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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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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sensing Service Transformer Secondary Currents using Planar Magnetic Pick-up Coils

The rapid deployment of distributed energy resources (DERs) is creating stresses on utility assets in the distribution networks. The service transformer, which is the most commonly used utility asset is often not monitored, since the cost of available sensing solutions is as high as the transformer itself. This paper presents a method to use an array of printed circuit board coils to intelligently monitor North American pole top service transformers. The approach, uses a novel, self-calibrating algorithm to infer the fixed geometry of the installation, by recording data over an extended period of time. The proposed method can enable rapid installation of a non-intrusive sensor that can be used to monitor loading levels of the distribution transformer. Furthermore, these sensors can help in planning, prognostics and advanced situational awareness for utilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Spy in the GPU-box: Covert and Side Channel Attacks on Multi-GPU System

The deep learning revolution has been enabled in large part by GPUs, and more recently accelerators, which make it possible to carry out computationally demanding training and inference in acceptable times. As the size of machine learning networks and workloads continues to increase, multi-GPU machines have emerged as an important platform offered on High Performance Computing and cloud data centers. Since these machines are shared among multiple users, it becomes increasingly important to protect applications against potential attacks. In this paper, we explore the vulnerability of Nvidia's DGX multi-GPU machines to covert and side channel attacks. These machines consist of a number of discrete GPUs that are interconnected through a combination of custom interconnect (NVLink) and PCIe connections. We reverse engineer the interconnected cache hierarchy and show that it is possible for an attacker on one GPU to cause contention on the L2 cache of another GPU. We use this observation to first develop a covert channel attack across two GPUs, achieving the best bandwidth of around 4 MB/s. We also develop a prime and probe attack on a remote GPU allowing an attacker to recover the cache access pattern of another workload. This access pattern can be used in any number of side channel attacks: we demonstrate a proof of concept attack that fingerprints the application running on the remote GPU, with high accuracy. We also develop a proof of concept attack to extract hyperparameters of a machine learning workload. Our work establishes for the first time the vulnerability of these machines to microarchitectural attacks and can guide future research to improve their security.

Dutta, Sankha↗
DOE OSTI2022

ornladios/ADIOS2

ADIOS 2: The Adaptable Input Output (I/O) System version 2 is an open-source framework that addresses scientific data management challenges, e.g. scalable parallel I/O, as we approach the exascale era in high-performance computing (HPC). ADIOS 2 bindings are available in C++, C, Fortran, Python and can be used on supercomputers, personal computers, and cloud systems running on Linux, macOS and Windows. ADIOS 2 has out-of-the-box support for MPI and serial environments.

ECP↗
DOE OSTI2025

Adaptive Computing (AC) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Renewable Energy Laborato↗
DOE OSTI2026

Adaptive Computing (AC) (Open Source) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly, adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Laboratory of the Rockies↗
DOE OSTI2020

The Impacts of Horizontal Grid Spacing and Cumulus Parameterization on Subseasonal Prediction in a Global Convection-Permitting Model

Monthlong simulations targeting four Madden–Julian oscillation events made with several global model configurations are verified against observations to assess the roles of grid spacing and convective parameterization on the representation of tropical convection and midlatitude forecast skill. Specifically, the performance of a global convection-permitting model (CPM) configuration with a uniform 3-km mesh is compared to that of a global 15-km mesh with and without convective parameterization, and of a variable-resolution “channel” simulation using 3-km grid spacing only in the tropics with a scale-aware convection scheme. It is shown that global 3-km simulations produce realistic tropical precipitation statistics, except for an overall wet bias and delayed diurnal cycle. The channel simulation performs similarly, although with an unrealistically higher frequency of heavy rain. The 15-km simulations with and without cumulus schemes produce too much light and heavy tropical precipitation, respectively. Without convection parameterization, the 15-km global model produces unrealistically abundant, short-lived, and intense convection throughout the tropics. Only the global CPM configuration is able to capture eastward-propagating Madden–Julian oscillation events, and the 15-km runs favor stationary or westward-propagating convection organized at the planetary scale. The global 3-km CPM exhibits the highest extratropical forecast skill aloft and at the surface, particularly during week 3 of each hindcast. Although more cases are needed to confirm these results, this study highlights many potential benefits of using global CPMs for subseasonal forecasting. Furthermore, results show that alternatives to global convection-permitting resolution—using coarser or spatially variable resolution—feature compromises that may reduce their predictive performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Microcam: A Low Power and Privacy Preserving Multi-modal Platform for Occupancy Detection (Final Report)

