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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DUNE Database Development

The DUNE experiment will produce vast amounts of metadata, which describe the data coming from the read-out of the primary DUNE detectors. Various databases will make up the overall DB architecture for this metadata. ProtoDUNE at CERN is the largest existing prototype for DUNE and serves as a testing ground for - among other things - possible database solutions for DUNE. The subset of all metadata that is accessed during offline data reconstruction and analysis is referred to as ‘conditions data’ and it is stored in a dedicated database. As offline data reconstruction and analysis will be deployed on HTC and HPC resources, conditions data is expected to be accessed at very high rates. It is therefore crucial to store it in a granularity that matches the expected access patterns allowing for extensive caching. This requires a good understanding of the sources and use cases of conditions data. This contribution will briefly summarize the database architecture deployed at ProtoDUNE and explain the various sources of conditions data. We will present how the conditions data is retrieved and streamed from the databases and how it is handled to match expected access patterns.

Vizcaya Hernandez, Ana Paula↗
DOE OSTI2025

dCache CI/CD migration to Kubernetes

For over two decades, the dCache project has provided open-source to satisfy ever-more demanding storage requirements. More than 80 sites worldwide rely on dCache to provide services for LHC experiments, Belle-II, Eu- XFEL, and others. This can be achieved only with a well-established process from a whiteboard, where ideas are created through development, packaging, and testing. The project’s build and test infrastructure is based on Jenkins CI and a set of virtual machines. This infrastructure is maintained by dCache developers. With the introduction of the DESY-central Gitlab server, the developers have started migrating from VM-based testing to container-based deployments in the onsite Kubernetes cluster. As a result, we have packaged dCache containers and Helm charts that can be used by other sites to reproduce our test and build steps quickly or to evaluate new releases on their pre-production systems and, eventually, become a standard model of dCache deployment at the sites. This paper describes the challenges we have faced, the techniques we used to solve them, and the issues that still need to be addressed.

Mkrtchyan, Tigran [DESY]↗
DOE OSTI2025

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as p2r, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these miniapps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Edge AI-Enhanced Traffic Monitoring and Anomaly Detection Using Multimodal Large Language Models

This paper addresses the challenge of traffic monitoring and incident detection in remote areas, utilizing multimodal large language models (LLMs) deployed on edge AI devices. The key novelty of the LLM is to convert real-time video streams into descriptive texts, enabling low-bandwidth transmissions and reliable detection of anomalies and incidents in environments of intermittent connectivity. The model is developed based on fine-tuning open-source LLMs and extending it with multi-modal capabilities to analyze video frames. Our work also involves deploying this model on edge devices such as Nvidia IGX Orin and is planned to be tested in realistic environments in future work. The methodology includes data set curation, iterative model fine-tuning and compression, and hardware-based optimization. This approach aims to enhance traffic safety and response speed in remote areas, marking a significant advancement in the application of AI for traffic monitoring and safety management.

Peruski, Ryan [University of Tennessee, Knoxville ↗
DOE OSTI2022

Multi-extreme conditions at the Second Target Station

Three concepts for the application of multi-extreme conditions under in situ neutron scattering are described here. The first concept is a neutron diamond anvil cell made from a non-magnetic alloy. It is shrunk in size to fit existing magnets and future magnet designs and is designed for best pressure stability upon cooling. This will allow for maximum pressures above 10 GPa to be applied simultaneously with (steady-state) high magnetic field and (ultra-)low temperature. Additionally, an implementation of miniature coils for neutron diamond cells is presented for pulsed-field applications. The second concept presents a set-up for laser-heating a neutron diamond cell using a defocused CO 2 laser. Cell, anvil, and gasket stability will be achieved through stroboscopic measurements and maximum temperatures of 1500 K are anticipated at pressures to the megabar. The third concept presents a hybrid levitator to enable measurements of solids and liquids at temperatures in excess of 4000 K. This will be accomplished by a combination of bulk induction and surface laser heating and hyperbaric conditions to reduce evaporation rates. The potential for deployment of these multi-extreme environments within this first instrument suite of the Second Target Station is described with a special focus on VERDI, PIONEER, CENTAUR, and CHESS. Furthermore, considerations for deployment on future instruments, such as the one proposed as TITAN, are discussed. Overall, the development of these multi-extremes at the Second Target Station, but also beyond, will be highly advantageous for future experimentation and will give access to parameter space previously not possible for neutron scattering.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Portable diagnostic package for Thomson scattering and optical emission spectroscopy on Princeton field-reversed configuration 2 (PFRC 2)

