Search NASA⌕ Search

SEARCH · Search NASA

Results for “Synthetic data generation”

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.

At least 451 records · Page 25

Invertible neural networks for E3SM land model calibration and simulation

We apply an invertible neural network (INN) for E3SM land model calibration and simulation with eight parameters at the Missouri Ozark AmeriFlux forest site. INN provides bijective (two-way) mappings between inputs and outputs, thus it can solve probabilistic inverse problems and forward approximations simultaneously. We demonstrate INN's inverse and forward capability in both synthetic and real-data applications. Results indicate that INN produces accurate parameter posterior distributions similar to Markov Chain Monte Carlo sampling and it generates model outputs close to the forward model simulations. Additionally, both the inverse and forward evaluations in INN are computationally efficient which allows for rapid integration of observations for parameter estimation and fast model predictions.

Lu, Dan↗

Multiplanar Synthetic Arrays and Their Application to Full-Scale Landing Gear Noise Source Identification

Identification and quantification of noise sources generated by the landing gears of large civil transports are critical for the development of viable abatement technologies that can be applied locally to affect solely the source regions. Leveraging validated computational data sets obtained from airframe noise simulations of a full-scale B777-300ER aircraft, a frame-work based on multiplanar synthetic arrays was developed to examine landing gear sources. The position of the arrays relative to the aircraft nose or main landing gears, the number of microphones in each array, and their distribution pattern were judiciously selected to provide adequate spatial resolution of the sources in the primary flyover, sideline, and upstream directions while maintaining reasonable signal-to-noise ratio and beamwidth over a wide frequency range. Overall, seven synthetic arrays with 800 microphones each, for a total of 5,600 microphones, were used in the framework. Fully synchronous synthetic pressure records at each microphone location were obtained from the simulated data sets via a Ffowcs-Williams and Hawkings integral approach, with flow quantities on a permeable data surface enclosing the source regions used as input. Various applications of synthetic multiplanar arrays to acoustic data analysis are presented; the advantages of the framework in properly resolving and identifying the B777 landing gear sources is demonstrated by comparing three-dimensional source distribution maps with those obtained from a synthetic version of the ground-based microphone array used during flight tests of the same aircraft.

airframe noise↗

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

59 BASIC BIOLOGICAL SCIENCES↗

Notes on Real-Beam Ground Mapping with Monopulse Radar

The spatial awareness required of modern flight systems is facilitated by images generated by ground-mapping radar. In the forward and aft directions, synthetic aperture techniques are not viable, leaving us with enhancing real aperture radar data. Enhancing real aperture radar data with monopulse information can be achieved with any of several monopulse beam sharpening techniques. Two such algorithms are discussed.

47 OTHER INSTRUMENTATION↗

Topographic mapping using radar interferometry - Processing techniques

In the summer of 1991 the NASA DC-8 airborne synthetic aperture radar (SAR) system acquired data with the radar configured in a C-band across-track interferometer mode. The data were processed to generate rectified topographic maps. A new processing scheme was developed featuring motion compensation, absolute phase retrieval, and three-dimensional 1ocation. The new processor has been tested using data which were acquired with extreme aircraft motion so that performance could be evaluated under adverse conditions. The topographic maps generated by the radar were compared to Digital Elevation Models (DEM's) derived using conventional optical stereo techniques. In one region we measured rms elevation deviations which were less than the specified DEM accuracy, and in the region covered by the more accurate DEM we found errors varying from 2.2 m rms in relatively flat terrain up to 5.0 m in mountainous areas. The rms difference between radar and DEM elevations over the 6.5 km by 22 km area covered by the more accurate DEM was 3.6 m.

Madsen, Soren N.↗

DOPHOT, a CCD photometry program: Description and tests

The design considerations and operational features of DOPHOT, a point-spread function (PSF) fitting photometry program, are described. Some relevant details of the PSF fitting are discussed. The quality of the photometry returned by DOPHOT is assessed via reductions of an 'artificial' globular cluster generated from a list of stars with known magnitudes and colors. Results from comparative tests between DOPHOT and DAOPHOT using this synthetic cluster and real data are also described.

