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At least 361 records · Page 20

Efficient Processing of Data for Locating Lightning Strikes

Two algorithms have been devised to increase the efficiency of processing of data in lightning detection and ranging (LDAR) systems so as to enable the accurate location of lightning strikes in real time. In LDAR, the location of a lightning strike is calculated by solving equations for the differences among the times of arrival (DTOAs) of the lightning signals at multiple antennas as functions of the locations of the antennas and the speed of light. The most difficult part of the problem is computing the DTOAs from digitized versions of the signals received by the various antennas. One way (a time-domain approach) to determine the DTOAs is to compute cross-correlations among variously differentially delayed replicas of the digitized signals and to select, as the DTOAs, those differential delays that yield the maximum correlations. Another way (a frequency-domain approach) to determine the DTOAs involves the computation of cross-correlations among Fourier transforms of variously differentially phased replicas of the digitized signals, along with utilization of the relationship among phase difference, time delay, and frequency.

Medelius, Pedro J.↗

Digital Assistance for System Requirement Discovery and Analysis using Machine Learning Natural Language Processing Algorithm

NASA’s Air Traffic Management-Exploration (ATM-X) Urban Air Mobility (UAM) Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future (see https://www.nasa.gov/uam-overview/ for more information). The complexity of UAM airspace, and its evolution through a series of transformative epochs, requires a planning tool to effectively organize, integrate, and communicate the research that will guide the evolution of UAM operations in the National Airspace System (NAS). The planning tool, called the UAM airspace research roadmap (or just roadmap), is being developed as a new system engineering methodology leveraging model based system engineering (MBSE) and machine learning natural language processing (ML NLP, or just NLP) capabilities. This presentation gives an overview of the NLP application within this system engineering methodology and will describe how it is being used to meet the ATM-X UAM Airspace Subproject’s overarching research goals.

ATM↗

Topographic hydro-conditioning to resolve surface depression storage and ponding in a fully distributed hydrologic model

Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data, such as optical and light detection and ranging (LiDAR) have favored surfaces without depressions to avoid adverse slopes that are problematic for many hydrologic routing methods. Here, in this study, we present a new topographic conditioning workflow, Depression-Preserved DEM Processing (D2P) algorithm, which is designed to preserve physically meaningful surface depressions for depression-integrated and efficient hydrologic modeling. D2P includes several features: (1) an adaptive screening interval for delineation of depressions, (2) the ability to filter out anthropogenic land surface features (e.g., bridges), (3) the ability to blend river smoothing (e.g., a general downslope profile) and depression resolving functionality. From a case study in the Goodwin Creek Experimental Watershed, D2P successfully resolved 86% of the ponds at a DEM resolution of 10 m. Topographic conditioning was achieved with minimum impact as D2P reduced the number of modified cells from the original DEM by 51% compared to a conventional algorithm. Furthermore, hydrologic simulation using a D2P processed DEM resulted in a more robust characterization on surface water dynamics based on higher surface water storage as well as an attenuated and delayed peak streamflow.

54 ENVIRONMENTAL SCIENCES↗

Signal averaging technique for noninvasive recording of late potentials in patients with coronary artery disease

An advanced non invasive signal averaging technique was used to detect late potentials in two groups of patients: Group A (24 patients) with coronary artery disease (CAD) and without sustained ventricular tachycardia (VT) and Group B (8 patients) with CAD and sustained VT. Recorded analog data were digitized and aligned using a cross correlation function with fast Fourier transform schema, averaged and band pass filtered between 60 and 200 Hz with a non-recursive digital filter. Averaged filtered waveforms were analyzed by computer program for 3 parameters: (1) filtered QRS (fQRS) duration (2) interval between the peak of the R wave peak and the end of fQRS (R-LP) (3) RMS value of last 40 msec of fQRS (RMS). Significant change was found between Groups A and B in fQRS (101 -/+ 13 msec vs 123 -/+ 15 msec; p < .0005) and in R-LP vs 52 -/+ 11 msec vs 71-/+18 msec, p <.002). We conclude that (1) the use of a cross correlation triggering method and non-recursive digital filter enables a reliable recording of late potentials from the body surface; (2) fQRS and R-LP durations are sensitive indicators of CAD patients susceptible to VT.

NASA Discipline Cardiopulmonary↗

A real-time adaptive Hadamard transform video compressor

An adaptive video compressor was designed as part of the CTS Digital Video Curriculum Sharing Experiment. The compressor was constructed using field-to-field differencing on fields processed using a Hadamard transform method. The spatial resolution was improved using a fixed-rate, three-mode adaptive system to compress each field.

