Search

Many practical engineering problems can be abstracted as corresponding function optimization problems. During the last few decades, many bionic algorithms have been proposed for this problem. However, when optimizing for large scale problems, such as 1000 dimensions, many existing search techniques may no longer perform well. Inspired by the social model of cockroaches, this paper presents a novel search technique called Cooperation cockroach colony optimization (CCCO). In the CCCO algorithm, two kinds of special biological behavior of cockroach, wall‐following and nest‐leaving, are simulated and the whole population is divided into wall‐following and nest‐leaving populations. By the collaboration of the two populations, CCCO accomplishes the computation of global optimization. The crucial parameters of CCCO are set by the self‐adaptive method. Moreover, a discussion on group model design is provided in this paper. The CCCO algorithm is evaluated with shifted test functions (1000 dimensions). Three state‐of‐the‐art cockroach‐inspired algorithms are used for the comparative experiments. Furthermore, CCCO is applied to a real‐world optimization problem concerning spread spectrum radar poly‐phase. Experiment results show that the CCCO algorithm can be applied to optimize large‐scale problems with the good performance.

Due to its exceptional quality as a biomedical metal, stainless steel is often utilized to produce a broad range of medical tools. The resistance of stainless steel to corrosion is a key indicator of how long and how effective it will serve its intended purpose, and it is an important factor in determining the biocompatibility of the material. However, due to the complex physiological environment within the human body, the corrosion management of medical-grade stainless steel is facing several challenges. In this article, an overview of the factors that influence the corrosion performance of medical-grade stainless steel is provided, and new technologies and methods that have been developed in recent years to improve the corrosion resistance are discussed. These cutting-edge methods are expected to improve the corrosion resistance and longevity of medical-grade stainless steel, providing strong support for the increased applicability of the material in the medical industry.

Elastomeric bearings consist of alternating rubber and metal spacer layers bonded via vulcanization technique. As important structural components in aerospace and bridge construction as well as other industries, the reliability of elastomeric bearings has a significant impact on the safety of the whole system. In this work, the finite element method is used to study the stress and displacement distributions of spherical laminated elastomeric bearings during helicopter flight, and then the theory of cumulative fatigue damage is used to analyze the fatigue lifetime of the bearing. By means of the comparative analysis of six single-load cases and a multiple-load case of the bearing categorized from the viewpoint of helicopter flight characteristics, the main influencing factors and how they affect the stress and displacement distributions are revealed. Finally, a durability test is conducted and the experimental results are well consistent with the calculated results, which indicates the prediction accuracy of the model. The work would be beneficial to the optimal design and reliable service of elastomeric bearings.