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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Sustainability and Reproducibility via Containerized Computing

Recent developments in the commercial open source community have catalysed the use of Linux containers for scalable deployment of web-based applications to the cloud. Scientific software can be containerized with dependencies, configuration files, post-processing tools and even simulation results, referred to as containerized computing. This new approach promises to significantly improve sustainability, productivity and reproducibility. In this article, we present our experiences, technology, and future plans for open source containerization of software used to model particle and radiation beams. Vagrant is central to our approach, using Docker for cloud deployment and VirtualBox virtual machines for deployment to Mac OS and Windows computers. Our technology enables seamless switching between the desktop and the cloud to simplify simulation development and execution.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four‐dimensional numerical model simulations is propelling the wider adoption of ultra‐resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well‐integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display‐to‐dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data‐intensive information. This information can be digital‐cinema animations, high‐resolution images, high‐definition video‐teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross‐platform, community‐driven, open‐source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Jedlovec, Gary↗
DOE OSTI2021

CSISAR--Complete System Integrated SAR

The CSISAR tool is GUI based and very simple to use. The algorithms are robust, and the unique processing flows, that the user is stepped through, virtually eliminate the possibility of error in GEOINT production. An integrated data manager is a key part of the CSISAR system. This data manager keeps track of the data available to a user and informs the user of what data is available and what can be done with that data. This keeps the user from having to be trained in the nuances of the algorithms. CSISAR also has an integrated product manager, which helps the user identify, view and manage previously made products. CSISAR was originally developed in 2010-2011 as a Windows based system. It was updated in 2015 to be a Linux based system. This SAND report is intended to make the Product Description and User’s Guide for CSISAR (originally included within the software) more widely available. New is a brief addition of Linux-specific installation details.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Three-Dimensional Audio Client Library

The Three-Dimensional Audio Client Library (3DAudio library) is a group of software routines written to facilitate development of both stand-alone (audio only) and immersive virtual-reality application programs that utilize three-dimensional audio displays. The library is intended to enable the development of three-dimensional audio client application programs by use of a code base common to multiple audio server computers. The 3DAudio library calls vendor-specific audio client libraries and currently supports the AuSIM Gold-Server and Lake Huron audio servers. 3DAudio library routines contain common functions for (1) initiation and termination of a client/audio server session, (2) configuration-file input, (3) positioning functions, (4) coordinate transformations, (5) audio transport functions, (6) rendering functions, (7) debugging functions, and (8) event-list-sequencing functions. The 3DAudio software is written in the C++ programming language and currently operates under the Linux, IRIX, and Windows operating systems.

Rizzi, Stephen A.↗
NASA NTRSDate not supplied

Rapid Spacecraft Payload Development: In-Orbit Demonstration of Flight Software Reuse, Scalability, and Dependability

As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.

computer programming↗
NASA NTRS2018

Increasing Flight Software Reuse with OpenSatKit

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospace's command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for users to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS "App Store".. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

Computer Programming and Software↗
NASA NTRS2018

Increasing Flight Software Reuse with OpenSatKit

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospaceâ€"TM"s command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for userâ€"TM"s to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS 'App Store'. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

McComas, David↗
DOE OSTI2014

FTP 100: An Ultra-High Speed Data Transfer Service Over Next Generation 100 Gigabit Per Second Network

Data-intensive applications, including high energy and nuclear physics, astrophysics, climate modeling, nano-scale materials science, genomics, and financing, are expected to generate exabytes of data over the coming years, which must be transferred, visualized, and analyzed by geographically distributed teams of users. High-performance network capabilities must be available to these users at the application level in a transparent, virtualized manner. Moreover, the application users must have the capability to move large datasets from local and remote locations across network environments to their home institutions. To solve these challenges, the main goal of our project is to design and evaluate high-performance data transfer software to support various data-intensive applications. First, we have designed a middleware software that provides access to Remote Direct Memory Access (RDMA) functionalities. This middleware integrates network access, memory management and multitasking in its core design. We address a number of issues related to its efficient implementation, for instance, explicit buffer management and memory registration, and parallelization of RDMA operations, which are vital to delivering the benefit of RDMA to the applications. Built on top of this middleware, an implementation and experimental evaluation of the RDMA-based FTP software, RFTP, is described and evaluated. This application has been implemented by our team to exploit the full capabilities of advanced RDMA mechanisms for ultra-high speed bulk data transfer applications on Energy Sciences Network (ESnet). Second, we designed our data transfer software to optimize TCP/IP based data transfer performance such that RFTP can be fully compatible with today’s Internet. Our kernel optimization techniques with Linux system calls sendfile and splice, can reduce data copy cost. In this report, we summarize the technical challenges of our project, the primary software design methods, the major project milestones achieved, as well as the testbed evaluation work and demonstrations during our project life time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Secure Storage Architectures

