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DOE OSTI2023

Containerization of Phase-2 Tracker Data Acquisition and Control Framework

The CMS Experiment has started an extensive upgrade program in the context of the High-Luminosity phase of the LHC (Phase-2). In order to cope with the highly demanding High-Luminosity conditions, CMS will need a completely new inner and outer tracking detectors. On top of R&D development, a Data AcQuisition (DAQ) software is being developed along with different applications to control, monitor and validate the newly produced modules of the future tracker. As more and more developers are getting involved to maintain all those codes, an environment where software and applications can work independently of the host machine operating system is crucial. The Phase-2 Tracker group decided to make use of Docker as containerization solution for its framework. This poster describes the containerization of DAQ software/applications utilized to test and validate the Tracker modules. This includes continuous integration and continuous deployment (so-called CI/CD) and running GUI applications inside containers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs

We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. The two complementary FPGA designs are based on OpenCL, a framework for writing programs that execute across heterogeneous platforms, and hls4ml, a high-level-synthesis-based compiler for neural network to firmware conversion. We evaluate and compare the resource usage, latency, and tracking performance of our implementations based on a benchmark dataset. We find a considerable speedup over CPU-based execution is possible, potentially enabling such algorithms to be used effectively in future computing workflows and the FPGA-based Level-1 trigger at the CERN Large Hadron Collider.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

State-Constrained Grid-Forming Inverter Control for Robust Operation of AC Microgrids

The control of grid-forming inverters has become an important problem to achieve high efficiency, reliability, and resilience of the future power grid. The distributed control that utilizes a sparse communication network has been proposed for AC microgrids, in which each DG only has access to the information of a small number of its neighboring DGs, reducing the computational complexity and improving the resiliency to faults and unknown parameters. However, these approaches have not provided a clear analysis of the coupling between active/reactive power injections and the voltage magnitude/frequency or a distributed updating law with a solid theoretical foundation. Additionally, in the existing approaches, tracking the references from the secondary control may violate operational constraints.

Xu, Ying↗

DOE OSTI2021

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Healthcare Needs of the State: Quantitative Analysis

Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory’s COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Crossflow membrane filtration system for operando fouling characterization using transmission x-ray scattering

Membrane-based separations are widely used for wastewater treatment due to their low cost and efficiency. However, membrane fouling, which is the unwanted deposition or attachment of contaminants on membrane surfaces and/or within membrane pores, remains a major challenge as it increases the mass transfer resistance and reduces membrane productivity. Membrane fouling is typically probed by macroscopic performance metrics, such as flux decline, and ex situ characterization. However, this does not capture the membrane and fouling layer evolution under operating conditions, potentially masking important mechanisms and nonequilibrium pathways that impact fouling. Here, we present a remotely controlled crossflow membrane system and a custom membrane cell for operando fouling characterization using transmission small/wide angle x-ray scattering (SAXS/WAXS). This approach allows direct observation of the nanoscale changes occurring at the membrane surface during pressurized water treatment processes, enabling a new way to understand the connections between dynamic fouling behaviors and membrane performance. Nanoparticle fouling of porous membranes during ultrafiltration was investigated using operando SAXS, and mineral scaling of reverse osmosis membranes was investigated using operando WAXS. Furthermore, this system allows for tracking membrane fouling in real time and under realistic conditions, providing fundamental physical insights into how water chemistry and operating conditions affect macroscopic membrane performance. Moreover, this system opens the door for future in situ and operando studies, and it serves as a testbed for evaluating novel materials/processes for membrane-based separations.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Power Profile Monitoring and Tracking Evolution of System-Wide HPC Workloads

The power & energy demands of HPC machines have grown significantly. Modern exascale HPC systems require tens of megawatts of combined power for computing resources and cooling facilities at full capacity. The current energy trend is not sustainable for future HPC systems, and there is a need to work toward the energy efficiency aspect of HPC performance. Energy awareness of the HPC applications at the job level is essential for running an efficient HPC system. This work aims to develop a pipeline to provide a production-level system-wide overview of the HPC workloads' power profile while handling evolving workloads exhibiting new power trends. We developed an open-set classification model for HPC jobs based on the properties of power profiles to continuously provide a system-wide holistic view of recently completed jobs. The pipeline helps continuously monitor the job-level power usage pattern of HPC and enables us to capture the new trends in applications' power behavior. We employed a comprehensive set of techniques to generate job-level data, custom-designed feature extraction methods to extract critical features from jobs' power profiles, clustering techniques powered by generative modeling, and open-set classification for identifying job profiles into known classes or an unknown set. With extensive evaluations, we demonstrate the effectiveness of each component in our pipeline. We provide an analysis of the resulting clusters that characterize the power profile landscape of the Summit supercomputer from more than 60K jobs executed in a year. The open-set classification classifies the known data sets into known classes with high accuracy and identifies unknown data noints with over 85% accuracy.

