4 citations · 7 across the 3 of their papers we have counts for
3 papers
Efficient machine-learning surrogates for large-scale geological carbon and energy storage
Teeratorn Kadeethum, Stephen J. Verzi, Hongkyu Yoon
Geological carbon and energy storage are pivotal for achieving net-zero carbon emissions and addressing climate change. However, they face uncertainties due to geological factors a…
Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer
Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi +2
Data-driven modeling can suffer from a constant demand for data, leading to reduced accuracy and impractical for engineering applications due to the high cost and scarcity of infor…
Data-scarce surrogate modeling of shock-induced pore collapse process
Siu Wun Cheung, Youngsoo Choi, H. Keo Springer +1
Understanding the mechanisms of shock-induced pore collapse is of great interest in various disciplines in sciences and engineering, including materials science, biological science…