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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Developing and Managing Data Acquisition Software Using Spack

The Data Acquisition systems of particle physics experiments regularly push the boundaries of high-throughput computing, demanding low-latency collection of data from thousands of devices, collating data into time-sliced events, processing these events and making trigger decisions, and writing the selected data streams to disk. To accomplish these tasks, the DAQ Engineering and Operations department at Fermilab leverages multiple software libraries and builds reusable DAQ frameworks on top. These libraries must be delivered in well-defined bundles and are thoroughly tested for compatibility and functionality before being deployed to live detectors. We have several techniques used to ensure that a consistent set of dependencies can be delivered and re-created at need. We must also support active development of DAQ software components, ideally in an environment as close as possible to that of the detectors. This development often occurs across multiple packages which have to be built in concert and features tested in a consistent and reproducible manner. I will present our scheme for accomplishing these goals using Spack environments, bundle packages, and Github Actions-based CI.

Flumerfelt, Eric [Fermilab]↗
DOE OSTI2023

Artificial Intelligence for Isotopes: Report on the 2022 Workshop on Artificial Intelligence for Isotope R&D and Production

The Department of Energy Isotope Program (DOE IP) hosted a virtual workshop on Artificial Intelligence (AI) for Isotope R&D and Production on March 17 and April 14, 2022. The purpose of the workshop was for DOE IP to further its understanding of the potential roles for and subsequent opportunities to incorporate AI into its activities. The workshop brought over 80 participants together from both the AI and isotope science communities. Participants contributed ideas through plenary talks, lightning talks, and breakout discussion sessions. The primary focus of all discussions was related to isotope production and processing. However, isotope enrichment, workforce development, and supply chain management were also discussed. This report documents the information presented and discussed at the workshop.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Extracting Vehicle Trajectories from Partially Overlapping Roadside Radar

This work presents a methodology for extracting vehicle trajectories from six partially-overlapping roadside radars through a signalized corridor. The methodology incorporates radar calibration, transformation to the Frenet space, Kalman filtering, short-term prediction, lane-classification, trajectory association, and a covariance intersection-based approach to track fusion. The resulting dataset contains 79,000 fused radar trajectories over a 26-h period, capturing diverse driving scenarios including signalized intersections, merging behavior, and a wide range of speeds. Compared to popular trajectory datasets such as NGSIM and highD, this dataset offers extended temporal coverage, a large number of vehicles, and varied driving conditions. The filtered leader–follower pairs from the dataset provide a substantial number of trajectories suitable for car-following model calibration. The framework and dataset presented in this work has the potential to be leveraged broadly in the study of advanced traffic management systems, autonomous vehicle decision-making, and traffic research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Investing in STEM Benefits Community, Company, and Industry - 20243

Like many organizations and groups, the Department of Energy Environmental Management program and the nuclear industry are facing an aging employee population and record numbers of employee retirements. This 'silver tsunami' of retirees means the industry as a whole is recruiting graduates at a fast pace. So, how do we ensure the nuclear industry has a robust pipeline of graduates with the necessary background? Fluor Idaho's investment in science, technology, engineering, and mathematics (STEM) education programs helps promote the next generation of technical professionals, benefiting both the company and the industry. Through community outreach initiatives and student mentoring programs, Fluor Idaho promotes kids' interest in STEM. The programs are designed to spark STEM interest in grade school and then foster and grow that interest through high school and higher education. After igniting student excitement about STEM topics in school, Fluor Idaho focuses on providing work-specific opportunities including mentoring and intern programs. These programs give students a better look at real-world job opportunities while still stimulating their interest in STEM. These programs ultimately provide career opportunities for the students and a pipeline of workers. Fluor Idaho's strategy for its summer interns has been to place students in a wide variety of projects - from the commissioning of a first-of-a-kind nuclear processing facility, to operating nuclear waste management facilities, to developing computer programs and applications - and give them responsibilities that make them feel like valued contributors. This approach has created a positive and rewarding summer-intern program experience for the students. Fluor Idaho's investment in its future today is reducing the knowledge gap - or cliff - that many contractors in the nuclear industry are facing. It's a worthwhile investment that is readily visible within its many cleanup projects. The next generation of technical professionals is making an impact now - benefiting both the company and the nuclear industry. This paper will review Fluor Idaho's programs, including STEM community outreach and education and mentoring programs. It will also present statistics about the reach of those programs and their successes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Borehole Disposal: Update on the Science, Technology, and Potentially Suitable Radioactive Wastes - 20170

