Bayesian Statistical Modeling of Corrosion Depth Evolution in Automotive Sheet-Metal Components Using Field-Return Data

Atsushi Tokunaga (SUBARU)

Due to the limited sample size and big variances in corrosion data from field-recovered components, some adjustments are needed for regression analysis of corrosion amount over time challenging. This study proposes a Bayesian statistical method to estimate statistically reasonable time evolution of corrosion amount and to accurately estimate the upper tail of the probability distribution. An extended approach incorporating automotive sales plans is also introduced.

Evaluation of Corrosion Resistance of Aluminum Components by Low-Temperature Sealing

Shintaro Ono･Haruhiko Murakami･Masahiro Fujita (Suzuki Motor)

Since outboard motor engines use seawater for cooling, high corrosion resistance is required for cooling channels with complex geometries. In this study, we developed a new surface treatment technology that combines an anodization process with low geometry dependency and a novel sealing process that achieves both heat and corrosion resistance at low temperatures and in a short time. In this paper, we report the performance evaluation results of this technology and demonstrate its effectiveness.

Mechanistic analysis of degradation phenomena considering electrode–electrolyte interfaces

Kazuhiro Sakuramoto･Keisuke Shirai (Toyota Industries)

At electrode–electrolyte interfaces that control battery performance and lifetime, complex phenomena such as electric double layers occur, making experiments and conventional simulations difficult. This study uses simulations to analyze interfacial structures and demonstrates applications to Al-related corrosion phenomena.