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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41

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NASA NTRS2016

Next Generation P-Band Planetary Synthetic Aperture Radar

The Space Exploration Synthetic Aperture Radar (SESAR) is an advanced P-band beamforming radar instrument concept to enable a new class of observations suitable to meet Decadal Survey science goals for planetary exploration. The radar operates at full polarimetry and fine (meter scale) resolution, and achieves beam agility through programmable waveform generation and digital beamforming. The radar architecture employs a novel low power, lightweight design approach to meet stringent planetary instrument requirements. This instrument concept has the potential to provide unprecedented surface and near- subsurface measurements applicable to multiple DecadalSurvey Science Goals.

Wide band↗

NASA NTRS2017

Next Generation P-Band Planetary Synthetic Aperture Radar

P-band↗

DOE OSTI2024

Extreme-value statistics in nonlinear optics

We show that, although nonlinear optics may give rise to a vast multitude of statistics, all these statistics converge, in their extreme-value limit, to one of a few universal extreme-value statistics. Specifically, in the class of polynomial nonlinearities, such as those found in the Kerr effect, weak-field harmonic generation, and multiphoton ionization, the statistics of the nonlinear-optical output converges, in the extreme-value limit, to the exponentially tailed, Gumbel distribution. Exponentially growing nonlinear signals, on the other hand, such as those induced by parametric instabilities and stimulated scattering, are shown to reach their extreme-value limits in the class of the Fréchet statistics, giving rise to extreme-value distributions (EVDs) with heavy, manifestly nonexponential tails, thus favoring extreme-event outcomes and rogue-wave buildup.

Zheltikov, Aleksei M. (ORCID:0000000291380576)↗

DOE OSTI2015

Big Data: Next-Generation Machines for Big Science

Addressing the scientific grand challenges identified by the US Department of Energy’s (DOE’s) Office of Science’s programs alone demands a total leadership-class computing capability of 150 to 400 Pflops by the end of this decade. The successors to three of the DOE’s most powerful leadership-class machines are set to arrive in 2017 and 2018—the products of the Collaboration Oak Ridge Argonne Livermore (CORAL) initiative, a national laboratory–industry design/build approach to engineering nextgeneration petascale computers for grand challenge science. These mission-critical machines will enable discoveries in key scientific fields such as energy, biotechnology, nanotechnology, materials science, and high-performance computing, and serve as a milestone on the path to deploying exascale computing capabilities.

High-performance computing↗

DOE OSTI2019

High-efficiency, large-aperture fifth-harmonic: Generation of 211-nm pulses in ammonium dihydrogen phosphate crystals for fusion diagnostics

High-energy ultraviolet (UV) sources are required to probe hot dense plasmas from fusion experiments by using Thomson scattering resulting from the lower self-generated background from the plasma in the 180 to 230-nm spectral region. Although recently we demonstrated efficient, joule-class fifth harmonic conversion of 1053-nm pulses using a cesium lithium borate (CLBO) crystal, larger crystals are necessary for increased UV energy. This paper presents an alternative approach for fifth-harmonic generation of a large-aperture neodymium laser using ammonium dihydrogen phosphate (ADP). An Nd:YLF laser was optimized to produce square pulses with a flattop, square beam profile (1053 nm, 1 to 2.8 ns, 12 x 12 mm, ≤1.5 J, ≤5 Hz). Noncritical phase matching in ADP suitable for sum–frequency mixing the fourth harmonic with residual fundamental light was achieved by cooling the crystal (65 x 65 x 10 mm) in a two-chamber cryostat to 200 K. The crystal chamber used helium (1 atm) as the thermally conductive medium between the crystal and the crystal chamber, which in turn was surrounded by a high-vacuum chamber that contained a liquid nitrogen reservoir to cool the crystal chamber. Temperature variation of 0.4 K across the crystal aperture was obtained using two 50-W heaters with active feedback. The total conversion efficiency from the fundamental to the fifth harmonic, including surface losses and absorption, was 26%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Fast generation of sparse random kernel graphs

The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in time at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

The second-generation Shifted Boundary Method and its numerical analysis

Recently, the Shifted Boundary Method (SBM) was proposed within the class of unfitted (or immersed, or embedded) finite element methods. By reformulating the original boundary value problem over a surrogate (approximate) computational domain, the SBM avoids integration over cut cells and the associated problematic issues regarding numerical stability and matrix conditioning. Accuracy is maintained by modifying the original boundary conditions using Taylor expansions. Hence the name of the method, that shifts the location and values of the boundary conditions. In this article, we present enhanced variational SBM formulations for the Poisson and Stokes problems with improved flexibility and robustness. These simplified variational forms allow to relax some of the assumptions required by the mathematical proofs of stability and convergence of earlier implementations. First, we show that these new SBM implementations can be proved asymptotically stable and convergent even without the rather restrictive assumption that the inner product between the normals to the true and surrogate boundaries is positive. Second, we show that it is not necessary to introduce a stabilization term involving the tangential derivatives of the solution at Dirichlet boundaries, therefore avoiding the calibration of an additional stabilization parameter. Finally, we prove enhanced L 2 -estimates without the cumbersome assumption – of earlier proofs – that the surrogate domain is convex. Instead we rely on a conventional assumption that the boundary of the true domain is smooth, which can also be replaced by requiring convexity of the true domain. The aforementioned improvements open the way to a more general and efficient implementation of the Shifted Boundary Method, particularly in complex three-dimensional geometries. We complement these theoretical developments with numerical experiments in two and three dimensions.

42 ENGINEERING↗

DOE OSTI2016

A Ka-band radial relativistic backward wave oscillator with GW-class output power

A novel radial relativistic backward wave oscillator with a reflector is proposed and designed to generate GW-level high power microwaves at Ka-band. The segmented radial slow wave structure and the reflector are matched to enhance interaction efficiency. We choose the volume wave TM{sub 01} mode as the working mode due to the volume wave characteristic. The main structural parameters of the novel device are optimized by particle-in-cell simulation. High power microwaves with power of 2 GW and a frequency of 29.4 GHz are generated with 30% efficiency when the electron beam voltage is 383 kV, the beam current is 17 kA, and the guiding magnetic field is only 0.6 T. Simultaneously, the highest electric field in the novel Ka-band device is just about 960 kV/cm in second slow wave structure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Fabrication and test of a 6-tesla-class high-temperature superconducting dipole magnet at 4.2 K

Superconducting magnets enable energy-frontier accelerators by generating strong magnetic fields to steer and focus the particles. Although high-temperature superconductors such as REBa 2 Cu 3 O x (, RE = rare earth) hold a strong potential for generating a higher magnetic field than Nb-Ti and Nb 3 Sn , the associated magnet and conductor technology for accelerator applications is still in its infancy. The U.S. Magnet Development Program is developing magnet technology in collaboration with industry. Here we report an experiment of making a dipole magnet called C3 using commercial high-temperature superconducting wires. The magnet, following a canted cos θ design, generated a dipole field of 5.99 T at 4.2 K in its clear aperture of 65 mm at 6.795 kA when a resistive voltage of 105 μ V appeared across one of the coils in the magnet. The stored energy was 53 kJ at the peak field. The magnet showed no degradation in the current-carrying capability at 4.2 K after the thermal cycle. We report on the detailed design, fabrication, and performance of the C3 magnet that can be of interest to potential users of this emerging technology. We also discuss issues and research needs to inform future magnet development. The experiment represented another step to addressing if the high-temperature superconducting accelerator magnet technology can increase the discovery capability of future particle accelerators.

