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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Recent Advances in Analytical Electron Microscopy for Irradiated Materials

Analytical electron microscopy (AEM) in the scanning transmission electron microscope (STEM) has long been a staple of post-irradiation examination (PIE) and materials development campaigns. Recently, new advances in both STEM hardware and post-processing data-analysis software, along with ancillary advances such as in focused ion beam (FIB) sample preparation, has led to exciting advances in the quantity and quality of data that can be obtained. This talk will summarize recent experiments performed at Oak Ridge National Laboratory (ORNL), especially work on neutron-irradiated materials and fuels taking advantage of a newly-installed latest-generation AEM tool in the ORNL irradiated materials laboratories. ORNL installed a new FEI Talos F200X microscope, a 200 keV, high-brightness Schottky emission AEM system optimized for high-speed, high-efficiency X-ray mapping experiments. The F200X features the FEI 'SuperX' four-sector silicon drift detector (SDD) X-ray detector, which provides 0.9 sr solid angle of collection. By combining the high-brightness electron source, latest-generation electron optics, and fast computers and pulse processors, X-ray mapping speed is increased by a factor of 50-100 x compared to the previous-generation instruments. In addition to improvements in hardware, data mining via multivariate statistical analysis (MVSA) allows for maximum insight to the data obtained from the new hardware. MVSA data mining of the X-ray maps allows, for instance, unbiased computational identification of the phases present, and discovery of small phases or precipitates not expected by the human analyst. This talk will present examples of experiments performed using the most modern AEM tools and software. Silicon carbide is a major candidate for next-generation nuclear applications. Nano-infiltration by transient eutectic (NITE) SiC requires low sintering temperatures. X-ray mapping of the NITE structure find pockets of different oxides, such as Zr-Y-oxide, Y-Al-oxide, and yttria. MVSA data mining finds the regions where different oxides are present and indicates that Y additions preferentially wet grain boundaries, where Zr additions are preferentially concentrated at grain triple points. SiC coatings from AGR-I experiment TRISO particles were found to contain significant quantities of fission products (e.g., Pd) as well as actinides (U, Pu). MVSA data mining found complex precipitates and grain boundary films of the fission products and actinides deep (∼several microns) into the SiC layer. Advanced AEM methods, combined with MVSA data mining, makes possible both rapid and detailed PIE. Ferritic alloys, such as accident-tolerant FeCrAl grades, benefit greatly from advanced AEM examination. Neutron-irradiated FeCrAl precipitates the detrimental Cr-rich α' phase. Because the SuperX SDD system has four detectors, it is possible to obtain high X-ray count rates even on a highly tilted specimen, as might be needed to obtain STEM images of dislocation loops. Results on neutron-irradiated FeCrAl indicates that α' size and number density can be obtained by AEM, and MVSA results determine that minor elements (such as Si) has complex radiation-induced segregation behavior at grain boundaries. We have also developed and validated computer models of the AEM experiment, allowing different microstructures' X-ray map results to be simulated for different STEM instruments. This allows X-ray mapping to be more quantitative, such as by estimating what size nanoclusters in an oxide-dispersion strengthened steel would be visible or invisible in STEM. In summary, new advanced AEM technology provides a major leap forward in experiments possible in PIE of irradiated materials. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermal Modeling of Advanced Test Reactor Fuel in a Generalized Dry Storage System Under Hypothetical Accident Conditions

Work was performed to investigate the thermal behavior of a sealed aluminum-clad spent nuclear fuel (ASNF) dry storage configuration under hypothetical accident conditions during long-term storage. The considered system consists of a concrete dry storage overpack; a welded over canister, backfilled with argon; and nine Department of Energy (DOE) standardized canisters (DOESCs) loaded with ASNF, backfilled with helium gas. One technical concern associated with the long-term storage of ASNF includes radiolytic hydrogen generation. The yield of large quantities of hydrogen could lead to DOESC over pressurization or a flammable internal atmosphere. While flammability concerns can be resolved by preventing the ingress of oxygen, the canister pressure is partially controlled by the atmosphere temperature. This memorandum summarizes the results of modeling and simulation (M&S) work completed with Star CCM+ (a computational fluid dynamics [CFD] software) considering the thermal effects of a fully engulfing flame and another scenario with the vent ports of the concrete dry storage overpack completely blocked. The goal was to determine the bounding maximum temperature of the DOESC internal atmosphere to evaluate a worst-case pressure scenario, as well as the critical vent port blockage durations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗
DOE OSTI2020

