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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Characterization of Infrared Optical Motion Tracking System in NASA's Simulated Lunar Operations (SLOPE) Laboratory

This work characterizes the accuracy of a 16 camera OptiTrack motion tracking system installed in NASA Glenn Research Center's Simulated Lunar Operations (SLOPE) laboratory. The position of a rigid body mounted on a motorized linear stage is compared to its position reported by the motion tracking system as it travels through the facility's 777m$^3$ capture volume of interest. Experiments show that the mean error reported by the motion tracking system for the aggregate capture volume is in-line with independent measurements collected using the motion stage. Error within regions of the capture volume exceed the mean error reported by the motion tracking system, likely due to occlusion, and suggests that additional cameras should be used to increase measurement accuracy in these regions. Overall, results show that error values reported by the motion tracking system are representative of the measurement error in a collected data set and validates the system's use for characterizing the mobility and tractive performance of robots, rovers, and other vehicles for planetary exploration.

Motion capture↗
DOE OSTI2025

Immersive Digital Twin Laboratory for Engineering Education (CRADA Final Report)

This project aimed to create an immersive digital twin laboratory that incorporates advanced tracking and visualization capabilities. In collaboration with Fort Lewis College, NREL designed a state-of-the-art physical visualization laboratory, developed a software platform to enable interaction with tracked physical objects in the laboratory, and provided proof-of-concept curricula that included manipulating these tracked objects. The project was initiated to address the growing need for innovative educational tools in engineering education. As renewable energy systems, particularly solar installations, become more complex, there is a pressing need to bridge the gap between theoretical knowledge and practical application. Traditional methods of teaching solar engineering concepts often fall short of providing students with a comprehensive, hands-on understanding. This immersive digital twin laboratory was conceived to fill that gap by creating a safe, non-energized setting where students can interact with augmented solar installation objects, gaining valuable insights into system performance, design, and maintenance. The project utilized extended reality (XR) technologies, including head-mounted displays (HMDs) and a whole-room optical motion tracking system, to connect physical objects with their digital twins in real time. The laboratory was equipped with MagicLeap 2 HMDs, supported by a Vicon Vero 2.2 Optical Tracking System, which provided precise 6-degrees-of-freedom (6-DOF) tracking. We developed a software platform to manage the interaction between the tracked physical objects and their virtual counterparts, enabling real-time data synchronization, object recognition, and virtual overlays. We designed the system to be flexible and extendable, allowing for future integration of additional objects and curriculum. This research advances the field of engineering education by demonstrating the potential of immersive digital twin environments. The laboratory provides a dynamic learning space where students can experiment, collaborate, and learn without the risks associated with live experimentation. The ability to simulate and manipulate solar installation objects under various conditions has broad implications for workforce development, particularly in renewable energy. The project also highlights the economic feasibility of using XR technologies in educational settings, offering a cost-effective solution for institutions looking to enhance their curriculum. By fostering a deeper understanding of solar energy systems, this work contributes to the broader goal of supporting the global energy transition and preparing the next generation of engineers and technicians.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Performance Evaluation of an Offshore Wave Measurement Buoy in Monochromatic Waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6 s to 30 s. For wave periods between 5 s and 25 s, the buoy provides accurate wave height measurements. For short periods less than 5 s, the 1.28 Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25 s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. Furthermore, analysis of three field-derived cases shows that frequency-domain estimates at 1.28 Hz agree within 2% of the corresponding 100 Hz estimates, while larger method-dependent differences are observed for the Hilbert method.

16 TIDAL AND WAVE POWER↗
NASA NTRSDate not supplied

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Observations of atmospheric 3D winds are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we compare state-of-the-art convolutional neural networks for optical flow in a physics-guided deep learning framework for predicting AMVs. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

Geostationary↗
NASA NTRSDate not supplied

Towards Physics Guided Optical Flow for Tracking Atmospheric Motion

Atmospheric 3D winds in the horizontal and vertical directions are critical for improving short-range and long-range forecasting. Such advancement in forecasting directly applies to research in a number of areas including convective processes, wildfire plumes and tornado prediction. Atmospheric Motion Vectors (AMVs) provide a passively sensed approach to quantifying horizontal motion and cloud heights, which are typically sourced from geostationary sensors due to the availability of high frequency observations. Recent work has shown that estimating AMVs by tracking individual pixels with dense optical flow is a promising new direction. In this work, we use a state-of-the-art convolutional neural network for optical flow (FlowNetS) in a physics-guided deep learning framework for predicting AMVs in the horizontal direction. The approach is semi-supervised and uses physically informed wind vectors from high-resolution numerical simulations (DYAMOND) for supervised learning followed by fine-tuning though warping and reconstruction of full-disk geostationary images (GOES-16). In the vertical direction, we use labels from the CALIPSO low-earth orbit satellite to predict cloud height from 16-band geostationary images with a neural network. We present results for both tasks on held-out time periods and secondary datasets.

