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Numerical Investigation on the Reynolds Number Effects of Supercritical Airfoil
2012
Procedia Engineering
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The aerodynamic characteristics of supercritical airfoil are rather sensitive to Reynolds number. ...
Therefore, Reynolds number has great effects on the economy, comfort and even safety of large aircrafts. ...
training-edge pressure coefficient and Reynolds number. ...
doi:10.1016/j.proeng.2012.01.998
fatcat:2wm45hia7ndzzozzmhkaefpmfa
A general Reynolds analogy theory for the compressible wall-bounded turbulence
[article]
2013
arXiv
pre-print
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2012 pre-print arXiv:1208.4541v2 fatcat:feqsrsltovfq3ncqrrt63fotpaOther Versions
A general Reynolds analogy (GRA) theory is proposed for the mean and fluctuating velocity and temperature in compressible wall-bounded turbulent flows. ...
The fluctuation temperature-velocity relations derived by GRA are slightly different from the modified strong Reynolds analogy derived phenomenologically by Huang et al. ...
(Xin-Liang et al. 2006).
Figure 2 .Figure 3 . 23 Figure 2. (color online). Mach number (left) and wall-temperature effects (right) of the temperature-velocity relationship Eq. (4.6) in CTBL. ...
arXiv:1208.4541v5
fatcat:yfj7pvncczbu3eq7iegjpge554
Investigation of Reynolds Number Effects on Aerodynamic Characteristics of a Transport Aircraft
2021
Aerospace (Basel)
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layer development, shock wave/boundary layer interaction, and induced flow separation at different Reynolds numbers. ...
tests of a transport aircraft reference model with a wing-body configuration were conducted in the European Transonic Windtunnel (ETW) at different Reynolds numbers. ...
Reynolds number. ...
doi:10.3390/aerospace8070177
doaj:ff4102daac324e72913564c69b5ed8cc
fatcat:5rs5o2tsnrefrephfpfafttcse
Evolution characteristic analysis of double-helical vortex wake of high Reynolds number flow
2018
Wuli xuebao
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High Reynolds number helical vortex system possesses a dominant characteristic of helicopter rotor flow field, whose spatiotemporal evolution is one of the most important factors affecting the aerodynamic ...
The highly-resolved flow field of Caradonna-Tung rotor with two blades in hover, with a tip Mach number of 0.439 and a tip Reynolds number of 1.92 × 10 6 , is obtained using delayed detached eddy simulation ...
doi:10.7498/aps.67.20171291
fatcat:pzzbxwf5obfy5k45q2wvyi3qyy
An Overview of Numerical Methods for Reynolds Equation
2018
DEStech Transactions on Computer Science and Engineering
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Turbulent boundary layer separation control using plasma actuator at Reynolds number 2000000
2016
Chinese Journal of Aeronautics
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An experimental investigation was conducted to evaluate the effect of symmetrical plasma actuators on turbulent boundary layer separation control at high Reynolds number. ...
It turns out that the maximum lift coefficient increased by approximately 8.98% and the stall angle of attack was delayed by approximately 2°at Reynolds number 2 10 6 . ...
Reynolds numbers. ...
doi:10.1016/j.cja.2016.08.006
fatcat:maoc4zxdtfajxiai6jocd4waza
Universal Background Models
[chapter]
2009
Encyclopedia of Biometrics
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A Universal Background Model (UBM) is a model used in a biometric verification system to represent general, personindependent feature characteristics to be compared against a model of person-specific feature characteristics when making an accept or reject decision. For example, in a speaker verification system, the UBM is a speaker-independent Gaussian Mixture Model (GMM) trained with speech samples from a large set of speakers to represent general speech characteristics. Using a
doi:10.1007/978-0-387-73003-5_197
fatcat:tznfvid3g5hxnlqaxewefzvk3i
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... c GMM trained with speech samples from a particular enrolled speaker, a likelihood-ratio test for an unknown speech sample can be formed between the match score of the speaker-specific model and the UBM. The UBM may also be used when training the speaker-specific model by acting as a the prior model in MAP parameter estimation.
