As a consultant in the area of Computational Fluid Dynamics, it is important to review the journey of the technology over last two decades. At Tridiagonal, we have been a part of this journey since 2006 and its fascinating to see the adoption of technology, its spread across industry verticals, use of high performance computing with public and private clouds, use of open source platforms, attempts to make technology reach in the hands of operators and designers and many such developments. This article is a small attempt to highlight the progress across different stages of evolution and extend it to predict how the technology will shape over the next few years.
Phase-1: Simple Geometry, Complex Physics (1998 - 2006)
- Prior to 1998, basic Navier-Stokes solvers were already in place.
- CFD evolved from academic codes to commercial platforms.
- Results were validated and CFD became useful for predicting fluid flow patterns.
- Aerospace and Automotive industries were primary adopters.
- Electronics, HVAC, Power, Oil & Gas, FMCG became early adopters.
- Engineers handled simplified geometries with complex physics.
Phase-2: Consolidation; Complex Geometry and Complex Physics (2007 - 2015)
- FLUENT was acquired by Ansys.
- Star-CD was acquired by Siemens.
- CFD became established as an independent technology adjacent to CAD platforms.
- Engineers gained confidence in simulation accuracy.
- Complex geometry and multiphysics simulations became mainstream.
- Advancements occurred in mesh generation, surface wrapping, automated meshing, and polyhedral cells.
- Industries expanded to Metals & Mining, Chemicals, Food, and Pharmaceuticals.
Key Technologies in Phase-2
- Multiphysics Models
- Fluid Structure Interaction (FSI)
- Chemical Reactions
- Combustion
- Automated Meshing
- Polyhedral Cells
Open Source Platforms
- OpenFOAM
- SU2
- Salome
- Code Saturn/Neptune
Phase-3: How soon can I get the results?
Industry demand shifted toward faster simulation turnaround. Trust in CFD technology became established across industries, and software providers focused on speed and workflow automation.
High Performance Computing (HPC)
- Large cell-count meshes became common.
- Parallel scalability improved.
- Simulations reached 50M to 100M cells.
- Combustion simulations at Tridiagonal regularly use 80M to 100M cells.
Automated Workflows
- Automation reduced manual errors.
- Automation improved turnaround time.
- Ansys and Siemens focused heavily on workflow automation.
Phase-4: The Future
Future CFD evolution will focus on speed, cloud platforms, and AI-driven simulation data handling.
Speed of Simulation
- GPU-based formulations will increase.
- LBM and SPH methods will gain adoption.
- Integration with structural calculations and DEM will improve realism.
Handling of Simulation Data (AI/ML)
- Simulation data will integrate with AI/ML systems.
- Data science will influence plant and operational decisions.
- Simulation-driven intelligence will align R&D and plant operations.
