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DOE OSTI2021

Characterizing the Influence of Organic Polymers on the Specific Reactivity of Particulate Remedial Amendments

Commercially available particulate amendments demonstrate high reactivity for effective treatment of water soluble organic and inorganic contaminants in laboratory studies; however, transport of these particles is constrained in the subsurface. In many field applications, particulate amendments are mixed with organic polymers to enhance mobility for direct push applications or stabilize suspensions for high mass loadings. As such, the interactions between particulate amendments, organic polymers and contaminant species need to be systematically investigated to properly understand mechanistic processes that facilitate predictive performance metrics for specific applications in situ . In this study, batch experiments were conducted to quantify the effects of organic polymers (xanthan gum, guar gum, and sodium alginate), polymer concentration (800 and 4,000 mg/L), and aging (up to 28 days) on chromate treatment rate and capacity by two classes of amendments: reductants [granular zero-valent iron (gZVI), micron-ZVI (mZVI), sulfur modified iron (SMI)], and an adsorbent (bismuth sub-nitrate). When particulate amendments were suspended in polymer solutions, reductants retained between 84–100% of the amendment treatment capacity. Conversely, the adsorbent maintained 63–97% relative treatment capacity of the no-polymer control. Polymer solutions had a more pronounced impact on the rate of chromate removal; first order rates of chemical reduction decreased by as much as 70% and adsorption by up to 81% relative to the no-polymer controls. Polymer–amendment aging experiments also showed decreased Cr(VI) treatment capacity; reductants decreased by as much as 24% and adsorption decreased by as much as 44% after 28 days of incubation. While polymer suspensions are needed to aid the injection of particulate amendments into the subsurface, the results from this study indicate potential losses of treatment capacity and a decrease in the rate of remedial performance due to the physical and chemical interactions between polymer suspensions and reactive particulate amendments. Simple batch systems provide baseline characterization of tripartite interactions for the removal of Cr(VI). Additional work is needed to quantify the full impact of polymers on remedial outcomes under site relevant conditions at field scale.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Cxcl12 Deletion in Mesenchymal Cells Increases Bone Turnover and Attenuates the Loss of Cortical Bone Caused by Estrogen Deficiency in Mice

ABSTRACT CXCL12 is abundantly expressed in reticular cells associated with the perivascular niches of the bone marrow (BM) and is indispensable for B lymphopoiesis. Cxcl12 promotes osteoclastogenesis and has been implicated in pathologic bone resorption. We had shown earlier that estrogen receptor α deletion in osteoprogenitors and estrogen deficiency in mice increase Cxcl12 mRNA and protein levels in the BM plasma, respectively. We have now generated female and male mice with conditional deletion of a Cxcl12 allele in Prrx1 targeted cells (Cxcl12∆Prrx1) and show herein that they have a 90% decrease in B lymphocytes but increased erythrocytes and adipocytes in the marrow. Ovariectomy increased the expression of Cxcl12 and B-cell number in the Cxcl12f/f control mice, but these effects were abrogated in the Cxcl12∆Prrx1 mice. Cortical bone mass was not affected in Cxcl12∆Prrx1 mice. Albeit, the cortical bone loss caused by ovariectomy was greatly attenuated. Most unexpectedly, the rate of bone turnover in sex steroid–sufficient female or male Cxcl12∆Prrx1 mice was dramatically increased, as evidenced by a more than twofold increase in several osteoblast- and osteoclast-specific mRNAs, as well as increased mineral apposition and bone formation rate and increased osteoclast number in the endosteal surface. The magnitude of the Cxcl12∆Prrx1-induced changes were much greater than those caused by ovariectomy or orchidectomy in the Cxcl12f/f mice. These results strengthen the evidence that CXCL12 contributes to the loss of cortical bone mass caused by estrogen deficiency. Moreover, they reveal for the first time that in addition to its effects on hematopoiesis, CXCL12 restrains bone turnover—without changing the balance between resorption and formation—by suppressing osteoblastogenesis and the osteoclastogenesis support provided by cells of the osteoblast lineage. © 2020 American Society for Bone and Mineral Research.