The purpose of this report is to clarify the challenges associated with storage for secure enclaves. The major focus areas for the report are: - review of relevant parallel filesystem technologies to identify assets and gaps; - review of filesystem isolation/protection mechanisms, to include native filesystem capabilities and auxiliary/layered techniques; - definition of storage architectures that can be used for customizable compute enclaves (i.e., clarification of use-cases that must be supported for shared storage scenarios); - investigate vendor products related to secure storage. This study provides technical details on the storage and filesystem used for HPC with particular attention on elements that contribute to creating secure storage. We outline the pieces for a a shared storage architecture that balances protection and performance by leveraging the isolation capabilities available in filesystems and virtualization technologies to maintain the integrity of the data. Key Points: There are a few existing and in-progress protection features in Lustre related to secure storage, which are discussed in (Chapter 3.1). These include authentication capabilities like GSSAPI/Kerberos and the in-progress work for GSSAPI/Host-keys. The GPFS filesystem provides native support for encryption, which is not directly available in Lustre. Additionally, GPFS includes authentication/authorization mechanisms for inter-cluster sharing of filesystems (Chapter 3.2). The limitations of key importance for secure storage/filesystems are: (i) restricting sub-tree mounts for parallel filesystem (which is not directly supported in Lustre or GPFS), and (ii) segregation of hosts on the storage network and practical complications with dynamic additions to the storage network, e.g., LNET. A challenge for VM based use cases will be to provide efficient IO forwarding of the parallel filessytem from the host to the guest (VM). There are promising options like para-virtualized filesystems to help with this issue, which are a particular instances of the more general challenge of efficient host/guest IO that is the focus of interfaces like virtio. A collection of bridging technologies have been identified in Chapter 4, which can be helpful to overcome the limitations and challenges of supporting efficient storage for secure enclaves. The synthesis of native filesystem security mechanisms and bridging technologies led to an isolation-centric storage architecture that is proposed in Chapter 5, which leverages isolation mechanisms from different layers to facilitate secure storage for an enclave. Recommendations: The following highlights recommendations from the investigations done thus far. - The Lustre filesystem offers excellent performance but does not support some security related features, e.g., encryption, that are included in GPFS. If encryption is of paramount importance, then GPFS may be a more suitable choice. - There are several possible Lustre related enhancements that may provide functionality of use for secure-enclaves. However, since these features are not currently integrated, the use of Lustre as a secure storage system may require more direct involvement (support). (*The network that connects the storage subsystem and users, e.g., Lustre s LNET.) - The use of OpenStack with GPFS will be more streamlined than with Lustre, as there are available drivers for GPFS. - The Manilla project offers Filesystem as a Service for OpenStack and is worth further investigation. Manilla has some support for GPFS. - The proposed Lustre enhancement of Dynamic-LNET should be further investigated to provide more dynamic changes to the storage network which could be used to isolate hosts and their tenants. - The Linux namespaces offer a good solution for creating efficient restrictions to shared HPC filesystems. However, we still need to conduct a thorough round of storage/filesystem benchmarks. - Vendor products should be more closely reviewed, possibly to include evaluation of performance/protection of select products. (Note, we are investigation the option of evaluating equipment from Seagate/Xyratex.) Outline: The remainder of this report is structured as follows: - Section 1: Describes the growing importance of secure storage architectures and highlights some challenges for HPC. - Section 2: Provides background information on HPC storage architectures, relevant supporting technologies for secure storage and details on OpenStack components related to storage. Note, that background material on HPC storage architectures in this chapter can be skipped if the reader is already familiar with Lustre and GPFS. - Section 3: A review of protection mechanisms in two HPC filesystems; details about available isolation, authentication/authorization and performance capabilities are discussed. - Section 4: Describe technologies that can be used to bridge gaps in HPC storage and filesystems to facilitate...

