Latest Articles for Safety Engineering

New techniques enhance the verification of deep neural networks for safer applications.

This article examines how neutron radiation alters zirconium alloy properties critical for nuclear reactors.

MARVeLus bridges verification and implementation for safer cyber-physical systems.

Research on deuteron interactions with molybdenum is essential for nuclear energy safety.

Introducing a method for robots to navigate safely without detailed maps.

A tool to verify the safety of deep learning models.

Introducing a method for robots to navigate safely using control density functions.

Using machine learning to improve electric vehicle battery enclosures for safety and efficiency.

A new model enhances battery predictions for safe eVTOL aircraft operation.

CERN upgrades beam stoppers to boost safety and efficiency for high-energy particle beams.

Research focuses on making neural network control systems reliable and safe.

This study examines how passenger brain activity can improve safety in automated vehicles.

Combining learning and planning improves robot safety and efficiency in complex tasks.

New error bounds improve GPR's reliability in safety-sensitive fields.

A new method ensures stability in neural network controllers for critical applications.

A method to assess what states stochastic systems can reach over time.

A new method enhances event-triggered control for better resource efficiency.

A novel method enhances robot safety using visual data without complete information.

Explore Mean-Field Control Barrier Functions for safer swarm management.

Introducing a safety filtering framework for effective boundary control in dynamic systems.

Learn how ZOCBFs help robots and self-driving cars avoid dangers.

Discover how Rectified Control Barrier Functions enhance safety in complex control systems.

Learn how predictive control enhances robot safety in complex environments.

Discover advanced methods to keep robots safe in unpredictable environments.