Ponte, Filipa (ORCID:0000000197133640)↗

DOE OSTI2026

Benchmarking of three DWM-based wake models at below-rated wind speeds

Wind turbine wake models are essential tools for predicting power losses and structural loads in wind farms. Among these, the dynamic wake meandering (DWM) model, included as a recommended approach in the International Electrotechnical Commission design standard, is a widely used engineering-fidelity method that balances accuracy and computational cost. This study compares the performance of three DWM-based wake model implementations (from the Technical University of Denmark, the National Renewable Energy Laboratory, and the Institute for Energy Technology) under below-rated wind speed conditions. Model predictions of wake flow, power output, and structural loads for a four-turbine row are evaluated across different ambient turbulence levels and wind-direction misalignments and compared against high-fidelity large-eddy simulation results. All three models captured the overall wake evolution and mean turbine performance with reasonable accuracy; their predicted time-averaged thrust and power were typically within 5 %–10 % of the large-eddy simulation benchmark. However, notable differences emerged in wake structure and unsteady load predictions, with discrepancies increasing for turbines further downstream. These differences highlight the importance of modelling choices such as wake summation and turbulence treatment, which strongly influence power-deficit and fatigue-load predictions. Comparison with large-eddy simulations reveals each approach's strengths and weaknesses, indicating where improvements are needed. Overall, the findings point to specific refinements for DWM models to improve their fidelity, ultimately enabling more robust wake predictions for wind farm design and operation.

17 WIND ENERGY↗

DOE OSTI2023

Power flow in magnetically insulated transmission lines with ion backscatter effects

Ion backscattering off of surfaces in magnetically insulated transmission lines (MITLs) is often ignored in kinetic simulations of MITL power flow. Backscattering reduces ion current losses and the surface impact heating, which dictates the rate at which surface-adsorbed contaminants are liberated into the anode–cathode gap. Backscatter probabilities are difficult to implement in a kinetic code because there are limited data for incident ion energies less than a few keV. This paper presents an analytic model based on the Rutherford scattering formula that reproduces the measured backscatter probabilities at high incident energies and transitions to the highly reflective behavior expected at low incident energies. The backscatter model is implemented in power flow simulations, which are validated with current loss experiments conducted on the 0.4 TW Mykonos accelerator at Sandia National Laboratories. This simulation setup is then used in a high-current Z-machine shot. In conclusion, backscatter effects are found to be unimportant in the low-current Mykonos regime but significantly reduce current losses at the Z-machine scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Arabidopsis stromal carbonic anhydrases exhibit non–overlapping roles in photosynthetic efficiency and development

Carbonic anhydrases (CAs) are ubiquitous enzymes that accelerate the reversible conversion of CO 2 to HCO 3 – . The Arabidopsis genome encodes members of the α-, β- and γ-CA families, and it has been hypothesized that βCA activity has a role in photosynthesis. In this work, we tested this hypothesis by characterizing the two plastidial βCAs, βCA1 and βCA5, in physiological conditions of growth. We conclusively established that both proteins are localized in the chloroplast stroma and that the loss of βCA5 induced the expression of βCA1, supporting the existence of regulatory mechanisms to control the expression of stromal βCAs. We also established that βCA1 and βCA5 have markedly different enzymatic kinetics and physiological relevance. Specifically, we found that βCA5 had a first-order rate constant ~10-fold lower than βCA1, and that the loss of βCA5 is detrimental to growth and could be rescued by high CO 2 . Furthermore, we established that, while a βCA1 mutation showed near wild-type growth and no significant impact on photosynthetic efficiency, the loss of βCA5 markedly disrupted photosynthetic efficiency and light-harvesting capacity at ambient CO 2 . Therefore, we conclude that in physiological autotrophic growth, the loss of the more highly expressed βCA1 does not compensate for the loss of a less active βCA5, which in turn is involved in growth and photosynthesis at ambient CO 2 levels. These results lend support to the hypothesis that, in Arabidopsis,βCAs have non-overlapping roles in photosynthesis and identify a critical activity of stromal βCA5 and a dispensable role for βCA1.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Temperature-dependent Battery Performance of a Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT Cathode and In-situ Heat Generation on Cycling

