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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhancing Lifetime and Reducing Costs for Fish Diversion Netting Structures (Abstract)

This effort will focus on technology transfer and commercialization of antifouling coatings with an enthusiastic and engaged industrial team. Environmental requirements and operational demands call for a nontoxic coating/paint to prevent fouling on fish passage guidance netting at hydropower facilities. For example, one netting customer estimated the capital cost for compliance at $\$12$ million to $\$15$ million. This project will build partnerships between PNNL and private companies to optimize, demonstrate, mature, and commercialize a novel PNNL-developed technology that addresses this critical coating need of the hydropower industry. This effort will support modification of existing coatings for application to flexible netting structures. Industrial partners include commercial coating development specialist (Lorama), hydrophobic material manufacturer and paint developer (Dry Surface Technologies), aquatic applications specialists (Prometheus Innovations and River Connectivity Systems), and hydropower netting producer (Pacific Netting Products). Engagement with the U.S. Army Corps of Engineers (USACE) and Bureau of Reclamation (BOR), two hydropower operators, throughout the project will provide expertise and field test sites that will provide crucial proof of real-world performance data (additional details provided in Teaming section). Taylor Shellfish Farms will provide organisms and fouling expertise as well as a perspective of potential broader impacts for the blue economy. Sample netting will demonstrate performance in a range of environments for key hydropower applications. PNNL will work with industrial partners to overcome commercialization barriers as well as resolving any manufacturing or regulatory issues. This Phase 1 effort is focused on technology optimization for application to fish passage guidance netting and technology validation as verified by independent testing (through USACE, BOR, Taylor Shellfish and Prometheus Innovations). Through this effort, SLIC will be demonstrated for netting applications at technology readiness level (TRL) 5. The field test data will allow optimization of SLIC formulation and performance which is key to enabling technology transfer of a mature proven technology to industry and production of a viable commercial product specifically focused for hydropower needs.

13 HYDRO ENERGY↗
DOE OSTI2023

Advanced Anti-Fouling Coatings to Improve the Efficiency of Coal Power Plants

As the total cost of carbon to generate energy has become a global concern, operators are increasingly looking at all parts of the generation cycle to find areas where efficiency gains may be found. It has been long identified that fouling of heat exchangers is a persistent cause of up to 2.5% of global CO 2 emissions. Unfortunately, practice has also demonstrated that unless a powerful economic driver exists to encourage preemptive mitigation of fouling, there will always be a strong tendency for operators to minimize any form of intervention due to high costs and challenges in scheduling downtime. The objective of this proposed research effort was to demonstrate how existing power plants could lower their carbon emissions and significantly improve heat transfer efficiency using new surface treatment materials to control fouling in a variety of heat exchange equipment. The surface treatment material which was optimized and deployed in this effort is now known commercially as HeatX. It is a low-surface energy, water- and oil-repellent, abrasion resistant material which can be applied in-situ to a wide variety of previously worn/used/in-service substrates. Once applied, it provides a barrier against corrosion, scale deposit formation, and biofilm adhesion on the circulating water-containing tube-side. Alternatively, if applied to the tube exterior, the non-wetting nature of the surface was demonstrated to promote dropwise condensation, subsequently lowering condenser backpressure and increasing overall plant efficiency. As part of this cooperative effort, the Department of Energy’s support was crucial to de-risk and demonstrate the concept of HeatX, while validating both the performance and economic benefit in multiple pilot field studies. The HeatX material properties were optimized in this effort for full field applicability to heat exchangers and condensers, and Oceanit developed the necessary procedures and protocols to provide enough material to support extended length, multi-year demonstrations in the power generation, desalination, and refining industries, making this technology broadly applicable and ready for commercial transition. Field deployment case studies at thermal power plants have shown that the HeatX treatment can provide economic savings of up to $15,000 per day for an operator based on avoiding maintenance costs and lowering fuel usage. The complete mitigation of fouling effects can increase the efficiency of equipment by up to 7%, in a field where gains of 0.5% are generally seen as operationally significant. The HeatX treatment has also demonstrated exceptional lifetime and compatibility with a wide variety of seawater and hydrocarbon environments, further increasing both the return on investment and the effective emission reduction. Such efficiency improvements correlate to massive carbon savings. For every 1 GW of capacity, operators can see carbon emissions reductions of 300,000 tons of CO 2 per year. When looking at the bigger picture, improved condenser function across the U.S. has the potential to prevent 221.3 million tons of CO 2 emissions, equivalent to the sequestration capacity of 129 million acres of forest. If applied on a global scale, 1.26 billion metric tons of CO 2 could be averted from the atmosphere, the same amount of carbon sequestrated by 1.5 billion acres of forest annually or 262,000 wind turbines operating annually. As businesses across multiple industries take a more active role in focusing on environmental, social, and governance (ESG) solutions as part of their core business operations, HeatX will be an attractive technology for commercial investment.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Cybersecurity Center for Secure Evolvable Energy Delivery Systems (SEEDS)