Schechter, Paul L.↗

One‐Pot Synthesis of Xanthone by Carbonylative Suzuki Coupling Reaction

Abstract Xanthone derivatives have a dibenzo‐y‐pyrone scaffold which has gained great interest in Medicinal Chemistry due to their diverse biological activities. Usually, its synthesis requires multi‐step synthetic routes using harsh conditions and high catalyst loadings. In this communication, we report for the first time a one‐pot synthesis of the xanthone scaffold based on a carbonylative Suzuki coupling. Iodophenol and (2‐methoxyphenyl)boronic acid were coupled under carbon monoxide, generated from a carbon monoxide surrogate. An experimental data‐based model was built to guide the reaction optimization. The optimized conditions were 1 mol% of a pincer complex as palladium catalyst, 5 equivalents of K 2 CO 3 as base, and DMF:water (7 : 3) as solvent. The robustness of the synthetic method, namely in terms of the reactants scope, was also evaluated. This approach provided the xanthone scaffold in high yields and provided a deep insight into the carbonylative Suzuki couplings.

Loureiro, Daniela R. P.↗

Controlling radioisotope proportions when randomly sampling from Dirichlet distributions in PyRIID

As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

In Hot Pursuit of the Hidden Companion of Carinae: An X-Ray Determination of the Wind Parameters

We present X-ray spectral fits to a recently obtained Chandra grating spectrum of eta Carinae, one of the most massive and powerful stars in the Galaxy and which is strongly suspected to be a colliding wind binary system. Hydrodynamic models of colliding winds are used to generate synthetic X-ray spectra for a range of mass-loss rates and wind velocities. They are then fitted against newly acquired Chandra grating data. We find that due to the low velocity of the primary wind (approximately 500 km per sec), most of the observed X-ray emission appears to arise from the shocked wind of the companion star. We use the duration of the lightcurve minimum to fix the wind momentum ratio at eta = 0.2. We are then able to obtain a good fit to the data by varying the mass-loss rate of the companion and the terminal velocity of its wind. We find that M(sub 2) is approximately 10(exp -5) solar mass per yr and upsilon(sub infinity(sub 2)) is approximately 3000 km per sec. With observationally determined values of approximately 500- 700 km per sec for the velocity of the primary wind, our fit implies a primary mass-loss rate of M(sub 1) approximately 2.5 x 10(exp -4) solar mass per yr. This value is smaller than commonly inferred, although we note that a lower mass-loss rate can reduce some of the problems noted when a value as high as 10(exp -3) solar mass per yr is used. The wind parameters of the companion are indicative of a massive star which may or may not be evolved. The line strengths appear to show slightly sub-solar abundances, although this needs further confirmation. It also appears that the primary star is responsible for the nebula.

Pittard, J. M.↗

Data and Multistage Optimization for the New Grid

Three essential capabilities for using exascale computing resources on next generation power grid applications are: generating large renewable energy datasets, modeling damage and operations during and after extreme events, and employing multi-stage optimization for infrastructure planning. Powerscenarios, developed as part of the ExaSGD project, addresses these capabilities by enabling users to build synthetic wind farms for large test systems using numerical weather prediction-based data sources. We share examples of using Powerscenarios to build out wind farms on the ACTIVSg2000 test system, to enable simulated operations and emergency asset allocation during a hurricane strike, and to compute multi-stage infrastructure buildouts.

economic dispatch↗

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗

Characterization of the indoor far-field aerosol transmission in a model commercial office building

As businesses gradually reopen and employees return to work, the potential spread of SARS-CoV-2 and its variants through airborne transmission via the heating, ventilation, and air-conditioning (HVAC) systems of commercial building raises concerns. Since the general practice in commercial buildings is to use low-efficiency air filters and given that indoor air is generally recycled, the degree to which cross-zone aerosol transmission occurs is of interest. To quantify the cross-zone aerosol transmission, experiments were conducted using a synthetic test aerosol in the five zones on the first floor of a model commercial office building at the Oak Ridge National Laboratory. Because the synthetic aerosol was tagged with fluorescent salt, the aerosol generated from the source zone can be distinguished from the background aerosols due to its unique fluorescent signal. Data from cross-zone campaigns showed that submicron-aerosol transmission was higher than the micron aerosols. In campaigns with doors closed, the submicron aerosol transmission was less than 16% and less than 11% for micron aerosol transmission. Finally, opening the interior doors that connecting different zones can significantly enhance the aerosol transmission for zones at the close proximity to the source, but has less impact on those farther away.

