Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Danial Ahangari"'
Publikováno v:
Petroleum, Vol 8, Iss 2, Pp 174-184 (2022)
Geochemical parameters are useful properties to enhance hydrocarbon exploration certainty. Though, attaining these parameters, for instance total organic carbon (TOC), volatile and residual hydrocarbon (S1 & S2) is a challenge for geologists due to t
Externí odkaz:
https://doaj.org/article/b0792bcd5443400b830af2c7c5506185
Autor:
Tzu-Chia Chen, Hasan Sh. Majdi, Aras Masood Ismael, Jamshid Pouresmi, Danial Ahangari, Saja Mohammed Noori
Publikováno v:
International Journal of Chemical Engineering, Vol 2022 (2022)
Thermal conductivity (TC) of a phase change material (PCM) may be enhanced by distributing nanostructured materials (NSMs) termed nano-PCM. It is critical to accurately estimate the TC of nano-PCM to assess heat transfer during phase transition proce
Externí odkaz:
https://doaj.org/article/89d9c05cc3ef4fb1ac1ccc71d4202f20
Publikováno v:
International Journal of Chemical Engineering, Vol 2021 (2021)
This paper deals with modeling hydrogen contents of bio-oil (H-BO) as a function of pyrolysis conditions and biomass compositions of feedstock. The support vector machine algorithm optimized by the grey wolf optimization method has been used in model
Externí odkaz:
https://doaj.org/article/b27aada64d8e40baadafec541efa31e5
Publikováno v:
Petroleum. 8:174-184
Geochemical parameters are useful properties to enhance hydrocarbon exploration certainty. Though, attaining these parameters, for instance total organic carbon (TOC), volatile and residual hydrocarbon (S1 & S2) has a challenge for geologists due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::861dbd3f7fac1e85132f6383bcc69ff0
https://doi.org/10.1016/j.petlm.2021.04.007
https://doi.org/10.1016/j.petlm.2021.04.007
Autor:
Amin Taghavinejad, Danial Ahangari, Mahdi Abbasi, Mohammad Sharifi, Bahram Soltani Soulgani, Mohammad Zarekhormizi, Mehdi Ostadhassan
Publikováno v:
Fuel. 324:124454
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0e878d9d17d81d334187f8c60509070
https://doi.org/10.1016/j.fuel.2022.124454
https://doi.org/10.1016/j.fuel.2022.124454
Publikováno v:
International Journal of Chemical Engineering, Vol 2021 (2021)
This paper deals with modeling hydrogen contents of bio-oil (H-BO) as a function of pyrolysis conditions and biomass compositions of feedstock. The support vector machine algorithm optimized by the grey wolf optimization method has been used in model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87a9d182b00e0f772427baab4f870cce