SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
During the past decade, Radar Polarimetry has established itself as a mature science and advanced technology in high resolution POL-SAR imaging, image target characterization and selective image feature extraction.
In regions lacking direct observations, the assimilation of radiances from infrared and microwave sounders is the primary method for characterizing the atmosphere in the analysis process. In recent years, technological advances have led to the launching of more advanced sounders, particularly in the thermal infrared spectrum. With the advent of these hyperspectral sounders, the amount of data available for the analysis process has and will continue to be dramatically increased. However, the utilization of infrared radiances in variational assimilation can be problematic in the presence of clouds; specifically the assessment of the presence of clouds in an instantaneous field of view (IFOV) and the contamination in the individual channels within the IFOV. Various techniques have been developed to determine if a channel is contaminated by clouds. The work presented in this paper and subsequent presentation will investigate traditional techniques and compare them to a new technique, the C02 sorting technique, which utilizes the high spectral resolution of the Atmospheric Infrared Sounder (AIRS) within the framework of the Gridpoint Statistical Interpolation (GSI) 3DVAR system. Ultimately, this work is done in preparation for the assessment of short-term forecast impacts with the regional assimilation of AIRS radiances within the analysis fields of the Weather Research and Forecast Nonhydrostatic Mesoscale Model (WRF-NMM) at the NASA Short-term Prediction Research and Transition (SPORT) Center.
The Wide-Field Imaging Interferometry Testbed (WIIT) at NASA's Goddard Space Flight Center was designed to demonstrate the practicality and application of techniques for wide-field spatial-spectral ("double Fourier") interferometry. WIIT is an automated system, and it is now producing substantial amounts of high-quality data from its state-of-the-art operating environment, Goddard's Advanced Interferometry and Metrology Lab. In this paper, we discuss the characterization and operation of the testbed and present the most recent results. We also outline future research directions. A companion paper within this conference discusses the development of new wide-field double Fourier data analysis algorithms.
Jupiter is one of the two most studied planets other than Earth in our Solar System. It is the largest, fastest rotating, has the strongest magnetic field, and an incredibly diverse set of satellites, most prominent of which are the four Galilean satellites discovered in 1610. Io, Europa, Ganymede and Callisto encompass some of the most bizarre environments known in the solar system, from Io, the most volcanically active and perhaps the most inhospitable body known, to Europa, currently thought to be the most likely extraterrestrial abode for habitability, to Ganymede, which is larger than Mercury, and Callisto, which has the oldest surface known in the solar system with the widest array of crater morphologies known. One of the premier areas of scientific return in solar system research in the past 15 years, due in large part to the Galileo mission and observations by the Hubble Space Telescope, has been a remarkable increase in our knowledge about these satellites. Discoveries have been made of tenuous molecular oxygen atmospheres on Europa and Ganymede, a magnetic field and accompanying auroral emissions at the poles of Ganymede, and of ozone and sulfur dioxide embedded in the surfaces of Europa, Ganymede and Callisto. Io's unusual sulfur dioxide atmosphere, including its volcanic plumes and strong electrodynamic interaction with magnetospheric plasma, has finally been quantitatively characterized. This talk will present highlights from the recent discoveries and advances in our understanding of these fascinating objects.
One of the most eagerly studied questions upon initial return of lunar samples was whether significant amounts of organic compounds, including amino acids, were present. Analyses during the 1970s produced only tentative and inconclusive identifications of indigenous amino acids. Those analyses were hampered by analytical difficulties including relative insensitivity to certain compounds, the inability to separate chiral enantiomers, and the lack of compound-specific isotopic measurements, which made it impossible to determine whether the detected amino acids were indigenous to the lunar samples or the results of contamination. Numerous advances have been made in instrumentation and methodology for amino acid characterization in extraterrestrial samples in the intervening years, yet the origin of amino acids in lunar regolith samples has been revisited only once for a single lunar sample, (3) and remains unclear. Here, we present initial data from the analyses of amino acid abundances in 12 lunar regolith samples. We discuss these abundances in the context of four potential amino acid sources: (1) terrestrial biological contamination; (2) contamination from lunar module (LM) exhaust; (3) derivation from solar windimplanted precursors; and (4) exogenous delivery from meteorites.
