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Distributed Percolation Analysis for Turbulent Flows
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0002-5469-1324
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0002-3234-9368
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0001-6570-5499
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2019 (English)In: 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 42-51, article id 8944383Conference paper, Published paper (Refereed)
Abstract [en]

Percolation analysis is a valuable tool to study the statistical properties of turbulent flows. It is based on computing the percolation function for a derived scalar field, thereby quantifying the relative volume of the largest connected component in a superlevel set for a decreasing threshold. We propose a novel memory-distributed parallel algorithm to finely sample the percolation function. It is based on a parallel version of the union-find algorithm interleaved with a global synchronization step for each threshold sample. The efficiency of this algorithm stems from the fact that operations in-between threshold samples can be freely reordered, are mostly local and thus require no inter-process communication. Our algorithm is significantly faster than previous algorithms for this purpose, and is neither constrained by memory size nor number of compute nodes compared to the conceptually related algorithm for extracting augmented merge trees. This makes percolation analysis much more accessible in a large range of scenarios. We explore the scaling of our algorithm for different data sizes, number of samples and number of MPI processes. We demonstrate the utility of percolation analysis using large turbulent flow data sets.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 42-51, article id 8944383
Keywords [en]
Computing methodologies, Discrete mathematics, Distributed algorithms, Distributed computing methodologies, Graph theory, Mathematics of computing, Paths and connectivity problems
National Category
Computer and Information Sciences
Research subject
Computer Science; SRA - E-Science (SeRC)
Identifiers
URN: urn:nbn:se:kth:diva-267897DOI: 10.1109/LDAV48142.2019.8944383ISI: 000525833000006Scopus ID: 2-s2.0-85078123360OAI: oai:DiVA.org:kth-267897DiVA, id: diva2:1410816
Conference
9th IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2019; Vancouver; Canada; 21 October 2019
Funder
Swedish e‐Science Research CenterSwedish Foundation for Strategic Research, BD15-0082
Note

QC 20200302

Part of ISBN 9781728126050

Available from: 2020-03-02 Created: 2020-03-02 Last updated: 2024-10-21Bibliographically approved
In thesis
1. Coherent structures and control in wall-bounded turbulent flows
Open this publication in new window or tab >>Coherent structures and control in wall-bounded turbulent flows
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis is concerned with two distinct topics related to the study of wall-bounded turbulence: the connection between instantaneous three-dimensional coherent structures and mean-flow properties, and the development and analysis of pre-determined control techniques for adverse-pressure-gradient boundary layers.

We examined regions with intense velocity fluctuations in various flowcases. In turbulent ducts, we found that, on the one hand, the specific geometry of the domain has measurable effects on the shape and dimensions of these structures. On the other hand, however, their contribution to the mean secondary flow, which is the main distinguishing feature of turbulent ducts, is not particularly significant. Intense events contribute to the mean velocity in a similar way as in periodic channels, where the secondary flow is not present. Studying adverse- and zero-pressure-gradient turbulent boundary layers, we found that there are qualitative differences in how intense-fluctuation events affect the mean properties of these two flows. Our results suggest that coherent structures may help to explain history effects and development of the outer peak in wall-tangential fluctuations. An efficient algorithm for percolation analysis and an in-situ adaptor for the simulation code Nek5000 and the visualization software Paraview have also been developed as part of this effort.

We also created a new dataset including various combinations of uniform blowing and suction applied to a NACA4412 airfoil, employing high-fidelity numerical simulations and turbulence models. There are significant discrepancies between how the control interacts with turbulence under different pressure-gradient conditions, which illustrates the need of considering test cases as similar as possible to operative conditions in control studies. We also found that the most promising control configuration for a wide range of Reynolds numbers is uniform blowing applied to the airfoil pressure side. In particular, it reduces both pressure and skin-friction drag, resulting in higher aerodynamic efficiency and potential net-energy saving when the actuation cost is included.

Abstract [sv]

Denna avhandling handlar om två olika ämnen relaterade till studien av väggbunden turbulens: sambandet mellan momentana tredimensionella koherenta strukturer och medelflödesegenskaper och utveckling och analys av förutbestämda styrtekniker för negativ tryckgradientgräns skikten. 

Vi undersökte regioner med intensiva hastighetsfluktuationer i olika studiefall. I turbulenta kanaler fann vi att å ena sidan har domänens specifika geometri mätbara effekter på formen och dimensionerna hos dessa strukturer. Å andra sidan är deras bidrag till det genomsnittliga sekundära flödet, som är huvudfunktionen i turbulenta kanaler, inte särskilt signifikant. Intensiva händelser bidrar till medelhastigheten på ett liknande sätt som i periodiska kanalströmmar, där sekundärflödet inte finns. När vi studerade ogynnsamma och nolltryckgradient turbulenta gränsskikt, fann vi att det finns kvalitativa skillnader i hur intensiva fluktuationshändelser påverkar medelegenskaperna för dessa två flöden. Våra resultat tyder på att sammanhängande strukturer kan hjälpa till att förklara historiska effekter och utveckling av den yttre toppen i väggtangentiella fluktuationer. En effektiv algoritm för perkoleringsanalys och en adapter på plats för simuleringskoden Nek5000 och visualiseringsmjukvaran Paraview har också utvecklats som en del av detta arbete.

