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At least 757 records · Page 42

Prospective CO 2 saline resource estimation methodology: Refinement of existing US-DOE-NETL methods based on data availability

Carbon storage resource estimation in subsurface saline formations plays an important role in establishing the scale of carbon capture and storage activities for governmental policy and commercial project decision-making. Prospective CO 2 resource estimation of large regions or subregions, such as a basin, occurs at the initial screening stages of a project using only limited publicly available geophysical data, i.e. prior to project-specific site selection data generation. As the scale of investigation is narrowed and selected areas and formations are identified, prospective CO 2 resource estimation can be refined and uncertainty narrowed when site-specific geophysical data are available. Here, we refine the United States Department of Energy – National Energy Technology Laboratory (US-DOE-NETL) methodology as the scale of investigation is narrowed from very large regional assessments down to selected areas and formations that may be developed for commercial storage. In addition, we present a new notation that explicitly identifies differences between data availability and data sources used for geologic parameters and efficiency factors as the scale of investigation is narrowed. This CO 2 resource estimation method is available for screening formations in a tool called CO 2 -SCREEN.

54 ENVIRONMENTAL SCIENCES↗

Thermal-striping analysis methodology for sodium-cooled reactor design

Computational fluid dynamics simulations have been performed to study the applicability of engineering CFD methods for thermals striping analysis. Thermal striping is the fluctuating temperature profile in a solid caused by fluctuating fluid temperature, and the resulting fluctuating thermal stresses cause high cycle fatigue and eventual material failure. Here this study presents the methodology for thermal striping analysis that including a transient conjugate heat transfer RANS model and benchmark the results against a sodium triple jet experiment. The multiphysics calculations are implemented to analyze the thermal stresses in the solid domain caused by the coupled heat transfer between the fluid and solid domains. Validation data from a liquid sodium triple jet experiment include time-averaged temperature measurements and power spectra of the temperature signal. The numerical results agree well with these experimental measures, demonstrating key features such as the dominant frequency of temperature fluctuations. The applicability of a low-cost wall treatment method is demonstrated, enabling key computational savings. Finally, the performance of two finite element stress analysis software packages is compared, and the validity of the lower-cost method is confirmed. These results demonstrate the applicability of engineering methods for computational thermal striping calculations, enabling thermal striping estimations in large fluid systems such as the core of a Sodium-cooled nuclear reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Faraday detector uranium isotope ratio measurement: Insights from solution- and laser ablation-based sampling methodologies on the Neoma MC-ICP-MS

In this study we utilize an all-faraday cup detector configuration on the Neoma MC-ICP-MS to perform uranium isotope ratio determinations from certified reference materials and a nuclear fuel precursor material via solution and laser ablation based sampling methodologies. The goal in performing these measurements is primarily to demonstrate that the all-faraday cup method can produce highly precise and accurate isotope ratios even at relatively low signal intensity levels while also developing a preliminary understanding of how the complex interplay between different amplifier resistor levels (e.g. 10 11 vs 10 13 Ω) and integration times impacts the precision and accuracy of different types of measurements. Our results show that the faraday cups with 1013 Ω resistors in their amplifier feedback loops can be used to produce accurate and relatively precise isotope ratios for ion beams down to ~5 K cps. However, at the lower end of the signal intensities observed in this study, longer integration times are necessary to mitigate the impact of ion beam instability that can occur during laser ablation based sampling. Despite this potential limitation, the all-faraday cup method is highly versatile as exemplified by the analysis of a collection of uranium reference materials with highly variable uranium isotopic compositions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A review of control methodologies for vapor compression and absorption heat pumps; Examen des méthodes de régulation des pompes à chaleur à compression et à absorption de vapeur

Here this paper presents an overview of control systems for heat pumps, and more specifically, a critical review of control methodologies for thermally activated absorption heat pumps. The objectives of a control system are identified and discussed, including optimal system operation, ability for continuous turndown, and fast response to changes in the operating conditions. Key details of different aspects of research and development such as steady-state and transient thermodynamic models, control algorithm development, and implementation are presented. Advanced multivariable feedback controls are able to perform better than individual feedback control loops and conventional on/off controls. The knowledge of the transient response of heat pump systems through models or experimental data is crucial for advanced control system design and implementation. Recently, data-based methods have also gained interest, but they are difficult to generalize. A general outlook with limitations and the potential of different approaches, and recommendations for future work are provided.

