scholarly journals Stability and Limit Oscillations of a Control Event-Based Sampling Criterion

2012 ◽  
Vol 2012 ◽  
pp. 1-25 ◽  
Author(s):  
M. De la Sen ◽  
J. C. Soto ◽  
A. Ibeas
Keyword(s):  
Adaptive Sampling ◽  
Initial Conditions ◽  
Signal Amplitude ◽  
Absolute Difference ◽  
Sampling System ◽  
Sampled Signal ◽  
Control Event ◽  
Threshold Amplitude ◽  
The Time Domain ◽  
Event Based

This paper investigates the presence of limit oscillations in an adaptive sampling system. The basic sampling criterion operates in the sense that each next sampling occurs when the absolute difference of the signal amplitude with respect to its currently sampled signal equalizes a prescribed threshold amplitude. The sampling criterion is extended involving a prescribed set of amplitudes. The limit oscillations might be interpreted through the equivalence of the adaptive sampling and hold device with a nonlinear one consisting of a relay with multiple hysteresis whose parameterization is, in general, dependent on the initial conditions of the dynamic system. The performed study is performed on the time domain.

Experimental Validation of a Dynamic Simulation

1990 ◽  
Author(s):  
K. Harold Yae ◽  
Su-Tai Chern ◽  
Howyoung Hwang
Keyword(s):  
Dynamic Analysis ◽  
Dynamic Simulation ◽  
Time Domain ◽  
Experimental Validation ◽  
Initial Conditions ◽  
Hydraulic Cylinder ◽  
Force Output ◽  
Inverse Dynamic ◽  
Inverse Dynamic Analysis ◽  
The Time Domain

Abstract Using forward and inverse dynamic analysis, the dynamic simulation of a backhoe has been compared with experiments. In the experiment, recorded were the configuration and force histories; that is, velocity and position, and force output from the hydraulic cylinder-all were measured in the time domain. When the experimental force history is used as driving force in the simulation, forward dynamic analysis produces a corresponding motion history. And when the experimental motion history is used as if a prescribed trajectory, inverse dynamic analysis generates a corresponding force history. Therefore, these two sets of motion and force histories — one set from experiment, and the other from the simulation that is driven forward and backward with the experimental data — are compared in the time domain. The comparisons are discussed in regard to the effects of variations in initial conditions, friction, and viscous damping.

scholarly journals Application of nonlinear dynamics methods for quantitative and qualitative evaluation of properties of 2D models of S-chaos

2021 ◽  
Vol 16 (91) ◽  
pp. 125-143
Author(s):  
Aleksei A. Gavrishev ◽  
Keyword(s):  
Nonlinear Dynamics ◽  
Lower Bound ◽  
Time Domain ◽  
Initial Conditions ◽  
Qualitative Evaluation ◽  
Recurrence Analysis ◽  
Combined Application ◽  
Student Version ◽  
The Time Domain ◽  
Property Characteristic

In this article, based on the mathematical, numerical and computer modeling carried out by the combined application of E&F Chaos, Past, Fractan, Visual Recurrence Analysis, Eviews Student Version Lite programs, some of the well-known 2D models of S-chaos are modeled, the data obtained are studied using nonlinear dynamics methods and the fact of their relation or non-relation to chaotic (quasi-chaotic) processes is established. As a result, it was found that the time diagrams obtained for the studied 2D models of S-chaos have a complex noise-like appearance and are continuous in the time domain. The resulting spectral diagrams have both a complex noise-like and regular appearance and are continuous in the spectral regions. The obtained values of BDS-statistics show that some of the time implementations can be attributed to chaotic (quasi-chaotic) processes. Also, the obtained values of BDS-statistics show that the studied 2D models of S-chaos have a property characteristic of classical chaotic (quasi-chaotic) processes: the slightest change in the initial conditions leads to the generation of a new set of signals. The obtained values of the lower bound of the KS-entropy show that the studied models also have the properties of chaotic (quasi-chaotic). Taking into account the conducted research and data from known works [1–5], it is possible to conclude that 2D models of S-chaos can relate to chaotic (quasi-chaotic) processes.

