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Gradient and nongradient optimization algorithms are currently available for structural design in structural optimization course. Despite the successful application of gradient algorithm in structural optimization, nongradient algorithm is also extensively adopted to solve the structural optimization problem. However, the efficiency of nongradient algorithm has caused a heated debate recently. To clarify this issue for the graduate students, sequential linear programming and genetic algorithm are, respectively, chosen as the representatives of gradient and nongradient algorithms to solve truss size optimization problem. Firstly, the size optimization formulations of truss structure for sequential linear programming and genetic algorithm are summarized, respectively. Secondly, an educational finite element software for truss structure is developed by using the object-oriented programming to create the software framework. This study aims to provide an open-source, extensible, and benchmarking software, which do assist the students to understand the structural optimization process in engineering education. Finally, two benchmarking examples are introduced to compare the efficiency and accuracy of sequential linear programming and genetic algorithm.

Rotary-wing unmanned aerial vehicles (UAVs) are widespread in both the military and civilian applications. However, there are still some problems for the UAV design such as the long design period, high manufacturing cost, and difficulty in maintenance. Therefore, this paper proposes a novel design method to obtain a lightweight and maintainable UAV frame from configurable design to detailed design. First, configurable design is implemented to determine the initial design domain of the UAV frame. Second, topology optimization method based on inertia relief theory is used to transform the initial geometric model into the UAV frame structure. Third, process design is considered to improve the manufacturability and maintainability of the UAV frame. Finally, dynamic drop test is used to validate the crashworthiness of the UAV frame. Therefore, a lightweight UAV frame structure composed of thin-walled parts can be obtained and the design period can be greatly reduced via the proposed method.

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In this Note, we develop a real-time magnetic field imaging system by employing a multi-magneto-inductive (MI) sensor array. The sensor array consists of 3 × 3 tri-axial MI sensors, which we constructed by using three sensor coils. Outputs from several rows of sensors are routed to a master-controller responsible for data pre-processing and data reconstruction. The data are streamed to a host computer via a universal serial bus interface, and the image can be generated and displayed at a rate of several frames per second. The magnetic field imaging is implemented on a knowledge of the MI sensors’ response, magnetic field perturbations, and the nature of the ferromagnetic object respecting permeability and conductivity. The performance of the system has been further evaluated by extensive numerical modeling of magnetic field distribution patterns with partial differential equation solution. The proposed magnetic field imaging system can be employed in many potential applications, for instance, medicine, security screening, quality assurance, and other areas of nondestructive evaluation, designs associated with magnetic fields, teaching, and research.