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NASA NTRS2015

Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

computational mechanics↗

NASA NTRS2019

Updating the Space Communications and Navigation (SCaN) Link Tool Executable Software to Version 5

NASA’s Space Communications and Navigation (SCaN) program is responsible for providing space communication channels in low Earth orbit, geosynchronous orbit, and deep space for a variety of space missions. The SCaN Link Tool is a standalone, executable, and personal computer (PC)-based software operated via a user interface, which provides NASA civil servants and contractors, as well as the public by way of the tool’s inclusion in the NASA Software Catalog, with in-depth satellite communications link analysis capability. Version 4 of the tool was built using PythonTM (Python Software Foundation) with the help of libraries such as NumPy and SciPy for numerical calculations, Matplotlib for graphical visualizations, and PyQt5 for the graphical user interface. It utilizes radiofrequency (RF) and optical communications link analysis calculations to give users the ability to input known link parameters and calculate select link performance outputs. With the development of the next-generation architecture for space satellite communications in the coming decade, NASA will benefit by having more in-depth communications link analysis tools at its disposal. The tool’s update from version 4 to version 5 aims to provide higher output value accuracy, the ability to solve for a more diverse set of output variables, as well as analog and digital repeater capabilities. Options included in the tool’s functionality, such as the ability to save configuration parameter values, graphs, and results, as well as the provision of default parameter values, increase the tool’s versatility. Users will have access to in-depth, accurate communications link analysis as more advanced satellite constellations are designed and deployed by NASA and the growing commercial aerospace community.

Green, Jack L.↗

NASA NTRS2015

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite while the effect on the axial properties is shown to be insignificant.

nanocomposites↗

NASA NTRS2003

Some approaches to medical support for Martian expedition

Medical support in a Martian expedition will be within the scope of crew responsibilities and maximally autonomous. Requirements to the system of diagnostics in this mission include considerable use of means and methods of visualization of the main physiological parameters, telemedicine, broad usage of biochemical analyses (including "dry" chemistry), computerized collection, measurement, analysis and storage of medical information. The countermeasure system will be based on objective methods of crew fitness and working ability evaluation, individual selection of training regimens, and intensive use of computer controlled training. Implementation of the above principles implies modernization and refinement of the countermeasures currently used by space crews of long-term missions (LTM), and increases of the assortment of active and passive training devices, among them a short-arm centrifuge. The system of medical care with the functions of prevention, clinical diagnostics and timely treatment will be autonomous, too. The general requirements to medical care during the future mission are the following: availability of conditions and means for autonomous urgent and special medical aid and treatment of the most possible states and diseases, "a hospital", and assignment to the crew of one or two doctors. To ensure independence of medical support and medical care in an expedition to Mars an automated expert system needs to be designed and constructed to control the medical situation as a whole. c2003 Published by Elsevier Science Ltd.

Mars↗

NASA NTRS2015

Space Biotech: Hindsight, Insight, Foresight

Over the past forty years, microgravity has inspired and enabled applications in a wide range of sectors including medicine, materials, computers, communications, and national defense. Trends show that demand for high-tech solutions is increasing in these sectors, solutions that require higher resolution, greater precision, novel materials, innovative processes, and more sophisticated tools. These are areas where microgravity can offer unique capabilities for innovation. The Emerging Space Office (ESO) has engaged in multiple studies over the past year that have found that microgravity RD is one of the most promising technology areas for contributing to economic growth and to NASAs mission. The focus of these studies was on terrestrial markets rather than NASA applications, applied research rather than basic research, and commercial rather than academic investigators. There have been more success stories than are generally appreciated and there are significant areas of promising future potential. Many of the problems that have limited commercial microgravity development in the past are being solved. Microgravity research and development (RD) requires iteration and learning, as rapidly as possible. New technologies enable high throughput and rapid data collection in increasingly small payloads. The International Space Station is in orbit and provides a laboratory that is available 247 at least until 2024. Frequent flights by commercial space providers to and from the ISS now enable the fast learning cycles needed by high-tech industries. Launch costs are decreasing and the ability to return payloads to Earth is increasing. New commercial space laboratories, such as those being developed by SpaceX and Bigelow Aerospace, are in the final stages of development and testing. This ecosystem for microgravity RD has never been available before. These are game-changer conditions for attracting high-tech industries to space for terrestrial, as well as NASA, applications. However, few know that these capabilities are available or how to use them. In aggregate, the potential value for new applications from microgravity RD over the next ten years could add billions of dollars per year in terrestrial applications to the future economy, create new jobs, and generate a wide range of public benefits in medical advances, while broadening the customer base for the emerging space industry.

