SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Large Eddy Models (LES) and Single Column Models (SCM) are used in a surrogate climate change 101 to investigate the physical mechanism of low cloud feedbacks in climate models. Enhanced surface-102 driven boundary layer turbulence and shallow convection in a warmer climate are found to be 103 dominant mechanisms in SCMs.
Explore the source record for details and available documents.
Electric vehicles (EVs) have seen rapid growth in adoption over the last several years. Advancements to increase battery life and performance, policy shifts, and high charging rate are expected to further accelerate the development of next generation of EVs. Battery improvements continue to emerge, enabling increased driving range, total distance driven over the life of vehicles, and ability to charge at high rates. Herein, an analysis framework to provide insights into inclusive design metrics, such as specific energy of batteries, energy consumption of vehicles, and charging power infrastructure development, is developed. Various cell-level fast charge protocols to realistic battery designs to understand the infrastructure needs associated with achieving range replacement of 32.25 km min -1 (20 mi min -1 ) are also scaled. Additionally, by calculating scaled power and peak to average power ratio, it is found that there needs to be more distinct alignment between the research efforts focused at the cell level and what is being developed for EV charging infrastructure needs. Finally, impact of high direct current voltage architecture in next-generation EVs is discussed. The findings in this work provide an insight into recent advancements in battery technology to next-generation EVs.
Not provided.
Abstract not provided
Explore the source record for details and available documents.
Not Available
We present a high-throughput infrastructure for the automated calculation of molecular properties with a focus on battery electrolytes. The infrastructure is largely open-source and handles both practical aspects (input file generation, output file parsing, and information management) as well as more complex problems (structure matching, salt complex generation, and failure recovery). Using this infrastructure, we have computed the ionization potential (IP) and electron affinities (EA) of 4830 molecules relevant to battery electrolytes (encompassing almost 55,000 quantum mechanics calculations) at the B3LYP/6-31+G(*) level. We describe automated workflows for computing redox potential, dissociation constant, and salt-molecule binding complex structure generation. We present routines for automatic recovery from calculation errors, which brings the failure rate from 9.2% to 0.8% for the QChem DFT code. Automated algorithms to check duplication between two arbitrary molecules and structures are described. We present benchmark data on basis sets and functionals on the G2-97 test set; one finding is that a IP/EA calculation method that combines PBE geometry optimization and B3LYP energy evaluation requires less computational cost and yields nearly identical results as compared to a full B3LYP calculation, and could be suitable for the calculation of large molecules. Our data indicates that among the 8 functionals tested, XYGJ-OS and B3LYP are the two best functionals to predict IP/EA with an RMSE of 0.12 and 0.27 eV, respectively. Application of our automated workflow to a large set of quinoxaline derivative molecules shows that functional group effect and substitution position effect can be separated for IP/EA of quinoxaline derivatives, and the most sensitive position is different for IP and EA. Published by Elsevier B.V
Prescribed burning is an accepted practice to manage biomass in the United States and throughout the world. It is a particularly important practice in pine forests throughout the world, many of which have evolved in the presence of fire [1]. A recent survey [2] of prescribed fire use reported that 2.62 x 106 ha of forest land in the southeastern U.S. (defined by the National Association of State Foresters) burned in 2011 for silvicultural purposes such as hazardous fuel reduction, wildlife habitat improvement, and forest regeneration. Earlier surveys reported 0.9 to 1.7 x 106 ha of prescribed burning in the southern U.S. [3–5] using different survey techniques. While it is not possible to determine confidence intervals on these estimates, it is clear that the use of prescribed burning has increased since the first published estimate of 1 x 106 ha we were able to locate or the recent survey captured more information. Smoke is an important consequence of prescribed burning that must be managed, [6] and a great deal of research has been performed since the 1970s trying to characterize the composition, production, and transport of smoke from such fires. A recent review of the state of science behind estimation of the contribution of wildland fire to greenhouse gases and black carbon in the U.S. identified several areas of research that must be performed [7]. In particular, two areas of knowledge that still need improvement are fuel characterization and smoke emissions, and the correlation(s) between the two. While many fuel types in the southeastern U.S. have been described for fire behavior and fire danger prediction, characterization of fuel bed components important for smoke production is more limited. Emissions characterization, both chemical and particulate, is needed to determine potential impacts of prescribed burning on nutrient cycling, planetary albedo, human health, and highway visibility [e.g. 8–10].
Not provided.