Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “consensus algorithm”

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.

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

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

NASA's SnowEx Campaign and Measuring Global Snow from Space

Snow blankets 30% of Earth's land surface (60% of northern hemisphere land) in midwinter, dramatically changing our planet's land surface and affecting our weather for months. Seasonal snow is critically important to society for the management of water resources, natural hazards, water security, and in many economic sectors. The only practical way to estimate the quantity of snow on a global scale is through satellites. Despite 4 decades of satellite observations, the highly variable nature of snow still presents significant challenges toward achieving this goal. For example, current space-based techniques underestimate snow water equivalent (SWE) by as much as 50%, and model-based estimates can differ greatly versus estimates based on remotely-sensed observations. Snow community consensus is that a multi-sensor approach is needed to adequately address global snow, combined with modeling and data assimilation to fill the gaps in space and time. What remains, then, is how best to combine and use the various sensors under different types of snow conditions and confounding factors. NASA's multi-year SnowEx airborne campaign is designed to collect measurements needed to enable algorithm development and to guide those mission trade studies. Year 1 (2017) focused on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. This paper will discuss the various remote sensing options for snow, the challenging factors, and describe the recently-completed first year of SnowEx in Colorado, USA. Ground-based remote sensing and in situ data collection involved nearly 100 participants over three weeks. The airborne campaign included nine sensors on five aircraft. We will conclude by discussing options for a future snow satellite mission.

campaign↗
NASA NTRS2024

Smallsat 2024 - Starling Cubesat Swarm Technology Demonstration Flight Results

The Starling swarm of four 6U CubeSats launched in July 2023 to test four key technologies to enable future swarm missions: 1) Mobile Ad-Hoc Networking (MANET) over a crosslink radio network 2) Autonomous onboard decision-making for operations 3) Optical-based absolute and relative navigation 4) Autonomous maneuver planning and execution The Starling team implemented the Better Approach to Mobile Ad-hoc Networking (B.A.T.M.A.N.) protocol to automatically manage the crosslink network of four satellites. The B.A.T.M.A.N. protocol uses a decentralized approach to managing a multi-hop mesh network of devices, in this case, a satellite swarm. The four satellites were able to successfully establish a network at multiple data rates and demonstrate file transfer and command issuance between spacecraft over the network. Starling incorporated Distributed Spacecraft Autonomy's (DSA) software to demonstrate onboard decision-making. The DSA software takes L1/L2 band GPS measurements and uses them to estimate the relative Total Electron Count (TEC) in the ionosphere. The onboard software then determines if there are any features of interest and provides that information to the other satellites over the crosslink network. The swarm of satellites then reaches a consensus on the optimal TEC observation strategy and adjusts its measurement collection tactics autonomously. The Starling Formation-Flying Optical Experiment (StarFOX), produced by Stanford's Space Rendezvous Laboratory, uses the onboard star trackers to collect images of the other swarm spacecraft and produce angles-only navigation estimates. This system is envisioned to be valuable in applications in which Global Navigation Satellite Systems (GNSS) are not available, such as in cis-lunar or deep space. StarFOX successfully applied its algorithms to multiple simultaneous spacecraft targets using the star tracker imagery. Finally, Starling used Emergent Space's Cluster Flight Application (CFA) software suite for the Reconfiguration and Orbit Maintenance Experiments Onboard (ROMEO) demonstration of autonomously planning and executing propulsive maneuvers. Large swarms will need to be able to maintain formation requirements with minimal operator involvement, especially as the size of the swarm scales up. Results from the ROMEO experiment are presented. Starling is funded by the Small Spacecraft Technology (SST) program out of NASA's Space Technology Mission Directorate (STMD).

distributed systems↗
NASA NTRS1997

Onward to Petaflops Computing

With the recent demonstration of a computing rate of one Tflop/s at Sandia National Lab, one might ask what lies ahead for high-end computing. The next major milestone is a sustained rate of one Pflop/s (also written one petaflops, or 10(exp 15) floating-point operations per second). It should be emphasized that we could just as well use the term "peta-ops", since it appears that large scientific systems will be required to perform intensive integer and logical computation in addition to floating-point operations, and completely non- floating-point applications are likely to be important as well. In addition to prodigiously high computational performance, such systems must of necessity feature very large main memories, between ten Tbyte (10(exp 13) byte) and one Pbyte (10 (exp 15) byte) depending on application, as well as commensurate I/O bandwidth and huge mass storage facilities. The current consensus of scientists who have performed initial studies in this field is that "affordable" petaflops systems may be feasible by the year 2010, assuming that certain key technologies continue to progress at current rates. A sustained petaflops computing capability however is a daunting challenge; it appears significantly more challenging from today's state-of-the-art than achieving one Tflop/s has been from the level of one Gflop/s about 12 years ago. Challenges are faced in the arena of device technology, system architecture, system software, algorithms and applications. This talk will give an overview of some of these challenges, and describe some of the recent initiatives to address them.

