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Data Assimilation

These days, technology is becoming so complex that many systems are built in a partnership of specialized companies. This has the obvious benefit of using the best possible knowledge and experience, but it also has pitfalls. Here are six rules, illustrated with our experiences in a recent project.

The launch of ChatGPT made the world aware that Machine Learning will fundamentally change the way we live and work. The field of computing and simulation will be no exception. But it’s not just ChatGPT: there are other innovations from machine learning that are bringing exciting changes for computing. In this blog, we’ll explore the potential of this new technology.

Models and sensor data are an indispensible combination. Sensor data is needed to validate models and the models are often necessary to understand and extrapolate the data. VORtech has been working a two very exciting projects in the past few months in which sensor data and models are combined in an innovative application.

The Summer school "Data Assimilation and its Applications in Oceanography, Hydrology, Risk & Safety and Reservoir Engineering" in Sibiu, Romania.

When I first heard the term Digital Twin, I was immediately fascinated. It opens up an entire new realm of simulation.

On the 4th National eScience Symposium 2016 there will be a standing table where OpenDA will be presented by the Netherlands eScience Center and VORtech.

Groundwater flow models require proper setting of parameters. Obtaining optimal settings based on measurement by using the OpenDA data-assimilation tool.