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Research

Research Methodologies

At CIMNE, we leverage advanced methodologies in numerical methods and computational modelling to tackle pressing societal challenges. By integrating discretization techniques, data-driven models, and high-performance computing, we drive frontier research and innovation for a sustainable tomorrow.

Research

Research Methodologies

At CIMNE, we leverage advanced methodologies in numerical methods and computational modelling to tackle pressing societal challenges. By integrating discretization techniques, data-driven models, and high-performance computing, we drive frontier research and innovation for a sustainable tomorrow.

Discretization techniques

Research focused on challenges

Methods that transform continuous equations into discrete forms for numerical solutions in engineering. Discretization techniques approximate derivatives and integrals on grids or particles, enabling simulations via novel grid-based, grid-free, or unfitted approaches. This allows efficient analysis of complex systems.

  • Novel grid-based approaches
  • Particle and meshfree methods
  • Unfitted methods
  • Techniques for coupled problems
  • Error assessment and adaptivity
  • Geometry and simulation representation

Physical and mathematical models

Research focused on challenges
Frameworks that represent engineering phenomena using equations and principles. They integrate multiphysics constitutive relations and variational methods to simulate real-world behavior, supporting optimization and analysis of compound systems.

Data-driven models

Research focused on challenges

Approaches that leverage data to predict engineering outcomes. These include machine learning (ML), reduced order models (ROM), and big data to capture patterns, quantify uncertainty, and create digital twins for efficient system analysis and optimization.

  • Science based Machine Learning and Artificial Intelligence
  • Reduced-Order Modelling
  • Inverse methods
  • Big data management
  • Uncertainty Quantification
  • Digital twins

High-performance computational models

Research focused on challenges

Advanced systems for rapid, accurate engineering simulations. They harness optimized algorithms and parallel computing to solve complex numerical problems, enabling cutting-edge analysis with applications in real-world engineering settings.

  • Domain decomposition and pre-conditioning
  • Emerging architectures (e.g. Quantum computation)
  • New coding paradigms

Our research priorities

CIMNE's work is spreadheaded by local and international priorities and driven by significant societal challenges.


Discover our Research Priorities