The Evolution of SPH. J. J. Monaghan Monash University Australia

Similar documents
Numerical Simulations. Duncan Christie

Toy stars in one dimension

The effect of magnetic fields on the formation of circumstellar discs around young stars

Pressure corrected SPH for fluid animation

CHAPTER 4. Basics of Fluid Dynamics

Fluid Dynamics. Part 2. Massimo Ricotti. University of Maryland. Fluid Dynamics p.1/17

Three Dimensional Models of RR Lyrae Pulsation

Computational Astrophysics

WAVE-STRUCTURE INTERACTION USING SMOOTHED PARTICLE HYDRODYNAMICS

Smoothed Particle Hydrodynamics (SPH) 4. May 2012

Moving mesh cosmology: The hydrodynamics of galaxy formation

KELVIN-HELMHOLTZ INSTABILITY BY SPH

Binary star formation

Dynamics of Astrophysical Discs

Fluid Dynamics. Massimo Ricotti. University of Maryland. Fluid Dynamics p.1/14

NUMERICAL METHODS IN ASTROPHYSICS An Introduction

Game Physics. Game and Media Technology Master Program - Utrecht University. Dr. Nicolas Pronost

what scientist believe happened to form the universe, and it is called the Big Bang Theory.

Treecodes for Cosmology Thomas Quinn University of Washington N-Body Shop

Smooth Particle Hydrodynamic (SPH) Presented by: Omid Ghasemi Fare Nina Zabihi XU Zhao Miao Zhang Sheng Zhi EGEE 520

Simulation of Liquid Jet Breakup Process by Three-Dimensional Incompressible SPH Method

Dedalus: An Open-Source Spectral Magnetohydrodynamics Code

Accretion Disks I. High Energy Astrophysics: Accretion Disks I 1/60

Turbulent Magnetic Helicity Transport and the Rapid Growth of Large Scale Magnetic Fields

Ari Schjelderup David Schaffer PHYS /30/11 The Big Bang Theory

Soft Bodies. Good approximation for hard ones. approximation breaks when objects break, or deform. Generalization: soft (deformable) bodies

Dynamics of Galaxies: Basics. Frontiers in Numerical Gravitational Astrophysics July 3, 2008

Sink particle accretion test

arxiv: v3 [astro-ph] 2 Jun 2008

ASP2062 Introduction to Astrophysics

Advective and Diffusive Turbulent Mixing

High performance computing and numerical modeling

SPH Molecules - a model of granular materials

Constrained hyperbolic divergence cleaning in smoothed particle magnetohydrodynamics with variable cleaning speeds

Superbubble Feedback in Galaxy Formation

Cosmic Structure Formation on Supercomputers (and laptops)

SPH for simulating impacts and collisions

Brad Gibson Centre for Astrophysics & Supercomputing Swinburne University

Computing a null divergence velocity field. using smoothed particle hydrodynamics

Tests of Spurious Transport in Smoothed Particle Hydrodynamics

arxiv: v1 [astro-ph.co] 9 Dec 2009

MULTIGRID CALCULATIONS FOB. CASCADES. Antony Jameson and Feng Liu Princeton University, Princeton, NJ 08544

FISIKA KOMPUTASI (COMPUTATIONAL PHYSICS) Ishafit Program Studi Pendidikan Fisika Universitas Ahmad Dahlan

Simulating magnetic fields in structure formation

The Magnetorotational Instability

Towards Understanding Simulations of Galaxy Formation. Nigel Mitchell. On the Origin of Cores in Simulated Galaxy Clusters

The Hopf equation. The Hopf equation A toy model of fluid mechanics

Daniel Price Monash University Melbourne, Australia. Guillaume Laibe University of St Andrews, Scotland

arxiv:astro-ph/ v2 22 Nov 1996

Computational Astrophysics 1 Particle Mesh methods

Accretion disks. AGN-7:HR-2007 p. 1. AGN-7:HR-2007 p. 2

Particle-based Fluids

(Refer Slide Time: 01:11) So, in this particular module series we will focus on finite difference methods.

