Fatima E. M. Alaoui

Teaching Thermodynamics to Electronic Engineers through active teaching strategies

The paper presents the experience of a structured problem-based learning approach to the teaching of a study module on Thermodynamics in the second year of an Electronic Engineering graduate program at the University of Burgos. In the light of the experience gained, a list of recommendations is presented that might prove of interest to academics interested in pursuing a similar approach.

Thermodynamic Properties of Propanol and Butanol as Oxygenate Additives to Biofuels

Alternative and renewable energy technologies are being sought throughout the world to reduce pollutant emissions and increase the efficiency of energy use. Oxygenate second-generation biofuels fuels lead to a reduction in pollutant emissions and their thermodynamic and transport properties allow that the facilities for transport, storage and distribution of fuels could be used without modification. Higher alcohols, like propanol and butanol, enhance the octane number, boosting the anti-knock effect in gasoline. Then the compression ratio of the engines can be increased without risk of knocking, leading to higher delivery of power. From the combustion point of view, the production of carbon monoxide and volatile hydrocarbons from the combustion of alcohols is less than the one of gasoline. This chapter covers mixtures of butanol and propanol with hydrocarbons. The properties reviewed are excess volume or density (VE), vapour-liquid equilibrium (VLE), and heat capacity (Cp).

Multiple regression and genetic programming for coal higher heating value estimation

ABSTRACT The higher heating value (HHV) is an important characteristic for the determination of fuels quality. Nevertheless, its experimental measurement requires intricate technologies. In this work, the HHV of coal was predicted from ultimate composition using two methods: multiple regression and genetic programming. A dataset of 100 samples from literature was exploited (75% for training and 25% for testing). A comparative study was elaborated between the developed models and published ones in terms of correlation coefficient, root mean square error, and mean absolute percent error. The adopted models gave a good statistical performance. Abbreviations: C: Carbon; CC: Correlation coefficient; H: Hydrogen; HHV: Higher heating valueI; GT: Institute of gas technology; GP: Genetic programming; LHV: Lower heating value; MAPE: Mean absolute percent error; N: Nitrogen; O: Oxygen; RMSE: Root mean square error; S: sulfur; Wt: Weight percentage