scholarly journals Hydrological model performance and parameter estimation in the wavelet-domain

2009 ◽  
Vol 13 (10) ◽  
pp. 1921-1936 ◽  
Author(s):  
B. Schaefli ◽  
E. Zehe
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Time Domain ◽  
Model Performance ◽  
Time Varying ◽  
Wavelet Domain ◽  
Frequency Content ◽  
Time Varying Frequency ◽  
The Time Domain

Abstract. This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights the frequencies that are not well reproduced by the model, which gives specific indications about how to improve the model structure.

scholarly journals Hydrological model performance and parameter estimation in the wavelet-domain

2009 ◽  
Vol 6 (2) ◽  
pp. 2451-2498 ◽  
Author(s):  
B. Schaefli ◽  
E. Zehe
Keyword(s):  
Time Series ◽  
Parameter Estimation ◽  
Time Domain ◽  
Model Performance ◽  
Time Varying ◽  
Wavelet Domain ◽  
Frequency Content ◽  
Time Varying Frequency ◽  
The Time Domain

Abstract. This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation – runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights which frequencies are not well reproduced by the model, which gives specific indications about how to improve the model structure.

scholarly journals Using the VO to Study the Time Domain

2011 ◽  
Vol 7 (S285) ◽  
pp. 221-226
Author(s):  
Rob Seaman ◽  
Roy Williams ◽  
Matthew Graham ◽  
Tara Murphy
Keyword(s):  
Time Series ◽  
Time Domain ◽  
Time Varying ◽  
Diverse Group ◽  
Virtual Observatory ◽  
Research Challenges ◽  
Astronomical Time ◽  
Transient Events ◽  
The Time Domain ◽  
Network Technologies

AbstractJust as the astronomical “Time Domain” is a catch-phrase for a diverse group of different science objectives involving time-varying phenomena in all astrophysical régimes from the solar system to cosmological scales, so the “Virtual Observatory” is a complex set of community-wide activities from archives to astroinformatics. This workshop touched on some aspects of adapting and developing those semantic and network technologies in order to address transient and time-domain research challenges. It discussed the VOEvent format for representing alerts and reports on celestial transient events, the SkyAlert and ATELstream facilities for distributing these alerts, and the IVOA time-series protocol and time-series tools provided by the VAO. Those tools and infrastructure are available today to address the real-world needs of astronomers.

scholarly journals Identification of Methamphetamine Abstainers by Resting-State Functional Magnetic Resonance Imaging

2021 ◽  
Vol 12 ◽  
Author(s):  
Tingting Dong ◽  
Qiuping Huang ◽  
Shucai Huang ◽  
Jiang Xin ◽  
Qiaolan Jia ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Time Domain ◽  
Resting State ◽  
Time Varying ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Normal People ◽  
The Time Domain

Methamphetamine (MA) can cause brain structural and functional impairment, but there are few studies on whether this difference will sustain on MA abstainers. The purpose of this study is to investigate the correlation of brain networks in MA abstainers. In this study, 47 people detoxified for at least 14 months and 44 normal people took a resting-state functional magnetic resonance imaging (RS-fMRI) scan. A dynamic (i.e., time-varying) functional connectivity (FC) is obtained by applying sliding windows in the time courses on the independent components (ICs). The windowed correlation data for each IC were then clustered by k-means. The number of subjects in each cluster was used as a new feature for individual identification. The results show that the classifier achieved satisfactory performance (82.3% accuracy, 77.7% specificity, and 85.7% sensitivity). We find that there are significant differences in the brain networks of MA abstainers and normal people in the time domain, but the spatial differences are not obvious. Most of the altered functional connections (time-varying) are identified to be located at dorsal default mode network. These results have shown that changes in the correlation of the time domain may play an important role in identifying MA abstainers. Therefore, our findings provide valuable insights in the identification of MA and elucidate the pathological mechanism of MA from a resting-state functional integration point of view.

