Research on Volume Identification with the Method of Discharging at the Velocity of Sound

The method of volume identification in pneumatics was studied through theoretical analysis and experimental investigation. Regarding discharging from a container as a thermodynamic process with invariable index the dependence of the container’s volume on the pressure in the container and the index, during discharging at the velocity of sound, is deduced. Then through a lot of experiments, the value of index n of the process is found with a given precision and a specified volume range. Furthermore, the feasibility and practicability of this method are verified by experiments.

Using artificial neural network to predict velocity of sound in liquid water as a function of ambient temperature, electrical and magnetic fields

One of the main thermophysical properties of liquid water is velocity of sound.However,the effect of different externalities on velocity of sound in liquid water is not well known.Therefore,in current study,by designing an artificial neural network(ANN)velocity of sound in liquid water under different externalities is predicted.Selected externalities are ambient temperature from 272.65 K to 348.43 K,different electrical fields in range of 0 V/m to 4.03E+9 V/m and magnetic fields in range of 0-10.0594 T.To prepare of reference dataset for entry to ANN,numerical and experimental data as macroscopic reference data are extracted from microscopic characteristic of water HB strength.In order to achieve an appropriate ANN,ANN architecture sensitivity analysis is conducted by using an iterative algorithm.Learning procedure in the selected feed-forward back propagation ANN is done by hyperbolic transfer functions.Also,Levenberg-Marquardt algorithm is utilized for the optimization process.ANNs output showed that the maximum MSE in prediction of velocity of sound is 0.00066.Also,the minimum of correlation coefficient in prediction of velocity of sound is 0.99131.Based on the ANNs outputs,weights and bias,an equation to predict of velocity of sound in liquid water under intended externalities is proposed.Also,according to weight sensitivity analysis input of electrical fields with 63%relative importance percentage has a grater impression on the response variable of velocity of sound in liquid water.©2016 Shanghai Jiaotong University.Published by Elsevier B.V.

Validation for equation of state in wide regime:Copper as prototype

In this paper we introduce the wide regime equation of state(WEOS)developed in Institute of Applied Physics and Computational Mathematics(IAPCM).A semi-empirical model of the WEOS is given by a thermodynamically complete potential of the Helmholtz free energy which combines several theoretical models and has some adjustable parameters calibrated via some experimental and theoretical data.The validation methods of the equation of state in wide regime are presented using copper as a prototype.The results of the WEOS are well consistent with the available theoretical and experimental data,including ab initio cold curve under compression,isotherm,Hugoniot,off-Hugoniot and sound velocity data.It enhances our confidence in the accuracy of the WEOS,which is very important for the validation and verification of equation of state in high temperature and pressure technology.

Thermoelectric enhancement of p-type Si_(80)Ge_(20) alloy via co-compositing of dual oxides:Respective regulation for power factor and thermal conductivity byβ-Ga_(2)O_(3) and SiO_(2) aerogel powders

Si-based thermoelectric(TE)materials are exhibiting remarkable perspectives in self-energized applications with their special advantages.However,the relatively high total thermal conductivity(κ)prevents their TE enhancement.Here,a strategy of co-compositing dual oxides was implemented for enhancing the TE properties of p-type Si_(80)Ge_(20) bulks.Composited Ga2O_(3) was demonstrated to enhance the power factor(PF)due to the crystallization-induced effect of produced Ga by decomposition on SiGe matrix.Associating with compositing SiO_(2) aerogel(a-SiO_(2))powder,not only introduced the fine amorphous inclusions and decreased the grain size of host matrix,but also various nano morphologies were formed,i.e.,nano inclusions,precipitations,twin boundaries(TBs),and faults.Combining with the eutectic Ge,hierarchical scattering centers impeded the phonon transport comprehensively(decreasing the phonon group velocity(a v)and relaxation time)for reducing the lattice-induced thermal conductivity(lκ).As a result,a minimumκof 2.38 W·m^(−1)·K^(−1) was achieved,which is significantly dropped by 32.6%in contrast with that of the pristine counterpart.Ultimately,a maximal dimensionless figure of merit(ZT)of 0.9 was achieved at 600℃,which is better than those of most corresponding oxide-composited Si-based bulks.

An Adaptive SVP Simplification Based on Area Difference

Sound velocity profile(SVP)data is indispensable in the multi-beam data processing.The sampling density is of great importance for SVP to represent the vertical variation of sound velocity accurately and guarantee the accuracy of sound ray tracing(SRT).However,the SVP also affects the SRT efficiency significantly,especially in deep-sea multi-beam sounding data processing.To improve SRT efficiency and ensure SRT accuracy,an adaptive SVP simplification method based on area difference is proposed in this article.Firstly,the relationship between the area difference of the raw SVP and the simplified one and SRT bias is studied,and the relationship model of them is built.Then,by considering the constraint of SRT accuracy,the SVP simplification method and the simplifying SVP procedure SVP are given.Finally,a deep water experiment is conducted to verify the proposed method.Compared to the existing method,the proposed method improves the robustness,feasibility of SVP simplification as well as the accuracy and efficiency of SRT.