The SEEDS Center has successfully completed its mission to research and develop a plethora of technologies during its six-year timeframe. The Center institutions of the University of Arkansas, the University of Arkansas at Little Rock, Carnegie-Mellon University, Florida International University, Lehigh University, and MIT all worked together with industry partners to define relevant energy sector cybersecurity issues, create projects to address those issues, and execute those projects in roughly two and three-year increments. The short project descriptions below indicate some really keystone areas of research. The teams generally met all of their objectives with only a few exceptions, which is tremendous in an R&D center. In fact, the success of one project led to the creation of a startup company, Bastazo, Inc. that is commercializing the SPARTAN project. In addition to creating new technologies, the Center helped to educate a desperately needed workforce. Lastly, a big success is that the UA seriously followed the mandate of the original program manager to try to become self-sustaining. This effort has resulted in a combined NSF center with the CREDC Center at the University of Illinois, Urbana-Champaign. To summarize the SEEDS effort, great research was funded, students were educated and put into the workforce, technology is being commercialized and offered to the electric sector, and the research efforts are being sustained through additional funding. The effort was an unqualified success.

03 NATURAL GAS↗
DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗
DOE OSTI2023

Cosmic Frontier Project at SMU

The SMU group led by Professor Robert Kehoe continued to work to constrain dark energy measurements of the Dark Energy Spectroscopic Instrument (DESI). These constraints are obtained by measuring the expected peak in characteristic distance scale between galaxies, the ‘BAO peak’, as a function of redshift for four different types of galaxy. DESI will cover the redshift range to z<3.5 with approximately 40 million galaxy spectra. SMU’s primary emphasis during the funding period was on the early DESI data, including the development of software that would allow the measurement of the impact of incomplete targeting of galaxies in the survey. We provided software to calculate the weights that are critical to permit us to correctly compare data to the theoretical calculations of dark matter halos. SMU also began development of software that can be integrated into the analysis pipeline that uses alternate targeting to generate these weights. Baryonic physics has a critical impact on galaxy development and placement within dark matter halos. SMU also increased its efforts in the area of modeling this galaxy-halo connection in two areas. The primary emphasis was to work on a sub-halo abundance matching scheme using dark matter simulation with very fine mass resolution (‘Uchuu’). Our effort here is to produce models for use by DESI that more correctly account for the subhalo structure of dark matter distribution, and its manifestation in satellite galaxies. Our initial effort had been for emission line galaxies. In the funding period, we were able to produce first halo-occupation distribution models. This work is slated to contribute to DESI Key Project papers. We also furthered our ongoing effort to study galaxy placement in halos using semi-analytic methods. Kehoe’s group also continued to maintain its strong role in DESI Operations, with SMU postdoc serving as a Lead Observing Scientist.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

National Virtual Biotechnology Laboratory: Report on Rapid R&D Solutions to the COVID-19 Crisis

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply short ages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. Within months, NVBL teams produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment (PPE), creating nearly 1,000 new jobs. They used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported U.S. Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and U.S. Department of Defense (DoD) efforts to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. NVBL teams also studied how to control indoor virus movement to minimize uptake and protect human health. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development (R&D) solutions. As the fight against COVID continues, sustained efforts are needed to confront this pandemic as well as future threats. Examples include: 1) Establishing “supply chains on demand” to meet emergency production needs by leveraging the materials and manufacturing expertise of DOE national laboratories and developing advances in electronics, sensing, robotics, and automation capabilities; 2) Improving the speed and robustness of drug discovery by integrating experimental platforms with DOE’s computational and experimental user facilities, which provide unique resources to support the discovery of high-potential therapeutic agents; 3) Protecting public, environmental, and animal health by developing new testing protocols and instrumentation adaptable to diverse sample types (both physiological and environmental) to quickly detect a wide range of pathogens and monitor other biorisks; 4) Supporting near-real-time data needs of decision-makers at the local, regional, state, and national levels by advancing data curation, analysis, and modeling using artificial intelligence and new data science tools for managing and evaluating large diverse datasets; 5) Harnessing DOE’s expertise in environmental modeling to design rooms and air handling for offices, classrooms, restaurants, and other structures to minimize biorisk transmissions. Going forward, NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, the Office of Science will continue to be an integral component of agency wide efforts to prepare for and respond to biorisks and other crises.

