Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "Kumar, Harish" wg kryterium: Autor

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-4 z 4
    Tytuł:
    An experimental study of solar air heater using arc shaped wire rib roughness based on energy and exergy analysis
    Autorzy:
    Ghritlahre, Harish Kumar
    Powiązania:
    https://bibliotekanauki.pl/articles/1955008.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial roughness
    energy analysis
    exergy analysis
    solar air heater
    Opis:
    In the present study, energy and exergy analysis has been evaluated for roughened solar air heater (SAH) using arc shaped wire ribs. To achieve this aim, two different types of flow arrangement have been considered. These arrangements are: apex upstream flow and apex downstream flo. In addition to this, a smooth duct SAH has been used for comparative study. The experiments were performed using the mass flow rate of 0.007– 0.022 kg/s on outdoor condition at Jamshedpur city of India. The absorber plate roughness geometry has been designed with relative roughness height 0.0395, rib size 2.5 mm, relative roughness pitch 10 and arc angle 60◦ . The energetic and exergetic performances have been examined on the basis of the first and second law of thermodynamics. According to the results, there is observed to be the maximum thermal efficiency and exergy efficiency as 73.2% and 2.64%, respectively, for apex upstream flow SAH at 0.022 kg/s, while, at same mass flow rate the maximum thermal efficiency and exergy efficiency is obtained as 69.4% and 1.89%, respectively, for apex downstream flow SAH. In addition to this, results reported that the maximum outlet temperature and temperature difference observed at lower mass flow rate. Also examined the outlet air temperature of SAH with various mass flow rates is very important for both analysis.
    Źródło:
    Archives of Thermodynamics; 2021, 42, 3; 115-139
    1231-0956
    2083-6023
    Pojawia się w:
    Archives of Thermodynamics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A comprehensive review on energy and exergy analysis of solar air heaters
    Autorzy:
    Ghritlahre, Harish Kumar
    Sahu, Piyush Kumar
    Powiązania:
    https://bibliotekanauki.pl/articles/240351.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    solar energy
    energy
    exergy analysis
    solar air heater
    thermal performance
    Opis:
    For economic growth of nation, the energy plays an important role. The excessive use of fossil fuels results the increase in global warming and depleting the resources. Due to this reason, the renewable energy sources are creating more attraction for researchers. In renewable energy sector, solar energy is the most abundant and clean source of energy. In solar thermal systems, solar air heater (SAH) is the main system which is used for heating of air. As it is simple in construction and cheaper in cost, it is of main interest for the researchers. The concept of first law and second law of thermodynamics is used for the study of the energy and exergy analysis respectively. The energy analysis is of great importance for the study of process effectiveness while the exergetic analysis is another significant concept to examine the actual behavior of process involving various energy losses and internal irreversibility. For efficient utilization of solar energy, the exergy analysis is very important tool for optimal design of solar air heaters. The aim of the present work is to review the works related to energy and exergy analysis of various types of solar air heaters and to find out the research gap for future work.
    Źródło:
    Archives of Thermodynamics; 2020, 41, 3; 183-222
    1231-0956
    2083-6023
    Pojawia się w:
    Archives of Thermodynamics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modelling of back propagation neural network to predict the thermal performance of porous bed solar air heater
    Autorzy:
    Ghritlahre, Harish Kumar
    Prasad, Radha Krishna
    Powiązania:
    https://bibliotekanauki.pl/articles/240570.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    solar air heater
    porous bed
    thermal performance
    artificial neural network
    Levenberg-Marquardt algorithm
    Opis:
    The objective of present work is to predict the thermal performance of wire screen porous bed solar air heater using artificial neural network (ANN) technique. This paper also describes the experimental study of porous bed solar air heaters (SAH). Analysis has been performed for two types of porous bed solar air heaters: unidirectional flow and cross flow. The actual experimental data for thermal efficiency of these solar air heaters have been used for developing ANN model and trained with Levenberg-Marquardt (LM) learning algorithm. For an optimal topology the number of neurons in hidden layer is found thirteen (LM-13).The actual experimental values of thermal efficiency of porous bed solar air heaters have been compared with the ANN predicted values. The value of coefficient of determination of proposed network is found as 0.9994 and 0.9964 for unidirectional flow and cross flow types of collector respectively at LM-13. For unidirectional flow SAH, the values of root mean square error, mean absolute error and mean relative percentage error are found to be 0.16359, 0.104235 and 0.24676 respectively, whereas, for cross flow SAH, these values are 0.27693, 0.03428, and 0.36213 respectively. It is concluded that the ANN can be used as an appropriate method for the prediction of thermal performance of porous bed solar air heaters.
    Źródło:
    Archives of Thermodynamics; 2019, 40, 4; 103-128
    1231-0956
    2083-6023
    Pojawia się w:
    Archives of Thermodynamics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Solar air heater performance prediction using artificial neural network technique with relevant input variables
    Autorzy:
    Ghritlahre, Harish Kumar
    Chandrakar, Purvi
    Ahmad, Ashfaque
    Powiązania:
    https://bibliotekanauki.pl/articles/240435.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial neural network
    solar air heater
    thermal performance
    multilayer perceptron
    Opis:
    Solar air heater (SAH) is an important device for solar energy utilization which is used for space heating, crop drying, timber seasoning etc. Its performance mainly depends on system parameters, operating parameters and meteorological parameters. Many researchers have been used these parameters to predict the performance of SAH by analytical or conventional approach and artificial neural network (ANN) technique, but performance prediction of SAH by using relevant input parameters has not been done so far. Therefore, relevant input parameters have been considered in this study. Total ten parameters were used such as mass flow rate, ambient temperature, wind speed, relative humidity, fluid inlet temperature, fluid mean temperature, plate temperature, wind direction, solar elevation and solar intensity to find out the relevant parameters for ANN prediction. Seven different neural models have been constructed using these parameters. In each model 10 to 20 neurons have been selected to find out the optimal model. The optimal neural models for ANN-I, ANN-II, ANN-III, ANN-IV, ANN-V, ANN-VI and ANN-VII were obtained as 10-17-1, 8-14-1, 6-16-1, 5- 14-1, 4-17-1, 3-16-1 and 2-14-1, respectively. It has been found that ANN-II model with 8-14-1 is the optimal model as compared to other neural models. Values of the sum of squared errors, mean relative error, and coefficient of determination were found to be 0.02138, 1.82% and 0.99387, respectively, which shows that the ANN-II developed with mass flow rate, ambient temperature, inlet and mean temperature of air, plate temperature, wind speed and direction, relative humidity, and relevant input parameters performed better. The above results show that these eight parameters are relevant for prediction.
    Źródło:
    Archives of Thermodynamics; 2020, 41, 3; 255-282
    1231-0956
    2083-6023
    Pojawia się w:
    Archives of Thermodynamics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies