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The Technical, Economic, Risk, and Adoption Assessment for Evaluating Work Reduction Opportunities in the Nuclear Industry

Automation and cost-saving initiatives, such as process automation with advances in artificial intelligence, are gaining traction in modernization efforts across the nuclear industry. As these innovations are increasingly adopted, it becomes crucial to evaluate their impacts comprehensively. Various technical and economic attributes, along with risk and human readiness factors, must be achieved to ensure that innovative projects enabling automation and modernization are successful. However, no systematic or integrated framework exists that allows plants to evaluate these innovative projects. To address this gap, the Technical, Economic, Risk, and Adoption (TERA) assessment offers a structured method to evaluate innovative technologies, ensuring solutions meet both operational and safety standards. The TERA framework integrates the disparate perspectives to assess modernization opportunities in nuclear operations. It combines qualitative and quantitative models to evaluate the relationship between performance and business impacts, while also enabling continuous re-evaluation during project development. This approach helps plant owners identify high-priority opportunities, optimize cost savings, and minimize risks, ensuring projects remain on track to achieve desired returns. By providing a comprehensive, systematic methodology, TERA enables informed, data-driven decisions that support successful modernization efforts, enhancing efficiency, safety, and cost savings across nuclear operations. This paper explains the TERA framework and its benefits for the nuclear industry.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

From electronic structure to model application of key reactions for gasoline/alcohol combustion: Hydrogen-atom abstractions by $CH_3\dot{O}$ radical

H-atom abstraction by methoxy radical ($CH_3\dot{O}$) plays an important role in capturing the kinetics of reactions between gasoline components and alcohols. This study focuses on determining the reaction rates and thermodynamic properties of methoxy radical reactions with five gasoline fuel components: n-heptane, iso-octane, 1-hexene, cyclopentane and toluene. Electronic structure calculations were per-formed for all the stationary points with M06-2X/6 -311 ++ g(d,p) method. G3 composite method with atomization method is used for determining Δ f H 0 of all the closed shell and radical species, using which the necessary thermodynamic data of all the species was determined. Coupled cluster theory QCISD(T)/cc-pVXZ (where X = D and T) and Møller-Plesset perturbation theory MP2/cc-pVXZ (where X = D, T and Q) were used to calculate single point energies. Subsequently, rate constants for all hydrogen atom ab-straction channels have been performed using conventional transition state theory with unsymmetric tunneling corrections. A systematic comparison of rates for abstraction from different sites within the same species and same site from different species is done in order to get insights into this reaction class. Here, the computed thermodynamic properties and rate constants were incorporated into a recent gasoline mechanism to investigate the impact of the calculations performed in this work. A shift in predicted NTC (negative temperature coefficient) behavior and significant reduction in model reactivity is observed upon incorporating the rates calculated herein.

33 ADVANCED PROPULSION SYSTEMS↗

Jet Mixing Enhancement by Feedback Control

The objective of this work has been to produce methodologies for high speed jet noise reduction based on natural mechanisms and enhanced feedback control to affect frequencies and structures in a prescribed manner. In this effort the two-point hot wire measurements obtained in the Langley jet facility by Ukeiley were used in conjuction with linear stochastic estimation (LSE) to implement the LSE component of the complementary technique. This method combines the Proper Orthogonal Decomposition (POD) and LSE to provide an experimental low dimensional time dependent description of the flow field. From such a description it should be possible to identify short time high strain rate events in the jet which contribute to the noise. The main task completed for this effort is summarized: LSE experiments were performed at the downstream locations where the two point hot wire measurements have been obtained by Ukeiley. These experiments involved sampling simultaneously hot wire signals from a relatively course spatial grid in gamma and theta. From this simultaneous data, coupled with the two-point measurements of Ukeiley via the LSE components of the complementary technique, an experimental low dimensional description of the jet at 4, 5, 6, 7 and 8 diameters downstream was obtained for Mach numbers of 0.3 and 0.6. We first present an overview of the theory involved. We finish up with a statement of the work performed and finally provide charts from a 1999 APS talk which summarizes the results.