Karimi, Ahmad Maroof↗

DOE OSTI2021

How Moist and Dry Intrusions Control the Local Hydrologic Cycle in Present and Future Climates

Models disagree on the magnitude of the intensification of hydrologic cycle extremes under climate change. Changes in these extremes are expected to scale with the Clausius-Clapeyron relation but may locally diverge due to the uncertain response of the atmospheric general circulation. Recent work has identified that the circulation contribution (the “dynamic” component) is the largest contributor to uncertainty in changes in hydrologic cycle extremes. In this work, we develop an exact budget for changes in wet and dry extremes based on changes in the associated moist and dry intrusions behind those extremes. We decompose changes into four contributors: thermodynamic, low-level convergence, anomalous meridional moisture advection, and zonal wave activity convergence. In analyzing these changes, we show that low-level convergence is the main dynamic contributor to the tropical and subtropical annual response, consistent with weakening of the Hadley circulation, and we show that anomalous meridional moisture advection is the primary dynamic contributor annually for the extratropics, consistent with storm track changes. We achieve a clean separation between dynamic and thermodynamic contributions through an empirical scaling between extremes and their associated wave activities, showing again that shifting storm tracks and expanding subtropics are critical to the dynamic response of the transient hydrologic cycle. We infer that changes in the large-scale circulation are predominantly responsible for the annual, dynamic response of hydrologic cycle extremes and therefore an important contributor to uncertainty in future projections.

Hydrological cycle, hydrological extremes, dynamic↗

DOE OSTI2021

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Multivariate Drought Monitoring, Propagation, and Projection Using Bias-Corrected General Circulation Models

Understanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological-hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought-related consequences.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Time Resolved Reflectivity Measurements of Convective Clouds

National Aeronautics and Space Administration's Investigations of Convective Updrafts (INCUS) mission aims to document convective mass flux through changes in the radar reflectivity (ΔZ) in convective cores captured by a constellation of three Ka-band radars sampling the same convective cells over intervals of 30, 90, and 120 s. Here, high spatiotemporal resolution observations of convective cores from surface-based radars that use agile sampling techniques are used to evaluate aspects of the INCUS measurement approach using real observations. Analysis of several convective cells confirms that large coherent ΔZ structure with measurable signal (>5 dB) can occur in less than 30 s and are correlated with underlying convective motions. The analysis indicates that the INCUS mission radar footprint and along track sampling are adequate to capture most of the desirable ΔZ signals. This unique demonstration of reflectivity time-lapse provides the framework for estimating convective mass flux independent from Doppler techniques with future radar observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

IOTA Run 2 Beam Dynamics Studies in Nonlinear Integrable Systems

Nonlinear integrable optics is a promising design approach for suppressing fast collective instabilities. To study it experimentally, a new storage ring, the Integrable Optics Test Accelerator (IOTA), was built at Fermilab. IOTA has recently completed its second scientific run, incorporating many hardware and instrumentation improvements. This report presents the results of the two integrable optics experiments - the quasi-integrable Henon-Heiles octupole system and the fully integrable Danilov-Nagaitsev system. We demonstrate tune spread and dynamic aperture in agreement with tracking simulations, and a stable crossing of the integer resonance. Based on recovered single-particle phase space dynamics, we show improved invariant jitter consistent with intended effective Hamiltonian. We conclude by outlining future plans and efforts towards proton studies and larger designs.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

AMPP-4 Metric Dashboard

The AMPP-4 Metric Dashboard is an interactive tool used for visualizing key performance indicators and milestones for the various teams in the Material Recovery & Recycle (AMPP-4) group. This dashboard provides current group data for FY25 tracking purposes. The dashboard is organized by various chapters: 1) AMPP-4 overview, 2) Scheduling, and 3) individual chapters for each team. AMPP-4 supports 7 teams, where the day- and swing-shift aqueous demolition teams are treated as one team for the purpose of metric tracking. The dashboard is used internally to monitor the success and health of the AMPP-4 teams. Additionally, the dashboard can be used externally to support programmatic reporting to sponsors and aid in future milestone and work package planning.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Ensemble-Based Characterization of Historical Storm Types in ERA5 over CONUS

