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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Contact-Less Integrity Verification of Microelectronics Using Near-Field EM Analysis

Modern microelectronics life-cycle and supply chain ecosystem bring multiple untrusted entities, which can compromise their integrity. A major integrity issue of microelectronics stems from piracy of intellectual properties (IP) and counterfeiting, which causes significant revenue loss to the semiconductor manufacturers. Further, these components often lead to compromised functionality, reliability, security, and safety of an electronic system. This paper presents secure information transmission and probing methods for verifying the integrity of digital integrated circuit (ICs) based on their electromagnetic (EM) near-field emissions and thereby protecting systems against counterfeit components. The proposed method has been tested on both high-level instructions executed by microprocessors or Systems-on-Chip (serving as examples of software), and also logic circuits within FPGA fabrics and ASICs (serving as examples of hardware). The authentication information required by each digital system is generated using a pseudo-random number generator circuit and securely transmitted via near-field magnetic emissions. The authorized party can probe these emissions using a near-field probe, process the acquired signals to improve the signal-to-noise ratio (SNR), and then recover the secure information through matched filtering. Experimental results from commercial SoCs are used to demonstrate the proposed technique. Methods for reducing EM interference during integrity verification of both FPGAs and ASICs are also described.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗
DOE OSTI2016

TU-FG-201-04: Computer Vision in Autonomous Quality Assurance of Linear Accelerators

Purpose: Routine quality assurance (QA) of linear accelerators represents a critical and costly element of a radiation oncology center. Recently, a system was developed to autonomously perform routine quality assurance on linear accelerators. The purpose of this work is to extend this system and contribute computer vision techniques for obtaining quantitative measurements for a monthly multi-leaf collimator (MLC) QA test specified by TG-142, namely leaf position accuracy, and demonstrate extensibility for additional routines. Methods: Grayscale images of a picket fence delivery on a radioluminescent phosphor coated phantom are captured using a CMOS camera. Collected images are processed to correct for camera distortions, rotation and alignment, reduce noise, and enhance contrast. The location of each MLC leaf is determined through logistic fitting and a priori modeling based on knowledge of the delivered beams. Using the data collected and the criteria from TG-142, a decision is made on whether or not the leaf position accuracy of the MLC passes or fails. Results: The locations of all MLC leaf edges are found for three different picket fence images in a picket fence routine to 0.1mm/1pixel precision. The program to correct for image alignment and determination of leaf positions requires a runtime of 21– 25 seconds for a single picket, and 44 – 46 seconds for a group of three pickets on a standard workstation CPU, 2.2 GHz Intel Core i7. Conclusion: MLC leaf edges were successfully found using techniques in computer vision. With the addition of computer vision techniques to the previously described autonomous QA system, the system is able to quickly perform complete QA routines with minimal human contribution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Stochastic Bistable Systems: Competing Hysteresis and Phase Coexistence

In this paper we describe the solution of a stochastic bistable system from a dynamical perspective. We show how a single framework with variable noise can explain hysteresis at zero temperature and two-state coexistence in the presence of noise. This feature is similar to the phase transition of thermodynamics. Our mathematical model for bistable systems also explains how the width of a hysteresis loop shrinks in the presence of noise, and how variation in initial conditions can take such systems to different final states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

In silico evolution of oscillatory gene dynamics formerly Code sharing for a manuscript to be submitted to the journal iScience

The disclosure is about the numerical simulations and visualization implemented in general-purpose language Python and C++. The simulations were in-silico evolution of hypothetical gene circuits that potentially admit oscillatory dynamics. The aim of the study, which was invited to be submitted to a special issue "Timekeeping, noise and development across kingdoms" in the journal iScience, is to demonstrate that in contrast to common belief, noise in gene expression dynamics could significantly facilitate the evolutionary process for searching oscillatory dynamics, which are essential for developing circadian rhythm in living organisms.

Lin, Yen Ting↗
DOE OSTI2018

Direct binary search for improved coherent beam shaping and optical differentiation wavefront sensing

Spatially dithered distributions of binary amplitude pixels are optimized using a full direct binary search taking into account the experimental configuration for amplitude modulation of coherent waves. This design process is shown to yield a significant reduction of the noise induced by binarization and pixelation over the region of interest. In this study, we demonstrate this approach for beam shaping and optical differentiation wavefront sensing, where the region of interest is in an image plane of the pixel distribution and in the far field of the pixel distribution, respectively. Lastly, the observed reduction in error compared to a standard error diffusion algorithm is significant for both applications because it improves performance without the tighter fabrication tolerance and cost associated with smaller pixels.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

A New Perspective for the Calibration of Computational Predictor Models.

This paper presents a framework for calibrating computational models using data from sev- eral and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncer- tainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of obser- vations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it is a description of the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain (i.e., roll-up and extrapolation).

Crespo, Luis Guillermo↗
DOE OSTI2020

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A New Perspective for the Calibration of Computational Predictor Models

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models’ ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it is a description of the model’s ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain (i.e., roll-up and extrapolation).

