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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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LiveCheckHSI: a Hardware/Software Co-verification Tool for Hyperspectral Imaging Systems with Embedded System-on-Chip Instrument Avionics
The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This paper describes hardware/software co-verification tools for the Xilinx Zynq-based control and data handling system that have been developed at the Jet Propulsion Laboratory (JPL) for visible-infrared imaging spectrometers. The system acquires and compresses images in real-time, in addition to programming the spectrometer (frame rate, exposure time), focus step motor, and heaters and reporting telemetry.
Augmenting Data Systems with Prediction Based Embeddings
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Using a Model of Scheduler Runtime to Improve the Effectiveness of Scheduling Embedded in Execution
Scheduling often interacts with execution. When the scheduler is developing a schedule, real time (execution) proceeds. Usually a scheduler cannot modify portions of the schedule expected to start execution prior to the scheduler's expected completion. In deployed systems, often little effort is spent on predicting scheduler runtime and instead an extremely conservative, simple model is used, resulting in loss of performance as less of the schedule can be updated. We develop predictive model(s) of scheduler runtime and use these models to improve scheduler and execution performance. We present several models of scheduler runtime based on a scheduler being deployed onboard NASA's next Mars rover, the M2020 rover Perseverance. The models consider algorithmic complexity, characteristics of the input plan, and prior runtime data. First, we show how these still relatively unsophisticated models can more accurately predict scheduler runtime compared to the static conservative baseline being used for the actual M2020 onboard scheduler. Second, we show how the more accurate scheduler runtime models' tighter (shorter) runtime predictions enable better scheduler performance as measured by makespan and percentage of activities executed. Finally, we discuss a number of future steps to further advance this line of work.
Embedded Force Sensing System for Mars Sample Return Arm Gripper
No abstract provided
Barefoot Rover: a Sensor-Embedded Rover Wheel Demonstrating In-Situ Engineering and Science Extractions using Machine Learning
No abstract provided
Barefoot Rover: A Sensor-Embedded Rover Wheel Demonstrating In-Situ Engineering and Science Extractions Using Machine Learning
No abstract provided
Embedding Climate Change in Urban Planning and Urban Design in New York City
Confronting the challenges of a rapidly urbanizing world threatened by climate change requires expanding the traditional influence and capabilities of urban planning and urban design, integrating climate science, natural systems and compact urban form to configure dynamic, desirable and healthy communities. Cost-effective planning and design measures that help mitigate emissions while bringing adaptive benefits should be prioritized. The chapter draws from the publication Climate Change and Cities (Cambridge University Press 2018) by the Urban Climate Change Research Network (UCCRN). The two-phase New York City case study by the Urban Design Climate Lab at the New York Institute of Technology and a team of international urban design climate experts illustrates how this emerging expertise can be replicated and implemented worldwide. Its focus on configuring people-centered public spaces that enhance energy efficiency and improve public health draws from four urban climate factors: improving efficiency of urban systems, both in energy and transportation; optimizing the form and layout of urban districts to enhance ventilation; promoting appropriate building materials with high reflectivity; and increasing green and blue urban infrastructure. The chapter highlights a set of tools and methods to measure success.
Nylon-11 Nanowires Embedded in Flexible Substrates for Piezoelectric Transducers
Nylon-11 nanowires have been fabricated in flexible track-etched polymer templates. Customized fabrication equipment was employed to realize an air-flow and gravity assisted template-wetting synthesis technique. X-ray diffraction analysis suggests that the strength of the piezoelectric phase of the nanowire crystals is directly proportional to the air-flow.
Embedding Differential Dynamic Logic in PVS
Runtime assurance is a control framework where a complex controller operates under the observation of a monitor. If the monitor detects the controller exhibiting undesirable behavior, control is passed off to a trusted controller until a desirable state is regained. The runtime assurance architecture provides a layer of assurance to the system being controlled, but special care must be taken that the resulting overall system, consisting of the monitors and controllers, is behaving as intended. This talk aims to formally model and reason about runtime assurance-equipped systems as hybrid programs- which are models that consist of both discrete and continuous components. Using the verification tool Plaidypvs, safety properties of some examples involving RTA architectures is shown.
Requirement Discovery Using Embedded Knowledge Graph with ChatGPT
- NASA’s Air Traffic Management-Exploration (ATM-X) Urban Air Mobility (UAM) Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future. - (see https://www.nasa.gov/uam-overview/ for more information) - The complexity of UAM airspace, and its evolution through a series of transformative epochs, requires a planning tool to effectively organize, integrate, and communicate the research that will guide the evolution of UAM operations in the National Airspace System (NAS). - The planning tool, called the UAM airspace research roadmap (or just roadmap), is being developed as a new system engineering methodology leveraging model based system engineering (MBSE) and artificial intelligence capabilities. This presentation gives an overview of the Knowledge Graph and ChatGPT applications within this system engineering methodology and will describe how it is being used to meet the ATM-X UAM Airspace Subproject’s overarching research goals.
Requirement Discovery Using Embedded Knowledge Graph With ChatGPT Video Demo
An overview of the UAM chatbot application.