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NASA NTRS1996

NanoDesign: Concepts and Software for a Nanotechnology Based on Functionalized Fullerenes

Eric Drexler has proposed a hypothetical nanotechnology based on diamond and investigated the properties of such molecular systems. While attractive, diamonoid nanotechnology is not physically accessible with straightforward extensions of current laboratory techniques. We propose a nanotechnology based on functionalized fullerenes and investigate carbon nanotube based gears with teeth added via a benzyne reaction known to occur with C60. The gears are single-walled carbon nanotubes with appended coenzyme groups for teeth. Fullerenes are in widespread laboratory use and can be functionalized in many ways. Companion papers computationally demonstrate the properties of these gears (they appear to work) and the accessibility of the benzyne/nanotube reaction. This paper describes the molecular design techniques and rationale as well as the software that implements these design techniques. The software is a set of persistent C++ objects controlled by TCL command scripts. The c++/tcl interface is automatically generated by a software system called tcl_c++ developed by the author and described here. The objects keep track of different portions of the molecular machinery to allow different simulation techniques and boundary conditions to be applied as appropriate. This capability has been required to demonstrate (computationally) our gear's feasibility. A new distributed software architecture featuring a WWW universal client, CORBA distributed objects, and agent software is under consideration. The software architecture is intended to eventually enable a widely disbursed group to develop complex simulated molecular machines.

Globus, Al↗

NASA NTRS1991

Optical joint correlator for real-time image tracking and retinal surgery

A method for tracking an object in a sequence of images is described. Such sequence of images may, for example, be a sequence of television frames. The object in the current frame is correlated with the object in the previous frame to obtain the relative location of the object in the two frames. An optical joint transform correlator apparatus is provided to carry out the process. Such joint transform correlator apparatus forms the basis for laser eye surgical apparatus where an image of the fundus of an eyeball is stabilized and forms the basis for the correlator apparatus to track the position of the eyeball caused by involuntary movement. With knowledge of the eyeball position, a surgical laser can be precisely pointed toward a position on the retina.

Juday, Richard D.↗

NASA NTRS2004

Software for Analyzing Sequences of Flow-Related Images

Spotlight is a computer program for analysis of sequences of images generated in combustion and fluid physics experiments. Spotlight can perform analysis of a single image in an interactive mode or a sequence of images in an automated fashion. The primary type of analysis is tracking of positions of objects over sequences of frames. Features and objects that are typically tracked include flame fronts, particles, droplets, and fluid interfaces. Spotlight automates the analysis of object parameters, such as centroid position, velocity, acceleration, size, shape, intensity, and color. Images can be processed to enhance them before statistical and measurement operations are performed. An unlimited number of objects can be analyzed simultaneously. Spotlight saves results of analyses in a text file that can be exported to other programs for graphing or further analysis. Spotlight is a graphical-user-interface-based program that at present can be executed on Microsoft Windows and Linux operating systems. A version that runs on Macintosh computers is being considered.

Klimek, Robert↗

NASA NTRS2004

Video Image Tracking Engine

A method and system for processing an image including capturing an image and storing the image as image pixel data. Each image pixel datum is stored in a respective memory location having a corresponding address. Threshold pixel data is selected from the image pixel data and linear spot segments are identified from the threshold pixel data selected.. Ihe positions of only a first pixel and a last pixel for each linear segment are saved. Movement of one or more objects are tracked by comparing the positions of fust and last pixels of a linear segment present in the captured image with respective first and last pixel positions in subsequent captured images. Alternatively, additional data for each linear data segment is saved such as sum of pixels and the weighted sum of pixels i.e., each threshold pixel value is multiplied by that pixel's x-location).

