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At least 415 records · Page 23

Washington Air-Sea Interaction Research Facility Waves and Currents Test Data

This archive includes data from the University of Washington WASIRF (Washington Air-Sea Interaction Research Facility) flume. WASIRF is a laboratory testing tank at the Northwest National Marine Renewable Energy Center designed to investigate wind-wave-current interactions. It includes test data for simultaneous waves and current generation done at the WASIRF lab. A report included in the archive further details testing methodology. Wave and current data is provided in .dat files.

16 TIDAL AND WAVE POWER↗

Anion-exchange membrane water electrolysis: insights from round-robin testing

As research and industrial interest in anion-exchange membrane water electrolysis (AEMWE) grows, there is an increasing need for reliable baselines and cross-lab validation of results. The wide variety of material sets and operating conditions under consideration for AEMWE has thus far limited efforts for standardization. In this study, round-robin testing was conducted in deionized water and KOH-based supporting electrolyte by 5 institutions from academia, national laboratories, and industry to provide baseline performance data and identify sources of cross-lab variability. Baseline membrane electrode assemblies were fabricated with commercial catalysts, membranes, and transport layers using standard techniques and tested using reagent-grade electrolytes, aiming for accessibility rather than state-of-the-art performance. From all tests, the average voltage at 1 A/cm 2 was 2.72 ± 0.17 V and 1.87 ± 0.03 V in deionized water and 0.1 M KOH, respectively. The maximum in-house and cross-lab variations at this current density were 118 mV and 476 mV in water and 60 and 88 mV in 0.1 M KOH. The KOH purity, station contamination, and temperature control were identified as possible factors affecting performance between labs, with in-house specific variation attributed to sample-to-sample differences in fabrication, cell assembly, and station contamination. This work provides a commercial baseline for the field and highlights the need for improved standardization and reproducibility in AEMWE research.

08 HYDROGEN↗

CJ15 global PDF analysis with new electroweak data from the STAR and SeaQuest experiments

We present updates to a recent CTEQ-Jefferson Lab (CJ) global analysis of parton distribution functions with a new set of electroweak data that provide unique access to quark flavor separation in the proton. In particular, recent W W and Z Z boson measurements from the STAR experiment at RHIC put additional constraints on light quarks and antiquarks near the valence regime. The new measurement of the Drell-Yan lepton pair production ratio in p+p p + p and p+d p + d collisions by the SeaQuest experiment at Fermilab extends the large- x x coverage of the previous E866 experiment and sheds new light on the light antiquarks distribution. In this report, the impact of these new data sets on parton distribution functions will be presented with emphasis given to the flavor asymmetry of the light antiquark sea at large values of the parton momentum x x .

Park, Sanghwa↗

Measurements of Polarization Transfers in Real Compton Scattering by a proton target at JLAB. A new source of information on the 3D shape of the nucleon

In this thesis work, results of the analysis of the polarization transfers measured in real Compton scattering (RCS) by the Collaboration E07-002 at the Je fferson Lab Hall-C are presented. The data were collected at large scattering angle (theta_cm = 70deg) and with a polarized incident photon beam at an average energy of 3.8 GeV. Such a kind of experiments allows one to understand more deeply the reaction mechanism, that involves a real photon, by extracting both Compton form factors and Generalized Parton Distributions (GPDs) (also relevant for possibly shedding light on the total angular momentum of the nucleon). The obtained results for the longitudinal and transverse polarization transfers K_LL and K_LT, are of crucial importance, since they confirm unambiguously the disagreement between experimental data and pQCD prediction, as it was found in E99-114 experiment, and favor the Handbag mechanism. The E99-114 and E07-002 results can contribute to attract new interest on the great yield of the Compton scattering by a nucleon target, as demonstrated by the recent approval of an experimental proposal submitted to the Jefferson Lab PAC 42 for a Wide-angle Compton Scattering experiment, at 8 and 10 GeV Photon Energies. The new experiments approved to run with the updated 12 GeV electron beam at JLab, are characterized by much higher luminosities, and a new GEM tracker is under development to tackle the challenging backgrounds. Within this context, we present a new multistep tracking algorithm, based on (i) a Neural Network (NN) designed for a fast and efficient association of the hits measured by the GEM detector which allows the track identification, and (ii) the application of both a Kalman filter and Rauch-Tung-Striebel smoother to further improve the track reconstruction. The full procedure, i.e. NN and filtering, appears very promising, with high performances in terms of both association effciency and reconstruction accuracy, and these preliminary results will be discussed in detail in the last chapters.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CJ15 global PDF analysis with new electroweak data from the STAR and SeaQuest experiments

