Sang-Bum Chi

Korea Institute of Ocean Science and Technology

Papers

Total Citations

H-Index

About

Sang-Bum Chi is a leading researcher in reliability-based design optimization (RBDO) and deep-sea mining robotics, with a focus on enhancing the performance and safety of autonomous underwater systems. His most influential work, a 2019 study on optimizing a pick-up device for a manganese nodule pilot mining robot using the Coandă effect, has garnered 51 citations, establishing a foundational approach for integrating fluid dynamics principles into robust mechanical design. Chi’s contributions extend to developing advanced statistical methods for handling bivariate type I interval multiply censored data, enabling more accurate identification of marginal and joint cumulative distribution functions in RBDO frameworks—a critical advancement for systems operating under extreme marine conditions. His 2021 paper on this topic, with 11 citations, further demonstrates his expertise in managing complex, censored data sets to improve design reliability. Chi’s work directly supports the sustainable extraction of deep-sea minerals, addressing challenges in structural integrity and operational efficiency. His research is pivotal for engineers and scientists developing resilient robotic systems for harsh environments, combining theoretical rigor with practical applications in offshore and mining technologies.