Howard, Richard T.↗

NASA NTRS2017

Stratospheric Instrusion Catalog: A 10-Year Compilation of Events Identified by using TRACK with NASA's MERRA-2 Reanalysis

Stratospheric intrusions "the introduction of ozone-rich stratospheric air into the troposphere" have been linked with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime. However, the impact of stratospheric intrusions in the remaining seasons and over the rest of the USA is less clear. A new approach to the study of stratospheric intrusions uses NASA's Goddard Earth Observing System Model (GEOS) model and assimilation products with an objective feature tracking algorithm to investigate the atmospheric dynamics that generate stratospheric intrusions and the different mechanisms through which stratospheric intrusions may influence tropospheric chemistry and surface air quality seasonally over both the western and the eastern USA. A catalog of stratospheric intrusions identified in the MERRA-2 reanalysis was produced for the period 2004-2015 and validated against surface ozone observations (focusing on those which exceed the national air quality standard) and a recent data set of stratospheric intrusion-influenced air quality exceedance flags from the US Environmental Protection Agency (EPA). Considering not all ozone exceedances have been flagged by the EPA, a collection of stratospheric intrusions can support air quality agencies for more rapid identification of the impact of stratospheric air on surface ozone and demonstrates that future operational analyses may aid in forecasting such events. An analysis of the spatiotemporal variability of stratospheric intrusions over the continental US was performed, and while the spring over the western USA does exhibit the largest number of stratospheric intrusions affecting the lower troposphere, the number of intrusions in the remaining seasons and over the eastern USA is sizable. By focusing on the major modes of variability that influence weather in the USA, such as the Pacific North American (PNA) teleconnection index, predicative meteorological patterns associated with stratospheric intrusions and their regional effects on tropospheric ozone were identified. Improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of such events.

PN↗

NASA NTRS2015

Biomimetic Fly Eye Sensor for Real-Time Target Tracking

The project objective is to design, build, and demonstrate a biomimetic (inspired by biology) smart sensor based on the common house fly eye for real-time target tracking in three dimensions (3-D). The sensor makes use of revolutionary optical sensor design resulting in significantly improved motion detection capabilities when compared with conventional optical sensors. The design is motivated by the parallel nature of the flys vision system and its demonstrated hyperacuity or precision of visual localization beyond the conventional resolution limit. This means that the sensor is able to accurately detect very fast motion and small changes in motion. The analog architecture of the sensor allows for real-time solution at adjustable bandwidths depending on the application. The low cost, exceptionally lightweight, small form factor, low power requirements, and low computation requirements of the sensor make it ideally suited to many aeronautics applications that have limitations on weight, power, and processing time. The sensor is modular and can be easily adapted in scale and manufactured for a wide variety of sensing applications. Advanced target tracking algorithms will be developed to allow the sensor to track a target in 3-D. These algorithms will be implemented in the smart sensors hardware to enable real-time target tracking.

wing position measurement system↗

NASA NTRS2012

NASA's Marshall Space Flight Center Recent Studies and Technology Developments in the Area of SSA/Orbital Debris

NASA/MSFC has been investigating the various aspects of the growing orbital debris problem since early 2009. Data shows that debris ranging in size from 5 mm to 10 cm presents the greatest threat to operational spacecraft today. Therefore, MSFC has focused its efforts on small orbital debris. Using off-the-shelf analysis packages, like the ESA MASTER software, analysts at MSFC have begun to characterize the small debris environment in LEO to support several spacecraft concept studies and hardware test programs addressing the characterization, mitigation, and ultimate removal, if necessary, of small debris. The Small Orbital Debris Active Removal (SODAR) architectural study investigated the overall effectiveness of removing small orbital debris from LEO using a low power, space-based laser. The Small Orbital Debris Detection, Acquisition, and Tracking (SODDAT) conceptual technology demonstration spacecraft was developed to address the challenges of in-situ small orbital debris environment classification including debris observability and instrument requirements for small debris observation. Work is underway at MSFC in the areas of hardware and testing. By combining off the shelf digital video technology, telescope lenses, and advanced video image FPGA processing, MSFC is building a breadboard of a space based, passive orbital tracking camera that can detect and track faint objects (including small debris, satellites, rocket bodies, and NEOs) at ranges of tens to hundreds of kilometers and speeds in excess of 15 km/sec,. MSFC is also sponsoring the development of a one-of-a-kind Dynamic Star Field Simulator with a high resolution large monochrome display and a custom collimator capable of projecting realistic star images with simple orbital debris spots (down to star magnitude 11-12) into a passive orbital detection and tracking system with simulated real-time angular motions of the vehicle mounted sensor. The dynamic star field simulator can be expanded for multiple sensors (including advanced star trackers), real-time vehicle pointing inputs, and more complex orbital debris images. This system is also adaptable to other sensor optics, missions, and installed sensor testing.

