PINNs Using NVIDIA Modulus

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Dr.Mohammad Samara

9:07:48

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1. Introduction

1. Introduction.mp4

03:55

2. Course Structure.mp4

05:04

3. Installing Anaconda.mp4

05:46

4. Deep Learning Theory.mp4

11:32

5. PINNs Theory.mp4

08:30

2. Pytorch Basics

1.1 links.txt

1. Install PyTorch CUDA.mp4

04:29

2.1 basic 1 main.zip

2. PyTorch Tensors Basics.mp4

18:53

3.1 basic 2 main.zip

3. Tensors to NumPy arrays.mp4

08:20

4. Backpropagation Theory.mp4

16:59

5.1 basic bp main.zip

5. Backpropagation using PyTorch.mp4

05:54

3. PINNs Solution for 1D Burgers Equation with Pytorch

1.1 burgers 1d main.zip

1. Define the Neural Network.mp4

10:42

2.1 burgers 1d main.zip

2. Initial Conditions and Boundary Conditions.mp4

24:42

3.1 burgers 1d main.zip

3. Optimizer.mp4

06:31

4.1 burgers 1d main.zip

4. Loss Function.mp4

18:08

5.1 burgers 1d main.zip

5. Train the Model.mp4

12:06

6.1 burgers 1d main.zip

6. Results Evaluation.mp4

08:56

4. 1D Wave Equation

1.1 config main.zip

1.2 post processing 1dwave main.zip

1.3 wave 1d main.zip

1.4 wave eq main.zip

1.5 wave equation main.zip

1. What is the Wave Equation.mp4

09:48

2.1 config main.zip

2.2 post processing 1dwave main.zip

2.3 wave 1d main.zip

2.4 wave eq main.zip

2.5 wave equation main.zip

2. Setting Up Google Colab.mp4

05:08

3.1 config main.zip

3.2 post processing 1dwave main.zip

3.3 wave 1d main.zip

3.4 wave eq main.zip

3.5 wave equation main.zip

3. Define the Wave Equation Function.mp4

16:48

4.1 config main.zip

4.2 post processing 1dwave main.zip

4.3 wave 1d main.zip

4.4 wave eq main.zip

4.5 wave equation main.zip

4. Define the Config File.mp4

08:49

5.1 config main.zip

5.2 post processing 1dwave main.zip

5.3 wave 1d main.zip

5.4 wave eq main.zip

5.5 wave equation main.zip

5. Import Needed Libraries.mp4

11:13

6.1 config main.zip

6.2 post processing 1dwave main.zip

6.3 wave 1d main.zip

6.4 wave eq main.zip

6.5 wave equation main.zip

6. Set Up the main RUN File.mp4

14:10

7.1 config main.zip

7.2 post processing 1dwave main.zip

7.3 wave 1d main.zip

7.4 wave eq main.zip

7.5 wave equation main.zip

7. Define the B.C, I.C, Interior Points.mp4

11:41

8.1 config main.zip

8.2 post processing 1dwave main.zip

8.3 wave 1d main.zip

8.4 wave eq main.zip

8.5 wave equation main.zip

8. Add Validator Functionality.mp4

08:35

9.1 config main.zip

9.2 post processing 1dwave main.zip

9.3 wave 1d main.zip

9.4 wave eq main.zip

9.5 wave equation main.zip

9. Solve.mp4

16:09

10.1 config main.zip

10.2 post processing 1dwave main.zip

10.3 wave 1d main.zip

10.4 wave eq main.zip

10.5 wave equation main.zip

10. Results Extraction.mp4

08:54

11.1 config main.zip

11.2 post processing 1dwave main.zip

11.3 wave 1d main.zip

11.4 wave eq main.zip

11.5 wave equation main.zip

11. Results Post Processing.mp4

18:16

5. Cavity Flow

1.1 cavity main.zip

1.2 cavity post main.zip

1.3 config.zip

1.4 output main.csv

1. Setting up env. in your personal computer.mp4

08:05

2.1 cavity main.zip

2.2 cavity post main.zip

2.3 config.zip

2.4 output main.csv

2. Cavity Flow Problem.mp4

04:07

3.1 cavity main.zip

3.2 cavity post main.zip

3.3 config.zip

3.4 output main.csv

3. Define the Config File.mp4

07:11

4.1 cavity main.zip

4.2 cavity post main.zip

4.3 config.zip

4.4 output main.csv

4. Import Needed Libraries.mp4

10:07

5.1 cavity main.zip

5.2 cavity post main.zip

5.3 config.zip

5.4 output main.csv

5. Set Up the main RUN File.mp4

03:56

6.1 cavity main.zip

6.2 cavity post main.zip

6.3 config.zip

6.4 output main.csv

6. Define the Navier-Stokes equation and DNN.mp4

06:41

7.1 cavity main.zip

7.2 cavity post main.zip

7.3 config.zip

7.4 output main.csv

7. Define the B.C, I.C, Interior Points.mp4

16:46

8.1 cavity main.zip

8.2 cavity post main.zip

8.3 config.zip

8.4 output main.csv

8. Solve.mp4

11:47

9.1 cavity main.zip

9.2 cavity post main.zip

9.3 config.zip

9.4 output main.csv

9. Results Extraction.mp4

03:30

10.1 cavity main.zip

10.2 cavity post main.zip

10.3 config.zip

10.4 output main.csv

10. Results Post Processing.mp4

13:45

11.1 cavity main.zip

