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At least 217 records · Page 12

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NASA NTRS2022

Using Atmospheric Trace Gas Vertical Profiles to Evaluate Model Fluxes: A Case Study of Arctic-Cap Observations and Geos Simulations for the ABoVE Domain

Accurate estimates of carbon–climate feedbacks require an independent means for evaluating surface flux models at regional scales. The altitude-integrated enhancement (AIE) derived from the Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of this bulk quantity for surface flux model evaluation. This bulk quantity leverages background mole fraction values from the middle free troposphere, is agnostic to uncertainties in boundary layer height, and can be derived from model estimates of mole fractions and vertical gradients. To demonstrate the utility of the bulk quantity, six airborne profiling surveys of atmospheric carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) throughout Alaska and northwestern Canada between April and November 2017 were completed as part of NASA’s Arctic–Boreal Vulnerability Experiment (ABoVE). The Arctic-CAP sampling strategy involved acquiring vertical profiles of CO2, CH4, and CO from the surface to 5 km altitude at 25 sites around the ABoVE domain on a 4- to 6-week time interval. All Arctic-CAP measurements were compared to a global simulation using the Goddard Earth Observing System (GEOS) modeling system. Comparisons of the AIE bulk quantity from aircraft observations and GEOS simulations of atmospheric CO2, CH4, and CO highlight the fidelity of the modeled surface fluxes. The model–data comparison over the ABoVE domain reveals that while current state-of-the-art models and flux estimates are able to capture broad-scale spatial and temporal patterns in near-surface CO2 and CH4 concentrations, more work is needed to resolve fine-scale flux features that are captured in CO observations

CO2↗

NASA NTRS2022

The Influence of Recent and Future Climate Change on Spring Arctic Cyclones

In recent decades, the Arctic has experienced rapid atmospheric warming and sea ice loss, with an ice-free Arctic projected by the end of this century. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, and the local and global climate. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses high resolution (4 km), regional modeling techniques and downscaled global climate reconstructions and projections to examine how recent and future climatic changes alter cyclone behavior. Results suggest that recent climate change has not yet had an appreciable effect on Arctic cyclone characteristics. However, future sea ice loss and increasing surface temperatures drive large increases in the near-surface temperature gradient, sensible and latent heat fluxes, and convection during cyclones. The future climate can alter cyclone trajectories and increase and prolong intensity with greatly augmented wind speeds, temperatures, and precipitation. Such changes in cyclone characteristics could exacerbate sea ice loss and Arctic warming through positive feedbacks. The increasing extreme nature of these weather events has implications for local ecosystems, communities, and socio-economic activities.

Chelsea L Parker↗

NASA NTRS1973

Theoretical autophotogrammetry. I - The method of the photometric potential

The present work presents preliminary efforts at a mathematical formulation of a photogrammetric method suitable for computerized processing. A theory is derived for the extraction of surface topography from stereometric pairs of photographs. The theory can be applied to either convergent or near-orthographic-projection stereo. Scene brightness is treated as a scalar function defined on a general surface embedded in ordinary three-dimensional space (the actual topography). Correspondence of points is based on adjustments leading to photometric equivalence, while the adjustments are based on the local value of the photometric gradient.

Wildey, R. L.↗

NASA NTRS2009

Combined MODIS/AMSR-E SST Composites for Regional Weather Applications

Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.

Jedlovec, Gary↗

NASA NTRS2026

AC and DC Fault Management for Megawatt Electrified Aircraft Electrical Powertrains Task 3: Lifetime and Reliability of Electrical Insulators

This research project was a collaborative investigation between researchers at the RTX Technology Research Center (RTRC) and the University of Texas at Austin and made a significant contribution to enabling electric aircraft. The transport of electric power between the points of generation and use requires power cables. These cables must be smaller, lighter and provide a more predictable life than power cables used in stationary applications. Consequently, this investigation provided heretofore unavailable information supporting the safety and reliability of smaller lighter power cables for electrified aircraft. In addition, the research identified key additional engineering data needed to support quantitative reliability assessments. Important advances included: • Demonstrated that at least one manufacturer can make a novel, smaller, lighter power cable that is free from serious defects. • Developed and published an appropriate analytical construct to describe the life of this novel cable. This is a necessary step for use in aviation where the understanding of remaining life is critical. • Demonstrated thermal-mechanical aging that suggested 1000+ flights before the thermal-mechanical processes produced defects large enough that the defect growth was accelerated electrically. • Showed that electrical aging took place at two rates. The first possibly lasting weeks to months and the second possibly days to weeks. If robust, this provides a good diagnostic for cable replacement. • Demonstrated that the traditional electrical testing of cable materials using manufactured voids can be misleading due to the size of the voids. Emerging laser drilling technology permitted demonstration that the physics of failure in realistically small voids is different from that in the unrealistically large voids used in earlier research, which is very important for high-quality, high-performance, small aircraft cables. Although this project represents a significant contribution to the specifics of cable aging in the aircraft environment, important additional research remains to be completed, including: • Non-uniform thermal cycling by applying the heat from the center conductor to maximize thermal stress next to the core area where the electric gradient is the strongest. This builds on the uniform thermal cycling that has been completed. • The augmentation of the thermal-mechanical failure rate by electrical processes. Better understanding of these time constants strongly affects the ability to predict life. • Termination design: Terminations provide not only electrical reflection potential, but a location for a series arc fault and an area where ozone can diffuse into the center conductor and negatively affect cable insulation. • The abrasion and ozone resistance of the cable jacket. • Pressure cycling as an accelerant of thermal, mechanical, and/or electrical aging. • Possible methods for online PD detection and offline PD localization

