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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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Strawman is a system designed to explore the in situ visualization and analysis needs of simulation code teams running multi-physics calculations on many-core HPC architectures. It porvides rendering pipelines that can leverage both many-core CPUs and GPUs to render images of simulation meshes.
The VisIT Java Client (JVC) library is a lightweight thin client that is designed and written purely in the native language of Java (the Python & JavaScript versions of the library use the same concept) and communicates with any new unmodified standalone version of VisIT, a high performance computing parallel visualization toolkit, over traditional or web sockets and dynamically determines capabilities of the running VisIT instance whether local or remote.
SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.
The interaction between plants and their associated microbiomes is difficult to visualize in situ and requires a transparent culturing platform that can capture the length and time scales in which these dynamic relationships occur. We have used lab-on-a-chip technology to create such a platform and have successfully co-cultured Arabidopsis thaliana with beneficial bacteria. Here we quantify the changes in root morphology over time and discuss the potential of the system to characterize the kinetics and spatial distribution of root colonization.
The ultrafast laser excitation of matters leads to non-equilibrium states with complex solid-liquid phase transition dynamics. We used electron diffraction at mega-electronvolt energies to visualize the ultrafast melting of gold on the atomic scale length. For energy densities approaching the irreversible melting regime, we first observed heterogeneous melting on time scales of 100 ps to 1000 ps, transitioning to homogeneous melting that occurs catastrophically within 10-20 ps at higher energy densities. We showed evidence for the heterogeneous coexistence of solid and liquid. We determined the ion and electron temperature evolution and found superheated conditions. Our results constrain the electron-ion coupling rate, determine the Debye temperature and reveal the melting sensitivity to nucleation seeds.
Various technologies pertaining to computer-executable instruction sequence forensics are described herein. In a general embodiment, an application development framework supports a function library that includes a plurality of recording functions. Calls to these functions are inserted into source code or bytecode of the computer-executable instruction sequence. The source code is then compiled, resulting in formation of instrumented machine code of the computer-executable instruction sequence. Alternately, the runtime environment interprets instrumented bytecode for the instruction sequence. A processor executes the machine code, and the called functions cause the processor to generate forensic data pertaining to portions of the computer-executable instruction sequence that correspond to locations in the source code where the calls were inserted. An execution instance of the computer-executable instruction sequence is visualized based upon the forensic data.
A process transforms compiled software into a semantic form. The process transforms the code into a semantic form. The process analyzes behavior functionality by processing precise programming behavior abstractions stored in a memory and classifies the code as malware based on the code behavior. Another method identifies the starting point of execution of a compiled program. The method calculates a complexity measure by calculating the number of potential execution paths of local functions; identifies the number of arguments passed to local functions; and identifies the starting point of execution of the compiled program. Another method provides interactive, dynamic visualization of a group of related functions wherein a user can explore the rendered graph and select a specific function and display functions that are color coded by their ancestral relation and their function call distance to the selected function.
This paper details the design and system components of the Multi-Modal Autonomous Vehicle Network system (MAVNet). MAVNet was designed to provide reliable and redundant command, control and payload data distribution for unmanned vehicles operating beyond visual line of sight. Current industry solutions do not adequately solve key networking challenges, do not support network diversity and fall short of providing desirable next-generation requirements including data fusion from national air space data sources, multi-pilot and multi-agent control. The MAVNet system and the approach taken to solve these issues will be detailed in this paper.
The present disclosure pertains to systems and methods for simulating data packet routing within a software defined network (“SDN”), visualizing the results of the simulation, and permitting a user to search the resulting simulation. In one specified embodiment, a system may receive from a user a simulation parameter associated with a packet to be simulated in the SDN. A packet based on the at least one simulation parameter may be generated. A response of the SDN to the packet may be simulated by identifying applicable traffic routing rules and identifying a subsequent destination based on the applicable traffic routing rules. A record of the subsequent destination may be added to the simulation result, and the process may continue until a terminating condition is satisfied.
The Frontier Experiment RegistRY System (FERRY) is a metadata database that contains information about employees, the groups and experiments they belong to, and grid mapping and quota management for the Fermi National Accelerator Laboratory. It is predominantly used to acquire user information. FERRY is accessed through the use of APIs (Application Programming Interface), shown in Figure 1. Corresponding attributes are then displayed for the user in JSON (Java Script Object Notation) format. The goal of this project has been to build upon and improve aspects of FERRY. Including the refactoring of the code, building a visual interface, and creating a testing system for FERRY’s APIs.
