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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Strategies for Validation Testing of Ground Systems

In order to accomplish the full Vision for Space Exploration announced by former President George W. Bush in 2004, NASA will have to develop a new space transportation system and supporting infrastructure. The main portion of this supporting infrastructure will reside at the Kennedy Space Center (KSC) in Florida and will either be newly developed or a modification of existing vehicle processing and launch facilities, including Ground Support Equipment (GSE). This type of large-scale launch site development is unprecedented since the time of the Apollo Program. In order to accomplish this successfully within the limited budget and schedule constraints a combination of traditional and innovative strategies for Verification and Validation (V&V) have been developed. The core of these strategies consists of a building-block approach to V&V, starting with component V&V and ending with a comprehensive end-to-end validation test of the complete launch site, called a Ground Element Integration Test (GEIT). This paper will outline these strategies and provide the high level planning for meeting the challenges of implementing V&V on a large-scale development program. KEY WORDS: Systems, Elements, Subsystem, Integration Test, Ground Systems, Ground Support Equipment, Component, End Item, Test and Verification Requirements (TVR), Verification Requirements (VR)

Annis, Tammy↗
NASA NTRS2016

Cobalt: Development and Maturation of GN&C Technologies for Precision Landing

The CoOperative Blending of Autonomous Landing Technologies (COBALT) instrument is a terrestrial test platform for development and maturation of guidance, navigation and control (GN&C) technologies for precision landing. The project is developing a third-generation Langley Research Center (LaRC) navigation doppler lidar (NDL) for ultra-precise velocity and range measurements, which will be integrated and tested with the Jet Propulsion Laboratory (JPL) lander vision system (LVS) for terrain relative navigation (TRN) position estimates. These technologies together provide precise navigation knowledge that is critical for a controlled and precise touchdown. The COBALT hardware will be integrated in 2017 into the GN&C subsystem of the Xodiac rocket-propulsive vertical test bed (VTB) developed by Masten Space Systems, and two terrestrial flight campaigns will be conducted: one open-loop (i.e., passive) and one closed-loop (i.e., active).

Carson, John M.↗
NASA NTRS2017

Development of an Axisymmetric Afterbody Test Case for Turbulent Flow Separation Validation

As identified in the CFD Vision 2030 Study commissioned by NASA, validation of advanced RANS models and scale-resolving methods for computing turbulent flows must be supported by improvements in high-quality experiments designed specifically for CFD implementation. A new test platform referred to as the Axisymmetric Afterbody allows for a range of flow behaviors to be studied on interchangeable afterbodies while facilitating access to higher Reynolds number facilities. A priori RANS computations are reported for a risk-reduction configuration to demonstrate critical variation among turbulence model results for a given afterbody, ranging from barely-attached to mild separated flow. The effects of body nose geometry and tunnel-wall boundary condition on the computed afterbody flow are explored to inform the design of an experimental test program.

Disotell, Kevin J.↗
NASA NTRS1998

What Determines the Response: Test or Reference?

The stability of sensory memory has been studied by presenting a reference stimulus, a delay, and a test stimulus. As has been pointed out by Lages and Treisman (1998 Vision Research 38 557-572), the usual measure of performance depends only on the effect of test variations on the responses. The Weber fraction characterizing performance is more properly called the test stimulus Weber fraction. We measure the relative contribution of the test and reference to the response by the ratio of the test Weber fraction to the reference Weber fraction. The stimuli were two dark lines on a bright background. Seven reference separations, varying from 9.5 to 16.7 arc min, were intermixed in each run. Interstimulus intervals (ISI) of 50, 200 and 2000 msec and intertrial intervals (ITI) of 500 and 2500 msec were investigated. When the ISI was short (50 or 200 msec), for both ITIs, responses were determined equally by the test and reference. For the long ISI (2000 msec), the reference stimulus contributed less. However, only for the 500 msec ITI (and not for all observers) was the contribution of the reference stimulus negligible, as Treisman's criterion setting theory might suggest.

Chukova, S. V.↗
NASA NTRS1986

A stereo model based upon mechanisms of human binocular vision

A model for stereo vision, which is based on the human-binocular vision system, is proposed. Data collected from studies of neurophysiology of the human binocular system are discussed. An algorithm for the implementation of this stereo vision model is derived. The algorithm is tested on computer-generated and real scene images. Examples of a computer-generated image and a grey-level image are presented. It is noted that the proposed method is computationally efficient for depth perception, and the results indicate accuracies that are noise tolerant.

