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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Validation of HELIOS for ATR Core Follow Analyses

This work summarizes the validation analyses for the HELIOS code to support core design and safety assurance calculations of the Advanced Test Reactor (ATR). Past and current core safety assurance is performed by the PDQ-7 diffusion code; a state of the art reactor physics simulation tool from the nuclear industry’s earlier days. Over the past twenty years, improvements in computational speed have enabled the use of modern neutron transport methodologies to replace the role of diffusion theory for simulation of complex systems, such as the ATR. More exact methodologies have enabled a paradigm-shift away from highly tuned codes that force compliance with a bounding safety envelope, and towards codes regularly validated against routine measurements. To validate HELIOS, the 16 ATR operational cycles from late-2009 to present were modeled. The computed power distribution was compared against data collected by the ATR’s on-line power surveillance system. It was found that the ATR’s lobe-powers could be determined with ±10% accuracy. Also, the ATR’s cold startup shim configuration for each of these 16 cycles was estimated and compared against the reported critical position from the reactor log-book. HELIOS successfully predicted criticality within the tolerance set by the ATR startup procedure for 13 out of the 16 cycles. This is compared to 12 times for PDQ (without empirical adjustment). These findings, as well as other insights discussed in this report, suggest that HELIOS is highly suited for replacing PDQ for core safety assurance of the ATR. Furthermore, a modern verification and validation framework has been established that allows reactor and fuel performance data to be computed with a known degree of accuracy and stated uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Validation of the Physics Analysis used to Characterize the AGR-1 TRISO Fuel Irradiation Test

The results of a detailed physics depletion calculation used to characterize the AGR-1 TRISO-coated particle fuel test irradiated in the Advanced Test Reactor (ATR) at the Idaho National Laboratory are compared to measured data for the purpose of validation. The particle fuel was irradiated for 13 ATR power cycles over three calendar years. The physics analysis predicts compact burnups ranging from 11.30-19.56% FIMA and cumulative neutron fast fluence from 2.21?4.39E+25 n/m 2 under simulated high-temperature gas-cooled reactor conditions in the ATR. The physics depletion calculation can provide a full characterization of all 72 irradiated TRISO-coated particle compacts during and post-irradiation, so validation of this physics calculation was a top priority. The validation of the physics analysis was done through comparisons with available measured experimental data which included: 1) high-resolution gamma scans for compact activity and burnup, 2) mass spectrometry for compact burnup, 3) flux wires for cumulative fast fluence, and 4) mass spectrometry for individual actinide and fission product concentrations. The measured data are generally in very good agreement with the calculated results, and therefore provide an adequate validation of the physics analysis and the results used to characterize the irradiated AGR-1 TRISO fuel.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Funding for the 2ND IAEA technical meeting on fusion data processing, validation and analysis

The International Atomic Energy Agency (IAEA) will organize the second Technical Meeting on Fusion Da Processing, Validation and Analysis from 30 May to 02 June, 2017, in Cambridge, MA USA. The meeting w be hosted by the MIT Plasma Science and Fusion Center (PSFC). The objective of the meeting is to provide a platform where a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolation needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge based understanding of the physical processes governing the dynamics of these plasmas. The meeting will aim at fostering, in particular, discussions of research and development results that set out or underline trends observed in the current major fusion confinement devices. General information on the IAEA, including its mission and organization, can be found at the IAEA websit Uncertainty quantification (UQ) Model selection, validation, and verification (V&V) Probability theory and statistical analysis Inverse problems & equilibrium reconstru ction Integrated data analysis Real time data analysis Machine learning Signal/image proc essing & pattern recognition Experimental design and synthetic diagnostics Data management

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Separate-Effects Validation Experiments for Models of Fracture in Ceramic Nuclear Fuel

