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Moving Particle Semi-implicit Method: A Meshfree Particle Method for Fluid Dynamics [Pehme köide]

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(Lecturer, Department of Systems Innovation, University of Tokyo, Japan), (Lecturer, Department of Systems Innovation, University of Tokyo, Japan), (Professor, The University of Tokyo, Tokyo, Japan), (Research Associate, Department of S)
  • Formaat: Paperback / softback, 306 pages, kõrgus x laius: 229x152 mm, kaal: 450 g
  • Ilmumisaeg: 02-Jun-2018
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128127791
  • ISBN-13: 9780128127797
Teised raamatud teemal:
Moving Particle Semi-implicit Method: A Meshfree Particle Method for Fluid DynamicsSuurem pilt
  • Formaat: Paperback / softback, 306 pages, kõrgus x laius: 229x152 mm, kaal: 450 g
  • Ilmumisaeg: 02-Jun-2018
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128127791
  • ISBN-13: 9780128127797
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128127797.html
Märksõnad:

Moving Particle Semi-implicit Method: A Meshfree Particle Method for Fluid Dynamics begins by familiarizing the reader with basic theory that supports their journey through sections on advanced MPH methods. The unique insights that this method provides include fluid-structure interaction, non-Newtonian flow, and cavitation, making it relevant to a wide range of applications in the mechanical, structural, and nuclear industries, and in bioengineering. Co-authored by the originator of the MPS method, this book is the most authoritative guide available. It will be of great value to students, academics and researchers in industry.

