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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 OSTI2026

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI↗
DOE OSTI2024

Precision-controlled ultrafast electron microscope platforms. A case study: Multiple-order coherent phonon dynamics in 1T-TaSe2 probed at 50 fs–10 fm scales

We report on the first detailed beam tests attesting the fundamental principle behind the development of high-current-efficiency ultrafast electron microscope systems where a radio frequency (RF) cavity is incorporated as a condenser lens in the beam delivery system. To allow for the experiment to be carried out with a sufficient resolution to probe the performance at the emittance floor, a new cascade loop RF controller system is developed to reduce the RF noise floor. Temporal resolution at 50 fs in full-width-at-half-maximum and detection sensitivity better than 1% are demonstrated on exfoliated 1T-TaSe2 system under a moderate repetition rate. To benchmark the performance, multi-terahertz edge-mode coherent phonon excitation is employed as the standard candle. The high temporal resolution and the significant visibility to very low dynamical contrast in diffraction signals via high-precision phase-space manipulation give strong support to the working principle for the new high-brightness femtosecond electron microscope systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimal Realization of Yang–Baxter Gate on Quantum Computers

Quantum computers provide a promising method to study the dynamics of many-body systems beyond classical simulation. On the other hand, the analytical methods developed and results obtained from the integrable systems provide deep insights on the many-body system. Quantum simulation of the integrable system not only provides a valid benchmark for quantum computers but is also the first step in studying integrable-breaking systems. The building block for the simulation of an integrable system is the Yang–Baxter gate. It is vital to know how to optimally realize the Yang–Baxter gates on quantum computers. Based on the geometric picture of the Yang–Baxter gates, the optimal realizations of two types of Yang–Baxter gates with a minimal number of controlled NOT (CNOT) or gates are presented. It is also shown how to systematically realize the Yang–Baxter gates via the pulse control. The different realizations on IBM quantum computers are tested and compared. It is found that the pulse realizations of the Yang–Baxter gates always have a higher gate fidelity compared to the optimal CNOT or realizations. On the basis of the above optimal realizations, the simulation of the Yang–Baxter equation on quantum computers is demonstrated. Finally, these results provide a guideline and standard for further experimental studies based on the Yang–Baxter gate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Model Development and Analysis of a High-Fidelity Neutron Transport Sensor: The Quadrupole Detector Concept for Measurement of the Neutron Flux Gradient

Accurate reconstruction of the neutron flux distribution within a reactor core is essential for safe and efficient reactor operation. Traditional power shape synthesis in Light Water Reactors relies on hundreds of in-core detectors. However, this approach becomes impractical for Advanced Reactors and Microreactors due to limited space and harsh environments. To address this challenge, we propose a data-driven methodology that combines high-fidelity modeling with real-time ex-core sensor measurements, enabling the reconstruction of core power distribution while minimizing the reliance on intrusive in-core instrumentation. This project began in FY24 and achieved two initial milestones: (1) the definition of a three-year development plan for a Digital Twin framework and (2) the development of high-fidelity neutronics models of the Purdue University Reactor One (PUR-1) using both MCNP6 and OpenMC. The PUR-1 reactor, a zero-power facility, was selected due to its suitability for neutronics-focused modeling and the availability of experimental data for validation. Both models were benchmarked using neutron flux measurements obtained from irradiated gold foils, which were strategically placed within the core during a dedicated campaign in July 2024. This report marks the continuation and completion of those foundational tasks. The OpenMC model has been refined (improved geometric accuracy, expanded cross-section libraries, and refined sampling) and validated using additional experimental data. An updated sensor design—based on quadrupole configuration—was designed to measure both ex-core flux and its spatial gradient. These measurements will serve as inputs to a neural network-based reconstruction algorithm. Finally, the methodology was demonstrated on a two-dimensional test case representative of the heterogeneous material composition of the PUR-1 reactor core. A neural network implementation of the Kirchhoff-Helmholtz integral equation was employed to solve the boundary value problem using peripheral sensor measurements. The preliminary results confirm the strong potential of the proposed approach for accurate and minimally invasive neutron flux reconstruction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Effects of Chlorine Capture and a Proposed Density Law on the Reactivity of Plutonium Solution Systems

