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DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Identifying Controlling Variables for Mercury Vapors in Alpha-4 at Y-12: Two Year Data Collection Update

Multiple sensor packages were deployed at Alpha-4 by SRNL, in collaboration with United Cleanup Oak Ridge LLC (UCOR), to monitor mercury vapor concentrations and meteorological parameters. These sensors collected data, inside and outside of the legacy-use facility, for approximately two years. Though data gaps still exist, particularly in colder months, several controlling variables were identified that govern mercury vapor concentrations within Alpha-4. Temperature, barometric pressure gradients, humidity, and wind speed have been identified as controlling variables. A strong positive correlation was seen between mercury vapor concentrations and temperature which generally followed diurnal fluctuations. Temperatures below approximately 10 degrees Celsius did not show any spikes above the PEL, indicating more work can be performed at any time during the winter months – more data should be collected to confirm consistency in this finding. Additionally, spikes in mercury vapor concentrations above that of the permissible exposure limit (PEL; 100 µg/m 3 ) occurred primarily in late afternoon or evening/overnight hours (between 3 PM and 6 AM), which suggests D&D operations might be best scheduled during morning or daytime hours prior to the late afternoon. However, a limited number of spikes did occur outside of the identified window, although this may be attributed to disturbances in air flow and mercury vapor release from work activities performed inside of the Alpha-4 building. The analysis conducted allows for a strong predictive capability for estimating mercury vapor concentrations based upon accurate meteorological parameters. Still, additional data collection, particularly in the winter months, could help to strengthen the predictive power and validate the identified data trends. Further, increased temporal resolution could also help to better characterize the incipient stages of the increases and decreases in the mercury vapor concentration. Continued monitoring support by SRNL at Y-12 is underway at Alpha-4 to further close remaining data gaps and support deactivation and decommissioning work. Within a collaborative effort with UCOR, the SRNL team is collecting mercury vapor data to study the efficacy of a novel mercury suppressant, FerroBlack® which was recently deployed at Alpha-4. In addition, modifications to the current monitoring setup to increase measurement resolution is also being investigated.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

AGC-4 Disassembly Report

The Advanced Reactor Terminology Graphite Research and Development program is currently measuring irradiated material property changes in several grades of nuclear graphite to predict behavior and operating performance within the core of these new high temperature reactor designs. The Advanced Graphite Creep (AGC) experiment, consisting of six irradiation capsules, will generate the irradiated graphite performance data for the Very High Temperature Reactor operating conditions. All six capsules in the experiment conducted at Idaho National Laboratory will be irradiated in the Advanced Test Reactor, disassembled in the Hot Fuel Examination Facility, and examined at the Idaho National Laboratory Research Center. This is the disassembly report describing the disassembly, shipment, post irradiation inspection, and storage of the graphite specimens contained within the AGC 4 irradiation test series capsule (the fourth irradiation capsule of the series). AGC 4 was irradiated in the Advanced Test Reactor (ATR) East Flux Trap (EFT) during ATR Cycle 157D, 158A, 162A, 162B, 164A, 164B, 166A, and Cycle 166B. Approximately 3.6 dpa was achieved. Desired experiment temperatures were exceeded by at least 100C during the second Cycle of irradiation due to the insertion of the KJRR experiment. The capsule was removed from the ATR and transferred to the Hot Fuel Examination Facility on May 15, 2020 and eventually unloaded into the Hot Fuel Examination Facility (HFEF) Decon Cell through Penetration 2D on February 26, 2021. It was moved to the HFEF Main Cell Window 3M for disassembly on March 15, 2021. Disassembly and specimen extraction began March 18, 2021, and packaging of the graphite specimens was completed on April 16, 2021. Several anomalies were noted, specifically that the radiological dose rates were nominally an order of magnitude higher than that of the previous AGC experiments. This report summarizes the disassembly of the AGC 4 experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

AGC-4 Disassembly Report

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Genarris 2.0: A Random Structure Generator for Molecular Crystals

