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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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Synchronization done by hardware to reduce software overhead. Computing resources located at both master-arm node and slave-arm node. This architecture provides for effective control while reducing computational burden on host computer and reducing and balancing load on communication channel.
NASAs Space Communication and Navigation(SCaN) Testbed was launched to the International Space Station in 2012. The objective is to promote new software defined radio technologies and associated software application reuse, enabled by this first flight of NASAs Space Telecommunications Radio System(STRS) architecture standard. Pre-launch testing with the testbeds software defined radios was performed as part of system integration. Radio services for the JPL SDR were developed during system integration to allow the waveform application to operate properly in the space environment, especially considering thermal effects. These services include receiver gain control, frequency offset, IQ modulator balance, and transmit level control. Development, integration, and environmental testing of the radio services will be described. The added software allows the waveform application to operate properly in the space environment, and can be reused by future experimenters testing different waveform applications. Integrating such services with the platform provided STRS operating environment will attract more users, and these services are candidates for interface standardization via STRS.
The purpose of this document is to describe the GNC architecture and associated interfaces for all ARES simulations. Establishing a common architecture facilitates development across the ARES simulations and provides an efficient mechanism for creating an end-to-end simulation capability. In general, the GNC architecture is the frame work in which all GNC development takes place, including sensor and effector models. All GNC software applications have a standard location within the architecture making integration easier and, thus more efficient.
The development of numerical methods and software tools for parallel processors can be aided through the use of a hardware test-bed. The test-bed architecture must be flexible enough to support investigations into architecture-algorithm interactions. One way to implement a test-bed is to use a commercial parallel processor. Unfortunately, most commercial parallel processors are fixed in their interconnection and/or processor architecture. In this paper, we describe a modified n cube architecture, called the hypercluster, which is a superset of many other processor and interconnection architectures. The hypercluster is intended to support research into parallel processing of computational fluid and structural mechanics problems which may require a number of different architectural configurations. An example of how a typical partial differential equation solution algorithm maps on to the hypercluster is given.
We describe the autonomous control architecture for the JPL Mission Data System (MDS). MDS is a comprehensive new software infrastructure for supporting unmanned space exploration. The autonomous control architecture is one component of MDS designed to enable autonomous operations.
Designed and implemented in the 1980's, the Advanced Multi-Mission Operations System (AMMOS) was a breakthrough for deep-space NASA missions, enabling significant reductions in the cost and risk of implementing ground systems. By designing a framework for use across multiple missions and adaptability to specific mission needs, AMMOS developers created a set of applications that have operated dozens of deep-space robotic missions over the past 30 years. We seek to leverage advances in technology and practice of architecting and systems engineering, using model-based approaches to update the AMMOS. We therefore revisit fundamental aspects of the AMMOS, resulting in a major update to the Mission Operations System (MOS): MOS 2.0. This update will ensure that the MOS can support an increasing range of mission types, (such as orbiters, landers, rovers, penetrators and balloons), and that the operations systems for deep-space robotic missions can reap the benefits of an iterative multi-mission framework.12 This paper reports on the first phase of this major update. Here we describe the methods and formal semantics used to address MOS 2.0 architecture and some early results. Early benefits of this approach include improved stakeholder input and buy-in, the ability to articulate and focus effort on key, system-wide principles, and efficiency gains obtained by use of well-architected design patterns and the use of models to improve the quality of documentation and decrease the effort required to produce and maintain it. We find that such methods facilitate reasoning, simulation, analysis on the system design in terms of design impacts, generation of products (e.g., project-review and software-delivery products), and use of formal process descriptions to enable goal-based operations. This initial phase yields a forward-looking and principled MOS 2.0 architectural vision, which considers both the mission-specific context and long-term system sustainability.
