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DOE OSTI2022

A reusable neural network pipeline for unidirectional fiber segmentation

Abstract Fiber-reinforced ceramic-matrix composites are advanced, temperature resistant materials with applications in aerospace engineering. Their analysis involves the detection and separation of fibers, embedded in a fiber bed, from an imaged sample. Currently, this is mostly done using semi-supervised techniques. Here, we present an open, automated computational pipeline to detect fibers from a tomographically reconstructed X-ray volume. We apply our pipeline to a non-trivial dataset by Larson et al . To separate the fibers in these samples, we tested four different architectures of convolutional neural networks. When comparing our neural network approach to a semi-supervised one, we obtained Dice and Matthews coefficients reaching up to 98%, showing that these automated approaches can match human-supervised methods, in some cases separating fibers that human-curated algorithms could not find. The software written for this project is open source, released under a permissive license, and can be freely adapted and re-used in other domains.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Heliostat Sizing Methodology for Solar Heat for Industrial Processes

This study presents a method to obtain a heliostat size that minimizes the levelized cost of a heliostat-based concentrating solar thermal system for industrial process heat (IPH) applications at operating temperatures from 565 to 1550 degrees Celsius. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWhth. Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the levelized cost of heat (LCOH), producing a characteristic U-shaped trend with a robust near-optimal window of 8 - 12 m2; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats under deployment at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗

NASA NTRS2019

Agile Approach to Assuring the Safety-Critical Embedded Software for NASA's Orion Spacecraft

Human-rated missions like NASA's Exploration Mission - 1 (EM-1) and the Orion Multi-Purpose Crew Vehicle are becoming exceedingly complex in terms of software's contribution to achieving mission objectives. The increasing complexity and inherent safety critical nature of the embedded flight software imposes a unique resource challenge to assurance providers responsible for affirming that the mission is going to fly safely. Another challenge NASA and other Government agencies are facing is that more and more software is being developed using an agile development methodology, which is divergent from the typical waterfall, iterative, and incremental development methodologies assurance providers generally observe in the development of safety-critical embedded software. Orion Independent Verification and Validation (IV&V) has addressed these challenges by providing focused assurance results of critical mission capabilities prioritized by a dynamic assessment of risk level. Prior to this approach, Orion IV&V evaluated areas of risk in much broader, and more static, terms. Due to the agile software development life cycle that Orion follows, IV&V findings were often reported months out of phase with the developer thereby imposing increased rework costs. As a result of evolving the approach to adding assurance on Orion, IV&V is able to incrementally deliver high-priority assurance conclusions and more impactful issues more in phase with the developer activities, thereby increasing the value of the findings to the project. The agile IV&V approach employed by the Orion IV&V team strives to achieve a cadence of delivery that matches the pace of development. This agile approach provides increased flexibility for the assurance provider to become more efficient in reporting assurance conclusions and issues. This paper and presentation will discuss the principles which drive the design of our approach, results to date, and stimulate thinking for groups looking to add assurance to software being developed using an agile methodology.

Justin Smith↗

DOE OSTI2021

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

A common strategy for the dimensionality reduction of nonlinear partial differential equations (PDEs) relies on the use of the proper orthogonal decomposition (POD) to identify a reduced subspace and the Galerkin projection for evolving dynamics in this reduced space. However, advection-dominated PDEs are represented poorly by this methodology since the process of truncation discards important interactions between higher-order modes during time evolution. In this study, we demonstrate that encoding using convolutional autoencoders (CAEs) followed by a reduced-space time evolution by recurrent neural networks overcomes this limitation effectively. We demonstrate that a truncated system of only two latent space dimensions can reproduce a sharp advecting shock profile for the viscous Burgers equation with very low viscosities, and a six-dimensional latent space can recreate the evolution of the inviscid shallow water equations. Additionally, the proposed framework is extended to a parametric reduced-order model by directly embedding parametric information into the latent space to detect trends in system evolution. Furthermore, our results show that these advection-dominated systems are more amenable to low-dimensional encoding and time evolution by a CAE and recurrent neural network combination than the POD-Galerkin technique.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Combining protein sequences and structures with transformers and equivariant graph neural networks to predict protein function

