Volume 17, Issue 3-4 -

Stirling engines are regarded as an efficient and promising power system for underwater devices. Currently, many models have been used to evaluate thermodynamic performance of Stirling engine, but in which mechanical loss and auxiliary power still cannot be modeled with proper mathematical models. A four-cylinder double-acting Stirling engine for Unmanned Underwater Vehicle (UUV) is discussed in this paper. Referring to the Stirling engine experimental results from National Aeronautics and Space Administration (NASA), a one-dimensional model incorporated with empirical equations of mechanical loss and auxiliary power obtained from experiments is presented. The P-40 Stirling engine with sufficient testing results from NASA is utilized to validate the accuracy of the modified one-dimensional model. And the comparison results suggest good agreement between testing and simulation results. The output power maximum error of theoretical analysis results is less than 18 % over testing results, and the maximum error of input power is no more than 9 %. In short, the one-dimensional model is adequate to evaluate the thermodynamic performance of the Stirling engine.

This paper presents the geometric modeling methods based on the class and shape function transformation (CST) technique for the hypersonic vehicle. First, the typical waverider configuration is considered to be the basic shape for the hypersonic vehicle, and then the CST method is applied to describe and build the improved geometric shape. On this basis, the aerodynamic forces and thrust are estimated according to the shock wave and Rayleigh flow theory. Furthermore, the model dynamic features using the CST method are analyzed in comparison to the basic shape. Finally, the simulation results show the effectiveness of this method for the hypersonic vehicle.

A study is presented showing results of predictions of the amount of water ejected from shallow depth explosions. Measurements of the Equivalent Water Length ( EWL ) are determined by integrating the density along a horizontal line through the plume. These EWL values are important for the assessment of the viability of using plumes as an effective water barrier for vessel defense. The predictions are obtained using a model based on a generalized formulation of hydrodynamics using an incompressible liquid assumption. This formulation is well suited for predicting long-time bubble and plume dynamics and has been previously validated on a variety of applications including water plume predictions. The purpose of this study is to obtain estimates for EWL values at specified heights, the time length that these levels persist during the plume evolution, as well as estimates for the effects of charge depth and size.

Conventional approaches for simulating steady-state distributions of dilute particles under diffusive and advective transport involve solving the diffusion and advection equations in at least two dimensions. Here, we present an alternative computational strategy by combining a particle-based rather than a field-based approach with the initialisation of particles in proportion to their flux. This method allows accurate prediction of the steady state and is applicable even at intermediate and high Péclet numbers (Pe>1)$ (Pe \gt 1)$ where traditional particle-based Monte-Carlo methods starting from randomly initialised particle distributions fail. We demonstrate that generating a flux of particles according to a predetermined density and velocity distribution at a single fixed time and initial location allows for accurate simulation of mass transport under flow. Specifically, upon initialisation in proportion to their flux, these particles are propagated individually and detected by summing up their Monte-Carlo trajectories in predefined detection regions. We demonstrate quantitative agreement of the predicted concentration profiles with the results of experiments performed with fluorescent particles in microfluidic channels under continuous flow. This approach is computationally advantageous and readily allows non-trivial initial distributions to be considered. In particular, this method is highly suitable for simulating advective and diffusive transport in microfluidic devices, for instance in the context of diffusive sizing.