A recent Special Issue of the Energies Journal on Deep Borehole Disposal of Nuclear Waste has delivered a timely update on the science and technology of borehole disposal and the types of radioactive wastes it could potentially accommodate. The Special Issue papers discuss (i) circumstances under which a national waste management programme might wish to consider deep borehole disposal [1], (ii) a status report of deep borehole disposal options in Germany [2], (iii) the use of deep horizontal drill-holes in sedimentary, metamorphic or igneous rocks for disposal of spent nuclear fuel and high-level radioactive waste [3], (iv) the analysis of corrosion performance of engineered barrier systems [4], (v) a review of the potential cementing systems suitable for deep borehole disposal [5], (vi) the thermal evolution around heat-generating waste for a wide range of material properties and disposal configurations [6], (vii) a geochemical analysis of deep brines focussed on fluid-rock interactions [7], (viii) post-closure performance assessment calculations for deep borehole disposal of Cs/Sr capsules [8], and (ix) an example safety case for deep borehole disposal of nuclear wastes [9]. This paper provides an overview of the main findings from these publications and highlights some of the technological and scientific challenges that need to be overcome when developing a deep borehole disposal concept. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗
DOE OSTI2024

MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Non-Cooperative Game-Based Distributed Beam Scheduling Framework for 5G Millimeter-Wave Cellular Networks

Here, this paper studies the problem of distributed beam scheduling for 5G millimeter-Wave (mm-Wave) cellular networks where base stations (BSs) belonging to different operators share the same spectrum without centralized coordination among them. Our goal is to design efficient distributed scheduling algorithms to maximize the network utility, which is a function of the achieved throughput by the user equipment (UEs), subject to the average and instantaneous power consumption constraints of the BSs. We propose a Media Access Control (MAC) and a power allocation/adaptation mechanism utilizing the Lyapunov stochastic optimization framework and non-cooperative games. In particular, we first decompose the original utility maximization problem into two sub-optimization problems for each time frame, which are a convex optimization problem and a non-convex optimization problem, respectively. By formulating the distributed scheduling problem as a non-cooperative game where each BS is a player attempting to optimize its own utility, we provide a distributed solution to the non-convex sub-optimization problem via finding the Nash Equilibrium (NE) of the game whose weights are determined optimally by the Lyapunov optimization framework. Finally, we conduct simulation under various network settings to show the effectiveness of the proposed game-based beam scheduling algorithm in comparison to that of several reference schemes.

42 ENGINEERING↗
DOE OSTI2020

2020 LANL Contributions to the BATS Test in WIPP

The DOE Office of Nuclear Energy (DOE-NE) repository research and development program seeks to provide a sound technical basis for multiple viable disposal options, increase confidence in the robustness of generic disposal concepts, and develop science and engineering tools needed to support disposal concept implementation. Sandia, Los Alamos, and Lawrence Berkeley National labs are conducting research into salt, which includes the Brine Availability Test in Salt (BATS) field test at the Waste Isolation Pilot Plant (WIPP), a DOE Office of Environmental Management facility. BATS is leveraging the existing infrastructure associated with the WIPP to advance science informing generic disposal concepts. BATS is an ongoing heated borehole experiment being conducted in the WIPP underground. The goal of this experiment is to reduce the uncertainty associated with spent nuclear fuel disposition in geologic salt formations. The BATS experiments is designed to accomplish this by increasing our understanding of brine migration in salt, assessing damaged zones from mining and drilling, simulating a post-closure environment, confirming salt properties, and providing data for model validation. Phased testing for generic salt repository R&D was proposed in 2015. Subsequently, borehole thermal testing was developed as a first step in this process. This document summarizes the work conducted on the BATS experiment during fiscal year 2020 with an emphasis on the contributions by Los Alamos National Lab.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Sandia Academic Alliance Program Collaboration Report: 2020-2021 Accomplishments

University partnerships play an essential role in sustaining Sandia’s vitality as a national laboratory. The SAA is an element of Sandia’s broader University Partnerships program, which facilitates recruiting and research collaborations with dozens of universities annually. The SAA program has two three-year goals. SAA aims to realize a step increase in hiring results, by growing the total annual inexperienced hires from each out-of-state SAA university. SAA also strives to establish and sustain strategic research partnerships by establishing several federally sponsored collaborations and multi-institutional consortiums in science & technology (S&T) priorities such as autonomy, advanced computing, hypersonics, quantum information science, and data science. The SAA program facilitates access to talent, ideas, and Research & Development facilities through strong university partnerships. Earlier this year, the SAA program and campus executives hosted John Myers, Sandia’s former Senior Director of Human Resources (HR) and Communications, and senior-level staff at Georgia Tech, U of Illinois, Purdue, UNM, and UT Austin. These campus visits provided an opportunity to share the history of the partnerships from the university leadership, tours of research facilities, and discussions of ongoing technical work and potential recruiting opportunities. These visits also provided valuable feedback to HR management that will help Sandia realize a step increase in hiring from SAA schools. The 2020-2021 Collaboration Report is a compilation of accomplishments in 2020 and 2021 from SAA and Sandia’s valued SAA university partners.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Exploring Professor Motivations and Implementations of a Real-World Problem-Solving Project

Engineering education literature offers a variety of theoretical and conceptual frameworks for project-based learning. This study explores the implementation of real-world problem-solving projects in engineering education. The research team analyzed the motivations and methods behind professors' adoption of such projects through exploratory qualitative interviews with seven professor participants who integrated a nation-wide student competition into their courses. We analyzed the resulting data using a constructivist grounded theory approach to identify key themes of professor practices. Findings reveal that the real-world aspect of the projects and alignment with values and research interests were primary motivators for implementation. While implementation methods varied significantly based on context (i.e., university setting, course type), we found that these projects could be effectively integrated into various classroom settings. The findings support the recommendation for non-academic institutions to develop and manage competitions that can be integrated into classrooms and which offer a point of engagement that is available to professors from a wide range of disciplines.

