A MIXED-TIME-SCALE SGS MODEL WITH FIXED MODEL-PARAMETERS FOR PRACTICAL LES

2002 ◽  
pp. 257-266 ◽  
Author(s):  
M. Inagaki ◽  
T. Kondoh ◽  
Y. Nagano
Keyword(s):  
Time Scale ◽  
Model Parameters ◽  
Fixed Model

A Mixed-Time-Scale SGS Model With Fixed Model-Parameters for Practical LES

2005 ◽  
Vol 127 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Masahide Inagaki ◽  
Tsuguo Kondoh ◽  
Yasutaka Nagano
Keyword(s):  
Experimental Data ◽  
Time Scale ◽  
Bluff Body ◽  
Present Model ◽  
Plane Channel ◽  
Wall Turbulence ◽  
Model Parameters ◽  
Complex Flow ◽  
Smagorinsky Model ◽  
Fixed Model

A new subgrid-scale (SGS) model for practical large eddy simulation (LES) is proposed. The model is constructed with the concept of mixed time-scale, which makes it possible to use fixed model-parameters and to dispense with the distance from the wall. The model performance is tested in plane channel flows, and the results show that this model is able to account for near-wall turbulence without an explicit damping function as in the dynamic Smagorinsky model. The model is also evaluated in a backward-facing step flow and in a flow around a circular cylinder. The calculated results using the consistent model-parameters show good agreement with experimental data, while the results obtained using the dynamic Smagorinsky model show less accuracy and less computational stability. Furthermore, to confirm the validity of the present model in practical applications, the three-dimensional complex flow around a bluff body (Ahmed et al., SAE paper no. 840300) is also calculated with the model. The agreement between the calculated results and the experimental data is quite satisfactory. These results suggest that the present model is a refined SGS model suited for practical LES to compute flows in a complicated geometry.

scholarly journals An Enhanced Intrinsic Time-Scale Decomposition Method Based on Adaptive Lévy Noise and Its Application in Bearing Fault Diagnosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 617
Author(s):  
Jianpeng Ma ◽  
Shi Zhuo ◽  
Chengwei Li ◽  
Liwei Zhan ◽  
Guangzhu Zhang
Keyword(s):  
Fault Diagnosis ◽  
Time Scale ◽  
Lévy Noise ◽  
Model Parameters ◽  
Rolling Bearings ◽  
Intrinsic Time ◽  
Time Scale Decomposition ◽  
Weak Fault ◽  
Levy Noise ◽  
The Impact

When early failures in rolling bearings occur, we need to be able to extract weak fault characteristic frequencies under the influence of strong noise and then perform fault diagnosis. Therefore, a new method is proposed: complete ensemble intrinsic time-scale decomposition with adaptive Lévy noise (CEITDALN). This method solves the problem of the traditional complete ensemble intrinsic time-scale decomposition with adaptive noise (CEITDAN) method not being able to filter nonwhite noise in measured vibration signal noise. Therefore, in the method proposed in this paper, a noise model in the form of parameter-adjusted noise is used to replace traditional white noise. We used an optimization algorithm to adaptively adjust the model parameters, reducing the impact of nonwhite noise on the feature frequency extraction. The experimental results for the simulation and vibration signals of rolling bearings showed that the CEITDALN method could extract weak fault features more effectively than traditional methods.

Mutual Identifiability Analysis for Parameter Signature Isolation in the Time-Scale Plane

2008 ◽  
Author(s):  
Kourosh Danai ◽  
James R. McCusker ◽  
C. V. Hollot
Keyword(s):  
Time Scale ◽  
Prediction Error ◽  
Linear Models ◽  
Necessary Condition ◽  
Model Parameters ◽  
Identifiability Analysis ◽  
Individual Model ◽  
Model Parameter

It was shown recently that regions in the time-scale plane can be isolated wherein the prediction error can be attributed to the error of an individual model parameter. A necessary condition for this isolation capacity is the mutual (pairwise) identifiability of the model parameters. This paper presents conditions for mutual identifiability of parameters of linear models and refines these conditions for models that exhibit rank-1 dependency on the parameters.

