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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 127 records · Page 7

A comprehensive X-ray study of the Small Magellanic Cloud

A comprehensive analysis of the Einstein data base on the SMC is presented. Twenty-four soures are classified as objects in the SMC, and 13 as Galactic stars, AGN, and clusters of galaxies. The detected discrete emitters account for less than half of the excess emission associated with the SMC. The extensive diffuse emission has an X-ray spectrum substantially softer than that of the discrete sources, which is consistent with the presence of X-ray-emitting coronal gas associated with the SMC. A detailed study of the discrete sources is presented. An X-ray source is found to vary in its X-ray luminosity by a factor larger than 10 over a period of about 1 yr and has a relatively hard X-ray spectrum which apparently changes with the X-ray luminosity. It is suggested that this source, associated with a B1-type star, is a new high-mass X-ray binary in the Small Cloud.

Wang, Qingde↗

AI-Driven Crack Detection for Remanufacturing Cylinder Heads Using Deep Learning and Engineering-Informed Data Augmentation

Detecting cracks in cylinder heads traditionally relies on manual inspection, which is time-consuming and susceptible to human error. As an alternative, automated object detection utilizing computer vision and machine learning models has been explored. However, these methods often face challenges due to a lack of sufficiently annotated training data, limited image diversity, and the inherently small size of cracks. Addressing these constraints, this paper introduces a novel automated crack-detection method that enhances data availability through a synthetic data generation technique. Unlike general data augmentation practices, our method involves copying cracks from one location to another, guided by both random and informed engineering decisions about likely crack formations due to cyclic thermomechanical loads. The innovative aspect of our approach lies in the integration of domain-specific engineering knowledge into the synthetic generation process, which substantially improves detection accuracy. We evaluate our method’s effectiveness using two metrics: the F2 score, which emphasizes recall to prioritize detecting all potential cracks, and mean average precision (MAP), a standard measure in object detection. Experimental results demonstrate that, without engineering insights, our method increases the F2 score from 0.40 to 0.65, while maintaining a stable MAP. Incorporating detailed engineering knowledge further enhances the F2 score to 0.70 and improves MAP to 0.57, representing increases of 63% and 43%, respectively. These results confirm that our approach not only mitigates the limitations of traditional data augmentation but also significantly advances the reliability and precision of crack detection in industrial settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The small astronomy satellite-3 - A general description

Program objectives, components and subsystems operations of the Small Astronomy Satellite-3 are briefly described. A control system description is given covering the attitude control, the attitude detection system, the telemetry system, the command system, the power system and thermal control. Launch operations and in-orbit operations are also touched upon.

Riblet, H. B.↗

An Active Subspace Method for Accelerating Convergence in Delaunay-Based Optimization via Dimension Reduction

Delaunay-based derivative-free optimization, ∆DOGS, is an efficient and provably-convergent global optimization method for the problems which has computationally expensive objection function and the analytical expression for the objective function is not available. ∆-DOGS is a novel optimization scheme in the family of response surface methods (RSMs); however, it suffers from the curse of dimensionality since the computational cost increases dramatically as the number of design parameters increases. As a result, the number of design parameters in ∆-DOGS algorithm is relatively low (n.10). To avoid such problems, this paper proposes a combination of derivative-free optimization, seeking the global minimizer of an expensive and nonconvex objective function f(x) and active subspace method, detecting the directions of the most variability using evaluations of the gradient. The contribution of other directions to the objective function is bounded by a sufficiently small constant. This new algorithm iteratively applied Delaunay-based derivative-free optimization to seek the minimizer on the d-dimensional active subspace that has most function variation. Inverse mapping is needed to project data from active subspace to full-model for evaluating function values. This task is overcome by solving an inequality constrained problem that curves the response surface of the objective function. The test results show that this strategy is effective on a handful of optimization problems.

Bewley, Thomas R.↗

Detecting Changes in Terrain Using Unmanned Aerial Vehicles

In recent years, small unmanned aerial vehicles (UAVs) have been used for more than the thrill they bring to model airplane enthusiasts. Their flexibility and low cost have made them a viable option for low-altitude reconnaissance. In a recent effort, we acquired video data from a small UAV during several passes over the same flight path. The objective of the exercise was to determine if objects had been added to the terrain along the flight path between flight passes. Several issues accrue to this simple-sounding problem: (1) lighting variations may cause false detection of objects because of changes in shadow orientation and strength between passes; (2) variations in the flight path due to wind-speed, and heading change may cause misalignment of gross features making the task of detecting changes between the frames very difficult; and (3) changes in the aircraft orientation and altitude lead to a change in size of the features from frame-to-frame making a comparison difficult. In this paper, we discuss our efforts to perform this change detection, and the lessons that we learned from this exercise.

