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At least 469 records · Page 26

A cloud platform for atomic pair distribution function analysis: PDFitc

A cloud web platform for analysis and interpretation of atomic pair distribution function (PDF) data ( PDFitc ) is described. The platform is able to host applications for PDF analysis to help researchers study the local and nanoscale structure of nanostructured materials. The applications are designed to be powerful and easy to use and can, and will, be extended over time through community adoption and development. The currently available PDF analysis applications, structureMining, spacegroupMining and similarityMapping , are described. In the first and second the user uploads a single PDF and the application returns a list of best-fit candidate structures, and the most likely space group of the underlying structure, respectively. In the third, the user can upload a set of measured or calculated PDFs and the application returns a matrix of Pearson correlations, allowing assessment of the similarity between different data sets. structureMining is presented here as an example to show the easy-to-use workflow on PDFitc . In the future, as well as using the PDFitc applications for data analysis, it is hoped that the community will contribute their own codes and software to the platform.

97 MATHEMATICS AND COMPUTING↗

Overhead longwave infrared hyperspectral material identification using radiometric models

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimal atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms

Previous NREL research shows that solar photovoltaic (PV) customers tend to obtain lower installation quote prices on online quote platforms. In new research reported in Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms, we corroborate those results using data from the Pick My Solar quote platform. Furthermore, for the first time, we evaluate quote prices for batteries on online quote platforms. Given that few customers currently use quote platforms, we discuss various pathways to increase use of online quote platforms, including developing strategic partnerships, building customer trust, increasing market transparency, and providing quality guarantees.

14 SOLAR ENERGY↗

BigPanDA monitoring system evolution in the ATLAS Experiment

Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mobility Energy Productivity and Equity: E-Bike Impacts for Low-Income Essential Workers in Denver

New mobility technologies such as electrified and shared mobility, combined with polices and incentive programs, are emerging to help address sustainability and equity issues in transportation planning. However, it can be difficult to understand the impacts of novel mobility trends and emerging modes on energy-efficient access. This is owing to a lack of (1) open-source tools enabling rapid data collection, and (2) open-source metrics that consider multimodal, multiactivity access and mobility within the contexts of sustainability and equity. Here, this paper addresses the topic of improving evaluation of transportation modes and incentive programs by integrating an open-source platform for tracking human travel data—the Open Platform for Agile Trip Heuristics (OpenPATH)—with a mobility metric that quantifies the efficiency of a region’s transportation system: Mobility Energy Productivity (MEP). Integration is demonstrated in the context of pilot programs in Colorado, where low-income essential workers were provided with electric bikes (e-bikes). OpenPATH-informed MEP calculations showed that several locations in downtown Denver provided comparable time-, cost-, and energy-efficient access to opportunities using e-bikes compared with driving. Additionally, providing e-bikes to low-income essential workers was found to be meaningful, as they utilized e-bikes the most to commute, despite driving still being their most utilized mode and the mode with highest MEP scores in Denver. We show how data collected from open-source tools coupled with robust metrics such as MEP can help evaluate the impacts of emerging mobility options. This could support developing policies to incentivize novel modes to achieve greater levels of sustainable, equitable, and efficient access.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Design, Fabrication and Start-up of Test Facilities for the LAWPS Full-Scale IX Column Test and Engineering Scale Test - 17418

The U.S. Department of Energy (DOE), Office of River Protection's (ORP) primary mission is to retrieve and treat Hanford's tank waste and close the Tank Farms to protect the Columbia River. Mixed radioactive waste is stored in 177 underground tanks at the Hanford Site as reported in DOE/ORP 2003-02, Environmental Impact Statement for Retrieval, Treatment, and Disposal of Tank Waste and Closure of the Single Shell Tanks at the Hanford Site, Richland WA, Inventory and Source Term Data Package. The 177 underground tanks are estimated to contain about 56 million gallons of waste. The Low Activity Waste Pretreatment System (LAWPS) Project provides for the early production of immobilized low activity waste (ILAW) by feeding LAW directly from Tank Farms to the Hanford Waste Treatment Plant's (WTP's) LAW Facility, bypassing the Pretreatment Facility. Prior to the transfer of feed to the WTP LAW Vitrification Facility, tank supernatant waste will be pretreated in the LAWPS to meet the WTP LAW waste acceptance criteria. The LAWPS will also facilitate the return of secondary liquid wastes from the WTP LAW Vitrification Facility to the Tank Farms. In November of 2015 DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS), awarded a contract to the AECOM Team to design, fabricate and operate two test platforms to generate performance data at two different scales and demonstrate technology maturation. The first platform models the ion exchange (IX) columns at full scale, and the second platform models the integrated flowsheet (cross flow filter (CFF) and IX) at 1/9. scale. Both test platforms underwent shakedown and start-up testing in August 2016 and moved into actual testing and NQA-1 data generation shortly thereafter. This paper covers the engineering design, procurement, construction, installation, and acceptance testing of the test platforms (which are now operational) under an aggressive fast track schedule, and initial test data as available. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sensors with Intelligent Measurement Platform for Monitoring and Control in Distribution Circuits