During fissionable material processing, all normal and credible abnormal conditions must remain safely subcritical. Nuclear Criticality Safety (NCS) uses a number of methods to determine subcriticality, one of which is the use of neutron transport codes such as MCNP6. In order to create models for use with MCNP6, both the geometry and materials in fissionable material processes must be known, or assumptions must be made and quantified for the impact to bias. One of the systems with a significant amount of bias due to material modeling assumptions is in the area of aqueous plutonium processing. These solutions are typically plutonium nitrate solutions or plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution and there is no current predictive capability approved for use at Los Alamos National Laboratory (LANL) for modeling them. This research is currently underway to fill the gap and develop an algorithm for use with MCNP6 to model the density of plutonium chloride solutions. The method is to be validated with experimental data for density, and also validated with critical experiments using MCNP6. Note that the Chlorine Worth Study (CWS) was performed in December 2021 to help bridge the gap in chlorine data for critical experiments, and is currently awaiting International Criticality Safety Benchmark Evaluation Project (ICSBEP) review. This study was performed by LANL at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site (NNSS). Additional information regarding this experiment may currently be found in LA-UR- 22-29180. Additionally, the Chemistry-Actinide Analytical Chemistry (C-AAC) at LANL has performed a number of solution density measurements for PuCl 3 -HC 1 -H 2 O, allowing for such data be used to create a semi-empirical density via the Pitzer method. The published dataset for the measurements is documented in LA-UR-22-25454. This method has already been tested successfully for aqueous plutonium nitrate solutions in SCALE. Current solution density measurements exist of plutonium concentrations of 0-~142g/L, all at 2M HC1, at temperatures 20-40°C. Additional data was taken for HC1-corrected density values, which essentially mimics the data for a pure PuCl x -water solution. The calculations in this report aim to support the current research by demonstrating the difference in system reactivity for the current modeling method when compared to the new proposed modeling with a density law implementation, which is being written as a Python tool to be used with MCNP6.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Too big, too small, or just right? A benchmark assessment of density functional theory for predicting the spatial extent of the electron density of small chemical systems

Multipole moments are the first-order responses of the energy to spatial derivatives of the electric field strength. The quality of density functional theory prediction of molecular multipole moments thus characterizes errors in modeling the electron density itself, as well as the performance in describing molecules interacting with external electric fields. However, only the lowest non-zero moment is translationally invariant, making the higher-order moments origin-dependent. Therefore, instead of using the 3 × 3 quadrupole moment matrix, we utilize the translationally invariant 3 × 3 matrix of second cumulants (or spatial variances) of the electron density as the quantity of interest (denoted by K). The principal components of K are the square of the spatial extent of the electron density along each axis. A benchmark dataset of the principal components of K for 100 small molecules at the coupled cluster singles and doubles with perturbative triples at the complete basis set limit is developed, resulting in 213 independent K components. The performance of 47 popular and recent density functionals is assessed against this Var213 dataset. Several functionals, especially double hybrids, and also SCAN and SCAN0 predict reliable second cumulants, although some modern, empirically parameterized functionals yield more disappointing performance. The H, Li, and Be atoms, in particular, are challenging for nearly all methods, indicating that future functional development could benefit from the inclusion of their density information in training or testing protocols.

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

Improved melt model for power flow

Accelerators that drive z-pinch experiments transport current densities in excess of 1 MA/cm 2 in order to melt or ionize the target and implode it on axis. These high current densities stress the transmission lines upstream from the target, where rapid electrode heating causes plasma formation, melt, and possibly vaporization. These plasmas negatively impact accelerator efficiency by diverting some portion of the current away from the target, referred to as “current loss”. Simulations that are able to reproduce this behavior may be applied to improving the efficiency of existing accelerators and to designing systems operating at ever higher current densities. The relativistic particle-in-cell code CHICAGO ® is the primary code for modeling power flow on Sandia National Laboratories’ Z accelerator. We report here on new algorithms that incorporate vaporization and melt into the standard power-flow simulation framework. Taking a hybrid approach, the CHICAGO® kinetic/multi-fluid treatment has been expanded to include vaporization while the quasi-neutral equation-of-motion has been updated for melt at high current-densities. For vaporization, a new one-dimensional substrate model provides a more accurate calculation of electrode thermal, mass, and magnetic field diffusion as well as a means of emitting absorbed contaminants and vaporized metal ions. A quasi-fluid model has been implemented expressly to mimic the motion of imploding liners for accurate inductance histories. For melt, a multi-ion Hall-MHD option has been implemented and benchmarked against Alegra MHD. This new model is described with sufficient detail to reproduce these algorithms in any hybrid kinetic code. Physics results from the new code are also presented. A CHICAGO ® Hall-MHD simulation of a radial transmission line demonstrates that Hall physics, not included in Alegra, has no significant impact on the diffusion of electrode material. When surface contaminant desorption is mocked in as a hydrogen surface plasma, both the surface and bulk-material plasmas largely compress under the influence of the j × B force. Similar results are seen in Alegra, which also shows magnetic and material diffusion scaling with peak current. Test vaporization simulations using MagLIF and a power-flow experimental geometry show Fe + ions diffuse only a few hundred µm from the electrodes, so present models of Z power flow remain valid.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Ultra-High Efficiency and Stable All-Perovskite Tandem Solar Cells