Rahman, Zia-ur↗

Infrared intrusion detection system (IRIDS)

A system and method for intrusion detection includes an imager directed towards an object in an interior space. The imager is in data communication with a computer. The computer is arranged to process digital three-dimensional image data received from the imager and programmed to execute a change detection algorithm in response to the processed three-dimensional data to determine movement of the object. The computer generates an alarm output in response to detecting movement of the object above a predetermined threshold. The method includes providing an imager directed towards an object in an interior space; receiving Time of Flight signals by the imager; processing digital three-dimensional image data received from the imager; and executing a change detection algorithm in response to the processed three-dimensional data to determine movement of the object.

Russell, John L.↗

Comet/Asteroid Protection System (CAPS): Preliminary Space-Based Concept and Study Results

There exists an infrequent, but significant hazard to life and property due to impacting asteroids and comets. There is currently no specific search for long-period comets, smaller near-Earth asteroids, or smaller short-period comets. These objects represent a threat with potentially little or no warning time using conventional ground-based telescopes. These planetary bodies also represent a significant resource for commercial exploitation, long-term sustained space exploration, and scientific research. The Comet/Asteroid Protection System (CAPS) is a future space-based system concept that provides permanent, continuous asteroid and comet monitoring, and rapid, controlled modification of the orbital trajectories of selected bodies. CAPS would expand the current detection effort to include long-period comets, as well as small asteroids and short-period comets capable of regional destruction. A space-based detection system, despite being more costly and complex than Earth-based initiatives, is the most promising way of expanding the range of detectable objects, and surveying the entire celestial sky on a regular basis. CAPS would provide an orbit modification system capable of diverting kilometer class objects, and modifying the orbits of smaller asteroids for impact defense and resource utilization. This Technical Memorandum provides a compilation of key related topics and analyses performed during the CAPS study, which was performed under the Revolutionary Aerospace Systems Concepts (RASC) program, and discusses technologies that could enable the implementation of this future system.

Mazanek, Daniel D.↗

Machine learning-based real-time monitoring system for smart connected worker to improve energy efficiency

Recent advances in machine learning and computer vision brought to light technologies and algorithms that serve as new opportunities for creating intelligent and efficient manufacturing systems. In this study, the real-time monitoring system of manufacturing workflow for the Smart Connected Worker (SCW) is developed for the small and medium-sized manufacturers (SMMs), which integrates state-of-the-art machine learning techniques with the workplace scenarios of advanced manufacturing systems. Specifically, object detection and text recognition models are investigated and adopted to ameliorate the labor-intensive machine state monitoring process, while artificial neural networks are introduced to enable real-time energy disaggregation for further optimization. The developed system achieved efficient supervision and accurate information analysis in real-time for prolonged working conditions, which could effectively reduce the cost related to human labor, as well as provide an affordable solution for SMMs. The competent experiment results also demonstrated the feasibility and effectiveness of integrating machine learning technologies into the realm of advanced manufacturing systems.

42 ENGINEERING↗

Lunar Seismic Detector to Advance the Search for Strange Quark Matter

Detection of small seismic signals on the Moon are needed to study lunar internal structure and to detect possible signals from Strange Quark m&er transit events. The immediate objective is to create a prototype seismic detector using a tunnel diode oscillator with a variable capacitor attached to a proof mass. The device is designed to operate effectively on the Moon, which requires a low power consumption to operate through lunar night, while preserving sensitivity. The goal is capacitance resolution of better than 1 part in 10' and power consumption of less than 1 watt.

Galitzki, Nicholas B.↗

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗

Infrared line and continuum views of G333.6-0.2

A 1-micron CCD picture and maps of the Ne II and Ar III fine-structure lines have been obtained in a region roughly one arcmin in size centered on the core of the compact H II region G333.6 - 0.2. The two emission-line maps show nearly identical intensity distributions, although much different fluxes. The maps are similar to the 1-micron picture smoothed to their angular resolutions. The infrared line of S IV also was detected and appears to have a spatial intensity distribution similar to that of the other fine-structure lines. The 1-micron picture reveals a small number of objects of nearly stellar appearance in the core, suggesting that G333.6 - 0.2 is powered by a compact cluster of sources. Stellar continuum radiation probably is responsible in part for the low equivalent width of the B-gamma line in the core.

