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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Streamlined and Standardized Benthic Habitat Mapping Approach for Marine and Hydrokinetic Site Environmental Assessments

We have combined two seafloor mapping techniques to efficiently map benthic habitat conditions. Multibeam echosounder (MBES) surveys provide detailed bathymetry and backscatter mosaics. Sediment profile and plan view imaging (SPI/PV) rapidly provides dense ground truth data on seabed physical and biological features. A key innovation of this project has been the development of a computer-assisted image processing system that standardizes the SPI data generation process. A unique combination of machine- and deep-learning techniques for grain-size classification, sediment–water interface delineation, and object detection (e.g., infauna and feeding voids) is described. An automated SPI image analysis system provides a standardized and cost-effective approach for image processing. Combining MBES with SPI/PV camera technology provides a first tier approach to rapidly documenting seabed physical and biological conditions in high resolution at MHK sites. When coupled with computer automated data extraction from the imagery, this approach provides a standardized and cost-effective method to establish and monitor benthic habitat conditions over time.

Benthic Habitat Maping, Sediment-Profile Imaging, ↗
DOE OSTI2024

Revolutionizing Waste Management: AI-Powered Real-Time Characterization for Efficient Handling of Non-Recyclable Municipal Solid Waste

According to EPA, -300 MM tons of municipal solid waste (MSW) was available in the US as of 2018. Of that total material, nearly 50% was landfilled resulting in a significant loss for the potential to convert its energy value into cost effective and sustainable biofuels. Redirecting this material away from the landfill and into conversion ready feedstock for energy generation can directly address DOE's selling price < $2.50/GGE while securing the US national energy independence [1]. However, the paramount challenges in any rational fuel conversion strategy are understanding the chemical makeup, quality and associated calorific value of the MSW. Understanding these parameters is critical in achieving any acceptable fuel conversion and requires rapid characterization followed by accurate separation technologies. Therefore, we are proposing to address the rapid characterization by building a non-invasive, rapid, and highly accurate Artificial Intelligence (AI)-enabled spectrometric/optical approach augmented with multi-sensory information for advanced characterization of domestic heterogeneous MSW. North Carolina State University (NCSU) and the National Renewable Energy Laboratory (NREL), in partnership with strong support from the Town of Cary and IBM, Inc., will closely work together to implement this ground-breaking technology for the effective characterization of MSW for sustainable and affordable production of conversion-ready feedstocks, while solving the environment issue of planetary proportions.

artificial intelligence↗
DOE OSTI2023

Neural Image Compression: Generalization, Robustness, and Spectral Biases

Recent advances in neural image compression (NIC) have resulted in models which are starting to outperform traditional codecs. While this has led to growing excitement about using these methods in real-world applications, the successful adoption of any machine learning system (including NIC) in the wild requires it to generalize (and be robust) to unseen distribution shifts at deployment time. Unfortunately, current research lacks comprehensive datasets and informative tools to evaluate and understand compression performance in real-world settings. To bridge this crucial gap, first, this paper presents a comprehensive benchmark suite to evaluate the out-of-distribution (OOD) performance of image compression methods. Specifically, we design CLIC-C and Kodak-C by introducing 15 common corruptions to popular CLIC and Kodak benchmarks. Next, we propose spectrally inspired introspection tools to gain a deeper understanding of errors introduced by image compression methods as well as their OOD performance. To this end, we carry out a detailed performance comparison of the classical codec with various variants of NIC (e.g., original, variable rate, pruned), revealing intriguing findings that challenge our current understanding of the strengths and limitations of NIC. Finally, we corroborate our empirical findings with theoretical analysis, providing an in-depth view of the OOD performance of NIC. Our benchmarks, spectral introspection tools, and findings provide a crucial bridge to the real-world adoption of NIC. We hope that our work will propel future efforts in designing more robust and generalizable NIC methods.

neural networks, Variational Autoencoder, robustne↗
NASA NTRS1992

Method and apparatus for predicting the direction of movement in machine vision

A computer-simulated cortical network is presented. The network is capable of computing the visibility of shifts in the direction of movement. Additionally, the network can compute the following: (1) the magnitude of the position difference between the test and background patterns; (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern; and (3) the direction of a test pattern moved relative to a textured background. The direction of movement of an object in the field of view of a robotic vision system is detected in accordance with nonlinear Gabor function algorithms. The movement of objects relative to their background is used to infer the 3-dimensional structure and motion of object surfaces.

