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    Wyświetlanie 1-9 z 9
    Tytuł:
    Prediction of Two-Element Cylindrical Electrostatic Lens Parameters Using Dynamic Artificial Neural Network
    Autorzy:
    Isik, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1189865.pdf
    Data publikacji:
    2015-06
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    84.35.+i
    07.05.Mh
    41.85.Ne
    Opis:
    Two-element cylindrical electrostatic lens systems allowed to control low energy electron or charged particle beam have great importance. In this context, dynamic artificial neural network using nonlinear autoregressive exogenous model has been utilized to predict optimum linear magnification and overall voltage values for these lens designs. The focusing characteristics of electron beam in two-element cylindrical lens systems are investigated with two different nonlinear autoregressive exogenous based artificial neural network models. First artificial neural network model is employed for predicting of voltage ratios of lenses and magnification values. This model interpolates among the object (P) and image positions (Q) and finally finds optimum voltage ratios and magnification values through training dataset. Due to the deviations of electron trajectories in a real lens system, the spherical aberration effects are also taken into account to determine the optimal lens parameters. Therefore, the second artificial neural network model is constructed for predicting spherical aberration coefficients in image point. For each of artificial neural network models, training, test and validation data set are obtained from SIMION 8.1 ion and electron optics software. Artificial neural network model outputs are compared with the SIMION data and very good agreements are found. While artificial neural network is frequently applied in different fields, this is the first study that uses dynamic artificial neural network to predict the parameters of electrostatic lens. It is believed that this pioneering work will be a guide for the future investigations in lens design systems.
    Źródło:
    Acta Physica Polonica A; 2015, 127, 6; 1717-1721
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Investigation of Electron-Optical Parameters Using Artificial Neural Networks
    Autorzy:
    Isik, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1192484.pdf
    Data publikacji:
    2015-04
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    41.85.Ne
    07.05.Rm
    84.35.+I
    07.05.Mh
    Opis:
    The optimization of scientific instruments is crucially important to increase the quality of measurements. A major challenge for the development of these experimental tools is the precise determination of focal parameters. Therefore, usage of an innovative technique that meets our requirements is desirable. Among intelligent algorithms, artificial neural network (ANN) has an advantage of obtaining the optical parameters data with high accuracy. One of the most popular geometries used in electrostatic optical devices is geometry with cylinder lenses. In this study, the artificial neural network is applied for the first time to the subject of the magnification parameters of three-element electrostatic cylinder lenses for a wide range of values of the applied voltages. ANN-based optimization has been performed using Matlab/Simulink, and the performance analysis has also been conducted. High-performance results have been achieved using ANN approach. The commercial simulation package SIMION software is used as a data source for artificial neural network results. This approach provides new perspectives for the effective solution for the problems related to electrostatic lenses with different geometries.
    Źródło:
    Acta Physica Polonica A; 2015, 127, 4; 1317-1319
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Analysis of Radial Dependence of the Localized Magnetic Field using Artificial Neural Networks
    Autorzy:
    Isık, A.
    Isık, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/1030376.pdf
    Data publikacji:
    2017-01
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    42.79.Fm
    07.05.Tp
    07.77.-n
    Opis:
    The measurements of the angular distributions of charged particles have a long history in atomic and molecular collision studies. To detect all electrons originating from collision has great importance in experimental studies. Due to the physical constraints of the experimental instruments, electrons in definite angles can be detected. Magnetic angle changer is designed to steer electrons scattered at undetectable angles. The magnetic angle changer is a source of the localized magnetic field. A well-controlled magnetic field in the interaction region changes the angles of the electron trajectories. In this study, artificial neural networks have been performed to obtain variation of the magnetic field strength as a function of radial distance calculated from boundary element method. A stringent quality filter is used for data to produce more robust artificial neural network based prediction. The results indicate that the well-trained artificial neural networks can predict the effect on the radial dependence of the localized magnetic field with tremendous precision. It is believed that this study will introduce a new insight into collision studies.
    Źródło:
    Acta Physica Polonica A; 2017, 131, 1; 32-33
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Classification of Electron Gun Operation Modes Using Artificial Neural Networks
    Autorzy:
    Isik, N.
    Isik, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1186983.pdf
    Data publikacji:
    2016-04
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    41.85.Ne
    07.05.Rm
    84.35.+I
    07.05.Mh
    Opis:
    In electron collision experiments, the seven-element electron gun is commonly used to accelerate and focus an electron beam. The main operation modes of this experimental device are afocal, zoom and broad beam-modes. Each of these operation modes can be used for producing electron beam with desired diameter. In this study, the artificial neural network classification technique (ANN) is used for classification of electron gun operation modes depending on electrostatic lens voltages. For this purpose, we investigate the focusing condition for the first three-element lens. Other ANN is employed for the second four-element lens voltages to find the electron gun operation modes. A comprehensive training data is obtained from SIMION software which uses traditional ray-tracing method. ANNs are trained with this dataset. Moreover, performance evaluations are carried out to determine the classification power of ANNs. High performance values show that the ANN can easily categorize the operation mode of the electron gun as a function of lens voltages. The proposed approach may help to adjust electron gun voltages before collision experiments. It is believed that this study will be a model for the future research in electron collision systems. Network can be trained with experimental data for practical applications.
