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At least 649 records · Page 36

Mitigation Methods for Piperazine Oxidation in Post-Combustion Carbon Capture

Piperazine is a promising second-generation solvent for amine scrubbing in post-combustion CO2 capture. However, the oxidative degradation of PZ can cause environmental problems and economic loss. This work presents the effects of two mitigation methods: carbon treating and N2 sparging, on the PZ oxidation in long-term operations. The species and their respective quantities adsorbed by the activated carbon were tested in a bench-scale device. The carbon was then tested in the High Temperature Oxidation Reactor (HTOR), where the solvent oxidizes at a reasonably fast rate. Pilot plant campaigns were also performed at the UT Austin SRP and the National Carbon Capture Center (NCCC) and the effects were verified. When dissolved Fe is removed by carbon treating or other methods, available soluble Fe in the system dissolves and replaces the dissolved Fe. Therefore, all available Fe and ligands need to be removed for the mitigation to be effective. The sources of soluble Fe include fly ash and the corrosion of stainless steel, and the ligands are degradation products. 8 All PZ degraded solvents have two absorbance peaks at 320 nm and 538 nm. The 320 nm peak is caused by dissolved metals, especially Fe, complexed by degradation products. The 320 nm peak is related to the amine degradation level and can be used as a simple and efficient method to estimate the amine degradation rate. The pilot plant data suggest that NO2 can oxidize PZ significantly, possibly through radical reactions. 0.01 mmol/kg-hr absorption of NO2 increased the PZ oxidation rate from 1.2 mmol/kg-hr to 2.5 mmol/kg-hr.

Yuying, Wu↗

High-Nickel Cathode Materials for High-Energy, Long-Life, Low-Cost Lithium-Ion Batteries (Final Report)

The overall goal of this project is to produce Li-ion cells, which deliver at least 600 Wh kg -1 at the cathode level with usable lifetimes of at least 1,000 cycles or 15 years of storage (calendar life). A secondary goal of this project is to minimize the use of cobalt in the cathode, with the ultimate goal of eliminating cobalt entirely. To develop such a cathode, the University of Texas at Austin (UT Austin) team extensively investigated the structural, physical, and chemical properties of layered oxide materials. A panel of dopant elements were surveyed with an emphasis on identifying those, which impart electrochemical and thermal stability. Of those tested, Al and Mg showed the greatest performance improvements while still being easily incorporated into the cathode through simple alterations of the precursor coprecipitation method. Other dopants, such as Ta, Nb, B, and F significantly improved cathode performance, yet their mode of incorporation required additional processing which negated their use under scaled-up conditions. From this work, a first-generation cathode LiNi 0.85 Mn 0.075 Co 0.05 Al 0.02 Mg 0.005 O 2 (NMCAM-85) was produced and an initial set of 2 Ah cells was fabricated by Tesla Inc. These cells delivered 650 Wh kg -1 and a cycle life of just over 700 cycles. Further improvements were garnered through careful study of electrolyte additives. A tailored, ethylene carbonate (EC)-free electrolyte was developed, which improved capacity retention from 60% to 82% after 500 cycles in model LiNi 0.9 Mn 0.05 Al 0.05 O 2 (NMA-90) full cells. This study identified the additives fluoroethylene carbonate (FEC) and lithium difluorophosphate (LiPO 2 F 2 ) as beneficial additives, which were included in the electrolyte for the end-of-project cells. The UT Austin team developed a high-Ni layered oxide cathode LiNi 0.85 Mn 0.1 Al 0.05 Mg 0.005 O 2 (NMAM-85) capable of meeting the project goals. This cathode was synthesized in kilogram quantities and delivered to Tesla for fabrication into 2 Ah pouch cells for DOE testing. These large-format cells achieved 630 Wh kg -1 at the cathode level under the designated testing parameters, meeting the project goal with a completely cobalt-free cathode. The large-format cells are currently undergoing cycle life and calendar life evaluation at Idaho National Lab.

