31 |
Removal efficiency optimization of Pb2+ in a nanofiltration process by MLP-ANN and RSM Emami MRS, Amiri MK, Zaferani SPG Korean Journal of Chemical Engineering, 38(2), 316, 2021 |
32 |
Prediction of gas holdup in various types of airlift reactors Choi KH Korean Journal of Chemical Engineering, 38(9), 1781, 2021 |
33 |
Deep-learning modeling and control optimization framework for intelligent thermal power plants: A practice on superheated steam temperature Wang Q, Pan L, Lee KY, Wu Z Korean Journal of Chemical Engineering, 38(10), 1983, 2021 |
34 |
Real-time life and degradation prediction of ceramic filter tube based on state-space model Liu L Korean Journal of Chemical Engineering, 38(10), 2122, 2021 |
35 |
Rigidly-mounted roll mill as breakage tester for characterizing fine particle breakage Bottcher AC, Thon C, Fragniere G, Chagas A, Schilde C, Kwade A Powder Technology, 383, 554, 2021 |
36 |
Image-based prediction of granular flow behaviors in a wedge-shaped hopper by combing DEM and deep learning methods Liao ZH, Yang YZ, Sun CF, Wu RQ, Duan ZH, Wang YY, Li XP, Xu J Powder Technology, 383, 159, 2021 |
37 |
Prediction of particle circulation rate in an internally circulating fluidized bed with a central draft tube Chen HW, Song YF, Shi Y, Yang X Powder Technology, 380, 497, 2021 |
38 |
Statistical investigation of structural and transport properties of densely-packed assemblies of overlapping spheres using the resistor network method Birkholz O, Neumann M, Schmidt V, Kamlah M Powder Technology, 378, 659, 2021 |
39 |
Assessing predictability of packing porosity and bulk density enhancements after dry coating of pharmaceutical powders Kunnath K, Chen L, Zheng K, Dave RN Powder Technology, 377, 709, 2021 |
40 |
Modeling the corrosion rate of carbon steel in carbonated mixtures of MDEA-based solutions using artificial neural network Li Q, Wang DX, Zhao MY, Yang MH, Tang JF, Zhou K Process Safety and Environmental Protection, 147, 300, 2021 |