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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-count-rate effects in event processing for the XRISM/Resolve X-ray microcalorimeter. II. Energy scale and resolution in orbit

The Resolve instrument on the X-ray Imaging and Spectroscopy Mission (XRISM) uses a 36 pixel microcalorimeter designed to deliver high-resolution, non-dispersive X-ray spectroscopy. Although it is optimized for extended sources with low count rates, Resolve observations of bright point sources are still able to provide unique insights into the physics of these objects, as long as high-count-rate effects are addressed in the analysis. These effects include the loss of exposure time for each pixel, changes in the energy scale, and changes in the energy resolution. To investigate these effects under realistic observational conditions, we observed the bright X-ray source, the Crab Nebula, with XRISM at several offset positions with respect to the Resolve field of view and with continuous illumination from 55 Fe sources on the filter wheel. For the spectral analysis, we excluded data where exposure-time loss was too significant to ensure reliable spectral statistics. The energy scale at 6 keV shows a slight negative shift in the high-count-rate regime. The energy resolution at 6 keV worsens as the count rate in electrically neighboring pixels increases, but can be restored by applying a nearest-neighbor coincidence cut (“cross-talk cut”). We examined how these effects influence the observation of bright point sources, using GX 13+1 as a test case, and identified an eV-scale energy offset at 6 keV between the inner (brighter) and outer (fainter) pixels. Users who seek to analyze velocity structures on the order of tens of km s–1 should account for such high-count-rate effects. These findings will aid in the interpretation of Resolve data from bright sources and provide valuable considerations for designing and planning for future microcalorimeter missions.

X-rays: general↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗
DOE OSTI2025

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Integrated Solutions for Optimized Performance (ISOP) Final Technical Report

The goal of this project was to demonstrate technical feasibility of an integrated approach for deep energy retrofits by packaging innovative technologies with smart communicating controls that represent the next generation of energy efficiency. The integrated solutions for optimized performance (ISOP) package integrates (i) advanced lighting and plug load controls; (ii) intelligent daylight harvesting through automated self-powered shades and window films; (iii) advanced HVAC controls sequences (ASHRAE Guideline (GDL) 36); and (iv) fault detection and diagnosis (FDD) and continuous commissioning (CCx) using advanced analytics. These technologies address energy use across multiple building end uses that represent more than 60% of the energy consumption in all commercial buildings. The project was structured to be implemented over three budget periods: Budget Period 1 scope included site selection, project design, site-specific customization of technology packages, procurement of technologies, initiation of installation of technologies, the development of a measurement and verification plan and collection of pre-retrofit data collection. The first year go/no-go decision was based on securing host sites representing 250,000 sq. ft. of occupied operational spaces, savings analysis, technology procurement and initiation of installation. Budget Period 2 planned to complete technology installations and initiate data collection of post-retrofit performance data. The second year go/no-go was to be the completion of technology installations and commissioning, metering and data collecting to support the requirements laid out in site specific M&V plans. Budget Period 3 planned to collect and analyze post-retrofit performance data and provide data and reporting to support energy efficiency rebate programs. After the team completed activities planned for Budget Period 1, the team reached a Go/No-Go Decision Point. At that point, TRC recommended that DOE discontinue the project without prejudice due to challenges with securing demonstration sites to meet the full 250,000 sf of occupied operational spaces and DOE concurred. In Budget Period 1, the TRC team developed criteria to recruit and evaluate potential demonstration host sites. TRC worked with Princeton University, the project demonstration partner, to identify buildings on their campus as potential candidates for the demonstration. Following the selection of demonstration sites, the TRC team customized energy technology packages according to the needs and characteristics of each site. TRC defined technology specifications, identified vendors, and conducted analysis to estimate energy and cost savings potential. The project team then developed schedules for technology procurement processes and scheduled for installation at all selected demonstration sites. The project team worked with Princeton University and DOE to develop an approach to verify energy savings achieved through measurement and verification (M&V) 2.0 methods. Princeton University initiated open bids to procure the necessary materials and installation contractors. Bid results came back higher than estimates due to a couple of factors – lack of familiarity of the bidders with the proposed technologies and lack of local trained installers to execute the installation of these new measures. Due to the higher bids, projects no longer met the internal cost-effectiveness criteria used by Princeton to proceed with procurement of the full suite of technologies as proposed in ISOP. Princeton had already procured parts of the ISOP package as part of a campus-wide initiative for FDD and lighting retrofits, but with the higher costs for other ISOP components, Princeton could no longer commit to the full ISOP package on the selected sites. Based on this, the team reached the Go/No-Go decision point, where they decided not to proceed with the project. Princeton is separately installing portions of the ISOP package where they individually meet Princeton’s payback criteria but on a different schedule than would have been needed for the DOE ISOP project. The team has learned several lessons from project progress in the first budget period. The team will utilize these lessons in future projects, as should any team which proceeds with a project around the ISOP technology. The first lesson is that more information about the proposed sites is required earlier in the process (perhaps even at the proposal stage) in order to have a successful demonstration. Technical details not evident earlier in the process (such as the TLED limitations for ALCS) can derail project execution. The second lesson is that pricing of emerging technologies is highly variable due to lack of familiarity of local installers and distributor with the proposed technologies as well as alternate bids using products they were more familiar with, but that cost more than the ones proposed by TRC. Finally, the last major lesson is that the host site’s internal project criteria is of critical importance. Based on these higher installed costs and lack of an informed installer base for the products proposed for this project, the project does not meet Princeton’s simple payback goals of five years.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Technical and Licensing Considerations for Micro-Reactors

