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At least 811 records · Page 45

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

A new approach for distribution of grid points on the surface and in the volume has been developed and implemented in the NASA unstructured grid generation code VGRID. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

Pirzadeh, Shahyar Z.↗

Traceable random numbers from a non-local quantum advantage

The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations—the generation processes cannot be fully traced, audited and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol forms the basis for a public traceable and certifiable quantum randomness beacon that we have launched. Over the first 40 days of operation, we completed the protocol 7,434 out of 7,454 attempts—a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error multiplied by actual success probability bounded by 2−64. Further, the generation of certifiable and traceable randomness represents a public service that operates with an entanglement-derived advantage over comparable classical approaches.

97 MATHEMATICS AND COMPUTING↗

Spread and SpreadRecorder An Architecture for Data Distribution

The Space Acceleration Measurement System (SAMS) project at the NASA Glenn Research Center (GRC) has been measuring the microgravity environment of the space shuttle, the International Space Station, MIR, sounding rockets, drop towers, and aircraft since 1991. The Principle Investigator Microgravity Services (PIMS) project at NASA GRC has been collecting, analyzing, reducing, and disseminating over 3 terabytes of collected SAMS and other microgravity sensor data to scientists so they can understand the disturbances that affect their microgravity science experiments. The years of experience with space flight data generation, telemetry, operations, analysis, and distribution give the SAMS/ PIMS team a unique perspective on space data systems. In 2005, the SAMS/PIMS team was asked to look into generalizing their data system and combining it with the nascent medical instrumentation data systems being proposed for ISS and beyond, specifically the Medical Computer Interface Adapter (MCIA) project. The SpreadRecorder software is a prototype system developed by SAMS/PIMS to explore ways of meeting the needs of both the medical and microgravity measurement communities. It is hoped that the system is general enough to be used for many other purposes.

Wright, Ted↗

Crossing shock wave turbulent boundary layer interactions - Variable angle and shock generator length geometry effects at Mach 3

By comparing the detailed wall static pressure distributions for 9 inch and 11 inch long fins generating a crossing shock configuration at M = 2.93, the high resolution results of the 9 inch fins are shown to be free of exit effects. Analysis of the static pressure profiles have delineated the limited regions where the single fin results are valid. The characteristics of the complex interaction, with varying shock wave strength, have been described. The data provide a critical test for computational fluid dynamics which, in its initial phase, has performed poorly in predicting the measured wall static pressure distributions.

Bogdonoff, S. M.↗

Mechanical Solutions Scan Report

Power lines, poles, and towers are the backbone of the United States (U.S.) electric-power grid. These transmission and distribution networks route electricity from generator to loads. The characteristics of these routes are rapidly changing -- trending towards decentralized renewable generation, electric heating, vehicle charging, and large data-center loads. Coupled with aging infrastructure and the increased frequency of extreme weather events, there is concern about the future reliability and transmission capacity of conductors and adjacent components. This scan report seeks to provide an overview of mechanical solutions to challenges caused by extreme weather events associated with components of transmission and distribution infrastructure, including conductor heat sag, ice accumulation, wind, and wildfire. Many options could increase transmission capacity or reliability, and these are at various stages of technological readiness. Some have only been lab tested, while some have been widely deployed in the U.S. or overseas for decades. The solution categories and providers featured in this report are intended to be comprehensive at the time of publication and to serve as a reference for decision-makers concerned about transmission and distribution reliability. There are two other categories of large, complex solutions, which are not covered in this report: replacing existing conductors with advanced conductors and implementing digital grid enhancing technologies. A separate scan report titled “Advanced Conductor Scan Report,” which discusses advanced carbon-core conductors, was published by the Idaho National Laboratory (INL) in 2023. Information on digital technologies, such as dynamic line ratings, power-flow controllers, and other power electronics and communications-based devices, can be found on the Grid- Enhancing Technologies landing page. Mechanical grid-enhancing technologies, or solutions covered in this report, often do not require full equipment replacement and do not rely on digital components. Mechanical technologies are overlooked because they may be older, simpler, or seemingly “more obvious” than digital or carbon-core technologies. However, it is wise to consider mechanical solutions in a thorough evaluation of grid enhancing technology solutions.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

AUTOTEM - Automated geometry meshing and heat conduction calculation

Temperature distribution for an arbitrary irregular body is calculated by AUTOTEM, which generates required input data automatically by computer. Temperature distribution is calculated for a two-dimensional plane section in /x,y/ coordinates or for an axisymmetric irregular body in /r,z/ coordinates.

Lee, A. Y.↗

Postural tachycardia syndrome: time frequency mapping

Orthostatic tachycardia is common but its specificity remains uncertain. Our preliminary work suggested that using autonomic function testing in conjunction with time-frequency mapping (TFM), it might be possible to characterize a subset of the postural tachycardia syndrome (POTS), that is due to a restricted autonomic neuropathy. We describe 20 patients (17 women and 3 men, aged 14-43 years) with florid POTS and 20 controls (14 women and 6 men, aged 20-41 years). Autonomic failure was quantified by its distribution (cardiovagal, adrenergic and sudomotor) and severity, a symptom profile was generated, and spectral indices, based on modified Wigner distribution during rest and head-up tilt (80 degrees) were evaluated. During tilt-up POTS patients differed from controls by an excessive heart rate (> 130 bpm) (P < 0.001), and higher diastolic pressure (P < 0.01). During rest, cardiovagal oscillations (at respiratory frequencies [RF]) and slow rhythms at nonrespiratory frequencies (NONRF) (from 0.01 to 0.07 Hz) in R-R intervals (RRI) (P < 0.01) were reduced. Both RF and NONRF rhythms in RRI were further blunted with tilt-up (P < 0.001). Slow adrenergic vasomotor rhythms in blood pressure (BP) (approximately 0.07 Hz) surged with tilt-up and returned to normal levels afterwards. The index of sympatho-vagal balance (NONRF-Systolic BP (SBP)/RF-RRI) was dramatically increased in POTS (P < 0.001). Distal postganglionic sudomotor failure was observed, and impairment of the BP responses to the Valsalva maneuver (phase II) suggested peripheral adrenergic dysfunction. Persistent orthostatic dizziness, tiredness, gastrointestinal symptoms and palpitations were common in POTS patients. It is possible to identify a subset of POTS patients who have a length-dependent autonomic neuropathy, affecting the peripheral adrenergic and cardiovagal fibers, with relative preservation of cardiac adrenergic fibers.

NASA Discipline Number 14-10↗

Compositional and Microstructural Evolution of Olivine During Pulsed Laser Irradiation: Insights Based on a FIB/Field-Emission TEM Study

Introduction: The use of pulsed laser irradiation to simulate the short duration, high-energy conditions characteristic of micrometeorite impacts is now an established approach in experimental space weathering studies. The laser generates both melt and vapor deposits that contain nanophase metallic Fe (npFe(sup 0)) grains with size distributions and optical properties similar to those in natural impact-generated melt and vapor deposits. There remains uncertainty, however, about how well lasers simulate the mechanical work and internal (thermal) energy partitioning that occurs in actual impacts. We are currently engaged in making a direct comparison between the products of laser irradiation and experimental/natural hypervelocity impacts. An initial step reported here is to use analytical TEM is to attain a better understanding of how the microstructure and composition of laser deposits evolve over multiple cycles of pulsed laser irradiation. Experimental Methods: We irradiated pressed-powder pellets of San Carlos olivine (Fo(sub 90)) with up to 99 rastered pulses of a GAM ArF excimer laser. The irradiated surface of the sample were characterized by SEM imaging and areas were selected for FIB cross sectioning for TEM study using an FEI Quanta dual-beam electron/focused ion beam instrument. FIB sections were characterized using a JEOL2500SE analytical field-emission scanning transmission electron microscope (FE-STEM) optimized for quantitative element mapping at less than 10 nm spatial resolutions. Results: In the SEM the 99 pulse pressed pellet sample shows a complex, inhomogeneous, distribution of laser-generated material, largely concentrated in narrow gaps and larger depressions between grains. Local concentrations of npFe0 spherules 0.1 to 1 micrometers in size are visible within these deposits in SEM back-scatter images. Fig. 1 shows bright-field STEM images of a FIB cross-section of a one of these deposits that continuously covers the top and sloping side of an olivine grain. The deposit has 3 microstructurally distinct sub-layers composed of silicate glass with varying modal fractions and size distributions of npFe( sup 0) spherules, along with nanocrystalline silicate material. A relatively thin (50-300 nm) topmost surface layer has a high-concentration of npFe0 spherules 5-20 nm in size. Element mapping shows the layer to be enriched in Fe by a factor of 2.5 relative to the olivine substrate, with Mg and Si depleted by 20% and 10% respectively. This is compositionally complementary to the underlying, middle layer of the deposit that is depleted in Fe, enriched in Mg and has a much lower npFe0 concentration. A third layer of nanocrystalline olivine occurs at the substrate interface. Discussion: The FE-STEM results suggest the topmost layer is a vapor deposit, underlain by a thicker microstructurally complex melt-generated layer. The compositional relations suggest the melt layer was partially vaporized, preferentially losing more volatile elements (e.g., Fe). The vaporized material re-condensed to form the thin, npFe(sup 0)-rich surface deposit during or immediately after the scan cycle. Nanocrystalline olivine that grew within the melt layer as it formed and cooled is similar in volume and microstructure to what we have observed in the impact melt lining of a micrometeorite impact crater in olivine. This suggest the time-temperature relations attained in the laser sample may not be too different from a micrometeorite impact. Our TEM observations, however, do not show evidence for the same level of mechanical dam-age (e.g., fracturing) seen around the natural micrometeorite crater.

