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@ARTICLE{AR-CFD-19-4, author = {Campet, R. and Zhu, M. and Riber, E. and Cuenot, B. and Nemri, M. }, title = {Large Eddy Simulation of a single-started helically ribbed tube with heat transfer}, year = {2019}, volume = {132}, pages = {961–969}, journal = {International Journal of Heat and Mass Transfer}, abstract = {This work presents a study of the turbulent flow in a single-started helically ribbed tube with low blockage ratio. The Large Eddy Simulation (LES) approach is used in a wall-resolved periodic configuration. Both an adiabatic and a wall-heated simulations are performed and validated against experiment. Velocity profiles and wall temperatures were measured at the Von Karman Institute (VKI) using Stereoscopic Particle image Velocimetry (S-PIV) and Liquid Crystal Thermography (LCT) by Mayo et al. (2018). Comparisons show that the numerical methodology gives accurate results in terms of mean and fluctuating velocity fields as well as the correct friction drag. The wall temperature profile is also in good agreement with the experiment. The rib induces a large recirculation zone immediately downstream, with a reattachment point occurring a few rib heights farther downstream. The helical shape of the rib also induces a strong swirling motion close to the wall. The pressure drop is found equal to 3:37 Pa/m and is mostly due to the pressure drag. Maximum heat transfer is found just upstream of the reattachment point and on top of the ribs, which is in good agreement with experimentally obtained values. The mean Nusselt number in the ribbed tube is found 2.3 times higher than in a smooth tube confirming the positive impact of such geometry on heat transfer.}, keywords = {Heat transfer, Pressure loss, Ribbed tube}, url = {https://www.journals.elsevier.com/international-journal-of-heat-and-mass-transfer}}

@ARTICLE{AR-CMGC-19-1, author = {Häfliger, V. and Martin, E. and Boone, A. and Ricci, S. and Biancamaria, S. }, title = {Assimilation of Synthetic SWOT River Depths in a Regional Hydrometeorological Model}, year = {2019}, number = {78}, volume = {11}, pages = {2-24}, doi = {10.3390/w11010078}, journal = {Water}, pdf = {https://cerfacs.fr/wp-content/uploads/2019/01/GLOBC-Article-Ricci-Haefliger2019.pdf}, url = {http://www.mdpi.com/2073-4441/11/1/78}}

@ARTICLE{AR-CFD-18-116, author = {Bizzari, R. and Lahbib, D. and Dauptain, A. and Duchaine, F. and Richard, S. and Nicoud, F. }, title = {Low order modeling method for assessing the temperature of multi-perforated plates}, year = {2018}, number = {Part B}, volume = {127}, pages = {727–742}, doi = {10.1016/j.ijheatmasstransfer.2018.07.059}, journal = {International Journal of Heat and Mass Transfer}, abstract = {A low-order model is proposed to predict the temperature of a multi-perforated plate from an unresolved adiabatic computation. Its development relies on the analysis of both an adiabatic and a conjugate heat transfer wall resolved large eddy simulation of an academic multi-perforated liner representative of the cooling systems used in combustion chambers of actual aero-engines. These two simulations show that the time averaged velocity field is marginally modified by the coupling with the heat diffusion in the perforated plate when compared to the adiabatic case. This gives rise to a methodology to assess the wall temperature from an unresolved adiabatic computation. It relies on heat transfer coefficients from referenced correlations as well as a mixing temperature relevant to the flow in the injection region where the cold micro-jets mix with the hot outer flow. In this approach, a coarse mesh simulation using an homogeneous adiabatic model for the aerodynamics of the flow with effusion is post-processed to provide a low cost alternative to conjugate heat transfer computations based on hole resolved meshes. The model is validated on an academic test case and successfully applied to a real industrial combustion chamber.}, keywords = {Effusion cooling, Conjugate heat transfer, Large-Eddy simulations, Adiabatic computations, Coupled computation, Modeling}, url = {https://doi.org/10.1016/j.ijheatmasstransfer.2018.07.059}}