Griswold, N. C.↗
NASA NTRS1998

Broadband Interferometer for Measuring Transmitted Wavefronts of Optical Bandpass Filters for HST (ACS)

The transmitted wavefronts of optical filters for the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) are characterized using the Wildly and Openly Modified Broadband Achromatic Twyman Green (WOMBAT) Interferometer developed in the NASA/GSFC Optics Branch's Diffraction Grating Evaluation Facility (DGEF). Because only four of thirty-three of ACS's optical bandpass filters transmit the 633 nm light of most commercial interferometers, a broadband interferometer is required to verify specified transmitted wavefront of ACS filters. WOMBAT's design is a hybrid of the BAT interferometer developed by JPL used for HST Wide Field and Planetary Camera 2 (WFPC-2) filters and a WYKO 400 phase shifting interferometer. It includes a broadband light source, monochromator, off-axis, parabolic collimating and camera mirrors, an aluminum-coated fused silica beam splitter, flat retroreflecting mirrors for the test and reference arms, and a LTV-sensitive CCD camera. An outboarded, piezo-electric phase shifter holds the flat mirror in the interferometer's reference arm. The interferometer is calibrated through interaction between the WYKO system's software and WONMAT hardware for the test wavelength of light entering the beam splitter. Phase-shifted interferograms of the filter mounted in the test arm are analyzed using WYKO's Vision' software. Filters as large as 90 mm in diameter have been measured over a wavelength range from 200 to 1100 nm with a sensitivity of lambda/200 rms at lambda = 633 nm. Results of transmitted wavefront measurements are shown for ACS fixed band pass and spatially-variable bandpass filters for a variety of wavelengths.

Boucarut, R. A.↗
NASA NTRS2006

A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

Johnson, Daniel J.↗
DOE OSTI2026

CTRL-STEER: Closed-Loop Neuron Activation Control in Vision-Language-Action Models

Vision-Language-Action (VLA) models enable test-time behavioral steering via neuron-level interventions, but existing methods use fixed strengths and operate in open loop. This static modulation fails under evolving task dynamics, leading to overcorrection, oscillations, and reduced task success—especially for temporal attributes like speed. We propose CTRL-STEER, a control-theoretic framework that casts activation steering as closed-loop feedback with adaptive, time-varying interventions. Instead of assuming neurons encode temporal concepts, we steer along motion-aligned residual directions and regulate intervention magnitude via feedback. We instantiate this with both PID and reinforcement learning controllers that jointly optimize concept adherence and task success. Experiments on fine-tuned OpenVLA policies across four LIBERO suites show improved stability and a better steering–success trade-off over fixed-coefficient baselines, without retraining the base model.

Babu, Abhijith [Florida International University, ↗
DOE OSTI2025

NRIC Annual Report FY 2025

The National Reactor Innovation Center (NRIC), established in August 2019, is a national United States (U.S.) Department of Energy (DOE) program. NRIC’s mission is to partner with industry and national laboratories to bridge the gap between concept, demonstration, and commercialization of advanced nuclear technology. NRIC accomplishes this through building or enhancing existing DOE infrastructure to support testing of components and systems that are key to successfully deploying advanced nuclear technology. NRIC’s vision is that by 2028, NRIC will be partnered with industry and accelerating the demonstration and deployment of advanced nuclear technology using DOE national laboratory infrastructure and expertise. NRIC will establish four new experimental facilities and two large reactor test beds for integrated technology demonstrations and experimentation by 2028 and complete two advanced nuclear technology tests by 2030. Achieving this vision will enable urgently needed abundant and affordable clean energy both domestically and internationally. NRIC’s success will inspire our nation and the global community to embrace the promising contribution of innovative nuclear reactor technologies to the clean energy economy and re-establish the U.S. as the global leader in advanced nuclear energy. NRIC is tasked with expediting the development of advanced nuclear energy technologies by bringing together private-sector technology developers and the world-class capabilities of the DOE national laboratory system. Through this program, the U.S. private sector is given access to the physical infrastructure available at DOE national laboratories to test and demonstrate their reactor concepts. NRIC works closely with the DOE-Nuclear Energy (NE) program that grants access to technical, regulatory, and financial support for commercializing nuclear energy. NRIC builds upon these new reactor concepts and technology successes to effectively strengthen U.S. nuclear leadership.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

