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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High Temperature Anode Recycle Blower for Solid Oxide Fuel Cell, Phase II (Final Report)

Broad commercialization of solid oxide fuel cells (SOFCs) requires anode offgas recycle blowers (ARCB) that are specifically designed for handling the challenging operating conditions presented by the SOFC process gases. Otherwise, they can be susceptible to frequent maintenance, low reliability, and short life. This report presents details of a DOE-funded Phase II effort conducted by Mohawk Innovative Technology, Inc. (MiTi®) for the development and testing of an oil-free, low cost, high-temperature centrifugal ARCB based on compliant foil bearing (CFB) technology for support of a 100 kW solid oxide fuel cell power plant. This Phase II builds on the results of a successful Phase I development project that resulted in the demonstration of a low TRL-6 prototype, shown in Figure 1. This Phase II final report presents design improvements over the Phase I prototype, presents the assembled test ARCBs, and discusses the advantages of this novel technology, particularly its long life and maintenance-free operation, which are derived from the use of CFBs. Also included are preliminary techno-economic analysis considerations for cost-effective deployment of the technology. The specific objectives of this project, as stated in the statement of program objectives (SOPO) were 1) to follow the methodology of design for manufacturing (or manufacturability) and assembly for implementing improvements identified as part of the Phase I effort with the purpose of reducing cost, enabling mass production, and facilitating the commercialization of a revised ARCB design, and 2) to fabricate four complete ARCB units based on the revised design and demonstrating their performance in both a laboratory setting and in an actual SOFC power plant. Execution of this SOPO would be supported by a number of technical tasks resulting in the fabrication and testing of the prototypes. To this end, MiTi continued the teaming relationship started during Phase I of the program with subcontracting partner FuelCell Energy, Inc. (FCE), which integrated (under a parallel effort funded by DOE Award DE-FE0026199) a modular 200 kWe SOFC power plant. MiTi and FCE coordinated to ultimately incorporate one of MiTi’s ARCB prototypes into one of the 100 kWe SOFC Modular Power Blocks (MPB) that constitute the core of FCE’s SOFC power plant for in-situ long-duration testing. Additionally, MiTi would explore the scalability and extendibility of the technology to other applications, as well as conduct a basic techno-economic analysis.

03 NATURAL GAS↗
DOE OSTI2024

A More Precise Measurement of the Radius of PSR J0740+6620 Using Updated NICER Data

PSR J0740+6620 is the neutron star with the highest precisely determined mass, inferred from radio observations to be 2.08 ± 0.07 M ⊙ . Measurements of its radius therefore hold promise to constrain the properties of the cold, catalyzed, high-density matter in neutron star cores. Previously, Miller et al. and Riley et al. reported measurements of the radius of PSR J0740+6620 based on Neutron Star Interior Composition Explorer (NICER) observations accumulated through 2020 April 17, and an exploratory analysis utilizing NICER background estimates and a data set accumulated through 2021 December 28 was presented in Salmi et al. Here we report an updated radius measurement, derived by fitting models of X-ray emission from the neutron star surface to NICER data accumulated through 2022 April 21, totaling ~1.1 Ms additional exposure compared to the data set analyzed in Miller et al. and Riley et al., and to data from XMM-Newton observations. We find that the equatorial circumferential radius of PSR J0740+6620 is ${12.92}_{-1.13}^{+2.09}$ km (68% credibility), a fractional uncertainty ~83% the width of that reported in Miller et al., in line with statistical expectations given the additional data. If we were to require the radius to be less than 16 km, as was done in Salmi et al., then our 68% credible region would become $R={12.76}_{-1.02}^{+1.49}$ km, which is close to the headline result of Salmi et al. Our updated measurements, along with other laboratory and astrophysical constraints, imply a slightly softer equation of state than that inferred from our previous measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The XMM Cluster Survey analysis of the SDSS DR8 redMaPPer catalogue: implications for scatter, selection bias, and isotropy in cluster scaling relations