model↗

NASA NTRS1994

Development of the NASA/FLAGRO computer program for analysis of airframe structures

The NASA/FLAGRO (NASGRO) computer program was developed for fracture control analysis of space hardware and is currently the standard computer code in NASA, the U.S. Air Force, and the European Agency (ESA) for this purpose. The significant attributes of the NASGRO program are the numerous crack case solutions, the large materials file, the improved growth rate equation based on crack closure theory, and the user-friendly promptive input features. In support of the National Aging Aircraft Research Program (NAARP); NASGRO is being further developed to provide advanced state-of-the-art capability for damage tolerance and crack growth analysis of aircraft structural problems, including mechanical systems and engines. The project currently involves a cooperative development effort by NASA, FAA, and ESA. The primary tasks underway are the incorporation of advanced methodology for crack growth rate retardation resulting from spectrum loading and improved analysis for determining crack instability. Also, the current weight function solutions in NASGRO or nonlinear stress gradient problems are being extended to more crack cases, and the 2-d boundary integral routine for stress analysis and stress-intensity factor solutions is being extended to 3-d problems. Lastly, effort is underway to enhance the program to operate on personal computers and work stations in a Windows environment. Because of the increasing and already wide usage of NASGRO, the code offers an excellent mechanism for technology transfer for new fatigue and fracture mechanics capabilities developed within NAARP.

Forman, R. G.↗

NASA NTRS2002

Cirrus Parcel Model Comparison Phase 2

The Cirrus Parcel Model Comparison (CPMC) project, a project of the GEWEX Cloud System Study Working Group on cirrus clouds (GCSS WG2), is an international effort to advance our knowledge of numerical simulations of cirrus cloud initiation. This project was done in two phases. In Phase 1 of CPMC, the critical components determining the predicted cloud microphysical properties were identified using parcel models in which the aerosol and ice crystal size distributions are explicitly resolved, the formulation of the homogeneous freezing of aqueous solution droplets, especially the gradient of nucleation rate with respect to solution concentration; aerosol growth modeling; and the mass accommodation coefficient of water vapor on ice surface (the deposition coefficient). In Phase 1, all simulations were conducted using a given background aerosol distribution. To complete the comparison study, participant model responses to a range of background aerosol distributions are investigated in Phase 2.

Lin, Ruei-Fong↗

NASA NTRS1992

Microstructural development during directional solidification of peritectic alloys

Despite the widespread commercial use of peritectic alloys (e.g., steels, brass, bronze, intermetallic compounds, Co based superalloys and A3B type superconductors), the characterization of the microstructural development during directional solidification of peritectics has historically lagged behind similar efforts directed towards other types of binary invariant reactions such as eutectic or monotectic. A wide variety of possible microstructures has been shown to form in peritectics depending upon the imposed temperature gradient, G, the solidification velocity, V, as well as the presence or absence of convection in the melt. This has important technological implications since many commercially important alloys exhibit peritectics and processing methods such as casting and welding often involve widely changing conditions. It has been the aim of this project to examine, in a systematic fashion, both experimentally and theoretically, the influence of gravitationally driven convection on segregation and microstructural development during solidification in peritectic systems under terrestrial conditions. The scientific results of the project will be used to establish ground based data in support of a meaningful microgravity flight experiment.