The U.S. Nuclear Regulatory Commission (NRC) has interacted with vendors pursuing the commercialization of micro-reactors (i.e., reactors capable of producing about 1 MW(th) to 20 MW(th) of energy from nuclear fission). It is envisioned that micro-reactors could be assembled and fueled in a factory and shipped to a site. Many of the sites are expected to be remote locations requiring off-grid power or in some cases military bases. The objective of this effort is to explore the technical issues and the approach required to reach a finding of "reasonable assurance of public health and safety" for this new and different class of reactors. The analysis performed here leverages available micro-reactor design and testing data available from national laboratory experience as well as commercial design information to explore technical issues. Some factors considered include source term, accidents that would need to be analyzed, and the extent of the probabilistic risk assessment (PRA). The technical evaluation was performed within the framework of the Licensing Modernization Project (LMP) to identify licensing basis events, classification of structures, systems and components, and defense-in-depth needed to provide regulatory certainty. With this framework and technical evaluation in mind, the scope and content of a micro-reactor licensing application is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

EXCLUSIVE NEUTRAL PION ELECTROPRODUCTION CROSS SECTION MEASUREMENTSWITHANEUTRALPARTICLE SPECTROMETER

Deep Virtual Compton Scattering (DVCS), the exclusive electron-proton scattering process ep ¿e'p'¿, provides access to generalized parton distributions (GPDs), which correlate information about the longitudinal momentum and transverse spatial structure of quarks inside the nucleon. Experiment E12-13-010 in Hall C at Jefferson Lab was designed to take high-precision measurements of the DVCS cross section over an extended kinematic range using the newly commissioned Neutral Particle Spectrometer (NPS). The NPS features a high-resolution electromagnetic calorimeter and a streaming data acquisition system optimized for operation at high luminosities. This thesis presents the detector and analysis work carried out to support the NPS DVCS program. In particular, it focuses on the hardware design, calibration, and performance of the calorimeter. A development of a waveform reconstruction analysis of the calorimeter signals enabled improved extraction of pulse amplitudes and times. The waveform analysis was also extended to operate in a multithreaded environment, substantially reducing processing time for large datasets. Analysis of exclusive neutral pion electroproduction events in the calorimeter gives a strong validation of the calorimeter’s performance and resolution. Together these developments establish a foundation for future analyses and extraction of the DVCS cross section and its use in constraining the GPDs.

Kerver, Mitchell [Old Dominion Univ., Norfolk, VA ↗
DOE OSTI2025

srlife : a software tool for estimating the life of high temperature concentrating solar receivers. Part I – metallic receivers

Here, this paper introduces srlife, a tool for estimating the structural service life of concentrating solar power (CSP) receivers operating at high temperatures. Supporting both metallic and ceramic receiver designs, srlife is available as open-source software at https://github.com/applied-material-modeling/srlife and can be installed via the PyPi package manager (https://pypi.org). Given basic receiver geometry and incident heat flux, the tool performs thermohydraulic and structural analysis and estimates the life of a receiver. Designed for easy integration into a software stack, including solar field and levelized cost analysis, the tool can be utilized for optimizing receiver designs to meet service life and economic targets. This paper is Part I in a two-part series. Part I discusses the analysis process used to estimate the life of metallic receivers, along with a description of the required input data. Additionally, several heuristics applied within srlife can reduce analysis time significantly while maintaining accurate life estimations for metallic receivers when compared to full analyses. Several examples demonstrating the utility of srlife in receiver design are also discussed. Part II focuses on the life estimation of ceramic receivers, using time-dependent reliability analysis and various ceramic failure models implemented in srlife.

