This paper presents a mechanistic model for predicting the pressure gradient and other relevant flow characteristics during annular two-phase flow, by introducing a novel physical interpretation of the enhancement of the friction factor at the vapor–liquid interface, as a function of the liquid to vapor core inertia forces ratio. This interpretation is demonstrated to be consistent with literature relating the interfacial friction factor to the equivalent sand roughness. An experimental database, consisting of 6377 annular flow data points, has been used to enlarge the range of operating conditions with mass velocities from 99 to 2000 kg m-2s−1, tube diameters from 0.5 to 14.0 mm, reduced pressures from 0.0363 to 0.6896 and frictional pressure drop values from 0.3 to 1332 kPa/m. The proposed method is able to predict pressure gradients with a mean absolute percentage error of 18 % and 83 % of data points falling within a ± 30 % error range. The method allows also the calculation of the void fraction with a good agreement with the Rouhani-Axelsson correlation.

A mechanistic predictive model for pressure drop and void fraction calculation in two-phase flows and annular flow regime / Mauro, A. W.; Passarelli, A. F.; Pelella, F.; Viscito, L.. - In: EXPERIMENTAL THERMAL AND FLUID SCIENCE. - ISSN 0894-1777. - 170:(2026). [10.1016/j.expthermflusci.2025.111590]

A mechanistic predictive model for pressure drop and void fraction calculation in two-phase flows and annular flow regime

Mauro, A. W.
;
Passarelli, A. F.;Pelella, F.;Viscito, L.
2026

Abstract

This paper presents a mechanistic model for predicting the pressure gradient and other relevant flow characteristics during annular two-phase flow, by introducing a novel physical interpretation of the enhancement of the friction factor at the vapor–liquid interface, as a function of the liquid to vapor core inertia forces ratio. This interpretation is demonstrated to be consistent with literature relating the interfacial friction factor to the equivalent sand roughness. An experimental database, consisting of 6377 annular flow data points, has been used to enlarge the range of operating conditions with mass velocities from 99 to 2000 kg m-2s−1, tube diameters from 0.5 to 14.0 mm, reduced pressures from 0.0363 to 0.6896 and frictional pressure drop values from 0.3 to 1332 kPa/m. The proposed method is able to predict pressure gradients with a mean absolute percentage error of 18 % and 83 % of data points falling within a ± 30 % error range. The method allows also the calculation of the void fraction with a good agreement with the Rouhani-Axelsson correlation.
2026
A mechanistic predictive model for pressure drop and void fraction calculation in two-phase flows and annular flow regime / Mauro, A. W.; Passarelli, A. F.; Pelella, F.; Viscito, L.. - In: EXPERIMENTAL THERMAL AND FLUID SCIENCE. - ISSN 0894-1777. - 170:(2026). [10.1016/j.expthermflusci.2025.111590]
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0894177725001840-main.pdf

accesso aperto

Tipologia: Versione Editoriale (PDF)
Licenza: Dominio pubblico
Dimensione 11.35 MB
Formato Adobe PDF
11.35 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1011478
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact