SKILLS
Adjoint methods
We develop innovative approaches for stochastic adjoint methods
System Engineering
We combine in-depth engineering insight with the most modern computational technologies
HPC and Cloud Computing
We have a wide experience on cloud and HPC systems for data storage and computation
Monte Carlo methods
We build new methodologies Monte Carlo analysis and Perturbation Theory
Multiphysics Modeling
We create FV and FEM tools for the analysis of the most challenging multi-physics applications
Probabilistic modelling
We use Bayesian Machine Learning for robust Uncertainty Quantification
Particle transport
We develop advanced photon and neutron transport algorithms
Reduced Order Modeling
Reduced Order Models drive us towards accuracy and computational efficiency
Software Development
We have large experience in the development of high-quality, low-maintenance software
SERVICES
Modeling and Simulation
We provide innovative, customized tools and services to model your multiphysic system or component, combining CFD, solid mechanics, heat transfer, particle transport, etc.
System Engineering
We combine our wide experience in system engineering with our knowledge in computational science to support the design and operation of complex engineering systems
Digital Twin Models
We support our customers in the creation of digital twins of their systems to set up testing and experimental campaigns, optimize operation, and accelerate innovation
Predictive modelling
We employ our skills in machine learning, data science, reduced order modeling, and stochastic modeling to provide our customers with cutting edge predictive models for various applications
TEAM
