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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Wind Vision: A New Era for Wind Power in the United States (Highlights); U.S. Department of Energy (DOE), NREL (National Renewable Energy Laboratory)

This is a four-part Wind Vision project, consisting of Wind Vision Highlights, Executive Summary, a Full Report, and Appendix. The U.S. Department of Energy (DOE) Wind Program, in close cooperation with the wind industry, led a comprehensive analysis to evaluate future pathways for the wind industry. The Wind Vision report updates and expands upon the DOE's 2008 report, 20% Wind Energy by 2030, and defines the societal, environmental, and economic benefits of wind power in a scenario with wind energy supplying 10% of national end-use electricity demand by 2020, 20% by 2030, and 35% by 2050.

17 WIND ENERGY↗
DOE OSTI2021

A METHODOLOGY TO SUPPORT THE DEVELOPMENT OF A NEW STATE VISION FOR THE UNITED STATES NUCLEAR INDUSTRY

A new strategy in the way in which the United States nuclear power plants (NPPs) are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce cost. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures continued safe and efficient operations of the United States NPP fleet. This work builds on existing guidance and leverages previous research to comprehensively address both bottom-up (i.e., utility needs) and top-down (i.e., first principles) considerations important for developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Restoration of high-sensitivity and adapting vision with a cone opsin

Inherited and age-related retinal degenerative diseases cause progressive loss of rod and cone photoreceptors, leading to blindness, but spare downstream retinal neurons, which can be targeted for optogenetic therapy. However, optogenetic approaches have been limited by either low light sensitivity or slow kinetics, and lack adaptation to changes in ambient light, and not been shown to restore object vision. We find that the vertebrate medium wavelength cone opsin (MW-opsin) overcomes these limitations and supports vision in dim light. MW-opsin enables an otherwise blind retinitis pigmenotosa mouse to discriminate temporal and spatial light patterns displayed on a standard LCD computer tablet, displays adaption to changes in ambient light, and restores open-field novel object exploration under incidental room light. By contrast, rhodopsin, which is similar in sensitivity but slower in light response and has greater rundown, fails these tests. Thus, MW-opsin provides the speed, sensitivity and adaptation needed to restore patterned vision.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ultrafast structural changes direct the first molecular events of vision

Vision is initiated by the rhodopsin family of light-sensitive G protein-coupled receptors (GPCRs). A photon is absorbed by the 11-cis retinal chromophore of rhodopsin, which isomerizes within 200 femtoseconds to the all-transconformation, thereby initiating the cellular signal transduction processes that ultimately lead to vision. However, the intramolecular mechanism by which the photoactivated retinal induces the activation events inside rhodopsin remains experimentally unclear. Here we use ultrafast time-resolved crystallography at room temperature to determine how an isomerized twisted all-trans retinal stores the photon energy that is required to initiate the protein conformational changes associated with the formation of the G protein-binding signalling state. The distorted retinal at a 1-ps time delay after photoactivation has pulled away from half of its numerous interactions with its binding pocket, and the excess of the photon energy is released through an anisotropic protein breathing motion in the direction of the extracellular space. Notably, the very early structural motions in the protein side chains of rhodopsin appear in regions that are involved in later stages of the conserved class A GPCR activation mechanism. Our study sheds light on the earliest stages of vision in vertebrates and points to fundamental aspects of the molecular mechanisms of agonist-mediated GPCR activation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Accuracy improvement in a calibration test bench for accelerometers by a vision system

A procedure is described in this paper for the accuracy improvement of calibration of low-cost accelerometers in a prototype rotary test bench, driven by a brushless servo-motor and operating in a low frequency range of vibrations (0 to 5 Hz). Vibration measurements by a vision system based on a low frequency camera have been carried out, in order to reduce the uncertainty of the real acceleration evaluation at the installation point of the sensor to be calibrated. A preliminary test device has been realized and operated in order to evaluate the metrological performances of the vision system, showing a satisfactory behavior if the uncertainty measurement is taken into account. A combination of suitable settings of the control parameters of the motion control system and of the information gained by the vision system allowed to fit the information about the reference acceleration at the installation point to the needs of the procedure for static and dynamic calibration of three-axis accelerometers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DeepAndes: A Self-Supervised Vision Foundation Model for Multispectral Remote Sensing Imagery of the Andes