O. A Survey of Critical Experiments

Cosmic ray feedback in hydrodynamical simulations. simulations of galaxy and structure formation

Stellar Evolution: Outline

International Journal of Applied and Universal Research E-ISSN No: Volume III, Issue V, Sept-Oct Available online at:

Our Solar System: A Speck in the Milky Way

FLASH Code Tutorial. part III sink particles & feedback. Robi Banerjee Hamburger Sternwarte

Cosmic ray feedback in hydrodynamical simulations. simulations of galaxy and structure formation

SW103: Lecture 2. Magnetohydrodynamics and MHD models

Computational Astrophysics

Chapter 7. Basic Turbulence

Large Scale Structure

Smoothed Particles Hydrodynamics numerical simulations of droplets walking on viscous vibrating liquid

Prof. dr. A. Achterberg, Astronomical Dept., IMAPP, Radboud Universiteit

Godunov methods in GANDALF

Computational Methods in Plasma Physics

Contents. I Introduction 1. Preface. xiii

Effects of Forcing Scheme on the Flow and the Relative Motion of Inertial Particles in DNS of Isotropic Turbulence

Smooth Particle Applied Mechanics: The Method, with Three Example Problems

PHYS 643 Week 4: Compressible fluids Sound waves and shocks

Divergence-free interpolation of vector fields from point values exact B = 0 in numerical simulations

Fluid Mechanics Prof. T.I. Eldho Department of Civil Engineering Indian Institute of Technology, Bombay. Lecture - 17 Laminar and Turbulent flows

Gravitation. Adrian Ferent. This is a new quantum gravity theory which breaks the wall of Planck scale. Abstract

Spiral Density waves initiate star formation

Magnetic Effects Change Our View of the Heliosheath

Constrained hyperbolic divergence cleaning in smoothed particle magnetohydrodynamics with variable cleaning speeds

Detailed Study of a Turbulent multiphase multicomponent ISM

Gravitational heating, clumps, overheating. Yuval Birnboim (Harvard Smithsonian Center for Astrophysics) Avishai Dekel (Hebrew University)

The Effects of Radiative Transfer on Low-Mass Star Formation

Needs work : define boundary conditions and fluxes before, change slides Useful definitions and conservation equations

IMPLEMENTATION OF THE SMOOTHED PARTICLE HYDRODYNAMICS METHOD TO SOLVE PLASTIC DEFORMATION IN METALS

Abstracts of Powerpoint Talks - newmanlib.ibri.org - The Cosmos. Robert C. Newman

Applied Computational Fluid Dynamics. in Marine Engineering

11. SIMILARITY SCALING

Plasma Astrophysics Chapter 1: Basic Concepts of Plasma. Yosuke Mizuno Institute of Astronomy National Tsing-Hua University

Computational Fluid Dynamics Prof. Sreenivas Jayanti Department of Computer Science and Engineering Indian Institute of Technology, Madras

ASTRO 114 Lecture Okay. We re now gonna continue discussing and conclude discussing the entire

CSCI1950V Project 4 : Smoothed Particle Hydrodynamics

2 GOVERNING EQUATIONS

Stability of Stellar Filaments in Modified Gravity Speaker: Dr. Zeeshan Yousaf Assistant Professor Department of Mathematics University of the Punjab

Fluctuation dynamo amplified by intermittent shear bursts

Effects of Forcing Scheme on the Flow and the Relative Motion of Inertial Particles in DNS of Isotropic Turbulence

Discussion panel 1: Enforcing incompressibility in SPH

PLASMA ASTROPHYSICS. ElisaBete M. de Gouveia Dal Pino IAG-USP. NOTES: (references therein)

White dwarf dynamical interactions. Enrique García-Berro. Jornades de Recerca, Departament de Física

Set 3: Galaxy Evolution

Astro 1050 Wed. Apr. 5, 2017

Analysis of Jeans Instability of Partially-Ionized. Molecular Cloud under Influence of Radiative. Effect and Electron Inertia

Transcription:

The Evolution of SPH J. J. Monaghan Monash University Australia

planetary disks magnetic fields cosmology radiation star formation lava phase change dam break multiphase waves bodies in water fracture 1994 1977 fission binary stars SPH tree of life

clusters of processors GPU symplectic Tree code WCSPH link list Lagrangian h viscosity switch kernels interpolate SPH tree of wisdom

The aim in 1976 was to simulate star formation which occurred in a complicated way in complicated regions.