Excellent structural stability, high operating voltage, and high capacity have made Na 3 V 2 (PO 4 ) 2 F 3 a promising cathode material for sodium-ion batteries. However, high-temperature battery performances and heat generation measurements have not been systematically reported yet. Carbon-coated Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT (multi-walled carbon nanotube) samples are fabricated by a hydrothermal-assisted sol-gel method and the electrochemical performances are evaluated at three different temperatures (25, 45, and 55 °C). Furthermore, the well-crystallized Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT samples exhibit good cycling stability at both low and high temperatures; they deliver an initial discharge capacity of 120–125 mAhg -1 at a 1 C rate with a retention of 53 % capacity after 1,400 cycles with 99 % columbic efficiency. The half-cell delivers a capacity of 100 mAhg -1 even at a high rate of 10 C at room temperature. Furthermore, the Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT samples show good long-term durability; the capacity loss is an average of 0.05 % per cycle at a 1 C rate at 55 °C. Additionally, ionic diffusivity and charge transfer resistance are evaluated as functions of state of charge, and they explain the high electrochemical performance of the Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT samples. In-situ heat generation measurements reveal reversible results upon cycling owing to the high structural stability of the material. Excellent electrochemical performances are also demonstrated in the full-cell configuration with hard carbon as well as antimony Sb/C anodes.

25 ENERGY STORAGE↗

DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

DOE OSTI2025

Elevated Forest Canopy Loss After Wildfires in Moist and Cool Forests in the Pacific Northwest

Wildfire frequency, intensity, and rate of spread are increasing across the Western U.S, resulting in more severe ecosystem impacts. Significant tree mortality can occur years after fire events, but this has received little attention compared to the immediate tree loss during a fire. We overlapped forest cover loss data with burn severity maps in the U.S. Pacific Northwest and quantified the total and delayed forest canopy loss after fires. We found that wildfires resulted in total canopy loss fraction (CLF) of 84%, 53%, and 22% within 3 years in areas burned at high, moderate, and low severity, respectively. The delayed canopy loss accounted for approximately 1/3, 1/2, and 2/3 of the total canopy loss for high, moderate, and low severity burns. Delayed canopy loss was greater in moist and cool areas than in dry and warm areas, likely because tree species in wetter environments were less adapted to survive when fires did occur. Across all forests, delayed CLF doubled as temperature increased from the climatological mean to a hot anomaly and tripled as vapor pressure deficit increased from a wet anomaly to a dry anomaly. Fire impacts on forest ecosystems are likely to intensify under future climate scenarios as wildfires expand into areas that historically experienced infrequent fires. The impacts can also be exacerbated by more frequent compound extreme events, such as droughts, heatwaves, and fires. These findings highlight the urgent need for targeted forest management strategies, particularly in mesic forests, to mitigate future fire impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

DOE OSTI2025

Single-Objective Airy Light-Sheet Imaging

Despite its massive potential, standard light-sheet imaging (LSI) faces key challenges, such as the incompatibility with common sample mounting techniques and low-resolution imaging. Single-objective LSI attempts to address these issues but often suffers from limited fields-of-view and throughput rates, or requires multiple optics that increase costs, alignment complexity, and losses. To overcome these challenges of standard single-objective LSI, we introduce single-objective Airy light-sheet imaging (SoALSI). SoALSI leverages the extraordinary self-acceleration properties of the Airy beam, achieving 5× higher imaging rates and enhanced imaging efficiency than standard single-objective LSI. Here, we demonstrate SoALSI’s versatility through rigorous contrast and resolution characterizations and by high-resolution imaging of diverse biological specimens, including malaria parasite-infected red blood cells and plant root tissue. SoALSI seamlessly integrates with any standard inverted microscope frame, enabling broader accessibility for the bioimaging community to explore biological processes in a wide range of specimens with enhanced resolution and imaging contrast.

