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NASA NTRS2021

Delaware Ecological Forecasting: Assessing Land Cover and Soil to Identify Suitable Sites for Tidal Marsh Migration in Delaware

Tidal wetlands provide vital resources for the state of Delaware, crucial not only for maintaining important ecosystem functions, but also for providing human populations with substantial services. Healthy wetland networks offer protection from severe weather, reduce flooding, improve water quality, and provide opportunities for education and recreation. However, human activities in combination with natural events, continue to cause substantial loss of wetland cover and damage wetland health. Over the last thirty years, the state of Delaware has experienced a net loss of roughly 5,000 acres of wetland. In collaboration with the Delaware Department of Natural Resources and Environmental Control (DNREC), the team used NASA Earth observations including Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and Global Precipitation Measurement Integrated Multi-Satellite Retrievals (GPM IMERG) to develop a methodology to monitor recent changes in wetland cover and forecast landward marsh migration due to sea-level rise, changes to climate, and human development. Trend analysis of current and past climate conditions in precipitation and temperature revealed an overall increase in both metrics. Using Land Change Modeler in TerrSet and Suitability Modeler in ArcGIS Pro, the team visualized landcover shifts over the last 20 years, indicating a general pattern of net wetland loss and identified locations where marsh migration could potentially occur in the future. These observations will enable better planning for restoration activities and in form decision-making to preserve wetland health and ecosystem functions.

McKenna Brahler↗

NASA NTRSDate not supplied

Using Kamodo for CCMC ITM Output and Beyond

Kamodo is an official NASA open source python software package that functionalizes diverse datasets from models and observations in a consistent way, enabling advanced scientific analysis and visualization with simplistic syntax. Here we demonstrate this ability using several ITM models available through the Community Coordinated Modeling Center (CCMC). Users can now interact directly with model outputs, and satellites can be virtually flown through model output to allow many types of model/model and data/model comparisons. We will also provide information about significant updates and improvements to Kamodo and future plans.

Open Source Software↗

NASA NTRSDate not supplied

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop testing plays a crucial role in NASA's mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts' situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA's testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop testing for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive training experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

Simulation Modeling Virtual Reality Immersive Tech↗

NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗

NASA NTRSDate not supplied

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for immersing users in realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop simulations play a crucial role in NASA’s mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments, data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures, and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts’ situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA’s testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop simulations for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive simulation experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

HITL↗

NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗

NASA NTRSDate not supplied

Evaluating the Efficacy of Conditional Variational Autoencoders in Generating Synthetic Single Nuclei RNA-Seq Data for Space Biology Research

Astronauts are subject to unique stressors during spaceflight, leading to changes in their cellular function. However, neither astronauts nor model organisms respond the same to spaceflight, and research implicates a contribution of omics components in differential responses. Understanding how gene expression affects astronaut health is critical for the success of long-term space missions, prompting interest in developing personalized predictive models leveraging artificial intelligence (AI) and machine learning (ML) techniques. Developing such models requires extensive data, which is challenging to obtain and share. This study explores the use of conditional variational autoencoders (CVAEs) to synthetically generate single-nuclei RNA-seq (snRNA-seq) data. CVAEs build on standard variational autoencoders (VAEs) by conditioning data generation on covariates like sample identity and mission parameters, enhancing the relevance of generated data for specific contexts. For our work, we built two CVAEs with varying degrees of sparsity to optimize both interpretability and generative power. We train and validate models on existing snRNA-seq data collected from the brain tissue of mice subjected to spaceflight conditions and their ground control counterparts. We evaluate model performance using statistical tests and visualizations to compare synthetic data to real data. We aim to demonstrate that these prototype CVAE architectures could be used in future space biology work and that this is a method worth further exploring.

Sarah Golts↗

NASA NTRS1991

Modelling parallel programs and multiprocessor architectures with AXE

AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.

Yan, Jerry C.↗

NASA NTRS2015

Data Presentation and Visualization (DPV) Interface Control Document

Data Presentation and Visualization (DPV) is a subset of the modeling and simulation (M&S) capabilities at Kennedy Space Center (KSC) that endeavors to address the challenges of how to present and share simulation output for analysts, stakeholders, decision makers, and other interested parties. DPV activities focus on the development and provision of visualization tools to meet the objectives identified above, as well as providing supporting tools and capabilities required to make its visualization products available and accessible across NASA.

Ontology↗

NASA NTRS1998

NASA/NOAA/AMS Earth Science Electronic Theater

New method are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model result. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and three dimensional model results interactively.

Hasler, F.↗

NASA NTRSDate not supplied

Artemis III and IV Crew Health and Performance System Model Development

To maintain Crew Health and Performance (CHP) during an Artemis mission, the NASA Human Research Program (HRP) and Exploration Medical Capabilities (ExMC) element recognize the challenge that many different vehicles, habitats, and operational groups must come together to develop and implement cross program capabilities. To address this challenge, the ExMC team created the prototype 2023 Artemis CHP System Model to analyze how human system requirements are implemented throughout an Artemis mission and help understand the effects of changing an individual vehicle or habitat requirement on a full mission. Since presenting this work at the 2024 HRP Investigators’ Workshop, ExMC has continued this effort, now called the Artemis III and IV CHP System Model, to better support its operational end users within the NASA Human Health and Performance Directorate (HHPD) workforce. In this presentation, we will recapitulate how visualizing requirements and their relationships using a Model-Based Systems Engineering approach (MBSE) serves to improve understanding of an Artemis mission’s CHP capabilities along with discussion on updates made to the model to increase accessibility for users within HHPD so that it may be used in the development of cross program CHP capabilities at NASA.

