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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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DOE OSTI2015

Fuel Thermo-physical Characterization Project. Fiscal Year 2014 Final Report

The Office of Material Management and Minimization (M3) Reactor Conversion Fuel Thermo-Physical Characterization Project at Pacific Northwest National Laboratory (PNNL) was tasked with using PNNL facilities and processes to receive irradiated low enriched uranium–molybdenum (LEU-Mo) fuel plate samples and perform analysis in support of the M3 Reactor Conversion Program. This work is in support of the M3 Reactor Conversion Fuel Development Pillar that is managed by Idaho National Laboratory. The primary research scope was to determine the thermo-physical properties as a function of temperature and burnup. Work conducted in Fiscal Year (FY) 2014 complemented measurements performed in FY 2013 on four additional irradiated LEU-Mo fuel plate samples. Specifically, the work in FY 2014 investigated the influence of different processing methods on thermal property behavior, the absence of aluminum alloy cladding on thermal property behavior for additional model validation, and the influence of higher operating surface heat flux / more aggressive irradiation conditions on thermal property behavior. The model developed in FY 2013 and refined in FY 2014 to extract thermal properties of the U-Mo alloy from the measurements conducted on an integral fuel plate sample (i.e., U-Mo alloy with a thin Zr coating and clad in AA6061) continues to perform very well. Measurements conducted in FY 2014 on samples irradiated under similar conditions compare well to measurements performed in FY 2013. In general, there is no gross influence of fabrication method on thermal property behavior, although the difference in LEU-Mo foil microstructure does have a noticeable influence on recrystallization of grains during irradiation. Samples irradiated under more aggressive irradiation conditions, e.g., higher surface heat flux, revealed lower thermal conductivity when compared to samples irradiated at moderate surface heat fluxes, with the exception of one sample. This report documents thermal property measurements conducted in FY 2014 and compares results to values obtained from literature and measurements performed in FY 2013, where applicable, along with appropriate discussion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Aluminum Spent Fuel Performance in Dry Storage Task 4 Aluminum Oxide Sampling of ATR Dry Stored Fuel

Milestone report on sampling of long-term dry-stored ATR spent fuel elements. It describes tooling, sample acquisition methods and analysis of the aluminum oxide samples by scanning electron microscopy, thermogravimetric analysis, X-ray diffraction and transmission electron microscopy. The observations provide input to projections on controls necessary for maintaining the integrity of the fuel during extended interim storage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Real-Time Optimization Workflow Status Update

Economically optimal and safe operation of integrated energy systems (IES) requires optimization at many different time scales. A real-time optimization (RTO) workflow will attempt to maximize revenue and minimize operational costs on a time scale of minutes to hours. Such a workflow requires the use of a digital twin (DT), which is a virtual representation of a physical system. The DT is updated using real-time data from the physical system, and serves as a model in an optimization framework. The optimization results are then sent back to the physical system to complete the loop. This report details the progress made in developing building blocks for a DT/RTO framework. The Risk Analysis Virtual Environment (RAVEN) platform within the Framework for Optimization of Resources and Economics (FORCE) tool suite can perform many of the tasks required for building a DT and performing RTO. The first item of this report details RAVEN enhancements that enable RAVEN workflows to be run in various environments. Data communication between the physical system and its DT is essential for successful RTO. This includes preprocessing real-time data, loading data into a data warehouse, and querying the stored data. The second section of this report describes the progress made in implementing an adapter in Python in order for Deep Lynx to handle the data communication. Typical dispatch optimization frameworks are built on linear programming (LP). The prototype RTO workflow developed in this report uses an LP problem as a part of a receding-horizon- or economic model predictive control (EMPC) based optimization. The third section of this report details the framework of an RTO workflow in which the system consists of a simple electrical storage device. A DT can be built from a reduced-order model (ROM). Integrating a ROM into a typical LP optimization framework has been challenging because most optimization packages require the user to write algebraic expressions for the system model. The final section of this report shows how an externally built RAVEN ROM can be integrated in an RTO framework by using the Python package Pyomo. This demonstrates the RTO workflow capability from a software-only perspective and is an important step in demonstrating the capability to implement an RTO workflow for a physical system.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1967

A code transformation task that provides performance measures of nonverbal mediation /COTRAN/

Code transformation task for measuring performance of nonverbal mediation

HUMAN PERFORMANCE↗

NASA NTRS1991

An analysis of Space Shuttle countdown activities: Preliminaries to a computational model of the NASA Test Director