A number of advances have recently been made in modeling fracture initiation and propagation in ceramic light water reactor (LWR) fuel. These include the use of techniques such as peridynamics, the extended finite element method (XFEM), the discrete element method (DEM), and phase field fracture. Improved predictions of fracture in LWR fuel can benefit fuel performance simulations in a number of ways, with important implications for radial relocation, pellet-cladding mechanical interactions, and fragmentation during accident conditions. Although these modeling approaches appear promising, to-date most of their applications have been to fresh fuel. A major limitation in applying these approaches with confidence to a wider variety of conditions, such as fragmentation of high-burnup fuel, is that there is very limited data that can be directly used to validate the results of these fracture models. While fracture patterns are available from cross-sections of numerous irradiated fuel rods, the fuel rods have typically been subjected to complex irradiation histories. To validate models of fracture propagation, focused experiments that give snapshots of the initiation and propagation of fracture under well characterized prototypical reactor conditions are needed. Under a multi-institutional U.S. Department of Energy Integrated Research Project (IRP), three separate-effects validation experiments are underway to provide information on the propagation of cracks in LWR fuel under controlled conditions. The primary challenge in developing such an experiment is in providing conditions that result in a radial temperature distribution that is prototypical of LWR in-reactor conditions. Two out-of-reactor experiments are being planned that employ very different approaches to achieve such a temperature distribution. The first of these achieves this by employing a combination of inductive and resistive electrical heating to generate volumetric heating. The second experiment involves slowly heating a pellet in a metal rod to a high temperature, and then quenching that rod in a cold bath. The quenching process generates a temperature profile approximating that in an LWR fuel rod for a moment, but has a very different temperature history from the LWR. Finally, an experiment is being planned for the Idaho National Laboratory TREAT reactor that will use nuclear fission as a heat source, and which will employ a metal heat sink to replicate the thermal conditions provided by coolant in an LWR. These experiments all have their advantages and drawbacks, with varying levels of ability to reproduce actual LWR conditions and varying ability to use instruments to monitor quantities of interest over the course of the experiment that can be used to validate fracture models. For that reason, these different experimental approaches are complimentary to each other, and the combined results are expected to significantly improve confidence in the ability of computational models to simulate fracture in ceramic nuclear fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Realistic Synthetic Distribution Grids: Summary of Validation Results

The presentation slides will walk us through the validation process and results of the synthetic distribution grid data. The synthetic grids for the distribution systems were developed as part of the ARPA-E funded GRIDDATA program project, SMART-DS. Three large scale datasets for US style distribution system were developed: 1) SAF: Santa Fe urban region, 2) GSO: Greensboro urban, semi-urban and industrial region, and 3) SFO: San Francisco Bay Area urban, semi-urban, industrial and rural areas. These datasets were validated using a three-pronged validation process, including statistical, operational and expert validation phases; the results of which have been summarized in this deck.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Subcomponent Validation of Composite Joints for Marine Energy Structures

The Marine Energy Advanced Materials project addresses the barriers and uncertainties facing marine renewable energy developers in using composite materials for load-bearing structures. Sponsored by the U.S. Department of Energy's Water Power Technologies Office, the multiyear project comprises of collaborators from the National Renewable Energy Laboratory (NREL), Sandia National Laboratories, Pacific Northwest National Laboratory (PNNL), Montana State University (MSU), Florida Atlantic University (FAU), and industry stakeholders. As part of the Marine Energy Advanced Materials project, marine renewable energy industry surveys and assessments were conducted to identify key materials and knowledge gaps that hinder the adoption of composite materials in marine renewable energy structures. Specific knowledge gaps highlighted for composite materials were environmental effects, fatigue strengths, and bonded and bolted interconnects (composite/composite and composite/metal). It was concluded that many of these gaps could be addressed through subcomponent validation; consequently, a program was developed at NREL with the goals of developing subcomponent validation methods for appropriate marine energy materials, which would improve the understanding of design allowables for full-scale structural components and joints. Ultimately, the aim is to reduce timelines and costs associated with full-scale structural validation efforts while also providing near-net-scale static and fatigue data of composite/metal subcomponents for marine renewable energy systems. To approach these goals, a testing program was developed at NREL to investigate a variety of materials and structural design details at the subcomponent scale to understand (a) the effects of harsh and corrosive marine energy environments and (b) the static and fatigue strengths of the complex geometries. The recent study from this testing program is perhaps the largest that has ever been conducted with respect to specimen scale and geographic diversity of underwater environmental conditions that the specimens were subjected to. A variety of specimen geometries were designed by NREL to highlight key features of multimaterial (composite/composite or metal/composite) interconnects that may be used in marine renewable energy structural designs. The designs used several different composite matrices, adhesives, and marine-grade steels, which were highlighted in the surveys as being the most appropriate for harsh marine environments. Composite panels were then manufactured at MSU, and were subsequently manufactured into test specimens by NREL. The specimens were shipped to FAU and PNNL for conditioning in ocean water tanks at various temperatures for an extended period. The specimens were then returned to NREL for structural validation. This presentation will provide an overview of recent advances within the testing program in terms of specimen design and test methods, and will discuss results and key findings of the subcomponent testing program to date at NREL.