Genarris is an open source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. A MPI-based parallelization scheme has been implemented, which facilitates the seamless sequential execution of user-defined workflows. A new method for estimating the unit cell volume based on the single molecule structure has been developed using a machine-learned model trained on experimental structures. A new algorithm has been implemented for generating crystal structures with molecules occupying special Wyckoff positions. A new hierarchical structure check procedure has been developed to detect unphysical close contacts efficiently and accurately. New intermolecular distance settings have been implemented for strong hydrogen bonds. To demonstrate these new features, we study two specific cases: benzene and glycine. Genarris finds the experimental structures of the two polymorphs of benzene and the three polymorphs of glycine. Program summary Program Title: Genarris 2.0 Program Files doi: http://dx.doi.org/10.17632/grx6mz4pjn.1 Licensing provisions: BSD-3 Clause Programming language: Python, C External routines/libraries: Spglib, ASE, pymatgen, SciPy, mpi4py, scikit-learn, PyTorch, FHI-aims. Nature of problem: Molecular crystal structure prediction. Solution method: Genarris 2.0 generates molecular crystal structures over the 230 space groups, on general and special Wyckoff positions, using physical constraints. Down-sampling of the generated structures may be performed subsequently, based on molecular crystal packing descriptors and an unsupervised machine learning algorithm. Lastly, ab initio structure relaxation may be performed for the final pool. Depending on the user-defined workflow implemented, Genarris may be used to generate diverse molecular crystal datasets to seed evolutionary algorithms or to train machine learning algorithms or as a standalone crystal structure prediction method. Restrictions: For crystal structure generation, the molecule of interest must be semi-rigid with no bond rotational degrees of freedom. Unusual features: Genarris 2.0 is a highly distributed program, making use of MPI for Python parallelization. The user has the ability to design and implement workflows by executing a user-defined list of procedures. Genarris 2.0 offers new features including a machine learning model for estimating the molecular volume in the solid state from the single molecule structure, structure generation in special Wyckoff positions of space groups, hierarchical structure checks including rigorous treatment of non-orthogonal structures, and clustering and down-selection workflows combining first principles simulations with machine learning. (C) 2020 Elsevier B.V. All rights reserved.

Crystal structure prediction↗

NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗

DOE OSTI2022

Reactor physics benchmark of Westinghouse PWR core design suite for high burnup/high enrichment fuel - Part 1: Pin and lattice

Westinghouse has performed a comprehensive set of code-to-code benchmark comparisons to corroborate application of its state-of-the-art NEXUS-based code suite to high burnup and high enrichment (HB/HE) fueled PWR core design and reload analysis. This paper focuses on analysis of the predictions for pin and lattice designs representative of HB/HE core reloads from the Westinghouse advanced lattice code PARAGON2, the Monte-Carlo code SERPENT2 and MPACT, the deterministic neutronic component of VERA. A companion paper presented at this conference analyzes results obtained with the Westinghouse ANC9 core simulator, using lattice data provided by PARAGON2 with the NEXUS cross-section methodology, and MPACT for 2D and 3D core configurations incorporating HB/HE fuel reloads to achieve cycle length extension to 24-month in high-power density PWRs. The results of the pin and lattice benchmark presented in this paper show that the neutronic predictions from PARAGON2 for HB/HE fueled PWRs are in remarkable agreement with predictions from both SERPENT2 and MPACT including for depletion to high fuel burnup values, and employing a set of challenging lattices which feature combined use of burnable absorbers to obtain the required reactivity hold-down to support PWR transition to HB/HE fuel and 24-month operational cycles. As corroborated by this analysis and the analysis contained in the companion paper, the Westinghouse NEXUS-based PWR core analysis package can be confidently applied by industry for design analysis of PWR core reloads adopting HB/HE fuel and properly support the industry commercialization plans for in-reactor deployment. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2016

A multiscale hydro-geochemical-mechanical approach to analyze faulted CO 2 reservoirs: Original Research Article: A multiscale hydro-geochemical-mechanical approach to analyze faulted CO 2 reservoirs

This paper applies a multiscale hydro-geochemical-mechanical approach to analyze faulted CO 2 reservoirs using the STOMP-CO 2 -R code that is coupled to the ABAQUS® finite element package. STOMP-CO 2 -R models the reactive transport of CO 2 causing mineral volume fraction changes that are captured by an Eshelby-Mori-Tanka model implemented in ABAQUS®. A three-dimensional (3D) STOMP-CO 2 -R model for a reservoir containing an inclined fault was built to analyze a formation containing a reaction network with 5 minerals: albite, anorthite, calcite, kaolinite and quartz. A 3D finite element mesh that exactly maps the STOMP-CO 2 -R grid is developed for coupled hydro-geochemical-mechanical analyses. The model contains alternating sandstone and shale layers. The impact of reactive transport of CO 2 on the geomechanical properties of reservoir rocks and seals are studied in terms of mineral composition changes that affect their geomechanical responses. Simulations assuming extensional and compressional stress regimes with and without coupled geochemistry are performed to study the stress regime effect on the risk of hydraulic fracture. The tendency for the fault to slip is examined in terms of stress regime, geomechanical and geochemical-mechanical effects as well as fault inclination. The results show that mineralogical changes due to long-term injection of CO 2 reduce the permeability and elastic modulus of the reservoir, leading to increased risk of hydraulic fracture in the injection location and at the caprock seal immediately above the injection zone. Fault slip is not predicted to occur. However, fault inclination and stress regime have an important impact on the slip tendency factor.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks

Background: With cancer as one of the leading causes of death worldwide, accurate primary tumor type prediction is critical in identifying genetic factors that can inhibit or slow tumor progression. There have been efforts to categorize primary tumor types with gene expression data using machine learning, and more recently with deep learning, in the last several years. Methods In this paper, we developed four 1-dimensional (1D) Convolutional Neural Network (CNN) models to classify RNA-seq count data as one of 17 highly represented primary tumor types or 32 primary tumor types regardless of imbalanced representation. Additionally, we adapted the models to take as input either all Ensembl genes (60,483) or protein coding genes only (19,758). Unlike previous work, we avoided selection bias by not filtering genes based on expression values. RNA-seq count data expressed as FPKM-UQ of 9,025 and 10,940 samples from The Cancer Genome Atlas (TCGA) were downloaded from the Genomic Data Commons (GDC) corresponding to 17 and 32 primary tumor types respectively for training and validating the models. Results: All 4 1D-CNN models had an overall accuracy of 94.7% to 97.6% on the test dataset. Further evaluation indicates that the models with protein coding genes only as features performed with better accuracy compared to the models with all Ensembl genes for both 17 and 32 primary tumor types. For all models, the accuracy by primary tumor type was above 80% for most primary tumor types. Conclusions: We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. Further optimization of the models is needed to improve the accuracy of certain primary tumor types.

Jones, Sara↗

DOE OSTI2023

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-TeP1-03: Beam Quality Correction Factors for Linear Accelerator with and Without Flattening Filter

Purpose: The impact of removing the flattening filter on absolute dosimetry based on IAEA’s TPR-398 and AAPM’s TG-51 was investigated in this study using Monte Carlo simulations. Methods: The EGSnrc software package was used for all Monte Carlo simulations performed in this work. Five different ionization chambers and nine linear accelerator heads have been modeled according to technical drawings. To generate a flattening filter free radiation field the flattening filter was replaced by a 2 mm thick aluminum layer. Dose calculation in a water phantom were performed to calculate the beam quality correction factor k{sub Q} as a function of the beam quality specifiers %dd(10){sub x}, TPR{sub 20,10} and mean photon and electron energies at the point of measurement in photon fields with (WFF) and without flattening filter (FFF). Results: The beam quality correction factor as a function of %dd(10){sub x} differs systematically between FFF and WFF beams for all investigated ionization chambers. The largest difference of 1.8% was observed for the largest investigated Farmer-type ionization chamber with a sensitive volume of 0.69 cm{sup 3}. For ionization chambers with a smaller nominal sensitive volume (0.015 – 0.3 cm{sup 3}) the deviation was less than 0.4% between WFF and FFF beams for %dd(10){sub x} > 62%. The specifier TPR{sub 20,10} revealed only a good correlation between WFF and FFF beams (< 0.3%) for low energies. Conclusion: The results confirm that %dd(10){sub x} is a suitable beam quality specifier for FFF beams with an acceptable bias. The deviation depends on the volume of the ionization chamber. Using %dd(10){sub x} to predict k{sub Q} for a large volume chamber in a FFF photon field may lead to not acceptable errors according to the results of this study. This bias may be caused by the volume effect due to the inhomogeneous photon fields of FFF linear accelerators.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

Improved Creep-Fatigue Models on Advanced Materials for SFR Applications (Final Report)

