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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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At least 1,675 records · Page 93

Improving the Parameterization of Cloud and Rain Microphysics in E3SM using Novel Observationally-Constrained Bayesian Approach (Final Technical Report)

In this project, we sought to develop new cloud and rain microphysics frameworks within the Energy Exascale Earth System Model (E3SM). This work encompassed two primary avenues of research: 1) Further development of a Bayesian-based scheme called BOSS (Bayesian Observationally-constrained Statistical-physical Scheme) to represent cloud and rain microphysics, testing it in realistic high-resolution cloud models, and implementing it in E3SM; 2) Development of a methodology utilizing machine learning to enable computationally tractable use of tractable use of Markov chain Monte Carlo sampling for Bayesian parameter estimation in Earth system and cloud models. In this project, we adapted the BOSS microphysics scheme, originally formulated for rain-only, to include all liquid-phase microphysical processes for cloud and rain, in particular the processes that mediate between these two categories, for example the conversion from cloud to rain through collision and coalescence of drops. We constrained the scheme via comparison and testing against a detailed model that explicitly represents the evolution of cloud and rain particles, called a bin microphysics scheme.

54 ENVIRONMENTAL SCIENCES↗

Integration and Validation of Multi-Layer Mitigation Strategies for Cyber Physical Systems Resilience (RD2C Capstone I Project) (Technical Report)

This project demonstrated the effectiveness of RD2C-developed, resilience-driven control strategies on high-fidelity system models with high penetrations of inverter-based resources, under the impacts of unexpected natural events and cyber-physical attacks. Controller performance and overall system resilience were quantified using data from a comprehensive suite of scenarios, and provided a clear understanding on how to operate and deploy these mitigation strategies.

42 ENGINEERING↗

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

Kopp, H.↗

Inferring Reliability Model Parameters from Expert Opinion

Here, we propose a method for constructing bathtub models of reliability from opinion. The method is intended for reliability studies early in the design and prototyping of a new system, before data concerning reliability has become available. A stylized bathtub curve is presented for soliciting best engineering judgement from technical experts. By pooling these stylized curves, we produce data that can be used to infer parameters for a piece-wise Weibull model of reliability. A numerical example demonstrates the practicality of the method while also highlighting potential pitfalls when working with subjective data.

42 ENGINEERING↗

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites. Topical Report

This project aimed to integrate, optimize, and validate the fiber orientation and length distribution models previously developed and implemented in the Autodesk® Simulation Moldflow® Insight (ASMI) software package for injection-molded long-carbon-fiber (LCF) thermoplastic composite structures. The project was organized into two phases. Phase 1 demonstrated the ability of the advanced ASMI package to predict fiber orientation and length distributions in LCF/polypropylene (PP) and LCF/polyamide-6, 6 (PA66) plaques within 15% of experimental results. Phase 2 validated the advanced ASMI package by predicting fiber orientation and length distributions within 15% of experimental results for a complex three-dimensional (3D) Toyota automotive part injection-molded from LCF/PP and LCF/PA66 materials. Work under Phase 2 also included estimate of weight savings and cost impacts for a vehicle system using ASMI and structural analyses of the complex part. The present report summarizes the completion of Phases 1 and 2 work activities and accomplishments achieved by the team comprising Pacific Northwest National Laboratory (PNNL); Purdue University (Purdue); Virginia Polytechnic Institute and State University (Virginia Tech); Autodesk, Inc. (Autodesk); PlastiComp, Inc. (PlastiComp); Toyota Research Institute North America (Toyota); Magna Exteriors and Interiors Corp. (Magna); and University of Illinois. Figure 1 illustrates the technical approach adopted in this project that progressed from compounding LCF/PP and LCF/PA66 materials, to process model improvement and implementation, to molding and modeling LCF/PP and LCF/PA66 plaques. The lessons learned from the plaque study and the successful validation of improved process models for fiber orientation and length distributions for these plaques enabled the project to go to Phase 2 to mold, model, and optimize the 3D complex part.