airy beam↗

DOE OSTI2025

Window Cooling Studies and Disk Vibration Testing on a Subset of Mo-100 Disks

Production of metastable Technetium-99 (Tc-99m), a radioactive tracer that emits gamma rays, is vital to the medical imaging community. Tc-99m is extracted from the decay of Molybdenum-99 (Mo-99) which has a half-life of about 2-3 days. The work presented in this report is part of the NNSA’s mission to produce Mo-99 commercially, within the US, without the use of highly enriched uranium (HEU) in support of nonproliferation and global security. Los Alamos National Laboratory (LANL) is working with NorthStar Medical Radioisotopes (NMR) on their efforts to produce Mo-99 through the irradiation of Mo-100 targets using an electron beam. The NMR target comprises a stack of approximately 60-70 Mo-100 disks with diameter 24 mm and thickness 0.74 mm held in stainless steel laminations, each separated using 0.25 mm thick stainless-steel spacers. The symmetric target stack is housed in an Inconel vessel with two Inconel windows on either side. Two electron accelerators are used to produce 40 MeV, 3.16 µA electron beams each that penetrate the Inconel windows and irradiate the Mo-100 disks. Approximately 90% of the total 250 kW beam power is deposited in the NMR target during the irradiation process, with a smaller percentage adding up to 2.2 kW of heat deposited on the Inconel window. During irradiation, pressurized helium gas flows through thin gaps between the disks cooling the beam window, target disks, disk laminations and spacers. Both NMR and LANL have found during cold testing of the target system (no heat deposition) that the Mo 100 disks undergo significant mass loss and disk breakage due to vibrations induced by the flowing helium gas. The mass loss is not only undesirable due to monetary loss from reduced final quantities of Mo-99, but also due to the hazards associated with radioactive material trapped in the cooling lines and particle filters. The effect of flow rate and target geometry on the flow induced vibrations need to be quantified, and recommendations provided to minimize this mass loss. LANL has previously also tested NMR’s Inconel beam window by heating the window, while flowing pressurized helium, using the average heat deposited on the window. However, the NMR beam is pulsed with a duty cycle of 12.5%, which introduces oscillation in temperature around the nominal 600 °C steady state value with each pulse. Available fatigue curves for Inconel are few, established for room temperature, and they are based on mechanical strain cycles not thermally induced strain as in the NMR target. The effect of pulsed beam heating on the Inconel window therefore needs to be quantified. This report details the experiments conducted to assess the factors that lead to mass loss in the NMR target disks as well as to understand the effect of a pulsed beam on NMR’s Inconel window. This work describes LANL’s experimental characterization of the flow induced vibrations and disk mass loss in a reduced scale set-up containing 5 to 10 Mo-100 disks. We use high speed imaging, displacement measurements and microphone measurements combined with signal processing to estimate the vibration frequency of each disk. The effect of disk thickness, target fit and duration of testing on the mass loss is described. We find that in the current configuration of NMR targets, the vibrations and mass loss on the first disk are minimized, while those in the adjacent disks are highest. The microphone and high-speed image data show that increased flow rates and increased duration of testing increases vibration frequency and mass loss. The mass loss is due to both disk rotation and back and forth motion. There are visible wear marks on the disks with the highest mass loss. We also note that the current NMR window gap reduces flow induced vibrations compared to the previous smaller gaps. Improved target holders significantly reduce disk mass loss to almost negligible quantities. This work finds that the larger window to first disk gap and improved target holder geometry should allow NMR to successfully conduct irradiations with minimal mass loss. The window tests were conducted to understand the effect of a pulsed beam on both the window longevity and to estimate the window temperature and displacement during pulsing. The experiments presented here were performed at significantly low power, due to the limitations of the induction heating system. The window temperature rose to approximately 73 °C with a significantly reduced power of 45 W without beam pulsing. With a 5 Hz pulse rate, 12.5% duty cycle, the window temperature remained constant at 26 °C. These experiments will be repeated with improved coil geometry and reported in upcoming journal papers.

