Application of the Thermal Flash Technique for Low Thermal Diffusivity Micro/Nanofibers

The thermal flash method was developed to characterize the thermal diffusivity of micro/nanofibers without concern for thermal contact resistance, which is commonly a barrier to accurate thermal measurement of these materials. Within a scanning electron microscope, a micromanipulator supplies instantaneous heating to the micro/nanofiber, and the resulting transient thermal response is detected at a microfabricated silicon sensor. These data are used to determine thermal diffusivity. Glass fibers of diameter 15 mu m had a measured diffusivity of 1.21x10(-7) m(2)/s; polyimide fibers of diameters 570 and 271 nm exhibited diffusivities of 5.97x10(-8) and 6.28x10(-8) m(2)/s, respectively, which compare favorably with bulk values

Building electricity consumption: Data analytics of building operations with classical time series decomposition and case based subsetting

The commercial building sector consumes approximately one-fifth of U.S. total energy and exhibits significant operational inefficiencies, leaving a great opportunity to implement various energy-efficiency measures. However, conventional energy audit techniques are expensive, time-consuming, and frequently inaccurate. Conversely, classical time series decomposition of smart meter (i.e. 15 min interval) building electricity consumption provides quick, inexpensive, and useful insights to building operation and characteristics. Paired with complementary time series datasets such as outdoor temperature and solar irradiation, specific insights into HVAC scheduling, daily operational variation, and the relative impact of temperature and solar radiation were quantitatively assessed. This work analyzes six commercial buildings and identifies various building characteristics, including the potential for savings of over 700 MWh valued at $92,000 per year from building rescheduling alone. With access to only whole building smart meter data, these results are obtained virtually and instantaneously, making the case for a rigorous data analytics approach to unlock the potential of building energy efficiency

Building electricity consumption: Data analytics of building operations with classical time series decomposition and case based subsetting

The commercial building sector consumes approximately one-fifth of U.S. total energy and exhibits significant operational inefficiencies, leaving a great opportunity to implement various energy-efficiency measures. However, conventional energy audit techniques are expensive, time-consuming, and frequently inaccurate. Conversely, classical time series decomposition of smart meter (i.e. 15 min interval) building electricity consumption provides quick, inexpensive, and useful insights to building operation and characteristics. Paired with complementary time series datasets such as outdoor temperature and solar irradiation, specific insights into HVAC scheduling, daily operational variation, and the relative impact of temperature and solar radiation were quantitatively assessed. This work analyzes six commercial buildings and identifies various building characteristics, including the potential for savings of over 700 MWh valued at $92,000 per year from building rescheduling alone. With access to only whole building smart meter data, these results are obtained virtually and instantaneously, making the case for a rigorous data analytics approach to unlock the potential of building energy efficiency

Evaluating the effects of thin film patterns on the temperature distribution of silicon wafers during radiant processing

A numerical model was developed to find the temperature distributions during radiant heating of a silicon wafer with SiO2 thin film patterns. The radiative properties of silicon and the film structure were found by considering the effects of partial transparency and thin film interference. The average total properties over simple patterns with feature sizes of the order of a few micrometers were found, using an average of the properties of each region within the pattern, weighted by their relative areas. In general, wafers with a single SiO2 film or pattern reach a higher steady state temperature than a plain Si wafer due to higher total absorptivity. This applies to thin films of any thickness below several micrometers, where coherent effects are dominant. The temperature of patterned wafers vary nonlinearly with film thickness, with the highest temperature discrepancy from Si wafer occurring at film thickness of approximately 0.2 μm. For wafers with complex patterns, the temperature distributions can be estimated by the average of temperatures for simpler patterns, weighted by their respective areas. Due to limitations in the computational domain, the radiative processing of 3-in. wafers was modeled; however, results were confirmed for the 12-in. wafer for limited cases