The contact network of granular materials is often divided into strong and weak subnetworks, which play different roles in micromechanics. Within the strong contact network, there exists the largest connected component, that is, the largest cluster, which may connect system boundaries and could be the most important structure in force transmission of the whole system. This paper concerns the particular features of the largest cluster in the strong contact network of granular materials, by considering the combining effects of loading path and particle shape. A series of true triaxial tests with various intermediate principal stress ratios are conducted for granular assemblies of different shaped particles using the discrete element method (DEM). Both the macroscopic stress-strain responses and the microscopic topological changes of the contact network are investigated. It is found that both particle shape and loading path will influence the shear strength and the topological features of the strong network. The threshold zeta$\zeta $ (the ratio to the average force) is used to distinguish the strong and weak networks, and a critical threshold can be identified by comparing the network-based metrics. The largest cluster within the strong network approaching the critical threshold can span the boundaries in each direction with minimum contacts, which occupies a small portion of particles and contacts but transmits a considerable portion of the applied stress. In addition, the similar contribution weight of the largest cluster to the deviatoric stress is identified for granular materials with different particle shapes.

The present study deals with the prediction of the strength of the glue joint stressed in tension on a local wood species called Terminalia Superba (Frake) assembled according to the bevel configuration using two artificial intelligence models namely ANFIS and LSTM. The experimental data obtained during tensile tests on a tropical species allowed us to determine the mechanical properties taken as structural parameters for the LSTM and ANFIS models. The results of the analysis show that among all the LSTM methods, LSTM 'ADAM' offers a low root mean square error (RMSE), a high accuracy (Acc) (RMSE = 2.16, Acc = 0.756). For all methods, ANFIS obtained the best results, a high R-squared and a very low root mean square error (RMSE) (R-squared = 0.979, RMSE = 0.51). This indicates that the prediction of the tensile strength of the adhesive joint is more satisfactory with ANFIS than with LSTM.

Agrichemical losses are a severe threat to the ecological environment. Additionally, some agrichemical compounds contain abundant salt, which increases the instability of formulations, leading to a lower agrichemical utilization and soil hardening. Fortunately, the biological amphiphilic emulsifier sodium deoxycholate alleviates these problems by forming stable Janus core-shell emulsions through salinity-driven interfacial self-assembly. According to the interfacial behavior, dilational rheology, and molecular dynamics simulations, Janus-emulsion molecules are more closely arranged than traditional-emulsion molecules and generate an oil-water interfacial film that transforms into a gel film. In addition, at the same spray volume, the deposition area of the Janus emulsion increased by 37.70% compared with that of the traditional emulsion. Owing to the topology effect and deformation, the Janus emulsion adheres to rice micropapillae, achieving better flush resistance. Meanwhile, based on response of the Janus emulsion to stimulation by carbon dioxide (CO2), the emulsion lost to the soil can form a rigid shell for inhibiting the release of pesticides and metal ions from harming the soil. The pyraclostrobin release rate decreased by 50.89% at 4 h after the Janus emulsion was exposed to CO2. The Chao1 index of the Janus emulsion was increased by 12.49% as compared to coconut oil delivery in soil microbial community. The Janus emulsion ingested by harmful organisms can be effectively absorbed in the intestine to achieve better control effects. This study provides a simple and effective strategy, which turns waste into treasure, by combining metal ions in agrichemicals with natural amphiphilic molecules to prepare stable emulsions for enhancing agrichemical rainfastness and weakening environmental risk.

Underground train-induced vibrations can cause nearby residents discomfort, damage to buildings, and disturbance for equipment. One of the most effective ways to reduce vibrations is using wave barriers along the propagation path of the waves. Many parameters are involved in determining the efficiency of these barriers: the barrier's dimension, distance from the source of vibration, and material property, to name a few. Simultaneous study of these parameters is complex since numerical analysis of alternatives is time-consuming. Therefore, in this study, by coupling the three-dimensional finite element method and an optimization algorithm, an attempt is made to provide a comprehensive solution to find the optimal wave barriers for Tehran metro line 4 as a case study. The current study evaluates two strategies: using in-filled trenches and topology-optimized barriers. In the first strategy, results show that soft-material trenches with maximum depth close to the observation point have the best performance. Further investigations on jet grout trenches show better performance in stiffer soil and lower train speed. Using dual trenches improves performance only up to 2%, so it does not provide a suitable option. For various practical reasons, there may be no tendency to use soft-material trenches, which perform well in vibration reduction. Therefore, in the second strategy, the improvement of a hard trench (jet grout) performance by topology optimization is investigated. According to this study, topology optimization is an effective method for improving barrier performance.