SEARCH · Search NASA

Results for “Signal Processing Power”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56

All sources NASA NTRS DOE OSTI

NASA NTRS1975

Performance characteristics of the 12 GHz, 200 watt Transmitter Experiment Package for CTS

Measured performance characteristics from ground test of the Transmitter Experiment Package (TEP) for the Communications Technology Satellite are presented. The experiment package consists of a 200 W Output Stage Tube (OST) powered by a Power Processing System (PPS). Descriptions of both the PPS and OST are given. The PPS provides the necessary voltages with a measured dc/dc conversion efficiency of 89 per cent. The OST, a traveling wave tube with multiple collectors, has a saturated rf output power of 224 W and operates at an overall efficiency exceeding 40 per cent over an 85 MHz bandwidth at 12 GHz. OST performance given includes frequency response, saturation characteristics, group delay, AM to PM conversion, intermodulation distortion, and two channel gain suppression. Single and dual channel FM video performance is presented. It was determined that for 12 MHz peak to peak frequency deviation on each channel, dual channel FM television signals can be transmitted through the TEP at 60 W, each channel, with 40 MHz channel spacing (center to center).

Miller, E. F.↗

NASA NTRS1991

A directed search for extraterrestrial laser signals

The focus of NASA's Search for Extraterrestrial Intelligence (SETI) Program is on microwave frequencies, where receivers have the best sensitivities for the detection of narrowband signals. Such receivers, when coupled to existing radio telescopes, form an optimal system for broad area searches over the sky. For a directed search, however, such as toward specific stars, calculations show that infrared wavelengths can be equally as effective as radio wavelengths for establishing an interstellar communication link. This is true because infrared telescopes have higher directivities (gains) that effectively compensate for the lower sensitivities of infrared receivers. The result is that, for a given level of transmitted power, the signal to noise ratio for communications is equally as good at infrared and radio wavelengths. It should also be noted that the overall sensitivities of both receiver systems are quite close to their respective fundamental limits: background thermal noise for the radio frequency system and quantum noise for the infrared receiver. Consequently, the choice of an optimum communication frequency may well be determined more by the achievable power levels of transmitters rather than the ultimate sensitivities of receivers at any specific frequency. In the infrared, CO2 laser transmitters with power levels greater than 1 MW can already be built on Earth. For a slightly more advanced civilization, a similar but enormously more powerful laser may be possible using a planetary atmosphere rich in CO2. Because of these possibilities and our own ignorance of what is really the optimum search frequency, a search for narrowband signals at infrared frequencies should be a part of a balanced SETI Program. Detection of narrowband infrared signals is best done with a heterodyne receiver functionally identical to a microwave spectral line receiver. We have built such a receiver for the detection of CO2 laser radiation at wavelengths near 10 microns. The spectrometer uses a high-speed HgCdTe diode as the photomixer and a small CO2 laser as the local oscillator. Output signals in the intermediate frequency range 0.1-2.6 GHz are processed by a 1000-channel acousto-optic signal processor. The receiver is being used on a 1.5-m telescope on Mt. Wilson to survey a selected sample of 150 nearby stars. The current status of the work is discussed along with future project plans.

Betz, A.↗

NASA NTRS2012

Computational Ghost Imaging for Remote Sensing

This work relates to the generic problem of remote active imaging; that is, a source illuminates a target of interest and a receiver collects the scattered light off the target to obtain an image. Conventional imaging systems consist of an imaging lens and a high-resolution detector array [e.g., a CCD (charge coupled device) array] to register the image. However, conventional imaging systems for remote sensing require high-quality optics and need to support large detector arrays and associated electronics. This results in suboptimal size, weight, and power consumption. Computational ghost imaging (CGI) is a computational alternative to this traditional imaging concept that has a very simple receiver structure. In CGI, the transmitter illuminates the target with a modulated light source. A single-pixel (bucket) detector collects the scattered light. Then, via computation (i.e., postprocessing), the receiver can reconstruct the image using the knowledge of the modulation that was projected onto the target by the transmitter. This way, one can construct a very simple receiver that, in principle, requires no lens to image a target. Ghost imaging is a transverse imaging modality that has been receiving much attention owing to a rich interconnection of novel physical characteristics and novel signal processing algorithms suitable for active computational imaging. The original ghost imaging experiments consisted of two correlated optical beams traversing distinct paths and impinging on two spatially-separated photodetectors: one beam interacts with the target and then illuminates on a single-pixel (bucket) detector that provides no spatial resolution, whereas the other beam traverses an independent path and impinges on a high-resolution camera without any interaction with the target. The term ghost imaging was coined soon after the initial experiments were reported, to emphasize the fact that by cross-correlating two photocurrents, one generates an image of the target. In CGI, the measurement obtained from the reference arm (with the high-resolution detector) is replaced by a computational derivation of the measurement-plane intensity profile of the reference-arm beam. The algorithms applied to computational ghost imaging have diversified beyond simple correlation measurements, and now include modern reconstruction algorithms based on compressive sensing.

