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Regression comparison of organic working mediums for low grade heat recovery operating on Rankine cycle

Shahinfard S., Beyene A.

Journal of Power Technologies

2013

Vol. 93, nr 4

257--270

A logistic-regression based classifier is developed here to predict the probability of any working fluid as a desirable candidate for ultra-low grade heat driven organic Rankine cycle. Global warming abilities, ozone depleting potentials as well as thermodynamic properties of the working medium are used to develop this generalized classifier. As a validation of the suggested classifier, more than 80 working fluids are screened, and regression analyses used to rate the most appropriate candidates. The preferable working mediums among those evaluated based on environmental impacts are HFCs. Considering environmental issues, safety concerns, and performance characteristics however, the preferable working fluids among those tested are HFC-245fa, followed by HFC-134a, HFC-227ea, HFC-236ea, HFC-236fa, HC-600, HC-600a, HC-601, and HC-601a.

Działalność programu Industrial Assessment Center (IAC) fundowanego przez amerykański departament energii (Department of energy -DOE)

Śmiech M., Beyene A., Badyda K., Miller A.

Prace Naukowe Politechniki Warszawskiej. Konferencje

1999

z. 17

203-210

Niniejszy referat zawiera opis sposobu funkcjonowania programu Industrial Assessment Center (IAC) finansowanego przez Amerykański Departament Energii (Department of Energy - DOE), na przykładzie działalności na Uniwersytecie Stanowym w San Diego (San Diego State University - SDSU) w Kaliforni. Doświadczenia zostały zebrane w ramach umowy o współpracy pomiędzy Instytutem Techniki Cieplnej PW, a IAC - SDSU.

This paper describes the Industrial Assessment Center (IAC) Program; funded by U.S. Department of Energy (DOE), based on the activity of the IAC at San Diego State University (SDSU), California. That experience was achieved thanks to the agreement between the Institute of Heat Engineering, Warsaw University of Technology and IAC, SDSU.