adhesives↗
DOE OSTI2023

Bison Verification and Validation Activities for TRISO

Numerical modeling and simulation (M&S) tools play a key role in the research, development, and overall safety assessments of next-generation nuclear energy systems. One such tool, Bison, is a nuclear fuel performance code that is applicable to many fuel forms (e.g., light-water reactor fuel, oxide and metallic fuel for fast reactors, tri-structural isotropic (TRISO) fuel, and plate fuel), and it uses the finite element method to model the thermo- mechanical response of nuclear fuels. One fuel form widely utilized in Generation-IV high-temperature gas-cooled and fluoride- salt-cooled nuclear reactor concepts is TRISO fuel. Recently, Bison’s capabilities were significantly expanded to enable it to model the performance of TRISO particles and compacts. It is important that Bison’s computational results be reliable and predictive, since this code is used to inform high-consequence decisions. The various processes developed to address this issue generally entail two fundamental steps: verification and validation (V&V). Verification ensures that the code functions correctly and is reliable. Code/solution verification, code benchmark, and software quality assurance exercises are examples of verification activities. On the other hand, validation is the process of assessing a code’s capability to accurately model physical problems. Comparisons between code results and experiments quantify the validation level. Application of V&V procedures is crucial to the development of computational tools that are free of coding mistakes and can accurately represent reality. The current study presents an overview of Bison V&V activities relevant to the TRISO fuel concept, which include code/solution verification exercises, CRP-6 Benchmark—a Coordinated Research Program through the International Atomic Energy Agency (IAEA)—exercises, and validation exercises with the Advanced Gas Reactor (AGR)- 1/2/3/4 experiment series.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Design and Validation Testing of TruckScan to Assay Large Sacks of Fukushima Radioactive Debris on a Truck

As a result of the March 2011 earthquake and resulting tsunami in Japan, there was a serious accident at the Fukushima Dai-ichi Nuclear Power Plant. This accident has contaminated soil and vegetation in a wide area around the plant. Decontamination projects over the last 4 years have resulted in large numbers of 1 cubic meter canvas bags of debris, commonly called Super Sacks [SS]. These are currently stored nearby where they were generated, but starting in 2015, they will be moved to various Interim Storage Facilities [ISF]. Trucks will typically carry 8-20 of these SSs. When the trucks arrive at the ISF they need to be rapidly sorted into groups according to radioactivity level, for efficient subsequent processing. Canberra Industries, Inc. [CI] has designed a new truck monitoring system 'TruckScan' for use at these ISFs. The TruckScan system must measure the entire truck loaded with multiple closely packed SSs, and generate a nuclide specific assay report showing the radioactivity in each individual SS. The Canberra-Japan office, along with Obayashi Corporation have performed validation testing to demonstrate to the regulatory authorities that the proposed technique was sufficiently accurate. These validation tests were conducted at a temporary storage area in Fukushima prefecture. Decontaminated waste of various representative types and of various levels of radioactivity was gathered and mixed to create homogeneous volumes. These volumes were sampled multiple times and assayed with laboratory HPGe detectors to determine the reference concentration of each pile. Multiple SSs were loaded from each pile. Some of the SSs were filled 50% full, others 75% full, and others 100% full, to represent the typical loading configuration of the existing SSs in the field. The content of the SSs are either sand, soil, or vegetation with densities ranging from 0.3 g/cc - 1.6 g/cc. These SSs with known concentrations of Cs-134 and Cs-137 were then loaded onto trucks in a variety of configurations, typical of how they might be on the real trucks. A partial system was installed at the site and used to assay these trucks with the various loading configurations. Whereas the full system will have 8 collimated 3 x 3'' NaI detectors, the test system only had two detectors; therefore the truck was moved and counted 4 times. The data were acquired and analyzed with the Canberra Genie software to determine the peak counts for both Cesium nuclides. That data was then analyzed with a prototype version of a Maximum Entropy algorithm, to determine the individual SS activity. The goal of the validation tests was to demonstrate that the system could detect 1000 Bq/kg in 15 seconds, and to determine how accurately it could quantify individual SSs. The validation tests demonstrated that the product would perform as predicted. The TruckScan results were consistent with the sample assay results [y = 1.0029 x, R{sup 2} = 0.914]. The Total Propagated Uncertainty, including both uncertainties from these tests and others that were estimated but not tested was 16.6% percent. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Experimental and numerical validation of an ultrasonic visualization system for nuclear reactor application