Creep-fatigue analysis↗
DOE OSTI2026

Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers (Final Technical Report)

This report summarizes the carbon capture research and development conducted by The State University of New York at Buffalo (UB) and GTI Energy (GTI) for award “DE-FE0031969: Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers” sponsored by the U.S. Department of Energy (DOE). The objective of this project is to develop an innovative sorbent structure of trapped small amines in HNC embedded in PEF for DAC. This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An innovative sorbent structure of trapped small amines in hierarchical nanoporous capsules (HNC) embedded in porous electrospun fibers (PEF) was developed for direct air capture (DAC). This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An interfacial polymerization process was developed, which utilized loaded amines inside mesoporous silica and trimesoyl chloride (TMC) dissolved in organic solvents as the precursors, to generate a polyamide (PA) coating layer on mesoporous silica and thus trap amines. Reaction conditions, including TMC concentration, organic solvents, reaction time, etc., for interfacial polymerization were optimized to effectively trap loaded amines, and cyclic heating-cooling operation was conducted to evaluate the coating quality. Larger pore volume mesoporous silica was also synthesized to increase amine loading and thus increase CO 2 capacity. The optimized sorbent material exhibited CO 2 capacity as high as 4.88 mmol/g under humid DAC conditions and negligible loss (<1%) during 10 cyclic heating-cooling operations. The optimized PA-coated sorbent also showed fast adsorption and desorption kinetics, with <20% t1/2 increase compared to uncoated sorbent. PEF fabrication conditions, including organic solvents for dissolving core and shell polymers, voltage, distance from the nozzle to the collection panel, etc. were adjusted to better incorporate HNC. After incorporating the optimized sorbent material into PEF, the structured sorbent had a CO 2 capacity of approximately 4.0 mmol/g under humid DAC conditions, with capacity loss of 0.17% per cycle and t1/2 increase less than 10%. A techno-economic analysis (TEA) for the process design for a DAC system based on our developed sorbent structure of trapped small amines in HNC embedded in PEF was conducted. The process design included process description and major equipment sizing and energy and mass balances in addition to scale-up research results and estimated capture cost. Aspen Adsorption Simulator was used to fit the experimentally measured breakthrough curves and extract equilibrium and kinetic data of the optimized sorbent. Our results indicated that for a DAC plant with CO 2 productivity of 3,000 tonne/year, the levelized cost of CO 2 capture was $\$$612/tonne, with the largest contribution of 44.33% from the fixed operation cost. Increasing CO 2 productivity, while maintaining similar fixed operation cost, is expected to significantly reduce the CO 2 capture cost. A sensitivity study was also conducted to understand the influence of total plant cost, sorbent cost, CO 2 concentration in the feed, sorbent mat lifetime, sorbent regeneration electricity, and adsorption blower pressure drop on the levelized cost of CO 2 capture, revealing a capture cost range of $\$$520-870/tonne.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structure-guided design of a broadly cross-reactive multivalent group a streptococcal vaccine

The M protein of group A streptococci (Strep A) is a major virulence determinant and protective antigen. The N-terminal region of the M protein is variable in sequence, defines the M/emm type, and contains epitopes that elicit opsonic antibodies that protect animals from challenge infections. Although there are >200 M types of Strep A, there is now evidence that structurally related M proteins can be grouped into clusters and that immunity may be cluster-specific in addition to M type-specific. This observation has led to recent studies of structure-based design of multivalent M peptide vaccines to select peptides predicted to cross-react with heterologous M types to improve vaccine coverage. In the current study, we have applied a refined series of peptide structural algorithms to predict immunological cross-reactivity among 117N-terminal M peptides representing the most prevalent M types of Strep A. Based on the results of the structural analyses, in combination with global M type prevalence data, we constructed a 32-valent vaccine containing 19 cross-reactive vaccine candidates predicted to cross-react with 37 heterologous M peptides to which were added 13 type-specific M peptides. Further, the 4-protein recombinant vaccine was immunogenic in rabbits and elicited significant levels of antibodies against 31/32 (97%) vaccine peptides and 28/37 (76%) peptides predicted to cross-react. The vaccine antisera also promoted opsonophagocytic killing of vaccine and cross-reactive M types of Strep A. Based on a recent analysis of M type prevalence of Strep A, the potential global coverage of the 32-valent vaccine is ~90%, ranging from 68% in Africa to 95% in North America. Our results indicate the utility of structure-based design that may be applied to future studies of broadly protective M peptide vaccines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Entropy Analysis of FPGA Interconnect and Switch Matrices for Physical Unclonable Functions