42 ENGINEERING↗

International collaboration on used fuel disposition crystalline rocks

Active participation in international R&D is crucial for achieving the UFD long-term goals of conducting “experiments to fill data needs and confirm advanced modeling approaches” (by 2015) and of having a “robust modeling and experimental basis for evaluation of multiple disposal system options” (by 2020). DOE’s Office of Nuclear Energy (NE) and its Office of Used Fuel Disposition Research and Development (UFD) have developed a strategic plan to advance cooperation with international partners. The international collaboration on the evaluation of crystalline disposal media at Sandia National Laboratories (SNL) in FY16 focused on the following four activities: (1) thermal-hydrologic-mechanical-chemical modeling single fracture evolution; (2) simulations of flow and transport in Bedrichov Tunnel, Czech Republic, (3) completion of streaming potential testing at Korean Atomic Energy Research Institute (KAERI), and (4) technical data exchange with KAERI on thermal-hydrologic-mechanical (THM) properties and specifications of bentonite buffer materials. The first two activities are part of the Development of Coupled Models and their Validation against Experiments (DECOVALEX-2015) project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Subjective Assessment of Alternative Mission Architecture Operations Concepts for the Human Exploration of Mars at NASA Using a Three-Dimensional Multi-Criteria Decision Making Model

The primary driver for developing missions to send humans to other planets is to generate significant scientific return. NASA plans human planetary explorations with an acceptable level of risk consistent with other manned operations. Space exploration risks can not be completely eliminated. Therefore, an acceptable level of cost, technical, safety, schedule, and political risks and benefits must be established for exploratory missions. This study uses a three-dimensional multi-criteria decision making model to identify the risks and benefits associated with three alternative mission architecture operations concepts for the human exploration of Mars identified by the Mission Operations Directorate at Johnson Space Center. The three alternatives considered in this study include split, combo lander, and dual scenarios. The model considers the seven phases of the mission including: 1) Earth Vicinity/Departure; 2) Mars Transfer; 3) Mars Arrival; 4) Planetary Surface; 5) Mars Vicinity/Departure; 6) Earth Transfer; and 7) Earth Arrival. Analytic Hierarchy Process (AHP) and subjective probability estimation are used to captures the experts belief concerning the risks and benefits of the three alternative scenarios through a series of sequential, rational, and analytical processes.

Tavana, Madjid↗

Impact Testing of Aluminum 2024 and Titanium 6Al-4V for Material Model Development

One of the difficulties with developing and verifying accurate impact models is that parameters such as high strain rate material properties, failure modes, static properties, and impact test measurements are often obtained from a variety of different sources using different materials, with little control over consistency among the different sources. In addition there is often a lack of quantitative measurements in impact tests to which the models can be compared. To alleviate some of these problems, a project is underway to develop a consistent set of material property, impact test data and failure analysis for a variety of aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the FAA William J. Hughes Technical Center. Unique features of this set of data are that all material property data and impact test data are obtained using identical material, the test methods and procedures are extensively documented and all of the raw data is available. Four parallel efforts are currently underway: Measurement of material deformation and failure response over a wide range of strain rates and temperatures and failure analysis of material property specimens and impact test articles conducted by The Ohio State University; development of improved numerical modeling techniques for deformation and failure conducted by The George Washington University; impact testing of flat panels and substructures conducted by NASA Glenn Research Center. This report describes impact testing which has been done on aluminum (Al) 2024 and titanium (Ti) 6Al-4vanadium (V) sheet and plate samples of different thicknesses and with different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

Pereira, J. Michael↗

An Ontology-Based Virtual Orrery

Tutorials in this technical memorandum explain how to use the Protégé ontology editor to import data from Excel and export data from Protégé in the JavaScript Object Notation Linked Data (JSON-LD) format then how to transform the JSON-LD file into variables for web apps. These tutorials apply JavaScript and R programming languages and 3D graphics libraries. Ontologies enable standardization, data sharing, and semantic interoperability. An ontology models a domain of knowledge as taxonomies of annotated classes, data properties, relational object properties, and inference rules. This technical memorandum includes a data dictionary for a subset of the Space Situational Awareness Ontology (SSAO).