Abstract Motivation Millions of protein sequences have been generated by numerous genome and transcriptome sequencing projects. However, experimentally determining the function of the proteins is still a time consuming, low-throughput, and expensive process, leading to a large protein sequence-function gap. Therefore, it is important to develop computational methods to accurately predict protein function to fill the gap. Even though many methods have been developed to use protein sequences as input to predict function, much fewer methods leverage protein structures in protein function prediction because there was lack of accurate protein structures for most proteins until recently. Results We developed TransFun—a method using a transformer-based protein language model and 3D-equivariant graph neural networks to distill information from both protein sequences and structures to predict protein function. It extracts feature embeddings from protein sequences using a pre-trained protein language model (ESM) via transfer learning and combines them with 3D structures of proteins predicted by AlphaFold2 through equivariant graph neural networks. Benchmarked on the CAFA3 test dataset and a new test dataset, TransFun outperforms several state-of-the-art methods, indicating that the language model and 3D-equivariant graph neural networks are effective methods to leverage protein sequences and structures to improve protein function prediction. Combining TransFun predictions and sequence similarity-based predictions can further increase prediction accuracy. Availability and implementation The source code of TransFun is available at https://github.com/jianlin-cheng/TransFun.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

MULTI-LEADER: MULTI-source LEarning-Accelerated Design of high-Efficiency multi-stage compRessor (Final Technical Report)

The objective of MULTI-LEADER is to cut design costs by 80% while generating more energy-efficient designs of multi-stage compressors by developing and implementing novel machine learning (ML) techniques, which enable faster and fewer design iterations, improved solver performance, and concurrent multi-disciplinary design. Current industrial practices for the design of multi-stage compressors involve simulation-based design optimization with successive levels of model fidelity, iteratively evaluated between distinct disciplines, one stage at a time to tackle the high dimensional design variations. This project addresses these key design challenges: (1) concurrent optimization of multiple stages under many non-linear constraints; (2) multitude of evaluation of high-fidelity and expensive solvers and their gradients during optimization convergence in high-dimensional design; (3) multi-disciplinary design to maximize aerodynamic performance while guaranteeing structural integrity and additive manufacturability; (4) utilization of multiple fidelity of solvers with disparate parameterization and modeling assumptions. MULTI-LEADER achieved more than 5x speed up in detailed design of more energy-efficient compressors via these machine learning (ML) innovations: (i) rapid design surrogates by multi-source learning from diverse fidelities across multiple disciplines, (ii) physics-constrained data-augmented modeling for improved empiricism, (iii) generative manifold embedding for high dimensional concurrent design without gradient information; (iv) budget-constrained fidelity-adaptive sampling towards fewer design iterations.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1997

HARP: A Dynamic Inertial Spectral Partitioner

Partitioning unstructured graphs is central to the parallel solution of computational science and engineering problems. Spectral partitioners, such recursive spectral bisection (RSB), have proven effecfive in generating high-quality partitions of realistically-sized meshes. The major problem which hindered their wide-spread use was their long execution times. This paper presents a new inertial spectral partitioner, called HARP. The main objective of the proposed approach is to quickly partition the meshes at runtime in a manner that works efficiently for real applications in the context of distributed-memory machines. The underlying principle of HARP is to find the eigenvectors of the unpartitioned vertices and then project them onto the eigerivectors of the original mesh. Results for various meshes ranging in size from 1000 to 100,000 vertices indicate that HARP can indeed partition meshes rapidly at runtime. Experimental results show that our largest mesh can be partitioned sequentially in only a few seconds on an SP2 which is several times faster than other spectral partitioners while maintaining the solution quality of the proven RSB method. A parallel WI version of HARP has also been implemented on IBM SP2 and Cray T3E. Parallel HARP, running on 64 processors SP2 and T3E, can partition a mesh containing more than 100,000 vertices into 64 subgrids in about half a second. These results indicate that graph partitioning can now be truly embedded in dynamically-changing real-world applications.