We present Storm-Type Labeled Precipitation, a gridded dataset that classifies ERA5 precipitation over CONUS (20–50° N, 125–66° W) by storm type at 6-hourly resolution. Each grid cell/time step is assigned to one of five classes—mesoscale convective system (MCS), extratropical cyclone (ETC), hurricane (HUR), atmospheric river (AR), or other convective, with an “unidentified” code reserved for cases with no detected type. Two products are provided: (i) a TempestExtremes (TE)–only version, and (ii) a hybrid TRACK–TE version that uses TRACK for ETCs and HURs and TE for MCSs and ARs. Outputs are integer masks aligned to ERA5 precipitation, supporting storm-type attribution of rainfall, event compositing, trend analysis, and model evaluation. Future work will extend detection to high-resolution downscaled Earth system model projections to support evaluations of projected changes in hydrologic hazards that may threaten critical water and energy infrastructures.

Rastogi, Deeksha [ORNL] (ORCID:0000000204624027)↗

DOE OSTI2020

Energy Storage Grand Challenge: Energy Storage Market Report

As part of the Department of Energy's (DOE) Energy Storage Grand Challenge (ESGC), DOE intends to synthesize and disseminate best available energy storage data, information, and analysis to inform decision-making and accelerate technology adoption. The ESGC Roadmap provides options for addressing technology development, commercialization, manufacturing, valuation, and workforce challenges to position the United States for global leadership in the energy storage technologies of the future. This report provides a baseline understanding of the numerous, dynamic energy storage markets that fall within the scope of the ESGC via an integrated presentation of deployment, investment, and manufacturing data from the best, publicly-available sources. This report covers the following energy storage technologies: lithium ion batteries, lead acid batteries, pumped storage hydropower, comrpessed air energy storage, redox flow batteries, hydrogen, building thermal energy storage, and select long duration energy storage technologies. Not all energy storage technologies and markets could be addressed in this report. Due to the wide array of energy technologies, market niches, and data availability issues, this market report only included a select group of technologies. For example, thermal energy storage technologies are very broadly defined and cover a wide range of potential markets, technology readiness levels, and primary energy sources. In other areas, data scarcity necessitates a greater understanding of future applications and emerging science. Future efforts will update data presented in this report and be expanded to include other energy storage technologies. This data-driven assessment of the current status of energy storage markets is essential to track progress toward the goals described in the Energy Storage Grand Challenge and inform the decision-making of a broad range of stakeholders. At the same time, gaps identified through the development of this report can point to areas where further data collection and analysis could provide an even greater level of understanding of the full range of markets and technologies. Finally, numerous complementary analyses are planned, underway, or completed that will provide a deeper understanding of the specific technologies and markets covered at a high-level in this report.

25 ENERGY STORAGE↗

DOE OSTI2022

Getting lost tracking the carbon footprint of hydropower

In the transition to low-carbon electricity, well-quantified estimates of carbon dynamics are needed to ensure that emissions reduction targets are achieved. Here we review the state of the science on carbon accounting for hydropower reservoirs and identify limitations and future solutions. Nearly all research on reservoir greenhouse-gas (GHG) emissions has focused on individual reservoirs in isolation without considering their position in a freshwater network draining organic matter from upstream watersheds or the coordinated operation of reservoir cascades. Second, carbon inventories have extrapolated from a small, non-probabilistic sample of highly variable measurements of GHG emissions to unsampled reservoirs. A stronger statistical foundation is needed to estimate a global inventory and its uncertainty. Third, attribution to hydropower is based on ranks assigned to reservoir purpose. Instead, the physical influence of hydropower on carbon dynamics could be directly measured. Fourth, current carbon-accounting practices neglect time. A time-varying approach would quantify variation in emissions for electricity portfolios from changes in the fuel mix at different times and account for ancillary services, i.e., the ability to support the grid when variable renewables are not available without using natural gas. Reservoirs also sequester a significant portion of inflowing carbon in sediments and slow the carbon cycle by delaying the return of carbon to the atmosphere for decades to centuries. Together, these refinements would help to illuminate pathways toward meeting energy demand with the longest-possible delay in returning carbon to the atmosphere and without adding ancient sources to the pool of carbon cycling through aquatic ecosystems.