Future expeditions will enable exploration and study of the planetary surfaces of the Moon and Mars by performing extravehicular activity (EVA) operations. Present-day International Space Station (ISS) EVA operations require an intricate choreography of crew, space suits, tools, systems, and flight teams to plan, train, and execute with limited advanced informatics. In this paper, the Joint Augmented Reality Visual Informatics System (Joint AR) project team at NASA Johnson Space Center (JSC) characterizes the design space for developing a modular augmented reality (AR) device for a spacesuit form factor that can support crew decision-making for EVA. The Joint AR product was defined via trade studies and market analysis of previous EVA display efforts, various AR components such as optics, commercial AR systems, light engines, data interfaces, and graphics engine software. This paper outlines the defining architectural design decisions, including safety criticality considerations, interfaces, and computer architectures. The outcomes of these studies result in a prototype design which is defined here as the Joint AR product. This work aims to enable a community-wide discussion toward realizing necessary suit-compatible AR features and capabilities for future missions.
Future expeditions will enable exploration and study of the planetary surfaces of the Moon and Mars by performing extravehicular activity (EVA) operations. Present-day International Space Station (ISS) EVA operations require an intricate choreography of crew, space suits, tools, systems, and flight teams to plan, train, and execute with limited advanced informatics. In this paper, the Joint Augmented Reality Visual Informatics System (Joint AR) project team at NASA Johnson Space Center (JSC) characterizes the design space for developing a modular augmented reality (AR) device for a spacesuit form factor that can support crew decision-making for EVA. The Joint AR product was defined via trade studies and market analysis of previous EVA display efforts, various AR components such as optics, commercial AR systems, light engines, data interfaces, and graphics engine software. This paper outlines the defining architectural design decisions, including safety criticality considerations, interfaces, and computer architectures. The outcomes of these studies result in a prototype design which is defined here as the Joint AR product. This work aims to enable a community-wide discussion toward realizing necessary suit-compatible AR features and capabilities for future missions.
This paper presents the interim results from the Software Engineering Laboratory's (SEL) Reuse Study. The team conducting this study has, over the past few months, been studying the Generalized Support Software (GSS) domain asset library and architecture, and the various processes associated with it. In particular, we have characterized the process used to configure GSS-based attitude ground support systems (AGSS) to support satellite missions at NASA's Goddard Space Flight Center. To do this, we built detailed models of the tasks involved, the people who perform these tasks, and the interdependencies and information flows among these people. These models were based on information gleaned from numerous interviews with people involved in this process at various levels. We also analyzed effort data in order to determine the cost savings in moving from actual development of AGSSs to support each mission (which was necessary before GSS was available) to configuring AGSS software from the domain asset library. While characterizing the GSS process, we became aware of several interesting factors which affect the successful continued use of GSS. Many of these issues fall under the subject of evolving technologies, which were not available at the inception of GSS, but are now. Some of these technologies could be incorporated into the GSS process, thus making the whole asset library more usable. Other technologies are being considered as an alternative to the GSS process altogether. In this paper, we outline some of issues we will be considering in our continued study of GSS and the impact of evolving technologies.
Fault Management (FM) systems are ranked high in risk-based assessment of criticality within flight software, emphasizing the importance of establishing highly competent domain expertise to provide assurance for NASA projects, especially as spaceflight systems continue to increase in complexity. Insight into specific characteristics of FM architectures seen embedded within safety- and mission-critical software systems analyzed by the NASA Independent Verification Validation (IVV) Program has been enhanced with an FM Technical Reference (TR) suite. Benefits are aimed beyond the IVV community to those that seek ways to efficiently and effectively provide software assurance to reduce the FM risk posture of NASA and other space missions. The identification of particular FM architectures, visibility, and associated IVV techniques provides a TR suite that enables greater assurance that critical software systems will adequately protect against faults and respond to adverse conditions. The role FM has with regard to overall asset protection of flight software systems is being addressed with the development of an adverse condition (AC) database encompassing flight software vulnerabilities.Identification of potential off-nominal conditions and analysis to determine how a system responds to these conditions are important aspects of hazard analysis and fault management. Understanding what ACs the mission may face, and ensuring they are prevented or addressed is the responsibility of the assurance team, which necessarily should have insight into ACs beyond those defined by the project itself. Research efforts sponsored by NASAs Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs, and allowing queries based on project, mission type, domain component, causal fault, and other key characteristics. The repository has a firm structure, initial collection of data, and an interface established for informational queries, with plans for integration within the Enterprise Architecture at NASA IVV, enabling support and accessibility across the Agency. The development of an improved workflow process for adaptive, risk-informed FM assurance is currently underway.
