Analytical solution of the peak bending moment of an M boom for membrane deployable structures
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Yang, Hui (ORCID:000000032014598X)↗
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DuraMAT FY 2023 Annual Report: Toward Reliability Forecasting
The Durable Module Materials Consortium (DuraMAT) launched in November 2016 with five years of funding from the U.S. Department of Energy s (DOE's) Solar Energy Technologies Office (SETO). The program renewed in 2022 for an additional 6 years. DuraMAT is a multi-lab consortium led by the National Renewable Energy Laboratory, with Sandia National Laboratories (Sandia) and Lawrence Berkeley National Laboratory (LBNL) as core research labs. DuraMAT's overarching goal is to accelerate a sustainable, just, and equitable transition to zero-carbon electricity generation by 2035. 2023 has been a wild ride in the solar industry. Photovoltaic (PV) manufacturing is coming back to the United States, and deployment is booming again. DuraMAT has a unique opportunity to support flourishing manufacturing and deployment over the next couple of years.
durable module↗
An infrasound source analysis of the OSIRIS-REx sample return capsule hypersonic re-entry
The OSIRIS-REx sample return capsule's hypersonic re-entry into the atmosphere is a rare opportunity to test a variety of sonic boom source models since the projectile dimensions are well characterized. While the as-flown flight path is unknown, the predicted flight path enables a rough approximation of the source Mach number and location. Six infrasound microphones deployed in the boom carpet along the predicted flight path recorded impulsive signals from the OSIRIS-REx re-entry. Using a suite of atmosphere profiles and the geometric acoustics approximation, we estimate locations with uncertainty estimates along the flight path from which the signals were emitted. Acoustic overpressure and signal duration predictions from Whitham's far field theory, Carlson's simplified sonic boom prediction method, and a drag-dominated hypersonic model are analyzed with uncertainty estimates from the location estimate. While the Carlson simplified sonic boom prediction method could be accurate, our preference is for the drag-dominated source model. Using this source model with an inviscid Burgers's equation solver for propagation, we obtained an excellent match to the recorded data. In conclusion, these results will help better inform future sample return capsule re-entry observation campaigns as well as contribute to a better understanding of high altitude infrasonic sources.
58 GEOSCIENCES↗
Idaho National Laboratory’s Mobile Hot Cell Transportation: Engineering Solutions for Global Disused Sealed Radioactive Sources.
Title: Idaho National Laboratory’s Mobile Hot Cell Transportation: Engineering Solutions for Global Disused Sealed Radioactive Sources. Abstract: The Mobile Hot Cell (MHC), currently under development by Idaho National Laboratory (INL) for the Off-Site Source Recovery Project (OSRP), is designed to help international partners meet the unique challenges of end-of-life radioactive material management. The MHC will provide a critical resource for countries that require assistance securing and disposing of Disused Sealed Radioactive Sources (DSRS) and orphaned sources in challenging environments, allowing these sources to be secured against misuse and nefarious activities. The MHC is a rapidly deployable system for conditioning and preparing end-of-life radioactive sources for transportation or storage. It is designed to handle sources of up to 1,000 Ci Co-60 equivalent while maintaining full radiological and biological containment. It will be deployable within 48 hours of an alert, making it ideal for emergency situations. The MHC features an operational suite for control, support racks for electronics, pneumatics, and welding systems, and a modular robust steel structure providing radiological shielding and internal robotic support. This design allows configurations for multiple device types to be conditioned and the ability to safely manage routine issues such as leaking or damaged sources. The MHC has been designed with the transportation challenges of rapid deployment to difficult environments in mind. The system weighs approximately 150,000 pounds, with individual systems breaking down into pieces not exceeding 20,000 pounds. Components are to be transportable on standard 20ft ISO containers, with shielding shells on 20ft flat racks. It is estimated that a total of eight containers and flat racks will be required. The use of 20ft containers, as opposed to 40ft containers, minimizes the impact on less developed road infrastructures, enabling the MHC to be positioned in constrained environments such as hospital parking lots. The system’s modularity also allows for deployment using smaller equipment, such as a 10-ton boom truck or forklift, which is crucial given the potential logistical challenges in different countries. This transportation strategy, evaluated in collaboration with Utah State University, ensures the MHC can be deployed via ground, rail, sea, or air, addressing the primary concern of international transport logistics.
