In the aerospace industry, multiphase flows are encountered in a large variety of conditions. These flows may be submitted to extreme thermal and mechanical stresses. It is then essential that multifluid models are based on robust and accurate numerical methods and can be used with a wide range of physical models. In this context, two compressible diffuse interface multifluid models have been implemented in the simulation platform Cedre, namely the 4-equation model [1,2] and the 6-equation model with immediate pressure relaxation [3–6]. Cedre is a numerical framework dedicated to both research and realistic multi-physics applications. This tool is based on a cell-centered finite volume approach for general unstructured meshes and intends to tackle numerical issues related to pressure/temperature relaxation procedures, flux evaluation schemes, spatial reconstruction and time integration. This presentation aims to describe the most recent physical models and numerical methods developed in Cedre to the benefit of multifluid simulations. These latest advances include, among others, diffusion fluxes to model conductive heat exchange between fluids (with instantaneous or finite-time relaxation) and mass transfer modeling to handle vaporization and cavitation situations. The use of evolved equations of state is also addressed to provide robust descriptions to complex thermodynamic processes. Classical and challenging test cases involving shocks, interfaces and phase changes, such as shock-droplet interactions, are then performed to illustrate Cedre capabilities and to discuss the remaining difficulties. REFERENCES [1] Le Touze, C. et al. Applied Mathematical Modelling (2020). 84:265–286. ISSN 0307-904X. doi:10.1016/j.apm.2020.03.028. [2] Rutard, N. et al. International Journal of Multiphase Flow (2020). 122:103144. ISSN 03019322. doi:10.1016/j.ijmultiphaseflow.2019.103144. [3] Saurel, R. et al. Journal of Computational Physics (2009). 228(5):1678–1712. ISSN 00219991. doi:10.1016/j.jcp.2008.11.002. [4] Pelanti, M. & Shyue, K.-M. Journal of Computational Physics (2014). 259:331– 357. ISSN 0021-9991. doi:10.1016/j.jcp.2013.12.003. [5] Schmidmayer, K. et al. Journal of Computational Physics (2017). 334:468–496. ISSN 0021-9991. doi:10.1016/j.jcp.2017.01.001. [6] Cordesse, P. Ph.D. thesis, Université Paris-Saclay (2020).