential plus the crack face loading. In mixed mode crack problems the total J integral is split into J sub I, J sub II, and J sub III representing the severity of the crack front in three modes of deformations. The direct and decomposition methods are used to separate the modes. These two methods were applied to several mixed mode fracture problems, were analyzed, and results were found to agree well with those available in the literature. The method lends itself to be used as a post-processing subroutine in a general purpose finite element program.

An equivalent domain integral method for three-dimensional mixed-mode fracture problems

NASA Technical Reports Server (NTRS)

Shivakumar, K. N.; Raju, I. S.

1992-01-01

A general formulation of the equivalent domain integral (EDI) method for mixed mode fracture problems in cracked solids is presented. The method is discussed in the context of a 3-D finite element analysis. The J integral consists of two parts: the volume integral of the crack front potential over a torus enclosing the crack front and the crack surface integral due to the crack front potential plus the crack face loading. In mixed mode crack problems the total J integral is split into J sub I, J sub II, and J sub III representing the severity of the crack front in three modes of deformations. The direct and decomposition methods are used to separate the modes. These two methods were applied to several mixed mode fracture problems, were analyzed, and results were found to agree well with those available in the literature. The method lends itself to be used as a post-processing subroutine in a general purpose finite element program.

A method to identify the main mode of machine tool under operating conditions

NASA Astrophysics Data System (ADS)

Wang, Daming; Pan, Yabing

2017-04-01

The identification of the modal parameters under experimental conditions is the most common procedure when solving the problem of machine tool structure vibration. However, the influence of each mode on the machine tool vibration in real working conditions remains unknown. In fact, the contributions each mode makes to the machine tool vibration during machining process are different. In this article, an active excitation modal analysis is applied to identify the modal parameters in operational condition, and the Operating Deflection Shapes (ODS) in frequencies of high level vibration that affect the quality of machining in real working conditions are obtained. Then, the ODS is decomposed by the mode shapes which are identified in operational conditions. So, the contributions each mode makes to machine tool vibration during machining process are got by decomposition coefficients. From the previous steps, we can find out the main modes which effect the machine tool more significantly in working conditions. This method was also verified to be effective by experiments.

A statistical study of atypical wave modes in the Earth's foreshock region

NASA Astrophysics Data System (ADS)

Hsieh, W.; Shue, J.; Lee, B.

2010-12-01

The Earth's foreshock, the region upstream the Earth’s bow shock, is filled with back-streaming particles and ultra-low frequency waves. Three different wave modes have been identified in the region, including 30-sec waves, 3-sec waves, and shocklets. Time History of Events and Macroscale Interactions during Substorms (THEMIS), a satellite mission that consists of five probes, provides multiple measuements of the Earth’s foreshock region. The method of Hilbert-Huang transform (HHT) includes the procedures of empirical mode decomposition and instantaneous frequency calculation. In this study, we use HHT to decompose intrinsic wave modes and perform a wave analysis of chaotic magnetic fields in the Earth's foreshock region. We find that some individual atypical wave modes other than 30-sec and 3-sec appear in the region. In this presentation, we will show the statistical characteristics, such as wave frequency, wave amplitude, and wave polarization of the atypical intrinsic wave modes, with respect to different locations in the foreshock region and to different solar wind conditions.

Decoding Mode-mixing in Black-hole Merger Ringdown

NASA Technical Reports Server (NTRS)

Kelly, Bernard J.; Baker, John G.

2013-01-01

Optimal extraction of information from gravitational-wave observations of binary black-hole coalescences requires detailed knowledge of the waveforms. Current approaches for representing waveform information are based on spin-weighted spherical harmonic decomposition. Higher-order harmonic modes carrying a few percent of the total power output near merger can supply information critical to determining intrinsic and extrinsic parameters of the binary. One obstacle to constructing a full multi-mode template of merger waveforms is the apparently complicated behavior of some of these modes; instead of settling down to a simple quasinormal frequency with decaying amplitude, some |m| = modes show periodic bumps characteristic of mode-mixing. We analyze the strongest of these modes the anomalous (3, 2) harmonic mode measured in a set of binary black-hole merger waveform simulations, and show that to leading order, they are due to a mismatch between the spherical harmonic basis used for extraction in 3D numerical relativity simulations, and the spheroidal harmonics adapted to the perturbation theory of Kerr black holes. Other causes of mode-mixing arising from gauge ambiguities and physical properties of the quasinormal ringdown modes are also considered and found to be small for the waveforms studied here.

Structure functions in decomposing CuRh systems

NASA Astrophysics Data System (ADS)

Prem, M.; Blaschko, O.; Rosta, L.

1997-02-01

The time evolution of a CuRh alloy quenched within the miscibility gap is investigated by small and wide angle neutron scattering techniques. Near fundamental Bragg reflections diffuse satellites arising from a lattice parameter modulation induced by the precipitation pattern are investigated. The results show that in CuRh the precipitation morphology and its time evolution are quite different from decomposition characteristics recently observed in the system AuPt. The results are discussed and related to the larger lattice misfit present in CuRh in comparison to AuPt.

A Signal Processing Approach with a Smooth Empirical Mode Decomposition to Reveal Hidden Trace of Corrosion in Highly Contaminated Guided Wave Signals for Concrete-Covered Pipes

PubMed Central

Rostami, Javad; Chen, Jingming; Tse, Peter W.