This paper deals with the design of ultrasonic imaging systems for the next generation of nuclear reactors cooled by liquid metal. Indeed, a generation IV research nuclear reactor is being developed by the Belgian Nuclear Research Center (SCK-CEN) in the frame of the MYRRHA project (for Multipurpose hYbrid Research Reactor for High-tech Applications). This sub-critical/critical reactor is cooled by Lead-Bismuth Eutectic (LBE). The opacity of this liquid metal requires the development of an ultrasonic visualization system for internal inspection and object detection. But due to the peculiar conditions met in the core of the reactor, velocity as well as temperature gradients are expected and are likely to affect directly the ultrasonic propagation. The objective of this work is to validate the ultrasonic imaging strategy by tests performed in a dedicated test rig and by numerical simulations using a ray-tracing method. The experimental investigations have been performed on a specific water facility reproducing conditions similar to those encountered in the core of the MYRRHA reactor. These conditions include the propagation over large distance, and the presence of temperature and velocity gradients. In the MYRRHA reactor application, the distance to be travelled by the acoustic waves of the visualization system is about 5 m, including a reflection. The acoustic absorption, the scattering losses, the beam divergence and the transmitted energy during reflection have been determined as a function of the travelled distance. The experimental values are compared with the literature for validation. The presence of temperature and velocity gradients in the core of the reactor is due to the coolant circulation. These gradients are about 5 K over 0.1 m and 1 m/s over 0.2 m, respectively, and are reproduced in the facility for investigating their influence on the propagation of ultrasounds. The experimental data are used for improving and validating a ray-tracing algorithm. This algorithm is then applied to the full scale application for validating the ultrasonic visualization system for nuclear reactor application. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Calibration and validation of NRC fuel performance models

FRAPCON and FRAPTRAN are the steady-state and transient fuel performance codes, respectively, that are used by the U.S. Nuclear Regulatory Commission (NRC) in performing confirmatory calculations of licensee fuel performance codes and safety analysis methods during the review and approval of these codes and methods for light-water reactors. The NRC also uses these codes to perform calculations to direct regulatory research and to assist in the development of new regulations and regulatory guides. FRAPCON and FRAPTRAN are well-validated fuel performance codes that are kept in a constant state of maintenance. FRAPCON and FRAPTRAN have an extensive database of separate effects data used to validate individual material property and fuel performance models and an integral effects database used to assess the overall code prediction within the full range of fuel operations. The key code predictions that are of regulatory interest as they relate to various specified acceptable design limits are: fuel and cladding temperature, rod internal pressure, cladding hoop strain, cladding corrosion and hydriding, and fission gas release. To assess the ability of the code to accurately predict these values, the integral assessment database consists of measurements of fuel centerline temperature, fission gas release, void volume, cladding corrosion, and cladding hoop strain. This paper will discuss the activities that are performed to ensure that FRAPCON and FRAPTRAN represent the state of the industry and will describe the separate effect and integral effect databases that are used to validate the models and are continually being expanded to ensure validation over the full range of fuel operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Employing Whisper in selecting benchmarks for traditional validation methods

