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    Wyświetlanie 1-4 z 4
    Tytuł:
    Kernel function based regression approaches for estimating the oxygen transfer performance of plunging hollow jet aerator
    Autorzy:
    Kumar, M.
    Tiwari, N. K.
    Ranjan, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/368684.pdf
    Data publikacji:
    2019
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    volumetric oxygen transfer coefficient
    multiple nonlinear regression
    Gaussian process regression
    support vector regression
    współczynnik wnikania tlenu
    regresja nieliniowa
    proces gaussowski
    regresja wektora wsparcia
    Opis:
    Purpose: To evaluate the capability of various kernels employed with support vector regression (SVR) and Gaussian process regression (GPR) techniques in estimating the volumetric oxygen transfer coefficient of plunging hollow jets. Design/methodology/approach: In this study, a data set of 81 observations is acquired from laboratory experiments of hollow jets plunging on the surface of water in the tank. The jet variables: jet velocity, jet thickness, jet length, and water depth are varied accordingly and the values of volumetric oxygen transfer coefficient is computed. An empirical relationship expressing the oxygenation performance of plunging hollow jet aerator in terms of jet variables is formulated using multiple nonlinear regression. The performance of this nonlinear relationship is compared with various kernel function based SVR and GPR models. Models developed with the training data set (51 observations) are checked on testing data set (24 observations) for performance comparison. Sensitivity analysis is carried out to examine the influence of jet variables in effecting the oxygen transfer capabilities of plunging hollow jet aerator. Findings: The overall comparison of kernels yielded good estimation performance of Radial Basis Function kernel (RBF) and Pearson VII Function kernel (PUK) using the SVR technique which is followed by nonlinear regression, and other kernel function based regression models. Research limitations/implications: The results of the study pertaining to the performance of kernels are based on the current experimental conditions and the estimation potential of the regression models may fluctuate beyond the selection of current data range due to datadependant learning of the soft computing models. Practical implications: Volumetric oxygen transfer coefficient of plunging hollow jets can be predicted precisely using SVR model by employing RBF as kernel function as compared to empirical correlation and other kernel function based regression models. Originality/value: The comparative analysis of kernel functions is conducted in this study. In previous studies, the predictive modelling approaches are implemented in simulating the aeration properties of cylindrical solid jets only, while this paper simulates the volumetric oxygen transfer coefficient of diverging hollow jets with the jet variables by utilizing polynomial, normalized polynomial, PUK, and RBF kernels in SVR and GPR.
    Źródło:
    Journal of Achievements in Materials and Manufacturing Engineering; 2019, 95, 2; 74-84
    1734-8412
    Pojawia się w:
    Journal of Achievements in Materials and Manufacturing Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Estimation of the depth of penetration in a plunging hollow jet using artificial intelligence techniques
    Autorzy:
    Bodana, D.
    Tiwari, N. M.
    Ranjan, S.
    Ghanekar, U.
    Powiązania:
    https://bibliotekanauki.pl/articles/1818515.pdf
    Data publikacji:
    2020
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    depth of penetration
    machine learning model
    classical models
    plunging hollow jets
    głębokość penetracji
    model uczenia maszynowego
    modele klasyczne
    Opis:
    Purpose: Experimental investigations assessment and comparison of different classical models and machine learning models employed with Gaussian process regression (GPR) and artificial neural network (ANN) in the estimation of the depth of penetration (Hp) of plunging hollow jets. Design/methodology/approach: In this analysis, a set of data of 72 observations is derived from laboratory tests of plunging hollow jets which impinges into the water pool of tank. The jets parameters like jet length, discharge per unit water depth and volumetric oxygen transfer coefficient (Kla20) are varied corresponding to the depth of penetration (Hp) are estimated. The digital image processing techniques is used to estimate the depth of penetration. The Multiple nonlinear regression is used to establish an empirical relation representing the depth of penetration in terms of jet parameters of the plunging hollow jets which is further compared with the classical equations used in the previous research. The efficiency of MNLR and classical models is compared with the machine learning models (ANN and GPR). Models generated from the training data set (48 observations) are validated on the testing data set (24 observations) for the efficiency comparison. Sensitivity assessment is carried out to evaluate the impact of jet variables on the depth of penetration of the plunging hollow jet. Findings: The experimental performance of machine learning models is far better than classical models however, MNLR for predicting the depth of penetration of the hollow jets. Jet length is the most influential jet variable which affects the Hp. Research limitations/implications: The outcomes of the models efficiency are based on actual laboratory conditions and the evaluation capability of the regression models may vary beyond the availability of the existing data range. Practical implications: The depth of penetration of plunging hollow jets can be used in the industries as well as in environmental situations like pouring and filling containers with liquids (e.g. molten glass, molten plastics, molten metals, paints etc.), chemical and floatation process, wastewater treatment processes and gas absorption in gas liquid reactors. Originality/value: The comprehensive analyses of the depth of penetration through the plunging hollow jet using machine learning and classical models is carried out in this study. In past research, researchers were used the predictive modelling techniques to simulate the depth of penetration for the plunging solid jets only whereas this research simulate the depth of penetration for the plunging hollow jets with different jet variables.