Erkmen, Baris I.↗

DOE OSTI2019

Optimizing Performance of a Charge-Sensitive Amplifier for the LEGEND-200 Experiment

The observation of neutrinoless double-beta decay would provide evidence for the proposition that neutrinos are their own antiparticle, a property that is not prescribed in the Standard Model. The proposed Large Enriched Germanium Experiment for Neutrinoless double beta Decay (LEGEND) will search for this decay mode in 76Ge by deploying high-purity germanium (HPGe) detectors enriched in this isotope. The signal from two hundred kilograms of HPGe detectors will be fed to low-radioactivity, charge-sensing amplifiers (CSA) deployed in the first phase of the LEGEND experiment: LEGEND-200. We optimized the performance of the CSA in different test conditions by varying the operating parameters (including voltages supplied to the active components of the CSA) and measured the properties of the amplified waveform, such as rise time, dynamic range, and electronic noise. The optimized parameters lead to waveforms with the following characteristics: 90 ns rise time, a dynamic range from 0-10 MeV, and noise of 620 keV (FWHM) at a total power consumption of 156 mW in liquid nitrogen. The optimization process will continue as the circuit is integrated with other components of the experiment.

Lawley, Gannon↗

NASA NTRS1995

SSME Propellant Path Leak Detection

The primary objective of this phase of the investigation is the experimental validation of techniques for detecting and analyzing propellant path external leaks which have a high probability of occurring on the SSME. The selection of candidate detection methods requires a good analytic model for leak plumes which would develop from external leaks and an understanding of radiation transfer through the leak plume. One advanced propellant path leak detection technique is obtained by using state-of-art technology of infrared (IR) thermal imaging systems combined with computer, digital image processing and expert systems for the engine protection. The feasibility of the IR leak plume detection will be evaluated on subscale simulated laboratory plumes to determine sensitivity, signal to noise, and general suitability for the application. The theoretical analysis was undertaken with the objective of developing and testing simple, easy-to-use models to predict the amount of radiation coming from a radiation source, background plate (BP), which can be absorbed, emitted and scattered by the gas leaks.

Roger Crawford↗

NASA NTRS1975

Stepwise Iterative Fourier Transform: The SIFT

A program, designed specifically to study the respective effects of some common data problems on results obtained through stepwise iterative Fourier transformation of synthetic data with known waveform composition, was outlined. Included in this group were the problems of gaps in the data, different time-series lengths, periodic but nonsinusoidal waveforms, and noisy (low signal-to-noise) data. Results on sinusoidal data were also compared with results obtained on narrow band noise with similar characteristics. The findings showed that the analytic procedure under study can reliably reduce data in the nature of (1) sinusoids in noise, (2) asymmetric but periodic waves in noise, and (3) sinusoids in noise with substantial gaps in the data. The program was also able to analyze narrow-band noise well, but with increased interpretational problems. The procedure was shown to be a powerful technique for analysis of periodicities, in comparison with classical spectrum analysis techniques. However, informed use of the stepwise procedure nevertheless requires some background of knowledge concerning characteristics of the biological processes under study.