13 HYDRO ENERGY↗

DOE OSTI2023

Mesoscale Convective Systems in DYAMOND Global Convection‐Permitting Simulations

Abstract This study examines the deep convection populations and mesoscale convective systems (MCSs) simulated in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) winter project. A storm tracking algorithm is applied to six DYAMOND simulations and a global high‐resolution satellite cloud and precipitation data set for comparison. The simulated frequencies of tropical deep convection and organized convective systems vary widely among models and regions, although robust MCSs are generally underestimated. The diurnal cycles of MCS initiation and mature stages are well simulated, but the amplitudes are exaggerated over land. Most models capture the observed MCS lifetime, cloud shield area, rainfall volume and movement speed. However, cloud‐top height and convective rainfall intensity are consistently overestimated, and stratiform rainfall area and amount are consistently underestimated. Possible causes for the model differences compared to observations and implications for future model developments are discussed.

58 GEOSCIENCES↗

DOE OSTI2023

Application of NEAMS Multiphysics Framework for Species Tracking in Molten Salt Reactors

This report from Idaho National Laboratory (INL) summarizes the key modeling and simulation activities conducted under the Department of Energy (DOE) Molten Salt Reactor (MSR) Campaign during the Fiscal Year 2023 (FY23). The focus of the work was to leverage state-of-the-art modeling capabilities from the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes to enable novel multiphysics and multiscale modeling and simulation of MSRs. Through collaboration with NEAMS code developers, advanced multiphysics analysis capabilities for MSR systems were demonstrated by coupling depletion, thermal-hydraulics, and thermochemistry into an innovative framework for chemical species transport in MSRs. As a result, the framework can track nuclides throughout their lifetimes in the core, from production (depletion) to advection throughout the salt volume (thermal-hydraulics) and off-gassing or precipitation outside of the salt (thermochemistry). This work supports the near-term deployment of MSRs by integrating the synergistic efforts between the DOE’s MSR Campaign and NEAMS program. The resulting framework will help better connect system design modelers with experimentalists to better understand and predict complex physical behaviors in MSRs. Researchers and MSR developers alike can now leverage these new modeling and simulation capabilities to perform novel analyses with applications including: • MSR dynamics during normal operational transients and accident scenarios • Off-gas system design and performance for fuel cycle and depletion analysis • Corrosion and active chemistry control for reactor component health and lifetime determination • Source term, decay heat and activity determination in accident scenarios • Special nuclear material accountancy and chemical forensic analysis for safeguards • Digital twin development of experiments and experimental reactor demonstrations • Measurement requirements for instrumentation and control design • Uncertainty and sensitivity analysis of missing data to inform future experimental data collection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Autonomous thermal tracking reveals spatiotemporal patterns of seabird activity relevant to interactions with floating offshore wind facilities

Planning is underway for placement of infrastructure needed to begin offshore wind (OSW) energy generation along the West Coast of the United States and elsewhere in the Pacific Ocean. In contrast to the primarily nearshore windfarms currently in the North Atlantic, the seabird communities inhabiting Pacific Wind Energy Areas (WEAs) include significant populations of species that fly by dynamic soaring, a behavior dependent on wind and in which flight height increases steeply with wind speed. Therefore, a more precise and detailed assessment of their 3D airspace use is needed to better understand the potential collision risks that OSW turbines may present to these seabirds. Toward this end, a novel technology called the ThermalTracker-3D (TT3D), which uses thermal imaging and stereo vision, was developed to render high-resolution (on average within ±5 m) flight tracks and related behavior of seabirds. The technology was developed and deployed on a wind-profiling LiDAR buoy in the Humboldt WEA, located 34 to 57 km off California’s coast. During the at-sea deployment between 24 May and 13 August 2021, the TT3D successfully tracked birds moving between 10 and 500 m from the device, around the clock, and in all weather conditions; a total of 1407 detections and their corresponding 3D flight trajectories were recorded. Mean altitudes of detections ranged 6-295 m above sea level (asl). Considering the degree of overlap with anticipated rotor swept zones (RSZ), which extend 25-260 m asl, 79% of detected birds (per m 3 of airspace) moved below the RSZ, 21% moved at heights overlapping the RSZ, and another 0.04% occurred at heights exceeding the RSZ. The high-resolution tracks provided valuable insight into seabird space use, especially at heights that make them vulnerable to collision during various environmental conditions (e.g., darkness, strong winds). Observations made by the TT3D will be useful in filling critical knowledge gaps related to estimating collision and avoidance between seabirds and OSW facilities in the Pacific and elsewhere. Future research will focus on enhancing the TT3D’s identification capabilities to the lowest taxon through validation studies and artificial intelligence, further contributing to seabird conservation efforts associated with OSW.

17 WIND ENERGY↗