Results for “Data Collection” — Page 32

DOE OSTI2022

A Combined Computer Vision and Deep Learning Approach for Rapid Drone-Based Optical Characterization of Parabolic Troughs

Optical accuracy is a primary driver of parabolic trough concentrating solar power (CSP) plant performance, but can be damaged by wind loads, gravity, error during installation, and regular plant operation. Collecting and analyzing optical measurements over an entire operating parabolic trough plant is difficult, given the large scale of typical installations. Distant Observer, a software tool developed at the National Renewable Energy Laboratory, uses images of the absorber tube reflected in the collector mirror to measure both surface slope in the parabolic mirror and offset of the absorber tube from the ideal focal point. This technology has been adapted for fast data collection using low-cost commercial drones, but until recently still required substantial human labor to process large amounts of data. A new method leveraging advanced deep learning and computer vision tools can drastically reduce the time required to process images. This new method addresses the primary analysis bottleneck, identifying featureless, reflective mirror corner points to a high degree of accuracy. Recent work has shown promising results using computer vision methods. The combined deep learning and computer vision approach presented here proved highly effective and has the potential to further automate data collection and analysis, making the tool more robust. The method presented in this paper automatically identified 74.3% of mirror corners within 2 pixels of their manually marked counterparts and 91.9% within 3 pixels. This level of accuracy is sufficient for practical Distant Observer analysis within a target uncertainty. A commercial drone collected video of over 100 parabolic trough modules at an operating CSP plant to demonstrate the deep learning and computer vision method's usefulness in processing large amounts of data. These troughs were successfully analyzed using Distant Observer, paired with the new deep learning and computer vision algorithm, and can provide plant operators and trough designers with valuable insight about plant performance, operating strategies, and plant-wide optical error trends.

computer vision↗

DOE OSTI2025

LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory’s (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller Road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDAR System was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, and lidar data and imagery can be found in NGA281 (https://doi.org/10.5440/1671794).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Correlation of Injury Simulation with Clinical Assessment of Traumatic Brain Injury

This report contains a summary of our efforts to correlate head injury simulations predicting intracranial fluid cavitation with clinical assessments of brain injury from blunt impact to the head. Magnetic resonance imaging (MRI) data, collected on traumatic brain injury (TBI) subjects by researchers at the MIND Institute of New Mexico, was acquired for the current work. Specific blunt impact TBI case histories were selected from the TBI data for further study and possible correlation with simulation. Both group and single-subject case histories were examined. We found one single-subject case that was particularly suited for correlation with simulation. Diffusion tensor image (DTI) analysis of the TBI subject identified white matter regions within the brain displaying reductions in fractional anisotropy (FA), an indicator of local damage to the white matter axonal structures. Analysis of functional magnetic resonance image (fMRI) data collected on this individual identified localized regions of the brain displaying hypoactivity, another indicator of brain injury. We conducted high fidelity simulations of head impact experienced by the TBI subject using the Sandia head-neck-torso model and the shock physics computer code CTH. Intracranial fluid cavitation predictions were compared with maps of DTI fractional anisotropy and fMRI hypoactivity to assess whether a possible correlation exists. The ultimate goal of this work is to assess whether one can correlate simulation predictions of intracranial fluid cavitation with the brain injured sites identified by the fMRI and DTI analyses. The outcome of this effort is described in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

LiDAR Point Cloud Data from the 2018 NGEE Arctic UAS Campaign at the Kougarok 64 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from the EES-14 group at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 64 along the Kougarok road (Nome-Taylor Highway) between Nome, Alaska and Taylor, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data. The LiDAR data has undergone basic post-processing using Routescene LidarViewer Pro software to create point cloud data (.laz files). This data package contains point clouds (.laz), processing metadata files (json.lvp), and post-processed kinematic files (.csv). Ancillary aircraft data, flight mission parameters, weather conditions, raw LiDAR data, and RGB imagery can be found in NGA298.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Report on the recovery of legacy 1997-1998 Depth-of-Burial / Tunnel-and-Hole-Closure explosion data from the Kazakhstan former Soviet nuclear test site, Semipalatinsk.