This report provides an update on the materials performance criteria and methodology relevant to sodium-cooled fast reactors (SFRs). The report is the second deliverable (Level 2) in FY11 (M2A11AN040303) under the work package A-11AN040303 “Materials Performance Criteria and Methodology” as part of the Advanced Structural Materials Program for the Advanced Reactor Concepts. The overall objective of the Materials Performance Criteria and Methodology work project is to evaluate the key requirements for the ASME Code qualification and the Nuclear Regulatory Commission (NRC) approval of advanced structural materials in support of the design and performance of sodium-cooled fast reactors. Advanced materials are a critical element in the development of fast reactor technologies. Enhanced materials performance not only improves safety margins and provides design flexibility, but also is essential for the economics of future advanced fast reactors. Qualification and licensing of advanced materials are prominent needs for the development and implementation of advanced fast reactor technologies. Nuclear structural component designs in the U.S. comply with the ASME Boiler and Pressure Vessel (B&PV) Code Section III (Rules for Construction of Nuclear Facility Components), and the NRC grants licensing. As the SFRs will operate at higher temperatures than the current light water reactors (LWRs), the design of elevated-temperature components must comply with ASME Section III Subsection NH (Class 1 Components in Elevated Temperature Service). A number of technical issues relevant to materials performance criteria and high temperature design methodology in the SFR were identified and presented in earlier reports. A viable approach to resolve these issues and the R&D priority were also recommended. The development of mechanistically based creep-fatigue interaction models for life prediction and reliable data extrapolation was chosen to be the central focus in near-term efforts. Our current focus is on the creep-fatigue damage issue in high-strength ferritic/martensitic steels such as mod.9Cr-1Mo (G91) and NF616 (G92) steels. The current ASME creep-fatigue design rule puts severe limits of fatigue and creep loads for G91 steel, the lead structural material for fast reactors. High-strength ferritic/martensitic steels behave fundamentally differently from austenitic stainless steels, for which the current ASME creep-fatigue design rules were developed. The unique deformation and damage characteristics in G91 steel, e.g. cyclic softening, degradation of creep and rupture strength during cyclic service, demands a new creep-fatigue design procedure that explicitly accounts for the material’s unique creep-fatigue behavior. G92 steel, a variant of G91 steel, is the lead candidate in the Advanced Alloy Development program. There is currently no creep-fatigue design rule available for this advanced alloy. To support the predictive model development and resolve the over-conservative issue with the ASME design rule for G91 steel, we recovered stress relaxation data from thirteen creep-fatigue tests conducted in the late 1980s and early 1990s at Oak Ridge National Laboratory, and conducted extensive data analysis in FY10. Based on this database and available literature data, we have developed a Cyclic Softening Model and a Stress Relaxation Model specifically applied to G91 steel. The Cyclic Softening Model describes the cyclic stress variation as a function of cycle number during creep-fatigue loading, and well captures the cyclic softening effect in G91 steel. The Stress Relaxation Model predicts the stress relaxation curve during the hold time of cyclic loading, and its dependence on the cyclic softening effect of G91 steel. Two creep-fatigue test systems have been set up to conduct model-oriented creep-fatigue experiments. Results from three creep-fatigue experiments on Heat 30176 of G91 steel are presented in the report: (1) a test performed at 550°C with total strain amplitude of 0.25% and a hold time of 60 s applied at peak strains in both tension and compression, (2) a test performed at 400°C with total strain amplitude of 0.5% and a tension and compression hold time of 60 s, and (3) a test performed at 20°C with total strain amplitude of 0.5% and a tension and compression hold time of 60 s. Three different test temperatures were chosen for two primary reasons: to determine the transition temperature of creep-fatigue interaction from a plasticity-dominated process to a creep-dominated process; to develop unified creep-fatigue models applicable for a wide range of temperatures. With the detailed information obtained in the creep-fatigue experiments, we have further refined the Cyclic Softening Model and Stress Relaxation Model. The Cyclic Softening Model and Stress Relaxation Model were incorporated into the Bilinear Creep-Fatigue Damage Model, forming a powerful framework for the life prediction by an improved creep-fatigue evaluation methodology. The cyclic softening and consecutive stress relaxation responses in G91 steel can be considered for each cycle of the entire cyclic process in the model calculation. The creep-fatigue damage in G91 steel was evaluated using the improved Bilinear Creep-Fatigue Damage Model without any safety margins. It was found that due to the significant cyclic softening in G91 steel, the unit creep damage in each cycle decreased continuously with increasing number of cycles. This continuous change in creep damage with cycling has significant implication in the evaluation of the total creep-fatigue damage. The total creep damage can be one order of magnitude lower when the unit creep damage at half-life was used in the evaluation in comparison with the calculations using the unit creep damage at cycle 10. An important conclusion was that the accurate assessment of the creep-fatigue damage in G91 steel must consider the history of cycling. This analysis provides a more realistic assessment of creep-fatigue damage and identifies critical factors that must be considered in the development of future advanced models for high-strength ferritic/martensitic alloys. An accelerated creep-fatigue testing methodology is proposed for the design of model-oriented experiments to guide and validate model developments. Future work will focus on creep-fatigue experiments of both G91 and G92 steels, and development of creep-fatigue models applicable to advanced ferritic/martensitic alloys. The Cyclic Softening Model and Stress Relaxation Model will be improved by incorporating microstructural parameters of dislocation density, subgrain structure, and second-phase particles. Collaborative modeling of combined Cyclic Softening Model, Stress Relaxation Model, and Interactive Damage Rate Model will be pursued for life prediction under creep-fatigue loading with extended hold time. Accelerated, well-controlled creep-fatigue tests will be conducted to provide high-quality experimental data to refine key material parameters and validate models.