The only available techniques were finite difference and they were complicated for star formation problems. Bob Gingold and I decided to try a particle method.

First SPH paper by RAG and JJM evolved models to a static state. The code did not conserve momentum

A related paper by Leon Lucy discussed fission of stars. The algorithm did not conserve momentum. 300 particles used

RAG AND JJM fission of a rotating gas cloud using 80 SPH particles and equations based on a Lagrangian in 1978

Fission with 800 SPH particles in 1979 Higher resolution gives higher accuracy

But this was far removed from current astrophysical SPH calculations

How did we get from the low accuracy of 1979 to the high accuracy of 2015 for astrophysical problems?

Many of the SPH algorithms now used can be found by elegant methods that now seem obvious. But the way you find things out is to try many things for simple cases until the correct form is found. Then you often cover up the hard work.

Some of this work is in my notebooks

Here are some of the topics considered in the first notebook.

date 1976 Equ. of motion B smoothing f = 1/h**2

Implementing a boundary condition by a Lagrangian multiplier constraint v n =0 boundary condition X j v j n j j f 3/2 e f(x x j) 2 =0.

Lagrangian used by RAG and JJM in 1978 kinetic energy pressure energy gravitational energy kernel Why use a Lagrangian?

Software improvements 1. Improved kernels. 2. Improved rule for h. 3. Faster accessing of particles. 4. Finer control of dissipation e.g viscosity when simulating shocks. 5. Extended use of Lagrangians. 6. Methods to make Div(B) very small in MHD. Different people will have different favourites

Kernels

Gaussian kernel kernel 1. The gaussian kernel is continuous. 2. When <500 particles used the large range was not a problem. 3. The gravitational forces could be smoothed easily and consistently.

Spline kernels 1985 Finite domain

Wendland Kernels Wendland 1995 JJM 2005 Dehnen and Aly 2012 An example in two dimensions W (q) = 7 64 h 2 (2 q)4 (1 + 2q) q = r/h An example in three dimensions W (q) = 21 256 h 3 (2 q)4 (1 + 2q)

Super kernels Designed to remove higher order errors due to smoothing. They are corrupted by errors from approximating integrals by summation. 1979 W (q) = 1980 W (q) = 1 3/2 h e q 2 5 3 2 4 3/2 h e q 2 (1 3 2015 Hu + Adams q 2 3p q) 8 can be negative this repels because derivative does not vanish at q = 0

Combination of super and ordinary kernels W (q) = W s (q)+(1 )W o (q) The super kernels can be negative switch to ordinary near shocks switch to super otherwise The problem is how to make a good switch

Different kernels can be used for different processes. 1. Viscous terms. 2. Thermal terms. 3. Drag terms for dusty gas

An example. A kernel for the viscous term 1988 hmc X k (v j v k ) @W u@u One dimension if there are sinusoidal oscillations i! hc X j a(1 e ik(j k) ) @W u@u the continuum limit with a Gaussian kernel i!ca2 h (1 e K 2 /4 )! K 2 as K goes to zero

By choosing a super kernel W = 1 2 p 2e u2 p 2e u 2 /2 you get a dissipation term 1 e K2 /4 2! K 4 my notebook contains several pages of discussion of different kernels in 1D and 2D to reduce viscous effects. Nothing was published.

Drag terms for a dusty gas (Laibe and Price) Example W (q) / q 2 e q2 /h 2 Also used, but without success, by Joe Morris to remove the tensile instability

Flexibility The use of different kernels for different processes is equivalent to a finite difference scheme with different grids for different processes. This is very difficult to do so no one does it!

Calculating the gravitational field

Finding the gravitational field in the early days. r 2 =4 G substitute 3/2 X (r) = 1 h 2 b m b e (r r a) 2 /h 2 and integrate exactly.