11.2 cavity post main inf.zip

11.3 config.zip

11.4 inf data.zip

11. Pretrained Model Inference.mp4

31:16

6. 2D Heat Sink

1.1 config.zip

1.2 flow out.csv

1.3 force x.csv

1.4 force y.csv

1.5 heat out.csv

1.6 heat sink main.zip

1. 2d heat channel problem.mp4

02:09

2.1 config.zip

2.2 heat sink main.zip

2. Define the Config File.mp4

10:50

3.1 config.zip

3.2 heat sink main.zip

3. Import Needed Libraries.mp4

20:58

4.1 config.zip

4.2 heat sink main.zip

4. Set Up the main RUN File.mp4

04:38

5.1 config.zip

5.2 heat sink main.zip

5. Define the geometry.mp4

15:13

6.1 config.zip

6.2 heat sink main.zip

6. Define the Navier-Stokes equation and DNN.mp4

16:02

7.1 config.zip

7.2 heat sink main.zip

7. Define the B.C, I.C, Interior Points.mp4

28:49

8.1 config.zip

8.2 heat sink main.zip

8. Add Monitor.mp4

04:15

9.1 config.zip

9.2 heat sink main.zip

9. Solve.mp4

13:30

10.1 config.zip

10.2 config.zip

10.3 flow out.csv

10.4 force x.csv

10.5 force y.csv

10.6 heat out.csv

10. Results Extraction.mp4

08:22

11.1 config.zip

11.2 flow out.csv

11.3 flow out.csv

11.4 force x.csv

11.5 force y.csv

11.6 heat sink main.zip

11. Results Post Processing.mp4

05:53

Description

Easy Simulations with AI

What You'll Learn?

Build PINNs based pdes solver.
Understand the Theory behind PINNs PDEs solvers.
Build models using NVIDIA Modulus
Deploy NVIDIA Modulus useing GoogleColab and your own NVIDIA GPU

Who is this for?

Engineers and Programmers whom want to Learn PINNs

learn NVIDIA Modulus

What You Need to Know?

High School Math

Basic Python knowledge

More details

Description
Description
This is a introductory course that will prepare you to work with Physics-Informed Neural Networks (PINNs) using NVIDIA Modulus. We will cover the fundamentals of Solving partial differential equations (PDEs) using Physics-Informed Neural Networks (PINNs) from its basics and March towards solving PINNs with Nvidia modulus.

What skills will you Learn:
In this course, you will learn the following skills:
Understand the Math behind solving partial differential equations (PDEs) with PINNs.
Write and build Machine Learning Algorithms to solve PINNs using Pytorch.
Write and build Machine Learning Algorithms to solve PINNs using Nvidia Modulus.
Postprocess the results.
Use opensource libraries.
Define your own PDEs to solve them or use built in equations (such as the N.S equations in Nvidia Modulus).

We will cover:
How to deploy Nvidia Modulus on your own computer GPU and in Google Collab.
Physics-Informed Neural Networks (PINNs) Solution for 1D Burgers Equation using pytorch.
Physics-Informed Neural Networks (PINNs) Solution forÂ 1D wave Equation using Nvidia modulus.
Physics-Informed Neural Networks (PINNs) Solution forÂ cavity flow problem using Nvidia modulus.
Physics-Informed Neural Networks (PINNs) Solution forÂ 2D heat sink flow problem using Nvidia modulus.
If you do not have prior experience in Machine Learning or Computational Engineering, that's no problem. This course is complete and concise, covering the fundamentals of Machine Learning/ Physics-Informed Neural Networks (PINNs). Let's enjoy Learning Nvidia Modulus together.
Who this course is for:
Engineers and Programmers whom want to Learn PINNs
learn NVIDIA Modulus

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Neural Networks

Dr.Mohammad Samara

Instructor's Courses

11 Years experience in Computation Models building, since 7 year I am mainly focused on the use of Data to build machine learning based models, to solve practical Industry problems such as data analysis, Value prediction, performance classification (abnormality detection), and applying Machine Learning to machine vision problems as well as system control and behavior mapping via Reinforcement learning using data collected from the testing and simulation.I Have a Phd and masters From the University of Tokyo, and worked in several Japanese and International companies, currently I am working in Panasonic as a Data Science/Machine Learning Expert (Job Rank: Chief Engineer).I am absolutely passionate about Data Science use in Engineering companies and I am looking forward to sharing my passion and knowledge with you!

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