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At least 235 records · Page 13

Analysis of Unsteady Tip and Endwall Heat Transfer in a Highly Loaded Transonic Turbine Stage

In a previous study, vane-rotor shock interactions and heat transfer on the rotor blade of a highly loaded transonic turbine stage were simulated. The geometry consists of a high pressure turbine vane and downstream rotor blade. This study focuses on the physics of flow and heat transfer in the rotor tip, casing and hub regions. The simulation was performed using the Unsteady Reynolds-Averaged Navier-Stokes (URANS) code MSU-TURBO. A low Reynolds number k-epsilon model was utilized to model turbulence. The rotor blade in question has a tip gap height of 2.1 percent of the blade height. The Reynolds number of the flow is approximately 3x10(exp 6) per meter. Unsteadiness was observed at the tip surface that results in intermittent "hot spots". It is demonstrated that unsteadiness in the tip gap is governed by inviscid effects due to high speed flow and is not strongly dependent on pressure ratio across the tip gap contrary to published observations that have primarily dealt with subsonic tip flows. The high relative Mach numbers in the tip gap lead to a choking of the leakage flow that translates to a relative attenuation of losses at higher loading. The efficacy of new tip geometry is discussed to minimize heat flux at the tip while maintaining choked conditions. In addition, an explanation is provided that shows the mechanism behind the rise in stagnation temperature on the casing to values above the absolute total temperature at the inlet. It is concluded that even in steady mode, work transfer to the near tip fluid occurs due to relative shearing by the casing. This is believed to be the first such explanation of the work transfer phenomenon in the open literature. The difference in pattern between steady and time-averaged heat flux at the hub is also explained.

Shyam, Vikram↗

Particle track classification using quantum associative memory

Pattern recognition algorithms are commonly employed to simplify the challenging and necessary step of track reconstruction in sub-atomic physics experiments. Aiding in the discrimination of relevant interactions, pattern recognition seeks to accelerate track reconstruction by isolating signals of interest. In high collision rate experiments, such algorithms can be particularly crucial for determining whether to retain or discard information from a given interaction even before the data is transferred to tape. As data rates, detector resolution, noise, and inefficiencies increase, pattern recognition becomes more computationally challenging, motivating the development of higher efficiency algorithms and techniques. Quantum associative memory is an approach that seeks to exploits quantum mechanical phenomena to gain advantage in learning capacity, or the number of patterns that can be stored and accurately recalled. Here, we study quantum associative memory based on quantum annealing and apply it to the particle track classification. We focus on discrimination models based on Ising formulations of quantum associative memory model (QAMM) recall and quantum content-addressable memory (QCAM) recall. We characterize classification performance of these approaches as a function detector resolution, pattern library size, and detector inefficiencies, using the D-Wave 2000Q processor as a testbed. Discrimination criteria is set using both solution-state energy and classification labels embedded in solution states. We find that energy-based QAMM classification performs well in regimes of small pattern density and low detector inefficiency. In contrast, state-based QCAM achieves reasonably high accuracy recall for large pattern density and the greatest recall accuracy robustness to a variety of detector noise sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP

Large-scale scientific workflows rely heavily on high-performance file transfers. These transfers require strict quality parameters such as guaranteed bandwidth, no packet loss or data duplication. To have successful file transfers, methods such as predetermined thresholds and statistical analysis need to be done to determine abnormal patterns. Network administrators routinely monitor and analyze network data for diagnosing and alleviating these, making decisions based on their experience. However, as networks grow and become complex, monitoring large data files and quickly processing them, makes it improbable to identify errors and rectify these. Abnormal file transfers have been classified by simply setting alert thresholds, via tools such as PerfSonar and TCP statistics (Tstat). This paper investigates the feasibility of unsupervised feature extraction methods for identifying network anomaly patterns with three unsupervised classification methods—principal component analysis, autoencoder and isolation forest. Here, we collect file transfer statistics from two experiment sets—synthetic iPerf generated traffic and 1000 Genome workflow runs, with synthetically introduced anomalies. Our results show that while PCA and a simple autoencoder finds it difficult to detect clusters, the tree-variant isolation forest is able to identify anomalous packets by breaking down TCP traces into tree classes early.

