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At least 199 records · Page 11

Numerical Investigation of 'Transonic Resonance' with a Convergent-Divergent Nozzle

At pressure ratios lower than the design value, convergent-divergent (C-D) nozzles often undergo a flow resonance accompanied by the emission of acoustic tones. The phenomenon, driven by the unsteady shock within the divergent section of the nozzle, has been studied experimentally by Zaman et al. In this paper, the space-time conservation element solution element (CE/SE) method is employed to numerically investigate the phenomenon. The computations are performed for a given nozzle geometry for several different pressure ratios. Sustained 'limit cycle' oscillations are encountered in all cases. The oscillation frequencies, their variation with pressure ratio including a 'stage jump', agree well with the experimental results. The unsteady flow data confirm that stage 1 of the resonance (fundamental) involves a one-quarter standing wave while stage 2 (third harmonic) involves a three-quarter standing wave within the divergent section of the nozzle. Details of the shock motion, and the flow and near acoustic field, are documented for one case each of stages 1 and 2.

Loh, Ching Y.↗

An Assessment of CFD Effectiveness for Vortex Flow Simulation to Meet Preliminary Design Needs

The low-speed flight and transonic maneuvering characteristics of combat air vehicles designed for efficient supersonic flight are significantly affected by the presence of free vortices. At moderate-to-high angles of attack, the flow invariably separates from the leading edges of the swept slender wings, as well as from the forebodies of the air vehicles, and rolls up to form free vortices. The design of military vehicles is heavily driven by the need to simultaneously improve performance and affordability.1 In order to meet this need, increasing emphasis is being placed on using Modeling & Simulation environments employing the Integrated Product & Process Development (IPPD) concept. The primary focus is on expeditiously providing design teams with high-fidelity data needed to make more informed decisions in the preliminary design stage. Extensive aerodynamic data are needed to support combat air vehicle design. Force and moment data are used to evaluate performance and handling qualities; surface pressures provide inputs for structural design; and flow-field data facilitate system integration. Continuing advances in computational fluid dynamics (CFD) provide an attractive means of generating the desired data in a manner that is responsive to the needs of the preliminary design efforts. The responsiveness is readily characterized as timely delivery of quality data at low cost.

Raj, P.↗

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan Dejesus Oribello↗

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan D Oribello↗

SAR processing on the MPP

The processing of synthetic aperture radar (SAR) signals using the massively parallel processor (MPP) is discussed. The fast Fourier transform convolution procedures employed in the algorithms are described. The MPP architecture comprises an array unit (ARU) which processes arrays of data; an array control unit which controls the operation of the ARU and performs scalar arithmetic; a program and data management unit which controls the flow of data; and a unique staging memory (SM) which buffers and permutes data. The ARU contains a 128 by 128 array of bit-serial processing elements (PE). Two-by-four surarrays of PE's are packaged in a custom VLSI HCMOS chip. The staging memory is a large multidimensional-access memory which buffers and permutes data flowing with the system. Efficient SAR processing is achieved via ARU communication paths and SM data manipulation. Real time processing capability can be realized via a multiple ARU, multiple SM configuration.

Batcher, K. E.↗

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Detection of velocity in high temperature liquid metals

Various efforts have been made to measure velocity in liquid metals. All of these efforts, however, share the same inherent limitation, namely, not being operative at the high temperatures required by liquid metals and liquid slags in an industrial application. In this paper, the current methods used were reviewed, and a new technique was presented for the measurement of velocity in high temperature liquid metals. In using this technique there are two stages. Starting with the calibration stage and then moving to the actual measurement stage by making use of the data obtained from calibration stage. Calibration proceeds in the following manner. Metallic spheres moving with a specific velocity are immersed in liquid metal held under isothermal conditions and at specific temperature. Their melting times are determined very accurately with a novel technique. These measurements are repeated for different metal bath temperatures and for different velocities of metallic spheres. In this manner it is possible to calculate the correlation between velocity and melting times for each metal bath temperature. During the actual measurement stage, when the metal bath temperature is known and its velocity is unknown, the magnitude of the unknown liquid metal velocity can be derived as follows: metallic spheres are immersed into the moving liquid metal and their melting times are determined. Using the above mentioned correlations, it will be shown that the magnitude of the unknown velocity in liquid metal can be deduced. This new technique was applied to high temperature liquid aluminum and liquid steel and these results were presented. The potential applicability of this technique in other liquid metals and liquid slags will also be discussed.

Mikrovas, A. C.↗

Two-stage, low noise advanced technology fan. Volume 2: Aerodynamic data

Aerodynamic data from static tests of a two-stage advanced technology fan designed to minimize noise are presented. Fan design conditions include delivery of 209.1kg/sec/sq m (42.85 lbm/sec/sq ft) specific corrected flow at an overall pressure ratio of 1.9 and an adiabatic efficiency of 85.3 percent. The 0.836m (2.74ft) diameter first stage rotor has a hub/tip ratio of 0.4 and 365.8m/sec (1200ft/sec) design tip speed. In addition to the moderate tip speed and pressure rise per stage, other noise control design features involve widely spaced blade rows and proper selection of blade-vane ratios. Aerodynamic data are presented for tests with unifrom and with hub and tip radially distorted inlet flow. Aerodynamic data are also presented for tests of this fan with acoustic treatments, including acoustically treated casing walls, a flowpath exit acoustic ring, and a translating centerbody sonic inlet device. A complete tabulation of the overall performance data, the blade element data, and the power spectral density information relating to turbulence levels generated by the sonic inlet obtained during these tests is included. For vol. 1, see N74-33789.

