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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The imaging Time-of-Propagation detector at Belle II

Here, we report on the construction, operation, and performance of the Time-of-Propagation detector with imaging used for the Belle II experiment running at the Super-KEKB e + e - collider. This detector is located in the central barrel region and uses Cherenkov light to provide particle identification among hadrons. The Cherenkov light is radiated in highly polished bars of synthetic fused silica (quartz) and transported to the ends of the bars via total internal reflection. One bar end is instrumented with finely segmented micro-channel-plate photomultiplier tubes to record the light, while the other end has a mirror attached to reflect the photons back to the instrumented end. Both the propagation times and hit positions of the Cherenkov photons are measured; these depend on the Cherenkov angle and together provide good discrimination among charged pions, kaons, and protons with momenta up to around 4 GeV/ c . To date, the detector has been used to record and analyze almost 600 fb −1 of Belle II data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Barriers to adopting artificial intelligence and machine learning technologies in nuclear power

Artificial intelligence and machine learning (AI/ML) technologies offer unique opportunities to transform nuclear plant operations and power generation. Benefits will be felt not only within existing analog and digital instrumentation and control, but also within work processes, the integration of people with technology and most importantly, the business case. The application of this new technology can help simplify complex problems and produce more effective decision-making, making nuclear power safer, more efficient, and more economically viable in the current energy market. Nonetheless, there are potential barriers to its adoption that must be overcome. The purpose of this paper is to categorize, review, and discuss barriers to AI/ML adoption within the nuclear power industry, with a focus on existing commercial reactors. Unique considerations for advanced reactors are also offered. Here we provide a comprehensive overview of the historical, technical, and business barriers that the industry faces, as well as stakeholder readiness, and end-user acceptance. We underscore the importance of user experience and offer potential solutions in overcoming each barrier. These include provisions for easier plant data access, a friendly regulatory environment, and investment in user trust and explainable AI.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

MVP: a modular viromics pipeline to identify, filter, cluster, annotate, and bin viruses from metagenomes

While numerous computational frameworks and workflows are available for recovering prokaryote and eukaryote genomes from metagenome data, only a limited number of pipelines are designed specifically for viromics analysis. With many viromics tools developed in the last few years alone, it can be challenging for scientists with limited bioinformatics experience to easily recover, evaluate quality, annotate genes, dereplicate, assign taxonomy, and calculate relative abundance and coverage of viral genomes using state-of-the-art methods and standards. Here, we describe Modular Viromics Pipeline (MVP) v.1.0, a user-friendly pipeline written in Python and providing a simple framework to perform standard viromics analyses. MVP combines multiple tools to enable viral genome identification, characterization of genome quality, filtering, clustering, taxonomic and functional annotation, genome binning, and comprehensive summaries of results that can be used for downstream ecological analyses. Overall, MVP provides a standardized and reproducible pipeline for both extensive and robust characterization of viruses from large-scale sequencing data including metagenomes, metatranscriptomes, viromes, and isolate genomes. As a typical use case, we show how the entire MVP pipeline can be applied to a set of 20 metagenomes from wetland sediments using only 10 modules executed via command lines, leading to the identification of 11,656 viral contigs and 8,145 viral operational taxonomic units (vOTUs) displaying a clear beta-diversity pattern. Further, acting as a dynamic wrapper, MVP is designed to continuously incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field of viromics. MVP is available at https://gitlab.com/ccoclet/mvp and as versioned packages in PyPi and Conda.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Coupled Experimental and High-Temperature Discrete-Element Method Modeling Studies of Aluminosilicate Particle Handling in Concentrated Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrated solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrated solar power environments. Coupled experimental and numerical studies of aluminosilicate particles in rotary kilns and dense particle curtains were performed for bulk temperatures up to 1073 K. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Temperature, spatial, and velocity profile data were extracted from experimental runs using embedded K-type thermocouple probes and particle image velocimetry techniques. Experimental and numerical studies were compared using spatial temperature profiles, velocity fields, and shape profiles of the bulk, granular flows. Numerical models were developed using commercially available discrete element method modeling software, Aspherix®. Existing Aspherix® functionality was expanded by introducing coupled radiative exchange modeling tools. The laboratory-scale rotary kiln was developed to investigate the steady-state heat and mass transfer performance of aluminosilicate particles based on particle type, bulk handling temperature, and wall roughness. The rotational speed of the rotary kiln was varied to control the relative impact of collisional and frictional effects upon the granular flow behavior. Heat and mass transfer performance was categorized based on the Froude number and the observed flow regimes of slipping, rolling, cascading, and centrifuging. Coupled discrete element method modeling studies were used to evaluate the effects of temperature-dependent, particulate mechanical properties upon bulk flow behavior and upon the relative effects of radiative, advective, and/or conductive heat transfer. A high-temperature (< 1073 K) falling particle curtain was similarly fabricated to investigate the heat and mass transfer performance of aluminosilicate particles in particle handling situations dominated by inter-particle collisions. The impact of particle type, flow preheat temperatures (< 1073K), and bulk mass flow rates were investigated upon the particle curtain shape, temperature, and velocity profiles. Coupled discrete element method modeling studies were performed to evaluate the varying impact of temperature-dependent, particulate mechanical properties on the bulk flow behavior and the temperature profile of the particle curtain.

