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DOE OSTI2021

Elastic-instability–enabled locomotion

Locomotion of an organism interacting with an environment is the consequence of a symmetry-breaking action in space-time. Here we show a minimal instantiation of this principle using a thin circular sheet, actuated symmetrically by a pneumatic source, using pressure to change shape nonlinearly via a spontaneous buckling instability. This leads to a polarized, bilaterally symmetric cone that can walk on land and swim in water. In either mode of locomotion, the emergence of shape asymmetry in the sheet leads to an asymmetric interaction with the environment that generates movement––via anisotropic friction on land, and via directed inertial forces in water. Scaling laws for the speed of the sheet of the actuator as a function of its size, shape, and the frequency of actuation are consistent with our observations. The presence of easily controllable reversible modes of buckling deformation further allows for a change in the direction of locomotion in open arenas and the ability to squeeze through confined environments––both of which we demonstrate using simple experiments. Our simple approach of harnessing elastic instabilities in soft structures to drive locomotion enables the design of novel shape-changing robots and other bioinspired machines at multiple scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Demonstration of a rapidly-swept external cavity quantum cascade laser for atmospheric sensing applications

The application of quantum cascade lasers (QCLs) in atmospheric science for trace detection of gases has been demonstrated using sensors in point or remote sensing configurations. Many of these systems utilize single narrowly-tunable (~10 cm-1) distributed feedback (DFB-) QCLs that limit simultaneous detection to a restricted number of small chemical species like H2O or N2O. The narrow wavelength range of DFB-QCLs precludes accurate quantification of large chemical species with broad rotationally-unresolved vibrational spectra, such as volatile organic compounds, that play an important role in the chemistry of the atmosphere. External-cavity (EC-) QCL systems are available that offer tuning ranges >100 cm-1, making them excellent IR sources for measuring multiple small and large chemical species in the atmosphere. While the broad wavelength coverage afforded by an EC system enables measurements of large chemical species, most commercial systems can only be swept over their entire wavelength range at less than 10 Hz. This prohibits broadband simultaneous measurements of multiple chemicals in plumes from natural or industrial sources where turbulence and/or chemical reactivity are resulting in rapid changes in chemical composition on sub-1s timescales. At Pacific Northwest National Laboratory we have developed rapidly-swept EC-QCL technology that acquires broadband absorption spectra (~100 cm-1) on ms timescales. The spectral resolution of this system has enabled simultaneous measurement of narrow rotationally-resolved atmospherically-broadened lines from small chemical species, while offering the broad tuning range needed to measure broadband spectral features from multiple large chemical species. In this talk the application of this technology for open-path atmospheric measurements will be discussed based on results from laboratory measurements with simulated plumes of chemicals. The performance offered by the system for simultaneous detection of multiple chemical species will be presented.

Brumfield, Brian E.↗

DOE OSTI2025

Heavy quark mass effects in charged-current deep-inelastic scattering at approximate NNLO in the Aivazis-Collins-Olness-Tung scheme

The approximate SACOT-𝜒 scheme for heavy quark production in deep-inelastic scattering was initially formulated for the neutral current structure functions 𝐹 2 and 𝐹 𝐿 . We extend this approach to the charged current case (also including 𝐹 3 ), and thereby complete the definitions for the most relevant inclusive structure functions. Furthermore, we implement these structure functions in the open-source code APFEL++ which provides fast numerical evaluations over a wide kinematic range; this addition to the APFEL++ code is publicly available, with details provided in the Appendix. This SACOT-𝜒 implementation enables detailed numerical insights on the mass dependence of the structure functions and cross sections in the (𝑥,𝑄 2 )-plane for both neutral and charged current processes. We consider kinematic regions relevant for the experimental measurements from fixed-target 𝜈⁢ DIS experiments (NuTeV, CCFR, and Chorus) and HERA, and also projections for the upcoming EIC. In particular, the 𝜈⁢ DIS experiments reveal a surprisingly strong dependence on the mass effects, offering valuable insights that may help resolve long-standing challenges in accurately describing these datasets.