Glauser, Mark↗

Hydrogen Plasma Reduction of Silicates for Lunar Oxygen Liberation

As crewed missions to the moon become closer, the focus on in-situ resource utilization efforts has increased. Since lunar soil has abundant oxygen on the surface of the moon, work has been done to process this resource in an efficient manner. Hydrogen reduction of lunar regolith has emerged as a method of liberating oxygen that can be used for fuel and water production. Traditional reduction techniques require high temperatures and increased complexity when dealing with high amounts of silicates. Plasma can reduce silicates efficiently and thus has become of high interest for use in the lunar highlands where silicates exist in high quantities. NASA’s Kennedy Space Center is exploring the use of low temperature plasmas for the reduction of silicates. This work shows that exposing silicates to a hydrogen plasma produces water. Residual gas analysis and optical emission spectroscopy were used to measure the relative quantities of water vapor production and OH (A-X) emission for hydrogen plasma interactions with lunar highland simulant and silica. X-ray photo-electron spectroscopy and scanning electron microscopy/energy-dispersive X-ray spectroscopy were also used to observe surface modifications to the silicates that reflect the key chemical reactions that occurred. From this data, plasma has emerged as a promising solution to produce oxygen on the lunar surface. *Work supported by NASA's Science Technology Mission Directorate Center Innovation Fund.

R. P. Gott↗

Plasma Reduction of Regolith for Oxygen Liberation

As crewed missions to the moon become closer, the focus on in-situ resource utilization efforts has increased. Since lunar soil has abundant oxygen on the surface of the moon, work has been done to process this resource in an efficient manner. Hydrogen reduction of lunar regolith has emerged as a method of liberating oxygen that can be used for fuel and water production. Traditional reduction techniques require high temperatures and increased complexity when dealing with high amounts of silicates. Plasma can reduce silicates efficiently and thus has become of high interest for use in the lunar highlands where silicates exist in high quantities. NASA’s Kennedy Space Center is exploring the use of low temperature plasmas for the reduction of silicates. This work shows that exposing silicates to a hydrogen plasma produces water. Residual gas analysis and optical emission spectroscopy were used to measure the relative quantities of water vapor production and OH (A-X) emission for hydrogen plasma interactions with lunar highland simulant and silica. X-ray photo-electron spectroscopy and scanning electron microscopy/energy-dispersive X-ray spectroscopy were also used to observe surface modifications to the silicates that reflect the key chemical reactions that occurred. From this data, plasma has emerged as a promising solution to produce oxygen on the lunar surface.

Ryan Gott↗

Machine Learning Techniques for Data Reduction of Climate Applications

Scientists conduct large-scale simulations to compute derived quantities-of-interest (QoI) from primary data. Often, QoI are linked to specific features, regions, or time intervals, such that data can be adaptively reduced without compromising the integrity of QoI. For many spatiotemporal applications, these QoI are binary in nature and represent presence or absence of a physical phenomenon. We present a pipelined compression approach that first uses neural-network-based techniques to derive regions where QoI are highly likely to be present. Then, we employ a Guaranteed Autoencoder (GAE) to compress data with differential error bounds. GAE uses QoI information to apply low-error compression to only these regions. This results in overall high compression ratios while still achieving downstream goals of simulation or data collections. Experimental results are presented for climate data generated from the E3SM Simulation model for downstream quantities such as tropical cyclone and atmospheric river detection and tracking. These results show that our approach is superior to comparable methods in the literature.

