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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.

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At least 415 records · Page 23

The Characterization of Deep Convective Clouds as an Invariant Calibration Target and as a Visible Calibration Technique

Deep convective clouds (DCCs) are ideal visible calibration targets because they are bright nearly isotropic solar reflectors located over the tropics and they can be easily identified using a simple infrared threshold. Because all satellites view DCCs, DCCs provide the opportunity to uniformly monitor the stability of all operational sensors, both historical and present. A collective DCC anisotropically corrected radiance calibration approach is used to construct monthly probability distribution functions (PDFs) to monitor sensor stability. The DCC calibration targets were stable to within 0.5% and 0.3% per decade when the selection criteria were optimized based on Aqua MODerate Resolution Imaging Spectroradiometer 0.65-micrometer-band radiances. The Tropical Western Pacific (TWP), African, and South American regions were identified as the dominant DCC domains. For the 0.65-micrometer band, the PDF mode statistic is preferable, providing 0.3%regional consistency and 1%temporal uncertainty over land regions. It was found that the DCC within the TWP had the lowest radiometric response and DCC over land did not necessarily have the highest radiometric response. For wavelengths greater than 1 micrometer, the mean statistic is preferred, and land regions provided a regional variability of 0.7%with a temporal uncertainty of 1.1% where the DCC land response was higher than the response over ocean. Unlike stratus and cirrus clouds, the DCC spectra were not affected by water vapor absorption.

Doelling, David R.↗

Advanced Environmental Barrier Coating Development for SiC-SiC Ceramic Matrix Composite Components

This presentation reviews the NASA advanced environmental barrier coating (EBC) system development for SiC-SiC Ceramic Matrix Composite (CMC) combustors particularly under the NASA Environmentally Responsible Aviation, Fundamental Aeronautics and Transformative Aeronautics Concepts Programs. The emphases have been placed on the current design challenges of the 2700-3000F capable environmental barrier coatings for low NOX emission combustors for next generation turbine engines by using advanced plasma spray based processes, and the coating processing and integration with SiC-SiC CMCs and component systems. The developments also have included candidate coating composition system designs, degradation mechanisms, performance evaluation and down-selects; the processing optimizations using TriplexPro Air Plasma Spray Low Pressure Plasma Spray (LPPS), Plasma Spray Physical Vapor Deposition and demonstration of EBC-CMC systems. This presentation also highlights the EBC-CMC system temperature capability and durability improvements under the NASA development programs, as demonstrated in the simulated engine high heat flux, combustion environments, in conjunction with high heat flux, mechanical creep and fatigue loading testing conditions.

CMAS↗

Cluster Analysis of IRIS Spectroscopic Line Profiles and SDO/AIA EUV Emission in Observations and RMHD Simulations of the Solar Atmosphere

Spatially-resolved observations from the IRIS and SDO/AIA satellites, especially when coupled with realistic 3D RMHD simulations, are a powerful tool for analysis of processes in the solar chromosphere, transition region, and corona. However, the complexity of the data makes understanding the observations and modeling results difficult. In this work, we apply unsupervised clustering algorithms for analysis of observational and synthetic chromospheric Mg II h&k 2796Å&2803Å and transition region C II 1334Å&1335Å line profiles observed by IRIS, and extreme ultraviolet (EUV) emission observed by SDO/AIA, for various types of problems. The synthetic line profiles are computed for simulations of the quiescent solar atmosphere (using the StellarBox and RH1.5 codes). The K-Means clustering algorithm is applied, and the selection of an optimal number of clusters is supported by the average silhouette width technique. We discuss applications of the line profile clustering method to 1) visualization of computational and observational spectroscopic imaging data; 2) understanding of evolutionary trends and behavior patterns of quiet Sun emission and during solar flares; and 3) recognition of heating events and shock waves.

