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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

OVERVIEW OF PARTICLE DEPOSITION MODELS FOR SPENT NUCLEAR FUEL STORAGE SYSTEMS

Deposition models were built to evaluate contaminant deposition on spent nuclear fuel (SNF) canisters. The primary contaminant of concern is chloride, which is dispersed in the atmosphere and then deposits onto the canisters. During dry storage, the primary degradation process is likely to be Chloride Induced Stress Corrosion Cracking (CISCC) at the heat-affected zones of the canister welds. It is known that stainless steel canisters are susceptible to CISCC; however, the rate of chloride deposition onto the canisters is poorly known, based on sparse field data from a small number of sites. The models presented in this study could be useful for determining the rate of deposition on the canisters and the likelihood of CISCC to help with SNF canister ageing management. The deposition models were developed with the commercial computational fluid dynamics (CFD) code STAR-CCM+. Various deposition mechanisms were considered and incorporated into the models, and a sensitivity study was conducted to determine the most important mechanisms for deposition within a SNF storage system. The models included both a vertical and horizontal configuration storage system: NAC International’s Modular, Advanced Generation, Nuclear All-purpose STORage System (MAGNASTOR®) and a NUHOMS® horizontal storage module respectively. The resulting canister deposition on the horizontal canister is visually compared with inspection data taken onsite at the Calvert Cliffs Nuclear Power Plant. These models are preliminary, and development of the models will continue. Future validation exercises are currently being planned, including the Canister Deposition Field Demonstration (CDFD) effort funded by U.S. Department of Energy office of Nuclear Energy office of Spent Fuel Waste Science and Technology. The goal of the modeling presented is to demonstrate a potential modeling technique that could be used to plan and inform SNF canister ageing management programs with predictive models for the timing and occurrence of canister CISCC.

Suffield, Sarah R.↗
NASA NTRS1983

Evaluation of the radiometric quality of the TM data using clustering and multispectral distance measures

Radiometrically and geometrically corrected TM data from three different geographic locations were examined. Histograms were inspected for each band to determine the dynamic range of the data, the shape of the distributions, and to verify whether empty bins were introduced by the radiometric correction process. The effect of geometric correction on the radiometry of the resampled pixels was determined. The information content between TM and MSS data sets were compared and the TM data were used to map the thermal effluent discharge into a river ecosystem from a nuclear thermal power plant, and application only possible previously only possible through the acquisition of thermal infrared scanner data from aircraft altitudes.

Bartolucci, L. A.↗
DOE OSTI2023

Verification Testing of OLI Systems Mixed Solvent Electrolyte Model for the Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 ) System to High Ionic Strength at 25°C

This technical report summarizes model verification results and summary statistics for 41 evaporite mineral solubility cases evaluated by Savannah River National Laboratory using OLI Systems’ aqueous electrolyte thermodynamic modeling software. The 41 verification cases containing a total of 60 solubility curves comprise mineral solubility data from low to high ionic strength at 25°C for the eight-component system Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 O as reported by Harvie et al. (1984). Thermodynamic calculations were executed using OLI Systems’ Stream Analyzer computation module within the OLI Studio software platform (Ver. 11.0, Rev. 11.0.1.9). The Mixed Solvent Electrolyte (MSE) thermodynamic framework was chosen for this investigation because of its superiority in modeling high ionic-strength inorganic salt solutions and actinide redox chemistry and solubility, both of which are relevant to the geological repository conditions at the Waste Isolation Pilot Plant in Carlsbad, New Mexico. Mineral solubility data in various inorganic salt solutions were digitized and extracted from figures generated by Harvie et al. (1984). For each of the 60 solubility curves, a case-specific chemistry model and input file were generated in OLI Studio using OLI Stream Analyzer and the MSE (H 3 O + ion) public databank provided by OLI Systems. Model simulation results were exported to Microsoft Excel to calculate summary statistics and to generate graphs comparing the OLI model predictions to the solubility data. Summary statistics include residuals (model – data) and concordance (accuracy × precision, where precision is indicated by the Pearson correlation coefficient and accuracy accounts for bias and scale differential). Private databanks were not developed, and activity coefficient model regressions were not performed to improve OLI model fits to the data. Of the 41 model verification plots, 83% have a mean of the percent residuals less than or equal to 25%. Similarly, 75% display a concordance greater than or equal to 0.75. Only seven of the 41 verification plots fail to show good agreement between the model and data. Of these seven, three are relevant to the WIPP repository because they involve the Mg-OH-Cl-SO 4 -CO 3 aqueous system. The remaining four address salt solubilities at the pH extremes (strong acid and strong base). It should be noted that in two of the three Mg-OH-Cl-SO 4 -CO 3 system cases, the regressed Harvie et al. (1984) solubility curve also deviated from the data. Lack of agreement between the OLI model-predicted solubility curves and the data is attributable to one or more of the following: specific solid species are not included in the OLI MSE databank; there is significant variation among the different solubility datasets chosen by Harvie et al. (1984); the OLI MSE model’s thermodynamic parameters were determined using different solubility datasets; and the activity coefficient parameters for certain relevant ion-ion and ion-molecule pairs have not been optimized via data regression. Two recommendations for future work are to (1) evaluate solubility data for the Mg-OH-Cl-SO 4 -CO 3 system at high ionic strength and, if necessary, develop a private OLI MSE database that includes missing species and, where necessary, regressed standard state properties and interaction parameters; (2) perform similar verification testing of the OLI model for actinide solubility data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Improving fission-product decay data for reactor applications: part I—decay heat

