scholarly journals Mathematical modeling of a MOSFET transistor as modulator in AM transmission

2021 ◽  
pp. 36-45
Author(s):  
Eduardo Mota-Galván ◽  
Roberto Alejandro Reyes-Martinez
Keyword(s):  
Mathematical Modeling ◽  
Transfer Function ◽  
Frequency Domain ◽  
Characteristic Equations ◽  
Electronic Application ◽  
Optimization Control ◽  
The Difference

The necessary methodology is presented to characterize the alternating signal transistor in the time and frequency domain and obtain its characteristic equations including its transfer function. The behavior of the transistor gate is studied in different models of manufacturers in alternating signal, therefore the difference between the behavior relationship between the theory and the information obtained in the experimentation is shown. All of the above to have an optimization, control or description of the operation of a real transistor and be used in an electrical / electronic application in general, in this case, for an AM modulation.

Error analyses of a Multi-Input-Multi-Output cantilever beam test

2021 ◽  
pp. 107754632110337
Author(s):  
Arup Maji ◽  
Fernando Moreu ◽  
James Woodall ◽  
Maimuna Hossain
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Cantilever Beam ◽  
Transfer Functions ◽  
Linear Superposition ◽  
Transfer Function Matrix ◽  
Error Analyses ◽  
Pseudo Inverse ◽  
Function Matrix

Multi-Input-Multi-Output vibration testing typically requires the determination of inputs to achieve desired response at multiple locations. First, the responses due to each input are quantified in terms of complex transfer functions in the frequency domain. In this study, two Inputs and five Responses were used leading to a 5 × 2 transfer function matrix. Inputs corresponding to the desired Responses are then computed by inversion of the rectangular matrix using Pseudo-Inverse techniques that involve least-squared solutions. It is important to understand and quantify the various sources of errors in this process toward improved implementation of Multi-Input-Multi-Output testing. In this article, tests on a cantilever beam with two actuators (input controlled smart shakers) were used as Inputs while acceleration Responses were measured at five locations including the two input locations. Variation among tests was quantified including its impact on transfer functions across the relevant frequency domain. Accuracy of linear superposition of the influence of two actuators was quantified to investigate the influence of relative phase information. Finally, the accuracy of the Multi-Input-Multi-Output inversion process was investigated while varying the number of Responses from 2 (square transfer function matrix) to 5 (full-rectangular transfer function matrix). Results were examined in the context of the resonances and anti-resonances of the system as well as the ability of the actuators to provide actuation energy across the domain. Improved understanding of the sources of uncertainty from this study can be used for more complex Multi-Input-Multi-Output experiments.

Effect of titanium alloys elasticity modulus on warping of stamped blanks during cooling

2021 ◽  
pp. 221-227
Author(s):  
M.O. Smirnov ◽  
A.M. Zolotov ◽  
A.M. Tyukhtyaev
Keyword(s):  
Mathematical Modeling ◽  
Titanium Alloys ◽  
Room Temperature ◽  
Elevated Temperatures ◽  
Elasticity Modulus ◽  
Preliminary Deformation ◽  
Wide Spread ◽  
Temperature Dependences ◽  
Cumulative Deformation ◽  
The Difference

Wide spread in the values of the elasticity modulus of the titanium VT6 alloy and its analogs Ti—6Al—4V, Ti—6Al—4V ELI at room temperature and at elevated temperatures is revealed аs result of the literature sources analysis. The data are ambiguous, the available temperature dependences of the elasticity modulus have very different values starting from the temperature T l 500 °C. Mathematical modeling of the warping process is carried out on the example of figurine-shaped stamped blank of turbine blade using various dependences of the elasticity modulus on temperature. Cases of warping during cooling of stamped blank after cooling-down in stamp with and without cumulative deformation are considered. The difference in the course of thermal deformations during the cooling of the workpiece is obtained using different temperature dependences of the elasticity modulus. The presence of preliminary deformation increases the warping of the workpieces.

Multiscale mathematical modeling vs. the generalized transfer function approach for aortic pressure estimation: a comparison with invasive data

2018 ◽  
Vol 42 (5) ◽  
pp. 690-698 ◽  
Author(s):  
Andrea Guala ◽  
Francesco Tosello ◽  
Dario Leone ◽  
Luca Sabia ◽  
Fabrizio D’Ascenzo ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Transfer Function ◽  
Aortic Pressure ◽  
Function Approach ◽  
Pressure Estimation ◽  
Generalized Transfer Function

Fourier Series-Based Neural Networks for Vehicle System Identification

1999 ◽  
Author(s):  
Imtiaz Haque ◽  
Juergen Schuller
Keyword(s):  
Neural Networks ◽  
Fourier Series ◽  
System Identification ◽  
Transfer Function ◽  
Parameter Identification ◽  
Frequency Domain ◽  
Vehicle System ◽  
Non Linear ◽  
Function Identification ◽  
Non Linear System

