No abstract

No abstract

No abstract

The effect of acid corrosion on crack propagation of concrete beams was theoretically studied by the method of crack extension resistance curve. Based on this method, a calculation approach was proposed to determine fracture stress intensity factors in crack propagation of concrete beams. Loop iteration analysis was carried out to calculate maximum bearing capacity load, unstable crack toughness, resistance toughness curve, cohesive toughness curve and load-crack mouth opening displacement. Both bilinear and nonlinear softening traction-separation curves were adopted for each of these calculation parameters. The analysis results of each showed the effect of acid corrosion degrees. The influence of acid corrosion on fracture properties was discussed through the calculated results of cohesive toughness curves. These five kinds of simulated results were basically consistent, before the load attained the maximum value. However, with further crack propagation, cohesive toughness of nonlinear softening model was significantly larger than that of bilinear softening model, and the descending branch of P-CMOD curve by nonlinear law is higher than that by bilinear law. To validate the approach, tests of specimens under six different corrosion periods were experimentally studied, using three-point bending notched concrete beams soaked in sulphuric acid solution. The Double-K fracture parameters were investigated based on the test results, and load-crack mouth opening displacement curves for different acid conditions were obtained using synchronous sampling of a load sensor and clip-gauge. Numerical results by bilinear softening model showed a good correlation with the experimental ones.

A large number of studies have been conducted to examine China’s CO2 emissions problem disaggregated to the city level. However, few studies have delved further into the black box of economic production to examine the characteristics of CO2 emissions at the city supply chain level. In the context of the reality that Beijing takes the lead in achieving CO2 emissions reduction, this study decomposes CO2 emissions change in Beijing at three levels: overall, supply stage, and supply chain, using structural decomposition analysis (SDA) and structural path decomposition (SPD), filling the gap in urban CO2 emissions studies. The results show that: (i) energy consumption intensity is the most significant driver of emissions reduction, while per capita final demand is the largest factor in increasing emissions; (ii) Beijing’s emissions reduction contribution is mainly reflected in the first supply stage (76.50%) and the second supply stage (18.85%); (iii) the expansion of domestic exports and thus greater demand for transportation is significant in emissions increase supply chains; (iv) the improvement of the demand structure for electricity from domestic exports contributes a large part in emissions reduction supply chains; (v) the existence of many offsetting effects, such as the ebb and flow of domestic exports on the demand for different products, has led to the loss of emissions reduction. Finally, corresponding policy recommendations are presented from the energy, industry, and demand perspectives. Our study will provide assistance in developing more microscopic policies to reduce emissions and replicating the Beijing experience.

The stable development of agriculture is of great significance to alleviate the problem of food insecurity. As a significant yield zone along the Belt and Road Initiative, the Black Sea area is an ideal object for China to invest in agriculture. Therefore, it is particularly important to evaluate the agricultural investment environment in this region reasonably and effectively. This paper selects the countries around the Black Sea as the research objects and uses an Entropy‐ technique for order preference by similarity to an ideal solution (TOPSIS) model to analyse the agricultural investment environment and its influencing factors. The results show that: (a) There are significant differences in the agricultural investment environment among the six countries around the Black Sea, ranking as follows: Russia(0.5583) > Bulgaria(0.4782) > Georgia(0.4072) > Ukraine(0.3539) > Turkey(0.3493) > Romania(0.3167); (b) in primary indexes, agricultural production conditions, political environment, and social development have a relatively large impact, among which agricultural production is the most important factor; (c) among the secondary indexes, human capital index and railway (total kilometres) have high levels of impact. Unemployment rate, inflation rate and employment in agriculture (% of total employment) also have a significant impact. On this basis, suggestions are put forward according to the research results.

No abstract

No abstract