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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network

Over the past half century, the transmission electron microscope enabled insight into the fundamental arrangements and structures of materials. State-of-the-art electron microscopes can acquire large image datasets across multiple imaging modalities. However, the manual annotation process for feature or defect quantification may not be feasible with the modern microscope. Convolutional neural networks emerged to characterize individual microstructural features from an image in a cost-effective, consistent manner. However, many of these neural network approaches rely on thousands to hundreds of thousands of manual annotations of each feature type across hundreds of images to train the network for adequate performance. This work focused on the development and application of a pixel-wise defect detection machine-learning dynamic segmentation convolutional neural network with associated automated acquisition and postprocessing to identify microstructural features rapidly and quantitatively from a small initial dataset incorporating multiple imaging modes. The approach was demonstrated for characterization of superalloy 718 from both single image acquisition on multiple detectors to in-situ evolution captured with a single detector on a standard desktop computer to demonstrate the low barrier to entry required for widespread adoption. Pixel-by-pixel class identification was excellent with strong identification of chemically distinct phases, structurally distinct phases, and defect structures, thus demonstrating the new paradigm of machine learning-assisted characterization.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Computational Model of the Modulation of Gene Expression Following DNA Damage

High linear energy transfer (LET) radiation, such as heavy ions or neutrons, has an increased biological effectiveness compared to X rays for gene mutation, genomic instability, and carcinogenesis. In the traditional paradigm, mutations or chromosomal aberrations are causative of late effects. However, in recent years experimental evidence has demonstrated the important role of the description of the modification of gene expression by radiation in understanding the mechanisms of radiation action. In this report, approaches are discussed to the mathematical description of mRNA and protein expression kinetics following DNA damage. Several hypotheses for models of radiation modulation of protein expression are discussed including possible non-linear processes that evolve from the linear dose responses that follow the initial DNA damage produced by radiation.

NASA Center JSC↗
DOE OSTI2024

Impact of Higher Fidelity Design Iterations on Critical System Criteria

Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Perspectives on AI Architectures and Codesign for Earth System Predictability

Abstract Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper. Significance Statement This study aims to provide perspectives on AI architectures and codesign approaches for Earth system predictability. Such visionary perspectives are essential because AI-enabled model-data integration has shown promise in improving predictions associated with climate change, perturbations, and extreme events. Our forward-looking ideas guide what is next in codesign to enhance Earth system models, observations, and theory using state-of-the-art and futuristic computational infrastructure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Perspectives on AI Architectures and Co-design for Earth System Predictability

Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper.

58 GEOSCIENCES↗
DOE OSTI2026

HARMONY: Large-Scale Architecture Search for Efficient Hybrid Language Models

As large language models scale to trillions of parameters, their computational and memory requirements present critical challenges for efficient training and deployment. While Mixture of Experts (MoE) architectures enable efficient scaling through sparse parameter activation, and state-space models like Mamba offer linear-time complexity, principled methods for combining these paradigms remain undeveloped. We introduce HARMONY (Hybrid Architecture Research for Mamba, Optimized with Neural efficiencY), a multi-objective evolutionary neural architecture search framework for discovering efficient hybrid language models that integrate Transformer attention mechanisms, Mixture-of-Experts routing, and Mamba state-space components. Through large-scale distributed search using 16,384 MI250X GPUs on the Frontier supercomputer, HARMONY explores a comprehensive design space encompassing six attention variants (MHA, MQA, GQA, MLA, SWA, and Mamba-2), variable MoE configurations with both routed and shared experts, and extensive Mamba hyperparameters. Our framework discovers heterogeneous architectures that balance training performance with computational efficiency through multi-objective optimization incorporating latency penalties and fitness-based selection. Analysis of discovered architectures reveals that optimal hybrid designs favor heterogeneous component mixing rather than homogeneous patterns, with Mamba-2 and Multi-Head Latent Attention (MLA) emerging as preferred mechanisms. Discovered architectures demonstrate superior training efficiency: our best configuration achieves a final perplexity of 1.0874 with 2.38B parameters while processing 4,320 tokens/second, outperforming significantly larger manually designed models. Full-scale evaluation shows HARMONY's top architectures achieve better loss trajectories than equivalently-sized models using state-of-the-art configurations including Mixtral, Jamba, and Samba. Additionally, we demonstrate 91% weak scaling efficiency when training discovered 36B-parameter models across 1,024 GPUs. HARMONY is released as an open framework with comprehensive tools for building and training hybrid models using expert-data-pipeline parallelism, democratizing access to automated architecture design for next-generation language models.