An Advanced Research Projects Agency-Energy funded diagnostic system has been deployed to the Princeton field-reversed configuration 2 (PFRC-2) device, located at Princeton Plasma Physics Laboratory. The Portable Diagnostic Package (PDP), designed at Oak Ridge National Laboratory, allows for the measurement of Thomson Scattering (TS) for electron density and temperature and Optical Emission Spectroscopy (OES) for ion temperature, impurity density, and ion velocity. A tunable spectrometer on the PDP with three gratings provides the flexibility to measure low (1 eV) and high (1000 eV) electron temperature ranges from TS. Additionally, using a second spectrometer, the OES diagnostic can survey light emission from various ion excitation levels for wide wavelength ranges. The electron density (<2 × 10 19 m –3 ) of plasmas generated in PFRC-2 has been below the PDP TS discrimination threshold, which has made TS signal detection challenging against a high-background of laser stray light. The laser stray light was iteratively reduced by making modifications to the entrance and exit geometry on PFRC-2. Rayleigh scattering experiments on PFRC have yielded the TS discrimination sensitivity to be >1 × 10 20 m –3 for the PDP. A recently implemented narrow-band notch spectral filter that masks the second harmonic 532 nm Nd:YAG laser wavelength has increased the system’s TS light discrimination sensitivity 65 times compared to the instance when the notch filter was not implemented. The hardware implementation including design changes to the flight tubes and Brewster windows will be discussed, along with results from Rayleigh and rotational Raman scattering sensitivity analyses, which were used to establish a quantitative figure of merit on the system performance. Further, the Raman scattering calibration with the notch filter has improved the PDP electron density threshold to 1 ± 0.5 × 10 18 m –3 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Design and implementation of a prototype infrared video bolometer (IRVB) in MAST Upgrade

A prototype infrared video bolometer (IRVB) was successfully deployed in the Mega Ampere Spherical Tokamak Upgrade (MAST Upgrade or MAST-U), the first deployment of such a diagnostic in a spherical tokamak. The IRVB was designed to study the radiation around the lower x-point, another first in tokamaks, and has the potential to estimate emissivity profiles with spatial resolution beyond what is achievable with resistive bolometry. The system was fully characterized prior to installation on MAST-U, and the results are summarized here. After installation, it was verified that the actual measurement geometry in the tokamak qualitatively matches the design; this is a particularly difficult process for bolometers and was done using specific features of the plasma itself. The installed IRVB measurements are consistent both with observations from other diagnostics, including magnetic reconstruction, visible light cameras, and resistive bolometry, as well as with the IRVB-designed view. Early results show that with conventional divertor geometry and only intrinsic impurities (for example, C and He), the progression of radiative detachment follows a similar path to that observed for large aspect ratio tokamaks: The peak of the radiation moves along the separatrix from the targets to the x-point and high-field side midplane with a toroidally symmetric structure that can eventually lead to strong effects on the core plasma inside the separatrix.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Machine learning for modern power distribution systems: Progress and perspectives

The application of machine learning (ML) to power and energy systems (PES) is being researched at an astounding rate, resulting in a significant number of recent additions to the literature. As the infrastructure of electric power systems evolves, so does interest in deploying ML techniques to PES. However, despite growing interest, the limited number of reported real-world applications suggests that the gap between research and practice is yet to be fully bridged. To help highlight areas where this gap could be narrowed, this article discusses the challenges and opportunities in developing and adapting ML techniques for modern electric power systems, with a particular focus on power distribution systems. These systems play a crucial role in transforming the electric power sector and accommodating emerging distributed technologies to mitigate the impacts of climate change and accelerate the transition to a sustainable energy future. The objective of this article is not to provide an exhaustive overview of the state-of-the-art in the literature, but rather to make the topic accessible to readers with an engineering or computer science background and an interest in the field of ML for PES, thereby encouraging cross-disciplinary research in this rapidly developing field. To this end, the article discusses the ways in which ML can contribute to addressing the evolving operational challenges facing power distribution systems and identifies relevant application areas that exemplify the potential for ML to make near-term contributions. At the same time, key considerations for the practical implementation of ML in power distribution systems are discussed, along with suggestions for several potential future directions.