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Overview of New Tools to Perform Safety Analysis: BWR Station Black Out Test Case

Dynamic Probabilistic Risk Assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP, MELCOR) with simulation controller codes (e.g., RAVEN, ADAPT). While system simulator codes accurately model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic, operating procedures) and stochastic (e.g., component failures, parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by: 1) sampling values of a set of parameters from the uncertainty space of interest (using the simulation controller codes), and 2) simulating the system behavior for that specific set of parameter values (using the system simulator codes). For complex systems, one of the major challenges in using DPRA methodologies is to analyze the large amount of information (i.e., large number of scenarios ) generated, where clustering techniques are typically employed to allow users to better organize and interpret the data. In this paper, we focus on the analysis of a nuclear simulation dataset that is part of the Risk Informed Safety Margin Characterization (RISMC) Boiling Water Reactor (BWR) station blackout (SBO) case study. We apply a software tool that provides the domain experts with an interactive analysis and visualization environment for understanding the structures of such high-dimensional nuclear simulation datasets. Our tool encodes traditional and topology-based clustering techniques, where the latter partitions the data points into clusters based on their uniform gradient flow behavior. We demonstrate through our case study that both types of clustering techniques complement each other in bringing enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Constraint, Intelligence, and Control Hierarchy in Virtual Environments

This paper seeks to deal directly with the question of what makes virtual actors and objects that are experienced in virtual environments seem real. (The term virtual reality, while more common in public usage, is an oxymoron; therefore virtual environment is the preferred term in this paper). Reality is difficult topic, treated for centuries in those sub-fields of philosophy called ontology- "of or relating to being or existence" and epistemology- "the study of the method and grounds of knowledge, especially with reference to its limits and validity" (both from Webster s, 1965). Advances in recent decades in the technologies of computers, sensors and graphics software have permitted human users to feel present or experience immersion in computer-generated virtual environments. This has motivated a keen interest in probing this phenomenon of presence and immersion not only philosophically but also psychologically and physiologically in terms of the parameters of the senses and sensory stimulation that correlate with the experience (Ellis, 1991). The pages of the journal Presence: Teleoperators and Virtual Environments have seen much discussion of what makes virtual environments seem real (see, e.g., Slater, 1999; Slater et al. 1994; Sheridan, 1992, 2000). Stephen Ellis, when organizing the meeting that motivated this paper, suggested to invited authors that "We may adopt as an organizing principle for the meeting that the genesis of apparently intelligent interaction arises from an upwelling of constraints determined by a hierarchy of lower levels of behavioral interaction. "My first reaction was "huh?" and my second was "yeah, that seems to make sense." Accordingly the paper seeks to explain from the author s viewpoint, why Ellis s hypothesis makes sense. What is the connection of "presence" or "immersion" of an observer in a virtual environment, to "constraints" and what types of constraints. What of "intelligent interaction," and is it the intelligence of the observer or the intelligence of the environment (whatever the latter may mean) that is salient? And finally, what might be relevant about "upwelling" of constraints as determined by a hierarchy of levels of interaction?