Lograsso, Thomas A.↗

NASA NTRS2021

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the-art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts. The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners. However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen Michael Middleton↗

NASA NTRS2018

An Active Subspace Method for Accelerating Convergence in Delaunay-Based Optimization via Dimension Reduction

Delaunay-based derivative-free optimization, ∆DOGS, is an efﬁcient and provably-convergent global optimization method for the problems which has computationally expensive objection function and the analytical expression for the objective function is not available. ∆-DOGS is a novel optimization scheme in the family of response surface methods (RSMs); however, it suffers from the curse of dimensionality since the computational cost increases dramatically as the number of design parameters increases. As a result, the number of design parameters in ∆-DOGS algorithm is relatively low (n.10). To avoid such problems, this paper proposes a combination of derivative-free optimization, seeking the global minimizer of an expensive and nonconvex objective function f(x) and active subspace method, detecting the directions of the most variability using evaluations of the gradient. The contribution of other directions to the objective function is bounded by a sufﬁciently small constant. This new algorithm iteratively applied Delaunay-based derivative-free optimization to seek the minimizer on the d-dimensional active subspace that has most function variation. Inverse mapping is needed to project data from active subspace to full-model for evaluating function values. This task is overcome by solving an inequality constrained problem that curves the response surface of the objective function. The test results show that this strategy is effective on a handful of optimization problems.

Bewley, Thomas R.↗

NASA NTRSDate not supplied

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts.1,2 The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners.1 However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen M Middleton↗

NASA NTRS2016

Rheological Properties of Quasi-2D Fluids in Microgravity

Freely suspended smectic films of sub-micrometer thickness and lateral extensions of several millimeters are used to study thermally driven convection and diffusion in the film plane. The experiments were performed during a six minute microgravity phase of a TEXUS suborbital rocket flight (Texus 52, launched April 27, 2015). The project served as a preliminary test for a planned ISS Experiment with liquid crystal films (OASIS), and in addition it provided new experimental data on smectic films exposed to in-plane thermal gradients.We find an attraction of the smectic material towards the cold edge of the film in a temperature gradient, similar to a Soret effect. This process is reversed when this edge is heated up again. Thermal convection driven by two thermocontacts in the film is practically absent, even at temperature gradients up to 10 Kmm, thermally driven convection sets in when the hot post reaches the transition temperature to the nematic phase.An additional experiment was performed under microgravity conditions to test the stability of liquid crystal bridges in different smectic phases.

microgravity↗

NASA NTRS1992

Effects of solar radiation pressure torque on the rotational motion of an artificial satellite

The motion of an artificial satellite about its center of mass is studied considering torques due to the gravity gradient and direct solar radiation pressure. A model for direct solar radiation torque is derived for a circular cylindrical satellite. An analytical solution is obtained by the method of variation of the parameters. This solution shows that the angular variables have secular variation but that the modulus of the rotational angular momentum, the projection of rotational angular momentum on the z axis of the moment of inertia and inertial axis z, suffer only periodic variations. Considering a hypothetical artificial satellite, a numerical application is demonstrated.

Zanardi, Maria Cecilia F. P. S.↗

NASA NTRS2001

Active Flow Control For Inlets

This presentation describes the progress to date of the Small-Scale Demonstration for the Active Flow Control element of the Propulsion Airframe Integration Project. The goal of this work package is to demonstrate at small scale the ability to improve pressure recovery and distortion in an S-inlet with boundary layer ingestion representative of a Blended Wing Body (BWB) configuration. The effectiveness of several active and passive devices to control flow in an adverse pressure gradient with secondary flows present was evaluated in the Langley 15-Inch Low-Turbulence Tunnel. In this study, passive microvanes, microbumps, and piezoelectric synthetic jets were evaluated for their flow control characteristics using surface static pressures, flow visualization, and 3D Stereo Digital Particle Image Velocimetry. The microvanes imparted a higher level of vorticity to the flow than any of the other devices tested. Alternative actuator concepts are being pursued to support the Small-Scale Demonstration Level 1 milestone in FY03.

Gorton, Susan A.↗

NASA NTRS1997

Noise and Dynamical Pattern Selection in Solidification

The overall goal of this project was to understand in more detail how a pattern-forming system can adjust its spacing. "Pattern-forming systems," in this context, are nonequilibrium contina whose state is determined by experimentally adjustable control parameter. Below some critical value of the control system then has available to it a range of linearly stable, spatially periodic steady states, each characterized by a spacing which can lie anywhere within some band of values. These systems like directional solidification, where the solidification front is planar when the ratio of growth velocity to thermal gradient is below its critical value, but takes on a cellular shape above critical. They also include systems without interfaces, such as Benard convection, where it is the fluid velocity field which changes from zero to something spatially periodic as the control parameter is increased through its critical value. The basic question to be addressed was that of how the system chooses one of its myriad possible spacings when the control parameter is above critical, and in particular the role of noise in the selection process. Previous work on explosive crystallization had suggested that one spacing in the range should be preferred, in the sense that weak noise should eventually drive the system to that spacing. That work had also suggested a heuristic argument for identifying the preferred spacing. The project had three main objectives: to understand in more detail how a pattern-forming system can adjust its spacing; to investigate how noise drives a system to its preferred spacing; and to extend the heuristic argument for a preferred spacing in explosive crystallization to other pattern-forming systems.