97 MATHEMATICS AND COMPUTING↗

Method and system for pattern analysis using a coarse-coded neural network

A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.

Spirkovska, Liljana↗

Photoelastic tests on models of thermal protection system for space shuttle orbiter

The thermal protection system (TPS) of the space shuttle orbiter vehicle, consisting of ceramic tile/adhesive/strain isolator pad/adhesive/aluminum substructure, was modeled photoelasticity. A highly sensitive photoelastic material was used in the models to show the nature of the stress-transfer between the strain isolation pad (SIP) and the ceramic tile through the RTV-adhesive layer. Isochromatic fringe patterns were obtained for models subjected to tension and combined tension and bending. Tests indicated that the load-transfer between the SIP and the photoelastic material occurred at discrete locations causing stress concentrations in the photoelastic material. Stress concentration factors of the order of 1.9 were measured, but as the observed photoelastic response was an integrated effect through the model thickness, the local stress concentration factors at the SIP/tile interface could be even higher.

Prabhakaran, R.↗

Manufacturing Water‐Based Low‐Tortuosity Electrodes for Fast‐Charge through Pattern Integrated Stamping

Achieving high energy density and fast charging of lithium‐ion batteries can accelerate the promotion of electric vehicles. However, the increased mass loading causes poor charge transfer, impedes the electrochemical reaction kinetics, and limits the battery charging rate. Herein, this work demonstrated a novel pattern integrated stamping process for creating channels in the electrode, which benefits ion transport and increases the rate performance of the electrode. Meanwhile, the pressure applied during the stamping process improved the contact between electrode and current collector and also enhanced the mechanical stability of the electrode. Compared to the conventional bar‐coated electrode with the same thickness of 155 μm (delivered a discharge capacity of 16 mAh g −1 at the rate of 3 C), the stamped low‐tortuosity LiFePO 4 electrode delivered 101 mAh g −1 capacity. Additionally, water was employed as a solvent in this study. Owing to its eco‐friendliness, high scalability, and minimal waste generation, this novel stamping technique inspire a new method for the industrial‐level efficient roll to roll fabrication of fast‐charge electrodes.

25 ENERGY STORAGE↗

Training and cockpit design to promote expert performance

The behavior of expert pilots in familiar situations is explored and the implications for better training programs and cockpit designs are stated. Experts in familiar operational situations performing highly practiced tasks are said to recognize and respond to complex situations using pattern recognition or intuition. For some tasks this class of behaviors is desirable; performance can be improved by reducing cognitive load and increasing speed and accuracy. Part-task training, training for monitoring and techniques for the transfer of knowledge can facilitate the development of these skills. Methods for promoting pattern recognition through pilot-aircraft interface design include the use of spatial presentations of information and providing triggering events. In some instances, the familiar, well-practiced behavior is not appropriate and it is desirable to prevent the response. When prevention is necessary, barriers can be constructed in the interface to remind the pilot of the inappropriateness of the response.

Chappell, Sheryl L.↗

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows

While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing system complexity, such workflows present significant resource management challenges, requiring complex cost-performance tradeoffs. This paper presents RISE, an intelligent staging-based data management middleware, which builds on the DataSpaces framework and performs intelligent scheduling of data management operations to reduce I/O contention. In RISE, data are always written immediately to local buffers to reduce the effect of the transfer impact upon application performance. RISE identifies applications’ data access patterns and moves data towards data consumers only when the network is expected to be idle, reducing the impact of asynchronous background data movement upon critical data read/write requests. Here, we experimentally demonstrate that RISE can take advantage of staging nodes to offload data during writes without degrading application data movement performance.