Effort has been expended to assess the relative merits of undertaking further decay-data measurements of the main fission-product contributors to the decay heat of neutron-irradiated fissionable fuel and related actinides by means of Total Absorption Gamma-ray Spectroscopy (TAGS - sometimes abbreviated to TAS) and Discrete Gamma-ray Spectroscopy (DGS). This review has been carried out following similar work performed under the auspices of OECD/WPEC-Subgroup 25 (2005–2007) and the International Atomic Energy Agency (2009, 2014), and various highly relevant TAGS measurements completed as a consequence of such assessments. Here, we present our recommendations for new decay-data evaluations, along with possible requirements for total absorption and discrete high-resolution gamma-ray spectroscopy studies that cover approximately 120 fission products and various isomeric states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Evaluation of a Potential Groundwater Tracer Test in the Ringold Upper Mud Aquifer at the 100-H Area of the Hanford Site

This document presents an evaluation of a potential groundwater tracer test in the uppermost RUM (Ringold Formation member of Wooded Island – upper mud unit) aquifer in the 100-H Area of the Hanford Site. The results from field electrical resistivity tomography (ERT) investigations, numerical flow and transport (F&T) modeling, coupled ERT-F&T model simulations, and laboratory resin experiments provide the technical basis for evaluating tracer test scenarios that minimize impacts to the 100-HX pump and treat (HX P&T) operations, and maximize hydrologic data acquisitions including the use of advanced surface geophysical techniques for monitoring tracer transport.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Accomplishments of Thermal Neutron Scattering Research at North Carolina State University [Slides]

Thermal neutron scattering law (TSL) data evaluations have been completed and contributed to ENDF. New evaluations are underway. FLASSH is developing as a modern platform for thermal neutron data analysis featuring an enhanced user experience and low learning overhead. Advanced TSL techniques in combination with Doppler analysis have been developed, which were incorporated into FLASSH. ML/DL NeTS method development has been initiated. Experimental capabilities for validation have been developed at the PULSTAR reactor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Passive Temperature Sensors for Nuclear Applications

In April 2007, the Department of Energy (DOE) designated the Advanced Test Reactor (ATR) a National Scientific User Facility (NSUF) to advance US leadership in nuclear science and technology. By attracting new users from universities, laboratories, and industry, this program supports basic and applied nuclear research to help address the nation's energy security needs. In support of this program, the Idaho National Laboratory (INL) established in-house capabilities to develop, fabricate, test, and qualify new and enhanced temperature sensors for irradiation testing. This effort is continuing today through the DOE?s Advanced Sensors and Instrumentation (ASI) program. Although most efforts emphasize sensors capable of providing real-time data, selected tasks have been completed to enhance passive sensors for irradiations where instrumentation leads cannot be included. These sensors include silicon carbide (SiC) monitors, melt wires and the sublime temperature monitor. SiC monitors are available to detect peak irradiation temperatures between 200°C and 800°C in reactor locations where instrumentation leads cannot be used. SiC monitors may be evaluated using specialized equipment installed at INL?s Measurement Sciences Laboratory (MSL). A melt wire inventory is also maintained at MSL. This inventory contains wires for specific use in irradiation experiments ranging in temperatures from 30°C to 1500°C. Melt wires and SiC monitors have had decades of research and application. Recent research has produced a passive monitor known as the sublime temperature monitor. This passive sensor has the capability of recording temperature gradients. This paper will discuss passive temperature sensors currently being researched and implemented under the ASI program.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation

Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However, TRISO failure probabilities are small and the associated computational models are expensive. Here we used coupled active learning, multifidelity modeling, and subset simulation to estimate the failure probabilities of TRISO fuels using several 1D and 2D models. With multifidelity modeling, we replaced expensive high-fidelity (HF) model evaluations with information fusion from two low-fidelity (LF) models. For the 1D TRISO models, we considered three multifidelity modeling strategies: only Kriging, Kriging LF prediction plus Kriging correction, and deep neural network (DNN) LF prediction plus Kriging correction. While the results across these multifidelity modeling strategies compared satisfactorily, strategies employing information fusion from two LF models called the HF model least often. Next, for the 2D TRISO model, we considered two multifidelity modeling strategies: DNN LF prediction plus Kriging correction (data-driven) and 1D TRISO LF prediction plus Kriging correction (physics-based). The physics-based strategy, as expected, consistently required the fewest calls to the HF model. However, the data-driven strategy had a lower overall simulation time since the DNN predictions are instantaneous, and the 1D TRISO model requires a non-negligible simulation time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Data coverage assessment on neural network based digital twins for autonomous control system

We report in a recently developed Nearly Autonomous Management and Control (NAMAC) system, neural networks (NNs) are used to develop digital twins for diagnosis (DT-Ds). However, NNs are not usually considered extrapolation models and may result in large errors if they are applied to unseen data outside the training data (uncovered). In this study, we propose a data coverage assessment (DCA) to determine if the NN-based DT-Ds are extrapolated based on their epistemic uncertainty. The uncertainty quantification algorithms and uncertainty thresholds are selected based on the confusion matrix of classifying evaluation data into covered or uncovered data. To demonstrate the adaptability of the proposed framework, we applied it to a basic feedforward neural network and a more advanced recurrent neural network based on a more nonlinear database. Case studies show that the proposed framework can distinguish unseen data for both basic and advanced applications with proper uncertainty quantification algorithms and thresholds.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Evaluation of Load Behavior for Select Analytes in Hanford Tank Waste

Crystalline silicotitanate (CST) inorganic ion exchanger is a candidate material for remediation of highly alkaline (pH > 14) aqueous nuclear waste streams containing high sodium concentrations (>5 M). In this work, ion exchange column testing with wastes from Hanford tanks AP-105, AP-107, and AW-102 was carried out to study the uptake of 137 Cs to estimate the decontamination factor (DF) value. Additionally, DF values for uptake of Al, Ca, Pb, Np, Pu, U, and Sr were determined and the ion exchange capacity of CST toward these analytes was estimated. Limited data is available on the load behavior of other minor and trace elements with recent CST production lots and this characterization will help improve understanding of the behavior of CST and assist in identifying potential disposition pathways as well as assessing removal capabilities of CST for other components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sister Rod Destructive Examinations (FY23) Appendix F3: Uncertainty and Conservative Bias in the Cyclic Integrated Reversible-Bending Fatigue Test

