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The underwater vehicles operated remotely, known from the specialized literature under the name of ROV are common and are intensively used in the maritime industry. Depending on the area of use, ROV must satisfy numerous constructive and functional requirements, which are difficult to achieve in practice and the simulation is a challenging alternative. The big challenge is the simulation of the thrust force generated by the propeller. The present work aims to present such a simulation realized with the Ansys Fluid Dynamics software package. The simulation presented uses a 3D model of an asymmetrical propeller in the duct, having as reference the T100 propeller marketed by Blue Robotics. The fluid volume extracted after the model was made was separated into two domains one static and other rotating around the propeller, which was discretized using the default grid generator. The solution was obtained under stationary conditions using only the flow equations together with the standard k-ε model for turbulence modelling. The calculation was made for rotation speed values in the working domain. In the end, using the facilities of the program, the thrust force of the propeller was calculated. The obtained results were compared with the experimental measurements and critical analysis will be done.

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.