    Źródło:
    Archives of Materials Science and Engineering; 2020, 103, 2; 49--61
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Spatio-temporal variation of rainfall over Bihar State, India
    Przestrzenna i czasowa zmienność opadów w stanie Bihar w Indiach
    Autorzy:
    Warwade, P.
    Tiwari, S.
    Ranjan, S.
    Chandniha, S. K.
    Adamowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/293215.pdf
    Data publikacji:
    2018
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    climate change
    hydrology
    rainfall
    spatio-temporal variation
    hydrologia
    opady
    zmiana klimatu
    zmienność w czasie i przestrzeni
    Opis:
    This study detected, for the first time, the long term annual and seasonal rainfall trends over Bihar state, India, between 1901 and 2002. The shift change point was identified with the cumulative deviation test (cumulative sum – CUSUM), and linear regression. After the shift change point was detected, the time series was subdivided into two groups: before and after the change point. Arc-Map 10.3 was used to evaluate the spatial distribution of the trends. It was found that annual and monsoon rainfall trends decreased significantly; no significant trends were observed in pre-monsoon, monsoon, post-monsoon and winter rainfall. The average decline in rainfall rate was –2.17 mm·year–1 and –2.13 mm·year–1 for the annual and monsoon periods. The probable change point was 1956. The number of negative extreme events were higher in the later period (1957–2002) than the earlier period (1901–1956).
    W badaniach prezentowanych w niniejszej pracy wykryto po raz pierwszy długookresowe trendy rocznych i sezonowych wartości opadów w indyjskim stanie Bihar w latach 1901–2002. Stosując kumulatywny test odchyleń (CUSUM – ang. cumulative deviation test) i regresję liniową zidentyfikowano punkt zwrotny. Następnie serie czasowe zostały podzielone na dwie grupy: przed i po punkcie zwrotnym. Do oceny przestrzennego rozkładu trendów zastosowano program Arc-Map 10.3. Stwierdzono, że trendy rocznych i monsunowych opadów znacząco malały. Nie zaobserwowano istotnych trendów w odniesieniu do opadów przed monsunem, po monsunie i w okresie zimowym. Średnie zmniejszenie ilości opadów wynosiło 2,17 mm·rok–1 i 2,13 mm ·rok–1 odpowiednio dla opadów rocznych i monsunowych. Prawdopodobnym punktem zwrotnym był rok 1956. Liczba skrajnych negatywnych zjawisk była większa w okresie 1957–2002 niż w okresie 1901–1956.
    Źródło:
    Journal of Water and Land Development; 2018, 36; 183-197
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Studies on Viscoelastic, Thermal and Morphological Properties of Vinyl Ester - Mixed Diluents System
    Autorzy:
    Ranjan, J. K.
    Raghu Raja Pandiyan, K.
    Goswami, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/354420.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    vinyl ester resin
    dynamic mechanical analysis
    TGA
    DSC
    morphology
    Opis:
    Vinyl ester resin networks formed by using mixture of diluents were prepared. Methyl methacrylate (MMA) diluent was mixed in various proportions with vinyl ester resin which was already premixed with styrene diluent (45 wt. %). Weight ratios e.g. 80:20, 70:30 and 60:40 of VE resin: MMA diluents were studied. Viscoelastic properties of the cross-linked resin were studied by dynamic mechanical analyzer in terms of storage modulus and tanδ. Thermal analysis was performed using non-isothermal mode of Differential scanning calorimetry. The samples with mixed diluents, showed higher modulus, and glass transition temperature in comparison to that of the pure vinyl ester-styrene resin cross-linked in presence of styrene only. The difference in thermal stability between vinyl ester-styrene and vinyl ester-MMA-styrene was checked. Vinyl Ester – 20 wt. % MMA-Styrene samples have the best thermal property among all other prepared samples. Multiphase morphology was formed for the thermoset crosslinked with mixed diluents in contrast to that formed with single diluent. With increase in MMA content in the resin dispersed domain size increased.
    Źródło:
    Archives of Metallurgy and Materials; 2017, 62, 3; 1845-1850
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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