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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 109 records · Page 6

NASA Operational Simulator for Small Satellites: Tools for Software Based Validation and Verification of Small Satellites

The NASA Operational Simulator for Small Satellites (NOS3) is a suite of tools to aid in areas such as software development, integration test (IT), mission operations training, verification and validation (VV), and software systems check-out. NOS3 provides a software development environment, a multi-target build system, an operator interface-ground station, dynamics and environment simulations, and software-based hardware models. NOS3 enables the development of flight software (FSW) early in the project life cycle, when access to hardware is typically not available. For small satellites there are extensive lead times on many of the commercial-off-the-shelf (COTS) components as well as limited funding for engineering test units (ETU). Considering the difficulty of providing a hardware test-bed to each developer tester, hardware models are modeled based upon characteristic data or manufacturers data sheets for each individual component. The fidelity of each hardware models is such that FSW executes unaware that physical hardware is not present. This allows binaries to be compiled for both the simulation environment, and the flight computer, without changing the FSW source code. For hardware models that provide data dependent on the environment, such as a GPS receiver or magnetometer, an open-source tool from NASA GSFC (42 Spacecraft Simulation) is used to provide the necessary data. The underlying infrastructure used to transfer messages between FSW and the hardware models can also be used to monitor, intercept, and inject messages, which has proven to be beneficial for VV of larger missions such as James Webb Space Telescope (JWST). As hardware is procured, drivers can be added to the environment to enable hardware-in-the-loop (HWIL) testing. When strict time synchronization is not vital, any number of combinations of hardware components and software-based models can be tested. The open-source operator interface used in NOS3 is COSMOS from Ball Aerospace. For testing, plug-ins are implemented in COSMOS to control the NOS3 simulations, while the command and telemetry tools available in COSMOS are used to communicate with FSW. NOS3 is actively being used for FSW development and component testing of the Simulation-to-Flight 1 (STF-1) CubeSat. As NOS3 matures, hardware models have been added for common CubeSat components such as Novatel GPS receivers, ClydeSpace electrical power systems and batteries, ISISpace antenna systems, etc. In the future, NASA IVV plans to distribute NOS3 to other CubeSat developers and release the suite to the open-source community.

Verification↗

Using the CYBER-Champ Model to Determine Cyber Competencies and Role Alignment

Cybersecurity roles, tasks, and skills are seen by many organizations as nonessential, abstract, or complicated. Although standards are in place, such as the National Institute of Standards and Technology (NIST) 800-181 document titled “Workforce Framework for Cybersecurity (NICE Framework)” available since September 2012, companies are still showing security vulnerabilities in their cyber networks (Hatzes, 2020). Barriers towards creating a cyber-ready workforce are not always due to a lack of resources, but often caused by organizational structure. The need for cyber-cognizant job postings, improved communication between Operational Technology (OT) and Information Technology (IT) employees, increases in staffing and funding for cyber teams, and better communication of standards and training can all contribute to increasing an organization’s cyber resilience. Cybersecurity Competency Health and Maturity Progression model (CYBER-CHAMP) is a model aimed at evaluating an organization’s structure and individual employee’s cyber knowledge and helps develop a plan to reach competency. This model was used to engage with organizations to promote proper cyber protocols and policies. The aim of this paper is to answer if it is possible for an organization to build a cyber-ready workforce by providing education and training options for current employees and prepare the future workforce to be ready on day one of employment. Both open source and firsthand interviews with organizations were used to conduct the research contained in this document. Further research may include additional development to the CYBER-CHAMP model and its delivery platform.

