화학공학소재연구정보센터
검색결과 : 535건
No. Article
1 An experimental study of single unconventional biomass pellets: Ignition characteristics, combustion processes, and artificial neural network modeling
Bi HB, Lin QZ, Wang CX, Jiang XD, Jiang CL, Bao L
International Journal of Energy Research, 44(4), 2952, 2020
2 Medium, short and very short-term prognosis of load demand for the Greek Island of Tilos using artificial neural networks and human thermal comfort-discomfort biometeorological data
Moustris K, Kavadias KA, Zafirakis D, Kaldellis JK
Renewable Energy, 147, 100, 2020
3 Minimizing erosive wear through a CFD multi-objective optimization methodology for different operating points of a Francis turbine
Aponte RD, Teran LA, Grande JF, Coronado JJ, Ladino JA, Larrahondo FJ, Rodriguez SA
Renewable Energy, 145, 2217, 2020
4 Stochastic financial appraisal of offshore wind farms
Ioannou A, Angus A, Brennan F
Renewable Energy, 145, 1176, 2020
5 Reduced dynamic modeling approach for rectification columns based on compartmentalization and artificial neural networks
Schafer P, Caspari A, Kleinhans K, Mhamdi A, Mitsos A
AIChE Journal, 65(5), 2019
6 A neural network approach to the combined multi-objective optimization of the thermodynamic cycle and the radial inflow turbine for Organic Rankine cycle applications
Palagi L, Sciubba E, Tocci L
Applied Energy, 237, 210, 2019
7 A reinforcement learning framework for optimal operation and maintenance of power grids
Rocchetta R, Bellani L, Compare M, Zio E, Patelli E
Applied Energy, 241, 291, 2019
8 Pressure prediction of a spark ignition single cylinder engine using optimized extreme learning machine models
Mariani VC, Och SH, Coelho LD, Domingues E
Applied Energy, 249, 204, 2019
9 Experimental data and prediction of the physical and chemical properties of biodiesel
Arce PF, Guimaraes DHP, de Aguirre LR
Chemical Engineering Communications, 206(10), 1273, 2019
10 Building a data-driven reduced order model of a chemical vapor deposition process from low-fidelity CFD simulations
Gkinis PA, Koronaki ED, Skouteris A, Aviziotis IG, Boudouvis AG
Chemical Engineering Science, 199, 371, 2019