In 1996, negotiations between the National Nuclear Center of the Republic of Kazakhstan (NNC), the U.S. Defense Special Weapons Administration (DSWA) and the U.S. Department of Energy led to an agreement for a joint series of experiments at the former Soviet nuclear test site Semipalatinsk (STS). These experiments had a dual purpose: to close holes and tunnels originally created for the purpose of testing nuclear weapons, and to characterize explosive sources at a former nuclear test site. This report covers the recovery of legacy data from the experiments conduct in 1997 and 1998. Two teams collected data. Los Alamos National Laboratory (LANL), in collaboration with the NNC, collected the near-source (local) data out to approximately 20 km. Lamont-Doherty Earth Observatory (LDEO), with funding from Lawrence Livermore Laboratory (LLNL), also in collaboration with NNC, collected regional data, 200 – 1000 km distant, leveraging the KZ regional seismic network that LDEO had recently installed in collaboration with NNC. The two teams also worked together to some extent, regarding instrumentation and planning. This report primarily addresses the near-source data collected by the LANL/NNC team.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2023

Arctic shrub size and leaf traits, northern Alaska, summer 2017 (Version 2.0)

This data package contains leaf and size trait and environmental data collected from 170 plots of rapidly expanding shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a latitudinal and climate gradient in northern Alaska. The trait data were collected in summer 2017 and include leaf area, specific leaf area, leaf nitrogen concentration, leaf delta 15N, leaf delta 13C, shrub height, aboveground biomass, and the ratio of root biomass to aboveground biomass. These raw data support a submitted manuscript that examines the intraspecific variations of size, leaf and root traits of shrubs across the graminoid-dominated nutrient-poor arctic tundra and reveals the environmental drivers of deciduous shrub traits in tundra ecosystems (Fraterrigo et al., submitted). Data are presented by site (n=5) and patch (shrub or sedge plot) in separate csv files. The location data are provided in the “plot coordinates” file; all other files contain the data in the file title. Detailed methods are in the submitted manuscript. A companion data package contains root trait data collected simultaneously from the same plots (Fraterrigo and Chen, 2020). See the "Related references" section for more information.2023/07/20 Update: The latest version of this dataset publication is version 2.0. The latest version of the data package was updated to correct the leaf size trait.csv file.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2022 Next-Generation National Household Travel Survey - Origin-Destination Data Addendum for the Oahu Region

# 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region The 2022 Next-Generation National Household Travel Survey – Origin-Destination Data Addendum for the Oahu Region covers the Hawaiian island of Oahu and five counties in surrounding islands. An addendum to the nationwide version of the study conducted in 2019, this regional survey provided additional information and spatial granularity about people’s movements to, from, and within the areas under study. ## Data Collection Agency The survey was conducted for the Oahu Metropolitan Planning Organization. ## Survey Methodology Data were collected in two zones: the core area (census blocks in the island of Oahu) and the halo area (five counties in adjacent Hawaiian islands). All trips were assigned an origin zone and a destination zone, as well as a travel mode, purpose, and distance. Sociodemographic information related to age, income, and gender was also collected. ## Survey Records, Data, and Documentation Survey records include 1,154,167,619 trips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Development and Demonstration of a Prototype Molten Salt Sampling System

Molten salt reactors (MSRs) offer potential operability and safety advantages when compared to commercial light water reactors (LWRs). However, operating experience with MSRs is sparse in comparison to what exists for LWRs. Further, the chemical and isotopic composition of the fuel and/or coolant salt is dynamic and difficult to characterize continuously, posing potential safety, operability, and safeguards unknowns that need to be addressed. A molten salt sampling system (MSSS) is regarded as a necessary subsystem within first generation MSRs used to obtain samples of salt for chemical and isotopic analysis in support of the need to monitor and control salt composition during operation. The MSSS is being developed using the Safety-in-Design (SiD) methodology, which incorporates incremental integration of safety analysis into the design process. The MSSS conceptual design emerging from the application of the early stages of the SiD methodology consists of a sample collection system and its housing, a freeze port, and inert gas control and delivery systems. This article describes the prototypes developed to test the functions of these MSSS subsystems, presents the results of testing in both dry and molten salt environments (including reliability data collection performed in accordance with the principles of SiD and the development of a semiquantitative fault tree model), and summarizes the opportunities for future design and testing enhancements based on the results of prototype testing.

molten salt reactor↗

DOE OSTI2022

Utilizing machine learning to improve the precision of fluorescence imaging of cavity-generated spin squeezed states

We present a supervised learning model to calibrate the photon collection rate during the fluorescence imaging of cold atoms. The linear regression model finds the collection rate at each location on the sensor such that the atomic population difference equals that of a highly precise optical cavity measurement. This 192 variable regression results in a measurement variance 27% smaller than our previous single variable regression calibration. The measurement variance is now in agreement with the theoretical limit due to other known noise sources. This model efficiently trains in less than a minute on a standard personal computer's CPU and requires less than 10 min of data collection. Furthermore, the model is applicable across a large change in population difference and across data collected on different days.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