| Prediction of SOx–NOx emission from a coal-fired CFB power plant with machine learning: Plant data learned by deep neural network and least square support vector machine D Adams, DH Oh, DW Kim, CH Lee, M Oh Journal of Cleaner Production 270, 122310, 2020 | 127 | 2020 |
| Deep reinforcement learning optimization framework for a power generation plant considering performance and environmental issues D Adams, DH Oh, DW Kim, CH Lee, M Oh Journal of Cleaner Production 291, 125915, 2021 | 28 | 2021 |
| Actor-critic reinforcement learning to estimate the optimal operating conditions of the hydrocracking process DH Oh, D Adams, ND Vo, DQ Gbadago, CH Lee, M Oh Computers & Chemical Engineering 149, 107280, 2021 | 25 | 2021 |
| Dynamic modeling and simulation of the combustion of aluminized solid propellant with HMX and GAP using moving boundary approach TA Vo, M Jung, D Adams, H Shim, H Kim, R Hwang, M Oh Combustion and Flame 213, 409-425, 2020 | 15 | 2020 |
| Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen … S Kim, Y Choi, J Park, D Adams, S Heo, JH Lee Renewable and Sustainable Energy Reviews 190, 114049, 2024 | 14 | 2024 |
| Techno-economic analysis for design and management of international green hydrogen supply chain under uncertainty: An integrated temporal planning approach S Kim, J Park, W Chung, D Adams, JH Lee Energy Conversion and Management 301, 118010, 2024 | 6 | 2024 |
| Multiscale modeling and integration of a combined cycle power plant and a two-tank thermal energy storage system with gPROMS and SimCentral JH Chang, GH Lee, D Adams, HW Ahn, JC Lee, M Oh Korean Journal of Chemical Engineering 38, 1333-1347, 2021 | 6 | 2021 |
| Software Platform for Computation Fluid Dynamics Simulation of Mixing and Crystallization in a Stirred Vessel DH Oh, RY Jeon, D Adams, WY Jung, HM Shim, CH Lee, KJ Kim Crystal Growth & Design 20 (2), 1172-1185, 2019 | 6 | 2019 |
| Neural Additive Network for Interpretable Inferential Sensor Design D Adams 한국화학공학회 2022 년도 봄 총회 및 학술대회, 2022 | | 2022 |
| Multivariate Dynamic Inferential Sensor Development for Multi-step Forecasting of Process Quality Variables D Adams 한국화학공학회 2021 년도 가을 총회 및 학술대회, 2021 | | 2021 |
| Dynamic Simulation of Nano-Aluminized Solid Propellant Combustion using Moving Boundary Approach TA Vo, G Lee, DQ Gbadago, D Adams, M Oh 한국추진공학회 학술대회논문집, 563-563, 2018 | | 2018 |
