APPLICATION OF RELEVANCE VECTOR MACHINE IN SEISMIC ATTENUATION PREDICTION

2007 ◽  
Vol 01 (04) ◽  
pp. 299-309 ◽  
Author(s):  
PIJUSH SAMUI
Keyword(s):  
Sensitivity Analysis ◽  
Information Content ◽  
Relevance Vector Machine ◽  
Seismic Attenuation ◽  
Rock Properties ◽  
Input Parameters ◽  
Practical Tool ◽  
Data Sensitivity

The recently introduced relevance vector machine (RVM) technique is applied to predict seismic attenuation based on rock properties. The RVM provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. It evades complexity by producing models that have structure and as a result parameterization process that is appropriate to the information content of the data. Sensitivity analysis has been also performed to investigate the importance of each of the input parameters. The results show that RVM approach has the potential to be a practical tool for determination of seismic attenuation.

DETERMINATION OF SEISMIC ATTENUATION BENEATH EAST SEA

2019 ◽  
Author(s):  
Nguyen Le Minh ◽  
Satoru Tanaka ◽  
Yasushi Ishihara ◽  
Nguyen Tien Hung ◽  
Ha Vinh Long ◽  
...  
Keyword(s):  
Seismic Attenuation ◽  
East Sea

Analysis of methodologies for determination of DEM input parameters

2021 ◽  
Author(s):  
Rondinelli M. Lima ◽  
Rodolfo J. Brandao ◽  
Raphael L. Santos ◽  
Claudio R. Duarte ◽  
Marcos A. S. Barrozo
Keyword(s):  
Input Parameters

Determination of levitated molten metal shape in axisymmetric induction heating system using sensitivity analysis

1995 ◽  
Vol 31 (3) ◽  
pp. 2158-2161 ◽  
Author(s):  
Ghun-Deok Suh ◽  
Hong-Bae Lee ◽  
Song-Yop Hahn ◽  
Tae-Kyung Chung ◽  
Il-Han Park
Keyword(s):  
Sensitivity Analysis ◽  
Molten Metal ◽  
Induction Heating ◽  
Heating System ◽  
Induction Heating System ◽  
Metal Shape

Sobol′ Sensitivity Analysis Using a Neural Network Model of a LB-LOCA in the ZION Nuclear Power Plant With CATHARE-2 V2.5 Code

2013 ◽  
Author(s):  
Fabrice Fouet ◽  
Pierre Probst
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Nuclear Power ◽  
Uncertainty Propagation ◽  
Correlation Coefficients ◽  
Computer Code ◽  
Numerical Application ◽  
Loss Of Coolant Accident ◽  
Input Parameters ◽  
Artificial Neural Network Ann

In nuclear safety, the Best-Estimate (BE) codes may be used in safety demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. The uncertainty of output parameters, which comes mainly from the lack of knowledge of the input parameters, is evaluated by estimating the 95% percentile with a high degree of confidence. IRSN, technical support of the French Safety Authority, developed a method of uncertainty propagation. This method has been tested with the BE code used is CATHARE-2 V2.5 in order to evaluate the Peak Cladding Temperature (PCT) of the fuel during a Large Break Loss Of Coolant Accident (LB-LOCA) event, starting from a large number of input parameters. A sensitivity analysis is needed in order to limit the number of input parameters and to quantify the influence of each one on the response variability of the numerical model. Generally, the Global Sensitivity Analysis (GSA) is done with linear correlation coefficients. This paper presents a new approach to perform a more accurate GSA to determine and to classify the main uncertain parameters: the Sobol′ methodology. The GSA requires simulating many sets of parameters to propagate uncertainties correctly, which makes of it a time-consuming approach. Therefore, it is natural to replace the complex computer code by an approximate mathematical model, called response surface or surrogate model. We have tested Artificial Neural Network (ANN) methodology for its construction and the Sobol′ methodology for the GSA. The paper presents a numerical application of the previously described methodology on the ZION reactor, a Westinghouse 4-loop PWR, which has been retained for the BEMUSE international problem [8]. The output is the first maximum PCT of the fuel which depends on 54 input parameters. This application outlined that the methodology could be applied to high-dimensional complex problems.