Benignus, V. A.↗

NASA NTRS2011

Simplified Architecture for Precise Aiming of a Deep-Space Communication Laser Transceiver

The simplified architecture is a minimal system for a deep-space optical communications transceiver. For a deepspace optical communications link the simplest form of the transceiver requires (1) an efficient modulated optical source, (2) a point-ahead mechanism (PAM) to compensate for two-way light travel, (3) an aperture to reduce the divergence of the transmit laser communication signal and also to collect the uplink communication signal, and (4) a receive detector to sense the uplink communication signal. Additional components are introduced to mitigate for spacecraft microvibrations and to improve the pointing accuracy. The Canonical Transceiver implements this simplified architecture (see figure). A single photon-counting smart focal plane sensor combines acquisition, tracking, and forward link data detection functionality. This improves optical efficiency by eliminating channel splits. A transmit laser blind sensor (e.g. silicon with 1,550-nm beam) provides transmit beam-pointing feedback via the two-photon absorption (TPA) process. This vastly improves the transmit/receive isolation because only the focused transmit beam is detected. A piezoelectric tiptilt actuator implements the required point-ahead angle. This point-ahead mechanism has been demonstrated to have near zero quiescent power and is flight qualified. This architecture also uses an innovative 100-mHz resonant frequency passive isolation platform to filter spacecraft vibrations with voice coil actuators for active tip-tilt correction below the resonant frequency. The canonical deep-space optical communications transceiver makes synergistic use of innovative technologies to reduce size, weight, power, and cost. This optical transceiver can be used to retire risks associated with deep-space optical communications on a planetary pathfinder mission and is complementary to ongoing lunar and access link developments.

Ortiz, Gerard G.↗

NASA NTRS2022

Electromagnetic signatures from supermassive binary black holes approaching merger

We present fully relativistic predictions for the electromagnetic emission produced by accretion disks surrounding spinning and nonspinning supermassive binary black holes on the verge of merging. We use the code Bothros to post-process data from 3D General Relativistic Magnetohydrodynamic (GRMHD) simulations via ray-tracing calculations. These simulations model the dynamics of a circumbinary disk and the mini-disks that form around two equal-mass black holes orbiting each other at an initial separation of 20 gravitational radii, and evolve the system for more than 10 orbits in the inspiral regime. We model the emission as the sum of thermal blackbody radiation emitted by an optically thick accretion disk and a power-law spectrum extending to hard X-rays emitted by a hot optically thin corona. We generate time-dependent spectra, images, and light curves at various frequencies to investigate intrinsic periodic signals in the emission, as well as the effects of the black hole spin. We find that prograde black hole spin makes mini-disks brighter since the smaller ISCO angular momentum demands more dissipation before matter plunges to the horizon. However, compared to mini-disks in larger separation binaries with spinning black holes, our mini-disks are less luminous: unlike those systems, their mass accretion rate is lower than in the circumbinary disk, and they radiate with lower efficiency because their inflow times are shorter. Compared to a single black hole system matched in mass and accretion rate, these binaries have spectra noticeably weaker and softer in the UV. Finally, we discuss the implications of our findings for the potential observability of these systems.

Eduardo M. Gutiérrez↗

DOE OSTI2025

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗

DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗

NASA NTRS2004

Fabrication of a novel gigabit/second free-space optical interconnect - photodetector characterization and testing and system development

The time when computing power is limited by the copper wire inherent in the computer system and not the speed of the microprocessor is rapidly approaching. With constant advances in computer technology, many researchers believe that in only a few years, optical interconnects will begin to replace copper wires in your Central Processing Unit (CPU). On a more macroscopic scale, the telecommunications industry has already made the switch to optical data transmission as, to date, fiber optic technology is the only reasonable method of reliable, long range data transmission. Within the span of a decade, we will see optical technologies move from the macroscopic world of the telecommunications industry to the microscopic world of the computer chip. Already, the communications industry is marketing commercially available optical links to connect two personal computers, thereby eliminating the need for standard and comparatively slow wired and wireless Ethernet transfers and greatly increasing the distance the computers can be separated. As processing demands continue to increase, the realm of optical communications will continue to move closer to the microprocessor and quite possibly onto the microprocessor itself. A day may come when copper connections are used only to supply power, not transfer data. This summer s work marks some of the beginning stages of a 5 to 10 year, long-term research project to create and study a free-space, 1 Gigabit/sec optical interconnect. The research will result in a novel fabricated, chip-to-chip interconnect consisting of a Vertical Cavity Surface Emitting Laser (VCSEL) Diode linked through free space to a Metal- Semiconductor-Metal (MSM) Photodetector with the possible integration of microlenses for signal focusing and Micro-Electromechanical Systems (MEMS) devices for optical signal steering. The advantages, disadvantages, and practicality of incorporating flip-chip mounting technologies will also be addressed. My work began with the design and construction of a test setup for the experiment and then appropriate characterization of the test system. Specifically, I am involved in the characterization of a commercially available 1550nm wavelength, 5mW diode laser and a study of its modulation bandwidth. Commercially produced photodetectors as well as the incorporation of microwave technology, in the form of RF input and output, are used in the characterization procedure. The next stage involves the use of a probe station and network analyzer to characterize and test a series of photodetectors fabricated on a 2 inch, Indium Gallium Arsenide (InGaAs) wafer in the Branch s microlithography lab. Other project responsibilities include, but are not limited to the incorporation of a transimpedance amplifier to the photodetector circuit; a study of VCSEL technology; bit error rate analysis of an optical interconnect system; and analysis of free space divergence of the VCSEL, optical path length of the interconnect; and any other pertinent optical properties of the one gigabit per second interconnect for fabrication and testing.