Parameter Adaptation by Parameter Signature Isolation in the Time-Scale Domain

2008 ◽  
Author(s):  
Kourosh Danai ◽  
James R. McCusker
Keyword(s):  
Error Estimates ◽  
Time Scale ◽  
Prediction Error ◽  
Dynamic Models ◽  
Noise Suppression ◽  
Model Parameters ◽  
Isolation Method ◽  
Parameter Adaptation ◽  
Single Output ◽  
Parameter Error

It is shown that delineation of output sensitivities with respect to model parameters in dynamic models can be enhanced in the time-scale domain. This enhanced differentiation of output sensitivities then provides the capacity to isolate regions of the time-scale plane wherein a single output sensitivity dominates the others. Due to this dominance, the prediction error can be attributed to the error of a single parameter at these regions so as to estimate each model parameter error separately. The proposed Parameter Signature Isolation Method (PARSIM) that uses these parameter error estimates for parameter adaptation has been found to have an adaptation precision comparable to that of the Gauss-Newton method for noise-free cases. PARSIM, however, appears to be less sensitive to input conditions, while offering the promise of more effective noise suppression by the capabilities available in the time-scale domain.

Integrating Parameter Estimation Solutions From the Time and Time-Scale Domains

2009 ◽  
Author(s):  
James R. McCusker ◽  
Kourosh Danai
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Time Scale ◽  
Prediction Error ◽  
Nonlinear Least Squares ◽  
Integrated Approach ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Single Model ◽  
Iterative Estimation

A method of parameter estimation was recently introduced that separately estimates each parameter of the dynamic model [1]. In this method, regions coined as parameter signatures, are identified in the time-scale domain wherein the prediction error can be attributed to the error of a single model parameter. Based on these single-parameter associations, individual model parameters can then be estimated for iterative estimation. Relative to nonlinear least squares, the proposed Parameter Signature Isolation Method (PARSIM) has two distinct attributes. One attribute of PARSIM is to leave the estimation of a parameter dormant when a parameter signature cannot be extracted for it. Another attribute is independence from the contour of the prediction error. The first attribute could cause erroneous parameter estimates, when the parameters are not adapted continually. The second attribute, on the other hand, can provide a safeguard against local minima entrapments. These attributes motivate integrating PARSIM with a method, like nonlinear least-squares, that is less prone to dormancy of parameter estimates. The paper demonstrates the merit of the proposed integrated approach in application to a difficult estimation problem.

A Study of Impacts of Coupled Model Initial Shocks and State–Parameter Optimization on Climate Predictions Using a Simple Pycnocline Prediction Model

2011 ◽  
Vol 24 (23) ◽  
pp. 6210-6226 ◽  
Author(s):  
S. Zhang
Keyword(s):  
Time Scales ◽  
Parameter Optimization ◽  
Time Scale ◽  
Model Simulation ◽  
Coupled Model ◽  
State Parameter ◽  
Model Parameters ◽  
Forecast Errors ◽  
Long Time ◽  
The Impact

