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At least 1,369 records · Page 76

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NASA NTRS1998

Model-Trained Neural Networks and Electronic Holography Demonstrated to Detect Damage in Blades

Detect Damage in Blades Electronic holography can show damaged regions in fan blades at 30 frames/sec. The electronic holograms are transformed by finite-element-model-trained artificial neural networks to visualize the damage. The trained neural networks are linked with video and graphics to visualize the bending-induced strain distribution, which is very sensitive to damage. By contrast, it is very difficult to detect damage by viewing the raw, speckled, characteristic fringe patterns. For neural-network visualization of damage, 2 frames or 2 fields are used, rather than the 12 frames normally used to compute the displacement distribution from electronic holograms. At the NASA Lewis Research Center, finite element models are used to compute displacement and strain distributions for the vibration modes of undamaged and cracked blades. A model of electronic time-averaged holography is used to transform the displacement distributions into finite-element-resolution characteristic fringe patterns. Then, a feedforward neural network is trained with the fringe-pattern/strain-pattern pairs, and the neural network, electronic holography, and video are implemented on a workstation. Now that the neural networks have been tested successfully at 30 frames/sec on undamaged and cracked cantilevers, the electronic holography and neural-network processing are being adapted for onsite damage inspection of twisted fan blades and rotormounted blades. Our conclusion is that model-trained neural nets are effective when they are trained with good models whose application is well understood. This work supports the aeromechanical testing portion of the Advanced Subsonic Technology Project.

Decker, Arthur J.↗

NASA NTRS2001

Training Data Optimized and Conditioned to Learn Characteristic Patterns of Vibrating Blisks and Fan Blades

At the NASA Glenn Research Center, we have been training artificial neural networks to interpret the characteristic patterns (see the leftmost image) generated from electronic holograms of vibrating structures. These patterns not only visualize the vibration properties of structures, but small changes in the patterns can indicate structural changes, cracking, or damage. Neural networks detect these small changes well. Our objective has been to adapt the neural-network, electronic-holography combination for inspecting components in Glenn's Spin Rig.

Decker, Arthur J.↗

NASA NTRS2014

Wind Tunnel Testing of a 120th Scale Large Civil Tilt-Rotor Model in Airplane and Helicopter Modes

In April 2012 and October 2013, NASA and the U.S. Army jointly conducted a wind tunnel test program examining two notional large tilt rotor designs: NASA's Large Civil Tilt Rotor and the Army's High Efficiency Tilt Rotor. The approximately 6%-scale airframe models (unpowered) were tested without rotors in the U.S. Army 7- by 10-foot wind tunnel at NASA Ames Research Center. Measurements of all six forces and moments acting on the airframe were taken using the wind tunnel scale system. In addition to force and moment measurements, flow visualization using tufts, infrared thermography and oil flow were used to identify flow trajectories, boundary layer transition and areas of flow separation. The purpose of this test was to collect data for the validation of computational fluid dynamics tools, for the development of flight dynamics simulation models, and to validate performance predictions made during conceptual design. This paper focuses on the results for the Large Civil Tilt Rotor model in an airplane mode configuration up to 200 knots of wind tunnel speed. Results are presented with the full airframe model with various wing tip and nacelle configurations, and for a wing-only case also with various wing tip and nacelle configurations. Key results show that the addition of a wing extension outboard of the nacelles produces a significant increase in the lift-to-drag ratio, and interestingly decreases the drag compared to the case where the wing extension is not present. The drag decrease is likely due to complex aerodynamic interactions between the nacelle and wing extension that results in a significant drag benefit.