14 SOLAR ENERGY↗
DOE OSTI2025

Latest Results from the ICARUS Experiment at the Short-Baseline Neutrino Program

The ICARUS Collaboration is now entering its fifth year of continuing operations of the 760-ton liquid argon T600 detector. The T600 was overhauled at CERN after operations at the LNGS underground laboratory in Italy and moved to its present location at FNAL - as part of the Short-Baseline Neutrino (SBN) program - where it successfully completed its commissioning phase in June 2022. At FNAL ICARUS collects neutrino interactions from both the Booster Neutrino Beam (BNB) and off-axis from the Main Injector Neutrino beam (NuMI). To date, ICARUS has accumulated approximately 5.2\times 10^{20} protons on target (POT) with the BNB and about 6.2\times 10^{20} POT with NuMI. Within the SBN program ICARUS will search for evidence of short-baseline oscillations, potentially explained by eV-scale sterile neutrinos, jointly with the Short-Baseline Near Detector (SBND). In addition, ICARUS is performing stand-along oscillation searches in disappearance mode and measuring neutrino cross sections on argon with both the BNB and NuMI beams. It is also performing searches for additional Beyond the Standard Model signatures. Preliminary results from the ICARUS experiment, using data from the BNB and NuMI neutrino beams, will be presented.

Hausner, Harry [Fermilab]↗
DOE OSTI2025

Latest Results from the ICARUS Experiment at the SBN Program

The ICARUS Collaboration is now entering its fifth year of continuing operations of the 760-ton liquid argon T600 detector. The T600 was overhauled at CERN after operations at the LNGS underground laboratory in Italy and moved to its present location at FNAL - as part of the Short-Baseline Neutrino (SBN) program - where it successfully completed its commissioning phase in June 2022. At FNAL ICARUS collects neutrino interactions from both the Booster Neutrino Beam (BNB) and off-axis from the Main Injector Neutrino beam (NuMI). To date, ICARUS has accumulated approximately $7.5\cdot 10^20$ protons on target (POT) with the BNB and about $6.2\cdot 10^20$ POT with NuMI. Within the SBN program ICARUS will search for evidence of short-baseline oscillations, potentially explained by eV-scale sterile neutrinos, jointly with the Short-Baseline Near Detector (SBND). In addition, ICARUS is performing stand-along oscillation searches in disappearance mode and measuring neutrino cross sections on argon with both the BNB and NuMI beams. It is also performing searches for additional Beyond the Standard Model signatures. Preliminary results from the ICARUS experiment, using data from the BNB and NuMI neutrino beams, will be presented.

Ricci, Alessandro Maria [U. Pisa (main); INFN, Pis↗
DOE OSTI2022

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗
DOE OSTI2022

Demonstration of RELAP5-3D for transient analysis of a dual coolant lead lithium fusion blanket concept