ABSTRACT In this paper, we present the X-ray analysis of Sloan Digital Sky Survey DR8 redMaPPer (SDSSRM) clusters using data products from the XMM Cluster Survey (XCS). In total, 1189 SDSSRM clusters fall within the XMM–Newton footprint. This has yielded 456 confirmed detections accompanied by X-ray luminosity (LX) measurements. Of these clusters, 381 have an associated X-ray temperature measurement (TX). This represents one of the largest samples of coherently derived cluster TX values to date. Our analysis of the X-ray observable to richness scaling relations has demonstrated that scatter in the TX–λ relation is roughly a third of that in the LX–λ relation, and that the LX–λ scatter is intrinsic, i.e. will not be significantly reduced with larger sample sizes. Analysis of the scaling relation between LX and TX has shown that the fits are sensitive to the selection method of the sample, i.e. whether the sample is made up of clusters detected ‘serendipitously’ compared to those deliberately targeted by XMM. These differences are also seen in the LX–λ relation and, to a lesser extent, in the TX–λ relation. Exclusion of the emission from the cluster core does not make a significant impact on the findings. A combination of selection biases is a likely, but yet unproven, reason for these differences. Finally, we have also used our data to probe recent claims of anisotropy in the LX–TX relation across the sky. We find no evidence of anistropy, but stress this may be masked in our analysis by the incomplete declination coverage of the SDSS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Portable chemical detection platform for on-site monitoring of odorant levels in natural gas

The adequate odorization of natural gas is critical to identify gas leaks and to reduce accidents. To ensure odorization, natural gas utility companies collect samples to be processed at core facilities or a trained human technician smells a diluted natural gas sample. In this work, we report a detection platform that addresses the lack of mobile solutions capable of providing quantitative analysis of mercaptans, a class of compounds used to odorize natural gas. Detailed description of the platform hardware and software components is provided. Designed to be portable, the platform hardware facilitates extraction of mercaptans from natural gas, separation of individual mercaptan species, and quantification of odorant concentration, with results reported at point-of-sampling. The software was developed to accommodate skilled users as well as minimally trained operators. Detection and quantification of six commonly used mercaptan compounds (ethyl mercaptan, dimethyl sulfide, n-propylmercaptan, isopropyl mercaptan, tert–butyl mercaptan, and tetrahydrothiophene) at typical odorizing concentrations of 0.1–5 ppm was performed using the device. We demonstrate the potential of this technology to ensure natural gas odorizing concentrations throughout distribution systems.

03 NATURAL GAS↗
DOE OSTI2026

Quantitative SANS and multi-model analysis of spacer-dependent micellization of urea-based gemini surfactants

The micellization behavior of urea-based cationic gemini surfactants was investigated using small-angle neutron scattering (SANS) with multi-model form factor analysis. A homologous series of surfactants with urea group included in the hydrophobic tail and polymethylene spacers consisting of two to ten methylene units was analyzed using three form factor models: a core–shell ellipsoid and two variants of homogeneous ellipsoids. The results from all models show a consistent trend of the micelle structures, confirming that the spacer length critically influences micellar geometry, aggregation number, and hydration. The surfactant with four CH 2 groups in the spacer formed the largest micelles with the highest aggregation number, while longer spacers led to progressively smaller, more compact aggregates. The shell hydration—quantified as the volume fraction of heavy water within the hydrophilic region—decreased systematically with increasing spacer length due to enhanced hydrophobicity of the headgroup-spacer region. Intermicellar interactions, modeled as screened Coulomb interaction using the rescaled mean spherical approximation (RMSA), revealed the strongest electrostatic repulsion for the case of four methylene groups in the spacer, corresponding to the highest micellar charge and largest interparticle spacing. The observed spacer-dependent trends were robust across all modeling approaches, demonstrating that the spacer length serves as a key structural determinant of self-assembly in this type of urea-based gemini systems. These findings provide insight into the design of gemini surfactants with tailored aggregation behavior for applications in drug delivery, nanostructure templating, and solubilization technologies.