Wind Tunnel Testing of a 1/20th Scale↗

NASA NTRS2020

Evaluation, Analysis and Results of the DANTi Flight Test Data, the DAIDALUS Detect and Avoid Algorithm, and the DANTi Concept for Detect and Avoid in the Cockpit

The DAIDALUS Detect and Avoid Algorithm [1] was developed to address the operational needs of Unmanned Aerial Systems (UAS) and meet the Minimum Operational Performance Standards for Detect and Avoid [2]. The DANTi (Detect and Avoid iN the cockpit) concept [3], developed at the National Aeronautics and Space Administration (NASA) Langley Research Center, leverages advancements achieved in surveillance and Detect and Avoid technologies for unmanned aircraft systems as a safety enhancing capability for pilots of manned aircraft. Pilots operating under Visual Flight Rules and not receiving Air Traffic Control radar services rely on see and avoid to remain well clear of other aircraft and avoid collisions. The DANTi concept has been conceived as a safety enhancement capability to remain well clear and avoid potential collisions. The DANTi concept uses a traffic display to provide situational awareness, conflict detection, alerting, and guidance to remain well clear.

Detect and Avoid↗

DOE OSTI2020

Machine Vision-based Robot Manipulators for Nuclear Applications - 20370

Decommissioning and dismantling of nuclear facilities are major challenges facing the nuclear industry. Robot manipulators with capabilities of restoring nuclear structures and significantly prolonging nuclear power generation in addition to their applications in decommissioning and dismantling (D and D) would immensely ease the above-mentioned challenge. Ability to remotely sense/monitor and analyze dangerous and hazardous environments such as nuclear reactors as well as performing reparatory tasks in such environments using robot manipulators require additional information from vision sensors. Structural sample collection and inspection as well as restoration require object and position information. Computer vision is used to obtain precise 3D position information. The current work uses the Sawyer robot with the integrated Cognex camera. The research presents an approach to facilitate and improve operations in a nuclear reactor using robotic vision control. The vision control system is modeled with Augmented Image Space-based visual servoing approach. Results showing accurate robot control. Object recognition is used to recognize the image and calculate it poses. To transform coordinates of the object's pose from the camera frame to the robotic frame transformation matrices are employed. Future work will employ a 3D camera (with depth information) using Denso robot. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Volcano infrasound: progress and future directions

Over the past two decades (2000–2020), volcano infrasound (acoustic waves with frequencies less than 20 Hz propagating in the atmosphere) has evolved from an area of academic research to a useful monitoring tool. As a result, infrasound is routinely used by volcano observatories around the world to detect, locate, and characterize volcanic activity. It is particularly useful in confirming subaerial activity and monitoring remote eruptions, and it has shown promise in forecasting paroxysmal activity at open-vent systems. Fundamental research on volcano infrasound is providing substantial new insights on eruption dynamics and volcanic processes and will continue to do so over the next decade. The increased availability of infrasound sensors will expand observations of varied eruption styles, and the associated increase in data volume will make machine learning workflows more feasible. More sophisticated modeling will be applied to examine infrasound source and propagation effects from local to global distances, leading to improved infrasound-derived estimates of eruption properties. Future work will use infrasound to detect, locate, and characterize moving flows, such as pyroclastic density currents, lahars, rockfalls, lava flows, and avalanches. Infrasound observations will be further integrated with other data streams, such as seismic, ground- and satellite-based thermal and visual imagery, geodetic, lightning, and gas data. The volcano infrasound community should continue efforts to make data and codes accessible and to improve diversity, equity, and inclusion in the field. In summary, the next decade of volcano infrasound research will continue to advance our understanding of complex volcano processes through increased data availability, sensor technologies, enhanced modeling capabilities, and novel data analysis methods that will improve hazard detection and mitigation.