Marković, Marija (ORCID:0000000247839837)↗
DOE OSTI2023

Scaling Up CSP: How Long Will it Take?

Concentrating solar power (CSP) is one of the few scalable technologies capable of delivering dispatchable renewable power. Therefore, many expect it to shoulder a significant share of system balancing in a renewable electricity future powered by cheap, intermittent PV and wind power: the IEA, for example, projects 73 GW CSP by 2030 and several hundred GW by 2050 in its Net-Zero by 2050 pathway. In this paper, we assess how fast CSP can be expected to scale up and how long time it would take to get new, high-efficiency CSP technologies to market, based on observed trends and historical patterns. We find that to meaningfully contribute to net-zero pathways the CSP sector needs to reach and exceed the maximum historical annual growth rate of 30%/year last seen between 2010-2014 and maintain it for at least two decades. Any CSP deployment in the 2020s will rely mostly on mature existing technologies, namely parabolic trough and molten-salt towers, but likely with adapted business models such as hybrid CSP-PV stations, combining the advantages of higher-cost dispatchable and low-cost intermittent power. New third-generation CSP designs are unlikely to play a role in markets during the 2020s, as they are still at or before the pilot stage and, judging from past pilot-to-market cycles for CSP, they will likely not be ready for market deployment before 2030. CSP can contribute to low-cost zero-emission energy systems by 2050, but to make that happen, at the scale foreseen in current energy models, ambitious technology-specific policy support is necessary, as soon as possible and in several countries.

concentrated solar power↗
DOE OSTI2023

Leaving in the lead: Priorities for perovskite photovoltaics

The need for moving electricity generation to a sustainable model requires the development of low cost ubiquitous photovoltaics (PVs) to harvest the planet’s primary energy source, the Sun. Building upon the successes of Si-based and CdTe-based PV technologies, PVs with lower-embodied energy and requiring lower carbon dioxide equivalent to produce will be required to meet long-term sustainability goals. In particular, thin-film technologies, such as high-efficiency metal halide perovskite (MHP) PV modules, provide avenues to reduced embodied energy, lower energy payback times, and enabling energy-dense tandems [H. M. Wikoff et al., Joule 6(7), 1710–1725 (2022) and V. Fthenakis, Renewable Sustainable Energy Rev. 13(9), 2746–2750 (2009)]. The ability to improve efficiency and lower energy payback time of next generation thin-film PV modules is a critical foundation for green H2 and electrification more broadly. In this regard, Pb-based MHP-PVs have separated themselves as a result of the high-efficiencies that can be realized across a range of electronic gaps. Questions regarding Pb-based MHP-PVs that are often asked, as the challenges of efficiency and reliability are met, revolve around the “problem” of the Pb content. Specifically, “does Pb toxicity preclude MHP-PV modules from being deployed at the TW scale?” To provide this sense of scale, in 2021, the United States burned 10.5 quads of coal, with 90% of that used for electricity generation. Given the energy content of coal of 29 MJ/kg and a residual lead content in that coal of 30 mg/kg, electricity generation from coal resulted in more lead emitted into the atmosphere than what would be required to produce over 2 TW of MHP-PV name plate capacity (assuming a 20% module efficiency and an ∼700 nm active layer). This amounts to more PV power than has been deployed across all PV technologies and geographies to date. This only includes US coal consumption; the rest of the world would be much larger. This example illustrates the scale of the material usage relative to the energy production. Imagine a power-generation technology that offsets these Pb emissions from coal and essentially sequesters this Pb content between two sheets of impermeable glass. Why should we let Pb’s history of misuse prevent it from being included in next generation PV modules that can enable a sustainable energy future?