Aderholdt, Ferrol↗
DOE OSTI2022

NRAP-Open-IAM: NRAP Open Source Integrated Assessment Model

Note: This is the last version (a2.6.1) of NRAP-Open-IAM released during NRAP Phase II in 2022. The latest version of NRAP-Open-IAM is available here: https://edx.netl.doe.gov/dataset/phase-iii-nrap-open-iam NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability. NRAP-Open-IAM represents the next-generation in a line of systems-based computational models developed for quantitative geological carbon storage (GCS) risk assessment. The model comprises a set of reduced-order and analytical models of various components of the GCS system, potential leakage pathways, receptors of concern including impact to groundwater resources and the atmosphere, a framework to support stochastic simulation, time stepping, uncertainty quantification, other analytical functionality for scenario and risk-performance evaluation, and a basic graphical user interface to support scenario development, data input simulation definition, and basic post-processing and results display. As the NRAP Open-IAM functionality continues to evolve, we continue to add to its capability to develop quantitative, probabilistic, and time-dependent profiles of the evolution of risk at a GCS site and evaluate the influence of uncertain parameters on uncertainty in predicted risk. It can be used to quantify the dynamics of reservoir saturation plume and pressure-affected area, for evaluation of the area of potential groundwater impact (i.e., Area of Review) and monitoring requirements to support cost and regulatory analysis, and for consideration of different post-injection site care and closure scenarios. This submission contains the current version of NRAP-Open-IAM available for evaluation and testing. To use the NRAP-Open-IAM, download the source code (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/4c24a3da-3b40-4ffe-9892-c807ae9f8760) then open the NRAP-Open-IAM user's guide (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669) to read more about the tool. Installation instructions for Windows, Mac, and Linux can be found in the "installers" folder of the extracted NRAP-Open-IAM folder and describe setup of environment (e.g., Python libraries) needed for proper work of the tool. Test of installation can be done by running "python openiam_setup_tests.py" in the "setup" folder. The installation test also runs a test suite to see if the NRAP-Open-IAM has been installed correctly. To run the test suite separately, run "python iam_test.py" in the "test" folder. User's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669 Developer's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/3bc6ee7d-609d-4eb6-80ba-fa6130ee0313 Reservoir simulation data used in some examples distributed with NRAP-Open-IAM: - Kimberlina: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/eb62cece-61b2-4037-9b6d-32407dde2ab8 - Kimberlina (compartmentalized): https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/366f9530-3b32-4b84-affe-ab2df1d9a8b5 - FutureGen 2.0: https://edx.netl.doe.gov/dataset/futuregen-2-0-1008-simulation-reservoir-lookup-table NRAP-Open-IAM GitLab repository: https://gitlab.com/NRAP/OpenIAM Related publications: - Bacon, D., Yonkofski, C., Brown, C., Demirkanli, D. and Whiting, J., 2019. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM. International Journal of Greenhouse Gas Control 90: 102784. - Bacon, D. Demirkanli, D., and White, S., 2020. Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site. International Journal of Greenhouse Gas Control 102: 103153. - Harp, D., Oldenburg, C., and Pawar, R., 2019. A metric for evaluating conformance robustness during geologic CO2 sequestration operations. International Journal of Greenhouse Gas Control 85: 100-108. - Lackey, G., Vasylkivska, V., Huerta, N., King, S., and Dilmore, R., 2019. Managing well leakage risks at a geologic carbon storage site with many wells, International Journal of Greenhouse Gas Control, 88 :182-194. - Vasylkivska, V., Dilmore, R., Lackey, G., Zhang, Y., King, S., Bacon, D., Chen, B., Mansoor, K., and Harp, D., 2021. NRAP-Open-IAM: A flexible open-source integrated assessment model for geologic carbon storage risk assessment and management, Environmental Modelling & Software, 143: 105114. Presentations: - Chen, B., Harp, D., and Pawar, R., A data assimilation approach (ES-MDA) coupling with NRAP-Open-IAM for quantifying uncertainty reduction in geological CO2 sequestration. AGUFM 2019: T44A-02. - Chen, B., and Harp, D., Improving risk analysis precision for geologic CO2 sequestration by quantifying the uncertainty reduction before and after acquiring monitoring data. 14th Greenhouse Gas Control Technologies Conference, Melbourne, Australia, 2018, pp. 21-26. - Harp, D., National Risk Assessment Partnership Task 2: Containment Assurance. No. LA-UR-19-28654, Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2019. - Vasylkivska, V., King, S., Bacon, D., Harp, D., Chen, B., Mansoor, K., Onishi, T., Yang, Y., Zhang, Y., and Keating, E., NRAP-Open-IAM: An open-source integrated assessment model, poster, Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA, August 13-16, 2018. - Vasylkivska, V., Lackey, G., King, S., Wentworth, A., Huerta, N., Creason, C., DiGiulio, J., Yang, Y., and Dilmore, R., Long-term risk analysis of a geologic CO2 storage project during the post-injection period, SIAM Conference on Computational Science and Engineering, Spokane, WA, February 25-March 1, 2019. - Vasylkivska, V., Overview of the NRAP-Open-IAM tool for carbon storage (beta release), 2019 Annual NRAP Tool Users Meeting, Pittsburgh, PA, August 27, 2019. - Vasylkivska, V., Bacon, D., Chen, B., Dilmore, R., Harp, D., King, S., Lackey, G., Lindner, E., Liu, G., Mansoor, K. and Zhang, Y., NRAP-Open-IAM: A new, open-source code for integrated assessment of geologic carbon storage containment effectiveness and leakage risk, poster, American Geophysical Union Fall Meeting 2020 (virtual meeting), December 2020. - Vasylkivska, V., NRAP open-source integrated assessment model and relevant application, oral presentation, NRAP workshop "NRAP Tools for Geologic Carbon Storage Risk-Based Decision Making" held in conjunction with Groundwater Protection Council (GWPC) 2021 Annual Forum (virtual meeting), Salt Lake City, UT, September 2021. - Vasylkivska, V., NRAP-Open-IAM: open-source integrated assessment model, digital poster/demonstration, software demonstration session, 2022 Carbon Management Project Review Meeting, August 16, 2022

AoR↗