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    Wyświetlanie 1-4 z 4
    Tytuł:
    Fractal analysis of sandstone pore space geometry
    Autorzy:
    Figiel, M.
    Lewandowska-Śmierzchalska, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/298840.pdf
    Data publikacji:
    2018
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    pore space
    fractal structure
    fractal dimension
    lacunarity
    thin-section
    computer image analysis
    Opis:
    Fractal analysis is currently one of the fastest evolving branches of science. Numerous objects in nature exhibit a fractal structure. Additionally, the vast majority of rocks – especially reservoir rocks – take the form of a fractal. Computer image analysis based on thin-section images has been used for examining the fractal structure of pore spaces, directly applying the definition of the fractal box-counting dimension. For the examined sandstone sample, thin sections were made and photographed, and the corresponding values of the fractal dimension and lacunarity were calculated. Each of the photos was encompassed by porosity that was calculated based on the number of pixels. Furthermore, the volatility of the fractal dimension and lacunarity were studied as well as their relationships with the porosity. A correlation analysis between the fractal parameters and the porosity was carried out. The results were compared with the data obtained from a mercury porosimetry of the same sample of sandstone.
    Źródło:
    AGH Drilling, Oil, Gas; 2018, 35, 2; 377-389
    2299-4157
    2300-7052
    Pojawia się w:
    AGH Drilling, Oil, Gas
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Delivery-flow routing and scheduling subject to constraints imposed by vehicle flows in fractal-like networks
    Autorzy:
    Bocewicz, G.
    Banaszak, Z.
    Nielsen, I.
    Powiązania:
    https://bibliotekanauki.pl/articles/229533.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    transport network
    fractal structure
    declarative modeling
    multimodal processes
    delivery flow
    vehicles flow
    Opis:
    The problems of designing supply networks and traffic flow routing and scheduling are the subject of intensive research. The problems encompass the management of the supply of a variety of goods using multi-modal transportation. This research also takes into account the various constraints related to route topology, the parameters of the available fleet of vehicles, order values, delivery due dates, etc. Assuming that the structure of a supply network, constrained by a transport network topology that determines its behavior, we develop a declarative model which would enable the analysis of the relationships between the structure of a supply network and its potential behavior resulting in a set of desired delivery-flows. The problem in question can be reduced to determining sufficient conditions that ensure smooth flow in a transport network with a fractal structure. The proposed approach, which assumes a recursive, fractal network structure, enables the assessment of alternative delivery routes and associated schedules in polynomial time. An illustrative example showing the quantitative and qualitative relationships between the morphological characteristics of the investigated supply networks and the functional parameters of the assumed delivery-flows is provided.
    Źródło:
    Archives of Control Sciences; 2017, 27, 2; 135-150
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of CEC using fractal parameters by artificial neural networks
    Autorzy:
    Bayat, H.
    Davatgar, N.
    Jalali, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/25675.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Instytut Agrofizyki PAN
    Tematy:
    cation exchange capacity
    prediction
    fractal structure
    fractal theory
    particle size distribution
    artificial neural network
    pedotransfer function
    Opis:
    The prediction of cation exchange capacity from readily available soil properties remains a challenge. In this study, firstly, we extended the entire particle size distribution curve from limited soil texture data and, at the second step, calculated the fractal parameters from the particle size distribution curve. Three pedotransfer functions were developed based on soil properties, parameters of particle size distribution curve model and fractal parameters of particle size distribution curve fractal model using the artificial neural networks technique. 1 662 soil samples were collected and separated into eight groups. Particle size distribution curve model parameters were estimated from limited soil texture data by the Skaggs method and fractal parameters were calculated by Bird model. Using particle size distribution curve model parameters and fractal parameters in the pedotransfer functions resulted in improvements of cation exchange capacity predictions. The pedotransfer functions that used fractal parameters as predictors performed better than the those which used particle size distribution curve model parameters. This can be related to the non-linear relationship between cation exchange capacity and fractal parameters. Partitioning the soil samples significantly increased the accuracy and reliability of the pedotransfer functions. Substantial improvement was achieved by utilising fractal parameters in the clusters.
    Źródło:
    International Agrophysics; 2014, 28, 2
    0236-8722
    Pojawia się w:
    International Agrophysics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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