58 GEOSCIENCES↗

NASA NTRS2011

A Data Mining Project to Identify Cardiovascular Related Factors That May Contribute to Changes in Visual Acuity Within the US Astronaut Corps

Many of the cardiovascular-related adaptations that occur in the microgravity environment are due, in part, to a well-characterized cephalad-fluid shift that is evidenced by facial edema and decreased lower limb circumference. It is believed that most of these alterations occur as a compensatory response necessary to maintain a "normal" blood pressure and cardiac output while in space. However, data from both flight and analog research suggest that in some instances these microgravity-induced alterations may contribute to cardiovascular-related pathologies. Most concerning is the potential relation between the vision disturbances experienced by some long duration crewmembers and changes in cerebral blood flow and intra-ocular pressure. The purpose of this project was to identify cardiovascular measures that may potentially distinguish individuals at risk for visual disturbances after long duration space flight. Toward this goal, we constructed a dataset from Medical Operation tilt/stand test evaluations pre- (days L-15-L-5) and immediate post-flight (day R+0) on 20 (3 females, 17 males). We restricted our evaluation to only crewmembers who participated in both shuttle and space station missions. Data analysis was performed using both descriptive and analytical methods (Stata 11.2, College Station, TX) and are presented as means +/- 95% CI. Crewmembers averaged 5207 (3447 - 8934) flight hours across both long (MIR-23 through Expedition16) and short (STS-27 through STS-101) duration missions between 1988 and 2008. The mean age of the crew at the time of their most recent shuttle flight was 41 (34-44) compared to 47 (40-54) years during their time on station. In order to focus our analysis (we did not have codes to separate out subjects by symptomotology) , we performed a visual inspection of each cardiovascular measures captured during testing and plotted them against stand time, pre- to post-flight, and between mission duration. It was found that pulse pressure most clearly differentiated the two mission types. Statistical analysis confirmed that pulse pressure was significantly higher before [45.6; (42.1 to 49.1)] and after [50.7; (46.9 to 54.6)] time on station compared with their most recent shuttle flight [31.6 (27.8 to 35.4), and 32.2 (28.3 to 36.0) respectively] even after correcting differences in age and cumulative number of mission hours. Without knowing the identity of which long duration crewmembers demonstrated visual changes, we were limited to examining whether certain crew regulate components of pulse pressure, systolic and diastolic blood pressure, differently due to microgravity exposure. To that end, we stratified crew into tertiles based on either their pre-flight measure of systolic or diastolic blood pressure. Those crew in the highest tertile for both systolic (lower tertile (n=8; 103-111), middle tertile (n=7; 113-121), and upper tertile (n=5; 125-136) and diastolic blood pressure (lower tertile (n=8; 58-64), middle tertile (n=7; 67-73), and upper tertile (n=5; 75-81) demonstrated less variability in pulse pressure between R+0 and L-10 (Figure 2). Interestingly, those crewmembers with the highest resting systolic blood pressure demonstrated either no change or in some instances an increase in total peripheral resistance, where those in the lower tertiles had lower values of total peripheral resistance compared to pre-flight levels. In this study, it was found that crewmembers in the highest tertile for both systolic and diastolic blood pressure demonstrated less variability in pulse pressure and that the decrease in variability was due in part to lower levels of compliance as indicated by similar or higher levels of total peripheral resistance after compared with before flight levels. Whether there is a relation between blood pressure regulation and total peripheral resistance in crew presenting with negative changes in visual acuity remains unknown.

Westby, Christian M.↗

NASA NTRS1998

EDEN: a payload dedicated to neurovestibular research for Neurolab

The European Space Agency contributes to the Neurolab mission through the delivery of the ESA Developed Elements for Neurolab (EDEN). Those elements include one set supporting the Autonomic Nervous System experiment and one set supporting the Neurovestibular (so-called ATLAS) experiment. This second set is called the Visual and Vestibular Investigation System (VVIS). This paper describes the main characteristics of the VVIS and its various subsystems. The scientific objectives and operational constraints of the ATLAS experiment to be carried out with this equipment during Neurolab are presented to underline the correspondence between the VVIS design and the scientific requirements. Further scientific and technical perspectives for the VVIS, particularly within the scope of the International Space station, are also proposed.