The Nuclear Criticality Safety Program at Sandia National Laboratories (SNL) uses a collection of benchmarks developed from the International Handbook of Evaluated Criticality Safety Benchmark Experiments for validation of MCNP. In early 2016, an effort began to expand the benchmark collection to cover a broader range of materials and neutron spectra. The program undertook the task of updating current benchmarks to reflect best practices from Los Alamos National Laboratory (LANL) for MCNP calculations. Spring of 2016, LANL shared the Whisper code with SNL in a collaborated effort to investigate application of the code to activities at SNL. Whisper is a statistical package developed to support nuclear criticality safety validation efforts. It measures how well benchmarks correlate to a system or process and calculates a USL. Whisper has begun to develop into an asset for the SNL Nuclear Criticality Safety team to determine and reassure benchmarks selected for validation truly correlate process parameters (i.e., fall within an acceptable Area of Applicability). SNL's use of traditional statistical methods, with the abilities of Whisper to identify correlating benchmarks, has facilitated in ensuring confidence in validation and USL determination. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Validation Study in SAS4A Code in Simulated Mild TOP Condition

Model improvements and validation efforts for SAS4A code, which is the most advanced computer code for simulating the the primary phase of the Core Disruptive Accident (CDA) of MOX-fueled Sodium-cooled Fast Reactors, have been performed utilizing the experimental data from the CABRI programs by JAEA (Japan Atomic Energy Agency), IRSN (Institut de Radioprotection et de Surete Nucleaire), CEA (Commissariat a l'Energie Atomique et aux Energies Alternatives) and KIT (Karlsruhe Institute of Technology). In order to confirm validity of improved models of SAS4A, a systematic and comprehensive validation plan was defined. It was based on the PIRT (Phenomena Identification and Ranking Table) result for CDA of MOX-fueled fast reactors. The fuel failure position and time are the most important parameters, which dominate the analytical results in a reactor calculation. The failure position will affect the reactivity feedback due to the fuel distribution after failure and consequently would have an effect on the energy release in the initiating phase. This paper describes the preliminary result of validation study for SAS4A code in simulated Transient Over-Power (TOP) condition. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Experimental validation of the Cristal V2.0 French criticality calculation package - 14587

A new version of the CRISTAL criticality calculation package, named CRISTAL V2.0 [1], has been developed by IRSN and CEA, in collaboration with AREVA and EDF. Four calculation routes are now available, using nuclear data issued from the JEFF-3.1.1 evaluation: two multigroup routes based on 281 groups cross-sections (APOLLO2 - MORET 5 or APOLLO2-Sn calculations), a pointwise Monte Carlo route (TRIPOLI-4{sup R}) and a criticality standard calculation route. The CRISTAL V2.0 package, which will be delivered soon to OECD/NEA data bank, benefits from a broad validation database covering almost all areas of criticality-safety applications, from fuel fabrication to reprocessing, including transportation. 3,127 critical experiments, corresponding to 342 series, either issued from the OECD/ICSBEP Handbook or performed in French facilities (confidential data) were selected for the CRISTAL V2.0 validation database. Currently, more than 2,300 experiments are already part of the validation database. This validation work highlights an overall consistency to experimental data and inter-comparisons between the different calculation routes mainly show good agreements on a large set of common experiments. (authors)