Ontologies↗

The Artificial Intelligence Ontology: LLM-Assisted Construction of AI Concept Hierarchies

The Artificial Intelligence Ontology (AIO) is a systematization of artificial intelligence (AI) concepts, methodologies, and their interrelations. Developed via manual curation, with the additional assistance of large language models (LLMs), AIO aims to address the rapidly evolving landscape of AI by providing a comprehensive framework that encompasses both technical and ethical aspects of AI technologies. The primary audience for AIO includes AI researchers, developers, and educators seeking standardized terminology and concepts within the AI domain. We use the term “branches” for classes, and their subclasses, in our ontology that are subclasses of owl:Thing. AIO contains eight branches: Bias, Layer, Machine Learning Task, Mathematical Function, Model, Network, Preprocessing, and Training Strategy, each designed to support the modular composition of AI methods and facilitate a deeper understanding of deep learning architectures and ethical considerations in AI. AIO uses the Ontology Development Kit (ODK) for its creation and maintenance, with its content being more easily updated through AI-driven curation support. This approach not only ensures the ontology's relevance amidst the fast-paced advancements in AI but also significantly enhances its utility for researchers, developers, and educators by simplifying the integration of new AI concepts and methodologies. The ontology's utility is demonstrated through the annotation of AI methods data in a catalog of AI research publications and the integration into the BioPortal ontology resource, highlighting its potential for cross-disciplinary research. The AIO ontology is open source and is available on GitHub ( https://w3id.org/aio/ ) and BioPortal ( https://bioportal.bioontology.org/ontologies/AIO ).

Joachimiak, Marcin P. [Biosystems Data Science Dep↗

IBR Bulk System Protection Issues and Modeling Challenges

Issue to be Address: Difficulty in predicting Inverter (IBR) generation dynamic response characteristics. Main challenges are unavailability of proprietary control details for modeling and the aggregate mixed IBRs with different dynamic response characteristics all contributing during system faults. Framework for Discussion: Identifying issues by sharing experience Reviewing options to improve IBR modeling accuracy, computation speed, use of test results. Presenting related research by EPRI and PG&E (DOE project) Desired Outcomes: Provide technical update for participants Get feedback and suggestions for ongoing research Improve research collaboration

IBR, Protection Challenges, dynamic response, IBR ↗

Data Quality of Salt Property Measurements

Data quality is a key element to assessing technical uncertainties in property values of salt mixtures that are pivotal in molten salt reactor (MSR) design and safety assessments under both normal operating conditions and accident scenarios. Key properties for the salt mixtures being evaluated for use in MSRs have not been measured and the few values for relevant salt compositions available in the literature are inconsistent and not suitable for use in licensing. The applications of established techniques commonly used for property measurements to molten salts are still experimental in nature and vetted consensus standards are not yet available. Work is in progress to develop and standardize methods through DOE and commercially funded projects. The quality of measured property values limits the current ability to reliably design equipment and model normal MSR operation and the effects of operational upsets. Insights from experimental measurements pertinent to reducing technical uncertainty for regulatory development are summarized in this report. Quality controls are recommended for key properties based on the mathematical calculations used to derive property values and methods used to measure experimental values and salt produced for use in the measurements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Supporting New Advanced Nuclear Technologies for Commercial-Maritime Applications

The ANS summary doesn't require an abstract, but I will produce one for the purpose of LRS: The large demand for maritime nuclear power underscores the need for experimental campaigns and modeling and simulation of new advanced reactors, which offer numerous advantages in terms of safety, efficiency, and compactness. INL, through the work conducted by NRIC and ABS, has addressed some of the technical, regulatory, and economic aspects of potential nuclear commercial maritime applications. However, on the technical side, there remain important physical phenomena, particularly for advanced reactors, that are not yet fully understood. Addressing these knowledge gaps requires a combination of experiments and advanced modeling and simulation techniques. INL possesses significant expertise in Multiphysics modeling and simulation. By collaborating with INL, the maritime nuclear sector can leverage this expertise to advance the development and deployment of innovative nuclear technologies.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Southern Ocean Uptake in the MPAS-Ocean Model