Work carried out to re-engineer the mission analysis segment of JPL's mission planning ground system architecture is reported on. The aim is to transform the existing software tools, originally developed for specific missions on different support environments, into an integrated, general purpose, multi-mission tool set. The issues considered are: the development of a partnership between software developers and users; the definition of key mission analysis functions; the development of a consensus based architecture; the move towards evolutionary change instead of revolutionary replacement; software reusability, and the minimization of future maintenance costs. The current status and aims of new developments are discussed and specific examples of cost savings and improved productivity are presented.
In early 2015 the United States Department of Energy conceived of a consortium of collaborative bodies based on shared expertise, data, and resources that could be targeted towards the more difficult problems in energy materials research. The concept of virtual laboratories had been envisioned and discussed earlier in the decade in response to the advent of the Materials Genome Initiative and similar scientific thrusts. To be effective, any virtual laboratory needed a robust method for data management, communication, security, data sharing, dissemination, and demonstration to work efficiently and effectively for groups of remote researchers. With the accessibility of new, easily deployed cloud technology and software frameworks, such individual elements could be integrated, and the required collaboration architecture is now possible. The developers have leveraged open-source software frameworks, customized them, and merged them into a platform to enable collaborative energy materials science, regardless of the geographic dispersal of the people and resources. After five years in operations, the systems are demonstratively an effective platform for enabling research within the Energy Material Networks (EMN). This paper will show the design and development of a secured scientific data sharing platform, the ability to customize the system to support diverse workflows, and examples of the enabled research and results connected with some of the Energy Material Networks.
Scientific visualization software increasingly needs to support many-core architectures. However, development time is a significant challenge due to the breadth and diversity of both visualization algorithms and architectures. With this work, we introduce a development environment for visualization algorithms on many-core devices that extends the traditional data-parallel primitive (DPP) approach with several existing constructs and an important new construct: meta-DPPs. We refer to our approach as MCD 3 — Meta-DPPs, Convenience routines, Data management, DPPs, and Devices. The twin goals of MCD 3 are to reduce developer time and to deliver efficient performance on many-core architectures, and our evaluation considers both of these goals. For development time, we study 57 algorithms implemented in the VTK-m software library and determine that MCD 3 leads to significant savings. For efficient performance, we survey ten studies looking at individual algorithms and determine that the MCD 3 hardware-agnostic approach leads to performance comparable to hardware-specific approaches: sometimes better, sometimes worse, and better in the aggregate. In total, we find that MCD 3 is an effective approach for scientific visualization libraries to support many-core architectures.
There is a need for simple, fast, and memory-efficient multidimensional data structures for dense and sparse storage that arise with numerical methods and in software applications. The data structures must perform equally well across multiple computer architectures, including CPUs and GPUs. For this purpose, we developed MATAR, a C++ software library that allows for simple creation and use of intricate data structures that is also portable across disparate architectures using Kokkos. Here, the performance aspect is achieved by forcing contiguous memory layout (or as close to contiguous as possible) for multidimensional and multi-size dense or sparse MATrix and ARray (hence, MATAR) types. Our results show that MATAR has the capability to improve memory utilization, performance, and programmer productivity in scientific computing. This is achieved by fitting more work into the available memory, minimizing memory loads required, and by loading memory in the most efficient order. This document describes the purpose of the work, the implementation of each of the data types, and the resulting performance both in some simple baseline test cases and in an application code.
We report prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.