Lawton, Teri B.↗
NASA NTRS1990

Computation and parallel implementation for early vision

The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.

Gualtieri, J. Anthony↗
NASA NTRS1991

Stereo vision for planetary rovers - Stochastic modeling to near real-time implementation

JPL has achieved the first autonomous cross-country robotic traverses to use stereo vision, with all computing onboard the vehicle. This paper describes the stereo vision system, including the underlying statistical model and the details of the implementation. It is argued that the overall approach provides a unifying paradigm for practical domain-independent stereo ranging.

Matthies, Larry↗
NASA NTRSDate not supplied

Vision 2030 Aircraft Propulsion Grand Challenge Problem: Full-engine CFD Simulations with High Geometric Fidelity and Physics Accuracy

2014 NASA published the outcome of the 2030 CFD (Computational Fluid Dynamics) Vision study: “CFD Vision 2030: A path to Revolutionary Computational Aerosciences” . The study provided a comprehensive review of the state of the art of CFD in 2014 for aerospace applications including, but not limited to, numerical algorithms, physics models, MDAO (Multidisciplinary Design Analysis and Optimization) and HPC (High Performance Computing) hardware. The study also proposed four conceptual ideas of Grand Challenge problems that would build on and benefit from advances outlined in the roadmap. The proposed challenges were meant to foster more detailed descriptions of grand challenge problems for specific disciplines. One of the proposed challenges was in the gas turbine propulsion area, focusing on transient full engine simulations. The current paper addresses detailed technical aspects of that challenge, and proposes a plan to approach it in a gradual manner, which includes high fidelity modeling of components, component coupling, and targeted experimental campaigns relying on common research models.

turbine engine↗
DOE OSTI2023

Vision-based localization for cooperative robot-CNC hybrid manufacturing

Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.

Hybrid manufacturing↗
NASA NTRS1990

EVA/manned systems

Viewgraphs on extravehicular activity/manned systems are presented. Objectives of crewstation design include (1) development of human-computer interface technology and graphical presentations, including multi-dimensional visual and aural displays; (2) provide a technology base for autonomous vision and other perceptual systems, virtual workstation technology, and computational vision systems; and (3) develop databases and models of human strength, motion, and body positions in microgravity environments. Extravehicular technology is addressed.

Jenkins, James P.↗
NASA NTRS1991

Computer graphics testbed to simulate and test vision systems for space applications

Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

Cheatham, John B.↗
NASA NTRS1994

The software analysis project for the Office of Human Resources

There were two major sections of the project for the Office of Human Resources (OHR). The first section was to conduct a planning study to analyze software use with the goal of recommending software purchases and determining whether the need exists for a file server. The second section was analysis and distribution planning for retirement planning computer program entitled VISION provided by NASA Headquarters. The software planning study was developed to help OHR analyze the current administrative desktop computing environment and make decisions regarding software acquisition and implementation. There were three major areas addressed by the study: current environment new software requirements, and strategies regarding the implementation of a server in the Office. To gather data on current environment, employees were surveyed and an inventory of computers were produced. The surveys were compiled and analyzed by the ASEE fellow with interpretation help by OHR staff. New software requirements represented a compilation and analysis of the surveyed requests of OHR personnel. Finally, the information on the use of a server represents research done by the ASEE fellow and analysis of survey data to determine software requirements for a server. This included selection of a methodology to estimate the number of copies of each software program required given current use and estimated growth. The report presents the results of the computing survey, a description of the current computing environment, recommenations for changes in the computing environment, current software needs, management advantages of using a server, and management considerations in the implementation of a server. In addition, detailed specifications were presented for the hardware and software recommendations to offer a complete picture to OHR management. The retirement planning computer program available to NASA employees will aid in long-range retirement planning. The intended audience is the NASA civil service employee with several years until retirement. The employee enters current salary and savings information as well as goals concerning salary at retirement, assumptions on inflation, and the return on investments. The program produces a picture of the employee's retirement income from all sources based on the assumptions entered. A session showing features of the program was conducted for key personnel at the Center. After analysis, it was decided to offer the program through the Learning Center starting in August 1994.