Herron, Emily [ORNL] (ORCID:0000000273008172)↗
DOE OSTI2023

Fast Parallel Tensor Times Same Vector for Hypergraphs

Hypergraphs are a popular paradigm to rep- resent complex real-world networks exhibiting multi-way relationships of varying sizes. Mining centrality in hyper- graphs via symmetric adjacency tensors has only recently become computationally feasible for large and complex datasets. To enable scalable computation of these and related hypergraph analytics, here we focus on the Sparse Symmetric Tensor Times Same Vector (S3TTVC) oper- ation. We introduce the Compound Compressed Sparse Symmetric (CCSS) format, an extension of the compact CSS format for hypergraphs of varying hyperedge sizes and present a shared-memory parallel algorithm to compute S3TTVC. We experimentally show S3TTVC computation using the CCSS format achieves better performance than the naive baseline, and is subsequently more performant for hypergraph H-eigenvector centrality.

Shivakumar, Shruti↗
NASA NTRS1986

Status and projections of the NAS program

NASA's Numerical Aerodynamic Simulation (NAS) Program has completed development of the initial operating configuration of the NAS Processing System Network (NPSN). This is the first milestone in the continuing and pathfinding effort to provide state-of-the-art supercomputing for aeronautics research and development. The NPSN, available to a nation-wide community of remote users, provides a uniform UNIX environment over a network of host computers ranging from the Cray-2 supercomputer to advanced scientific workstations. This system, coupled with a vendor-independent base of common user interface and network software, presents a new paradigm for supercomputing environments. Background leading to the NAS program, its programmatic goals and strategies, technical goals and objectives, and the development activities leading to the current NPSN configuration are presented. Program status, near-term plans, and plans for the next major milestone, the extended operating configuration, are also discussed.

Bailey, Frank R.↗
NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗
DOE OSTI2020

Systems, methods and computer program products for self-tuning sensor data processing

Systems and methods are disclosed that include tools that utilize Dynamic Detector Tuning (DDT) software that identifies near-optimal parameter settings for each sensor using a neuro-dynamic programming (reinforcement learning) paradigm. DDT adapts parameter values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: parameters are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The DDT algorithm adapts in near real-time to changing conditions in an attempt to automatically self-tune a signal detector to identify (detect) only signals from events of interest. The disclosed systems and methods reduce the number of missed legitimate detections and the number of false detections, resulting in improved event detection.

Draelos, Timothy J.↗
DOE OSTI2025

From Data to Discovery: AI's Transformative Role in Thin Film Research

The advancement of thin film technologies is pivotal for progress in numerous fields, including energy, electronics, and quantum computing. However, the traditional trial-and-error approach to materials discovery is inherently slow and inefficient. This presentation will showcase how artificial intelligence (AI) is transforming thin film research by enabling a data-driven paradigm shift. We will highlight our past successes in applying AI to understand radiation damage in thin film oxides, demonstrating how graph analytics can unravel complex material behavior. Additionally, we will provide insights into our current work at the National Renewable Energy Laboratory, where we are leading the charge in autonomous materials science. Backed by a $14M investment in our characterization facility, we are developing AI-guided workflows that seamlessly integrate experimentation and AI-guided decision-making. By harnessing the power of AI, we aim to accelerate the discovery and design of high-performance thin films, propelling innovation across a multitude of industries.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Aerodynamic sound of flow past an airfoil

The long term objective of this project is to develop a computational method for predicting the noise of turbulence-airfoil interactions, particularly at the trailing edge. We seek to obtain the energy-containing features of the turbulent boundary layers and the near-wake using Navier-Stokes Simulation (LES or DNS), and then to calculate the far-field acoustic characteristics by means of acoustic analogy theories, using the simulation data as acoustic source functions. Two distinct types of noise can be emitted from airfoil trailing edges. The first, a tonal or narrowband sound caused by vortex shedding, is normally associated with blunt trailing edges, high angles of attack, or laminar flow airfoils. The second source is of broadband nature arising from the aeroacoustic scattering of turbulent eddies by the trailing edge. Due to its importance to airframe noise, rotor and propeller noise, etc., trailing edge noise has been the subject of extensive theoretical (e.g. Crighton & Leppington 1971; Howe 1978) as well as experimental investigations (e.g. Brooks & Hodgson 1981; Blake & Gershfeld 1988). A number of challenges exist concerning acoustic analogy based noise computations. These include the elimination of spurious sound caused by vortices crossing permeable computational boundaries in the wake, the treatment of noncompact source regions, and the accurate description of wave reflection by the solid surface and scattering near the edge. In addition, accurate turbulence statistics in the flow field are required for the evaluation of acoustic source functions. Major efforts to date have been focused on the first two challenges. To this end, a paradigm problem of laminar vortex shedding, generated by a two dimensional, uniform stream past a NACA0012 airfoil, is used to address the relevant numerical issues. Under the low Mach number approximation, the near-field flow quantities are obtained by solving the incompressible Navier-Stokes equations numerically at chord Reynolds number of 104. The far-field noise is computed using Curle's extension to the Lighthill analogy (Curle 1955). An effective method for separating the physical noise source from spurious boundary contributions is developed. This allows an accurate evaluation of the Reynolds stress volume quadrupoles, in addition to the more readily computable surface dipoles due to the unsteady lift and drag. The effect of noncompact source distribution on the far-field sound is assessed using an efficient integration scheme for the Curle integral, with full account of retarded-time variations. The numerical results confirm in quantitative terms that the far-field sound is dominated by the surface pressure dipoles at low Mach number. The techniques developed are applicable to a wide range of flows, including jets and mixing layers, where the Reynolds stress quadrupoles play a prominent or even dominant role in the overall sound generation.

Wang, Meng↗
DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗
NASA NTRS1987

NAS-current status and future plans

The Numerical Aerodynamic Simulation (NAS) has met its first major milestone, the NAS Processing System Network (NPSN) Initial Operating Configuration (IOC). The program has met its goal of providing a national supercomputer facility capable of greatly enhancing the Nation's research and development efforts. Furthermore, the program is fulfilling its pathfinder role by defining and implementing a paradigm for supercomputing system environments. The IOC is only the begining and the NAS Program will aggressively continue to develop and implement emerging supercomputer, communications, storage, and software technologies to strengthen computations as a critical element in supporting the Nation's leadership role in aeronautics.

Bailey, F. R.↗
NASA NTRS1986

Status and projections of the NAS Program

NASA's Numerical Aerodynamic Simulation (NAS) Program has completed development of the initial operating configuration of the NAS Processing System Network (NPSN). This is the first milestone in the continuing and pathfinding effort to provide state-of-the-art supercomputing for aeronautics research and development. The NPSN, available to a nation-wide community of remote users, provides a uniform UNIX environment over a network of host computers ranging from the new Cray-2 supercomputer to advanced scientific workstations. This system, coupled with a vendor-independent base of common user interface and network software, presents a new paradigm for supercomputing environments. Presented here is the background leading to the NAS Program, its programmatic goals and strategies, technical goals and objectives, and the development activities leading to the current NPSN configuration. Program status, near-term plans and plans for the next major milestone, the extended operating configuration, are also discussed.

Bailey, F. R.↗
NASA NTRS2013

Good Practices in Free-energy Calculations

As access to computational resources continues to increase, free-energy calculations have emerged as a powerful tool that can play a predictive role in drug design. Yet, in a number of instances, the reliability of these calculations can be improved significantly if a number of precepts, or good practices are followed. For the most part, the theory upon which these good practices rely has been known for many years, but often overlooked, or simply ignored. In other cases, the theoretical developments are too recent for their potential to be fully grasped and merged into popular platforms for the computation of free-energy differences. The current best practices for carrying out free-energy calculations will be reviewed demonstrating that, at little to no additional cost, free-energy estimates could be markedly improved and bounded by meaningful error estimates. In energy perturbation and nonequilibrium work methods, monitoring the probability distributions that underlie the transformation between the states of interest, performing the calculation bidirectionally, stratifying the reaction pathway and choosing the most appropriate paradigms and algorithms for transforming between states offer significant gains in both accuracy and precision. In thermodynamic integration and probability distribution (histogramming) methods, properly designed adaptive techniques yield nearly uniform sampling of the relevant degrees of freedom and, by doing so, could markedly improve efficiency and accuracy of free energy calculations without incurring any additional computational expense.

