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Whither turbulence and big data in the 21st century?

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Whither turbulence and big data in the 21st century?/ edited by Andrew Pollard ... [et al.].
其他題名:	Whither turbulence and big data in the twenty-first century?
其他作者:	Pollard, Andrew.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xviii, 574 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Turbulence. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-41217-7
ISBN:	9783319412177

Whither turbulence and big data in the 21st century?
Whither turbulence and big data in the 21st century?[electronic resource] /Whither turbulence and big data in the twenty-first century?edited by Andrew Pollard ... [et al.]. - Cham :Springer International Publishing :2017. - xviii, 574 p. :ill. (some col.), digital ;24 cm.

Part I HISTORICAL PERSPECTIVES -- 1 From Tennekes & Lumley to Townsend and to George a slow march to freedom -- 2 A 50 Year Retrospective and the Future -- Part II TURBULENT BOUNDARY LAYERS -- 3 Study of the streamwise evolution of turbulent boundary layers to high Reynolds numbers -- 4 Towards the direct numerical simulation of a self-similar adverse pressure gradient turbulent boundary layer flow -- 5 Analysis of velocity structures in a transitionally rough turbulent boundary -- 6 Streamwise relaxation of a shock perturbed turbulent -- Part III JETS -- 7 Turbulence and Data Analytics in the 21st Century The Round Free Jet -- 8 The Sound-field Produced by Clustered Rockets During Start up -- 9 Variable Viscosity Jets Entrainment and Mixing Process -- 10 POD Mode Robustness for the Turbulent Jet -- Part IV ENVIRONMENTAL FLOWS AND WIND ENERGY -- 11 Large Eddy Simulation of environmental flows from the laboratory-scale numerical experiments toward full-scale -- 12 Big data from Big experiments The WindEEE Dome -- 13 Visualizing Wind Farm Wakes Using SCADA Data Supplemental Analysis -- 14 Turbulent and Deterministic Stresses in the Near Wake of a Wind Turbine Array -- 15 Evaluation of Higher Order Moments and Isotropy in the Wake of a Wind Turbine Array -- Part V DATA MANIPULATION -- 16 Turbulent Flow Physics and Control The role of big data analyses tools -- 17 Data-driven methods in fluid dynamics Sparse classification from experimental data -- 18 Conversion of measured turbulence spectra from temporal to spatial domain -- 19 Effects of unsteady Coanda blowing on the wake and drag of a simplified blunt vehicle -- 20 Challenges for Large Eddy Simulation of Engineering Flows -- 21 Coarse Grained Simulation and Turbulent Material Mixing -- 22 Non-classical Exponential Decay Regimes in Multi-Scale Generated Isotropic Turbulence -- 23 A minimal flow unit for turbulence, combustion and astrophysics -- 24 Linear Stability Analysis of Compressible Channel Flow with Porous Walls -- 25 Dissipation and topological features conditioned by velocity level-crossings in wall turbulence -- Part VII- Four Perspectives On Big Data and The Turbulence Community -- 26 Cyberinfrastructure to Empower Scientific Research -- 27 Turbulence in the era of Big Data: Recent experiences with sharing large datasets -- 26 Cyberinfrastructure to Empower Scientific Research -- 27 Turbulence in the era of Big Data Recent experiences with sharing large datasets -- Public dissemination of raw turbulence data -- 29 Reacting LES@2030 Near Diskless and Near -- PART VIII-Discussion I-Challenges in Turbulence in the 21st Century - What Problems We Should Focus On in the Next 20 years? -- 30 -- Whither Turbulence and Big Data for the 21st Century-I -- Part IX-Discussion 2- Large Data Opportunities for Collaborations -- 31 Whither Turbulence and Big Data for the 21st Century-II.

This volume provides a snapshot of the current and future trends in turbulence research across a range of disciplines. It provides an overview of the key challenges that face scientific and engineering communities in the context of huge databases of turbulence information currently being generated, yet poorly mined. These challenges include coherent structures and their control, wall turbulence and control, multi-scale turbulence, the impact of turbulence on energy generation and turbulence data manipulation strategies. The motivation for this volume is to assist the reader to make physical sense of these data deluges so as to inform both the research community as well as to advance practical outcomes from what is learned. Outcomes presented in this collection provide industry with information that impacts their activities, such as minimizing impact of wind farms, opportunities for understanding large scale wind events and large eddy simulation of the hydrodynamics of bays and lakes thereby increasing energy efficiencies, and minimizing emissions and noise from jet engines. Elucidates established, contemporary, and novel aspects of fluid turbulence - a ubiquitous yet poorly understood phenomena; Explores computer simulation of turbulence in the context of the emerging, unprecedented profusion of experimental data, which will need to be stewarded and archived; Examines a compendium of problems and issues that investigators can use to help formulate new promising research ideas; Makes the case for why funding agencies and scientists around the world need to lead a global effort to establish and steward large stores of turbulence data, rather than leaving them to individual researchers.