scholarly journals A Heuristic Approach for Precipitation Data Assimilation: Characterization Using OSSEs

2019 ◽  
Vol 147 (9) ◽  
pp. 3445-3466 ◽  
Author(s):  
Andrés A. Pérez Hortal ◽  
Isztar Zawadzki ◽  
M. K. Yau
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Grid Point ◽  
Wrf Model ◽  
Ensemble Member ◽  
Absolute Difference ◽  
Time Interval ◽  
State Variables ◽  
Vertical Column ◽  
A New Technique

Abstract We introduce a new technique for the assimilation of precipitation observations, the localized ensemble mosaic assimilation (LEMA). The method constructs an analysis by selecting, for each vertical column in the model, the ensemble member with precipitation at the ground that is locally closest to the observed values. The proximity between the modeled and observed precipitation is determined by the mean absolute difference of precipitation intensity, converted to reflectivity and measured over a spatiotemporal window centered at each grid point of the model. The underlying hypothesis of the approach is that the ensemble members that are locally closer to the observed precipitation are more probable to be closer to the “truth” in the state variables than the other members. The initial conditions for the new forecast are obtained by nudging the background states toward the mosaic of the closest ensemble members (analysis) over a 30 min time interval, reducing the impacts of the imbalances at the boundaries between the different selected members. The potential of the method is studied using observing system simulation experiments (OSSEs) employing a small ensemble of 20 members. The ensemble is produced by the WRF Model, run at a horizontal grid spacing of 20 km. The experiments lend support to the validity of the hypothesis and allow the determination of the optimal parameters for the approach. In the context of OSSE, this new data assimilation technique is able to produce forecasts with considerable and long-lived error reductions in the fields of precipitation, temperature, humidity, and wind.

Thermoacoustic interplay between intrinsic thermoacoustic and acoustic modes: non-normality and high sensitivities

2019 ◽  
Vol 878 ◽  
pp. 190-220 ◽  
Author(s):  
Francesca M. Sogaro ◽  
Peter J. Schmid ◽  
Aimee S. Morgans
Keyword(s):  
Time Domain ◽  
Time Scale ◽  
Initial Conditions ◽  
Normal Modes ◽  
Time Domain Analysis ◽  
Normal Behaviour ◽  
Optimal Perturbation ◽  
Acoustic Modes ◽  
Energy Growth ◽  
The Time Domain

This study analyses the interplay between classical acoustic modes and intrinsic thermoacoustic (ITA) modes in a simple thermoacoustic system. The analysis is performed using a frequency-domain low-order network model as well as a time-domain spatially discretised model. Anti-correlated modal sensitivities are found to arise due to a pairwise interplay between acoustic and ITA modes. The magnitude of the sensitivities increases as the interplay between the modes grows stronger. The results show a global behaviour of the modes linked to the presence of exceptional points in the spectrum. The time-domain analysis results in a delay-differential equation and allows the investigation of non-normal behaviour and its consequences. Pseudospectral analysis reveals that energy amplification is crucially linked to an interplay between acoustic and ITA modes. While higher non-orthogonality between two modes is correlated with peaks in modal sensitivity, transient energy growth does not necessarily involve the most sensitive modes. In particular, growth estimates based on the Kreiss constant demonstrate that transient amplification relies critically on the proximity of the non-normal modes to the imaginary axis. The time scale for transient amplification is identified as the flame time delay, which is further corroborated by determining the optimal initial conditions responsible for the bulk of the non-modal energy growth. The flame is identified as an active and dominant contributor to energy gain. The frequency of the optimal perturbation matches the acoustic time scale, once more confirming an interplay between acoustic and ITA structures. Flame-based amplification factors of two to five are found, which are significant when feeding into the acoustic dynamics and eventually triggering nonlinear limit-cycle behaviour.