In the project period, the research team has fabricated more than 6,000 single-junction wide-bandgap (wide-E g ) and low-bandgap (low-E g ) perovskite solar cells (PSCs) and more than 2,000 all-perovskite tandem solar cells (APTSCs). The best-performing wide-E g and low-E g PSCs and APTSCs showed PCEs greater than 19%, 23%, and 30%, respectively. The average PCEs for wide-E g and low-E g PSCs and APTSCs fabricated by the benchmark processes are (18.5 ± 0.4)%, (21.9 ± 0.8)%, and (26.8 ± 2.1)%, respectively. We have demonstrated APTSCs with T 80 lifetime of more than 1,000 h, which were measured by maximum power point tracking (MPPT) under one sun operation in the air. The team has also utilized various advanced characterization techniques to study the optical and electrical properties of wide-E g and low-E g perovskite materials and devices, developing a better understanding of the unique working principle and degradation mechanism of APTSCs. The team has met most GNG decision criteria except for the stability goal of APTSCs under 85 °C/85 RH accelerated lifetime test (ALT). The shortfall of the device ALT stability is mainly limited by the intrinsic instability of Sn-Pb perovskites under illumination at elevated temperatures. The team discussed with stakeholders in the PV academic and industry about these durability concerns and concluded that this is the major technical barrier preventing the market entry of APTSCs. Future fundamental study and R&D work are needed to advance this promising technology.

14 SOLAR ENERGY↗
DOE OSTI2020

High-efficiency, air-stable manganese–iron oxide nanoparticle-pigmented solar selective absorber coatings toward concentrating solar power systems operating at 750 °C

Solar selective absorber coating with long-term thermal stability at high temperatures ≥750 °C in air is an important component to reduce the levelized cost of energy (LCOE) of concentrating solar power (CSP) systems toward 50% power efficiency and dispatchable solar electricity. Conventionally, solar spectral selectivity requires multilayer-interference coatings implemented by stringently controlled vacuum deposition, and these coatings degrade significantly at >700 °C in air. Herein, we established a quantitative design approach and demonstrated a proof-of-concept air-stable, manganese–iron oxide nanoparticle (NP)-pigmented solar selective coatings with a high solar absorptance of ~93%, a relatively low thermal emittance of ~52%, and an optical-to-thermal energy conversion efficiency >89% under 1,000× solar concentration at 750 °C toward Generation 3 CSP systems. These coatings demonstrate spectral selectivity using cost-effective spray coating approach, a notable improvement over conventional vacuum-deposited, multilayer solar selective coatings for low-cost, high-efficiency solar thermal receivers. In contrast to the thermal degradation of spectrally non-selective benchmark Pyromark 2500 coatings at 750 °C in air, the solar absorptance of the MnFe 2 O 4 -pigmented coatings on stainless steel 310 (SS 310) substrates is increased to ~92.9% and the optical-to-thermal energy conversion efficiency is improved to 89.7% after serving at 750 °C in air for 700 h. X-ray diffraction results reveal that this improvement is due to the transformation of MnFe 2 O 4 NPs into more thermodynamically stable, non-stoichiometric manganese-rich manganese ferrite and iron-rich manganese–iron oxide phases after 500 h aging at 750 °C. For >1,000 h-endurance testing at 750 °C in air and the subsequent 19 day-night thermal cycling between 750 °C (12 h/cycle) and 25 °C (12 h/cycle) on SS 310 substrates, the thermal degradation is mainly due to the CrO x microflake formation from SS 310 substrates rather than the coatings, which can be suppressed by preoxidizing the surface of SS 310. With lower emittance matrix material and further optimization of pigment NP stoichiometry, concentration, and coating thickness, it is promising to achieve an optimized thermal efficiency ≥92.5% with long-term thermal stability at 750 °C for Generation 3 CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Divertor heat load estimates on NSTX and DIII-D using new and open-source 2D inversion analysis code