Vi skapade en ny dataset inklusive olika kombinationer av enhetlig blåsning och sugning applicerad på en NACA4412-flygplatta, med användning av högkvalitativa numeriska simuleringar och turbulensmodeller. Det finns signifikanta skillnader mellan hur kontrollen interagerar med turbulens under olika tryckgradientförhållanden, vilket illustrerar behovet av att betrakta testfall som liknar operativa förhållanden i kontrollstudier. Vi fann också att den mest lovande kontrollkonfigurationen för ett brett spektrum av Reynolds-nummer är enhetlig blåsning som appliceras på flygplattans trycksida. I synnerhet minskar det både tryck- och hudfriktionsdragningar, vilket resulterar i högre aerodynamisk effektivitet och potentiell nettoenergibesparing när manöverkostnaden beräknas.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2021. p. 95
Series
TRITA-SCI-FOU ; 2021:23
Keywords
Turbulent boundary layers, numerical simulations, coherent structures, predetermined flow control., Turbulenta gränsskikt, numeriska simuleringar, koherenta strukturer, förutbestämd flödeskontroll
National Category
Mechanical Engineering
Research subject
Engineering Mechanics
Identifiers
urn:nbn:se:kth:diva-295682 (URN)978-91-7873-917-2 (ISBN)
Public defence
2021-06-14, Live-streaming via Zoom: https://kth-se.zoom.us/j/66964086047, Stockholm, 10:30 (English)
Opponent
Supervisors
Funder
Knut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research, BD15-0082
Available from: 2021-05-25 Created: 2021-05-25 Last updated: 2022-07-08Bibliographically approved
2. Static Visualizations for Dynamic Hierarchies
Open this publication in new window or tab >>Static Visualizations for Dynamic Hierarchies
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Statiska visualiseringar för dynamiska hierarkier
Abstract [en]

Dynamic hierarchical data describes phenomena in a wide range of domains, from file management to demographics and business administration, as well as feature extraction results in spatial scientific data. As with all data, visualization is an integral step for gaining understanding about dynamic hierarchical data. In contrast to the visualization of individual static hierarchies, the visualization of dynamic hierarchies comes with additional challenges since many different aspects of a hierarchy may be subject to change.

This thesis presents novel visualizations, compact data structures, and layout optimizations for dynamic hierarchies where both topology and data may change. Particular focus is placed on the type of hierarchies that stem from features in scalar fields, namely merge trees and derived discretized feature hierarchies. We propose several visualization schemes that summarize dynamic hierarchies statically by creating stacked one-dimensional representations. The stacking dimension corresponds to the data’s dynamic-inducing variable which is usually time. In contrast to animating individual visualizations for each variable setting or time step, our static overviews of the entirety of the data facilitate comparison both between multiple data sets and across the stacking dimension. For the preservation of a user’s mental map, we utilize correspondences between parts of the hierarchy to optimize the one-dimensional representations toward stability in regards to the dynamic-inducing dimension. To evaluate our proposed methods, we apply them to several real-world data sets, compare them against existing approaches, and study how the resulting visualizations are affected by method parameters.

Abstract [sv]

Dynamisk hierarkisk data beskriver fenomen inom ett brett spektrum av domäner, från filhantering till demografi, företagsadministration och som ett resultat av sär- dragsextrahering ur rumslig vetenskapliga data. Som för all data är visualisering ett viktigt steg för att kunna förstå dynamisk hierarkisk data. Jämfört med visualisering av enskilda statiska hierarkier medför dynamiska hierarkier ytterligare utmaningar eftersom många olika aspekter av en hierarki kan förändras. 

Denna avhandling presenterar nya visualiseringar, kompakta datastrukturer och layout-optimeringar för dynamiska hierarkier där både topologi och data förändras. Avhandlingen har särskilt fokus på den typen av hierarkier som härrör från särdrag i skalära fält, d.v.s., merge trees och härledda diskretiserade särdragshierarkier. Vi föreslår flera visualiseringsscheman som sammanfattar dessa och allmänna dynamiska hierarkier statiskt genom att skapa staplade endimensionella represen- tationer. Staplingsdimensionen motsvarar den variablen som inducerar dynamiken av datan, vilket vanligtvis är tid. Istället för att animera individuella visualiseringar för varje variabelinställning eller tidssteg, underlättar våra översikterna av hela datan jämförelser mellan flera datamängder och över staplingsdimensionen. För att bevara en användares mentala karta använder vi korrespondenser mellan delar av hierarkin för att optimera de endimensionella representationerna mot stabilitet gentemot denna dimension. För att utvärdera våra föreslagna metoder tillämpar vi dem på flera verkliga datamängder, jämför dem med befintliga metoder och studerar hur de resulterande visualiseringarna påverkas av olika metodparametrar.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2022. p. 112
Series
TRITA-EECS-AVL ; 2022:74
Keywords
Dynamic hierarchies, Static visualization, Pixel-based visualization, Scalar data, Topology, Layout stability, Dynamiska hierarkier, Statisk visualisering, Pixelbaserad visualisering, Skalärdata, Topologi, Layout-stabilitet
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-321089 (URN)978-91-8040-419-8 (ISBN)
Public defence
2022-12-07, https://kth-se.zoom.us/j/69442479434, Visualization Studio VIC, floor 4, Lindstedtsvägen 5, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
Swedish e‐Science Research CenterSwedish Foundation for Strategic Research, BD15-0082
Note

QC 20221111

Available from: 2022-11-11 Created: 2022-11-11 Last updated: 2022-12-01Bibliographically approved

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Friederici, AnkeKöpp, WiebkeAtzori, MarcoVinuesa, RicardoSchlatter, PhilippWeinkauf, Tino

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