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At least 757 records · Page 42

Validation study for crediting chlorine in critically analyses for spent nuclear fuel disposition - 14428

Spent nuclear fuel (SNF) management practices in the United States rely on dry storage systems that include both canister- and cask-based systems. The United States Department of Energy Used Fuel Disposition Campaign is examining the feasibility of direct disposal of dual-purpose (storage and transportation) canisters (DPCs) in a geological repository. One of the major technical challenges for direct disposal is the ability to demonstrate the subcriticality of the DPCs loaded with SNF for the repository performance period (e.g., 10,000 years or more) as the DPCs may undergo degradation over time. Specifically, groundwater ingress into the DPC (i.e., flooding) could allow the system to achieve criticality in scenarios where the neutron absorber plates in the DPC basket have degraded. However, as was shown by Banerjee et al., some aqueous species in the groundwater provide noticeable reactivity reduction for these systems. For certain amounts of particular aqueous species (e.g., chlorine, lithium) in the groundwater, subcriticality can be demonstrated even for DPCs with complete degradation of the neutron absorber plates or a degraded fuel basket configuration. It has been demonstrated that chlorine is the leading impurity, as indicated by significant neutron absorption in the water that is available in reasonable quantities for the deep geological repository media under consideration. This paper presents the results of an investigation of the available integral experiments worldwide that could be used to validate DPC disposal criticality evaluations, including credit for chlorine. Due to the small number of applicable critical configurations, validation through traditional trending analysis was not possible. The bias in the eigenvalue of the application systems due only to the chlorine was calculated using TSURFER analysis and found to be on the order of 100 percent mille (1 pcm = 10-5 k{sub eff}). This study investigated the design of a series of critical configurations with varying amounts of chlorine to address validation gaps. Such integral experiments would support the crediting of the chlorine neutron-absorption properties in groundwater and the demonstration of subcriticality for DPCs in deep geologic repositories with sufficient chlorine availability. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, 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. 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 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 can 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↗

Validating Mixtures of 233 U, 235 U, and 239 Pu for the Sum-of-Fractions Method

The Sum-of-Fractions method is a technique used to assure that homogeneous mixtures of fissile and fissionable isotopes are below a minimum margin of k eff or reactivity. Current work by Pacific Northwest National Laboratory examines different mixtures of 233 U, 235 U, and 239 Pu to determine critical mass limits for mixtures of transuranic actinides lacking a validation basis. To provide a validation basis for these limits, the work presented here describes the results of a sensitivity and uncertainty analysis of various mixtures of these isotopes in various concentrations moderated and reflected by light water and polyethylene. The TSUNAMI-1D sequence in the SCALE code system was used to generate sensitivity coefficients for three different concentrations of mixtures of 233 U, 235 U, and 239 Pu. The TSUNAMI-IP sequence was then used for similarity assessment (c k ) with critical benchmark experiment sensitivity data files (SDFs) from the Oak Ridge National Laboratory Verified, Archived Library of Inputs and Data and the Nuclear Energy Agency SDF database. The VADER sequence in SCALE was used for statistical testing and to generate upper subcritical limits from the data to develop a basis for validating critical mass limits.

07 ISOTOPE AND RADIATION SOURCES↗

Modeling and Validation of a Residential Multi-Functional Variable Refrigerant Flow Heat Pump System with Heat Recovery

