SEARCH · Search NASA

Results for “Selection optimization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39

All sources NASA NTRS DOE OSTI

NASA NTRS2014

Connecting Returned Apollo Soils and Remote Sensing: Application to the Diviner Lunar Radiometer

The Diviner Lunar Radiometer, onboard NASA's Lunar Reconnaissance Orbiter, has produced the first global, high resolution, thermal infrared observations of an airless body. The Moon, which is the most accessible member of this most abundant class of solar system objects, is also the only body for which we have extraterrestrial samples with known spatial context, returned Apollo samples. Here we present the results of a comprehensive study to reproduce an accurate simulated lunar environment, evaluate the most appropriate sample and measurement conditions, collect thermal infrared spectra of a representative suite of Apollo soils, and correlate them with Diviner observations of the lunar surface. It has been established previously that thermal infrared spectra measured in simulated lunar environment (SLE) are significantly altered from spectra measured under terrestrial or martian conditions. The data presented here were collected at the University of Oxford Simulated Lunar Environment Chamber (SLEC). In SLEC, we simulate the lunar environment by: (1) pumping the chamber to vacuum pressures (less than 10‐4 mbar) sufficient to simulate lunar heat transport processes within the sample, (2) cooling the chamber with liquid nitrogen to simulate radiation to the cold space environment, and (3) heating the samples with heaters and lamp to set‐up thermal gradients similar to those experienced in the upper hundreds of microns of the lunar surface. We then conducted a comprehensive suite of experiments using different sample preparation and heating conditions on Apollo soils 15071 (maria) and 67701 (highland) and compared the results to Diviner noontime data to select the optimal experimental conditions. This study includes thermal infrared SLE measurements of 10084 (A11 - LM), 12001 (A12 - LM), 14259 (A14 - LM), 15071 (A15 - S1), 15601 (A15 - S9a), 61141 (A16 - S1), 66031 (A16 - S6), 67701 (A16 - S11), and 70181 (A17 - LM). The Diviner dataset includes all six Apollo sites at approximately 200 m spatial resolution We find that analyses of Diviner observations of individual sampling stations and SLE measurements returned Apollo soils show good agreement, while comparisons to thermal infrared reflectance under ambient conditions do not agree well, which underscores the need for SLE measurements and validates the Diviner compositional measurement technique.

Greenhagen, B. T.↗

NASA NTRS2015

Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

small satellite↗

NASA NTRS2014

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗

NASA NTRS2016

Streamlining the Design Tradespace for Earth Imaging Constellations

Science Data Processing↗

NASA NTRS2018

ATMS Radiometric Noise Characterization

The Advanced Technology Microwave Sounder (ATMS), on SNPP and NOAA-20, provides vertical atmospheric temperature and moisture profiles that are a key input to numerical weather prediction. Full characterization of radiometric noise is critical to error modeling, algorithm development and the potential development of performance requirements and product improvements. This paper presents estimates of white noise and low-frequency 1/f noise as derived from the Allan variance and scan-to-scan autocorrelations of data from the internal hot calibration. This approach allows direct comparison of on-orbit performance of the two units as well as comparison between ground calibration test data and on-orbit performance. The autocorrelation at multiple scan intervals is used as input to a theoretical model of the NET of inferred scene brightness temperature, when using weighted samples of calibration data over multiple scans. This will support selection of optimized calibration weighting functions for each channel, as well as providing further insight into the striping phenomenon. These measured autocorrelations are also compared to the autocorrelations derived from the 1/f spectra obtained both in special ground and on-orbit tests that characterize gain fluctuation. Channel cross-correlations are also presented, which can have a significant impact on effectiveness of direct assimilation performance.

instrument calibration↗

NASA NTRS2018

Integrated Computational-Experimental Development of Lithium-Air Batteries for Electric Aircraft

The primary obstacle to enable NASA's vision of Green Aviation is the extraordinary energy storage requirements for electric aircraft. Significant advances in high energy, rechargeable, safe batteries are required to enable electric aviation. Boeing's SUGAR and NASA studies have identified 400 Wh/kg as the threshold energy density for general aviation and 750 Wh/kg for commercial regional air service. State of the Art Lithium Ion Battery (LIB) technology currently has a density of 200 Wh/kg and is expected to plateau at 300 Wh/kg due to fundamental chemistry limitations making it unsuitable for future electric aircraft. Additional demanding requirements include high power, rechargeability, and high safety. Such battery technology does not currently exist. The recent considerable activity in battery research (DOE, Tesla Gigafactory, etc) overwhelmingly has been geared towards reducing cost and improving safety of LIB technology in order to promote the adoption of electric automobiles; and thus it is expected to have little impact on electric aviation development. New battery materials will be needed for the "Beyond Li Ion" (BLI) technologies required for high energy, safe electric aviation. Li-Air batteries have the highest known theoretical energy density (3400 Wh/kg) and therefore and if realized promises to transform the global transportation system. These high energy batteries have the potential to meet the energy storage challenges of current and future NASA aeronautics and space missions in addition to many terrestrial transportation applications as well. However, this technology requires significant components development and integration, as it is currently unable to achieve aircraft requirements. The objective of this project is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build several Li-Air cells, and flight-demonstrate the corresponding Li-Air battery packs. A significant problem for current Lithium-Air batteries is large scale decomposition of the battery electrolyte during operation leading to battery failure after a handful of charge/discharge cycles. Therefore, development of large scale, ultra-high energy, rechargeable, and safe Lithium-Air batteries require highly stable electrolytes that are resistant to decomposition under operating conditions. A NASA-based cross-organizational "dream team" of high-powered experts combined integrated supercomputer modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. The ultimate goal for the team is to develop an integrated experimental/computational infrastructure to produce a reliable predictive capability for the selection of optimal components, their fabrication parameters, and "design rules" of novel cell components for advanced ultra-high energy batteries that can meet energy storage challenges of NASA missions and many terrestrial transportation applications.

