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This paper evaluates the applicability of the hexahedral block structured grids for marine propeller performance predictions. Hydrodynamic characteristics for Potsdam Propeller Test Case (PPTC), namely thrust and torque coefficients, were determined using numerical simulations in two commercial solvers: Ansys Fluent and STAR-CCM+. Results were attained for hexahedral and tetrahedral hybrid grids equivalent in terms of cell count and quality, and compared to the experimental results. Furthermore, accuracy of Realizable k- ϵ and SST k- ω turbulent models when analyzing marine propeller performance was investigated. Finally, performance characteristics were assessed in cavitating flow conditions for a single advance ratio using Zwart–Gerber–Belamri and Schnerr and Sauer models. The resulting cavitation pattern was compared to cavity extents and shape noted during measurements. The results suggest that hexa and hybrid grids, in certain range of advance ratios, do provide similar results; however, for low and high ratios, structured grids in conjunction with Realizable k- ϵ model can achieve more accurate results.

In the present paper, a Random Forest classifier is used to detect leak locations on two different sized water distribution networks with sparse sensor placement. A great number of leak scenarios were simulated with Monte Carlo determined leak parameters (leak location and emitter coefficient). In order to account for demand variations that occur on a daily basis and to obtain a larger dataset, scenarios were simulated with random base demand increments or reductions for each network node. Classifier accuracy was assessed for different sensor layouts and numbers of sensors. Multiple prediction models were constructed for differently sized leakage and demand range variations in order to investigate model accuracy under various conditions. Results indicate that the prediction model provides the greatest accuracy for the largest leaks, with the smallest variation in base demand (62% accuracy for greater- and 82% for smaller-sized networks, for the largest considered leak size and a base demand variation of ±2.5%). However, even for small leaks and the greatest base demand variations, the prediction model provided considerable accuracy, especially when localizing the sources of leaks when the true leak node and neighbor nodes were considered (for a smaller-sized network and a base demand of variation ±20% the model accuracy increased from 44% to 89% when top five nodes with greatest probability were considered, and for a greater-sized network with a base demand variation of ±10% the accuracy increased from 36% to 77%).

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Heat Equation Driven Area Coverage (HEDAC) is a state-of-the-art multi-agent ergodic motion control guided by a gradient of a potential field. A finite element method is hereby implemented to obtain a solution of Helmholtz partial di erential equation, which models the potential field for surveying motion control. This allows us to survey arbitrarily shaped domains and to include obstacles in an elegant and robust manner intrinsic to HEDAC's fundamental idea. For a simple kinematic motion, the obstacles and boundary avoidance constraints are successfully handled by directing the agent motion with the gradient of the potential. However, including additional constraints, such as the minimal clearance dsitance from stationary and moving obstacles and the minimal path curvature radius, requires further alternations of the control algorithm. We introduce a relatively simple yet robust approach for handling these constraints by formulating a straightforward optimization problem based on collision-free escapes route maneuvers. This approach provides a guaranteed collision avoidance mechanism, while being computationally inexpensive as a result of the optimization problem partitioning. The proposed motion control is evaluated in three realistic surveying scenarios simulations, showing the e ectiveness of the surveying and the robustness of the control algorithm. Furthermore, potential maneuvering di culties due to improperly defined surveying scenarios are highlighted and we provide guidelines on how to overpass them. The results are promising and indiacate real-world applicability of proposed constrained multi-agent motion control for autonomous surveying and potentially other HEDAC utilizations.