Skip to main content
USE CASE

Nuclear AI – Detection of nuclear material in containers using advanced artificial intelligence

Evaluation of the use of muon tomography for the detection of nuclear material in containers

Nuclear AI

GOAL

To develop a simulation software that replicates the interaction between muons and different materials and machine learning algorithms for computed tomography for the readings of muons.

TECHNOLOGIES

Machine Learning, Data analytics

ABOUT THE PROJECT

Collaboration in the European STAIRWAI programme

As validated AI experts and service providers within the European STAIRWAI programme, Logicmelt has collaborated with the company Digafer to develop an application for detecting nuclear material in containers using muon detectors. This technology is based on the fact that muons pass through any kind of matter, but interact differently with certain materials. By studying their behaviour, it is possible to analyse what materials are inside containers without having to open them.

Software development and Machine Learning algorithms

Logicmelt has collaborated with Digafer to study how different geometries and materials interact with muons. To do this, it has developed particle simulation software to replicate detector readings in various scenarios. Using this software, machine learning algorithms have been trained to estimate the density of the materials inside the containers, allowing the identification of potentially hazardous materials such as Uranium or Cesium.

This technology represents a significant advance in the development of a comprehensive application for the inspection of containers in ports, contributing to safer transport.

Utilizamos cookies propias y de terceros para fines analíticos y para mostrarte publicidad personalizada en base a un perfil elaborado a partir de tus hábitos de navegación (por ejemplo, páginas visitadas). Puedes obtener más información y configurar tus preferencias AQUÍ.                     
Privacidad