We present updates to a recent CTEQ-Jefferson Lab (CJ) global analysis of parton distribution functions with a new set of electroweak data that provide unique access to quark flavor separation in the proton. In particular, recent W and Z boson measurements from the STAR experiment at RHIC put additional constraints on light quarks and antiquarks near the valence regime. The new measurement of the Drell-Yan lepton pair production ratio in p+p and p+d collisions by the SeaQuest experiment at Fermilab extends the large-x coverage of the previous E866 experiment and sheds new light on the light antiquarks distribution. In this report, the impact of these new data sets on parton distribution functions will be presented with emphasis given to the flavor asymmetry of the light antiquark sea at large values of the parton momentum x.

Park, Sanghwa↗

Shallow Geothermal Resources for Cooling Applications at the University of Hawai‘i

Scientists at Berkeley Lab have teamed up with The University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s (DOE’s) Energy Transitions Initiative Partnership Project (ETIPP) to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology for building cooling, energy efficiency, and emissions reduction applications in Hawai’i. The team is assessing the data necessary to model the feasibility of deploying this technology, the actual models that will be used, and what hurdles need to be overcome to install a demonstration case. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project, and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, making it crucial to select sites with large enough values of these properties. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Both closed-loop and open-loop systems are being investigated. Another option being considered is using cool seawater as the source of chill. Currently work is progressing on two fronts. A hydrogeologic model for a closed-loop system is being developed for the Stan Sheriff Center at the UH Manoa campus, where a subsurface karst system immediately downgradient of the borefield may provide efficient removal of heated groundwater. The team will also develop a technoeconomic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air conditioning system. At the state scale, geographic information system (GIS) layers of various attributes relevant for GHE are being combined to develop an overall favorability map for employing GHE in Hawai‘i.

Doughty, C↗

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗

Final results of the GEp(III) experiment at Jefferson Lab

The set of proton elastic form factor ratio data was extended to Q{sup 2} = 8.5 GeV{sup 2} with a recent experiment at JLab, GEp(III); the nucleon form factor data base is discussed and several conclusions presented. These data are the result of measurements of the polarization of the recoil proton; they have been known to differ significantly from Rosenbluth separation of cross section data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Power Grid Contingency Analysis with Machine Learning: A Brief Survey and Prospects

We briefly review previous applications of machine learning (ML) in power grid analyses and introduce our ongoing effort toward developing a generative-adversarial (GA) model for fast and reliable grid contingency analyses. According to our review, the persisting limitation of traditional ML techniques in grid analyses is the need for an exhaustive amount of training data for model generalization and accurate predictions. GA models overcome this limitation by first learning true data distribution from a small training set, from which new samples assimilating true data are generated with some variations. Subsequently, GA models can transfer learn or super-generalize with increased accuracy, that is, accurately predict n - (k + 2) contingencies from a small n - k training set and generated n - (k + 1) data. The joint effort between Idaho National Lab and Florida State University strives to develop a zero-shot and deep learning-based contingency analysis tool, named Smart Contingency Analysis Neural Network (SCANN), by leveraging the aforementioned advantages of GA models. The basic architecture of SCANN stems from the Latent Encoding of Atypical Perturbations network combined with an adversarial network, and it is designed to generate imbalanced power flow data from learned true data distributions for prediction purposes. Here we also introduce the abstract concept of resilience-chaos plots, a new resilience characterization tool proposed to complement SCANN by aiding in the assessment of large amounts of high-order contingency predictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The DVCS program in Hall A at Jefferson Lab

The DVCS Hall A/JLab experiments aim at providing data relevant to the '3-D structure of the nucleon' exploration by measuring precise absolute cross sections in the Deep Exclusive domain. Deeply Virtual Compton Scattering off the nucleon is the simplest process which is sensitive to the Generalized Parton Distribution functions. Currently, the DVCS in Hall A program is articulated in three steps. The first generation of experiments showed the power of precise measurement of absolute cross sections to test factorization of the DVCS amplitude. The second generation of experiments (data under analysis) will separate (at twist-2 order) all of the terms making up the unpolarized cross section. And the third generation of experiments (data to be taken with the 12 GeV beam at JLab) will provide measurements over an extended kinematic range. In this conference proceeding, the status of the DVCS in Hall A/JLab program is reviewed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SULI End of Summer Presentation