25 ENERGY STORAGE↗

Investigation of fuel film formation and soot emissions in a GDI engine during cold-start with Split-injection strategies

This study investigates the impact of fuel-film formation on engine-out soot emissions in a gasoline direct injection (GDI) engine under cold-start conditions. Split-injection strategies were applied by varying the number of injections, injection duration, and total fuel quantity to affect wall wetting and control the average in-cylinder equivalence ratio. A combined experimental and numerical approach was employed to analyze fuel-film deposition, combustion efficiency, and engine-out soot and unburnt hydrocarbons (UHC) emissions. In particular, fuel film distribution estimated by means of non-reacting, 3-D, computational fluid dynamics (CFD) simulations, together with experimentally measured soot data, were used to investigate fuel film formation and its role in soot generation. In the experiments, a skip-fired engine control strategy was applied to mimic the transient nature of engine cold-start operation. The results indicate that, under the same total number of injections, increasing the average in-cylinder equivalence ratio through longer injection durations improves combustion stability, as indicated by the decrease of the coefficient of variation of IMEP n (Net Indicated Mean Effective Pressure) from 6.0 % to 0.6 %. However, this strategy leads to higher soot emissions, which increased by nearly an order of magnitude, primarily due to enhanced wall-film formation. In contrast, increasing the number of injections while maintaining a constant equivalence ratio significantly impacts fuel-film deposition and, consequently, soot emissions, with a fivefold reduction of the measured engine-out soot, decreasing from 3.5 mg to 0.7 mg. A soot-film correlation was developed and achieved a high coefficient of determination (r 2 = 0.95) and was further extended to account for spark timing effects. These findings confirm the effectiveness of split-injection for avoiding wall film formation and soot emissions, and the critical role of fuel film in soot generation, supporting the hypothesis that pool fires play a crucial role in contributing to soot formation under these cold-start conditions. In conclusion, the study also indicates the value of a predictive soot-film correlation for developing cold-start emission control strategies.

Engine Cold-start↗

Microcanonical rates from ring-polymer molecular dynamics: Direct-shooting, stationary-phase, and maximum-entropy approaches

We address the calculation of microcanonical reaction rates for processes involving significant nuclear quantum effects using ring-polymer molecular dynamics (RPMD), both with and without electronically non-adiabatic transitions. After illustrating the shortcomings of the naive free-particle direct-shooting method, in which the temperature of the internal ring-polymer modes is set to the translational energy scale, we investigate alternative strategies based on the expression for the microcanonical rate in terms of the inverse Laplace transform of the thermal reaction rate. It is shown that simple application of the stationary-phase approximation (SPA) dramatically improves the performance of the microcanonical rates using RPMD, particularly in the low-energy region where tunneling dominates. Using the SPA as a Bayesian prior, numerically exact RPMD microcanonical rates are then obtained using maximum entropy inversion of the thermal reaction rates for both electronically adiabatic and non-adiabatic model systems. Finally, the direct-shooting method is revisited using the SPA-determined temperature for the internal ring-polymer modes, leading to a simple, direct-simulation method with improved accuracy in the tunneling regime. This work suggests a general strategy for the extraction of microcanonical dynamical quantities from RPMD (or other approximate thermal) simulations.

Tao, Xuecheng↗

Uncertainty about the Uncertainty [Slides]

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable result in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates, in comparison to the measurement uncertainty. Range of true values depends on the physics of the experiment, while measurement uncertainty depends on the measurement method (properties of the detector not of the experiment). When data from one–of–a kind experiment are analyzed, only the measurement uncertainty is reported. It gives no information about the range, in which the true values of experiment would spread if the experiment was repeated. A frequently used approximation, that if a physical quantity is measured as a function of time, only measurement of this quantity, produces uncertainty is also in some real experiments fare to strong. Example: In reaction history time measurement uncertainty propagated to alpha dominated under certain conditions over the flux measurement uncertainty propagated to alpha. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Nonlinear photoconductivities and quantum geometry of chiral multifold fermions

