Solid oxide fuel cells (SOFCs) are expected to be widely applicable for both small and large-scale power generation systems. The reason is that the SOFC is simple, highly efficient, tolerant to impurities, and can at least partially internally reform hydrocarbon fuels. A multi-physics, multi-scale model structure is proposed by integrating three submodels, i.e., a macro-continuum model, a micro-scale model (random walk model) and an atomistic-level model. This multi-scale model has the capability of handling transport mechanisms on different length scales at the same time. The coarsest macro-continuum model is first proposed to simulate all energy transport processes in an electrolyte-/anode-supported SOFC. Then a novel micro-level model (random walk model) is developed to investigate the electrochemical performance in a composite electrode. Finally, a multi-scale model by combining the developed macro-level model and micro-level model is proposed for a lower temperature SOFC. Based on this multi-scale model, the dependence of electrochemical performance on the global parameters and micro-structures is assessed for the entire fuel cell stack.

Chilldown process is a complicated process involves unsteady two-phase heat and mass transfer and initiates the cryogenic fluids transport. To advance the understanding of this process, both experimental and modeling investigations have been carried. The chilldown process can be generally divided into three regions which are associated with different flow regimes and heat transfer mechanisms. Under low flow conditions, the two-phase flow during chilldown is dispersed. The statistic feature of the liquid filaments is studied and a model, in which the heat transfer at the bottom is considered as a sum of vapor and liquid components, has been developed for the dispersed flow film boiling. The bottom wall heat flux is found to decrease under microgravity condition. A cryogenic chilldown model has also been developed. The model focuses on both vertical tube orientation and microgravity chilldown and shows a good agreement with previous experimental data.

Working memory (WM), which includes short-term memory and cognitive control, has been found to be closely related to a wide range of high-level cognitive abilities and academic achievement. Prior studies showed children with attention-deficit/hyperactivity disorder improved their WM and fluid intelligence through computerized cognitive training (CCT) in a clinical setting. This research examined whether regular middle-school students would significantly improve their WM through CCT on WM; and if so, whether increase in WM would lead to improved fluid intelligence and science achievement. Two randomized pretest-posttest control-group experimental studies were conducted to answer these questions. Results showed CCT effectively improved regular students' WM in a school setting, with more increase in short-term memory than in cognitive control. No significant improvement was observed in fluid intelligence and science achievement immediately following training. Given the increasingly complex learning environment in schools, using CCT to improve students' cognition and academic learning has important implications for both practitioners and researchers in education.

This report examines Pittsburgh Public Schools' implementation and outcomes of the Pittsburgh Principal Incentive Program from school years 2007-2008 through 2010-2011, how principals and other school staff have responded to the reforms, and what outcomes accompanied program implementation.