42 ENGINEERING↗
DOE OSTI2023

Software Bill of Materials (SBOM) Sharing Lifecycle Report

As Software Bill of Materials (SBOM) adoption efforts mature, SBOM sharing continues to occur, but no single solution or set of solutions have become ubiquitous. The purpose of this report is to enumerate and describe the different parties and phases of the SBOM sharing lifecycle and assist readers in choosing suitable SBOM sharing solutions based on the amount of time, resources, subject-matter expertise, effort, and access to tooling that is available to the reader to implement a phase of the SBOM sharing lifecycle. The SBOM sharing lifecycle consists of the Discovery, Access, and Transport of an SBOM and this report details these individual phases and how an SBOM goes from author to the consumer. This report also details how potential enrichment activities may be performed on an SBOM to create a new product before or after it has been shared. The concept of a sophistication classification for SBOM sharing solutions is concurrently introduced with a focus on the inclusion or lack of certain features and effort associated with their implementation. Examples of low, medium, and high-sophistication solutions are provided; however, these examples and associated categorizations should not be seen as a qualitative judgment meant to push the reader towards a particular adoption strategy since sharing solutions are chosen based on the unique needs of the user. This report does recommend the SBOM community consider how to make current and future sharing solutions interoperable with each other as well as more automated methods to facilitate sharing and broader SBOM adoption. This report also highlights an SBOM sharing survey results obtained from interviews with stakeholders to understand the current SBOM sharing landscape. The categorized results of the survey suggest that SBOMs are currently transported directly to the receiver through email or similar informal communication mechanisms or alternatively the SBOM resides on a repository available to consumers. In addition to these transport methods, this report captures industry efforts to create private sharing solutions and services that can store and transport enrichment data and may use higher sophistication features that are cloud-based or using distributed ledger technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High Inlet Temperature Combustor for Direct-Fired Supercritical Oxy-Combustion

It is envisioned that supercritical CO 2 (sCO 2 ) electric power plant efficiencies can exceed 52% with 99% carbon capture using direct-fired oxy-combustion. Such efficiencies would be competitive with Natural Gas Combined Cycles (NGCC) and operate with nearly zero carbon emissions. To achieve high plant efficiencies, turbine inlet conditions must approach 1,200 °C at 250 bar. Such conditions, while desirable from a systems perspective, exceed the current state of the art in turbine design and materials qualification. The team of Southwest Research Institute ® (SwRI ® ), Georgia Institute of Technology (Georgia Tech), Spectral Energies, LLC (Spectral), GE Global Research (GE-GRC), and the University of Central Florida (UCF) sought to demonstrate an intermediate step toward these high efficiency plants with the development of a 1 MWth, subscale direct-fired oxy-fuel combustor. The efforts focused largely on the development of an auto-ignition based combustion system capable of providing the targeted 1200 °C and the pilot-scale plant to operate the combustor. While the project was stopped short of the commissioning and demonstration work, the advances made in this effort will reduce risks associated with chemical kinetics, thermal management, water separation, flue gas cleanup, materials selection, and corrosion in future demonstration efforts for the direct-fired oxy-fuel combustion cycles. The following report documents the design, analysis, and installation efforts completed during the project periods of performance.

03 NATURAL GAS↗
DOE OSTI2021

Hydrothermal Liquid Recovery of Rare Earth Elements and Critical Materials

This project demonstrated the technical viability of using tunable hydrothermal liquid (HTL) solutions to recover valuable minerals from a range of source materials. The effort focused upon rare earth elements (REE) and other minerals critical to the industrial security of the United States. This effort demonstrated, for the first time, that s, supercritical water (SCW) in particular, can: Extract critical and valuable minerals from a range of matrices ranging from rock ore to biomass; The process can be used to recover a wide range of minerals; This novel extraction chemistry can be cheap, simple, and nontoxic/”green”: The chemical extraction uses water, the cheapest industrial acid (sulfuric), and simple salts (i.e. sodium sulfate). However, other acids, salts, and additives could be used as appropriate. This Laboratory Directed Research and Development (LDRD) project identified that the process is complex with many interacting factors, but the benefits are significant if the complexities can be resolved. Challenges remain in the development of this technology and are described in this report. However, the results are positive, and commercial partners have already expressed interest. In summary, a novel, green, inexpensive mineral extraction process has been developed and demonstrated in a small batch reactor system. The effort provided information for an invention disclosure, proposal to DOE, and will support future business development efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Verification of the DIF3D Software to Support Fast Reactor Analysis (Rev. 3)

