🚀 AI in CFD 2026 – Part 3: Physics-Informed Neural Networks (PINNs) & Neural Operators

Physics-aware AI is redefining the future of simulation engineering.

This handbook provides a practical engineering-focused introduction to Physics-Informed Neural Networks (PINNs), Neural Operators, Fourier Neural Operators (FNOs), DeepONet, and next-generation simulation intelligence workflows.

📘 What You'll Learn

✅ Evolution from Classical CFD to Physics-Aware AI

✅ Physics-Informed Neural Networks (PINNs)

✅ Governing Equations, Boundary Conditions & Physics Loss Functions

✅ PINN Workflows for CFD, Heat Transfer & Engineering Applications

✅ Dataset Engineering & Validation Strategies

✅ Neural Operators & Fourier Neural Operators (FNOs)

✅ DeepONet & Operator Learning

✅ Industrial Case Studies & Engineering Deployment

✅ Hardware, GPU & Software Stack

✅ Career Roadmap for AI-Driven Simulation Engineers

👨‍💻 Ideal For

• CFD Engineers

• CAE Professionals

• Mechanical Engineers

• Aerospace Engineers

• Researchers & PhD Aspirants

• M.Tech & Engineering Students

• Engineers exploring AI for Simulation

📄 Format: PDF Handbook

🏷️ Launch Price: ₹999

Published by PRISM – Future Engineering Systems Platform

Simulation • Automation • Artificial Intelligence • Digital Twins