There are more and more newly established substations and transmission lines, contributing to subsequent and reliable power supply and socioeconomic development. Violations are prone to occur on construction sites arousing safety hazards. This paper describes a video-based approach to identifying safety risks on site, building typical security hazards and violations feature libraries, and developing a BP neural network algorithm to identify safety risks. That approach can effectively improve the efficiency of on-site safety inspections on power infrastructure sites and contribute to the compliance of power infrastructure operations.

With the development of the fourth-generation nuclear power technology, heat pipe cooled reactor (HPCR) plays an important role in achieving carbon neutrality and actively and orderly developing nuclear power. In this paper, the HPCR will be reviewed. Firstly, a basic introduction of the HPCR and heat pipes will be given. Then, the research status of the HPCR is introduced according to the application. After that, the research status of HPCR in physical and thermal hydraulic characteristics is introduced. Finally, some discussions and recommendations are put forward for the further study.

Rapid assembly modeling system is a tool that needs to be used in the design process. Because the three-dimensional modeling is intuitive, powerful and can be used in actual engineering, it is more and more used in manufacturing production. In the rapid development of computer-aided design technology, CAD/CAM software is the most commonly used and most widely used modeling tool. Therefore, the purpose of this article to study the rapid assembly modeling in the computer-aided design system is to improve the performance and accuracy of the assembly system and promote the high-quality production of products. This article mainly uses experimental method and case analysis method to test the assembly system designed in this article. The experimental results show that, under low temperature conditions, the relative error and absolute error of the assembly size are in a small space, which meets the actual requirements. Therefore, the system designed in this paper can be used in practice.

Surrogate models and adaptive methods can release the huge computational burden of structural reliability analysis. However, it is very difficult to guarantee the accuracy of uncertainty quantification, especially when noises are contained in samples, which may greatly reduce the confidence of reliability analysis. In this study, we propose a novel Nested Stochastic Kriging (NSK) model method with response noise parameters decoupled from other surrogate model parameters, which can significantly improve the accuracy of uncertainty quantification and modeling efficiency. The proposed NSK is for deterministic data with response noise, aiming at reliability analysis. Various types of uncertainty can be identified by the NSK, including the conditions of known and unknown, constant and variable variances. Moreover, a local sample verification method is established to improve the accuracy of uncertainty quantification. To further improve the accuracy of reliability analysis, an adaptive NSK framework is established with new samples added, and then reliability analysis can be conducted. Through several numerical examples, it can be seen that the NSK always provides the most accurate results with the fewest analysis calls.

In order to obtain a precise dynamic structural FE model for dynamic analysis, FE model updating is usually used to correct uncertainty parameters for an initial FE model using incomplete measured data. Despite numerous studies concerning FE model updating, the computational cost is still a challenging issue for the repeated eigenvalue structures. Firstly, an improved modal assurance criterion is proposed to evaluate the similarity of mode shapes for the repeated eigenvalue structures in this paper. And then, a novel ROM-based FE model updating framework consisting of an off-line phase and an on-line phase is proposed. In the off-line phase, a reduced-order basis is constructed by extracting primary components of a snapshot matrix using a proper orthogonal decomposition technique. The snapshot matrix represents a collection of static displacement vectors of the FE model under radial nodal loads, which are determined by incomplete measured mode shapes. In the on-line phase, FE model updating is performed via a reduced-order model with much cheaper computational cost. Finally, a numerical example and an experimental example demonstrate the accuracy and efficiency of the proposed framework. The results indicate that the proposed ROM-based FE model updating framework is more efficient and stable than the FOM-based FE model updating framework. (C) 2020 Elsevier Ltd. All rights reserved.

Based on the demand of impact attenuation and weight reduction for launch vehicles' separation system, three types of aluminum alloy circular shock isolation frames with triangular grid stiffeners have been designed, optimized and analyzed for load-bearing capability. According to the real geometric configuration, the finite element models of the shock isolation frames have been established through FEM parametric modelling based on Python and Abaqus. Combined with the Downhill Simplex algorithm on Isight, the three parameterized models have been optimized with the aim of load-bearing and weight reduction. The optimization results showed that the three optimized frames had the weight reduction of 5.29 kg, 5.94 kg and 6.64 kg compared with the original configurations respectively. Moreover, because of the limitation of shin thickness, the decisive factor affecting the optimization results was the limitation of structural buckling coefficient.

For the structural dynamic analysis of complicated beam-type structures, a detailed finite element model with large number of degrees of freedom is almost impossible to be used due to the huge computational cost and storage requirements. Therefore, a novel reduced-order model is proposed to determine the natural frequencies of the beam-type structures in this study, which is established by using a reduction basis along with the polynomial interpolation function. The basic idea is to convert the displacements of finite element model nodes in each cross section to a small set of nodes with a few generalized degrees of freedom. The proposed reduced-order model can gain a significant reduction of computational cost without sacrifice of accuracy; moreover, it has the ability to identify shell lobe-type modes and coupled modes. Several numerical case studies for different beam-type structures, including thin-walled cylinder, stiffened shells, and thin-walled cylinder with cutouts, are studied, and the outcomes are validated by benchmark studies.

This paper deals with the bending of rectangular thin plates point-supported at three corners using an analytic symplectic superposition method. The problems are of fundamental importance in both civil and mechanical engineering, but there were no accurate analytic solutions reported in the literature. This is attributed to the difficulty in seeking the solutions that satisfy the governing fourth-order partial differential equation with the free boundary conditions at all the edges as well as the support conditions at the corners. In the following, the Hamiltonian system-based equation for plate bending is formulated, and two types of fundamental problems are analytically solved by the symplectic method. The analytic solutions of the plates point-supported at three corners are then obtained by superposition, where the constants are obtained by a set of linear equations. The solution procedure presented in this paper offers a rigorous way to yield analytic solutions of similar problems. Some numerical results, validated by the finite element method, are shown to provide useful benchmarks for comparison and validation of other solution methods.

With regard to the requirements of performance and lightweight design for future vehicles under huge axial compres-sion, a novel long circle lightening hole model was developed, for middle rings of skin-stringer structures, which can produce a re-duction of structural weight accompanied with a slight increase of load-carrying capacity. Since the post-buckling analysis of such a skin-stringer structure is time-consuming, an optimization formulation for lightening holes of skin-stringer structures was established based on RBF model. Results of the illustrative example indicate that, the long circle lightening hole model has higher structural ef-ficiency and designability, compared to the initial design and the traditional circle hole model. It is expected that this novel lighte-ning hole configuration can be utilized in the skin-stringer structure design of future heavy-lift launch vehicles.

In this paper, a parametric model of a stiffened shell is built with Python language in Abaqus. The explicit FEM is used as an analysis tool in the optimal design of stiffened shell structures. The skin thickness and stiffener size are designed and optimized. The optimization contains two strategies: one is to obtain the minimum mass subjected to the structural performance, and the other is to obtain the high structural performance subject to the mass. In spite of the advantages of computer capacity and speed, the enormous computational cost of complex simulations makes it impractical to rely exclusively on simulation codes for the purpose of design optimization. To solve this problem, a surrogate model is built employing the experimental design and Kriging model, constructing the relationship between variables and standard deviation of the objective, reduced the computing time of uncertainty analysis in optimization to improve computing efficiency.