This paper presents a medium-voltage intelligent measurement platform that provides post-processing of raw measurements received from commercially-available voltage/current sensors to enhance accuracy and bandwidth of the monitoring system. Furthermore, this platform integrates into a Data Distribution Service (DDS) messaging bus for distributed control and interoperability. The authors present the design, specifications, and major components included in the platform, and argue for applications and use cases that most benefit from this new approach. A laboratory testbed has been created to demonstrate the functionality, for which test results are presented for selected test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ARM TBS and TigerShark deployment data in 2021

In 2021, observational data collected using ARM platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center and made publicly available to the user community.

54 ENVIRONMENTAL SCIENCES↗

Slycat v 1.0 Beta

Slycat is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed into Slycat, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users' desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat currently provides two types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, and time series analysis featuring clustering and comparative visualization of waveforms.

Source record↗

Slycat v 2.0

Slycat™ is a web-based system for analysis of large, high-dimensional data such as that produced by High Performance Computing (HPC) platforms. The Slycat™ server integrates data ingestion, scalable analysis, data management, and visualization with commodity web clients using a multi-tiered hierarchy of data and model storage. Analysis inputs are pushed or pulled into Slycat™, where models are generated and analysis artifacts are stored in a project database. These artifacts are the basis for visualizations that are delivered to users’ desktops through ordinary web browsers, eliminating the need to build and deploy platform-specific client applications. Slycat™ currently provides four types of analysis: canonical correlation analysis (CCA) to model relationships between inputs and output metrics, time series analysis featuring clustering and comparative visualization of waveforms, parameter space visualization including remote retrieval of images and movies from HPC disks, and VideoSwarm for modeling video similarities over time.

Letter, Matthew↗

Accomplishments of Thermal Neutron Scattering Research at North Carolina State University [Slides]

Thermal neutron scattering law (TSL) data evaluations have been completed and contributed to ENDF. New evaluations are underway. FLASSH is developing as a modern platform for thermal neutron data analysis featuring an enhanced user experience and low learning overhead. Advanced TSL techniques in combination with Doppler analysis have been developed, which were incorporated into FLASSH. ML/DL NeTS method development has been initiated. Experimental capabilities for validation have been developed at the PULSTAR reactor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SU-D-BRD-03: A Gateway for GPU Computing in Cancer Radiotherapy Research

Purpose: Graphics Processing Unit (GPU) has become increasingly important in radiotherapy. However, it is still difficult for general clinical researchers to access GPU codes developed by other researchers, and for developers to objectively benchmark their codes. Moreover, it is quite often to see repeated efforts spent on developing low-quality GPU codes. The goal of this project is to establish an infrastructure for testing GPU codes, cross comparing them, and facilitating code distributions in radiotherapy community. Methods: We developed a system called Gateway for GPU Computing in Cancer Radiotherapy Research (GCR2). A number of GPU codes developed by our group and other developers can be accessed via a web interface. To use the services, researchers first upload their test data or use the standard data provided by our system. Then they can select the GPU device on which the code will be executed. Our system offers all mainstream GPU hardware for code benchmarking purpose. After the code running is complete, the system automatically summarizes and displays the computing results. We also released a SDK to allow the developers to build their own algorithm implementation and submit their binary codes to the system. The submitted code is then systematically benchmarked using a variety of GPU hardware and representative data provided by our system. The developers can also compare their codes with others and generate benchmarking reports. Results: It is found that the developed system is fully functioning. Through a user-friendly web interface, researchers are able to test various GPU codes. Developers also benefit from this platform by comprehensively benchmarking their codes on various GPU platforms and representative clinical data sets. Conclusion: We have developed an open platform allowing the clinical researchers and developers to access the GPUs and GPU codes. This development will facilitate the utilization of GPU in radiation therapy field.

