Temperature-induced corrosion of the TRIGA 2000 research reactor tank liner in long-term normal operation

• Thermal gradients, govern oxide growth on TRIGA 2000 tank liner. • Thickest oxide layer forms at mid-depth with highest temperature; thinnest near reactor core. • Pitting corrosion and bayerite formation observed across all tank liner zones. • Microhardness increases due to dense oxide-bayerite layer. • Long term immersion in normal operation of the TRIGA 2000 reactor study used SEM, XRD, and microhardness for corrosion assessment. Aluminum alloy AA-6061-T6 is widely used as the tank liner in nuclear reactors due to its corrosion resistance and low neutron absorption. However, prolonged exposure induces degradation, threatening structural integrity and operational safety. While prior studies have emphasized radiation and water chemistry in aluminum corrosion of reactor core components, corrosion phenomena outside the core, especially those influenced by local temperature gradients are remain insufficiently understood. This gap hinders optimized aging management strategies for critical components, particularly tank liners. This study presents a novel application of long-term corrosion coupon exposure in a low-power research reactor environment by immersing AA-6061-T6 coupons for nine years at varying depths in the TRIGA 2000 reactor pool, simulating real thermal condition. The work focuses on correlating oxide layer formation with operational temperature distribution, employing visual, mechanical, and microstructural analyses to characterize degradation mechanisms. We observed the thinnest oxide layer on the coupon closest to the reactor core, while the thickest formed in the middle zone. Pitting corrosion was prevalent across all zones, with bayerite (α-Al(OH)₃) dominating the surface. In conclusion, thermal gradients strongly govern oxide growth in the TRIGA tank liner. Future studies will integrate axial and radial coupon placement with neutron and gamma flux mapping to improve spatial resolution and enhance predictive aging models for reactor tank liner.