Jones, H. W., Jr.↗

Status and characterization of the lithium beam diagnostic on DIII-D

The 30 keV lithium beam diagnostic on DIII-D is suitable to measure both the radial electron density and poloidal magnetic field profiles in the pedestal. The refurbished system features a new setup to measure the Doppler shift allowing accurate alignment of the spectral filters. The injector has been optimized to generate a stable lithium neutral beam with a current of I= 15−20 mA and a diameter of 1.9 ± 0.1 cm measured by beam imaging. The typical temporal resolution is Δt= 1−10 ms and the radial resolution of ΔR= 5 mm is given by the optical setup. A new analysis technique based on fast Fourier transform avoids systematic error contributions from the digital lock-in analysis and accounts intrinsically for background light correction. Latest upgrades and a detailed characterization of the system are presented. Proof-of-principle measurements of the poloidal magnetic field with a statistical error of typically 2% show a fair agreement with the predictions modeled with the Grad-Shafranov equilibrium solver EFIT within 4%.

43 PARTICLE ACCELERATORS↗

An all digital low data rate communication system

The advent of digital hardwares has made it feasible to implement many communication system components digitally. With the exception of frequency down conversion, the proposed low data rate communication system uses digital hardwares completely. Although the system is designed primarily for deep space communications with large frequency uncertainty and low signal-to-noise ratio, it is also suitable for other low data rate applications with time-shared operation among a number of channels. Emphasis is placed on the fast Fourier transform receiver and the automatic frequency control via digital filtering. The speed available from the digital system allows sophisticated signal processing to reduce frequency uncertainty and to increase the signal-to-noise ratio. The practical limitations of the system such as the finite register length are examined. It is concluded that the proposed all-digital system is not only technically feasible but also has potential cost reduction over the existing receiving systems.

Chen, C.↗

An all digital low data rate communication system

The advent of digital hardwares has made it feasible to implement many communication system components digitally. With the exception of frequency down conversion, the proposed low data rate communication system uses digital hardware completely. Although the system is designed primarily for deep space communications with large frequency uncertainty and low signal-to-noise ratio, it is also suitable for other low data rate applications with time-shared operation among a number of channels. Emphasis is placed on the fast Fourier transform receiver and the automatic frequency control via digital filtering. The speed available from the digital system allows sophisticated signal processing to reduce frequency uncertainty and to increase the signal-to-noise ratio.

Chen, C.-H.↗

Digital Assurance for High Consequence Systems: 2024 Mission Campaign White Paper

This Sandia National Laboratories Mission Campaign (MC) seeks to create the technical basis that allows national leaders to efficiently assess and manage the digital assurance of high consequence systems. We will call for transformative research that enables efficient (1) development of provably secure systems and secure integration of untrusted products, (2) intelligent threat mitigation, and (3) digital risk-informed engineering trade-offs. Ultimately, this MC will impact multiple national security missions; it will develop an informed Digital Assurance for High Consequence Systems (DAHCS) community and expand Sandia partnerships to build this national capability.

97 MATHEMATICS AND COMPUTING↗

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

36 MATERIALS SCIENCE↗

Scanning thermal plumes

Over a three-year period 800 thermal line scans of power plant plumes were made by an airborne scanner, with ground truth measured concurrently at the plants. Computations using centered finite differences in the thermal scanning imagery show a lower bound in the horizontal temperature gradient in excess of 1.6 C/m. Gradients persist to 3 m below the surface. Vector plots of the velocity of thermal fronts are constructed by tracing the front motion in successive thermal images. A procedure is outlined for the two-point ground calibration of a thermal scanner from an equation describing the scanner signal and the voltage for two known temperatures. The modulation transfer function is then calculated by input of a thermal step function and application of digital time analysis techniques using Fast Fourier Transforms to the voltage output. Field calibration tests are discussed. Data accuracy is limited by the level of ground truth effort chosen.

Scarpace, F. L.↗

LANDSAT-D investigations in snow hydrology

Thematic mapper radiometric characteristics, snow/cloud reflectance, and atmospheric correction are discussed with application to determining the spectral albedo of snow. The geometric characterics of TM and digital elevation data are examined. The geometric transformations and resampling required to coregister these data are discussed.

Dozier, J.↗

Laboratory demonstration of image reconstruction for coherent optical system of modular imaging collectors (COSMIC)

The first physical demonstration of the principle of image reconstruction using a set of images from a diffraction-blurred elongated aperture is reported. This is an optical validation of previous theoretical and numerical simulations of the COSMIC telescope array (coherent optical system of modular imaging collectors). The present experiment utilizes 17 diffraction blurred exposures of a laboratory light source, as imaged by a lens covered by a narrow-slit aperture; the aperture is rotated 10 degrees between each exposure. The images are recorded in digitized form by a CCD camera, Fourier transformed, numerically filtered, and added; the sum is then filtered and inverse Fourier transformed to form the final image. The image reconstruction process is found to be stable with respect to uncertainties in values of all physical parameters such as effective wavelength, rotation angle, pointing jitter, and aperture shape. Future experiments will explore the effects of low counting rates, autoguiding on the image, various aperture configurations, and separated optics.