42 ENGINEERING↗

High-fidelity wind farm simulation methodology with experimental validation

The complexity and associated uncertainties involved with atmospheric-turbine-wake interactions produce challenges for accurate wind farm predictions of generator power and other important quantities of interest (QoIs), even with state-of-the-art high-fidelity atmospheric and turbine models. A comprehensive computational study was undertaken with consideration of simulation methodology, parameter selection, and mesh refinement on atmospheric, turbine, and wake QoIs to identify capability gaps in the validation process. For neutral atmospheric boundary layer conditions, the massively parallel large eddy simulation (LES) code Nalu-Wind was used to produce high-fidelity computations for experimental validation using high-quality meteorological, turbine, and wake measurement data collected at the Department of Energy/Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility located at Texas Tech University’s National Wind Institute. The wake analysis showed the simulated lidar model implemented in Nalu-Wind was successful at capturing wake profile trends observed in the experimental lidar data.

17 WIND ENERGY↗

Current Issues in Nuclear Data Evaluation Methodology: {sup 235}U Prompt Fission Neutron Spectra and Multiplicity for Thermal Neutrons

Issues in evaluation methodology of the prompt fission neutron spectra (PFNS) and neutron multiplicity for the thermal-neutron-induced fission of the {sup 235}U are discussed. The inconsistency between the experimental differential and integral data is addressed. By using differential data as ”shape data” good consistency was achieved between available sets of differential data. Integral dosimetry data have been used to define the PFNS slope at high outgoing neutron energies, where the quality of the differential data is poor. The inclusion into the fit of measured integral (spectrum-averaged) cross sections had a very small impact in the region where differential PFNS data are abundant and accurate, but removed the discrepancy with integral data at higher neutron emission energies. All experimental data are consistently fitted giving a PFNS average energy of 2.008 MeV. The impact on criticality prediction of the newly evaluated PFNS was tested. The highly enriched {sup 235}U solution assemblies with high leakage HEU-SOL-THERM-001 and HEU-SOL-THERM-009 benchmarks are the most sensitive to the PFNS. Criticality calculations for those solutions show a significant increase in reactivity if the average neutron energy of the fission neutrons is reduced from the ENDF/B-VI.5 value of 2.03 MeV. The proposed reduction of the PFNS average energy by 1.1% can be compensated by reducing the average number of neutrons per fission ν{sup ¯} at the thermal energy to the Gwin et al. measured value. The simple least-squares PFNS fit was confirmed by a more sophisticated combined fit of differential PFNS data for {sup 233,235}U, {sup 239}Pu and {sup 252}Cf nuclides with the generalised least-squares method using the GMA and GANDR codes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quality Assurance methodology for the ATLAS Inner Tracker strip sensor production

The production of the strip sensors for the ATLAS Inner Tracker (ITk) will start in 2020. Nearly 22,000 large area sensors will be produced over a period of about five years by Hamamatsu Photonics K.K. (HPK). The institutes involved in the sensor development and production are committed to deliver and maintain the highest quality sensors for the experiment. A Quality Assurance (QA) strategy has been prepared to be carried out during the whole production period. Once the process has been characterized as providing the required pre-irradiation specifications and the proper radiation hardness, the onus is on the manufacturer to rigidly stick to that qualified process. Still, sample testing with specific device-element structures and irradiation of devices should be implemented by the ITk sensor collaboration. A detailed irradiation and testing plan has been prepared by the ATLAS-ITk Collaboration, together with a newly designed test chip with specific structures to monitor different key technological and device parameters during the whole production. The tests and irradiations will be carried out on a sample basis. In order to have a practical methodology, samples from alternating batches will be sent for irradiations with protons, neutrons and gammas, and then tested in order to check that the characteristics remain within specifications. Here we present the detailed plan and the design and test methods for the structures in the test chip.