Geballe, T. R.↗

Dielectric Scanning Locates Voids in Glass Foam

Capacitive probes succeed where X-ray and ultrasonic equipment do not. Crossbar switching of pairs of conductors enables detection of dielectric inhomogeneities in selected small volume elements of slab of material. Large void in sample detected as low capacitance reading for volume element containing void. Applicable in nondestructive testing of other dielectric objects for internal defects that exhibit dielectric inhomogeneities.

Gammell, P. M.↗

Ground-based lidar measurements of stratospheric ozone. The NASA/GSFC stratospheric ozone lidar trailer experiment STROZ LITE

The major research objective is the measurement of high precision vertical profiles of ozone between 20-40 kilometers. The precision is such that the instrument should be capable of detecting a small trend (on the order of less that 1 percent per year) over a 5-10 year period. Temperature was measured between 30 and 365 km. The Goddard Space Flight Center (GSFC) mobile lidar was installed at Table Mountain and a comparison between it and the permanent Jet Propulsion Laboratory (JPL) lidar was made over the course of about 3 weeks. The lidars agreed very well between 20 and 40 km, and under certain conditions up to 45-47 km. There were several anomalies that both lidars followed very well. Agreement with Rocket Ozonesonde (ROCOZ) and electrochemical concentration cell (ECC) sondes was also very good.

Mcgee, Thomas J.↗

Automated Propulsion Data Screening demonstration system

A fully-instrumented firing of a propulsion system typically generates a very large quantity of data. In the case of the Space Shuttle Main Engine (SSME), data analysis from ground tests and flights is currently a labor-intensive process. Human experts spend a great deal of time examining the large volume of sensor data generated by each engine firing. These experts look for any anomalies in the data which might indicate engine conditions warranting further investigation. The contract effort was to develop a 'first-cut' screening system for application to SSME engine firings that would identify the relatively small volume of data which is unusual or anomalous in some way. With such a system, limited and expensive human resources could focus on this small volume of unusual data for thorough analysis. The overall project objective was to develop a fully operational Automated Propulsion Data Screening (APDS) system with the capability of detecting significant trends and anomalies in transient and steady-state data. However, the effort limited screening of transient data to ground test data for throttle-down cases typical of the 3-g acceleration, and for engine throttling required to reach the maximum dynamic pressure limits imposed on the Space Shuttle. This APDS is based on neural networks designed to detect anomalies in propulsion system data that are not part of the data used for neural network training. The delivered system allows engineers to build their own screening sets for application to completed or planned firings of the SSME. ERC developers also built some generic screening sets that NASA engineers could apply immediately to their data analysis efforts.

Hoyt, W. Andes↗

Unique passive diagnostic for slapper detonators

The objective of this study was to find a material and configuration that could reliably detect the proper functioning of a slapper (non-explosive) detonator. Because of the small size of the slapper geometry (on the order of a 15 mils), most diagnostic techniques are not suitable. This program has the additional requirements that the device would be used on centrifuge so that it could not use any electrical power or output signals. This required that the diagnostic be completely passive. The paper describes the three facets of the development effort: complete characterization of the slapper using VISAR measurements, selection of the diagnostic material and configuration, and testing of the prototype designs. The VISAR testing required that use of a special optical probe to allow the laser light to reach both bridges of the dual-slapper detonator. Results are given in the form of flyer velocity as a function of the initiating charge voltage level. The selected diagnostic design functions in a manner similar to a dent block except that the impact of the Kapton disk from a properly-functioning slapper causes a fracture pattern. A quick visual inspection is all that is needed to determine if the flyer velocity exceeded the threshold value. Sub-threshold velocities produce a substantially different appearance.