Sheridan, Thomas B.↗
DOE OSTI2019

DXT: Darshan eXtended Tracing

As modern supercomputers evolve to exascale, their I/O subsystems are becoming increasingly complex, making optimization of I/O for scientific applications a daunting task. Although I/O profiling tools facilitate the process of optimizing application I/O performance, legacy profiling tools lack flexibility in their level of detail and ability to correlate traces with other sources of data. Additionally, a lack of robust trace analysis tools makes it difficult to derive actionable insights from large-scale I/O traces. Darshan is an HPC I/O characterization tool that records statistics in a lightweight manner that makes it appropriate for full-time production deployment. However, Darshan’s default characterization mechanism records information at a fixed granularity. We augment Darshan by proposing Darshan eXtended Tracing (DXT) for more detailed profiling of I/O software stacks. DXT enables users and administrators to vary the level of fidelity captured by Darshan at run time without modifying or recompiling applications. This capability facilitates systematic analysis on the I/O behavior of applications and can provide useful application kernel I/O traces to help advance parallel I/O research. We have demonstrated the power of DXT by obtaining a wide range of useful statistics for multiple case studies, and we further show that DXT is able to do so same with negligible overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Studying performance portability of LAMMPS across diverse GPU-based platforms

The molecular dynamics simulation software, LAMMPS, utilizes the Kokkos acceleration library to port computation to a diverse set of architectures including those based on GPU accelerators. In addition to Kokkos, LAMMPS contains a vast code base that leverages the CUDA application programming interface using library functions such as cuFFT, CUDA's fast-fourier transform (FFT) library, and, more recently, also support for AMD's Heterogeneous Interface for Portability (HIP) that is rapidly growing. While preparing LAMMPS tests for the AMD GPU-based test system precursors to Frontier, we investigated several strategies for accelerating LAMMPS on AMD GPUs, using the AMD Instinct MI100 and MI250X. In this work, we integrated the HIP FFT library, hipFFT, into the particle-particle particle-mesh (PPPM) long-range solver, which allowed the porting of PPPM calculations to the GPUs. Kokkos behavior on the MI100 and MI250X was also investigated through the package kokkos command of LAMMPS, targeting communication, memory usage, and particle grid decomposition. The Tersoff, Reax, Lennard-Jones (LJ), EAM, Granular, and PPPM potentials were investigated in this effort, and results from these experiments are provided. In conclusion, the selected potentials were run on Spock (AMD Instinct MI100), Crusher (AMD Instinct MI250X), AFW HPC11 (NVIDIA A100) and Summit (NVIDIA V100), for comparison. Operational roofline models were constructed and analyzed for the Tersoff, Reax, and Lennard–Jones potentials on Crusher and Summit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Studying Performance Portability of LAMMPS across Diverse GPU-based Platforms

The molecular dynamics simulation software, LAMMPS, utilizes the Kokkos acceleration library to port computation to a diverse set of architectures including those based on GPU accelerators. In addition to Kokkos, LAMMPS contains a vast code base that leverages the CUDA application programming interface using library functions such as cuFFT, CUDA’s fast-fourier transform (FFT) library, and, more recently, also support for AMD’s Heterogeneous Interface for Portability (HIP) that is rapidly growing. While preparing LAMMPS tests for the AMD GPU-based test system precursors to Frontier, we investigated several strategies for accelerating LAMMPS on AMD GPUs, using the AMD Instinct MI100 and MI250X. In this work, we integrated the HIP FFT library, hipFFT, into the particle-particle particle-mesh (PPPM) long-range solver, which allowed the porting of PPPM calculations to the GPUs. Kokkos behavior on the MI100 and MI250X was also investigated through the package kokkos command of LAMMPS, targeting com- munication, memory usage, and particle grid decomposition. The Tersoff, Reax, Lennard-Jones (LJ), EAM, Granular, and PPPM potentials were investigated in this effort, and results from these experiments are provided. The selected potentials were run on Spock (AMD Instinct MI100), Crusher (AMD Instinct MI250X), AFW HPC11 (NVIDIA A100) and Summit (NVIDIA V100), for comparison. Operational roofline models were constructed and analyzed for the Tersoff, Reax, and Lennard-Jones potentials on Crusher and Summit.

