Novel Automotive Waste Heat Recovery Techniques

The United States transportation industry is predicted to consume approximately 13 million barrels of liquid fuel per day by 2025. If one percent of the fuel energy were salvaged through waste heat recovery, there would be a reduction of 130 thousand barrels of liquid fuel per day. This dissertation focuses on automotive waste heat recovery techniques with an emphasis on two novel techniques. The first technique investigated was a combination coolant and exhaust-based Rankine cycle system, which utilized a patented piston-in-piston engine technology. The research scope included a simulation of the maximum mass flow rate of steam (700 K and 5.5 MPa) from two heat exchangers, the potential power generation from the secondary piston steam chambers, and the resulting steam quality within the steam chamber. The secondary piston chamber provided supplemental steam power strokes during the engine's compression and exhaust strokes to reduce the pumping work of the engine. A Class-8 diesel engine, operating at 1,500 RPM at full load, had a maximum increase in the brake fuel conversion efficiency of 3.1%. The second technique investigated the implementation of thermoelectric generators on the outer cylinder walls of a liquid-cooled internal combustion engine. The research scope focused on the energy generation, fuel energy distribution, and cylinder wall temperatures. The analysis was conducted over a range of engine speeds and loads in a two cylinder, 19.4 kW, liquid-cooled, spark-ignition engine. The cylinder wall temperatures increased by 17% to 44% which correlated well to the 4.3% to 9.5% decrease in coolant heat transfer. Only 23.3% to 28.2% of the heat transfer to the coolant was transferred through the TEG and TEG surrogate material. The gross indicated work decreased by 0.4% to 1.0%. The exhaust gas energy decreased by 0.8% to 5.9%. Due to coolant contamination, the TEG output was not able to be obtained. TEG output was predicted from cylinder wall temperatures and manufacturer documentation, which was less than 0.1% of the cumulative heat release. Higher TEG conversion efficiencies, combined with greater control of heat transfer paths, would be needed to improve energy output and make this a viable waste heat recovery technique.

Comportamiento metabólico, fisiológico y electrocardiográfico en trabajadores expuestos a altas temperaturas en una empresa líder en la explotación y coquización del carbón en Boyacá, Colombia, 2016

Objetivo: Establecer la relación entre la exposición ocupacional a altas temperaturas o sobrecarga térmica con el comportamiento fisiológico, metabólico y electrocardiográfico. Métodos: estudio de corte transversal, donde se incluyeron dos grupos (expuesto y no expuesto a altas temperaturas) en una empresa minera, en el departamento de Boyacá, Colombia, en el año 2016. El número de participantes fue de 160 trabajadores del género masculino, grupo expuesto (n=86) y grupo no expuesto (n=74). La exposición ocupacional a sobrecarga térmica se evaluó con el índice de temperatura de globo y bulbo húmedo (TGBH), el comportamiento fisiológico con el índice de costo cardiaco relativo (ICCR) con mediciones de frecuencia cardiaca (FC), el comportamiento metabólico con la determinación del colesterol total (CT), colesterol de alta densidad (C-HDL), colesterol de baja densidad (C-LDL), triglicéridos (TG) y glicemia basal (GL). Las alteraciones electrocardiográficas con la toma de Electrocardiograma de 12 derivaciones. También fueron evaluadas variables antropométricas, tensión arterial, hábitos y antecedentes de enfermedad cardiovascular en ambos grupos. Resultados: incrementos significativos del ICCR (p<0.001) y la carga física (p<0.001) fueron encontrados en los trabajadores expuestos a altas temperaturas. Los índices lipídicos y glicemia, así como los antecedentes personales cardiovasculares, IMC, consumo de cigarrillo y consumo de alcohol, no mostraron significancia. El antecedente familiar de ACV (p=0.043) y el EKG alterado (p=0.011) mostraron una asociación significativa con la exposición a altas temperaturas. El modelo de regresión lineal múltiple explicó la relación entre el incremento del ICCR y la exposición a altas temperaturas (β=4,213, IC 95%: 1.57,6.85) ajustado por variables fisiológicas y electrocardiográficas. Conclusiones: La exposición ocupacional a altas temperaturas, presenta asociación con las alteraciones cardiovasculares a nivel fisiológico y electrocardiográfico, aumentando el ICCR y la carga física de trabajo (GE trabajo).

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models.