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At least 163 records · Page 9

Updating Nuclear Energy Cost Estimates for Net Zero World Initiative

Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Decay spectroscopy of the blocked fission product 130 $\mathrm{I}$

We report numerous applications rely on the identification and quantification of fission products with the activation technique, where γ-rays emitted in the decay are used to estimate the initial activity of the radionuclide of interest. 130 I is a so-called blocked fission product, which can be produced only directly through fission, a property that makes it particularly attractive for nuclear forensics. A source of 130 I was produced using a (p,n) reaction on enriched 130 Te at the Brookhaven Tandem Van de Graaff and its decay was studied with Gammasphere at Argonne National Laboratory. Two new levels were identified, and over 25 transitions were added, removed or re-placed in the level scheme, with intensity measurements made down to I γ = 0.00066 per 100 decays. The uncertainty on the intensities of the strongest transitions, those that are commonly used to quantify the activity of the radionuclide, was improved by a factor of 2 compared to the previous best assessment and discrepancies in the literature values were resolved. A detailed angular correlation analysis further permitted the determination of a number of spin assignments for excited levels and mixing ratios for γ-ray transitions

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Oak Ridge National Laboratory NCSP Analytical Methods Subtask 3, AMPX Development and Maintenance, and NCSP Nuclear Data Subtask 6, SAMMY Modernization

The modernization of SAMMY continued with consolidation of access to covariance information for adjusted parameters and data in SAMMY. This consolidation allowed for removal of many scratch files. In addition, work was initiated to make the 0K cross section calculation more modular and less dependent on SAMMY global parameters. An initial application programming interface (API) was added to expose cross sections (including resolution broadening) generated by SAMMY to external fitting routines. The processing for thermal moderators in AMPX was updated for selected moderators for which the generated grid was not fine enough. Updated libraries were generated for SCALE. In addition, work continued to fully support new Evaluated Nuclear Data File (ENDF) formats, including the Generalized Nuclear Database Structure (GNDS) in AMPX.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensitivity Coefficients Calculated for the Prompt Neutron Decay Constant At or Near Delayed Critical

The derivation of a non-invasive prompt neutron decay constant sensitivity coefficient is provided in this work. The computation of the sensitivity coefficient derived in this work does not require modification of Monte Carlo source code and is based on capabilities available in Monte Carlo N-Particle R© Code Version 6.2. The prompt neutron decay constant sensitivity coefficients are calculated for 44-group and 252-group energy structures for specific nuclide-reaction pairs in the Jezebel benchmark experiment. The nuclide-reaction pairs investigated in this work include Pu- 239(n,f), Pu-240(n,f), and Pu-241(n,f). Physical explanations of the sensitivity profiles exhibited by the 252-group energy structure are investigated for the prompt neutron multiplication factor, mean neutron lifetime, and prompt neutron decay constant. The prompt neutron decay constant sensitivity coefficients calculated for the 44-group and 252-group energy structure of Pu-239(n,f) are compared. Lastly, the 44-group energy structure sensitivity coefficients calculated are used for nuclear-data induced uncertainty quantification of the neutron multiplication factor. This work shows that a reduction in the nuclear data-induced uncertainty of the neutron multiplication factor is possible for all nuclide-reaction pairs investigated when prompt neutron decay constant sensitivity coefficients are utilized. This is important for new critical experiment design optimization studies of measurement configurations. This work provides a basis for more detailed sensitivity analysis and uncertainty quantification of nuclide, reaction, and energy-specific cross section data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Local structure of Mott insulating iron oxychalcogenides La 2 O 2 Fe 2 OM2(M=S,Se)

Here, we describe the local structural properties of the iron oxychalcogenides, La 2 O 2 Fe 2 OM 2 (M=S,Se), by using pair distribution function analysis applied to total scattering data. Our results from neutron powder diffraction show that M = S and Se possess similar nuclear structures at low and room temperatures. The local crystal structures were studied by investigating deviations in atomic positions and the extent of the formation of orthorhombicity. Analysis of the total scattering data suggests that buckling of the Fe 2 O plane occurs below 100 K. The buckling may occur concomitantly with a change in octahedral height. Furthermore, within a typical range of 1-2 nm, we observed a short-range orthorhombiclike structure suggestive of nematic fluctuations in both of these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Determining the 9 $\mathrm{Be}$($n, γ$) 10 $\mathrm{Be}$ integral cross section at fission neutron energies