Abstract A skillful decadal prediction that foretells varying regional climate conditions over seasonal–interannual to multidecadal time scales is of societal significance. However, predictions initialized from the climate-observing system tend to drift away from observed states toward the imperfect model climate because of the model biases arising from imperfect model equations, numeric schemes, and physical parameterizations, as well as the errors in the values of model parameters. Here, a simple coupled model that simulates the fundamental features of the real climate system and a “twin” experiment framework are designed to study the impact of initialization and parameter optimization on decadal predictions. One model simulation is treated as “truth” and sampled to produce “observations” that are assimilated into other simulations to produce observation-estimated states and parameters. The degree to which the model forecasts based on different estimates recover the truth is an assessment of the impact of coupled initial shocks and parameter optimization on climate predictions of interests. The results show that the coupled model initialization through coupled data assimilation in which all coupled model components are coherently adjusted by observations minimizes the initial coupling shocks that reduce the forecast errors on seasonal–interannual time scales. Model parameter optimization with observations effectively mitigates the model bias, thus constraining the model drift in long time-scale predictions. The coupled model state–parameter optimization greatly enhances the model predictability. While valid “atmospheric” forecasts are extended 5 times, the decadal predictability of the “deep ocean” is almost doubled. The coherence of optimized model parameters and states is critical to improve the long time-scale predictions.

scholarly journals Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models

2010 ◽  
Vol 17 (6) ◽  
pp. 697-714 ◽  
Author(s):  
F. Serinaldi
Keyword(s):  
Time Resolution ◽  
Time Scale ◽  
Rainfall Intensity ◽  
Rainfall Series ◽  
Discrete Models ◽  
Model Parameters ◽  
Rainfall Time Series ◽  
Random Weights ◽  
Dry Spell ◽  
Temporal Disaggregation

Abstract. Discrete multiplicative random cascade (MRC) models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity) at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC) model based on beta distribution and a discrete canonical beta-logstable (BLS), the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM) model, which is used as a physically based benchmark model. Monte Carlo simulations point out that the dependence of MC and BLS parameters on rainfall intensity and cascade scales can be recognized also in CUM series, meaning that these relations cannot be considered as a definitive sign of departure from multifractality. Even though the modified MC model is not properly a scaling model (parameters depend on rainfall intensity and scale), it reproduces the empirical traces of the moments and moment exponent function as effective as the CUM model. Moreover, the MC model is able to reproduce some rainfall properties of hydrological interest, such as the distribution of event rainfall amount, wet/dry spell length, and the autocorrelation function, better than its competitors owing to its strong, albeit unrealistic, conservative nature. Therefore, even though the CUM model represents the most parsimonious and the only physically/theoretically consistent model, results provided by MC model motivate, to some extent, the interest recognized in the literature for this type of discrete models.

scholarly journals The roles of atomic and molecular gas on the redshift evolution of star formation and metallicity in galaxy formation models

2012 ◽  
Vol 8 (S292) ◽  
pp. 245-245
Author(s):  
Jian Fu ◽  
Guinevere Kauffmann
Keyword(s):  
Star Formation ◽  
Galaxy Formation ◽  
Time Scale ◽  
High Redshift ◽  
Formation Rate ◽  
Stellar Mass ◽  
Formation Time ◽  
Model Parameters ◽  
Molecular Gas ◽  
Mass Relation

AbstractWe study the redshift evolution of neutral and molecular gas in the interstellar medium with the results from semi-analytic models of galaxy formation and evolution, which track the cold gas related physical processes in radially resolved galaxy disks. Two kinds of prescriptions are adopted to describe the conversion between molecular and neutral gas in the ISM: one is related to the gas surface density and gas metallicity based on the model results by Krumholz, Mckee & Tumlinson; the other is related the pressure of ISM. We try four types of star formation laws in the models to study the effect of the molecular gas component and the star formation time scale on the model results, and find that the H2 dependent star formation rate with constant star formation efficiency is the preferred star formation law. We run the models based on both Millennium and Millennium II Simulation haloes, and the model parameters are adjusted to fit the observations at z = 0 from THINGS/HERACLES and ALFALFA/COLD GASS. We give predictions for the redshift evolution of cosmic star formation density, H2 to HI cosmic ratios, gas to star mass ratios and gas metallicity vs stellar mass relation. Based on the model results, we find that: (i) the difference in the H2 to HI ratio at z > 3 between the two H2 fraction prescriptions can help future observations to test which prescription is better; (ii) a constant redshift independent star formation time scale will postpone the star formation processes at high redshift and cause obvious redshift evolution for the relation between gas metallicity and stellar mass in galaxies at z < 3.

