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At least 469 records · Page 26

MenuFramework

The Menu Framework is a reusable Extended Reality multi-level menu system for the Unity Development Platform. The menu structure is architected for reusability to suit whatever need the developer may have for a multi-level, reusable menu framework. Menu Framework's architecture, GUI, and functionality are based on the paper "Extended Reality for Enhanced Training and Knowledge Capture" (SAND2020-2361C). This tool uses the Microsoft Mixed Reality ToolKit (MRTK) built in functionality to provide a suite of functionalities including bounding box, follow me, minimize, maximize, settings, and help commands. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1507 O

Klein, BrandonThorin↗

AI Design Assistant

SAND2025-01930O The AI Design Assistant uses ChatGPT to provide a natural language interface to airfoil analysis tools (XFOIL). Most of the code base is glue code, connecting XFOIL (a tool for analyzing airfoils) to the OpenAI interface. Among the more novel features are an airfoil geometry class and methods on how to extract detailed data from XFOIL. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Karcher, Cody↗

mvBayes

SAND2026-16980O mvBayes implements multivariate Bayesian regression using MATLAB and decomposes a multivariate or functional response into components based on a user-specified orthogonal basis. This allows for independent modeling of each component with any chosen univariate Bayesian regression model. This tool includes methods for prediction and visualization, facilitating the evaluation of Bayesian surrogate models through the application of Bayesian theory and Markov Chain Monte Carlo (MCMC) sampling techniques. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tucker, J. Derek [Sandia National Lab. (SNL-CA), L↗

Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

Neil, Doreen O.↗

Analytical Tool to evaluate Heterogeneous Neuromorphic Architectures (ATHENA)

SAND2022-7062 O The Analytical Tool to Evaluate Heterogeneous Neuromorphic Architectures (ATHENA) quickly evaluates performance metrics like energy, area, and latency for an AI/ML network. It currently supports the evaluation of analog neural networks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hahn, Andrew↗

Updating the Finite Element Model of the Aerostructures Test Wing using Ground Vibration Test Data

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the Aerostructures Test Wing (ATW), which was designed and tested at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Lung, Shun-fat↗

Updating the Finite Element Model of the Aerostructures Test Wing Using Ground Vibration Test Data

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the aerostructures test wing (ATW), which was designed and tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Lung, Shun-Fat↗

Can We Trust Computational Modeling for Medical Applications?

Operations in extreme environments such as spaceflight pose human health risks that are currently not well understood and potentially unanticipated. In addition, there are limited clinical and research data to inform development and implementation of therapeutics for these unique health risks. In this light, NASA's Human Research Program (HRP) is leveraging biomedical computational models and simulations (M&S) to help inform, predict, assess and mitigate spaceflight health and performance risks, and enhance countermeasure development. To ensure that these M&S can be applied with confidence to the space environment, it is imperative to incorporate a rigorous verification, validation and credibility assessment (VV&C) processes to ensure that the computational tools are sufficiently reliable to answer questions within their intended use domain. In this presentation, we will discuss how NASA's Integrated Medical Model (IMM) and Digital Astronaut Project (DAP) have successfully adapted NASA's Standard for Models and Simulations, NASA-STD-7009 (7009) to achieve this goal. These VV&C methods are also being leveraged by organization such as the Food and Drug Administration (FDA), National Institute of Health (NIH) and the American Society of Mechanical Engineers (ASME) to establish new M&S VV&C standards and guidelines for healthcare applications. Similarly, we hope to provide some insight to the greater aerospace medicine community on how to develop and implement M&S with sufficient confidence to augment medical research and operations.