Li, Xiao [University of Florida]↗

Melting and phase relations of Fe-Ni-Si determined by a multi-technique approach

Many studies have suggested silicon as a candidate light element for the cores of Earth and Mercury. However, the effect of silicon on the melting temperatures of core materials and thermal profiles of cores is poorly understood, due to disagreements among melt detection techniques, uncertainties in sample pressure evolution during heating, and sparsity of studies investigating the combined effects of nickel and silicon on the phase diagram of iron. Here, in this study we develop a multi-technique approach for measuring the high-pressure melting and solid phase relations of iron alloys and apply it to Fe 0.8 Ni 0.1 Si 0.1 (Fe-11wt%Ni-5.3wt%Si), a composition compatible with recent estimates for the cores of Earth and Mercury. This approach combines results (20-83 GPa) from two atomic-level techniques: synchrotron Mossbauer spectroscopy (SMS) and synchrotron x-ray diffraction (XRD). Melting is independently detected by the loss of the Mossbauer signal, produced exclusively by solid-bound iron nuclei, and the onset of a liquid diffuse x-ray scattering signal. The use of a burst heating and background updating method for quantifying changes in the reference background during heating facilitates the determination of liquid diffuse signal onsets and leads to strong reproducibility and excellent agreement in melting temperatures determined separately by the two techniques. XRD measurements additionally constrain the hcp-fcc phase boundary and in-situ pressure evolution of the samples during heating. We apply our updated thermal pressure model to published SMS melting data on fcc-Fe and fcc-Fe 0.9 Ni 0.1 to precisely evaluate the effect of silicon on melting temperatures. We find that the addition of 10 mol% Si to Fe 0.9 Ni 0.1 reduces melting temperatures by ~250 K at low pressures (<60 GPa) and flattens the hcp-fcc phase boundary. Extrapolating our results, we constrain the location of the hcp-fcc-liquid quasi-triple point at 147±14 GPa and 3140±90 K, which implies a melting temperature reduction of 500 K compared with Fe 0.9 Ni 0.1 . The results demonstrate the advantages of combining complementary experimental techniques in investigations of melting under extreme conditions.

36 MATERIALS SCIENCE↗

A comprehensive approach for elucidating the interplay between 4f n +1 and 4f n 5d 1 configurations in Ln 2+ complexes

Lanthanides (Ln) are typically found in the +3 oxidation state. However, in recent decades, their chemistry has been expanded to include the less stable +2 oxidation state across the entire series except promethium (Pm), facilitated by the coordination of ligands such as trimethylsilylcyclopentadienyl, C 5 H 4 SiMe 3 (Cp'). The [LnCp' 3 ] complexes have been the workhorse for the synthesis and theoretical study of the fundamental aspects of divalent lanthanide chemistry, where experimental and computational evidence have suggested the existence of different ground state (GS) configurations, 4f n+1 or 4f n 5d 1 , depending on the specific metal. Standard reduction potentials and 4f n+1 to 4f n 5d 1 promotion energies have been two factors usually considered to rationalize the occurrence of these variable GS configurations, however the driving force behind this phenomenon is still not clear. In this work we present a comprehensive theoretical approach to shed light on this matter using the [LnCp 3 ] - model systems. We begin by calculating 4f n+1 to 4f n 5d 1 promotion energies and successfully correlate them with existing experimental data. Furthermore, we analyze how changes in the GS charge distribution between the Ln ions, LnCp 3 and the reduced [LnCp 3 ] - complexes (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) correlate with experimental trends in redox potentials and the calculated promotion energies. For this purpose, a comprehensive theoretical work that includes relativistic ligand field density functional theory (LFDFT) and relativistic ab initio wavefunction methods was performed. This study will help the rational design of suitable environments to tune the different GS configurations as well as modulating the spectroscopic properties of new Ln 2+ complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of social structure and management on risk of disease establishment in wild pigs

Contact heterogeneity among hosts determines invasion and spreading dynamics of infectious disease, thus its characterization is essential for identifying effective disease control strategies. Yet, little is known about the factors shaping contact networks in many 28 wildlife species and how wildlife management actions might affect contact networks. Wild pigs in North America are an invasive, socially-structured species that pose a health concern for domestic swine given their ability to transmit numerous devastating diseases 2 such as African swine fever (ASF). Using proximity loggers and GPS data from 48 wild pigs in Florida and South Carolina, USA, we employed a probabilistic framework to estimate weighted contact networks. We determined the effects of sex, social group, and spatial distribution (monthly home range overlap and distance) on wild pig contact. We also estimated the impacts of management-induced perturbations on contact and inferred their effects on ASF establishment in wild pigs with simulation. Social group membership was the primary factor influencing contacts. Between-group contacts depended primarily on space use characteristics, with fewer contacts among groups separated by >2 km and no contacts among groups >4 km apart within a month. Modeling ASF dynamics on the contact network demonstrated that indirect contacts resulting from baiting (a typical method of attracting wild pigs or game species to a site to enhance recreational hunting) increased the risk of disease establishment by ~33% relative to direct contact. Low-intensity population reduction (<5.9% of the population) had no detectable impact on contact structure but reduced predicted ASF establishment risk relative to no population reduction. Here, we demonstrate an approach for understanding the relative role of spatial, social, and individual-level characteristics in shaping contact networks and predicting their effects on disease establishment risk, thus providing insight for optimizing disease control in spatially- and socially-structured wildlife species.

