1 |
Deep learning-based surrogate modeling and optimization for microalgal biofuel production and photobioreactor design del Rio-Chanona EA, Wagner JL, Ali H, Fiorelli F, Zhang DD, Hellgardt K AIChE Journal, 65(3), 915, 2019 |
2 |
Overview of Surrogate Modeling in Chemical Process Engineering McBride K, Sundmacher K Chemie Ingenieur Technik, 91(3), 228, 2019 |
3 |
Computationally efficient model for energy demand prediction of electric city bus in varying operating conditions Vepsalainen J, Otto K, Lajunen A, Tammi K Energy, 169, 433, 2019 |
4 |
SUSCAPE: A framework for the optimal design of SUStainable ChemicAl ProcEsses incorporating data envelopment analysis Gonzalez-Garay A, Guillen-Gosalbez G Chemical Engineering Research & Design, 137, 246, 2018 |
5 |
Optimizing the heat transfer performance of the recovery boiler superheaters using simulated annealing, surrogate modeling, and Cheek computational fluid dynamics Maakala V, Jarvinen M, Vuorinen V Energy, 160, 361, 2018 |
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Strategies for efficient machine learning of surrogate drag models from three-dimensional mesoscale computations of shocked particulate flows Das P, Sen O, Choi KK, Jacobs G, Udaykumar HS International Journal of Multiphase Flow, 108, 51, 2018 |
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Torque and efficiency maximization for a wave energy harvesting turbine: an approach to modify multiple design variables Halder P, Samad A International Journal of Energy Research, 41(7), 1014, 2017 |
8 |
A computationally efficient simulation-based optimization method with region-wise surrogate modeling for stochastic inventory management of supply chains with general network structures Ye WH, You FQ Computers & Chemical Engineering, 87, 164, 2016 |
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A data-driven method to characterize turbulence-caused uncertainty in wind power generation Zhang J, Jain R, Hodge BM Energy, 112, 1139, 2016 |
10 |
A novel adaptive surrogate modeling-based algorithm for simultaneous optimization of sequential batch process scheduling and dynamic operations Shi HY, You FQ AIChE Journal, 61(12), 4191, 2015 |