Here, chiral multifold fermions are quasiparticles that appear only in chiral crystals such as transition metal silicides in the cubic B20 structure (i.e., the CoSi family), and they may show exotic physical properties. Here we study the injection and shift photoconductivities and also the related geometrical quantities for several types of chiral multifold fermions, including spin-1/2 as well as pseudospin-1 and -3/2 fermions, dubbed as Kramers Weyl, triple-point, and Rarita-Schwinger-Weyl (RSW) fermions, respectively. We utilize the minimal symmorphic model to describe the triple-point fermions (TPF). We also consider the more realistic model Hamiltonian for the CoSi family including both linear and quadratic terms. We find that injection currents due to circularly polarized light are quantized as a result of the Chern numbers carried by the multifold fermions within the linear models. Surprisingly, we discover that in the TPF model, the linear shift conductivities, responsible for the shift current generation by linearly polarized light, are proportional to the pseudo spin-orbit coupling and independent of photon frequency. In contrast, for the RSW and Kramer Weyl fermions, the linear shift conductivity is linearly proportional to photon frequency. The numerical results agree with the power-counting analysis for quadratic Hamiltonians. The frequency independence of the linear shift conductivity could be attributed to the strong resonant symplectic Christoffel symbols of the flat bands. Moreover, the calculated symplectic Christoffel symbols show significant peaks at the nodes, suggesting that the shift currents are due to the strong geometrical response near the topological nodes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Sensitivity analysis, surrogate modeling, and optimization of pebble-bed reactors considering normal and accident conditions

This research provides a valuable tool that streamlines the optimization process while significantly increasing its accuracy. This study creates a robust framework for reactor design optimization by incorporating comprehensive modeling using the Comprehensive Reactor Analysis Bundle, or BlueCRAB, within the Multiphysics Object-Oriented Simulation Environment (MOOSE). BlueCRAB is the United States Nuclear Regulatory Commission's code suite for non-light water reactor analysis and includes the Griffin, Pronghorn, and Bison applications. This not only improves the efficiency of the optimization process but also enhances the reliability of the results. Such a tool is essential for advancing the state-of-the-art in pebble-bed reactor technology and is critical for achieving the goals of Generation IV reactors, which aim for safe, sustainable, and economically viable nuclear energy solutions. This work presents and applies this workflow on pebble-bed reactors while considering both normal and off-normal conditions. A representative gas-cooled pebble-bed reactor at equilibrium core conditions serves as the nominal design specification for normal operation and is based on previous research. The depressurized loss-of-forced-cooling accident is deployed for off-normal conditions in this work. After defining design-related parameters and quantities of interest regarding reactor safety and performance, this multiphysics model is sampled using the MOOSE stochastic tools module. The result is a comprehensive dataset of configurations, enabling sensitivity analysis and the generation of surrogate models. Subsequently, the dataset and surrogate models are employed in two optimization studies aimed at maximizing fuel utilization and economic profit while adhering to safety and operational constraints. Performing the optimization process with fuel utilization as the metric leads to an improvement of approximately 10%, compared to engineering-judgment-based nominal conditions. The optimization on economic profit leads to an estimated increase of ~300 million USD over the lifetime of the reactor.

97 MATHEMATICS AND COMPUTING↗

BeyondPlanck: I. Global Bayesian analysis of the Planck Low Frequency Instrument data

We describe the BEYONDPLANCK project in terms of our motivation, methodology, and main products, and provide a guide to a set of companion papers that describe each result in more detail. Building directly on experience from ESA’s Planck mission, we implemented a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations. The primary product is a full joint posterior distribution P(ω | d), where ω represents the set of all free instrumental (gain, correlated noise, bandpass, etc.), astrophysical (synchrotron, free-free, thermal dust emission, etc.), and cosmological (cosmic microwave background – CMB – map, power spectrum, etc.) parameters. Some notable advantages of this approach compared to a traditional pipeline procedure are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. As a practical demonstration of this framework, we focus in particular on low-ℓ CMB polarization reconstruction with Planck LFI. In this process, we identify several important new effects that have not been accounted for in previous pipelines, including gain over-smoothing and time-variable and non-1/f correlated noise in the 30 and 44 GHz channels. Modeling and mitigating both previously known and newly discovered systematic effects, we find that all results are consistent with the ΛCDM model, and we constrained the reionization optical depth to τ = 0.066 ± 0.013, with a low-resolution CMB-based χ 2 probability to exceed of 32%. This uncertainty is about 30% larger than the official pipelines, arising from taking a more complete instrumental model into account. The marginal CMB solar dipole amplitude is 3362.7 ± 1.4 μK, where the error bar was derived directly from the posterior distribution without the need of any ad hoc instrumental corrections. We are currently not aware of any significant unmodeled systematic effects remaining in the Planck LFI data, and, for the first time, the 44 GHz channel is fully exploited in the current analysis. We argue that this framework can play a central role in the analysis of many current and future high-sensitivity CMB experiments, including LiteBIRD, and it will serve as the computational foundation of the emerging community-wide COSMOGLOBE effort, which aims to combine state-of-the-art radio, microwave, and submillimeter data sets into one global astrophysical model.

