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SoftFlow: Build a Physics Simulator While Mastering C++
From Hello World to Lattice Boltzmann in 20 Hands-On Chapters
SoftFlow simulates soft particles in microfluidic flow using two coupled methods:
- Lattice Boltzmann Method (LBM): A mesoscopic fluid solver on the D2Q9 lattice.
Instead of solving the Navier-Stokes equations directly, LBM tracks particle distribution
functions that collide and stream on a discrete grid.
- Immersed Boundary Method
(IBM): Represents deformable particles as Lagrangian membrane nodes immersed in the
Eulerian fluid. Forces are spread from membrane to fluid; velocities are interpolated from
fluid to membrane.
Don’t worry if these terms are unfamiliar — the book introduces them gradually, with
everyday analogies and step-by-step code.
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About
About the Book
Most C++ textbooks teach the language in isolation — sorting arrays, counting words,
building toy calculators. You learn the syntax, but not why it matters.
This book is different. Every concept — from cout to templates, from pointers to
multithreading — is taught through a single, real project: SoftFlow, a 2D simulator of
deformable particles flowing through microfluidic channels.
By the end, you will have built a working Lattice Boltzmann + Immersed Boundary
Method simulator from scratch. Along the way, you’ll learn modern C++17, computational
physics, and software engineering practices used in real research code.
Author
About the Author
Ram Chand
Dr. Ram Chand is a computational physicist, scientific programmer, and educator serving as Chairperson of the Department of Natural Sciences at The Begum Nusrat Bhutto Women University, Sukkur, Sindh, Pakistan.
He earned his PhD in Computational Physics, where his doctoral research centered on mesoscopic simulation of soft deformable particles in microfluidic channel flows using the Lattice Boltzmann Method coupled with the Immersed Boundary Method — the very physics that powers the SoftFlow simulator built throughout this book.
Dr. Chand is an expert in modern C++ and Python, with years of experience developing high-performance simulation codes for complex fluid systems. His technical repertoire spans object-oriented design, parallel computing with OpenMP, Python-C++ interoperability via pybind11, and Machine Learning applications in physics-informed modeling.
His research interests include:
- Lattice Boltzmann simulations of non-Newtonian and multiphase flows
- Immersed Boundary Methods for fluid-structure interaction
- Machine Learning for surrogate modeling in computational fluid dynamics
- High-performance scientific computing and code optimization
As an academic leader, Dr. Chand is committed to transforming how computational physics is taught in developing regions. He believes that project-based learning — writing real simulation code rather than toy examples — produces deeper understanding and stronger programmers. This book is a direct product of that philosophy.
Dr. Chand has authored multiple research publications in computational physics and actively mentors students in scientific computing, open-source development, and research methodology.
Contact: Department of Natural Sciences, The Begum Nusrat Bhutto Women University, Sukkur, Sindh, Pakistan
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