Temat: neural modelling - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Experimental study and neural network modelling of aerodynamic and dynamic characteristics of flapping wings micro aerial vehicle
Autorzy:: Czekałowski, P.
Sibilski, K.
Żyluk, A.
Powiązania:: https://bibliotekanauki.pl/articles/242331.pdf
Data publikacji:: 2018
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Tematy:: entomopter
flapping wings
aerodynamics
neural network
modelling
aerodynamika
sieć neuronowa
modelowanie
Opis:: The article is close connected with building flying object, that fly like an insect (entomopter). Present work concerns on concept of aerodynamic model using artificial neural networks. Model is used in simulations of flight of entomopter. Aerodynamic model based on experimental data. Necessary data are taken from experiment performed in water tunnel on entomopter model. For this case dynamic test are required. Measurements are ducted during sinusoidal motion of whole model. Modelled object is dipterous. Each wing can perform various spherical motions (wing is rotated around point). The motion of the wing in this case was two-dimensional; it was rotated around two axis. As a model, specially trained neural network is used. For training are used data from measurement. Presented in this article approach is based on artificial neural networks. In this article, innovative concept of model, describing unsteady aerodynamics of entomopter was proposed. It was shown that it could be easily implemented as mathematical model. Unsteady effects related to many state variables can be easily captured. Model can be easily adopted to predict different states of flight by networks training on appropriate data. Test has to reproduce real conditions as close, as it is possible. In reality, it is challenging to design test that will reproduce similar motion.
Źródło:: Journal of KONES; 2018, 25, 4; 49-57
1231-4005
2354-0133
Pojawia się w:: Journal of KONES
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 2.

Tytuł:: Application of artificial neural networks in tribology - prediction and classification models
Autorzy:: Gocman, K.
Kałdoński, T.
Powiązania:: https://bibliotekanauki.pl/articles/244086.pdf
Data publikacji:: 2009
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Tematy:: tribology
boundary friction
ubricity
modelling of tribological processes
artificial neural networks
Opis:: The influence of load and rotational speed on wear and moment of friction is presented in this paper. The tests were carried out under both constant and increasing load and at wide range of rotational speed. During the tests moment offriction, oil temperature and weather conditions were registered. On the basis of obtained results neural models for prediction of wear, moment of friction and friction classifiers were created. The different kinds of artificial neural networks and different training algorithms were applied in order to obtain the best generalisation and quality of created models. All researches showed that artificial neural networks are useful as prediction and classification models. Because of too small teaching data models were limited only to two inputs - load and rotational speed and one output — wear, moment offriction or state. The best models achieved very good precision — testing error lower than 5%. It was also proved, that various types of networks have different usefulness for different applications. MLP networks turned out to be the best wear models, GRNN networks gave the best results as models of moment offriction and RBF networks were proved to be the best classifiers. To obtain model which will give better characterization of processes proceeded in tribological pairs, much more experiments to increase teaching data have to be conducted.
Źródło:: Journal of KONES; 2009, 16, 1; 137-144
1231-4005
2354-0133
Pojawia się w:: Journal of KONES
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 3.

Tytuł:: The ANN approximation of the CH4 combustion model : the heat release
Autorzy:: Kowalski, J.
Powiązania:: https://bibliotekanauki.pl/articles/246946.pdf
Data publikacji:: 2010
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Tematy:: modelling
internal combustion engines
approximation
artificial neural network
combustion process
heat release
Opis:: The calculation of the heat release from the combustion process of the CH4 is presented of the paper. Correct calculation results of the heat released from combustion is important for design, modelling and testing phenomena in combustion chambers of internal combustion engines. The paper presents results of calculations for the kinetic mechanism of methane combustion GriMech 3 for different thermodynamic parameters and composition of the combusted mixture. The calculations were performed for all possible configurations of the variable temperaturę range from 1100K to 3600K, the variable pressure in the range of 2MPa to 5MPa, variable humidity of charged air from 10 to 30 grams of water per l kg of air and variable mole fractions of charge air. Results of the kinetic calculation of combustion process are qualitatively consistent with the data available in literature. The next stage of research was approximation of obtained results with the trained artificial neural network. Input data needed to approximate the energy of the combustion process consisted of 52 mole fractions of chemical species and temperature and pressure process. Approximation results have meant square error not exceeded 0.04% for the test data and 0.02% for the validation data. The maximum error for a single result was 1.9% compared to data obtained with chemical kinetic calculations.
Źródło:: Journal of KONES; 2010, 17, 2; 225-232
1231-4005
2354-0133
Pojawia się w:: Journal of KONES
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Informacja

Wyszukujesz frazę "neural modelling" wg kryterium: Temat

Źródło danych

Dostawca treści

Kolekcja

Rok wydania

Wydawca

Temat

Autor

Typ dokumentu

Język