SEARCH · Search NASA

Results for “Open source”

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 55 records · Page 3

All sources NASA NTRS DOE OSTI

DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

DOE OSTI2026

A Streamlined, Open Source Neutronics Toolkit for Fusion Reactor Design (Final Report)

Final report for the DOE Fusion Energy Sciences project titled "A Streamlined, Open Source Neutronics Toolkit for Fusion Reactor Design". This project developed unstructured mesh tracking capabilities in OpenMC as well as two shutdown dose rate methodologies, and performed extensive performance improvements and validation of the open source Monte Carlo code, OpenMC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2014

Open Source Initiative Powers Real-Time Data Streams

Under an SBIR contract with Dryden Flight Research Center, Creare Inc. developed a data collection tool called the Ring Buffered Network Bus. The technology has now been released under an open source license and is hosted by the Open Source DataTurbine Initiative. DataTurbine allows anyone to stream live data from sensors, labs, cameras, ocean buoys, cell phones, and more.

Source record↗

NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗

DOE OSTI2025

OpenSn: A massively parallel, open-source simulation environment for discrete ordinates radiation transport

OpenSn is an open-source, massively parallel deterministic radiation transport code for solving the discrete-ordinates ( S N ) form of the Boltzmann transport equation on unstructured, arbitrary polyhedral meshes. It supports high-fidelity simulations involving steady-state, eigenvalue, and adjoint problems for neutral particles (e.g., neutrons, photons, multi-particles), using the multigroup approximation in energy. OpenSn combines angular discretization via discrete ordinates with a discontinuous Galerkin finite element method (DGFEM) in space, enabling accurate resolution of transport physics on arbitrary polyhedral cells, included locally refined spatial grids. It includes multiple angular quadrature types, including locally refined angular quadratures. Written in modern C++ with a Python API, OpenSn runs efficiently on platforms ranging from laptops to supercomputers. The transport sweep algorithm is implemented using a task-based, directed-acyclic-graph (DAG) approach for each angle and supports asynchronous parallelism across thousands of MPI ranks. Group-set aggregation improves compute intensity, and synthetic acceleration techniques (e.g., diffusion synthetic acceleration, second-moment method) enhance solver convergence. OpenSn has been verified on reactor physics problems and demonstrated excellent weak and strong scaling performance on more than 32,768 processes, making it a versatile and robust platform for large-scale transport simulations in complex geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

An Open-Source Coupling for Depletion During Fuel Cycle Modeling

Fuel depletion is an important aspect of fuel cycle modeling, allowing a user to account for how loaded fuel compositions affect in-core and spent fuel compositions and their related fuel cycle metrics. Therefore, multiple methods have been developed to account for depletion within fuel cycle simulations. This work adds to that list of methods by introducing an open-source coupling between C$\scriptsize{YCLUS}$ and OpenMC to perform fuel depletion during a fuel cycle simulation, called OpenMCyclus. This work explains the methodology of OpenMCyclus and presents a benchmark comparison between the performance of OpenMCyclus and another C$\scriptsize{YCLUS}$ archetype that uses recipes to define spent fuel compositions. In conclusion, the development of this coupling expands the functionalities possible through C$\scriptsize{YCLUS}$ by providing real-time fuel depletion that is reactor agnostic and open source.

C$\scriptsize{YCLUS}$↗

NASA NTRS2016

Finding Stuff Underwater: Open-Source Tools for Underwater Field Science

Since 2009, we have been developing and testing Exploration Ground Data Systems (xGDS). xGDS is a software suite, built on open-source web technologies, for supporting NASA terrestrial field science analog missions. We will describe our recent work supporting underwater mapping and dive operations at the Pavilion Lake Research Project (PLRP - www.pavilionlake.com). At PLRP we used open-source mapping technologies to meet an operational need to quickly guide divers and underwater vehicles to locations of interest, and the scientific goal of building a map showing the locations and characteristics of the microbialites at the bottom of the lake. We will discuss some of the benefits and lessons-learned from our recent transition from Google Earth to OpenLayers as the primary mapping engine to support our work. Well also explain the challenges we faced and solutions weve developed to support mapping and data collection in an underwater environment.Beyond their immediate value for advancing scientific research on Earth, NASA analogs explore new ideas for supporting scientists working in extreme environments (e.g. underwater) to develop best practices for future human missions to the Moon or Mars. Science at PLRP involved imaging, sampling and characterizing microbialites growing beneath the surface of an alpine lake in British Columbia. To support PLRP operations and science, xGDS helped plan data collection tasks and provided accurate tracking and mapping of the locations of the underwater assets (human-piloted submersibles, remotely operated vehicles (ROVs) and human divers) collecting imagery and samples from the lake. The data collected during our field work was registered with precursor bathymetry data collected by an autonomous underwater vehicle (AUV) and was globally located on a satellite base layer map of the area surrounding the lake.