Li, Meimei↗

DOE OSTI2018

A New Approach for Short-Term Solar Radiation Forecasting Using the Estimation of Cloud Fraction and Cloud Albedo

Solar generation is an increasing part of the energy portfolio in the United States. An accurate forecast of the available solar resource and power is essential to managing the electric grid, market operations, and reducing the cost of solar energy. High-frequency forecasts of solar radiation in intra-hour horizons is important for real-time electric power system energy management, especially at the distribution level. Conventional Numerical Weather Prediction models perform poorly in intra-hour, high-frequency forecasts because of the limits on real-time computing, spatial resolution, and infrequent availability of observations. Although a number of alternative technologies, e.g., time-series analysis and machine learning, have been used to fill this gap, the smart persistence model is among the top-performing models in short-term forecasting and therefore often serves as the baseline to evaluate other forecasting models. Although the smart persistence model often serves as the baseline model in these intra-hour forecasts, obvious uncertainties exist in the current smart persistence model: (1) clear-sky index does not respond to the variation of the solar incident angle when cloud conditions are persistent within the forecast horizon, and (2) cloud coverage is inherently persistent though it is constrained by cloud advection. In this study, we developed a Physics-Based Smart Persistence Model for Intra-Hour Solar Forecasting (PSPI) that integrates cloudy property estimation, a radiative transfer model, and cloud fraction forecasts to improve the performance of the smart persistence model. Compared to the smart persistence model, PSPI does not require additional observations of various atmospheric parameters past global horizontal irradiance, but it is customizable because additional observations, if available, can be ingested to further improve the forecast. Our results show that the PSPI outperforms the persistence and smart persistence model on 5-minute, 15-minute, and 30-minute forecast horizons. The software package of PSPI is flexible to users' needs and provides low computational time to run at site-specific locations across the continental United States.

14 SOLAR ENERGY↗

NASA NTRS2009

Reaction Wheel Disturbance Model Extraction Software - RWDMES

The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral densities); converting PSDs to order analysis data; extracting harmonics; initializing and simultaneously tuning a harmonic model and a wheel structural model; initializing and tuning a broadband model; and verifying the harmonic/broadband/structural model against the measurement data. Functional operation is through a MATLAB GUI that loads test data, performs the various analyses, plots evaluation data for assessment and refinement of analysis parameters, and exports the data to documentation or downstream analysis code. The harmonic models are defined as specified functions of frequency, typically speed-squared. The reaction wheel structural model is realized as mass, damping, and stiffness matrices (typically from a finite element analysis package) with the addition of a gyroscopic forcing matrix. The broadband noise model is realized as a set of speed-dependent filters. The tuning of the combined model is performed using nonlinear least squares techniques. RWDMES is implemented as a MATLAB toolbox comprising the Fit Manager for performing the model extraction, Data Manager for managing input data and output models, the Gyro Manager for modifying wheel structural models, and the Harmonic Editor for evaluating and tuning harmonic models. This software was validated using data from Goodrich E wheels, and from GSFC Lunar Reconnaissance Orbiter (LRO) wheels. The validation testing proved that RWDMES has the capability to extract accurate disturbance models from flight reaction wheels with minimal user effort.

Blaurock, Carl↗

DOE OSTI2018

Development of Ultra-Fine Multigroup Cross Section Library of the AMPX/SCALE Code Packages

