NESTER, RYAN TIMOTHY. Organic Rankine Cycles: A Comparative Study and Analysis of Multiple Applications.

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NESTER, RYAN TIMOTHY. Organic Rankine Cycles: A Comparative Study and Analysis of Multiple Applications. ( nester-ryan-timothy-organic-rankine-cycles-comparative-study )

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The previous graphs display the expected trends. It was expected that the sun would be highest in the sky close to solar noon. It was also expected that the sun would be higher in the sky during the summer months than the winter months. When the sun is higher in the sky it also emits more insolation which means the collectors can absorb more heat at these times. These insolation values were calculated following the same procedure as above but an air mass correction factor had to be calculated. Since the air mass index can theoretically approach infinity a maximum value was set at 7. This value was chosen because after this threshold the air mass index did not seem to affect the amount of absorbed radiation as much. These values appear to be accurate since the highest amount of total radiation on the collector is less than but close to the maximum theoretical value of 1000 W/m2. A main problem with these results is that they do not include cloud cover or shading effects and are only theoretical values. Since there are many problems with these calculated values it was assumed that they would be too inaccurate to be used to calculate actual performance of the STORC. Instead the values used to calculate the performance of the cycle and the actual operating parameters were obtained from NASA’s solar and meteorological database and are based on a 22-year average. These values are based on a monthly daily average which means that the value in question was measured for 22 years and the average monthly value was taken to be an average day in that month and is assumed to be an accurate measurement of the value for everyday of that month. It was decided that these values would provide a better actual idea of how well the device would perform since they would include cloud cover and many other variations in solar data. 85

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