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With the continuous development of urbanization and industrialization in the world, concrete is widely used in various engineering constructions as an engineering material. However, the consequent problem of durability of concrete structures is also becoming increasingly prominent. As an important additional measure, a protective coating can effectively improve the durability of concrete performance. Moreover, the uniformity of the concrete surface coating will directly affect its protective effect. Therefore, we propose a nondestructive inspection and evaluation method of coating uniformity based on infrared imaging and cluster analysis for concrete surface coating uniformity detection and evaluation. Based on the obtained infrared images, a series of processing and analysis of the images were carried out using MATLAB software to obtain the characteristics of the infrared images of the concrete surface. Finally, by extracting the temperature distribution data of the pixel points on the concrete surface, an evaluation method of concrete surface coating uniformity based on a combination of cluster analysis and hierarchical analysis was established. The evaluation results show that the determination results obtained by this method are consistent with the actual situation. This study has a positive contribution to the testing of concrete surface coating uniformity and its evaluation.

Novel divergent domino annulation reactions of sulfur ylides with aryldiazonium tetrafluoroborates have been developed, affording various tetra- and trisubstituted pyrazole derivatives in moderate to good yields. Three molecules of sulfur ylides were applied as C1 synthon to construct the complex products with five new chemical bonds formed in these one-pot reactions.

In this paper, the uncertainty of diesel generator (hereinafter referred to as DG) output and load demand is studied by multi scenario analysis. Firstly, this paper studies the timing characteristics of DG power generation and load demand, and describes the annual and daily distribution of photovoltaic power generation, wind power generation and load demand. Then it introduces the method of multi scene analysis, describes the process of dealing with the uncertainty in multi scene in detail, and generates enough scenes through the density function of classification probability to get the probability of each scene. Finally, H-K compound clustering algorithm is used to solve the above problems. The scale scene is compressed to get a typical “planning scene”.

This paper studies the relationship and differences between carbon emissions and industrial development in four countries with different development levels from a global perspective. First, the Tapio decoupling model was established, and the overall dependence of countries of various development levels on carbon emissions was analyzed from strong to weak. Then, establish a panel data model to study the influencing factors of carbon emissions in countries with different development levels from 2015 to 2019. The results show that the added value of industry and agriculture has a significant positive effect on carbon emissions in countries of various development levels, and forest area has a significant negative effect on carbon emissions. Developed countries are still the largest emitters. Therefore, industrial and agricultural production is still the most important factor affecting carbon emissions, and the increase in forest area helps reduce the impact of carbon dioxide.

In the intelligent distribution network environment, the demand side resources (DSR) are the electric vehicle, energy storage, controllable load and other resources located in different locations, showing the characteristics of small single capacity and decentralized layout. How to build a multi time scale integrated scheduling framework of demand side resources and renewable energy, to schedule the distributed demand side resources in an orderly manner, and to realize the efficient integration of demand side resources and renewable energy, are the key problems of demand side resources participating in grid scheduling. Based on this, this paper proposes a multi time scale integrated scheduling method based on hierarchical scheduling for DSR and renewable energy in intelligent distribution network, and uses the modified cuckoo search algorithm (MCS) to solve the problem. The effectiveness of the proposed model and algorithm is verified by the integrated scheduling of electric vehicles and renewable energy in intelligent distribution network.