Mulugeta, Lealem↗

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

In 2008 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organization to find ways to reduce the costs of International Space station (ISS) console operations in the Mission Control Center (MCC). Each MOD organization was asked to identify projects that would help them attain a goal of a 30% reduction in operating costs by 2012. The MOD Operations and Planning organization responded to this challenge by launching several software automation projects that would allow them to greatly improve ISS console operations and reduce staffing and operating costs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the plan of eliminating two full time ISS console support positions by 2012. This will account for an overall 10 EP reduction in staffing for the Operations and Planning organization. These automation projects focused on utilizing software to automate many administrative and often repetitive tasks involved with processing ISS planning and daily operations information. This information was exchanged between the ground flight control teams in Houston and around the globe, as well as with the ISS astronaut crew. These tasks ranged from managing mission plan changes from around the globe, to uploading and downloading information to and from the ISS crew, to even more complex tasks that required multiple decision points to process the data, track approvals and deliver it to the correct recipient across network and security boundaries. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture between several planning tools; as well as a engaging a previously research level technology (TRL 2-3) developed by Ames Research Center (ARC) that utilized an intelligent agent based system to manage and automate file traffic flow, archiving f data, and generating console logs. This technology called OCAMS (OCA (Orbital Communication System) Management System), is now considered TRL level 9 and is in daily use in the Mission Control Center in support of ISS operations. These solutions have not only allowed for improved efficiency on console; but since many of the previously manual data transfers are now automated, many of the human error prone steps have been removed, and the quality of the planning products has improved tremendously. This has also allowed our Planning Flight Controllers more time to focus on the abstract areas of the job, (like the complexities of planning a mission for 6 international crew members with a global planning team), instead of being burdened with the administrative tasks that took significant time each console shift to process. The resulting automation solutions have allowed the Operations and Planning organization to realize significant cost savings for the ISS program through 2020 and many of these solutions could be a viable

Hall, Timothy A.↗

Friction Stir Welding Development at National Aeronautics and Space Administration-Marshall Space Flight Center

This paper presents an over-view of friction stir welding (FSW) process development and applications at Marshall Space Flight Center (MSFC). FSW process development started as a laboratory curiosity but soon found support from many users. The FSW process advanced very quickly and has found many applications both within and outside the aerospace industry. It is currently being adapted for joining key elements of the Space Shuttle External Tank for improved producibility and reliability. FSW process modeling is done to better understand and improve the process. Special tools have been developed to weld variable thickness materials including very thin and very thick materials. FSW is now being applied to higher temperature materials such as copper and to advanced materials such as metal matrix composites. FSW technology is being successfully transferred from MSFC laboratory to shop floors of many commercial companies.

Bhat, Biliyar N.↗

Evaluation of NCAR Icing/SLD Forecasts, Tools and Techniques Used During The 1998 NASA SLD Flight Season

Supercooled Large Droplet (SLD) icing conditions were implicated in at least one recent aircraft crash, and have been associated with other aircraft incidents. Inflight encounters with SLD can result in ice accreting on unprotected areas of the wing where it can not be removed. Because this ice can adversely affect flight characteristics of some aircraft, there has been concern about flight safety in these conditions. The FAA held a conference on in-flight icing in 1996 where the state of knowledge concerning SLD was explored. One outcome of these meetings was an identified need to acquire SLD flight research data, particularly in the Great Lakes Region. The flight research data was needed by the FAA to develop a better understanding of the meteorological characteristics associated with SLD and facilitate an assessment of existing aircraft icing certification regulations with respect to SLD. In response to this need, NASA, the Federal Aviation Administration (FAA), and the National Center for Atmospheric Research (NCAR) conducted a cooperative icing flight research program to acquire SLD flight research data. The NASA Glenn Research Center's Twin Otter icing research aircraft was flown throughout the Great Lakes region during the winters of 1996-97 and 1997-98 to acquire SLD icing and meteorological data. The NASA Twin Otter was instrumented to measure cloud microphysical properties (particle size, LWC (Liquid Water Content), temperature, etc.), capture images of wing and tail ice accretion, and then record the resultant effect on aircraft performance due to the ice accretion. A satellite telephone link enabled the researchers onboard the Twin Otter to communicate with NCAR meteorologists. who provided real-time guidance into SLD icing conditions. NCAR meteorologists also provided preflight SLD weather forecasts that were used to plan the research flights, and served as on-board researchers. This document contains an evaluation of the tools and techniques NCAR forecasters used to predict the location of SLD icing conditions during the winter of 1997-1998. The objectives of this report are to: (1) assess the tools used to forecast in-flight icing. (2) assess the success/failure rate of the forecasts, and (3) discuss suggested changes to forecast techniques.