59 BASIC BIOLOGICAL SCIENCES↗

Simple and Scalable Process for Nanocellulose Production from Residues and Waste (CRADA Final Report)

This project successfully developed an innovative, cost-effective, and scalable method for converting low-cost agricultural waste feedstocks into nanocellulose—a sustainable material with wide-ranging industrial applications. It addressed the critical challenges of high production costs and limited global supply, which have hindered the widespread adoption of nanocellulose in industry. Through this work, significant advancements were made in optimizing resource use, improving process efficiency, and reducing costs. Notable achievements included a 50% reduction in water usage, 30% lower chemical consumption, and 20% energy savings, all while maintaining high-quality product standards. The technical feasibility of the process was further validated at a 10L scale in collaboration with the Advanced Biofuels and Bioproducts Development Unit (ABPDU), demonstrating scalability and replicability. Key challenges in reducing nanocellulose production costs were addressed by utilizing low-cost biomass feedstocks and implementing low-temperature conversion reactions, leading to lower capital and operating expenses. The project also mitigated financial risk by generating critical data on the feasibility, adaptability, and scalability of the conversion technology, paving the way for its commercial implementation. Public benefits include advancing the circular bioeconomy, reducing environmental impact, fostering job creation, and enabling a shift toward biobased materials as sustainable alternatives to fossil-based products. These outcomes align closely with national goals to reduce greenhouse gas emissions and promote sustainable technological innovation.

09 BIOMASS FUELS↗

Testing for X-ray Periodicities in Seyfert Galaxies

The Deep Survey instrument on the Extreme Ultraviolet Explorer obtained long, continuous light-curves of 10 Seyfert galaxies with durations of 5-33 days each. We present a uniform reduction of these data, which account for a total of 209 days of observation. Several of the light curves are uniquely suited to a search for periodicity or QPOs in the range of hours to days that might be expected from dynamical effects in the inner accretion disks around approximately 10(exp 8) solar mass black holes. Power spectra show features in three of the longest observations that could be transient periods: 0.9 days in RX J0437.4-4711, 2.1 days in Ton S180, and 5.8 days in 1H 0419-577. These period values seem to be unrelated to the length of the observations, which are similar in the three cases, but they do roughly scale as the luminosity of the objects, which would be expected in a dynamical scenario if the black hole masses also scale with luminosity. The significance of these periods will be evaluated in a future publication by using the method of Timmer & Konig (1995), which properly takes into account the red-noise properties of AGN light curves.

Halpern, Jules P.↗

Comparison of modular analytical wake models to the Lillgrund wind plant

Efficient and accurate wake models are required for wind plant performance modeling and the suite of engineering processes that support wind plant layout, control, and monitoring. Although many analytical and engineering wake models with low computational costs have been proposed, their ability to represent the power production of large wind plants in a wide range of atmospheric conditions is not completely understood. The following validation study reviews the underlying theory for analytical wake models, outlines quality control procedures for observational data, and compares model results with observational data from the Lillgrund Wind Plant. Lillgrund makes a valuable case study for wake modeling because of its regular arrangement and the relatively close spacing of constituent wind turbines, which lead to regular and significant wake interactions within the wind plant and the development of deep array flow conditions. Formulations for the velocity deficit, wake-added turbulence, and wake superposition methods are considered in a modular sense, yielding many possible configurations to represent wind turbine wakes, of which seven are examined in detail. Velocity deficit models that account for flow conditions in the near wake are better able to reproduce power production for wind turbines in the transitional region of the wind plant, where wind turbines experience as many as five wakes from upstream turbines. Finally, in the deep array, where power production reaches asymptotic values and wake statistics become quasi-periodic, wake superposition schemes become the largest driver in error reduction; using the linear or maximum wake superposition methods can reduce the relative root mean square error by as much as 40% in the deep array.