Earth analogs↗

NASA NTRSDate not supplied

The State of CryptoLib – The Open-Source Satellite Cryptography Library

What state would the world be in if all internet traffic was unencrypted? Imagine an alternate universe where you can plug a packet sniffing device into your home internet and capture the web traffic of the entire world. It seems obvious that this scenario is less than desirable. If we would not allow this for the internet, why would we allow this in the space domain? With the advent of open-source ground stations, commercial off the shelf hardware, and ground stations as a service, the barrier to entry for space communications is rapidly lowering. New players enter the space realm everydayevery day, and the presence of tools to allow apprentice evildoers the ability to exploit satellite communications is on the horizon. Not only are legacy missions at risk, but future missions are as well - particularly lower budget science missions with more stringent sciencesize, weight, and power constraints. that may find it difficult to utilize hardware-based encryption solutions. In terms of Civilian Aerospace, NASA Standard 1006 generally directs that missions "shall protect the command stack with encryption that meets or exceeds Federal Information Processing Standards (FIPS) 140". Fortunately, the Consultative Committee for Space Data Systems (CCSDS) has published an international standard on Space Data Link Security. The combination of these two forces has resulted in CryptoLib - an open-source, C-based, encryption library that aims to be CCSDS SDLS compliant. CryptoLib is designed to support smaller missions on a tight budget that may be subject to the more stringent command link encryption requirements. Additionally, CryptoLib serves as an underpinning in JPL's Key Management & Cryptography (KMC) suite and is also designed to function as a 'drop-in' for smaller missions. CryptoLib is in active development and currently provides Telecommand (TC), Telemetry (TM), and Advanced Orbiting Systems (AOS) encryption and decryption capabilities with a variety of encryption and authentication schemes. This presentation will report the latest features, current status, and future plans for CryptoLib.

open-source encryption↗

NASA NTRSDate not supplied

The State of Cryptolib – The Open-Source Satellite Cryptography Library

open-source encryption↗

NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗

DOE OSTI2025

Open Source Intelligence for Cybersecurity Events via Twitter Data

Open-Source Intelligence (OSINT) is largely regarded as a necessary component for cybersecurity intelligence gathering to secure network systems. With the advancement of artificial intelligence (AI) and increasing usage of social media, like Twitter, we have a unique opportunity to obtain and aggregate information from social media. In this study, we propose an AI-based scheme capable of automatically pulling information from Twitter, filtering out security-irrelevant tweets, performing natural language analysis to correlate the tweets about each cybersecurity event (e.g., a malware campaign), and validating the information. This scheme has many applications, such as providing a means for security operators to gain insight into ongoing events and helping them prioritize vulnerabilities to deal with. To give examples of the possible uses, we present three case studies demonstrating the event discovery and investigation processes. We also examine the potential of OSINT for identifying the network protocols associated with specific events, which can aid in the mitigation procedures by informing operators if the vulnerability is exploitable given their system’s network configurations.