42 ENGINEERING↗

DOE OSTI2024

Dynamic gain and frequency comb formation in exceptional-point lasers

Abstract Exceptional points (EPs)—singularities in the parameter space of non-Hermitian systems where two nearby eigenmodes coalesce—feature unique properties with applications such as sensitivity enhancement and chiral emission. Existing realizations of EP lasers operate with static populations in the gain medium. By analyzing the full-wave Maxwell–Bloch equations, here we show that in a laser operating sufficiently close to an EP, the nonlinear gain will spontaneously induce a multi-spectral multi-modal instability above a pump threshold, which initiates an oscillating population inversion and generates a frequency comb. The efficiency of comb generation is enhanced by both the spectral degeneracy and the spatial coalescence of modes near an EP. Such an “EP comb” has a widely tunable repetition rate, self-starts without external modulators or a continuous-wave pump, and can be realized with an ultra-compact footprint. We develop an exact solution of the Maxwell–Bloch equations with an oscillating inversion, describing all spatiotemporal properties of the EP comb as a limit cycle. We numerically illustrate this phenomenon in a 5-μm-long gain-loss coupled AlGaAs cavity and adjust the EP comb repetition rate from 20 to 27 GHz. This work provides a rigorous spatiotemporal description of the rich laser behaviors that arise from the interplay between the non-Hermiticity, nonlinearity, and dynamics of a gain medium.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Modeling the Contribution of Precipitation Loss to a Radiation Belt Electron Dropout Observed by Van Allen Probes

A drift-diffusion model is used to simulate the low-altitude electron distribution, accounting for azimuthal drift, pitch angle diffusion, and atmospheric backscattering effects during a rapid electron dropout event on 21st August 2013, at L = 4.5. Additional external loss effects are introduced during times when the low-altitude electron distribution cannot be reproduced by diffusion alone. Here, the model utilizes low-altitude electron count rate data from five POES/MetOp satellites to quantify pitch angle diffusion rates. Low-altitude data provides critical constraint on the model because it includes the drift loss cone region where the electron distribution in longitude is highly dependent on the balance between azimuthal drift and pitch angle diffusion. Furthermore, a newly derived angular response function for the detectors onboard POES/MetOp is employed to accurately incorporate the bounce loss cone measurements, which have been previously contaminated by electrons from outside the nominal field-of-view. While constrained by low-altitude data, the model also shows reasonable agreement with high-altitude data. Pitch angle diffusion rates during the event are quantified and are faster at lower energies. Precipitation is determined to account for all of the total loss observed for 450 keV electrons, 88% for 600 keV and 38% for 900 keV. Predictions made in the MeV range are deemed unreliable as the integral energy channels E3 and P6 fail to provide the necessary constraint at relativistic energies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Nonlinear viscoelastic response of silicone additively manufactured direct ink write (DIW) foams under repetitive compression

To investigate dynamic fatigue behavior of foam in military protective applications, such as helmets, additively manufactured (AM) foams were compressively strained into the plateau region using a reduced design of experiments. A simple power law was found to govern the decline in dynamic stiffness (complex modulus) as the foams underwent the purchase order requirement of 10,000 cycles of small deformation in the plateau region. This rate of decline was newly found to correlate with the degree of nonlinearity in the material’s deformation, quantified using total harmonic distortion. Materials with low nonlinearity exhibited relatively stable stiffness across cycles, while those with high nonlinearity experienced greater losses. The observed nonlinearity depended on both applied stress and strain rate. A strong linear correlation (R 2 = 0.78) was identified between second-order nonlinearity and the time-dependent stiffness response. Two lattice structures were examined: face-centered tetragonal (FCT) and simple cubic (SC). The SC material exhibited higher total harmonic distortion (5%) and lower stiffness retention than the FCT (2%). In conclusion, these results suggest that for cyclic compression applications in a wide variety of industries such as packaging, personal protective equipment, or aerospace, selecting materials with lower stress and greater structural uniformity can enhance the stability of dynamic performance.