The 9 B neutron capture cross section has significant implications for Be materials in the nuclear industry as well as the α process in stellar nucleosynthesis. While the cross section is well constrained at thermal neutron energies, there is a lack of experimental data at higher neutron energies, and the evaluated nuclear data libraries can differ by up to two orders of magnitude. We calculate the 9 Be(n, γ) 10 Be integral cross section at fission neutron energies in an effort to resolve disagreements amongst the nuclear data libraries. Foil irradiation experiments were performed using the Flattop critical assembly at the National Criticality Experiments Research Center with either the highly enriched U or Pu cores, with target foil stacks placed at multiple locations to exploit different neutron energy profiles. Accelerator mass spectrometry was used to measure the 10 Be/ 9 Be ratio in irradiated Be foils, while all other activation products were quantified through gamma spectrometry. The experiments were simulated using the Monte Carlo N-Particle radiation transport code and combined with experimental results to determine the total neutron fluence, while the staysl-pnnl suite and fispact-ii code were used to validate the model and assess the systematic uncertainty. The new 9 Be(n, γ) 10 Be integral cross sections calculated in this work are 26.5 ± 2.2µb at 0.59 ± 0.07 MeV, 24 ± 3 µb at 0.98 ± 0.14 MeV, 21.7 ± 1.3 µb at 1.26 ± 0.11 MeV, 21.8 ± 1.4 µb at 1.32 ± 0.11 MeV, and 18.6 ± 1.1 µb at 1.46 ± 0.13 MeV. These results do not agree with integral cross sections from any of the nuclear data library evaluations. Discrepancies between the new integral cross sections reported here and the nuclear data libraries suggest a more complex cross-section structure in the MeV range which allows for more resonance contributions, and more work is needed to further constrain the evaluated cross sections.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Nuclear Data Sheets for A=246

For this work, available information pertaining to the nuclear structure of ground and excited states for all known nuclei with mass number A = 246 have been compiled and evaluated. The adopted level and decay schemes, as well as the detailed nuclear properties and configuration assignments based on experimental data, are presented for these nuclides. When there are insufficient data, expected values from systematics of nuclear properties and/or theoretical calculations are utilized. Unexpected or discrepant experimental results are also noted. In cases where weighted averaging procedures have been used, the assigned uncertainty in the result is generally not lower than the lowest uncertainty in the data points used in the procedure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An enhancement of NASTRAN for the seismic analysis of structures

New modules, bulk data cards and DMAP sequence were added to NASTRAN to aid in the seismic analysis of nuclear power plant structures. These allow input consisting of acceleration time histories and result in the generation of acceleration floor response spectra. The resulting system contains numerous user convenience features, as well as being reasonably efficient.

Burroughs, J. W.↗

Informing Plant Asset Reliability and Availability Through AI-Driven Analysis of Operator Logs

The availability and reliability of nuclear power plant (NPP) structures, systems, and components (SSCs) are critical parameters for NPP safety. Tracking these parameters is necessary but costly and labor-intensive, requiring the collection and evaluation of SSC event data such as shutdowns, startups, and failures. To show how these events are needed for the parameters an example is given: one measure of reliability is based on the number of equipment failure events and the number of run hours (i.e., the time from a startup event to a shutdown event). Here, this work investigates using artificial intelligence (AI) to mine NPP operator log entry texts for SSC event data. Four AI approaches were explored for identifying these events, including natural language processing (NLP) methods, generative AI, generative AI combined with NLP, and topic modeling. A key challenge addressed with all four approaches is the brevity of operator log entries. Among these four a neural network–based NLP method was shown to be the most promising for this application, achieving F1 scores of 86.0% for shutdowns, 92.2% for startups, and 80.4% for failures on a subject-matter-expert-curated dataset from NPP operator logs, compared to a baseline of 66.6% for a random classifier. This shows that NLP methods can perform better than generative AI. Additionally, the NLP methods combined with generative AI were shown to perform better than generative AI alone. Generative AI was most successful at providing the background information for the NLP methods to use. This work demonstrates the potential to use AI to automate parameter collection from NPP operator log entries and other records.

97 - MATHEMATICS AND COMPUTING↗

C 12 ( n , n 1 ′ γ ) partial γ -ray cross section measured using the GENESIS array

Improved neutron inelastic scattering cross sections have repeatedly been identified as a top priority nuclear data need, important for basic science and a range of applications in nuclear energy, stockpile stewardship, and proliferation detection. For the C 12 ( n , n ′ γ ) reaction in particular, recent measurements have unveiled some structural discrepancies, demonstrating incongruities among themselves and in relation to the ENDF/B-VIII.0 nuclear data evaluation. To help resolve these disagreements, a measurement was performed at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory using a broad-spectrum neutron beam and a 99.8% pure natural carbon target. The Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering (GENESIS) was employed to measure energy-differential γ -ray emission spectra as a function of incident neutron energy in the energy range of 5.5 to 16.7 MeV. The C 12 partial γ -ray cross sections were extracted at 63 ∘ , 122 . 5 ∘ , and 150 ∘ with respect to the incoming neutron beam and integrated using angular distribution data available in the literature. The data show agreement with a recent literature measurement and evaluation from 11 to 15 MeV, but indicate a larger cross section for incident neutron energies between 5.5 and 8.5 MeV. The measured relative angular distributions are also reported and were found to agree with evaluation. Published by the American Physical Society 2025

Gordon, J. M. (ORCID:0009000789886897)↗

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Gamma Decay of the 154 Sm Isovector Giant Dipole Resonance: Smekal-Raman Scattering as a Novel Probe of Nuclear Ground-State Deformation

𝛾 decays of the isovector giant dipole resonance (IVGDR) of the deformed nucleus 154 Sm were measured using 2$^{+}_{1}$-Smekal-Raman and elastic scattering of linearly polarized, quasimonochromatic photon beams. The two scattering processes were disentangled through their distinct angular distributions. Their branching ratio and cross sections were determined at six excitation energies covering the 154 Sm IVGDR. Both agree with the predictions of the geometrical model for the IVGDR and confirm 𝛾 decay as an observable sensitive to the structure of the resonance. Consequently, the data place strong constraints on the nuclear shape, including the degree of triaxiality. The derived 154 Sm shape parameters 𝛽 = 0.2925⁢(25) and 𝛾 = 5.0⁢(15)° agree well with other measurements and recent Monte Carlo shell-model calculations.