14 SOLAR ENERGY↗
DOE OSTI2024

Diagnostic development and needs for laser driven MeV x-ray radiography

Laser-driven MeV x-ray radiography of dynamic, dense objects demands a small, high flux source of energetic x-rays to generate an image with sufficient quality. Understanding the multi-MeV x-ray spectrum underscores the ability to extrapolate from the current laser sources to new future lasers that might deploy this radiography modality. Here, in this study, we present a small study of the existing x-ray diagnostics and techniques. We also present work from National Ignition Facility-Advanced Radiographic Capability, where we deploy three diagnostics to measure the x-ray spectrum up to 30 MeV. Finally, we also discuss the needs and developments of two new diagnostics: a single crystal scintillator spectrometer and a fast decay activation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Measuring the robustness of predictive probability for early stopping in two-group comparisons

We report physical experiments are often expensive and time-consuming. Test engineers must certify the compatibility of aircraft and their weapon systems before they can be deployed in the field, but the testing required is time consuming, expensive, and resource limited. Adopting Bayesian adaptive designs is a promising way to borrow from the successes seen in the clinical trials domain. The use of predictive probability (PP) to stop testing early and make faster decisions is particularly appealing given the aforementioned constraints. Given the high-consequence nature of the tests performed in the national security space, a strong understanding of new methods is required before being deployed. Although PP has been thoroughly studied for binary data, there is less work with continuous data, where many reliability studies are interested in certifying the specification limits of components. A simulation study evaluating the robustness of this approach indicates early stopping based on PP is reasonably robust to minor assumption violations, especially when only a few interim analyses are conducted. The simulation study also compares PP to conditional power, showing its relative strengths and weaknesses. A post-hoc analysis exploring whether release requirements of a weapon system from an aircraft are within specification with desired reliability resulted in stopping the experiment early and saving 33% of the experimental runs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrating Advanced Modeling and Accelerated Testing for a Modernized Fuel Qualification Paradigm

With the increasing interest in sodium fast reactor technology, as seen by applications to the U.S. Nuclear Regulatory Commission for the OKLO Aurora plant, fuel testing for the TerraPower Traveling Wave Reactor, and the impending construction and startup of the versatile test reactor (VTR), a modernized, accelerated approach to fuel qualification is needed. To guide this effort, a Phenomena Identification Ranking Table–styled analysis was performed for a U-Pu-Zr sodium-free annular fuel system. This analysis evaluated a series of fuel design properties and parameters against their contributions to key fuel performance phenomena. The resulting priority parameters were then reviewed against existing modeling and experimental capabilities to support investigation of the highest-priority parameters. A pathway for qualification was then established using highthroughput, high-volume experiments from MiniFuel and FAST in parallel with advanced physics-based model development. This effort outlines how the first stages of qualification can be reduced from the typical 20+-year development cycle to 5 to 7 years by deploying accelerated irradiation testing platforms. As with any accelerated test, these methods are prototypic in some aspects and less so in others; however, by coupling with advanced fuel performance modeling and simulation capabilities, the larger space of irradiation parameters and material response provided offers advantages for the validation of physics-based models supporting the deployment of novel fuel designs. As a test case, this paper utilizes a proposed Mark II fuel system for the upcoming VTR. Thus, an accelerated qualification method can be tested for the development of MARK II driver fuel so that by the time of VTR startup, lead test assemblies for a Mark II fuel can be initiated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Foreword: Special issue on the U.S. Department of Energy Microreactor Program

This is a foreword for a sponsored Nuclear Technology Special Issue that is focused on the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) Microreactor Program and associated research and development (R&D) activities. Led by Idaho National Laboratory (INL), the DOE-NE Microreactor Program is one of four, national advanced reactor campaigns under the Advanced Reactor Technologies umbrella in the Office of Nuclear Reactor Deployment. The other three national advanced reactor campaigns are focused on Molten Salt, High Temperature Gas, and Fast reactor concepts providing a robust portfolio of national laboratory and university expertise and R&D infrastructure in support of enabling and accelerating commercial deployment of advanced reactor (generally non-light water cooled) concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Feasibility of Recycling Discharged Microreactor Heavy Metal in Light Water and Sodium-Cooled Fast Reactors: A Neutronics Analysis