Risse, P. [Westfälische Wilhelms-Universität Münst↗

DOE OSTI2017

Biochemical and structural characterization of a novel arginine kinase from the spider Polybetes pythagoricus

Energy buffering systems are key for homeostasis during variations in energy supply. Spiders are the most important predators for insects and therefore key in terrestrial ecosystems. From biomedical interest, spiders are important for their venoms and as a source of potent allergens, such as arginine kinase (AK, EC 2.7.3.3). AK is an enzyme crucial for energy metabolism, keeping the pool of phosphagens in invertebrates, and also an allergen for humans. In this work, we studied AK from the Argentininan spider Polybetes pythagoricus ( Pp AK), from its complementary DNA to the crystal structure. The Pp AK cDNA from muscle was cloned, and it is comprised of 1068 nucleotides that encode a 384-amino acids protein, similar to other invertebrate AKs. The apparent Michaelis-Menten kinetic constant ( K m ) was 1.7 mM with a k cat of 75 s –1 . Two crystal structures are presented, the apo Pv AK and Pp AK bound to arginine, both in the open conformation with the active site lid (residues 310–320) completely disordered. The guanidino group binding site in the apo structure appears to be organized to accept the arginine substrate. Lastly, these results contribute to knowledge of mechanistic details of the function of arginine kinase.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Pseudonymization at Scale: OLCF’s Summit Usage Data Case Study

The analysis of vast amounts of data and the processing of complex computational jobs have traditionally relied upon high performance computing (HPC) systems, which offer reliable and efficient management of large-scale computational and data resources. Understanding these analyses’ needs is paramount for designing solutions that can lead to better science, and similarly, understanding the characteristics of the user behavior on those systems is important for improving user experiences on HPC systems. A common approach to gathering data about user behavior is to extract workload characteristics from system log data available only to system administrators. Recently at Oak Ridge Leadership Computing Facility (OLCF), however, we unveiled user behavior about the Summit supercomputer by collecting data from a user’s point of view with ordinary Unix commands.In this paper, we discuss the process, challenges, and lessons learned while preparing this dataset for publication and submission to an open data challenge. The original dataset contains personal identifiable information (PII) about the users of OLCF which needed be masked prior to publication, and we determined that anonymization, which scrubs PII completely, destroyed too much of the structure of the data to be interesting for the data challenge. We instead chose to pseudonymize the dataset, which reduced the linkability of the dataset to the users’ identities. Pseudonymization is significantly more computationally expensive than anonymization, and the size of our dataset, which is approximately 175 million lines of raw text, necessitated the development of a parallelized workflow that could be reused on different HPC machines. We demonstrate the scaling behavior of the workflow on two leadership class HPC systems at OLCF, and we show that we were able to bring the overall makespan time from an impractical 20+ hours on a single node down to around 2 hours. As a result of this work, we release the entire pseudonymized dataset and make the workflows and source code publicly available.

Maheshwari, Ketan↗

DOE OSTI2019

Mesoscale Numerical Characterization of Kevlar and Carbon–Kevlar Hybrid Plain-Woven Fabric Compression Behavior

A mesoscale finite element model (FEM) of the plain-woven fabric representative elementary volume (REV/unit cell) is developed. The developed FEM is used to predict the nonlinear compaction behavior of monolithic and intraply hybrid fabric made of high-strength carbon and Kevlar fibers. For geometrical modeling of the fabric REV, TexGen, an open-source geometrical modeling software (developed at Nottingham University), is utilized, and for mechanical characterization, FE simulation tool Abaqus{sup ®} is used. Geometrical nonlinearity of the fabric, including periodic boundary conditions and yarn interactions, is incorporated in the REV FE model. Material nonlinearity caused by transversely isotropic behavior of fibrous yarns is implemented through the user material subroutine form in FE simulation along with local orientation assigned to each yarn in the REV. Material properties of fibers are extracted from the literature and supplier data. The compression behavior of monolithic Kevlar and hybrid carbon–Kevlar (carbon warp and Kevlar weft yarns, C–K) fabric is predicted using the proposed FE model. FEM-predicted results were found to have good agreement with the experimentally obtained ones. Results depict that C–K hybrid fabrics have improved compression strength. Hybridization effect is governed by yarns mutual interaction, yarn area at crossovers, and transverse in-plane properties of the interyarn hybridized fabric. The proposed FE model can be used to predict the mechanical behavior of woven fabrics with different weaving patterns, unit cell geometry, material properties, and loading conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2018

IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes

The Integrated Microbial Genomes & Microbiomes system v.5.0 (IMG/M: https://img.jgi.doe.gov/m/) contains annotated datasets categorized into: archaea, bacteria, eukarya, plasmids, viruses, genome fragments, metagenomes, cell enrichments, single particle sorts, and metatranscriptomes. Source datasets include those generated by the DOE's Joint Genome Institute (JGI), submitted by external scientists, or collected from public sequence data archives such as NCBI. All submissions are typically processed through the IMG annotation pipeline and then loaded into the IMG data warehouse. IMG's web user interface provides a variety of analytical and visualization tools for comparative analysis of isolate genomes and metagenomes in IMG. IMG/M allows open access to all public genomes in the IMG data warehouse, while its expert review (ER) system (IMG/MER: https://img.jgi.doe.gov/mer/) enabled registered users to access their private genomes and to store their private datasets in workspace for sharing and for further analysis. IMG/M data content has increased by 60% since the last report published in the 2017 NAR Database Issue. IMG/M v.5.0 has a new and more powerful genome search feature, new statistical tools, and supports metagenome binning.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Extending tetrahedral network similarity to carbon: A type-I carbon clathrate stabilized by boron

Clathrates are guest/host framework compounds composed of polyhedral cages, yet despite their prevalence among tetrahedral network formers, clathrates with a carbon host lattice remain unrealized synthetic targets. Here, we report a type-I carbon-based framework—a ubiquitous clathrate structure type found throughout compounds containing tetrahedral building blocks. Following a boron-stabilization scheme based on first-principles predictions in the Ca–B–C system at high pressure, type-I Ca 8 B x C 46−x (x ≈ 9) was synthesized in the archetypal $Pm\bar{3}n$ lattice with stability derived from substitutionally disordered boron atoms on hexagonal ring framework positions. The synthesized clathrate, which is recoverable to ambient conditions, expands topological network similarity across tetrahedral systems and opens possibilities for a broad family of diamond-like, carbon-based compounds with tunable properties based on the wide potential for guest/host-atom substitutions and framework versatility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Fluidization of Group A Glass Particles: Experiments and Preliminary Validation

This work is aimed at providing reliable high-quality data from fluidization experiments. Geldart Group A glass beads are used as bed material. The fluidizing medium is air at atmospheric pressure which enters the system at 40% relative humidity. The air inlet velocity is varied over a broad range from 2 U mf to 26 U mf , where the minimum fluidization velocity, U mf , is 0.608 cm/s. There is not a significant change in the mean values of differential pressure; however, there are noticeable trends in their standard deviation values. Preliminary validation studies are performed using the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developed by the National Energy Technology Laboratory (NETL). The results from Eulerian-Eulerian (MFiX-TFM, two-fluid model) and Eulerian-Lagrangian (MFiX-PIC, particle-in-cell) formulations are compared. The work presented in this report highlights the applicability of MFiX-PIC for large-scale applications, and reveals that PIC simulation offers a suitable alternative to TFM simulation when effects due to multiple components or polydispersity are significant. PIC modeling provides a readily extendible framework for such systems. However, PIC models do rely on an empirical closure for inter-particle stress. Some solution discrepancies were evident in MFiX-PIC predictions which require further analysis. As such, the study underlines the need for a systematic approach to quantify the sources of numerical uncertainty within the PIC model. However, even with known empiricism, MFiX-PIC has demonstrated considerable potential in analyzing gas-solid systems. The results obtained are encouraging and warrant further investigation to improve the predictive capability of MFiX-PIC.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A scalable compressible volume of fluid solver using a stratified flow model