17 WIND ENERGY↗

User's manual for the one-dimensional hypersonic experimental aero-thermodynamic (1DHEAT) data reduction code

A FORTRAN computer code for the reduction and analysis of experimental heat transfer data has been developed. This code can be utilized to determine heat transfer rates from surface temperature measurements made using either thin-film resistance gages or coaxial surface thermocouples. Both an analytical and a numerical finite-volume heat transfer model are implemented in this code. The analytical solution is based on a one-dimensional, semi-infinite wall thickness model with the approximation of constant substrate thermal properties, which is empirically corrected for the effects of variable thermal properties. The finite-volume solution is based on a one-dimensional, implicit discretization. The finite-volume model directly incorporates the effects of variable substrate thermal properties and does not require the semi-finite wall thickness approximation used in the analytical model. This model also includes the option of a multiple-layer substrate. Fast, accurate results can be obtained using either method. This code has been used to reduce several sets of aerodynamic heating data, of which samples are included in this report.

Hollis, Brian R.↗

Copoly(imide siloxane) Abhesive Materials with Varied Siloxane Oligomer Length

In this work, low surface energy copoly(imide siloxane)s were synthesized with various siloxane segment lengths. Characterization of these materials revealed that domain formation of the low surface energy component within the matrix was more prevalent for longer siloxane segments as indicated by increased opacity, decreased mechanical properties, and variation of the Tg. Incorporation of siloxanes lowered the polymer s surface energy as indicated by water contact angle values. Topographical modification of these materials by laser ablation patterning further reduced the surface energy, even generating superhydrophobic surfaces. Combined, the contact angle data and particle adhesion testing indicated that copoly(imide siloxane) materials may provide greater mitigation to particulate adhesion than polyimide materials alone. These enhanced surface properties for abhesive applications did result in a reduction of the tensile moduli of the copolymers. It is possible that lower siloxane loading levels would result in retention of the mechanical properties of the polyimide while still affording abhesive surface properties. This hypothesis is currently being investigated. Laser ablation patterning offers further reduction in particle retention as the available surface area for particle adhesion is reduced. Pattern variation and size dependencies are currently being evaluated. For the purposes of lunar dust adhesion mitigation, it is likely that this approach, termed passive due to the lack of input from an external energy source, would not be sufficient to mitigate surface contamination or clean contaminated surfaces for some lunar applications. It is feasible to combine these materials with active mitigation strategies - methods that utilize input from external energy sources - would broaden the applicability of such materials for abhesive purposes. Collaborative efforts along these lines have been initiated with researchers at NASA Kennedy Space Center where experiments are being conducted involving a series of embedded electrodes within polymeric matrices.

Wohl, Christoper J.↗

Start-up and Emergency Shutdown Modeling for a Coal-fired 10MWe sCO₂ Power Plant

As part of a Phase II Front End Engineering Design (FEED) study for the DOE Fossil Fuel Large Scale Pilots program, investigations of novel start-up and emergency shutdown methods for a stoker-fed, coal-fired, 10MWe sCO₂ power plant proposal were performed. These investigations were performed using 1D transient system models of the plant created within the GT-SUITE system modeling platform. The system model components were created using vendor quotation data (heat exchangers), performance maps (turbomachines), or FMU models (fired heater). Previously, Echogen Power Systems (Echogen) has used a sCO₂ power cycle start-up method that fills the system with liquid CO₂ to facilitate easy use of an electrically-driven start pump to transition the system from initial CO₂ fill to turbo-compressor initialization. The novel start-up method presented attempts this transition with a minimal filling of the system with liquid CO₂, to reduce the total CO₂ inventory required. This method leaves the start pump vulnerable to a two phase inlet condition as system pressure is below the CO₂ saturation pressure for the condenser cooling water temperature (Tcw). System model cases at Tcw of 18°C, 26°C, and 32°C, corresponding to cold, design, and hot ambient days, were analyzed to determine if the SP inlet condition could be kept as a subcooled liquid and estimate the CO₂ inventory reduction amount./p> Stoker-fed, coal-fired heaters continue to emit heat for some time even after emergency shutdown from events such as a power failure. This heat emission would lead to a failure of the fired heater, as the metal overheats, if the CO₂ flow is shut off. The emergency shutdown method presented utilizes CO₂ vented by a controllable vent valve (CRV) to provide CO₂ cooling flow to the fired heater. To determine the effectiveness of this method at keeping the fired heater peak tubing metal temperature below the ASME material temperature limit, for pressures below 5 MPa, of 816 °C, system model cases with CRV diameters ranging from 4” to 10”, and an alternative CO₂ vent routing with CRV size of 6”, were investigated./p>