geostationary↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
DOE OSTI2021

New Design Yields Robust Large-Area Framing Camera

Manuscript to be submitted to Review of Scientific Instruments to determine interest in possible publication. Website: https://aip.scitation.org/rsi/authors/manuscript High-speed imaging is a core diagnostic capability for the Nevada National Security Site (NNSS). Data from experiments that measure the behavior of materials under extreme conditions are essential for the stockpile mission. For example, during subcritical experiments, materials that are shocked and compressed under high-explosive drive change behavior rapidly over timescales measured in millionths or even billionths of a second. Characterizing and understanding this behavior requires radiographic and/or optical imaging to track motion on these timescales. Framing cameras provide a discrete series of images over a short period of time in a manner that mimics a high-speed movie camera, but with individual shutter times that must be extremely short in order to capture freeze-frame images of rapidly evolving phenomena such as high-explosive shock-driven ejecta, dynamic compression of metals, and high-velocity fluid flow.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Vision-based recursive estimation of rotorcraft obstacle locations

The authors address vision-based passive ranging during nap-of-the-earth (NOE) rotorcraft flight. They consider the problem of estimating the relative location of identifiable features on nearby obstacles, assuming a sequence of noisy camera images and imperfect measurements of the camera's translation and rotation. An iterated extended Kalman filter is used to provide recursive range estimation. The correspondence problem is simplified by predicting and tracking each feature's image within the Kalman filter framework. Simulation results are presented which show convergent estimates and generally successful feature point tracking. Estimation performance degrades for features near the optical axis and for accelerating motions. Image tracking is also sensitive to angular rate.

Leblanc, D. J.↗
NASA NTRS2015

Spherical Coordinate Systems for Streamlining Suited Mobility Analysis

Introduction: When describing human motion, biomechanists generally report joint angles in terms of Euler angle rotation sequences. However, there are known limitations in using this method to describe complex motions such as the shoulder joint during a baseball pitch. Euler angle notation uses a series of three rotations about an axis where each rotation is dependent upon the preceding rotation. As such, the Euler angles need to be regarded as a set to get accurate angle information. Unfortunately, it is often difficult to visualize and understand these complex motion representations. It has been shown that using a spherical coordinate system allows Anthropometry and Biomechanics Facility (ABF) personnel to increase their ability to transmit important human mobility data to engineers, in a format that is readily understandable and directly translatable to their design efforts. Objectives: The goal of this project was to use innovative analysis and visualization techniques to aid in the examination and comprehension of complex motions. Methods: This project consisted of a series of small sub‐projects, meant to validate and verify a new method before it was implemented in the ABF's data analysis practices. A mechanical test rig was built and tracked in 3D using an optical motion capture system. Its position and orientation were reported in both Euler and spherical reference systems. In the second phase of the project, the ABF estimated the error inherent in a spherical coordinate system, and evaluated how this error would vary within the reference frame. This stage also involved expanding a kinematic model of the shoulder to include the rest of the joints of the body. The third stage of the project involved creating visualization methods to assist in interpreting motion in a spherical frame. These visualization methods will be incorporated in a tool to evaluate a database of suited mobility data, which is currently in development. Results: Initial results demonstrated that a spherical coordinate system is helpful in describing and visualizing the motion of a space suit. The system is particularly useful in describing the motion of the shoulder, where multiple degrees of freedom can lead to very complex motion paths.

