No abstract

Mining scrapers as an important part of scraper conveyors are highly prone to wear and fatigue failure. A new scraper capable of turning sliding friction into rolling friction was designed to limit wear and reduce failure rate. To determine the safety and reliability of the new scraper, numerical pulling force measurement was conducted on its physical model and finite element analysis was performed on its 3D model based on SolidWorks Simulation. The results were then compared with data of the traditional scraper. Numerical pulling force measurement results indicated impressively lower friction for the new scraper. Stress, strain, and displacement distributions obtained by static stress analysis based on SolidWorks Simulation proved conformance with the strength and deflection standards. Damage percentage and total life nephograms yielded from fatigue analysis indicated no significant life reduction. Numerical pulling force measurement combined with analysis based on SolidWorks Simulation can help reduce the production cost and development cycle. It plays a great role in determining the safety, reliability, and stability of the new scraper.

The software reliability modeling is of great significance in improving software quality and managing the software development process. However, the existing methods are not able to accurately model software reliability improvement behavior because existing single model methods rely on restrictive assumptions and combination models cannot well deal with model uncertainties. In this article, we propose a Bayesian model averaging (BMA) method to model software reliability. First, the existing reliability modeling methods are selected as the candidate models, and the Bayesian theory is used to obtain the posterior probabilities of each reliability model. Then, the posterior probabilities are used as weights to average the candidate models. Both Markov Chain Monte Carlo (MCMC) algorithm and the Expectation-Maximization (EM) algorithm are used to evaluate a candidate model's posterior probability and for comparison purpose. The results show that the BMA method has superior performance in software reliability modeling, and the MCMC algorithm performs better than EM algorithm when they are used to estimate the parameters of BMA method.

Mining scrapers as an important part of scraper conveyors are highly prone to wear and fatigue failure. A new scraper capable of turning sliding friction into rolling friction was designed to limit wear and reduce failure rate. To determine the safety and reliability of the new scraper, numerical pulling force measurement was made on its physical model and finite element analysis was performed on its 3D model based on SolidWorks Simulation. The results are then compared with data of the traditional scraper. Numerical pulling force measurement results indicated impressively lower friction for the new scraper. Stress, strain, and displacement distributions obtained by static stress analysis based on SolidWorks Simulation proved conformance with the strength and deflection standards. Damage percentage and total life nephograms yielded from fatigue analysis indicated no significant life reduction. Numerical pulling force measurement combined with analysis based on SolidWorks Simulation can help reduce the production cost and development cycle. It plays a great role in determining the safety, reliability, and stability of the new scraper.

Based on the complex network analysis technology, the core drugs and their compatibility rules of traditional Chinese medicine for the prevention of viral respiratory infectious diseases were excavated, and the core prescriptions of traditional Chinese medicine for the prevention of viral respiratory infectious diseases were analyzed. Firstly, the standard database of prescriptions for viral respiratory infectious diseases is constructed by combining the relevant theories of traditional Chinese medicine and database. Secondly, at the micro level, the weighted correlation network of traditional Chinese medicine prescriptions for three typical diseases COVID-19, H1N1 and SARS is constructed, and at the macro level, the weighted correlation network of traditional Chinese medicine prescriptions for viral respiratory infectious diseases is constructed. Then use Python3.6 software to analyze the node strength and compatibility of the data, use Gephi9.2 software to visualize the data, and draw a schematic diagram of complex network data analysis. By using the relevant theoretical knowledge of complex network, statistics and pharmacology, this paper studies and analyzes the weighted association network of traditional Chinese medicine prescriptions of single disease and multiple diseases from the aspects of structure and function. dig out the broad-spectrum core prescription of traditional Chinese medicine for the prevention of viral respiratory infectious diseases, and provide data reference for the active prevention of viral respiratory infectious diseases. So as to provide more scientific ideas and basis for TCM experts in formulating preventive prescriptions for traditional Chinese medicine.