79 ASTRONOMY AND ASTROPHYSICS↗

What Is the Limit of Quantification for the Minor Phase in Time-of-Flight Neutron Diffraction? A Case Study on Fe and Ni Powder Mixtures at VULCAN

A phase present in small quantities within materials may not simply serve as a secondary component; it can play a crucial role in determining the integrity, properties, and performance of the material. These minor but important phases usually draw attention in material design and processing for fundamental understanding as well as material quality control. Accurately quantifying a minor phase amid a majority phase, especially at extremely low fractions, remains a challenging task. Time-of-flight neutron diffraction, coupled with advanced pattern analysis techniques like Rietveld refinement, is a powerful tool for crystal structure identification and phase quantification. The deep penetrating capability of neutrons enables the detection and quantification of trace phases within materials. In this study, the quantification limits of time-of-flight neutron diffraction were explored using the VULCAN diffractometer at the Spallation Neutron Source, using Fe–Ni powder mixtures as a sample system. By comparing the refinement results to the known weighed values, it was determined that the reliable quantification of a minor Ni phase is achievable down to about 0.1 wt% while a Ni fraction as low as 0.02 wt% is difficult to trace. Effective control of the refinement parameters, especially the profile function parameters, are found to significantly influence the convergence of fittings and the accuracy of phase quantification.

Rietveld refinement↗

Investigation of Thermolytic Hydrogen Generation Rate in Tank 44 Dissolved Saltcake Samples

Saltcake core samples collected from Tank 44 in 2006 were dissolved to provide material for HGR measurements applicable to F-Area dissolved saltcake material. Additionally, characterization was performed on the Tank 44 saltcake material. The following are key results from the Tank 44 saltcake characterization. The Tank 44 Upper Saltcake Composite, corresponding to the 171 to 285 inch tank level, contained by mass approximately 69% sodium nitrate, 11% sodium carbonate, 8% sodium nitrite, smaller amounts of other salts and components, and 9% unquantified (which includes water, water of hydration, oxygen/hydrogen content of oxides and hydroxides, and uncertainty). The Tank 44 Lower Saltcake Composite, corresponding to the 76 to 114 inch tank level, contained by mass approximately 49% sodium carbonate, 18% sodium nitrate, smaller amounts of other salts, at least 8% sludge, and 9% unquantified (see above). The dissolved saltcake contained free hydroxide less than quantifiable (<0.01 M) due to the limited quantity of material that could be removed from the Shielded Cells based on the sample radioactivity. Measurement by pH paper provided an approximate pH of 12. The following are key results from the Tank 44 HGR testing. During boiling at 106.7 °C, HGR for Tank 44 dissolved saltcake without added glycolate was 7.2×10 -8 ft 3 h -1 gal -1 . During boiling at 106.9 °C, HGR for Tank 44 dissolved saltcake with 1000 mg/L of added glycolate was 8.2×10 -8 ft 3 h -1 gal -1 . For the test without added glycolate, the first several HGR measurements at 70, 85, and 100 °C gave indication of the release of dissolved hydrogen and should not be used to represent the sustained thermolytic HGR for those temperatures. The measurements at boiling are the best representation of thermolysis in this testing. Carbon dioxide was observed at concentrations up to 6 vol% in the flow-system offgas for the test at boiling. Methane generation was observed at 100 °C and boiling. Methane concentration in the total gas generated during testing remained well below the lower flammability limit for methane in air. The addition of 1000 mg/L of glycolate did not have a significant impact on the hydrogen generation rates measured during this testing. The low hydroxide concentration in the Tank 44 dissolved saltcake likely influenced the relatively low thermolytic HGR and high carbon dioxide release observations in this testing. Based on the observation that methane was generated or released upon heating SRS radioactive Tank 44 waste samples to 100 °C and above, we recommend gaining a greater understanding of the cause and mechanism of its generation. First, the applicable literature should be reviewed to reveal the thermolytic methane generation mechanisms of possible methane generating species in the SRS CSTF. If warranted, a plan should be developed for simulant tests with methylated siloxanes and other applicable compounds in order to gain a better mechanistic understanding of methane generation in the SRS CSTF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Investigation of Thermolytic Hydrogen Generation Rate in Tank 44 Dissolved Saltcake Samples