Ultrasound-based nondestructive evaluation (NDE) is a common technique for damage detection in composite materials. There is a need for advanced NDE that goes beyond damage detection to damage quantification and characterization in order to enable data driven prognostics. The damage types that exist in carbon fiber-reinforced polymer (CFRP) composites include microcracking and delaminations, and can be initiated and grown via impact forces (due to ground vehicles, tool drops, bird strikes, etc), fatigue, and extreme environmental changes. X-ray microfocus computed tomography data, among other methods, have shown that these damage types often result in voids/discontinuities of a complex volumetric shape. The specific damage geometry and location within ply layers affect damage growth. Realistic threedimensional NDE and structural health monitoring (SHM) simulations can aid in the development and optimization of damage quantification and characterization techniques. This paper is an overview of ongoing work towards realistic NDE and SHM simulation tools for composites, and also discusses NASA's need for such simulation tools in aeronautics and spaceflight. The paper describes the development and implementation of a custom ultrasound simulation tool that is used to model ultrasonic wave interaction with realistic 3-dimensional damage in CFRP composites. The custom code uses elastodynamic finite integration technique and is parallelized to run efficiently on computing cluster or multicore machines.
Upper stage and in-space liquid rocket engines are optimized for performance through the use of high area ratio nozzles to fully expand combustion gases to low exit pressures increasing exhaust velocities. Due to the large size of such nozzles and the related engine performance requirements, carbon-carbon (C/C) composite nozzle extensions are being considered for use in order to reduce weight impacts. NASA and industry partner Carbon-Carbon Advanced Technologies (C-CAT) are working towards advancing the technology readiness level of large-scale, domestically-fabricated, C/C nozzle extensions. These C/C extensions have the ability to reduce the overall costs of extensions relative to heritage metallic and composite extensions and to decrease weight by 50%. Material process and coating developments have advanced over the last several years, but hot fire testing to fully evaluate C/C nozzle extensions in relevant environments has been very limited. NASA and C-CAT have designed, fabricated and hot fire tested multiple subscale nozzle extension test articles of various C/C material systems, with the goal of assessing and advancing the manufacturability of these domestically producible materials as well as characterizing their performance when subjected to the typical environments found in a variety of liquid rocket and scramjet engines. Testing at the MSFC Test Stand 115 evaluated heritage and state-of-the-art C/C materials and coatings, demonstrating the capabilities of the high temperature materials and their fabrication methods. This paper discusses the design and fabrication of the 1.2k-lbf sized carbon-carbon nozzle extensions, provides an overview of the test campaign, presents results of the hot fire testing, and discusses potential follow-on development work.
The emergence of small Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) vehicles has motivated the need to acoustically characterize the rotors found on these vehicle platforms. Hover chamber tests of small rotors are beneficial in assessing the noise impact of UAS, and potentially larger AAM vehicles. Various experiments have been conducted in the NASA Langley Small Hover Anechoic Chamber (SHAC), formerly known as the Small Anechoic Jet Facility (SAJF), in order to investigate the noise and performance of small rotors. One of these tests was that of an “ideally twisted rotor”, which was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor was fabricated using state-of-the-art rapid prototyping and tested in the SHAC. Aerodynamic load and acoustic data were acquired across a range of rotation rates and rotor collective settings. Both tonal and broadband components were identified in the acoustic data, with broadband noise being a prominent contributor to the overall rotor system noise.
Starshades are a leading technology to enable the direct detection and spectroscopic characterization of Earth- like exoplanets. Critical starshade technologies are currently being advanced through the S5 Project and at the Princeton starshade testbed. We report on the status of Milestone 2 of the S5 Project, optical model validation. We present results from optical experiments of starshades with intentional perturbations built into their design. These perturbations are representative of the type of perturbations possible in a flight design and serve as points of validation for dffraction models and error budgets. We show experimental results for two perturbed shapes, a mask with all petals shifted radially outward by 5 um and a mask with shallow sine waves built into two petals. We compare these data to outputs of the optical model and demonstrate better than 25% agreement. We also present images taken in crossed polarized light and use those data to constrain physical parameters of the optical edge. Bringing in previously obtained results for other perturbed shapes, we show an agreement between experiment and model of better than 25% and argue that this satisfies the Milestone 2 criteria.