The development and application of the Cyclic Integrated Reversible-Bending Fatigue Tester (CIRFT) has been documented over the past 10 years. The CIRFT system was developed in collaboration with the U.S. Nuclear Regulatory Commission (NRC) to address the concern that high-burnup fuel rod fatigue performance was degraded compared to cladding-only behavior. Fatigue data measured by CIRFT on high-burnup fuel rods were then used by the NRC to develop a fatigue response curve for pressurized water reactor fuel rods with Zircaloy-4 cladding in NUREG-2224. Subsequently, CIRFT has been used in the sister rod project to test whether reoriented hydrides associated with vacuum drying influenced the fatigue lifetime, to extend the fatigue testing database to include fuel rods with ZIRLO cladding, and to add to the experience on both Zircaloy-4 and M5 cladding. These data will be used as a reference for subsequent characterization of fuel rods removed from the high-burnup demonstration cask to better understand the effects of long-term dry storage, which can be thought of as a multiyear elevated temperature anneal. The objective of fatigue testing is to provide data that can be used to develop a best-estimate fatigue curve and a conservative fatigue design curve that accounts for uncertainty and can be compared with actual transportation conditions. The process for defining a design fatigue curve for commercial used fuel rods was developed by Oak Ridge National Laboratory (ORNL) in FY22. One issue noted in the fatigue evaluation was that the calculated combined uncertainty in the strain amplitude values determined from the measured data was large. It was proposed then to directly measure the uncertainty in the strain amplitude to either validate the calculated combined uncertainty or update the uncertainty based on the measurement data. Thus, the purpose of this appendix is to document the measured uncertainty in the strain amplitude data. In the process, it was determined that there has been a conservative bias in the calculated strain amplitude that is small enough to be within the measurement uncertainty. This observation is discussed herein, and a case is made to continue to include the conservative bias in the data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Open-source microreactor design models for technoeconomic assessments

Technoeconomic analyses for advanced nuclear technologies are essential for identifying cost drivers which allow for optimizing the technology to achieve better economic performance. Microreactors are emerging as a promising and reliable-energy solution, offering inherent safety, low capital investment, and rapid deployment capabilities. Past studies have conducted technoeconomic analyses for microreactors, but there remains a need for open-source technoeconomic models that can enhance collaboration, transparency, and consistency when performing this type of analysis. The present article introduces an open-source technoeconomic model for microreactors based on bottom-up cost estimation. Since no real cost data for microreactors exists, this model leverages cost data and insights gleaned from the Microreactor Applications, Research, Validation and Evaluation (MARVEL) project. It estimates the first-of-a-kind cost of two microreactor technologies and can also calculate the N th of a kind (NOAK) cost via accounting for learning and mass factory production. The two technologies considered in this paper are the liquid–metal thermal reactor (LTMR) and the gas-cooled microreactor (GCMR). In conclusion, the goal of this study is to demonstrate bottom-up cost estimation of these microreactor technologies and provide the cost estimation models that other users can leverage for various applications such as design optimization and financial planning.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Propagating neutronic uncertainties for FFTF LOFWOS Test #13

The safety evaluation conducted for licensing a Sodium-cooled Fast Reactor (SFR) may require modeling transients with best-estimate calculation tools that must first be validated against real-world measurements. To provide the community with a valuable benchmarking opportunity for validating SFR analysis tools and methods, the International Atomic Energy Agency (IAEA) initiated a coordinated research project (CRP) in 2018 for the analysis of the Fast Flux Test Facility (FFTF) Loss of Flow Without Scram (LOFWOS) Test #13. The impact of nuclear data uncertainties on neutronics parameters was previously investigated based on the COMMARA-2.0 covariance matrix. Since the transient simulation results are very sensitive to certain reactivity coefficients, it was decided to employ rigorous uncertainty propagation methods to quantify the impact of nuclear data uncertainties on the best-estimate predication of FFTF LOFWOS Test #13. The DAKOTA code is used to propagate neutronic uncertainties through SAS4A/SASSYS-1 transient simulations, while taking into account spatial and reaction-wise correlations within these uncertainties. This study shows that the remaining discrepancies observed between the Argonne National Laboratory (ANL) best-estimate results and the experimental measurements can be partly explained by the uncertainty associated with Gas Expansion Module (GEM) worth, which contributes the majority of the overall nuclear data uncertainty on the output from the FFTF LOFWOS Test #13 transient simulation. This study also confirmed the importance of including spatial and reaction-wise correlations of nuclear data uncertainties on feedback coefficients in the uncertainty propagation to avoid under-estimating their impact during the transient simulations.

