Prediction of Thermal Performance of Unidirectional Flow Porous Bed Solar Air Heater with Optimal Training Function Using Artificial Neural Network

Ghritlahre, Harish Kumar; Prasad, Radha Krishna

doi:10.1016/j.egypro.2017.03.033

Cited by 61 publications

(23 citation statements)

References 10 publications

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“…Ghirtlahre and Prasad [56] have done prediction of thermal performance of unidirectional porous bed solar air heater. A process diagram of unidirectional flow SAH is shown in Figure 12.…”

Section: Performance Prediction Of Solar Water/ Air Heating Systems Umentioning

confidence: 99%

Implementation of ANN technique for performance prediction of solar thermal systems: A Comprehensive Review

Ahmad¹,

Ghritlahre²,

Chandrakar³

2020

Tr Ren Energy

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“…Ghirtlahre and Prasad [56] have done prediction of thermal performance of unidirectional porous bed solar air heater. A process diagram of unidirectional flow SAH is shown in Figure 12.…”

Section: Performance Prediction Of Solar Water/ Air Heating Systems Umentioning

confidence: 99%

Implementation of ANN technique for performance prediction of solar thermal systems: A Comprehensive Review

Ahmad¹,

Ghritlahre²,

Chandrakar³

2020

Tr Ren Energy

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“…The remaining MRE and COV are calculated by Eqs. (25) and (26) respectively. It has been found that the values of MSE, COV and MRE are very low for the predicted value of exergetic performance parameters.…”

Section: Ann Simulationmentioning

confidence: 99%

“…It has wide applications in the field of thermal engineering especially for the prediction of performance of thermal systems including solar energy systems. Many researchers have used ANN in recent years [17] to [25]. To evaluate the exergetic performance of an SAH from the actual experiments takes more time and is costlier.…”

Section: Introductionmentioning

confidence: 99%

Exergetic Performance Prediction of a Roughened Solar Air Heater Using Artificial Neural Network

2018

SV-JME

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Energy plays an essential role in the economic growth of a nation. Fossil fuels are limited and are becoming exhausted day-by-day, so it is necessary to develop alternative sources of energy. Among various types of renewable sources of energy, solar energy is one of the most abundant and clean sources. There are two ways of solar energy utilization: active and passive. A solar air heater (SAH) is in the category of active solar energy utilization. In the solar air heating system, the solar collector or absorber plate is the main component, which collects the solar radiation in the form of heat and transfers it to air flowing across it. Due to the lower value of heat capacity and low thermal conductivity of air, the convective heat transfer coefficient between the absorber plate and the air passing through it is low; thus, the major issue is to enhance the value of the heat transfer coefficient. One of the best techniques for enhancement of heat transfer coefficient is to use artificial roughness on the airflow side of the absorber plate. The use of roughness creates turbulence near the surface of absorber plate, which increases the heat transfer coefficient. Researchers (Bhushan and Singh) have studied the performance enhancement of SAHs by using artificial roughness on the absorber plate.The actual performance of SAH can be evaluated by the implementation of both energy and exergy analyses. The energy analysis alone does not give the direction of the process implementation and the information about the quality of various kinds of energies involved in the system. It also does not indicate the various internal irreversibilities. These problems are overcome by using exergy analysis [5] to [8]. In view of this, in the present investigation, the exergy analysis of roughened SAH has been carried out.Recently 0.99584, 0.99997, 0.99517, 0.99997 and 0.99983

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“…ANN with sigmoid activation functions was used to solve several issues such as inference of rivers water quality (Palani et al, 2008); electricity power demand prediction (Manohar and Reddy, 2008); and solar air-heater modeling (Ghritlahre and Prasad, 2017), among others. The typical S-shaped graph of this function is shown in Figure 11.…”

Section: Sigmoid Functionmentioning

confidence: 99%

“…The R 2 is an algorithm (Eq. 17) that is widely used in ANNs to assess the performance of models (Gholami and Fakhari, 2017), including approaches in regression, classification and predictions problems (Ghritlahre and Prasad, 2017;Moghaddam et al, 2016;Palani et al, 2008;Tetko et al, 1995;Turan et al, 2011).…”

Section: Eq 15mentioning

confidence: 99%

Applications of artificial neural networks in three agro-environmental systems: microalgae production, nutritional characterization of soils and meteorological variables management

Ortellado¹,

Manuel²

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Prediction of Thermal Performance of Unidirectional Flow Porous Bed Solar Air Heater with Optimal Training Function Using Artificial Neural Network

Cited by 61 publications

References 10 publications

Implementation of ANN technique for performance prediction of solar thermal systems: A Comprehensive Review

Implementation of ANN technique for performance prediction of solar thermal systems: A Comprehensive Review

Exergetic Performance Prediction of a Roughened Solar Air Heater Using Artificial Neural Network

Applications of artificial neural networks in three agro-environmental systems: microalgae production, nutritional characterization of soils and meteorological variables management

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