Computers & Structures最新文献

The article presents a novel strain-based finite element family for the analysis of material softening of planar frame structures. In our case, the softening zone is described by a discrete crack, which is considered as an ‘excluded’ finite element point, i.e., the deformation quantities in the crack are considered separately from the deformation quantities of the element. They are connected to the element only through kinematic quantities, used to describe the crack opening. The criterion for crack initiation is defined as the limit axial-bending resistance of the cross-section. The advantage of the presented model is that it is not necessary to define cracks or softening zones in advance and that the solution is mesh-independent in the sense that no further densification of the mesh is needed purely on account of capturing material softening. The accuracy and efficiency of the presented finite element family is illustrated by the example of a clamped–simply supported concrete beam and a portal concrete frame. The examples demonstrate that even with a minimum number of finite elements of suitable accuracy, sufficiently accurate results are obtained for normal engineering practice.

Traditionally, nonprobabilistic methods for reliability problems evaluate the reliability level of single failure modes, lacking the capability to perform comprehensive reliability analysis series–parallel systems formed by multiple failure modes. In this paper, the nonprobabilistic systematic reliability method (NSRM) is proposed to evaluate the reliability of series–parallel systems within the nonprobabilistic framework. Firstly, the correlation propagation analysis is introduced to quantify the ellipsoidal uncertain domain of limit state functions, upon which all subsequent reliability analyses are based. Subsequently, an equivalence-based method based is proposed to determine the equivalent limit state functions of parallel subsystems, accompanied by the establishment of an optimal equivalence strategy. The NSRM is further established by combining the second order reliability bound techniques. Lastly, the paper presents two numerical examples and an engineering application, showcasing the efficacy and precision of the proposed NSRM in practical scenarios.

The Gurson-Tvergaard-Needleman (GTN) model has been improved to extend its application for high strain rate loading and assessed by using the Taylor impact process of 7xxx aluminum alloys. The existing modification method based on independent shear damage variables has been integrated into the enhanced GTN model to assess shear fracture. In addition, the effects of strain rate hardening, temperature softening, and viscosity resistance terms have been taken into account in the constitutive equation to accurately depict the material’s deformation behavior under high strain rates. A series of quasi-static mechanical tests and Split Hopkinson Pressure Bar (SHPB) tests with strain rates ranging from 1000$s^{-1}$ ∼ 5000 $s^{-1}$ were conducted on 7A52-T6 alloy and 7A62-T6 alloy. The Taylor impact experiments showed that the mushrooming deformation and shear fractures occurred as the impact velocity increased. Both the 7A52 and 7A62 alloys exhibited fracture characteristics of shear and void nucleation, and the voids only grew slightly after formation. The predicted fracture patterns in Taylor impact and the evolution trend of material strength using the enhanced GTN model are consistent with the experimental results.

During the in-orbit service, mesh reflector antennas inevitably withstand the long-term creep behavior, resulting in changes in material properties and loss of cable tensions, thus decreasing the structural stiffness and surface accuracy. Pretension design plays an important role for mesh reflector antennas in achieving high surface accuracy, and different levels of pretension also affect the antenna’s creep behavior in the time dimension, which can be actively utilized to improve stability of the antenna surface accuracy. In this paper, we present an anti-creep pretension determination method for mesh reflector antennas to improve the surface accuracy stability. The creep model in the discretized time domain is adopted to describe the cable creep behavior. The time-related nonlinear equilibrium equation of the mesh reflector antenna is established with the force density method. The time-related tangent stiffness matrix is derived and adopted to solve the nonlinear equilibrium equation by the Newton-Raphson method, providing an effective way to analyze the antenna creep phenomenon in the discretized time domain. Aiming to minimize the long-term peak value of the time-variant surface error, the pretension schemes are generated and optimized. Finally, this approach is effectively applied to a thirty-unit mesh reflector antenna and its feasibility and effectiveness are verified.

Regular monitoring of the hanger system is essential for preserving structural integrity in tied-arch bridges. This proactive monitoring enables preventive maintenance and early detection of hanger damage. To confront this issue, we propose a novel scanning method for assessing the impact of damaged hangers on the dynamic behaviour of single-span tied-arch railway bridges. Using each hanger as a positional reference, this method employs an instrumented vehicle as a mobile scanner to indirectly acquire vibration data from the traversed bridge deck. The hybrid approach integrates vehicle-bridge interaction (VBI) dynamics, vehicle scanning method (VSM), and moving windowed Fourier transform (mw-FT) technique to generate time–frequency spectrograms from the collected signals. In this representation, the time axis indicates the duration of the inspection vehicle traversing the bridge deck. By analysing frequency shifts within the spectrogram, we can identify damaged hangers through observed variations in frequency content over time. Numerical studies demonstrate the efficacy of the proposed hybrid vehicle scanning technique in detecting potential hanger damage in tied-arch railway bridges.

