In the current article, an experimental investigation has been implemented of flow and heat transfer characteristics in a parabolic trough solar collector (PTSC) using both nano-fluids and artificial neural networks modeling. Water was used as a standard working fluid in order to compare with two different types of nano-fluid namely, nano-CuO /H2O and nano-TiO2/ H2O, both with a volume concentration of 0.02. The performance of the PTSC system was eval-uated using three main indicators: outlet water temperature, useful energy and thermal efficiency under the influence of mass flowrate ranging from 30 to 80 Lt/hr. In parallel, an artificial neural network (ANN) has been proposed to predict the thermal efficiency of PTSC depending on the experimental re-sults. An Artificial Neural Network (ANN) model consists of four inputs, one output parameter and two hidden layers, two neural network models (4-2-2-1) and (4-9-9-1) were built. The experimental results show that CuO/ H2O and TiO2/H2O have higher thermal performance than water. Overall, it was veri-fied that the maximum increase in thermal efficiency of TiO2/H2O and CuO/H2O compared to water was 7.12% and 19.2%, respectively. On the oth-er hand, the results of the model 4-9-9-1 of ANN provide a higher reliability and accuracy for predicting the Thermal efficiency than the model 4-2-2-1. The results revealed that the agreement in the thermal efficiency between the ANN analysis and the experimental results about of 91% and RMSE 3.951 for 4-9-9-1 and 86% and RMSE 5.278 for 4-2-21.
A solar water heating system has been fabricated and tested to analyze the thermal performance of Parabolic Trough Solar Collector (PTSC) using twisted tape insert inside absorber tube with twisted ratio about TR=y/w=1.33. The performance of PTSC system was evaluated by using three main important indicators: water outlet temperature (Tout), useful energy and thermal efficiency (ηth) under the effect of mass flow rate (ṁ) ranges between 0.02 and 0.04 Kg/s with the corresponding of Reynolds number (Re) range (2000 to 4000). In a parallel, a fuzzy-logic model was proposed to predict the thermal efficiency (ηth) and Nusselt number (Nu) of PTSC depending on the experimental results. The fuzzy model consists of five input and two output parameters. The input parameters include: solar intensity (I), receiver temperature (Tr), water inlet temperature (Tin), water outlet temperature (Tout) and water mass flow ( ) while, the output include the thermal efficiency (ηth) and Nu. The final results indicate that, owing to the mixture of the swirling flow of the perforated twisted-tape insert, the perforated twist tape insert enhances the heat transfer characteristics and the thermal efficiency of the PTSC system. More specifically, the use of perforate twist tape inserts enhanced the thermal efficiency by 4% to 4.5% higher than smooth absorber tube. Also, the predicted values were found to be in close agreement with the experimental counterparts with accuracy of ~92 %. So, the suggested Fuzzy model system would have high validity and precision in forecasting the success of a PTSC system compared to that of the traditional model. Pace, versatility, and the use of expert knowledge for estimation relative to those of the traditional model are the advantages of this approach
An experimental and theoretical study has been conducted to determine the thermal efficiency of a parabolic trough solar collector. The experiments have been performed during winter and summer at Tikrit-Iraq. The solar radiation of Tikrit University was calculated theoretically and a theoretical study was performed by using FORTRAN 90 program. The dimensions and specifications of the collector were entered to the program to determine the theoretical thermal efficiency. It has been found the experimental thermal efficiency of collector is less than the theoretical one in percentage between (7-15) .So the increase in water mass flow rate leads to an increase in the thermal efficiency, and there is no significant change in thermal efficiency when the water mass flow rate becomes more than forty kilograms per hour.
In this article, an experimental study of the single-pass hybrid (PV/T) collector is conducted in the climatic conditions of Fallujah city, where the experimental results are compared with a previous research to validate the results. The effect of changing the angle of inclination of the hybrid collector (PV/T) and its effect on the electrical power in the range (20°-50°) is studied. The optimum angle of the collector is found to be 30°, which gives a maximum electrical power of 58.8 W at average solar radiation of 734.35 W/m2. In another experimental study with different air flow rates ranged from 0.04 kg/s to 0163 kg/s, where it is found that the maximum electrical power of 57.66 W at an air flow rate of 0.135 kg/s, while the maximum thermal efficiency reaches 33.53% at an air flow of 0.163 kg/s at average solar radiation of 786 W/m2.
In this article, an experimental study of the single-pass hybrid (PV/T) collector is conducted in the climatic conditions of Fallujah city, where the experimental results are compared with a previous research to validate the results. The effect of changing the angle of inclination of the hybrid collector (PV/T) and its effect on the electrical power in the range (20°-50°) is studied. The optimum angle of the collector is found to be 30°, which gives a maximum electrical power of 58.8 W at average solar radiation of 734.35 W/m2. In another experimental study with different air flow rates ranged from 0.04 kg/s to 0163 kg/s, where it is found that the maximum electrical power of 57.66 W at an air flow rate of 0.135 kg/s, while the maximum thermal efficiency reaches 33.53% at an air flow of 0.163 kg/s at average solar radiation of 786 W/m2.
Internet-based platforms such as social media have a great deal of big data that is available in the shape of text, audio, video, and image. Sentiment Analysis (SA) of this big data has become a field of computational studies. Therefore, SA is necessary in texts in the form of messages or posts to determine whether a sentiment is negative or positive. SA is also crucial for the development of opinion mining systems. SA combines techniques of Natural Language Processing (NLP) with data mining approaches for developing inelegant systems. Therefore, an approach that can classify sentiments into two classes, namely, positive sentiment and negative sentiment is proposed. A Multilayer Perceptron (MLP) classifier has been used in this document classification system. The present research aims to provide an effective approach to improving the accuracy of SA systems. The proposed approach is applied to and tested on two datasets, namely, a Twitter dataset and a movie review dataset; the accuracies achieved reach 85% and 99% respectively.
In order to increase output power and thermal efficiency, the temperature going into a gas turbine is much higher than the point at which the material would melt. In order to protect the airfoil of a gas turbine from hot gas and, as a result, extend the blade's life, new internal and film cooling arrangements must be developed immediately. When the incoming air is heated, the gas turbine's output rises proportionately as well. The power output of a gas turbine is determined by the amount of mass flowing through it. Because of this, electricity generation decreases on warm days due to a decrease in air density. It takes a 1% rise in air temperature to reduce power production by 1%. The purpose of this research is to discuss current strategies for cooling incoming air to gas turbines. Mechanical chillers, evaporative coolers, and fogging methods have all been examined. This study focuses primarily on the fogging inlet air cooling system. There are many ways to cool the air going into the engine, but the high-pressure intake fogging method has become more popular over the past ten years because it costs less and makes a big difference in power.