Sadykov, Viacheslav↗

Numerical and Experimental Study of Local Resin Pressure for the Manufacturing of Composite Structures and Their Effect on Porosity

Porosity can have significant impact on the mechanical performance of composite structures. The primary sources of voids during the cure of composites include air entrapped during lay-up, bag or tool leaks, and the off gassing of volatiles. Capturing the physics of void evolution during composite processing is a challenge due to the number of sources and changing phenomena that give rise to voids as the resin cures. Local changes in resin pressure due to geometric features or cure shrinkage have been experimentally linked to a higher likelihood of void formation. In this work, a preliminary model was developed to predict local resin pressure which can be used to identify regions more susceptible to porosity. Experiments were conducted to validate the model accuracy. Ultimately, this model can be used as a tool to minimize the likelihood of porosity by optimizing the material selection, part design, layup, and cure process.

Bedayat, Houman↗

Probiotics in the Space Food System: Delivery, Microgravity Effects, and the Potential Benefit to Crew Health

As mission distance and duration increase, the need grows for non‐invasive disease prevention and immunomodulation, especially given the limited medical response capability expected for these missions and the immune dysregulation documented in crew. Additionally, changes in diet, lifestyle, antibiotic usage, and the environmental stresses during spaceflight may alter crewmembers' intestinal microbiome. The addition of probiotic bacteria to the space food system is expected to confer immunostimulatory benefits on crewmembers, with the potential to counteract the immune dysregulation that has been documented in spaceflight. Based on previous studies that demonstrated unique microbiological responses to the low shear environment of spaceflight, probiotic organisms hold the potential to induce enhanced beneficial responses through mechanisms, such as beneficial interactions with human immune cells and repression of colonization of pathogens on the mucosa. The work presented here will begin to address two research gaps related to providing probiotics in spaceflight: 1) delivery, and 2) the effect of the low shear microgravity environment on probiotic attributes. The probiotic Lactobacillus acidophilus was selected for investigation due to its wide commercial use and documented benefits that include inhibition of virulence related gene expression in pathogens and mucosal stimulation of immune cells. The delivery system for probiotics has not been determined for spaceflight, where the food system is shelf stable and the lack of refrigeration prevents the use of traditional dairy delivery methods. In order to demonstrate the potential of the space food system to deliver viable probiotic bacteria to crewmembers, the probiotic L. acidophilus was packaged in high barrier flight packaging in nonfat dry milk (NFDM) or retained in commercial capsule form. Viable cells were enumerated over 8 months of storage at 22, 4, and ‐80ºC. The survival of L. acidophilus rehydrated in NFDM, in a PBS control, and directly from the capsule was also evaluated following stress challenge with simulated gastric and intestinal juices to determine the method that would deliver the most viable cells to the intestine, where they would be expected to confer beneficial effects. L. acidophilus was found to be stable to gastric and intestinal juice challenge when delivered in rehydrated NFDM, even after two hours of exposure. In comparison, L. acidophilus was reduced by 1‐5 logs when exposed to gastric and intestinal juice directly and when rehydrated in a PBS control. Shelf life data indicated that L. acidophilus would require refrigerated or frozen storage to remain viable at adequate levels over the multi‐year storage periods required for spaceflight. This study suggests that the protective effect provided by the dairy matrix, and not merely rehydration prior to consumption, extends probiotic viability and stress tolerance during storage in spaceflight and in simulated digestion conditions more adequately than a capsule. In addition to effective delivery, it is essential to understand the microgravity effects on the stress tolerances and genetic expression of probiotic bacteria to enable optimization of growth, survival, strain selection, and conferred benefits in spaceflight. In our current study, ground‐based characterization of the growth, stress response, and transcriptomic response of L. acidophilus will be accomplished using the low shear modeled microgravity (LSMMG) culture environment in the rotating wall vessel (RWV). We hypothesize that L. acidophilus will maintain or improve its growth and stress response following culture in the LSMMG environment, and that transcriptomic analysis will define the associated molecular mechanism(s), resulting in the ability to optimize strain selection.