scholarly journals Constraints on precipitation-limited hot haloes from massive galaxies to galaxy clusters

2020 ◽  
Vol 501 (2) ◽  
pp. 2467-2477
Author(s):  
Priyanka Singh ◽  
G M Voit ◽  
Biman B Nath
Keyword(s):  
Time Scale ◽  
Free Fall ◽  
Mass Range ◽  
Model Parameters ◽  
Data Sets ◽  
X Ray ◽  
Massive Galaxies ◽  
Galaxy Groups ◽  
Diffuse Halo ◽  
Halo Gas

ABSTRACT We present constraints on a simple analytical model for hot diffuse halo gas, derived from a fit spanning two orders of magnitude in halo mass ($M_{500} \sim 10^{12.5}\!-\!10^{14.5} \, \mathrm{M}_{\odot }$). The model is motivated by the observed prevalence of a precipitation limit, and its main free parameter is the central ratio of gas cooling time-scale to free-fall time-scale (tcool/tff). We use integrated X-ray and thermal Sunyaev–Zel’dovich observations of the environments around massive galaxies, galaxy groups, and clusters, averaged in halo mass bins, and obtain the best-fitting model parameters. We find tcool/tff ∼ 50–110, depending on the model extrapolation beyond the halo virial radius and possibly on biases present in the data sets used in the fitting analysis. The model adequately describes the entire mass range, except for intermediate mass haloes ($M_{500} \sim 10^{13.5} \, \mathrm{M}_{\odot }$) that systematically fall below the model predictions. However, the best fits for tcool/tff substantially exceed the values typically derived from X-ray observations of individual systems (tcool/tff ∼ 10–30). We consider several explanations for those discrepancies, including X-ray selection biases and a potential anticorrelation between X-ray luminosity and the central galaxy’s stellar mass.

Short time-scale LV systolic dynamics: pressure vs. volume clamps and effect of activation

1993 ◽  
Vol 264 (3) ◽  
pp. H946-H959 ◽  
Author(s):  
S. G. Shroff ◽  
K. B. Campbell ◽  
R. D. Kirkpatrick
Keyword(s):  
Time Scale ◽  
Left Ventricular ◽  
Model Parameters ◽  
Short Time Scale ◽  
Mean Square ◽  
Mechanical Perturbation ◽  
Well Model ◽  
Short Time ◽  
Parameter Values ◽  
Baseline State

We recently proposed a new model-based approach to quantifying short time-scale left ventricular (LV) systolic dynamics. In this study we examine the hypothesis that the quantitation of LV dynamics using the proposed approach is independent of external mechanical perturbations and the level of activation. Mechanical perturbation independence was assessed in seven isolated ferret hearts in which controlled changes in pressure (pressure clamp) or volume (volume clamp) were introduced at the time of peak isovolumetric pressure (protocol 1), and responses to these clamps were analyzed over the first 16 ms. The model described both pressure- and volume-clamps responses equally well. Model parameters were not different among various pressure clamps, and parameters estimated from volume clamps could accurately predict responses to pressure clamps [r2 range: 0.993–0.999; normalized root-mean-square error (NRMSE) range: 2.35–5.86%]. To examine activation independence, volume- (4 hearts) and pressure-clamp (4 hearts) responses were obtained and analyzed for baseline and postextrasystolic potentiated beats in a manner similar to protocol 1. The model parameter values estimated from the baseline state accurately predicted responses for the postextrasystolic potentiated state (r2 and NRMSE range for volume-clamp data: 0.989–0.998 and 3.35–6.88%, respectively; r2 and NRMSE range for pressure-clamp data: 0.992–0.996 and 4.26–5.23%, respectively). Thus the proposed approach can dissect the contributions of changes in activation from those due to changes in contractile unit properties on the function of the intact LV.

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