Harley, K. G.↗

Data analysis and noise prediction for the QF-1B experimental fan stage

The results of a fan noise data analysis and prediction effort using experimental data obtained from tests on the QF-1B research fan are described. Surface pressure measurements were made with flush mounted sensors installed on selected rotor blades and stator vanes and noise measurements were made by microphones located at the far field. Power spectral density analysis, time history studies, and calculation of coherence functions were made. The emphasis of these studies was on the characteristics of tones in the spectra. The amplitude behavior of spectral tones was found to have a large, often predominant, random component, suggesting that turbulent processes play an important role in the generation of tonal as well as broadband noise. Inputs from the data analysis were used in a prediction method which assumes that acoustic dipoles, produced by unsteady blade and van forces, are the important source of fan noise.

Bliss, D. B.↗

Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.

Computational biology and bioinformatics↗

A Study of the Non-Thermal X-ray Emission of Shell-Type Supernova Remnants

The term of the forth year of the award is the period from March 15, 2003 to March 14, 2004. During this year, Dr. Thomas Pannuti, who had been performing most of the analyses, made a transition to a new position at Caltech. As of September 2003, Dr. Michael Stage began performing most of the analyses. Dr. Stage has begun constructing a detailed catalog of the spatial and spectral properties of young supernova remnants as described in sections 1 and 4 of the proposal. Specifically, he has focused on the analysis of Chandra ACIS data. The exquisite spatial resolution of the Chandra telescope and the modest spectral resolution of the CCDs make these data ideal. Dr. Stage has developed a standard set of procedures to reduce the data, generate telescope and detector response libraries and handle instrumental and celestial background subtraction. He has also adapted some existing code to automate spectral extraction and fitting. This code enables us to analyze the spectra of tens of thousands of small subregions of supernova remnants. Dr. Stage has recently applied this process to ACIS data for the supernova remnants Cas A and Kepler. The results include maps of the fitted parameters, such as individual line intensities and centroids (i.e. Doppler shifts), the electron temperature, and the absorption column density. These maps are more accurate than simple energy-cut images because it is difficult (and sometimes impossible) to cleanly separate the line emission from the underlying continuum (especially at low energies). It is now possible to identify the locations at which emission from each element is produced. Some of the elements are seen to be layered. The electron temperature maps demonstrate that the outer edges of Cas A and Kepler are very hot with weak lines. This emission is almost certainly synchrotron dominated. Therefore, not only are the maps interesting in and of themselves, but they also provide an unbiased means of easily identifying features in the remnants that can be studied in more detail using, for example, synchrotron models. Over the next year, Dr. Stage will refine the analysis procedures, expand the analyses to include several other remnants, present the results at major scientific conferences and publish a catalog of the results. Since this work is producing impressive results, we have applied for very long Chandra observations of Kepler and Tycho to obtain enough counts to take lull advantage of the technique. A i Ms observation of Cas A is already scheduled. Over the past year, I completed a joint, spectra,l analysis of some X-ray, radio, and gamma-ray data for the supernova remnant SN 1006. The results of this analysis show that the synchrotron and, hence, electron spectrum of the remnant is curved. The amount of curvature in the electron spectrum is quantitatively consistent with predictions of the amount of curvature in the proton spectrum of the remnant. A paper describing this work is nearly complete. When Dr. Pannuti left, he was analyzing X-ray data for the young supernova remnant G266.2-1.2. Dr. Pannuti found the first evidence of thermal X-ray emission from this remnant. Furthermore, like SN 1006, the cutoff frequency varies with azimuth along the bright northeastern rim. This work will be published during the coming year.

Allen, Glenn E.↗

Incomplete fuzzy data processing systems using artificial neural network

In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

Patyra, Marek J.↗

Ares I-X First Stage Internal Aft Skirt Re-Entry Heating Data and Modeling

The CLVSTATE engineering code is being used to predict Ares-I launch vehicle first stage reentry aerodynamic heating. An engineering analysis is developed which yields reasonable predictions for the timing of the first stage aft skirt thermal curtain failure and the resulting internal gas temperatures. The analysis is based on correlations of the Ares I-X internal aft skirt gas temperatures and has been implemented into CLVSTATE. Validation of the thermal curtain opening models has been accomplished using additional Ares I-X thermocouple, calorimeter and pressure flight data. In addition, a technique which accounts for radiation losses at high altitudes has been developed which improves the gas temperature measurements obtained by the gas temperature probes (GTP). Updates to the CLVSTATE models are shown to improve the accuracy of the internal aft skirt heating predictions which will result in increased confidence in future vehicle designs

Schmitz, Craig P.↗

SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)

Abstract In this paper, the design and performance differences between Relational Database Management Systems (RDBMS) and NoSQL Database Systems are examined, with attention to their applicability for real-world Internet of Things for manufacturing (IoTfM) data. While previous work has extensively compared SQL and NoSQL for both generalized and IoT uses, this work specifically examines the tradeoffs and performance differences for manufacturing applications by using a high-fidelity data set collected from a large US manufacturing firm. Growing an IoT system beyond the pilot stage requires scalable data storage; this work seeks to determine the impact of selected database systems on data write performance at scale. Payload size and message frequency were used as the primary characteristics to maintain model fidelity in simulated clients. As the number of simulated asset clients grow, the data write latency was calculated to determine how both database systems’ performance were affected. To isolate the RDBMS and NoSQL differences, a cloud environment was created using Amazon Web Services (AWS) with two identical data ingestion pipelines: writing data to an RDMBS (1) using AWS Aurora MySQL, and (2) using AWS DynamoDB NoSQL. The findings may provide guidance for further experimentation in large-scale manufacturing IoT implementations.

Gamero, David↗