The influence of precipitated calcium carbonate on the strength and microstructure of red clay was studied. Precipitated calcium carbonate was added to red clay at ratios of 0%, 5%, 10%, 15%, and 20%. Shear tests were carried out on the samples to observe the effect of calcium carbonate on the mechanical properties of red clay. The results showed that, with increasing calcium carbonate content, the strength of red clay first decreased and then increased. The maximum strength was obtained for the sample with 20% calcium carbonate. Scanning electron microscopy (SEM) was used to observe the changes in microstructure caused by addition of calcium carbonate. The pores and cracks analysis system (PCAS) was used to quantitatively characterize the microstructure changes detected in SEM images. The addition of calcium carbonate decreased the pore area and increased the total number of pores of red clay. The incorporation of calcium carbonate caused the red clay particles to agglomerate. The higher the calcium carbonate content, the stronger the agglomeration of red clay particles in the soil samples.

Pillararene-based supramolecular membranes with the rose-petal effect and nanostructure-modulated tunable water adhesion was fabricated via integrating electrospraying with the breath figure approach.

To improve the performance of the PID controller for a steel strip deviation control system (SSDCS), an enhanced artificial bee colony algorithm (EABC) is proposed to optimize PID controller gains (EABC-PID). The proposed EABC changes the candidate solution equation to balance its explorative and exploitative capabilities. The experiment presents a detailed comparison of EABC-PID and four bio-inspired algorithms based PID controllers considering four types of objective functions. Simulation results show that EABC-PID proves to be superior for SSDCS compared to four bio-inspired algorithms based PID controller in terms of convergence, dynamic adjustment, and robustness.

The PID parameters determine the PID controller performance. A reformative artificial bee colony (RABC) algorithm is proposed for the PID parameter optimization problem. The algorithm balances the exploitation capability and exploration capability of the ABC algorithm by introducing a global optimal solution and improving the food source probability. The proposed algorithm is validated by simulation with six benchmark functions, and the results show that the RABC algorithm has higher search accuracy and faster search speed than other variants of the artificial bee colony algorithm. The RABC algorithm-optimized PID controller has better control with minimum overshoot and fast response, as verified by comparison with PSO-PID, DE-PID, and GA-PID methods in three typical systems.