This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models.
The overall goal of the NASA Urban Air Mobility Noise Working Group (UNWG) Ground and Flight Test Subgroup (SG2) is to develop a research measurement protocol, or set of guidelines, which can be used to adequately quantify the Urban Air Mobility (UAM) community noise impact via the creation of acoustic profiles that describe the vehicle source emission characteristics. This document lays out a measurement protocol for acquiring data suitable for the development of compact noise hemispheres that characterize the source acoustic emissions from full-scale UAM or Advanced Air Mobility (AAM) vehicles in outdoor flight. It also provides a narrative describing the numerous aspects of outdoor flight test design and execution that will hopefully prove useful to flight test engineers and practitioners.
Silicon carbide / silicon carbide ceramic matrix composites (SiC/SiC CMCs) are structural ceramics that are well-suited for the extreme environment conditions of aerospace applications largely due to their low weight, creep resistance, damage tolerance, and high specific strength. In CMCs, the initiation and evolution of damage is influenced by a number of factors including characteristics of the constituent landscape (porosity, interfacial properties, and geometric distribution of CMC constituents), thermo-mechanical loading parameters, and environmental conditions. However, much is still unknown about these factors and the interactions between them. In order to accurately predict the lifetimes of these advanced composites, it is critical to understand the evolution of damage and to characterize which early damage mechanisms (and their relationship to key microstructural features) subsequently lead to crack coalescence and macroscopic failure. This research focuses on the use of a multi-modal, experimental approach to examine the relative activity of surface and subsurface damage mechanisms in CMCs. The impact of fabrication choices on the evolution of damage to final failure, and the influence of constituent architecture on early damage mechanisms, are investigated. This approach combines acoustic emission (AE) with microscale deformation tracking via digital image correlation inside a scanning electron microscope (SEM-DIC). The potential application of this combined approach towards characterization of damage in SiC/SiC CMCs under more complex testing conditions is explored.
[This is a 90% discussion draft.] This is the third Synthesis Memorandum funded by the U.S. Army Corps of Engineers and developed for the Columbia Estuary Ecosystem Restoration Program (CEERP) on the topic of habitat restoration in the Columbia River Estuary (CRE) from Bonneville Dam to the river mouth. While the first two were developed by PNNL and NOAA without the benefit of stakeholder participation, for the current memo, two key activities were initiated: (1) review, by the Expert Regional Technical Group (ERTG), of status and trends monitoring and action effectiveness monitoring funded by CEERP, and (2) a workshop including representatives of the Bonneville Power Administration and the U.S. Army Corps of Engineers (the action agencies [AAs]), the National Oceanic and Atmospheric Administration (NOAA), major research agencies contributing to CEERP, and sponsors who implement CEERP restoration actions. A systematic literature review was conducted using ClarivateTM Web of ScienceTM database. The topics of interest for CRE relevant research included salmon ecology, physical processes, and wetland habitats, and therefore required the use of broad search terms. Our final search criteria included a combination of Boolean operators and an approach to combine different sets of search terms. The final search result yielded 669 records. The records were classified by groups and assigned to the relevant disciplinary expert for review. The review identified substantive advances in understanding the provision of salmon habitat functions through spatiotemporally dynamic physical and ecological processes, and the use of CRE habitats by numerous stocks of juvenile salmon. It also uncovered heretofore unincorporated historical documentation of riparian habitats across the CRE. The characterization of the structural components of floodplain habitat including plant associations and channel networks has advanced considerably, together with the understanding of seasonal changes and long-term trends. The relative influence of salmon-habitat location in the CRE as compared with temporal factors, mainly season, has been well described, which affects the prioritization of restoration. Stressors on the ecosystem and fish, and the drivers of these stressors, have been more carefully elucidated and predictive models are in various stages of development. The vision, aims, and design of restoration projects have advanced together with methods of data collection, analysis, and modeling that have seen substantial improvements. Experiments intended to inform the design of restoration projects are underway or have been completed. An important outstanding area of research that has lagged behind the advances in fundamental understanding of the ecosystem and salmon habitat functions remains the peer-reviewed documentation of the outcomes of restoration for both habitats and fish functions.