Saltcake core samples collected from Tank 44 in 2006 were dissolved to provide material for HGR measurements applicable to F-Area dissolved saltcake material. Additionally, characterization was performed on the Tank 44 saltcake material. The following are key results from the Tank 44 saltcake characterization. The Tank 44 Upper Saltcake Composite, corresponding to the 171 to 285 inch tank level, contained by mass approximately 69% sodium nitrate, 11% sodium carbonate, 8% sodium nitrite, smaller amounts of other salts and components, and 9% unquantified (which includes water, water of hydration, oxygen/hydrogen content of oxides and hydroxides, and uncertainty). The Tank 44 Lower Saltcake Composite, corresponding to the 76 to 114 inch tank level, contained by mass approximately 49% sodium carbonate, 18% sodium nitrate, smaller amounts of other salts, at least 8% sludge, and 9% unquantified (see above). The dissolved saltcake contained free hydroxide less than quantifiable (<0.01 M) due to the limited quantity of material that could be removed from the Shielded Cells based on the sample radioactivity. Measurement by pH paper provided an approximate pH of 12. The following are key results from the Tank 44 HGR testing. During boiling at 106.7 °C, HGR for Tank 44 dissolved saltcake without added glycolate was 7.2×10 -8 ft 3 h -1 ga l-1 . During boiling at 106.9 °C, HGR for Tank 44 dissolved saltcake with 1000 mg/L of added glycolate was 8.2×10 -8 ft 3 h -1 gal -1 . ∙ For the test without added glycolate, the first several HGR measurements at 70, 85, and 100 °C gave indication of the release of dissolved hydrogen and should not be used to represent the sustained thermolytic HGR for those temperatures. The measurements at boiling are the best representation of thermolysis in this testing. Carbon dioxide was observed at concentrations up to 6 vol% in the flow-system offgas for the test at boiling. ∙ Methane generation was observed at 100 °C and boiling. Methane concentration in the total gas generated during testing remained well below the lower flammability limit for methane in air. The addition of 1000 mg/L of glycolate did not have a significant impact on the hydrogen generation rates measured during this testing. The low hydroxide concentration in the Tank 44 dissolved saltcake likely influenced the relatively low thermolytic HGR and high carbon dioxide release observations in this testing. Based on the observation that methane was generated or released upon heating SRS radioactive Tank 44 waste samples to 100 °C and above, we recommend gaining a greater understanding of the cause and mechanism of its generation. First, the applicable literature should be reviewed to reveal the thermolytic methane generation mechanisms of possible methane generating species in the SRS CSTF. If warranted, a plan should be developed for simulant tests with methylated siloxanes and other applicable compounds in order to gain a better mechanistic understanding of methane generation in the SRS CSTF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The discrete Green's function paradigm for two-way coupled Euler–Lagrange simulation

