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February 2017


Sebastian Desand

Intelligent algorithms and Automated Flow Prediction dramatically increase value output from CFD-engineers

CFD engineers play an important role in product design by conducting high quality simulations which can be used to optimise design. Their simulations can generate knowledge and insight which increase product performance and competitive advantage that will make the difference between mediocre and outstanding financial results. But to what extent does a CFD-engineers' de facto spend on activities that can be considered truly value-creating, like analysis of simulation results and drawing conclusions for optimisation of a design?

Discouragingly little it seems when we talk to experienced CFD engineers across different industries. While the share of time spent on value-creating activities naturally differs from one company to another, it is painfully clear that an overwhelming majority of the time is spent on non-value creating activities, like generating and refining the mesh, setting parameters and post-processing the result. Typically, less than 25% is spent on what CFD engineers perceive as value-creating activities.




But it does not have to be that way. By automating the process of flow simulations- the larger part of the non-value creating manual activities can be eliminated. We estimate that instead of spending 25% on analysis, close to 80% of the time spent on working with a simulation could be spent on analysing the results and collaborating with design engineers to optimise the design based on the results from the simulations.

To meet this need, Ingrid Cloud offers a cloud-based service (SaaS), providing customers with fully-automated flow simulations. Our innovation in Automated Flow Prediction, is the result of a spin-off from world-leading research conducted over the last decade by a team of researchers at KTH Royal Institute of Technology in Stockholm.


The method is based on a quantitative a posteriori error estimation, which means that the user prescribes what to compute, and then the mesh is automatically optimised to compute that quantity to a prescribed tolerance with minimal computational cost. The groundbreaking algorithms in our model are adaptive and parameter-free which enables an automated simulation process, as well as a reliable estimation of error margin.

The issue of increasing the level of CFD automation and simplifying the process of simulations is NOT a question of reducing costs. It is first and foremost about increasing the value generated by CFD, increasing the competitive advantage of the product and ultimately boosting shareholder value.

We believe that the capability of automated flow predictions not only increases the value of CFD engineers, but also the importance of CFD in the product development process as a whole. This should be reason enough for any CFD engineer to champion for automated simulations.

If you are curious about our groundbreaking solution: Automated Flow Predictions, you should definitely apply to our upcoming beta and have the chance to affect the functionalities and design of the user interface.