Device Modeling of a-Si:H Alloy Solar Cells: Calibration Procedure for Determination of Model Input Parameters

1998 ◽  
Vol 507 ◽  
Author(s):  
M. Zeman ◽  
R.A.C.M.M. Van Swaaij ◽  
E. Schroten ◽  
L.L.A. Vosteen ◽  
J.W. Metselaar
Keyword(s):  
Solar Cell ◽  
Material Properties ◽  
Calibration Procedure ◽  
Model Parameters ◽  
Model Input ◽  
A Value ◽  
Input Parameters ◽  
Simulated Material ◽  
Good Agreement

ABSTRACTA calibration procedure for determining the model input parameters of standard a-Si:H layers, which comprise a single junction a-Si:H solar cell, is presented. The calibration procedure consists of: i) deposition of the separate layers, ii) measurement of the material properties, iii) fitting the model parameters to match the measured properties, iv) simulation of test devices and comparison with experimental results. The inverse modeling procedure was used to extract values of the most influential model parameters by fitting the simulated material properties to the measured ones. In case of doped layers the extracted values of the characteristic energies of exponentially decaying tail states are much higher than the values reported in literature. Using the extracted values of model parameters a good agreement between the measured and calculated characteristics of a reference solar cell was reached. The presented procedure could not solve directly an important issue concerning a value of the mobility gap in a-Si:H alloys.

scholarly journals High-Fidelity Sensitivity Analysis of Modal Properties of Mistuned Bladed Disks Regarding Material Anisotropy

2018 ◽  
Author(s):  
Adam Koscso ◽  
Guido Dhondt ◽  
E. P. Petrov
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Natural Frequencies ◽  
Mode Shapes ◽  
Finite Element Models ◽  
Coordinate Systems ◽  
Bladed Disks ◽  
Bladed Disk ◽  
Material Orientation

A new method has been developed for sensitivity calculations of modal characteristics of bladed disks made of anisotropic materials. The method allows the determination of the sensitivity of the natural frequencies and mode shapes of mistuned bladed disks with respect to anisotropy angles that define the crystal orientation of the monocrystalline blades using full-scale finite element models. An enhanced method is proposed to provide high accuracy for the sensitivity analysis of mode shapes. An approach has also been developed for transforming the modal sensitivities to coordinate systems used in industry for description of the blade anisotropy orientations. The capabilities of the developed methods are demonstrated on examples of a single blade and a mistuned realistic bladed disk finite element models. The modal sensitivity of mistuned bladed disks to anisotropic material orientation is thoroughly studied.

Seismic hazard sensitivity analysis: A multi-parameter approach

1991 ◽  
Vol 81 (3) ◽  
pp. 796-817
Author(s):  
Nitzan Rabinowitz ◽  
David M. Steinberg
Keyword(s):  
Sensitivity Analysis ◽  
Seismic Hazard ◽  
Subjective Probability ◽  
Probability Distributions ◽  
Input Parameter ◽  
The Other ◽  
Probabilistic Assessment ◽  
Input Parameters ◽  
Parameter Approach

Abstract We propose a novel multi-parameter approach for conducting seismic hazard sensitivity analysis. This approach allows one to assess the importance of each input parameter at a variety of settings of the other input parameters and thus provides a much richer picture than standard analyses, which assess each input parameter only at the default settings of the other parameters. We illustrate our method with a sensitivity analysis of seismic hazard for Jerusalem. In this example, we find several input parameters whose importance depends critically on the settings of other input parameters. This phenomenon, which cannot be detected by a standard sensitivity analysis, is easily diagnosed by our method. The multi-parameter approach can also be used in the context of a probabilistic assessment of seismic hazard that incorporates subjective probability distributions for the input parameters.

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