60 APPLIED LIFE SCIENCES↗

A Parallel Graph Environment for Real-World Data Analytics Workflows

Economic competitiveness and national security depend increasingly on the insightful analysis of large data sets. The diversity of real-world data sources and analytic workflows impose challenging hardware and software requirements for parallel graph platforms. The irregular nature of graph methods is not supported well by the deep memory hierarchies of conventional distributed systems, requiring new processor and runtime system designs to tolerate memory and synchronization latencies. Moreover, the efficiency of relational table operations and matrix computations are not attainable when data is stored in common graph data structures. In this paper, we present HAGGLE, a high-performance, scalable data analytics platform. The platform’s hybrid data model supports a variety of distributed, thread-safe data structures, parallel programming constructs, and persistent and streaming data. An abstract runtime layer enables us to map the stack to conventional, distributed computer systems with accelerators. The runtime uses multithreading, active messages, and data aggregation to hide memory and synchronization latencies on large-scale systems.

Graph Analytics↗

On the predominance of unstable atmospheric conditions in the marine boundary layer offshore of the U.S. northeastern coast

Abstract The marine boundary layer of the northeastern U.S. is studied with focus on wind speed, atmospheric stability, and turbulent kinetic energy (TKE), the three most relevant properties in the context of offshore wind power development. Two long‐term observational data sets are analyzed. The first one consists of multilevel meteorological variables measured up to 60 m during 2003–2011 at the offshore Cape Wind tower, located near the center of the Nantucket Sound. The second data set comes from the 2013–2014 IMPOWR campaign (Improving the Modeling and Prediction of Offshore Wind Resources), in which wind and wave data were collected with new instruments on the Cape Wind platform, in addition to meteorological data measured during 19 flight missions offshore of New York, Connecticut, Rhode Island, and Massachusetts. It is found that, in this region: (1) the offshore wind resource is remarkable, with monthly average wind speeds at 60 m exceeding 7 m s −1 all year round, highest winds in winter (10.1 m s −1 ) and lowest in summer (7.1 m s −1 ), and a distinct diurnal modulation, especially in summer; (2) the marine boundary layer is predominantly unstable (61% unstable vs. 21% neutral vs. 18% stable), meaning that mixing is strong, heat fluxes are positive, and the wind speed profile is often nonlogarithmic (~40% of the time); and (3) the shape of the wind speed profile (log versus nonlog) is an effective qualitative proxy for atmospheric stability, whereas TKE alone is not.

54 ENVIRONMENTAL SCIENCES↗

NETL Plastic Pipes Project (Final Report)

Plastic or composite pipelines have been the bane of the utility locating industry because they are neither conductive nor magnetic which are the properties traditionally used to locate buried utilities. Ground penetrating radar (GPR) is an effective geophysical tool for locating plastic/composite pipelines where resistive cover allows for adequate penetration of radar energy. However, GPR has limited applicability in areas where the soil cover is conductive due to significant clay and/or salt content. This study examines complementary near-surface geophysical methods that are potentially useful for locating buried plastic/composite pipelines, either singly or in combination. Specifically, this modeling study used computational numerical methods to forward model the response of GPR, resistivity, seismic, gravity gradiometry, and photoacoustic/thermoacoustic imaging methods to plastic/composite pipelines for various scenarios including: (1) pipe diameters ranging between 2 in. to 12 in.; (2) burial depths ranging between 3 ft. to 4 ft.; (3) various degrees in contrast in physical properties (i.e., electrical permittivity, elasticity, resistivity, density); and (4) various experimental acquisition choices (e.g., GPR radar and seismic source frequencies, electrode spacing). Numerical modeling performed herein reconfirmed that GPR is the preferred method for detecting/locating plastic pipelines. A caveat for GPR detection is that the material covering the plastic pipe (trench fill material and adjacent soil) must be sufficiently resistive to allow the two-way propagation to the required depth of investigation and back to the surface. GPR was the only method modeled in this study that can be used to directly detect plastic pipelines of 2-in.-diameter and larger when buried 3-ft-deep. GPR data processing and imaging also can determine pipe depth, pipe diameter, trench dimensions, and moisture conditions. Seismic modeling results suggest that direct detection of a 12-in.-diameter plastic pipe at 3-ft.-depth may be possible under favorable conditions; however, the associated signature would be weak (e.g., surface- to S-wave, backscattered surface-waves, and/or forward scattered surface-waves to S-wave). Direct pipe detection under field conditions with noise and strong lateral geologic heterogeneity is doubtful. Numerical modeling also suggests that plastic pipelines can be indirectly located by detecting the trench in which they are buried. GPR, direct current (DC) resistivity, and seismic methods have the potential to locate the pipeline trench if there is sufficient contrast between the trench-wall and trench-fill materials for the physical property being measured by each method (i.e., electrical permittivity for GPR; resistivity for DC resistivity; or density, compressional velocity, or shear velocity for seismic). Modeling also indicated that currently available (commercial) gravity gradiometers would be unable to directly detect/locate plastic pipelines ≤ 8-in.-diameter when buried 3-ft.-deep given the typical instrument noise floor for field surveying as well as the expected density variations due to geologic heterogeneity. The numerical modeling performed in this project did not identify a universal geophysical technology that can locate buried plastic pipelines in all parts of the United States (although GPR is suggested for all areas with resistive cover). However, the project results suggest that a towed land streamer simultaneously acquiring multiple geophysical data types including multi-offset GPR, multi-channel DC resistivity, seismic geophone- and/or distributed acoustic sensing (DAS), and potentially photoacoustic/thermoacoustic data would be an appropriate platform for locating buried plastic pipeline. Moreover, the complementary multiphysics data acquired by a towed land streamer would permit the use of joint and/or cooperative inversion frameworks for a more rigorous and consistent data interpretation.

