Computers & Structures最新文献

This paper develops a numerical integration for an elastoplastic model for hardening materials which has an anisotropic yield surface, and displays asymmetric behavior under tension and compression yielding. The model also captures nonlinear isotropic and kinematic hardening and softening behavior. The developed numerical integration, called return-free integration, automatically updates the stress on the yield surface during the plastic phase, hence it is capable of simulating the behavior of the anisotropic-hardening material model exactly. Furthermore, the return-free integration for the material model is examined through the analysis of consistency errors, average errors, and iso-errors. The influence of the non-zero initial condition of stress, pre-straining path, and loading paths on the consistency error is explored. The convergence analysis of average error is investigated and the iso-error maps are established. All error analysis demonstrates the return-free integration for the proposed model with the anisotropic yield surface and the nonlinear isotropic-kinematic-mixed hardening rule is stable, acceptable, and reliable.

This paper provides a procedure to obtain the uniform strength of frame and lattice structures. Uniform strength condition is achieved by performing the shape optimization of all beam elements of the structure. The beam shape which guarantees uniform strength is analytically deduced from the one-dimensional Timoshenko model. The optimization problem presents itself as the search for the zeros of the objective-functions vector, which is a non-linear system of equations representing the kinematic-congruence and forces balance at every node of the structure. The analytical formulation of the optimization problem allows to construct the objective-functions vector without the use of external structural computation, i.e. not recurring to any Finite Element Analysis to accomplish iterations. This latter feature entails a great advantage in terms of computing time required to perform optimization. The proposed analytical formulation allows to directly insert the uniform strength condition into the objective-functions vector, transforming the optimization into an unconstrained problem. Some examples are shown in which the performance of the optimization procedure is discussed in terms of robustness and rate of computational complexity while increasing the degrees of freedom of the structure. The reliability and the quality of the optimization are verified through Finite Element Analysis.

This paper introduces an improved shear-deformable beam formulation for nonlinear buckling analysis of laminated composite beam-type structures with thin-walled cross-sections. Each wall of a cross-section is assumed to be a thin symmetric and balanced angle-ply laminate. The incremental equilibrium equations of a straight beam element are derived by applying the virtual work principle within the framework of updated Lagrangian formulation, Hooke’s law and the nonlinear displacement field of a thin-walled cross-section, which takes into account restrained warping and large rotation effects. Incremental stress resultants are calculated by the Timoshenko–Ehrenfest beam theory for bending and the modified Vlasov theories for torsion. Shear coupling problems occurring at non-symmetric thin-walled cross-sections and arising from the shear forces-warping torsion moment couplings are considered. As a result, new shear-correction factors for a cross-section composed of thin angle-ply laminates are derived. Force recovering is performed according to the conventional procedure based on the concept of semitangential rotations. The shear-locking occurrence is prevented by applying the Hermitian cubic interpolation functions for deflections and twist rotation, and the associated quadratic functions for slopes and warping. The effectiveness of the proposed geometrically nonlinear shear-deformable beam formulation is validated through the test problems.

Uncertain parameters with spatial dependency exist in actual bridges inevitably, which significantly affect the bridge dynamic response. However, such spatial dependency is often neglected when investigating its influence on bridge response. This study proposes a bridge dynamic response analysis method considering the spatial dependency of uncertain parameters. Firstly, the bridge uncertain parameter is described by a non-probabilistic interval field model, and the spatial dependency between adjacent values of the interval field is quantified by the Karhunen-Loève like expansion. Thus the bridge is transformed into a system with multidimensional interval parameters by finite element method. Then, the system with multidimensional interval parameters is decomposed into several one-dimensional subsystems with only one interval parameter. Finally, the interval parameters of each one-dimensional system are divided into several subintervals with small uncertainties, and the dynamic response is obtained by combining analysis of subinterval results. Numerical examples are used to verify the accuracy and efficiency of the proposed method, and the results indicate that the proposed method significantly reduces the computational effort and improves the computational efficiency. Higher level of spatial dependency of the interval field, larger subinterval number, and lower uncertainty level of the non-probabilistic interval field leads to higher dynamic analysis accuracy.

The paper presents a novel non-linear one-dimensional finite element with 16 degrees of freedom aimed at modelling Fiber Reinforced Cementitious Matrix strengthening systems. Such composite is typically constituted by three superimposed layers −namely an outer matrix, a central fiber textile and an inner matrix- subjected to a prevailing longitudinal monoaxial stress state. They interact by means of interfaces exchanging both tangential and −when the reinforcing system is applied to curved substrates- traction/compression stresses. Matrix is made by mortar −possibly reinforced- exhibiting medium to high strength, whereas the fiber net can be aramid, carbon, glass, steel, basalt, etc. The reinforcing system is then connected to a substrate by means of a further interface. The finite element is a two-noded assemblage of three trusses representing matrix and fiber layers. Shear and normal springs are lumped at the nodes, mutually connecting contiguous trusses and the inner matrix to the substrate. They represent the interfaces and exchange normal and shear actions between contiguous layers or transfer them from the reinforcing system to the substrate. The degrees of freedom, 8 per node, are the longitudinal and transversal displacements of the three layers and of the substrate, evaluated at the nodes. Material non-linearity can be considered both for trusses and springs, giving the possibility to account for all the experimentally documented damaging cases that can be encountered in practice. Both softening and inelastic behavior are numerically tackled with a fully explicit algorithm where the elastic modulus of the layers and the stiffness of the interfaces are reduced at the new iteration if in the previous one the elastic limit is exceeded. The stiffness matrix is provided straightforwardly also in the inelastic case, showing the promising simplicity of the element when coupled with the non-linear solver. The performance of the novel finite element is validated against a comprehensive experimental dataset referring to curved masonry pillars reinforced with Fiber Reinforced Cementitious Matrix and tested in single lap shear.