42 ENGINEERING↗

DOE OSTI2023

Flow Induced Vibration Studies in Pressurized Helium Gas Cooling Channels

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Chemical Kinetics of the Autoxidation of Poly(ethylenimine) in CO 2 Sorbents

The oxidative degradation rates of a CO 2 sorbent composed of a mesoporous alumina impregnated with poly- (ethylenimine) (PEI) are measured under systematically varied conditions and a reaction rate law is created. Good agreement is shown between the rate of oxidation obtained via in situ calorimetric heat measurement during oxidative degradation reactions and the loss of CO 2 capture performance presented as amine efficiency (mol CO 2 /mol amine). PEI mass loss and elemental composition are tracked over the course of the reaction and used in conjunction with the oxidation rate measurements to shed insight into the oxidation reaction(s). These data, in combination with measurements of the heat of reaction, suggest a common reaction set across the range of temperatures, oxygen concentrations, and sorbent compositions tested. The data are consistent with the basic autoxidation scheme (BAS), the accepted mechanism of autoxidation of aliphatic polymers. We propose a lumped kinetic model to describe the oxidation reaction set and estimate an activation energy of 105 kJ/mol and an oxygen reaction order of 0.5–0.7 from the data accordingly. Furthermore, these parameters can be incorporated into process cycle models to estimate the material lifetime, a critical uncertainty in the deployment of DAC technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2023

SAS4A/SASSYS-1 Validation with EBR-II Tests Performed During the SHRT Testing Program (Rev. 2)

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates. This report documents the results of modeling and simulation of tests from the Shutdown Heat Removal Test program to support validation of Argonne’s SAS4A/SASSYS-1 fast reactor safety analysis code. SHRT-17 and SHRT-6 were protected loss of flow tests where a loss of electrical power to all sodium coolant pumps was simulated to demonstrate the effectiveness of natural circulation cooling characteristics. SHRT-45R, SHRT-39, and SHRT-43R were unprotected loss of flow tests where the control rod scram function of the plant protection system was disabled to demonstrate the effectiveness of EBR-II’s passive reactivity feedbacks. BOP-301 and BOP-302R were unprotected loss of heat sink tests that demonstrated how reactivity feedback effects driven by changes to the core inlet temperature can shut down the fission process. PICT-5/6 demonstrated how core power could be increased and decreased via changes in the intermediate sodium and feedwater flow rates. This validation activity leverages modeling and simulation efforts that originated under an International Atomic Energy Agency Coordinated Research Project for benchmark analysis of the EBR-II Shutdown Heat Removal Tests. The SAS4A/SASSYS-1 models originally developed for the CRP have been modernized to utilize new code features and modeling practices. Differences between the predicted and measured test data were explored and the causes of these differences were identified as being due to modeling approximations, uncertainty in transient component behavior, and instrumentation uncertainties. Overall, it was concluded that for all tests simulated there was good agreement between the flow, power, and temperature predictions and the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

Identifying unseen electromagnetic waveforms is critical for many applications, like interference management, electronic warfare and spectrum management. Traditionally this is done using statistical methods for anomaly detection, which has evolved to deep learning models for identifying the unseen data, formally termed as open set recognition. Some prior methods use a generative model to emulate open set data, which face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. To alleviate this issue, we propose a discriminative model that effectively combines time and frequency domain features of communication signals for accurate predictions. We further introduce a cosine similarity loss that makes the domain specific features unique to enhance the prediction rate. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