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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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Molecular charge transfer doping affords widely tunable carrier density and conductivity in s-SWCNTs (and OSCs in general), however, a pervasive challenge for such systems is reliable measurement of charge carrier density and mobility.
In this paper, a new approach for a multilayer elastic beam to provide a driving force and driving distance for a MEMS safe and arming system is presented. In particular this is applied where a monolayer elastic beam cannot provide adequate driving force and driving distance at the same time in limited space. Compared with thicker elastic beams, the bilayer elastic beam can provide twice the driving force of a monolayer beam to guarantee the MEMS safe and arming systems work reliably without decreasing the driving distance. In this paper, the theoretical analysis, numerical simulation and experimental verification of the multilayer elastic beam is presented. The numerical simulation and experimental results show that the bilayer elastic provides 1.8–2 times the driving force of a monolayer, and a method that improves driving force without reducing the driving distance.
The secondary electron emission of metals induced by slow ions is characterized in a beam chamber by means of two coaxial semi-cylindrical electrodes with different apertures. The voltages of the outer electrode (screening), inner electrode (collector), and sample holder (target) were set independently in order to measure the effective yield of potential and kinetic electron emissions during ion bombardment. Aluminum samples were exposed to quantified beams of argon ions up to 2000 eV and to oxygen atoms and molecules in order to mimic the plasma-surface interactions on metallic targets during reactive sputtering. The variation of electron emission yield was correlated to the ion energy and to the oxidation state of Al surfaces. This system provides reliable measurements of the electron yields in real time and is of great utility to explore the fundamental surface processes during target poisoning occurring in reactive magnetron sputtering applications.
This work presents a system upgrade of the High Resolution Thomson Scattering (HRTS) diagnostic on JET that allows it to measure low temperature (1–500 eV) plasma pre- and post-Thermal quench (TQ), which would help us further understand the Shattered Pellet Injection (SPI) physics. The upgrade was done by connecting optic fibers from the original HRTS system to four spectrometers specialized in measuring low temperature plasmas. The upgraded system allows for the measurement of low temperature plasma at up to 12 spatial points, which can be flexibly distributed throughout the JET outer midplane profile during the dedicated SPI experiments. In other JET experiments, four previously unused groups of fibers were used to measure the central plasma to provide disruption data without changing the standard HRTS system. The low temperature Thomson scattering system was installed, commissioned, and cross-calibrated against the standard HRTS diagnostic in a calibration pulse. The system worked reliably during the JET experiments and provided electron density and temperature profiles for pre- and post-TQ low temperature plasmas in the SPI campaign.
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Hurricanes are a dominant disaster in the Caribbean, always causing serious power outages throughout the islands. Hurricane Maria was a prime example, causing unimaginable destruction of the power infrastructure of Puerto Rico (PR). Consequently, one month after the hurricane landfall, approximately 80% of the population was still without power. After an event of such massive destruction, the electric power restoration process progresses very slowly. This timeline can be improved using power outage (PO) forecast models that help identify the vulnerable places before the hurricane landfall. Generally, these models are trained with historical power outages records, associated data on weather conditions, and additional information about the natural and built environments. However, PO records are often difficult to acquire, and, in many instances, the power utility companies may not record them. This study utilizes a satellite-based Visible Infrared Imaging Radiometer Suite (VIIRS) night light data product as a surrogate for the power delivery to predict hurricane-induced PO in areas having limited to nonexistent historical data records. The processed satellite data is then used along with geographic variables, and simulated weather data to formulate machine learning-based algorithms to predict PO for future hurricane events. These models are applied and validated in the context of the PR catastrophic storm, Hurricane Maria.
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Extreme scenarios in wind power generation occur with higher frequency and larger magnitude in the recent years due to the ever-increasing extreme meteorological factors. Accurate forecasting of the occurrence of extreme values in wind power generation is of great concern to ensure reliable power system operation. Recently, deep learning models have surged in popularity for wind power forecasting, with the mean squared error (MSE) loss function being commonly used. However, the MSE loss function, being sensitive to extreme values, disproportionately penalizes larger errors, cannot adequately capture the extreme values present in wind energy data, and novel loss functions have seldom been tailored for wind power forecasting. To this end, in this paper, we introduce a novel loss function specifically crafted to capture extreme values in wind power forecasting. The experimental results with four fundamental deep learning methods on open source wind power dataset validate that the new loss function is efficient and superior in all cases compared to MSE in capturing extreme values while maintaining forecasting performance.
