Predictive models for engineering.
INDUSTRIES
ABOUT US
We investigate reality and control emergencies, solving problems all over the world.
Turin, 2007 — when everything started. Cantene was born from a vision: to put on the market the excellence of computational fluid dynamic modelling. We’re a team of engineers and mathematical analysts who are supported by an academic committee and build models to understand complexity. Always evolving, as a young, open-minded team, we’re driven by an inextinguishable passion for discovery. We’ve been managing risk for over a decade.
Cantene studies how complex systems such as tunnels, buildings, industrial processes and crowds work in order to anticipate their complications. We develop predictive models based on the study of numerical codes with advanced procedures to best support safety strategies. Our roots as a company are anchored in computational fluid dynamic analysis, which is crucial to analyze the behavior of highway and subway tunnels in normal and emergency conditions, and to design more efficient and reliable ventilation systems.
With a long experience in fire engineering and thermal sciences applied to ventilation and energy, we describe predictive models for fire scenarios inside buildings and optimize thermal processes in the chemical industry in order to maximize the production. Cantene deals with human beings: studying and simulating the dynamic of crowds is essential to guarantee the safety of people in public spaces during big events like concerts or parades.
PROJECTS
PRODUCTS
Cantene owns softwares to best design safety solutions and distributes licenses for tools that quickly simulate emergency scenarios and help you manage the unexpected. We use sophisticated interfaces to define the details of complex fire models (Pyrosim) and to simulate emergency egresses and evacuations (Pathfinder). We also provide analyses with an in-house tool (ARTU), that reproduces smoke propagation in galleries and evaluates the interferences among people and combustion products.