biotech↗

NASA NTRSDate not supplied

Aerothermodynamic Measurements in Hypersonic Non-Equilibrium Flows

High enthalpy arc-jets are unique facilities particularly suited for simulating complex flows in the aerospace field, such as the aerothermodynamics of a re-entry vehicle. Arc-jets are often used to evaluate important design factors such as heat shield materials and vehicle design. Characterization of these facilities is important, as studies often match specific in-flight environments during experiments. Due to the complex environment produced by an arc-jet, with effects such as thermodynamic and chemical non-equilibrium occurring in the flow, characterization experiments are significantly more difficult than in traditional blow-down wind tunnels. The current work aims to characterize an arc-jet facility in terms of flow temperature, velocity and unsteadiness, in a spatially-resolved analysis. To achieve this goal, a non-intrusive imaging technique called “planar laser-induced fluorescence” was performed in the NASA Langley Hypersonic Materials Environ-mental Test System arc-jet facility. The experimental data was analyzed to produce the quantitative measurements in multiple regions of the flow around a blunt body sample. A quasi-1D low fidelity solver was created to numerically simulate the flow to investigate non-equilibrium effects occur-ring outside the imaging region in the arc-jet nozzle. Unsteadiness in the test section was minimized by analyzing a subset of data assessing the gas injection location. Radial velocity, rotational temperature and translational temperature measurements are provided that can be used to validate future high-fidelity computational studies. The temperature measurements revealed rotational non-equilibrium potentially occurring in the flow. This work provides a methodology for characterizing arc-jet facilities, identifying and correcting sources of systematic error, and estimating the uncertainty associated with the quantitative measurements.

laser induced fluorescence↗

NASA NTRS2022

Aerothermodynamic Measurements of Hypersonic Non-Equilibrium Flows

High enthalpy arc-jets are unique facilities particularly suited for producing complex flows in the aerospace field, such as the aerothermodynamics of a re-entry vehicle. Arc-jets are often used to evaluate important design factors that include heat shield materials and vehicle design. Characterization of these facilities is important, as studies often aim to match specific in-flight environments during experiments. Due to the complex environment produced by an arc-jet, with effects such as thermodynamic and chemical non-equilibrium occurring in the flow, characterization experiments are significantly more difficult than in conventional blow-down wind tunnels. The current work aims to characterize an arc-jet facility through spatially-resolved measurements of flow unsteadiness, temperature, and velocity. To achieve this goal, a non-intrusive imaging technique called “planar laser-induced fluorescence” was performed in the NASA Langley Hypersonic Materials Environmental Test System arc-jet facility. The experimental data was analysed to produce the quantitative measurements in multiple regions of the flow around a blunt body specimen. A three-temperature low fidelity numerical solver was created to simulate the flow in order to investigate thermal non-equilibrium effects occurring outside the imaging region in the arc-jet nozzle. Unsteadiness in the test section of the arc-jet was minimized by analyzing a subset of data assessing the gas injection configuration. Radial velocity, rotational temperature and translational temperature measurements are provided that can be used to validate future computational studies. The temperature measurements revealed rotational non-equilibrium occurring behind the bow-shock near the specimen surface. Computational results show the facility is capable of producing thermal non-equilibrium flow in the arc-jet nozzle. This work provides the first experimental and computational evidence of thermal trans-rotational non-equilibrium occurring in multiple regions of this arc-jet facility. Significant improvements to the methodology are also identified as recommendations for future arc-jet characterization studies.