On the Dynamic Analysis of Roller Chain Drives: Part II — Case Study

1992 ◽  
Author(s):  
Nicholas M. Veikos ◽  
Ferdinand Freudenstein
Keyword(s):  
Dynamic Analysis ◽  
Time Domain ◽  
Equations Of Motion ◽  
Axial Stiffness ◽  
Roller Chain ◽  
Computer Aided ◽  
Computational Aspects ◽  
The Time Domain ◽  
Chain Drives

Abstract Part I of this paper (5) summarized the previous work and has described the theoretical and computational aspects of a computer-aided procedure which has been developed by the authors for the dynamic analysis of roller chain drives. Lagrange’s equations of motion have been derived by assuming the roller chain to behave as a series of masses lumped at the roller centers and connected by bars of constant axial stiffness. The equations of motion are solved in the time domain until steady state conditions are achieved.

On Vessel Motion Induced Vortex-Induced Vibrations of a Steel Lazy Wave Riser

2021 ◽  
Author(s):  
Decao Yin
Keyword(s):  
Vortex Shedding ◽  
Time Domain ◽  
Oscillatory Flow ◽  
Domain Model ◽  
Time Varying ◽  
Structure Interaction ◽  
Response Characteristics ◽  
Vortex Induced Vibrations ◽  
The Time Domain ◽  
Vessel Motion

Abstract Deepwater steel lazy wave risers (SLWR) subject to vessel motion will be exposed to time-varying oscillatory flow, vortices could be generated and the cyclic vortex shedding force causes the structure vibrate, such fluid-structure interaction is called vortex-induced vibrations (VIV). To investigate VIV on a riser with non-linear structures under vessel motion and oscillatory flows, time domain approaches are needed. In this study, a time-domain approach is used to simulate a full-scale SLWR. Two cases with simplified riser top motions are simulated numerically. By using default input parameters to the time domain approach, the key oscillatory flow induced VIV response characteristics such as response frequency, curvature and displacements are examined and discussed. More accurate VIV prediction could be achieved by using realistic hydrodynamic inputs into the time domain model.

scholarly journals Frequency and Vibration Characteristics of High-Speed Gear-Rotor-Bearing System with Tooth Root Crack considering Compound Dynamic Backlash

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Jie Liu ◽  
Weiqiang Zhao ◽  
Weiwei Liu
Keyword(s):  
Time Domain ◽  
Crack Depth ◽  
Transmission System ◽  
Gear System ◽  
Time Varying ◽  
Tooth Root ◽  
Meshing Stiffness ◽  
The Time Domain ◽  
Center Distance ◽  
Root Crack

Considering the microstructure of tooth surface and the dynamic characteristics of the vibration responses, a compound dynamic backlash model is employed for the gear transmission system. Based on the fractal theory and dynamic center distance, respectively, the dynamic backlash is presented, and the potential energy method is applied to compute the time-varying meshing stiffness, including the healthy gear system and the crack fault gear system. Then, a 16-DOF coupled lateral-torsional gear-rotor-bearing transmission system with the crack fault is established. The fault characteristics in the time-domain waveform and frequency response and statistics data are described. The effect of crack on the time-varying meshing stiffness is analyzed. The vibration response of three backlash models is compared. The dynamic response of the system is explored with the increase in crack depth in detail. The results show that the fault features of countershaft are more obvious. Obvious fluctuations are presented in the time-domain waveform, and sidebands can be found in the frequency domain responses when the tooth root crack appears. The effect of compound dynamic backlash on the system is more obvious than fixed backlash and backlash with changing center distance. The vibration displacement along meshing direction and dynamic meshing force increases with the increase in crack depth. Backlash and variation of center distance show different tendencies with increasing crack depth under different rotational speeds. Amplitude of the sidebands increases with crack depth increasing. The amplitude of multiplication frequency of rotational frequency has an obvious variation with growing crack depth. The sidebands of the multiplication frequency of meshing frequency show more details on the system with complex backlash and crack fault.

