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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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100 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Open Source Subtitle Editor Software Study for Section 508 Close Caption Applications

This paper will focus on a specific item within the NASA Electronic Information Accessibility Policy - Multimedia Presentation shall have synchronized caption; thus making information accessible to a person with hearing impairment. This synchronized caption will assist a person with hearing or cognitive disability to access the same information as everyone else. This paper focuses on the research and implementation for CC (subtitle option) support to video multimedia. The goal of this research is identify the best available open-source (free) software to achieve synchronized captions requirement and achieve savings, while meeting the security requirement for Government information integrity and assurance. CC and subtitling are processes that display text within a video to provide additional or interpretive information for those whom may need it or those whom chose it. Closed captions typically show the transcription of the audio portion of a program (video) as it occurs (either verbatim or in its edited form), sometimes including non-speech elements (such as sound effects). The transcript can be provided by a third party source or can be extracted word for word from the video. This feature can be made available for videos in two forms: either Soft-Coded or Hard-Coded. Soft-Coded is the more optional version of CC, where you can chose to turn them on if you want, or you can turn them off. Most of the time, when using the Soft-Coded option, the transcript is also provided to the view along-side the video. This option is subject to compromise, whereas the transcript is merely a text file that can be changed by anyone who has access to it. With this option the integrity of the CC is at the mercy of the user. Hard-Coded CC is a more permanent form of CC. A Hard-Coded CC transcript is embedded within a video, without the option of removal.

Murphy, F. Brandon↗
NASA NTRSDate not supplied

Toward Adjoint-Based Aeroacoustic Optimization for Propeller and Rotorcraft Applications

The goal of the present project is to build a multidisciplinary, rapid, robust, and accurate computational tool to optimize wing-mounted propeller designs. The full Farassat’s formulation F1Afor aeroacoustic analysis is implemented in the open-source software SU2.This extension enables the prediction of far-field noise generated by moving sources. The formulation is verified, for a stationary and rotating sphere in a wind tunnel and for a tiltrotor in forward flight, by comparing the acoustic predictions ofSU2 with the predictions computed by NASA’s aeroacoustics code ANOPP2. The algorithmic differentiation capability of SU2 provides discretely consistent, adjoint-based sensitivity analysis for this formulation. The adjoint-based sensitivities are verified through comparison with complex-step sensitivities

R Omur Icke↗
NASA NTRS2020

A Modified Algorithm and Open-Source Computational Package for the Determination of Infrared Optical Constants Relevant to Astrophysics

Infrared (IR) telescopes, such as Spitzer and SOFIA, have revealed a rich variety of chemical species trapped in interstellar ices. The most fundamental parameters to be derived from observed IR spectra are the identity and abundance of each component. Several compounds have been conclusively or tentatively identified, but the band strengths and optical constants needed to derive accurate abundances for many of these are poorly constrained. We have developed a modified approach to the extraction of the real and imaginary parts of the refractive index (optical constants) of a thin film from a single transmission spectrum measured in the IR spectral range. Our algorithm is similar to those implemented by previous authors, with some major changes that yield results for strong absorptions where previous approaches fail: (1) an adaptive k-correction step size, (2) the use of a root-finding algorithm to obtain a more accurate k-correction at each iteration, and (3) a k-correction step that prevents non-physical results such as negative n-values that prevent convergence in the calculation algorithm. The algorithm is presented and described, with examples to show agreement with some existing results and improvements upon others. New optical-constants calculations for CH3OH, CO2, N2O, and CH4 are presented, and potential implications for the modeling of interstellar and planetary ice data from space telescopes are discussed. With the objective of being open-source and transparent, the full source code in the free Python programming language is made available along with the compiled version and the laboratory data used to produce the results shown.

Perry A. Gerakines↗
NASA NTRS2018

Fast Linearized Coronagraph Optimizer (FALCO) I: A Software Toolbox for Rapid Coronagraphic Design and Wavefront Correction

The Fast Linearized Coronagraph Optimizer (FALCO) is an open-source toolbox of routines for coronagraphic focal plane wavefront correction. The goal of FALCO is to provide a free, modular framework for the simulation or testbed operation of several common types of coronagraphs. FALCO includes routines for pair-wise probing estimation of the complex electric field and Electric Field Conjugation (EFC) control, and we ask the community to contribute other wavefront correction algorithms. FALCO utilizes and builds upon PROPER, an established optical propagation library. The key innovation in FALCO is the rapid computation of the linearized response matrix for each deformable mirror (DM), which facilitates re-linearization after each control step for faster DM-integrated coronagraph design and wavefront correction experiments. FALCO is freely available as source code in MATLAB at github.com/ajeldorado/falco-matlab and will be available later this year in Python 3 at github.com/ajeldorado/falco-python.