Benson, Elizabeth↗
NASA NTRS2014

Spherical Coordinate Systems for Streamlining Suited Mobility Analysis

When describing human motion, biomechanists generally report joint angles in terms of Euler angle rotation sequences. However, there are known limitations in using this method to describe complex motions such as the shoulder joint during a baseball pitch. Euler angle notation uses a series of three rotations about an axis where each rotation is dependent upon the preceding rotation. As such, the Euler angles need to be regarded as a set to get accurate angle information. Unfortunately, it is often difficult to visualize and understand these complex motion representations. One of our key functions is to help design engineers understand how a human will perform with new designs and all too often traditional use of Euler rotations becomes as much of a hindrance as a help. It is believed that using a spherical coordinate system will allow ABF personnel to more quickly and easily transmit important mobility data to engineers, in a format that is readily understandable and directly translatable to their design efforts. Objectives: The goal of this project is to establish new analysis and visualization techniques to aid in the examination and comprehension of complex motions. Methods: This project consisted of a series of small sub‐projects, meant to validate and verify the method before it was implemented in the ABF's data analysis practices. The first stage was a proof of concept, where a mechanical test rig was built and instrumented with an inclinometer, so that its angle from horizontal was known. The test rig was tracked in 3D using an optical motion capture system, and its position and orientation were reported in both Euler and spherical reference systems. The rig was meant to simulate flexion/extension, transverse rotation and abduction/adduction of the human shoulder, but without the variability inherent in human motion. In the second phase of the project, the ABF estimated the error inherent in a spherical coordinate system, and evaluated how this error would vary within the reference frame. This stage also involved expanding a kinematic model of the shoulder, to include the torso, knees, ankle, elbows, wrists and neck. Part of this update included adding a representation of 'roll' about an axis, for upper arm and lower leg rotations. The third stage of the project involved creating visualization methods to assist in interpreting motion in a spherical frame. This visualization method will be incorporated in a tool to evaluate a database of suited mobility data, which is currently in development.

Benson, Elizabeth↗
DOE OSTI2021

Facile Measurement of the Rotation of a Single Optically Trapped Nanoparticle Using the Diagonal Ratio of a Quadrant Photodiode

Optical tweezers are a powerful tool for exploring physical properties of particles in various environments through analysis of their dynamics in a trapping potential. Analysis of the trapped particle's position is often done using interferometric back-focal-plane detection microscopy in which interference between the trapping laser and the light interacting with the trapped particle is projected on a quadrant photo-diode (QPD). The QPD measurements are almost universally the voltage ratios between the transverse components of the detector (left/right; up/down) that are calibrated to ascertain particle positions and orientations (i.e., rotation). In this paper, we demonstrate how measuring the diagonal ratio of the QPD allows tracking the spinning and orbital motion of optically trapped objects with enhanced sensitivity compared to the conventional transverse ratio and reveals additional information about particle dynamics. The diagonal ratio "balances" the signal from opposite sides of the QPD, allowing common mode noise reduction and increased measurement sensitivity of the rotating nanospheres at frequencies from below 200 Hz to above 15 kHz. We show that the variability in particle rotation rates is due to slight differences in the aspect ratio of the nanoparticles. We also measure in situ a gradual acceleration in the spinning frequency of trapped nanoparticles due to photothermal shedding of surface ligands and the resulting decrease of rotational friction in solution. The accelerating particles spin at rates exceeding 30 kHz and are eventually "optically printed" onto the glass coverslip on top of the liquid cell enclosure. The diagonal ratio is a simple, readily available, and powerful enabler for measuring rotational dynamics with a 5-fold sensitivity increase over conventional QPD measurements. This affords opportunities for controlling the orientational dynamics of trapped nanoparticles, which is crucial for various applications, including nanoscale mechanical motors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

Detection of obstacles on runway using Ego-Motion compensation and tracking of significant features

This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.

Kasturi, Rangachar↗
DOE OSTI2022

Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method

Computer-vision-based target tracking is a technology applied to a wide range of research areas, including structural vibration monitoring. However, current target tracking methods suffer from noise in digital image processing. In this paper, a new target tracking method based on the sparse optical flow technique is introduced for improving the accuracy in tracking the target, especially when the target has a large displacement. The proposed method utilizes the Oriented FAST and Rotated BRIEF (ORB) technique which is based on FAST (Features from Accelerated Segment Test), a feature detector, and BRIEF (Binary Robust Independent Elementary Features), a binary descriptor. ORB maintains a variety of keypoints and combines the multi-level strategy with an optical flow algorithm to search the keypoints with a large motion vector for tracking. Then, an outlier removal method based on Hamming distance and interquartile range (IQR) score is introduced to minimize the error. The proposed target tracking method is verified through a lab experiment—a three-story shear building structure subjected to various harmonic excitations. It is compared with existing sparse-optical-flow-based target tracking methods and target tracking methods based on three other types of techniques, i.e., feature matching, dense optical flow, and template matching. The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method. The proposed sparse-optical-flow-based target tracking method achieves the best accuracy compared to other existing target tracking methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dynamic motion trajectory control with nanoradian accuracy for multi-element X-ray optical systems via laser interferometry

