Wszystkie pola: Kononenko - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Impact from Counterion Nature on Current Transfer Through Structural Fragments of Sulphocationic Resin
Autorzy:: Malovanyy, Myroslav
Kononenko, Natalia
Demina, Olga
Petrushka, Kateryna
Powiązania:: https://bibliotekanauki.pl/articles/124840.pdf
Data publikacji:: 2019
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: ion-exchange resin
counter-ions
extended three-wire model
conductivity
Opis:: The parameters of an extended three-wire model of ion-exchange materials conductivity, which characterize the current particles flowing through various structural fragments of the ion exchanger, were calculated based on the concentration dependence of the sulphocationite KU-2 resin electrical conductivity in electrolyte solutions of different nature. It was shown that most of the current in the resin is transferred through the channel with a consecutive arrangement of conducting gel and solution phases, regardless of the counterion nature. The differences in model parameters for the resin in the salt and proton form, related to the specific mechanism of proton transfer, confirmed the adequacy of the applied approach to the estimation of the counterion nature effect on the current transfer in resin.
Źródło:: Journal of Ecological Engineering; 2019, 20, 3; 7-12
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: The Long-Term Prediction of Landslide Processes within the Precarpathian Depression of the Cernivtsi Region of Ukraine
Autorzy:: Hablovskyi, Bohdan
Hablovska, Nadiia
Shtohryn, Liudmyla
Kasiyanchuk, Dmytro
Kononenko, Maryna
Powiązania:: https://bibliotekanauki.pl/articles/27323822.pdf
Data publikacji:: 2023
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: engineering-geological area
landslide
statistical method
factor
time series
forecast
Opis:: The purpose of this publication was the long-term forecasting of the landslide processes activation for the territory of the Precarpathian depression within the Chernivtsi region, taking into account the complex effect of natural factors. On the basis of statistical analysis and processing of long-term observations of landslide activation and natural time factors in particular solar activity, seismicity, groundwater levels, precipitation and air temperature, the relationship was analysed, the main periods of landslide activation were determined, the contribution of each time factor to the complex probability indicator of landslide development was estimated and long-term forecasting was carried out. An analysis of the influence of geomorphology on the landslide development was performed by using GIS MapІnfo. By means of cross-correlation, Fourier spectral analysis, the periodicities were analysed and the relationships between the parameters were established. It was found that the energy of earthquakes precedes the activation of landslides by 1 year, which indicates the “preparatory” effect of earthquakes as a factor that reduces the stability of rocks. The main periodicities of the forecast parameters of 9–11, 19–21, 28–31 years were highlighted, which are consistent with the rhythms of solar activity. The forecasting was carried out using artificial neural networks and the prediction function of the Mathematical package Mathcad, based on the received data, the activation of landslides is expected in 2023–2026, 2030–2035, 2040–2044 with some short periods of calm. The main periods of the dynamics of the time series of landslides and natural factors for the territory of the Precarpathian depression within the Chernivtsi region were determined, and a long-term forecast of landslides was made. Taking into account the large areas of the spread of landslide processes, forecasting the likely activation is an important issue for this region, the constructed predictive time models make it possible to assess the danger of the geological environment for the purpose of early warning and making management decisions aimed at reducing the consequences of a natural disaster.
Źródło:: Journal of Ecological Engineering; 2023, 24, 7; 254--262
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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