Arsen Iskhakov
Also known as: Iskhakov A.S.; Arsen S. Iskhakov
https://orcid.org/0000-0003-4064-9894
Nuclear Engineering
Works (9)
Updated: May 22nd, 2023 08:38
2023 article
Data-Driven High-to-Low for Coarse Grid System Thermal Hydraulics
Iskhakov, A. S., Leite, V. C., Merzari, E., & Dinh, N. T. (2023, April 28). NUCLEAR SCIENCE AND ENGINEERING, Vol. 4.
author keywords: Coarse grid computational fluid dynamics; data-driven high-to-low; machine learning; mixing; turbulence modeling
Sources: Web Of Science, ORCID
Added: May 15, 2023
2023 article
Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry
Iskhakov, A. S., Tai, C.-K., Bolotnov, I. A., Nguyen, T., Merzari, E., Shaver, D. R., & Dinh, N. T. (2023, March 16). NUCLEAR TECHNOLOGY, Vol. 3.
author keywords: Machine learning; turbulence modeling; forced convection; low- and high-Prandtl fluids; data-driven modeling
Sources: Web Of Science, ORCID
Added: March 16, 2023
2022 article
A Perspective on Data-Driven Coarse Grid Modeling for System Level Thermal Hydraulics
Iskhakov, A. S., Tai, C.-K., Bolotnov, I. A., & Dinh, N. T. (2022, September 10). NUCLEAR SCIENCE AND ENGINEERING, Vol. 9.
author keywords: Data-driven methods; coarse grid modeling; system thermal hydraulics; machine learning; multiscale bridging
Sources: Web Of Science, ORCID
Added: September 9, 2022
2022 article
Data-driven Hi2Lo for Coarse-grid System Thermal Hydraulic Modeling
ArXiv. http://www.scopus.com/inward/record.url?eid=2-s2.0-85126815096&partnerID=MN8TOARS
Source: ORCID
Added: October 16, 2022
2022 article
Direct Numerical Simulation of Low and Unitary Prandtl Number Fluids in Reactor Downcomer Geometry
ArXiv. http://www.scopus.com/inward/record.url?eid=2-s2.0-85128839982&partnerID=MN8TOARS
Source: ORCID
Added: October 16, 2022
2021 journal article
Integration of neural networks with numerical solution of PDEs for closure models development
PHYSICS LETTERS A, 406.
author keywords: Physics-informed machine learning; PDE-integrated neural network; Closure model
arxiv.org (repository)
Sources: Web Of Science, ORCID
Added: June 10, 2021
2021 article
Review of physics-based and data-driven multiscale simulation methods for computational fluid dynamics and nuclear thermal hydraulics
ArXiv. http://www.scopus.com/inward/record.url?eid=2-s2.0-85102858814&partnerID=MN8TOARS
Source: ORCID
Added: October 16, 2022
2020 article
Physics-integrated machine learning: Embedding a neural network in the navier-stokes equations. Part II
ArXiv. http://www.scopus.com/inward/record.url?eid=2-s2.0-85108266968&partnerID=MN8TOARS
Source: ORCID
Added: October 16, 2022
2018 journal article
Pressure Waves due to Rapid Evaporation of Water Droplet in Liquid Lead Coolant
Science and Technology of Nuclear Installations, 10.
Source: ORCID
Added: October 16, 2022