Abraimov, Dmytro [National High Magnetic Field Lab↗

DOE OSTI2016

Field and laboratory evaluations of commercial and next–generation alumina-forming austenitic foil for advanced recuperators

Alumina-forming austenitic (AFA) steels represent a new class of corrosion- and creep-resistant austenitic steels designed to enable higher temperature recuperators. Field trials are in progress for commercially rolled foil with widths over 39 cm. The first trial completed 3000 hrs in a microturbine recuperator with an elevated turbine inlet temperature and showed limited degradation. A longer microturbine trial is in progress. A third exposure in a larger turbine has passed 16,000 hrs. Furthermore, to reduce alloy cost and address foil fabrication issues with the initial AFA composition, several new AFA compositions are being evaluated in creep and laboratory oxidation testing at 650–800 °C and the results compared to commercially fabricated AFA foil and conventional recuperator foil performance.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A New Class of Proton Conductors with Dramatically Enhanced Stability and High Conductivity for Reversible Solid Oxide Cells

Reversible solid oxide cells based on proton conductors (P-ReSOCs) have potential to be the most efficient and low-cost option for large-scale energy storage and power generation, holding promise as an enabler for the implementation of intermittent renewable energy technologies and the widespread utilization of hydrogen. Here, the rational design of a new class of hexavalent Mo/W-doped proton-conducting electrolytes with excellent durability while maintaining high conductivity is reported. Specifically, BaMo(W) 0.03 Ce 0.71 Yb 0.26 O 3-δ exhibits dramatically enhanced chemical stability against high concentrations of steam and carbon dioxide than the state-of-the-art electrolyte materials while retaining similar ionic conductivity. In addition, P-ReSOCs based on BaW 0.03 Ce 0.71 Yb 0.26 O 3-δ demonstrate high peak power densities of 1.54, 1.03, 0.72, and 0.48 W cm –2 at 650, 600, 550, and 500 °C, respectively, in the fuel cell mode. During steam electrolysis, a high current density of 2.28 A cm –2 is achieved at a cell voltage of 1.3 V at 600 °C, and the electrolysis cell can operate stably with no noticeable degradation when exposed to high humidity of 30% H 2 O at –0.5 A cm –2 and 600 °C for over 300 h. Altogether, this work demonstrates the promise of donor doping for obtaining proton conductors with both high conductivity and chemical stability for P-ReSOCs.

25 ENERGY STORAGE↗

NASA NTRS1995

Automatic blocking for complex three-dimensional configurations

A new blocking technique for complex three-dimensional configurations is described. This new technique is based upon the concept of an abstraction, or squared-up representation, of the configuration and the associated grid. By allowing the user to describe blocking requirements in natural terms (such as 'wrap a grid around this leading edge' or 'make all grid lines emanating from this wall orthogonal to it'), users can quickly generate complex grids around complex configurations, while still maintaining a high level of control where desired. An added advantage of the abstraction concept is that once a blocking is defined for a class of configurations, it can be automatically applied to other configurations of the same class, making the new technique particularly well suited for the parametric variations which typically occur during design processes. Grids have been generated for a variety of real-world, two- and three-dimensional configurations. In all cases, the time required to generate the grid, given just an electronic form of the configuration, was at most a few days. Hence with this new technique, the generation of a block-structured grid is only slightly more expensive than the generation of an unstructured grid for the same configuration.

Dannenhoffer, John F., III↗

DOE OSTI2022

Data augmentation for disruption prediction via robust surrogate models

The goal of this work is to generate large statistically representative data sets to train machine learning models for disruption prediction provided by data from few existing discharges. Such a comprehensive training database is important to achieve satisfying and reliable prediction results in artificial neural network classifiers. Here, we aim for a robust augmentation of the training database for multivariate time series data using Student t process regression. We apply Student t process regression in a state space formulation via Bayesian filtering to tackle challenges imposed by outliers and noise in the training data set and to reduce the computational complexity. Thus, the method can also be used if the time resolution is high. We use an uncorrelated model for each dimension and impose correlations afterwards via colouring transformations. We demonstrate the efficacy of our approach on plasma diagnostics data of three different disruption classes from the DIII-D tokamak. To evaluate if the distribution of the generated data is similar to the training data, we additionally perform statistical analyses using methods from time series analysis, descriptive statistics and classic machine learning clustering algorithms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Data augmentation for disruption prediction via robust surrogate models