A thermography inversion algorithm has been developed in the open-source Python-based computer code, HYPERION, to calculate the heat flux incident on plasma-facing components (PFCs) in axisymmetric tokamaks. The chosen mesh size at the surface significantly affects the calculated transient heat flux results. The calculated transient heat flux will exceed the real value when the mesh size tends to zero but will underestimate the real value when the mesh size is large. A criterion for determining the appropriate mesh size for the transient heat flux calculation will be discussed. The numerical scheme for HYPERION uses a 2D fully implicit finite-difference approach, allowing temperature-dependent thermal properties of PFC materials. The inversion algorithm is benchmarked against established heat flux calculation codes, TACO and THEODOR, based on thermography data from NSTX and DIII-D respectively. The primary benefits of HYPERION compared to TACO and THEODOR are that it is open-source and it allows for the optimization of mesh thickness along the substrate. The algorithm also accounts for the thermal properties of thin surface layers that characteristically form on PFCs due to plasma-material interactions. The agreement between HYPERION and THEODOR is excellent, as the percent difference between the codes is ~5% on average in the case of the DIII-D data for moderate to high heat flux. Verification tests with TACO show slightly higher average percent differences of 8% and 12%. In using HYPERION to study filaments in heat flux, the initial results indicate that small ELMs filaments significantly broaden the divertor heat flux, and decrease divertor peak flux. Compared to the inter-ELM, the small ELM filaments decrease the divertor peak surface temperature. With intermittent divertor filaments, the divertor heat flux width is comparable with that found in L-mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Improving deep learning-based protein distance prediction in CASP14

Abstract Motivation Accurate prediction of residue–residue distances is important for protein structure prediction. We developed several protein distance predictors based on a deep learning distance prediction method and blindly tested them in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The prediction method uses deep residual neural networks with the channel-wise attention mechanism to classify the distance between every two residues into multiple distance intervals. The input features for the deep learning method include co-evolutionary features as well as other sequence-based features derived from multiple sequence alignments (MSAs). Three alignment methods are used with multiple protein sequence/profile databases to generate MSAs for input feature generation. Based on different configurations and training strategies of the deep learning method, five MULTICOM distance predictors were created to participate in the CASP14 experiment. Results Benchmarked on 37 hard CASP14 domains, the best performing MULTICOM predictor is ranked 5th out of 30 automated CASP14 distance prediction servers in terms of precision of top L/5 long-range contact predictions [i.e. classifying distances between two residues into two categories: in contact (<8 Angstrom) and not in contact otherwise] and performs better than the best CASP13 distance prediction method. The best performing MULTICOM predictor is also ranked 6th among automated server predictors in classifying inter-residue distances into 10 distance intervals defined by CASP14 according to the precision of distance classification. The results show that the quality and depth of MSAs depend on alignment methods and sequence databases and have a significant impact on the accuracy of distance prediction. Using larger training datasets and multiple complementary features improves prediction accuracy. However, the number of effective sequences in MSAs is only a weak indicator of the quality of MSAs and the accuracy of predicted distance maps. In contrast, there is a strong correlation between the accuracy of contact/distance predictions and the average probability of the predicted contacts, which can therefore be more effectively used to estimate the confidence of distance predictions and select predicted distance maps. Availability and implementation The software package, source code and data of DeepDist2 are freely available at https://github.com/multicom-toolbox/deepdist and https://zenodo.org/record/4712084#.YIIM13VKhQM. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

In-Transit Data Transport Strategies for Coupled AI-Simulation Workflow Patterns

Coupled AI-Simulation workflows are becoming the major workloads for HPC facilities, and their increasing complexity necessitates new tools for performance analysis and prototyping of new in-situ workflows. We present SimAI-Bench, a tool designed to both prototype and evaluate these coupled workflows. In this paper, we use SimAI-Bench to benchmark the data transport performance of two common patterns on the Aurora supercomputer: a one-to-one workflow with co-located simulation and AI training instances, and a many-to-one workflow where a single AI model is trained from an ensemble of simulations. For the one-to-one pattern, our analysis shows that node-local and DragonHPC data staging strategies provide excellent performance compared Redis and Lustre file system. For the many-to-one pattern, we find that data transport becomes a dominant bottleneck as the ensemble size grows. Our evaluation reveals that file system is the optimal solution among the tested strategies for the many-to-one pattern.

