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214 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A real-time search for Type Ia Supernovae with late-time interactions with circumstellar material in ZTF data

While it is generally accepted that Type Ia supernovae (SNe Ia) are the terminal explosions of white dwarfs (WDs), the nature of their progenitor systems and the mechanisms that lead up to these explosions remain widely debated. In rare cases, the SN ejecta interact with circumstellar material (CSM) that had previously been ejected from the progenitor system. The longer the delay between the creation of the CSM and the SN explosion, the greater the distance between the SN explosion site and the CSM and the later the onset of the interaction. The unknown distance between the CSM and SN explosion site makes it impossible to predict when the interaction will start. If the time between the SN explosion and the onset of the CSM interaction is of the order of several months to years, the SN has generally faded and it is no longer actively followed up on. This makes it even more difficult to detect the interaction while it is happening. In this work, we report on a real-time monitoring programme running between 13 November 2023 and 9 July 2024. It monitored 6914 SNe Ia for signs of late-time rebrightening using the Zwicky Transient Facility (ZTF). Flagged candidates were rapidly followed up on with photometry and spectroscopy to confirm the late-time excess and its position. We report the discovery of a ∼50 day rebrightening event in SN 2020qxz around 1200 rest-frame days after the peak of its light curve. SN 2020qxz exhibited signs of an early CSM interaction, but had faded from view over two years before its reappearance. Initial follow-up spectroscopy revealed the presence of four emission lines, while later follow-up spectroscopy showed that these had faded shortly after the end of the ZTF-detected rebrightening event. Our best match for these emission lines are H β (blueshifted by ∼5900 km s −1 ) and Ca II λ8542 , N I λ8567 , and K I λλ8763, 8767 (all blueshifted by 5100 km s −1 ; although we note that the line identifications are uncertain). This shows that catching and following up on late-time interactions as they occur can offer new clues on the nature of the progenitor systems that produce these SNe by putting constraints on the possible type of donor star. The only way to do this systematically is to use large sky surveys such as ZTF and the upcoming Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) to monitor a large sample of objects for the rare events that reappear long after the object has faded from view.

circumstellar matter↗
DOE OSTI2024

Boundary spanning increases knowledge and action on invasive species in a changing climate

Abstract Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary‐spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary‐spanning activities could support proactive, research‐informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary‐spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non‐members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non‐members and short‐term members more frequently identifying range‐shifting neonative species and their impacts on native communities as higher priorities compared to long‐term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range‐shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication : Although real‐world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary‐spanning efforts to address other global change challenges to conservation.

Evans, Annette E.↗
DOE OSTI2025

Characterization of W production during ICRF operations: experiments and modeling

For successfully heating plasma with waves in the ion cyclotron range of frequencies (ICRFs), mitigating impurity production is just as crucial as maximizing power coupling, especially in high-Z environments. ICRF can effectively deposit energy on ions, modify turbulence-driven transport, and enhance fusion reaction efficiency, but only when its power coupling has minimal impact on impurity production. To do so, one must rely on a toroidal array of at least three active elements excited with appropriate phasing and power ratio to reduce the currents induced on the antenna frame below levels critical for physical sputtering. In contrast to classic two-strap antennas, which are optimized for dipole phasing with equal power on both straps, three-strap antennas in ASDEX Upgrade (AUG)—but also four-strap antennas in JET, Alcator C-Mod, SPARC and ITER—offer the possibility to act also on the power ratio between the central and outer straps. With optimal settings, impurity production can be reduced substantially, making the ICRF compatible with the high-Z wall. This paper explores the characteristics of the AUG three-strap antennas in terms of impurity production, as well as the key role of plasma composition in this process. Numerical simulations were performed using SSWICH and Petra-M (finite element codes) to quantify impurity production and compare with experimental results. Energies of ions falling on antenna limiters (measured with probes) are well predicted by both codes. These tools are then used to further describe the source of the impurity, namely the gross erosion of tungsten from an ICRF antenna, for different plasma mixtures. Results are also compared to spectroscopy data. Ultimately, we show that deleterious effects of the ICRF on plasma surface interactions will be weaker in plasmas containing larger fractions of highly ionized heavier low-Z impurity, which is typically relevant for experiments relying on impurity seeding.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

