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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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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Challenges, progress, and future perspectives for cyanobacterial polyhydroxyalkanoate production

Polyhydroxyalkanoates (PHA) are a promising bio-based alternative to traditional plastics derived from petroleum. Cyanobacteria are photosynthetic organisms that produce PHA from CO 2 and sunlight, which can potentially reduce production costs and environmental footprint in comparison to heterotrophic bacteria cultures because (1) they utilize inorganic carbon sources for growth and (2) they do not require intensive aeration for oxygenation. Moreover, supplementing precursors such as propionate, acetate, valerate, etc., can be used to obtain various copolymers with plastic customizable properties in comparison to the classical homopolymers, such as polyhydroxybutyrate, PHB. This critical review covers the latest advances in PHA production, including recent discoveries in the metabolism interplay between PHA and glycogen production, and new insights into cultivation strategies that enhance PHA accumulation, and purification processes. This review also addresses the challenges and suggests potential solutions for a viable industrial PHAs production process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Constraining primordial non-Gaussianity from DESI DR1 quasars and Planck PR4 CMB lensing

We present the first measurement of local-type primordial non-Gaussianity from the cross-correlation between 1.2 million spectroscopically confirmed quasars from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI) and the Planck PR4 CMB lensing reconstructions. The analysis is performed in three tomographic redshift bins covering 0.8 < z < 3.5, covering a sky fraction of ∼20%. We adopt a catalog-based pseudo-C ℓ estimator and apply linear imaging weights validated on noiseless mocks. Compared to previous analyses using photometric quasar samples, our results benefit from the high purity of the DESI spectroscopic sample, the reduced noise of PR4 lensing, and the absence of excess large-scale power in the spectroscopic quasar auto-correlation. Fitting simultaneously for the non-Gaussianity parameter f NL and the linear bias amplitude in each redshift bin, we obtain f NL = 2 +28 -34 for a response parameter p = 1.6, and f NL = 6 +20 -24 for p = 1.0. These results improve the constraints on f NL by ∼35% compared to the previous analysis based on the Legacy Imaging Survey DR9. Additionally, we derive an optimal weighting scheme to maximize the constraining power. In this case, and assuming p = 1.6, we obtain f NL = 19 +25 -31 . Our results demonstrate the statistical power of DESI quasars for probing inflationary physics, and highlight the promise of future DESI data releases.

cosmological parameters from CMBR↗
DOE OSTI2026

Production of Renewable Natural Gas from Waste Carbon Dioxide Sources (CRADA Final Report)

This CRADA provides new funding from SoCalGas and DOE's BETO and FCTO Offices focused hydrogen mass transfer limitations in H2@Scale processes. The project leverages the existing hydrogen production capabilities at the Energy Systems Integration Facility (ESIF) and SoCalGas' 700 L bioreactor system designed, built, and delivered to NLR under the first phase of this CRADA. This Joint Work Statement will cover new hardware modifications between NLR's electorlyzer stack and the SoCalGas bioreactor located outdoors. The new hardware and controls will provide researchers with the tools needed to obtain preliminary experimental data for a non-provisional application due in July 2019. The IP being developed is expected to improve the productivity of the bioreactor and would have wider impacts on other end-use processes using pressurized hydrogen (H2). In addition, this new funding enhances an existing BETO Biopower award by developing a 10-15 kW electrolyzer that is scalable to the MW-class with reduced capital cost and higher efficiency aimed at improving H2 mass transfer to downstream processes, like biomethanation. Finally due to the close-coupling between the electrolyzer stack and bioreactor, R&D will focus on cell retention, nutrient maintenance, optimal water management and process controls.

08 HYDROGEN↗
DOE OSTI2026

Margin to onset of nucleate boiling and flow instability studies for preliminary MITR design-demonstration element thermal-hydraulics

This study covers the onset of flow instability (OFI) preliminary results obtained from leveraging correlations, in addition to the preliminary thermal hydraulics results such as pressure, flow velocity, temperature, and oxide layer over the design demonstration experiment (DDE) for the Massachusetts Institute of Technology Reactor (MITR). Current computational fluid dynamics (CFD) models in fluid structure interaction (FSI) have added the capability of assessing margins to onset of nucleate boiling (ONB). This study initiates the capability to model the margin to OFI and ONB presented for the MITR. Such study is supportive of the United States High Performance Research Reactor (USHPRR) program. Previous studies provided preliminary thermal-hydraulic and mechanical analyses of the hydrodynamic effects in the MITR DDE under conservative approximations for plate power distribution. In conclusion, this study focuses on providing insights into the OFI future research direction optimizing the transport of thermal energy, mass-flow rates, flow-channel geometries, and boundary conditions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations

This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019–2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High-shade dryland agrivoltaic conditions enhanced carbon uptake and water-use efficiency in zucchini ( Cucurbita pepo )

Introduction: The increasing global demand for food and energy is intensifying land-use competition. Agrivoltaic systems are a multifunctional land-use approach that vertically integrates the production of agricultural crops and solar power on the same land area. Most food crops are adapted to full-sun conditions, and the physiological responses of these crops to the novel microclimate under solar panels remain poorly understood. We hypothesized that the microclimate beneath the high-density photovoltaic system would influence carbon uptake, water use, and yield outcomes of zucchini summer squash.Methods: We conducted a field experiment in a hot, semi-arid climate on zucchini (Cucurbita pepo). Plants were grown under an agrivoltaic system with a 75% ground cover ratio (GCR) and in a full-sun control plot, each with two irrigation regimes (100 and 50%). We measured leaf-level photosynthesis, microclimate variables, and fruit yield at plant maturity and throughout the growing season.Results: The agrivoltaic array reduced photosynthetically active radiation (PAR) by ~79%, resulting in a cooler (−1.1 °C), more humid environment with higher soil moisture. These microclimatic conditions enhanced midday photosynthesis and daily cumulative carbon uptake. However, fruit yield was consistently lower under the panels, indicating a shift in carbon allocation toward vegetative growth. Photosynthesis was primarily driven by PAR across treatments, while soil moisture significantly influenced photosynthesis only in the control plots, suggesting water limitation was alleviated under the panels.Discussion: These findings highlight a trade-off between improved physiological performance and reduced yield under high-density agrivoltaics. While the system buffered heat and drought stress and improved overall plant function, excessive shade reduced reproductive output. Optimizing panel density or selecting crops cultivated for non-fruit yields will be essential for balancing food production and energy generation in dryland agrivoltaic settings.

14 SOLAR ENERGY↗
DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Structure-Based Analysis of Semisynthetic Anti-TB Rufomycin Analogues

This study employed structural information from cocrystals of rufomycin 4 (1a) and caseinolytic protein C1 (ClpC1)-NTD-wt to guide design and semisynthesis of rufomycin analogues, evaluate their antituberculosis (TB) biological profiles, and establish structure–activity relationships (SAR). Covering three regions of interest (ROIs, A–C) as modification sites, 14 of the 30 semisynthetic analogues (2–31) showed similar or improved MICs relative to the main natural precursors, rufomycins 4/6 (1a/b). Compounds 5 and 27 exhibited up to 10-fold enhanced potency against Mycobacterium tuberculosis (Mtb) in vitro, with MIC values of 1.9 and 1.4 nM, respectively. Evaluation of ClpC1-binding properties used existing ClpC1-NTD complexes with rufomycin 4 (PDB: 6cn8) and ecumicin (PDB: 6pbs) as references. The newly reported X-ray ClpC1-NTD cocrystal structure of 11 (syn. But4-Cl) revealed significant conformational effects involving the side chains of certain amino acids of the heptapeptide and confirmed the importance of ROIs A–C for medicinal chemistry efforts. Observed interactions of the N-terminal tail of ClpC1 with the rufomycin analogues vs ecumicin explains their different modes of inactivating the ClpC1/P1/P2 homeostatic machinery. Collectively, the observations inform further SAR optimization strategies for the rufomycin class of antibiotics and complement our understanding of their mode of action.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

In Situ MOF Pyrolysis Construction of Hierarchical Porous Co‐Nanoparticles/Carbon Cloth Composites for Enhanced Electromagnetic Wave Shielding and Absorption

The development of high-performance electromagnetic protection materials integrating broadband absorption and effective shielding capabilities is hindered by challenges in simultaneously optimizing multiple electromagnetic properties through conventional material designs. This study pioneers a hierarchical porous Co nanoparticle/carbon cloth (Co/CC) composite via controlled annealing of a Co-MOF precursor on carbon cloth. The Co-MOF served a dual role as both magnetic source and pore-forming agent, enabling in situ generation of uniformly dispersed Co nanoparticles and creation of abundant pores/interfaces on the CC fibers during pyrolysis. This unique architecture synergistically enhanced dielectric loss (via interfacial/dipolar polarization) and magnetic loss (via natural resonance, exchange interactions, and eddy currents), significantly improving impedance matching. The hierarchical pores further functioned as integrated “absorption–reflection” units for efficient electromagnetic energy attenuation. Consequently, the Co/CC composite annealed at 800°C (Co/CC-800) achieves minimum reflection loss (−40.69 dB) and 120% effective absorption bandwidth extension (6.16 GHz) as a filler, and exhibits superior electromagnetic interference shielding effectiveness (46.66 dB) as an integrated component. Significantly, Co/CC-800 demonstrated robust photothermal and electrothermal conversion capabilities, ensuring operational stability in ice-covered and humid harsh environments. This work pioneers a pore-structure-mediated strategy to harmonize dielectric–magnetic synergy, providing a new paradigm for designing advanced multifunctional electromagnetic protection materials.