Bernstein, Ben C.↗

Bringing Climate Scientist's Tools into Classrooms to Improve Conceptual Understandings

Efforts to address anthropogenic global climate change (AGCC) require public understanding of Earth and climate science. To meet this need, educational reforms and prominent scientists have called for instructional approaches that teach students how climate scientists examine AGCC. Yet, only a few educational studies have reported clear empirical results on what instructional approaches and climate education technologies best accomplish this goal. This manuscript presents detailed analysis and statistically significant results on the educational impact pre to post of students learning to use a National Aeronautics and Space Administration (NASA) global climate model (GCM). This series of case studies demonstrates that differing instructional approaches and climate education technologies result in differing levels of understanding of AGCC and ability to engage with policies addressing it. Students who learned the scientific process of climate modeling scored significantly higher pre to post on exams (quantitatively) and gained more complete conceptual understandings of the issue (qualitatively). Yet, teaching students to conduct research with complex technology can be difficult. This study also found lecture-based learning better improved recall of facts about GCMs tested by multiple-choice questions. Our findings indicate what educational systems and related technologies might provide the public with the conceptual understandings necessary to engage in the political debate over AGCC.

Public understanding↗

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

Validation↗

A Comprehensive Framework for Assessing Terrestrial Analogue Field Sites for Ocean Worlds

Field studies at terrestrial analogue sites represent an important contribution to the science of ocean worlds. The value of the science and technology investigations conducted at field analogue sites depends on the relevance of the analogue environment to the target ocean world. We accept that there are no perfect analogues for many of the unique environments represented by ocean worlds but suggest that a one‐to‐one matching of environmental characteristics and conditions is not crucial to the success or impact of the work. Instead, we must determine which processes and parameters are required to map directly to the target ocean world environment with high fidelity to address the science question. In this review paper, we discuss the outcomes of a workshop aimed at developing a new framework for evaluating the suitability of analogue field locations for ocean worlds research. Here we present a two‐step approach to (a) identify the most crucial processes and parameters associated with a given science question and (b) assess the fidelity of these processes and parameters at a proposed field site to those expected for the target ocean world. We demonstrate this approach in a test case evaluating three types of ocean world analogue environments with respect to a science question. The consensus document presented here equips veteran and new investigators with valuable tools to better assess and justify their analogue site selections.

58 GEOSCIENCES↗

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗

Assembly of a Full-Scale External Tank Barrel Section Using Friction Stir Welding

A full-scale pathfinder barrel section of the External Tank for the National Aeronautics and Space Administration (NASA) Space Transport System (Space Shuttle) has been assembled at Marshall Space Flight Center (MSFC) via a collaborative effort between NASA/MSFC and Lockheed Martin Michoud Space Systems. The barrel section is 27.5 feet in diameter and 15 feet in height. The barrel was assembled using Super-Light-Weight (SLWT), orthogrid, Al-Li 2195 panel sections and a single longeron panel. A vertical weld tool at MSFC was modified to accommodate FSW and used to assemble the barrel. These modifications included the addition of a FSW weld head and new controller hardware and software, the addition of a backing anvil and the replacement of the clamping system with individually actuated clamps. Weld process 4evelopment was initially conducted to optimize the process for the welds required for completing the assembly. The variable thickness welds in the longeron section were conducted via both two-sided welds and with the use of a retractable pin tool. The barrel assembly was completed in October 1998. Details of the vertical weld tool modifications and the assembly process are presented.

Jones, Chip↗

System Performance of an Integrated Airborne Spacing Algorithm with Ground Automation

The National Aeronautics and Space Administration's (NASA's) first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the Terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools to enable precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise spacing behind another aircraft. Recent simulations and IM algorithm development at NASA have focused on trajectory-based IM operations where aircraft equipped with IM avionics are expected to achieve a spacing goal, assigned by air traffic controllers, at the final approach fix. The recently published IM Minimum Operational Performance Standards describe five types of IM operations. This paper discusses the results and conclusions of a human-in-the-loop simulation that investigated three of those IM operations. The results presented in this paper focus on system performance and integration metrics. Overall, the IM operations conducted in this simulation integrated well with ground-based decisions support tools and certain types of IM operational were able to provide improved spacing precision at the final approach fix; however, some issues were identified that should be addressed prior to implementing IM procedures into real-world operations.

Swieringa, Kurt A.↗