scholarly journals Safe Separation Distance Calculation Model with Changing Area of Fuel Packages in Large Space

2011 ◽  
Vol 11 ◽  
pp. 666-674
Author(s):  
Zhang Jia-qing ◽  
Lu Shou-xiang ◽  
Yuan Man ◽  
Li Chang-hai ◽  
Li Qiang
Keyword(s):  
Separation Distance ◽  
Calculation Model ◽  
Large Space ◽  
Distance Calculation

An Improved Fast Algorithm of Spacecraft Separation Distance Calculation

2013 ◽  
Vol 774-776 ◽  
pp. 1560-1566
Author(s):  
Zi Long Hao ◽  
Xin Jian Liu
Keyword(s):  
Fast Algorithm ◽  
Simulation Analysis ◽  
Separation Distance ◽  
Separation Process ◽  
Distance Calculation ◽  
Shortest Distance ◽  
Spatial Bodies

A faster algorithm for calculating the shortest distance between two spatial bodies based on existing algorithms was presented. A simulation analysis of missile models separation process was built by using this algorithm. The simulation proved that this algorithm has the same precision and faster speed compared with other existing algorithms.

The Analysis of Large Space Shear Wall Structure under Wind Load Force

2012 ◽  
Vol 549 ◽  
pp. 830-833
Author(s):  
Li Jian Zhou ◽  
Ming Kang Shan ◽  
Jin Zhou He ◽  
Yuan Gang Fan
Keyword(s):  
Three Dimensional ◽  
Shear Wall ◽  
Internal Force ◽  
Calculation Model ◽  
Wind Loads ◽  
Load Force ◽  
Wall Structure ◽  
Large Space ◽  
Finite Element Software ◽  
Different Thickness

This paper established three-dimensional calculation model of three large space shear wall structures of different thickness,using finite element software ANSYS to analyze the wind loads and vertical loads of the internal force. And analyze the displacement, internal force distribution pattern. Under the wind loads and vertical loads of three different thickness wall of the large space wall structure.

Seti Space Missions

1997 ◽  
Vol 161 ◽  
pp. 761-776 ◽  
Author(s):  
Claudio Maccone
Keyword(s):  
Electromagnetic Waves ◽  
Space Missions ◽  
Gravitational Lens ◽  
The Sun ◽  
Space Antenna ◽  
Focal Distance ◽  
Large Space ◽  
The Earth ◽  
Space Antennas ◽  
New Space

AbstractSETI from space is currently envisaged in three ways: i) by large space antennas orbiting the Earth that could be used for both VLBI and SETI (VSOP and RadioAstron missions), ii) by a radiotelescope inside the Saha far side Moon crater and an Earth-link antenna on the Mare Smythii near side plain. Such SETIMOON mission would require no astronaut work since a Tether, deployed in Moon orbit until the two antennas landed softly, would also be the cable connecting them. Alternatively, a data relay satellite orbiting the Earth-Moon Lagrangian pointL2would avoid the Earthlink antenna, iii) by a large space antenna put at the foci of the Sun gravitational lens: 1) for electromagnetic waves, the minimal focal distance is 550 Astronomical Units (AU) or 14 times beyond Pluto. One could use the huge radio magnifications of sources aligned to the Sun and spacecraft; 2) for gravitational waves and neutrinos, the focus lies between 22.45 and 29.59 AU (Uranus and Neptune orbits), with a flight time of less than 30 years. Two new space missions, of SETI interest if ET’s use neutrinos for communications, are proposed.

A fuzzy neural network approach for modeling the growth kinetics of FeB and Fe2B layers during the boronizing process

2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Fuzzy Neural Network ◽  
Treatment Time ◽  
Calculation Model ◽  
Average Error ◽  
Network Approach ◽  
Neural Network Approach ◽  
Fuzzy Neural ◽  
Kinetics Of

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.

Development of the Partial Discharge Inception Calculation Model in a Non-uniform Air Gap Considering the Effect of Humidity

2011 ◽  
Vol 131 (12) ◽  
pp. 1017-1023 ◽  
Author(s):  
Norihito Yanagita ◽  
Tatsuro Kato ◽  
Toshiaki Rokunohe ◽  
Takeshi Iwata ◽  
Hiroki Kojima ◽  
...  
Keyword(s):  
Partial Discharge ◽  
Calculation Model ◽  
Air Gap
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