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This work presents direct numerical simulations (DNS) of a circular turbulent jet impinging on rough plates. The roughness is once resolved through an immersed boundary method (IBM) and once modeled through a parametric forcing approach (PFA) which accounts for surface roughness effects by applying a forcing term into the Navier–Stokes equations within a thin layer in the near-wall region. The DNS with the IBM setup is validated using optical flow field measurements over a smooth and a rough plate with similar statistical surface properties. In the study, IBM-resolved cases are used to show that the PFA is capable of reproducing mean flow features well at large wall-normal distances, while less accurate predictions are observed in the near-wall region. The demarcation between these two regions is approximately identified with the mean wall height $��{�k�}_{�m�}�$ of the surface roughness distribution. Based on the observed differences in the results between IBM- and PFA-resolved cases, plausible future improvements of the PFA are suggested.

Streaming Dynamic Mode Decomposition (sDMD) is a low-storage version of dynamic mode decomposition (DMD), a data-driven method to extract spatiotemporal flow patterns. Streaming DMD avoids storing the entire data sequence in memory by approximating the dynamic modes through incremental updates with new available data. In this paper, we use sDMD to identify and extract dominant spatiotemporal structures of different turbulent flows, requiring the analysis of large datasets. First, the efficiency and accuracy of sDMD are compared to the classical DMD, using a publicly available test dataset that consists of velocity field snapshots obtained by direct numerical simulation of a wake flow behind a cylinder. Streaming DMD not only reliably reproduces the most important dynamical features of the flow; our calculations also highlight its advantage in terms of the required computational resources. We subsequently use sDMD to analyse three different turbulent flows that all show some degree of large-scale coherence: rapidly rotating Rayleigh–Bénard convection, horizontal convection and the asymptotic suction boundary layer (ASBL). Structures of different frequencies and spatial extent can be clearly separated, and the prominent features of the dynamics are captured with just a few dynamic modes. In summary, we demonstrate that sDMD is a powerful tool for the identification of spatiotemporal structures in a wide range of turbulent flows.

Active turbulence control has been pursued continuously for the last decades, striving for an altered, energetically more favorable flow. In this article, our focus is on a promising method inducing a spanwise wall movement in order to reduce turbulence intensity and hence friction drag, investigated by means of direct numerical simulation. This approach transforms a previously time dependent oscillatory wall motion into a static spatial modulation with prescribed wavelength in the streamwise direction [48]. Most procedures related to turbulence control including the present one have been overwhelmingly applied to incompressible flow. This work is different and novel to the effect, that this control method is applied to compressible, supersonic channel flow up to a bulk Mach number of $��M�a�=�3�$. Due to substantial variations of viscosity, density, and temperature within the near-wall region in supersonic flow, the impact of the control method is altered compared to solenoidal flow conditions. By creating a data set of different Mach-/Reynolds numbers and control parameters, knowledge is gained in which way the effectiveness of oscillatory techniques and physical mechanisms change under the influence of compressibility. It is shown that the control method is able to effectively reduce turbulence levels and lead to large drag reduction levels in compressible supersonic flow. Variable property effects even enhance this behavior for the whole set of investigated parameters. Overall, the higher Mach number cases show a larger net power saving compared to the incompressible ones. Furthermore, we observe an increase of the optimum wavelength with increasing Mach number, which helps in guiding optimal implementations of such a control method.

In Noll et al.,¹ an error was published in the Acknowledgement section. The name “Lena Koppka” was misspelled in the original publication.

The correct Acknowledgement section is presented below:

Two investigations on the sound generation mechanisms of lean methane–air flames are reviewed and linked. A two-step approach is used for the analysis. First, the compressible conservation equations are solved in a large-eddy simulation formulation to compute the acoustic source terms of the reacting fluid. Second, the acoustic source terms are used in computational aeroacoustics simulations to determine the acoustic field by solving the acoustic perturbation equations. To identify the contributions of the different source terms to the overall sound emission of the flames different source term formulations are considered in the computational aeroacoustics simulations. The results of various flames of increasing complexity are shown: harmonically excited laminar flames, a turbulent jet flame, and an unconfined and a confined swirl flame. The results show that in general the heat release source alone does not determine the acoustic emission of the flame. Only the acoustic emission of the unconfined swirl flame could be computed by the heat release source. To accurately predict the phase and the amplitude of the sound emission of the other flames the acceleration of density gradients occurring at the flame front must be included in the considered set of source terms.

In this article, a proof-of-concept study is presented, in which in-situ full-field deformation measurements via digital image correlation, finite element analysis, and nonlinear optimization techniques are combined to characterize the heterogeneous structural behavior of a bio-based material 3D-printed via binder jetting. The special features of this composite material are its biodegradability and its easy manufacturability using conventional 3D printers. The binder-jetting process enables innovative applications such as additively manufactured, highly customized, recyclable, or compostable packaging solutions. Compared to other 3D printing techniques, it is relatively fast and inexpensive and can make use of raw material powders that are by-products of the food or other industries. As an initial step towards gaining a simulation-supported understanding of the complex process-structure-property relations, a first quantitative assessment of the effective behavior of a bio-based binder-jetted material is conducted under the following operating assumptions: (i) Its mechanical response can be described by means of a nonlinear elasto-plastic constitutive law, enriched by a cohesive damage model capturing failure on the structural level, (ii) established mechanical tests on a 3D-printed component, involving standardized sample geometries, and optical measurements, should yield sufficient information to allow the identification of the corresponding material parameters. First, experimental results of optically monitored four-point bending tests, with varying alignments of loading axes and printing directions, are presented in detail. Then the proposed parameter identification strategy is explained and its capabilities and limitations, as made evident from quantitative case studies based on the measured structural response data, are thoroughly discussed.

We investigate two numerical challenges in thermal finite element simulations of laser powder bed fusion (LPBF) processes. First, we compare the behavior of first- and second-order implicit time-stepping schemes on a fixed domain. While both methods yield comparable accuracies in the pre-asymptotic regime, the second-order method eventually outperforms the first-order method. However, the oscillations present in the pre-asymptotic range of the second-order method can render it less suitable for simulating LPBF processes. Then, we consider sudden domain extensions resulting from subsequently adding new layers of material with ambient temperature. We model this extension on the continuous level in an energy conservative manner. The discontinuities introduced here reduce the convergence order for both time-stepping schemes to 0.75. First and second order accuracy could only be achieved by strongly grading the time-steps towards the domain expansion.

This work presents multilayer phase-field simulation of selective sintering process and the calculation of effective mechanical properties and residual stress of the microstructure using the finite element method. The dependence of the effective properties and residual stress on the process parameters, such as beam power and scan speed, are analyzed. Significant partial melting of powders is observed for large beam power and low scan speed, which results in low porosity of the microstructure. Nonlinear relationship between the effective mechanical properties and process parameters is observed. The increasing rate of effective mechanical properties decreases with increasing beam power, while increases with decreasing scan speed. The dependence of effective Young's modulus and Poisson's ratio on porosity are well established using power law models. Stress concentrations are found at the necking region of powders and the intensity increases with the level of partial melting, which results in increasing residual stress in the microstructure. The numerical results reveal quantitatively the process-microstructure-property relation, which implies the feasibility of the subsequent data-driven approach.