42 ENGINEERING↗
DOE OSTI2022

Pronghorn Porous Media Model Validation with Pressure Drop Measurements

The verification and validation (V&V) of Pronghorn is imperative to assert its accuracy when predicting the fluid velocity, temperature, and pressure in high temperature gas-cooled reactors. Pronghorn is a coarse-mesh, intermediate-fidelity, and multidimensional thermal-hydraulics (TH) code developed by the Idaho National Laboratory (INL). New pebble bed experiments are used to observe the details of the fluid motion and pressure drop in the porous bed under the reactor normal operation. This paper focuses on the validation of the Pronghorn compressible and incompressible Navier-Stokes equations using the pressure drop measurements performed at the engineering-scale pebble bed facility at the Texas A&M university (TAMU). Various pressure drop correlations and porosity functions are implemented in both Pronghorn and STAR-CCM+ to compare the pressure drop due to the combined viscous and inertial resistances in the porous bed. The correlations accounting for the near-wall effect are also utilized to observe if the pressure drop estimates can be improved. Pronghorn porous media models predict the pressure drop well relative to the STAR-CCM+ simulation results and 1D correlations, and both the finite element method (FEM) and finite volume method (FVM) perform accurately. Pronghorn models are also validated with the experimental measurements given the different Reynolds number ranges and specific aspect ratios. The likelihood of the statistical significance between the pressure drop measurements and specific correlations or simulations is low provided that the overlap of their confidence intervals is more than the half of a single arm. Several validation metrics are reasonable in regard to the similar studies from other literature. The precise average pebble bed porosity estimation has much impact on the pressure drop, and the Foumeny and Montillet (dense packing) models carry out the accurate pressure drop prediction by considering the near-wall effect.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS

This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

RELAP5-3D HTGR Validation Work at Idaho National Laboratory

Prismatic block-type high-temperature gas-cooled reactors (HTGRs) were built in the United States decades ago, and now advanced reactor vendors are seeking to deploy them again for a variety of applications. Deploying these reactors requires modelling and simulation tools that have been validated against conditions representative of the HTGR application. Idaho National Laboratory (INL) is leading the execution an of HTGR thermal hydraulics benchmark to accelerate the validation of thermal hydraulics modelling and simulation tools for these applications. That benchmark is based on a facility called the High Temperature Test Facility (HTTF). This work provides an overview of work conducted at INL over the last 2 years to validate RELAP5-3D against data from HTTF. This presentation shows results from multiple RELAP5-3D models and an HTTF experiment to assess the impact of certain modelling assumptions on results. The contents of this talk sit on the cutting edge of RELAP5-3D validation for HTGR analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Validation of Scale-Derived Ages in Wild Juvenile and Adult Steelhead Using Parental-Based Tagging

Abstract Accurate age information is a critical component in fisheries monitoring, management, and research. The ability to assign accurate ages to fish by using nonlethal structures is vital in calculating cohort productivity for fish species with low abundances and variable life histories. A common nonlethal method to assign ages is by interpretation of patterns in scales. Validation of ages is not easily obtained for free-ranging fishes; however, the development of genetic “tags” has expanded age validation opportunities. In this study, we used parental-based genetic tagging to validate ages determined from scales collected from juvenile and adult steelhead Oncorhynchus mykiss in two streams within the Snake River basin. Juvenile scale ages were in agreement with 93% of the known ages. Adult scale ages were in agreement with 89% of the known ages. Although overall bias in juvenile ages was very low, we saw a slight positive bias in younger fish (young of the year and age 1) and a small negative bias in older juveniles (ages 2–4). A small negative bias in ages of adults was a consequence of errors in freshwater age. The errors observed did not significantly bias age compositions because the 90% confidence intervals about the age proportions based on scales contained the known proportions; therefore, scale analysis is an acceptable method for assigning ages to Snake River steelhead. We discuss the value of validated known-age scales as a reference collection, and as an illustrative use, we constructed a circulus count guide to aid technicians in identifying missing annuli and distinguishing true from false annuli. To demonstrate the use of the circulus guidelines, we reanalyzed samples with age discrepancies, applying the circulus count data and the known age to identify mistakes.

Reinhardt, Leslie↗
DOE OSTI2024

Development and cross‐validation of a circumference‐based predictive equation to estimate body fat in an active population

Abstract Objective The U.S. Army uses sex‐specific circumference‐based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations. Methods Body size and composition were evaluated in a representatively sampled cohort of 1904 active‐duty Soldiers (1261 Males, 643 Females), using dual‐energy X‐ray absorptiometry (%BF DXA ), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BF DXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers. Results Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3‐site model to a 1‐site model had minimal impact on measurements of model accuracy and performance. Male‐specific equations demonstrated larger gains in accuracy, whereas female‐specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort. Conclusions The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1‐site waist circumference‐based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

Taylor, Kathryn M.↗