In this paper, a novel and efficient neural network-based methodology is proposed to achieve seismic total cost optimization of steel moment-resisting frames in a timely manner. The computational burden of an optimization process based on performing nonlinear time-history analysis is prohibitively high. To address this crucial issue, a new and efficient neural network model is proposed in this paper to accurately predict the nonlinear time history response of steel frames during the optimization process. In the proposed neural network model, an ensemble of parallel neural networks is used to provide excellent prediction accuracy. In addition, a new repairability constraint is proposed to check the seismic damage level of structures during the optimization process with the aid of the proposed neural network model. Moreover, an efficient metaheuristic algorithm is used to achieve the optimization task. Two numerical examples are illustrated to demonstrate the efficiency of the proposed methodology. The results show that the proposed neural network model outperforms the existing standard models in terms of prediction accuracy. Furthermore, it is shown that by using the proposed methodology, the optimal seismic total cost of steel frames increases by less than 2.5%, yet their seismic collapse capacity increases by at least 30%.

Reactive transport within porous reactors is crucial to many diverse applications, and the efficacy of these reactors hinges on their microstructure. Mathematical modeling and optimization play a pivotal role in the exploration of efficient designs, enabling the generation of structures that may not be achievable through random realizations of packings. In this study, we propose a framework for high-resolution topological optimization of porous flow-through reactors based on pore-scale simulations using a non-dominated sorting genetic algorithm II. A pore network model for an advection–diffusion-reaction system is developed to simulate reactor performance. This model is integrated with a mathematical optimization algorithm, incorporating a background grid and Delaunay tessellation. The optimization framework generates enhanced porous structures, simultaneously maximizing conversion rates while minimizing pumping costs. Striking a balance between permeability and reactive surface area, the final designs yield a set of Pareto optimal solutions, encompassing diverse non-dominated designs with varying reaction rates and hydraulic requirements. The results demonstrate that optimal pore configurations lead to a 280% increase in conversion rates and a 6% reduction in pumping costs at one end, while on the opposite end of the Pareto front, a 15.2% increase in reaction rates and an 11.3% reduction in pumping costs are observed.

In this study, we present an efficient Topology Optimization (TO) approach designed to optimize support structures in metal Additive Manufacturing (AM), with a particular focus on Powder Bed Fusion (PBF) technology. The developed framework uses a purely thermal formulation to identify regions within the design that are susceptible to high heat concentrations. In the proposed modeling of the AM process, we postulate that new material layers are included in a partially built design that has already cooled to a controlled temperature. This aspect provides a layer-by-layer model of AM entirely local, enabling the building process parallelization and resulting in an algorithm with superior computational efficiency. Numerical results show the robustness of the proposed strategy, with the successful incorporation of support structures beneath overhanging surfaces and their effectiveness across a wide range of geometries and orientations. Furthermore, this framework is also applied to optimize the geometry orientation within the build chamber, further enhancing its applicability in the AM context.

The coupled motion between bridges and vehicles is known as vehicle–bridge interaction (VBI). It is crucial for bridge design, monitoring, and vehicle safety and comfort. VBI studies typically rely on general-purpose finite element (FE) software. Although precise, they are not optimized for simulating large-scale bridges with numerous vehicles, which can result in long processing times and modeling challenges. This paper presents a self-developed framework in MATLAB™ for large-scale VBI simulation. The framework divides the simulation task into five modules and supports asynchronous seismic excitation (ASE), handles different deck geometries, unifies all road vehicle models and inputs with a vehicle library, supports variable vehicle velocity (VVV) and different traffic scenarios, and handles wheel–deck detachment. All functions have been designed with easily accessible interfaces to facilitate secondary development. The framework was verified using a 2D sprung mass benchmark case compared to a closed-form solution, and a 3D simplified model compared to commercial FE software. It was also validated through a laboratory experiment. Further demonstrations of a large-scale VBI system highlighted new phenomena and emphasized the significance of considering the ASE effect in similar systems. With ongoing improvements, the framework has the potential to become a practical tool for VBI simulation.

This paper aims for developing topology optimization methodology to design the shape of electrodes in Dielectrophoresis (DEP)-based devices. The DEP force is due to a non-uniform electric field induced by applied voltages to the electrodes. Shape of the electrodes has the principal effect on the direction and magnitude of the DEP force. In medical therapy microfluidic devices, DEP force is used for cell sorting and cell separation. While the direction and magnitude of the DEP force are desired to be determined and maximized respectively, the magnitude of the electric field should be minimized to avoid damaging cells. Approaching these goals is counter intuitive where the existing electrode designs are basic. Therefore, a detailed finite element model (FEM) is developed for DEP force and electric field to formulate an optimization problem to maximize the DEP force in a particular direction while there is a constraint on electric field's magnitude. Using the developed FEM, explicit formulations for sensitivity analysis are derived to implement a gradient-based topology optimization. The performance of developed methodology is assessed numerically to determine the direction of the DEP force and constraining the electric field and experimentally in a practical case study of particle trapping in a microfluidic channel.