Non-NASA Center↗

DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗

NASA NTRS2017

Flight Test Evaluation of an Unmanned Aircraft System Traffic Management (UTM) Concept for Multiple Beyond-Visual-Line-of-Sight (BVLOS) Operations

Many applications of small Unmanned Aircraft System (UAS) have been envisioned. These include surveillance of key assets such as pipelines, rail, or electric wires, deliveries, search and rescue, traffic monitoring, videography, and precision agriculture. These operations are likely to occur in the same airspace in the presence of many static and dynamic constraints such as airports, and high wind areas. Therefore, operations of small UAS need to be managed to ensure safety and operation efficiency is maintained. NASA has advanced a concept for UAS Traffic Management (UTM) and has initiated a research effort to refine that concept and develop operational and system requirements. A UTM research platform is in development and flight test activities to evaluate core functions and key assumptions focusing exclusively on UAS operations in different environments are underway. This seminar will present lessons learned from a recent flight test focused on enabling operations of multiple UAS in lower-risk environments within and beyond visual line of sight (BVLOS).

UTM↗

DOE OSTI2021

Interdisciplinary Research Collaborative Trains Students to See Through Turbulent Systems

Despite the availability of interdisciplinary academic training programs, the practice of environmental science is often hampered by a lack of convergence across diverse disciplines. This gap is particularly salient in settings characterized by complex environmental issues, such as multiple-use coastal ecosystems. In response, we developed and implemented a training, research, and communication framework to provide undergraduates with an authentic operative experience working at the interface of interdisciplinary science and public decision-making within a case study of marine renewable energy. In our program, students gained hands-on experience with the scientific process and learned how to make information relevant, useful, and accessible to diverse stakeholder groups. Application of this framework demonstrates that the process of integrating data from biological (visual and acoustic monitoring of fish and marine mammals), physical (hydrodynamics), and social (local ecological knowledge) sciences can provide a more complete understanding of complex and turbulent ecosystems for better informed decision-making. We offer several recommendations to facilitate the adaptation and implementation of our interdisciplinary framework to diverse research contexts, with a focus on interdisciplinary training for the next generation of marine scientists.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

Using the application visualization system to view HALOE three-dimensional satellite data

The Application Visualization System (AVS) is used to view a three-dimensional data field containing the volume mixing ratios of a chemical species in the middle atmosphere obtained by the Halogen Occultation Experiment (HALOE) aboard the Upper Atmosphere Research Satellite (UARS). Since launch in September 1991, HALOE has been collecting data on approximately 30 sunrise/sunset events in two narrow latitude bands each day. The vertical volume mixing ratio profiles are retrieved for eight species for each event. The accumulated data for approximately 30 days cover most of the globe (limited by sunlit latitudes), and this monthly data block can be described as the volume mixing ratio of a specific species in the atmosphere as a function of latitude, longitude, and height. The data were remapped using linear interpolation for pressure levels and Gaussian weighted binning from sampling locations to a three-dimensional grid. An AVS network is constructed that allows for viewing the three-dimensional field with rendered slices at constant latitudes, longitudes or pressure levels. Discussions are given on the advantages and some disadvantages learned about from experiences applying AVS to visualize HALOE three dimensional data.

Luo, Mingzhao↗

NASA NTRS2016

Background-Oriented Schlieren used in a hypersonic inlet test at NASA GRC

Background Oriented Schlieren (BOS) is a derivative of the classical schlieren technology, which is used to visualize density gradients, such as shock wave structures in a wind tunnel. Changes in refractive index resulting from density gradients cause light rays to bend, resulting in apparent motion of a random background pattern. The apparent motion of the pattern is determined using cross-correlation algorithms (between no-flow and with-flow image pairs) producing a schlieren-like image. One advantage of BOS is its simplified setup which enables a larger field-of-view (FOV) than traditional schlieren systems. In the present study, BOS was implemented into the Combined Cycle Engine Large-Scale Inlet Mode Transition Experiment (CCE LIMX) in the 10x10 Supersonic Wind Tunnel at NASA Glenn Research Center. The model hardware for the CCE LIMX accommodates a fully integrated turbine based combined cycle propulsion system. To date, inlet mode transition between turbine and ramjet operation has been successfully demonstrated. High-speed BOS was used to visualize the behavior of the flow structures shock waves during unsteady inlet unstarts, a phenomenon known as buzz. Transient video images of inlet buzz were recorded for both the ramjet flow path (high speed inlet) and turbine flow path (low speed inlet). To understand the stability limits of the inlet, operation was pushed to the point of unstart and buzz. BOS was implemented in order to view both inlets simultaneously, since the required FOV was beyond the capability of the current traditional schlieren system. An example of BOS data (Images 1-6) capturing inlet buzz are presented.