99 GENERAL AND MISCELLANEOUS↗

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗

Integrative path modeling and QTL mapping identify maturity, stem strength, and cell wall composition driving lettuce resistance to Sclerotinia minor

Lettuce ( Lactuca sativa ) is highly vulnerable to Sclerotinia minor , the pathogen causing lettuce drop. Breeding for resistance is the most effective control strategy; however, full resistance has not been achieved, and current partial resistance sources are often linked with undesirable traits, such as early bolting. This study aimed to unravel the genetic basis of partial resistance to S. minor and its relationship with plant maturity (bolting), stem mechanical strength (SMS), and cell wall composition (CWC) using a recombinant inbred line (RIL) population derived from a cross between the susceptible iceberg cv. ‘Salinas’ and the resistant oil-seed accession PI 251246. Field evaluations indicated that resistance was linked to earlier bolting, stronger stems, and higher pentose content. Path analysis demonstrated that earlier-maturing plants exhibited increased resistance through enhanced SMS and modified CWC, particularly with higher xylose and lower arabinose levels. Further analysis indicated a significant relationship between syringyl lignin content and resistance, especially in plants with varying bolting responses. Three key quantitative trait loci (QTLs) on linkage groups (LG) 2, 6, and 7 were consistently associated with resistance, bolting, and SMS. Importantly, residual QTL analysis revealed that the resistance locus on LG7 acted independently of maturity, suggesting a distinct resistance mechanism. Callose synthase emerged as a key candidate gene within the LG7 resistance QTL, located near - but distinct from - genes associated with plant maturity and flowering. These findings provide valuable insights into decoupling resistance from early bolting, suggesting a pathway for breeding lettuce cultivars with improved disease resistance and delayed bolting.

Lactuca↗

Evaluating Nonuniform Reduction in HIP and SYCL on GPUs

Motivated by maturing programming models and portability for heterogeneous computing, we describe the challenges posed by hardware architectures and programming models when migrating an optimized implementation of nonuniform reduction from CUDA to HIP and SYCL. We explain the migration experience, evaluate the performance of the reduction on GPU -based computing platforms, and provide feedback on improving portability for the development of the SYCL programming model.

Jin, Zheming↗

Demonstration of the Cybersecurity Framework through Real-world Cyber Attack

The Cybersecurity Framework (CSF) developed by the National Institute of Standards and Technology Cybersecurity, provides five concurrent and continuous functions to Identify, Protect, Detect, Respond, and Recover from cyber threats and vulnerabilities to buildings. Based on the core architecture and security best practices defined in the CSF guidelines, we developed the CSF webtools. The CSF webtools provide actionable functions that can be easily adopted by a facility operator to enhance their critical infrastructure security. The essence is captured in a set of “how-to” instructions for the facility operators to adopt, adapt, and apply to their critical infrastructure facilities. When considered together, these functions provide a high-level, strategic view of the lifecycle of an organization’s cybersecurity risk management. The CSF webtools provide an easy to follow set of cybersecurity best practices, policies, and procedures to improve the cybersecurity posture of our nation’s buildings and other critical infrastructures. The CSF webtools are also designed to facilitate communication of cybersecurity activities and outcomes across the organization from the executive to operations levels. Finally, the CSF webtools allow the critical infrastructure operators to assess the overall cybersecurity maturity and posture. The goal of this paper is to demonstrate the capabilities of the CSF webtools through an illustrative cyber-attack based on a real-world scenario.

cybersecurity framework, maturity model, critical ↗

Ex Situ Catalytic Fast Pyrolysis of Lignocellulosic Biomass to Hydrocarbon Fuels: 2020 State of Technology

Biomass catalytic fast pyrolysis (CFP) research was funded by the Bioenergy Technologies Office (BETO) of the U.S. Department of Energy (DOE) to enable technical breakthroughs to help reduce the cost of conversion of biomass to liquid hydrocarbon fuels. The key goals were to achieve a mature plant modeled Minimum Fuel Selling Price of $3/GGE, with greater than 60% greenhouse gas (GHG) reduction over petroleum derived gasoline by 2022. Experimental results at NREL and PNNL, along with lifecycle analysis by ANL show that we achieved these goals based on performance at the bench scale. A Pt/TiO2 catalyst was used in a fixed bed reactor for upgrading pyrolysis vapors from an upstream fast pyrolysis reactor (ex-situ configuration) to produce CFP oil with 16.5% oxygen content. Subsequent co-hydrotreating of 10 vol% of CFP oil with 90 vol% straight run diesel (SRD) at the bench scale yielded greater than 95% carbon efficiency for the CFP oil portion of the feed. Light oxygenated coproducts were recovered from the off gases from the CFP process via adsorption and subsequent desorption. Aspen Plus modeling of purification of the desorbed stream using the UNIFAC property method showed that acetone and methyl-ethyl-ketone can be purified to chemicals grade and sold as coproducts to benefit the economics and reduce GHG emissions attributed to the fuel product. Some of the key risks and uncertainties associated with this process, and potential future work are mentioned in this report.

