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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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NECX debut: Shaping the next era of energy
The sold-out inaugural Nuclear Energy Conference & Expo (NECX) got off to a roaring start in Atlanta, Ga., Tuesday morning with an opening plenary that was a live highlight reel discussing the latest industry achievements.
Starting with a lively promo video that left the audience amped up for Entergy’s CEO and NEI chair Drew Marsh, who welcomed everyone to the event, hosted jointly by the American Nuclear Society and the Nuclear Energy Institute. He spoke to a full house of more than 1,300 attendees, promising a blend of science, technology, policy, and advocacy centered around the future of nuclear energy.
Arsen S. Iskhakov, Cheng-Kai Tai, Igor A. Bolotnov, Tri Nguyen, Elia Merzari, Dillon R. Shaver, Nam T. Dinh
Nuclear Technology | Volume 210 | Number 7 | July 2024 | Pages 1167-1184
Research Article | doi.org/10.1080/00295450.2023.2185056
Articles are hosted by Taylor and Francis Online.
Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. This work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.