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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Multichannel meta-imagers for accelerating machine vision

Rapid developments in machine vision technology have impacted a variety of applications, such as medical devices and autonomous driving systems. These achievements, however, typically necessitate digital neural networks with the downside of heavy computational requirements and consequent high energy consumption. As a result, real-time decision-making is hindered when computational resources are not readily accessible. Here we report a meta-imager designed to work together with a digital back end to offload computationally expensive convolution operations into high-speed, low-power optics. Further, in this architecture, metasurfaces enable both angle and polarization multiplexing to create multiple information channels that perform positively and negatively valued convolution operations in a single shot. We use our meta-imager for object classification, achieving 98.6% accuracy in handwritten digits and 88.8% accuracy in fashion images. Owing to its compactness, high speed and low power consumption, our approach could find a wide range of applications in artificial intelligence and machine vision applications.

47 OTHER INSTRUMENTATION↗

NASA NTRS1985

Computers in Aerospace Conference, 5th, Long Beach, CA, October 21-23, 1985, Technical Papers

Among the topics discussed are: access control models for a distributed CAIS-conforming system; a knowledge-based advisory system for casualty procedures; and automated interactive simulation modeling system. Consideration is also given to: reusable software concepts and software development methodologies; the electronic device aspects of neutral network memories; an expert system for automated satellite anomaly resolution; and the use of automatic programming techniques for fault-tolerant computing systems. Among additional topics discussed are: systems approaches to software fault tolerance; a Space Shuttle navigation validation system; and a vision-based road following system for an autonomous land vehicle.

Source record↗

NASA NTRS1994

SAVA 3: A testbed for integration and control of visual processes

The development of an experimental test-bed to investigate the integration and control of perception in a continuously operating vision system is described. The test-bed integrates a 12 axis robotic stereo camera head mounted on a mobile robot, dedicated computer boards for real-time image acquisition and processing, and a distributed system for image description. The architecture was designed to: (1) be continuously operating, (2) integrate software contributions from geographically dispersed laboratories, (3) integrate description of the environment with 2D measurements, 3D models, and recognition of objects, (4) capable of supporting diverse experiments in gaze control, visual servoing, navigation, and object surveillance, and (5) dynamically reconfiguarable.

Crowley, James L.↗

NASA NTRS2000

Biomaterials, Biomimetics and Biological Interfaces Research at the Oak Ridge National Laboratory

A viewgraph presentation outlines the development of biomaterials, biomimetics (mimicking biological processes and functions), and biological interfaces research. The different types of biomaterials are described, including details on bio-ceramics, biocompatible materials, materials characterization, and 'hybrid' biomaterials. The vision for biomimetics in creating a virtual human is discussed. Biological interfaces research is outlined, including information on interfaces with materials and computing.

Mark E. Reeves↗

NASA NTRS2014

A Cloud-Based Global Flood Disaster Community Cyber-Infrastructure: Development and Demonstration

Flood disasters have significant impacts on the development of communities globally. This study describes a public cloud-based flood cyber-infrastructure (CyberFlood) that collects, organizes, visualizes, and manages several global flood databases for authorities and the public in real-time, providing location-based eventful visualization as well as statistical analysis and graphing capabilities. In order to expand and update the existing flood inventory, a crowdsourcing data collection methodology is employed for the public with smartphones or Internet to report new flood events, which is also intended to engage citizen-scientists so that they may become motivated and educated about the latest developments in satellite remote sensing and hydrologic modeling technologies. Our shared vision is to better serve the global water community with comprehensive flood information, aided by the state-of-the- art cloud computing and crowdsourcing technology. The CyberFlood presents an opportunity to eventually modernize the existing paradigm used to collect, manage, analyze, and visualize water-related disasters.