Here, in this paper, a Volume of Fluid method which uses a Stratified Flow model for flux calculation is proposed to solve a compressible multiphase flow in a way that has high parallel efficiency. The solver is part of an open-source computing tool to study fuel entrainment and combustion in the application of paraffin-based hybrid rocket motors. This paper focuses on the compressible Volume of Fluid solver for the liquid and gaseous phases in this environment. This solver uses perfect gas and stiffened gas models for equation of state, with the ability to easily add other models as desired. Additionally a comparison of a Riemann solver versus an AUSM+up scheme is conducted, showing improvement with the later in the solution of multiphase flows. This solver successfully reproduces shock tube cases with the expected accuracy, as well as simulating two-dimensional shear and gravity-driven flows. Results also show that the code is able to utilize a Stratified Flow model to evaluate shear flow without the need for interface reconstruction or gradient calculations. Finally, it is shown that the solver has near-ideal scaling under strong scaling tests as well as good performance in static scaling, giving improved performance over current options and implying future advancement of high-performance computing efficiency for multiphase flow solvers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗

DOE OSTI2020

Surface Passivation by Excess Sulfur for Controlled Synthesis of Large, Thin SnS Flakes

Tin sulfide (SnS) is part of the group IV chalcogenides (SnX, GeX; X: S, Se), a family of anisotropic layered materials considered for thin film photovoltaics, optoelectronics, and valleytronics, and predicted narrow bandgap multiferroic materials. Large ultrathin SnS flakes, suitable for a variety of applications, are challenging to synthesize because of the enhanced surface reactivity due to the open layer structure of SnS which gives rise to a competition between lateral and vertical growth. Here we investigate the effects of added sulfur on passivating the surface and modifying the balance between lateral expansion and thickening of SnS flakes in chemical vapor transport from a SnS precursor. In addition, we investigate the growth of SnS flakes and compare the results of synthesis from a pure SnS precursor with growth, in which a slight excess of sulfur is supplied in different ways. Our results demonstrate that small amounts of excess sulfur can profoundly affect the size and thickness distributions of SnS flakes. The largest and thinnest flakes are obtained if (i) traces of sulfur are added and (ii) the sulfur source consists either of small Sx fragments released at high temperatures from the reactor walls, or atomic S supplied by sublimation from SnS 2 . The likely mechanism for the observed growth modifications is a transient surface passivation of SnS flakes during growth, which reduces the reactivity of the top facet of the flakes, limits vertical growth, and thus gives rise to ensembles with increased lateral size and reduced thickness.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Beneficial influence of Hf and Zr additions to Nb4at%Ta on the vortex pinning of Nb 3 Sn with and without an O source

In this paper we show that addition of Hf to Nb4Ta can significantly improve the high field performance of Nb 3 Sn, making it suitable for dipole magnets for a machine like the 100 TeV Future Circular Collider (FCC). A big challenge of the FCC is that the desired non-Cu critical current density (J c ) target of 1500 A mm –2 (16 T, 4.2 K) is substantially above the best present Nb 3 Sn conductors doped with Ti or Ta (~1300 A mm –2 in the very best sample of the very best commercial wire). Recent success with internal oxidation of Nb–Zr precursor has shown significant improvement in the layer J c of Nb 3 Sn wires, albeit with the complication of providing an internal oxygen diffusion pathway and avoiding degradation of the irreversibility field H Irr . We here extend the Nb1Zr oxidation approach by comparing Zr and Hf additions to the standard Nb4Ta alloy of maximum H c2 and H Irr . Nb4Ta rods with 1Zr or 1Hf were made into monofilament wires with and without SnO 2 and their properties measured over the entire superconducting range at fields up to 31 T. We found that Group IV alloying of Nb4Ta does raise H Irr , though O 2 addition still slightly degrades it. As noted in earlier Nb1Zr work with an O source, the pinning force density F p is strongly enhanced and its peak value shifted to higher field by internal oxidation. A surprising result of this work is that we found better properties in Nb4Ta1Hf without SnO 2 , F pMax achieving 2.35 times that of the standard Nb4Ta alloy, while the oxidized Nb4Ta1Zr alloy achieved 1.54 times that of the Nb4Ta alloy. The highest layer J c (16 T, 4.2 K) of 3700 A mm –2 was found in the SnO 2 -free wire made with Nb4Ta1Hf alloy. Using a standard A15 cross-section fraction of 60% for modern powder-in-tube and rod restack process wires, we estimated that a non-Cu J c of 2200 A mm –2 is obtainable in modern conductors, well above the 1500 A mm –2 FCC specification. Moreover, since the best properties were obtained without SnO 2 , the Nb4Ta1Hf alloy appears to open a straightforward route to enhanced properties in Nb 3 Sn wires manufactured by virtually all the presently used commercial routes employed today.

