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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

From Edge to HPC: Investigating Cross-Facility Data Streaming Architectures

In this paper, we investigate three cross-facility data streaming architectures, Direct Streaming (DTS), Proxied Streaming (PRS), and Managed Service Streaming (MSS). We examine their architectural variations in data flow paths and deployment feasibility, and detail their implementation using the Data Streaming to HPC (DS2HPC) architectural framework and the SciStream memory-to-memory streaming toolkit on the production-grade Advanced Computing Ecosystem (ACE) infrastructure at Oak Ridge Leadership Computing Facility (OLCF). We present a workflow-specific evaluation of these architectures using three synthetic workloads derived from the streaming characteristics of scientific workflows. Through simulated experiments, we measure streaming throughput, round-trip time, and overhead under work sharing, work sharing with feedback, and broadcast and gather messaging patterns commonly found in AI-HPC communication motifs. Our study shows that DTS offers a minimal-hop path, resulting in higher throughput and lower latency, whereas MSS provides greater deployment feasibility and scalability across multiple users but incurs significant overhead. PRS lies in between, offering a scalable architecture whose performance matches DTS in most cases.

George, Anjus [ORNL] (ORCID:0000000179737061)↗
DOE OSTI2020

EASEE: Edge Advertisements into Snapshots using Evolving Expectations

Code developed in conjunction with a research paper. This code demonstrates how to identify static graph snapshots from a stream of communication events. A second, related code generates simulated communication events with known split moments for accuracy testing.SAND2020-12245 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Wendt, Jeremy↗
DOE OSTI2021

REAL-TIME EDGE INFERENCE FOR PTYCHOGRAPHIC NANOSCALE XRAY IMAGING

The consolidated code is deployed in an embedded GPU System (Jetson AGX Xavier Developer Kit), performs inference on the pVA stream sent from the X-ray detector. The inferred output is sent back to the local detector machine as a PVA stream and can be viewed in an ImageJ viewer.

VASANTHAKUMARIBABU, ANAKHA↗
DOE OSTI2023

CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK

SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.

CHAN, HENRYT↗
DOE OSTI2022

Nano-porous GaN cladding and scattering loss in edge emitting laser diodes

We report continuous wave operation of electrically injected InGaN laser diodes using nano-porous GaN n-side cladding with 33% porosity. At 454 nm emission wavelength, the pulsed injection slope efficiency is 0.24 W/A with a high loss of 82 cm -1 . The considerable 60 cm -1 of excess loss of the nano-porous clad lasers is attributed to scattering at pores in unintentionally 3% porosified layers, supported by numerical modeling. Simulations comparing porous GaN cladding to AlInN cladding for lasers operating at 589 nm indicate that the porous cladding provides similar internal loss and lower thermal impedance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Green edge emitting lasers with porous GaN cladding

GaN lasers with green emission wavelength at λ = 510 nm have been fabricated using novel nano-porous GaN cladding under pulsed electrical injection. The low slope efficiency of 0.13 W/A and high threshold current density of 14 kA/cm 2 are related to a combination of poor injection efficiency and high loss, analyzed by the independent characterization methods of variable stripe length and segmented contacts. Continuous wave operation showed narrowed spectra and augmented spontaneous emission.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

III-nitride m-plane violet narrow ridge edge-emitting laser diodes with sidewall passivation using atomic layer deposition

A novel deep-ridge laser structure with atomic-layer deposition (ALD) sidewall passivation was proposed that enhances the optical characteristics of 8-µm ridge width III-nitride violet lasers on freestanding m -plane GaN substrates. The internal loss was determined using the variable stripe length method, where the laser structure with ALD sidewall passivation showed lower internal loss compared to the conventional shallow-ridge laser design. ALD sidewall passivation plays a critical role in device improvements; compared to the lasers without ALD sidewall passivation, the lasers with ALD sidewall passivation yield improved optoelectrical performance and longer lifetime under continuous-wave operation at high current density. This work demonstrates the importance of ALD sidewall passivation to laser performance, which enables high energy efficiency.

Wong, Matthew S.↗
DOE OSTI2023

Enhancement of chiral edge currents in ($d$+1)-dimensional atomic Mott-band hybrid insulators

We consider the effect of a local interatomic repulsion on synthetic heterostructures where a discrete synthetic dimension is created by Raman processes on top of SU(N) S U ( N ) -symmetric two-dimensional lattice systems. At a filling of one fermion per site, increasing the interaction strength, the system is driven towards a Mott state which is adiabatically connected to a band insulator. The chiral currents associated with the synthetic magnetic field increase all the way to the Mott transition, where they reach the maximum value, and they remain finite in the whole insulating state. The transition towards the Mott-band insulator is associated with the opening of a gap within the low-energy quasiparticle peak, while a mean-field picture is recovered deep in the insulating state.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Integrating System to Edge-of-Network Architecture and Management for SHINES (SEAMS) Technologies of High Penetration Grids

Consistent with the U.S. DOE’s EERE SHINES FOA objectives, the goal of this project was to enable integration from EMS to variable DER in a way that delivered visibility and opportunities for managing and controlling distributed resources using SEAMS technologies. This project implemented several SHINES technologies, which included: (1) three Stem battery systems; (2) six ConnectDER PV collars; (3) two E-Gear PV/Battery storage interfaces; and (4) eight Kitu smart inverter emulators. A Siemens Energy IP DEMS was deployed in a development environment and integrated with the SHINES technologies via OpenADR and IEEE 2030.5 protocols with documented architecture. In the case of IEEE 2030.5, a suite of technologies including a gateway, an API, software and a server from Kitu Systems (the Citadel, Convoy, Kitu Crosslink API, and Kitu Spark) were used to demonstrate that the utility could achieve visibility of distributed energy resources (DER) and control of single and multiple DER systems with a single command. The project also included a LCOE analysis of SHINES technologies compared to traditional system and circuit mitigation measures.

14 SOLAR ENERGY↗
DOE OSTI2021

Accelerator Real-time Edge AI for Distributed Systems (READS) (Proposal)

Over the last decade, Machine Learning (ML) technologies have slowly made their way into the accelerator community. Rapid advances in recent years in deep learning, particularly reinforcement learning for control system applications and the accessibility of deep learning in embedded hardware, have generated renewed interest and spawned a number of applications. The Fermilab Accelerator Complex, shown in Fig. 1, has provided High Energy Physics (HEP) experiments with proton beams for nearly fifty years. The current focus of the laboratory is its world-class experimental program at the intensity frontier. While increasing beam intensity certainly presents its own challenges, preserving beam size while minimizing beam losses – particles lost through interactions with the beam vacuum pipe – turns out to be, in many ways, the main challenge. The accelerator is controlled via a complex system of hundreds of thousands of devices. Enabling fine tuning and real-time optimization of their parameters using ML methods and stepping beyond experience-based reasoning of human operators are key to the success of future intensity upgrades. Our objective will be to integrate ML into accelerator operations and furthermore, provide an accessible framework, which can also be used by a broad range of other accelerator systems with dynamic tuning needs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Edge and scrape-off layer modeling for a Fusion Nuclear Science Facility with tungsten walls; a summary report for 2019-21

This report summarizes model development and simulations for the edge/scrape-off layer (SOL) region of a Fusion Nuclear Science Facility (FNSF) as part of the DOE Fusion Energy Systems Studies project. An overview of the FNSF device is given in Ref. 1. Our earlier related modeling of FNSF in the 2015-16 timeframe is reported in Ref. 2, and similar work on the ARIES ACT-1 tokamak device is described in Ref. 3. During 2017-18, we contributed to the analysis of a liquid lithium wall for FNSF [4].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