CyberFlood↗

DOE OSTI2021

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

The Biomechanics of Indirect Traumatic Optic Neuropathy Using a Computational Head Model With a Biofidelic Orbit

Indirect traumatic optic neuropathy (ITON) is an injury to the optic nerve due to head trauma and usually results in partial or complete loss of vision. In order to advance a mechanistic understanding of the injury to the optic nerve, we developed a head model with a biofidelic orbit. Head impacts were simulated under controlled conditions of impactor velocity. The locations of impact were varied to include frontal, lateral, and posterior parts of the head. Impact studies were conducted using two types of impactors that differed in their rigidity relative to the skull. The simulated results from both the impactors suggest that forehead impacts are those to which the optic nerve is most vulnerable. The mode and location of optic nerve injury is significantly different between the impacting conditions. Simulated results using a relatively rigid impactor (metal cylinder) suggest optic nerve injury initiates at the location of the intracranial end of the optic canal and spreads to the regions of the optic nerve in the vicinity of the optic canal. In this case, the deformation of the skull at the optic canal, resulting in deformation of the optic nerve, was the primary mode of injury. On the other hand, simulated results using a relatively compliant impactor (soccer ball) suggest that primary mode of injury comes from the brain tugging upon the optic nerve (from where it is affixed to the intracranial end of the optic canal) during coup countercoup motion of the brain. This study represents the first published effort to employ a biofidelic simulation of the full length of the optic nerve in which the orbit is integrated within the whole head.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2011

Computational Models of the Eye and their Applications in Long Duration Space Flight

Astronauts are exposed to cephalad fluid shift, increased carbon dioxide levels and other environmental factors during space flight. As a result of these conditions, it is believed that they are at risk of developing increased intracranial pressure (ICP) and intraocular pressure (IOP), which in turn may cause papilledema and other disorders of the eye that can lead to temporary or permanent changes in vision. However, the mechanisms behind this risk are not fully understood. Ground analog and flight studies pose challenges because there are limited non-invasive methods that can be used to study the eye and intracranial space. Therefore it is proposed that computational models can be applied to help address this gap by providing a low cost method for studying the effects of IOP, ICP and various properties of the eye on these diseases. The information presented by the authors provides a summary of several models found in literature that could potentially be augmented and applied to inform research. Specifically, finite element models of the optic nerve head, sclera and other structures of the eye can be readily adapted as potential building blocks. These models may also be integrated with a brain/cerebrospinal fluid (CSF) model which will take into account the interaction between the CSF fluid and its pressure on the optic nerve. This integration can enable the study of the effects of microgravity on the interaction between the vasculature system and CSF system and can determine the effects of these changes on the optic nerve, and in turn the eye. Ultimately, it can help pinpoint the influences of long-term exposure to microgravity on vision and inform the future research into countermeasure development. In addition to spaceflight, these models can provide deeper understanding of the mechanisms of glaucoma, papilledema and other eye disorders observed in terrestrial conditions.

Chen, Richard↗

NASA NTRS1989

Robotic Target-Tracking Subsystem

Position and orientation of target measured in six degrees of freedom. Robotic vision subsystem measures relative position and orientation of specially designed target. Uses standard image-processing algorithms implemented directly in circuitry instead of computer programs. This feature makes it possible to extract complete sets of target-tracking data from successive image frames at rate of 30 frames per second. Five bright circles of target positioned in such way that video images of them processed into data on position and orientation of target relative to camera. Subsystem useful in industrial assembly operation requiring automatic joining of parts initially oriented and moving randomly.

Shawaga, Lawrence M.↗

NASA NTRS1993

Multirate and event-driven Kalman filters for helicopter flight

A vision-based obstacle detection system that provides information about objects as a function of azimuth and elevation is discussed. The range map is computed using a sequence of images from a passive sensor, and an extended Kalman filter is used to estimate range to obstacles. The magnitude of the optical flow that provides measurements for each Kalman filter varies significantly over the image depending on the helicopter motion and object location. In a standard Kalman filter, the measurement update takes place at fixed intervals. It may be necessary to use a different measurement update rate in different parts of the image in order to maintain the same signal to noise ratio in the optical flow calculations. A range estimation scheme that accepts the measurement only under certain conditions is presented. The estimation results from the standard Kalman filter are compared with results from a multirate Kalman filter and an event-driven Kalman filter for a sequence of helicopter flight images.