Our research aims to build a multiphysics framework for transient analysis of the Dual- Coolant Lead-Lithium (DCLL) blanket design of the proposed Fusion Nuclear Science Facility (FNSF) for all Onticipated Operational Occurrences (AOOs) using Reduced Order Models (ROMs). This paper presents an assessment of using RELAP5-3D for transient thermal-hydraulic blanket analysis of the DCLL design. Preliminary validation studies for the RELAP5-3D properties were conducted using a representative vertical flow loop model and a comparison study using experimental data from the thermal convection corrosion loops at ORNL. These studies inspected the thermal hydraulic response of Lead-Lithium Eutectic (PbLi) systems within the RELAP5-3D code; mainly pressure drop and heat transfer, as compared to analytical calculations and experimental data. The Magnetohydrodynamic (MHD) pressure drop effect for liquid metal under the effects of a uniform magnetic field was implemented into our models using an equivalent forms loss coefficient based on the phasic momentum equations. We verified our implementation of MHD pressure drop within RELAP5-3D using a systematic approach consisting of two studies. Models were developed to perform comparison studies based on experimental data from the Argonne Liquid metal EXperiment (ALEX) facility and the Magnetohydrodynamic PbLi Experiment (MaPLE) facility. Using the developed validation basis, we built a simplified DCLL channel model within RELAP5-3D, inspected MHD pressure drop and performed transient temperature analysis. The DCLL channel model used radial heating data from the International Thermonuclear Experimental Reactor (ITER) which was normalized to the FNSF design. Here, a representative startup transient was performed using a relative power curve from the initial ramp up of a long-term power pulse of the Tore Supra reactor. This study demonstrated that RELAP5-3D ROMs are capable of accurate transient analysis of the DCLL blanket. We have since utilized MCNP to develop heating profiles based on the FNSF design and are working toward implementing them into our DCLL model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Perspectives on Polyolefin Catalysis in Microfluidics for High-Throughput Screening: A Minireview

Polyolefins are the largest produced plastics in the world which traditionally employ continuous stirred tank reactors and fluidized bed reactors for commercial production. The operating condition, reaction kinetics, and molecular interactions inside the reactor strongly affect the polyolefin properties, which require stringent process control in conventional procedures. Understanding the catalytic pathway, behavior of polymer particles and effect of reactor conditions are essential for designing specific polymer properties, namely the molecular weight, chain length, polydispersity, etc. Microfluidics can play a significant role in designing polymers tailored to the user needs. Smaller channel dimensions help obtain uniform reaction conditions over the length of the microfluidic reactor in a controlled environment. With real-time monitoring techniques in microfluidics, even single particle growth of polymer can be studied to understand the parameters affecting the polymer properties. High throughput microfluidics can help catalyst screening in a short duration with less consumption of reagents generating less waste. When supplemented with efficient machine learning algorithms, automated high throughput microfluidics has the potential to rapidly optimize the process and develop new knowledge even with a limited data set. When trained on data sets generated using microfluidic experiments that are designed efficiently with working knowledge of the process, machine learning algorithms can provide the relationship between the multivariable parameters space and polymer properties, which is not possible with the traditional statistical methods and interpolation techniques. Here, the rise in the utilization of microfluidics, with the advancement of machine learning algorithms, for polyolefin catalysis, highlights the importance of microfluidics for catalyst discovery, parameter optimization, and understanding reaction pathway for producing polymers with specific properties for specialized applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Computing Hypergraph Homology in Chapel

In this paper, we discuss our experience in implementing homology computation, in particular Betti number calculation in Chapel hypergraph Library (CHGL). Given a dataset represented as a hypergraph, a Betti number for a particular dimension $k$ indicates how many $k$-dimensional `voids' are present in the dataset. Computing Betti number involves various array-centric and linear algebra operations. We demonstrate that implementing these operations in Chapel is both concise and intuitive. In addition, we show that Chapel provides language constructs for implementing parallel and distributed execution of the linear algebra kernels with minimal effort. Syntactically, Chapel provides succinctness of Python, while delivering comparable and better performance than C++-based and Julia-based packages for calculating Betti numbers respectively.

