Advances in Engineering Software最新文献

This study presents an innovative approach to mitigating seismic responses in multi-storey buildings equipped with a base-isolation (BI) system and passive friction-tuned mass dampers (PFTMDs). The key innovation lies in the combined use of a BI system and a PFTMD system, as well as the activation of this mechanical system by controllers. Additionally, the research design optimizes the parameters of these devices specifically for each earthquake scenario and compares the results to the average of the optimal parameters, which has not been investigated in previous studies. In this study, a 10-storey structure is modeled, featuring a BI system beneath the first floor and a PFTMD system on the roof. The parameters for the BI, PFTMD, BI-PFTMD, and BI-active FTMD (BI-AFTMD) systems are independently optimized using a multi-objective particle swarm optimization (MOPSO) algorithm. To enhance the passive BI-PFTMD system, a proportional-integral-derivative (PID) controller is incorporated into the friction-tuned mass damper system, resulting in the BI-AFTMD hybrid control system that adjusts the final control force transmitted to the structure. The seismic performance of these systems is assessed for the 10-storey building under both far-field and near-field earthquakes. The findings reveal that these control systems significantly decrease average peak displacement, acceleration, and inter-storey drift as compared to an uncontrolled structure, especially when system parameters are optimized for the same earthquake scenario. Using average optimal parameters, the BI-AFTMD system achieves the most substantial reduction in average peak displacement, while the BI system offers the greatest reduction in average peak acceleration and inter-storey drift.

The Structure Equivalent Reduction-Expansion Process (SEREP), which has been widely used to expand experimental mode shapes, has the limitation of low accuracy of expansion for experimental mode shapes that are poorly correlated with finite element (FE) mode shapes. To address this limitation, a novel mode shape expansion method using modal approach and artificial neural network (ANN) is proposed in this paper. The ANN replaced the least-squares method to optimize the modal coordinates and considered the natural frequency and experimental mode shape of the master DOFs as input data. The superiority of the proposed ANN method compared with the SEREP was verified using a numerical cable-stayed bridge model. The proposed method, which can use a large number of FE mode shapes and optimize modal coordinates based on the ANN, achieved high accuracy (modal assurance criterion > 0.9 and normalized mean absolute percent error < 5 %) in expanding experimental mode shapes that have poor correlation. In addition, using the proposed method, the number of required experimental data can be reduced, and additional processes such as optimal selection of FE mode shapes and FE model modification can be omitted.

Building Information Physical Model (BIPM) is a new special information model in which information processes and physical processes are coupled and intertwined, integrating static information, dynamic interaction mechanisms and physical mechanisms, while how to model and verify the theory of BIPM becomes an urgent problem to be solved. In this paper, firstly, we further improve the BIPM conceptual framework to make the interaction between the information model, the physical model, the interaction model and the three sub-models more clear and complete. In this way, we achieve the purpose of integrating dynamic and static attribute information and physical information of buildings into one environment. Secondly, we combine the implementation logic of BIPM with a strict mathematical description to establish the theoretical model of BIPM, so that BIPM accurately and realistically reflects the behavioral state in physical space, realizes the two-way interaction of virtual physics, achieving the purpose of controlling physics with virtual and optimal regulation. Again, we validated the theoretical model of BIPM by formal modelling using Communication Sequential Process (CSP), which proved the reliability and correctness of BIPM. Further, we have built a BIPM prototype system in conjunction with a chiller to validate the proposed modelling approach, which proves the feasibility and effectiveness of the modelling approach. BIPM is expected to form a new paradigm for information model of the building, which will provide basic support for the development of new platforms such as BIPM-based building operation and maintenance and urban digital twin.

This research introduces a novel and unified optimization design method for multi-stage non-circular gear transmission (MNCGT) to address the challenges in designing MNCGT for complex motion requirements. The method optimizes non-circular gears comprehensively, reducing design and manufacturing difficulties while ensuring the realization of specified transmission requirements. A unified parameterization method, grounded on periodic B-spline interpolation, is introduced to establish the transmission function of non-circular gears and map it to a finite unified variable space. This innovative approach effectively reduces the difficulty and constraints of MNCGT optimization design. The proposed method takes into account crucial factors such as non-circularity, smoothness, processing conditions, and contact ratio, which significantly impact the transmission performance and manufacturing feasibility of non-circular gears. The effectiveness and superiority of this method are demonstrated through two practical examples and a real-world application in a planetary gear transplant mechanism, highlighting its potential for solving complex engineering problems.