MLlib: Machine Learning in Apache Spark
[article]
2015
arXiv
pre-print
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Apache Spark is a popular open-source platform for large-scale data processing that is well-suited for iterative machine learning tasks. In this paper we present MLlib, Spark's open-source distributed machine learning library. MLlib provides efficient functionality for a wide range of learning settings and includes several underlying statistical, optimization, and linear algebra primitives. Shipped with Spark, MLlib supports several languages and provides a high-level API that leverages Spark's
arXiv:1505.06807v1
fatcat:xqjx7ioxizgldgec5vb7l64o24
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... rich ecosystem to simplify the development of end-to-end machine learning pipelines. MLlib has experienced a rapid growth due to its vibrant open-source community of over 140 contributors, and includes extensive documentation to support further growth and to let users quickly get up to speed.
Study on Traveling Wave Wall Control Method for Suppressing Wake of Flow around a Circular Cylinder at Moderate Reynolds Number
2022
Applied Sciences
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In contrast, the optimal combination of control parameters under the present Reynolds number is concluded with "Downstream" propagating direction, maximum wave amplitude ratio of 0.02, and velocity ratio ...
The numerical calculations are carried out with a Reynold number of 4.1 × 10 4 , and the turbulence flow is calculated by SST k-ω model. ...
The mean drag coefficient d C versus Reynolds shown in Figure 3a, and it can be observed that d C is very close to previous results similar Re range. ...
doi:10.3390/app12073433
fatcat:io7a25bwvvfyjaxfkd574nc2v4
GraphX
2013
First International Workshop on Graph Data Management Experiences and Systems - GRADES '13
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From social networks to targeted advertising, big graphs capture the structure in data and are central to recent advances in machine learning and data mining. Unfortunately, directly applying existing data-parallel tools to graph computation tasks can be cumbersome and inefficient. The need for intuitive, scalable tools for graph computation has lead to the development of new graph-parallel systems (e.g., Pregel, PowerGraph) which are designed to efficiently execute graph algorithms.
doi:10.1145/2484425.2484427
dblp:conf/sigmod/XinGFS13
fatcat:qwlrklz6wbgzhlogl5bqkvrskm
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... ly, these new graph-parallel systems do not address the challenges of graph construction and transformation which are often just as problematic as the subsequent computation. Furthermore, existing graph-parallel systems provide limited fault-tolerance and support for interactive data mining. We introduce GraphX, which combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. We leverage new ideas in distributed graph representation to efficiently distribute graphs as tabular data-structures. Similarly, we leverage advances in data-flow systems to exploit in-memory computation and fault-tolerance. We provide powerful new operations to simplify graph construction and transformation. Using these primitives we implement the PowerGraph and Pregel abstractions in less than 20 lines of code. Finally, by exploiting the Scala foundation of Spark, we enable users to interactively load, transform, and compute on massive graphs.
CrowdDB
2011
Proceedings of the 2011 international conference on Management of data - SIGMOD '11
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Many data management problems are inherently vague and hard for algorithms to process. Take for example entity resolution, also known as record linkage, the process to resolve records for the same entity from heterogeneous sources. Properly resolving such records require not only the syntactic structure of the data, but also contextual semantics that are hard for machines to understand. To properly perform such data management tasks requires human inputs for providing information that is
doi:10.1145/1989323.1989331
dblp:conf/sigmod/FranklinKKRX11
fatcat:v3c335roqbfupnlmgh3xhinwu4
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... from the structured data that machines can read, for performing computationally difficult functions, and for matching, ranking, or aggregating results based on fuzzy criteria. The rise of microtask crowdsourcing platforms, e.g. Amazon's Mechanical Turk, provides a unique opportunity to integrate human inputs into the algorithmic data flow. There are two recent work, CrowdDB [1] and CrowdER [2] , that combine human inputs with machine computation to answer otherwise unanswerable queries.