hypergraph, topological data analysis↗
DOE OSTI2021

Transportation Hub Infrastructure Expansion: Decision Support Under Uncertainty

The Athena project (www.athena-mobility.org) has worked to investigate the relationship between the Dallas-Fort Worth Airport (DFW) and the greater Dallas area in order to better understand and therefore better inform future decision-making regarding the critical infrastructure that influence mobility between the airport and the city. Through this work, infrastructure related to curbside pickup and drop-off, parking, public transit, and the road network congestion were identified as critical to the operation of the DFW transportation hub. The infrastructure analysis and expansion aspect of the Athena project is focused on the restructuring of the CTA curb as a hierarchical curb and the building or repurposing of parking infrastructure as the interplay between these two areas. Many sources of uncertainty exist that may impact future airport and transportation hub operations, such as passenger volume growth, population demographic changes over time, electric vehicle (EV) adoption rates, and autonomous vehicle (AV) adoption rates. Due to these sources of uncertainty, we have selected for our research a modeling framework that can capture various types of uncertainty and hedge against those uncertainties in the optimization process. We analyze road network and curb congestion, the rise of transportation networking companies, trends in parking usage, existing policies around this infrastructure, airport revenue streams, and other contributing factors to enable infrastructure decision making with less uncertainty. To accomplish this wholistic analysis, we have developed a novel multi-stage, multi-period stochastic optimization model which considers the airport's decisions from 2025-2045 under different possible future macro trajectories and day-to-day variations in operational conditions captured as "annual representation of operations" scenarios with respective probabilities. This model has also been designed to leverage the outputs of various efforts under the Athena project to create a combined decision framework for infrastructure decisions. These various efforts include the route optimization model, the ASPIRES simulation, the mode choice model, and the SUMO traffic simulation. Our computational experiments of this system at scale have resulted in a working version of our infrastructure model which enables the explicit representation and consideration of various sources of uncertainty in the decision process to enable robust, flexible decision-making. This model has been effectively run on NREL's HPC system, Eagle, with large numbers of stochastic scenarios and shows promise as a scalable tool for robust consideration of uncertainties in airport planning. We have tested our model using 30,240 operational circumstances in total, resulting in a problem with more 200 million variables. This model was solved in several different configurations, and a workflow to simulate the performance of the infrastructure model results was developed and deployed. In general, our results indicate that a combination of remote parking, remote curb infrastructure, and dynamic pricing can generate revenue, reduce emissions, accommodate emerging technologies such as AVs and EVs, and manage airport passenger growth over time. We note the success of the proposed strategy depends on the data collection and forecasting abilities of DFW. We have also seen that the AV adoption by TNCs might necessitate larger amounts of remote curb. The results of this work inform strategies for airport infrastructure decision making, as well as demonstrate the value of an adaptable model, but also indicate that there are avenues remaining where further research would be of value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Benchmark Specification for Select Experiments Conducted at the University of Wisconsin-Madison Thermal Stratification Test Facility

The Department of Energy (DOE)-Nuclear Energy University Programs (NEUP) supported the creation and operation of the Thermal Stratification Test Facility (TSTF) at the University of Wisconsin Madison (UWM) as part of a larger effort to understand thermal stratification behavior in liquid-metal-cooled reactors. The TSTF was designed to simulate transients in a reactor plenum that are known to cause thermal stratification. High-reliability and high-resolution measurements of the flow and temperature were collected for use as experimental benchmarks to support validation efforts for computational models. The results of these tests contribute to the greater understanding of thermal stratification behavior of liquid sodium under various configurations and operating conditions. The six TSTF tests selected for benchmarking are a set of forced circulation tests at a fixed flow rate with different Upper Internal Structure (UIS) configurations in the test section (no UIS, solid UIS, and a UIS with flow area of 4, 8, 12, and 100%). This report provides a complete description of the benchmark problems, including all key test facility details, descriptions of each test condition, and measured data for comparison with modeled results.

42 ENGINEERING↗
DOE OSTI2025

Measurement of Spray Chamber Ignition Delay and Cetane Numbers for Aviation Turbine Fuels

Experiments using pure compounds, National Jet Fuels Combustion Program (NJFCP) test fuels, and commercial jet fuels were conducted to demonstrate the equivalence of the indicated cetane number (ICN) and derived cetane number (DCN) for jet fuels. The calibrated range for ICN was also extended to lower cetane number (CN) values (5 to 35) to allow CN quantification for jet fuel synthetic blending components (SBCs) with low CN. ICN and DCN were shown to be highly correlated for values above about 30. This study presents the most comprehensive comparison of these two methods published to date. Because of the importance of low-volume test methods for early-stage SBC production process development, we demonstrated that ICN and DCN can be accurately measured with 15 mL of fuel, well below 40 to 100 mL required by standard methods. ICN or DCN is important for jet fuels because fuels with lower CN are more prone to lean blowout (LBO), an undesirable operational failure in a jet engine. Comparing data on a fuel-to-air ratio (Φ) at LBO for the NJFCP fuels shows similar linear correlations for ICN and DCN. Ignition delay measurements at lower-pressure and higher-temperature conditions may be more directly relevant to LBO. At 675 °C, 0.5 MPa, and a global Φ of roughly 0.68, ignition delay time correlations to LBO were similar to those produced from DCN and ICN. A much weaker correlation was obtained with a global Φ value of 0.34.