Core–shell ellipsoid model↗
DOE OSTI2020

TChem 2.0

The TChem toolkit is an object-oriented C++ software library that enables numerical simulations using complex chemistry and facilitates the analysis of detailed kinetic models. The toolkit provides capabilities for thermodynamic properties and gas-phase and surface chemistry. The computations rely on the Kokkos framework for parallel execution on many-core and GPU-based platforms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2752 O

Kim, Kyungjoo↗
DOE OSTI2026

Consist v0.1.0

A Python library for provenance tracking, intelligent caching, and data virtualization in scientific simulation workflows. It automatically records code, configuration, and input data to skip redundant computations and enables querying results across many runs without manual bookkeeping. Designed to support multi-model simulation workflows like the BEAM CORE toolset at LBL, but designed to be extensible to a wide range of research workflows. Combines lineage tracking features as provided by OpenLineage with deterministic hashing like SnakeMake, and adds powerful analysis tools on model outputs.

Needell, Zachary [Lawrence Berkeley National Labor↗
DOE OSTI2022

Approach to Analyzing VTR Core Performance Sensitivities to Fuel Manufacturing Uncertainties and Application to Fuel Slug Diameter

This report documents the initial effort to characterize sensitivity of VTR core performance to fuel manufacturing uncertainties. The effects of variation in the as-fabricated fuel slug diameter on VTR neutronics performance are evaluated, using both high-fidelity Monte Carlo (OpenMC) and the main core design solver (DIF3D) for all cases. This work and follow-on work will inform the VTR Project’s fuel manufacturing processes and associated acceptable criteria, as well as detailed uncertainty analysis in later stages of VTR development and deployment. In addition, this work demonstrates the approach to performing such evaluations and provides a basis for reducing the scope of calculations in future sensitivity analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Synthesis and Characterization of Mesoporous Silica Nanoparticles Loaded with Pt Catalysts

Coating the catalyst with a nanoporous layer has been demonstrated to be an effective approach to improve catalyst stability. Herein, we systematically investigate two types of core-shell mesoporous silica nanoparticles with a platinum nanocatalyst using a variety of characterization methods. One of the mesoporous particles has a unique amine ring structure in the middle of a shell (Ring-mSiO 2 /Pt-5.0/SiO 2 ), and the other one has no ring structure (mSiO 2 /Pt-5.0/SiO 2 ). Brunauer–Emmett–Teller/Barrett–Joyner–Halenda (BET/BJH) presented a similar surface area for both particles, and the pore size was 2.4 nm. Ultra-Small-Angle X-ray Scattering (USAXS)/ Small-Angle X-ray Scattering (SAXS) showed the size of mSiO 2 /Pt-5.0/SiO 2 and Ring-mSiO 2 /Pt-5.0/SiO 2 were 420 nm and 272 nm, respectively. It also showed that the ring structure was 30 nm above the silica core. Using high-resolution Transmission Electron Microscopy (TEM), it was found that the platinum nanoparticles are loaded evenly on the surface of the silica. In situ SAXS heating experiments and Thermogravimetric Analysis (TGA) indicated that the mSiO 2 /Pt-5.0/SiO 2 were more stable during the high temperature, while the Ring-mSiO 2 /Pt-5.0/SiO 2 had more change in the particle.

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

Xarray Climate Data Analysis Tools

xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an "open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.

Vo, Tom↗
DOE OSTI2026

Satellite Metallicity Enhancement I: Suppressed Star Formation, Stellar Mass Loss, and Enriched Inflow of DESI and EAGLE Galaxies around Massive Clusters

Environmental effects are a primary driver of elevated gas-phase metallicities in galaxies around massive clusters, but the underlying physical mechanisms for this satellite metallicity enhancement (SME) are still unclear. Using the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, we present the first measurement of the average SME as a function of projected cluster-centric distance. The resulting profile reveals three distinct regimes: a steep decline from the cluster center, a plateau near the cluster boundary, and an extended downturn across several cluster radii. Remarkably, the complex shape and amplitude of this observed SME profile are successfully reproduced in the EAGLE cosmological simulation. Drawing insights from EAGLE, we develop a novel satellite chemical evolution model to decompose the observed SME into physical contributions from suppressed star formation, stellar mass loss, and enriched gas inflow. Our analysis shows that continuous accretion of enriched intracluster medium dominates the SME plateau within the cluster virial radius, while mass loss and quenching jointly drive the rapid metallicity decline in the cluster core. Our method disentangles the impacts of three environmental processes on galactic chemical enrichment in the cosmic web, providing a powerful framework for understanding cluster galaxy evolution with current and future spectroscopic surveys.