Before all systems are go just prior to the launch of a space shuttle, thousands of operations and tests have been performed to ensure that all shuttle and support subsystems are operational and ready for launch. These steps, which range from activating the orbiter's flight computers to removing the launch pad from the itinerary of the NASA tour buses, are carried out by launch team members at various locations and with highly specialized fields of expertise. The liability for coordinating these diverse activities rests with the NASA Test Director (NTD) at NASA-Kennedy. The behavior is being studied of the NTD with the goal of building a detailed computational model of that behavior; the results of that analysis to date are given. The NTD's performance is described in detail, as a team member who must coordinate a complex task through efficient audio communication, as well as an individual taking notes and consulting manuals. A model of the routine cognitive skill used by the NTD to follow the launch countdown procedure manual was implemented using the Soar cognitive architecture. Several examples are given of how such a model could aid in evaluating proposed computer support systems.

John, Bonnie E.↗

NASA NTRS1990

Flexibility effects on the control system performance of large scale robotic manipulators

Structural flexibility of robotic manipulators becomes significant and limits the performance of a control system when manipulators are large structures, manipulating on large payloads, and/or operating at high speeds. The question of when a manipulator can be considered rigid or must be considered flexible is studied as a function of manipulator dynamics and task characteristics. Results are interpreted in simple quantitative forms which can be used as design and analysis tools to decide whether or not the manipulator flexibility will be a significant factor for a given task condition. The limitations imposed by the manipulator flexibility on the joint variable feedback control system performance is determined using linear and nonlinear methods. The closed loop eigenstructure behavior of finite dimensional models under joint variable feedback is studied and results are compared with the previously reported results.

Cetinkunt, Sabri↗

NASA NTRS1972

Technical, analytical and computer support

The development of a rigorous mathematical model for the design and performance analysis of cylindrical silicon-germanium thermoelectric generators is reported that consists of two parts, a steady-state (static) and a transient (dynamic) part. The material study task involves the definition and implementation of a material study that aims to experimentally characterize the long term behavior of the thermoelectric properties of silicon-germanium alloys as a function of temperature. Analytical and experimental efforts are aimed at the determination of the sublimation characteristics of silicon germanium alloys and the study of sublimation effects on RTG performance. Studies are also performed on a variety of specific topics on thermoelectric energy conversion.

Source record↗

NASA NTRS1993

Intelligent assistance in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and run time estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks.

Chien, Steve↗

NASA NTRS1990

Vehicle processing operations database

The Vehicle Processing Operations Data base (VPOD) has been designed and constructed to enable the collection and preliminary analysis of data relative to the processing of planetary exploration vehicles in low Earth orbit. VPOD has the capability to hierarchically store the events, assemblies, and equipment data needed for performing vehicle processing analysis, to whatever level of detail available. This permits some analysis to be performed even during the very early phases of vehicle and mission design. As more data about the events, assemblies, or equipment become available, the analysis can then be refined using the increased level of detail. VPOD output is based on a mission defined by selecting from the VPOD Events data base the events that are required to perform the desired tasks. The outputs available include total crew time, crew skill requirements, equipment needed, assemblies worked per event, to any available level of detail. The VPOD design is structured to interface with an operations simulation capability which is currently in the requirements definition phase. The simulator will use information from the VPOD to perform operations analysis for missions being conducted in low Earth orbit. VPOD information, along with information from the science missions operations data base and a Space Station configuration data base, will be used by the simulator to provide a capability to study total system operations and resources requirements.

Ganoe, George G.↗

DOE OSTI2014

ACTINIDE REMOVAL PROCESS SAMPLE ANALYSIS, CHEMICAL MODELING, AND FILTRATION EVALUATION

Filtration within the Actinide Removal Process (ARP) currently limits the throughput in interim salt processing at the Savannah River Site. In this process, batches of salt solution with Monosodium Titanate (MST) sorbent are concentrated by crossflow filtration. The filtrate is subsequently processed to remove cesium in the Modular Caustic Side Solvent Extraction Unit (MCU) followed by disposal in saltstone grout. The concentrated MST slurry is washed and sent to the Defense Waste Processing Facility (DWPF) for vitrification. During recent ARP processing, there has been a degradation of filter performance manifested as the inability to maintain high filtrate flux throughout a multi-batch cycle. The objectives of this effort were to characterize the feed streams, to determine if solids (in addition to MST) are precipitating and causing the degraded performance of the filters, and to assess the particle size and rheological data to address potential filtration impacts. Equilibrium modelling with OLI Analyzer{sup TM} and OLI ESP{sup TM} was performed to determine chemical components at risk of precipitation and to simulate the ARP process. The performance of ARP filtration was evaluated to review potential causes of the observed filter behavior. Task activities for this study included extensive physical and chemical analysis of samples from the Late Wash Pump Tank (LWPT) and the Late Wash Hold Tank (LWHT) within ARP as well as samples of the tank farm feed from Tank 49H. The samples from the LWPT and LWHT were obtained from several stages of processing of Salt Batch 6D, Cycle 6, Batch 16.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2004

