In computational fluid dynamics simulations of industrial flows, models based on the
Reynolds-averaged Navier–Stokes (RANS) equations are expected to play an important …

Accurate quantification of uncertainties is paramount in the contemporary design of aero-
engines, demanding substantial computational resources. This investigation introduces an …

The use of uncertainty quantification and machine learning platforms in ensuring the
robustness of small modular reactor (or popularly known as SMR) core design is rare. Most …

A stochastic analysis of the sensitivity to grid resolution and modeling of large-eddy
simulations (LES) results is carried out for the flow around a 5: 1 rectangular cylinder, which …

An uncertainty quantification and validation framework is presented to account for both
aleatory and epistemic uncertainties in stochastic simulations of turbine engine components …

One of the key enablers of valued early decision-making in composite material designs is
the ability to account for different aspects/scale of uncertainties within models and design …

This paper revisits an old problem of validating computational fluid dynamics simulations
with experiments in turbomachinery. The case considered here is NASA rotor 37. Prior …

The stochastic computations of a NASA gas turbine vane are conducted to investigate the
effects of the operational uncertainties on the flow and heat transfer characteristics of the …

Wind turbine blade deterioration issues have come to the attention of researchers and
manufacturers due to the relevant impact they can have on the actual annual energy …

Uncertainty quantification (UQ) is an increasingly important area of research. As
components and systems become more efficient and optimized, the impact of uncertain …