A new partially averaged Navier–Stokes (PANS) closure is derived based on the $k−kL$ (KSKL) model. The aim of this new model is to incorporate the desirable features of the KSKL model, compared to the $k−ω$ shear stress transport model, into the PANS framework. These features include reduced eddy-viscosity levels, a lower dependency on the cell height at the wall, well-defined boundary conditions, and improved iterative convergence. As well as the new model derivation, the paper demonstrates that these desirable features are indeed maintained, for a range of modeled-to-total turbulence kinetic energy ratios (f_k), and even for multiphase flow.

Inflow turbulence is relevant for many engineering applications relating to noise generation, including aircraft wings, landing gears, and non-cavitating marine propellers. While modelling of this phenomenon is well-established for higher Mach number aerospace problems, lower Mach number applications, which include marine propellers, still lack validated numerical tools. For this purpose, simplified cases for which extensive measurement data are available can be used. This paper investigates the effect of inflow turbulence on a circular cylinder at a Reynolds number of 14,700, a Mach number of 0.029, and with inflow turbulence intensities ranging between 0% and 22%. In the present work focus is put on the hydrodynamics aspect, with the aim of addressing radiated noise in a later study. The flow is simulated using the partially averaged Navier Stokes equations, with turbulence inserted using a synthetic inflow turbulence generator. Results show that the proposed method can successfully replicate nearfield pressure variations and relevant flow features in the wake of the body. In agreement with the literature, increasing inflow turbulence intensity adds broadband frequency content to all the presented fluctuating flow quantities. In addition, the applied variations in inflow turbulence intensity result in a major shift in flow dynamics around a turbulence intensity of 15%, when the dominant effect of von Kármán vortices on the dominant flow dynamics becomes superseded by freestream turbulence.

Sound maps are essential and practical tools for hindcasting and forecasting sound levels, supporting both environmental assessments and policymaking. The NAVISON (Navis Sonus) project, funded and managed by the European Maritime Safety Agency (EMSA), developed comprehensive shipping sound maps for European seas covering the period from 2016 to 2050. These maps provide results for the 63 Hz and 125 Hz decidecade bands, key frequencies for assessing Good Environmental Status under the EU Marine Strategy Framework Directive. Source levels, computed along Automatic Identification System (AIS) ship tracks using the novel PIANO source model, serve as inputs to a sound mapping tool based on the parabolic equation method, which accounts for environmental factors, such as sound speed profiles, sediment properties, and bathymetry. The NAVISON project delivered hindcast (2016–2023) and forecast (2030, 2040, 2050) sound maps and sound energy densities by vessel type, season, and region. The forecast modeling incorporates scenarios that combine mitigation measures for both greenhouse gas emissions and underwater radiated noise. Maintained and disseminated by EMSA, these outputs provide a comprehensive, long-term perspective on shipping noise trends, quantify vessel-type contributions, enable regional comparisons, and support the evaluation of mitigation strategies.

Underwater radiated noise (URN) from shipping is a pervasive marine pollutant that affects marine wildlife and habitats globally. Although various technological and operational measures have been proposed to reduce ship URN emissions, no mandatory international roadmap for their adoption exists, unlike for greenhouse gases. To address this gap, and to support environmental assessments and policymaking, the Navis Sonus (NAVISON) project, funded and managed by the European Maritime Safety Agency (EMSA), developed a new probabilistic method for rapidly generating URN foresight scenarios in European seas. This method produces forecasts by combining component sound map layers for different mitigation measures, according to joint probability tables for a given scenario. Separate sound map layers are generated for propeller cavitation noise and machinery (main and auxiliary engine) noise for several ship types. Spatially varying adjustment factors are associated with these layers for each distinct mitigation measure. Combining and adjusting these layers according to their joint probabilities offers managers a practical and efficient method to assess multiple scenarios without recalculating the underlying sound map layers. This approach provides a flexible marine spatial planning tool to enable evaluation of future URN management strategies.