Data Science and Engineering

Data Science and Engineering

27 February 2025

Data generation for computer vision

Creating high-quality computer vision datasets that accurately reflect real-world scenarios can be a challenge. To address this challenge, NLR has developed a virtual sandbox environment that allows us to generate realistic 3D objects from various angles. This environment also enables us to place objects in diverse settings, such as different weather conditions, ensuring that our datasets are robust and applicable to specific real-world use cases.

Data Science and Engineering

26 February 2025

Virtual testing

Virtual testing methods can be employed to reduce time, costs and risks associated with physical testing. This approach involves utilising modelling capabilities for metal and composite test articles in their test setup, allowing for the simulation of various testing scenarios before and during physical testing. By leveraging knowledge of testing procedures, analytical, numerical and experimental methods, the effects of defects, such as fibre waviness, on composite materials can be investigated. Furthermore, Non-Destructive Inspection (NDI) methods can be used to inspect test articles for manufacturing defects, providing valuable input for virtual testing. Additionally, optical 3D deformation measurement during physical tests enables correlation with virtual tests, fostering a collaborative environment for simulation, manufacturing and testing teams.

Data Science and Engineering

25 February 2025

Collaborative engineering

NLR has the expertise and capabilities to translate complex technical knowledge into seamless integrated engineering environments. By leveraging our expertise and state-of-the-art tools, including cutting-edge web and security technologies, we facilitate collaboration among multidisciplinary engineers and engineering teams located across different geographical locations. We develop integrated engineering environments for, e.g., engineer design analysis, optimisation studies, modelling & simulation, and virtual testing.

Data Science and Engineering

25 February 2025

Computational mechanics

NLR has extensive experience in virtual manufacturing and testing, utilizing modern finite element software such as ABAQUS to analyse composite and hybrid structures under various loading conditions, including quasi-static and dynamic loading, impact, and post-buckling analysis. We also have expertise in metal additive manufacturing, including distortion and thermal predictions, as well as vibration analysis and topology optimisation of aircraft parts.

Data Science and Engineering

25 February 2025

Big data

Data are available in ever increasing volume, variety and velocity. To optimise your processes and operations, and to access up-to-date information, it is essential to collect, integrate and analyse these data. NLR is the one-stop shop to support the entire data ‘chain’, from data-acquisition and advanced analysis to information visualisation and decision support. Our expertise in (big) data and aerospace enables you to turn data into intelligence and deliver practical solutions for your needs.

NLR X-Lab: frontrunner in augmented reality in MRO aerospace
Data Science and Engineering

05 April 2023

Balanced use of artificial intelligence

Technological development has always been extremely important to the armed forces. Its influence can be seen in weapons, sensor and platform systems, in soldiers’ equipment, in all forms of military actions and within the Defence Ministry’s own organisational operations. The role of artificial intelligence (AI) is increasing too.

Digital twin proces monitoring
Construction and Manufacturing

26 October 2022

R&D case: Digital Twins for automated composite manufacturing

The aerospace manufacturing and production industries are increasingly challenged to be more competitive, and do more with less. To be able to comply with higher production rates, affordability and constant quality, high levels of automation are required for current-day manufacturing processes. This results in more parts meaning more process data to control and keep track of while the number of operators at the production floor has not grown.