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DOE OSTI2022

Development and demonstration of next generation technology for Nb_3Sn accelerator magnets with lower cost, improved performance uniformity, and higher operating point in the 12-14 T range

The scope of the proposal outlined in this white paper is the development and demonstration of the technology needed for next generation of Nb_3Sn accelerator magnets in the 12-14 T range. The main goal is to cut magnet cold-mass cost by a factor 2 or higher with respect to the Nb_3Sn magnets produced by the US Accelerator Upgrade Project (AUP) for the High-Luminosity Large Hadron Collider (HL-LHC). This goal will be achieved by significant reduction of labor hours, higher operating point, and improved performance uniformity. A key factor will be automation that will be achieved through industry involvement and benefitting from the experience gained in US national laboratories through the production of the AUP magnets. This partnership will enable the development of a technology that will be easily transferable to industry for mid- and large-scale production of Nb_3Sn accelerator magnets in the 12-14 T range. This step is essential to enable next generation of colliders such as the FNAL-proposed Muon Collider, FCC and other HEP hadron colliders. This is a Directed R&D where direction is given by the field range and industry involvement for high-automation and industry-ready technology. The plan includes ten milestones, to be achieved in 6-8 years at the cost of 5-7 $M/year.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Understanding and modeling current and future coastal wetland methane dynamics (Final Report)

The coastal terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system that plays a critical role in biogeochemical cycling. Due to its dynamic nature, the processes that regulate decomposition and methane (CH 4 ) emissions are of greater significance at the TAI than in upland systems. Despite this, we have limited mechanistic understanding of how climate stressors interact to regulate the electron acceptors and donors that determine decomposition pathways within TAIs, including the generation of hot spots and hot moments. Accurately modeling these processes is critical for incorporating the coastal TAI into Earth systems models, such as DOE’s E3SM. With previous DOE support, we adapted an aerobic terrestrial representation of decomposition using PFLOTRAN, a reactive flow and transport model, and added anerobic decomposition pathways, salinity, and oxygen (O 2 ) that fluctuates independently of water table level. However, because this model (PFLOTRAN TAI ) is based on decomposition rates and organic matter carbon to nitrogen ratios from terrestrial systems, its performance in TAI systems is currently limited by the lack of empirical data to properly parameterize variables. In addition, while PFLOTRAN TAI can simulate movement of O 2 into sediments, it is not currently capable of tracking the movement of CH 4 gas through plant tissues due to both current model structure and lack of available data. Our overall objective of the project was the increase our mechanistic understanding of CH 4 dynamics in response to environmental change, such that we can improve the representation of these dynamics in PFLOTRAN. We installed automated flux chambers in a new field-scale active soil warming experiment and set up marsh organs (mesocosms) to test effects of warming, flooding, and salinity. This resulted in a new dataset consisting of chamber-level CH 4 flux measurements across multiple sites, ecological conditions, and timeframes, as well as corresponding measurements on porewater chemistry, soil carbon quality, plant biomass, and redox reaction rates. Using these data, we improved PFLOTRAN TAI to more accurately model CH 4 dynamics and successfully tested our hypotheses. This grant contributed to the professional development of 3 postdocs, 4 undergraduate interns, 4 teacher interns, 17 technicians, and 15 participatory scientists. The automated chamber technology designed for this grant has also been shared with multiple new projects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗

DOE OSTI2023

Exploring Benchmarks for Self-Driving Labs using Color Matching

Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case, as it requires experiment proposal, sample creation, and sample analysis, three common components in autonomous discovery applications. We present a robotic solution to the color matching problem that allows for fully autonomous execution of a color matching protocol. Our solution leverages the WEI science factory platform to enable portability across different robotic hardware, the use of alternative optimization methods for continuous refinement, and automated publication of results for experiment tracking and post-hoc analysis.