Kurtze, Douglas A.↗

NASA NTRS2002

Robust Low Cost Liquid Rocket Combustion Chamber by Advanced Vacuum Plasma Process

Next-generation, regeneratively cooled rocket engines require materials that can meet high temperatures while resisting the corrosive oxidation-reduction reaction of combustion known as blanching, the main cause of engine failure. A project was initiated at NASA-Marshal Space Flight Center (MSFC) to combine three existing technologies to build and demonstrate an advanced liquid rocket engine combustion chamber that would provide a 100 mission life. Technology developed in microgravity research to build cartridges for space furnaces was utilized to vacuum plasma spray (VPS) a functional gradient coating on the hot wall of the combustion liner as one continuous operation, eliminating any bondline between the coating and the liner. The coating was NiCrAlY, developed previously as durable protective coatings on space shuttle high pressure fuel turbopump (HPFTP) turbine blades. A thermal model showed that 0.03 in. NiCrAlY applied to the hot wall of the combustion liner would reduce the hot wall temperature 200 F, a 20% reduction, for longer life. Cu-8Cr-4Nb alloy, which was developed by NASA-Glenn Research Center (GRC), and which possesses excellent high temperature strength, creep resistance, and low cycle fatigue behavior combined with exceptional thermal stability, was utilized as the liner material in place of NARloy-Z. The Cu-8Cr-4Nb material exhibits better mechanical properties at 650 C (1200 F) than NARloy-Z does at 538 C (1000 F). VPS formed Cu-8Cr-4Nb combustion chamber liners with a protective NiCrAlY functional gradient coating have been hot fire tested, successfully demonstrating a durable coating for the first time. Hot fire tests along with tensile and low cycle fatigue properties of the VPS formed combustion chamber liners and witness panel specimens are discussed.

Holmes, Richard↗

NASA NTRS2012

Peak Seeking Control for Reduced Fuel Consumption with Preliminary Flight Test Results

The Environmentally Responsible Aviation project seeks to accomplish the simultaneous reduction of fuel burn, noise, and emissions. A project at NASA Dryden Flight Research Center is contributing to ERAs goals by exploring the practical application of real-time trim configuration optimization for enhanced performance and reduced fuel consumption. This peak-seeking control approach is based on Newton-Raphson algorithm using a time-varying Kalman filter to estimate the gradient of the performance function. In real-time operation, deflection of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of a modified F-18 are directly optimized, and the horizontal stabilators and angle of attack are indirectly optimized. Preliminary results from three research flights are presented herein. The optimization system found a trim configuration that required approximately 3.5% less fuel flow than the baseline trim at the given flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These preliminary results show the algorithm has good performance and is expected to show similar results at other flight conditions and aircraft configurations.

Brown, Nelson↗

NASA NTRS2024

Deciphering the Spectra of Flowers to Map Landscape-scale Blooming Dynamics

Like leaves, floral coloration is driven by inherent optical properties, which are determined by pigments, scattering structure, and thickness. However, establishing the relative contribution of these factors to canopy spectral signals is usually limited to in-situ observations. Modeling flowering dynamics (e.g., blooming duration, spatial distribution) at the landscape scale may reveal insights into ecological processes and phenological adaptations to environmental changes. Multitemporal visible to shortwave infrared (VSWIR) imaging spectroscopy observations are especially suited for such efforts. Reflectance in this spectral range is sensitive to major flower pigments, flowering phenology traces, and biophysical differences between flowers and other plant parts. We explored how flowers contribute to spectral signals using a time series of imagery from the Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) collected as part of the SBG High-Frequency Time Series (SHIFT) campaign as a case study. Airborne data were collected weekly during the spring of 2022 across two natural reserves in California. Field spectra were gathered from blooming plots at leaf, flower, and canopy levels at two time points during the campaign. The processed data was used to investigate flowering species' spectro-temporal variation and spatial distribution using Spectral Mixture Residual, Gaussian clustering techniques, and a proposed narrow-band flowering index. Linear spectral unmixing allowed the computation of the weighted contribution of four major high-variance endmembers (leaves, flowers, soil, dark) and low-variance residual signal that comprises subtle spectral features used to track biophysical processes. The reflectance residual was projected on a low principal component basis to characterize flowering clusters' variation and spatial distribution based on the Gaussian mixture model, providing an uncertainty metric to assess the results. Mapping flowering events from modeling spectro-temporal dynamics throughout the season, from pre-blooming to post-flowering stages, allowed us to identify gradient variations in spectral features within the VSWIR spectral range linked to flowering pigments. Time series of the Mixture Residual Blooming Index and the Red-Edge Normalized Difference Vegetation Index revealed specific flowering and greenness phenophases across the two main species (Coreopsis gigantea, Artemisia californica) in the flowering areas. Overall, our approach opens opportunities for future satellite monitoring of floral cycles at broader scales.

Yoseline Angel↗