This study presents a simple approach and its associated MATLAB toolbox for 3D block cutting and mesh cutting. The approach is suitable for the meshes of numerical methods including the Key Block Theory (KBT), the Discontinuous Deformation Analysis (DDA), the Numerical Manifold Method (NMM), and the cut Finite Element Method (Cut-FEM). The strategy is based on calculations on convex bodies. It uses two different forms of representation: the geometric representation which includes vertices and faces, and the algebraic representation which consists of inequalities. The cutting was implemented on the algebraic representation, and the resulting inequalities were converted into a geometric representation. The above strategy turned out to be robust and straightforward to execute, at the cost of a general body being regarded as a combination of convex bodies. The efficiency guarantee was considered through pre-checking algorithms. The source code was provided, as well as some simple examples.

This paper presents a new parameterized method for establishing OSD models and analyzing WRS, and two plugins are developed based on the graphical user interface (GUI) of Abaqus. This parameterized method addresses the extremely high cost of manual modeling of OSD in Abaqus. In the two presented plugins, the OSD dimensions and welds size, the material properties, the welding heating source, and the mesh properties are parameterized, and the OSD model can be created automatically by the plugins without users’ pre-processing operations in Abaqus, which significantly facilitates the OSD modeling and the WRS analysis. The plugins developed in this study can provide the WRS analysis in the OSD with any dimensions and welding technologies, and the applicability of the plugins is verified by the consistency between the simulated WRS analysis results by plugins and those reported in the literature.

Current discrete element parameter calibration methods primarily rely on mechanical tests to analyze particle properties and often overlook the machinery's interaction with the particles. The extensive variation in particle sizes of crushed coal poses challenges in accurately applying parameters derived from mechanical test calibrations to industrial simulations. DEM models of mechanical tests for coal were developed to examine how parameters influence coal's mechanical properties through factor analysis. Simplified engineering test models were developed based on mining equipment, with the equipment responses used as indicators to optimize mechanical test calibration parameters. On this basis, a calibration method of discrete elemental parameters of coal based on the crushing simulation of mining equipment was proposed. This method was validated through mechanical and engineering simplification tests, resulting in a mean error of <10 % in the time-varying response. The research findings enable calibration of discrete element parameters for crushed coal in industrial simulation.

The recent rise of deep learning has led to numerous applications, including solving partial differential equations using Physics-Informed Neural Networks. This approach has proven highly effective in several academic cases. However, their lack of physical invariances, coupled with other significant weaknesses, such as an inability to handle complex geometries or their lack of generalization capabilities, make them unable to compete with classical numerical solvers in industrial settings. In this work, a limitation regarding the use of automatic differentiation in the context of physics-informed learning is highlighted. A hybrid approach combining physics-informed graph neural networks with numerical kernels from finite elements is introduced. After studying the theoretical properties of our model, we apply it to complex geometries, in two and three dimensions. Our choices are supported by an ablation study, and we evaluate the generalization capacity of the proposed approach.

The identification of boundary conditions in electromagnetic inverse scattering is of importance in various engineering applications, ranging from geophysical exploration to wireless communication. Conventional numerical methods solving this problem often suffer from the iterative process, leading to inefficiencies and non-convergence. This paper introduces a weighted scheme of the stabilized Lagrange interpolation collocation method (weighted SLICM) to resolve this problem. Weighted SLICM efficiently integrates governing equations, boundary conditions, and measurement conditions using a weighted least squares approach, offering a straightforward single-step solution and obviating the need for iterative processes in traditional methods like the finite element method. By incorporating regularization techniques, weighted SLICM decreases measurement errors which are unavoidable in engineering problems, thereby ensuring high efficiency and accuracy. In addition, characterized as a strong-form collocation method that relies solely on point information but not on grid connectivity, the weighted SLICM is readily extendible to complex three-dimensional applications in electromagnetic inverse scattering. Extensive simulations of benchmark problems show its ability to achieve accurate and stable results in boundary condition identification in electromagnetic inverse scattering problems including 1D, 2D, and 3D environments, highlighting the effectiveness of the weighted SLICM in navigating complex engineering challenges and substantially enriching research methodologies in this area.

A tuned mass damper (TMD) optimization can be performed under various assumptions and objectives. All the variables of the optimization, such as structural model, performance index and load type affect the optimal parameters of the TMD. This paper presents a new optimization method that implements straightforward performance index and allows taking load spectral characteristics into account. Thanks to the usage of modal coordinates, the method allows fast numerical optimization of TMD attached to large or complicated structures with numerous degrees of freedom. One of the complicated tasks while optimizing TMD is the choice of a performance index. In this paper, the mean value of potential energy stored in the elastic deformation of a structure under periodic load serves as a performance index, which leads to a low numerical complexity task if the optimization is performed in the frequency domain. The new method also allows a simple inclusion of load spectral characteristics and permits TMD optimization for any loading spectral range. When applied to a structure with a single degree of freedom, this method leads to H₂ optimization in the case of white noise excitation. However, it is applicable to multiple degrees of freedom structures with single or multiple TMDs and any given load. The paper also presents several examples of numerical optimization of the TMD attached to both single and multiple degrees of freedom structures under various loads, including white noise excitation, pedestrian load, and earthquake strong motion.