As probably the most complicated and critical infrastructure system, U.S. power grids become increasingly vulnerable to extreme events such as cyber-attacks and severe weather, as well as higher DER penetrations and growing information mismatch among system operators, utilities (transmission or generation owners), and end-users. This paper proposes a data-driven democratized control architecture considering two democratization pathways to assist transmission system operators, with a targeted use case of developing online proactive islanding strategies. Detailed discussions on load capability profiling at transmission buses and disaggregation of DER generations are provided and illustrated with real-world utility data. By Combining network and operational constraints, transmission system operators can be equipped with new tools built on top of this architecture, to derive accurate, proactive, and strategic islanding decisions to incorporate the wide range of dynamic portfolios and needs when facing extreme events or unseen grid contingencies.
The high-power klystron amplifiers at the Spallation Neutron Source (SNS) have been in operation for over 100,000 hours. Overcurrent faults from the klystron cathodes comprise the bulk of RF System downtime. Reliable operation is of particular interest to the SNS, and data from over a decade of operation is used to help mitigate repetitive overcurrent conditions.
Lamination-free minimodules are constructed with silicon solar cells between glass sheets and an edge seal of polyisobutylene and silicone. These samples are stressed using a repeated sequential testing sequence including ultraviolet-containing simulated solar spectrum light exposure at elevated temperature, damp heat, humidity freeze, and thermal cycling adapted from the International Electrotechnical Commission (IEC) TS 63209-2:2022. The minimodule performance throughout the stressing is characterized by flash testing and electroluminescence imaging. Results are compared to conventional laminated minimodules using the same type of solar cells. The lamination-free minimodules experience up to 8% power loss compared to roughly 3% for the laminated versions. However, those losses, dominated by current and fill factor, are caused by glass soiling and busbar ribbon separation on the cells. When glass is replaced and the stressed cells are contacted with probes bypassing the delaminated ribbons, the initial performance is recovered, and overall losses of the lamination-free samples become negligible.
The New York City boroughs of Brooklyn and Queens are undergoing a period of gentrification, infrastructure rebuilding, new construction, and load growth not experienced in decades. Significant numbers of residents are moving in, and structures that had been abandoned or were in disrepair are being refurbished and modernized to accommodate the burgeoning population. Homes, businesses, and industries are reviving areas long in decline, and Brooklyn's growth has made it the nation's fourth most populous city, according to the U.S. Census Bureau.
Module performance can be characterized by imaging using baseline and periodic images to track defects and degradation. Both thermal images, which can be acquired during sunny operating conditions, and photoluminescence images, which could be acquired at night, can be collected without electrical connection. Electroluminescence (EL) images, which are useful to detect many types of defects such as cracks, interconnect and solder faults, and resistances, have typically required electrical connection to drive current in the cells and modules. Here, a contactless EL imaging technique is proposed, which provides an EL image without the need for electrical connection to drive current through the module. Such EL imaging has the capability to be collected at night without disruption to daytime power generation.
The present work reports on the initial results of an international collaboration aiming to investigate the spectral effects of soiling losses. Identical glass coupons have been exposed outdoors for eight weeks in different locations worldwide, and weekly direct and hemispherical transmittance (T%) measurements are compared. Maximum losses as high as 7% and 50% in hemispherical and direct transmittance, respectively, have been found during the 8-week outdoor exposure. At the end of the data collection, a preliminary analysis of the spectral impact of soiling has been performed. The results show that the blue end of the spectrum is more affected and that lower hemispherical T% correlate to larger area covered by particles.
We investigate the local ionic motion in the absorber layer of perovskite solar cells using scanning thermo-ionic microscopy (STIM). STIM images of perovskite films show higher STIM amplitude at most of the grain boundaries due to higher ionic motion at those regions. The perovskite absorber layer of devices aged under blue (450 nm) light soaking shows higher amplitude in STIM signal compared to controls kept in dark storage. Such enhancement of STIM amplitude upon aging under light implies an increased concentration or diffusivity (or both) of mobile ionic species in stressed devices. Our results demonstrate the utilization of the STIM technique to assess and understand the intrinsic local ionic motion in perovskite absorbers for further advancement in device stability and functionality.