99 - GENERAL AND MISCELLANEOUS↗
Surface albedo spatial variability in North America: Gridded data vs. local measurements
Considering the current booming interest for the large-scale deployment of bifacial photovoltaic modules, the solar industry now requires accurate estimates of broadband surface albedo at high spatial resolution. In this context, the present study evaluates the adequacy and performance over North America of two Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo products (at 500-m and 1-km resolution) and the National Solar Radiation Database (NSRDB) product at 4-km resolution. Two variations of the 500-m MODIS product are also considered: black-sky albedo and all-sky albedo. Albedo observations from 36 radiometric stations during 2011–2015 are analyzed while considering the apparent homogeneity of the surface characteristics over the 4x4 km NSRDB pixel in which they are located. Even at sites where the albedo around the station has been found “homogeneous” in the literature, marked differences are found between the daily observations and the gridded estimates at any spatial resolution. Furthermore, differences in seasonal behavior and between the three different albedo types also impact the accuracy of the albedo estimates, with overtones caused by local specificities and inhomogeneities. All this precludes the desirable evaluation of the local albedo at a specific site of relatively small size compared to its corresponding 4x4-km pixel if only the mean albedo over that pixel is known. Significant discrepancies are also found at snow-impacted sites, most importantly in the case of the NSRDB albedo estimates, which are typically much too high.
14 SOLAR ENERGY↗
Site G - Sonic Anemometer / Reviewed Data
This dataset contains sonic anemometer data deployed on tethered balloon system at AWAKEN site G. The sonic data include time stamp, wind speed, wind direction, turbulence, and boom attitude and motion. Z02 refers to the second height position of the sonic anemometers mounted on the tethered balloon.
17 WIND ENERGY↗
Site G - Sonic Anemometer / Reviewed Data
This dataset contains sonic anemometer data deployed on tethered balloon system at AWAKEN site G. The sonic data include time stamp, wind speed, wind direction, turbulence, and boom attitude and motion. Z01 refers to the first height position of the sonic anemometers mounted on the tethered balloon.
17 WIND ENERGY↗
Site A1 - Sonic Anemometer / Reviewed Data
This dataset contains sonic anemometer data deployed on tethered balloon system at AWAKEN site A1. The sonic data include time stamp, wind speed, wind direction, turbulence, and boom attitude and motion.
17 WIND ENERGY↗
Seismology in the Cloud: A New Streaming Workflow
Data-intensive research in seismology is experiencing a recent boom, driven in part by large volumes of available data and advances in the growing field of data science. However, there are significant barriers to processing large data volumes, such as long retrieval times from data repositories, complex data management, and limited computational resources. New tools and platforms have reduced the barriers to entry for scientific cluster computing, including the maturation of the commercial cloud as an accessible instrument for research. Here, we build a customized research cluster in the cloud to test a new workflow for large-scale seismic analysis, in which data are processed as a stream (retrieved on-the-fly and acted upon without storing), with data from the Incorporated Research Institutions for Seismology Data Management Center. We use this workflow to deploy a spectral peak detection algorithm over 5.6 TB of compressed continuous seismic data from 2074 stations of the USArray Transportable Array EarthScope network. Using a 50-node cluster in the cloud, we completed the noise survey in 80 hr, with an average data throughput of 1.7 GB per minute. By varying cluster sizes, we find the scaling of our analysis to be sublinear, due to a combination of algorithmic limitations and data center response times. The cloud-based streaming workflow represents an order-of-magnitude increase in acquisition and processing speed compared to a traditional download-store-process workflow, and offers the additional benefits of employing a flexible, accessible, and widely used computing architecture. It is limited, however, due to its reliance on Internet transfer speeds and data center service capacity, and may not work well for repeated analyses or those for which even higher data throughputs are needed. These research applications will require a new class of cloud-native approaches in which both data and analysis are in the cloud.
58 GEOSCIENCES↗