In-depth study on the solubility of elemental sulfur in sour gas mixtures based on the Chrastil's association model

Accurately predicting the solubility of elemental sulfur in sour gas mixtures is a primary task.As a current and widely-used model on the solubility of elemental sulfur in sour gas mixtures,Chrastil's association model has a big error in the process of predicting experimental data based on different fitting methods.This paper combined with experimental data reported by relevant scholars about elemental sulfur solubility in sour gases and selected density,temperature and pressure as three important influential factors.According to different fitting methods,we can calculate the correlation parameters in Chrastil's model.Then different solubility formulas can be used to predict the solubility of elemental sulfur in sour gas mixtures.Through in-depth research and analysis of Chrastil's solubility model from numerical aspects,it's easy to find the irrationality about Chrastil's solubility model and fitting methods.Especially in fitting methods,further improvement of the fitting method is proposed and used to predict the solubility of elemental sulfur in sour gas mixtures.The calculation results show that some improvements of the predicting precision have been achieved by using the improved fitting method in Chrastil's association model.

Hydraulic metal structure health diagnosis based on data mining technology

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

Tracking a maneuvering target in clutter with out-of-sequence measurements for airborne radar

There are many proposed optimal or suboptimal al- gorithms to update out-of-sequence measurement（s） （OoSM（s）） for linear-Gaussian systems, but few algorithms are dedicated to track a maneuvering target in clutter by using OoSMs. In order to address the nonlinear OoSMs obtained by the airborne radar located on a moving platform from a maneuvering target in clut- ter, an interacting multiple model probabilistic data association （IMMPDA） algorithm with the OoSM is developed. To be practical, the algorithm is based on the Earth-centered Earth-fixed （ECEF） coordinate system where it considers the effect of the platform＇s attitude and the curvature of the Earth. The proposed method is validated through the Monte Carlo test compared with the perfor- mance of the standard IMMPDA algorithm ignoring the OoSM, and the conclusions show that using the OoSM can improve the track- ing performance, and the shorter the lag step is, the greater degree the performance is improved, but when the lag step is large, the performance is not improved any more by using the OoSM, which can provide some references for engineering application.

Thermodynamic assessment of the Bi-Mg binary system

The Bi-Mg binary system had been assessed by adopting the ionic melt and the modified quasi-chemical models to describe the liquid phase with short range ordering behavior. In general considerations of the development of the thermodynamic database of the multi-component Mg-based alloys and the consistency of the thermodynamic models of the related phases, the Gibbs energy descriptions of all the phases in the Bi-Mg binary system were reasonably re-modeled and critically re-assessed in the present work. Especially for the liquid phase, the associate model was used with the constituent species Bi, Mg and Bi2Mg3. The Mg-rich terminal phase hcp_A3 was modeled as a substitutional solution following Redlich-Kister equation and the Bi-rich terminal phase Rhombohedral_A7 was treated as a pure Bi substance since the extremely small solubility of Mg in Bi. The low and high temperature non- stoichiometric compounds β-Bi2Mg3 and α-Bi2Mg3 were described by the sublattice models （Bi,Va）2Mg3 and （Bi）1（Bi,Va）3Mg6 respectively based on their structure features. A set of self-consistent thermodynamic parameters of the Bi-Mg system was obtained and the experimental thermodynamic and phase equilibrium data were well reproduced by the optimized thermodynamic data.