DVA as a Diagnostic Test for Vestibulo-Ocular Reflex Function

The vestibulo-ocular reflex (VOR) stabilizes vision on earth-fixed targets by eliciting eyes movements in response to changes in head position. How well the eyes perform this task can be functionally measured by the dynamic visual acuity (DVA) test. We designed a passive, horizontal DVA test to specifically study the acuity and reaction time when looking in different target locations. Visual acuity was compared among 12 subjects using a standard Landolt C wall chart, a computerized static (no rotation) acuity test and dynamic acuity test while oscillating at 0.8 Hz (+/-60 deg/s). In addition, five trials with yaw oscillation randomly presented a visual target in one of nine different locations with the size and presentation duration of the visual target varying across trials. The results showed a significant difference between the static and dynamic threshold acuities as well as a significant difference between the visual targets presented in the horizontal plane versus those in the vertical plane when comparing accuracy of vision and reaction time of the response. Visual acuity increased proportional to the size of the visual target and increased between 150 and 300 msec duration. We conclude that dynamic visual acuity varies with target location, with acuity optimized for targets in the plane of rotation. This DVA test could be used as a functional diagnostic test for visual-vestibular and neuro-cognitive impairments by assessing both accuracy and reaction time to acquire visual targets.

Wood, Scott J.↗
NASA NTRS1991

Operator-coached machine vision for space telerobotics

A prototype system for interactive object modeling has been developed and tested. The goal of this effort has been to create a system which would demonstrate the feasibility of high interactive operator-coached machine vision in a realistic task environment, and to provide a testbed for experimentation with various modes of operator interaction. The purpose for such a system is to use human perception where machine vision is difficult, i.e., to segment the scene into objects and to designate their features, and to use machine vision to overcome limitations of human perception, i.e., for accurate measurement of object geometry. The system captures and displays video images from a number of cameras, allows the operator to designate a polyhedral object one edge at a time by moving a 3-D cursor within these images, performs a least-squares fit of the designated edges to edge data detected with a modified Sobel operator, and combines the edges thus detected to form a wire-frame object model that matches the Sobel data.

Bon, Bruce↗
NASA NTRS1990

Flight investigation of variations in rotorcraft control and display dynamics for hover

Results are presented from a flight test of experimental control/display systems for the U.S. Army/NASA CH-47B variable-stability research helicopter in hovering maneuvers, supplementing the preliminary report of Eshow et al. (1987). The display format was a simplified version of the pilot night-vision system for the Apache AH-64, and the tests measured pilot performance in hover-pad capture and hover-pad tracking tasks (under simulated zero visibility) using displays based on (1) gainlike and (2) integratorlike controlled-element responses to control inputs. The implementation of the vehicle-response dynamics through an explicit model-following control system and the derivation of the display laws are described, and the test results are presented in extensive tables and graphs. Display type (1) was found to be preferred by the pilots and to give generally better performance than type (2).

Eshow, Michelle M.↗
DOE OSTI2025

ORNL Package Testing Program Overview

When transporting radioactive or hazardous materials, safety and security are top priorities. Packaging and transportation regulations require reliable evidence that containers have passed rigorous performance tests to ensure that the public and the environment are protected from the hazardous nature of the cargo. Because of its long history in energy and security research, Oak Ridge National Laboratory (ORNL) has needed to ship hazardous packages for the past 65 years. Since the 1940s, ORNL has made significant contributions to transportation regulations and has been at the forefront of regulatory testing development. Today, ORNL is a leader in standards development and testing of designs of radioactive material packages. ORNL plays a critical role in ensuring the safe transportation of radioactive materials across the United States by executing rigorous testing campaigns of packages that contain radioactive materials. Early testing activities focused on supporting the development of transportation regulations established by both the International Atomic Energy Agency (IAEA) and the United States. Currently, all package testing activities are performed under the Package Testing Program (PTP) at the Package Evaluation Facility (PEF) located at the National Transportation Research Center (NTRC), which is about 10 miles from the main ORNL campus. The PTP develops and evaluates testing solutions, ensuring that they are safe efficient, and in compliance with regulatory requirements. The vision for the PTP is to be a world-class leader in the evaluation and testing of radioactive and hazardous material packages. The key elements necessary to fulfill this mission are an experienced and professional staff; state-of-the-art facilities, equipment, and instrumentation; and completion of challenging programs and projects important to package transportation. Collaborations with other internal and external organizations play a significant role in building stronger teams and achieving this vision. By adhering to and advancing regulatory standards, ORNL’s PTP supports development of safe and compliant packaging, safeguarding the transportation process from potential risks associated with radioactive material logistics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗
NASA NTRS2010