dielectric‐magnetic synergy↗
DOE OSTI2025

Flow instabilities in helical-coil steam generators for small modular reactors: A review

Here, this study covers the research and discoveries in two-phase flow-boiling instabilities available in the literature—specifically for a helical-coil steam generator (HCSG), including experimental findings, theoretical research, computational models, and system code analyses—supporting research and development of representative small modular reactors (SMRs). Like other new and advanced reactor systems, water-cooled SMRs require experimental data from both integral and separate thermal-hydraulics test facilities for the verification and validation (V&V) of the computational models and computer codes in order to design and obtain regulatory approval. The complex dynamics of two-phase flow-boiling instabilities includes flow regimes physics phenomena, flow-channel geometries, heat-transfer behavior, and interactions among the solid–liquid-gas within the system boundary, all of which are pivotal for understanding the design and operational challenges of SMRs. This study focuses on identifying the relevant knowledge gaps on boiling instabilities—specifically for a HCSG—and provides insights about future research direction optimizing the transport of thermal energy, mass-flow rates, and boundary conditions that ensure the adequate heat-transfer performance, operational stability, and safety associated with SMR systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

The Snow Albedo Evolution (SALVO) Campaign at the North Slope of Alaska Field Campaign Report

The springtime surface-albedo transition in the Alaskan Arctic, along with the forces that determine its duration and nature, was the focus of the Snow ALbedo eVOlution (SALVO) campaign. The SALVO team investigated the reasons and durations of the stages of spring melt, during which albedo values decrease from 0.8 to 0.1, signifying the year’s largest and most significant radiative energy change. SALVO II (2022, 2024) built on findings from the successful SALVO I (2019) melt season campaign and previous research on the melt transition period conducted by Grenfell and Perovich (2004). SALVO used the ARM NSA observatory, thus aligning with a core principle of the ARM Decadal Vision to “provide comprehensive and impactful field measurements to support scientific advancement of atmospheric process understanding.” SALVO fieldwork was conducted in the spring near the ARM NSA Central Facility in Utqiagvik, Alaska (Figure 1). Comprehensive data sets were collected in 2019, 2022, and 2024, which included spectral and broadband albedos, snow and meltwater depths, snow stratigraphy, snow grain size data, and aerial imagery. In April of each project year, before the snow began to melt, we established survey lines at three or four locations: inland tundra at NSA E12, coastal tundra at the NSA C1 site, Elson Lagoon, and offshore on the Chukchi Sea sea ice (2022 only). We set up a 200-meter-long line, marked every five meters, to enable repeated measurements of surface albedo and snow depth at each location. During most site visits, the SALVO II team dug at least one snow pit to assess the characteristics of the vertical snow layers, including the types and sizes of snow grains, snow density, and the distribution of liquid water. We evaluated the characteristics of flowing or pooled water at the bottom of the snowpack. Watching snow melt in the Arctic has been compared by some to being as exciting as watching paint dry, but it is far more exciting and dynamic than that. Initially, changes happen slowly while the snow cover remains above 80%, but then reductions in the albedo of the landscape, from about 0.8 to 0.4, combined with rising spring temperatures, begin to accelerate the melt. It happens so quickly that no matter how hard the field team works, they cannot keep up with documenting the changes. At first, liquid water is scarce—only a few wet layers of snow in the snowpack. But then, water becomes ubiquitous, transporting melt energy and creating an extremely heterogeneous albedo and melt landscape. At the end of each field season, the SALVO team is exhausted, relieved to see the snow gone, and joyful to play in the melt ponds on the sea ice under the midnight sun. Overall, the 2024 SALVO field campaign was a highlight, reflecting numerous lessons learned from 2019 and 2022. Daily measurements were taken more than 10 times at each site, resulting in a comprehensive time series of snow conditions and albedo. The team deployed using snowmachines and then on foot when snowmachine travel was no longer permitted on the melting tundra. Instrument mounts and packaging were optimized for quick deployment, regardless of the mode of transportation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Examining Graphite Degradation in Molten Salt Environments: A Chemical, Physical, and Material Analysis