36 MATERIALS SCIENCE↗

DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

DOE OSTI2021

New high-sensitivity searches for neutrons converting into antineutrons and/or sterile neutrons at the HIBEAM/NNBAR experiment at the European Spallation Source

The violation of baryon number, , is an essential ingredient for the preferential creation of matter over antimatter needed to account for the observed baryon asymmetry in the Universe. However, such a process has yet to be experimentally observed. The HIBEAM/NNBAR program is a proposed two-stage experiment at the European Spallation Source to search for baryon number violation. The program will include high-sensitivity searches for processes that violate baryon number by one or two units: free neutron–antineutron oscillation () via mixing, neutron–antineutron oscillation via regeneration from a sterile neutron state (), and neutron disappearance (n → n′); the effective process of neutron regeneration () is also possible. The program can be used to discover and characterize mixing in the neutron, antineutron and sterile neutron sectors. The experiment addresses topical open questions such as the origins of baryogenesis and the nature of dark matter, and is sensitive to scales of new physics substantially in excess of those available at colliders. A goal of the program is to open a discovery window to neutron conversion probabilities (sensitivities) by up to three orders of magnitude compared with previous searches. The opportunity to make such a leap in sensitivity tests should not be squandered. The experiment pulls together a diverse international team of physicists from the particle (collider and low energy) and nuclear physics communities, while also including specialists in neutronics and magnetics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Sources and levels of ambient ocean sound near the antarctic peninsula

Arrays of hydrophones were deployed within the Bransfield Strait and Scotia Sea (Antarctic Peninsula region) from 2005 to 2009 to record ambient ocean sound at frequencies of up to 125 and 500 Hz. Icequakes, which are broadband, short duration signals derived from fracturing of large free-floating icebergs, are a prominent feature of the ocean soundscape. Icequake activity peaks during austral summer and is minimum during winter, likely following freeze-thaw cycles. Iceberg grounding and rapid disintegration also releases significant acoustic energy, equivalent to large-scale geophysical events. Overall ambient sound levels can be as much as ~10–20 dB higher in the open, deep ocean of the Scotia Sea compared to the relatively shallow Bransfield Strait. Noise levels become lowest during the austral winter, as sea-ice cover suppresses wind and wave noise. Ambient noise levels are highest during austral spring and summer, as surface noise, ice cracking and biological activity intensifies. Vocalizations of blue ( Balaenoptera musculus ) and fin ( B. physalus ) whales also dominate the long-term spectra records in the 15–28 and 89 Hz bands. Blue whale call energy is a maximum during austral summer-fall in the Drake Passage and Bransfield Strait when ambient noise levels are a maximum and sea-ice cover is a minimum. Fin whale vocalizations were also most common during austral summer-early fall months in both the Bransfield Strait and Scotia Sea. The hydrophone data overall do not show sustained anthropogenic sources (ships and airguns), likely due to low coastal traffic and the typically rough weather and sea conditions of the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