Random variations in microelectronic circuit structures represent the source of entropy for physical unclonable functions (PUFs). In this paper, we investigate delay variations that occur through the routing network and switch matrices of a field-programmable gate array (FPGA). The delay variations are isolated from other components of the programmable logic, e.g., look-up tables (LUTs), flip-flops (FFs), etc., using a feature of Xilinx FPGAs called dynamic partial reconfiguration (DPR). A set of partial designs is created to fix the placement of a time-to-digital converter (TDC) and supporting infrastructure to enable the path delays through the target interconnect and switch matrices to be extracted by subtracting out common-mode delay components. Delay variations are analyzed in the different levels of routing resources available within FPGAs, i.e., local routing and across-chip routing. Data are collected from a set of Xilinx Zynq 7010 devices, and a statistical analysis of within-die variations in delay through a set of the randomly-generated and hand-crafted interconnects is presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Here, we show that unsupervised machine learning (ML) using principal component analysis (PCA) provides a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of the chemical and catalytic properties of materials. We demonstrate the approach by finding chemisorption descriptors for metal alloys and surface oxygens on metals and metal oxides. In both cases, the principal component (PC) descriptors yield ML models that predict the material’s chemical properties with competitive accuracy compared to ML models built using established descriptors. Importantly, interpreting the electronic-structure patterns captured by each PC descriptor via signal reconstruction suggests potential design motifs for future electronic-structure descriptor design and allows us to identify links between a material’s geometric and catalytic properties. Ultimately, we show that the unsupervised ML approach provides a route to find electronic-structure descriptors of the catalytic properties of materials that readily connect to geometric structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

MEITNER Resource Team Modeling and Simulation Support to Holos-Quad Reactor Development (Final CRADA Report)

The main objective of this CRADA is to provide Argonne National Laboratory (ANL)’s modeling and simulation capabilities via ARPA-E's MEITNER (Modeling-Enhanced Innovations Trailblazing Nuclear Energy Reinvigoration) Resource Team (RT) arrangement to support the demonstration of the viability of HolosGen’s Holos-Quad reactor design. The Holos-Quad reactor design is an advanced reactor concept that incorporates many new design features, such as the neutron-coupled Subcritical Power Modules (SPMs) in its core design, elimination of balance of plant (BOP) by direct integration of a helium Brayton cycle power conversion system with each SPM, among many other innovative features. The demonstration of the viability of such an innovative reactor design warrants iterations of modeling and simulation and testing. The purpose of this project is to utilize ANL’s modeling and simulation capabilities in nuclear reactor analysis and power conversion system analysis to inform HolosGen and the Design Team (DT) in the design and optimization of the Holos-Quad concept. The major work scopes of this project include: to investigate conceptual designs and materials for radiation shielding to protect personnel and internal components such as turbomachinery; Assess the the helium Brayton cycle power conversion system performance in both nominal and load following conditions; Investigate power conversion components and overall system performance; Identify control strategies to enable load following; Perform simulations of HolosGen’s subscale simulator and using available test data for code validation/benchmark purpose; Perform core thermal-hydraulics, safety analysis, and structural analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Preliminary description of a new creep-fatigue design method that reduces over conservatism and simplifies the high temperature design process

The report provides the initial description of a new creep-fatigue design method for structural components in high temperature nuclear service. The new method is based on an integrated elastic-perfectly plastic (EPP) analysis and Simplified Model Test (SMT) approach that reduces over conservatism, improves the treatment of elastic follow up, and simplifies the design procedure, when compared with the current creep-fatigue design methods in ASME Boiler and Pressure Vessel Code. Developing the design charts for the EPP-SMT design method requires extrapolating SMT test data as a function of hold time and follow up factor. The report develops the preliminary design charts for Alloy 617 at temperatures between 800°C and 950°C by combining two extrapolation approaches developed in a previous work. The report also presents a comparative analysis between the EPP-SMT design method and the current ASME creep-fatigue design methods by evaluating design life of two sample geometries under different loading conditions. Results from the comparative analysis verify the EPP-SMT design charts but suggest the requirement of additional test data in the low strain range regime for improving the extrapolation procedure that will further reduce the over conservatism in the creep-fatigue damage evaluation. The report also concludes that the EPP-SMT design procedure can account for effect of primary load on creep-fatigue life by using a fixed, bounding value of follow up in constructing the design charts. The conclusions to this report describe the future work required to complete this new design method so it can be codified through a nuclear Code Case.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗
DOE OSTI2024