    Źródło:
    Acta Physica Polonica A; 2016, 129, 4; 628-630
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Time Series Artificial Neural Network Approach for Prediction of Optical Lens Properties
    Autorzy:
    Isik, A.
    Isik, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/1398712.pdf
    Data publikacji:
    2016-04
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    41.85.Ne
    07.05.Tp
    84.35.+I
    07.05.Mh
    Opis:
    Well-designed electrostatic cylindrical lenses are commonly used to control charged particles in atomic and molecular physics instruments such as electron guns and electron microscopes. The most commonly used of these, three-element electrostatic lenses are capable of keeping magnification constant for definite image position. The correct determination of focal and aberration characteristics of these lenses is very important for experimental studies. In this study, motions of electrons in three-element electrostatic cylindrical lenses have been investigated with nonlinear autoregressive exogenous based time series artificial neural network technique. The spherical and chromatic aberrations which affect the beam are also predicted with time series artificial neural network technique. This method is a mathematical model that emulates the biological neural networks. The basic working principle of time series artificial neural network technique is training of network with the known data and then prediction of the unknown data. Simulation results from SIMION 8.1 ray-tracing program are used as training and test data set. According to the results obtained from time series artificial neural network technique technique, a considerably agreement is found between simulation and artificial neural network technique prediction results. The study shows that such an artificial neural network model which has time advantage can be applicable to various electron and ion beam apparatus.
    Źródło:
    Acta Physica Polonica A; 2016, 129, 4; 514-516
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of First Order Focusing Properties of Ideal Hemispherical Deflector Analyzer Using Artificial Neural Network
    Autorzy:
    Isik, N.
    Isik, A.
    Sise, O.
    Guvenc, U.
    Powiązania:
    https://bibliotekanauki.pl/articles/1030354.pdf
    Data publikacji:
    2017-01
    Wydawca:
    Polska Akademia Nauk. Instytut Fizyki PAN
    Tematy:
    42.79.Fm
    07.05.Tp
    Opis:
    Electrostatic energy analyzers are irreplaceable instruments to analyze the electron beams energies. In this context, the knowledge of electron trajectories in electrostatic energy analyzers has major importance in collision physics as well as in different scientific instruments for surface science. In this study, electron trajectories for different energies in an ideal field 180° hemispherical deflector analyzer are investigated by artificial neural network prediction method. The SIMION 8.1 simulation program is used as a data source for training and testing of artificial neural network. Artificial neural network based prediction has been performed using Matlab R2012b program. Obtained performance results indicate that this approach provides new perspectives for the rapid solution to the problems in charged particle optics.
    Źródło:
    Acta Physica Polonica A; 2017, 131, 1; 10-12
    0587-4246
    1898-794X
    Pojawia się w:
    Acta Physica Polonica A
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Prediction of Surface Temperature in Drilling of Ti6Al4V
    Przewidywanie temperatury powierzchni podczas wiercenia stopu Ti6Al4V
    Autorzy:
    Işik, B.
    Kentli, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/353425.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    machining
    Ti6Al4V
    heat effect
    drilling
    regression analysis
    obróbka
    efekt cieplny
    wiercenie
    analiza regresji
    Opis:
    Titanium and its alloys are attractive materials due to their unique high strength-weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. The major application of titanium has been in the aerospace industry. However, the focus shift of market trends from military to commercial and aerospace to industry also been reported. On the other hand, titanium and its alloys are notorious for their poor thermal properties and are classified as difficult-to-machine materials. These properties limit the use of these materials especially in the markets where cost is much more of a factor than in aerospace. Machining is an important manufacturing process because it is almost always involved if precision is required and is the most effective process for small volume production. Due to the low machinability of the alloys under study, selecting the machining conditions and parameters is crucial. The range of feeds and cutting speeds, which provide a satisfactory tool life, is very limited. On the other hand, adequate tool, coating, geometry and cutting flow materials should be used: otherwise, the high wear of the tool, and the possible tolerance errors, would introduce unacceptable flaws in parts that require a high degree of precision. In this study, heat changes of Ti6Al4V has been examined on the basis of cutting parameters such as depth of cut, feedrate and cutting speed during drilling. Heat changes of the material and tool was monitored by a thermal camera. Maximum temperatures of the experiments were taken to examine optimum cutting parameters. Obtained results have been used to generate a regression analysis and it is seen that regression has given accurate data.