Tureman, Robert L., Jr.↗
NASA NTRS2005

Insect-Inspired Flight Control for Unmanned Aerial Vehicles

Flight-control and navigation systems inspired by the structure and function of the visual system and brain of insects have been proposed for a class of developmental miniature robotic aircraft called "biomorphic flyers" described earlier in "Development of Biomorphic Flyers" (NPO-30554), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 54. These form a subset of biomorphic explorers, which, as reported in several articles in past issues of NASA Tech Briefs ["Biomorphic Explorers" (NPO-20142), Vol. 22, No. 9 (September 1998), page 71; "Bio-Inspired Engineering of Exploration Systems" (NPO-21142), Vol. 27, No. 5 (May 2003), page 54; and "Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration" (NPO-30286), Vol. 28, No. 5 (May 2004), page 36], are proposed small robots, equipped with microsensors and communication systems, that would incorporate crucial functions of mobility, adaptability, and even cooperative behavior. These functions are inherent to biological organisms but are challenging frontiers for technical systems. Biomorphic flyers could be used on Earth or remote planets to explore otherwise difficult or impossible to reach sites. An example of an exploratory task of search/surveillance functions currently being tested is to obtain high-resolution aerial imagery, using a variety of miniaturized electronic cameras. The control functions to be implemented by the systems in development include holding altitude, avoiding hazards, following terrain, navigation by reference to recognizable terrain features, stabilization of flight, and smooth landing. Flying insects perform these and other functions remarkably well, even though insect brains contains fewer than 10(exp -4) as many neurons as does the human brain. Although most insects have immobile, fixed-focus eyes and lack stereoscopy (and hence cannot perceive depth directly), they utilize a number of ingenious strategies for perceiving, and navigating in, three dimensions. Despite their lack of stereoscopy, insects infer distances to potential obstacles and other objects from image motion cues that result from their own motions in the environment. The concept of motion of texture in images as a source of motion cues is denoted generally as the concept of optic or optical flow. Computationally, a strategy based on optical flow is simpler than is stereoscopy for avoiding hazards and following terrain. Hence, this strategy offers the potential to design vision-based control computing subsystems that would be more compact, would weigh less, and would demand less power than would subsystems of equivalent capability based on a conventional stereoscopic approach.

Thakoor, Sarita↗
NASA NTRS2003

Sonoluminescence Bubble Measurements using Vision-Based Algorithms

Vision-based measurement methods were used to measure bubble sizes in this sonoluminescence experiment. Bubble imaging was accomplished by placing the bubble between a bright light source and a microscope-CCD camera system. A collimated light-emitting diode was operated in a pulsed model with an adjustable time delay with respect to the piezo-electric transducer drive signal. The light-emitting diode produced a bubble shadowgraph consisting of a multiple exposure made by numerous light pulses imaged onto a charge-couple device camera. Each image was transferred from the camera to a computer-controlled machine vision system via a frame grabber. The frame grabber was equipped with on-board memory to accomodate sequential image buffering while images were transferred to the host processor and analyzed. This configuration allowed the host computer to perform diameter measurements, centroid position measurements and shape estimation in "real-time" as the next image was being acquired. Bubble size measurement accuracy with an uncertainty of 3 microns was achieved using standard lenses and machine vision algorithms. Bubble centroid position accuracy was also within the 3 micron tolerance of the vision system. This uncertainty estimation accounted for the optical spatial resolution, digitization errors and the edge detection algorithm accuracy. The vision algorithms include camera calibration, thresholding, edge detection, edge position determination, distance between two edges computations and centroid position computations.

Hall, Nancy R.↗
NASA NTRS1990

Algorithms and architectures for robot vision

The scope of the current work is to develop practical sensing implementations for robots operating in complex, partially unstructured environments. A focus in this work is to develop object models and estimation techniques which are specific to requirements of robot locomotion, approach and avoidance, and grasp and manipulation. Such problems have to date received limited attention in either computer or human vision - in essence, asking not only how perception is in general modeled, but also what is the functional purpose of its underlying representations. As in the past, researchers are drawing on ideas from both the psychological and machine vision literature. Of particular interest is the development 3-D shape and motion estimates for complex objects when given only partial and uncertain information and when such information is incrementally accrued over time. Current studies consider the use of surface motion, contour, and texture information, with the longer range goal of developing a fused sensing strategy based on these sources and others.

Schenker, Paul S.↗