scholarly journals Uranium Concentrations and the System Response Function in Gamma Ray Logging

1980 ◽  
Author(s):  
J G Conaway
Keyword(s):  
Response Function ◽  
Gamma Ray ◽  
System Response

Power Spectra Density Replication Control Strategy for 2-Axis Hydraulic Shaker Based on HV Estimator

2014 ◽  
Vol 596 ◽  
pp. 610-615
Author(s):  
Yu Chen ◽  
Qiang Li Luan ◽  
Zhang Wei Chen ◽  
Hui Nong He
Keyword(s):  
Response Function ◽  
Control Algorithm ◽  
Power Spectra ◽  
Time History ◽  
Good Effect ◽  
System Response ◽  
Power Spectral ◽  
Iterative Correction ◽  
Replication Control ◽  
The Given

Hydraulic shaker, equipment of simulating laboratory vibration environment, can accurately replicate the given power spectral density (PSD) and time history with an appropriate control algorithm. By studying method Hv estimator of frequency response function (FRF) estimation, a FRF identification strategy based on the Hv estimator is designed to increase the convergence rapidity and improve the system response function specialty. The system amplitude-frequency characteristics in some frequency points or frequency bands have large fluctuation. To solve this issue, a step-varying and frequency-sectioning iterative correction control algorithm is proposed for the control of 2-axial exciter PSD replication tests and the results show that the algorithm has a good effect on the control of hydraulic shaker, and can achieve reliable and high-precision PSD replication.

The probe particle scattering cross-section off the many-fermion systems in the impulse approximation

2021 ◽  
Author(s):  
Yahya Younesizadeh ◽  
Fayzollah Younesizadeh
Keyword(s):  
Experimental Data ◽  
Distribution Function ◽  
Spectral Function ◽  
Cross Section ◽  
Response Function ◽  
Momentum Distribution ◽  
Impulse Approximation ◽  
System Response ◽  
Probe Particle ◽  
Momentum Distribution Function

In this work, we study the differential scattering cross-section (DSCS) in the first-order Born approximation. It is not difficult to show that the DSCS can be simplified in terms of the system response function. Also, the system response function has this property to be written in terms of the spectral function and the momentum distribution function in the impulse approximation (IA) scheme. Therefore, the DSCS in the IA scheme can be formulated in terms of the spectral function and the momentum distribution function. On the other hand, the DSCS for an electron off the [Formula: see text] and [Formula: see text] nuclei is calculated in the harmonic oscillator shell model. The obtained results are compared with the experimental data, too. The most important result derived from this study is that the calculated DSCS in terms of the spectral function has a high agreement with the experimental data at the low-energy transfer, while the obtained DSCS in terms of the momentum distribution function does not. Therefore, we conclude that the response of a many-fermion system to a probe particle in IA must be written in terms of the spectral function for getting accurate theoretical results in the field of collision. This is another important result of our study.

Response Function of Collimated Detector for Non Axial Detector-Source Geometry

2013 ◽  
Vol 772 ◽  
pp. 571-578
Author(s):  
Rahadi Wirawan ◽  
M. Djamal ◽  
A. Waris ◽  
Gunawan Handayani ◽  
Hong Joo Kim
Keyword(s):  
Monte Carlo ◽  
Response Function ◽  
Gamma Ray ◽  
Geant4 Simulation ◽  
Fundamental Parameter ◽  
Response Functions ◽  
Energy Response ◽  
Simulation Code ◽  
Source Geometry ◽  
Detector Axis

Response function is a fundamental parameter for all detectors in order to analyze the energy distribution of gamma ray which undergoes scattering interaction with the material. The response functions of a 3 in. x 3 in. NaI(Tl) collimated detector for non axis detector-source geometry has been calculated using a Monte Carlo approach from GEANT4 simulation code with 0.662 MeV of mono-energetic of photon gamma ray. Collimated Pb with 4 cm thickness and 2 cm of holes diameter were employed for shielding. The source was assumed as an isotropic point source and it is placed at various positions to the detector axis. The comparison between the measured energy response functions and the simulated energy response functions after normalization were also performed in order to validate the modeling results.

Statistical determination of geophysical well log response functions

Geophysics ◽  
1983 ◽  
Vol 48 (11) ◽  
pp. 1525-1535 ◽  
Author(s):  
Eugene A. Nosal
Keyword(s):  
Power Spectrum ◽  
Response Function ◽  
System Response ◽  
General Terms ◽  
Induction Logging ◽  
Conductivity Profile ◽  
Statistical Determination ◽  
The One

The vertical response function of induction logging tools is shown to be derivable from a power spectrum analysis of the measurement. The vertical response function is the one‐dimensional sequence of weights that characterizes how the tool combines the rock conductivities along the borehole to form an output called the apparent conductivity; it is the system impulse response. The value of knowing this function lies in the possible use of filter theory to aid in data processing and interpretation. Two general notions establish the framework for the analysis. The first is that logging is a linear, convolutional operation. Second, the earth’s conductivity profile forms a stochastic process. The probabilistic component is fleshed out by reasonably based assumptions about the occurrence of bed boundaries and nature of conductivity changes across them. Brought together, these tenets create a characterization of the conductivity sequence that is not a stationary process, but rather is intrinsic, as defined in the discipline of geostatistics. Such a process is described by a variogram, and it is increments of the process that are stationary. The connection between the power spectrum of the measurement and the system response function is made when the convolutional model is merged with the conductivity process. Some examples of induction log functions are shown using these ideas. The analysis is presented in general terms for possibly wider application.

Experimental gamma ray response function for the OSO-7 spacecraft

1973 ◽  
Vol 108 (1) ◽  
pp. 167-176 ◽  
Author(s):  
P. Higbie ◽  
D. Forrest ◽  
I. Gleske ◽  
E. Chupp ◽  
D. Burtis
Keyword(s):  
Response Function ◽  
Gamma Ray
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