We outline a methodology for the simulation of two-way coupled particle-laden flows. The drag force that couples fluid and particle momentum depends on the undisturbed fluid velocity at the particle location, and this latter quantity requires modelling. We demonstrate that the undisturbed fluid velocity, in the low particle Reynolds number limit, can be related exactly to the discrete Green's function of the discrete Stokes equations. In addition to hydrodynamics, the method can be extended to other physics present in particle-laden flows such as heat transfer and electromagnetism. The discrete Green's functions for the Navier–Stokes equations are obtained at low particle Reynolds number in a two-plane channel geometry. We perform verification at different Reynolds numbers for a particle settling under gravity parallel to a plane wall, for different wall-normal separations. Compared with other point-particle schemes, the Stokesian discrete Green's function approach is the most robust at low particle Reynolds number, accurate at all wall-normal separations. To account for degradation in accuracy away from the wall at finite Reynolds number, we extend the present methodology to an Oseen-like discrete Green's function. The extended discrete Green's function method is found to be accurate within 6% at all wall-normal separations for particle Reynolds numbers up to 24. Furthermore, the discrete Green's function approach is well suited to dilute systems with significant mass loading and this is highlighted by comparison against other Euler–Lagrange as well as particle-resolved simulations of gas–solid turbulent channel flow. Strong particle–turbulence coupling is observed in the form of turbulence modification and turbophoresis suppression, and these observations are placed in context of the different methods.

42 ENGINEERING↗

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

Non-invasive characterization of complex coronary lesions

Conventional invasive diagnostic imaging techniques do not adequately resolve complex Type B and C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes. These lesions are often excluded from large-scale non-invasive clinical trials and there does not exist a validated approach to characterize hemodynamic quantities and guide percutaneous intervention for such lesions. This work identifies key biomarkers that differentiate complex Type B and C lesions from simple Type A lesions by introducing and validating a coronary angiography-based computational fluid dynamic (CFD-CA) framework for intracoronary assessment in complex lesions at ultrahigh resolution. Among 14 patients selected in this study, 7 patients with Type B and C lesions were included in the complex lesion group including ostial, bifurcation, serial lesions and lesion where flow was supplied by collateral bed. Simple lesion group included 7 patients with lesions that were discrete, <10mm long and readily accessible. Intracoronary assessment was performed using CFD-CA framework and validated by comparing to clinically measured pressure-based index, such as FFR. Local pressure, endothelial shear stress (ESS) and velocity profiles were derived for all patients. We validates the accuracy of our CFD-CA framework and report excellent agreement with invasive measurements (n=14,R 2 =0.6,p=0.0013). Ultra-high resolution achieved by the model enable physiological assessment in complex lesions and quantify hemodynamic metrics in all vessels up to 1mm in diameter. Importantly, we demonstrate that in contrast to traditional pressure-based metrics, there is a significant difference in the intracoronary hemodynamic forces, such as ESS, in complex lesions compared to simple lesions at both resting and hyperemic physiological states [n = 14, p=0.03]. Higher ESS was observed in the complex lesion group (7.0±4.7 Pa) than in simple lesion group (4.8±3.6 Pa). Complex coronary lesions have higher ESS compared to simple lesions, such differential hemodynamic evaluation can provide much the needed insight into the increase in adverse outcomes for such patients and has incremental prognostic value over traditional pressure-based indices, such as FFR.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quantification of Aerosol Transmission through Stress Corrosion Crack-Like Geometries

The formation of a stress corrosion crack (SCC) in the canister wall of a dry cask storage system (DCSS) has been identified as a potential issue for the long-term storage of spent nuclear fuel. The presence of an SCC in a storage system could represent a through-wall flow path from the canister interior to the environment. Modern, vertical DCSSs are of particular interest due to the commercial practice of using more significant backfill pressures in the canister, up to approximately 800 kPa. This pressure differential offers a relatively high driving potential for blowdown of any particulates that might be present in the canister. In this study, the rates of gas flow and aerosol transmission of a spent fuel surrogate through an engineered microchannel with dimensions representative of an SCC were evaluated experimentally using coupled mass flow and aerosol analyzers. The microchannel was formed by mating two gage blocks with a linearly tapering slot orifice nominally 13 μm (0.005 in.) tall on the upstream side and 25 μm (0.0010 in.) tall on the downstream side. The orifice is 12.7 mm (0.500 in.) wide by 8.86 mm (0.349 in.) long (flow length). Surrogate aerosols of cerium oxide, CeO 2 , were seeded and mixed with either helium or air inside a pressurized tank. The aerosol characteristics were measured immediately upstream and downstream of the simulated SCC at elevated and ambient pressures, respectively. These data sets are intended to add to previous testing that characterized SCCs under well-controlled boundary conditions through the inclusion of testing improvements that establish initial conditions in a more consistent way. These ongoing testing efforts are focused on understanding the evolution in both size and quantity of a hypothetical release of aerosolized spent fuel particles from failed fuel to the canister interior and ultimately through an SCC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Regulatory Considerations for Domestic Reprocessing Facility Physical Security