Bailey, David H.↗
NASA NTRS1998

Challenges of Future High-End Computing

The next major milestone in high performance computing is a sustained rate of one Pflop/s (also written one petaflops, or 10(circumflex)15 floating-point operations per second). In addition to prodigiously high computational performance, such systems must of necessity feature very large main memories, as well as comparably high I/O bandwidth and huge mass storage facilities. The current consensus of scientists who have studied these issues is that "affordable" petaflops systems may be feasible by the year 2010, assuming that certain key technologies continue to progress at current rates. One important question is whether applications can be structured to perform efficiently on such systems, which are expected to incorporate many thousands of processors and deeply hierarchical memory systems. To answer these questions, advanced performance modeling techniques, including simulation of future architectures and applications, may be required. It may also be necessary to formulate "latency tolerant algorithms" and other completely new algorithmic approaches for certain applications. This talk will give an overview of these challenges.

Bailey, David↗
DOE OSTI2026

Fidelity-preserving enhancement of ptychography with foundational text-to-image models

Ptychographic phase retrieval enables high-resolution imaging of complex samples but often suffers from artifacts such as grid pathology and multislice crosstalk, which degrade reconstructed images. We propose a plug-and-play (PnP) framework that integrates physics model-based phase retrieval with text-guided image editing using foundational diffusion models. By employing the alternating direction method of multipliers, our approach ensures consensus between data fidelity and artifact removal subproblems, maintaining physical consistency while enhancing image quality. Artifact removal is achieved using a text-guided diffusion image editing method (LEDITS++) with a pre-trained foundational diffusion model, allowing users to specify artifacts for removal in natural language. Demonstrations on simulated and experimental datasets show significant improvements in artifact suppression and structural fidelity, validated by metrics such as peak signal-to-noise ratio and diffraction pattern consistency. This work highlights the combination of text-guided generative models and model-based phase retrieval algorithms as a transferable and fidelity-preserving method for high-quality diffraction imaging.

image editing↗
DOE OSTI2021

Key predictors of soil organic matter vulnerability to mineralization differ with depth at a continental scale

Abstract Soil organic matter (SOM) is the largest terrestrial pool of organic carbon, and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic climate change. However, our understanding of the controls on SOM mineralization is still incomplete, and as such, our ability to predict carbon-climate feedbacks is limited. To improve our understanding of controls on SOM decomposition, A and upper B horizon soil samples from 26 National Ecological Observatory Network (NEON) sites spanning the conterminous U.S. were incubated for 52 weeks under conditions representing site-specific mean summer temperature and sample-specific field capacity (−33 kPa) water potential. Cumulative carbon dioxide respired was periodically measured and normalized by soil organic C content to calculate cumulative specific respiration (CSR), a metric of SOM vulnerability to mineralization. The Boruta algorithm, a feature selection algorithm, was used to select important predictors of CSR from 159 variables. A diverse suite of predictors was selected (12 for A horizons, 7 for B horizons) with predictors falling into three categories corresponding to SOM chemistry, reactive Fe and Al phases, and site moisture availability. The relationship between SOM chemistry predictors and CSR was complex, while sites that had greater concentrations of reactive Fe and Al phases or were wetter had lower CSR. Only three predictors were selected for both horizon types, suggesting dominant controls on SOM decomposition differ by horizon. Our findings contribute to the emerging consensus that a broad array of controls regulates SOM decomposition at large scales and highlight the need to consider changing controls with depth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Repetitive proteins that undergo large conformational changes evade structural prediction algorithms