The goal of this work is to generate large statistically representative datasets to train machine learning models for disruption prediction provided by data from few existing discharges. Such a comprehensive training database is important to achieve satisfying and reliable prediction results in artificial neural network classifiers. Here, we aim for a robust augmentation of the training database for multivariate time series data using Student-t process regression. We apply Student-t process regression in a state space formulation via Bayesian filtering to tackle challenges imposed by outliers and noise in the training data set and to reduce the computational complexity. Thus, the method can also be used if the time resolution is high. We use an uncorrelated model for each dimension and impose correlations afterwards via coloring transformations. We demonstrate the efficacy of our approach on plasma diagnostics data of three different disruption classes from the DIII-D tokamak. To evaluate if the distribution of the generated data is similar to the training data, we additionally perform statistical analyses using methods from time series analysis, descriptive statistics, and classic machine learning clustering algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Livewire: Automatic Annotations

Diogenes processes datasets to provide data quality metrics for the Livewire platform and creates standardized data dictionaries from data annotations. Diogenes needs data annotations that clearly outline thenformat and organization of the data. It also relies on the type, class, and unit of each data piece for comprehensive analysis, which it cannot determine independently. The Annotation Tool significantly reduces the time needed to create annotations for Diogenes by generating data annotations with the correct formatting and content. It also employs machine learning and hard-coded models to automatically annotate data class, quality type, and data units.

33 - ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRSDate not supplied

A Model Predictive Control Approach for In-Flight Acoustic Constraint Compliance

Vehicle noise remains one of the major barriers to public acceptance of Urban Air Mobility-class aircraft. This work focuses on motion planning for aircraft in noise-sensitive areas. A nonlinear Model Predictive Path Integral~(MPPI) control law is used to generate a finite-horizon trajectory that satisfies acoustic level constraints at a set of observer locations. The MPPI framework places no restrictions on the class of state-dependent cost functionals that can be employed, making it well-suited for use with sophisticated acoustic models and metrics, in addition to dynamic and mission-relevant constraints. The proposed control law is also suitable for implementation in a real-time application. A simulation example demonstrates the ability of the controller to modify the flight trajectory in order to satisfy acoustic constraints at multiple measurement locations.

Aircraft motion planning↗

DOE OSTI2022

Disrupting autorepression circuitry generates “open-loop lethality” to yield escape-resistant antiviral agents

Across biological scales, gene-regulatory networks employ autorepression (negative feedback) to maintain homeostasis and minimize failure from aberrant expression. In this study, we present a proof of concept that disrupting transcriptional negative feedback dysregulates viral gene expression to therapeutically inhibit replication and confers a high evolutionary barrier to resistance. We find that nucleic-acid decoys mimicking cis-regulatory sites act as “feedback disruptors,” break homeostasis, and increase viral transcription factors to cytotoxic levels (termed “open-loop lethality”). Feedback disruptors against herpesviruses reduced viral replication >2-logs without activating innate immunity, showed sub-nM IC 50 , synergized with standard-of-care antivirals, and inhibited virus replication in mice. In contrast to approved antivirals where resistance rapidly emerged, no feedback-disruptor escape mutants evolved in long-term cultures. For SARS-CoV-2, disruption of a putative feedback circuit also generated open-loop lethality, reducing viral titers by >1-log. These results demonstrate that generating open-loop lethality, via negative-feedback disruption, may yield a class of antimicrobials with a high genetic barrier to resistance.

59 BASIC BIOLOGICAL SCIENCES↗