U.S. advanced non-light-water reactor vendors may pursue collocated on-site reprocessing activities. Therefore, these facilities are likely to possess formula quantities, or Category I quantities, of special nuclear material (SNM) during normal operations. The U.S. Nuclear Regulatory Commission (U.S. NRC) has yet to formally establish a regulatory framework for commercial reprocessing. While Category I requirements would explicitly not apply in this circumstance under current regulatory requirements, regulatory certainty does not exist. A novel framework should be developed to ensure public health and safety while also risk-informing the physical security requirements. This report reviews the relevant background of related rulemaking activities and proposes risk-informed physical protection requirements to satisfy these objectives. Insights from NRC security-related rulemaking activities provide a substantial technical basis to approach potential establishment of physical security requirements for reprocessing facilities. If a licensee can provide justification that the material satisfies a sufficient self-protecting radiation dose threshold, the material may not be subject to theft or diversion requirements and only potential sabotage requirements would apply. Furthermore, if the material can be justified to be moderately dilute, a set of risk-informed requirements could provide adequate protection of public health and safety. A revised performance objective for prevention of theft of moderately dilute Category I SNM may be detection to allow prompt recovery by a local law enforcement agency. However, a significant caveat to the proposed categorization scheme is the unknown integration of radiological sabotage with requirements for the protection against theft. Future licensees should consult with the NRC regarding treatment of this regulatory topic. Additionally, the self-protecting radiation dose threshold (either the existing or a proposed future threshold) would need to be considered. An integrated approach may apply graded potential requirements for protection against the design basis threat of radiological sabotage currently applicable to commercial nuclear power plants and Category I SNM facilities defined within 10 CFR 73.1(a).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗

The anomalous magnetic moment of the muon in the Standard Model

We review the present status of the Standard Model calculation of the anomalous magnetic moment of the muon. This is performed in a perturbative expansion in the fine-structure constant α and is broken down into pure QED, electroweak, and hadronic contributions. The pure QED contribution is by far the largest and has been evaluated up to and including O(α 5 ) with negligible numerical uncertainty. The electroweak contribution is suppressed by (m μ / M W ) 2 and only shows up at the level of the seventh significant digit. It has been evaluated up to two loops and is known to better than one percent. Hadronic contributions are the most difficult to calculate and are responsible for almost all of the theoretical uncertainty. The leading hadronic contribution appears at O(α 2 ) and is due to hadronic vacuum polarization, whereas at O(α 3 ) the hadronic light-by-light scattering contribution appears. Given the low characteristic scale of this observable, these contributions have to be calculated with nonperturbative methods, in particular, dispersion relations and the lattice approach to QCD. The largest part of this review is dedicated to a detailed account of recent efforts to improve the calculation of these two contributions with either a data-driven, dispersive approach, or a first- principle, lattice-QCD approach. The final result reads $a$$^{SM}_{μ}$ = 116 591 810(43) × 10 −11 and is smaller than the Brookhaven measurement by 3.7σ. The experimental uncertainty will soon be reduced by up to a factor four by the new experiment currently running at Fermilab, and also by the future J-PARC experiment. Furthermore, this and the prospects to further reduce the theoretical uncertainty in the near future – which are also discussed here – make this quantity one of the most promising places to look for evidence of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