Prace 2020 Presentation V1.Pdf

Prof Fernando Pinho Department of Mechanical Engineering University of Porto

Brussels, 31 January 2020

Invitation for a talk at the EuroHPC Summit Week 2020 / PRACEdays20

Dear Prof Fernando Pinho,

It is my pleasure to inform you that your application for a presentation at the PRACE Scientific and Industrial Conference 2020 – PRACEdays20 – that will be held in Porto, Portugal from 23 to 27 March 2020, is accepted. PRACEdays20 will be part of the EuroHPC Summit Week 2020, and we are looking forward to including your presentation in the high-level programme.

As Chair of the Organisation and Programme Committee (OPC), I would like to draw your attention to some important details: Your slot will last 15 minutes, followed by 5 minutes for questions from the audience. Your presentation is scheduled for the Scientific Track Energy / Renewable Energy on 25 March 2020 from 14:30 to 18:00. Please register under following link: https://www.eiseverywhere.com/ehpcsw2020 You can find a list of hotels on the event website: https://events.prace- ri.eu/event/937/page/87-accommodation . We recommend booking a hotel room as soon as possible. Please note that we cannot reimburse travel and accommodation costs, and that accompanying persons are at your own expense.

We will announce your talk on our event website. The materials we received for the Call for Contributions (photo, short bio, title of the talk, abstract) will be published on the website too. Silke Lang ([email protected] ) will contact you to gather the necessary information, should anything be missing.

Yours sincerely,

Serge Bogaerts Managing Director of PRACE aisbl Chair of the EuroHPC Summit Week 2019 / PRACEdays19 Organisation and Programme Committee

PRACE | Partnership for Advanced Computing in Europe aisbl Rue du Trône 98, 1050 Brussels, Belgium BE 0826 890 059 www.prace-ri.eu Developing turbulence models for Large-eddy simulation of jet flows of viscoelastic fluids

S. Parvar1, C. B. da Silva2, F. T. Pinho1 1CEFT/FEUP, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal 2LAETA, IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

1 EuroHPC Summit Week 2020, 23 March 2020 to 27 March 2020, Porto, Portugal Drag Reduction

District heating cooling System

2 Turbulent Energy Orszag & Patterson 1972 Accuracy & Expensive

Turbulent viscoelastic Expensive ↑, moderate range, far Engineering

Osborne Reynolds, primarily approach Reynolds decomposition simple - cost

Limitation, unsteady, transient, separate, rotation, strong curvature Smagorinsky 60s, possess main portion, feature, (SGS) splitted low-pass filtering-

Model, cost DNS↓, SGS model – Important topic 3 Main role SGS model represent kinetic energy transfer

Richardson-Kolmogorov hypothesis

Energy Cascade: Mean, large, small, viscosity, Smallest scales, statistically isotropic universal, dissipate the kinetic energy received large scales

Describe interscale interaction well, main reason R. Reis, PhD thesis, Instituto Superior Técnico, 2011. 4 Thais (2010) et al. the first SGS model for temporal LES for FENE-P Channel Stable, reduce computational time Only active near, hard assess performance SGS, complicated to implement, Conformation Ohta (2014) et al, purely viscous non-Newtonian fluids Channel Effect of variable viscosity, an extended Smagorinsky Wang (2014) et al. used the SGS model of Thais, FENE-P at Taylor Re, FHIT

Li et al (2018), the idea of temporal SGS model of Thais Channel FENE-P : multiple relaxation times Masoudian (2016) et al. FENE-P - Channel A-priori analyze effect of the polymer additives on the SGS energy Ferreira (2016) et al. distortion similarity model (DSIM) HIT self-similarity of the polymer stretching terms, The global equilibrium of the trace Simple implement, acceptable computational cost

Both analyzing filtered governing: Identify negligible - SGS advection Determine terms require SGS closures - polymer stretching 5 The main objective Develop LES models for in-homogeneous & wall-free FENE-P Better assessment of the SGS model performance Planar jet Without facing, problem , presence of walls Investigate the effect of inhomogeneities

The starting point is implementing the DSIM

Proposed by Ferreira et al. The model may need some modification or

calibration to be implemented properly. 6 First step Filtered governing equations for FENE-P developing LES model ഥ� ′ � filtering ��ത� ��ത� ��ത� 1 ��ത �� ҧ = 0 + �ത� = − + − + governing equations ��

� � 1 �� Newtonian Solvent Stress (��) �� = 2�� = + 2 �� ′ ′ 1 ′ SGS Newtonian solvent stress (�� ) � − � � = − 2� � � = (� ∆)2 � �� 3 �� 2 � �� − 3 Polymer Stress (� ) �� = � � � − �(�)� �� = 2 and � � = 1 � � − ��

GS & SGS of the conformation tensor equation Why FENE-P? Main features of the ҧ ҧ �� ത� ��ത� 1 rheology of dilute polymer + �ത� = ��ҧ + ��ҧ − � �� − �� − �� + �� solutions memory effects, �� ҧ �� ത �� ത �� shear-thinning, �� = �� − �ത� �� = �� − ��ҧ + �� − ��ҧ �� bounded elastic stresses7 Fundamental hypothesis for developing LES closures for FENE-P fluid flow Self-similarity in inertial range H1 � �� ≈ � ��ҧ ��ҧ Sink term

H2 �� ≈ 0 SGS Polymer stretching terms Structurally Self-similar H3 �� = �� ∆෨= 2∆ ෫ ෪ ෫ ෪ When two different ��ത� ��ത� ෪ ��ത� ��ത� ෪ �� = ��ҧ − ��ҧ + ��ҧ − ��ҧ Near sized filters ��

Balance Polymer stretching rate �� 1 & relaxation H4 2 � = � � � − � �� Global equilibrium ҧ ҧ �� ത� 1 Trace conformation tensor + �ത� = 2 ��ҧ − � �� ҧ − �� − �� + �� ต�� proportional � � 8 � �� Elastic energy store polymer DSIM model

Statistically Steady fully developed turbulence

��ത� 1 2 ��ҧ − � ��ҧ ��ҧ − �� − �� = 0 ��

1 ��ത� � ��ҧ ��ҧ − �� − ��ҧ �� 2� �� = ෫ ෪ ��ത� ��ത� ෪ ��ҧ − ��ҧ ��

9 Simulations are performed by

CEFT FEUP, Porto, Portugal

Gesualdo Marconi Arquimedes Cineca, Bologna, Coppe/UFRJ, Italy Rio de Janeiro, Brazil

10 Girds Size : 512 ×512 ×128 for DNS U =0.091 1 Fluctuation = 0.1 Girds Size : 128× 160 × 32 for LES U2=1.091

4π λ×∆U Box height: 36 = h h = 0.349 Wi= Box height h

λ =0.4 Wi = 1.1 Re=3500 L = 100 , Bp=0.2, Htheta : 30

Statistical accumulated data from 160000 iterations H1 H2 H3 H4 H4

CEFT cluster of 64 cores (2.1 GHz Intel Xeon E5 CPUs)

A good performance in planar jets

LES simulations able to predict well the mean flow features

Reduce engineering computational cost and time

18 Acknowledgements Project PTDC/EMS-ENE/2390/2014, POCI-01-0145-FEDER-016669

Fundo Europeu de Desenvolvimento Regional, via COMPETE2020

Centro de Estudos de Fenómenos de Transporte through project UID/EMS/00532/2019.