The Consortium for Advanced Simulation of Light Water Reactors Virtual Environment for Reactor Applications (VERA) neutronic simulator MPACT is being developed by Oak Ridge National Laboratory and the University of Michigan for various reactor applications. The MPACT and simplified MPACT 51- and 252-group cross section libraries have been developed for the MPACT neutron transport calculations by using the AMPX and Standardized Computer Analyses for Licensing Evaluations (SCALE) code packages developed at Oak Ridge National Laboratory. It has been noted that the conventional AMPX/SCALE procedure has limited applications for fast-spectrum systems such as boiling water reactor (BWR) fuels with very high void fractions and fast reactor fuels because of its poor accuracy in unresolved and fast energy regions. This lack of accuracy can introduce additional error sources to MPACT calculations, which is already limited by the Bondarenko approach for resolved resonance self-shielding calculation. To enhance the prediction accuracy of MPACT for fast-spectrum reactor analyses, the accuracy of the AMPX/SCALE code packages should be improved first. The purpose of this study is to identify the major problems of the AMPX/SCALE procedure in generating fast-spectrum cross sections and to devise ways to improve the accuracy. For this, various benchmark problems including a typical pressurized water reactor fuel, BWR fuels with various void fractions, and several fast reactor fuels were analyzed using the AMPX 252-group libraries. Isotopic reaction rates were determined by SCALE multigroup (MG) calculations and compared with continuous energy (CE) Monte Carlo calculation results. This reaction rate analysis revealed three main contributors to the observed differences in reactivity and reaction rates: (1) the limitation of the Bondarenko approach in coarse energy group structure, (2) the normalization issue of probability tables, and (3) neglect of the self-shielding effect of resonance-like cross sections at high energy range such as (n,p) cross section of Cl35. The first error source can be eliminated by an ultra-fine group (UFG) structure in which the broad scattering resonances of intermediate-weight nuclides can be represented accurately by a piecewise constant function. A UFG AMPX library was generated with modified probability tables and tested against various benchmark problems. The reactivity and reaction rates determined with the new UFG AMPX library agreed very well with respect to Monte Carlo Neutral Particle (MCNP) results. To enhance the lattice calculation accuracy without significantly increasing the computational time, performing the UFG lattice calculation in two steps was proposed. In the first step, a UFG slowing-down calculation is performed for the corresponding homogenized composition, and UFG cross sections are collapsed into an intermediate group structure. In the second step, the lattice calculation is performed for the intermediate group level using the condensed group cross sections. A preliminary test showed that the condensed library reproduces the results obtained with the UFG cross section library. This result suggests that the proposed two-step lattice calculation approach is a promising option to enhance the applicability of the AMPX/SCALE system to fast system analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2011

Crowdsourcing for Challenging Technical Problems - It Works!

The NASA Johnson Space Center Space Life Sciences Directorate (SLSD) and Wyle Integrated Science and Engineering (Wyle) will conduct a one-day business cluster at the 62nd IAC so that IAC attendees will understand the benefits of open innovation (crowdsourcing), review successful results of conducting technical challenges in various open innovation projects, and learn how an organization can effectively deploy these new problem solving tools to innovate more efficiently and effectively. Results from both the SLSD open innovation pilot program and the open innovation workshop conducted by the NASA Human Health and Performance Center will be discussed. NHHPC members will be recruited to participate in the business cluster (see membership http://nhhpc.nasa.gov) and as IAF members. Crowdsourcing may be defined as the act of outsourcing tasks that are traditionally performed by an employee or contractor to an undefined, generally large group of people or community (a crowd) in the form of an open call. The open call may be issued by the organization wishing to find a solution to a particular problem or complete a task, or by an open innovation service provider on behalf of that organization. In 2008, the SLSD, with the support of Wyle, established and implemented pilot projects in open innovation (crowdsourcing) to determine if these new internet-based platforms could indeed find solutions to difficult technical challenges. These unsolved technical problems were converted to problem statements, called Challenges by some open innovation service providers, and were then posted externally to seek solutions to these problems. In addition, an open call was issued internally to NASA employees Agency wide (11 Field Centers and NASA HQ) using an open innovation service provider crowdsourcing platform to post NASA challenges from each Center for the others to propose solutions). From 2008 to 2010, the SLSD issued 34 challenges, 14 externally and 20 internally. The 14 external problems or challenges were posted through three different vendors: InnoCentive, yet2.com and TopCoder. The 20 internal challenges were conducted using the InnoCentive crowdsourcing platform designed for use internal to an organization and customized for NASA use, and promoted as NASA@Work. The results were significant. Of the seven InnoCentive external challenges, two full and five partial awards were made in complex technical areas such as predicting solar flares and long-duration food packaging.

Davis, Jeffrey R.↗

NASA NTRS2012

Evaluating the Contribution of NASA Remotely-Sensed Data Sets on a Convection-Allowing Forecast Model

The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer will be presented to assess the potential added-value of the SPoRT datasets and data assimilation methodology compared to a WRF configuration without the unique datasets and data assimilation.

Zavodsky, Bradley T.↗