The Artificial Intelligence Enhanced Co-Design for Next Generation Microelectronics virtual workshop was held April 4-5, 2023, and attended by subject matter experts from universities, industry, and national laboratories. This was the third in a series of workshops to motivate the research community to identify and address major challenges facing microelectronics research and production. The 2023 workshop focused on a set of topics from materials to computing algorithms, and included discussions on relevant federal legislation and such as the Creating Helpful Incentives to Produce Semiconductors and Science Act (CHIPS Act) which was signed into law in the summer of 2022. Talks at the workshop included edge computing in radiation environments, new materials for neuromorphic computing, advanced packaging for microelectronics, and new AI techniques. We also received project updates from several of the Department of Energy (DOE) microelectronics co-design projects funded in the fall of 2021, and from three of the Energy Frontier Research Centers (EFRCs) that had been funded in the fall of 2022. The workshop also conducted a set of breakout discussions around the five principal research directions (PRDs) from the 2018 Department of Energy workshop report: 1) define innovative material, device, and architecture requirements driven by applications, algorithms, and software; 2) revolutionize memory and data storage; 3) re-imagine information flow unconstrained by interconnects; 4) redefine computing by leveraging unexploited physical phenomena; 5) reinvent the electricity grid through new materials, devices, and architectures. We tasked each breakout group to consider one primary PRD (and other PRDs as relevant topics arose during discussions) and to address questions such as whether the research community has embraced co-design as a methodology and whether new developments at any level of innovation from materials to programming models requires the research community to reevaluate the PRDs developed back in 2018.
NASA established the Small Explorer (SMEX) program in 1988 to provide frequent opportunities for highly focused and relatively inexpensive space science missions that can be launched into low earth orbit by small expendable vehicles. The development schedule for each SMEX spacecraft was three years from start to launch. The SMEX program has produced five satellites; Solar Anomalous and Magnetospheric Particle Explorer (SAMPEX), Fast Auroral Snapshot Explorer (FAST), Submillimeter Wave Astronomy Satellite (SWAS), Transition Region and Coronal Explorer (TRACE) and Wide-Field Infrared Explorer (WIRE). SAMPEX and FAST are on-orbit, TRACE is scheduled to be launched in April of 1998, WIRE is scheduled to be launched in September of 1998, and SWAS is scheduled to be launched in January of 1999. In each of these missions, the Attitude Control System (ACS) software was written using a modular procedural design. Current program goals require complete spacecraft development within 18 months. This requirement has increased pressure to write reusable flight software. Object-Oriented Design (OOD) offers the constructs for developing an application that only needs modification for mission unique requirements. This paper describes the OOD that was used to develop the SMEX-Lite ACS software. The SMEX-Lite ACS is three-axis controlled, momentum stabilized, and is capable of performing sub-arc-minute pointing. The paper first describes the high level requirements which governed the architecture of the SMEX-Lite ACS software. Next, the context in which the software resides is explained. The paper describes the benefits of encapsulation, inheritance and polymorphism with respect to the implementation of an ACS software system. This paper will discuss the design of several software components that comprise the ACS software. Specifically, Object-Oriented designs are presented for sensor data processing, attitude control, attitude determination and failure detection. The paper addresses the benefits of the OOD versus a conventional procedural design. The final discussion in this paper will address the establishment of the ACS Foundation Class (AFC) Library. The AFC is a large software repository, requiring a minimal amount of code modifications to produce ACS software for future projects, saving production time and costs.
During the software development life cycle process, basic testing starts with the development team. At the end of the development process, an acceptance test is performed for the user to ensure that the deliverable is acceptable. Ideally, the delivery is an operational product with zero defects. However, the goal of zero defects is normally not achieved but is successful to various degrees. With the emphasis on building low cost ground support systems while maintaining a quality product, a key element in the test process is simulator capability. This paper reviews the Transportable Payload Operations Control Center (TPOCC) Advanced Spacecraft Simulator (TASS) test tool that is used in the acceptance test process for unmanned satellite operations control centers. The TASS is designed to support the development, test and operational environments of the Goddard Space Flight Center (GSFC) operations control centers. The TASS uses the same basic architecture as the operations control center. This architecture is characterized by its use of distributed processing, industry standards, commercial off-the-shelf (COTS) hardware and software components, and reusable software. The TASS uses much of the same TPOCC architecture and reusable software that the operations control center developer uses. The TASS also makes use of reusable simulator software in the mission specific versions of the TASS. Very little new software needs to be developed, mainly mission specific telemetry communication and command processing software. By taking advantage of the ground data system attributes, successful software reuse for operational systems provides the opportunity to extend the reuse concept into the test area. Consistency in test approach is a major step in achieving quality results.