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    Wyświetlanie 1-5 z 5
    Tytuł:
    Mathematical modelling of steam-water cycle with auxiliary empirical functions application
    Autorzy:
    Szapajko, G.
    Rusinowski, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/240935.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    model pół-empiryczny
    obieg parowo-wodny
    turbina upustowo-kondensacyjna
    układ CHP
    bleed-condensing turbine
    CHP unit
    semi-empirical model
    steam-water cycle
    Opis:
    Research oriented on identification of operating states variations with the application of mathematical models of thermal processes has been developed in the field of energy processes diagnostics. Simple models, characterised by short calculation time, are necessary for thermal diagnostics needs. Such models can be obtained using empirical modelling methods. Good results brings the construction of analytical model with auxiliary empirical built-in functions. The paper presents a mathematical model of a steam-water cycle containing mass and energy balances and semi-empirical models of steam expansion line in turbine as well as heat transfer in exchangers. A model of steam expansion line in a turbine is worked out with the application of a steam flow capacity equation and an internal efficiency of process equation for each group of stages for the analysed turbine. A model of a heat exchanger contains energy balance and the relation describing heat transfer in an exchanger, proposed by Beckman. Estimation of empirical equations coefficients was realised with the application of special and reliable measurements. Estimation criterion was a weighted relative sum of the remainder squares. There are exemplary calculations results presented in the final part of paper.
    Źródło:
    Archives of Thermodynamics; 2010, 31, 3; 165-183
    1231-0956
    2083-6023
    Pojawia się w:
    Archives of Thermodynamics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Model-driven systems engineering: state-of-the-art and research challenges
    Autorzy:
    Lauder, M.
    Schlereth, M.
    Rose, S.
    Schurr, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/200678.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    model-driven development
    integration
    automation engineering
    TGG
    empirical
    Opis:
    Model-driven software engineering is a well investigated and heavily used technique for software development. Within automation engineering we want to benefit from these ideas and concepts by adopting them to systems engineering. Parallel processes in systems engineering demand high synchronization effort between different disciplines, their engineers, and processes. Unfortunately, these processes are concurrently established, but do only support sequential engineering. With model-driven systems engineering we want to enable systems engineers to model their domain knowledge and tooling on a more abstract level. Thus, engineers may benefit in increasing efficiency and quality for the resulting products from existing integration approaches of engineering artifacts and tools. By means of an integration approach we are able to synchronize and check consistency of model data that evolved parallel in different tools. In this contribution, we present a new classification scheme for integration scenarios and explain our modeling and integration approach together with a proof-of-concept use case and prototype, located in automation engineering.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2010, 58, 3; 409-421
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Mathematical modelling of thermal processes by the use of regression and neural models
    Autorzy:
    Rusinowski, H.
    Plis, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/240114.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    mathematical model
    empirical functions
    neural modeling
    regression modeling
    model matematyczny
    funkcje empiryczne
    modelowanie neuronowe
    Opis:
    The paper presents a description of used methods and exemplary mathematical models which are classified into theoretical-empirical models of thermal processes. Such models encompass equations resulting from the laws of physics and additional empirical functions describing processes for which analytical models are complex and difficult to develop. The principle of developing, advantages and disadvantages of presented models as well as quality prediction assessment were presented. Mathematical models of a steam boiler, a steam turbine as well as a heat recovery steam generator were described. Exemplary calculation results were presented and compared with measurements.
    Źródło:
    Archives of Thermodynamics; 2018, 39, 3; 111-127
    1231-0956
    2083-6023
    Pojawia się w:
    Archives of Thermodynamics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Statistical Calibration Method of Propagation Prediction Model Based on Measurement Results
    Autorzy:
    Kelner, Jan M.
    Kryk, Michał
    Łopatka, Jerzy
    Gajewski, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/226022.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    calibration of propagation model
    empirical measurements
    path loss model
    propagation
    parabolic equation method
    radio environment maps
    Opis:
    Radio environment maps (REMs) are beginning to be an integral part of modern mobile radiocommunication systems and networks, especially for ad-hoc, cognitive, and dynamic spectrum access networks. The REMs will use emerging military systems of tactical communications. The REM is a kind of database used at the stage of planning and management of the radio resources and networks, which considers the geographical features of an area, environmental propagation properties, as well as the parameters of radio network elements and available services. At the REM, for spatial management of network nodes, various methods of propagation modeling for determining the attenuation and capacity of wireless links and radio ranges are used. One method of propagation prediction is based on a numerical solution of the wave equation in a parabolic form, which allows considering, i.a., atmospheric refraction, terrain shape, and soil electrical parameters. However, the determination of a current altitudinal profile of atmospheric refraction may be a problem. If the propagation-prediction model uses a fixed refraction profile, then the calibration of this model based on empirical measurements is required. We propose a methodology for calibrating the analyzed model based on an example empirical research scenario. The paper presents descriptions of the propagation model, test-bed and scenario used in measurements, and obtained signal attenuation results, which are used for the initial calibration of the model.
    Źródło:
    International Journal of Electronics and Telecommunications; 2020, 66, 1; 11-16
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Short-term wind power combined prediction based on EWT-SMMKL methods
    Autorzy:
    Li, Jun
    Ma, Liancai
    Powiązania:
    https://bibliotekanauki.pl/articles/1955182.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    combined model
    empirical wavelet transform
    prediction
    soft margin multiple kernel learning
    wind power
    model łączony
    empiryczna transformacja falkowa
    przewidywanie
    miękki margines uczenia wielokrotnego jądra
    energia wiatrowa
    Opis:
    Since wind power generation has strong randomness and is difficult to predict, a class of combined prediction methods based on empirical wavelet transform (EWT) and soft margin multiple kernel learning (SMMKL) is proposed in this paper. As a new approach to build adaptive wavelets, the main idea is to extract the different modes of signals by designing an appropriate wavelet filter bank. The SMMKL method effectively avoids the disadvantage of the hard margin MKL method of selecting only a few base kernels and discarding other useful basis kernels when solving for the objective function. Firstly, the EWT method is used to decompose the time series data. Secondly, different SMMKL forecasting models are constructed for the sub-sequences formed by each mode component signal. The training processes of the forecasting model are respectively implemented by two different methods, i.e., the hinge loss soft margin MKL and the square hinge loss soft margin MKL. Simultaneously, the ultimate forecasting results can be obtained by the superposition of the corresponding forecasting model. In order to verify the effectiveness of the proposed method, it was applied to an actual wind speed data set from National Renewable Energy Laboratory (NREL) for short-term wind power single-step or multi-step time series indirectly forecasting. Compared with a radial basic function (RBF) kernel- based support vector machine (SVM), using SimpleMKL under the same condition, the experimental results show that the proposed EWT-SMMKL methods based on two different algorithms have higher forecasting accuracy, and the combined models show effectiveness.
    Źródło:
    Archives of Electrical Engineering; 2021, 70, 4; 801-817
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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