Heating, ventilation, and air conditioning (HVAC) consumes a significant portion of the energy used in buildings. Much of this is wasted energy, used when buildings are either not occupied at all, or occupied well under their maximum design conditions. This project has focused on residential occupancy detection to autonomously control HVAC systems and save energy. Limitations of existing occupancy sensors include one or more of the following: (i) they employ sensors or algorithms that are not able to detect stationary occupants; (ii) they cannot classify the source of the motion (such as a pet); (iii) depending on the camera resolution and employed algorithms, they do not allow for embedded or onboard computation, and require external or cloud-based processing; (iv) many algorithms developed for camera-based systems are sensitive to lighting changes, and thus prone to missed detections or false alarms; (v) Most existing systems depend on adjustment of settings for different scenarios, complicating self-commissioning; (vi) they cannot provide high enough accuracy; (vii) they are costly; (viii) they are not battery-powered, thus limiting ease of use and installation. In this project, Syracuse University and its partner SRI have developed a low-cost, high accuracy, standalone residential occupancy sensing platform, referred to as the MicroCam, to address all of the aforementioned challenges. MicroCam can operate on typical alkaline batteries without relying on the “cloud” or external computing resources, and consists of low-power, Artificial Intelligence (AI)-based, IoT platforms. Each platform has multi-modal sensors and can process motion, audio and video data, and send binary occupancy result to a lead platform. All sensor data is processed locally on platforms, and the only transmitted data is the binary occupancy state. In addition, preliminary work has been done on images wherein occupants are not discernable. Thus, MicroCam is a standalone solution preserving privacy of the occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1984

Large-scale turbulence in the Jovian atmosphere

Voyager 1 and 2 image pairs taken one rotation period (10 hr) apart are analyzed in order to compute average cloud velocities in the Jovian atmosphere, as well as to study the global energetics of the processes, in particular the sign and the magnitude of the energy transfer from the fluctuating to the mean flow. Particular attention is paid to the Great Red Spot phenomenon; it is suggested to have originated as a small vortex extracting energy from the surrounding flow. Since the eddy, presently in its near-equilibrium state, has reached a considerable size, while the mean shear lies close to that of a neutrally stable profile, it can be concluded that the presence of one large eddy precludes the growth of any others in the depleted mean shear.

Mitchell, J. L.↗
NASA NTRS1986

Turbulent dispersion of the icing cloud from spray nozzles used in icing tunnels

To correctly simulate flight in natural icing conditions, the turbulence in an icing simulator must be as low as possible. But some turbulence is required to mix the droplets from the spray nozzles and achieve an icing cloud of uniform liquid water content. The goal for any spray system is to obtain the widest possible spray cloud with the lowest possible turbulence in the test section of a icing tunnel. This investigation reports the measurement of turbulence and the three-dimensional spread of the cloud from a single spray nozzle. The task was to determine how the air turbulence and cloud width are affected by spray bars of quite different drag coefficients, by changes in the turbulence upstream of the spray, the droplet size, and the atomizing air. An ice accretion grid, located 6.3 m downstream of the single spray nozzle, was used to measure cloud spread. Both the spray bar and the grid were located in the constant velocity test section. Three spray bar shapes were tested: the short blunt spray bar used in the NASA Lewis Icing Research Tunnel, a thin 14.6 cm chord airfoil, and a 53 cm chord NACA 0012 airfoil. At the low airspeed (56 km/hr) the ice accretion pattern was axisymmetric and was not affected by the shape of the spray bar. At the high airspeed (169 km/hr) the spread was 30 percent smaller than at the low airspeed. For the widest cloud the spray bars should be located as far upstream in the low velocity plenum of the icing tunnel. Good comparison is obtained between the cloud spread data and predicitons from a two-dimensional cloud mixing computer code using the two equation turbulence (k epsilon g) model.

