Igor Bolotnov

Associate Professor of Nuclear Engineering, Joint Faculty Appointment with ORNL, ABET Coordinator

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  • Burlington Laboratory 2142
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Dr. Bolotnov holds a joint faculty appointment with Oak Ridge National Laboratory. He is a member of CASL, the DOE-funded energy innovation hub. He is also a member of Thermal Hydraulics Methods focus area, where he collaborates with his colleagues from ORNL, LANL, MIT and TAMU to develop a new generation of multiphase boiling flow models based new experimental and direct numerical simulation data.  His research includes:

Using multiscale approach for nuclear reactors simulations The required technological and safety standards for future Gen-IV Reactors can only be achieved if advanced simulation capabilities become available, which combine high performance computing with the necessary level of modeling detail and high accuracy of predictions. Interaction between different numerical codes working on various scales (DNS, RaNS, solid/structure interaction) on different parts of multiphase three-dimensional transient problem (such as nuclear reactor accident scenario) gives the ability to develop new multiscale multi-field models and simulations in various areas of nuclear engineering.

Development of new spectral cascade transfer multiphase flow turbulence models The modeling of multiphase flows has wide range of applications in the fields of nuclear, chemical, biomedical engineering. Recent advances in the development of single and two-phase spectral turbulent models show promising results in extending those models to more complex type of two-phase bubbly flows (such as non-homogeneous conduit flows, boundary layer flows, free shear flows) and multi-component flows. The new generation of the advanced turbulence two-phase flow models will provide unprecedented abilities in designing new generation of safe and powerful nuclear power plants.

Direct numerical simulation of single and multiphase turbulent flows DNS approach recently became an affordable tool in obtaining multiphase turbulence data for testing and validation of the new spectral turbulence models. Performing the DNS of multiphase flows using a state of the art massively parallel finite element based code (PHASTA) provides a unique opportunity to contribute to the development of new closure laws necessary for successful application of computational multiphase fluid dynamics in nuclear reactor thermal-hydraulics analysis.


Ph.D. 2008

Engineering Physics

Rensselaer Polytechnic Institute

M.S. 2003

Engineering Physics

Rensselaer Polytechnic Institute

B.S. 2001

Applied Mathematics and Informatics

Bashkir State University, Russia

Research Description

Dr. Bolotnov is interested in using multiscale approaches for nuclear reactor simulations, development of new spectral cascade transfer multiphase flow turbulence models, and direct numerical simulation of single and multiphase turbulent flows.


Two-Phase Turbulence Statistics from High Fidelity Dispersed Droplet Flow Simulations in a Pressurized Water Reactor (PWR) Sub-Channel with Mixing Vanes
Saini, N., & Bolotnov, I. A. (2021), FLUIDS, 6(2). https://doi.org/10.3390/fluids6020072
Annular Flow Simulation Supported by Iterative In-Memory Mesh Adaptation
Fang, J., Purser, M. K., Smith, C., Balakrishnan, R., Bolotnov, I. A., & Jansen, K. E. (2020), NUCLEAR SCIENCE AND ENGINEERING. https://doi.org/10.1080/00295639.2020.1743577
Exploring Two-Phase Flow Regime Transition Mechanisms Using High-Resolution Virtual Experiments
Zimmer, M. D., & Bolotnov, I. A. (2020), NUCLEAR SCIENCE AND ENGINEERING. https://doi.org/10.1080/00295639.2020.1722543
Interface capturing simulations of bubble population effects in PWR subchannels
Cambareri, J. J., Fang, J., & Bolotnov, I. A. (2020), NUCLEAR ENGINEERING AND DESIGN, 365. https://doi.org/10.1016/j.nucengdes.2020.110709
Interface-Resolved Simulations of Reactor Flows
Fang, J., Cambareri, J. J., Li, M., Saini, N., & Bolotnov, I. A. (2020). [Review of , ]. NUCLEAR TECHNOLOGY, 206(2), 133–149. https://doi.org/10.1080/00295450.2019.1620056
Machine-learning based error prediction approach for coarse-grid Computational Fluid Dynamics (CG-CFD)
Hanna, B. N., Dinh, N. T., Youngblood, R. W., & Bolotnov, I. A. (2020), PROGRESS IN NUCLEAR ENERGY, 118. https://doi.org/10.1016/j.pnucene.2019.103140
Simulation scaling studies of reactor core two-phase flow using direct numerical simulation
Cambareri, J. J., Fang, J., & Bolotnov, I. A. (2020, March), NUCLEAR ENGINEERING AND DESIGN, Vol. 358. https://doi.org/10.1016/j.nucengdes.2019.110435
The evaporation and condensation model with interface tracking
Li, M., & Bolotnov, I. A. (2020), INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 150. https://doi.org/10.1016/j.ijheatmasstransfer.2019.119256
Development of a New Contact Angle Control Algorithm for Level-Set Method
Li, M., Zeng, K., Wonnell, L., & Bolotnov, I. A. (2019), JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME, 141(6). https://doi.org/10.1115/1.4041987
Slug-to-churn vertical two-phase flow regime transition study using an interface tracking approach
Zimmer, M. D., & Bolotnov, I. A. (2019), INTERNATIONAL JOURNAL OF MULTIPHASE FLOW, 115, 196–206. https://doi.org/10.1016/j.ijmultiphaseflow.2019.04.003

View all publications via NC State Libraries


Multiple Bubble Boiling Simulation Scaling and Evaluation
US Dept. of Energy (DOE)(9/08/20 - 11/30/20)
Center for thermal-fluids application in nuclear energy: Establishing the knowledge base for thermal-hydraulic multiscale simulation to accelerate the deployment of advanced reactors.
US Dept. of Energy (DOE)(10/01/20 - 9/30/23)
Pilot Study on Two-Phase flow DNS Application to Heat Transfer Enhancement Pipe
Mitsubishi Heavy Industries, Ltd.(7/01/20 - 12/31/20)
Computationally Efficient Prediction of Containment Thermal Hydraulics Using Multi-Scale Simulation
US Dept. of Energy (DOE)(11/21/16 - 9/30/18)
Research and Technical Assistance Related to Severe Accidents in Nuclear Power Plants
US Nuclear Regulatory Commission(9/08/16 - 6/30/19)
Computationally Efficient Prediction of Containment Thermal Hydraulics Using Multi-Scale Simulation: Feasibility Study (FY 16 NUC)
US Dept. of Energy (DOE)(12/23/15 - 9/30/16)
Development and Application of a Data-Driven Methodology for Validation of Risk Informed Safety Margin Characterization Models
US Dept. of Energy (DOE)(10/01/16 - 12/30/20)
Development and Validation of a Societal Risk Goal for Nuclear Power Plant Safety (2014-2015)
US Dept. of Energy (DOE)(11/04/14 - 9/30/15)
Turbulent Multiphase Flows for Nuclear Reactor Safety.
US Dept. of Energy (DOE) - Advanced Scientific Computing Research (ASCR)(7/01/14 - 6/30/15)
Simulation and Modeling of the Interactions of Liquid Turbulent Eddies and Gas Bubbles
National Science Foundation (NSF)(7/15/13 - 6/30/17)