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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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NASA NTRSDate not supplied

Data Science Challenges for Urban Air Mobility

Aviation is a combination of aircraft, airspace and airports. The data science life cycle comprises of five steps - capture, maintain, process, analyze and communicate. The presentation introduces the legacy of conventional aviation research in the context of the data science life cycle to motivate the challenges with Urban Air Mobility, a field that is quite nascent. A summary of recent research will be presented to highlight the innovative ways to address the challenges. Examples provided will include the generation of synthetic data, encounter models from simulations, and leveraging novel and diverse data sets from traditional transportation and non-aviation sources, to analyze problems of operation in urban airspace. Finally, opportunities will be identified for further exploration, niche development and filling the gaps in the field of data science for UAM.

Data Science↗

NASA NTRS2020

Data Science Challenges for Urban Air Mobility

Data Science↗

NASA NTRSDate not supplied

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography, digital radiography, and ultrasound. The accuracy of the fused estimates are validated against data generated from synthetic specimens, and by comparison against high resolution X-ray computed tomography inspections of built specimens.

thermal nondestructive evaluation↗

NASA NTRS1998

MODIS Science Team Member Semi-annual Report

This paper presents a semi-annual report of the MODerate resolution imaging Spectroradiometer (MODIS) Science Team Members. The most important activities undertaken during this reporting period are the following: 1) Versions 2.1 and 2.2 surface reflectance L2/L3 DAAC/SDST delivery; 2) Version 2.0 1km and 250m VI product delivery (assist Arizona); 3) Version 2.1 surface reflectance L2 testing; 4) Land Synthetic data set generator improvements; 5) QA; 6) Surface reflectance error budget generation (SWAMP request); 7) SCF Hardware; 8) Aerosol transport modeling; 9) Aerosol optical depth retrieval from AVHRR data; 10) Aerosol characteristics retrieval from SeaWIFS/AVHRR fusioned data; 11) Validation activities; 12) Aerosol climatology; and 13) 6S code. The report includes summaries of the topics above.

Vermote, Eric↗

NASA NTRS2003

LISA Optics Model: Early Results

The Laser Interferometer Space Antenna (LISA) optics model is used to generate a synthetic data stream in the absence of gravitational waves. The simulation has the spacecraft in moving in their respective Keplerian orbits. The pointing of the spacecraft and station keeping about the proof masses is accomplished using a control scheme, which minimizes the disturbance on the proof masses in the sensitive direction. The resulting data stream gives an indication of the magnitude of instrumental noise due to pointing jitter and motions of the spacecraft with respect to the proof masses. Computational details are presented and the results discussed.

Waluschka, Eugene↗

NASA NTRS2015

On the Use of Fourier Transform Infrared (FT-IR) Spectroscopy and Synthetic Calibration Spectra to Quantify Gas Concentrations in a Fischer-Tropsch Catalyst System

One possible origin of prebiotic organic material is that these compounds were formed via Fischer-Tropsch-type (FTT) reactions of carbon monoxide and hydrogen on silicate and oxide grains in the warm, inner-solar nebula. To investigate this possibility, an experimental system has been built in which the catalytic efficiency of different grain-analog materials can be tested. During such runs, the gas phase above these grain analogs is sampled using Fourier transform infrared (FT-IR) spectroscopy. To provide quantitative estimates of the concentration of these gases, a technique in which high-resolution spectra of the gases are calculated using the high-resolution transmission molecular absorption (HITRAN) database is used. Next, these spectra are processed via a method that mimics the processes giving rise to the instrumental line shape of the FT-IR spectrometer, including apodization, self-apodization, and broadening due to the finite resolution. The result is a very close match between the measured and computed spectra. This technique was tested using four major gases found in the FTT reactions: carbon monoxide, methane, carbon dioxide, and water. For the ranges typical of the FTT reactions, the carbon monoxide results were found to be accurate to within 5% and the remaining gases accurate to within 10%. These spectra can then be used to generate synthetic calibration data, allowing the rapid computation of the gas concentrations in the FTT experiments.

Infrared Spectroscopy↗

NASA NTRS2016

Performance Assessment of Different Pulse Reconstruction Algorithms for the ATHENA X-Ray Integral Field Unit

The X-ray Integral Field Unit (X-IFU) microcalorimeter, on-board Athena, with its focal plane comprising 3840 Transition Edge Sensors (TESs) operating at 90 mK, will provide unprecedented spectral-imaging capability in the 0.2-12 keV energy range. It will rely on the on-board digital processing of current pulses induced by the heat deposited in the TES absorber, as to recover the energy of each individual events. Assessing the capabilities of the pulse reconstruction is required to understand the overall scientific performance of the X-IFU, notably in terms of energy resolution degradation with both increasing energies and count rates. Using synthetic data streams generated by the X-IFU End-to-End simulator, we present here a comprehensive benchmark of various pulse reconstruction techniques, ranging from standard optimal filtering to more advanced algorithms based on noise covariance matrices. Beside deriving the spectral resolution achieved by the different algorithms, a first assessment of the computing power and ground calibration needs is presented. Overall, all methods show similar performances, with the reconstruction based on noise covariance matrices showing the best improvement with respect to the standard optimal filtering technique. Due to prohibitive calibration needs, this method might however not be applicable to the X-IFU and the best compromise currently appears to be the so-called resistance space analysis which also features very promising high count rate capabilities.

