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Spectral function for 4 He using the Chebyshev expansion in coupled-cluster theory

Here, we compute spectral function for 4 He by combining coupled-cluster theory with an expansion of integral transforms into Chebyshev polynomials. Our method allows us to estimate the uncertainty of spectral reconstruction. The properties of the Chebyshev polynomials make the procedure numerically stable and considerably lower in memory usage than the typically employed Lanczos algorithm. We benchmark our predictions with other calculations in the literature and with electron-scattering data in the quasi-elastic peak. The spectral function formalism allows one to extend ab initio lepton-nucleus cross sections into the relativistic regime. This makes it a promising tool for modeling this process at higher-energy transfers. The results we present open the door for studies of heavier nuclei, important for the neutrino oscillation programs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Progress on Computational Modeling of Water-Based NSTF (FY2021)

This report documents the FY21 progress and achievements made in the computational analyses of the water-based NSTF. Both system-level and high-fidelity Computational Fluid Dynamics (CFD) analyses were performed to gain a complete understanding of the complex flow and heat transfer phenomena in natural convection systems. The progress on the waterbased NSTF experimental testing is summarized in a companion report (ANL-ART-230). As a continuation of progress from previous years, in FY21 the RELAP5 model of the NSTF was first updated to include a representative heated cavity that incorporated convection and conduction means of heat transfer. Two different cavity models were developed, one that models the radiation heat exchange among all surfaces in one enclosure (Cavity Model 1), and another that employs multiple radiation enclosures with each considering the surfaces at one axial level (Cavity Model 2). This updated RELAP5 deck was benchmarked with single-phase test data to tune form loss coefficients of the elbows and tees, along with heat transfer coefficients within the cavity and off the external insulation panels. This tuned model was then found to accurately predict fluid temperatures within 2.5% and both system and riser flow rates within 6% during single-phase, steady-state simulations. For transient simulations, there is a slight over prediction of the flow rate, fluid temperatures, and heater temperatures during the heat-up period, which indicate that the transient heat loss may be underestimated. Following, the capabilities of RELAP5-3D were examined, which feature a conduction enclosure model that is not present in the current version of RELAP5-MOD3.3 used for all previous NSTF simulations. As an initial comparison of the two codes, single-phase simulations were run that used similar input decks. The results indicate that the single-phase flow predicted by the two codes was very similar, however RELAP5-3D appears to predict a higher system flow during the two-phase transient when compared to the flow rates predicted by RELAP5-MOD3.3. Furthermore, RELAP5-3D run did not capture the density wave oscillations or geysering phenomena, which are large oscillation flow instabilities observed in the experimental facility. To further the prediction capabilities for capturing two-phase instabilities, Options 55, 57, 58, 61, which are implemented by default in RELAP5-MOD3.3 but not in RELAP5-3D, were investigated. When enabling Option 61, RELAP5-3D agrees well with MOD3.3 in predicting the total system flow, while other options have negligible effect on the predicted total system flow by RELAP5-3D. However, none of these options enables RELAP5-3D to produce the same flow instabilities. For future steps, efforts are currently underway to investigate RELAP5-3D’s different behavior in predicting low-pressure two-phase instabilities. STAR-CCM+ was used to perform CFD analysis of the water-based test facility and provide simulation results for comparisons to experimental data. Efforts first focused on describing the characteristics of flow within the heated cavity. A study was performed on whether possible leakage flow between the two sides of the cavity could substantially impact and explain the results. An additional second assumption was examined which defined adiabatic side walls, so physical insulation structures were added to the models to allow conduction across this outer insulation. The results suggest that potential porosity of the insulation could be a major factor in the temperature distribution within the cavity and should be considered in any studies where it is desirable to know the cavity wall temperatures to higher accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

TRISO Particle Isolation and Graphite Removal Using SRNL Vapor Digestion Technology