Laser induced fluorescence↗

NASA NTRS2015

Online Dectection and Modeling of Safety Boundaries for Aerospace Application Using Bayesian Statistics

The behavior of complex aerospace systems is governed by numerous parameters. For safety analysis it is important to understand how the system behaves with respect to these parameter values. In particular, understanding the boundaries between safe and unsafe regions is of major importance. In this paper, we describe a hierarchical Bayesian statistical modeling approach for the online detection and characterization of such boundaries. Our method for classification with active learning uses a particle filter-based model and a boundary-aware metric for best performance. From a library of candidate shapes incorporated with domain expert knowledge, the location and parameters of the boundaries are estimated using advanced Bayesian modeling techniques. The results of our boundary analysis are then provided in a form understandable by the domain expert. We illustrate our approach using a simulation model of a NASA neuro-adaptive flight control system, as well as a system for the detection of separation violations in the terminal airspace.

Statistics↗

NASA NTRS2015

Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

molecular dynamics↗

NASA NTRS1997

Algorithms for Performance, Dependability, and Performability Evaluation using Stochastic Activity Networks

Modeling tools and technologies are important for aerospace development. At the University of Illinois, we have worked on advancing the state of the art in modeling by Markov reward models in two important areas: reducing the memory necessary to numerically solve systems represented as stochastic activity networks and other stochastic Petri net extensions while still obtaining solutions in a reasonable amount of time, and finding numerically stable and memory-efficient methods to solve for the reward accumulated during a finite mission time. A long standing problem when modeling with high level formalisms such as stochastic activity networks is the so-called state space explosion, where the number of states increases exponentially with size of the high level model. Thus, the corresponding Markov model becomes prohibitively large and solution is constrained by the the size of primary memory. To reduce the memory necessary to numerically solve complex systems, we propose new methods that can tolerate such large state spaces that do not require any special structure in the model (as many other techniques do). First, we develop methods that generate row and columns of the state transition-rate-matrix on-the-fly, eliminating the need to explicitly store the matrix at all. Next, we introduce a new iterative solution method, called modified adaptive Gauss-Seidel, that exhibits locality in its use of data from the state transition-rate-matrix, permitting us to cache portions of the matrix and hence reduce the solution time. Finally, we develop a new memory and computationally efficient technique for Gauss-Seidel based solvers that avoids the need for generating rows of A in order to solve Ax = b. This is a significant performance improvement for on-the-fly methods as well as other recent solution techniques based on Kronecker operators. Taken together, these new results show that one can solve very large models without any special structure.

Deavours, Daniel D.↗

DOE OSTI2026

Rapid Evaluation Framework for the CMIP7 Assessment Fast Track

As Earth system models (ESMs) grow in complexity and in volume of output data, there is an increasing need for rapid, comprehensive evaluation of their scientific performance. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require expeditious response for model analyses designed to inform and drive integrated Earth system assessments. To meet this challenge, the Rapid Evaluation Framework (REF), a community-driven platform for benchmarking and performance assessment of ESMs, was designed and developed. The initial implementation of the REF, constructed to meet the near-term needs of the CMIP7 Assessment Fast Track, builds upon four disparate community evaluation and benchmarking tools that are coupled together using the Coordinated Model Evaluation Capabilities (CMEC) framework. The REF runs within a containerized workflow for portability and reproducibility and is aimed at generating and organizing diagnostics covering a variety of model variables. The REF leverages well documented observational datasets to provide assessments of model fidelity across a collection of diagnostics. All diagnostics were identified and selected with community involvement and consultation. Operational integration with the Earth System Grid Federation (ESGF) will permit automated execution of the REF for selected diagnostics as soon as model output data are published on ESGF by the originating modeling centers. The REF is designed to be portable across a range of current computational platforms to facilitate use by modeling centers for assessing the evolution of model versions or gauging the relative performance of CMIP simulations before being published on ESGF. When integrated into production simulation workflows, results from the REF provide immediate quantitative feedback that allows model developers and scientists to quickly identify model biases and performance issues. After the REF is released to the community, its subsequent development and support will be prioritized by an international consortium of scientists and engineers, enabling a broader impact across Earth science disciplines. For instance, the REF will facilitate improvements to models and will enhance confidence in model projections through process-based selection of models based on their performance with respect to observations. Production of reproducible diagnostics and community-based assessments are key features of the REF. Furthermore, providing interoperability with existing evaluation packages assures that contributions from previous community efforts will be available for use in future model intercomparison projects.

