lecture 32: Pretrained Model Inference

lecture 32: Pretrained Model Inference

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PINNs Using Physics-Nemo [Modulus ]

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Section 1: Introduction

lecture 1: Introduction

lecture 2: Course Structure

lecture 3: Deep Learning Theory

lecture 4: PINNs Theory

ref.txt

Section2: PINNs Solution for 1D Burgers Equation with Pytorch

Section-2 Files

lecture 5: Define the Neural Network2

lecture 6: Initial Conditions and Boundary Conditions2

lecture 7: Optimizer

lecture 8: Loss Function3

lecture 9: Train the Model

lecture 10: Results Evaluation

Section 3: 1D Wave Equation

Section-3 Files

lecture 11: What is the Wave Equation

lecture 12: Setting Up Google Colab

lecture 13: Define the Wave Equation Function

lecture 14: Define the Config File

lecture 15: Import Needed Libraries

lecture 16: Set Up the main RUN File

lecture 17: Define the B.C, Interior Points

lecture 18: Add Validator Functionality

lecture 19: Solve

lecture 20: Results Extraction

lecture 21: Results Post Processing

Nvidia-modulus To Physicsnemo

Section 4: Cavity Flow

Section-4 Files

lecture 22: Setting up env. in your personal computer

lecture 23: Cavity Flow Problem

lecture 24: Define the Config File

lecture 25: Import Needed Libraries

lecture 26: Set Up the main RUN File

lecture 27: Define the Navier-Stokes equation and DNN

lecture 28: Define the B.C, I.C, Interior Points

lecture 29: Solve

lecture 30: Results Extraction

lecture 31: Results Post Processing

lecture 32: Pretrained Model Inference

Section 5: 2D Heat Sink

Section-5 Files

lecture 33: 2D heat channel problem

lecture 34: Define the Config File

lecture 35: Import Needed Libraries

lecture 36: Set Up the main RUN File

lecture 37: Define the geometry

lecture 38: Define the Navier-Stokes equation and DNN

lecture 39: Define the B.C, Interior Constraints

lecture 40: Add Monitor

lecture 41: Solve

lecture 42: Results Extraction

lecture 43: Results Post Processing

Section 6: 2D Stress Analysis

Section-6 Files

lecture 44: 2D Stress Analysis Problem

lecture 45: Define the Config File

lecture 46: Import Needed Libraries

lecture 47: Define the DNN

lecture 48: Define the geometry - part a

lecture 49: Define the geometry - part b

lecture 50: Set Changing Parameters

lecture 51: Define the B.C, Interior Constraints

lecture 52: Case Inferencing

lecture 53: Solve4

lecture 54: Results Post Processing1