Tri-structural isotropic fueled reactors are planned to come online in the next decade, but there is not currently a widely agreed upon disposition pathway for this new fuel stream. For long term used nuclear fuel storage, there would be a significant benefit if the waste volume could be reduced or mitigated. Most of the volume from used TRISO fuel contains graphite. SRNL currently has an active patent which describes one pathway to digest the graphite. One benefit in the utilization of this pathway is that multiple cylindrical pieces can be stacked end-to-end in a reaction tube, then nitric acid and water vapor can be flowed through the tube, and the weight change of the individual cores can provide both a reaction profile and overall oxidant use efficiency. The reaction of nitric acid and graphite passes through a series of intermediate products – NO 2 , NO, and N 2 O – from reaction and decomposition to eventually form N2. The data shows that NO2 grows in with increasing temperature between 500-600°C and then decreases by way of either reaction with graphite or decomposition. Nitric oxide, a reaction and thermal decomposition product of NO 2 , exhibits a consistent decline as a function of temperature, which is consistent with the literature. Similarly, the concentrations of N 2 O and N 2 increase as a function of temperature as their reactions with graphite become more favorable.

Advanced Reactors↗

Technical Documents for Gateway for Accelerated Innovation in Nuclear (GAIN)

The Gateway for Accelerated Innovation in Nuclear (GAIN) provides the nuclear energy community with access to the technical, regulatory, and financial support necessary to move new or advanced nuclear reactor designs toward commercialization. GAIN provides the nuclear community with a single point of access to the broad range of capabilities (i.e., people, facilities, materials, and data) across the U.S. Department of Energy (DOE) complex and its National Lab capabilities. The Fast Flux Test Facility (FFTF) is the most recent liquid metal reactor (LMR) to be designed, constructed, and operated by DOE. The 400-MWt sodium-cooled, fast-neutron flux reactor plant was designed for irradiation testing of nuclear reactor fuels and materials for liquid metal fast breeder reactors. Following the demise of the breeder reactor program in the United States, FFTF continued to play a key role in providing a test bed for demonstrating performance of advanced fuel designs and demonstrating operation, maintenance, and safety of advanced liquid metal reactors. The FFTF Program provides valuable information for potential follow-on reactor projects in the areas of plant system and component design, component fabrication, fuel design and performance, reactor control, prototype testing, and site construction. This report provides documents related to three important aspects of FFTF design and operation: 1) irradiation behavior of structural alloys and absorber materials, 2) thermohydraulics of rod bundles (i.e., coolant mixing), and 3) natural circulation heat transfer in the areas of modeling and validation. These technical documents are believed to be of interest to the nuclear industry and in particular to designers of new liquid metal reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cluster Structures with Machine Learning Support in Neutron Star M-R relations

Neutron stars (NS) are compact objects with strong gravitational fields, and a matter composition subject to extreme physical conditions. The properties of strongly interacting matter at ultra-high densities and temperatures impose a big challenge to our understanding and modelling tools. Some difficulties are critical, since one cannot reproduce such conditions in our laboratories or assess them purely from astronomical observations. The information we have about neutron star interiors are often extracted indirectly, e.g., from the star mass-radius relation. The mass and radius are global quantities and still have a significant uncertainty, which leads to great variability in studying the micro-physics of the neutron star interior. This leaves open many questions in nuclear astrophysics and the suitable equation of state (EoS) of NS. Recently, new observations appear to constrain the mass-radius and consequently has helped to close some open questions. In this work, utilizing modern machine learning techniques, we analyze the NS mass-radius (M-R) relationship for a set of EoS containing a variety of physical models. Our objective is to determine patterns through the M-R data analysis and develop tools to understand the EoS of neutron stars in forthcoming works.

79 ASTRONOMY AND ASTROPHYSICS↗

Coulomb sum rule for 4 He and 16 O from coupled-cluster theory

We demonstrate the capability of coupled-cluster theory to compute the Coulomb sum rule for the 4 He and 16 O nuclei using interactions from chiral effective field theory. We perform several checks, including a few-body benchmark for 4He. We provide an analysis of the center-of-mass contaminations, which we are able to safely remove. We then compare with other theoretical results and experimental data available in the literature, obtaining a fair agreement. This is a first and necessary step towards initiating a program for computing neutrino-nucleus interactions from first principles in coupled-cluster theory and supporting the experimental long-baseline neutrino program with a state-of-the-art theory that can reach medium-mass nuclei.