The past decades have witnessed the development of new X-ray beam sources with brightness growing at a rate surpassing Moore’s law. Current and upcoming diffraction limited and fully coherent X-ray beam sources, including multi-bend achromat based synchrotron sources and high repetition rate X-ray free electron lasers, puts increasingly stringent requirements on stability and accuracy of X-ray optics systems. Parasitic motion errors at sub-micro radian scale in beam transport and beam conditioning optics can lead to significant loss of coherence and brightness delivered from source to experiment. To address this challenge, we incorporated optical metrology based on interferometric length and angle sensing and real-time correction as part of the X-ray optics motion control system. A prototype X-ray optics system was constructed following the optical layout of a tunable X-ray cavity. On-line interferometric metrology enabled dynamical feedback to a motion control system to track and compensate for motion errors. The system achieved sub-microradian scale performance, as multiple optical elements are synchronously and continuously adjusted. This first proof of principle measurement demonstrated both the potential and necessity of incorporating optical metrology as part of the motion control architecture for large scale X-ray optical systems such as monochromators, delay lines, and in particular, X-ray cavity systems to enable the next generation cavity-based X-ray free electron lasers.

47 OTHER INSTRUMENTATION↗
NASA NTRS1984

Spacecraft system study: A study to define the impact of laser communication systems on their host spacecraft

The mutual influence of a laser communication system and its host spacecraft and the degree to which the mutual influence limited acquisition, tracking and pointing processes were investigated. A laser klink between a low earth orbiting (LEO) satellite and a geosynchronous earth orbiting (GEO) satellite was used as a baseline. The laser link between satellites was a generic channel transferring 500 Mbps data from the LEO to GEO using the GaAlAs laser as the laser light source. Major aspects of pointing and tracking with a satelliteborne optical system were evaluated including: (1) orbital aspects such as spacecraft relative motions, point ahead, and Sun snd Moon optical noise; (2) burst errors introduced by the electronic and optical noise levels; (3) servo system design and configurations, and the noise sources such as, sensor noise, base motion disturbances, gimbal friction torque noise; (4) an evaluation of the tracking and beacon link and the type of sensors used; (5) the function of the acquisition procedure and an evaluation of the sensors employed; and (6) an estimate of the size, weight and power needed for the satellite system.

Source record↗
NASA NTRS2000

Ground-to-Ground Optical Communications Demonstration

A bidirectional horizontal-path optical link was demonstrated between Strawberry Peak (SP), Lake Arrowhead, California, and the JPL Table Mountain Facility (TMF), Wrightwood, California, during June and November of 1998. The 0.6-m telescope at TMF was used to broadcast a 4-beam 780-nm beacon to SP. The JPL-patented Optical Communications Demonstrator (OCD) at SP received the beacon, performed ne tracking to compensate for the atmosphere-induced beacon motion and retransmitted a 844-nm communications laser beam modulated at 40 to 500 Mb/s back to TMF. Characteristics of the horizontal-path atmospheric channel as well as performance of the optical communications link were evaluated. The normalized variance of the irradiance fluctuations or scintillation index delta2/I at either end was determined. At TMF where a single 844-nm beam was received by a 0.6-m aperture, the measured delta2/I covered a wide range from 0.07 to 1.08. A single 780-nm beam delta2/I measured at SP using a 0.09-m aperture yielded values ranging from 0.66 to 1.03, while a combination of four beams reduced the scintillation index due to incoherent averaging to 0.22 to 0.40. This reduction reduced the dynamic range of the fluctuations from 17 to 21 dB to 13 to 14 dB as compared with the OCD tracking sensor dynamic range of 10 dB. Predictions of these values also were made based on existing theories and are compared. Generally speaking, the theoretical bounds were reasonable. Discussions on the probability density function (PDF) of the intensity fluctuations are presented and compared with the measurements made. The lognormal PDF was found to agree for the weak scintillation regime as expected. The present measurements support evidence presented by earlier measurements made using the same horizontal path, which suggests that the aperture averaging effect is better than theoretically predicted.

Biswas, A.↗
NASA NTRS1982

An advanced tracker design for pointing and control of space vehicles using the charge injection device

The use of charge transfer devices (CTD) in pointing and control of space vehicles is examined, with emphasis on the use of charge injection devices (CID). The selection of CTD type and CID operation, including CID signal and noise analysis and signal improvement, are discussed. Star tracking operational advantages of the CTD are pointed out, and the tracking optical concept is discussed and graphically depicted. The position interpolation procedure and the effects of rate of stellar motion on position interpolation are considered, and error analysis is examined. Finally, the breadboard and test program are discussed in detail, coarse and fine acquisition, test for star, track pattern, test procedure and results. An overall accuracy performance of approximately 0.02 pixels or approximately 0.8 arcsec for the test equipment and tracker was obtained.

Jones, C.↗
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↗