VAIM-CFF: a variational autoencoder inverse mapper solution to Compton form factor extraction from deeply virtual exclusive reactions

We develop a new methodology for extracting Compton form factors (CFFs) from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized inverse problem solver, a variational autoencoder inverse mapper (VAIM). The VAIM-CFF framework not only allows us access to a fitted solution set possibly containing multiple solutions in the extraction of all 8 CFFs from a single cross section measurement, but also accesses the lost information contained in the forward mapping from CFFs to cross section. We investigate various assumptions and their effects on the predicted CFFs such as cross section organization, number of extracted CFFs, use of uncertainty quantification technique, and inclusion of prior physics information. We then use dimensionality reduction techniques such as principal component analysis to visualize the missing physics information tracked in the latent space of the VAIM framework. Through re-framing the extraction of CFFs as an inverse problem, we gain access to fundamental properties of the problem not comprehensible in standard fitting methodologies: exploring the limits of the information encoded in deeply virtual exclusive experiments.

Accelerator Physics↗
DOE OSTI2025

TDCOSMO - XVII. New time delays in 22 lensed quasars from optical monitoring with the ESO-VST 2.6m and MPG 2.2m telescopes

We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σ depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag – similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.Key words: methods: data analysis / surveys / distance scale

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Structural and functional analyses of SARS-CoV-2 Nsp3 and its specific interactions with the 5’ UTR of the viral genome

ABSTRACT Non-structural protein 3 (Nsp3) is the largest open reading frame encoded in the SARS-CoV-2 genome, essential for the formation of double-membrane vesicles (DMV) wherein viral RNA replication occurs. We conducted an extensive structure-function analysis of Nsp3 and determined the crystal structures of the ubiquitin-like 1 (Ubl1), nucleic acid binding (NAB), β-coronavirus-specific marker (βSM) domains, and a sub-region of the Y domain of this protein. We show that the Ubl1, ADP-ribose phosphatase (ADRP), human SARS Unique (HSUD), NAB, and Y domains of Nsp3 bind the 5’ UTR of the viral genome and that the Ubl1 and Y domains possess affinity for recognition of this region, suggesting high specificity. The Ubl1-Nucleocapsid (N) protein complex binds the 5’ UTR with greater affinity than the individual proteins alone. Our results suggest that multiple domains of Nsp3, particularly Ubl1 and Y, shepherd the 5’ UTR of the viral genome during translocation through the DMV membrane, priming the Ubl1 domain to load the genome onto N protein. IMPORTANCE The largest protein encoded by the SARS-CoV-2 genome is Nsp3. In infected cells, this multi-domain protein forms a pore structure in the virus-induced double-membrane vesicles (DMV). We have incomplete data on Nsp3 molecular structure, and here, we describe crystal structures for multiple domains of Nsp3. It is thought that newly replicated viral RNA transits through the DMV pore; however, we possess incomplete data on which regions of Nsp3 actually interact with RNA. Here, we present data showing that five domains of Nsp3 interact with the 5’ UTR of the SARS-CoV-2 RNA, including the Y domain for which no function has ever been discovered. These data suggest that the pore structure plays an active role in recognizing the terminal end of the genome, transiting and loading the viral RNA onto the cytoplasmic nucleocapsid protein. These data help expand our knowledge of Nsp3 structure and function and the SARS-CoV-2 replication cycle.