6 ≤ A ≤ 19A ≤ 5↗

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Abstract The improvement of Pt‐based catalysts for propane dehydrogenation (PDH) has progressed by recent investigations that have identified Zn as a promising promoter for Pt subnanometer catalysts. It is desirable to gain insights into the structure, stability, and activity of such active sites and the factors that influence them, such as Zn : Pt ratio, Pt coordination and nuclearity. Here, we employ density functional theory and microkinetic simulations to investigate the stability of Pt x Zn y ( x =1–3, y=0–3) active sites grafted on silanols of Silicalite‐1 and the PDH activity of Pt. We find that the coordination of a Pt atom to a nest of grafted Zn(II) atoms increases the stability of the Pt 1 Zn y sites, whose activity is similar for y=0–2 and drops dramatically for y>2. We further demonstrate, via linear scaling relations and microkinetic simulations, that the turnover frequency obeys a volcano law as a function of propylene binding strength. The Pt 2 Zn 1 and Pt 3 Zn 1 sites are stable and exhibit activity similar to Pt 1 Zn 2 , but only Pt 1 Zn 2 manifests reaction kinetics consistent with experimental data, strongly suggesting the active site composition in the synthesized catalyst samples. The methodology presented here suggests a general strategy for deducing active site information such as composition through simple kinetic experiments.

Liu, Yilang↗

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Abstract The improvement of Pt‐based catalysts for propane dehydrogenation (PDH) has progressed by recent investigations that have identified Zn as a promising promoter for Pt subnanometer catalysts. It is desirable to gain insights into the structure, stability, and activity of such active sites and the factors that influence them, such as Zn : Pt ratio, Pt coordination and nuclearity. Here, we employ density functional theory and microkinetic simulations to investigate the stability of Pt x Zn y ( x =1–3, y=0–3) active sites grafted on silanols of Silicalite‐1 and the PDH activity of Pt. We find that the coordination of a Pt atom to a nest of grafted Zn(II) atoms increases the stability of the Pt 1 Zn y sites, whose activity is similar for y=0–2 and drops dramatically for y>2. We further demonstrate, via linear scaling relations and microkinetic simulations, that the turnover frequency obeys a volcano law as a function of propylene binding strength. The Pt 2 Zn 1 and Pt 3 Zn 1 sites are stable and exhibit activity similar to Pt 1 Zn 2 , but only Pt 1 Zn 2 manifests reaction kinetics consistent with experimental data, strongly suggesting the active site composition in the synthesized catalyst samples. The methodology presented here suggests a general strategy for deducing active site information such as composition through simple kinetic experiments.

Liu, Yilang↗

Validation of the single-event method for low-energy electron transport via stopping power calculations with $\mathrm{MCNP}$

Monte Carlo simulations of low-energy ( <50 keV) electron transport in matter are essential for a broad range of application fields. Several Monte Carlo codes have developed specialized treatments for this case, but a comprehensive validation of low-energy electron transport for general-purpose simulations remains lacking in the literature. One approach to accomplish this validation is calculation of stopping power using low-energy electron transport physics, as stopping power is a fundamental radiation transport quantity which must be simulated accurately for nearly any application. Here in this work, we use the Monte Carlo N-Particle (MCNP) radiation transport code with the single-event method for electron transport to calculate stopping powers of low-energy electrons (50 eV to 30 keV) in 41 elemental solids, 14 compound solids, and five rare gas solids, comparing simulation results to published semi-empirical stopping power calculations from optical measurements. In general, the simulations give good agreement (typically within ±10%) with semi-empirical stopping power values at higher energies: 300 eV and above for most elemental solids, 1 keV and above for compound solids, and 400 eV and above for rare gas solids. Agreement between MCNP and semi-empirical values is worse below these energies. The most significant source of error is the EPRDATA14 cross section data, which does not account for changes in electronic structure due to solid-state bonding, particularly in compound materials. The simplistic model of atomic excitation used to generate the EPRDATA14 cross sections is another key source of error. Additionally, the breakdown of the continuous slowing-down approximation introduces significant uncertainty at low energies, although this is a limitation of the calculation method and not of the simulation procedure. Accounting for these and other uncertainty sources, the single event method in MCNP is robust and able to give good accuracy for a variety of low-energy electron transport problems through diverse kinds of materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Enthalpy of Uranium Adsorption onto Hematite