Protein structure prediction algorithms, such as AlphaFold, have accelerated protein design and advanced the understanding of the relationship between amino acid sequence and protein structure. However, these algorithms are limited in their ability to predict the structures of conformationally dynamic, intrinsically disordered, and stimuli-responsive proteins. To evaluate sequence-to-structure predictions of such challenging proteins, we explored a class of conformationally dynamic, repeats-in-toxin (RTX) proteins. RTX proteins adopt intrinsically disordered conformations in the absence of calcium and undergo reversible folding into β-roll structures upon binding to calcium. RTX proteins are characterized by tandem repeats of the sequence GGXGXDXUX, in which X can be any amino acid and U is an aliphatic amino acid. We designed RTX sequence variants with global substitutions of nonconserved amino acids, tandem repeats of consensus sequences GGAGXDTLY, and tandem repeats of scrambled sequences GGAGXDTYL. AlphaFold2 and AlphaFold3 predicted that all of these RTX variants adopt β-roll structures, characteristic of wild-type RTX bound to calcium. However, modeling the predicted structures with molecular dynamics simulations and characterizing the protein variants with circular dichroism spectroscopy, small-angle x-ray scattering, and x-ray crystallography revealed that variants adopt diverse, sequence-dependent structures in the absence and presence of calcium. To better design proteins for applications in biotechnology and sustainability, it is critical to build predictive tools that consider intrinsically disordered protein states and validate these tools with multi-mode, multi-scale experimental data.

Chang, Marina P. [Stanford Univ., CA (United State↗
NASA NTRS2008

Onboard Image Registration from Invariant Features

This paper describes a feature-based image registration technique that is potentially well-suited for onboard deployment. The overall goal is to provide a fast, robust method for dynamically combining observations from multiple platforms into sensors webs that respond quickly to short-lived events and provide rich observations of objects that evolve in space and time. The approach, which has enjoyed considerable success in mainstream computer vision applications, uses invariant SIFT descriptors extracted at image interest points together with the RANSAC algorithm to robustly estimate transformation parameters that relate one image to another. Experimental results for two satellite image registration tasks are presented: (1) automatic registration of images from the MODIS instrument on Terra to the MODIS instrument on Aqua and (2) automatic stabilization of a multi-day sequence of GOES-West images collected during the October 2007 Southern California wildfires.

descriptors↗
NASA NTRS2000

Atmospheric Boundary Layer Wind Data During the Period January 1, 1998 Through January 31, 1999 at the Dallas-Fort Worth Airport: Quality Assessment - Volume 1

The quality of the Aircraft Vortex Spacing System (AVOSS) is critically dependent on representative wind profiles in the atmospheric boundary layer. These winds observed from a number of sensor systems around the Dallas-Fort Worth airport were combined into single vertical wind profiles by an algorithm developed and implemented by MIT Lincoln Laboratory. This process, called the AVOSS Winds Analysis System (AWAS), is used by AVOSS for wake corridor predictions. During times when AWAS solutions were available, the quality of the resultant wind profiles and variance was judged from a series of plots combining all sensor observations and AWAS profiles during the period 1200 to 0400 UTC daily. First, input data was evaluated for continuity and consistency from criteria established. Next, the degree of agreement among all wind sensor systems was noted and cases of disagreement identified. Finally, the resultant AWAS solution was compared to the quality-assessed input data. When profiles differed by a specified amount from valid sensor consensus winds, times and altitudes were flagged. Volume one documents the process and quality of input sensor data. Volume two documents the data processing/sorting process and provides the resultant flagged files.

Zak, J. Allen↗
DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗
DOE OSTI2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: growth rate of structure measurement from cosmic voids

ABSTRACT We present a void clustering analysis in configuration-space using the completed Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 samples. These samples consist of Luminous Red Galaxies (LRGs) combined with the high-redshift tail of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) DR12 CMASS galaxies (called as LRG+CMASS sample), Emission Line Galaxies (ELGs), and quasars (QSOs). We build void catalogues from the three eBOSS DR16 samples using a ZOBOV-based algorithm, providing 2814 voids, 1801 voids, and 4347 voids in the LRG+CMASS, ELG, and QSO samples, respectively, spanning the redshift range 0.6 < z < 2.2. We measure the redshift space distortions around voids using the anisotropic void-galaxy cross-correlation function and we extract the distortion parameter β. We test the methodology on realistic simulations before applying it to the data, and we investigate all our systematic errors on these mocks. We find βLRG(z = 0.74) = 0.415 ± 0.087, βELG(z = 0.85) = 0.665 ± 0.125 and βQSO(z = 1.48) = 0.313 ± 0.134, for the LRG+CMASS, ELG, and QSO sample, respectively. The quoted errors include systematic and statistical contributions. In order to convert our measurements in terms of the growth rate fσ8, we use consensus values of linear bias from the eBOSS DR16 companion papers, resulting in the following constraints: fσ8(z = 0.74) = 0.50 ± 0.11, fσ8(z = 0.85) = 0.52 ± 0.10, and fσ8(z = 1.48) = 0.30 ± 0.13. Our measurements are consistent with other measurements from eBOSS DR16 using conventional clustering techniques.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Simulation of rotor blade element turbulence