    Tytan i jego stopy to atrakcyjne materiały ze względu na ich unikalnie wysoki stosunek wytrzymałości do ciężaru właściwego, utrzymywany w podwyższonej temperaturze i ich wyjątkową odporność na korozję. Głównym zastosowaniem tytanu jest przemysł lotniczy. Jednak zmiana trendów na rynku z wojskowego na cywilny i z przemysłu lotniczego na inne gałęzie przemysłu jest również obserwowana. Z drugiej strony tytan i jego stopy są znane z ich słabych właściwości termicznych i są klasyfikowane jako materiały trudne w obróbce. Właściwości te ograniczają wykorzystywanie tych materiałów zwłaszcza na rynkach, na których koszt jest znacznie większym czynnikiem niż w przemyśle lotniczym. Obróbka mechaniczna jest ważnym procesem wytwarzania, ponieważ prawie zawsze ma miejsce, jeżeli wymagana jest precyzja i jest to najbardziej skuteczny sposób wytwarzania małych objętości. Ze względu na niską obrabialność stopów badanych, dobór warunków obróbki i parametrów jest krytyczny. Zakres posuwów i prędkości skrawania, które zapewniają zadowalającą trwałość narzędzia, jest bardzo ograniczony. Z drugiej strony, należy stosować odpowiedni materiał narzędzia, powłoki, geometrię, w przeciwnym razie wysokie zużycie narzędzia i ewentualne błędy tolerancji wprowadzą niedopuszczalne błędy w częściach które wymagają wysokiego stopnia precyzji. W pracy badano zmiany cieplne w stopach Ti6A14V wynikające z parametrów cięcia takich jak głębokość skrawania, posuw i prędkość skrawania podczas wiercenia. Zmiany cieplne materiału i narzędzia monitorowano za pomocą kamery termicznej. Maksymalne wartości temperatury eksperymentów zostały dobrane w celu zbadania optymalnych parametrów skrawania. Otrzymane wyniki wykorzystano do analizy regresji i jest widoczne, że regresja daje dokładne dane.
    Źródło:
    Archives of Metallurgy and Materials; 2014, 59, 2; 467-471
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Influence of Waste Toothbrush Fiber on Strength and Freezing–Thawing Behavior in High Plasticity Clay
    Autorzy:
    Isik, Fatih
    Akbulut, R. Kagan
    Zaimoglu, A. Sahin
    Powiązania:
    https://bibliotekanauki.pl/articles/1845156.pdf
    Data publikacji:
    2021
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    waste material
    polypropylene fiber
    toothbrush bristle
    freezing–thawing
    unconfined compression test
    reinforced clay
    Opis:
    The use of waste materials in civil engineering applications has gained importance nowadays. Consuming limited natural resources and increasing waste disposal costs have led researchers to evaluate waste materials for different geotechnical applications. In this respect, some waste materials are used as reinforcement in soils to improve their engineering properties. The main objective of this paper was to investigate the usability of waste polypropylene fiber as a reinforcement material in high plasticity fine-grained soils. For this purpose, waste toothbrush bristle (WTB) was used as a polypropylene fiber reinforcement material and added to fine-grained soil at ratios of 0.2%, 0.4%, 0.6% and 0.8% by dry total weight. The effect of WTB on freezing–thawing behavior and unconfined compression strength of unreinforced and reinforced clayey soil was evaluated. The results indicated that addition of WTB to high plasticity clay improved its behavior against freezing–thawing. Also, undrained shear strength increases with respect to increment in WTB ratio.
    Źródło:
    Studia Geotechnica et Mechanica; 2021, 43, 1; 15--21
    0137-6365
    2083-831X
    Pojawia się w:
    Studia Geotechnica et Mechanica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Pollen morphology in the tribe Nigelleae (Ranunculaceae): a worldwide palynological investigation into the species
    Autorzy:
    Isik, S.
    Donmez, E.O.
    Aydin, Z.U.
    Donmez, A.A.
    Powiązania:
    https://bibliotekanauki.pl/articles/2117898.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    Garidella
    Komaroffia
    multivariate analysis
    Nigella
    Ranunculaceae
    pollen morphology
    Opis:
    The pollen morphology of many collections of taxa of the tribe Nigelleae from the family Ranunculaceae which occur worldwide is presented in this study. A total of 88 specimens from 21 taxa, some of which were recently proposed, belonging to the genera Komaroffia, Garidella, and Nigella of Nigelleae were examined using light microscopy (LM) and scanning electron microscopy (SEM). In the tribe, the pollen type is mostly trizonocolpate, but in many taxa and specimens, both trizonocolpate and non-trizonocolpate types occur together. The pollen grains are small to medium (25–53.75 μm × 20–55 μm) in size and oblate to prolate in shape. The exine pattern at the mesocolpium in all the taxa investigated is similar: micro-echinate in LM and micro-echinate-punctate in SEM. The colpus membrane in Komaroffia and Nigella is micro-echinate in both LM and SEM. In Garidella, it is micro-echinate in LM but echinate (spinulose) in SEM. In this study, multivariate analyses, principal component analysis (PCA), and unweighted pair group method with arithmetic mean (UPGMA), were used to evaluate relationships between the genera and species within the tribe with respect to pollen morphology. PCA results show three main groups in the tribe: Garidella, Komaroffia, and Nigella. Moreover, the UPGMA tree also chiefly supports generic segregation into the smaller genera. An overall synthesis of the pollen characteristics of the three genera is provided and discussed.
    Źródło:
    Acta Biologica Cracoviensia. Series Botanica; 2019, 61, 1; 93-102
    0001-5296
    Pojawia się w:
    Acta Biologica Cracoviensia. Series Botanica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

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