This presentation made on Power Point is a brief summary of my work enhancing the Supervisory Control and Data Acquisition (SCADA) architecture for Idaho National Lab’s Critical Infrastructure Test Range Complex (CITRC). This work was part of an on-going project to create a digital twin of CITRC that will be implemented for resiliency research. Resiliency is growing more important as extreme weather, aging infrastructure, and increasing load all exert stress on the United States power grid. This presentation highlights how I documented the existing devices and data flow on site and then updated specific device settings to better support the needs of the project. It also examines future use of this data in the digital twin data warehouse (DeepLynx), and future Artificial Intelligence and Advanced Distribution Management System applications. It will be presented to the B751 Water and Energy Systems Analysis group at INL during my last week.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

University of Hawai‘i, Shallow Geothermal Resources: Energy Technology Innovation Partnership Project (Final Report)

Scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) have teamed up with the University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s Energy Technology Innovation Partnership Project to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology. UH requested this analysis to evaluate opportunities in building cooling, energy efficiency, and emissions reduction applications in Hawai‘i. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that, over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, so sites with large enough values of these properties must be selected. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Primarily, closed-loop systems have been investigated. Other options considered are open-loop systems and using cool seawater as the chilling source. Project work investigated the feasibility of GHE technology at two scales. At the island scale, GIS layers of various attributes relevant for GHE were combined to develop an overall favorability map for employing GHE in Hawai‘i. At the local scale, a hydrogeologic model for the subsurface component of a closed-loop system was developed for the Stan Sheriff Center at the UH Manoa campus. This site is considered promising because the rock below and immediately downgradient of the borefield is highly permeable, consisting of a subsurface karst system (limestone containing high-permeability open channels), which is underlain by a thick, high-permeability fractured basalt. Moreover, the site is near the base of the Ko‘olau Range, providing a large hydraulic head gradient. Thus, groundwater flow through the site is expected to be large, enabling efficient removal of heated groundwater. A full-GHE-system model of the site was also developed, with a simplified representation of the subsurface, in which groundwater flow is not considered and heat transfer is purely by conduction. Using the building cooling load data provided by UH, simulation results show that with groundwater flow present, a GHE can operate successfully for at least 10 years, but with no groundwater flow, the subsurface begins to heat up after only one year of operation, making the GHE unviable within 2-6 years. The team also developed a techno-economic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air-conditioning system. The GHE system is advantageous economically if favorable tax incentives and interest rates can be obtained.

15 GEOTHERMAL ENERGY↗

Spin Asymmetries and Helicity Amplitudes in Photo-Production from Polarized Neutrons

Pseudoscalar meson photoproduction experiments lead the search for an expanded $N^*$ spectroscopy that is required by lattice solutions of QCD. Extensive data have been collected with proton targets that can potentially over-determine the production amplitude and allow a search for weak resonances. In contrast, data on photoproduction from neutrons is drastically limited. Both are needed since the $\gamma p N^*$ and $\gamma n N^*$ photo-couplings to I = 1/2 states are different and provide complementary information on the mechanisms for resonance excitation. The main subtleties in experiments with an effective polarized neutron target are reviewed. The considerable impact of new polarization data on multipole analyses are discussed, using the example of recent $\pi^- p$ measurements of the beam-target helicity asymmetry ($E$) from polarized $H\!D$ in CLAS at Jefferson Lab. Here, new partial wave analyses incorporating these data have found significant changes in helicity amplitudes of some established resonances, and signatures of weak resonances that previously were observed only in hyperon decay channels.