Savich, Gregory R.↗

DOE OSTI2019

Decentralized Signal Processing and Distributed Control of Collaborative Autonomous Networks (17-ERD-101 LDRD Final Report)

Intelligent autonomous sensor networks, often comprised of large numbers of sensors, must be capable of jointly exploiting data collected at each agent in the network, and using that data to optimize their future actions towards multiple mission objectives. Centralized signal processing and optimization solutions process all data and determine all future actions at a single agent, and the resulting information and commands are disseminated back to the network. The communications bandwidth this requires and the single point of failure the central agent represents often make these solutions untenable for national security applications. In this project, several fundamental algorithms for solving both the decentralized signal processing and network optimization were developed, as well as simulation software to validate the results of these algorithms at scale. Specifically, novel algorithms for Bayesian decentralized estimation and decentralized detection and optimization based on the alternating direction method of multipliers (ADMM) were developed for autonomous sensor networks and published in the literature. The first large scale simulation of autonomous sensor networks (1000 agents) was conducted on this project, validating the performance of the developed algorithms. These algorithms and simulation tools are critical components of any decentralized autonomous network and have current and future national security applications, including distributed sensor networks for detection, estimation, and tracking problems, and large decentralized cyber-physical infrastructure such as the power grid.

42 ENGINEERING↗

NASA NTRS2018

Ka-band High-Rate Downlink System for the NISAR Mission

This paper provides a description and analyses of the high-rate Ka-band telecom system for the upcoming NISAR (NASA-ISRO Synthetic Aperture Radar) mission. NISAR is a collaborative Earth-Science mission between National Aeronautics and Space Administration (NASA) and Indian Space Research Organization (ISRO), which features an L-band SAR instrument and an S-band SAR instrument. The simultaneous dual-frequency radar system at peak rates will produce data at gigabit-per-second speeds, which drives the data-volume requirements. The key driving requirement for the payload communication subsystem is to provide a minimum of 26 Terabits per day of radar science data to the ground. The high-rate transmitter on the flight system is a software-defined radio developed at the Jet Propulsion Laboratory (JPL), based on the Universal Space Transponder platform, providing an offset quadrature phase shift key modulated waveform with Low-Density Parity-Check encoding of the data transfer frames. Two transmitters used in a dual-polarization configuration with each transmitter providing two giga-symbols per second (Gsps) of coded data provides an aggregate rate of four Gsps. In this system, only one watt of signal power is necessary on each polarization to overcome propagation losses and achieve a successful RF link. Several Near Earth Network (NEN) ground station sites (Alaska in the United States, Svalbard in Norway, and Punta Arenas in Chile) are baselined for the space-to-Earth communications link. Each ground station will also feature multiple upgrades to support NISAR’s transmission starting with new Ka-band antennas, wideband downconverters and high-rate receivers. In addition, a baseband data processor called Data Acquisition Processor and Handling Network Environment (DAPHNE), newly developed by the NEN, provides data storage and connectivity to backhaul networks. With NISAR’s large quantities of data (over 3.5 Petabytes over the mission), the processing of science data will be primarily performed on a cloud system to reduce the overall cost to the mission. The system described herein will be the first operational use of Gsps-class downlink rates on an Earth-Science mission.

