
VORtech Blog

2017-11-23
Mathematics in software
Simulation of the world around us by numerical computation has improved a lot in the past decades. Together with Johan Dijkzeul we will look back at this period.
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2017-10-27
Woudschoten Conference: Highlight for Applied Mathematicians
The forty-second Woudschoten Conference was held at the Woudschoten Conference Centre, Zeist, The Netherlands from 4-6 October 2017.
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2017-10-13
Models and sensor data: a powerful combination
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.
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2017-08-11
Summer School: Data Assimilation
The Summer school "Data Assimilation and its Applications in Oceanography, Hydrology, Risk & Safety and Reservoir Engineering" in Sibiu, Romania.
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2017-06-02
The next step in solving the wave equation efficiently
The propagation of waves through a medium is described by the famous wave equation. This is a partial differential equation that is not easy to solve. The time-independent form of the wave equation is called the Helmholtz equation.
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2017-02-14
Meetup Data Science in Industry
On Thursday February 23, 2017, VORtech hosted our first Meetup on Data Science: "Data Science in Industry"
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2017-02-02
Study Group Mathematics with Industry 2017
This year the Study Group Mathematics with Industry took place in Amsterdam, from January 23 till 27. Bas van βt Hof and Jok Tang, two of VORtechβs mathematical consultants, attended the SWI this year.
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2017-01-12
Digital Twins in Asset Management
When I first heard the term Digital Twin, I was immediately fascinated. It opens up an entire new realm of simulation.
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2016-07-19
10 Rules for Scientific Software Engineering
In the 20 years that VORtech has been in the business of scientific software engineering, we've seen many different codes and witnessed many different development processes.
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2016-06-30
Big Data MBA
What if you are, say, an engineering company with loads of experience in building complex installations but without any data science background. Where do you start?
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