Artificial intelligence↗

DOE OSTI2024

High-Throughput Data Processing at FRIB Using ESnet

Real-time or nearly real-time (nearline) data processing methods are critical tools as detector technologies and data acquisition (DAQ) systems allow for higher data rates and volumes. The introduction of the energy sciences network (ESnet), a U.S. Department of Energy (DOE) supported high-speed network for scientific research, creates opportunities to leverage the computing power of DOE facilities like the National Energy Research Scientific Computing Center (NERSC). As a first step toward realizing a DOE Office of Science Integrated Research Infrastructure (IRI) pattern, an automated workflow was developed to remotely process data obtained from a nuclear physics experiment at the Facility for Rare Isotope Beams (FRIB) at NERSC with data transferred between FRIB and NERSC over ESnet. The workflow demonstrated the ability to process one week’s worth of experimental data in approximately 90 min and was used successfully for nearline analysis during a recently completed FRIB experiment. Here, a summary of the workflow development and results of recent demonstrations will be presented.

Data processing↗

DOE OSTI2023

BISON-FIPD integration enhanced low-burnup SFR metallic fuel swelling model evaluation framework

Experiments indicated that metallic fuel in sodium-cooled fast reactors (SFRs) rapidly swells radially and axially at low burnup. Despite that, prior studies have been focused on describing high burnup axial fuel elongation. With recent conventional and non-conventional metallic fuel concepts being considered for license applications, understanding multidimensional fuel swelling at a wide range of burnup levels is important to fuel analysis and qualification activities. Here, we report the development and demonstration efforts of a low-burnup SFR metallic fuel swelling model evaluation framework using the BISON advanced fuel performance code. The framework leverages the Integral Fast Reactor (IFR) program X423 experiment data through the ongoing integration project to enable standardized and automated use of legacy metallic fuel irradiation data maintained in the SFR fuel irradiation and physics database (FIPD) for BISON metallic fuel model verification and validation. In conclusion, the performance of the framework was demonstrated using the two representative metallic fuel swelling model sets implemented in BISON, with a series of insights about future advanced swelling model development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Scalable Multi-Facility Workflows for Artificial Intelligence Applications in Climate Research

Earth observation satellites and earth system models are sources of vast, multi-modal datasets that are invaluable for advancing climate and environmental research. However, their scale and complexity pose significant challenges for processing and analysis. In this paper we discuss our experiences in developing and using a scientific research application using an automated multi-facility workflow that orchestrates data collection, preprocessing, artificial intelligence (AI) inferencing, and data movement across diverse computational resources, leveraging the Advanced Computing Ecosystem Testbed at the Oak Ridge Leadership Computing Facility (OLCF). We demonstrate that our workflow can be seamlessly integrated and orchestrated across research facilities managed by different federal agencies, thus allowing users to extract new scientific insights from climate datasets. The experimental results indicate that the multi-facility workflow significantly reduces processing time, enhances scalability, and maintains high efficiency across varying workloads. Notably, our workflow processes 12,000 high-resolution satellite images in just 44 seconds using 80 workers distributed across 10 nodes on the OLCF systems. Such high throughput is essential for dynamic tokenization and sharding of petascale satellite data for distributed AI model training and inferencing at scale across thousands of GPUs.

Kurihana, Takuya [ORNL] (ORCID:0000000156698565)↗

DOE OSTI2020

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Applicable Experiment Selection [Slides]

This presentation discusses the UNF-ST&DARDS which performs many analyses for as-loaded SNF canisters, including criticality safety, shielding, thermal-hydraulic, and containment. It also discusses the experiment selection based on c k assessment of similarity and that the c k value of 0.8 or greater considered applicable for validation. 11 PWR SNF canisters (MPC-32) are used in this work. 1 model represents a failed fuel assembly as fresh, per the design basis and the remaining 10 models represent all 32 assemblies with depleted fuel. In conclusion, critical experiment selection can be performed with S/U techniques for as-loaded canisters in UNF-ST&DARDS. Sufficient benchmark experiments exist to support validation and additional MOX experiments that are a good match for commercial SNF would be a benefit to provide independent data. The presentations states that S/U techniques identify different pools of experiments for different systems and that the process is amenable to automation within UNF-ST&DARDS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1988