A piloted, motion-based simulation of Sikorsky's Black Hawk helicopter was used as a platform for the investigation of rotorcraft responses to vertical turbulence. By using an innovative temporal and geometrical distribution algorithm that preserved the statistical characteristics of the turbulence over the rotor disc, stochastic velocity components were applied at each of twenty blade-element stations. This model was implemented on NASA Ames' Vertical Motion Simulator (VMS), and ten test pilots were used to establish that the model created realistic cues. The objectives of this research included the establishment of a simulation-technology basis for future investigation into real-time turbulence modeling. This goal was achieved; our extensive additions to the rotor model added less than a 10 percent computational overhead. Using a VAX 9000 computer the entire simulation required a cycle time of less than 12 msec. Pilot opinion during this simulation was generally quite favorable. For low speed flight the consensus was that SORBET (acronym for title) was better than the conventional body-fixed model, which was used for comparison purposes, and was determined to be too violent (like a washboard). For high speed flight the pilots could not identify differences between these models. These opinions were something of a surprise because only the vertical turbulence component on the rotor system was implemented in SORBET. Because of the finite-element distribution of the inputs, induced outputs were observed in all translational and rotational axes. Extensive post-simulation spectral analyses of the SORBET model suggest that proper rotorcraft turbulence modeling requires that vertical atmospheric disturbances not be superimposed at the vehicle center of gravity but, rather, be input into the rotor system, where the rotor-to-body transfer function severely attenuates high frequency rotorcraft responses.

Mcfarland, R. E.↗
NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗
NASA NTRS2011

Towards a Standard for Provenance and Context for Preservation of Data for Earth System Science

Long-term data sets with data from many missions are needed to study trends and validate model results that are typical in Earth System Science research. Data and derived products originate from multiple missions (spaceborne, airborne and/or in situ) and from multiple organizations. During the missions as well as well past their termination, it is essential to preserve the data and products to support future studies. Key aspects of preservation are: preserving bits and ensuring data are uncorrupted, preserving understandability with appropriate documentation, and preserving reproducibility of science with appropriate documentation and other artifacts. Computer technology provides adequate standards to ensure that, with proper engineering, bits are preserved as hardware evolves. However, to ensure understandability and reproducibility, it is essential to plan ahead to preserve all the relevant data and information. There are currently no standards to identify the content that needs to be preserved, leading to non-uniformity in content and users not being sure of whether preserved content is comprehensive. Each project, program or agency can specify the items to be preserved as a part of its data management requirements. However, broader community consensus that cuts across organizational or national boundaries would be needed to ensure comprehensiveness, uniformity and long-term utility of archived data. The Federation of Earth Science Information Partners (ESIP), a diverse network of scientists, data stewards and technology developers, has a forum for ESIP members to collaborate on data preservation issues. During early 2011, members discussed the importance of developing a Provenance and Context Content Standard (PCCS) and developed an initial list of content items. This list is based on the outcome of a NASA and NOAA meeting held in 1998 under the auspices of the USGCRP, documentation requirements from NOAA and our experience with some of the NASA Earth science missions. The items are categorized into the following 8 high level categories: Preflight/Pre-Operations, Products (Data), Product Documentation, Mission Calibration, Product Software, Algorithm Input, Validation, Software Tools.

Ramaprian, Hampapuram K.↗
DOE OSTI2022

Estimating mass-absorption cross-section of ambient black carbon aerosols: theoretical, empirical, and machine learning models

The mass-absorption cross-section of black carbon (MAC BC ) is an essential parameter to link the atmospheric concentration of black carbon (BC) with its radiative forcing. When a direct calculation of MAC BC based on observations of aerosol light absorption and BC mass concentration is impossible, we rely on modeling and simulations to estimate MAC BC , but currently, there is no consensus model that can be relied on for accurate predictions across all atmospheric environments when BC particles have different coating thicknesses. Here, we applied five MAC BC prediction models (including three light scattering theories, an empirical model based on observations of particle mass concentrations, and a machine learning model developed in our previous work) to aerosols from three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) field campaigns. While many studies have found that increasing the complexity of the models helps to constrain biases of the estimated MAC BC , our effort is to evaluate the models based on the criteria of simplicity and accuracy. We find that our machine learning model (support vector machine for regression, SVM) generally performs well across all DOE ARM field campaign data, while the accuracy of core-shell Mie theory depends on the bias correction algorithm applied to filter-based light absorption data. Generally, the empirical model for internally-mixed particles that we considered tends to over-predict MAC BC , while Mie theory for externally-mixed particles tends to under-predict MAC BC . An examination of the influence of coating material on BC cores suggests that the performance of our current SVM model is degraded when the BC is thickly-coated (e.g., it has undergone aging and mixing with other materials in the atmosphere).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Inventory of Public Key Cryptography in US Electric Vehicle Charging