42 ENGINEERING↗
DOE OSTI2022

Pumped Thermal Energy Storage With Liquid Storage

Pumped Thermal Energy Storage (PTES) uses electricity to power a heat pump; transferring heat from a cold space to a hot space forms a hot and a cold thermal reservoir, thereby storing energy. To discharge, the temperature difference between the two stores is used to drive a heat engine which generates electricity. In this chapter, PTES systems which store energy in liquids will be described. The chapter will concentrate on Joule-Brayton power cycles with molten salt storage. Part-load operation of Joule-Brayton PTES with liquid storage can be managed with "inventory control," and it is demonstrated that this control method leads to relatively good performance over a range of operating points.

Carnot batteries↗
DOE OSTI2021

Understanding the efficacy of concentrated interstitial carbon in enhancing the pitting corrosion resistance of stainless steel

By introducing a high fraction of interstitial carbon through low temperature carburization, the pitting corrosion resistance of austenitic stainless steel can be significantly improved. Previous work attributed this to strengthening of the passive film by carbon. Here, however, we present a paradigm shift by showing that carbon actually weakens the passive film but strengthens the bonding within the alloy by forming localized (covalent) bonds with the metal atoms (Fe, Cr, Ni). Accordingly, the enhancement in pitting resistance is a result of carbon reducing the metal dissolution rate in a local pit environment by many orders of magnitude, which extremely decreases the growth stability of a pit and prevents it from transitioning into stable growth. Electronic structure calculations confirm that carbon bonds to the metal atoms and that the metal–carbon bonds are 1.4 to 2.0 times stronger than the metal–metal bonds. These results suggest a new strategy for the design of corrosion resistant alloys, namely surface engineering by infusion of concentrated interstitials that form strong bonds with the matrix atoms.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Blockchain Smart Contract Reference Framework and Program Logic Architecture for Transactive Energy Systems

This paper proposes a reference framework for a transactive energy market based on blockchain. The framework was designed based on the engineering requirements of a distribution-scale market; including participant needs, expected market transactions, and the cybersecurity constructs required to support a fair, secure and efficient market operation. It leverages the existing blockchain primitives to provide clear value propositions to the transactive market, including identity management (access control), data security (integrity), resiliency (decentralization, scalability and performance). The validity of the proposed framework is demonstrated using a real-time 5-min double-auction market. The results highlight its benefits while providing strong validation of applicability to blockchain within transactive energy systems.

Gourisetti, Sri Nikhil Gupta↗
DOE OSTI2021

Unbundling Smart Meter Services Through Spatio-Temporal Decomposition Agents in DER-rich Environment

Smart meters and the advanced metering infrastructure (AMI) facilitate distribution system operators (DSOs) to gather information on energy consumption at the customer level. With the increasing penetration of building-level intermittent distributed energy resources (DERs) behind the meter, DER information is not available to DSOs. At the same time, smart meter enables users to participate in grid, with real-time information. Information for behind the meter is needed by user to coordinate building level assets for maximum benefits. The concept of unbundled smart meter (USM) needs agents to decompose smart meter measurements to provide service to DSO as well as customers. In this paper, we propose a Spatio-Temporal Decomposition Agent (STDA) for USM based on Artificial Intelligence (AI). STDA can help users optimize their energy usage, help DSO to utilize building assets for the grid operation. The energy usage strategy developed by STDA is suitable for different users, and can be customized by deep learning (DL) models according to the different energy consumption habits of each user. The power prediction performance results of various DL models and evaluation using a set of data from a Hawaii utility is presented. Furthermore, STDA integration with Home Energy management Systems (HEMS) to manage resources is presented and validated. STDA pre-processes the measurements before model training, and provides the spatio-temporal decomposed forecasting.

42 ENGINEERING↗
DOE OSTI2023

1.2-kW all-fiber Yb-doped multicore fiber amplifier

Here we have demonstrated a record-high 1.2 kW, all-fiber multicore amplifier using a six-core single-mode Yb-doped fiber and a multicore pump-signal combiner (PSC). The output power is limited by the pump power of 1.9 kW. We have developed double-clad six-core fibers and PSCs for this demonstration. Each of the six Yb-doped cores has a 17-µm mode-field diameter (MFD) with a trench index profile and is capable of kW-class operation. The potential power scaling to the 10-kW level in a single amplifier with high brightness should be feasible with advanced thermal management and coherent beam combination.

42 ENGINEERING↗