The research added to the understanding of Southern Ocean Uptake in the following ways. 1) No single process in the model could be “tuned” to improve Southern Ocean uptake of heat, CO 2 and CFCs. 2) More comprehensive studies revealed that multiple aspects of the model are important; in particular the general circulation control of deep (>200m) stratification (Small et al., 2019) and salinity contributions to the shallow (< 200 m) stratification (DuVivier et al, 2018). These two aspects are not strongly connected. The first can be very much improved by increasing horizontal resolution, primarily because of more transport of high salinity water from the Indian Ocean into the Southern Ocean south of Africa, so we now know that “parameterizing” this salinity source will be one necessary step to improving the Southern Ocean uptake at low resolution. 3) However, the second was found to be more than just a resolution issue, which may explain why many studies have found that higher resolution improves only some aspects of model solutions, but degrades others. Even in cases where the surface wind is too strong, the shallow stratification is sufficient to inhibit vertical mixing even though the salinity stabilization is weak compared to observations. The conclusion is that the process responsible for mixing through the stable salinity barrier above 200m is missing from the model. Therefore, a second necessary step is to find the process then incorporate it into the model. The project focused on ocean surface wave driven Langmuir turbulence as the source of additional mixing by studying Large Eddy Simulations (LES) of Southern Ocean boundary layers as they eroded a realistic salinity barrier. The wind, buoyancy and wave driven boundary layer turbulence was found to be well described by Monin-Obukhov similarity by developing similarity functions of the wave driving, and combining these with the established wind and buoyancy functions (Large et al., 2018a). These functions and a novel analysis of the momentum flux and vertical shear fields from the LES revealed two distinct aspects where the boundary layer turbulence was much more organized than expected, and hence much more amenable to implementation in the model (Large et al., 2018b). First, there is a robust non-local across-shear transport of momentum throughout the ocean boundary layer; a hitherto missing process. Furthermore, this transport is related to the across-shear component of the wind stress in the same way that non-local buoyancy transport is related to the surface buoyancy flux, both in the ocean and atmosphere. Even the coefficients are similar in the convective limit. Second, the turbulent fluxes of momentum and buoyancy are distributed through the ocean boundary layer of the LES in a very orderly fashion given by a single shape function that appears to be applicable to both momentum and buoyancy, with or without surface wave driving. Thus, a very technically effective and economic path to incorporating surface wave driving in the vertical mixing scheme of the model is now clear. The high degree of order found for ocean boundary layer turbulence, including Langmuir turbulence, is more amenable to empirical models than to statistical turbulence models, and the computational cost is very much less. Fortuitously, the empirical K-Profile Parameterization is already implemented in the model and the wave-driving similarity function, the non-local momentum transport and the vertical shape function are straightforward enhancements.

58 GEOSCIENCES↗

Floating Photovoltaic Systems: Assessing the Technical Potential of Photovoltaic Systems on Man-Made Water Bodies in the Continental United States

We report that floating photovoltaic (FPV) systems, also called floatovoltaics, are a rapidly growing emerging technology application in which solar photovoltaic (PV) systems are sited directly on water. The water-based configuration of FPV systems can be mutually beneficial: Along with providing such benefits as reduced evaporation and algae growth, it can lower PV operating temperatures and potentially reduce the costs of solar energy generation. Although there is growing interest in FPV, to date there has been no systematic assessment of technical potential in the continental United States. We provide the first national-level estimate of FPV technical potential using a combination of filtered, large-scale datasets, site-specific PV generation models, and geospatial analytical tools. We quantify FPV co-benefits and siting considerations, such as land conservation, coincidence with high electricity prices, and evaporation rates. Our results demonstrate the potential of FPV to contribute significantly to the U.S. electric sector, even using conservative assumptions. A total of 24?419 man-made water bodies, representing 27% of the number and 12% of the area of man-made water bodies in the contiguous United States, were identified as being suitable for FPV generation. FPV systems covering just 27% of the identified suitable water bodies could produce almost 10% of current national generation. Lastly, many of these eligible bodies of water are in water-stressed areas with high land acquisition costs and high electricity prices, suggesting multiple benefits of FPV technologies.

14 SOLAR ENERGY↗