Performance analysis of solar chimney for passive cooling of the building

The solar chimney is a passive device that is applied to enhance room ventilation. The chimney could be vertical or inclined. The chimney inclination angle and air inlet opening position are important parameters that greatly affects flow pattern and ventilation rate inside the room. In this study, the effect of air inlet opening position and chimney inclination angle on air change per hour and air flow pattern inside the room was numerically investigated. A numerical simulation using CFD code was used to predict flow pattern. Then the results were compared with published experimental measurements. Find out the effect of air inlet opening position and inclination angle of chimney on mass flow rate at outlet of the chimney

Study of Traffic Forecast for Intelligent Transportation System

The number of cities, particularly those with advanced infrastructure, is increasing rapidly. There has been a steady increase in the number of automobiles on the road, which has led to severe congestion and wasted time and money. Increasing the number of roads or lanes available is a costly solution to traffic congestion. The primary objective of this research was to examine the traffic pattern using machine learning technologies, which is the optimal method in such situations. The primary objective was to compare the LSTM and ARIMA algorithms across 15-minute intervals, which is confirmed by calculating the observed error. The data obtained was then normalized and filtered to meet the requirements of this study, and machine learning methods are used to make predictions about traffic volume and average speed. Predictions from regression models can be utilized for decision-making. A prediction is a statement about how a variable will change or stay the same. A decision, on the other hand, is what to do in response to a prediction. The LSTM model has less error from the start of the project, while the ARIMA model performance improves with time or at the latter stage. The percentage error of the LSTM model is about 15% less than that of the ARIMA model, hence it can conclude that the LSTM model will perform better than the ARIMA model

Performance Study of Dual Fuel Engine Using Producer Gas as Secondary Fuel

In the present paper, development of producer gas fuelled 4 stroke diesel engine has been investigated. Producer gas from biomass has been examined and successfully operated with 4 stroke diesel engine. The effects of higher and lower loads were investigated on the dual fuel mode. The experimental investigations revealed that at lower loads dual fuel operation with producer gas shows lower efficiency due to lower combustion rate cause by low calorific value of the producer gas. Beyond 40% load the brake thermal efficiency of dual fuel operation improved due to faster combustion rate of producer gas and higher level of premixing. It can be observed that at lower load and 20% opening of producer gas the gaseous fuel substitution found to be 56% whereas at 100% opening of producer gas it reaches 78% substitution. The CO2 emission increased at high producer gas opening and high load because at 100% producer gas maximum atoms of carbons were there and at high load condition the diesel use increased. At 80% load and producer gas varying from 20% to 100. Power output was almost comparable to diesel power with marginal higher efficiency. Producer gas is one such technology which is environmentally benign and holds large promise for future