47 OTHER INSTRUMENTATION↗

Evaluation of SNOLAB background mitigation procedures through the use of an ICP-MS based dust monitoring methodology

Dust particulate fallout on materials in use for rare-event searches is a concerning source of radioactive backgrounds due to the presence of the naturally occurring radionuclides 40 K, 232 Th, 238 U, and their progeny in dust. Much effort is dedicated to inform radioactive backgrounds from dust and evaluate the efficacy of mitigation procedures. A great portion of such effort relies on fallout models and assumed dust composition. Here, in this work, an ICP-MS based methodology was employed for a direct determination of fallout rates of radionuclides and stable isotopes of interest from dust particulate at the SNOLAB facility. Hosted in an active mine, the SNOLAB underground laboratory strives to maintain experimental areas at class 2000 cleanroom level. This work validates the mitigation procedures in place at SNOLAB and informs dust backgrounds during laboratory activities. Fallout rates of major constituents of the local rock were measured two to three orders of magnitude lower in the clean experimental areas compared to non-clean transition areas from the mine to the laboratory. An increase of approximately two orders of magnitude in the fallout rate of stable Pb isotopes was determined in an experimental area during activities involving handling of Pb bricks. Increased 40 K, 232 Th, and 238 U fallout rates were measured in clean experimental areas during activities generating particulate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A novel methodology for gamma-ray spectra dataset procurement over varying standoff distances and source activities

The adoption of machine learning approaches for gamma-ray spectroscopy has received considerable attention in the literature. Many studies have investigated the deployment of various algorithm architectures to a specific task. However, little attention has been afforded to the development of the datasets leveraged to train the models. Such training datasets typically span a set of environmental or detector parameters to encompass a problem space of interest to a user. Variations in these measurement parameters will also induce fluctuations in the detector response, including expected pile-up and ground scatter effects. Fundamental to this work is the understanding that 1) the underlying spectral shape varies as the measurement parameters change and 2) the statistical uncertainties associated with two spectra impact their level of similarity. While previous studies attribute some arbitrary discretization to the measurement parameters for the generation of their synthetic training data, this work introduces a principled methodology for efficient spectral-based discretization of a problem space. A signal-to-noise ratio (SNR) respective spectral comparison measure and a Gaussian Process Regression (GPR) model are used to predict the spectral similarity across a range of measurement parameters. This innovative approach effectively showcased its capability by dividing a problem space, ranging from 5 cm to 100 cm standoff distances and 5 μCi–100 μCi of 137 Cs, into three unique combinations of measurement parameters. The findings from this work will aid in creating more robust datasets, which incorporate many possible measurement scenarios, reduce the number of required experimental test set measurements, and possibly enable experimental training data collection for gamma-ray spectroscopy.

data science↗

A methodology for customizing implantation profiles of light ions using a single thin foil energy degrader

We report a method was developed to quantify the spatial distribution and implantation depth of energy-degraded light ions with a thin foil rotating energy degrader for use during multiple ion beam irradiation. The methodology covers three physical phenomena: ions passing through the thin foil, ions travelling through the vacuum to the target, and ion implantation into the target, and accounts for the distribution of ions both in depth and in plane. The processes of energy straggling and scattering were calculated using SRIM. The effects of raster-scanning, and the geometry of the system were implemented in scripts handling the SRIM output files. Elastic backscattering (EBS) using 2.38 MeV H+ protons was used to measure the helium depth profiles after implantation with and without thin foil energy degradation. Defect analysis with transmission electron microscopy confirmed the implantation profiles measured with EBS and calculated with SRIM.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A methodology for determining the dynamic exchange of resources in nuclear fuel cycle simulation