42 ENGINEERING↗

Testing Results from the Low Activity Waste Pretreatment System (LAWPS) Full-Scale Ion Exchange Column Test and Engineering Scale Integrated System Test - 18634

The U.S. Department of Energy (DOE), Office of River Protection's (ORP) primary mission is to retrieve and treat Hanford's tank waste and close the Tank Farms to protect the Columbia River. Mixed radioactive waste is stored in 177 underground tanks at the Hanford Site as reported in DOE/ORP 2003- 02, Environmental Impact Statement for Retrieval, Treatment, and Disposal of Tank Waste and Closure of the Single Shell Tanks at the Hanford Site, Richland WA, Inventory and Source Term Data Package. The 177 underground tanks are estimated to contain about 56 million gallons of waste. The Low Activity Waste Pretreatment System (LAWPS) Project provides for the early production of immobilized low activity waste (ILAW) by feeding LAW directly from Tank Farms to the Hanford Waste Treatment Plant's (WTP's) LAW Facility, bypassing the Pretreatment Facility. Prior to the transfer of feed to the WTP LAW Vitrification Facility, tank supernatant waste will be pretreated in the LAWPS to meet the WTP LAW waste acceptance criteria. The LAWPS will also facilitate the return of secondary liquid wastes from the WTP LAW Vitrification Facility to the Tank Farms. In November of 2015 DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS), awarded a contract to the AECOM team to design, fabricate and operate two test platforms to generate performance data at two different scales and demonstrate technology maturation. The first platform models the ion exchange (IX) columns at full scale, and the second platform models the integrated flowsheet (cross flow filter (CFF) and IX) at 1/9. scale. Overarching technical objectives of performing the full-scale ion exchange test and the engineering-scale integrated test are to: 1. Test interactions between unit process operations; 2. Test removal of non-radioactive cesium from process stream; 3. Test removal of undissolved solids from process stream; 4. Confirm operational flow rate range and stability; 5. Confirm volumetric throughput of waste stream over flow operating range; 6. Confirm range of process temperatures over planned operating range; 7. Establish system hydraulics and process criteria; 8. Coordinate key control and monitoring components; 9. Establish treated product chemistry meets requirements (cesium, solids, and pH); and 10. Test the hazard control strategy for a no flow condition through the IX column. Data collected during testing will be used by WRPS to validate the preliminary design, inform the final design of the permanent plant equipment, and demonstrate that the critical technology elements have advanced to a technology readiness level of 6 (prototypical system validation in a relevant environment). Testing on both platforms started in fall of 2016 generating NQA-1 data. This paper covers test results from the first five phases of testing on the 1/9. scale integrated test platform. A further three phases of testing are currently being executed, these including a 5.6 M sodium simulant containing foulant, a high viscosity simulant and finally a run performed with a lower Cs concentration (all earlier tests were spiked to 4 x Cs to reduce volume and cost). Results from these tests were not available at the time of writing available. Results are also presented from the full scale IX testing. Eight test were performed covering column loading, elution and regeneration; column loading, elution and regeneration with upflow displacement; IX column loading and gas migration; resin removal; solids accumulation; and IX column emergency recirculation and vent. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hydrological Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (Findable, Accessible, Interoperable, and Reusable: (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology-oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provide more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICON) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them.

(ICON) principles to address↗

UAS remote sensing (AltaX platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance (Level 0 data), Seward Peninsula, Alaska, 2023

Airborne remote sensing data collected using Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) AltaX platform on the Seward Peninsula, Alaska, USA. This package includes raw (L0) data from 11 flights flown over the NGEE-Arctic Kougarok mile marker 64 (MM64) and Teller MM 27 sites in July, 2023. The AltaX is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350 – 1000 nm. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), binary (*.dat, *.ulg), tabular (*.csv), geospatial (*.kml. *kmz), image (*.jpg, *.png, *.tif) and pdf formats. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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↗