Pohorille, Andrew↗
NASA NTRS2004

Spaceflight Operations Services Grid (SOSG)

In an effort to adapt existing space flight operations services to new emerging Grid technologies we are developing a Grid-based prototype space flight operations Grid. This prototype is based on the operational services being provided to the International Space Station's Payload operations located at the Marshall Space Flight Center, Alabama. The prototype services will be Grid or Web enabled and provided to four user communities through portal technology. Users will have the opportunity to assess the value and feasibility of Grid technologies to their specific areas or disciplines. In this presentation descriptions of the prototype development, User-based services, Grid-based services and status of the project will be presented. Expected benefits, findings and observations (if any) to date will also be discussed. The focus of the presentation will be on the project in general, status to date and future plans. The End-use services to be included in the prototype are voice, video, telemetry, commanding, collaboration tools and visualization among others. Security is addressed throughout the project and is being designed into the Grid technologies and standards development. The project is divided into three phases. Phase One establishes the baseline User-based services required for space flight operations listed above. Phase Two involves applying Gridlweb technologies to the User-based services and development of portals for access by users. Phase Three will allow NASA and end users to evaluate the services and determine the future of the technology as applied to space flight operational services. Although, Phase One, which includes the development of the quasi-operational User-based services of the prototype, development will be completed by March 2004, the application of Grid technologies to these services will have just begun. We will provide status of the Grid technologies to the individual User-based services. This effort will result in an extensible environment that incorporates existing and new spaceflight services into a standards-based framework providing current and future NASA programs with cost savings and new and evolvable methods to conduct science. This project will demonstrate how the use of new programming paradigms such as web and grid services can provide three significant benefits to the cost-effective delivery of spaceflight services. They will enable applications to operate more efficiently by being able to utilize pooled resources. They will also permit the reuse of common services to rapidly construct new and more powerful applications. Finally they will permit easy and secure access to services via a combination of grid and portal technology by a distributed user community consisting of NASA operations centers, scientists, the educational community and even the general population as outreach. The approach will be to deploy existing mission support applications such as the Telescience Resource Kit (TReK) and new applications under development, such as the Grid Video Distribution System (GViDS), together with existing grid applications and services such as high-performance computing and visualization services provided by NASA s Information Power Grid (IPG) in the MSFC s Payload Operations Integration Center (POIC) HOSC Annex. Once the initial applications have been moved to the grid, a process will begin to apply the new programming paradigms to integrate them where possible. For example, with GViDS, instead of viewing the Distribution service as an application that must run on a single node, the new approach is to build it such that it can be dispatched across a pool of resources in response to dynamic loads. To make this a reality, reusable services will be critical, such as a brokering service to locate appropriate resource within the pool. This brokering service can then be used by other applications such as the TReK. To expand further, if the GViDS application is constructed using a services-based mel, then other applications such as the Video Auditorium can then use GViDS as a service to easily incorporate these video streams into a collaborative conference. Finally, as these applications are re-factored into this new services-based paradigm, the construction of portals to integrate them will be a simple process. As a result, portals can be tailored to meet the requirements of specific user communities.

Bradford, Robert N.↗
DOE OSTI2024

Multi-hadron systems via Lattice QCD

This project supported a broad set of research in theoretical nuclear physics which has been designed to support current and future experimental DOE facilities. The broad summary of physical observables of interest in this project were the bread-and-butter observables obtained in experimental nuclear and particle physics experiments, namely scattering amplitude including multi-hadronic states. The primary goal of this project was to design a systematically improvable paradigm for accessing such amplitudes directly from the Standard Model of Particle Physics. The main tools that were used and explored in this project were scattering theory, lattice QCD, and future quantum computers. The physics outputs included various novel formalisms, exploratory lattice QCD calculations, and a new proposal for studying any scattering observable using future quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