09 BIOMASS FUELS↗

A structure for maturing intelligent tutoring system student models

A special structure is examined for evolving a detached model of the user of an intelligent tutoring system. Tutoring is used in the context of education and training devices. A detached approach to populating the student model data structure is examined in the context of the need for time dependent reasoning about what the student knows about a particular concept in the domain of interest. This approach, to generating a data structure for the student model, allows an inference engine separate from the tutoring strategy determination to be used. This methodology has advantages in environments requiring real-time operation.

Holmes, Willard M.↗

MESSOC capabilities and results

MESSOC (Model for Estimating Space Station Operations Costs) is the result of a multi-year effort by NASA to understand and model the mature operations cost of Space Station Freedom. This paper focuses on MESSOC's ability to contribute to life-cycle cost analyses through its logistics equations and databases. Together, these afford MESSOC the capability to project not only annual logistics costs for a variety of Space Station scenarios, but critical non-cost logistics results such as annual Station maintenance crewhours, upweight/downweight, and on-orbit sparing availability as well. MESSOC results using current logistics databases and baseline scenario have already shown important implications for on-orbit maintenance approaches, space transportation systems, and international operations cost sharing.

Shishko, Robert↗

Lunar and Planetary Science XXXV: Moon and Mercury

The session" Moon and Mercury" included the following reports:Helium Production of Prompt Neutrinos on the Moon; Vapor Deposition and Solar Wind Implantation on Lunar Soil-Grain Surfaces as Comparable Processes; A New Lunar Geologic Mapping Program; Physical Backgrounds to Measure Instantaneous Spin Components of Terrestrial Planets from Earth with Arcsecond Accuracy; Preliminary Findings of a Study of the Lunar Global Megaregolith; Maps Characterizing the Lunar Regolith Maturity; Probable Model of Anomalies in the Polar Regions of Mercury; Parameters of the Maximum of Positive Polarization of the Moon; Database Structure Development for Space Surveying Results by Moon -Zond Program; CM2-type Micrometeoritic Lunar Winds During the Late Heavy Bombardment; A Comparison of Textural and Chemical Features of Spinel Within Lunar Mare Basalts; The Reiner Gamma Formation as Characterized by Earth-based Photometry at Large Phase Angles; The Significance of the Geometries of Linear Graben for the Widths of Shallow Dike Intrusions on the Moon; Lunar Prospector Data, Surface Roughness and IR Thermal Emission of the Moon; The Influence of a Magma Ocean on the Lunar Global Stress Field Due to Tidal Interaction Between the Earth and Moon; Variations of the Mercurian Photometric Relief; A Model of Positive Polarization of Regolith; Ground Truth and Lunar Global Thorium Map Calibration: Are We There Yet?;and Space Weathering of Apollo 16 Sample 62255: Lunar Rocks as Witness Plates for Deciphering Regolith Formation Processes.

Source record↗

Optmization and Fabrication Studies in the Development of Structurally Integrated Thermal Protection System Technology

NASA HYP M&S is pursuing the development of SITPS: 1) Working with HYP MDAO to formulate methodology to incorporate SITPS into hypersonic vehicle design trades. 2) SITPS-0 to SITPS-1 (FY10): a) Manufacturing development and weight reduction (5.8 to 3.1 lb(sub m)/sq ft); b) Structural testing to mature SITPS model. 3) SITPS-2 (FY11): a) Focus on panel closeout, panel-to-panel load transfer, and panel curvature. 4) Extend fabrication technology to include alternate cores and insulations (FY12).