97 MATHEMATICS AND COMPUTING↗

Near surface structure of ultrathin epitaxial Ru films on graphene/amorphous SiO 2 revealed by azimuthal RHEED

Ru has been considered as an alternative metallic candidate for future local interconnects. The 2D reciprocal space map constructed from the azimuthal reflection high-energy electron diffraction patterns reveals that ultrathin Ru(0001) is epitaxially grown on transferred graphene on amorphous SiO 2 through quasi-van der Waals interaction. The in-plane and out-of-plane lattice constants are measured from streaks’ separation and intensity modulations along streaks, respectively. Weak and broad rings indicate that a low density of nanoscale polycrystals exist on the surface. In this work, The intensities of 00 and non-00 diffraction spots vs. azimuthal angles in the 2D map show a few degrees out-of-plane and in-plane angular misorientations among grains, respectively. As the film thickness decreases these angular misorientations increase. Transmission electron microscopy carried out in this study also provides precise values of lattice constant and sub-grain sizes in the films. These findings show that ultrathin Ru film is epitaxial but not exactly single crystalline.

36 MATERIALS SCIENCE↗

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗

Holographic interferometry - Errors caused by thermal gradients in holographic plates

Thermal effects as sources of errors in holographic interferometry are illustrated on an example of reflection holography patterns obtained on graphite-epoxy specimens exposed before and after compressive loading. The numerical interpretation of the obtained holograms indicated some peculiar unexpected thickness changes in the specimen. In addition, some patterns showed random occurrence of zones of low and zero contrast. These discrepancies occurred usually in the first of the two exposures and were traced to thermal warping and thermal relaxation patterns caused by small temperature gradients that resulted from heat transfer to the photographic plates during their installation. Suggested precautions to minimize thermal effects include using thick holographic plates (photographic plates attached to glass plates) and insulated gloves during handling and allowing time to establish thermal equilibrium before the exposure.

Post, D.↗

Waves, advection, and cloud patterns on Venus

The stable layers adjacent to the nearly neutral layer within the Venus clouds are found to be capable of supporting vertically trapped, horizontally propagating waves with horizontal wavelengths of about 10 km and speeds of a few meters per second relative to the mean wind in the neutral layer. These waves may possibly be excited by turbulence within the neutral layer. Here, the properties of the waves, and the patterns which they might produce within the visible clouds if excited near the subsolar point are examined. The patterns can be in agreement with many features in images. The waves are capable of transferring momentum latitudinally to help maintain the general atmospheric spin, but at present we are not able to evaluate wave amplitudes. We also examine an alternative possibility that the cloud patterns are produced by advection and shearing by the mean zonal and meridional flow of blobs formed near the equator. It is concluded that advection and shearing by the mean flow is the most likely explanation for the general pattern of small scale striations.

Schinder, Paul J.↗

Mechanical and analytical screening of braided composites for transport fuselage applications

The mechanics of materials progress in support of the goal of understanding the application of braided composites in a transport aircraft fuselage are summarized. Composites consisting of both 2-D and 3-D braid patterns are investigated. Both consolidation of commingled graphite/PEEK and resin transfer molding of graphite-epoxy braided composite processes are studied. Mechanical tests were used to examine unnotched tension, open hole tension, compression, compression after impact, in-plane shear, out-of-plane tension, bearing, and crippling. Analytical methods are also developed and applied to predict the stiffness and strengths of test specimens. A preliminary study using the test data and analytical results is performed to assess the applicability of braided composites to a commercial aircraft fuselage.

Fedro, Mark J.↗

Origin and early evolution of photosynthesis

Photosynthesis was well-established on the earth at least 3.5 thousand million years ago, and it is widely believed that these ancient organisms had similar metabolic capabilities to modern cyanobacteria. This requires that development of two photosystems and the oxygen evolution capability occurred very early in the earth's history, and that a presumed phase of evolution involving non-oxygen evolving photosynthetic organisms took place even earlier. The evolutionary relationships of the reaction center complexes found in all the classes of currently existing organisms have been analyzed using sequence analysis and biophysical measurements. The results indicate that all reaction centers fall into two basic groups, those with pheophytin and a pair of quinones as early acceptors, and those with iron sulfur clusters as early acceptors. No simple linear branching evolutionary scheme can account for the distribution patterns of reaction centers in existing photosynthetic organisms, and lateral transfer of genetic information is considered as a likely possibility. Possible scenarios for the development of primitive reaction centers into the heterodimeric protein structures found in existing reaction centers and for the development of organisms with two linked photosystems are presented.

