In the process of sustainable development within modern agriculture, in order to ensure that agricultural production has adequate water resources, canal lining (CL) is often used to transport water in order to reduce water seepage, thus promoting the sustainable utilization of water resources. However, due to the influence of the terrain, environment, human factors and other factors, the CL often suffers a certain degree of damage. Therefore, it is necessary to evaluate the serviceability of the CL, so to realize the sustainable use of the CL strategy. Aiming at the weight assignment of CL evaluation indices that are subjective and not combined with actual index data, a weight calculation method based on the Analytic Hierarchy Process (AHP)–simple correlation function (SCF) method was proposed, and game theory was used to achieve combination weighting. For the evaluation indices with the characteristics of fuzziness and randomness, the cloud model (CM) was used to comprehensively consider these characteristics in order to realize the evaluation. Finally, a method to measure serviceability of CL based on AHP–SCF–CM was proposed. Taking a CL project in China as an example, this method was used to evaluate the serviceability of the CL. The evaluation result showed that the serviceability of the CL was poor, and the qualitative evaluation result was consistent with the actual damage condition of the project; meanwhile, a comparative study was performed in combination with the AHP–Entropy Weight (EW)–unascertained measurement theory (UMT). The quantitative evaluation results of the two methods displayed the same grade of serviceability, which verifies that the method proposed in this paper is more reasonable, objective and feasible from both qualitative and quantitative perspectives. Furthermore, the evaluation results lay the foundation for subsequent maintenance and fault prevention of the canal.
With the acceleration of infrastructure construction in various countries, more and more highway tunnels have been built. As a permanent structure to maintain the long-term stability and durability of the tunnel, the tunnel lining structure (TLS) is prone to durability damage in the later operation process, which affects the safety of traffic and the whole loading capacity of the tunnel, so it is very important to evaluate the durability of the TLS. Nowadays, the TLS durability evaluation methods ignore the ambiguity and randomness of the lining structure (LS) durability evaluation index, which have certain limitations. In order to evaluate the durability of highway TLS scientifically and rationally, this paper proposes a method for evaluating the durability of highway TLS based on the matter-element extension (MEE)- simple correlation function (SCF) method- cloud model (CM). A case study was carried out by combining the advantages of the above three methods, a LS durability evaluation model was established, and based on the relevant data from the actual inspection of a highway tunnel lining durability disease in China, the model was used to evaluate the durability of the lining of this highway tunnel, and the durability grades were equivalently divided into five grades: in good shape(I), slightly damaged(II), medium damaged(III), severely damaged(IV), extremely dangerous(V). The result show that this tunnel lining belongs to IV, and the result of this evaluation method is in accordance with the actual damage condition of the project, and the accuracy reaches 92.75%. At the same time, a comparative study was carried out in combination with the AHP-Extenics to verify the reasonableness and feasibility of this method. This study provides a new method for durability evaluation of LS, offers a theory basis for judging the durability of highway TLS, and lays a foundation for subsequent maintenance and prevention.
Artificial ground freezing (AGF) is a widely used method in coastal tunnel construction and reinforcement. With more and more underground construction in coastal areas, clay–sand combined formation, which is common in coastal areas, brings more challenges to AGF. In this paper, the frost–thaw characteristics of soft clay during AFG under the construction of combined formation seepage were studied by model test. It was found that the shape of the freezing curtain changed under the condition of seepage, and the water content of the upper soft soil layer decreased markedly after settlement. Subsequently the micro characteristics of melted soil by CT were also conducted for further mechanism analysis, and it was indicated that the distribution of CT number had obvious segmentation characteristics along the height. Finally, the 3D structure of melted clay was reconstructed, and a method was proposed to calculate freeze–thaw settlement through CT numbers.
In order to investigate the main influencing factors and development rules of the shear performance of high strength concrete (HSC) beams without web reinforcement under concentrated loads, analyze and compare the rationality of the China and American Code formulas and Zsutty formula, in this paper, 303 sets of experimental data about the shear test of HSC beams without web reinforcement at home and abroad were selected, based on these experimental data, the calculation method of the shear capacity of HSC beams without web reinforcement was discussed. The results showed that the measured shear bearing capacity of HSC beams without web reinforcement gradually increases with the decrease of the shear-span ratio. The nominal shear stress of HSC beams without web reinforcement gradually increases with the increase of concrete strength, the increase of longitudinal reinforcement ratio and the decrease of section height. The shear bearing capacity formula proposed by Zsutty is the most accurate prediction than other formulas. Based on the experimental data and considering the influence of the longitudinal reinforcement ratio on the shear bearing capacity of structure, a new calculation formula for the shear bearing capacity of HSC beams without web reinforcement under concentrated loads was obtained by regression analyze, and this formula is more comprehensive than the other three calculation formulas, moreover, the calculation results are more reasonable.
Orthogonal experiments were performed to study the flexural strength of an eco‐friendly concrete containing fly ash (FA) and ground granulated blast‐furnace slag (GGBFS). The effects of different test parameters, such as water‐binder ratio (W/B), FA content, GGBFS content, sand ratio, gravel gradation, and curing time, on the flexural strength of the concrete were analyzed. The significance level of each influencing factor and the optimal mixing proportion of the concrete were determined by range analysis and hierarchy analysis. It was found that the W/B ratio had the greatest influence on the flexural strength of the concrete. The flexural strength of the concrete decreased gradually with the increase of W/B. The GGBFS content and the sand ratio had a greater influence in the early stage of concrete curing. The middle and later stages of concrete curing were mainly affected by gravel gradation and the FA content. A flexural strength prediction model of the concrete was developed based on a backpropagation neural network (BPNN) and a support vector machine (SVM) model. It was noticed that the BPNN and SVM models both had higher accuracy than the empirical equation, and the BPNN model was more accurate than the SVM model.
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