ISBN: 9783319412177

Standard No.: 10.1007/978-3-319-41217-7doiSubjects--Topical Terms:

559839
Turbulence.

LC Class. No.: QA913

Dewey Class. No.: 532.0527

Whither turbulence and big data in the 21st century?
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505 0 $a Part I HISTORICAL PERSPECTIVES -- 1 From Tennekes & Lumley to Townsend and to George a slow march to freedom -- 2 A 50 Year Retrospective and the Future -- Part II TURBULENT BOUNDARY LAYERS -- 3 Study of the streamwise evolution of turbulent boundary layers to high Reynolds numbers -- 4 Towards the direct numerical simulation of a self-similar adverse pressure gradient turbulent boundary layer flow -- 5 Analysis of velocity structures in a transitionally rough turbulent boundary -- 6 Streamwise relaxation of a shock perturbed turbulent -- Part III JETS -- 7 Turbulence and Data Analytics in the 21st Century The Round Free Jet -- 8 The Sound-field Produced by Clustered Rockets During Start up -- 9 Variable Viscosity Jets Entrainment and Mixing Process -- 10 POD Mode Robustness for the Turbulent Jet -- Part IV ENVIRONMENTAL FLOWS AND WIND ENERGY -- 11 Large Eddy Simulation of environmental flows from the laboratory-scale numerical experiments toward full-scale -- 12 Big data from Big experiments The WindEEE Dome -- 13 Visualizing Wind Farm Wakes Using SCADA Data Supplemental Analysis -- 14 Turbulent and Deterministic Stresses in the Near Wake of a Wind Turbine Array -- 15 Evaluation of Higher Order Moments and Isotropy in the Wake of a Wind Turbine Array -- Part V DATA MANIPULATION -- 16 Turbulent Flow Physics and Control The role of big data analyses tools -- 17 Data-driven methods in fluid dynamics Sparse classification from experimental data -- 18 Conversion of measured turbulence spectra from temporal to spatial domain -- 19 Effects of unsteady Coanda blowing on the wake and drag of a simplified blunt vehicle -- 20 Challenges for Large Eddy Simulation of Engineering Flows -- 21 Coarse Grained Simulation and Turbulent Material Mixing -- 22 Non-classical Exponential Decay Regimes in Multi-Scale Generated Isotropic Turbulence -- 23 A minimal flow unit for turbulence, combustion and astrophysics -- 24 Linear Stability Analysis of Compressible Channel Flow with Porous Walls -- 25 Dissipation and topological features conditioned by velocity level-crossings in wall turbulence -- Part VII- Four Perspectives On Big Data and The Turbulence Community -- 26 Cyberinfrastructure to Empower Scientific Research -- 27 Turbulence in the era of Big Data: Recent experiences with sharing large datasets -- 26 Cyberinfrastructure to Empower Scientific Research -- 27 Turbulence in the era of Big Data Recent experiences with sharing large datasets -- Public dissemination of raw turbulence data -- 29 Reacting LES@2030 Near Diskless and Near -- PART VIII-Discussion I-Challenges in Turbulence in the 21st Century - What Problems We Should Focus On in the Next 20 years? -- 30 -- Whither Turbulence and Big Data for the 21st Century-I -- Part IX-Discussion 2- Large Data Opportunities for Collaborations -- 31 Whither Turbulence and Big Data for the 21st Century-II.
520 $a This volume provides a snapshot of the current and future trends in turbulence research across a range of disciplines. It provides an overview of the key challenges that face scientific and engineering communities in the context of huge databases of turbulence information currently being generated, yet poorly mined. These challenges include coherent structures and their control, wall turbulence and control, multi-scale turbulence, the impact of turbulence on energy generation and turbulence data manipulation strategies. The motivation for this volume is to assist the reader to make physical sense of these data deluges so as to inform both the research community as well as to advance practical outcomes from what is learned. Outcomes presented in this collection provide industry with information that impacts their activities, such as minimizing impact of wind farms, opportunities for understanding large scale wind events and large eddy simulation of the hydrodynamics of bays and lakes thereby increasing energy efficiencies, and minimizing emissions and noise from jet engines. Elucidates established, contemporary, and novel aspects of fluid turbulence - a ubiquitous yet poorly understood phenomena; Explores computer simulation of turbulence in the context of the emerging, unprecedented profusion of experimental data, which will need to be stewarded and archived; Examines a compendium of problems and issues that investigators can use to help formulate new promising research ideas; Makes the case for why funding agencies and scientists around the world need to lead a global effort to establish and steward large stores of turbulence data, rather than leaving them to individual researchers.
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