With always-on remote monitoring network
A study from Seoul National University of Science and Technology (SEOULTECH) evaluates how risk-based statistical modeling can predict cooling pipe safety in nuclear power plants, replacing worst-case assumptions with realistic data. Traditional nuclear designs plan around extreme, highly unlikely worst-case scenarios—such as a cooling pipe snapping entirely in half. The research team used probabilistic modeling to track how real-world variables like welding stress, material wear, and routine safety inspections affect pipe health over an 80-year operational span. Study details Research question: How can risk-based analysis help engineers evaluate the actual likelihood of nuclear pipe breaks to improve plant safety and maintenance? Key…
The company celebrated 150 years at the show, featuring eight new products and a series of technological solutions
SwarmLens and rp² launch AssureLens
The two applications demonstrate how high-speed, non-contact metrology can provide closed-loop process control while protecting materials and components
The first certification under ISO/PAS 8800 demonstrates the practical application of the emerging standard for the safe development of AI-based vehicle systems
Strengthening its automotive vision portfolio
Providing improved availability and faster access to certified electronic components
The company says established connector technologies can help UAV designers avoid the…
The device is intended to address the trade-off between current measurement accuracy…
Pilgangoora is the world’s largest sensor-based sorting plant
Sign in to your account