Li-air battery↗

NASA NTRS2018

Remote Optical Recession Measurement of Orion Thermal Protection System

For the Orion Multi-Purpose Crew Vehicle (MPCV) project, NASA is minimizing the use of onboard diagnostics, especially external sensors that penetrate the structure. Nonetheless, there is a desire to measure the Thermal Protection System (TPS) recession during reentry. One noninvasive technique currently under investigation is the insertion of indicator metals into the heatshield at varied depths and spatial locations. A remote (airborne) spectrometer detects the emissions from the ionized metal to reveal the time (thus depth) of the metal release. Innovative processing enables the emission features from trace amounts of the selected metals to be reliably detected against the complex and structured spectral background of the shock layer and ablated TPS material. The con-cept has been proven viable through ground testing at NASA HyMETS and AHF arc jet facilities using the Orion TPS material (Avcoat). This presentation highlights the parametric testing that was conducted to select the optimal indicator metals and to assess the accuracy of remote recession measurements using this technique. The CONOPS for integrating the technique into the Orion flight tests is also presented. This includes the onboard indicator metal "seeded plugs" and the offboard airborne sensor platform that would be deployed.

Scriven, Gordon↗

NASA NTRS2018

Instrument Modeling Concepts for Tradespace Analysis of Satellite Constellations

Constellations are gaining popularity in government and commercial space-based missions for Earth Observation (EO) due to their risk tolerance and ability to improve observation sampling in space and time. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the concept of modeling the primary science instruments within TAT-C, using a radar as an example, but extendable to imagers, occulters and lidars. The modularity of TAT-C's software architecture allows for crisply defining the interface between TAT-C's user defined or internal variables and the payload variables. The described module will inform TAT-C users of payload-dependent performance differences among thousands of constellation architectures (e.g. revisit time of the sensor swath, differential signal to noise ratio (SNR), spatial resolution of measurements) and allow them to pick an appropriate constellation architecture for detailed development. The module may also inform operational decisions of satellite modes, based on ground optimization or onboard autonomy.

Nag, Sreeja↗

NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗

NASA NTRS2019

NASA's Behavioral Health and Performance Services for Long Duration Spaceflight Missions

Goals of the presentation include: Understand how NASA selects astronauts optimally suited for long duration spaceflight missions (missions 30 days or longer). Understand the basics of space station development and long duration spaceflight history, as well as the behavioral challenges associated long duration spaceflight training and missions. Understand how NASA and its international partners (Russia, Europe, Japan, and Canada) provide behavioral health and performance services and countermeasures to astronauts and cosmonauts during long duration spaceflight missions on the International Space Station.

Beven, Gary E.↗

NASA NTRS2020

Enabling Global Lunar Access for Human Landing Systems Staged at Earth-Moon L2 Southern Near Rectilinear Halo and Butterfly Orbits

NASA’s Artemis program will return astronauts to the lunar surface using a Human Landing System staged at Gateway’s 9:2 L2 southern NRHO. The current study explores global lunar access for Gateway’s baseline NRHO and a comparable butterfly orbit. Additionally, increasing transfer time and loitering in low lunar orbit are analyzed to reduce lunar surface access costs. The results show selecting the optimal staging orbit for a landing site, increasing transfer times, and leveraging low lunar orbit loiter greatly reduce performance requirements.