Leveraging BERT and Network-Based Attention Analysis for Identifying Treatment Milestones in EHRs

This study introduces a sophisticated data-driven framework for analyzing Electronic Health Records (EHRs) using transformer-based models to identify and disentangle overlapping treatment contexts. The framework leverages a preprocessing pipeline that transforms structured procedural codes into semantically enriched descriptive text, enabling the use of attention mechanisms to cluster medical events into treatment milestones—cohesive and distinct components of care processes. The methodology is rigorously validated using synthetic datasets derived from the MIMIC-III database, designed to simulate the heterogeneity and overlapping procedural contexts characteristic of real-world EHR scenarios. Quantitative evaluation highlights the framework’s robustness in disentangling concurrent care pathways, with attention metrics and unsupervised clustering approaches demonstrating the ability to preserve intra-context relationships while distinguishing inter-context dependencies. By addressing challenges inherent in data heterogeneity, this approach provides a foundation for uncovering complex treatment patterns, advancing clinical decision-making, and optimizing resource allocation in diverse healthcare environments.

Kim, Minsu [ORNL] (ORCID:0000000224185535)↗
DOE OSTI2023

First-Principles Cost Estimation of a Sodium Fast Reactor Nuclear Plant

A multi-tiered cost analysis is performed to estimate full costs of a nuclear power plant (NPP) based on sodium-cooled fast reactor (SFR) technology. To address the lack of fully transparent cost estimations from past undertakings for NPPs, we have developed a detailed and first-principles-based cost estimate for a generalized SFR NPP. Our intent is to achieve a high degree of transparency with our cost assumptions and develop a cost model that is flexible and easily extendable to variations in NPP design and other nuclear reactor types. Furthermore, we strive to achieve a clear organization of costs and complete identification of key cost drivers based on first principles. To this end, the cost results of our analysis as given in Table 24 and Table 25 are organized and categorized into a code of accounts (COA) under development at Idaho National Laboratory (INL). Varying degrees of first-principles methods are employed, such as design for manufacture and assembly® (DFMA® ), to elucidate costs in all process levels of the plant equipment, buildings and site structures, personnel, and other miscellaneous but significant cost elements. These approaches have been successfully applied in past cost analysis projects and are designed to enable rapid and flexible cost estimation. Application of these techniques for evaluating NPP costs is similar in concept to the full, detailed estimation of construction and fabrication costs determined in a later stage of NPP development. Note that our approach tries to avoid use of other past analysis results and data such as those from the legacy Energy Economic Data Base (EEDB) Program, as these resources are based on historical NPP costs and thus may not be indicative of new reactor technologies or construction and fabrication/manufacturing techniques. However, we provide a comparison of our SFR NPP cost results in Table 90 against those included in the EEDB for a representative pressurized water reactor (PWR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Specimen sizing and remaining life sample calculations for high temperature reactor material surveillance

Advanced high-temperature nuclear reactors rely on structural components that will operate for decades under combined mechanical, thermal, and environmental loading. Materials surveillance programs are a promising strategy for managing the resulting uncertainty in long-term structural integrity by monitoring degradation in service using passively actuated mechanical test articles. Previous reports have developed a simplified, spreadsheetimplementable framework for sizing these test articles and for inferring accumulated creep damage and remaining life from ex-situ test data. This report advances that work toward practical deployment by providing a sample-problem book: a collection of worked, end-toend examples in which the ASME Section III, Division 5 design analysis of a representative high-temperature reactor component is carried through to a sized surveillance article, verified with detailed finite-element analysis, and concluded with a remaining-life assessment based on an assumed ex-situ creep-rate measurement on the retrieved specimen. The report also summarizes ongoing ANL engagement with ASTM Committee E10 on Nuclear Technology and Applications toward drafting a standard covering surveillance procedures for advanced reactors.

Barua, Bipul (ORCID:0000000247184113)↗
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