Simon, Horst D.↗

NASA NTRSDate not supplied

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗

NASA NTRS1994

Innovation and application of ANN in Europe demonstrated by Kohonen maps

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

Goser, Karl↗

NASA NTRS2006

Improving the Near-Earth Micrometeoroid and Orbital Debris Environment Definition with LADC

The Large Area Debris Collector (LADC) is a 10 m(sup 2) aerogel and acoustic sensor system designed to characterize and collect submillimeter micrometeoroids and orbital debris on the International Space Station (ISS). The project is led by the U.S. Naval Research Laboratory (NRL) with major collaboration by the NASA Orbital Debris Program Office at Johnson Space Center. The U.S. Department of Defense Space Test Program (STP) is responsible for the integration, deployment, and retrieval of the system. The deployment is scheduled for August 2007 with an orbital collection period of one to two years. The combined area time product of LADC will provide a much needed orbital debris population update in the size regime that is important to the safety community - 100 mm and larger. Another key element for LADC is the source identification of the collected samples. Impact features such as track length and track volume can be used to estimate the impact speed and direction of any selected residual embedded in aerogel. Acoustic sensors can provide impact timing and impact location information. The combined dynamical signatures make it possible to reconstruct the orbits of some of the collected samples and lead to their source identification. Compositional analysis on the residuals can also separate debris from meteoroids and provide additional population breakdown for orbital debris (e.g., Al, paint, steel, Al2O3). To maximize the science return and minimize potential contamination from other ISS modules, a careful selection of the location and orientation of LADC on the ISS is needed. Key issues and engineering constraints encountered during mission preparation, and the expected science return based on the mission configuration, are summarized in this paper.

Liou, J.-C.↗

DOE OSTI2023

Resilient Hydrogels from the Nanoscale to the Macroscale

Biological systems illustrate how a material composed of fragile molecular components can collectively be highly resilient. While the average protein, cell, or even tissue may not last more than a few weeks, many animals and plants live for more than a century. Continual component regeneration and multiple systems to resist mechanical and chemical damage together make this longetivity possible. This project sought to develop biomimetic methods to enable a specific type of material, a hydrogel, to resist damage across multiple scales using distinct, modular damage protection mechanisms. Because hydrogels share many features with biological tissues, they are an ideal substrate for exploring biomimetic strategies for designing resilience and self-repair. We specifically focused in this study on DNA-crosslinked hydrogels, which contain DNA strands that can serve as material to link it together or to control its current state or properties. We investigated how new tools from dynamic DNA nanotechnology could make it possible to actively recover from damage by continually growing and forming a materials shape, or by identifying damage and directing an adaptive response to that damage involving chemical synthesis to reconstruct a structure. We developed embedded molecular sensors able to detect and strain of the gel before damage occurred and react to counteract damage. We also developed methods to continually create shapes and patterns using chemical processes that will allow those patterns to reform when they are damaged. The ability to design resilient materials capable of self-repair has important implications for materials engineering. Instead of designing a material to withstand the worst stresses it may encounter, we could instead design a material to survive under average conditions, but self-repair or reconfigure to resist impending damage. Resilient, self-repairing hydrogels will also have diverse applications such as sensors or actuators.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Reusable Rack Interface Controller Common Software for Various Science Research Racks on the International Space Station

