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This paper addresses a detection problem where sparse measurements are utilized to estimate the source parameters in a mixed multi-modal radiation field. As the limitation of dimensional scalability and the unimodal characteristic, most existing algorithms fail to detect the multi-point sources gathered in narrow regions, especially with no prior knowledge about intensity and source number. The proposed Peak Suppressed Particle Filter (PSPF) method utilizes a hybrid scheme of multi-layer particle filter, mean-shift clustering technique and peak suppression correction to solve the major challenges faced by current existing algorithms. Firstly, the algorithm realizes sequential estimation of multi-point sources in a cross-mixed radiation field by using particle filtering and suppressing intensity peak value, while existing algorithms could just identify single point or spatially separated point sources. Secondly, the number of radioactive sources could be determined in a non-parametric manner as the fact that invalid particle swarms would disperse automatically. In contrast, existing algorithms either require prior information or rely on expensive statistic estimation and comparison. Additionally, to improve the prediction stability and convergent performance, distance correction module and configuration maintenance machine are developed to sustain the multimodal prediction stability. Finally, simulations and physical experiments are carried out in aspects such as different noise level, non-parametric property, processing time and large-scale estimation, to validate the effectiveness and robustness of the PSPF algorithm.

Accurate prediction of the self-propulsion performance is one of the most important factors for the energy-efficient design of a ship. In general, the hydrodynamic performance of a full-scale ship could be achieved by model-scale simulation or towing tank tests with extrapolations. With the development of CFD methods and computing power, directly predict ship performance with full-scale CFD is an important approach. In this article, a numerical study on the full-scale self-propulsion performance with propeller operating behind ship at model- and full-scale is presented. The study includes numerical simulations using the RANS method with a double-model and VOF (Volume-of-Fluid) model respectively and scale effect analysis based on overall performance, local flow fields and detailed vortex identification. The verification study on grid convergence is also performed for full-scale simulation with global and local mesh refinements. A series of sea trail tests were performed to collect reliable data for the validation of CFD predictions. The analysis of scale effect on hull-propeller interaction shows that the difference of hull boundary layer and flow separation is the main source of scale effect on ship wake. The results of the fluctuations of propeller thrust and torque along with circulation distribution and local flow field show that the propeller’s loading is significantly higher for model-scale ship. It is suggested that the difference of vortex evolution and interaction is more pronounced and has larger effects on the ship’s powering performance at model-scale than full-scale according to the simulation results. From the study on self-propulsion prediction, it could be concluded that the simplification on free surface treatment does not only affect the wave-making resistance for bare hull but also the propeller performance and propeller induced ship resistance which can be produced up to 5% uncertainty to the power prediction. Roughness is another important factor in full-scale simulation because it has up to an approximately 7% effect on the delivery power. As a result of the validation study, the numerical simulations of full-scale ship self-propulsion shows good agreement with the sea trail data especially for cases that have considered both roughness and free surface effects. This result will largely enhance our confidence to apply full-scale simulation in the prediction of ship’s self-propulsion performance in the future ship designs.

Accurate prediction of the self-propulsion performance is one of the most important factors for energy-efficient design of a ship. In general, the hydrodynamic performance of a full-scale ship could be achieved by model-scale simulation or towing tank test with extrapolations. With the development of CFD methods and computing power, directly predict ship performance with full-scale CFD is an important approach. In this article, a numerical study on the full-scale self-propulsion performance with propeller operating behind ship at model- and full-scale is presented. The study includes numerical simulations using RANS method with double-model and VOF model respectively and scale effect analysis based on overall performance, local flow fields and detailed vortex identification. Verification study on grid convergence is also performed for full-scale simulation with global and local mesh refinements. And a series of sea trail tests were performed to collect reliable data for the validation of CFD predictions. The analysis of scale effect on hull-propeller interaction shows that the difference on hull boundary layer and flow separation is the main source of scale effect on ship wake. And the results of the fluctuations of propeller thrust and torque along with circulation distribution and local flow field show that propeller’s loading is significantly higher for model-scale ship. It is suggested that the difference on vortex evolution and interaction is more pronounced and have larger effects on ship’s powering performance at model-scale than full-scale according to the simulation results. From the study on self-propulsion prediction, it could be concluded that the simplification on free surface treatment does not only affect the wave-making resistance for bare hull but also the propeller performance and propeller induced ship resistance which can produced up to 5% uncertainty to the power prediction. Roughness is another important factor in full-scale simulation because it has up to approximately 7% effect on the delivery power. As a result of validation study, the numerical simulations of full-scale ship self-propulsion shows good agreement with the sea trail data especially for cases that have considered both roughness and free surface effects. This result will largely enhance our confidence to apply full-scale simulation in the prediction of ship’s self-propulsion performance in the future ship designs.

In this paper, we present a coupling potential and Reynolds-averaged Navier–Stokes (RANS) approach for the analysis of propeller loading and propulsion performance at self-propulsion condition. There is a presentation of a combination of unsteady RANS method for ship flow with free surface taking into account by volume of fluid method and Lifting Line Model for propeller operating behind ship. An intensified coupling strategy is proposed to simulate the propeller effect in the ship wake. The effective wake is re-examined through the iterations, and there is a presentation of the spatial distribution of propeller forces. Propeller unsteady loading of KCS test case is predicted by flow field from both Full RANS and the Coupling method and compared to experiment results. A circulation-based analysis is made to scrutinize the spatial distribution of propeller loading. The simulation results prove that the coupling method can estimate propeller’s loading and effect on averaged flow field. Ultimately, the coupling method is applied to design an optimal propeller accounting for hull–propeller interaction, which shows its potential for further integrated optimization application.