microcalorimeters↗

NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗

NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

Distributed sensing↗

NASA NTRSDate not supplied

Computational Characterization and Model Verification for 3D Microstructure Reconstruction of Additively-Manufactured Materials

The goal of this study is to characterize and validate the texture and grain topology of additively-manufactured anisotropic three-dimensional (3D) polycrystalline microstructures. The special focus is on developing methodologies to compare the grain shapes and orientations of two-dimensional (2D) and 3D microstructure representations using the same metric. To generate statistical data, synthetic microstructures are reconstructed from experimental data using Markov random field (MRF). The statistical similarity between the experimental and synthetic microstructures is verified by comparing their grain topologies. A universal measure to compare 2D and 3D grains is portrayed through the concept of image moments that are invariant to shape transformations. The graphical plots developed based on moment invariants to compare the 2D and 3D grains are used to verify the synthetic model

Materials Characterization↗

NASA NTRSDate not supplied

Optimal Sensor Mobility Design for Target Tracking with Distributed Sensing, Communication and Computing Infrastructure

The paper presents an airborne target tracking approach with data fusion from distributed stationary and mobile sensor network transmitted through a wireless/wired communication network and using a distributed computing infrastructure. To obtain high quality measurements, sensor flight platforms' positions and orientations are optimized with respect to the available target's position and velocity estimates, and a formation control strategy is applied to derive desired trajectories for the flight platforms. As sensors move, the communication network topology switching is determined using the worst-case approach to handle uncertainties in the target's and sensors' positions, which alters communication delays for sensors' data transmission to computing centers. An optimal data migration algorithm is periodically applied to determine these communication delays for each sensor and the optimal location with minimum end-to-end latency for the target tracking algorithm execution, which is based on adaptive information fusion from multi-modal mobile and stationary sensors inside an Extended Kalman Filter framework. The approach is validated in a desktop simulation environment using synthetic sensor data generated for a simulated target's flight.

Distributed sensing↗

NASA NTRSDate not supplied

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.

Distributed sensing↗

NASA NTRSDate not supplied

Optimal Communication Topology Construction and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach with no estimation feedback to sensors selection and communication network topology computation for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes maximum airspace coverage with minimal resources, minimum communication time and power consumption while guaranteeing the system observability and providing in-time high quality information to both stationary and mobile users. The developed algorithms use multi-objective optimization strategy taking into account trade-offs between conflicting objectives and are implemented using off-the-shelf computational tools. The algorithms are validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace and parameters of a notional wireless communication network.

Distributed sensing↗

NASA NTRS1991

Generation of topographic terrain models utilizing synthetic aperture radar and surface level data

Topographical terrain models are generated by digitally delineating the boundary of the region under investigation from the data obtained from an airborne synthetic aperture radar image and surface elevation data concurrently acquired either from an airborne instrument or at ground level. A set of coregistered boundary maps thus generated are then digitally combined in three dimensional space with the acquired surface elevation data by means of image processing software stored in a digital computer. The method is particularly applicable for generating terrain models of flooded regions covered entirely or in part by foliage.

Imhoff, Marc L.↗

NASA NTRS1988

Data volume reduction for imaging radar polarimetry

Two alternative methods are presented for digital reduction of synthetic aperture multipolarized radar data using scattering matrices, or using Stokes matrices, of four consecutive along-track pixels to produce averaged data for generating a synthetic polarization image.

Zebker, Howard A.↗

NASA NTRS1989

Data volume reduction for imaging radar polarimetry

Two alternative methods are disclosed for digital reduction of synthetic aperture multipolarized radar data using scattering matrices, or using Stokes matrices, of four consecutive along-track pixels to produce averaged data for generating a synthetic polarization image.

Zebker, Howard A.↗

NASA NTRS1987

Digital simulation of the SIR-C sensor electronics

In this paper software for simulation of the response of the SIR-C sensor to a point target is described. Synthetic SAR data is generated by passing successive chirps through a simulation of the transmitter electronics, propagation path and receiver electronics. This result is then processed with a digital correlator to yield the point target response of the system. This allows an accurate assessment of the effect of the radar design on the final image product.

Klein, Jeffrey D.↗

NASA NTRS2008

Black Hole Mergers as Probes of Structure Formation

Intense structure formation and reionization occur at high redshift, yet there is currently little observational information about this very important epoch. Observations of gravitational waves from massive black hole (MBH) mergers can provide us with important clues about the formation of structures in the early universe. Past efforts have been limited to calculating merger rates using different models in which many assumptions are made about the specific values of physical parameters of the mergers, resulting in merger rate estimates that span a very wide range (0.1 - 104 mergers/year). Here we develop a semi-analytical, phenomenological model of MBH mergers that includes plausible combinations of several physical parameters, which we then turn around to determine how well observations with the Laser Interferometer Space Antenna (LISA) will be able to enhance our understanding of the universe during the critical z 5 - 30 structure formation era. We do this by generating synthetic LISA observable data (total BH mass, BH mass ratio, redshift, merger rates), which are then analyzed using a Markov Chain Monte Carlo method. This allows us to constrain the physical parameters of the mergers. We find that our methodology works well at estimating merger parameters, consistently giving results within 1- of the input parameter values. We also discover that the number of merger events is a key discriminant among models. This helps our method be robust against observational uncertainties. Our approach, which at this stage constitutes a proof of principle, can be readily extended to physical models and to more general problems in cosmology and gravitational wave astrophysics.

Alicea-Munoz, E.↗