Wiegmann, Bruce M.↗

DOE OSTI2025

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations Using Random Finite Sets

Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.

Schlenker, Lauren↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations using Random Finite Sets

Schlenker, Lauren↗

DOE OSTI2025

An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras

The talk at the NAWEA Wind Tech 2024 conference discusses how to leverage the potential of real-time thermal-imaging methodologies in quantifying nocturnal bat activities at wind turbines, using 3D computer vision techniques within a deep learning framework. This innovation enables the automatic detection and classification of bats, birds, and insects in thermal-imaging videos captured at wind turbine sites, facilitating efficient and accurate data analysis for enhanced understanding and mitigation of bat-wind turbine interactions.

AI↗

DOE OSTI2025

An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras

The poster at the 15th Wind Wildlife Research Meeting discusses how to leverage the potential of real-time thermal-imaging methodologies in quantifying nocturnal bat activities at wind turbines, using 3D computer vision techniques within a deep learning framework. This innovation enables the automatic detection and classification of bats, birds, and insects in thermal-imaging videos captured at wind turbine sites, facilitating efficient and accurate data analysis for enhanced understanding and mitigation of bat-wind turbine interactions.

AI↗

DOE OSTI2025

Spatiotemporal Variations in the Characteristics of Mesoscale Convective Systems Over Indian Monsoon Zone

Here, this study examines cloud and precipitation properties of mesoscale convective systems (MCSs) in the Indian monsoon zone using 6 years of high-resolution satellite-based tracking data. MCSs exhibit strong regional and seasonal variations, peaking during the summer monsoon (June–September). Concentrated along a southeast-northwest band of the monsoon trough, MCS contribute 40%–70% of total precipitation and predominantly move westward at an average speed of 6.3 m s -1 . Long-lived MCSs (> 40 hr), although 10 times less frequent than short-lived MCSs (5–20 hr), produce 2–3 times more rainfall. Longer MCS lifespans and higher rainfall are associated with stronger deep-layer wind shear and enhanced lower free-tropospheric moisture at initiation. Land and ocean MCSs exhibit distinct diurnal cycles. Most land-based MCSs initiate around 16 LT and mature at 18 LT, whereas Bay of Bengal (BoB) MCSs initiate between 04 and 06 LT and peak by 14 LT. Convective precipitations from MCSs significantly surpasses that from non-MCSs systems, emphasizing their critical role in intense monsoon rainfall. Short- and long-lived MCSs showed distinct lifecycle evolution. Long-lived MCSs over the BoB show 37% larger cold-cloud shields, 44% larger precipitation feature areas, and 33% higher rain rates than their land counterparts, yielding 67% more total rainfall. These BoB MCSs also grow faster and experience more frequent cloud mergers early in their lifecycle. These findings offer critical insights into monsoonal MCSs lifecycle evolution, providing observational constraints for improving model simulations of monsoonal convection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Vehicle Tracking with Crop-based Detection

End-to-end production of vehicle tracking data from video in real-time and with high accuracy remains a challenging problem due to the computational cost of object detection on each frame. In this work we present Tracking with Crop-based Detection, a method for speeding object tracking in constrained contexts (with stable cameras and relatively-predictable object motion) such as vehicle traffic monitoring. We leverage this context to provide a strong prior for object locations, which we use to 1.) boost detection speed by detecting objects only in regions corresponding to object priors on most frames and 2.) inform the selection of the detector output for each object. We evaluate Crop-based Detection as an extension to the KIOU object tracker (Crop-KIOU) on the UA-DETRAC dataset. The proposed tracker outperforms all other reported algorithms in terms of PR-MOTA, PR-MOTP, and mostly tracked objects on the UA-DETRAC benchmark, establishing a new state-of-the-art. Relative to tracking by detection with KIOU, Crop-KIOU achieves a 26% higher frame-rate and increases accuracy. Furthermore, Tracking with Crop-based Detection can be combined with frame skipping; we show a 149% increase in framerate relative to KIOU with no decrease in accuracy using this combination of methods.