Sridhar, Banavar↗

NASA NTRS1994

Mapping Van

A NASA Center for the Commercial Development of Space (CCDS) - developed system for satellite mapping has been commercialized for the first time. Global Visions, Inc. maps an area while driving along a road in a sophisticated mapping van equipped with satellite signal receivers, video cameras and computer systems for collecting and storing mapping data. Data is fed into a computerized geographic information system (GIS). The resulting amps can be used for tax assessment purposes, emergency dispatch vehicles and fleet delivery companies as well as other applications.

Source record↗

DOE OSTI2024

US-UK fusion energy collaborations in the digital space

The US and UK share the vision for fusion as a vital part of the clean energy future. This vision is reflected in the respective national plans in the form of the Bold Decadal Vision for Commercial Fusion (BDV) in the US and the Spherical Tokamak for Energy Production (STEP) program in the UK. Digital tools such as simulation and control frameworks, design tools, AI/ML, high performance computing (HPC), and virtual reality (VR) will play an important role in developing, diagnosing, operating, and further improving burning-plasma-class fusion power plants. Therefore, a collaborative approach, involving both the public and private sectors, to developing these digital tools can accelerate the path to fusion energy commercialization. In this report we discuss previous and ongoing collaborations and opportunities to expand these collaborations into new areas. We conclude this report with near term actions and a vision of the collaboration to the Joint Coordinating Committee.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Integrated Research Infrastructure Architecture Blueprint Activity (Final Report 2023)

The complexity of scientific pursuits is increasing rapidly with aspects that require dynamic integration of experiment, observation, theory, modeling, simulation, visualization, machine learning (ML), artificial intelligence (AI), and analysis. Research projects across the Department of Energy (DOE) are increasingly data and compute intensive. Innovative research teams are accelerating the pace of discovery by using high-performance computational and data tools in their research workflows and leveraging multiple research infrastructures. Additionally, several recent high-level U.S. government reports underscore the necessity of a new advanced computing ecosystem for international competitiveness and national security. International competitors are moving forward with major research infrastructure integration efforts that seek to capture a competitive advantage in the global innovation race. Owing to its unparalleled constellation of world-class experimental and observational facilities and high-performance and extreme-scale computational, data, and networking infrastructure, DOE is positioned to be a global leader in this new era of integrated science. However, this new integration paradigm will demand continuing evolution to ensure the U.S. remains a global leader in research and innovation. The DOE Office of Science (SC) has seized on the strategic importance of integration and has adopted a vision for Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. To respond to the evolving computational requirements of research and the competitive international innovation landscape, experimental facilities could be connected with high performance computing resources for near real-time analysis, and resources should be provided for merging enormous and diverse data for AI/ML techniques and analysis.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗

NASA NTRS2017

Vision-Aided Inertial Navigation

This document discloses, among other things, a system and method for implementing an algorithm to determine pose, velocity, acceleration or other navigation information using feature tracking data. The algorithm has computational complexity that is linear with the number of features tracked.