NASA Program Exobiology↗

Plasticity of Neurovestibular Systems Following Micro- and Hyper-Gravity Exposure and Readaptation to Earth's 1G

The gravity-sensing organs sense the sum of inertial force due to head translation and head orientation relative to gravity. Normally gravity is constant, and yet the neural sensors show remarkable plasticity. When the force of gravity changes, such as in spaceflight or during centrifugation, the neurovestibular system responds by regulating its neural output, and this response is similar for the vertebrate utricular nerve afferents and for the statocyst hair cell in invertebrates. First, we examine the response of utricular afferents in toadfish following exposure to G on two orbital missions (STS-90 and 95). Within the first day after landing, magnitude of neural response to an applied acceleration was significantly elevated, and re-adaptation back to control values occurred within approximately 30 hours. Time course of return to normal approximately parallels the decrease in vestibular disorientation in astronauts following return. Next, we use well-controlled hyper-G experiments in the vertebrate model to address: If G leads to adaptation and subsequent re-adaptation neural processes, does the transfer from 1G to hyper-G impart the opposite effects and do the effects accompanying transfer from the hyper-G back to the 1G conditions resemble as an analog the transfer from 1G to the microG Results show a biphasic pattern in reaction to 3G exposures: an initial sensitivity up-regulation (3- and 4-day) followed by a significant decrease after longer exposure. Return to control values is on the order of 4-8 days. Utricular sensitivity is strongly regulated up or down by gravity load and the duration of exposure. Interestingly, we found no correlation of response and hair cell synaptic body counts despite the large gain difference between 4- and 16-Day subjects. Lastly, we examine responses of statocyst receptors in land snail following exposure to G on two unmanned Russian Orbital missions (Foton M-2 and -3). Here, we have the ability to measure the output directly from the hair cells. Similar to afferents in vertebrates the hair cells increased their response sensitivity to vestibular stimulation. Two major pieces of information are needed: the precise vertebrate hair cell response to altered gravity and the impact of longer duration exposures on sensory plasticity.

Boyle, Richard D.↗

Numerical modeling and performance analysis of a membrane-based air dehumidifier using ionic liquid desiccant

Membrane-based Liquid Desiccant Air Dehumidifier (MLDAD) has the potential to overcome the shortcomings of the conventional open-tower liquid desiccant air dehumidifier. The MLDAD uses membranes with high water vapor permeability to separate air stream from the liquid desiccant and thus eliminates carry-over and the resulting corrosion issues. Recently, the ionic liquid desiccant becomes a promising alternative to conventional liquid desiccant. The ionic liquid desiccant has a large potential of dehumidification, which is also non-corrosive to metals and non-crystallizable. A two-dimensional numerical heat and mass transfer model of the MLDAD using a recently identified ionic liquid desiccant, [EMIM]OAc, is presented here. This model can simulate the performance of the MLDAD with various designs, including different selections of liquid desiccant and membrane materials, dimensions of the MLDAD, and flow patterns. For porous membranes, this model accounts for several micro-scale mass transfer mechanisms of vapor transportation across the membrane. It can also model the mass transfer performance of dehumidifiers using non-porous membranes based on the experimentally measured membrane permeance. The numerical model was validated against the performance data available from literature and experimental tests. The maximum discrepancy of the latent effectiveness between the measured and the model-predicted results was about 6% when porous membranes were used. A parametric study was conducted with the numerical model. Finally, the results indicated that the membrane permeability, air path height, and solution to air mass ratio were the most critical parameters, determining the dehumidification performance of the MLDAD.

42 ENGINEERING↗

Cryogenic Transfer Line Chilldown

The transient behavior of a small scale cryogenic transfer line was investigated during chilldown to cryogenic temperatures. The vacuum-jacketed apparatus consisted of a vertical tube followed by a near horizontal tube. The apparatus was equipped with view ports in the near horizontal section to allow visual observation of the flow patterns. Wall temperatures were measured at various locations along the length of the transfer line. Each test was conducted at a constant liquid volumetric flowrate at the transfer line inlet until saturation temperatures were obtained throughout the system.

VanDresar, Neil T.↗