42 ENGINEERING↗
DOE OSTI2021

DETECTING FIRE WITH MACHINE LEARNING-ENABLED VISUAL MONITORING FOR NUCLEAR POWER PLANT ENVIRONMENTS

Nuclear power plants are experiencing significant cost challenges to remain competitive with other energy-generation utilities. Unlike other industries, the cost of operation and maintenance activities is mostly attributed to workforce costs. To mitigate this, nuclear power plant stakeholders are increasingly interested in the development and deployment of machine learning methods to potentially automate or augment manually intensive tasks to reduce costs, especially for monitoring activities. One monitoring function that is visually demanding and that can occur frequently to meet the requirements of a fire protection program is visually monitoring an area for fire occurrence. Currently, fire watch activities consist of a worker physically stationed at a given location with the sole responsibility of observing a given area to ensure a fire is detected and mitigated promptly. This effort focused on the development and evaluation of a suitable deep convolutional neural network to classify individual video frames at a sub-second frequency for the occurrence of “fire” and “no fire” in varying industrial environments similar to nuclear power plants. It is believed that a trained neural network model could be integrated with existing facility video surveillance camera feeds to generate alerts when fire inferences occur in individual frames captured at sub-second temporal resolutions. Extensive effort was dedicated to identifying and curating suitable imagery training data representing varying environments and scene settings with and without flame features to maximize generalization in nuclear power plant environments. The data collection effort resulted in the aggregation of a large, labeled image library exceeding 12,000 images to support model training for diverse industrial environments. A deep neural network model incorporating parallel multi-scale capabilities was developed and trained to support accurate image-based detection of flame incidents of varying sizes and spectral feature properties within heterogeneous scenes. Analysis results show that the trained model can achieve high inference accuracy despite heterogeneous scene environments and components. Testing accuracy exceeded 95.0 percent with very low false positive and false negative inferences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Naval Reactors Facility Environmental Monitoring Report (CY2020)

This report presents the results of the radiological and non-radiological environmental monitoring programs for 2020 at the Naval Reactors Facility (NRF). Current operations at NRF are in compliance with applicable regulations governing use, emission, and disposal of solid, liquid, and gaseous materials. The results obtained from the environmental monitoring programs verify that releases to the environment from operations at NRF did not have any adverse effect on human health or the environment. Evaluation of the environmental data confirms that the operation of NRF continues to have no adverse effect on the environment or the health and safety of the general public. Furthermore, a conservative assessment of radiation exposure to the general public as a result of NRF operations demonstrated that the maximum potential dose received by any member of the public was well below the most restrictive dose limits prescribed by the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the Nuclear Regulatory Commission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Technical report with results for 156Eu

The evaluated γ-ray branching ratio values after the decay of 156 Eu are based on measurements done in the 1960s and 1970s which improve upon measurements done back in the 1950s. These experiments, while improving on each other, were not able to produce nearly pure samples and impurities produced along with the sample ( 152 Eu, 154 Eu, and 155 Eu) interfered with the study of the beta spectrum for 156Eu. The values for the branching ratios of 156 Eu from National Nuclear Data Center (NNDC) [4] have uncertainties of ranging from 7-14% for the 10 most intense γ rays and up to 30% for the weaker ones. This work aims to improve the precision on the majority of these γ-ray branches.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Production of Fischer-Tropsch Synfuels at Nuclear Plants

