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of 31
pro vyhledávání: '"Nilesh Kumar, Jha"'
Autor:
Cut Aja Fauziah, Ahmed Al-Yaseri, Emad Al-Khdheeawi, Nilesh Kumar Jha, Hussein Rasool Abid, Stefan Iglauer, Christopher Lagat, Ahmed Barifcani
Publikováno v:
Energies, Vol 14, Iss 17, p 5542 (2021)
Wettability is one of the main parameters controlling CO2 injectivity and the movement of CO2 plume during geological CO2 sequestration. Despite significant research efforts, there is still a high uncertainty associated with the wettability of CO2/br
Externí odkaz:
https://doaj.org/article/3883964a6c054fc9b68a91350be847f6
Autor:
Vincent K. N. Lau, Nilesh Kumar Jha
Publikováno v:
IEEE Internet of Things Journal. 9:7051-7064
We propose a model driven Bayesian deep learning framework for multiple access uplink systems in Multi-user MIMO systems. Utilising tools from Streaming Variational Inference, we combine graphical models with neural networks to enable fast online mac
Publikováno v:
2023 International Conference on Power, Instrumentation, Energy and Control (PIECON).
Publikováno v:
Energies, Vol 13, Iss 21, p 5594 (2020)
Wettability of surfaces remains of paramount importance for understanding various natural and artificial colloidal and interfacial phenomena at various length and time scales. One of the problems discussed in this work is the wettability alteration o
Externí odkaz:
https://doaj.org/article/b4d0bc6e3bdc40fba3fd303784f124bc
Autor:
Mohsen Ghasemi, Nilesh Kumar Jha, Duraid Al-Bayati, Mohammad Sarmadivaleh, Maxim Lebedev, Ahmed Al-Yaseri
Publikováno v:
International Journal of Hydrogen Energy. 46:34822-34829
The challenge associated with large-scale hydrogen storage is a pertinent one to achieve a hydrogen economy. The increasing global demand for clean and green energy is the driving force to propel such an economy. Furthermore, hydrogen is also conside
Autor:
Vincent K. N. Lau, Nilesh Kumar Jha
Publikováno v:
IEEE Journal on Selected Areas in Communications. 39:2374-2387
We propose a Bayesian deep learning framework for model driven online sparse channel estimation task in Multi-user MIMO systems. Tools from Bayesian neural network and stochastic variational Bayesian Inference are utilized to capture aleatoric and ep
Autor:
Jitendra S. Sangwai, Ahmed Barifcani, Mohammad Sarmadivaleh, Anastasia A. Ivanova, Maxim Lebedev, Nilesh Kumar Jha, Stefan Iglauer, Alexey Cheremisin
Publikováno v:
Journal of Colloid and Interface Science. 586:315-325
Hypothesis The advanced low salinity aqueous formulations are yet to be validated as an injection fluid for enhanced oil recovery (EOR) from the carbonate reservoirs and CO2 geosequestration. Interaction of various ionic species present in the novel
Autor:
Muhammad Rizwan Azhar, Abdul Razak Ismail, Alireza Keshavarz, Udit Surya Mohanty, Muhammad Ali, Adnan Aftab, Muhammad Faraz Sahito, Nilesh Kumar Jha, Stefan Iglauer, Hamed Akhondzadeh
Publikováno v:
ACS Sustainable Chemistry & Engineering. 8:11224-11243
The energy industry is exploring sustainable chemistry and engineering solutions for exploitation of shale reservoirs. Smectite-rich shale is challenging to drill with traditional water-based drill...
Autor:
Mohammad Sarmadivaleh, Ali Saeedi, Zain-UL-Abedin Arain, Alireza Keshavarz, Muhammad Faraz Sahito, Muhammad Ali, Nilesh Kumar Jha, Stefan Iglauer, Shoaib Memon
Publikováno v:
Journal of Colloid and Interface Science. 559:304-312
Hypothesis Nanofluid treatment is a promising technique which can be used for wettability reversal of CO2-brine-mineral systems towards a further favourable less CO2-wet state in the existence of organic acids. However, literature requires more infor
Autor:
Lingping Zeng, Alireza Keshavarz, Nilesh Kumar Jha, Ahmed Al-Yaseri, Mohammad Sarmadivaleh, Quan Xie, Stefan Iglauer
Publikováno v:
Journal of Molecular Liquids. 371:121076