The influence of temperature on the adsorption of metal-ions at the solid-water interface is often overlooked, despite the important role that adsorption plays in metal ion fate and transport in the natural environment where temperatures vary widely. Herein, we examine the temperature-dependent adsorption of uranium, a widespread radioactive contaminant, onto the ubiquitous iron oxide, hematite. The multi-temperature batch adsorption data and surface complexation models indicate that adsorption of uranium, as the hexavalent uranyl (UO 2 2+ ) ion, increases significantly with increasing temperature, with an adsorption enthalpy (ΔH ads ) of +71 kJ mol –1 . We suggest that this endothermic, entropically-driven adsorption behavior is linked to reorganization of the uranyl-ion-hydration and interfacial water structures upon U VI adsorption at the hematite surface. Altogether, this work provides fundamental insight into the thermodynamics driving metal-ion adsorption reactions and provides the specific enthalpy value necessary for improved predictive geochemical modeling of U VI adsorption in the environment.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Flaw Tolerance Assessment for DOE Standard SNF Dry Storage Canisters - 26550

The U.S. DOE has designed four spent nuclear fuel (SNF) dry storage canisters for storing DOE standardized SNFs. The DOE standard canisters are cylindrical shells with a diameter of 24 inches (610 m) or 18 inches (457 m), a wall thickness of 0.5 inches (12.7 m) or 0.375 inches (9.53 m), and a length of 15 feet (4.57 m) or 10 feet (3.05 m). These DOE canister geometries are completely different from commercial canisters. The latter may experience chloride-induced stress cracking corrosion (CI-SCC) because they are stored near coastal regions. The former may not experience CI-SCC but face different challenges because they are stored in the SNF storage facilities. Because of large residual stresses, mechanical flaws may occur in the DOE canisters during long-distance transportation or lifting handling. To date, only limited structural integrity analyses were carried out through drop tests on the DOE canisters, but a more general flaw tolerance assessment has not been performed. Therefore, the failure assessment diagram (FAD)-based fracture mechanics method, as codified by the latest API 579-1/ASME FFS-1-2021 Edition, is adopted in this work to assess surface flaw tolerance for DOE canisters under operation loading and welding residual stresses (WRS), where the new code-recommended WRS distributions are used. To more adequately consider the transverse distribution of WRS, an equivalent WRS distribution is proposed to account for the WRS reduction with distance from the weld centerline. Moreover, the closed-form solutions of stress intensity factor K, which serves as the crack driving force during subcritical crack growth, are developed from the tabular data of the K factors provided in API 579-1/ASME FFS-1 and used to determine more accurate flaw sizes at flaw instability. Subsequently, the Level 2 assessment procedures with 12 assessment steps, as codified and detailed in API 579-1 and ASME FFS-1, are followed to assess the flaw tolerance for the surface flaws in the DOE standard canisters with consideration of normal or accident operation loads combined with WRS. The assessment results show that the four designs of DOE standard canisters can tolerate all surface flaws that meet the code permitted maximum sizes of a flaw length of 8 inches (i.e., 200 mm) and a flaw depth of 80% wall thickness. This demonstrates that all designs of DOE standard canisters are robust and reliable.

DOE standard canister↗

Predicting magnetic properties of single-molecule magnets from self-interaction-free density-functional theory (Final Report)

In this project we investigated electronic structure of an intermediate-sized copper-based molecule and magnetic and hyperfine properties of several small non-magnetic and magnetic molecules including transition-metal elements by applying self-interaction corrections to density functional theory (DFT). In a sufficient number of cases, DFT-calculated electronic structure and magnetic properties of single-molecule magnets qualitatively differ from corresponding experimental data. This is partly due to self-interacting electrons within the DFT formalism. Recently, an efficient method to correct the self-interactions was proposed, i.e., Fermi-Lowdin prbital (FLO) based self-interaction corrected (SIC) methodology, within DFT. Henceforth, this method is referred to as FLO-SIC method which exists in FLOSIC code. We used this FLO-SIC method for our studies of electronic structure and magnetic and hyperfine properties of small magnetic molecules and non-magnetic molecules. Our study will provide insight into predictions of magnetic properties of single-molecule magnets where self-interaction corrections play a critical role. There are two components of this project. In the first work, we studied the electronic structure of a planar mononuclear Cu-based molecule in two oxidation states, using DFT with the FLO-SIC method. We chose this system because it is small enough and it includes a transition metal element. We found that the standard FLO-SIC method takes too much compute time even for the small transition-metal molecule and so we slightly modified the method in order to expedite the process. In the dianionic state, we found that the FLO-SIC spin density agrees quantitatively with accurate quantum chemistry methods, while DFT spin density without self-interaction corrections are severely deviated from the quantum chemistry methods. We also showed that the energy gap between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of the dianionic state is larger than that of the monoanionic state. This result is consistent with experimental data. In the second work, we investigated how the interaction between the electron spin and nuclear spin is affected by electron self-interactions within small non-magnetic and magnetic molecules. Such an interaction is called hyperfine interaction. For molecules without significant orbital angular momentum, the hyperfine interaction consists of Fermi contact and dipolar interaction terms. Since the Fermi contact term depends on electron spin density at the nuclear site, it would be highly affected by self-interaction corrections. Therefore, we calculated the hyperfine interaction for the small molecules using DFT with the slightly modified expedited FLO-SIC method which was obtained in the first work, and compared the results to experimental data and DFT calculations without self-interaction corrections. We found significant improvement of the Fermi contact term computed using the FLO-SIC method for small magnetic molecules. Overall, the first and second work provided positive outlook of application of the FLO-SIC method to magnetic molecules and systems including transition-metal elements.