Microbiology↗
DOE OSTI2025

Evaluation of the Energy, Hygrothermal, and Thermal Capacity Performance of Cross-Laminated Timber

Cross-laminated timber (CLT) construction is gaining momentum in the US because it offers multiple advantages over traditional construction methods. Benefits that have received the most attention focus on constructability, the environment, and protection (e.g., blast resistance), although CLT construction is likely to offer other benefits, as well. Still, these have not been studied at length because such evaluations are costly, requiring long-term assessments in an actual building and specialized technical knowledge. Among the possible benefits, CLT construction likely provides a higher-performing building envelope. Using CLT panels to enclose a building means fewer joints in the opaque envelope than what is required in traditional stick-framed construction. Fewer joints mean fewer locations where the air- and water-resistive barrier (WRB) could be compromised; thus, a CLT building enclosure may require less maintenance and have a longer lifespan than a traditionally built structure because of fewer air and water leaks. In addition, CLT’s thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours, reducing operational energy consumption throughout the lifetime of the CLT building (Salonvaara et al., 2022). Furthermore, more stable indoor temperatures can increase occupant comfort. The CLT’s thermal mass can also reduce energy costs by adjusting to utility time-of-use pricing without affecting occupant comfort. The ability of CLT buildings to bridge periods without HVAC operation prepares them for future grid interaction and provides a certain level of resilience against power outages. Researchers have attempted to quantify these benefits; however, their work is based on simplified simulations with numerous assumptions. To correctly understand the benefits, an actual building must be monitored. Therefore, information needs to be gathered on indoor and outdoor temperatures, HVAC energy consumption, thermostat setpoints, temperatures, and thermal transport in CLT components to comprehend how these parameters are affected by the CLT’s thermal mass. These data are needed to reduce the number of assumptions and calibrate simulation models to optimize HVAC controls to minimize overall energy consumption, reduce energy use and higher fees during peak demand, and maintain occupant comfort. Additionally, the calibrated simulation model allows the optimization exercise to be repeated in various US climates. Potential benefits can be tailored to buildings in various locations, and decisions can be made on where CLT construction could be most advantageous. Furthermore, monitoring and simulation results are needed to evaluate the durability of the CLT structures in different climates. This project’s researchers gathered information to help understand and quantify the benefits of CLT buildings concerning operational energy, moderated indoor temperatures, and comfort; the dynamic operation to provide grid services; and resilience in times of power outage. Through the corroboration of simulation models with real-world measurements, this study paves the way for extrapolating findings to other climatic zones and building typologies, thereby broadening the understanding of CLT’s multifaceted benefits and reinforcing its position as a material of choice in sustainable construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Implementation of compound refractive lenses for large field-of-view x-ray phase-contrast imaging during hypervelocity impact experiments

Synchrotron x-ray phase-contrast imaging (XPCI) offers time-resolved visualization of dynamic compression phenomena, but its intrinsically small field-of-view (FOV) limits the time that key features remain in frame. A novel approach to enlarge the FOV is achieved by positioning a two-dimensional parabolic compound refractive lens (CRL) upstream of the sample to deliberately defocus the white beam. Ray-tracing simulations and XPCI measurements show that this CRL configuration can expand the beam by ∼50% vertically and ∼15% horizontally based on the full width at half-maximum of the beam. Implementing the CRL, however, attenuates the photon flux and lowers signal-to-noise ratio (SNR). Task-based analysis using a calibration grid (30 μm dots) showed that both setups fail to consistently meet the Rose criterion (SNR ≥ 5) for features of this size in single-bunch imaging. Extrapolating the measured SNR Rose values suggests that the minimum consistently detectable feature lies closer to 30–40 μm for the standard XPCI setup and above 40 μm for CRL-XPCI. Despite this limitation, the CRL configuration nearly doubles the illuminated area, enabling simultaneous tracking of front and rear observations of boron carbide targets subjected to rod and sphere impacts at 1.0–2.6 km/s. Image tracking algorithms and photonic Doppler velocimetry were used to measure penetration and rear-surface velocity histories. Together, these measurements capture crack fronts, penetration, and material breakout, offering new benchmark data for validating high-strain-rate constitutive models of ceramic materials.