Lin, Yuanye [Shanghai Jiao Tong U.; Shanghai Jiaot↗
DOE OSTI2023

CNRS Molten Salt Reactor Benchmark Analysis Using Griffin-Pronghorn Coupled Multi-physics Code System

Molten salt reactors (MSRs) with flowing fuel have the unique feature of utilizing the fuel salt for heat generation and extraction at the same time, since the fuel salt is circulating through the whole primary loop. This movement of fuel salt results in a partial decay of the delayed neutron precursors (DNPs) outside the core and the corresponding redistribution of the DNPs in the active region of the core. To capture this effect, neutronics and thermal-hydraulics (T/H) codes need to be able to handle the movement of DNPs and their decay [1, 2]. Idaho National Laboratory (INL) is actively working on developing the neutronics and T/H codes to model the MSRs with flowing fuel. As one of the efforts, the neutronics code Griffin [3] and the T/H code Pronghorn [4] that are built upon the MOOSE framework [5] have been extended to handle the flowing fuel involving the drift of DNPs, and this capability is being tested and verified with MSR benchmark problems including the CNRS benchmark problem [6]. Additionally, a multi-physics analysis of the molten salt reactor experiment (MSRE) is being conducted to verify and validate the codes against available experimental data [7]. This work presents the analysis of the CNRS benchmark problem using the Griffin-Pronghorn coupled multi-physics code system of INL. Both steady-state and transient problems are analyzed, and the results are compared with those of other participants presented in [6]. The following section provides a description of the benchmark, along with input parameters and observables for each step. Then, the results for each step are presented in comparison with other participants’ results, followed by summary and conclusion.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Analysis of near-field and far-field aerosol dispersion for microreactors

The current paper presents a simulation-based analysis of aerosol dispersion in the near-field and far-field of a generic, conceptual microreactor operating at pressures close to the ambient pressure; therefore, in the event of an accident that causes radionuclide leakage from the microreactor containment, the radionuclide particles are less likely to travel too far from the reactor, as opposed to conventional reactors. Accordingly, the presented work provides estimates of average and 95-percentile values of the relative effluent concentration. A parametric study is then performed to narrow down the parameters which affect the aerosol dispersion characteristics most significantly. Simulations were performed in the computer code ARCON96, and the parameters found to affect aerosol dispersion characteristics are the atmospheric stability class, and the distance between the release point and the receptor. It is recommended that the computer code RADTRAD be used to calculate actual dosage over distance, using the outputs from ARCON96 as inputs, along with reactor-specific core term inventories. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Computing Bottleneck Structures at Scale for High-Precision Network Performance Analysis

The Theory of Bottleneck Structures is a recently-developed framework for studying the performance of data networks. It describes how local perturbations in one part of the network propagate and interact with others. This framework is a powerful analytical tool that allows network operators to make accurate predictions about network behavior and thereby optimize performance. Previous work implemented a software package for bottleneck structure analysis, but applied it only to toy examples. In this work, we introduce the first software package capable of scaling bottleneck structure analysis to production-size networks. Here, we benchmark our system using logs from ESnet, the Department of Energy's high-performance data network that connects research institutions in the U.S. Using the previously published tool as a baseline, we demonstrate that our system achieves vastly improved performance, constructing the bottleneck structure graphs in 0.21 s and calculating link derivatives in 0.09 s on average. We also study the asymptotic complexity of our core algorithms, demonstrating good scaling properties and strong agreement with theoretical bounds. These results indicate that our new software package can maintain its fast performance when applied to even larger networks. They also show that our software is efficient enough to analyze rapidly changing networks in real time. Overall, we demonstrate the feasibility of applying bottleneck structure analysis to solve practical problems in large, real-world data networks.

