On the role of visible radiation in ozone profile retrieval from nadir UV/VIS satellite measurements: An experiment with neural network algorithms inverting SCIAMACHY data

2012 ◽  
Vol 113 (12) ◽  
pp. 1429-1436 ◽  
Author(s):  
P. Sellitto ◽  
A. Di Noia ◽  
F. Del Frate ◽  
A. Burini ◽  
S. Casadio ◽  
...  
Keyword(s):  
Neural Network ◽  
Satellite Measurements ◽  
Visible Radiation ◽  
Network Algorithms ◽  
Ozone Profile

ROLE OF MULTIPLE SCATTERING IN OZONE PROFILE RETRIEVAL FROM SATELLITE MEASUREMENTS IN THE ULTRAVIOLET

1980 ◽  
pp. 219-231 ◽  
Author(s):  
S.L. Taylor ◽  
P.K. Bhartia ◽  
V.G. Kaveeshwar ◽  
K.F. Klenk ◽  
Albert J. Fleig ◽  
...  
Keyword(s):  
Multiple Scattering ◽  
Satellite Measurements ◽  
Ozone Profile

scholarly journals The use of neural network algorithms for modeling injection doses of modern fuel injectors

2021 ◽  
Author(s):  
Karol Abramek ◽  
Tomasz Osipowicz ◽  
Łukasz Mozga
Keyword(s):  
Neural Network ◽  
Combustion Engine ◽  
Experimental Models ◽  
Fuel Injector ◽  
Backpropagation Algorithm ◽  
Injection Equipment ◽  
Network Algorithms ◽  
Fuel Injectors ◽  
Black Boxes

The article presents the possibilities of using artificial intelligence methods to model the injection doses of a modern Common Rail (CR) fuel injector. The presented neural network solution belongs to the experimental models known as black boxes in mechatronics. The backpropagation algorithm and its Levenberg-Marquardt expansion were used for the simulation. The analysis showed that there is a good match between the measurements and the computational model. The proposed solution can be used in the processes of diagnosing not only elements of the injection equipment, but also the internal combustion engine. The paper presents the construction and operation of fuel injectors and the important role of precision pairs work.

scholarly journals Management of the Torch Structure with the New Methodological Approaches to Regulation Based on Neural Network Algorithms

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1909
Author(s):  
Konstantin Osintsev ◽  
Sergei Aliukov ◽  
Yuri Prikhodko
Keyword(s):  
Neural Network ◽  
Coal Dust ◽  
Combustion Process ◽  
Analytical Calculation ◽  
Continuous Distribution ◽  
Initial Section ◽  
Distribution Functions ◽  
Thermophysical Characteristics ◽  
Network Algorithms ◽  
Furnace Volume

A method for evaluating the thermophysical characteristics of the torch is developed. Mathematically the temperature at the end of the zone of active combustion based on continuous distribution functions of particles of solid fuels, in particular coal dust. The particles have different average sizes, which are usually grouped and expressed as a fraction of the total mass of the fuel. The authors suggest taking into account the sequential nature of the entry into the chemical reactions of combustion of particles of different masses. In addition, for the application of the developed methodology, it is necessary to divide the furnace volume into zones and sections. In particular, the initial section of the torch, the zone of intense burning and the zone of afterburning. In this case, taking into account all the thermophysical characteristics of the torch, it is possible to make a thermal balance of the zone of intense burning. Then determines the rate of expiration of the fuel-air mixture, the time of combustion of particles of different masses and the temperature at the end of the zone of intensive combustion. The temperature of the torch, the speed of flame propagation, and the degree of particle burnout must be controlled. The authors propose an algorithm for controlling the thermophysical properties of the torch based on neural network algorithms. The system collects data for a certain time, transmits the information to the server. The data is processed and a forecast is made using neural network algorithms regarding the combustion modes. This allows to increase the reliability and efficiency of the combustion process. The authors present experimental data and compare them with the data of the analytical calculation. In addition, data for certain modes are given, taking into account the system’s operation based on neural network algorithms.

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