Shaklan, Stuart B.↗
NASA NTRS2021

Aircraft Flaps Modeling in OpenMDAO

The goal of this project was to develop a model for a single subsystem in the aerodynamics discipline, in this case the flaps of an aircraft. Flaps are high-lift devices used by planes to allow for quicker takeoffs, and slower landings. A computer-based aircraft model of the flaps of an aircraft was developed using the Python based open-source framework OpenMDAO. OpenMDAO is used to develop multi-disciplinary aircraft models using gradient-based optimization; design optimization (MDO) is concerned with solving design problems involving numerical models of complex engineering systems. There were 4 components in the model; each has input values, output variables, and equations to calculate said outputs. The variables and equations are sourced from NASA Fortran code from the 1970s, in a project called the General Aviation Synthesis Program (GASP). These variables and equations which create the model are being converted to Python for ease of use. The flaps model developed will be integrated into a larger model of a conventional aircraft’s flight phases. All subsystems of the model will first be built using the parameters of a Boeing 737 MAX-8, to validate its functionality and accuracy. Then, the aircraft model will be used for hybrid-electric research; running optimizations to improve efficiency, minimize fuel burn, and advance hybrid-electric technology in the aerospace field.

Computer-based aircraft modeling↗
NASA NTRS2022

Building a Transdisciplinary, Exascale-Capable Workforce for Geospace Science

Key Points: ●First-principles, self-consistent geospace modeling will require at least exascale-level computing capabilities; however, the technical skills necessary to develop such simulation codes are not taught as part of Heliophysics training/PhD programs. ●Developing exascale Heliophysics codes will require transdisciplinary collaborations between physicists, computer scientists, software engineers, data scientists, and applied mathematics. Such teams must be persistent and formed around specific skills, not specific problems. ●We must have stable, positive long-term career outcomes for Heliophysics scientific developers in order to retain knowledge of and promote future innovation in scientific algorithm development and advanced computing techniques. One such way to do this is by funding long-term scientific programming groups, akin to Heliophysics DRIVE Centers. ●We must have a balance between promoting innovation via funding short-term closed-source development and allowing the open-source community to benefit from and build on the newest scientific modeling techniques.

C Bard↗
NASA NTRS2016

EVEREST: Pixel Level Decorrelation of K2 Light Curves

We present EPIC Variability Extraction and Removal for Exoplanet Science Targets (EVEREST), an open-source pipeline for removing instrumental noise from K2 light curves. EVEREST employs a variant of pixel level decorrelation to remove systematics introduced by the spacecraft’s pointing error and a Gaussian process to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0–7, yielding light curves with precision comparable to that of the original Kepler mission for stars brighter than K(sub p) ≈ 13, and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline and compare our light curves to the other de-trended light curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these light curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST light curves and the source code used to generate them are freely available online.

Catalogs↗
NASA NTRSDate not supplied

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗
NASA NTRS2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consists of eighty-channel detector plane histograms that accumulate photon counts over time periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey dataset between 14 and 195 keV. Survey data comprises >90% of all BAT data by volume and allows for the tracking of long term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey dataset has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis python package , a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the python code and exemplify its usefulness and accuracy by analyzing survey data from the Crab Pulsar, NGC 2992, and a previously uncataloged MAXI Transient. The BatAnalysis package allows for ∼ 18 years of BAT survey to be used in a systematic way to study a large variety of astrophysical sources.

Tyler Parsotan↗
NASA NTRS2023

Towards Streamlining Auditing for Compliance With Requirements in Open-Source Software at NASA

Context: NASA requires all software to meet several requirements (NPR 7150.2) depending on software criticality. The instantiation of these requirements may vary per project; however, once decided upon, projects must undergo audits to evaluate compliance with these requirements. Aim: We propose that audit effort can be reduced when requirements are realized by leveraging commonly used open-source infrastructure for version control, issue tracking and continuous integration, and the generated records are analyzed using a repository mining software tool to quantify process compliance. Method: We perform a case study in the NASA-funded Copilot project, utilizing Kaiaulu, a repository mining software tool. We define four software compliance metrics based on the Copilot’s requirements, and analyze their impact on source code quality. Results: Our work demonstrates how it is possible to leverage existing open source tools and platforms to facilitate software certification and qualification, and to streamline the auditing process required even when stringent requirements must be enforced. Conclusion: Together, both project and tool can be utilized to visualize project compliance, and metrics can be defined to more easily identify process irregularities to minimize auditing efforts. Project Repository: github.com/Copilot-Language/copilot Tool Repository: github.com/sailuh/kaiaulu

code-quality↗