GraphX: Unifying Data-Parallel and Graph-Parallel Analytics
[article]
2014
arXiv
pre-print
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From social networks to language modeling, the growing scale and importance of graph data has driven the development of numerous new graph-parallel systems (e.g., Pregel, GraphLab). By restricting the computation that can be expressed and introducing new techniques to partition and distribute the graph, these systems can efficiently execute iterative graph algorithms orders of magnitude faster than more general data-parallel systems. However, the same restrictions that enable the performance
arXiv:1402.2394v1
fatcat:xxx2uvx6arbgdnjqiw7igqztnm
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... ns also make it difficult to express many of the important stages in a typical graph-analytics pipeline: constructing the graph, modifying its structure, or expressing computation that spans multiple graphs. As a consequence, existing graph analytics pipelines compose graph-parallel and data-parallel systems using external storage systems, leading to extensive data movement and complicated programming model. To address these challenges we introduce GraphX, a distributed graph computation framework that unifies graph-parallel and data-parallel computation. GraphX provides a small, core set of graph-parallel operators expressive enough to implement the Pregel and PowerGraph abstractions, yet simple enough to be cast in relational algebra. GraphX uses a collection of query optimization techniques such as automatic join rewrites to efficiently implement these graph-parallel operators. We evaluate GraphX on real-world graphs and workloads and demonstrate that GraphX achieves comparable performance as specialized graph computation systems, while outperforming them in end-to-end graph pipelines. Moreover, GraphX achieves a balance between expressiveness, performance, and ease of use.
Shark: SQL and Rich Analytics at Scale
[article]
2012
arXiv
pre-print
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Shark is a new data analysis system that marries query processing with complex analytics on large clusters. It leverages a novel distributed memory abstraction to provide a unified engine that can run SQL queries and sophisticated analytics functions (e.g., iterative machine learning) at scale, and efficiently recovers from failures mid-query. This allows Shark to run SQL queries up to 100x faster than Apache Hive, and machine learning programs up to 100x faster than Hadoop. Unlike previous
arXiv:1211.6176v1
fatcat:cdpyu3sp3bd7rcdzaaci4juayi
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... ems, Shark shows that it is possible to achieve these speedups while retaining a MapReduce-like execution engine, and the fine-grained fault tolerance properties that such engines provide. It extends such an engine in several ways, including column-oriented in-memory storage and dynamic mid-query replanning, to effectively execute SQL. The result is a system that matches the speedups reported for MPP analytic databases over MapReduce, while offering fault tolerance properties and complex analytics capabilities that they lack.
Reynolds Number Effects Investigation of Supercritical Airfoil Based on EFD and CFD
2013
Research Journal of Applied Sciences Engineering and Technology
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This study aimed to investigate the transonic Reynolds number effects of supercritical airfoil by EFD and CFD method. ...
It is also noticed that the lift coefficient increased, drag and pitching moment coefficient decreased as Reynolds number increasing. ...
GAO Chao, ZHAO Zi-jie, PENG Xin, XU Xin, ZHOU Qiang, TAO Yang and others devoting themselves to this research. ...
doi:10.19026/rjaset.6.3441
fatcat:t3zotefunvcqncfdzmbu6dozym
MEET DB2
2010
Proceedings of the VLDB Endowment
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Commercial databases compete for market share, which is composed of not only net-new sales to those purchasing a database for the first time, but also competitive "win-backs" and migrations. Database migration, or the act of moving both application code and its underlying database platform from one database to another, presents a serious administrative and application development challenge fraught with large manual costs. Migration is typically a high cost effort due to incompatibilities
doi:10.14778/1920841.1921016
fatcat:tlaczsdc7jgnjlpxqirwptymom
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... database platforms. Incompatibilities are caused most often by product specific extensions to language support, procedural logic, DDL, and administrative interfaces. The migration evaluation is the first step in any competitive database migration process. Historically this has been a manual process, with the high costs and subjective results. This has led us to reexamine traditional practices and explore an automatic, innovative solution. We have designed and implemented the Migration Evaluation and Enablement Tool for DB2 for Linux Unix and Windows, or MEET DB2, a tool for automatically evaluating database migration projects. Encapsulated in a simple one-click interface, MEET DB2 is able to provide detailed evaluation of migration complexity based on its deep analysis on the source database. In this paper, we present MEET DB2, and discuss many aspects of our design, and report measurements from real-world use cases. In particular, we show a novel way to use XML and XQuery in this domain for better extensibility and interoperability. We have evaluated MEET DB2 on 18 source code samples, covering nearly 1 million lines of code. The utility has provided benefits in several dimensions including: dramatically reduced time for evaluation, consistency, improved accuracy over human analysis, improved reporting, reduced skill requirements for migration analysis, and clear analytics for product planning.
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