Brigham, William P.↗

The Detection of Circumnuclear X-Ray Emission from the Seyfert Galaxy NGC 3516

We present the first high-resolution, X-ray image of the circumnuclear regions of the Seyfert 1 galaxy NGC 3516, using the Chandra X-ray Observatory (CXO). All three of the CXO observations reported were performed with one of the two grating assemblies in place, and here we restrict our analysis to undispersed photons (i.e. those detected in the zeroth-order). A previously-unknown X-ray source is detected approximately 6 arcsec (1.1h(sub 75)(exp -1) kpc) NNE of the nucleus (position angle approximately 29 degrees) which we designate CXOU 110648.1 + 723412. Its spectrum can be characterized as a power law with a photon index (Gamma) approximately 1.8 - 2.6, or as thermal emission with a temperature kT approximately 0.7 - 3 keV. Assuming a location within NGC 3516, isotropic emission implies a luminosity L approximately 2 - 8 x 10(exp 39)h(sub 75)(exp-2) erg s(exp -1) in the 0.4 - 2 keV band. If due to a single point source, the object is super-Eddington for a 1.4 solar mass neutron star. However, multiple sources or a small, extended source cannot be excluded using the current data. Large-scale extended S-ray emission is also detected out to approximately 10 arcsec (approximately 2h(sub 75)(exp -1) kpc) from the nucleus to the NE and SW, and is approximately aligned with the morphologies of the radio emission and extended narrow emission line region (ENLR). The mean luminosity of this emission is 1 - 5 x 10(exp 37)h(sub 75)(exp -2) erg s(exp -1) arcsec(exp -2), in the 0.4 - 2 keV band. Unfortunately the current data cannot usefully constrain its spectrum. These results are consistent with earlier suggestions of circumnuclear X-ray emissi in NGC 3516 based on ROSAT observations, and thus provide the first clear detection of extended X-ray emission in a Seyfert 1.0 galaxy. If the extended emission is due to scattering of the nuclear X-ray continuum, then the pressure in the X-ray emitting gas is at least two orders of magnitude too small to provide the confining medium for the ENLR clouds.

George, I. M.↗

An Overview of Ground-Based Radar and Optical Measurements Utilized By the Nasa Orbital Debris Program Office

For over 30 years, the NASA Orbital Debris Program Office (ODPO) has led the characterization of orbital debris (OD) too small to be tracked by the U.S. Space Surveillance Network (SSN), yet which may pose the greatest threat to human spaceflight and robotic missions. Measurements from specialized sensors, including ground-based radars and telescopes capable of detecting smaller objects, provide the foundation for developing statistical models to describe the current state and future evolution of the OD environment from low Earth orbit (LEO) to geosynchronous Earth orbit (GEO). Since 1990, the ODPO has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data using the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) – formerly Haystack – to characterize OD in LEO with a sensitivity of approximately 5 mm at 1000 km altitude. In addition, since 1993, the Goldstone Orbital Debris Radar, operated by NASA’s Jet Propulsion Laboratory, has provided data on OD as small as approximately 2-3 mm for altitudes below 1000 km, some of the most sensitive ground-based measurements achievable at these altitudes. Recently, collaborations with the 18 th Space Control Squadron of the U.S. Space Force have also provided the ODPO with special datasets from the Space Fence to extend coverage below the historical SSN limit of 10 cm and to characterize individual breakup events in LEO. For GEO altitudes, the Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a joint NASA-Air Force Research Laboratory project that reached full operational capability in 2021, collects data on debris smaller than 1 m and provides coverage of debris in historically under-sampled high-altitude orbital regimes. This paper summarizes the radar and optical sensors utilized by the ODPO, their unique capabilities, and recent datasets and applications for statistical sampling of the dynamic OD environment.

Alyssa Manis↗

An Overview of Ground-Based Radar and Optical Measurements Utilized By the Nasa Orbital Debris Program Office

For over 30 years, the NASA Orbital Debris Program Office (ODPO) has led the characterization of orbital debris (OD) too small to be tracked by the U.S. Space Surveillance Network (SSN), yet which may pose the greatest threat to human spaceflight and robotic missions. Measurements from specialized sensors, including ground-based radars and telescopes capable of detecting smaller objects, provide the foundation for developing statistical models to describe the current state and future evolution of the OD environment from low Earth orbit (LEO) to geosynchronous Earth orbit (GEO). Since 1990, the ODPO has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data using the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) – formerly Haystack – to characterize OD in LEO with a sensitivity of approximately 5 mm at 1000 km altitude. In addition, since 1993, the Goldstone Orbital Debris Radar, operated by NASA’s Jet Propulsion Laboratory, has provided data on OD as small as approximately 2-3 mm for altitudes below 1000 km, some of the most sensitive ground-based measurements achievable at these altitudes. Recently, collaborations with the 18 th Space Control Squadron of the U.S. Space Force have also provided the ODPO with special datasets from the Space Fence to extend coverage below the historical SSN limit of 10 cm and to characterize individual breakup events in LEO. For GEO altitudes, the Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a joint NASA-Air Force Research Laboratory project that reached full operational capability in 2021, collects data on debris smaller than 1 m and provides coverage of debris in historically under-sampled high-altitude orbital regimes. This paper summarizes the radar and optical sensors utilized by the ODPO, their unique capabilities, and recent datasets and applications for statistical sampling of the dynamic OD environment.

Alyssa Manis↗