5 papers
A Fast and Generalizable Fourier Neural Operator-Based Surrogate for Melt-Pool Prediction in Laser Processing
Alix Benoit, Toni Ivas, Mateusz Papierz +3
High-fidelity simulations of laser welding capture complex thermo-fluid phenomena, including phase change, free-surface deformation, and keyhole dynamics, however their computation…
Predictive control of blast furnace temperature in steelmaking with hybrid depth-infused quantum neural networks
Nayoung Lee, Minsoo Shin, Asel Sagingalieva +5
Accurate prediction and stabilization of blast furnace temperatures are crucial for optimizing the efficiency and productivity of steel production. Traditional methods often strugg…
Multi-stream physics hybrid networks for solving Navier-Stokes equations
Aleksandr Sedykh, Tatjana Protasevich, Mikhail Surmach +4
Understanding and solving fluid dynamics equations efficiently remains a fundamental challenge in computational physics. Traditional numerical solvers and physics-informed neural n…
Hybrid quantum recurrent neural network for remaining useful life prediction of turbofan engines
Olga Tsurkan, Aleksandra Konstantinova, Aleksandr Sedykh +5
Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems. We propose a Hybrid Quantum Recurrent Neura…
Photovoltaic power forecasting using quantum machine learning
Asel Sagingalieva, Stefan Komornyik, Arsenii Senokosov +6
Accurate forecasting of photovoltaic power is essential for reliable grid integration, yet remains difficult due to highly variable irradiance, complex meteorological drivers, site…