42 ENGINEERING↗
DOE OSTI2022

Unmanned Aerial Vehicle Synthetic Aperture RADAR for Surface Change Monitoring

Space-based and airplane-based synthetic aperture RADAR (SAR) can monitor ground height using interferometric SAR (InSAR) collections. However, fielding the airplane-based SAR is expensive and coordinating the frequency and timing of ground experiments with space-based SAR is challenging. This research explored the possibility of using a small, mobile unmanned aerial vehicle- base (UAV) SAR to see if it could provide a quick and inexpensive InSAR option for the Source Physics Experiment (SPE) Phase III project. Firstly, a local feasibility collection using a UAV-based SAR showed that InSAR products and height measurements were possible, but that in-scene fiducials were needed to assist in digital elevation model (DEM) construction. Secondly, an InSAR collection was planned and executed over the SPE Phase III site using the same platform configuration. We found that the image formation by the SAR manufacturer creates discontinuities, and that noise impacted the generation and accuracy of height maps. These processing artifacts need to be overcome to generate an accurate height map.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Constraining warm dark matter mass with cosmic reionization and gravitational waves

We constrain the warm dark matter (WDM) particle mass with observations of cosmic reionization and CMB optical depth. We suggest that the gravitational waves (GWs) from stellar-mass black holes (BHs) could give a further constraint on WDM particle mass for future observations. The star formation rates (SFRs) of Population I/II (Pop I/II) and Population III (Pop III) stars are also derived. If the metallicity of the universe is enriched beyond the critical value of Z{sub crit}=10{sup −3.5} Z{sub ⊙}, the star formation shifts from Pop III to Pop I/II stars. Our results show that the SFRs are quite dependent on the WDM particle mass, especially at high redshifts. Combined with the reionization history and CMB optical depth derived from the recent Planck mission, we find that the current data require the WDM particle mass to be in a narrow range of 1 keV≲m{sub x}≲3 keV. Furthermore, we suggest that the stochastic gravitational wave background (SGWB) produced by stellar BHs could give a further constraint on the WDM particle mass for future observations. For m{sub x}=3 keV, with Salpeter (Chabrier) initial mass function (IMF), the SGWB from Pop I/II BHs has a peak amplitude of Ω{sub GW}≈2.8×10{sup −9} (5.0×10{sup −9}) at f=316Hz, while the GW radiation at f<10 Hz is seriously suppressed. For m{sub x}=1 keV, the SGWB peak amplitude is the same as that for m{sub x}=1 keV, but a little lower at low frequencies. Therefore, it is hard to constrain the WDM particle mass by the SGWB from Pop I/II BHs. To assess the detectability of the GW signal, we also calculate the signal-to-noise ratios (S/N), which are S/N=37.7 (66.5) and 27 (47.7) for m{sub x}=3 keV and m{sub x}=1 keV for the Einstein Telescope with Salpeter (Chabrier) IMF, respectively. The SGWB from Pop III BHs is very dependent on the WDM particle mass, the GW strength could be an order of magnitude different, and the frequency band could be two times different for m{sub x}=1 keV and m{sub x}=3 keV. Moreover, the SGWB from Pop III BHs with m{sub x}=1 keV could be detected by the Laser Interferometer Space Antenna for one year of observation, but it cannot be detected for those with m{sub x}=3 keV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

An Updated 2017 Astrometric Solution for Betelgeuse

We provide an update for the astrometric solution for the Type II supernova progenitor Betelgeuse using the revised Hipparcos Intermediate Astrometric Data (HIAD) of van Leeuwen, combined with existing VLA and new e-MERLIN and ALMA positions. The 2007 Hipparcos refined abscissa measurements required the addition of so-called Cosmic Noise of 2.4 mas to find an acceptable 5-parameter stochastic solution. We find that a measure of radio Cosmic Noise should also be included for the radio positions because surface inhomogeneities exist at a level significant enough to introduce additional intensity centroid uncertainty. Combining the 2007 HIAD with the proper motions based solely on the radio positions leads to a parallax of π=5.27±0.78 mas (190{sub −25}{sup +33} pc), smaller than the Hipparcos 2007 value of 6.56 ± 0.83 mas (152{sub −17}{sup +22} pc). Furthermore, combining the VLA and new e-MERLIN and ALMA radio positions with the 2007 HIAD, and including radio Cosmic Noise of 2.4 mas, leads to a nominal parallax solution of 4.51 ± 0.80 mas (222{sub −34}{sup +48} pc), which, while only 0.7σ different from the 2008 solution of Harper et al., is 2.6σ different from the solution of van Leeuwen. An accurate and precise parallax for Betelgeuse is always going to be difficult to obtain because it is small compared to the stellar angular diameter (θ=44 mas). We outline an observing strategy utilizing future mm and sub-mm high-spatial resolution interferometry that must be used if substantial improvements in the precision and accuracy of the parallax and distance are to be achieved.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Echelle spectra image processing for the International Ultraviolet Explorer

This paper presents the techniques needed to convert the International Ultraviolet Explorer (IUE) high-resolution echelle spectra into useful scientific data. The image is obtained with a digitally controlled vidicon camera system. The processes that must be carried out on the image include: noise removal, correction for geometric and optical distortion, nonuniform photometric corrections, and two-dimensional wavelength determination. Results from the breadboard camera system are presented.

Klinglesmith, D. A.↗
NASA NTRS1976

Testing thinned, backside illuminated CCD area image sensors

Test techniques were developed making use of computer processing of the video data. The results of testing device noise and nonuniformity were obtained. Read-out noise levels of 25 to 50 electrons rms and uncorrected nonuniformity of response of about 1 to 3% were measured. A simple technique for linearly correcting nonuniformity was described and examples given. The technique was shown to be successful in reducing nonuniformity to the level of random noise.

Root, G.↗
NASA NTRS1977

Non-parametric PCM to ADM conversion

An all-digital technique to convert pulse code modulated (PCM) signals into adaptive delta modulation (ADM) format is presented. The converter developed is shown to be independent of the statistical parameters of the encoded signal and can be constructed with only standard digital hardware. The structure of the converter is simple enough to be fabricated on a large scale integrated circuit where the advantages of reliability and cost can be optimized. A concise evaluation of this PCM to ADM translation technique is presented and several converters are simulated on a digital computer. A family of performance curves is given which displays the signal-to-noise ratio for sinusoidal test signals subjected to the conversion process, as a function of input signal power for several ratios of ADM rate to Nyquist rate.

Locicero, J. L.↗