A Smarter Bridge | MX3D

31 de October de 2017

Industrial & Infrastructure, Innovative Products, Products, Projects

MX3D is 3D printing a 12 meter long stainless steel pedestrian bridge, which will be in place and crossing one of Amsterdam’s canals in the old city center by late 2018. We have teamed up with a consortium of mathematicians, IoT specialists and e to develop a smart sensor network to monitor the bridge’s health in real time. A great example of data centric engineering.

The partners joining the MX3D project include: Autodesk, The Alan Turing Institute and the Amsterdam Institute for Advanced Metropolitan Solutions (AMS).

The team from The Alan Turing Institute is responsible for designing and installing a sensor network on the bridge. These sensors will collect structural measurements such as strain, displacement and vibration, and will measure environmental factors such as air quality and temperature, enabling engineers to measure the bridge’s health in real time and monitor how it changes over its lifespan. This data will also allow us to “teach” the bridge to understand what is happening on it, how many people are crossing it and how quickly.

The data from the sensors will be input into a ‘digital twin’ of the bridge, a living computer model that will reflect the physical bridge with growing accuracy in real time as the data comes in. The performance and behavior of the physical bridge can be tested against its digital twin, which will provide valuable insights to inform designs for future 3D printed metallic structures. It will also enable the current 3D bridge to be modified to suit any required changes in use, ensuring it is safe for pedestrians under all conditions.

Autodesk is supplying the cloud services that will power the bridge’s data collection and processing. Autodesk is also working with The Alan Turing Institute researchers to develop machine learning algorithms that will enable the bridge to interpret and to react intelligently to its environment. AMS will be implementing new ways to use, visualize and connect the bridge’s data to other sources of environmental data in the Metropolitan Area of Amsterdam.