Space information systems in the Space Station era; Proceedings of the AIAA/NASA International Symposium on Space Information Systems, Washington, DC and Greenbelt, MD, June 22, 23, 1987

Technological and planning issues for data management, processing, and communication on Space Station Freedom are discussed in reviews and reports by U.S., European, and Japanese experts. The space-information-system strategies of NASA, ESA, and NASDA are discussed; customer needs are analyzed; and particular attention is given to communication and data systems, standards and protocols, integrated system architectures, software and automation, and plans and approaches being developed on the basis of experience from past programs. Also included are the reports from workshop sessions on design to meet customer needs, the accommodation of growth and new technologies, and system interoperability.

Gerard, Mireille↗

NASA NTRS2001

Langley Research Center's Unitary Plan Wind Tunnel: Testing Capabilities and Recent Modernization Activities

Description, capabilities, initiatives, and utilization of the NASA Langley Research Center's Unitary Plan Wind Tunnel are presented. A brief overview of the facility's operational capabilities and testing techniques is provided. A recent Construction of Facilities (Car) project to improve facility productivity and efficiency through facility automation has been completed and is discussed. Several new and maturing thrusts are underway that include systematic efforts to provide credible assessment for data quality, modifications to the new automation control system for increased compatibility with the Modern Design of Experiments (MDOE) testing methodology, and process improvements for better test coordination, planning, and execution.

Micol, John R.↗

NASA NTRS2001

Langley Research Center's Unitary Plan Wind Tunnel: Testing Capabilities and Recent Modernization Activities

Description, capabilities, initiatives, and utilization of the NASA Langley Research Center's Unitary Plan Wind Tunnel are presented. A brief overview of the facility's operational capabilities and testing techniques is provided. A recent Construction of Facilities (CoF) project to improve facility productivity and efficiency through facility automation has been completed and is discussed. Several new and maturing thrusts are underway that include systematic efforts to provide credible assessment for data quality, modifications to the new automation control system for increased compatibility with the Modern Design Of Experiments (MDOE) testing methodology, and process improvements for better test coordination, planning, and execution.

Micol, John R.↗

NASA NTRS2002

Use of Traffic Intent Information by Autonomous Aircraft in Constrained Operations

This paper presents findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision-making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous flight management were compared under conditions of low and high operational complexity (traffic and airspace hazard density). The tactical mode was characterized primarily by the use of traffic state data for conflict detection and resolution and a manual approach to meeting operational constraints. The strategic mode involved the combined use of traffic state and intent information, provided the pilot an additional level of alerting, and allowed an automated approach to meeting operational constraints. Operational constraints applied in the experiment included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. The strategic operational mode was found to be effective in reducing unnecessary maneuvering in conflict situations where the intruder's intended maneuvers would resolve the conflict. Conditions of high operational complexity and vertical maneuvering resulted in increased proliferation of conflicts, but both operational modes exhibited characteristics of stability based on observed conflict proliferation rates of less than 30 percent. Scenario case studies illustrated the need for maneuver flight restrictions to prevent the creation of new conflicts through maneuvering and the need for an improved user interface design that appropriately focuses the pilot's attention on conflict prevention information. Pilot real-time assessment of maximum workload indicated minimal sensitivity to operational complexity, providing further evidence that pilot workload is not the limiting factor for feasibility of an en-route distributed traffic management system, even under highly constrained conditions.