150 ≤ A ≤ 189↗

Nuclear Sciences References (NSR)

Nuclear Science literature database, containing about 250,000 articles covering more than 120 years of nuclear science research. Approximately 80 journals are routinely scanned for relevant articles; it also includes PhD thesis and private communications. Each article in NSR is assigned a distinctive 8-character primary key, known as ‘key number’, and a set of keywords that briefly describe the article's content. These keywords follow strict rules since they are used in web search forms. Typically, an article is incorporated in NSR within a few weeks after its web publication. About 4,000 articles are added per year. All the compilation effort is supported by the US Nuclear Data Program and coordinated by the National Nuclear Data Center at Brookhaven National Laboratory, which is also responsible for its web dissemination.

Basic Nuclear Research, Applied Nuclear Technologi↗

First observation of a high-𝐾 band structure in 162 Er and implications in the context of the identical bands phenomenon

The first ever identification of a high-𝐾 band structure in 162 Er is reported. Based on a 𝐾 𝜋 = 7 (−) isomer, it is found to be identical in nature to the corresponding 𝐾 𝜋 = 7 − sequence in 164 Er up to its highest observed spin. Furthermore, the phenomenon of identical high-K bands built on a two-quasiparticle configuration in an isotopic chain is reported here for the first time. While this is a notable addition to the systematics of known identical bands in nuclei at normal deformation, a satisfactory global understanding of the phenomenon remains elusive.

150 ≤ A ≤ 189↗

Dipole response in Te 128 , 130 below the neutron threshold

Numerous studies of the ground-state decay of the pygmy dipole resonance (PDR) have been carried out in the past. However, data on the decay of the PDR to low-lying excited states is still very scarce due to limitations of the sensitivity to weak branching transitions of experimental setups. Here, we present a detailed examination of the low-energy dipole response of 128 Te and 130 Te below their neutron separation thresholds of 8.8 and 8.5 MeV, respectively. Photonuclear reactions with the subsequent γ-ray spectroscopy of the decay channel with continuous-energy bremsstrahlung at varying endpoint energies and linearly polarized quasimonochromatic γ-ray beams with energies ranging from 2.7 to 8.9 MeV in steps of roughly 250 keV were used for probing the decay behavior of the low-energy dipole response in 128Te and 130Te. In addition, (γ,γ' γ") reactions were used to study the population of low-lying states of 128 Te. Spin-parity quantum numbers and reduced transition probabilities are determined for individual photo-excited states. The analysis of average decay properties for nuclear levels in narrow excitation-energy bins enable the extraction of photoabsorption cross sections, average branching ratios to the $2$$^{+}_{1}$ state, and the distinction between E1 and M1 transitions to the ground state and to the $2$$^{+}_{1}$ state accounting for resolved and unresolved transitions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Chemical and Hydrodynamical Models of Cometary Comae

Multi-fluid modelling of the outflowing gases which sublimate from cometary nuclei as they approach the Sun is necessary for understanding the important physical and chemical processes occurring in this complex plasma. Coma chemistry models can be employed to interpret observational data and to ultimately determine chemical composition and structure of the nuclear ices and dust. We describe a combined chemical and hydrodynamical model [1] in which differential equations for the chemical abundances and the energy balance are solved as a function of distance from the cometary nucleus. The presence of negative ions (anions) in cometary comae is known from Giotto mass spectrometry of 1P/Halley. The anions O(-), OH(-), C(-), CH(-) and CN(-) have been detected, as well as unidentified anions with masses 22-65 and 85-110 amu [2]. Organic molecular anions such as C4H(-) and C6H(-) are known to have a significant impact on the charge balance of interstellar clouds and circumstellar envelopes and have been shown to act as catalysts for the gas-phase synthesis of larger hydrocarbon molecules in the ISM, but their importance in cometary comae has not yet been fully explored. We present details of new models for the chemistry of cometary comae that include atomic and molecular anions and calculate the impact of these anions on the coma physics and chemistry af the coma.

Charnley, Steven↗

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

A Knowledge Graph Approach to Analyze Systems and Assets Health

Nuclear power plants collect large amounts of equipment reliability data elements that contain information on the statuses of component, assets, and systems. All these data elements precisely record asset and system performance and health throughout the lifecycle of those assets and systems. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly focuses on the integration of numeric and textual data elements in order to assist plant system engineers in analyzing equipment reliability data. This task begins with preprocessing the data by extracting knowledge from textual data via natural language processing methods and quantifying system, asset, and component health based on numeric data. We then employed model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Data elements were then associated with a single MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 - MATHEMATICS AND COMPUTING↗