Hoffman, Forrest [ORNL] (ORCID:0000000158024134)↗

NASA NTRS2015

Development and Characterization of a Rate-Dependent Three-Dimensional Macroscopic Plasticity Model Suitable for Use in Composite Impact Problems

Several key capabilities have been identified by the aerospace community as lacking in the material/models for composite materials currently available within commercial transient dynamic finite element codes such as LS-DYNA. Some of the specific desired features that have been identified include the incorporation of both plasticity and damage within the material model, the capability of using the material model to analyze the response of both three-dimensional solid elements and two dimensional shell elements, and the ability to simulate the response of composites composed with a variety of composite architectures, including laminates, weaves and braids. In addition, a need has been expressed to have a material model that utilizes tabulated experimentally based input to define the evolution of plasticity and damage as opposed to utilizing discrete input parameters (such as modulus and strength) and analytical functions based on curve fitting. To begin to address these needs, an orthotropic macroscopic plasticity based model suitable for implementation within LS-DYNA has been developed. Specifically, the Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The coefficients in the yield function are determined based on tabulated stress-strain curves in the various normal and shear directions, along with selected off-axis curves. Incorporating rate dependence into the yield function is achieved by using a series of tabluated input curves, each at a different constant strain rate. The non-associative flow-rule is used to compute the evolution of the effective plastic strain. Systematic procedures have been developed to determine the values of the various coefficients in the yield function and the flow rule based on the tabulated input data. An algorithm based on the radial return method has been developed to facilitate the numerical implementation of the material model. The presented paper will present in detail the development of the orthotropic plasticity model and the procedures used to obtain the required material parameters. Methods in which a combination of actual testing and selective numerical testing can be combined to yield the appropriate input data for the model will be described. A specific laminated polymer matrix composite will be examined to demonstrate the application of the model.

Impact↗

NASA NTRS2016

MONTE Python for Deep Space Navigation

The Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) is the Jet Propulsion Laboratory’s (JPL) signature astrodynamic computing platform. It was built to support JPL’s deep space exploration program, and has been used to fly robotic spacecraft to Mars, Jupiter, Saturn, Ceres, and many solar system small bodies. At its core, MONTE consists of low-level astrodynamic libraries that are written in C++ and presented to the end user as an importable Python language module. These libraries form the basis on which Python-language applications are built for specific astrodynamic applications, such as trajectory design and optimization, orbit determination, flight path control, and more. The first half of this paper gives context to the MONTE project by outlining its history, the field of deep space navigation and where MONTE fits into the current Python landscape. The second half gives an overview of the main MONTE libraries and provides a narrative example of how it can be used for astrodynamic analysis.

aerospace↗

NASA NTRSDate not supplied

“Cold-Flow” Experiments Supporting CFD of Mixing Flowfields for High-Speed Fuel Injectors for Scramjet Applications

Recent flight demonstrations of supersonic combustion ramjet (scramjet) vehicles prove their increasing promise for military (rapid response and strike capability on global scale), aerospace (safer and more affordable access to space), and civil aviation (hypersonic point-to-point transport) applications. Currently, these technologies are still in their early development stages with commercial interest and investment at only a fraction of that of government organizations such as NASA and DoD. To advance hypersonic air-breathing propulsion technologies to the technology readiness levels necessary for access to space or widespread commercialization, further government investments and university engagement are needed over the next decade and likely beyond. This is because designing scramjet propulsion devices capable of robust high-speed air-breathing operation, characterized by rapid fuel and air mixing, short combustion times, and ensuring stable flame, has proven difficult. In this presentation, after a brief engineering-level introduction to scramjets technology, we will discuss one of the key challenges in high-speed propulsion design, namely the fuel injector design. Attempts at improving fuel injection to enhance fuel-air mixing while simultaneously reducing engine thrust losses have received a great deal of attention over the years. Although some amount of loss is thermodynamically unavoidable and occurs due to the desired effect of molecular mixing of fuel and air, any losses beyond this minimum required amount reduces the thrust potential of the engine. The Enhanced Injection and Mixing Project (EIMP) at NASA Langley Research Center aims at addressing this design challenge by analyzing the performance of a number of baseline and novel fuel injectors for high-speed applications. The project leverages computational and experimental capabilities with the goal to investigate scramjet fuel injection and mixing physics, improve our understanding of the underlying physical process, and develop enhancement strategies relevant to hypersonic flight Mach numbers. The talk will discuss the current computational and experimental research approaches using one of the baseline injectors considered by the EIMP as an example.