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Jost, Gabriele↗

DOE OSTI2017

Determination of a Generic Human Error Probability Distribution, Part 1: A Dynamic Formulation of SPAR-H

In almost all major nuclear power plants (NPP) events include a significant human error component. As an example, in Fukushima Daiichi (2011) nuclear meltdown, the human actions related to the high-pressure injection cooling strongly affected accident evolution. Furthermore, in the Three Mile Island accident (1979) (which was initiated by a stuck open valve and thus was triggered a loss of coolant accident) the unit operators made decisions based upon false assumptions that contributed negatively to the accident. Given these premises, the ability to accurately model human interactions with plant evolution and, in particular, dynamically calculate human error probability (HEP) plays a major role in a probabilistic risk analysis (PRA). Human reliability analysis (HRA) identifies and models the causes of human errors, and quantifies HEP by applying different methodologies. HRA methods identify errors and reflect on the understanding of error-prone people and systems. There are a number of HRA methods available that assist in identifying the vulnerabilities in the system and provide guidance in determining the HEP. HEP is the probability of a human failure event (HFE), and quantification of HEPs under various situations is utilized in PRA of large complex systems. One of the more prominent HRA methods is the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method that was developed to estimate HEPs for the use in the Standardized Plant Analysis Risk (SPAR) PRA models employed in U.S. NPPs. SPAR-H is implemented in U.S. NPPs by regulators at the U.S. Nuclear Regulatory Commission (NRC) to determine the HEP based on expert estimation through the use of calculation worksheets. In SPAR-H, the nominal HEPs (NHEPs) are multiplied by performance shaping factors (PSF) multiplier values to obtain the overall error probability. PSFs encompass the human components, individual characteristics, their environment, and aspects of the task. With PSFs, the goal is to capture all factors that can affect human performance. In SPAR-H there are eight PSFs used, each having respective levels corresponding to multipliers: Available Time, Stress/Stressors, Complexity, Experience/Training, Procedures, Ergonomics/Human Machine Interface, Fitness for Duty, and Work Processes. The PSF multipliers indicate enhanced, nominal, or degraded human performance. The SPAR-H method estimates the HEP through multiplying a NHEP with PSFs. Hence, SPAR-H is a traditional HRA method that assesses human performance at a fixed, or static, point in time. In a dynamic HRA framework, human performance is assessed on a continuous time basis. SPAR-H can be used within a dynamic PRA framework through the use of simulation and stochastic models. The goal of dynamic HRA is to build a more realistic model of the human-system interaction to enhance calculation of reliability, risk and safety analysis. The progression of events in dynamic SPAR-H considers that some PSFs may experience gradual change, while other change can be sudden due to individualistic differences or rapid plant status changes. The PSF changes are caused by contextual changes in the scenario. For example, as more time passes, the realization that a task should be completed sooner may cause the operator more stress. In another example, a sudden relay of information about sickness of a family member may alter the operator's general stress level and fitness for duty. Each PSF has a different dynamic nature; PSFs like stress and complexity change more quickly over the course of a task than experience and training. While the experience of an operator changes over the course of attaining the objective, the amount that this added experience changes the HEP is very minimal. In contrast, the stress, complexity, and procedures PSFs may change quite a bit over the course of task completion.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗

DOE OSTI2023

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Assessing the Relationships Between Sensorimotor Biomarkers and Post-Landing Functional Task Performance