@ARTICLE{AR-CFD-18-184, author = {Odier, N. and Sanjosé, M. and Gicquel, L.Y.M. and Poinsot, T. and Moreau, S. and Duchaine, F. }, title = {A characteristic inlet boundary condition for compressible, turbulent, multispecies turbomachinery flows}, year = {2018}, volume = {178}, pages = {41-55}, doi = {10.1016/j.compfluid.2018.09.014}, journal = {Computers and Fluids}, abstract = {A methodology to implement non-reflecting boundary conditions for turbomachinery applications, based on characteristic analysis is described in this paper. For these simulations, inlet conditions usually correspond to imposed total pressure, total temperature, flow angles and species composition. While directly imposing these quantities on the inlet boundary condition works correctly for steady RANS simulations, this approach is not adapted for compressible unsteady Large Eddy Simulations because it is fully reflecting in terms of acoustics. Deriving non-reflecting conditions in this situation requires to construct characteristic relations for the incoming wave amplitudes. These relations must impose total pressure, total temperature, flow angle and species composition, and simultaneously identify acoustic waves reaching the inlet to let them propagate without reflection. This treatment must also be compatible with the injection of turbulence at the inlet. The proposed approach shows how characteristic equations can be derived to satisfy all these criteria. It is tested on several cases, ranging from a simple inviscid 2D duct to a rotor/stator stage with turbulence injection.}, keywords = {Characteristic inlet boundary condition, turbomachinery inflow conditions, compressible flow, turbulence injection, acoustic reflectivity}, url = {https://doi.org/10.1016/j.compfluid.2018.09.014}}

@ARTICLE{AR-CFD-18-213, author = {Granados-Ortiz, F.-J. and Perez-Arroyo, C. and Puigt, G. and Lai, C.-H. and Airiau, C. }, title = {On the Influence of Uncertainty in Computational Simulations of a High-Speed Jet Flow from an Aircraft Exhaust}, year = {2018}, doi = {10.1016/j.compfluid.2018.12.003}, journal = {Computers and Fluids}, abstract = {A classic approach to Computational Fluid Dynamics (CFD) is to perform simulations with a fixed set of variables in order to account for parameters and boundary conditions. However, experiments and real-life performance are subject to variability in their conditions. In recent years, the interest of performing simulations under uncertainty is increasing, but this is not yet a common rule, and simulations with lack of information are still taking place. This procedure could be missing details such as whether sources of uncertainty affect dramatic parts in the simulation of the flow. One of the reasons of avoiding to quantify uncertainties is that they usually require to run an unaffordable number of CFD simulations to develop the study. To face this problem, Non-Intrusive Uncertainty Quantification (UQ) has been applied to 3D Reynolds-Averaged Navier-Stokes simulations of an under-expanded jet from an aircraft exhaust with the Spalart-Allmaras turbulent model, in order to assess the impact of inaccuracies and quality in the simulation. To save a large number of computations, sparse grids are used to compute the integrals and built surrogates for UQ. Results show that some regions of the jet plume can be more sensitive than others to variance in both physical and turbulence model parameters. The Spalart-Allmaras turbulent model is demonstrated to have an accurate performance with respect to other turbulent models in RANS, LES and experimental data, and the contribution of a large variance in its parameter is analysed. This investigation explicitly outlines, exhibits and proves the details of the relationship between diverse sources of input uncertainty, the sensitivity of different quantities of interest to said uncertainties and the spatial distribution arising due to their propagation in the simulation of the high-speed jet flow. This analysis represents first numerical study that provides evidence for this heuristic observation.}, keywords = {Uncertainty Quantification, Polynomial Chaos, Kriging, CFD, Jets, RANS}, pdf = {https://cerfacs.fr/wp-content/uploads/2018/12/CFD_Granados_Perez_CompFl2018.pdf}}