Pregled bibliografske jedinice broj: 1157514
Fouling detection in industrial heat exchanger using number of transfer units method, neural network and nonlinear finite impulse response models
Fouling detection in industrial heat exchanger using number of transfer units method, neural network and nonlinear finite impulse response models // Heat transfer engineering, 43 (2022), 21; 1852-1866 doi:10.1080/01457632.2021.2016149 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1157514 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Fouling detection in industrial heat exchanger using number of transfer units method, neural network and nonlinear finite impulse response models
Autori
Ujević Andrijić, Željka ; Bolf, Nenad ; Rimac, Nikola ; Brzović, Adriana
Izvornik
Heat transfer engineering (0145-7632) 43
(2022), 21;
1852-1866
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
fouling detection ; neural network ; heat exchanger
Sažetak
Due to reduced energy efficiency and productivity loss caused by fouled heat exchangers in industrial plants there is an obvious need for detection of fouling formation. Based on continuously measured temperatures and flow rates collected from the refinery plant history database, a semi-empirical number of transfer units (NTU) model and neural network-based models are developed. In order to confirm the reliability of proposed fouling factor calculation, the entire procedure was performed by developing a dynamic nonlinear finite impulse response (NFIR) model. Developed models are intended for fouling detection for industrial shell and tube heat exchangers. The performance criteria of developed models together with residual monitoring indicate that not only neural networks but the NTU and NFIR models effectively detect fouling formation.
Izvorni jezik
Engleski
Znanstvena područja
Kemijsko inženjerstvo
POVEZANOST RADA
Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
Uključenost u ostale bibliografske baze podataka::
- CA Search (Chemical Abstracts)