We investigate different variants of the method of fundamental solutions for solving scattering problems from infinite elastic thin plates. These provide novelty and desirable ease of implementation as direct accurate and fast solvers to be used iteratively in solving the corresponding inverse problems. Various direct problems associated with physical states of clamped, simply supported, roller–supported and free plates can be solved efficiently using the proposed meshless method. In particular, the numerical implementation performed for clamped plates leads to results showing very good agreement with the analytical solution, where available, and with previously obtained boundary integral method solutions. As for the inverse obstacle identification, the study further develops a constrained nonlinear regularization method for identifying a cavity concealed in an infinite elastic thin plate that has important benefits to the structural monitoring of aircraft components using non–destructing material testing.

A new approach to performing sensitivity analysis of arbitrary objective functionals for anisotropic elasticity is proposed in this work. Three different objective functionals have been considered, and good agreement is achieved between derived topological derivatives and numerical ones. Following the verification of topological derivatives, structural topology optimizations for selected anisotropic problems are conducted. To efficiently achieve the exact free boundary representation, our Finite Element Method (FEM)-based optimization comprises two loops. In the initial loop, a fixed and coarse mesh is employed to solve the anisotropic problem and update the level-set function. Once this loop concludes, the second loop reconstructs the material domain, ensuring an exact boundary representation. The convergence of the second loop is facilitated by (1) utilizing topological derivatives instead of explicit derivatives of ϕ (similar to density derivatives) and (2) imposing the exact volume constraint on the Reaction-Diffusion Equation (RDE)-based level-set method. Moreover, we introduce a scheme to prevent structural breakdown, allowing for the standalone implementation of Loop 2 always with exact free boundary representation. The previously proposed algorithm for the exact volume constraint has been generalized to accommodate inequalities, resulting in an acceleration of the equivalent optimization process.

High–efficiency solutions for extremely long bridge structures are a challenge in vehicle-bridge interaction modelling. In the present work, a novel modelling methodology for a monorail train and large-scale bridge interaction system is developed based on moving element technology. First, the governing equations for the monorail train subsystem are derived by adopting the Newton-Euler method, and an extremely long bridge is modelled based on an improved component mode synthesis method in which a bridge unit with finite length is updated and moved as the train moves forward. The train and bridge subsystems are coupled together by a nonlinear wheel–track interaction model. Subsequently, the convergence of the proposed method is discussed in detail, and reasonable values of several crucial model parameters are determined. On this basis, the simulation results obtained by the proposed methodology are compared with those of the finite element method (FEM) and field test data, validating the reliability of the proposed methodology and revealing its remarkable advantages. Finally, by applying the proposed methodology, the dynamic performance of the monorail train-bridge system is evaluated under different operating conditions. Results indicate that the proposed methodology can achieve good calculation accuracy for the vehicle-bridge dynamic responses; additionally, its computational efficiency is much higher than that of the FEM. The variation of the bridge section profile has a notable effect on the dynamic performance of the monorail vehicle-bridge system, which becomes more significant with increasing train speed.

The line finite element method (LFEM) is the predominant simulation method in structural design due to its robustness in large-scale structural analysis. However, it sometimes suffers from the tedious computational process due to its fine-mesh requirement to ensure accuracy. The machine learning (ML) technique provides an efficient mesh-free alternative but necessitating tremendous training datasets for modeling large-scale structural systems. In this paper, a novel numerical framework, named the neural networks-based line element (NNLE) method, synergizing the unique advantages of the finite element method and ML technique, is proposed and presented within the context of large deflection frame analysis. The neural networks (NN) model is only trained for modeling single components, thereby significantly diminishing the model scale and the required training dataset. Then, the NN model is used to formulate a new NNLE and implemented within the existing LFEM framework to simulate the entire structural system. Extensive examples are performed to demonstrate the accuracy, efficiency, compatibility, and flexibility of the proposed NNLE method compared with the conventional LFEM and ML techniques. It is convinced that the proposed NNLE method will offer new insights into the combination of the traditional finite element method and the emerging ML approach.

This paper introduces a formulation of the robust topology optimization problem that is tailored for designing fiber-reinforced composite structures with spatially varying principal mechanical properties. Specifically, a methodology is developed that incorporates the spatial variability in the engineering constants of the composite lamina into the concurrent topology (i.e., material distribution) and morphology (i.e., fiber orientation distribution) optimization problem for the minimization of the robust compliance function. The spatial variability in the mechanical properties of the lamina is modeled as a homogeneous random field within the design domain by means of the Karhunen-Lo$\acute{\text{e}}$ve series expansion, and is thereafter intrusively propagated into the stochastic finite element analysis of the composite structure. To carry out the stochastic finite element analysis per iteration of the optimization cycle, the first-order perturbation method is utilized for approximating the current state variables of the physical system. The resulting robust topology and fiber orientation optimization problem is formulated step-by-step for the minimization of the robust compliance function. With the view of solving the optimization problem at hand by means of gradient-based solution algorithms, the first-order derivatives of the involved design functions $w.r.t.$ the associated design variables are analytically derived. The present work concludes with a series of numerical examples, focusing on the benchmark academic case studies of the 2D cantilever and the half part of the Messerschmitt-Bölkow-Blohm beam, aiming to demonstrate the developed methodology as well as to explore the effect that different parameterization instances of the random field bear on the predicted topology and morphology of the beams.