To bridge the existing gap in modeling the variable refrigerant flow heat pump systems with heat recovery (VRFHR), we developed a suite of dynamic VRFHR system models in Modelica. These models are specifically tailored for residential multi-functional VRFHR (MF-VRFHR) applications, including space conditioning and domestic hot water (DHW) heating, utilizing both the TIL library for HVAC equipment and the Buildings library for thermal load calculations. The development comprises essential component models, including the newly developed heat recovery unit (HRU), along with system models that integrate the heat pump system and building envelope. These system models accommodate various operational modes such as heating-only, cooling-only, and heating-recovery (including heating-dominant and cooling-dominant) modes. Furthermore, we propose an efficient optimization-based model calibration method that identifies critical model parameters while utilizing a small amount of data obtained from either real systems or manufacturer's specifications. We demonstrate the effectiveness of these models and the proposed calibration method for a MF-VRFHR system installed in Richland, WA. The developed models are calibrated and validated using data collected under different operational modes during both heating and cooling seasons. The results show that the models capture the system dynamics and achieve high accuracy, with the coefficient of the variation of the root-mean-square-error less than 15% for variables such as outdoor unit power consumption, compressor speed, space temperature and DHW temperature. The validated models serve as a reliable representation of the MF-VRFHR system, facilitating the development and validation of optimized controls needed to realize the full benefits of integrated heat pump systems. Future research will utilize these models to develop advanced controls and optimize system performance for improved energy efficiency and demand flexibility.

Modeling, Variable refrigerant flow (VRF) systems,↗

EMT Model Validation of a 2 MVA PV Inverter Using Transient and Frequency-Domain Hardware Testing: Preprint

This paper presents results and new insights gained from a hardware test campaign on a 2 MVA PV inverter for validating its vendor-supplied EMT model. The test campaign was conducted using a 7 MVA grid simulator and a 2 MW PV emulator. It considered both time-domain transient tests and frequency-domain impedance scan tests. The paper highlights the inadequacy of transient tests in capturing all critical resonance modes of the inverter, and the effectiveness of the frequency scan testing in addressing this problem. The paper shows the frequency scan testing as an effective tool for EMT model validation of IBR units which can highlight inaccuracies in the EMT models that are easy to overlook when model validation is performed using only the time-domain transient tests such as voltage ride-through and phase jump tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simulation and Experimental Validation of an Integrated Heat Pump – Thermal Energy Storage Using a Room-Temperature Phase Change Material

As the dependence on electrical heat pumps (HPs) and intermittent renewables increases, grid strains are expected to grow. This necessitates an energy storage system to reduce the mismatch between energy supply and demand. Thus, a proposed dual-mode commercially available 14.1 kW HP was integrated with a single 22°C phase change material (PCM) thermal storage system (TES) to load-shift both cooling and heating loads. The HP-TES system was manufactured and experimentally tested using a novel test matrix based on AHRI 210/240 psychrometric conditions. Furthermore, transient dual-mode system-level HP-TES models were developed in Modelica and validated using the experimental test conditions. Base HP cooling and heating experimental tests at ambient temperatures of 35°C and −8.3°C show that the modified HP-TES maintained the rated system capacity and performance. The HP-TES discharge provided approximately 30% and 50% reductions in cooling and heating demand, respectively. The transient HP-TES models predicted system capacity and total power input for discharge and recharge operating modes within ±4% mean percentage error, and recharge power input within ±2%, with maximum errors occurring at the equipment startup. During system operation, the sources of model deviations are first-order polynomial fits of the PCM digital scanning calorimetry (DSC) data and unaccounted supercooling in the PCM during solidification. Nonetheless, the model predictions agree with the experimental tests, demonstrating the availability of robust, accurate, and validated transient models that can be used for further validation and the development of system controls.

25 ENERGY STORAGE↗

Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud-Resolving Model Intercomparison and Cross Validation Using Radar Observations

Evolution of precipitation structures are simulated and compared with radar observations for the November Madden-Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground-based, ship-borne, and spaceborne precipitation radars and three cloud-resolving models (CRMs) driven by observed large-scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0-dBZ echo-top heights, and convective organization by contiguous 17-dBZ areas. The multi-radar and multi-model framework allows for more stringent model validations. The emphasis is on testing models' ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site-specific large-scale forcing can reproduce not only common features in cloud populations but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo-top heights for the strongest convection within large, organized precipitation features. Cross validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large-scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo-top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well-validated model simulations could be used to constrain uncertainties in observed echo-top heights when the low-resolution surveillance scanning strategy is used.