A standard finite‐difference scheme for the time‐domain computation of anelastic wavefields

Geophysics ◽  
1994 ◽  
Vol 59 (2) ◽  
pp. 290-296 ◽  
Author(s):  
E. S. Krebes ◽  
Gerardo Quiroga‐Goode
Keyword(s):  
Finite Difference ◽  
Difference Scheme ◽  
Time Domain ◽  
Finite Difference Scheme ◽  
Initial Conditions ◽  
Homogeneous Medium ◽  
Standard Technique ◽  
Equation Of Motion ◽  
Central Difference ◽  
The Time Domain

We show that the finite‐differencing technique based on the consecutive application of the central difference operator to spatial derivatives, a standard well‐known technique that has been commonly used in the seismological literature for solving the elastic equation of motion, can also be used to obtain a stable time‐domain, finite‐difference scheme for solving the anelastic equation of motion. We compare the results of the scheme for a heterogeneous medium with those of the time‐domain finite‐difference scheme previously developed by Emmerich and Korn and find that they agree very closely. We show, analytically, that in the case of a homogeneous medium, the two schemes give identical numerical results for certain zero initial conditions. The scheme based on the standard technique uses more computer time and memory than the scheme of Emmerich and Korn. However, from a theoretical viewpoint, it is easier to analyze, as it is developed solely with a familiar standard method.

A New Cost Function for Parameter Estimation of Chaotic Systems Using Return Maps as Fingerprints

2014 ◽  
Vol 24 (10) ◽  
pp. 1450134 ◽  
Author(s):  
Sajad Jafari ◽  
Julien C. Sprott ◽  
Viet-Thanh Pham ◽  
S. Mohammad Reza Hashemi Golpayegani ◽  
Amir Homayoun Jafari
Keyword(s):  
Parameter Estimation ◽  
Cost Function ◽  
Chaotic Systems ◽  
Time Series Data ◽  
Initial Conditions ◽  
Model Systems ◽  
Series Data ◽  
Return Maps ◽  
Active Interest ◽  
The Time Domain

Estimating parameters of a model system using observed chaotic scalar time series data is a topic of active interest. To estimate these parameters requires a suitable similarity indicator between the observed and model systems. Many works have considered a similarity measure in the time domain, which has limitations because of sensitive dependence on initial conditions. On the other hand, there are features of chaotic systems that are not sensitive to initial conditions such as the topology of the strange attractor. We have used this feature to propose a new cost function for parameter estimation of chaotic models, and we show its efficacy for several simple chaotic systems.

A MODIFIED CORRELATION METHOD FOR T-WAVE ALTERNANS DETECTION

2013 ◽  
Vol 25 (03) ◽  
pp. 1350030
Author(s):  
Xiangkui Wan ◽  
Kanghui Yan ◽  
Minggui Li ◽  
Dingcheng Xiang
Keyword(s):  
Heart Diseases ◽  
Correlation Method ◽  
Absolute Difference ◽  
T Wave ◽  
Formidable Challenge ◽  
Maximum Absolute Difference ◽  
T Wave Alternans ◽  
Improved Performance ◽  
The Time Domain ◽  
Electrocardiogram Ecg

Identification of individuals who are at risk for sudden cardiac death (SCD) remains a formidable challenge. T-wave alternans (TWA) evaluation is emerging as an important tool for risk stratification in patients with heart diseases. Several methods have been developed in recent years to detect and quantify TWA. One such method is known as the correlation method (CM). This method performs well for different levels of TWA and phase shifts in the time domain, but it is sensitive to noise and requires higher quality of electrocardiogram (ECG) signal for test. In this paper, we propose a modified correlation method (MCM) to ensure a robust and accuracy detection of TWA. Compared with CM, MCM add a stage of T-wave curve fitting before media T-wave template, and the TWA magnitude is obtained by meaning the maximum absolute difference between even and odd T-wave. Our assessment study demonstrates the improved performance of the proposed algorithm.

scholarly journals Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

2011 ◽  
Vol 11 (1) ◽  
pp. 157-170 ◽  
Author(s):  
Y. Tramblay ◽  
C. Bouvier ◽  
P.-A. Ayral ◽  
A. Marchandise
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Radar Data ◽  
Rain Gauge ◽  
Production Model ◽  
Initial Condition ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Moisture Index ◽  
Event Based

Abstract. A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM) model developed by Météo-France was used. This study was done in the Gardon catchment (545 km2) in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R2 values increasing from 0.61 to 0.72.

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