Roumeliotis, Stergios I.↗

DOE OSTI2023

MyCrunchGPT: A LLM Assisted Framework for Scientific Machine Learning

Scientific machine learning (SciML) has advanced recently across many different areas in computational science and engineering. Here, the objective is to integrate data and physics seamlessly without the need of employing elaborate and computationally taxing data assimilation schemes. However, preprocessing, problem formulation, code generation, postprocessing, and analysis are still time- consuming and may prevent SciML from wide applicability in industrial applications and in digital twin frameworks. Here, we integrate the various stages of SciML under the umbrella of ChatGPT, to formulate MyCrunchGPT, which plays the role of a conductor orchestrating the entire workflow of SciML based on simple prompts by the user. Specifically, we present two examples that demonstrate the potential use of MyCrunchGPT in optimizing airfoils in aerodynamics, and in obtaining flow fields in various geometries in interactive mode, with emphasis on the validation stage. To demonstrate the flow of the MyCrunchGPT, and create an infrastructure that can facilitate a broader vision, we built a web app based guided user interface, that includes options for a comprehensive summary report. The overall objective is to extend MyCrunchGPT to handle diverse problems in computational mechanics, design, optimization and controls, and general scientific computing tasks involved in SciML, hence using it as a research assistant tool but also as an educational tool. While here the examples focus on fluid mechanics, future versions will target solid mechanics and materials science, geophysics, systems biology, and bioinformatics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

AdaParse

SF-25-127AdaParse (Adaptive Parallel PDF Parsing and Resource Scaling Engine) enables scalable, high-accuracy PDF parsing. AdaParse is a data-driven strategy that assigns an appropriate parser to each document, offering high accuracy for any computational budget. Moreover, it offers a workflow of various PDF parsing software that includes extraction tools: PyMuPDF, pypdf traditional OCR: Tesseract, modern OCR (e.g., Vision Transformers): Nougat and Marker

Siebenschuh, Carlo↗

DOE OSTI2023

Can the United States Maintain Its Leadership in High-Performance Computing? - A report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR Office

The United States (U.S.) is no longer the unambiguous leader in the vitally important field of high performance computing (HPC). Japan, the European Union (EU), and China have fielded systems that are on par with our fastest supercomputers. The supply chain for everything from semiconductors to scientific software is globally distributed. Yet our economic future and security depend critically on our ability to innovate faster than our competitors, and the speed of innovation depends increasingly on large-scale computational science and engineering and thus HPC. How should the United States respond to this challenge? This report seeks to initiate a new and potentially transformative national discussion on this vital question. The Department of Energy’s (DOE) Advanced Scientific Computing Research (ASCR) program is well-positioned to make informed, targeted decisions about where the United States should cooperate and where it should compete in the global market for scientific exploration and discovery. By setting its sights on problems critical to our nation and the world, by establishing productive new collaborations, and by making strategic investments, ASCR can restore and maintain U.S. scientific leadership in the critical areas described in this report while strengthening our research infrastructure and training a large, diverse cohort of scientists. In doing so, ASCR and its scientists will pave the way for a secure and prosperous future for America. For more than 30 years, the ASCR program has provided the HPC and networking capabilities and expertise needed to support DOE’s mission to advance the national, economic, and energy security of the United States. The program now faces the challenge of developing and deploying the next generation of HPC systems and technologies, as well as supporting the application of HPC and artificial intelligence (AI) technologies to a wide range of scientific and engineering research problems. Through its research and development efforts, the ASCR program must also advance the state of the art in HPC and accelerate the pace of scientific discovery and technological innovation. Fulfilling this promise will require significantly increased investments, as well as innovative policies and programs. This subcommittee is aware that we are making recommendations and calls for action at a time when federal resources are limited. We understand that a wide range of competing priorities must be balanced by the nation’s leaders and that there is a need to leverage resources in new ways and seek efficiencies in facilities and operations. However, we must not let these realities limit our imagination or silence our advocacy. The ASCR program is a key part of the U.S. research infrastructure and an important component of economic growth and U.S. competitiveness. ASCR has a responsibility to pursue its mission, including advanced scientific computing, applications of AI technologies, and the required advanced research facilities, with determination and enthusiasm. To fulfill the scientific enterprise’s responsibility to the nation, the ASCR program must not only develop and publish a clear vision with an associated list of goals, priorities, and recommendations but also demonstrate scientific leadership by consistently securing long-term funding. This will allow the program to build on its achievements to date, to realize its ambitious vision, and to make lasting contributions to the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