Tummalapalli, Harikrishna [Argonne National Labora↗
DOE OSTI2026

Defining Electrode-Level Metrics for Enabling Earth-Abundant, Mn-Rich Cathodes: A Technoeconomic Analysis of Experimental Materials

Manganese-rich oxides are attractive options as next-generation, earth-abundant cathodes and significant efforts are being directed toward commercial implementation. We report here an updated techno-economic analysis of the lithium- and manganese-rich (LMR) class of earth-abundant cathodes for electric vehicle applications. BatPaC modeling was used to define the cell-level metrics that must be met for these materials to be cost and energy competitive with the current commercial earth-abundant benchmark, LiFePO 4 , as well as anticipated variations such as LiMn 0.8 Fe 0.2 PO 4 . The model was used to evaluate a high-performance material from the literature and subsequently define R&D targets as the likely limits of practical performance for similar LMR systems. Experimental validation and BatPaC evaluation of an advanced, cobalt-free LMR cell system was also conducted. Results show that the advanced LMR cells come within ∼5% of the defined limits and exceed the energy of LiFe(Mn)PO 4 cells at a similar cost. Excellent cycle-life, low impedance, and low impedance rise were also achieved under the conditions tested and reveal that cobalt is not necessary to achieve high-performance LMR oxides. Although the analysis conducted herein reports on LMR cell systems, the methodology and target values defined for performance metrics easily extend to the evaluation of other systems under consideration as earth-abundant options.

Chen, Jiajun [Argonne National Laboratory (ANL), A↗
DOE OSTI2020

Goldsim Modeling of Vadose Zone Transport for E-Area Naval Reactor Component Disposal Areas: Model Description and Benchmarking

This report documents the development of a GoldSim® model of flow and radionuclide transport to the water table through the Naval Reactor Components Disposal Area (NRCDA) waste disposal sites and underlying vadose zones. The model is designed to be used for Monte Carlo uncertainty analysis in support of the E-Area Performance Assessment (PA). This report describes the model and shows results obtained from benchmarking the model to best-estimate deterministic results obtained using a PORFLOW model of NRCDA vadose zone transport. The PORFLOW model is three-dimensional while the GoldSim model is a simplified one-dimensional treatment. Nevertheless, the GoldSim model was able to accurately reproduce PORFLOW results with some adjustment to the nominal dispersion coefficient and vadose zone flow area used as “tuning” parameters. An example of the results obtained comparing GoldSim and PORFLOW calculation of releases of I-129, Tc-99, C-14 and Ni-59 from waste disposal containers at the 643-26E site is shown in Figure 1 below. For all of the test cases evaluated, GoldSim predicted peak concentrations within 6% of the PORFLOW values and peak times agreed within 8% with the majority of the results in better agreement. The close agreement between the two models provides confidence that GoldSim will give results accurately reflecting the behavior of releases from the NRCDA under off-normal operating conditions for sensitivity and uncertainty analysis

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Product Consistency Test Results for the HLW HAlG Glasses

This report summarizes the chemical analysis of Product Consistency Test leachates received from Pacific Northwest National Laboratory (PNNL). The leachates are from a series of quenched simulated nuclear waste glasses designated High-Level Waste High Aluminum Glass that were designed and fabricated at PNNL. The reported data is provided to be used in the development, validation, and implementation of enhanced property/composition models for waste glass vitrification at Hanford. The elemental release for the study glasses is reported as normalized concentration NCi. NCi of several elements was computed for both the target and measured glass compositions. Several of the glasses exhibited NC B , NC Li , and/or NC Na values that were greater than the Environmental Assessment (EA) benchmark values. Several of the leachates from approved reference material (ARM) glasses included with the study glasses had elemental concentrations greater than the expected ranges. Two water blanks contained measurable amounts of Si; measurements confirmed by rerun samples. One water blank also contained a measurable amount of Na.