We report simulation of the nuclear fuel cycle can be performed using a wide range of techniques and methodologies. Past efforts have focused on specific fuel cycles or reactor technologies. The CYCLUS fuel cycle simulator seeks to separate the design of the simulation from the fuel cycle or technologies of interest. In order to support this separation, a robust supply–demand communication and solution framework is required. Accordingly an agent-based supply-chain framework, the Dynamic Resource Exchange (DRE), has been designed implemented in CYCLUS. It supports the communication of complex resources, namely isotopic compositions of nuclear fuel, between fuel cycle facilities and their managers (e.g., institutions and regions). Instances of supply and demand are defined as an optimization problem and solved for each timestep. Importantly, the DRE allows each agent in the simulation to independently indicate preference for specific trading options in order to meet both physics requirements and satisfy constraints imposed by potential socio-political models. To display the variety of possible simulations that the DRE enables, example scenarios are formulated and described. Important features include key fuel-cycle facility outages, introduction of external recycled fuel sources (similar to the current mixed oxide (MOX) fuel fabrication facility in the United States), and nontrivial interactions between fuel cycles existing in different regions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Flow Instabilities in boiling channels and their suppression methodologies—A review

Small modular reactors (SMRs) are gaining significant attention as a promising solution for clean and sustainable nuclear-power generation. However, the operation of SMRs is subject to various challenges, including two-phase flow instabilities. Flow instability has the potential to trigger flow-induced vibration and cyclic fluctuations in local thermal stress. These instabilities frequently manifest because of the complex interplay among a multitude of factors, encompassing thermal-hydraulic conditions, the geometric configuration of the steam generator, and operational parameters. These conditions could subsequently lead to premature critical heat flux, equipment malfunctions, and other safety concerns. Here, the endeavor to address steam-generator flow instabilities is of utmost importance in augmenting the sustainability and efficiency of contemporary energy production. This study offers a comprehensive review of instabilities in two-phase flow, with a particular focus on the influential factors impacting the stability of flow boiling. Furthermore, it delves into the processes of identifying, characterizing, and ameliorating these instabilities, emphasizing pivotal findings, methodologies employed, and avenues for prospective research. The primary parameters of concern encompass the efficient transfer of thermal energy, the optimization of mass-flow rates, and the establishment of favorable boundary conditions, all in the context of steam generator design to alleviate instability for water-cooled SMRs. These discernments bear substantial ramifications for enhancing reactor performance and ensuring operational safety.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗

Integrated modeling methodology for ash agglomeration in poly-disperse fluidized beds using particle population framework

This article discusses a unique agglomeration modeling methodology developed based on binary collisions to combine the effects of heterogeneity in ash chemistry and granular physics. A simple population balance is defined to find changes in the particle size distribution (PSD) of a fluidized bed. Thermodynamic equilibrium calculations and a computational fluid dynamics (CFD) code, are used to obtain hydrodynamic parameters. A method to calculate and use a distribution of collision frequencies in fluidized beds, corresponding to a poly-disperse particle size distribution, was developed in order to incorporate the particle level heterogeneities. A distribution of collision frequencies obtained for poly-dispersed particles showed a three orders of magnitude higher collision frequency amongst the smaller particles than the coarser ones, at the initiation of agglomeration. Ash agglomeration occurred when the slag amount (binder) was less than 10 wt% at temperatures <850 °C for Pittsburgh No. 8 coal.

42 ENGINEERING↗

Assessment of HRA method predictions against operating crew performance: Part I: Study background, design and methodology

This is the first in a series of four papers document ing two large -scale human reliability analysis (HRA) empirical studies – the International HRA Empirical Study and the US HRA Empirical Study. The two studies are the first major efforts in recent years to benchmark HRA methods by comparing HRA method predictions against actual operator performance in accident scenarios simulated on nuclear power plant (NPP) simulators. When a met hod was applied by different analyst teams, the predictions of the different teams were also compared against each other. The purpose of the comparisons was to obtain insights concerning the strengths and weaknesses of the HRA methods addressed in the studies as well as the factors contributing to inter-analyst (or intra-method) variability. The background and motivation for the studies is first presented in the article. Then, the overall study design is described with a discussion on high-level tasks and participants. Next, the methodology to achieve the high-level tasks is discussed. Finally, concluding remarks are made concerning lessons learned on benchmarking HRA methods with crew performance of scenarios on NPP simulators.

