Automated Hazard Assessment Through Hierarchical Semantic Scoring & Dynamic Simulation (ASHDS)

**Abstract:** Traditional hazard assessment methodologies rely heavily on manual review and expert judgment, leading to inconsistencies and delays. This paper introduces Automated Hazard Assessment Through Hierarchical Semantic Scoring & Dynamic Simulation (ASHDS), a novel framework leveraging multi-modal data ingestion, symbolic reasoning, and dynamic simulation to achieve accelerated and more consistent hazard identification and quantification. ASHDS autonomously parses technical documents (safety data sheets, operational manuals), extracts relevant information, resolves logical dependencies, and dynamically simulates potential accident scenarios to generate a comprehensive hazard profile. The system incorporates a hyper-scoring mechanism that prioritizes critical risks and enables data-driven decision-making for proactive mitigation strategies, promising a significant advancement in process safety management within the 위해성 평가 domain.