Abstract The use of neural networks in system identification is an emerging field. Neural networks have become popular in recent years as a means to identify linear and non-linear systems whose characteristics are unknown. The success of sigmoidal networks in parameter identification has been limited. However, harmonic activation-based neural networks, recent arrivals in the field of neural networks, have shown excellent promise in linear and non-linear system parameter identification. They have been shown to have excellent generalization capability, computational parallelism, absence of local minima, and good convergence properties. They can be used in the time and frequency domain. This paper presents the application of a special class of such networks, namely Fourier Series neural networks (FSNN) to vehicle system identification. In this paper, the applications of the FSNNs are limited to the frequency domain. Two examples are presented. The results of the identification are based on simulation data. The first example demonstrates the transfer function identification of a two-degree-of freedom lateral dynamics model of an automobile. The second example involves transfer function identification for a quarter car model. The network set-up for such identification is described. The results of the network identification are compared with theory. The results indicate excellent prediction properties of such networks.

Integrated and frequency-band magnitude, two alternative measures of the size of an earthquake

1970 ◽  
Vol 60 (3) ◽  
pp. 917-937 ◽  
Author(s):  
B. F. Howell ◽  
G. M. Lundquist ◽  
S. K. Yiu
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Frequency Band ◽  
Transfer Functions ◽  
Body Wave ◽  
Average Amplitude ◽  
Equivalent Quantity ◽  
Short Period ◽  
Alternative Measures ◽  
Body Wave Magnitude

Abstract Integrated magnitude substitutes the r.m.s. average amplitude over a pre-selected interval for the peak amplitude in the conventional body-wave magnitude formula. Frequency-band magnitude uses an equivalent quantity in the frequency domain. Integrated magnitude exhibits less scatter than conventional body-wave magnitude for short-period seismograms. Frequency-band magnitude exhibits less scatter than body-wave magnitude or integrated magnitude for both long- and short-period seismograms. The scatter of frequency-band magnitude is probably due to real azimuthal effects, crustal-transfer-function variations, errors in compensation for seismograph response, microseismic moise and uncertainties in the compensation for attenuation with distance. To observe azimuthal variations clearly, the crustal-transfer functions and seismograph response need to be known more precisely than was the case in this experiment, because these two sources of scatter can be large enough to explain all of the observed variations.

scholarly journals Impact of mild orthostatic stress on aortic-cerebral hemodynamic transmission: insight from the frequency domain

2017 ◽  
Vol 312 (5) ◽  
pp. H1076-H1084 ◽  
Author(s):  
Jun Sugawara ◽  
Tsubasa Tomoto ◽  
Tomoko Imai ◽  
Seiji Maeda ◽  
Shigehiko Ogoh
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Systemic Vascular Resistance ◽  
Vascular Resistance ◽  
Low Frequency ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Slow Oscillations ◽  
Transfer Function Gain ◽  
The Brain

High cerebral pressure and flow fluctuations could be a risk for future cerebrovascular disease. This study aims to determine whether acute systemic vasoconstriction affects the dynamic pulsatile hemodynamic transmission from the aorta to the brain. We applied a stepwise lower body negative pressure (LBNP) (−10, −20, and −30 mmHg) in 15 young men to induce systemic vasoconstriction. To elucidate the dynamic relationship between the changes in aortic pressure (AoP; estimated from the radial arterial pressure waveforms) and the cerebral blood flow velocity (CBFV) at the middle cerebral artery (via a transcranial Doppler), frequency-domain analysis characterized the beat-to-beat slow oscillation (0.02–0.30 Hz) and the intra-beat rapid change (0.78–9.69 Hz). The systemic vascular resistance gradually and significantly increased throughout the LBNP protocol. In the low-frequency range (LF: 0.07–0.20 Hz) of a slow oscillation, the normalized transfer function gain of the steady-state component (between mean AoP and mean CBFV) remained unchanged, whereas that of the pulsatile component (between pulsatile AoP and pulsatile CBFV) was significantly augmented during −20 and −30 mmHg of LBNP (+28.8% and +32.4% vs. baseline). Furthermore, the relative change in the normalized transfer function gain of the pulsatile component at the LF range correlated with the corresponding change in systemic vascular resistance ( r = 0.41, P = 0.005). Regarding the intra-beat analysis, the normalized transfer function gain from AoP to CBFV was not significantly affected by the LBNP stimulation ( P = 0.77). Our findings suggest that systemic vasoconstriction deteriorates the dampening effect on the pulsatile hemodynamics toward the brain, particularly in slow oscillations (e.g., 0.07–0.20 Hz). NEW & NOTEWORTHY We characterized the pulsatile hemodynamic transmission from the heart to the brain by frequency-domain analysis. The low-frequency transmission was augmented with a mild LBNP stimulation partly due to the elevated systemic vascular resistance. A systemic vasoconstriction deteriorates the dampening effect on slow oscillations of pulsatile hemodynamics toward the brain.

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