54 ENVIRONMENTAL SCIENCES↗

Ball-on-ring test validation for equibiaxial flexural strength testing of engineered ceramics

The validation of a ball-on-ring, equibiaxial flexural strength method to obtain the transverse rupture strength (TRS) of right cylindrical ceramic specimens was performed in this study. Validation of the test method was achieved using commercially available engineered high purity alumina disks and finite element (FE) model analysis. The validated fixture was then used to obtain the TRS and Weibull statistical analysis of MgO-partially stabilized zirconia (MSZ) and Y 2 O 3 -partially stabilized zirconia (YSZ) ceramic disks. TRS data for alumina, MSZ, and YSZ agreed with the TRS values reported in the literature. A statistically relevant number of samples (N > 30) for each material were tested to allow for a Weibull statistical analysis. Weibull parameters for these materials were within the expected values for engineered ceramics. The characteristic strength for alumina, MSZ, and YSZ were determined to be 289, 786, and 814 MPa, respectively. The Weibull modulus was determined between 10 and 25 for each material, which is typical of engineered ceramics. In addition, FE model results were in close agreement with experimental fracture values for the three ceramic materials tested in this study.

36 MATERIALS SCIENCE↗

Experimental validation of a Kalman observer using linearized OpenFAST and a fully instrumented 1:70 model

Abstract To enable real‐time monitoring and control strategies for floating offshore wind turbines, accurate information about the state of the system is needed. This paper details the application of a Kalman filter to the UMaine VolturnUS‐S floating wind platform to provide accurate state estimates in real time using minimal system measurements. The midfidelity nonlinear simulation tool OpenFAST was used to generate the underlying linear state‐space model for the Kalman filter. This linear model and its limitations are demonstrated through comparison with experimental data collected on a 1:70 froude‐scaled model of the floating platform and tower. Using a selection of five measurements from the real system, a Kalman filter was developed to provide estimates for the remaining system states and measurements. These estimates were then validated against the experimental values collected from testing of the scale model. Validation of the Kalman filter produced accurate estimates of surge, heave, and tower base bending moment, measurements of which were not available to the Kalman filter. Performance of the Kalman filter was tested and validated over a range of sea conditions from rated wind speed to storm events and demonstrated robustness in the Kalman filter to maintain accuracy across all operating conditions despite significant error in the underlying linear model for extreme conditions.

17 WIND ENERGY↗

Crystal Plasticity Model Validation Using Combined High-Energy Diffraction Microscopy Data for a Ti-7Al Specimen

High-Energy Diffraction Microscopy (HEDM) is a 3-d x-ray characterization method that is uniquely suited to measuring the evolving micromechanical state and microstructure of polycrystalline materials during in situ processing. The near-field and far-field configurations provide complementary information; orientation maps computed from the near-field measurements provide grain morphologies, while the high angular resolution of the far-field measurements provide intergranular strain tensors. The ability to measure these data during deformation in situ makes HEDM an ideal tool for validating micro-mechanical deformation models that make their predictions at the scale of individual grains. Crystal Plasticity Finite Element Models (CPFEM) are one such class of micro-mechanical models. While there have been extensive studies validating homogenized CPFEM response at a macroscopic level, a lack of detailed data measured at the level of the microstructure has hindered more stringent model validation efforts. Here, we utilize an HEDM dataset from an alphatitanium alloy (Ti-7Al), collected at the Advanced Photon Source, Argonne National Laboratory, under in situ tensile deformation. The initial microstructure of the central slab of the gage section, measured via near-field HEDM, is used to inform a CPFEM model. The predicted intergranular stresses for 39 internal grains are then directly compared to data from 4 far-field measurements taken between ~4% and ~80% of the macroscopic yield strength. In conclusion, the intergranular stresses from the CPFEM model and far-field HEDM measurements up to incipient yield are shown to be in good agreement, and implications for application of such an integrated computational/experimental approach to phenomena such as fatigue and crack propagation is discussed.

36 MATERIALS SCIENCE↗

Validation Data for Benchmarking Wire Arc Additive Manufacturing Process Simulations

Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.