Christoffersen, R.↗

Modelling of the electron cyclotron emission burst from a laboratory tokamak plasma with loss-cone maser instability

The maser instability associated with the loss-cone distribution has been widely invoked to explain the radio bursts observed in the astrophysical plasma environment, such as aurora and corona. In the laboratory plasma of a tokamak, events reminiscent of these radio bursts have also been frequently observed as an electron cyclotron emission (ECE) burst in the microwave range (~2f ce near the last closed flux surface) during transient magnetohydrodynamic events. These bursts have a short duration of ~10 μs and display a radiation spectrum corresponding to a radiation temperature T e,rad of over 30 keV while the edge thermal electron temperature T e is only in the range of 1 keV. Suprathermal electrons can be generated through magnetic reconnection, and a loss-cone distribution can be generated through open stochastic field lines in the magnetic mirror of the near-edge region of a tokamak plasma. Radiation modelling shows that a sharp distribution gradient ∂f/∂v ⊥ > 0 at the loss-cone boundary can cause a negative absorption of ECE radiation through the maser instability. The negative absorption then amplifies the radiation so that the microwave intensity is significantly stronger than the thermal value. The significant T e,rad from the simulations suggests the potential role of the loss-cone maser instability in generating the ECE burst in a tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗

Nationwide assessment of potential output from wind-powered generators

A method for computing the actual expected power for a wind-powered generator from a given observed speed distribution is described and applied to estimate the potential output for different locations in the continental U.S. A contour map of generator capacity factor values (fraction of the rated output realizable) is obtained for wind-powered generator systems with a cut-in speed of 3.6 m/sec and a rated speed of 8.0 m/sec, and for a unit with hypothetical values for the 1 MW class (cut-in speed, 6.7 m/sec; rated speed, 13.4 m/sec). Results indicate that in the central U.S. and in certain areas of the New England coast at a height of 61 m, over 60% of the rated output power could be obtained on an annual average. In these areas capacity factors of over 20% could be obtained with the 1MW system.

Justus, C. G.↗

WetNet operations

WetNet is an interdisciplinary Earth science data analysis and research project with an emphasis on the study of the global hydrological cycle. The project goals are to facilitate scientific discussion, collaboration, and interaction among a selected group of investigators by providing data access and data analysis software on a personal computer. The WetNet system fulfills some of the functionality of a prototype Product Generation System (PGS), Data Archive and Distribution System (DADS), and Information Management System for the Distributed Active Archive Center. The PGS functionality is satisfied in WetNet by processing the Special Sensor Microwave/Imager (SSM/I) data into a standard format (McIDAS) data sets and generating geophysical parameter Level II browse data sets. The DADS functionality is fulfilled when the data sets are archived on magneto optical cartridges and distributed to the WetNet investigators. The WetNet data sets on the magneto optical cartridges contain the complete WetNet processing, catalogue, and menu software in addition to SSM/I orbit data for the respective two week time period.