97 MATHEMATICS AND COMPUTING↗

A morphology independent methodology for quantifying planview river change and characteristics from remotely sensed imagery

Remotely sensed imagery of rivers has long served as a means for characterizing channel properties and detection of planview change. In the last decade the dramatic increase in the availability of satellite imagery and processing tools has created the potential to greatly expand the spatial and temporal scale of our understanding of river morphology and dynamics. To date, the majority of GIS and automated analyses of planview changes in rivers from remotely sensed data has been developed for single-threaded meandering river systems. These methods have limited applicability to many of the earth's rivers with complex multi-channel planforms. Here we present the methodologies of a set of analysis algorithms collectively called Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM). SCREAM analyzes planview river metrics regardless of river morphology. These algorithms quantify both the erosion and accretion rates of riverbanks from binary masks of channels generated from imagery acquired at two time periods. Additionally, the program quantifies the area of change between river channels and the surrounding floodplain and area of islands lost or formed between these two time periods. To examine variations in erosion rates in relation to local channel attributes and make rate comparisons between river systems of varying sizes, the program determines channel widths and bank curvature at every bank pixel. SCREAM was developed and tested on rivers with diverse and complex planform morphologies in imagery acquired from a range of observational platforms with varying spatial resolutions. Here, validation and verification of SCREAM-generated metrics against manual measurements show no significant measurement errors in determination of channel width, erosion, and bank aspects. SCREAM has the potential to provide data for both the quantitative examination of the controls on erosion rates and for the comparison of these rates across river systems ranging broadly in size and planform morphology.

47 OTHER INSTRUMENTATION↗

Impact of environmental variables on the degradation of photovoltaic components and perspectives for the reliability assessment methodology

Backsheet cracking has been a major issue observed in the field; however, standardized qualification tests, such as IEC61215, are inadequate to reliably identify such failures of PV modules due to the lack of the critical weathering factors applied sequentially or in combination, such as those found in the service environments. To address this problem, in this work we investigated the effects of various environmental variables on the degradation and failure behaviors of the polyamide-based backsheet in PV modules retrieved from five different locations, encompassing a variety of climates, including humid subtropical, hot-summer Mediterranean, tropical savanna climate and hot arid. The correlations between the degradation indicators and the weathering variables were further demonstrated by principle components analysis (PCA). We found strong relationships between: carbonyl formation and reflected solar radiation; hydroxyl formation and module temperature; yellowness and NO2 concentration, while no simple correlation could be found between a specific weathering factor and cracking. By introducing additional stress factors to the aged polyamide-based backsheet films with the novel 'fragmentation test', we successfully reproduced the field cracking behaviour. This study has demonstrated that different degradation modes of PV components respond differently to the environmental stresses encountered in service. Thereby, any accelerated laboratory test based on a single set condition or lacking key environmental variables would be inadequate to assess the long-term performance of PV modules and components. A new reliability-based methodology is proposed to quantitatively link laboratory testing with field results for the service life prediction of PV materials.

14 SOLAR ENERGY↗

Heliostat sizing methodology for concentrating solar thermal industrial process heat projects

This study presents a method to obtain a heliostat size that minimizes the levelized cost of heat (LCOH) of a heliostat-based concentrating solar thermal system for applications of solar heating for industrial processes at operating temperatures from 565 to 1550°C. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model to supplement the previously developed cost models, which we update to reflect current pricing trends. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWh th . Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the LCOH, producing a characteristic U-shaped trend with a robust near-optimal window of 7-20 m 2 ; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats being deployed at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