Spaceflight drives adaptive changes in healthy individuals appropriate for sensorimotor function in a microgravity environment. These changes are maladaptive for return to earth's gravity. The inter-individual variability of sensorimotor decrements is striking, although poorly understood. The goal of this study is to identify a set of behavioral, neuroimaging and genetic measures that can be used to predict early post-flight performance on a set of sensorimotor tasks. Astronauts are recruited who previously participated in sensorimotor field tests and/or posturography soon after long-duration spaceflight. Behavioral tests include assessments of sensory dependency and adaptability. Visual dependency involves treadmill walking while viewing a moving virtual visual scene. Vestibular thresholds are measured while seated during lateral translations. Proprioception dependency is measured during one-legged stance on a horizontal air-bearing surface. Ground assessment of adaptability is performed (1) during treadmill walking with a virtual linear hallway and a moving walking surface, and (2) during multiple trials of navigating an obstacle course while wearing reversing prisms. The neuroimaging tests will characterize individual differences in regional brain volumes (using Structural MRI) and white matter microstructure (using Diffusion Tensor Imaging) to serve as potential predictors of adaptive capacity. The genetic tests will utilize saliva samples to examine variations in four genes chosen because of their ability to differentiate sensorimotor adaptation ability in a normative population, including Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Brain-derived neurotrophic factor (BDNF) and the α2-adrenergic receptor. Twenty-one ISS crewmembers have been tested to date, including 6 from this past year after testing resumed post-COVID. This cohort includes 9 first-time fliers, 4F, and mission durations lasting 182 ± 32 days, mean ± std. We are utilizing a combination of three post-flight functional task outcomes: tandem walk, recovery from fall and dynamic posturography. There is considerable variability among the post-flight performance outcomes for the 21 participants to date. Based on a partial sample using an ordinal scale survey, 80% indicated their ability to perform functional tasks were more impacted postflight relative to inflight with 50% indicating they needed to restrict movements for a longer period postflight relative to inflight. While there is a strong association within tests obtained at different R+0 timepoints, by R+24 hr performance on one post-flight test does not necessarily correlate with performance on other post-flight tests. There are apparent relationships between individual measures and specific post-flight outcome measures; however, additional data is needed to draw conclusions. Preliminary statistical analysis indicates combining biomarkers will increase predictive power and this will be explored with future analyses. Our preliminary findings underscore the importance of a comprehensive post-flight test battery including different types of tasks with varying sensory feedback. We expect that understanding the relationships between these sensorimotor biomarkers and post-flight functional task performance will improve both our understanding of the individual variability and our strategy to optimize sensorimotor countermeasures.

S J Wood↗

NASA NTRS2010

Spacecraft VHF Radio Propagation Analysis in Ocean Environments Including Atmospheric Effects

The Communication Systems Simulation Laboratory (CSSL) at the National Aeronautics and Space Administration (NASA)/Johnson Space Center (JSC) is tasked to perform spacecraft and ground network communication system simulations. The CSSL has developed simulation tools that model spacecraft communication systems and the space/ground environment in which they operate. This paper is to analyze a spacecraft's very high frequency (VHF) radio signal propagation and the impact to performance when landing in an ocean. Very little research work has been done for VHF radio systems in a maritime environment. Rigorous Radio Frequency (RF) modeling/simulation techniques were employed for various environmental effects. The simulation results illustrate the significance of the environmental effects on the VHF radio system performance.

Hwu, Shian↗

NASA NTRS2024

Vertiport Management from Simulation to Flight: Continued Human Factors Assessment of Vertiport Operations

The Urban Air Mobility concept envisions a new future for transportation in urban environments, primarily focused around vertiport operations. A vertiport refers to an identifiable ground or elevated area used for the vertical takeoff and landing of an aircraft. One critical role within vertiport operations that has been proposed but is under-researched is the vertiport manager. The vertiport manager is expected to manage the ground-to-air operations at the vertiport, but their precise responsibilities, tasks, and challenges are currently undefined. The High Density Vertiplex Subproject at NASA is responsible for developing and testing technologies, concepts, and architectures that will support the infrastructure needed for terminal environments around vertiports. Our previous work investigated ground control station operators performing simulated and live flight operations within a remote operations environment. In the current study, we extended from our previous work to explore the role of a vertiport manager. Specifically, we investigated five participants serving as a vertiport manager across both simulated and live flight operations. We performed multiple knowledge elicitation techniques, a thematic content analysis of qualitative data, and naturalistic observations to create a list of insights, design and training recommendations, and a simplified cognitive task diagram of the vertiport manager’s primary task. Findings from this study are discussed within the context of the current debate on the degree to which this role should be automated. A third alternative is suggested to allow a human vertiport manager to be successful by teaming with increasingly autonomous systems, designing the role to improve safety and efficiency of Urban Air Mobility operations.

AAM↗

NASA NTRS2024

Vertiport Management from Simulation to Flight: Continued Human Factors Assessment of Vertiport Operations

AAM↗