Crew Health and Performance↗

NASA NTRS1980

Space shuttle orbiter flow visualization study

The vortex flows generated at subsonic speed during the final portion of atmospheric reentry were defined using a 0.01 scale model of the orbiter in a diagnostic water tunnel. Flow visualization photographs were obtained over an angle-of-attack range to 40 deg and sideslip angles up to 10 deg. The vortex flow field development, vortex path, and vortex breakdown characteristics were determined as a function of angle-of-attack at zero sideslip. Vortex flows were found to develop on the highly swept glove, on the wing, and on the upper surface of the fuselage. No significant asymmetries were observed at zero sideslip in the water tunnel tests. The sensitivity of the upper surface vortex flow fields to variations in sideslip angle was also studied. The vortex formed on the glove remained very stable in position above the wing up through the 10 deg of sideslip tested. There was a change in the vortex lifts under sideslip due to effective change in leading-edge sweep angles. Asymmetric flow separation occurred on the upper surface of the fuselage at small sideslip angles. The influence of vortex flow fields in sideslip on the lateral/ directional characteristics of the orbiter is discussed.

Lorincz, D. J.↗

NASA NTRS1984

Flow visualization and interpretation of visualization data for deflected thrust V/STOL nozzles

Flow visualization studies were made for four deflected thrust nozzle models at subsonic speeds. Based on topological rules and the assumption that observed streaks constitute continuous vector fields, available visualization pictures are interpreted and flow patterns on interior surfaces of the nozzles are synthesized. In particular, three dimensional flow structure and separations are discussed. From the synthesized patterns, the overall features of the flow field in a given nozzle can be approximately perceived.

Kao, H. C.↗

NASA NTRS1984

Flow visualization and interpretation of visualization data for deflected thrust V/STOL nozzles

Kao, H. C.↗

NASA NTRS1984

Signal-to-noise ratio for the wide field-planetary camera of the Space Telescope

Signal-to-noise ratios for the Wide Field Camera and Planetary Camera of the Space Telescope were calculated as a function of integration time. Models of the optical systems and CCD detector arrays were used with a 27th visual magnitude point source and a 25th visual magnitude per arc-sq. second extended source. A 23rd visual magnitude per arc-sq. second background was assumed. The models predicted signal-to-noise ratios of 10 within 4 hours for the point source centered on a signal pixel. Signal-to-noise ratios approaching 10 are estimated for approximately 0.25 x 0.25 arc-second areas within the extended source after 10 hours integration.

Zissa, D. E.↗

NASA NTRS1989

High-alpha aerodynamic characteristics of crescent and elliptic wings

Static longitudinal and lateral-directional forces and moments were measured for elliptic- and crescent-wing models at high angles of attack in the NASA Langley 14-by-22-ft Subsonic Tunnel. The forces and moments were obtained for an angle-of-attack range including stall and post-stall conditions at a Reynolds number based on the average wing chord of about 1.8 million. Flow-visualization photographs using a mixture of oil and titanium-dioxide were also taken for several incidence angles. The force and moment data and the flow-visualization results indicated that the crescent wing model with its highly swept tips produced much better high-angle-of-attack aerodynamic characteristics than the elliptic model. Leading-edge separation-induced vortex flow over the highly swept tips of the crescent wing is thought to produce this improved behavior at high angles of attack. The unique planform design could result in safer and more efficient low-speed airplanes.

Van Dam, C. P.↗

NASA NTRS2010

GUI to Facilitate Research on Biological Damage from Radiation

A graphical-user-interface (GUI) computer program has been developed to facilitate research on the damage caused by highly energetic particles and photons impinging on living organisms. The program brings together, into one computational workspace, computer codes that have been developed over the years, plus codes that will be developed during the foreseeable future, to address diverse aspects of radiation damage. These include codes that implement radiation-track models, codes for biophysical models of breakage of deoxyribonucleic acid (DNA) by radiation, pattern-recognition programs for extracting quantitative information from biological assays, and image-processing programs that aid visualization of DNA breaks. The radiation-track models are based on transport models of interactions of radiation with matter and solution of the Boltzmann transport equation by use of both theoretical and numerical models. The biophysical models of breakage of DNA by radiation include biopolymer coarse-grained and atomistic models of DNA, stochastic- process models of deposition of energy, and Markov-based probabilistic models of placement of double-strand breaks in DNA. The program is designed for use in the NT, 95, 98, 2000, ME, and XP variants of the Windows operating system.

Cucinotta, Frances A.↗

NASA NTRS1989

High angle-of-attack aerodynamic characteristics of crescent and elliptic wings

Static longitudinal and lateral-directional forces and moments were measured for elliptic- and crescent-wing models at high angles-of-attack in the NASA Langley 14 by 22-Ft Subsonic Tunnel. The forces and moments were obtained for an angle-of-attack range including stall and post-stall conditions at a Reynolds number based on the average wing chord of about 1.8 million. Flow-visualization photographs using a mixture of oil and titanium-dioxide were also taken for several incidence angles. The force and moment data and the flow-visualization results indicated that the crescent wing model with its highly swept tips produced much better high angle-of-attack aerodynamic characteristics than the elliptic model. Leading-edge separation-induced vortex flow over the highly swept tips of the crescent wing is thought to produce this improved behavior at high angles-of-attack. The unique planform design could result in safer and more efficient low-speed airplanes.

Vandam, C. P.↗