Services
First-Principles Modelling & Simulation
Mathematical, Chemical and Physical Models
Data is incredibly powerful and so when you use data-driven models, complete with pattern and trend prediction, you can go far when it comes to understanding your audience or your system. Having said that, data-driven models, as powerful as they may be, have their limitations and that is especially obvious when it comes to predicting behaviour far beyond the range of the data that is available. Extrapolating too far introduces a lot of uncertainty and can quite easily lead to incorrect predictions, with very wrong decisions being taken as a result.
So, what do we do in such cases? Many real-world processes can be modelled directly from first principles, such as laws of physics or complex logic. These types of models offer far greater flexibility enabling you to explore new operating conditions, diagnose complex behaviours and gain a deeper insight into how your system truly works.
.png)
Which way to go with depends on what you have or know. If you have lots of quality data, but not as much knowledge, then data-driven models are best to use. Alternatively, if the dataset is not as large, but you do know how your system works and can describe that using an equation or a set of equations, however complex, then first-principles models are best suited for you. And if you have both the data and the knowledge then you can go with either data-driven models of first-principles, or else get the best of both worlds and combine the two methods together.
-- Molecular Dynamics --
Our expertise, both in-house and through trusted collaborators, covers a wide range of advanced first-principles modelling techniques. These include:
-
Reaction Kinetics and Thermodynamic modelling
-
Molecular Dynamics (MD)
-
Process Modelling
-
Computational Fluid Dynamics (CFD)
-
Finite Element Analysis (FEA)
-
Discrete Element Modelling (DEM)
-
Discrete Event Simulation (DES)
These methods are not limited solely to science or engineering applications. In fact, we have successfully applied physical-modelling principles to economic and operational systems bringing clarity to environments where intuition and experience alone may fall short.
-- Output from a Reaction Kinetics and Thermodynamics Predictive Model --
We also have experience in building fast surrogate models by combining data science with first- principles modelling training machine-learning algorithms on Monte Carlo outputs from complex physics-based models, reducing prediction times from minutes or hours to near-instant. This is fundamental for speeding up decision-taking through instantaneous predictions.
In summary, we can support businesses and teams across any sector in building models. These can range from simple chemical reactions to highly complex multi-physics processes. Through equation-based modelling & simulation as well as a problem-solving focused mindset, our solutions are tailored to your needs.