We present 1) a work in progress method to visually segment key regions of scientific articles using an object detection technique augmented with contextual features, and 2) a novel dataset of region-labeled articles. A continuing challenge in scientific literature mining is the difficulty of consistently extracting high-quality text from formatted PDFs. To address this, we adapt the object-detection technique Faster R-CNN for document layout detection, and incorporate contextual information that leverages the inherently localized nature of article contents to improve the region detection performance. Due to the limited availability of region-labels for scientific articles, we also contribute a novel dataset of region annotations, the first version of which covers 9 region classes and 822 article pages. Initial experimental results demonstrate a 23.9% absolute improvement in mean average precision over the baseline by incorporating contextual features, and a processing speed 14x faster than a text-based technique. Ongoing work on further improvements is also discussed.
The Oak Ridge National Laboratory is developing a cloud-based platform for the deployment and evaluation of mobility- and efficiency-oriented connected and automated vehicles (CAVs) applications that will include fundamental data management, communications and visualization elements. This system will serve as a data portal, providing indirect communications that are relevant to efficiency applications, and can be used for both real world CAVs deployments and virtual systems that allow evaluation of new CAVs applications and algorithms. Predictive vehicle speed control algorithms have been developed and will be integrated with the real-time queryable transportation database and geospatial platform to achieve optimized energy efficiency and improved traffic flow in off-freeway driving. This paper describes the technology and summarizes evaluations being conducted for a corridor in Chattanooga, Tennessee, where the technology is expected to be initially deployed. To evaluate the fuel savings resulting from the vehicle speed control and the RTMCS data framework, vehicle powertrain simulations will be completed using results from a calibrated microscopic traffic model.
Bilayer graphene was theorized to host a moire miniband with flat dispersion if the layers are stacked at specific twist angles known as the magic angles. Recently, such twisted bilayer graphene (tBLG) with the first magic angle twist was reported to exhibit correlated insulating state and superconductivity, where the presence of the flat miniband in the system is thought to be essential for the emergence of these ordered phases in the transport measurements. Tunneling spectroscopy and electronic compressibility measurements in tBLG have revealed a van Hove singularity that is consistent with the presence of the flat miniband. However, a direct observation of the flat dispersion in the momentum-space of such moire miniband in tBLG is still elusive. Here, we report the visualization of the flat moire miniband by using angle-resolved photoemission spectroscopy with nanoscale resolution (nanoARPES). The high spatial resolution in nanoARPES enabled the measurement of the local electronic structure of the tBLG. We clearly demonstrate the existence of the flat moire band near the charge neutrality for tBLG close to the magic angle at room temperature.
In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.
An apparatus and method for real-time visualization of particulate matter suspended in a static or flowing fluid and fluid flow patterns in a pipe, tube, conduit, or other container, are described. Ultrasonic scanning and detection of scattered sound from the particles in the fluid create a real-time image of the particles, or of flow patterns in the liquid. A mechanical wobbler directs a piezoelectric transducer over a chosen angle in an oscillatory manner. The transducer is operated in a pulse-echo mode wherein the same transducer detects the return signal from the target region through which particles are passing and/or a flow is present. The pulse-echo measurements are made rapidly and continuously during a single sweep of the transducer over the chosen angle. Received signals are processed in the ultrasound scanner electronics module and displayed as an image in real-time.
High Performance Computing (HPC) systems are complex setups of servers, storage devices, network switches, and cables that are specifically designed to accommodate hundreds of users running highly computationally intensive applications at a time. These applications require numerous softwares, licenses, and various levels of storage as well. All of these resources must be monitored and managed by HPC administrators, which presents a daunting task. In this project, I created numerous software tools as part of an HPC Visualization and Management system, which is now used by HPC administrators on a daily basis.
A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. This presentation will review and contrast nine current impact assessment methods and describe their granularity, scope, data requirements, and capabilities within the context of identifying regional and sectoral transfers of impacts that could result from transitioning to a circular economy for energy systems. The review of current approaches highlights the need for a new hybrid circularity assessment framework that leverages multiple methods. We describe one such approach: the Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework. CELAVI uses system dynamics to model material flows for multiple circular economy pathways, network theory to track the spatial and sectoral flow of functional units across a graph, and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable enough to accommodate multiple energy materials and multiple energy technologies. CELAVI's hybridization of multiple existing methods yields additional capabilities, which may help answer questions about how flows between the technosphere and ecosphere may evolve if the circularity of energy systems is modified.
Connecting a bulk material’s microscopic defects to its macroscopic properties is an age-old problem in materials science. Long-range interactions between dislocations (line defects) are known to play a key role in how materials deform or melt, but we lack the tools to connect these dynamics to the macroscopic properties. We introduce time-resolved dark-field X-ray microscopy to directly visualize how dislocations move and interact over hundreds of micrometers, deep inside bulk aluminum. With real-time movies, we reveal the thermally activated motion and interactions of dislocations that comprise a boundary, and show how weakened binding forces inhomogeneously destabilize the structure at 99% of the melting temperature. Connecting dynamics of the microstructure to its stability, we provide important opportunities to guide and validate multiscale models that are yet untested.