A case study analysis was performed to evaluate nuclear-powered synthetic fuel production in the midwestern United States (U.S.). A Fischer-Tropsch (FT) fuel synthesis plant design was used as the basis for the analysis. The FT plant design was configured to produce a product slate consisting of diesel fuel, jet fuel, and motor gasoline blend stocks from carbon dioxide (CO 2 ) and hydrogen (H 2 ) feedstocks. The CO 2 feedstock for the FT plant was assumed to be sourced from biorefineries in the region around a Midwest light water reactor (LWR) nuclear power plant (NPP). The analysis specifies that power from the LWR is used to produce H 2 via high-temperature steam electrolysis and to operate the FT synfuel production plant. Capital costs were estimated for the FT plant while capital costs for the electrolysis plant were based on previous Idaho National Laboratory (INL) studies. In addition to labor and maintenance costs for the FT and electrolysis plants, operating costs also include the costs for CO 2 feedstock transport. An analysis was performed to determine the cost of transporting CO 2 from the distributed biorefinery sources to the centralized fuel synthesis plant as a function of the synfuel plant capacity and corresponding CO 2 demand. The primary revenue streams are associated with sales of the synthetic fuel products. The synthetic fuel products will likely follow the same market trends as the conventional fuel products. The synfuel price data was thus based on projections made by the U.S. Energy Information Administration (EIA) 2021 Annual Energy Outlook (AEO) for conventional fuel products minus federal and state taxes, as well as marketing and distribution costs. The economic analysis also considered cases that included and excluded revenues from the 2022 Inflation Reduction Act (IRA) clean hydrogen production tax credit (PTC) of $\$ $3.00/kg for the first ten years of operation. The economic analysis calculated the net present value (NPV) for cases involving steady-state synfuel production for comparison with the NPV for a business-as-usual case in which NPP continues to sell only electric power to the grid. A synfuel production “Reference Case” was considered in addition to sensitivity cases in which the plant capacity, electricity price, and synthetic fuel product prices were perturbed. The synfuel production Reference Case considered a scenario in which the electrolysis and synfuel plants utilized a combined electrical load of 1000 megawatt electrical (MWe) from the LWR with the balance of the LWR power output being sold to the electric grid. The economic analysis suggests that the synfuel production Reference Case evaluated in this analysis would lead to considerable economic potential for near-term deployment of a nuclear-based synfuel production plant. Specifically, the economic analysis suggests that the deployment of a 1000 megawatt (MW) nuclear-powered synfuel plant could result in a NPV increase of approximately $\$ $1.7 billion for a case with no clean synfuel price premium relative to conventional petroleum fuels when accounting for the additional revenues from the 2022 IRA clean hydrogen PTCs of $\$ $3/kg. Sensitivity analysis was performed to evaluate the effect of perturbation of selected model input parameters on the NPV for the synfuel production Reference Case. The sensitivity analysis indicates that the plant capacity has the largest impact on the differential NPV, with a smaller synfuel production capacity resulting in a decrease in revenue when a larger fraction of the power from the NPP is sold to the grid and a smaller fraction of the power is used to produce synthetic fuel products. The synfuel product pricing has the next largest impact on the differential NPV, with lower synfuel prices resulting in decreased NPV from decreased synfuel sales revenue while higher synfuel prices result in increased NPV from increased synfuel sales revenue. Electricity pricing has a smaller effect on the NPV than the fuel sales price since, in the Reference Case, most of the energy from the NPP is used for synfuel production and a smaller amount of the system revenues are associated with electrical power sales. However, the electricity price sensitivity does indicate that the Synfuel Integrated Energy System (IES) would have a greater NPV than the business-as-usual case (e.g., grid power sales only) when electricity market prices are low, suggesting that synfuel production could provide a strategy for decreasing the economic risks to NPPs posed by a loss of revenues attributed to falling electricity market prices.

10 SYNTHETIC FUELS↗
DOE OSTI2020

Evaluation of the Specification for Safety-Related Steel Structures for Nuclear Facilities, ANSI/AISC N690-18, for Application to Nuclear Power Plants

This report describes the assessment of the recently published ANSI/AISC N690-18, Specification for Safety-Related Steel Structures for Nuclear Facilities. This work was performed for the U.S. Nuclear Regulatory Commission for potential endorsement of N690-18 for use in the design of nuclear power plants. Currently the NRC endorses the use of an earlier version: N690-1994 (R2004), and thus, a technical review of the updated N690 Specification, which contains significant changes, is warranted. The N690-18 Specification reflects advances and improvements in steel design gained from experience, analytical studies, and experimental data over the years. The N690-18 specification also contains a new Appendix N9 that addresses the design of safety-related steel-plate composite (SC) walls which are a relatively new type of structural member for which previously there has not been any U.S. code or standard that governs its design. The technical review of N690-18 was performed in order to assess the adequacy of the provisions for use by the NRC in updating its regulatory guidance for nuclear power plants. The research developed the technical basis for acceptance of the new specification and also identified areas where additional staff guidance is needed for the design of safety-related steel structures at nuclear power plants. The results of the research have determined that the N690-18 specification is a significant enhancement from the N690-1994 (R2004) edition. The new specification contains substantial upgrades in the design of structural steel and includes new provisions for design of SC wall sections, which can benefit the nuclear power industry as well as the NRC review process. All of the improvements, if endorsed by the NRC with certain regulatory positions, will allow clearer and more consistent regulatory guidance, and will avoid the need for justification by licensees and related reviews each time certain methods or approaches are used.

42 ENGINEERING↗