Stephens, Craig A.↗

A Conceptual Enterprise Framework for Managing Scientific Data Stewardship

Scientific data stewardship is an important part of long-term preservation and the use/reuse of digital research data. It is critical for ensuring trustworthiness of data, products, and services, which is important for decision-making. Recent U.S. federal government directives and scientific organization guidelines have levied specific requirements, increasing the need for a more formal approach to ensuring that stewardship activities support compliance verification and reporting. However, many science data centers lack an integrated, systematic, and holistic framework to support such efforts. The current business- and process-oriented stewardship frameworks are too costly and lengthy for most data centers to implement. They often do not explicitly address the federal stewardship requirements and/or the uniqueness of geospatial data. This work proposes a data-centric conceptual enterprise framework for managing stewardship activities, based on the philosophy behind the Plan-Do-Check-Act (PDCA) cycle, a proven industrial concept. This framework, which includes the application of maturity assessment models, allows for quantitative evaluation of how organizations manage their stewardship activities and supports informed decision-making for continual improvement towards full compliance with federal, agency, and user requirements.

Scientific data stewardship↗

Next Steps Following Quality Management System Implementation

While Quality Management Systems (QMS) have become increasingly common in industry over the past twenty-five to thirty years, government has been slow to adopt. There are several reasons, including the fact that government is not as tightly focused on specific groups of products as is private industry, and therefore must adapt from a product realization focus to a mission realization focus. This article will present an approach for translating the production-oriented Quality Management Systems Standards, such as those included in ISO 9001, Quality management systems-Requirements and translating them to a mission realization approach. Once a mission approach is developed and understood, it will provide the needed greater clarity and a framework for an agency to implement a QMS. When the QMS is established and implemented, agencies can then take the next steps toward continual improvement. The graphic in Table 1 illustrates the ISO 9001 provisions and the corresponding mission-related concepts and definitions are included in Table 2.

Quality Management System↗

Cybersecurity Education, Training, and WFD

Availability of skilled workforce in sufficient number is one of the most often cited barriers to improving cybersecurity. INL's research has determined that this is not a cybersecurity problem but rather a strategic business imperative; in response INL created the Cyber Competency Health and Maturity Progression Model (Cyber-CHAMP) to help organizations learn the realities of their cyber workforce and their development needs. The presentation starts with an overview of Cyber-CHAMP as a unifying theme for workforce development and then provides brief introductions to selected DHS (ICS cybersecurity hands-on training), DOE (CyberStrike, OT Defender Fellowship, Liberty Eclipse), and INL (Cybercore Summer Camp, University Collaboration Laboratory) programs. Cyber-Informed Engineering discussion concludes the presentation, with an update on activities conducted by the CIE Education Working Group to further the second pillar of the National CIE Strategy, Education.

42 ENGINEERING↗

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). We use the GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple + + prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general purpose Python can benefit from adding code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

Godoy, William↗

A Metallic Fuel Performance Benchmark Problem Based on the IFR-1 Experiment

Metallic nuclear fuels are an active area of research and development for use in advanced reactors. Robust and accurate metallic fuel performance models are necessary for the design, safety analysis, and licensing of such reactors. However, metallic fuel performance models are not as mature as ceramic fuel performance models and require additional development. In order to better gauge the accuracy of existing models, identify high-priority models for development, and quantify the improvements made by future model development, ORNL has developed a benchmark problem based on the IFR-1 experiment. This work gathers all relevant information on the IFR-1 experiment and uses it to develop the benchmark problem. It simulates the problem using the fuel performance code BISON and compare the results to post-irradiation examination data from the experiment. Then a sensitivity analysis is performed on the BISON model to determine the benchmark problem’s sensitivity to uncertainty in the input parameters. The results suggest that BISON’s mechanical models require additional development. Plastic deformation is under-predicted in the cladding and axial swelling is over-predicted in the fuel. These problems may be related. Additionally, there is a bias in the temperature which may be a result of uncertainty in the input parameters rather than an issue with the fuel performance models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