The purpose of the EXPRESS (Expedite the PRocessing of Experiments to Space Station) rack project is to provide a set of predefined interfaces for scientific payloads which allow rapid integration into a payload rack on International Space Station (ISS). VxWorks' was selected as the operating system for the rack and payload resource controller, primarily based on the proliferation of VME (Versa Module Eurocard) products. These products provide needed flexibility for future hardware upgrades to meet everchanging science research rack configuration requirements. On the International Space Station, there are multiple science research rack configurations, including: 1) Human Research Facility (HRF); 2) EXPRESS ARIS (Active Rack Isolation System); 3) WORF (Window Observational Research Facility); and 4) HHR (Habitat Holding Rack). The RIC (Rack Interface Controller) connects payloads to the ISS bus architecture for data transfer between the payload and ground control. The RIC is a general purpose embedded computer which supports multiple communication protocols, including fiber optic communication buses, Ethernet buses, EIA-422, Mil-Std-1553 buses, SMPTE (Society Motion Picture Television Engineers)-170M video, and audio interfaces to payloads and the ISS. As a cost saving and software reliability strategy, the Boeing Payload Software Organization developed reusable common software where appropriate. These reusable modules included a set of low-level driver software interfaces to 1553B. RS232, RS422, Ethernet buses, HRDL (High Rate Data Link), video switch functionality, telemetry processing, and executive software hosted on the FUC computer. These drivers formed the basis for software development of the HRF, EXPRESS, EXPRESS ARIS, WORF, and HHR RIC executable modules. The reusable RIC common software has provided extensive benefits, including: 1) Significant reduction in development flow time; 2) Minimal rework and maintenance; 3) Improved reliability; and 4) Overall reduction in software life cycle cost. Due to the limited number of crew hours available on ISS for science research, operational efficiency is a critical customer concern. The current method of upgrading RIC software is a time consuming process; thus, an improved methodology for uploading RIC software is currently under evaluation.

Lu, George C.↗

DOE OSTI2025

Coupled Climate Simulations With E3SM‐MMF

Simulations of the recent historical period from 1950 to 2014 are conducted with E3SM‐MMF, which uses an embedded 2D cloud resolving model that runs efficiently on GPUs in place of traditional parameterizations for cloud and turbulence. Analysis of the climate and variability reveal several aspects where E3SM‐MMF produces smaller biases compared to E3SMv2, including better agreement with the observed evolution of global mean surface temperature, although the representation of ENSO is too weak and fast. Three idealized abrupt CO 2 experiments were also conducted to assess climate sensitivity and feedbacks. These yield three estimates of effective climate sensitivity (4.38, 5.21, and 6.06 K), with a corresponding spread in the shortwave cloud feedbacks. These estimates are on the higher end of sensitivity estimates from CMIP ensembles, and the spread indicates substantial state‐dependent feedbacks. These results demonstrate how multiscale modeling framework (MMF) models can be used for climate relevant experiments and projections by leveraging modern GPU enabled computational platforms. The unique qualities of E3SM‐MMF shown in previous literature are largely still present, but various instances of reduced biases suggest that MMF models have utility in improving future projections.

E3SM↗

DOE OSTI2022

Candidate cosmic filament in the GJ526 field, mapped with the NIKA2 camera

Distinctive large-scale structures have been identified in the spatial distribution of optical galaxies up to redshift z ~ 1. In the more distant universe, the relationship between the dust-obscured population of star-forming galaxies observed at millimetre wavelengths and the network of cosmic filaments of dark matter apparent in all cosmological hydrodynamical simulations is still under study. Using the NIKA2 dual-band millimetre camera, we mapped a field of ~90 arcmin 2 in the direction of the star GJ526 simultaneously in its 1.15-mm and 2.0-mm continuum wavebands to investigate the nature of the quasi-alignment of five sources found ten years earlier with the MAMBO camera at 1.2 mm. We find that these sources are not clumps of a circumstellar debris disc around this star as initially hypothesized. Rather, they must be dust-obscured star-forming galaxies, or sub-millimetre galaxies (SMGs), in the distant background. The new NIKA2 map at 1.15 mm reveals a total of seven SMGs distributed in projection on the sky along a filament-like structure crossing the whole observed field. Furthermore, we show that the NIKA2 and supplemental Herschel photometric data are compatible with a model of the spectral energy distributions (SEDs) of these sources when a common redshift of 2.5 and typical values of the dust parameters for SMGs are adopted. Hence, we speculate that these SMGs might be located in a filament of the distant ‘cosmic web’. The length of this candidate cosmic filament crossing the whole map is at least 4 cMpc (comoving), and the separations between sources are between 0.25 cMpc and 1.25 cMpc at this redshift, in line with expectations from cosmological simulations. Nonetheless, further observations to determine the precise spectroscopic redshifts of these sources are required to definitively support this hypothesis of SMGs embedded in a cosmic filament of dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2005