  • Presents the differences between MPH and SPH, helping readers choose between methods for different purposes
  • Provides pieces of computer code that readers can use in their own simulations
  • Includes the full, extended algorithms
  • Explores the use of MPS in a range of industries and applications, including practical advice
Preface ix
1 Introduction
1(24)
1.1 Concept of Particle Methods
1(10)
1.1.1 Lagrangian Description
2(1)
1.1.2 Meshless Discretization
3(2)
1.1.3 Continuum Mechanics
5(6)
1.2 MPS Method
11(9)
1.2.1 Weighted Difference
11(1)
1.2.2 Particle Interaction Models
12(4)
1.2.3 Semi-implicit Algorithm
16(2)
1.2.4 MPS and SPH
18(2)
1.3 Research History of Particle Methods
20(5)
References
23(2)
2 Fundamental of Fluid Simulation by the MPS Method
25(86)
2.1 The Elements of the MPS Method
26(7)
2.1.1 Setting the Initial Positions of Particles
28(1)
2.1.2 Setting Initial Velocities of Particles
29(1)
2.1.3 How to Move Particles
29(2)
2.1.4 How to Calculate Acceleration of Particles
31(2)
2.2 Basic Theory of the MPS Method
33(41)
2.2.1 Mass of a Particle
33(2)
2.2.2 Governing Equations
35(1)
2.2.2.1 The Navier---Stokes Equations
35(3)
2.2.2.2 Equation of Continuity
38(1)
2.2.2.3 Notation by Vectors
39(1)
2.2.3 Particle Number Density and Weight Function
40(2)
2.2.3.1 The Standard Particle Number Density n°
42(1)
2.2.3.2 Relationship Between Particle Number Density and Fluid Density
43(1)
2.2.3.3 Example of Calculation
44(1)
2.2.3.4 The Form of a Weight Function
45(1)
2.2.4 Approximation of Partial Differential Operators
45(1)
2.2.4.1 Gradient
46(1)
2.2.4.2 The Gradient Model of the MPS Method (Nabla Model)
46(1)
2.2.4.3 The Meaning of Each Parts of the Gradient Model
47(4)
2.2.4.4 Example of Gradient Calculation
51(2)
2.2.4.5 Laplacian Operator and Its Uses
53(1)
2.2.4.6 The Laplacian Model of the MPS Method
53(4)
2.2.5 Semi-implicit Method
57(1)
2.2.5.1 How to Calculate Pressure, and the Necessity of the Semi-implicit Method
57(2)
2.2.5.2 The Outline of the Semi-implicit Method in the MPS Method
59(2)
2.2.5.3 Details of the Semi-implicit Method of the MPS Method
61(7)
2.2.5.4 Derivation of Pressure Poison Equation of the MPS Method
68(2)
2.2.5.5 How to Calculate the Pressure Poisson Equation
70(3)
2.2.5.6 The Boundary Condition of Pressure
73(1)
2.2.5.7 The Boundary Condition of Velocity
74(1)
2.3 Outline of Simulation Programs
74(29)
2.3.1 Contents of Program
74(10)
2.3.2 How to Compile and Execute the Sample Programs
84(1)
2.3.3 How to Visualize the Simulation Result
85(1)
2.3.4 Functions of the Program
86(1)
2.3.4.1 Libraries and Declarations
86(2)
2.3.4.2 Main Function
88(1)
2.3.4.3 initializeParticlePositionAndVelocity_for 2dim() Function
88(2)
2.3.4.4 calculateNZeroAndLambda() Function
90(1)
2.3.4.5 weight() Function
90(1)
2.3.4.6 mainLoopOfSimulation() Function
91(2)
2.3.4.7 calculateGravity Function
93(1)
2.3.4.8 calculateViscosity Function
93(2)
2.3.4.9 moveParticle() Function
95(1)
2.3.4.10 calculatePressure() Function
95(1)
2.3.4.11 calculateNumberDensity() Function
96(1)
2.3.4.12 setBoundaryCondition() Function
97(1)
2.3.4.13 setSourceTerm() Function
98(1)
2.3.4.14 setMatrix() Function
98(1)
2.3.4.15 solveSimultaniousEquationsBy GaussianElimination() Function
99(1)
2.3.4.16 calculatePressureGradient() Function
100(1)
2.3.4.17 calculatePressure_forExplicitMPS() Function
101(1)
2.3.4.18 calculatePressureGradient_forExplicitMPS() Function
102(1)
2.4 Exercise of Simulation
103(1)
24.1 Exercises
103(1)
2.5 Hints of Exercises
104(1)
2.6 Frequently Asked Questions
105(6)
2.6.1 What Is the Best Effective Radius of the Interaction Zone?
105(1)
2.6.2 Why Do We Need to Arrange Dummy Wall Particles Behind Wall Particles?
105(1)
2.6.3 Particles Penetrated a Wall: What Is the Possible Reason?
106(1)
2.6.4 How Do We Set the Time Increment Δt?
106(1)
2.6.5 It Seems Simulation Diverged Because Particles Exploded: What Is the Reason?
107(1)
2.6.6 Fluid Was Compressed: What Is the Reason?
107(1)
2.6.7 How Can We Add a Function of Inlet or Outlet Boundary in a Simulation Program?
107(1)
2.6.8 What Is the Most Time-Consuming Part in an MPS Simulation?
108(1)
2.6.9 What Are the Drawbacks and the Strong Points of the Semi-implicit Method?
108(1)
References
108(3)
3 Extended Algorithms
111(44)
3.1 Compressible-incompressible Unified Algorithm
111(7)
3.2 Explicit Algorithm Using Pseudo-Compressibility
118(7)
3.3 Symplectic Scheme
125(9)
3.4 Arbitrary Lagrangian-Eulerian
134(6)
3.5 Rigid Body Model
140(6)
3.6 Structural Analysis
146(9)
References
150(3)
Further Reading
153(2)
4 Boundary Conditions
155(62)
4.1 Introduction
155(4)
4.2 Solid Wall
159(30)
4.2.1 Wall Particle Representation
162(6)
4.2.2 Mirror Particle Representation
168(8)
4.2.3 Distance Function---Based Polygon Representation
176(4)
4.2.4 Boundary Integral---Based Polygon Representation
180(9)
4.3 Free Surface
189(18)
4.3.1 Free-Surface Particle Detection
193(7)
4.3.2 Pressure Calculation
200(7)
4.4 Inlet and Outlet Boundary Modeling
207(10)
References
212(5)
5 Surface Tension Models in Particle Methods
217(16)
5.1 Surface Tension Calculation Using CSF Continuum Equation
218(5)
5.1.1 CSF-Based Model Proposed by Nomura et al. (2001)
218(4)
5.1.2 Other Surface Tension Models Based on CSF Equation
222(1)
5.2 Surface Tension Calculation Based on a Pairwise Potential
223(6)
5.2.1 Potential-Based Model Proposed by Kondo et al. (2007a,b)
224(3)
5.2.2 Further Improvement of the Potential-Based Approach
227(1)
5.2.3 Wettability Calculation in the Potential Model
227(2)
5.3 Applications of the Surface Tension Models Using the MPS Method
229(4)
References
231(2)
6 Advanced Techniques
233(48)
6.1 Liquid---Solid Phase Change Model
233(3)
6.2 Gas---Liquid Two-Phase Flow and Phase Change Model
236(6)
6.3 Turbulence
242(3)
6.4 Suppression of Pressure Fluctuations
245(2)
6.5 Higher-Order Schemes
247(3)
6.6 Parallel Computing
250(4)
6.7 Multiresolutions
254(5)
6.8 V&V and Applications
259(22)
6.8.1 Verification and Validation
259(1)
6.8.2 Application to Automobile Industry
260(5)
6.8.3 Application to Chemical Engineering
265(3)
6.8.4 Application to Metal Engineering
268(2)
6.8.5 Application to Biomechanics
270(3)
References
273(8)
Index 281
Professor at the Department of Systems Innovation, and Director of the Koshizuka Lab, at the University of Tokyo, Japan. He was credited with developing the particle semi-implicit method (MPS) in 1996. He has since co-authored 5 books on this topic, and many journal articles on topics across particle simulation, and physics based computer graphics. Graduation from the Department of Systems Innovation of the University of Tokyo in 2002, Ph.D. from the University of Tokyo in 2007, Researcher of the National Maritime Research Institute in 2007, Research Associate of the University of Tokyo in 2009, Lecturer in 2013, and Associate Professor in 2017. Graduation from the Department of Systems Innovation of the University of Tokyo in 2005, Ph.D. from the University of Tokyo in 2009, Researcher of the Central Research Institute of Electric Power Industry in 2010, Research Associate of the University of Tokyo in 2014, and Lecturer in 2016. Graduation from the Department of Mechanical Engineering and Materials Science of the Yokohama National University in 2012, Ph.D. from the University of Tokyo in 2016, and Research Associate of the University of Tokyo in 2016.