Nuclear microreactors (MRs) offer unique advantages, such as rapid deployment, potability, low maintenance requirements, and operational flexibility. Their compact size makes them a promising solution for decentralized power generation, particularly in remote areas, military bases, and disaster-stricken regions. However, MRs face challenges, including unutilized fissile material at the end of life, economic inefficiency, increased heavy metal (HM) waste complicating disposal, and the accumulation of plutonium (Pu) with high 239 Pu concentrations raising proliferation risks. Here, this study investigated the neutronics feasibility of a novel three-stage fuel cycle where discharged HM from MRs is recycled and burned in light water reactors and sodium-cooled fast reactors. This approach converts discharged HM into valuable fuel, enhancing the efficiency of MR deployments while improving the safeguardability of their final waste products. Neutronics analysis demonstrated that the safety characteristics of reactor designs in each stage were minimally impacted by the proposed cycle. For two representative MR designs, a fast-spectrum MR with solid pellet fuel and a thermal-spectrum MR with TRISO (TRi-structural-ISOtropic) fuel compacts, the proposed fuel cycle reduced the uranium disposal mass flow rate by ~60%, decreased the 235 U enrichment of the discharge fuel to ~1 wt%, eliminated plutonium disposal, and increased the cumulative fuel burnup to ~580 gigawatt-day per metric ton of initial heavy metal (GWd/t-iHM) or 60% fissions per initial metal atom. Despite the significant differences between the two MR designs, the performance and infrastructure requirements of the developed fuel cycles were remarkably similar, indicating its generalizability to a broader class of MRs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Welch Method and Bootstrapping Applied to Subcritical Gamma Noise

We measured the prompt neutron decay constant 𝛼 of the CROCUS zero-power reactor at the Swiss Federal Institute of Technology Lausanne using cross-power spectral density (CPSD) analysis of gamma-gamma correlations from two trans-stilbene organic scintillators positioned near the reactor core. We measured critical and subcritical states, with water levels ranging from 960 mm (critical) to 800 mm (𝜌=−1.4 $ subcritical). Our analysis used the Welch method, dividing signal segments for fast Fourier transform (FFT) frequency analysis and applying bootstrapping uncertainty quantification that uses Welch-defined segments. Results demonstrated a clear increase in the measured 𝛼 as reactor reactivity decreased, distinguishing critical from subcritical conditions. At the 960-mm critical level, 𝛼 was estimated at 155.9 ± 0.7 s −1 , and for the 800-mm subcritical level, 𝛼 increased significantly to 367.3 ± 6.9 s –1 . A linear regression of subcritical states yielded a critical estimate of 154.0 ± 3.1 s –1 , aligning with the static 𝛼 estimate at critical. The bootstrapping method produced normally distributed 𝛼 estimates, confirming data consistency. The gamma CPSD 𝛼 estimates clearly distinguish reactor states and improve monitoring of zero-power reactors. The future deployment of modular and microreactors as potential candidates for noise analysis is demonstrated in CROCUS, particularly zero-power mock-ups of new designs. The improvement of noise analysis in the subcritical domain from this work will support experimental data for reactor deployment and procedure.

CROCUS↗
DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗
DOE OSTI2025

Where to cool off: a geospatial framework for placement of cooling centers

Indoor cooling is essential to reduce heat stress and increase passive survivability during heatwaves. Although air conditioning (AC) is recommended for maintaining indoor thermal comfort, low- and medium-income households in the U.S. often do not own an AC and/or limit AC usage to reduce energy consumption and associated costs, thereby risking their health and safety. With the frequency and intensity of heatwaves increasing, cooling centers are considered an appropriate alternative to indoor cooling and a possible mitigation strategy to prevent adverse health impacts of heat exposure. However, these centers are limited in numbers and not always accessible. This requires (i) developing a geospatial framework using physical and social factors for optimal siting of cooling centers to meet future needs and (ii) ranking of existing and potential cooling centers (schools, libraries, religious institutions) based on their accessibility among vulnerable populations and proximity to healthcare facilities. We developed and deployed a geospatial framework based on the Multi-criteria Decision Analysis approach in five U.S. cities (Los Angeles (LA), Phoenix, Austin, Atlanta, Miami) to evaluate the effectiveness of the framework in ranking cooling centers based on accessibility and population coverage. The results revealed that (i) access to cooling centers varies across cities and 32.2–50.7% of centers are within walking distance of the most vulnerable populations, (ii) vulnerable populations exposed to Urban Heat Island (UHI) effects are more likely to experience energy burden, and (iii) about 21.2–49.4% of population with high energy burden have access to these centers. Considering that more cooling centers are needed to assist energy burdened households alleviate heat exposure impacts, the framework developed herein could be adapted to incorporate other factors (e.g. health impacts, policies) to assess site suitability of existing shelters, identify potential sites for new cooling centers, and geo-target communities where energy efficient emerging technologies could be deployed to reduce heat stress.

58 GEOSCIENCES↗