09 BIOMASS FUELS↗
DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for the Proposed Versatile Test Reactor, Oak Ridge, Tennessee

The US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre (~13,000-ha) Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park (NERP) and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education also represent potential effects of federal actions on the NERP, and impacts on, e.g., deer harvest, must be considered on the Oak Ridge Wildlife Management Area when other aspects of the human environment are affected. The United States currently has no fast neutron testing capability to support advanced nuclear research and development. The proposed Versatile Test Reactor (VTR) will take advantage of current investments by the US government and private industry in nuclear reactors to expedite the design and construction process, using proven technology to create a world-class scientific infrastructure. The VTR will take advantage of fast neutrons provided by this proven technology, along with a capability to rapidly insert, conduct, and remove state-of-the-art experiments. An advantage of the VTR is that it can support future innovations in experimental capabilities without modifying the facility. The VTR will support progress in a variety of science and technology areas, including testing and qualification of advanced reactor fuels; testing and qualification of innovative structural materials; testing of innovative components and instruments; validation of advanced modeling and simulation tools; and versatility for future technical missions. Through proven technology, the VTR can take advantage of existing reactor designs and operating experience to reduce the risk, cost, and time for design and construction. The top available resources of DOE laboratories, industry, and universities will be used to expedite reactor design and construction toward developing the scientific infrastructure that affords a strong testing capability that can be sustained over many years. This report summarizes current knowledge of natural and cultural resources primarily within the VTR construction area. At the time of this report, the proposed VTR site design includes a construction area of ~150.4 acres (~69.9 ha), which contains an ~51.3-acre (~20.8-ha) operations area, located within forested natural areas of the ORR. The primary goal of the work presented here was to evaluate potential effects on sensitive resources that might result from development and construction activities associated with VTR. In addition to on-the-ground surveys during spring and summer 2020 by the ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled from a 2011 forest inventory and supplemented with limited ground observations in 2020. The individuals who obtained and compiled the data presented here are familiar with and routinely assess sensitive resources on the ORR. Anyone who references this report must consider that the timing of surveys did not permit a complete delineation of the resources that will be affected. If the VTR project proceeds, additional surveys will be required to account for the seasonal patterns of various threatened and endangered species. Data deficiencies and potential resources that likely went undetected are indicated where possible. Accordingly, this report should facilitate more environmentally sound decisions during planning and 2 development of the VTR site, provide a foundation for further assessment of sensitive and cultural resources, and help project managers better address regulatory guidance and DOE policies on sustainable development in compliance with, for example, the US Endangered Species Act (ESA), Migratory Bird Treaty Act (MBTA), Tennessee Rare Plant Protection and Conservation Act of 1985, Tennessee Nongame and Endangered or Threatened Wildlife Species Conservation Act of 1974, several federal and state regulations regarding aquatic resource protection, and site-specific policies as outlined in various ORR management plans developed by ORNL and TWRA for DOE.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Measurements and Analyses to Enable Science for the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE)

Coastal cities provide the opportunity to characterize the substantial effects of manmade particles on marine cloud properties and processes. La Jolla lies to the north of San Diego, California, but it is often about a day directly downwind of the major pollution sources located in the ports of Los Angeles and Long Beach. The large dynamic range of aerosol particle concentrations combined with the multi-hour to multi-day persistence of stratocumulus cloud layers makes the site ideal for investigating the seasonal changes in cloud and aerosol properties as well as the quantitative relationships between cloud and aerosol properties. The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized the extent, radiative properties, aerosol interactions, and precipitation characteristics of stratocumulus clouds in the Eastern Pacific across all four seasons at two coastal sites in La Jolla. This project was designed to enhance and expand the scientific uses of the ARM AMF1 measurements from EPCAPE. The goal was to ensure meaningful observations were collected that would enable science. The project included the following objectives: (1) Reviewing the ARM AMF1 measurements [ARM, 2021a; b] and circulating a summary of the measurements each week, (2) Comparing AMF1 measurements to those provided by collaborators (including filter measurements at the pier), (3) Collecting and analyzing filter samples from Scripps Pier by Fourier Transform Infrared spectroscopy (FTIR) and X-ray Fluorescence (XRF), (4) Assisting in operations of instruments provided by Guest PIs when possible, and (5) Providing an initial compilation of EPCAPE aerosol and cloud seasonal differences. The expected outcomes of these objectives were enhanced proposals and publications using EPCAPE measurements by helping to identify instrument issues, expanded data access and awareness by distributing weekly plots and related summaries, improved source-related attribution of aerosols with elemental tracers, additional observations provided by Guest PIs, and accelerated ACI studies enabled by the compiled seasonal summaries of aerosol and cloud properties. Three examples of the science enabled by this project are findings that (i) aerosol and cloud aqueous production contributes more than half of sulfate particle mass concentration, (ii) upwind sources make chemical composition very similar at nearby sites despite local differences in meteorology, and (iii) most of the large mass concentration of semi-volatile organic components is co-emitted and co-evaporated with nitrate. Together these findings illustrate how ARM extended field campaigns in coastal regions can be used to constrain ACI processes with direct observations. By using the unique ARM suite of cloud radiative products in addition to the measured aerosol properties at a coastal location, we were able to address the more specific question of which aerosol particles cause how much of the effects on clouds. Identifying this signature in coastal areas provides an opportunity to test the representation of aerosol sources by global models in a range of clean and urban-influenced conditions.