36 MATERIALS SCIENCE↗

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗

Extraction of the worm-gear TMD g1t from COMPASS , HERMES and JLab data on semi-inclusive DIS

Transverse momentum dependent parton distributions (TMDs) are an important class of functions required to understand the 3D structure of hadrons in terms of their underlying partons. One of the least known TMDs in terms of a global QCD analysis is the worm-gear TMD g1t . It carries the probabilistic interpretation of finding longitudinally polarized quarks inside transversely polarized hadrons. In this proceedings, we present the first-ever global QCD analysis of the semi-inclusive DIS $A^ {cos(φ_h-φ_S)}_{LT}$ data using Monte Carlo techniques to extract the worm-gear TMD g1T . The relevant data are available from COMPASS, HERMES and JLab. We compare our results for g1T with different theoretical approaches, including the large-N c approximation, the Wandzura Wilczek-type approximation, and lattice QCD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The ScIDEP muon radiography project at the Egyptian Pyramid of Khafre

The ScIDEP Collaboration is constructing muon telescopes based on scintillator technology to investigate the internal structure of the Egyptian Pyramid of Khafre at Giza near Cairo using cosmic-ray muons. The collaboration aims to scan the pyramid from multiple viewpoints, both inside the king’s burial chamber that is located centrally at the base of the pyramid, and outside of the pyramid, to potentially identify any new internal structures. An overview of the project is presented, including the development of the data-acquisition system, the simulation framework, and very first detector studies.

47 OTHER INSTRUMENTATION↗

α-cluster structure of 18 Ne

In this work, we investigate α-clustering in 18 Ne and compare it with what is known about clustering in the mirror nucleus 18 O. The excitation function for resonant elastic scattering of 14 O + α was measured in inverse kinematics using the TexAT active-target detector system, covering excitation energies from 8 to 17 MeV. The data were analyzed using a multi-channel R-matrix approach. Detailed spectroscopic information—including excitation energies, spin and parity assignments, and partial α and total widths—was extracted from the R-matrix analysis and compared with theoretical models and previously available data. Correspondence between levels in 18 O and 18 Ne is established. An extensive shell-model analysis of the 18 O– 18 Ne mirror pair shows very good agreement between theory and experiment, especially in the distribution of clustering strength. The comparison reveals that certain states, particularly at higher excitation energies, exhibit significantly stronger α-cluster character than predicted. This suggests that these states have a collective structure aligned with the corresponding α-reaction channel.

6 ≤ A ≤ 19↗

Initial development of a high temperature life prediction method directly accounting for variability in material properties

This report presents the initial development of a life prediction method that accounts for the variability of the material properties in Grade 91 steel. We account for material variability by both fitting a variable 3-parameter Weibull distribution to the rupture data of the material and by quantifying the effect that the creep deformation properties have on stresses via a Monte Carlo approach. To ensure a reasonable time frame when applying Monte Carlo to the creep stress, we propose a methodology that models the material as an extremely viscous Stokes flow with a non-Newtonian viscosity, therefore solving the problem in a single step. We use the final probabilistic model for structural failure developed in this document to evaluate a Flat Head Vessel designed with the Section III, Division 5 ASME Boiler Pressure and Vessel Code rules with a 100,000h design life and assess its probability of premature failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