Smooth pathways
Grace in every phase
Proven power in every case
Our Vision
At SoftPath, we develop cutting-edge software to revolutionize fluid dynamics simulations by reducing computational time and enhancing accuracy. Through innovative CFD technology developed in partnership with CEMEF, Mines Paris, we aim to cut computation time and power up to 100x. Our solutions push the boundaries of engineering, providing advanced tools that inspire technical excellence.
Innovations
Our project introduces several groundbreaking innovations:
- Advanced Anisotropic Adaptive Meshing: Enhances accuracy and reduces computational power by dynamically adjusting mesh.
- Multi-Scale Finite Element Method: Reduces power requirements while maintaining precision.
- Parallelized Solver Calculations: Optimizes computation time for faster results.
The SoftPath team's innovative solutions redefine fluid dynamics simulations, significantly reducing computational time and power consumption while maintaining high accuracy.
SoftPath helps you innovate
With the convergence of High Performance Computing and Data Science, discover new possibilities to improve your business.
Driving progress forward
Softpath is uniquely positioned to uncover and drive forward new applications across diverse industries.
Science Highlights
Discover the Science that makes SoftPath unique.
About the CFL Team
The High-Performance Computing and Fluid Mechanics (CFL) research group at CEMEF, Mines Paris, is dedicated to developing innovative methods and techniques to tackle a variety of engineering, physics, and life sciences challenges. Their work focuses on massively parallel numerical methods to effectively model physical processes and phenomena at different industrial scales. The team also employs experimental techniques to complement and validate their models.
Key research areas include computational mathematics and mechanics, mesh adaptation with error estimators, high-performance computing, and both experimental and computational fluid dynamics (CFD) using stabilized FEM and multi-scale variational methods. Their expertise spans:
- Complex and non-Newtonian fluids
- Free surfaces and multiphase flows
- Machine learning for fluid mechanics
- Phase change and conjugate heat transfer
- Turbulence and fluid-structure interaction
- Aerodynamics, wing engineering, and performance
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The CFL team's extensive research and innovative approaches make them a leading force in the field of fluid mechanics and computational engineering.
Advanced Anisotropic Adaptive Meshing
Anisotropic Mesh Elements are stretched along specific directions to better align with fields of interest, such as fluid flow, object surfaces, and temperature distributions.
Adaptive Mesh The mesh continuously adapts to evolving fields of interest throughout the simulation, ensuring optimal resolution where it is needed most.
Iterative Procedure This iterative approach ensures the mesh is fine-tuned to capture the smallest and most critical details of the objects being simulated.
Multi-Scale Finite Element Method
Reduced Element Count By utilizing fewer mesh elements, we achieve the same level of detail and accuracy, enhancing efficiency.
Multi-Scale Approach This method allows for detailed modeling at multiple scales, ensuring accurate representation of complex phenomena.
Enhanced Accuracy Despite the reduced element count, our method ensures that all critical features and interactions are accurately captured.
Parallelized Solver Calculations
Parallel Processing By leveraging multiple processors simultaneously, our solvers perform calculations more quickly than traditional methods.
Optimized Algorithms Our algorithms are specifically designed to maximize the efficiency of parallel processing, reducing overall computation time.
Scalability This approach is scalable, allowing it to handle large and complex simulations with ease, providing timely and accurate results.
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