Electric vehicles (EVs) and charging infrastructure are networked systems, which employ high-level communications in support of charging and grid service decisions. Public key cryptography (PKC) underlies much of the security and privacy protections of the information exchange. We are entering a new epoch where quantum computing threats must be seriously considered. A sufficiently large quantum computer, so named Cryptographically Relevant Quantum Computer (QRQC), will be able to perform the mathematical operations to efficiently attack the underpinnings of traditional PKC, thus jeopardizing the digital foundations for trust, communications security, and data security. Estimates suggest a QRQC can break public key encryption and digital signatures in the manner of tens to hundreds of hours, compared to traditional computing that would demand more than 10 18 years in a brute force-style attack. A consensus belief of quantum theorists, quantum experimenters, and cryptographers suggest that the quantum threat will be likely realized in the next twenty years. To address the threat, post-quantum cryptography, which is cryptosystems that are designed to be secure against both traditional and quantum computing threats, must be adopted. Migration from traditional PKC to quantum-resilient cryptography is a global undertaking and likely represents the largest transition in computing history. The nascent state of EV public key infrastructure, combined with limited adoption of the vehicle secure charging features, presents an opportunity to establish a preference for quantum-resistant cryptography as a step on the migration path. Delays will stunt the efforts as rapidly accelerating EVs sales and huge infrastructure investments will create large growing bases of long-lived vehicles and infrastructure. Migration preparations can commence while NIST continues the process to standardize post-quantum cryptography (PQC), which are quantum-resilient algorithms designed to be secure against traditional and quantum computing threats. The first step in preparing EV charging is to identify the presence of traditional public key cryptography algorithms and applications. With this objective in mind, this report is intended to advise the vehicle manufacturers, charging station manufacturers, charging station operators, charge network providers and other EV charging stakeholders with information on traditional PKC application and the potential risks when PKC becomes insecure. This report, the first in a series of reports discussing the topics existing at the confluence of post-quantum cryptography adoption and EV charging, identifies traditional public key applications employed and identifies potential consequences of leaving EV charging infrastructure vulnerable to quantum computing. The focus remains squarely on the of EV charging and infrastructure with respect to PKC and is believed by the authors to complement the NIST SP 1800-38 Migration to Post-Quantum Cryptography. While the report is centered on infrastructure, there are implications to vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies

The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Wall Modeled Large Eddy Simulations for NASA’s Jet Noise Consensus Database of Single-Flow, Round, Convergent Jets

A campaign of wall-modeled large-eddy simulations (WMLES) using structured curvilinear overlapping grids has been performed with the Launch Ascent and Vehicle Aerodynamics(LAVA) computational fluid dynamics (CFD) software to predict jet noise for single-stream axisymmetric round jets. The simulations address the new Prediction Uncertainty Reduction(PUR) technical challenge within the context of NASA’s Commercial Supersonic Technology(CST) project. The goal of PUR is to quantify and reduce uncertainties from scale-resolving simulations to assess noise characteristics of next generation quiet supersonic commercial jets during takeoff and landing conditions where the noise from the exhaust jet dominates. The focus of this effort is to generate a simulation database for single-stream axisymmetric round nozzles at several conditions both for static (no ambient co-flow), which is the focus of this article, and in-flight (flight stream co-flow) conditions, which are beyond the current scope. Nine different flow conditions ranging in jet exit Mach number from 0.38 to 1.0 with nozzle temperature ratios (NTR) from 0.84 to 2.7 have been conducted. Details of the structured overset grids, numerical discretization and wall-model are provided. Near-field comparisons to PIV data show great agreement for both velocity and normal stresses, however a systematic TKE overshoot at the nozzle exit is seen in the lip line shear-layer. A permeable Ffowcs Williams Hawkings (FWH) surface, enclosing the jet, is used to predict far-field noise from the simulated flow-field. Comparison of CFD predictions to microphone array measurements demonstrate excellent agreement within the resolved frequency range. A systematic under-prediction of far-aft observer angles larger than 150 degrees has been observed across all simulations. We achieved a cost reduction of an order of magnitude for these WMLES compared to an earlier study of this configuration due to algorithmic and software improvements. The accuracy of the results and short turnaround time demonstrate that WMLES within the LAVA framework is a cost-effective approach for jet noise predictions that could soon be incorporated into the design cycle of jet noise reduction technologies.

CST↗