Ceramic materials↗
DOE OSTI2026

Electrochemical Modeling of PID Leakage Current of PV Modules: Steady-State Current, Transient Current, and RC-Equivalent Circuit

Potential-induced degradation (PID) remains a significant reliability concern for photovoltaic (PV) modules, arising when a voltage difference between the module frame and the solar cells drives unintended leakage current through the glass-encapsulant stack. Although PID ultimately manifests as PID-s, PID-p, or PID-c, the underlying behavior of the leakage current-its magnitude and time dependence-requires clearer electrochemical interpretation. Traditional explanations attribute the initial transient current to bulk capacitive elements of the glass, encapsulant, and antireflection coatings, and the steady-state current according to their effective ohmic resistance. More recent studies, however, indicate that electrochemical charge-transfer processes at the encapsulant-metallization interface can play a dominant role in defining the leakage-current path. This paper develops a unified electrochemical framework for modeling PID leakage current. First, an RC-equivalent circuit is formulated by combining conventional RC elements with a Randles-type interface to capture transient leakage current through double-layer capacitance and faradaic processes at ionic-electronic boundaries. Second, the steady-state current-voltage behavior is explained using a linearized Butler-Volmer relationship, showing that the measured ohmic response corresponds to the low-overpotential limit of charge-transfer kinetics. Analytical results demonstrate that, for typical module materials-3.2-mm soda-lime glass and 0.45-mm encapsulant-the dominant modulators to PID leakage current are the glass surface resistance (under dry-surface conditions), the glass bulk capacitance, and the encapsulant resistance (under wet-surface conditions), with soda lime glass surface and EVA/POE encapsulant resistances primarily governing steady-state current. The proposed electrochemical model is validated against measured leakage-current data, showing good agreement in both the magnitude and the time-dependent evolution of PID leakage current.

14 SOLAR ENERGY↗
DOE OSTI2025

FY2025 Status Report: Model 9975 O Ring Fixture Long-Term Leak Performance

Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package have been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The mock-up PCV fixtures are leak tested periodically, and all GLT O-ring fixtures aged at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aged at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years of aging without failure. Two of these retired fixtures were returned to testing and heated to 350 °F to evaluate the impact of additional heating at higher temperature for aged O-rings. Fixture #20 failed after 3 months while fixture #18 failed after 9 months at 350 °F. These O-rings demonstrated that aged and in-service O-rings can continue to be used, even at higher temperatures, after being in storage, and their leak performance are consistent with other samples at 350 °F. There has been one GLT O-ring fixture which failed after 13.4 years of aging at 200 °F. However, 20 other GLT O-rings aging at 200 °F have remained leak-tight for over 16.9 years and remain in test. There are two GLT O-ring fixtures at 270 °F; one fixture has failed after 12.9 years while the other fixture remains in test after 12.5 years. All GLT-S O-ring fixtures aged at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 250 °F for 14.9 years, while one GLT-S O-ring fixture failed after 12.4 years at 200 °F. The leak testing data to date suggest the GLT and GLT-S O-rings aging in the K-Area Complex (KAC) storage at temperatures of 158 °F might maintain a leak-tight seal for up to 59 years. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in KAC. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 24 mock-up PCV fixtures.

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

High-Speed and High-Quality Field Welding Repair Based on Advanced Non-Destructive Evaluation and Numerical Modeling

