IEC TR 63039 — Probabilistic Risk Assessment of Nuclear Power Plants: Insights from Research

The safe operation of nuclear power plants (NPPs) depends not only on deterministic design-basis analysis but also on a comprehensive understanding of accident sequences, their probabilities, and their potential consequences. IEC TR 63039 provides a structured framework for applying probabilistic risk assessment (PRA) to nuclear power plants, synthesising insights from decades of international research. This technical report serves as a bridge between academic risk methodologies and practical plant-specific safety evaluations, offering engineers and regulators a common reference for identifying vulnerabilities and prioritising safety improvements.

Core Methodology and Analytical Framework

IEC TR 63039 defines a three-tier PRA framework covering Level 1 (core damage frequency assessment), Level 2 (containment performance and large early release frequency), and Level 3 (off-site consequences and societal risk). The report emphasises that all three levels should be integrated to provide a complete risk picture. Each level relies on event tree analysis for accident sequence modelling and fault tree analysis for system failure logic. The standard provides detailed guidance on data sources, including generic failure rate databases (e.g., IAEA TECDOC-478) and plant-specific operational experience.

One of the distinctive contributions of IEC TR 63039 is its treatment of dependent failures. Common-cause failures (CCF) — where a single event disables multiple redundant components — are identified as a dominant contributor to core damage frequency in most plants. The report recommends using the beta-factor model or the more detailed multiple Greek letter (MGL) model for quantifying CCF probabilities, with worked examples showing how these models are applied to emergency diesel generators and reactor protection systems.

Human Reliability Analysis and Plant-Specific Insights

Human actions play a critical role in both accident initiation and mitigation. IEC TR 63039 dedicates substantial attention to human reliability analysis (HRA), recommending the use of standardised HRA methods such as THERP (Technique for Human Error Rate Prediction) or SPAR-H (Standardised Plant Analysis Risk-Human Reliability Analysis). The report provides tables of nominal human error probabilities for typical operator actions — including diagnosis, manual valve manipulation, and control room decision-making — alongside guidance for modifying these probabilities based on performance-shaping factors such as stress level, training quality, and available time.

Beyond the methodological details, IEC TR 63039 presents several key insights derived from international PRA research. Notably, the report observes that station blackout (complete loss of AC power) and internal floods are frequently underestimated risk contributors in older plant designs. It also highlights the importance of considering shutdown conditions (low-power and shutdown states), which can account for a significant fraction of total plant risk despite the reactor being subcritical.

Engineering Design Insights and Practical Applications

From a design engineering perspective, IEC TR 63039 offers concrete recommendations for integrating PRA into the plant lifecycle. During the design phase, PRA can identify dominant risk contributors before construction begins, allowing designers to incorporate inherent safety features rather than relying on expensive retrofits. For operating plants, the report recommends periodic PRA updates (typically every 3–5 years) to reflect plant modifications, ageing effects, and new operational data.

The report also addresses the interface between PRA and deterministic safety analysis, noting that the two approaches are complementary rather than competing. Deterministic analysis establishes conservative safety margins, while PRA provides a realistic assessment of risk and identifies scenarios that deterministic methods may overlook. The integration of both approaches forms the basis of a risk-informed decision-making framework that is increasingly adopted by regulatory bodies worldwide.