Ongoing design activities at Argonne National Laboratory are requiring a thorough verification of the Argonne Reactor Computation codes be performed. DIF3D is central to this system. The driver for this effort requires the 3D Cartesian, triangular-Z, and hexagonal-Z core geometry options of DIF3D be verified. Previous work identified the DIF3D features required to be verified to support current design activities, features of which are generally applicable to hexagonal-Z fast reactor designs. The scope of this verification effort includes verifying DIF3D’s ability to correctly translate the user’s model in to DIF3D’s preferred format, verifying that options planned for use have the desired effect, and verifying the correctness of the eigenvalue, fixed-source, forward, and adjoint solvers in DIF3D-FD and DIF3D-VARIANT. This manuscript provides the verification tasks and their results with respect to the features needed for current design activities. Since analytic solutions of the neutron diffusion and transport equations are either limited in scope or not possible, multiple tiers of problems unique to each solver and geometry type were implemented. Each of these tiers tests features independent and complementary arguments for why the separate testing of functionalities is acceptable. Finally, this separate testing was also supplemented with a high-level integral check of each the diffusion and transport capabilities and applicable geometries. To accommodate cases which an analytic solution is not feasible, MCNP6.2 was relied upon to provide a higher-order reference solution. This therefore required that the capabilities within MCNP6.2 which were relied upon for this work are also verified in this work. No MCNP discrepancies were noted in this effort. Note that the MCNP6.2 verification included in this work does not stand as a full verification of MCNP6.2, but merely verifies the features used in verifying DIF3D. The verification effort identified no issues that are debilitating or otherwise impactful to design usage of DIF3D, and thus DIF3D version 11.0, release 3012 is considered verified. As some additional changes have been made to the ARC software since this point all versions between release 3012 and 3266 can be considered verified as version 3253 was used for all updates in this revision. The types of issues that were identified were predominantly in the areas of: unclear documentation, software bugs which were inconsequential to final results, editing options which were ignored in favor of printing more information than requested, bugs in the outputs of intermediate results, or secondary output binary file information which was not present. While not a bug, this verification report also identified that the algorithm used to evaluate the peak fast flux in a nodal transport solution can be quite unreliable due to the methodology used and the location of the peak within the mesh. The authors of the report therefore recommend the usage of the EvaluateFlux software (distributed with ARC) as a more robust alternative noting that DIF3D will properly notify the user when the peaking values it is providing are potentially incorrect.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Phase 1: Duke Energy Zero Emission Resource Integration Study (ZERIS); Phase 2: Carbon-Free Resource Integration Study for Duke Energy (Final Report)

Phase 1: This statement of work makes up Phase 1 of a larger effort. During this Phase 1 effort, NREL will work with Duke Energy to analyze the impacts of integrating significant amounts of new solar power into the Duke Energy power system under a variety of different penetrations scenarios, with a maximum of ten (10) full scenarios examined. The existing fleet, particularly the nuclear generation, will be considered in the quantitative assessments and discussions. Duke Energy is looking to quantify how much solar generation its system can handle. NREL will work with Duke Energy to quantify solar potential, identify likely integration challenges and possible opportunities for wind, storage, demand side resources and other technologies. Phase 2: This Statement of Work consists of a follow-up effort (Phase 2) to a recently completed Phase 1 modeling effort. During Phase 2, NREL will work closely with Duke Energy to analyze the impacts of integrating significant amounts of variable generation resources (wind and solar) and storage into Duke Energy's system in the Carolinas. The existing fleet, particularly nuclear generation, will be considered in the quantitative assessment and discussions. This Statement of Work also includes an extension to Phase II of the Carbon-Free Resource Integration Study for Duke Energy. In this extension, NREL will work closely with Duke Energy to extend the production cost analysis developed in Phase II to 2018 weather and load data for Duke Energy's territory. This extension leverages the modeling tools and datasets developed as part of Phase II. The analysis will compare results from Phase II (using 2012 weather and load) with 2018 results to assess system operations with increased penetration of renewables and storage. Simplifying assumptions will be made for modeling Duke Energy's neighbors in the production cost model.