01 COAL, LIGNITE, AND PEAT↗

Laser-Induced Spectrochemical Assay for Uranium Enrichment (LISA-UE)

Uranium hexafluoride (UF6) is the uranium compound typically involved in uranium enrichment process. As the first line of defense against nuclear proliferation, accurate determinations of the uranium enrichment ratio in UF6 are critical for materials verification, accounting and safeguards. Shipping gaseous UF6 samples off-site for analysis with mass spectrometry is cumbersome and costly, and results are not available for some time (months). In-field UF6 enrichment assay has the potential to substantially reduce the time, logistics and expense of sample handling. At present, COMPUCEA is the only accepted method for UF6 enrichment assay in the field. Laser-Induced Spectrochemical Assay for Uranium Enrichment (LISA-UE) is an all-optical (based on laser induced plasma emission) analytical technique intended for fieldable, accurate, precise and rapid UF6 enrichment assay. In its operation, laser induced plasma is created directly in the gaseous UF6 sample. Because different U isotopes emit at slightly different wavelengths, the isotopic information of the UF6 sample is inherently encoded in the atomic emission from the plasma. Isotopic emissions from 235U and 238U are measured simultaneously, which eliminate correlated noise from the laser induced plasma. Isotopic information of the UF6 sample can be extracted from the acquired spectrum with theoretical multi-variable non-linear spectral fitting. To date, advances made by the LISA-UE research team include optimization of the spectral window for direct gaseous UF6 enrichment assay with laser induced plasma, development of data reduction algorithms, and demonstrations of the LISA-UE technique with gaseous UF6 samples. In this presentation, the technical aspect of LISA-UE will be overviewed, the data reduction algorithm will be described, and performance of the technique will be discussed.

Chan, George↗

Beam Hardening Artifact Reduction in X-Ray CT Reconstruction of 3D Printed Metal Parts Leveraging Deep Learning and CAD Models

Nondestructive evaluation (NDE) of additively manufactured (AM) parts is important for understanding the impacts of various process parameters and qualifying the built part. X-ray computed tomography (XCT) has played a critical role in rapid NDE and characterization of AM parts. However, XCT of metal AM parts can be challenging because of artifacts produced by standard reconstruction algorithms as a result of a confounding effect called “beam hardening.” Beam hardening artifacts complicate the analysis of XCT images and adversely impact the process of detecting defects, such as pores and cracks, which is key to ensuring the quality of the parts being printed. In this work, we propose a novel framework based on using available computer-aided design (CAD) models for parts to be manufactured, accurate XCT simulations, and a deep-neural network to produce high-quality XCT reconstructions from data that are affected by noise and beam hardening. Using extensive experiments with simulated data sets, we demonstrate that our method can significantly improve the reconstruction quality, thereby enabling better detection of defects compared with the state of the art. We also present promising preliminary results of applying the deep networks trained using CAD models to experimental data obtained from XCT of an AM jet-engine turbine blade.

Ziabari, Amir↗

New Yield Estimates for Nuclear Detonations Over Water

One of the primary methods used by the United States to estimate the yields of atmospheric nuclear tests performed in the 1940’s, 50’s, and 60’s was to film each detonation with a high-speed camera, measure the blast radius as a function of time, and then use Taylor’s spherical blast wave equation to calculate the source energy (i.e., the yield). For surface detonations, the yield in Taylor’s equation was assumed to be twice as large as the actual yield to account for the energy reflected from the surface, assuming the ground was a perfect reflector. Recent simulations of surface detonations over water (referred to as barge shots) have shown that Taylor’s equation must be modified further to account for material entrainment and heat losses. We have computed this lost energy using a high-order radiation-hydrodynamics code to determine the reduction in blast radius vs. time. By analyzing simulation data in the same manner as film data, we have determined that a yield correction factor of 1.27± 0.04 should be applied to the barge shots.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