Zachary D May↗

NASA NTRSDate not supplied

A Case Study on the Challenges and Opportunities for the Deployment of PHM Capabilities in Existing Engineering Systems

The field of Prognostics and Health Management (PHM) of engineering systems has experienced considerable growth over the last decade. From benefits associated with faster and more powerful hardware in the form of wireless sensors, edge devices, and general computing capabilities (GPU’s and cloud computing), to development of powerful algorithms for anomaly detection and remaining useful life (RUL) estimation, the number of engineering systems featuring advanced diagnostics and prognostics capabilities continues to grow at an increasingly faster pace. However, the deployment of PHM capabilities as part of the upgrade of existing engineering systems presents multiple challenges to the PHM practitioner charged with retrofitting such systems. Issues include a lack of specific instrumentation needed to capture the signals of interest; insufficient data and sampling rates required for fault detection and diagnosis, and for detection of failure/degradation indicators; and difficulties in the identification of a system’s nominal behavior as a result of age induced degradation. Today’s PHM practitioner must be able to quickly identify and assess these types of issues to effectively evaluate and select the optimal PHM strategies required to achieve the desired results. This paper presents results from the preliminary evaluation of the High-Pressure Gas Facility (HPGF) infrastructure at NASA’s Stennis Space Center in Hancock County, Mississippi. This evaluation is part of a feasibility study conducted prior to the deployment of prognostics and diagnostics capabilities in the pumps skids of the liquid nitrogen (LN2) system of the HPGF.

Condition Based Maintenance↗

NASA NTRSDate not supplied

A Preliminary Modeling Study of Biofilm Accumulation in the Water Recovery System

Bacterial biofilms are ubiquitous in wastewater systems on earth and in spacecraft, such as in the International Space Station (ISS) wastewater processing assembly (WPA), where they cause problems in the tank, solenoid valves, and pipelines. Downstream filter applications, tank cycling, and regular biocide water flushing have been used to control biofilm accumulation on board the ISS. Biofilm control is expected to be a challenge for long-term missions with a dormancy period of up to a year, as stagnant water systems are highly susceptible to biofilm growth. Flushing of the system with biocidal water has been proposed to avoid biomass problems for long-term missions. To validate the proposed flush method, a mathematical model, based on the metabolism maintenance rate of bacteria, is being developed to understand the current biofilm accumulation rate in the ISS WPA system and to calculate the biomass production rate under dormancy-like conditions. This method of quantification of biofilm can be applied as a function of nutrient inputs to guide the selection and optimization of biofilm mitigation approaches. The method can also be helpful in understanding, defining, quantifying, visualizing, and simulating the state of the water processing system during operation and after dormancy.

Angie M Diaz↗

NASA NTRSDate not supplied

Topology Optimization of Low-Speed Aeroelastic Wind Tunnel Models

The goal of this work is to utilize topology optimization methods to obtain low-speed flexible wind tunnel models with simple jig outer mold lines, but highly-tuned aeroelastic flutter behavior. The wing is conceptually constructed with commonly-available 3D printed materials, of which the optimizer may select one of two at every location in the wing; a stiffer material meant to bear the loads, and a softer rubber-like material for space filling, and to form the outer mold line, where needed. Results are shown for three topological parameterizations: 2D topologies with a fixed nondesignable plate through the camber line, 2D parameterizations without the plate, and 3D parameterizations where the topology can vary though the depth of the wing, at a given planform location.

Aeroelasticity↗

NASA NTRS2017

The Epic Chronicle of Designing Cassini's Titan Flyby Altitudes

The selection and optimization of Titan flyby altitudes for NASA's Cassini mission at Saturn has traveled a long, fascinating, and often torturous sixteen-year path - starting in 2001, when pre-arrival trajectory design decisions had to be made, through April of 2017 when Cassini's last, and arguably most critical, low flyby takes place. The chronicle of designing and updating the Titan flyby altitudes have twists and turns enough to satisfy a full-length novel or feature film, including: critical design decision-making before arrival with multiple atmospheric models, high uncertainties, and limited data; early flybys that seemed to show trends that weren't there; use and misuse of statistical analysis; unexpected surprises with limited reaction time; navigation of a scientific, engineering, and management community with a wide array of inherent biases; and consideration of a variety of project risk postures in a high-scrutiny, high-impact, high-reward environment.

Bittner, Molly↗

NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗

NASA NTRS2020

Traversability-aware Signal Coverage Planning for Communication Node Deployment in Planetary Cave Exploration

In this paper we describe an automated planning system that selects the optimal target location to drop a communication node in an unknown cave environment to maximize communication coverage while minimizing the risk of violating safety constraints for all robots traversing the area based on local environmental and operational constraints.

Agha-mohammadi, Ali-akbar↗

NASA NTRSDate not supplied

Power System Redundancy Design Trends for All-Electric eVTOL Quadrotors

Electrical vertical takeoff and landing (eVTOL) vehicles promise to enable a variety of new local and intraregional air transport missions. However, there are significant challenges that must be solved to enable their use. One challenge is the relatively low reliability of power components (e.g. motors, power electronic devices, and batteries). No clear development path to create reliable eVTOL power systems has been articulated in the literature, though it is generally assumed redundancy is part of the solution. This work proposes an analysis process to examine the redundancy design space and select mass optimal designs for eVTOL power systems. The process is applied to a six passenger quadrotor vehicle, and results are used to highlight redundancy design trends for this class of vehicle. This process and associated data can help vehicle designers more effectively develop eVTOLs that meet reliability requirements.

Electric vertical takeoff and landing↗