scholarly journals Time-Domain Substructure Transient Vibration Transfer Path Analysis Based on Time-Varying Frequency Response Functions under Operational Excitations

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Rong He ◽  
Hong Zhou
Keyword(s):  
Path Analysis ◽  
Frequency Response ◽  
Time Domain ◽  
Time Varying ◽  
Response Functions ◽  
Transient Vibration ◽  
Transfer Path ◽  
Time Varying Systems ◽  
Transfer Path Analysis ◽  
The Time Domain

The time-domain substructure inverse matrix method has become a popular method to detect and diagnose problems regarding vehicle noise, vibration, and harshness, especially for those impulse excitations caused by roads. However, owning to its reliance on frequency response functions (FRFs), the approach is effective only for time-invariable linear or weak nonlinear systems. This limitation prevents this method from being applied to a typical vehicle suspension substructure, which shows different nonlinear characteristics under different wheel transient loads. In this study, operational excitation was considered as a key factor and applied to calculate dynamic time-varying FRFs to perform accurate time-domain transient vibration transfer path analysis (TPA). The core idea of this novel method is to divide whole coupled substructural relationships into two parts: one involved time-invariable components; normal FRFs could be obtained through tests directly. The other involved numerical computations of the time-domain operational loads matrix and FRFs matrix in static conditions. This method focused on determining dynamic FRFs affected by operational loads, especially the severe transient ones; these loads are difficult to be considered in other classical TPA approaches, such as operational path analysis with exogenous inputs (OPAX) and operational transfer path analysis (OTPA). Experimental results showed that this new approach could overcome the limitations of the traditional time-domain substructure TPA in terms of its strict requirements within time-invariable systems. This is because in the new method, time-varying FRFs were calculated and used, which could make the FRFs at the system level directly adapt to time-varying systems from time to time. In summary, the modified method extends TPA objects studied in time-invariable systems to time-varying systems and, thus, makes a methodology and application innovation compared to traditional the time-domain substructure TPA.

scholarly journals A New Method for Time Series Filtering near Endpoints

2008 ◽  
Vol 25 (4) ◽  
pp. 534-546 ◽  
Author(s):  
Anthony Arguez ◽  
Peng Yu ◽  
James J. O’Brien
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Time Domain ◽  
Southern Oscillation ◽  
Fundamental Property ◽  
Great Promise ◽  
Constraint Forces ◽  
Variance Method ◽  
Equal Variance ◽  
The Time Domain

Abstract Time series filtering (e.g., smoothing) can be done in the spectral domain without loss of endpoints. However, filtering is commonly performed in the time domain using convolutions, resulting in lost points near the series endpoints. Multiple incarnations of a least squares minimization approach are developed that retain the endpoint intervals that are normally discarded due to filtering with convolutions in the time domain. The techniques minimize the errors between the predetermined frequency response function (FRF)—a fundamental property of all filters—of interior points with FRFs that are to be determined for each position in the endpoint zone. The least squares techniques are differentiated by their constraints: 1) unconstrained, 2) equal-mean constraint, and 3) an equal-variance constraint. The equal-mean constraint forces the new weights to sum up to the same value as the predetermined weights. The equal-variance constraint forces the new weights to be such that, after convolved with the input values, the expected time series variance is preserved. The three least squares methods are each tested under three separate filtering scenarios [involving Arctic Oscillation (AO), Madden–Julian oscillation (MJO), and El Niño–Southern Oscillation (ENSO) time series] and compared to each other as well as to the spectral filtering method—the standard of comparison. The results indicate that all four methods (including the spectral method) possess skill at determining suitable endpoints estimates. However, both the unconstrained and equal-mean schemes exhibit bias toward zero near the terminal ends due to problems with appropriating variance. The equal-variance method does not show evidence of this attribute and was never the worst performer. The equal-variance method showed great promise in the ENSO project involving a 5-month running mean filter, and performed at least on par with the other realistic methods for almost all time series positions in all three filtering scenarios.

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