Molten-salt reactors (MSRs) are Generation IV nuclear reactors that use liquid salt as a coolant and/or fuel. In several MSR designs, graphite serves as a moderator and/or reflector. However, due to limited experimental data and operational experience, our understanding of graphite behavior in molten salt environments remains incomplete. This report aims to identify the degradation mechanisms of nuclear graphite in MSRs, detail the mechanisms of each factor, and provide an initial assessment of their impact on the structural integrity of graphite components. This assessment is based on an extensive literature review and insights from subject matter experts. Furthermore, given the limited data, a modeling strategy using existing Grizzly software is proposed for a more thorough analysis where appropriate. Additionally, it presents mitigation strategies where applicable. The report covers physical degradation mechanisms such as infiltration, erosion, and abrasion, as well as chemical degradation mechanisms including fluorination, intercalation, corrosion, and oxidation. Molten salt can infiltrate the porous structure of graphite, leading to several detrimental effects. Entrapment of fissile products within the graphite pores can cause radiation damage and could pose challenges in the handling and disposal of contaminated components. The differential thermal expansion between the infiltrated salt and graphite, along with internal stress from pressurized molten salt and volumetric heating, can compromise the structural integrity of graphite. To mitigate these effects, employing ultra-fine graphite grades and applying sealants and coatings are effective strategies. A computational model based on coupled solid mechanics and heat transfer phenomena could be used to predict the internal stresses using Grizzly software. In pebble-bed MSRs, graphite fuel pebbles can cause abrasion against reactor components due to friction and wear. The severity of wear is influenced by various factors such as temperature, environment, and the presence of lubricants. Tribological studies reveal that higher temperatures and molten salt environments, such as FLiBe, significantly reduce wear rates compared to dry conditions. Additionally, the chemical composition of the salt can further optimize graphite's tribological performance. Long-term wear effects can be modeled by incorporating surface defects into the geometry and predict stresses under thermal and radiation effects using Grizzly software. Chemical degradation of graphite in a molten salt environment can occur through fluorination and intercalation. Fluorination can occur via replacement of hydrogen or oxygen atoms, or at the active sites, but does not cause structural degradation. Intercalation, on the other hand, can lead to exfoliation, where layers of graphite separate and peel away, damaging the graphite. Protective coatings can enhance graphite's resistance to intercalation. Graphite generally exhibits good chemical stability in molten salt environments, though it can corrode under specific conditions, particularly in the presence of impurities or oxidants. Studies have shown that protective coatings, such as plasma-sprayed partially stabilized zirconia (PSZ), can effectively prevent such degradation. Corrosion behavior varies significantly with different graphite grades and coating applications, underscoring the need for detailed studies on uncoated and coated graphite to understand and mitigate corrosion mechanisms in MSRs. Research indicates that the presence of oxidants and impurities can accelerate graphite degradation in molten salts, making it essential to explore acceptable impurity limits. Oxidation is another critical degradation mechanism, leading to weight loss and structural damage due to the formation of CO and CO 2 from the reaction of carbon atoms with oxygen. This process creates new porosity and compromises graphite's integrity. While extensive research on graphite oxidation has been conducted for gas-cooled reactors, studies specific to MSRs are limited. Findings from the coal industry suggest that molten alkali metal salts can significantly accelerate graphite oxidation, a hypothesis worth exploring for fluoride salts in MSRs. Understanding oxidation behavior in MSRs is vital for developing protective measures. The analysis of post-irradiated graphite from the MSRE experiment demonstrated exceptional chemical compatibility with molten fluoride salt, suggesting that the extent of chemical attack on graphite largely depends on the salt's infiltration capability. Therefore, the use of ultra-fine grade graphite could help mitigate chemical degradation effects. Existing oxidation modeling capabilities in Grizzly, which use reaction-diffusion equations to model graphite-air interactions, could be adapted to simulate the chemical degradation effects of graphite in molten salt environments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Predicting Selective Laser Printing Print Quality of Polymer Powders through Melt Flow Index