36 MATERIALS SCIENCE↗

A validated thermal and biological model for predicting algal productivity in large scale outdoor cultivation systems

Proper assessment of the sustainability of algal products requires an understanding of algal growth rate with regional and temporal resolution. This study developed a bulk growth model that utilizes geospatial data, reactor geometry inputs, and a maximum of six strain-specific parameters to predict algal productivity with temporal and regional resolution. The model requires local weather data to calculate the time-resolved culture temperature which is combined with a biological model based on maximum theoretical carbon fixation to predict the time-resolved algal concentration. Validation of the model against experimental data illustrates an average ac- curacy of 0.27% ± 5.32% when comparing algal concentration at harvest over 45 days of cultivation data for Galdieria sulphuraria 5587.1, and Galdieria sulphuraria Soos grown in photobioreactors (PBRs) in Mesa, AZ (33.4152° N, 111.8315° W). For open raceway ponds (ORPs), an accuracy of 0.9% ± 2.35% was achieved when comparing algal concentration at harvest over 50 days of cultivation data for Chlorella vulgaris, Desmodesmus intermedius, Nannochloropsis oceanica grown in Atlanta, GA (33.7490° N, 84.3880° W) and Mesa, AZ (33.4152° N, 111.8315° W). The validation trials spanned three seasons (winter, spring, and summer) to ensure model ac- curacy throughout the year, and concentration between harvests was modeled with hourly resolution. The validated model is used to assess the productivity at several case-study locations in the United States with Chlorella vulgaris, grown in open raceway ponds and Galdieria sulphuraria grown in vertical flat panel photo- bioreactors. In conclusion, the model has been published as an open-source tool, in an effort to increase the fidelity of future studies that rely on outdoor algae cultivation for feedstock production and allow for time resolved results for future techno-economic and life cycle assessments.

59 BASIC BIOLOGICAL SCIENCES↗

Re-evaluation of Spent Nuclear Fuel Assay Data for the Three Mile Island Unit 1 Reactor and Application to Code Validation

Destructive radiochemical assay measurements of spent nuclear fuel rod segments from an assembly irradiated in the Three Mile Island unit 1 (TMI-1) pressurized water reactor have been performed at Oak Ridge National Laboratory (ORNL). Assay data are reported for five samples from two fuel rods of the same assembly. The TMI-1 assembly was a 15 X 15 design with an initial enrichment of 4.013 wt% 235 U, and the measured samples achieved burnups between 45.5 and 54.5 gigawatt days per metric ton of initial uranium (GWd/t). Measurements were performed mainly using inductively coupled plasma mass spectrometry after elemental separation via high performance liquid chromatography. High precision measurements were achieved using isotope dilution techniques for many of the lanthanides, uranium, and plutonium isotopes. Measurements are reported for more than 50 different isotopes and 16 elements. One of the two TMI-1 fuel rods measured in this work had been measured previously by Argonne National Laboratory (ANL), and these data have been widely used to support code and nuclear data validation. Recently, ORNL provided an important opportunity to independently cross check results against previous measurements performed at ANL. The measured nuclide concentrations are used to validate burnup calculations using the SCALE nuclear systems modeling and simulation code suite. These results show that the new measurements provide reliable benchmark data for computer code validation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Validation of statistical uncertainties in subcritical benchmark measurements: Part II – Measured data

Part I of this work presented an uncertainty approach which incorporates the singles and doubles counting rates determined by the Hage-Cifarelli formalism of the Feynman Variance-to-Mean method. This moments-based approach utilizes time correlations between prompt neutrons detections to assess the system multiplication. Additionally, it presented a validation which utilized simulated data generated using a 0-D point-kinetics Monte Carlo code. In Part II, this same method and validation approach is applied to measured data of a subcritical benchmark experiment. These measurements were performed with a 4.5 kg sphere of alpha-phase weapons grade plutonium reflected by copper and/or polyethylene. Finally, the results of 17 configurations are shown including detailed validation for four of the configurations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Experimental validation of the mechanistic scale-up methodology of gas–solid spouted beds using radioactive particle tracking (RPT)