By mapping sites at large scales usingremotely sensed data, archaeologists can generate unique insights into long-term demographic trends, interregional social networks, and human adaptations in the past. Remote sensing surveys complement field-based approaches, and their reach can be especially great when combined with deep learning and computer vision techniques. However, conventional supervised deep learning methods face challenges in annotating fine-grained archaeological features at scale. In addition, while recent vision foundation models have shown remarkable success in learning large-scale remote sensing data with minimal annotations, most off-the-shelf solutions are designed for RGB images rather than multispectral satellite imagery, such as the eight-band data used in our study. In this article, we introduce DeepAndes, a transformer-based vision foundation model trained on three million multispectral satellite images, specifically tailored for Andean archaeology. DeepAndes incorporates a customized DINOv2 self-supervised learning algorithm optimized for eight-band multispectral imagery, marking the first foundation model designed explicitly for the Andes region. We evaluate its image understanding performance through imbalanced image classification, image instance retrieval, and pixel-level semantic segmentation tasks. Our experiments show that DeepAndes achieves superior F1 scores, mean average precision, and Dice scores in few-shot learning scenarios, significantly outperforming models trained from scratch or pretrained on smaller datasets. This underscores the effectiveness of large-scale self-supervised pretraining in archaeological remote sensing.

Guo, Junlin [Vanderbilt Univ., Nashville, TN (Unit↗
DOE OSTI2016

Identifying local structural states in atomic imaging by computer vision

Abstract The availability of atomically resolved imaging modalities enables an unprecedented view into the local structural states of materials, which manifest themselves by deviations from the fundamental assumptions of periodicity and symmetry. Consequently, approaches that aim to extract these local structural states from atomic imaging data with minimal assumptions regarding the average crystallographic configuration of a material are indispensable to advances in structural and chemical investigations of materials. Here, we present an approach to identify and classify local structural states that is rooted in computer vision. This approach introduces a definition of a structural state that is composed of both local and nonlocal information extracted from atomically resolved images, and is wholly untethered from the familiar concepts of symmetry and periodicity. Instead, this approach relies on computer vision techniques such as feature detection, and concepts such as scale invariance. We present the fundamental aspects of local structural state extraction and classification by application to simulated scanning transmission electron microscopy images, and analyze the robustness of this approach in the presence of common instrumental factors such as noise, limited spatial resolution, and weak contrast. Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in an experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect-engineered multilayer graphene surface.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Interoperability Strategic Vision

The Interoperability Strategic Vision whitepaper aims to promote a common understanding of the meaning and characteristics of interoperability and to provide a strategy to advance the state of interoperability as applied to integration challenges facing grid modernization. This includes addressing the quality of integrating devices and systems and the discipline to improve the process of successfully integrating these components as business models and information technology improve over time. The strategic vision for interoperability described in this document applies throughout the electric energy generation, delivery, and end-use supply chain. Its scope includes interactive technologies and business processes from bulk energy levels to lower voltage level equipment and the millions of appliances that are becoming equipped with processing power and communication interfaces. A transformational aspect of a vision for interoperability in the future electric system is the coordinated operation of intelligent devices and systems at the edges of grid infrastructure. This challenge offers an example for addressing interoperability concerns throughout the electric system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Developing a Human Factors Engineering Program Plan and End State Vision to Support Full Nuclear Power Plant Modernization