Castro, S. L.↗

Optimizing serendipitous detections of kilonovae: cadence and filter selection

The rise of multimessenger astronomy has brought with it the need to exploit all available data streams and learn more about the astrophysical objects that fall within its breadth. One possible avenue is the search for serendipitous optical/near-infrared counterparts of gamma-ray bursts (GRBs) and gravitational-wave (GW) signals, known as kilonovae. With surveys such as the Zwicky Transient Facility (ZTF), which observes the sky with a cadence of ∼3 d, the existing counterpart locations are likely to be observed; however, due to the significant amount of sky to explore, it is difficult to search for these fast-evolving candidates. Thus, it is beneficial to optimize the survey cadence for realtime kilonova identification and enable further photometric and spectroscopic observations. We explore how the cadence of wide field-of-view surveys like ZTF can be improved to facilitate such identifications. We show that with improved observational choices, e.g. the adoption of three epochs per night on a ∼ nightly basis, and the prioritization of redder photometric bands, detection efficiencies improve by about a factor of two relative to the nominal cadence. We also provide realistic hypothetical constraints on the kilonova rate as a form of comparison between strategies, assuming that no kilonovae are detected throughout the long-term execution of the respective observing plan. These results demonstrate how an optimal use of ZTF increases the likelihood of kilonova discovery independent of GWs or GRBs, thereby allowing for a sensitive search with less interruption of its nominal cadence through Target of Opportunity programs.

methods: observational↗

Landing Site Selection with a Variable-Resolution SLAM-Refined Map

In many scenarios it is desirable for planetary landers to select or modify their landing sites autonomously during descent. We present a landing site selection algorithm which is optimized to work in conjunction with a Simultaneous Localization and Mapping system. Our algorithm selects landing sites based on site slope, roughness, and operator-defined interest. In addition, we generate guidance commands and approximate fuel consumption for the highest ranked sites. We validate our algorithm with LiDAR and inertial data gathered by a vertical take-off and landing vehicle.

Chen, Po-Ting↗

SeGRAm - A practical and versatile tool for spacecraft trajectory optimization

An implementation of the Sequential Gradient/Restoration Algorithm, SeGRAm, is presented along with selected examples. This spacecraft trajectory optimization and simulation program uses variational calculus to solve problems of spacecraft flying under the influence of one or more gravitational bodies. It produces a series of feasible solutions to problems involving a wide range of vehicles, environments and optimization functions, until an optimal solution is found. The examples included highlight the various capabilities of the program and emphasize in particular its versatility over a wide spectrum of applications from ascent to interplanetary trajectories.

Rishikof, Brian H.↗

Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e.g., biophysical characterization of crops). The findings of this study will make a significant contribution to future hyperspectral missions such as NASA's HyspIRI. Index Terms-Hyperion, field reflectance, imaging spectroscopy, HyspIRI, biophysical parameters, hyperspectral vegetation indices, hyperspectral narrowbands, broadbands.

Vegetation↗

Structural design utilizing updated, approximate sensitivity derivatives

A method to improve the computational efficiency of structural optimization algorithms is investigated. In this method, the calculations of 'exact' sensitivity derivatives of constraint functions are performed only at selected iterations during the optimization process. The sensitivity derivatives utilized within other iterations are approximate derivatives which are calculated using an inexpensive derivative update formula. Optimization results are presented for an analytic optimization problem (i.e., one having simple polynomial expressions for the objective and constraint functions) and for two structural optimization problems. The structural optimization results indicate that up to a factor of three improvement in computation time is possible when using the updated sensitivity derivatives.

Scotti, Stephen J.↗

Rapid near-optimal trajectory generation and guidance law development for single-stage-to-orbit airbreathing vehicles