benchmark↗
DOE OSTI2022

Neutronic design and fuel cycle analysis of a fluoride salt-cooled High Temperature Reactor (FHR)

The Fluoride salt-cooled High temperature Reactor (FHR) is a new Gen IV reactor concept that can operate under near atmospheric pressure circumstances and further enhance the inherent safety. In this study, an FHR core design with 165 megawatts of thermal output (MWth) is proposed. The reactor core employs tri-structural-isotropic (TRISO) particle fuel within prismatic graphite blocks as the basic fuel form, FLiBe (2 {sup 7}LiF-BeF{sub 2}) as the primary coolant, and a three-batch fuel cycle scheme. Sensitivity analyses on various parameters were performed to optimize the cycle length and neutronic parameters. The fuel cycle of this core design was evaluated in detail from 4 aspects: cycle length, power peaking factor (PPF), discharge burnup, and temperature coefficient. It was found that larger fuel channel pitch (FCP) would have a relatively harder neutron spectrum, and yield relatively longer cycle length, lower, better fuel temperature coefficient (FTC), and moderator temperature coefficient (MTC). In addition, burnable poison (BP), Er{sub 2}O{sub 3}, can effectively reduce PPF, hold down the multiplication factor, and more importantly it can improve the MTC. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

3D Bragg Coherent Diffraction Imaging of Extended Nanowires: Defect Formation in Highly Strained InGaAs Quantum Wells

InGaAs quantum wells embedded in GaAs nanowires can serve as compact near-infrared emitters for direct integration onto Si complementary metal oxide semiconductor technology. While the core–shell geometry in principle allows for a greater tuning of composition and emission, especially farther into the infrared, the practical limits of elastic strain accommodation in quantum wells on multifaceted nanowires have not been established. One barrier to progress is the difficulty of directly comparing the emission characteristics and the precise microstructure of a single nanowire. Here, in this study, we report an approach to correlating quantum well morphology, strain, defects, and emission to understand the limits of elastic strain accommodation in nanowire quantum wells specific to their geometry. We realize full 3D Bragg coherent diffraction imaging (BCDI) of intact quantum wells on vertically oriented epitaxial nanowires, which enables direct correlation with single-nanowire photoluminescence. By growing In 0.2 Ga 0.8 As quantum wells of distinct thicknesses on different facets of the same nanowire, we identified the critical thickness at which defects are nucleated. A correlation with a traditional transmission electron microscopy analysis confirms that BCDI can image the extended structure of defects. Finite element simulations of electron and hole states explain the emission characteristics arising from strained and partially relaxed regions. This approach, imaging the 3D strain and microstructure of intact nanowire core–shell structures with application-relevant dimensions, can aid the development of predictive models that enable the design of new compact infrared emitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗
DOE OSTI2025

Q2 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q2: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $\circ$ Run CESOL with BOUT++/Hermes-3 and immersed boundary condition to directly map to wall: • Run BOUT++/Hermes-3 through the IPS workflow to find radial particle and energy diffusivities to match either the Eich or the physics-based scaling of the SOL heat flux width, and • Expand source of first wall heat flux to include charged particles, neutrals, and radiation from the core+edge. 2. Generate medium fidelity parametrized CAD: $\circ$ Develop the TRACER tool to read an existing CAD, regenerate the geometry based on vertex location and connectivity information, define vertex translation and parameters needed for scaling the CAD, and $\circ$ Utilize the FreeGS code to determine CAT PF coil placement, including minimizing the number of coils, coil current, and electromechanical stresses. 3. Utilize plasma loading for engineering analysis: $\circ$ Couple the plasma loading to input for OpenFOAM and demonstrate initial test of thermal analysis of CAT first wall loading with typical DCLL blanket component cooling boundary conditions. 4. Demonstrate nuclear analysis: $\circ$ Apply initial analysis of tritium transport in DCLL blanket by evaluating spatially resolved tritium generation rates, tritium diffusion and convection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