The Light Water Reactor Sustainability (LWRS) Program, which is sponsored by the United States (U.S.) Department of Energy (DOE), conducts research and development (R&D) to establish the technical bases to sustain U.S. nuclear assets. One area in the LWRS program is the Plant Modernization pathway, which includes human factors R&D, human factors engineering (HFE), and ergonomics. LWRS program researchers in this pathway conduct targeted R&D to address aging and reliability concerns with the legacy instrumentation and control (I&C) and related information systems in commercial nuclear power plants (NPPs). One key aspect of this pathway is to develop a strategy for full nuclear plant modernization, which previous LWRS plant modernization milestone reports have begun to describe. To further support this comprehensive plan and vision for full plant modernization, additional details need to be further developed. In particular, a core aspect of a strategy for full nuclear plant modernization is an HFE program plan and an end state vision for plant modernization that is well-integrated with both 1) a technically defensible approach to migrating the existing, mostly analog I&C infrastructure to a digital I&C infrastructure, and 2) a valid business case methodology to cost-justify the modernization activity. Thus, the purpose of this LWRS R&D activity and milestone report is threefold. First, the report provides guidance for operating commercial NPPs to support their development and evaluation of an HFE program management plan (HFE PMP) and an end state vision for plant modernization. The report presents best practices and lessons learned related to HFE PMPs based on MCR modifications in which analog systems were replaced by digital I&C systems. Second, the report summarizes the rationale for full digital I&C integration, highlights a number of factors that are critical to consider, and describes how HFE should merge with full digital I&C integration. Finally, the report summarizes and integrates the economic factors that must be considered to cost-justify HFE involvement in plant modernization.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Hydropower Vision A New Chapter for America's 1st Renewable Electricity Source

The U.S. Department of Energy’s (DOE’s) Wind and Water Power Technologies Office has led a first-of-its- kind comprehensive analysis to evaluate future pathways for low-carbon, renewable hydropower (hydropower generation and pumped storage) in the United States, focused on continued technical evolution, increased energy market value, and environmental sustainability. Undertaken through a broad-based collaborative effort, the Hydropower Vision initiative had four principal objectives: characterize the current state of hydropower in the United States, including trends, opportunities, and challenges; identify ways for hydropower to maintain and expand its contributions to the electricity and water management needs of the nation from the present through 2030 and 2050; examine critical environmental and social factors to assess how existing hydropower operations and potential new projects can minimize adverse effects, reduce carbon emissions from electricity generation, and contribute to stewardship of waterways and watersheds; and develop a roadmap identifying stakeholder actions that could support responsible ongoing operations and potential expansion of hydropower facilities. The Hydropower Vision analysis finds that U.S. hydropower could grow from 101 gigawatts (GW) of capacity to nearly 150 GW by 2050. Growth under this modeled scenario would result from a combination of 13 GW of new hydropower generation capacity (upgrades to existing plants, adding power at existing dams and canals, and limited development of new stream-reaches), and 36 GW of new pumped storage capacity. If this level of growth is achieved, benefits such as a savings of $209 billion from avoided greenhouse gas (GHG) emissions could be realized, of which $185 billion would be attributable to operation of the existing hydropower fleet. Transformative technical innovations able to meet the co-objectives of environmental sustainability and low-carbon energy will be critical to enabling additional hydropower growth beyond these levels. The Hydropower Vision report specifically does not evaluate or recommend new policy actions but instead analyzes the feasibility and certain benefits and costs of various credible scenarios, all of which could inform policy decisions at the federal, state, tribal, and local levels.

13 HYDRO ENERGY↗
DOE OSTI2019

Goals, Policies and Actions that will Affect Improved Outcomes in District Heating in Ukraine: Summary of Policy Vision for Transformation

This policy paper lays out a vision for reforming the Ukrainian district heating system. This includes goals, policy priorities and actions to achieve that vision. This vision describes the transformation of the sector in the long-term, with sequencing to achieve real results starting in the near term.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Vision Transformers Explained Series

Since their introduction in 2017 with Attention is All You Need¹, transformers have established themselves as the state of the art for natural language processing (NLP). In 2021, An Image is Worth 16x16 Words successfully adapted transformers for computer vision tasks. Since then, numerous transformer-based architectures have been proposed for computer vision. This article walks through the Vision Transformer (ViT) as laid out in An Image is Worth 16x16 Words.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗
DOE OSTI2024

In Search of Optimum Fresh-Cut Raw Material: Using Computer Vision Systems as a Sensory Screening Tool for Browning-Resistant Romaine Lettuce Accessions