Hagerty, Nick↗
NASA NTRS2016

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Trevino, Luis↗
NASA NTRS1998

Improved instrumental magnitude prediction expected from version 2 of the NASA SKY2000 master star catalog

The SKY2000 Master Star Catalog (MC), Version 2 and its predecessors have been designed to provide the basic astronomical input data needed for satellite acquisition and attitude determination on NASA spacecraft. Stellar positions and proper motions are the primary MC data required for operations support followed closely by the stellar brightness observed in various standard astronomical passbands. The instrumental red-magnitude prediction subsystem (REDMAG) in the MMSCAT software package computes the expected instrumental color index (CI) [sensor color correction] from an observed astronomical stellar magnitude in the MC and the characteristics of the stellar spectrum, astronomical passband, and sensor sensitivity curve. The computation is more error prone the greater the mismatch of the sensor sensitivity curve characteristics and those of the observed astronomical passbands. This paper presents the preliminary performance analysis of a typical red-sensitive CCDST during acquisition of sensor data from the two Ball CT-601 ST's onboard the Rossi X-Ray Timing Explorer (RXTE). A comparison is made of relative star positions measured in the ST FOV coordinate system with the expected results computed from the recently released Tycho Catalogue. The comparison is repeated for a group of observed stars with nearby, bright neighbors in order to determine the tracker behavior in the presence of an interfering, near neighbor (NN). The results of this analysis will be used to help define a new photoelectric photometric instrumental sensor magnitude system (S) that is based on several thousand bright star magnitudes observed with the PXTE ST's. This new system will be implemented in Version 2 of the SKY2000 MC to provide improved predicted magnitudes in the mission run catalogs.

Sande, C. B.↗
DOE OSTI2012

Building Agent™ Software (BA) [SWRs 12-05 and 17-21]

Energy interfaces provide a new level of motivational information. Many studies have reported energy savings after dashboards for operators are installed, but these provide little actionable information to the occupant and the occupant cannot report individual comfort. The Building Agent™ (BA), in development at the National Renewable Energy Laboratory (NREL), provides an interface for the occupant to converse with the building control system and aims to actively engage and affect occupant behavior to achieve positive energy outcomes. Energy savings achieved via occupant behavioral changes could be as high as 25%, and could rival savings achieved by technological measures. For example, energy audits often show that more than 50% of the energy used in a building is consumed at night. Occupants leaving equipment and lighting on after they leave work is a large contributing factor. Similar savings opportunities have been identified when occupants were away from their desks 50% of the time, while most of their computers, lights, and other equipment remained powered on. Building Agent aims to create cohesion between building automation system (BAS) data, local measurements, and occupant feedback to provide visualizations, empowering occupants and building engineers to take diagnostic, proactive, energy-saving, and comfort-improving actions. The multilayer BA architecture consists of central server, measurement, and distributed application layers. The server layer aggregates global and localized measurements with occupant feedback to correlate perceived comfort with actual data throughout the building. The measurement layer complements BAS data with localized, environmental condition measurements at workstations. The application layer provides a bidirectional communications mechanism between the building and the occupants that accepts comfort feedback and provides energy performance information. The interface layer also uses three displays to influence building energy use: empathetic and personalized gauges, graphical data, and competitive rankings. Building Agent was implemented at NREL in the Research Support Facility (RSF), a LEED Platinum and Net Zero office building, which has received many awards. The constant feedback from occupants has enabled BA to better enhance the BAS data controls. Continued work is being done on BA to increase visualization of data and enhanced the user experience.

Long, Nicholas↗
DOE OSTI2018

HyRAM V1.1 User Guide

Hydrogen Risk Assessment Models (HyRAM) is a software toolkit that provides a basis for quantitative risk assessment and consequence modeling for hydrogen infrastructure and transportation systems. HyRAM integrates validated, analytical models of hydrogen behavior, statistics, and a standardized QRA approach to generate useful, repeatable data for the safety analysis of various hydrogen systems. HyRAM is a software developed by Sandia National Laboratories for the U.S. Department of Energy. This document demonstrates how to use HyRAM to recreate a hydrogen system and obtain relevant data regarding potential risk. Specific examples are utilized throughout this document, providing detailed tutorials of HyRAM features with respect to hydrogen system safety analysis and risk assessment.