Marek, C. J.↗
NASA NTRS1990

Description of SAFIRE for ISES

The SAFIRE (Spectroscopy of the Atmosphere using Far Infrared Emission) is a limb emission experiment using a far-IR Fourier transform spectrometer (FTS) and a mid-IR broadband multispectral radiometer covering the range 80 to 1600/cm. The purpose of this experiment is to obtain vertical distributions of temperature and key constituents of O(y), HO(y), NO(y), ClO(y), and BrO(y) families in the stratosphere, mesosphere, and thermosphere. The spectral channels and gases within each channel are summarized. The instrument includes a 48 element (6 x 8) Ge:GA detector array operating at 4 K in the far-IR and a 105 element (7 x 15) HgCdTe array operating at 80 K in the mid-IR. The SAFIRE uses four different scan modes for vertical coverage and resolution to address various scientific requirements. The SAFIRE data reduction will start with the retrieval of temperature profile as a function of pressure using two CO2 channel data. Constituent distributions then are obtained from other channel data using the retrieved temperature profile. The SAFIRE measurements are limited to the region above the tropopause because of radiance saturation by H2O and clouds. The computational capability necessary to process at the instrument data rate is estimated to be 19 MFLOPS for FTS data and 0.02 MFLOPS for radiometer data. It seems, therefore, that the real-time applications of SAFIRE data using an onboard processing device is not feasible. Although a temperature anomaly may be detected from the two CO2 radiometer channels using an onboard processor for the stratosphere, it is not possible to distinguish between CO2 outflux and temperature anomaly. Temperature anomaly does not, therefore, offer tropospheric information useful for real-time application.

Park, Jae H.↗
NASA NTRS1998

Atmospheric Aerosol Chemical Composition Measurements for the Subsonic Aircraft: Contrail and Cloud Effects Special Study (SUCCESS)

We received funding to provide measurements of the chemical composition of aerosols aboard the NASA Ames DC-8 research aircraft during the SUCCESS mission. These measurements were successfully completed and the final data resides in the Cloud I computer archive at NASA Ames Research Center. The interpretation of the data obtained on this mission over the central United States has been published in special issues of Geophysical Research Letters. The papers with the University of New Hampshire as first author constitute this report and summarize the salient features of our data. The paper by Talbot et al. discusses the impact of vertical transport on free tropospheric chemistry over the the central USA in springtime. This transport was a dominant feature of the aerosol chemistry during SUCCESS. The paper by Dibb et al. discusses aerosol chemistry specifically as it related to free tropospheric sulfate related to jet exhaust and surface sources. Somewhat surprisingly, we found that surface sources appeared to dominant the distribution of aerosol sulfate in the free troposphere. In addition to these first authored papers, researchers from the University of New Hampshire were co-authors on numerous other companion papers in the special issues.

Talbot, Robert W.↗
NASA NTRS2017

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data Via Hyrax Server Data Server

This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.

AWS cost↗
NASA NTRS2017

NASA's EOSDIS Cumulus: Ingesting, Archiving, Managing, and Distributing Earth Science Data from the Commercial Cloud

NASA's Earth Observing System Data and Information System (EOSDIS) has been working towards a vision of a cloud-based, highly-flexible, ingest, archive, management, and distribution system for its ever-growing and evolving data holdings. This system, Cumulus, is emerging from its prototyping stages and is poised to make a huge impact on how NASA manages and disseminates its Earth science data. This talk will outline the motivation for this work, present the achievements and hurdles of the past 18 months and will chart a course for the future expansion of the Cumulus expansion. We will explore on not just the technical, but also the socio-technical challenges that we face in evolving a system of this magnitude into the cloud and how we are rising to meet those challenges through open collaboration and intentional stakeholder engagement.

Earth Scienc↗