Creep strength-enhanced ferritic (CSEF) steels such as Grade 91 (9Cr-1Mo-V) and Grade 92 (Fe-9Cr-2W-0.5Mo) steels are widely used in the fossil-fuel-fired and nuclear power plants. The weld integrity of these steels is crucial for power plants' safe and reliable operations. Due to harsh service conditions, the steel weld can become susceptible to environmental degradation. Field welding repair is used to restore the degraded weld’s performance where a controlled temper-bead welding technique is commonly used to temper the freshly formed martensite during welding. However, knowledge of weld repairability is limited and experimental trial and error optimization to achieve desired microstructure and joint properties is expensive and time-consuming. Many existing computational models, e.g., finite element models, are limited to solving heat conduction equation and ignoring convective heat transfer due to molten metal flow. These models can result in over-prediction of peak temperatures of weld pool and heat-affected zone (HAZ), which in turn can affect the accuracy of tempering prediction. Moreover, these finite element models require an input of the deposit profiles in advance and thus limits the usability of these models. Here, a molten pool-based, multi-pass multi-layer model has been developed based on computational fluid dynamics (CFD) approach with the Volume of Fluid (VOF) method. The model calculates the bead formation, thereby eliminating the need for pre-determined bead profiles required by finite element models. For computational efficiency, a coordinate system attached to the moving heat source is utilized. A subroutine is developed to convert the temperature profiles in the reference frame stationary to the heat source to that stationary to the workpiece. The converted thermal cycles are then imported into a microstructure model to compute the tempering kinetics and resultant hardness using a Johnson-Mehl-Avrami-Kolmogorov (JMAK), and modified Grange-Baughman parameter. The modeling approach is first developed and validated on single- and multi-pass deposition of stainless steel filler metal onto a SA-533 high strength steel substrate. The models are then applied to a multi-pass V-groove repair weld of Grade 91 steel plate as well as directed energy deposition of Grade 92 steel. Non-destructive characterization of microstructures was performed on Grade 91 and 92 steel welds. Two welding processes, cold metal transfer (CMT) and flux-cored arc welding (FCAW), were investigated for the Grade 91 steel weld samples. For the Grade 92 weld samples, three different heat inputs (low, medium, and high) of gas tungsten arc welding (GTAW) were utilized to replicate traditional field welding processes. The non-destructive evaluation (NDE) method used for this research was immersion ultrasonic testing (UT) using a micro-resolution ultrasonic imaging methodology specifically designed to operate in the through-transmission configuration operating at 20 MHz of frequency. The system used a focused ultrasonic beam spot size diameter between 250-300 μm, and a 6 μm laser vibrometer spot size for detection, to produce highly defined images with longitudinal and mode-converted shear waves. From the micro-resolution ultrasonic C-scan images, three microstructural regions, i.e., weld metal (WM), HAZ, and base metal (BM), were clearly identifiable. Various levels of ultrasonic amplitudes distributed over the three regions were correlated with electron beam backscattered diffraction (EBSD) images using grain size, grain boundaries, and dislocation densities. The results showed that areas with relatively higher ultrasonic amplitude levels were associated with smaller grains and higher dislocation densities, while areas with lower amplitude levels were associated with larger grains and lower dislocation densities. In addition, ultrasonic velocity data obtained across the three different weld microstructural regions of Grade 91 test samples were correlated with optical metallographic images and hardness measurements. The results showed distinctive decreases in ultrasonic velocity and hardness over the HAZ region, where weld failures often occur during service.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Driving Economics and Reducing Risks: The Business Case for Security-by-Design in Nuclear Power

This report provides an analysis of the financial, operational, and strategic advantages of incorporating Security-by-Design (SeBD) early in the lifecycle of nuclear power plant projects. By framing security as a foundational design element rather than a late-stage add-on, owners, vendors, and operators can reduce budget overruns, strengthen regulatory compliance, and increase revenue opportunities. The report details key lifecycle phases, highlighting the strategic imperative for organizations (including project developers, investors, vendors, and regulators) to adopt SeBD. Drawing on industry estimates, real-world case studies, and comparative cost analyses, the findings underscore that even a modest upfront investment in SeBD can yield substantial long-term returns by preventing costly retrofit activities, minimizing regulatory delays, and positioning nuclear vendors for the ability to adapt in the evolving security market. By avoiding excessive retrofit expenses and positioning security as a built-in feature rather than an afterthought, nuclear projects can protect their financial performance, enhance public trust, and secure a competitive edge in an increasingly complex global energy market. The authors advocate for SeBD’s strategic implementation, supported by established quality management methodologies, thereby promoting continuous improvement and defect avoidance. Ultimately, early SeBD integration represents a strategic investment, yielding significant returns by preventing costly retrofits and positioning nuclear projects for enhanced competitiveness and public trust.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results

Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO 2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