60 APPLIED LIFE SCIENCES↗

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

Quantification of morphological change in materials based on image data utilizing machine learning techniques

Computed tomography (CT) resolution has become high enough to monitor morphological changes due to aging in materials in long-term applications. We explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images visually reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect. Both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

Fine Resolution Topographic Mapping of the Jovian Moons: A Ka-Band High Resolution Topographic Mapping Interferometric Synthetic Aperture Radar

The topographic data set obtained by MOLA has provided an unprecedented level of information about Mars' geologic features. The proposed flight of JIMO provides an opportunity to accomplish a similar mapping of and comparable scientific discovery for the Jovian moons through use of an interferometric imaging radar analogous to the Shuttle radar that recently generated a new topographic map of Earth. A Ka-band single pass across-track synthetic aperture radar (SAR) interferometer can provide very high resolution surface elevation maps. The concept would use two antennas mounted at the ends of a deployable boom (similar to the Shuttle Radar Topographic Mapper) extended orthogonal to the direction of flight. Assuming an orbit altitude of approximately 100km and a ground velocity of approximately 1.5 km/sec, horizontal resolutions at the 10 meter level and vertical resolutions at the sub-meter level are possible.

Madsen, S. N.↗

Fine resolution topographic mapping of the Jovian moons: a Ka-band high resolution topographic mapping interferometric synthetic aperture radar

The topographic data set obtained by MOLA has provided an unprecedented level of information about Mars' geologic features. The proposed flight of JIMO provides an opportunity to accomplish a similar mapping of and comparable scientific discovery for the Jovian moons through us of an interferometric imaging radar analogous to the Shuttle radar that recently generated a new topographic map of Earth. A Ka-band single pass across-track synthetic aperture radar (SAR) interferometer can provide very high resolution surface elevation maps. The concept would use two antennas mounted at the ends of a deployable boom (similar to the Shuttle Radar Topographic Mapper) extended orthogonal to the direction of flight. Assuming an orbit altitude of approximately 100 km and a ground velocity of approximately 1.5 km/sec, horizontal resolutions at the 10 meter level and vertical resolutions at the sub-meter level are possible.

Jupiter Icy Moon Orbiter↗

Modeling aerosol transmission spectra from n(λ) and k(λ) infrared optical constants measurements of organic liquids and solids

The effects of light scattering and refraction play significantly different roles for aerosols than for bulk materials, making it challenging to identify aerosolized chemicals using traditional spectral methods or spectral reference libraries. Due to a potentially infinite number of particle morphologies, sizes, and compositions, constructing a database of laboratory-measured aerosol spectra is not a practical solution. Here, as an alternative approach, the measured n / k optical vectors of two example organic materials (diethyl phthalate and D-mannitol) are used in combination with particle absorption / scattering theory (Mie theory and FDTD) and the Beer-Lambert law to generate a series of synthetic infrared transmission / scattered light spectra. The synthetic spectra show significant differences versus simple slab transmission spectra, even for small changes in particle size (e.g., 5 vs. 10 µm) for both single particles and ensembles, potentially serving as useful reference data for aerosol sensing. For spherical single particles with diameters of 1 to 10 µm, FDTD simulations predict changes in the magnitudes of spectral shifts and the shapes of the peaks vs. particle size with only small deviations from Mie theory predictions, yet reliably capture the direction of the shifts. Typical spectral peak shifts in the longwave infrared correspond to Δλ ∼0.20 µm (∼34 cm -1 ) when compared to corresponding slab transmission spectra. Additionally, synthetic spectra generated from the n / k values derived using two different methods (KBr pellet transmission and single-angle reflectance) are compared using the Mie theory model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Extreme waves in present and future climates using physics-based synthetic tropical cyclones in the Gulf of Mexico.

Historically, extreme waves have been the most destructive force in the Gulf of Mexico, destroying and damaging thousands of offshore structures. The American Petroleum Institute has revised its design criteria for offshore platforms several times over the decades, as new data continues to become available, showing that data for our present climate is insufficient. This problem is exacerbated in a changing climate. By using synthetic physics-based tropical cyclones to force a third-generation wave model, we can generate adequate statistics for present and future climates. These simulations have been completed using Joule Supercomputer.

Climate Change↗