The very high-temperature reactors (VHTRs) are highly ranked among candidates of Generation IV of nuclear reactors due to their high efficiency, safety, the resistance to proliferation, and reliability. The VHTRs are preferentially fueled by Tristructural-isometric (TRISO) coated fuel particles which has fuel kernels of fissile material coated by four coating layers: a porous buffer pyrolysis carbon layer (buffer PyC), an inner dense pyrolysis carbon layer (IPyC), a silicon carbide layer (SiC) and an outer dense pyrolysis carbon layer (OPyC). The heart of the operation and safety of the VHTRs significantly depends on the reliability of the coating layers of TRISO particles to retain metallic and gaseous fission products within the particles. The technique used for coating TRISO particles are gas-solids spouted beds via chemical vapor deposition (CVD). Fabrication of high-quality low-defect TRISO fuel particles fuel at larger scale spouted beds is required to support the commercialization of the VHTRs. In this work, our new developed mechanistic scale-up methodology of gas-solids spouted beds based on matching the radial profile of gas-holdup has been demonstrated and validated using radioactive particle tracking (RPT). Two spouted beds of small and larger scales were used in the study. Three sets of conditions were carried out which include the conditions of the reference case in the large scale, conditions that provide similar gas holdup radial profile to that of the reference case and conditions that provided dissimilar gas holdup radial in the small-scale spouted beds. The results confirm the validation of the scale-up methodology in terms of the dimensionless values of the spout diameter, cumulative probability distribution of the solids particles penetration into the spout, fraction of cycle time in each region of the bed, the radial profiles of the dimensionless values of the root-mean-square particle velocities and solids eddy diffusivity. Finally, the results further advance the knowledge and understanding of the gas-solids spouted beds provide deeper insight into their solids dynamics and presenting important benchmarking data for validating computational fluid dynamics codes and models. At last, procedures are established for the implementation of the new scale-up methodology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗

Validation of an inverse model of zone air heat balance

Our work introduces the validation method and results of an inverse model of zone air heat balance. The inverse model, implemented in EnergyPlus and published in a previous article [1], calculates highly uncertain model parameters such as internal thermal mass and infiltration airflow by inversely solving the zone air heat balance equation using the easy-to-measure zone air temperature data. The paper provides technical details of validation from the experiments using LBNL's Facility for Low Energy eXperiment in Buildings (FLEXLAB) that measures zone air temperature under the controlled experiment of two levels of internal mass and four levels of infiltration airflow. The simulation results of the zone infiltration airflow and internal thermal mass from the inverse model agree well with the measured data from the FLEXLAB experiments. The validated inverse model in EnergyPlus can be utilized to enhance the energy modeling of existing buildings that enables energy performance assessments for energy efficiency improvements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development, calibration, and validation of a novel gray-box energy model for residential split air conditioners

Energy models for vapor compression refrigeration in residential air conditioners have been developed through white-box, gray-box, and black-box methods in decades. However, existing white-box and gray-box models require complicated equations with detailed geometries while black-box models require substantial experimental data. Further, this paper aims to develop and validate a simple gray-box steady-state energy model without the need for detailed geometries, which can accurately predict the cooling capacity and electrical power input based on outdoor and indoor air conditions, and supply airflow rates. First three state variables, including the evaporation and condensation temperatures, and refrigerant mass flowrate, are applied to develop the energy model and are solved by three physical equations, including the energy conservations at the evaporator and condenser, and the refrigerant volume-mass flow correlation of the compressor. Secondly, seven performance property functions related to three state variables and three physical equations are identified and calibrated by simple temperature and power measurements. Finally, field experiments are conducted on a residential air conditioner to calibrate these performance property functions and validate the developed model. The validated results reveal the model can accurately predict the cooling capacity and electrical power input, with the normalized root mean square errors of 2.3% and 0.87% respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