The popularity of ready-to-eat (RTE) salads has prompted novel technology to prolong the shelf life of their ingredients. Fresh-cut romaine lettuce is widely used in RTE salads; however, its tendency to quickly discolor continues to be a challenge for the industry. Selecting the ideal lettuce accessions for use in RTE salads is essential to ensure maximum shelf life, and it is critical to have a practical way to assess and compare the quality of multiple lettuce accessions that are being considered for use in fresh-cut applications. Thus, in this work we aimed to determine whether a computer vision system (CVS) composed of image acquisition, processing, and analysis could be effective to detect visual quality differences among 16 accessions of fresh-cut romaine lettuce during postharvest storage. The CVS involved a post-capturing color correction, effective image segmentation, and calculation of a browning index, which was tested as a predictor of quality and shelf life of fresh-cut romaine lettuce. The results demonstrated that machine vision software can be implemented to replace or supplement the scoring of a trained panel and instrumental quality measurements. Overall visual quality, a key sensory parameter that determines food preferences and consumer behavior, was highly correlated with the browning index, with a Pearson correlation coefficient of −0.85. Other important sensory decision parameters were also strongly or moderately correlated with the browning index, with Pearson correlation coefficients of −0.84 for freshness, 0.79 for off odor, and 0.57 for browning. The ranking of the accessions according to quality acceptability from the sensory evaluation produced a similar pattern to those obtained with the CVS. This study revealed that multiple lettuce accessions can be effectively benchmarked for their performance as fresh-cut sources via a CVS-based method. Future opportunities and challenges in using machine vision image processing to predict consumer preferences for RTE salad greens is also discussed.

Agriculture↗
NASA NTRS1973

Landing performance by low-time private pilots after the sudden loss of binocular vision - Cyclops II

Study of low-time general aviation pilots, who, in a series of spot landings, were suddenly deprived of binocular vision by patching either eye on the downwind leg of a standard, closed traffic pattern. Data collected during these landings were compared with control data from landings flown with normal vision during the same flight. The sequence of patching and the mix of control and monocular landings were randomized to minimize the effect of learning. No decrease in performance was observed during landings with vision restricted to one eye, in fact, performance improved. This observation is reported at a high level of confidence (p less than 0.001). These findings confirm the previous work of Lewis and Krier and have important implications with regard to aeromedical certification standards.

Lewis, C. E., Jr.↗
NASA NTRS1979

Robotic vision

Robotic vision, involving the use of a vision system to control a process, is discussed. Design and selection of active sensors employing radiation of radio waves, sound waves, and laser light, respectively, to light up unobservable features in the scene are considered, as are design and selection of passive sensors, which rely on external sources of illumination. The segmentation technique by which an image is separated into different collections of contiguous picture elements having such common characteristics as color, brightness, or texture is examined, with emphasis on the edge detection technique. The IMFEX (image feature extractor) system performing edge detection and thresholding at 30 frames/sec television frame rates is described. The template matching and discrimination approach to recognize objects are noted. Applications of robotic vision in industry for tasks too monotonous or too dangerous for the workers are mentioned.

Williams, D. S.↗
NASA NTRS1979

Some influences of vision on susceptibility to motion sickness

Two experiments were performed to evaluate the influence of vision on susceptibility to motion sickness during exposure to constant patterns of vestibular stimulation. The motion profile involved accelerating subjects at 20 deg/sec per sec to 300 deg/sec, maintaining them at that constant velocity for 30 sec, and decelerating them to a rapid stop in about 1.5 sec. The number of stops tolerated by a subject before reaching the motion sickness endpoint served as his score. In Experiment 1, subjects were tested twice with their eyes open and twice with their eyes blindfolded. They tolerated fewer sudden stops when permitted sight of the experimental chamber. In Experiment 2, the effect of having the eyes open or closed at different stages of the motion profile was evaluated. Having the eyes open during any stage of the test was more stressful than having the eyes closed, but this was especially true during the sudden stops. The findings are discussed in terms of their general implications for understanding (1) situations in which vision alone elicits symptoms of motion sickness, and (2) situations involving vestibular stimulation where vision heightens susceptibility.

Lackner, J. R.↗