Dissanayake, Asoka↗

DOE OSTI2023

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗

NASA NTRS1985

The Serendip II design

Serendip II is an automated system designed to perform a real time search for narrow band radio signals in the spectra of sources in a regularly scheduled, non-Seti, astronomical observing program. Because Serendip II is expected to run continuously without requiring dedicated observing time, it is hoped that a large portion of the sky will be surveyed at high sensitivity and low cost. Serendip II will compute the power spectrum using a 65,536 channel fast Fourier transform processor with a real time bandwidth of 128 KHz and 2 Hz per channel resolution. After searching for peaks in a 100 KHz portion of the radio telescope's IF band, Serendip II will move to the next 100 KHz portion using a programmable frequency synthesizer; when the whole IF band has been scanned, the process will start again. Unidentified peaks in the power spectra are candidates for further study and their celestial coordinates will be recorded along with the time and power, IF and RF frequency, and bandwidth of the peak.

Werthimer, D.↗

NASA NTRS2004

Assurance Technology Challenges of Advanced Space Systems

The initiative to explore space and extend a human presence across our solar system to revisit the moon and Mars post enormous technological challenges to the nation's space agency and aerospace industry. Key areas of technology development needs to enable the endeavor include advanced materials, structures and mechanisms; micro/nano sensors and detectors; power generation, storage and management; advanced thermal and cryogenic control; guidance, navigation and control; command and data handling; advanced propulsion; advanced communication; on-board processing; advanced information technology systems; modular and reconfigurable systems; precision formation flying; solar sails; distributed observing systems; space robotics; and etc. Quality assurance concerns such as functional performance, structural integrity, radiation tolerance, health monitoring, diagnosis, maintenance, calibration, and initialization can affect the performance of systems and subsystems. It is thus imperative to employ innovative nondestructive evaluation methodologies to ensure quality and integrity of advanced space systems. Advancements in integrated multi-functional sensor systems, autonomous inspection approaches, distributed embedded sensors, roaming inspectors, and shape adaptive sensors are sought. Concepts in computational models for signal processing and data interpretation to establish quantitative characterization and event determination are also of interest. Prospective evaluation technologies include ultrasonics, laser ultrasonics, optics and fiber optics, shearography, video optics and metrology, thermography, electromagnetics, acoustic emission, x-ray, data management, biomimetics, and nano-scale sensing approaches for structural health monitoring.

Chern, E. James↗

DOE OSTI2021

Multiphonon diffuse scattering in solids from first principles: Application to layered crystals and two-dimensional materials

Time-resolved diffuse scattering experiments have gained increasing attention due to their potential to reveal nonequilibrium dynamics of crystal lattice vibrations with full momentum resolution. Although progress has been made in interpreting experimental data on the basis of one-phonon scattering, understanding the role of individual phonons can be sometimes hindered by multiphonon excitations. In Ref. [M. Zacharias, H. Seiler, F. Caruso, D. Zahn, F. Giustino, P. C. Kelires, and R. Ernstorfer, Phys. Rev. Lett. 127, 207401 (2021)], we have introduced a rigorous approach for the calculation of the all-phonon inelastic scattering intensity of solids from first-principles. In the present work, we describe our implementation in detail and show that multiphonon interactions are captured efficiently by exploiting translational and time-reversal symmetries of the crystal. We demonstrate its predictive power by calculating the scattering patterns of monolayer molybdenum disulfide (MoS 2 ), bulk MoS 2 , and black phosphorus (bP), and we obtain excellent agreement with our measurements of thermal electron diffuse scattering. Remarkably, our results show that multiphonon excitations dominate in bP across multiple Brillouin zones, while in MoS 2 they play a less pronounced role. We expand our analysis for each system and examine the effect of individual atomic and interatomic vibrational motion on the diffuse scattering signals. We further demonstrate the high-throughput capability of our approach by reporting all-phonon scattering maps of two-dimensional MoSe 2 , WSe 2 , WS 2 , graphene, and CdI 2 , rationalizing in each case the effect of multiphonon processes. As a side point, we show that the special displacement method reproduces the thermally distorted configuration that generates precisely the all-phonon diffuse pattern. In conclusion, the present methodology opens the way for systematic calculations of the scattering intensity in crystals and the accurate interpretation of static and time-resolved inelastic scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