Background-oriented schlieren↗

NASA NTRS2018

In Situ Thermal Inspection of Automated Fiber Placement Operations for Tow and Ply Defect Detection

The advent of Automated Fiber Placement (AFP) systems have aided the rapid manufacturing of composite aerospace structures. One of the challenges that AFP systems pose is the uniformity of the deposited prepreg tape layers, which complicates detection of laps, gaps, overlaps and twists. The current detection method used in industry involves halting fabrication and performing a time consuming, visual inspection of each tape layer. Typical AFP systems use a quartz lamp to heat the base layer to make the surface tacky as it deposits another tape layer. The innovation proposed in this paper is to use the preheated base layer as a through-transmission heat source for inspecting the newly added tape layer in situ using a thermographic camera mounted on to the AFP hardware. Such a system would not only increase manufacturing throughput by reducing inspection times, but it would also aid in process development for new structural designs or material systems by providing data on as-built parts. To this end, a small thermal camera was mounted onto an AFP robotic research platform at NASA, and thermal data was collected during typical and experimental layup operations. The data was post processed to reveal defects such as tow overlap/gap, wrinkling, and peel-up. Defects that would have been impossible to detect visually were also discovered in the data, such as poor/loss of adhesion between plies and the effects of vacuum debulking. This paper will cover the results of our experiments, and the plans for future versions of this inspection system.

Juarez, Peter D.↗

NASA NTRS2014

NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data

There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.

soil moisture data↗

DOE OSTI2022

Best practices for first-principles simulations of epitaxial inorganic interfaces

Abstract At an interface between two materials physical properties and functionalities may be achieved, which would not exist in either material alone. Epitaxial inorganic interfaces are at the heart of semiconductor, spintronic, and quantum devices. First principles simulations based on density functional theory (DFT) can help elucidate the electronic and magnetic properties of interfaces and relate them to the structure and composition at the atomistic scale. Furthermore, DFT simulations can predict the structure and properties of candidate interfaces and guide experimental efforts in promising directions. However, DFT simulations of interfaces can be technically elaborate and computationally expensive. To help researchers embarking on such simulations, this review covers best practices for first principles simulations of epitaxial inorganic interfaces, including DFT methods, interface model construction, interface structure prediction, and analysis and visualization tools.

Physics↗

DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

NASA NTRS1975

Conspicuity of target lights: The influence of flash rate and brightness

The stimulus characteristics of lights that might aid a pilot to see and avoid, by alerting him to a potential threat were studied. The relative conspicuity of foveally equated, point-source, steady and flashing lights of several brightnesses, seen against a star background was examined. From the subject's viewpoint, these target lights could appear anywhere within a large (40 deg horizontal by 35 deg vertical) field of view. The lights appeared at random time intervals while the subject was periodically distracted by a simulated cockpit task. The results indicate that correct target detection increases and reaction time decreases with increased target intensity. Steady lights are missed more frequently and acquired more slowly than flashing lights, but no significant differences are found among the wide range of flash rates employed. The intensity of the light has a greater effect on both detection and reaction time to steady lights than to flashing lights. These results are compared with results of other researchers who used targets which appeared at fixed locations. The longest reaction times were recorded to lights which appeared either at the extremes or at the very center of the visual field.

Connors, M. M.↗