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The purpose of this paper is to provide a fast, efficient, and low-cost digital design method for the design of suction mufflers in refrigerator compressor plants. The main content of this paper is to establish a three-dimensional acoustic model of the compressor suction muffler by using Solidedge software, combine the upper suction port of the muffler with the valve group, then use Hypermesh to mesh the acoustic model and carry out the theoretical calculation, transform the control differential equation in the solution domain into the integral equation on the boundary by Green's function, discretize the boundary and carry out the numerical solution. The boundary is discretized and solved numerically. The transfer matrix quadrupole parameters are used to describe the acoustic components, and the transfer matrix of the discontinuous cross section is obtained to transform the complex system into a chain superposition of simple systems. The dependent variable in the partial differential equation to be solved is changed to a linear system of equations, and the transmission loss is calculated from the incident and transmitted sound pressure. The theoretical calculation of the transmission loss of the muffler is performed using LMS. Virtual. Lab software and the design solution is continuously optimized using this software. The experimental analysis shows that the designed muffler is printed and trimmed by 3D printing equipment and loaded onto the transmission loss test bench for experimental testing, and the highest theoretical value differs from the test result by 10dB.

Aiming to tackle the problems of low classification accuracy, difficult data processing, long analysis time, and the influence of subjective consciousness of traditional Baijiu (Chinese liquor), this paper reports a method based on the combination of laser-induced breakdown spectroscopy with high-frequency ultrasonic atomization system (AS-LIBS) and optimized grid search cross validation (Opt-GSCV) for high-precision and rapid classification of Baijiu of different dimensions. Multi-dimensional high-precision classification of 23 Baijiu samples with different series, degrees, and production dates from Shanxi Xinghuacun Fen Wine Factory Co., Ltd was performed. By studying the growth and evolution mechanism of plasma generated by laser excitation, a new method of Baijiu spectral signal acquisition was realized by combining LIBS with Baijiu detection. Aiming at addressing the shortcomings of high breakdown thresholds and poor signal stability due to the direct breakdown of Baijiu with high ethanol content, a high-frequency atomization system based on ultrasonic technology is proposed to realize the efficient extraction of Baijiu plasma spectral signals. With regard to the selection of the number of nodes, weights and thresholds of the implicit layer of the back-propagation (BP) network, an optimization model based on the combination of the particle swarm optimization (PSO) algorithm combined with the genetic algorithm (GA) is proposed to realize the construction of the BP optimal network architecture. By constructing a secondary optimization seeking network model based on OptGSCV, the technical problem of mismatch between optimal parameter selection and optimal network construction is solved, and a new network integrating an intelligent qualitative analysis algorithm and a traditional classification algorithm is realized. The experimental results show that the proposed OptGSCV quadratic optimization network combined with the AS-LIBS multidimensional Baijiu high-precision classification model not only introduces an innovative and high-efficiency detection method for the Baijiu industry, but also provides important technical support and new ideas for the key areas of food safety production and Baijiu quality control. [ABSTRACT FROM AUTHOR]

A facile and efficient method to synthesize thioethers from sulfonyl chlorides and benzylic trimethylammonium salts is presented. This protocol provides a simple and direct approach to realize the reductive coupling reaction of readily available sulfonyl chlorides with benzyl ammonium salts in the presence of triphenylphosphine along with base via C−N cleavage of benzyl ammonium salts. This reaction features mild conditions and good substrate compatibility to afford thioethers in moderate to good yields. [ABSTRACT FROM AUTHOR]

Focusing on the problems of complicated sample processing and long detection time of traditional soil composition testing in mining areas, this paper proposes a rapid soil classification method of grid search and cross validation (GSCV) quadratic optimization-seeking network combined with magnetic field enhanced laser-induced breakdown spectroscopy (MF-LIBS), which can quickly and accurately classify standard soil samples from 10 different mining areas. First, the effects of different magnetic field strengths on the enhancement factor, signal-to-noise ratio (SNR) and plasma electron temperature of the characteristic spectral lines were investigated. Next, 5400 12 248-dimensional spectral data under the 0.98 T magnetic field constraint were preprocessed using principal component analysis (PCA). Then the back propagation (BP) network was optimized by combining the sparrow search algorithm (SSA) external optimization network with the genetic algorithm (GA) internal optimization network. Finally, the hyperparameters of the optimal network architecture are refined by GSCV for secondary optimization. By comparing with the unoptimized network, the results show that the classification accuracy of GSCV-SSA-GA-BP is 0.99997, the precision is 0.99977, the recall is 0.99981, and the F1-score is 0.99979. The proposed technique of GSCV quadratic optimization network combined with MF-LIBS soil classification can not only play an important role in soil research, but also provide a new scheme for rapid detection and high-precision qualitative analysis of soil components. [ABSTRACT FROM AUTHOR]