14 SOLAR ENERGY↗
DOE OSTI2023

Inventory for Crystalline Silicon Module Recycling: Cooperative Research and Development (Final Report)

A critical challenge for the continued expansion of photovoltaics (PV) is to develop technically feasible, inexpensive and environmentally friendly practices for handling and recycling modules at the end of their usable life. The National Renewable Energy Laboratory (NREL) is requested by the Electric Power Research Institute (EPRI) to collect primary data regarding the environmental performance of currently operational PV module recycling facilities in Europe. Very little has been published regarding crystalline silicon (C-Si) module recycling. Thus, much effort will be needed in direct industry outreach, collection of information and other business intelligence strategies similar to NREL's approaches for developing cost models for PV manufacturing. The goal of this work effort is to produce a detailed inventory that accounts for physical (e.g., energy, water, materials) flows through each step of a C-Si recycling process. The inventory (a life cycle inventory, or LCI) shall be designed so that it can be extended to include an accounting of costs for each process step, inputs, etc. This work effort shall leverage prior LCI data collection NREL performed for the United States Department of Energy, Solar Energy Technologies Office, under the auspices of the U.S. contribution to International Energy Agency's Photovoltaics Power Systems (PVPS) Task 12 (Environmental Health and Safety), which SETO nominated NREL to chair. The primary purpose of this work effort is to augment the prior data collection to increase the sample size of manufacturers' primary data in the LCI.

14 SOLAR ENERGY↗
DOE OSTI2023

Contributions to the LZ Experiment (Final Report)

We describe our contributions to the LZ Experiment, grouped into three broad categories: 1. Hardware Efforts; 2. Analysis Efforts; 3. Leadership/Administration. All the efforts described here were accomplished by the PI and two PhD students. The first LZ science data and first results papers (including Phys. Rev. Lett. 131, 041002 (2023) ) would not have been possible without these efforts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

MSTL Re-Start Phase 1.5 Project Final Report

This document provides an overview of re-start efforts at Sandia National Laboratories (SNL), National Solar Thermal Test Facility (NSTTF), for the SNL Molten Salt Test Loop (MSTL). MSTL is one of the world’s only industrial-scale molten salt test systems, capable of testing commercial-scale thermal hydraulic equipment at an industrial scale, required for confident bankability of products. This work was facilitated as part of the Phase 1 re-start effort for facilitating forensics assessments to inform final refurbishments and upgrades costs and schedule information for revitalizing MSTL for use during a separate Phase 2 effort. This work was facilitated to further de-risk a Phase 2 effort pertaining to the tank and the pump, which were considered during Phase 1 to be high-risk items for a successful re-start. Impact from a successful re-start will allow SNL and other industrial molten salt systems companies, such as those in the Market Utilization Report provided in the Phase 1 submission package. An objective of this document is to also ensure longevity of utilization of MSTL after re start.

14 SOLAR ENERGY↗
DOE OSTI2024

Multiple Beam Triode Driven RF Sources for Accelerator Applications Phase I Final Report

Calabazas Creek Research, Inc, (CCR), in collaboration with Microwave Power Products, Inc. (MPP), formerly Communications & Power Industries, LLC (CPI,) and JP Accelerator Works, Inc. (JPAW), embarked on a program to develop multiple beam triodes to produce RF power from 350 – 800 MHz with an average power exceeding 200 kW. The effort was motivated by the performance of a triode-based RF source which produces 25 kW of UHF power at 90% efficiency. The CCR effort focused on implementing this technology into a multiple beam device to increase the output power while retaining the low cost, compact size, and high efficiency. The program performed extensive simulations indicating that the goals could be achieved, and a prototype multiple beam triode was built, baked, and tested. Unfortunately, a grid to cathode short terminated the testing before the tube could generate RF power. Nevertheless, the effort demonstrated that a multiple beam triode could be designed, built, baked, and energized to high voltage. The multiple beam triode used oxide cathodes, which are only capable of pulsed operation. The multiple beam triode will be rebuilt using dispenser cathodes, which will allow high duty or continuous operation. The grids were also modified to be more robust to avoid previous issues. The MB triode will provide the beam power for RF generation. The RF is generated by surrounding the triode with input and output cavities to convert beam power to RF power. RF cavities to generate 200 kW CW at 350-450 MHz using the MB triode with dispenser cathodes was assembled during the program. The next Phase of this effort is to assemble the multiple beam triode using the subassemblies built in the Phase I program and test with the RF cavities. The Phase I program also initiated design of a higher frequency, higher power multiple beam triode. That design is forecast to produce approximately 500 kW CW from 350 - 500 MHz.

43 PARTICLE ACCELERATORS↗