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

Charpy Impact Characterization of Surveillance Specimens Harvested from Palisades High Fluence A-60 Capsule

Located on the shores of Lake Michigan, the Palisades Nuclear Generating Station (PNGS) was a nuclear power plant that operated in Covert Township, Michigan. The plant had a single pressurized water reactor that produced electricity for the region. The PNGS was shut down in 2022 after more than four decades of service. The PNGS included in its surveillance program a surveillance capsule, designated A-60, containing specimens of a weld metal with nickel content of about 1.36 wt% and copper content of about 0.25 wt%. The capsule was removed from its surveillance position in early 1995 and has been resident in the spent fuel pool since that time. This capsule was irradiated to a fluence of 1.96×10 20 n/cm 2 (E>1MeV) that is equivalent for more than 150 effective full power years (EFPYs) for the US reactor pressure vessel (RPV) fleet. The material is also of special interest because of its very high nickel content and potential for development of NiMnSi (nickel-manganese-silicon) precipitates. Combination of very high fluence and very high Ni and Cu content makes the material in this capsule of great interest as benchmark for currently developing embrittlement trend curves (ETC) aiming to predict embrittlement at high fluences. Multi-year efforts by the Light Water Reactor Sustainability (LWRS) Program personnel from the Materials Research Pathway (MRP) to harvest this capsule finally succeeded in 2023. As a result, the Westinghouse Electric Company (WEC) through contract with Oak Ridge National Laboratory (ORNL) came to PNGS site, retrieved the A-60 capsule, brought it to WEC Churchill hot cell facility, opened the capsule and sent all surveillance specimens in the capsule to ORNL for future characterization by July 2023. Total of 9 tensile and 48 Charpy specimens were inventoried in the ORNL hot cells. Testing plan has been developed based on available specimens. It includes hardness, tensile, Charpy impact, Mini-CT fracture toughness testing, in-situ thermal annealing, and microstructural characterization, including Atom Probe Tomography (APT). Charpy impact testing has been completed and results are presented in this report. Moreover, negotiations with Pressurized Water Reactors Owners Group (PWROG) and Westinghouse resulted in Westinghouse donating to ORNL a piece of archive weld and base metal such that unirradiated characterization of these materials can be performed as part of this project. Comparison of measured hardening and embrittlement has been performed and data are compared to available large database.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Worldwide benchmarking of cost-effective radiometers for direct and diffuse irradiance

Solar energy projects can benefit from direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) measurements during all project phases. Several commercial measurement systems for DNI and DHI are available. Sun trackers with pyranometers and pyrheliometers can provide highly accurate measurements but are often impractical in solar energy applications. For less expensive and more robust sensors, it is often unclear which accuracy can be expected under a project site's specific atmospheric conditions. We address this challenge through our dedicated experimental comparison of relevant sensor systems (rotating shadowband irradiometer [short RSI], Delta-T SPN1, EKO MS-90, PyranoCam, Sunto CaptPro, Kipp & Zonen CSD3) at up to six sites worldwide. The RSI systems (rRMSD 3 to 8.6%, DNI; 4.8 to 7.6%, DHI) and PyranoCam (rRMSD 2.6 to 5.2%, DNI; 4.4 to 5.8%, DHI) exhibit similar error metrics and are the most accurate systems in the test. Delta-T SPN1 and EKO MS-90 (rRMSD 6.8 to 15%, DNI; 10.6 to 20.1%, DHI) but especially Kipp & Zonen CSD3 and Sunto CaptPro show significant deviations (rRMSD 17.7 to 20%, DNI; 33 to 58%, DHI). We evaluate the influence of relevant atmospheric parameters on the sensors' accuracies by a rather unique measurement setup. MS-90's DNI errors depend on DNI itself, with overestimations for low reference DNI. The deviations of SPN1's DHI and DNI measurements increase sharply in situations with high circumsolar irradiance. Also CaptPro and CSD3's increased measurement errors are related to circumsolar irradiance. For RSI and PyranoCam, only moderate influences on the measurements are identified, indicating a general applicability of these instruments.

14 SOLAR ENERGY↗
DOE OSTI2020

FAUST - Benchmark and Validation Framework [Slides]

This presentation discusses Python packages for nuclear data applications and for benchmarking. It also discusses the goals and objectives for FAUST which include providing input and output processing for different calculation codes, allowing for exchanging results between different applications and codes, running benchmarks and processing the results, automating and simplify plot and report generation, and providing a basis for developing applications useful for nuclear data evaluators. The presentation also discusses how the packages can be used both inside and outside LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