08 HYDROGEN↗
DOE OSTI2019

Quantifying Uncertainty in Emulations (LDRD Report)

This report summarizes the work performed under the project “Quantifying Uncertainty in Emulations.” Emulation can be used to model real-world systems, typically using virtualization to run the real software on virtualized hardware. Emulations are increasingly used to answer mission-oriented questions, but how well they represent the real-world systems is still an open area of research. The goal of the project was to quantify where and how emulations differ from the real world. To do so, we ran a representative workload on both, and collected and compared metrics to identify differences. We aimed to capture behaviors, rather than performance, differences as the latter is more well-understood in the literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Algorithm and program for precise determination of unit-cell parameters of single crystal taking into account the sample eccentricity

A technique has been developed to refine the unit-cell parameters of single crystals with minimization of the influence of instrumental errors on the result. The corresponding computational procedure HuberUB is added to the software package of Huber-5042 diffractometer with a point detector and closedcycle helium cryostat Displex DE-202. The parameters of unit cell, its orientation, the goniometer zero angles, the sample eccentricity, the distances in the goniometer, and the radiation wavelength were refined by the nonlinear least-squares method, which allows imposition of constraints on the unit-cell parameters, depending on the crystal symmetry. The technique is approved on a LuB{sub 12} single crystal. The unit-cell parameters are determined in a temperature range of 20–295 K, with an absolute error not larger than 0.0004 Å (the relative error is of ~5 × 10{sup –5}). The estimates of the unit-cell parameters obtained by the proposed method are evidenced to be unbiased. Some specific features of the behavior of parameters in the ranges of 120–140 and 20–50 K are revealed, which correlate with the anomalies of the physical properties of the crystal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Causal network inference using biochemical kinetics

Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. Results: We present a general framework for network inference and dynamical prediction using time course data that is rooted in nonlinear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown. Availability and implementation: MATLAB R2014a software is available to download from warwick.ac.uk/chrisoates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Advanced Laboratory and Field Arrays: Technical Report for Performance Enhancement for Marine Energy Converter (MEC) Arrays (Task 5)

Task 5 consisted of two parts, wave energy converter (WEC) arrays and current energy converter (CEC) arrays. The two parts of the project were executed independently, and this report covers only the work on WECs. In this part of the task, the team characterized the behavior of and developed control schemes for wave energy converter (WEC) arrays that improved performance (i.e., maximized aggregate power generation and reduced the levelized cost of energy) over baseline, non-coordinated control approaches. Specifically, for WEC arrays: the team developed optimal layouts of arrays that considered the effect of WEC placement within an array on coordinated array control with real-time estimation schemes. The numerical codes developed through this task were made available to users for array design. These tools utilized existing commercial software as well as software developed within the project team.

13 HYDRO ENERGY↗
DOE OSTI2024

COMPUTER-AIDED LATTICE DESIGN AND ADVANCED MODELING FOR THE DEVELOPMENT OF LIGHTWEIGHT STRUCTURAL MATERIALS

The notion of a “fission battery” conveys a vision focused on realizing very simple “plug-and-play” nuclear systems that can be integrated into a variety of applications requiring affordable, reliable energy in the form of electricity and/or heat and function without operations and maintenance staff. Fission batteries require lightweight structural materials to increase their mobility, and the lightweight materials must demonstrate structural resilience under various conditions. The objective of this work is to develop lattice structured lightweight structural material featuring a good combination of mechanical properties using advanced modeling and simulation together with an advanced additive manufacturing technique such as laser powder bed fusion. The preliminary results show that different lattice structures and types can be successfully meshed using nTopology software, and the lattice structure data can be successfully transformed to Multiphysics Object-Oriented Simulation (MOOSE) Environment input. Finite Element Analysis (FEA) displays that, at macro/engineering scale simulation, the weight saving design has an obvious effect on tensile behavior such as effective elastic modulus and yield stress. The novel approaches of this work are (1) development of lattice structures for improved mechanical properties using advanced simulation and modeling techniques; and (2) model predictions of the mechanical properties (e.g., strength and stress distribution) of macroscopic materials in order to preliminarily select a lattice structure for additive manufacturing.

36 MATERIALS SCIENCE↗