Measurement and Prediction of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

Previous work at NASA Langley Research Center (LaRC) involved fabrication and testing of composite beams with embedded, pre-strained shape memory alloy (SMA) ribbons within the beam structures. That study also provided comparison of experimental results with numerical predictions from a research code making use of a new thermoelastic model for shape memory alloy hybrid composite (SMAHC) structures. The previous work showed qualitative validation of the numerical model. However, deficiencies in the experimental-numerical correlation were noted and hypotheses for the discrepancies were given for further investigation. The goal of this work is to refine the experimental measurement and numerical modeling approaches in order to better understand the discrepancies, improve the correlation between prediction and measurement, and provide rigorous quantitative validation of the numerical analysis/design tool. The experimental investigation is refined by a more thorough test procedure and incorporation of higher fidelity measurements such as infrared thermography and projection moire interferometry. The numerical results are produced by a recently commercialized version of the constitutive model as implemented in ABAQUS and are refined by incorporation of additional measured parameters such as geometric imperfection. Thermal buckling, post-buckling, and random responses to thermal and inertial (base acceleration) loads are studied. The results demonstrate the effectiveness of SMAHC structures in controlling static and dynamic responses by adaptive stiffening. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.

Davis, Brian↗

NASA NTRS2004

New Effective Material Couple--Oxide Ceramic and Carbon Nanotube-- Developed for Aerospace Microsystem and Micromachine Technologies

The prime driving force for using microsystem and micromachine technologies in transport vehicles, such as spacecraft, aircraft, and automobiles, is to reduce the weight, power consumption, and volume of components and systems to lower costs and increase affordability and reliability. However, a number of specific issues need to be addressed with respect to using microsystems and micromachines in aerospace applications--such as the lack of understanding of material characteristics; methods for producing and testing the materials in small batches; the limited proven durability and lifetime of current microcomponents, packaging, and interconnections; a cultural change with respect to system designs; and the use of embedded software, which will require new product assurance guidelines. In regards to material characteristics, there are significant adhesion, friction, and wear issues in using microdevices. Because these issues are directly related to surface phenomena, they cannot be scaled down linearly and they become increasingly important as the devices become smaller. When microsystems have contacting surfaces in relative motion, the adhesion and friction affect performance, energy consumption, wear damage, maintenance, lifetime and catastrophic failure, and reliability. Ceramics, for the most part, do not have inherently good friction and wear properties. For example, coefficients of friction in excess of 0.7 have been reported for ceramics and ceramic composite materials. Under Alternate Fuels Foundation Technologies funding, two-phase oxide ceramics developed for superior high-temperature wear resistance in NASA's High Operating Temperature Propulsion Components (HOTPC) project and new two-layered carbon nanotube (CNT) coatings (CNT topcoat/iron bondcoat/quartz substrate) developed in NASA's Revolutionary Aeropropulsion Concepts (RAC) project have been chosen as a materials couple for aerospace applications, including micromachines, in the nanotechnology lubrication task because of their potential for superior friction and wearf properties in air and in an ultrahigh vacuum, spacelike environment. At the NASA Glenn Research Center, two-phase oxide ceramic eutectics, Al2O3/ZrO2(Y2O3), were directionally solidified using the laser-float-zone process, and carbon nanotubes were synthesized within a high-temperature tube furnace at 800 C. Physical vapor deposition was used to coat all quartz substrates with 5-nm-thick iron as catalyst and bondcoat, which formed iron islands resembling droplets and serving as catalyst particles on the quartz. A series of scanning electron micrographs showing multiwalled carbon nanotubes directionally grown as aligned "nanograss" on quartz is presented. Unidirectional sliding friction eperiments were conducted at Glenn with the two-layered CNT coatings in contact with the two-phase Al2O3/ZrO2(Y2O3) eutectics in air and in ultrachigh vacuum. The main criteria for judging the performance of the materials couple for solid lubrication and antistick applications in a space environment were the coefficient of friction and the wear resistance (reciprocal of wear rate), which had to be less than 0.2 and greater than 10(exp 5) N(raised dot)/cubic millimetes, respectively, in ultrahigh vacuum. In air, the coefficient of friction for the CNT coatings in contact with Al2O3/ZrO2 (Y2O3) eutectics was 0.04, one-fourth of that for quartz. In an ultrahigh vacuum, the coefficient of friction for CNT coatings in contact with Al2O3/ZrO2 (Y2O3) was one-third of that for quartz. The two-phase Al2O3/ZrO2 (Y2O3) eutectic coupled with the two-layered CNT coating met the coefficient of friction and wear resistance criteria both in air and in an ultrahigh vacuum, spacelike environment. This material's couple can dramatically improve the stiction (or adhesion), friction, and wear resistance of the contacting surfaces, which are major issues for microdevices and micromachines.

