Turbulent flow

This session is focused on turbulent flows and comprises the following talks: 1. Unveiling Hidden Order in Turbulence: Quiescent Interludes and Invariant States in Square-Duct Flow 2. Compressible synthetic turbulence generator in Nektar++. 3. Turbomachinery Applications of Nektar++ Unveiling Hidden Order in Turbulence: Quiescent Interludes and Invariant States in Square-Duct Flow In the dynamical system view of turbulence, stable manifolds of low-dimensional invariant solutions form a scaffold around which the turbulent attractor is organised. While the invariant solutions remain unstable, the low codimension of their stable manifolds causes the flow state to spend substantial amounts of time in their proximity while shadowing their stable manifolds without ever settling onto them. Consequently, turbulence often manifests in a surprising degree of organisation that transpires in the form of well-defined secondary flows. One such example is the formation of either four- or eight-vortex states known to occur in the turbulent square-duct flow. This work investigates the intriguing connection between a previously identified invariant solution and selected transiently quiescent interludes of the turbulent square-duct flow Compressible synthetic turbulence generator in Nektar++ Recent advances in hardware performance and numerical methods have greatly increased the use of scale-resolving simulations like Direct Numerical Simulations in industrial settings. For effective application, these simulations require the generation of realistic incoming turbulence to ensure accurate predictions of the flow field. Implementing an inflow turbulence generation method is decisive for improving predictions in areas such as boundary layer transitions, flow separation, and reattachment. This is especially important in aerodynamic design for turbines, fans, and intakes, where precise modeling of these phenomena plays a significant role. This talk addresses the challenge of injecting realistic turbulence into the computational domain using a source term formulation of the Synthetic Eddy Method (SEM), implemented within the Nektar++ framework for both incompressible and compressible solvers. The efficacy of the method will be validated in a compressible plane channel flow. In addition, its application will be demonstrated in an industrial case. The effects of turbulence inflow on the flow field will be investigated for the low-pressure turbine T106A linear cascade. Through this study, we show the potential of this methodology not only to enhance the fidelity of the simulation but also how the source term formulation of the SEM allows computational savings in practical turbomachinery applications Turbomachinery Applications of Nektar++ Over the past few years, there has been a growing interest in high-fidelity methodologies within the turbomachinery community. Up to now, RANS tools have provided significant benefits in terms of experimental cost reduction. Nevertheless, these codes are not able to model the chaotic unsteadiness characteristic of these types of flows. Moreover, LES/DNS strategies allow a detailed study of the physical mechanisms occurring, unlike experiments that can only quantify component performance. These are the reasons behind the growing interest in high-order methods. Recently, many examples of high-fidelity code deployment on jet engine components have appeared within the literature: successful modelling of intakes, high/low pressure turbines and compressors has been reported. In this presentation, the efforts around the use of Nektar++ on various turbomachinery configurations will be demonstrated. In particular, the main focus will be around a compressor and the well-known LS89 high-pressure turbine. In the first case, preliminary results will be shown relating to the 2.5D study of the case in LES/DNS resolution. In particular, the complexities in load matching and the effects of turbulence injection will be discussed. Concerning the LS89 configuration, the un-shocked and shocked clean inflow cases will be outlined, along with strategies to improve experimental comparison.