These methods were superseded by 1. Finite difference methods (4th order) 2. Tree codes

Resolution length h Need to choose h proportional to a natural length scale. For astrophysics we thought the natural length scale came from the gravitational energy 1 h / grav energy Gravitational energy

h was later related to the average density h / 1 < > 1/d where X X e r2 ij /h2 = constant i j Therefore h was constant in space but varied with time.

The reason for this is that we didn t know how to take account a spatial variation in h. This has now been resolved for compressible flow by taking h d = constant then using a Lagrangian to get the equations of motion. Daniel Price: J. Comp. Phys. vol 231,(2010) J.J. Monaghan: Rep. Prog. Phys. vol 68, (2005) J. J. M. MNRAS 2002, Springel + Hernquist MNRAS 2002.

See the paper concerning h for astrophysical problems with magnetic fields Ben Lewis

Variable h is even necessary with incompressible fluids if they contain dust and other particulate matter

SPH simulation of dust and water Note the inhomogeneous SPH dust particles

Accessing particles 1. Direct summation & using symmetry 2. Link lists & Rank lists 3. Tree code

A key improvement came from Hardware which meant more particles. Date n 1977 40 1978 80 1983 1000 direct CDC and Vax 1986 12,700 summation computers 1997 93,000 link list Clusters of 2005 10 6 tree code processors 2015 10 6 10 10 2025 10 9 10 12 This is approximately Moore s Law

Using these various techniques Matthew Bate simulated star formation in detail.

Matthew Bate - Exeter SPH simulation of Stars forming in a large gas cloud

In astrophysics magnetic field produce important forces

SPH Magnetic field simulations The 8 year jump? Rag + jjm 1977 Phillips + jjm 1985 Price+ jjm 2004 Price + Tricco 2012 The crucial constraint r B =0 satisfied by introducing an extra equation

Springel et al. Cosmology 10 10 dark matter SPH particles galaxies forming

Gas and Dark matter 3 10 9 SPH particles Mon. Not. Roy. Astro. Soc. Schaye et al. 2015

SPH extended to problems involving water in 1994

The Volcanic eruption of Thera 1500 BC & its effect on the Minoans Cliff 200m high yachts in the Caldera deposits from pyroclastic flows 30 m deep 51

Pyroclastic flow at Montserrat T = 600 C steam

For marine scientists and engineers one aim was to simulate waves on the coast or ships in a storm.

Simulating the flow of water with and without solid bodies began in 1994, using the early astrophysical algorithms. A key point was to make the fluid weakly compressible. P = B 0 1

The first simulations were simple.

1994 2D dam break with 3000 SPH particles Wedge

Around 2005 they became more complex. See also the Web site for the company Next Limit specializing in special effects.

Casting of Aluminium Ingots from a fadewheel system CSIRO Paul Cleary, Mahesh Prakash Joseph Ha based on codes from JJM 500000 liquid particles boundaries with boundary particles 2001

Some new techniques were found such as moving with a different v note XSPH 1989 ˆv a = v a + X b m b ab (v b v a )W ab note dv dt = F dr dt = ˆv

Extended to turbulence SPH 2011 conservation Note L = X b m b 1 2 ˆv b v b u( b ) a Conserves circulation accurately and truncates the spectrum

another formulation 2013 adami hu adams correcting the acceleration using a constant background pressure ˆv a (t + dt) =v a (t)+dt dˆva dt 1 rp back a

The Future Speeding up the code 1.Hardware improvements: memory and cycle time and communication.

2. Possible Software improvements 1. Something like PIC with 2 sets of particles 2. Multi-set iteration Similar to Multi-grid for Heat conduction. 3. In link-list cells average properties.

PIC like scheme Calculate forces on the black ringed particles Map these forces to the other particles

Multi-set iteration Similar to Multi-grid for Heat conduction. Instead of grids use subsets of particles which have greater spacing and faster convergence.

Fine grid Next Coarse

The green denotes virtual particles

planetary disks magnetic fields radiation cosmology plasma general relativity high res star formation medical tissue biology earth quake waves boiling lava phase change bodies in water fracture star formation dam break 1994 1977 fission binary stars SPH tree of life grows and grows

There is much more that can be considered. I look forward to hearing about unexpected and useful ideas during the next few days. Thank you