Abstract
Hydrogen is the leading candidate for achieving the goal of decarbonization and making countries energy-independent in the
long term. However, spreading hydrogen in different sectors faces various issues, including safety: its flammability
characteristics and the ability to permeate and embrittle most metallic materials raise concerns. Safety functions are of the
utmost importance in managing conditions that can be hazardous. Preventing an event or controlling or limiting its
consequences through safety barriers is possible. They also represent a means to increase a resilience, enabling
quicker reactions or preventive actions. The lack of them and their wrong installation and/or improper use can be crucial in
developing undesired events. This study aims to understand the role of safety barriers in several hydrogen-related undesired
events in the past. The available descriptions of past events can provide valuable information, but the number of records
makes manual data extraction challenging. First, a set of safety barriers relevant to hydrogen events is developed, extracting
information from the ARAMIS project deliverables. Subsequently, the HIAD 2.0 database is analyzed to find any connection
with the safety barriers dataset through text comparison, leading to new information mining.
Keywords: hydrogen safety, safety barriers, accident analysis, resilience, Natural Language Processing.
long term. However, spreading hydrogen in different sectors faces various issues, including safety: its flammability
characteristics and the ability to permeate and embrittle most metallic materials raise concerns. Safety functions are of the
utmost importance in managing conditions that can be hazardous. Preventing an event or controlling or limiting its
consequences through safety barriers is possible. They also represent a means to increase a resilience, enabling
quicker reactions or preventive actions. The lack of them and their wrong installation and/or improper use can be crucial in
developing undesired events. This study aims to understand the role of safety barriers in several hydrogen-related undesired
events in the past. The available descriptions of past events can provide valuable information, but the number of records
makes manual data extraction challenging. First, a set of safety barriers relevant to hydrogen events is developed, extracting
information from the ARAMIS project deliverables. Subsequently, the HIAD 2.0 database is analyzed to find any connection
with the safety barriers dataset through text comparison, leading to new information mining.
Keywords: hydrogen safety, safety barriers, accident analysis, resilience, Natural Language Processing.