General problems associated with on-board trajectory optimization, propulsion system cycle selection, and with the synthesis of guidance laws were addressed for an ascent to low-earth-orbit of an air-breathing single-stage-to-orbit vehicle. The NASA Generic Hypersonic Aerodynamic Model Example and the Langley Accelerator aerodynamic sets were acquired and implemented. Work related to the development of purely analytic aerodynamic models was also performed at a low level. A generic model of a multi-mode propulsion system was developed that includes turbojet, ramjet, scramjet, and rocket engine cycles. Provisions were made in the dynamic model for a component of thrust normal to the flight path. Computational results, which characterize the nonlinear sensitivity of scramjet performance to changes in vehicle angle of attack, were obtained and incorporated into the engine model. Additional trajectory constraints were introduced: maximum dynamic pressure; maximum aerodynamic heating rate per unit area; angle of attack and lift limits; and limits on acceleration both along and normal to the flight path. The remainder of the effort focused on required modifications to a previously derived algorithm when the model complexity cited above was added. In particular, analytic switching conditions were derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another for two cases: the case in which engine cycle operations can overlap, and the case in which engine cycle operations are mutually exclusive. The resulting guidance algorithm was implemented in software and exercised extensively. It was found that the approximations associated with the assumed time scale separation employed in this work are reasonable except over the Mach range from roughly 5 to 8. This phenomenon is due to the very large thrust capability of scramjets in this Mach regime when sized to meet the requirement for ascent to orbit. By accounting for flight path angle and flight path angle rate in construction of the flight path over this Mach range, the resulting algorithm provides the means for rapid near-optimal trajectory generation and propulsion cycle selection over the entire Mach range from take-off to orbit.

Calise, A. J.↗

Focal-plane optimization for detector noise limited performance in cryogenic Fourier transform spectrometer /FTS/ sensors

A study was performed to determine the optimum focal plane configuration including optics, filters and detector-preamplifier selection. The configuration was optimized particularly with respect to minimizing the noise level, but fabrication considerations for a cryogenic environment were also taken into account. The noise terms from source, background, detector electronics and charged particle radiation were quantitatively evaluated. It appears that noise equivalent spectral radiance less than 10 to the -11th W/sq cm per sr per kayser can be achieved between 2.5 and 20 microns.

Mcguirk, M.↗

QSPIN: A High Level Java API for Quantum Computing Experimentation

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Quantu↗

A method for determining optimum phasing of a multiphase propulsion system for a single-stage vehicle with linearized inert weight

A general analytical treatment is presented of a single-stage vehicle with multiple propulsion phases. A closed-form solution for the cost and for the performance and a derivation of the optimal phasing of the propulsion are included. Linearized variations in the inert weight elements are included, and the function to be minimized can be selected. The derivation of optimal phasing results in a set of nonlinear algebraic equations for optimal fuel volumes, for which a solution method is outlined. Three specific example cases are analyzed: minimum gross lift-off weight, minimum inert weight, and a minimized general function for a two-phase vehicle. The results for the two-phase vehicle are applied to the dual-fuel rocket. Comparisons with single-fuel vehicles indicate that dual-fuel vehicles can have lower inert weight either by development of a dual-fuel engine or by parallel burning of separate engines from lift-off.

Martin, J. A.↗

Geomagnetic field modeling by optimal recursive filtering

Data sets selected for mini-batches and the software modifications required for processing these sets are described. Initial analysis was performed on minibatch field model recovery. Studies are being performed to examine the convergence of the solutions and the maximum expansion order the data will support in the constant and secular terms.

Source record↗

Evaluation of optimal control type models for the human gunner in an Anti-Aircraft Artillery (AAA) system

The selection of the structure of optimal control type models for the human gunner in an anti aircraft artillery system is considered. Several structures within the LQG framework may be formulated. Two basic types are considered: (1) kth derivative controllers; and (2) proportional integral derivative (P-I-D) controllers. It is shown that a suitable criterion for model structure determination can be based on the ensemble statistics of the tracking error. In the case when the ensemble tracking steady state error is zero, it is suggested that a P-I-D controller formulation be used in preference to the kth derivative controller.

Phatak, A. V.↗

Thermal energy storage systems using fluidized bed heat exchangers

The viability of using fluidized bed heat exchangers (FBHX) for thermal energy storage (TES) in applications with potential for waste heat recovery was investigated. Of the candidate applications screened, cement plant rotary kilns and steel plant electric arc furnaces were identified, via the chosen selection criteria, as having the best potential for successful use of FBHX/TES system. A computer model of the FBHX/TES systems was developed and the technical feasibility of the two selected applications was verified. Economic and tradeoff evaluations in progress for final optimization of the systems and selection of the most promising system for further concept validation are described.

Ramanathan, V.↗

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Penaloza, Mauel A.↗