Selective Laser Sintering (SLS) uses a precisely controlled laser to fuse polymer powder to build complex 3D shapes. While SLS covers a wide application space, the processing knowledge of polymer powder is limited, restricting the number of commercial powders available. This study serves to expand the processing knowledge of polypropylene and polyethylene in parallel with a “mature” SLS feedstock, nylon, through melt flow index (MFI) characterization. Differential Scanning Calorimetry (DSC) was used to explore the sintering window of the polymers. Polyethylene and polypropylene exhibited a relatively narrow sintering window between 4 – 5 °C, whereas the sintering window of nylon was much wider, between 23 – 24 °C. This suggests that the print quality between polyethylene and polypropylene would be similar; however, X-ray computed tomography revealed a higher volume of print defects, voids, and de lamination in polyethylene than in polypropylene. MFI analysis provided additional insight into the difference in print quality, as the MFI of polyethylene was 7.16 g/10 min, 9.95 g/10 min for polypropylene, and 17.23 g/10 min for nylon. MFI is inversely correlated to melt viscosity, and a low melt viscosity is desired for proper coalescing between the layers and particles. These results suggest that MFI is a promising tool, in conjunction with traditional thermal analysis, for screening candidate powder feedstocks for SLS and optimization of print parameters for novel powders.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An introduction to Spent Nuclear Fuel decay heat for Light Water Reactors: a review from the NEA WPNCS

This paper summarized the efforts performed to understand decay heat estimation from existing spent nuclear fuel (SNF), under the auspices of the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. Needs for precise estimations are related to safety, cost, and optimization of SNF handling, storage, and repository. The physical origins of decay heat (a more correct denomination would be decay power) are then introduced, to identify its main contributors (fission products and actinides) and time-dependent evolution. Due to limited absolute prediction capabilities, experimental information is crucial; measurement facilities and methods are then presented, highlighting both their relevance and our need for maintaining the unique current full-scale facility and developing new ones. The third part of this report is dedicated to the computational aspect of the decay heat estimation: calculation methods, codes, and validation. Different approaches and implementations currently exist for these three aspects, directly impacting our capabilities to predict decay heat and to inform decision-makers. Finally, recommendations from the expert community are proposed, potentially guiding future experimental and computational developments. One of the most important outcomes of this work is the consensus among participants on the need to reduce biases and uncertainties for the estimated SNF decay heat. If it is agreed that uncertainties (being one standard deviation) are on average small (less than a few percent), they still substantially impact various applications when one needs to consider up to three standard deviations, thus covering more than 95% of cases. The second main finding is the need of new decay heat measurements and validation for cases corresponding to more modern fuel characteristics: higher initial enrichment, higher average burnup, as well as shorter and longer cooling time. Similar needs exist for fuel types without public experimental data, such as MOX, VVER, or CANDU fuels. A third outcome is related to SNF assemblies for which no direct validation can be performed, representing the vast majority of cases (due to the large number of SNF assemblies currently stored, or too short or too long cooling periods of interest). A few solutions are possible, depending on the application. For the final repository, systematic measurements of quantities related to decay heat can be performed, such as neutron or gamma emission. This would provide indications of the SNF decay heat at the time of encapsulation. For other applications (short- or long-term cooling), the community would benefit from applying consistent and accepted recommendations on calculation methods, for both decay heat and uncertainties. This would improve the understanding of the results and make comparisons easier.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗
DOE OSTI2025

A bilevel multistage stochastic self-scheduling model with indivisibilities for trading in the continuous intraday electricity market

In this paper, we study the profit maximization problem of a virtual power plant trading in the continuous intraday electricity market. Our virtual power plant model is compatible with renewable, and thermal assets, covering a range of virtual power plants currently participating in energy markets. We model the trading problem as a bilevel multistage stochastic program. The upper level of the problem accounts for the profit maximization of the virtual power plant with explicit modeling of the technical constraints of the operational status of the thermal power plant including minimum start-up and shut-down times, ramp-up and ramp-down rates, and minimum generation level. The upper level also decides which continuous and indivisible (fill-or-kill) orders are submitted to the market. The lower-level problem accounts for the clearing of the continuous intraday market, i.e., matching of buy and sell orders. Because of the presence of fill-or-kill orders, the lower-level problem is mixed-integer, which prevents its direct conversion to a single-level problem using duality. In order to solve this challenging problem, we develop a convex-hull extended formulation for the lower-level problem, apply duality theory to obtain a single-level stochastic equivalent formulation, and employ McCormick envelopes to turn the problem into a multistage stochastic mixed-integer linear problem, which we solve using the stochastic dual dynamic integer programming algorithm. We conduct numerical experiments and analyze the optimal trading behavior of a virtual power plant trading in an ideal continuous market without arbitrage.

Bilevel multistage stochastic programming problem↗