Pregled bibliografske jedinice broj: 1184846
Exergy analysis of a complex four-cylinder steam turbine
Exergy analysis of a complex four-cylinder steam turbine // XIX International scientific congress machines. technologies. materials - winter session - 2022 : proceedings / Popov, Georgi ; Dikova, Tsanka (ur.).
Sofija: Scientific technical union of mechanical engineering Industry - 4.0, 2022. str. 13-17 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1184846 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Exergy analysis of a complex four-cylinder steam
turbine
Autori
Mrzljak, Vedran ; Prpić-Oršić, Jasna ; Senčić, Tomislav ; Jelić, Maro
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
XIX International scientific congress machines. technologies. materials - winter session - 2022 : proceedings
/ Popov, Georgi ; Dikova, Tsanka - Sofija : Scientific technical union of mechanical engineering Industry - 4.0, 2022, 13-17
Skup
XIX International scientific congress machines. technologies. materials - winter session - 2022
Mjesto i datum
Borovec, Bugarska, 09.03.2022. - 12.03.2022
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
exergy analysis ; complex steam turbine ; turbine cylinders ; destruction ; efficiency
Sažetak
This paper presents an exergy analysis of a complex four-cylinder steam turbine, which operate in a coal-fired power plant. Analyzed steam turbine consists of high pressure single flow cylinder (HPC), intermediate pressure dual flow cylinder (IPC) and two low pressure dual flow cylinders (LPC1 and LPC2). The highest part of cumulative mechanical power (787.87 MW) is developed in IPC (389.85 MW) and HPC (254.67 MW), while both low pressure cylinders develop a small part of cumulative mechanical power (70.29 MW in LPC1 and 73.06 MW in LPC2). Cylinder exergy destruction (cylinder exergy power loss) continuously increases as the steam expands through the turbine. The lowest exergy destruction has HPC (13.07 MW), followed by the IPC (20.95 MW), while the highest exergy destructions are noted in low pressure cylinders (24.37 MW in LPC1 and 27.17 MW in LPC2). Cylinder exergy efficiency continuously decreases as the steam expands through the turbine. The highest exergy efficiency has HPC (95.12%), followed by the IPC (94.90%) and LPC1 (74.25%), while the lowest exergy efficiency of all cylinders is obtained in LPC2 (72.89%). Exergy efficiencies of LPC1 and LPC2 are much lower in comparison to other low pressure dual flow cylinders from comparable steam power plants. The whole observed steam turbine has exergy efficiency equal to 90.20%.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
IP-2018-01-3739 - Sustav potpore odlučivanju za zeleniju i sigurniju plovidbu brodova (DESSERT) (Prpić-Oršić, Jasna, HRZZ - 2018-01) ( CroRIS)
NadSve-Sveučilište u Rijeci-UNIRI_TEHNIC‐18‐18‐1146 - Nesigurnosti procjene brzine broda u pri realnim vremenskim uvjetima (Prpić-Oršić, Jasna, NadSve ) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-14 - Optimizacija dizalica topline i rashladnih sustava koji koriste radne tvari niskog utjecaja na globalno zatopljenje korištenjem numeričkih simulacija (Pavković, Branimir, NadSve - NATJEČAJ „UNIRI PROJEKTI“ Natječaj za dodjelu sredstava potpore znanstvenim istraživanjima na Sveučilištu u Rijeci za 2018. godinu - projekti iskusnih znanstvenika i umjetnika od 03. 09. 2018.) ( CroRIS)
InoUstZnVO-CIII-HR-0108-10 - Concurrent Product and Technology Development - Teaching, Research and Implementation of Joint Programs Oriented in Production and Industrial Engineering (Car, Zlatan, InoUstZnVO - CEEPUS) ( CroRIS)
--KK.01.2.2.03.0004 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan; Slavić, Nataša; Vilke, Siniša) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-275-1447 - Razvoj inteligentnog ekspertnog sustava za online diagnostiku raka mokračnog mjehura (Car, Zlatan, NadSve - UNIRI potpore) ( CroRIS)
Ostalo-CEI - 305.6019-20 - Use of regressive artificial intelligence (AI) and machine learning (ML) methods in modelling of COVID-19 spread (COVIDAi) (Car, Zlatan, Ostalo - CEI Extraordinary Call for Proposals 2020) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka,
Sveučilište u Dubrovniku
Profili:
Maro Jelić
(autor)
Jasna Prpić-Oršić
(autor)
Tomislav Senčić
(autor)
Vedran Mrzljak
(autor)