| 1 |
The Potential of Hybrid Mechanistic/Data-Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns
Schafer P, Caspari A, Schweidtmann AM, Vaupel Y, Mhamdi A, Mitsos A
Chemie Ingenieur Technik, 92(12), 1910, 2020 |
| 2 |
Surrogate model uncertainty in wind turbine reliability assessment
Slot RMM, Sorensen JD, Sudret B, Svenningsen L, Thogersen ML
Renewable Energy, 151, 1150, 2020 |
| 3 |
Robust optimization of an organic Rankine cycle for geothermal application
Serafino A, Obert B, Verge L, Cinnella P
Renewable Energy, 161, 1120, 2020 |
| 4 |
Global optimization of distillation columns using explicit and implicit surrogate models
Kessler T, Kunde C, McBride K, Mertens N, Michaels D, Sundmacher K, Kienle A
Chemical Engineering Science, 197, 235, 2019 |
| 5 |
Application of reduced-order models based on PCA & Kriging for the development of digital twins of reacting flow applications
Aversano G, Bellemans A, Li ZY, Coussement A, Gicquel O, Parente A
Computers & Chemical Engineering, 121, 422, 2019 |
| 6 |
Surrogate modeling of phase equilibrium calculations using adaptive sampling
Nentwich C, Engell S
Computers & Chemical Engineering, 126, 204, 2019 |
| 7 |
Energy performance analysis of continuous processes using surrogate models
Beisheim B, Rahimi-Adli K, Kramer S, Engell S
Energy, 183, 776, 2019 |
| 8 |
Multi-fidelity optimization of blade thickness parameters for a horizontal axis tidal stream turbine
Kumar PM, Seo J, Seok W, Rhee SH, Samad A
Renewable Energy, 135, 277, 2019 |
| 9 |
An efficient MILP framework for integrating nonlinear process dynamics and control in optimal production scheduling calculations
Kelley MT, Pattison RC, Baldick R, Baldea M
Computers & Chemical Engineering, 110, 35, 2018 |
| 10 |
Advances in surrogate based modeling, feasibility analysis, and optimization: A review
Bhosekar A, Ierapetritou M
Computers & Chemical Engineering, 108, 250, 2018 |