Goodman, H. Michael↗

Probing scrambling and operator size distributions using random mixed states and local measurements

The dynamical spreading of quantum information through a many-body system, typically called scrambling, is a complex process that has proven to be essential to describe many properties of out-of-equilibrium quantum systems. Scrambling can, in principle, be fully characterized via the use of out-of-time-ordered correlation functions, which are notoriously hard to access experimentally. In this work, we put forward an alternative toolbox of measurement protocols to experimentally probe scrambling by accessing properties of the operator size probability distribution, which tracks the size of the support of observables in a many-body system over time. Our measurement protocols require the preparation of separable mixed states together with local operations and measurements, and combine the tools of randomized operations, a modern development of near-term quantum algorithms, with the use of mixed states, a standard tool in NMR experiments. We demonstrate how to efficiently probe the probability-generating function of the operator distribution and discuss the challenges associated with obtaining the moments of the operator distribution. We further show that manipulating the initial state of the protocol allows us to directly obtain the individual elements of the distribution for small system sizes. Published by the American Physical Society 2024

Blocher, Philip Daniel (ORCID:0000000163027567)↗

Lower hybrid heating of ionospheric ions due to ion ring distributions in cusp

The stability of H(+) and H(++) ring distributions which have been observed downflowing into the cusp on the DE and S3-3 satellites is examined in the context of the feedback of those instabilities on plasma of ionospheric origin consisting of (H(+) and O(+). Lower hybrid waves are excited by the ring distributions in three distinct phases of wave-particle interaction: linear growth, trapping, and quasi-linear diffusion.The latter phase accounts for most particle heating. Including background O(+) and/or a He(++) ring introduces new modes not present in a pure H(+) plasma which play an important role in heating heavier ions. O(+) is heated significantly more by a He(++) ring than a H(+) ring of comparable energy density. It is suggested that lower hybrid waves generated by downflowing ion ring distributions play a role in energizing ion conics in the cusp.

Roth, I.↗

Economic optimization of the energy transport component of a large distributed solar power plant

A solar thermal power plant with a field of collectors, each locally heating some transport fluid, requires a pipe network system for eventual delivery of energy power generation equipment. For a given collector distribution and pipe network geometry, a technique is herein developed which manipulates basic cost information and physical data in order to design an energy transport system consistent with minimized cost constrained by a calculated technical performance. For a given transport fluid and collector conditions, the method determines the network pipe diameter and pipe thickness distribution and also insulation thickness distribution associated with minimum system cost; these relative distributions are unique. Transport losses, including pump work and heat leak, are calculated operating expenses and impact the total system cost. The minimum cost system is readily selected. The technique is demonstrated on six candidate transport fluids to emphasize which parameters dominate the system cost and to provide basic decision data. Three different power plant output sizes are evaluated in each case to determine severity of diseconomy of scale.

Turner, R. H.↗

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗

A comparison of probabilistic generative frameworks for molecular simulations

Generative artificial intelligence is now a widely used tool in molecular science. Despite the popularity of probabilistic generative models, numerical experiments benchmarking their performance on molecular data are lacking. Here, in this work, we introduce and explain several classes of generative models, broadly sorted into two categories: flow-based models and diffusion models. We select three representative models: neural spline flows, conditional flow matching, and denoising diffusion probabilistic models, and examine their accuracy, computational cost, and generation speed across datasets with tunable dimensionality, complexity, and modal asymmetry. Our findings are varied, with no one framework being the best for all purposes. In a nutshell, (i) neural spline flows do best at capturing mode asymmetry present in low-dimensional data, (ii) conditional flow matching outperforms other models for high-dimensional data with low complexity, and (iii) denoising diffusion probabilistic models appear the best for low-dimensional data with high complexity. Our datasets include a Gaussian mixture model and the dihedral torsion angle distribution of the Aib9 peptide, generated via a molecular dynamics simulation. We hope our taxonomy of probabilistic generative frameworks and numerical results may guide model selection for a wide range of molecular tasks.

Artificial intelligence↗