Traub, W. A.↗

Advanced Engine Health Management Applications of the SSME Real-Time Vibration Monitoring System

The Real Time Vibration Monitoring System (RTVMS) is a 32-channel high speed vibration data acquisition and processing system developed at Marshall Space Flight Center (MSFC). It Delivers sample rates as high as 51,200 samples/second per channel and performs Fast Fourier Transform (FFT) processing via on-board digital signal processing (DSP) chips in a real-time format. Advanced engine health assessment is achieved by utilizing the vibration spectra to provide accurate sensor validation and enhanced engine vibration redlines. Discrete spectral signatures (such as synchronous) that are indicators of imminent failure can be assessed and utilized to mitigate catastrophic engine failures- a first in rocket engine health assessment. This paper is presented in viewgraph form.

Fiorucci, Tony R.↗

Image transfer protocol in progressively increasing resolution

A method of transferring digital image data over a communication link transforms and orders the data so that, as data is received by a receiving station, a low detail version of the image is immediately generated with later transmissions of data providing progressively greater detail in this image. User instructions are accepted, limiting the ultimate resolution of the image or suspending enhancement of the image except in certain user defined regions. When a low detail image is requested followed by a request for a high detailed version of the same image, the originally transmitted data of the low resolution image is not discarded or retransmitted but used with later data to improve the originally transmitted image. Only a single copy of the transformed image need be retained by the transmitting device in order to satisfy requests for different amounts of image detail.

Percival, Jeffrey W.↗

DeepLynx Ecosystem 2025

Poor data integration and governance continue to plague complex engineering projects, resulting in missed cost, schedule, and performance targets. Departments operate in isolated systems with manual data exchange, creating fragmented information that compounds errors and leads to significant delays and cost overruns. The DeepLynx ecosystem addresses these challenges through an open-source, modular data management platform that transforms fragmented project data into an integrated digital thread. Built on a federated microservice architecture, the ecosystem comprises seven specialized tools centered around DeepLynx Nexus, a unified data catalog with hierarchical organization and graph-based navigation capabilities. The ecosystem includes: DeepLynx Stream for real-time timeseries data ingestion from industrial sources; DeepLynx Ingest for governed data uploads with formal review workflows; DeepLynx Lattice for ontology-based entity and relationship extraction; DeepLynx Run for workflow orchestration and secure AI/ML compute; DeepLynx Visualize for 3D digital twin visualization; and DeepLynx Insight for AI-assisted document analysis with traceable, grounded responses. Deployable in cloud, on-premise, or hybrid environments using containerized Docker applications and Helm charts, the DeepLynx ecosystem provides flexible infrastructure that adapts to organizational requirements. By consolidating project data into a unified data lake with role-based access controls and OAuth2 authentication, DeepLynx enables digital thread and digital twin capabilities that improve decision-making, reduce risk, and support complex engineering workflows throughout the project lifecycle.

42 - ENGINEERING↗

Applications of wavelet-based compression to multidimensional Earth science data

A data compression algorithm involving vector quantization (VQ) and the discrete wavelet transform (DWT) is applied to two different types of multidimensional digital earth-science data. The algorithms (WVQ) is optimized for each particular application through an optimization procedure that assigns VQ parameters to the wavelet transform subbands subject to constraints on compression ratio and encoding complexity. Preliminary results of compressing global ocean model data generated on a Thinking Machines CM-200 supercomputer are presented. The WVQ scheme is used in both a predictive and nonpredictive mode. Parameters generated by the optimization algorithm are reported, as are signal-to-noise (SNR) measurements of actual quantized data. The problem of extrapolating hydrodynamic variables across the continental landmasses in order to compute the DWT on a rectangular grid is discussed. Results are also presented for compressing Landsat TM 7-band data using the WVQ scheme. The formulation of the optimization problem is presented along with SNR measurements of actual quantized data. Postprocessing applications are considered in which the seven spectral bands are clustered into 256 clusters using a k-means algorithm and analyzed using the Los Alamos multispectral data analysis program, SPECTRUM, both before and after being compressed using the WVQ program.

Bradley, Jonathan N.↗

Digital Twin and Cybersecurity Requirements for Beartooth

This report summarizes the requirements for the Cybersecurity and the Digital Twin for Beartooth. The Beartooth digital twin will ultimately allow for both comprehensive offline data analysis and transformational autonomy. This document places limits on the IPL-funded work scope to end at a predictive digital twin stage but allow for future expansion to support full autonomy. It is expected that this work will support both currently funded LDRD and future direct-funded digital twin research.

42 ENGINEERING↗