Scramjet↗

NASA NTRS2003

A Computational Study of the Abrupt Wing Stall (AWS) Characteristics for Various Fighter Jets: F/A-18E and F-16C - Part 1

Steady state Computational Fluid Dynamic (CFD) simulations are used to gain an understanding of the physics behind the Abrupt Wing Stall (AWS) phenomenon and to arrive at static Figures of Merit (FOMs). Navier-Stokes simulations are conducted using the NASA Langley developed TetrUSS simulation suite which is based on tetrahedral, unstructured grids. The physics of the AWS phenomenon is understood by comparing CFD simulation results on two aircraft; a pre-production F/A-18E configuration which exhibits AWS phenomenon under certain geometric and flow conditions, and an F-16C aircraft configuration that does not. The CFD code is first validated against two sets of experimental data to build confidence in its use for the problem of AWS. An attempt is then made to understand the possible causes of AWS by analyzing and comparing the detailed flow fields between the two configurations under a variety of flow conditions. Based on this approach, a number of static Figures of Merit are developed to predict the potential existence of AWS. The FOMs include the break in the lift and wing root bending moment versus angle-of-attack (AoA) curves and the rate of change of sectional lift with respect to AoA. A companion paper, in Part II, describes a similar CFD study on two other aircraft, the AV-8B Harrier and F/A-18C. Results from both these studies, as well as other CFD studies conducted as part of the AWS program are used to recommend a CFD procedure for predicting the existence of AWS in future aerospace designs.

Parikh, Paresh↗

NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

Simultaneous Localization and Mapping (SLAM) is a promising technique that provides localization information and precise mapping of the physical environment without having much prior knowledge of the surroundings. SLAM may have a vital role in aeronautics and aerospace, where vehicles and aircraft must operate in complex environments with traditional localization services that may be degraded or unavailable. This paper compares several pre-canned 3D SLAM algorithms based on vision and LiDAR, namely ORB-SLAM, ORB-SLAM2, LOAM, A-LOAM, and F-LOAM on NASA UAS (Unmanned Aircraft System) flight test data. The NASA ARC UAS flight test demonstrates preliminary SLAM algorithm results, which serve as a stepping stone to simulated AAM (Advanced Air Mobility) concepts. Conducting AFRC UAS flight test for simulated AAM approach and landing with SLAM algorithms provides an Alternative Precision Navigation and Timing solution based on distributed landmarks and fiducials in the landing zone. These algorithms use the telemetry data as ground truth for a baseline comparison. The criteria of the performance comparison include robustness, accuracy, re-localization, response to environmental changes, and real-time effectiveness, which are currently qualitative but to be quantitative in the future.

computer vision↗

NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

computer vision↗

DOE OSTI2026

Benchmark for two-dimensional large scale coherent structures in partially magnetized E × B plasmas—community collaboration & lessons learned

Low-temperature plasmas (LTPs) are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a vital tool for uncovering new physical phenomena and guiding technological development. Code benchmarking remains crucial for verifying implementations and evaluating performance. This work continues the Landmark benchmark initiative, a series specifically designed to support the verification of LTP codes. In this study, seventeen simulation codes from a collaborative community of nineteen international institutions modeled a partially magnetized E × B Penning discharge. The emergence of large scale coherent structures, or rotating plasma spokes, endows this configuration with an enormous range of time scales, making it particularly challenging to simulate. The codes showed excellent agreement on the rotation frequency of the spoke as well as key plasma properties, including time-averaged ion density, plasma potential, and electron temperature profiles. Achieving this level of agreement came with challenges, and we share lessons learned on how to conduct future benchmarking campaigns. Comparing code implementations, computational hardware, and simulation runtimes also revealed interesting trends, which are summarized with the aim of guiding future plasma simulation software development.

benchmarking↗