74 ATOMIC AND MOLECULAR PHYSICS↗

FY2019 Energy Efficient Mobility Systems Annual Progress Report

EEMS Program activities during FY 2019 focused on analytical research to understand the impacts that new mobility technologies and services will have at the vehicle, traveler, and overall transportation system-level. This research included the development of vehicle and transportation system simulation models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system. This document presents a brief overview of the EEMS Program and documents progress and results for projects within four of the five EEMS activity areas: (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) High Performance Computing and Big Data Solutions for Mobility Data, (3) Advanced R&D Projects conducted by industry and academia, and (4) Core Modeling, Simulation, and Evaluation, Similarly, the remaining EEMS activity area – (5) Living Labs (managed under VTO’s Technology Integration Program). Each of the individual progress reports provide a project overview and highlights of the technical results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Efficient Mobility Systems 2018 Annual Progress Report

Energy Efficient Mobility Systems (EEMS) Program activities during FY 2018 focused on analytical research to understand the impacts that new mobility technologies and services will have at the vehicle, traveler, and overall transportation system-level. This research included the development of vehicle and transportation system simulation models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system This document presents a brief overview of the EEMS Program and documents progress and results for projects within four of the five EEMS activity areas: (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) High Performance Computing and Big Data Solutions for Mobility Data, (3) Advanced R&D Projects conducted by industry and academia, and (4) Core Modeling, Simulation, and Evaluation, Similarly, the remaining EEMS activity area – (5) Living Labs (managed under VTO’s Technology Integration Program). Each of the individual progress reports provide a project overview and highlights of the technical results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

National Geothermal Data System: A Geothermal Data System for Exploration and Development

Geothermal-relevant geosciences data from all 50 states (www.stategeothermaldata.org), federal agencies, national labs, and academic centers are being digitized and linked in a distributed online network funded by the U.S. Department of Energy Geothermal Data System (GDS) to foster geothermal energy exploration and development through use of interactive online ‘mashups,’data integration, and applications. Emphasis is first to make as much information as possible accessible online, with a long range goal to make data interoperable through standardized services and interchange formats. A growing set of more than thirty geoscience data content models is in use or under development to define standardized interchange formats for: aqueous chemistry, borehole temperature data, direct use feature, drill stem test, seismic event hypocenter, fault feature, geologic contact feature, geologic unit feature, thermal/hot spring description, metadata, quaternary fault, volcanic vent description, well header feature, borehole lithology log, crustal stress, gravity, heat flow/temperature gradient, permeability, and feature description data like developed geothermal systems, geologic unit geothermal characterization, permeability, production data, rock alteration description, rock chemistry, and thermal conductivity. Map services are also being developed for isopach maps, aquifer temperature maps, and several states are working on geothermal resource overview maps. Content models are developed based on existing community datasets to encourage widespread adoption and promulgate content quality standards. Geoscience data and maps from other GDS participating institutions, or “nodes” (e.g., U.S. Geological Survey, Southern Methodist University, Oregon Institute of Technology, Stanford University, the University of Utah) are being supplemented with extensive land management and land use resources from the Western Regional Partnership (15 federal agencies and 5 Western states) to provide access to a comprehensive, holistic set of data critical to geothermal energy development. As of May 2012 , we have nearly 37,000 records registered in the system catalog, and 550,075 data resources online, along with hundreds of Web services to deliver integrated data to the desktop for free downloading or online use. The data exchange mechanism is built on the U.S. Geoscience Information Network (USGIN, http://usgin.org and http://lab.usgin.org) protocols and standards developed as a partnership of the Association of American State Geologists (AASG) and U.S. Geological Survey (USGS). Keywords Data

15 GEOTHERMAL ENERGY↗

Overview of SIDIS results from Hall B at Jefferson Lab

We present studies of spin and azimuthal asymmetries in pion production in semi-inclusive deep inelastic scattering (SIDIS), using the data sets from the CEBAF Large Acceptance Spectrometer (CLAS) at Jefferson Lab with polarized $NH_3$ and unpolarized hydrogen targets. Three run periods, e1-6, e1-f and eg1-dvcs used respectively 5.7, 5.5 and 5.8 GeV longitudinally polarized electron beam and unpolarized liquid hydrogen (e1-6, e1-f) and polarized $NH_3$ (eg1-dvcs) targets. Pion channels ($\pi^+$, $\pi^-$, $\pi^0$) were studied over a broad kinematical range ($x = 0.1 - 0.6$, $Q^2 = 1.0 - 4.5 $ GeV$^2$, $z = 0.0 - 1.0$, $\Phperp^2 = 0.0 - 1.0$ GeV$^2$, and $-180^\circ < \phi < 180^\circ$). These measurements give insights into the transverse momentum dependence of parton distribution functions (PDFs) for different polarization states, describing the dynamics of quarks and gluons inside of the proton.

Avakian, Harut↗

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