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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.
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From roads to roofs: How urban and rural mobility influence building energy consumption
In this article, understanding the relationship between travel behavior and building energy use at an urban scale is crucial for developing effective energy management strategies. Mobility patterns significantly impact building occupancy, which in turn affects energy consumption. However, existing methods often focus on individual buildings, whereas geographical influences on energy usage are not adequately examined. This study addresses this gap by using transportation origin-destination (OD) data to estimate building occupancy and energy. The proposed method assigns OD trips from census block groups to the building level, incorporating building, travel survey, and census data to derive building occupancy profiles. This method was applied to urban and rural areas with 4062 buildings in 70 census block groups. We found that the OD-informed occupancy profile exhibits smoother energy consumption patterns compared with that of Department of Energy reference occupancy profiles. Our analysis reveals distinct building energy consumption patterns among groups with long and short commutes, emphasizing the effect of commute times and work schedules on residential energy usage. This framework is useful for practitioners in transportation agencies and utility companies, enabling the estimation of building energy based on mobility patterns. Overall, this study shows the potential of integrating transportation and building energy data to inform cross-sector energy management strategies.
A comprehensive study on two types of supercapacitor composite electrodes comprising MnO 2 and activated carbon nanofibers: Self-supporting membrane and ground powder
Manganese dioxide (MnO 2 )@carbon composites have been attractively considered as electrode materials for supercapacitors (SCs) due to synergistic effects. This work systematically investigated the structure of MnO 2 @carbon nanofiber (CNF) composite electrodes with the different forms of CNFs and the corresponding electrochemical performance of SCs. In brief, novel activated carbon nanofibers were first fabricated by electrospinning the hydroxyl-containing poly(amic acid) solution, and then the preferred CNF material was decorated by MnO 2 crystals in the form of self-supporting membrane and ground powders, respectively. Additionally, the synthesis parameters were investigated and optimized based on the electrochemical performance of SCs. The results reveal that the powdered composite electrode exhibits a higher specific surface area of 501 m 2 g –1 compared to the self-supporting membrane composite electrode under the same conditions, resulting in a promising specific capacity of 214.1 mAh g –1 (770.8 Fg –1 ) in 6M KOH solution at 0.5 A g –1 . In addition, the capacitance of the symmetrical SC device assembled by G-HMC-1:3–80 reaches 179.8 Fg –1 , coupled with an energy density of 24.86 Whkg –1 at 230 Wkg –1 power density. This work provides valuable hints for designing SC composite electrode materials with outstanding performance.
Assessment of sulfur trioxide formation due to enhanced interaction of nitrogen oxides and sulfur oxides in pressurized oxy-combustion
Pressurized oxy-combustion is emerging to be one of the best technologies for significantly decreasing the energy penalty for CO 2 capture in coal-fired power plants. However, the higher pressure boosts the formation of acid gases, including SO 3 and NO 2 , which could increase the risk of corrosion. The synergistic promotion of SO 3 and NO 2 formation in pressurized oxy-combustion is kinetically evaluated under representative conditions (1 ~ 30 atm, 600 ~ 1200 °C, NO/SO 2 = 0.1 ~ 5). We begin with a comprehensive mechanism (72 species and 428 reactions), covering nitrogen and sulfur chemistry, relying on GRI-Mech 3.0. This analysis shows that the interaction of SO X and NO X enhances the conversion rates of SO 2 → SO 3 , and this effect is more apparent at elevated pressures and lower temperatures. Mechanism analyses indicate that at elevated pressures, the formation pathways of SO 3 through HOSO 2 + O 2 = SO 3 + HO 2 , and NO 2 through HO 2 + NO = NO 2 + OH, are promoted due to the strong interaction between SO X and NO X . The intermediate between these two reactions is SO 2 + OH + M = HOSO 2 + M, resulting in a strong cycle, that can be expressed by the global reaction NO + SO 2 + O 2 = NO 2 + SO 3 . Finally, a nine-step reduced chemistry is developed and validated to accurately predict the formation of SO 3 in the post-flame region at elevated pressures.
Development of intelligent control module for the J-TEXT electron cyclotron emission imaging system
An Electron Cyclotron Emission Imaging (ECEI) system has been developed on the J-TEXT tokamak and employed for the multi-dimensional electron temperature fluctuation imaging measurement in 2019 campaign. The intelligent control module has been developed and been used to flexibly setup the 256-channel ECEI system configurations for different plasma scenarios. The adjustments of key parameters are merged in this module including size and position of the geometric observation window, and the dynamic range of the signal and image resolution. The user-friendly interface is also developed for the tokamak operator to set the ECEI system focusing on physics interested region. Furthermore, this module is installed close to the diagnostic system around the J-TEXT tokamak, which can be remotely controlled by authorized operators in the control room. It significantly improves ECEI flexibility and stability, and also keeps the operation technician away from the harsh radiation environment.
The globus compute dataset: An open function-as-a-service dataset from the edge to the cloud
Here we present a unique function-as-a-service (FaaS) dataset capturing the use of the Globus Compute (previously funcX) platform. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud -hosted service. The dataset covers 31 weeks and includes 2121472 task submissions from 252 users executed on 580 remote computing endpoints. It includes 277386 registered functions. We describe the dataset and various observations, some that are similar to other FaaS datasets, for example, that 74% of tasks run for less than 1 s, and some that are unique to Globus Compute, for example, that endpoints are used in different ways and that the majority of functions are related to scientific computing and machine learning. To the best of our knowledge, this dataset represents the first federated FaaS dataset that includes user workloads, distributed computing endpoints, and analysis of registered function bodies. We expect the dataset to be useful for researching FaaS architectures, workload modeling, container warming, and other distributed computing architectures.