2017-01-01

Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves’ signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the interpretation of guided wave signals. The problem deepens if defects have irregular shapes such as natural corrosion. Signal processing techniques that have been proposed for guided wave signals’ analysis are generally good for simple signals obtained in a highly controlled experimental environment. In fact, guided wave signals in a real situation such as the existence of natural corrosion in wall-covered pipes are much more complicated. Considering pipes in residential buildings that pass through concrete walls, in this paper we introduced Smooth Empirical Mode Decomposition (SEMD) to efficiently separate overlapped guided waves. As empirical mode decomposition (EMD) which is a good candidate for analyzing non-stationary signals, suffers from some shortcomings, wavelet transform was adopted in the sifting stage of EMD to improve its outcome in SEMD. However, selection of mother wavelet that suits best for our purpose plays an important role. Since in guided wave inspection, the incident waves are well known and are usually tone-burst signals, we tailored a complex tone-burst signal to be used as our mother wavelet. In the sifting stage of EMD, wavelet de-noising was applied to eliminate unwanted frequency components from each IMF. SEMD greatly enhances the performance of EMD in guided wave analysis for highly contaminated signals. In our experiment on concrete covered pipes with natural corrosion, this method not only separates the concrete wall indication clearly in time domain signal, a natural corrosion with complex geometry that was hidden and located inside the concrete section was successfully exposed. PMID:28178220

A Signal Processing Approach with a Smooth Empirical Mode Decomposition to Reveal Hidden Trace of Corrosion in Highly Contaminated Guided Wave Signals for Concrete-Covered Pipes.

PubMed

Rostami, Javad; Chen, Jingming; Tse, Peter W

2017-02-07

Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves' signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the interpretation of guided wave signals. The problem deepens if defects have irregular shapes such as natural corrosion. Signal processing techniques that have been proposed for guided wave signals' analysis are generally good for simple signals obtained in a highly controlled experimental environment. In fact, guided wave signals in a real situation such as the existence of natural corrosion in wall-covered pipes are much more complicated. Considering pipes in residential buildings that pass through concrete walls, in this paper we introduced Smooth Empirical Mode Decomposition (SEMD) to efficiently separate overlapped guided waves. As empirical mode decomposition (EMD) which is a good candidate for analyzing non-stationary signals, suffers from some shortcomings, wavelet transform was adopted in the sifting stage of EMD to improve its outcome in SEMD. However, selection of mother wavelet that suits best for our purpose plays an important role. Since in guided wave inspection, the incident waves are well known and are usually tone-burst signals, we tailored a complex tone-burst signal to be used as our mother wavelet. In the sifting stage of EMD, wavelet de-noising was applied to eliminate unwanted frequency components from each IMF. SEMD greatly enhances the performance of EMD in guided wave analysis for highly contaminated signals. In our experiment on concrete covered pipes with natural corrosion, this method not only separates the concrete wall indication clearly in time domain signal, a natural corrosion with complex geometry that was hidden and located inside the concrete section was successfully exposed.

Health monitoring of pipeline girth weld using empirical mode decomposition

NASA Astrophysics Data System (ADS)

Rezaei, Davood; Taheri, Farid

2010-05-01

In the present paper the Hilbert-Huang transform (HHT), as a time-series analysis technique, has been combined with a local diagnostic approach in an effort to identify flaws in pipeline girth welds. This method is based on monitoring the free vibration signals of the pipe at its healthy and flawed states, and processing the signals through the HHT and its associated signal decomposition technique, known as empirical mode decomposition (EMD). The EMD method decomposes the vibration signals into a collection of intrinsic mode functions (IMFs). The deviations in structural integrity, measured from a healthy-state baseline, are subsequently evaluated by two damage sensitive parameters. The first is a damage index, referred to as the EM-EDI, which is established based on an energy comparison of the first or second IMF of the vibration signals, before and after occurrence of damage. The second parameter is the evaluation of the lag in instantaneous phase, a quantity derived from the HHT. In the developed methodologies, the pipe's free vibration is monitored by piezoceramic sensors and a laser Doppler vibrometer. The effectiveness of the proposed techniques is demonstrated through a set of numerical and experimental studies on a steel pipe with a mid-span girth weld, for both pressurized and nonpressurized conditions. To simulate a crack, a narrow notch is cut on one side of the girth weld. Several damage scenarios, including notches of different depths and at various locations on the pipe, are investigated. Results from both numerical and experimental studies reveal that in all damage cases the sensor located at the notch vicinity could successfully detect the notch and qualitatively predict its severity. The effect of internal pressure on the damage identification method is also monitored. Overall, the results are encouraging and promise the effectiveness of the proposed approaches as inexpensive systems for structural health monitoring purposes.

m=1 diocotron mode damping in the Electron Diffusion Gauge (EDG) experiment

NASA Astrophysics Data System (ADS)

Paul, Stephen F.; Morrison, Kyle A.; Davidson, Ronald C.; Jenkins, Thomas G.

2002-01-01

The evolution of the amplitude of the m=1 diocotron mode is used to measure the background neutral pressure in the Electron Diffusion Gauge (EDG), a Malmberg-Penning trap. Below 5×10-8 Torr, the dependence on pressure scales as P1/4, and is sensitive to pressure changes as small as ΔP=5×10-11 Torr. Previous studies on the EDG showed that the diocotron mode is more strongly damped at higher neutral pressures. Both the diocotron mode damping rate and the plasma expansion rate depend similarly on experimental parameters, i.e., conditions which favor expansion also favor suppression of the diocotron mode. The sensitivity of the mode evolution is examined as a function of the resistive growth driving conditions, which are controlled by the amount of wall resistance connected to the trap.