An Advanced Predictive MATLAB-Based Multi-Physics Framework for Thermal Cable Degradation Modeling and Comprehensive Aging Assessment of Low-Voltage Nuclear Cables with Nondestructive Diagnostics of EPDM Terminations

Abstract

Low-voltage cables in nuclear power plants are critical safety components that must operate reliably under prolonged thermal and environmental stress during extended service life. Progressive insulation degradation, particularly in ethylene propylene diene monomer (EPDM) terminations, can lead to electrical failure, unplanned outages, and safety risks. Conventional aging assessment methods primarily rely on empirical Arrhenius extrapolation or periodic threshold-based inspections, which often fail to capture spatially non-uniform degradation mechanisms or provide early predictive insights. This study proposes an advanced predictive MATLAB-based multi-physics framework for thermal cable degradation modeling and comprehensive aging assessment of low-voltage nuclear cables, with integrated nondestructive diagnostics targeting EPDM terminations. The proposed framework couples transient heat transfer modeling with thermo-oxidative degradation kinetics and diffusion-limited oxidation mechanisms to simulate spatial and temporal aging evolution under realistic loading conditions. Temperature-dependent reaction modeling is integrated with geometry-aware thermal field computation to capture localized hotspot formation and stress concentration effects in termination regions. A property evolution module translates physicochemical degradation into progressive variations in key electrical and mechanical parameters, including insulation resistance, dielectric loss tangent, relative permittivity, and elastic modulus. These parameter shifts are further linked to a nondestructive diagnostic layer that simulates measurable inspection signatures, enabling a quantitative correlation between degradation state and observable field indicators. Unlike conventional single-physics or purely empirical lifetime estimation approaches, the proposed framework establishes a closed predictive loop connecting thermal stress exposure, material-level degradation mechanisms, measurable nondestructive signatures, and health index–based prognostic assessment. A representative case study under steady-state and cyclic thermal loading demonstrates non-uniform aging acceleration in EPDM termination interfaces and highlights improved early-stage degradation sensitivity compared to traditional threshold-based monitoring strategies. Comparative evaluation against classical Arrhenius models and standalone thermal simulations indicates enhanced prediction stability, improved spatial resolution of degradation progression, and stronger mechanism-consistent interpretability. The modular MATLAB implementation ensures reproducibility, parameter adaptability, and extensibility for integration of additional stressors such as radiation, moisture ingress, and electrical overstress. The proposed digital multi-physics framework provides a robust predictive tool for condition-based maintenance planning, long-term safety validation, and intelligent asset management of nuclear power plant cable systems.