When construction of Space Station Freedom reaches the Permanent Manned Capability (PMC) stage, the Water Recovery and Management Subsystem will be fully operational such that (distilled) urine, spent hygiene water, and humidity condensate will be reclaimed to provide water of potable quality. The reclamation technologies currently baselined to process these waste waters include adsorption, ion exchange, catalytic oxidation, and disinfection. To ensure that the baseline technologies will be able to effectively remove those compounds presenting a health risk to the crew, the National Research Council has recommended that additional information be gathered on specific contaminants in waste waters representative of those to be encountered on the Space Station. With the application of new analytical methods and the analysis of waste water samples more representative of the Space Station environment, advances in the identification of the specific contaminants continue to be made. Efforts by the Water and Food Analytical Laboratory at JSC were successful in enlarging the database of contaminants in humidity condensate. These efforts have not only included the chemical characterization of condensate generated during ground-based studies, but most significantly the characterization of cabin and Spacelab condensate generated during Shuttle missions. The analytical results presented in this paper will be used to show how the composition of condensate varies amongst enclosed environments and thus the importance of collecting condensate from an environment close to that of the proposed Space Station. Although advances were made in the characterization of space condensate, complete characterization, particularly of the organics, requires further development of analytical methods.
Focal Area(s): (1) We put forward the concepts of data assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization and unsupervised learning applied to downscale information within Earth System Models (ESMs). (2) We discuss predictive modeling through the use of AI techniques and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection) to improve the characterization of extreme hydroclimate events in ESMs. The AI-based models will run five-six order of magnitude times faster, yet will provide similar accuracy, allowing us to provide range bounds on uncertainty faster and thus enabling faster extreme event identification. (3) Further, we consider the insight gleaned from complex data (observed/simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI to improve the characterization of extreme hydroclimate events in ESMs.
The analysis of environmental samples is a critical component of nuclear compliance verification and safeguards activities. While the associated particle analyses have benefitted from recent advances in the production of actinide-bearing particulates with uniform and well-characterized particle size, material phase, and isotopic ratios to serve as reference materials for calibration and interlaboratory comparisons, there is an outstanding need for surrogate environmental samples, which resemble field-collected samples, with the aforementioned reference particulates to support future nuclear compliance verification exercises and method development. This effort seeks to leverage the recent advances in tailored reference particle production to generate surrogate environmental swipe samples via parallel production techniques (direct and indirect) which are uniquely suited to the hydrothermal and aerosol-based synthesis routes developed at PNNL and SRNL, respectively. PNNL’s hydrothermal particle production method was used to generate surrogate reference particles for the indirect production of test swipes.
The preliminary assessment of the performance and safety of advanced reactors, as well as the identification of research and development needs, rely on computer simulations due to the lack of operational experience. Those simulations should be based on verified and validated computational tools, calculation schemes, and nuclear data libraries, and should be accompanied of a proper characterization of the involved uncertainties, providing confidence in the computational-based predictions. Thus, sensitivity and uncertainty studies, together with integral experiments, play an essential role in that process. Sensitivities are then a critical element and guidelines about how to produce accurate enough sensitivities depending on the subsequent analyses to be performed are of interest. The present study addresses the sensitivities biases arising from the use of different nuclear data libraries, computational methods and the assumption of modelling simplifications. Not only sensitivities for multiplication factor but also for safety-relevant reactivity responses have been analyzed. In the study, propagated uncertainties are also included for the considered parameters to illustrate the impact of the sensitivity profiles obtained for each case on the final uncertainty. Then, relevant recommendations are given for sensitivity analyses of highly complex systems. (authors)
Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.