Dynamic Visual Acuity: a Functionally Relevant Research Tool

Coordinated movements between the eyes and head are required to maintain a stable retinal image during head and body motion. The vestibulo-ocular reflex (VOR) plays a significant role in this gaze control system that functions well for most daily activities. However, certain environmental conditions or interruptions in normal VOR function can lead to inadequate ocular compensation, resulting in oscillopsia, or blurred vision. It is therefore possible to use acuity to determine when the environmental conditions, VOR function, or the combination of the two is not conductive for maintaining clear vision. Over several years we have designed and tested several tests of dynamic visual acuity (DVA). Early tests used the difference between standing and walking acuity to assess decrements in the gaze stabilization system after spaceflight. Supporting ground-based studies measured the responses from patients with bilateral vestibular dysfunction and explored the effects of visual target viewing distance and gait cycle events on walking acuity. Results from these studies show that DVA is affected by spaceflight, is degraded in patients with vestibular dysfunction, changes with target distance, and is not consistent across the gait cycle. We have recently expanded our research to include studies in which seated subjects are translated or rotated passively. Preliminary results from this work indicate that gaze stabilization ability may differ between similar active and passive conditions, may change with age, and can be affected by the location of the visual target with respect to the axis of motion. Use of DVA as a diagnostic tool is becoming more popular but the functional nature of the acuity outcome measure also makes it ideal for identifying conditions that could lead to degraded vision. By doing so, steps can be taken to alter the problematic environments to improve the man-machine interface and optimize performance.

Peters, Brian T.↗
NASA NTRS2018

GTTC Future of Ground Testing Meta-Analysis of 20 Documents

National research, development, test, and evaluation ground testing capabilities in the United States are at risk. There is a lack of vision and consensus on what is and will be needed, contributing to a significant threat that ground test capabilities may not be able to meet the national security and industrial needs of the future. To support future decisions, the AIAA Ground Testing Technical Committee’s (GTTC) “Future of Ground Test” (FoGT) Working Group selected and reviewed 20 “seminal” documents related to the application and direction of ground testing. Each document was reviewed, with the content main points collected and organized into sections in the form of a gap analysis – current state, future state, major challenges/gaps, and recommendations. This paper includes key findings and selected commentary by an editing team.

Dunn, Steven C.↗
NASA NTRS1992

Development of a machine vision system for automated structural assembly

Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.

Sydow, P. Daniel↗
NASA NTRSDate not supplied

Validation of Image-Based Neural Network Controllersthrough Adaptive Stress Testing

Neural networks have become state-of-the-art for computer vision problems because of their ability to efficiently model complex functions from large amounts of data. While neural networks can be shown to perform well empirically fora variety of tasks, their performance is difficult to guarantee.Neural network verification tools have been developed that can certify robustness with respect to a given input image; however,for neural network systems used in closed-loop controllers,robustness with respect to individual images does not address multi-step properties of the neural network controller and itsenvironment. Furthermore, neural network systems interacting in the physical world and using natural images are operating in a black-box environment, making formal verification in-tractable. This work combines the adaptive stress testing (AST)framework with neural network verification tools to search for the most likely sequence of image disturbances that cause the neural network controlled system to reach a failure. Anautonomous aircraft taxi application is presented, and results show that the AST method finds failures with more likely image disturbances than baseline methods. Further analysis of AST results revealed an explainable cause of the failure, giving insight into the problematic scenarios that should be addressed.

Adaptive Stress Testing, Marabou, Deep Neural Netw↗