Dale, Dakota↗

NASA NTRSDate not supplied

Transforming NASA Earth Science Data Systems: A Journey from Big Earth Data Initiative (BEDI) to Open-Source Science Initiative (OSSI)

NASA's Earth Science Data and Information Systems (ESDIS) have undergone a significant evolution, particularly with the introduction of the Big Earth Data Initiative (BEDI) and the Open-Source Science Initiative (OSSI). In this talk, I will provide an overview of NASA's Earth Science Data and Information systems, highlighting key components such as EOSDIS, ESDIS, and ESDS. Moving forward, I will delve into the BEDI initiative, discussing its objectives, key players, and lessons learned. The second part of the talk will cover the OSSI initiative, exploring its objectives, strategy, and innovative solutions. Throughout the presentation, I will provide insights into the requests, strategies, and solutions behind both BEDI and OSSI. By the end, you will gain a comprehensive understanding of how NASA's Earth Science Data Systems have evolved over the years and witness the organization's commitment to advancing an open-source and collaborative approach to data science. Join me for an enlightening exploration into the future of Earth science data and the pivotal role played by NASA in shaping this transformative landscape.

Jennifer Wei↗

NASA NTRS2012

Developing an Open Source, Reusable Platform for Distributed Collaborative Information Management in the Early Detection Research Network

For the past decade, the NASA Jet Propulsion Laboratory, in collaboration with Dartmouth University has served as the center for informatics for the Early Detection Research Network (EDRN). The EDRN is a multi-institution research effort funded by the U.S. National Cancer Institute (NCI) and tasked with identifying and validating biomarkers for the early detection of cancer. As the distributed network has grown, increasingly formal processes have been developed for the acquisition, curation, storage, and dissemination of heterogeneous research information assets, and an informatics infrastructure has emerged. In this paper we discuss the evolution of EDRN informatics, its success as a mechanism for distributed information integration, and the potential sustainability and reuse benefits of emerging efforts to make the platform components themselves open source. We describe our experience transitioning a large closed-source software system to a community driven, open source project at the Apache Software Foundation, and point to lessons learned that will guide our present efforts to promote the reuse of the EDRN informatics infrastructure by a broader community.

Early Detection Research Network (EDRN)↗

DOE OSTI2026

DC Cryogenic Modeling of Open-Source SkyWater 130 nm MOSFETs at 77 K Using BSIM4

Cryogenic applications in high-energy physics (HEP) demand reliable, low-power CMOS electronics capable of operating at liquid nitrogen temperatures (77 K). The open-source SkyWater 130nm (SKY130) CMOS process has previously been shown to operate at temperatures as low as 4 K making it a promising candidate for HEP applications. In this work, we characterize and model SKY130 low-threshold voltage transistors at 77 K, which is a temperature commonly used in modeling applications for liquid argon detectors. DC characteristic measurements were performed at both room temperature and liquid nitrogen temperature. We created a cryogenic modeling approach to produce a SPICE-compatible, isothermal BSIM4-based model for select transistor sizes at 77 K. The resulting model agrees with data at 77 K with an average error on the order of 20% (relative RMS) and shows no dependence on drain voltage. Due to the open-source nature of SKY130, we have made our models publicly available on Github. We hope this work will continue the trend for democratizing circuit design at cryogenic temperatures in high-energy physics by enabling open access to accurate cryogenic CMOS device models at 77 K.

Beall, F. [Texas U., Arlington]↗

NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

DOE OSTI2025

Development, validation, and verification of multi-pass thermo-mechanical welding simulations using the open-source MOOSE framework: NeT TG4 benchmark weldment

This study develops and validates a sequentially coupled thermo-mechanical welding simulation for the three-pass 316L stainless steel NeT TG4 benchmark weldment using the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) and the Nuclear Engineering Material model Library (NEML). A diffused ellipsoidal heat source was calibrated against thermocouple data and weld macrographs to accurately model the fusion zone geometry and transient thermal fields. Material hardening is represented using the Lemaitre-Chaboche mixed isotropic-kinematic hardening model, while four annealing models - no annealing, single-stage at 1050 °C and 1300 °C, and two-stage at 800 °C/1300 °C - were implemented to assess the impact of annealing models on the accuracy of the predicted welding-induced plasticity, distortions, and residual stresses. The predictions were validated against experimental measurements and benchmarked against results from commercial software, demonstrating that thermo-mechanical MOOSE welding simulations achieve comparable accuracy with enhanced computational efficiency. This work highlights the potential of using open-source finite element frameworks like MOOSE for advanced manufacturing simulations.

Ji, Wendy [Australian Nuclear Science and Technolo↗

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↗