Russell, Lynn [Univ. of California, San Diego, CA ↗
DOE OSTI2022

A New Search for Low-mass Dark Matter and an Examination and Reduction of the Uncertainty due to the Photoelectric Absorption Cross Section using a Cryogenic Silicon Detector with Single-charge Sensitivity

Many astrophysical observations point to the abundant existence of dark matter (DM) in the universe composed of particles beyond the Standard Model. However despite numerous experiments using different techniques, DM particles have yet to be directly observed. The Super Cryogenic Dark Matter Search (SuperCDMS) SNOLAB experiment will employ silicon and germanium crystal detectors operated at temperatures as low as 15~mK to probe DM interactions using phonon and ionization signals. Recently, R\&D; facilities have developed gram-sized high-voltage eV-scale (HVeV) silicon detectors that achieve single-electron-hole-pair resolution. By probing effective DM-electron interactions, these devices can be used for searches of low-mass DM candidates.This dissertation presents a DM search experiment known as HVeV Run~2 that employs a second-generation HVeV detector operated in an above-ground laboratory at Northwestern University (IL, USA). Energy spectra are obtained from a blind analysis with 0.39 and 1.2\,g-days of exposure with the detector biased at 60 and 100\,V, respectively. The 0.93~gram detector achieves a 3\,eV phonon energy resolution, corresponding to a world-leading charge resolution of 3\,\% of a single electron-hole pair for a detector bias of 100\,V. With charge carrier trapping and impact ionization effects incorporated into the DM signal models, the resulting exclusion limits are reported for inelastic DM-electron scattering for DM masses from 0.5--$10^{4}$\,MeV$/c^{2}$; in the mass range from 1.2--50\,eV$/c^{2}$ the limits for dark photon and axion-like particle absorption are reported.Several DM search experiments, including HVeV Run~2, are sensitive to low-mass DM candidates that rely on the temperature-dependent photoelectric absorption cross section of silicon. However discrepancies in the underlying literature data result in dominating systematic uncertainties on the DM exclusion limits. In order to reduce these systematic uncertainties, this dissertation presents a novel method of making a direct, low-temperature measurement of the photoelectric absorption cross section of silicon at energies near the band gap (1.2--2.8\,eV).

Wilson, Matthew James↗
DOE OSTI2024

Demonstration of Temperature Compensation Techniques for SPNDs Operating in High Temperatures

This report presents the testing results of rhodium-based self-powered neutron detectors (Rh-SPND) irradiated in a furnace dry tube from ambient temperature to 850°C at the Ohio State University Research Reactor. The purpose of the experiment is to demonstrate the technique and application of a temperature compensation technique for the Rh-SPND. This is performed by characterizing the temperature effects observed in past experiments—a displacement current and a stabilized dark current—of the Rh-SPND as a function of temperature under the models of shifting space charges as a product of photoconductivity properties. Low-power irradiation at the OSURR was performed with stabilized temperatures of ambient, 550, 575, 600, 625, 650, 675, and 700°C were first performed to obtain the curve fit parameters that describes the temperature effects. The results provided further insight for the behavior of the SPND at high temperatures in accordance with available insulation conductivity models. Transition points from photoconductivity to ionic conductivity were identified in the range of 550–600°C. Additionally, transition points ionic to electric conductivity were observed in the range of 675–700°C, however, the data was not able to fully capture the transition and did not have enough resolution to provide predictive compensation based only on temperature readings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