Gloudemans, Derek↗

DOE OSTI2026

A bi-level advanced control framework for large-scale control of buildings with system-level impact

Increased electricity consumption combined with new forms of generation is testing the reliability of our grid infrastructure. This work describes a method to improve the reliability of the grid through large-scale advanced building control. This paper develops a bi-level distributed control framework to shift the load of 153 buildings to achieve a system-level objective of tracking a power reference signal. This bi-level control is based on the previously-developed ANPV-MPC, a predictive controller that uses a Bayesian neural network to generate an accurate control model and adapt to changing conditions over time. By shifting the building electricity demand to better match the available power, the grid system supplying the buildings is more reliable as evidenced by the analysis of node voltages across an IEEE 13-bus distribution system. The proposed bi-level control framework tracks the system-level power reference with enough accuracy to regulate node voltages across the IEEE 13-bus distribution system within ANSI limits of ±5%. Additionally, the adaptive nature of ANPV-MPC allows each building across the system to adapt to changing conditions, further amplifying the system-level reliability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantitative spatiotemporal mapping of thermal runaway propagation rates in lithium-ion cells using cross-correlated Gabor filtering

Abuse testing of lithium-ion batteries is widely performed in order to develop new safety standards and strategies. However, testing methodologies are not standardised across the research community, especially with failure mechanisms being inherently difficult to reproduce. High-speed X-ray radiography is proven to be a valuable tool to capture events occurring during cell failure, but the observations made remain largely qualitative. We have therefore developed a robust image processing toolbox that can quantify, for the first time, the rate of propagation of battery failure mechanisms revealed by high-speed X-ray radiography. Using Gabor filter, the toolbox selectively tracks the electrode structure at the onset of failure. This facilitated the estimation of the displacement of electrodes undergoing abuse via nail penetration, and also the tracking of objects, such as the nail, as it propagates through a cell. Further, by cross-correlating the Gabor signals, we have produced practical, illustrative spatiotemporal maps of the failure events. From these, we can quantify the propagation rates of electrode displacement prior to the onset of thermal runaway. The highest recorded acceleration (≈514 mm s -2 ) was when a nail penetrated a cell radially (perpendicular to the electrodes) as opposed to axially (parallel to the electrodes). The initiation of thermal runaway was also resolved in combination with electrode displacement, which occurred at a lower acceleration (≈108 mm s -2 ). Our assistive toolbox can also be used to study other types of failure mechanisms, extracting otherwise unattainable kinetic data. Ultimately, this tool can be used to not only validate existing theoretical mechanical models, but also standardise battery failure testing procedures.

25 ENERGY STORAGE↗

DOE OSTI2020

2020 Transportation Research Board Workshop: Infrastructure Spatial Sensing at Intersections: The Potential to Enhance Safety and Enable Automation

The sensing technology that is enabling vehicle automation also can revolutionize traffic intersection safety, control, and efficiency. Infrastructure spatial sensing technology refers to the deployment of sensors that can detect and track all objects in the field of view - for example, mounting lidar sensors, radar, and video imaging at an intersection and fusing the data to produce a three-dimensional dynamic operational awareness. Combining such sensing capability with fail-safe vehicle communications can facilitate applications such as eco-approach and departure, optimizing efficient vehicle-signal coordination, and reducing traffic accidents through increasing safety. Furthermore, evidence is mounting suggesting that infrastructure-based sensing is needed in order to safely deploy automated public mobility alongside the normal vehicle and pedestrian traffic in our cities. Six speakers were invited to present their work from various aspects (safety, efficiency, and automation) addressing infrastructure-based sensing at the workshop on Infrastructure Spatial Sensing hosted in Washington DC as part of the Transportation Research Board Annual Meeting in January 12, 2019. A summary of the presentation are included herein.

47 OTHER INSTRUMENTATION↗