Work

Performance Analysis of Methane–Hydrogen Mixture Transportation in Pipelines Using Aspen Plus and Artificial Neural Networks

Year: 2025

Type: article

Source: Journal of Pipeline Systems Engineering and Practice

DOI: 10.1061/jpsea2.pseng-1838

Authors: Moslem Abrofarakh, Mortaza Zivdar, Davod Mohebbi-Kalhori

Institution: University of Sistan and Baluchestan

Language: English

Topic: Water Systems and Optimization

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: closed

OpenAlex ID: W4409962357

FWCI: 1.145

Cites: 33

Cited by: 3

Related to: 10