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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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NASA NTRS2024

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗

NASA NTRS2002

The Efficiency and the Scalability of an Explicit Operator on an IBM POWER4 System

We present an evaluation of the efficiency and the scalability of an explicit CFD operator on an IBM POWER4 system. The POWER4 architecture exhibits a common trend in HPC architectures: boosting CPU processing power by increasing the number of functional units, while hiding the latency of memory access by increasing the depth of the memory hierarchy. The overall machine performance depends on the ability of the caches-buses-fabric-memory to feed the functional units with the data to be processed. In this study we evaluate the efficiency and scalability of one explicit CFD operator on an IBM POWER4. This operator performs computations at the points of a Cartesian grid and involves a few dozen floating point numbers and on the order of 100 floating point operations per grid point. The computations in all grid points are independent. Specifically, we estimate the efficiency of the RHS operator (SP of NPB) on a single processor as the observed/peak performance ratio. Then we estimate the scalability of the operator on a single chip (2 CPUs), a single MCM (8 CPUs), 16 CPUs, and the whole machine (32 CPUs). Then we perform the same measurements for a chache-optimized version of the RHS operator. For our measurements we use the HPM (Hardware Performance Monitor) counters available on the POWER4. These counters allow us to analyze the obtained performance results.

Frumkin, Michael↗

NASA NTRSDate not supplied

Advanced Information Systems Technology for NASA Earth System Digital Twins (ESDT)

ESA and NASA have both started programs to design and develop Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. Earth System Digital Twins integrate diverse Earth and human activity models, continuous observations, and information system capabilities to provide unified, comprehensive representations and predictions that can be utilized for monitoring the health of the Planet, as well as for developing actionable information to support decision making. More generally, Digital Twins will help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change. This Townhall will first provide a short description of ESA’s, NASA’s and CNES’s current efforts in Digital Twins: • Destination Earth (DestinE) is the first initiative of the European Union to create a Digital Twin of the Earth, particularly focused on weather and climate, and as a coordinated effort between the European Centre for Medium-Range Weather Forecasts (ECMWF), ESA and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). • Additionally, ESA is developing several Digital Twin Earth Precursor Activities to study some of the key scientific and technical challenges associated with building a “Digital Twin Earth”. These include forests, hydrology, Antarctica, food systems, oceans, and climate hot spots Digital Twin prototypes. • NASA Earth Science Technology Office (ESTO)’s Advanced Information Systems Technology (AIST) Program has started an initiative in Earth System Digital Twins (ESDT), with 14 current projects in this area, developing various information systems technologies and prototypes that will help prepare the development of future NASA Digital Twins. • CNES is currently developing the concept of a Digital Twin Factory (DTF), which relies on a data lake, a high computing capability using clouds and/or HPC and has thematic algorithms and methodologies able to generate registered and coherent layers of information in order to enrich a datacube from which physical indicators can be computed spatially. NASA, ESA and CNES are also currently defining science use cases that will be presented during the townhall; those and a few short discussions of current projects will serve as a starting point to engage a dialogue about Digital Twins of the Earth with the IGARSS community.

earth science remote sensing; Information systems↗