Analysis of the Behrens-Fisher Problem Based on Bayesian Evidence

The Behrens-Fisher problem concerns the inferences for the difference between the means of two normal populations without making any assumption about the variances. Although the problem has been extensively studied in the literature, researchers cannot agree on its solution at present. In this paper, we propose a new method for dealing with the Behrens-Fisher problem in the Bayesian framework. The Bayesian evidence for testing the equality of two normal means and a credible interval at a specified level for the difference between the means are derived. Simulation studies are carried out to evaluate the performance of the provided Bayesian evidence

Liver Transplantation in China

Liver transplantation has been developed in Mainland China for about 40 years, from clinical trials to maturity. Its number has become the second in the world, its quality is also in line with the international level, and the source of donors has gradually transitioned to donation after citizen’s death (DCD). This chapter is aimed to elaborate the liver transplant work in China from the history and current status of liver transplantation, the main operating methods, major indications, donor maintenance and donor quality assessment, postoperative major complications, and application of immunosuppressive agents to the postoperative follow-up. Liver transplantation is a meaningful and challenging work currently in China; all the Chinese transplant surgeons and scholars are devoting themselves to this work in order to give more effective help to the patients

Numerical and Experimental Investigation of the Conjugate Heat Transfer for a High-Pressure Pneumatic Control Valve Assembly

This paper uses heat transfer experiments and computational fluid dynamics (CFD) simulations to investigate the conjugate heat transfer (CHT) in a high-pressure pneumatic control valve assembly. A heat transfer test rig was constructed, and time–temperature histories of five test points placed on the valve assembly’s outer surface were recorded for study validation. The Unsteady Reynolds-Averaged Navier–Stokes (URANS) CFD methods with the standard k-ε turbulence closure equations were adopted in the numerical computations. Polyhedral grids were used; time step and mesh convergence studies were conducted. Simulated and measured temperatures profile comparisons revealed a good agreement. The CHT results obtained from CFD showed huge velocity fields downstream of the valve throat and the vent hole. The airflow through the valve was icy, mainly in the supersonic flow areas. Low temperatures below 273.15 K were recorded on the internal and external walls of the valve assembly. The consistency of the measured data with the numerical results demonstrates the effectiveness of polyhedral grids in exploring the CHT using CFD methods. The local entropy production rate analysis revealed that irreversibility is mainly due to viscous dissipation. The current CHT investigation provides a potential basis for thermostress analysis and optimization

Research on the vibration band gaps of isolators applied to ship hydraulic pipe supports based on the theory of phononic crystals

According to the theory of phononic crystals, a new isolator applied to ship hydraulic pipe-support with a one-dimensional periodic composite structure is designed, which is composed of metal and rubber. The vibration of the ship hydraulic pipeline can be suppressed by the band gaps (BGs) of the isolator. The band structure and frequency response function of the isolator is figured out by the transfer matrix method and the finite element method respectively. The frequency ranges and width of the BGs can be modulated to obtain the best structure of the isolator by changing the geometrical parameters. The experimental results provide an attenuation of over 20 dB in the frequency range of the BGs, and the results show good agreement with those of the numeric calculations. The research provides an effective way to control the vibration of ship hydraulic pipelines

Optimization Design of Pressure Hull for Long-Range Underwater Glider Based on Energy Consumption Constraints

Underwater gliders are a class of ocean observation equipment driven by buoyancy, and their energy consumption source is mainly generated by the active regulation of buoyancy. The periodic elastic deformation of the pressure hull during the upward and downward movement of the underwater glider can have a large impact on its driving buoyancy. This paper relates the optimization problem of the pressure hull with the energy consumption of underwater glider, and the energy improvement factor is taken as the optimization objective. Based on the mechanical theory, the theoretical optimization model and constraint model are derived. A hybrid genetic simulated annealing algorithm (HGSAA) is adopted to optimize the pressure hull of the underwater glider developed by Huazhong University of Science and Technology (HUST). Additionally, the effectiveness of the optimized mathematical model and optimization results were verified by the tests. The sea trial results show that after the pressure hull optimization, the energy consumption of the buoyancy regulation unit decreased by 21.9%, and the total energy carried increased by 12.4%

Surrogate-based optimization design for surface texture of helical pair in helical hydraulic rotary actuator

Abstract A good surface texture design can effectively improve the tribological performance of the helical pair within a helical hydraulic rotary actuator(HHRA). However, the optimization design process can be time-consuming due to the multiple design variables involved and the complexity of the mathematical model. This paper proposes a modified efficient global optimization (MEGO) method for solving such demanding surface texture design challenges. The MEGO utilizes a Kriging model with the optimized Latin hypercube sampling (OLHS) for initial sampling and the proposed modified expected improvement (MEI) function for sequential sampling. A comparative study of several global optimization algorithms with the MEGO on the surface texture design is performed. Subsequently, surrogate-based optimization and parameter analysis are carried out, resulting in the identification of an optimal set of texture parameters. The findings reveal the superiority of the MEGO in both model prediction accuracy and refinement of minima. Moreover, compared to the base design, the friction coefficient can be reduced by up to 45.2%