Wing, David J.↗

NASA NTRS2003

Analysis and Forecast of Two Storms Characterized by Extreme Deepening Rates

Between 25 and 27 December 1999 two very intense cyclones, named Lothar and Martin, swept across northern and western France causing substantial life and property loss. In this work, the finite volume general circulation model and data assimilation system (fvDAS) developed at the Data Assimilation Office of the NASA Goddard Space and Flight Center is being used to investigate these storms. In the first part of this article the dynamics of the storms is analyzed, and some important mechanisms are unveiled. The second part describes a set of eleven data assimilation experiments to study the impact of different data types on the automated analyses. Cloud-track winds provided by EUMETSAT and surface winds from QuikSCAT are being used. These data are assimilated with a range of different parameter settings of the forecast error covariance model. The results show that generally the additional wind data set have positive impacts on the analyses: particularly, the analysis of Lothar can be slightly improved by using the Eumetsat winds, and the analysis of Martin can be strongly improved by using the full-resolution QuikSCAT winds with a more localized influence. The third part of this article is focused on the forecast of Lothar which is very well predicted in the 1-5 day range by the fvDAS system.

Reale, Oreste↗

NASA NTRS2013

Proposed US Contributions to LOFT

Proposed US Enhancements include:Tantalum X -ray collimator, Additional ground station, Large Observatory for X-Ray Timing (LOFT) instrument team participation, US science support center & data archive, and Science enabled by US hardware. High-Z material with excellent stopping power. Fabricated using a combination of laser micromachining and chemical etching. Known technology capable of producing high-aspect ratio holes and large open fractions. Reduces LOFT LAD background by a factor of 3. Telemetry formats for LOFT based upon RXTE/EDS experience. Ground system software and strategies for WFM based upon RXTE/ASM automated pipeline software. MSFC engineering trade studies supporting the Ta collimator. Burst alert triggers based upon Fermi/GBM and HETE-2. Science Enhancements Enabled by US Hardware include: Tantalum collimator: Reduces background by factor of 3. Improves sensitivity to faint sources such as AGN. Eliminates contamination by bright/variable sources. outside the LAD field of view. US Ground Station: Enables continuous telemetry of all events from the WFM. Allows LAD to observe very bright >500 mCrab sources with full event resolution.

Wilson-Hodge, Colleen↗

NASA NTRSDate not supplied

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS and ISS ground control segments.

BioSentinel↗

NASA NTRSDate not supplied

BioSentinel: NASA’s First Deep Space Biological Mission

BioSentinel↗

NASA NTRS2022

Evolution of Biological Satellites: From Low Earth Orbit to NASA’s BioSentinel Deep Space Mission

NASA has set its sights on human exploration in deep space with the Artemis missions, with an ambitious plan to put astronauts back on the Moon and to eventually land human missions on Mars. Such missions will require significant countermeasures, likely both technological and biomedical, to protect biology from chronic radiation exposure. Small satellites like CubeSats can inform these countermeasures by querying relevant space environments with model organisms over relevant durations. NASA has launched five biological CubeSats into low Earth orbit (LEO) from GeneSat in 2006 to EcAMSat in 2017. Each one of these missions increased our understanding of the effects of spaceflight, while refining technologies and imparting valuable lessons to the next generation of CubeSats. The Artemis I rocket will carry ten CubeSats, each of them with its own objective. One in particular, BioSentinel, will conduct the first study of the biological response to interplanetary space radiation beyond LEO since Apollo 17. Once it reaches its heliocentric orbit – after a short lunar fly-by – BioSentinel will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast cells will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical density. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles.

Sergio R Santa Maria↗

DOE OSTI2024

DETERMINATION OF STRUT QUALITY FACTORS IN ADDITIVELY MANUFACTURED LATTICES USING IN-SITU COMPRESSION TESTING µ-CT

In response to the need for an automated, commercial method to qualify additively manufactured (AM) lattice components, an experiment was conducted to evaluate the effects of defective lattice struts on the structural compression strength. Lattice samples with known defective or missing struts were compressed using a Deben CT5000RT and imaged using xray µ-CT. The compressive force and x-ray computed tomography results were compared to defect free standards to evaluate the impact of each defect type on the overall structure’s compressive strength. This analysis will allow for simplifications to Finite Element Analysis (FEA) on AM parts without sacrificing model fidelity. Understanding the contribution of each defect type and severity will also better inform non-destructive evaluation (NDE) personnel of the inspection parameters necessary to detect the smallest feature of importance.

Dinova, Vincent A.↗