Miyoshi, Kazuhisa↗

NASA NTRS1995

Analysis of the heliospheric current sheet at Earth's orbit and model comparisons

IMP 8 magnetic field data for the first half of the year 1994, i.e., for about 6 solar rotations, are analyzed around regions of sector boundary crossings with the purpose of obtaining both gross- and fine-scale characteristics of the related heliospheric current sheets separating the observed sectors. For purposes of estimating the attitudes of the normals to the sector boundaries. analysis intervals (sometimes 30 min or more in length) allowing the field to fully complete an excursion of about 180 deg were used in the study, which consisted of variance analyses of the field within those intervals. The resulting boundary normals were analyzed and compared to known (generic) models of projected heliospheric current sheets and to a coronal field model for the same time period. One of the most outstanding features of the resulting ensemble of estimated boundary normals for this period is that they strongly prefer low inclinations, indicating that the observations do not support a 1 AU model that predicts a current sheet whose surface is approximately parallel with the sun's equator, such as the 'sombrero' model. They instead support a model that predicts a relatively high inclination current sheet at 1 AU. Also the normals assume a surprisingly large range of longitudes, somewhat favoring those consistent with a Parker model (45 deg and 225 deg) and/or radial alignment (0 deg and 180 deg). These boundary structures, as defined, are shown typically to be as broad as several hundred proton gyroradii, but having embedded within them very thin structures associated with stronger currents. Such thin structures have normals usually differing markedly from the gross boundary. For some crossings there are indications of a wave-like structure in the current sheet as it passed the spacecraft.

Lepping, R. P.↗

NASA NTRS2011

Airport Noise Tech Challenge Overview

The Supersonics Project, operating under NASA Aeronautics Mission Directorate#s Fundamental Aero Program, has been organized around the Technical Challenges that have historically precluded commercial supersonic flight. One of these Challenges is making aircraft that are capable of such high aerodynamic performance quiet enough around airports that they will not be objectionable. It is recognized that a successful civilian supersonic aircraft will be a system where many new technologies will come together, and for this to happen not only will new low noise propulsion concepts be required, but new engineering tools that predict the noise of the aircraft as these technologies are combined and compromised with the rest of the aircraft design. These are the two main objectives of the Airport Noise Tech Challenge. " ! As a Project in the Fundamental Aero Program, we work at a relatively low level of technology readiness. However, we have high level milestones which force us to integrate our efforts to impact systems-level activities. To keep the low-level work tied to delivering engineering tools and low-noise concepts, we have structured our milestones around development of the concepts and organized our activities around developing and applying our engineering tools to these concepts. The final deliverables in these milestones are noise prediction modules validated against the best embodiment of each concept. These will then be used in cross-disciplinary exercises to demonstrate the viability of aircraft designs to meet all the Technical Challenges. Some of the concepts being developed are shown: Fan Flow Diverters, Multi-jet Shielding, High-Aspect Ratio Embedded Nozzles, Plasma Actuated Instability Manipulation, Highly Variable Cycle Mixer- Ejectors, and Inverted Velocity Profiles. These concepts are being developed for reduced jet noise along with the design tools which describe how they perform when used in various aircraft configurations. Several key upcoming events are highlighted, including tests of the Highly Variable Cycle Mixer-Ejectors, and Inverted Velocity Profiles. Other key events are milestones to be delivered within the next calendar year.

Bridges, James↗