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Separately, nonlinear finite element analysis, artificial neural networks (ANNs) and continuous damage mechanics (CDM) attracted many investigators to model masonry infilled frames. The purpose of this paper is to pursue four phases to develop a versatile model for partially and fully low-rise infilled RC frames using these tools.

The first phase included the study of the behavior of 1,620 low-rise infilled reinforced concrete frames using macro-scale nonlinear pushover finite element analysis. The approach helped to explore the effects of imposing different masonry infill distributions for one of the typical models of school buildings in Egypt. The outputs of this phase were used in the second phase for the development of an ANN model where input neurons included number of stories, continuity conditions, frame geometry, infill distribution and properties of RC sections. The third phase included the employment of the notions of CDM on the structural scale. Monitoring frames’ stiffness degradation allowed for damage variables identification. In the fourth phase, the simpler equivalent static lateral load (ESLL) for elastic analysis was employed in conjunction with ANN and CDM to obtain the capacity curves for partially and fully low-rise infilled RC frames.

The obtained capacity curves were compared with the nonlinear finite element results. The close agreement of all curves indicated how rigorous, yet simple, the suggested solution procedure is.

The study is concerned with an important type of service buildings. These are the school buildings of Egypt.

The paper presents a combination of four phases that include FE analysis, ANNs, ESLL, and CDM to obtain the capacity curves for partially and fully low-rise infilled RC frames. Such a combination of approaches in tackling a practical problem related to service buildings is innovative and deserves research interest.

This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R² = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions.

This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R² = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior.

The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R²” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction.

The authors confirm the originality of this paper.

This paper aims to present a multi-scale stochastic damage model (SDM) for concrete and apply it to the stochastic response analysis of reinforced concrete shear wall structures.

The proposed SDM is constructed at two scales, i.e. the macro-scale and the micro-scale. The general framework of the SDM is established on the basis of the continuum damage mechanics (CDM) at the macro-scale, whereas the detailed damage evolution is determined through a parallel fiber buddle model at the micro-scale. The parallel buddle model is made up of micro-elements with stochastic fracture strains, and a one-dimensional random field is assumed for the fracture strain distribution. To represent the random field, a random functional method is adopted to quantify the stochastic damage evolution process with only two variables; thus, the numerical efficiency is greatly enhanced. Meanwhile, the probability density evolution method (PDEM) is introduced for the structural stochastic response analysis.

By combing the SDM and PDEM, the probabilistic analysis of a shear wall structure is performed. The mean value, standard deviation and the probability density function of the shear wall responses, e.g., shear capacity, accumulated energy consumption and damage evolution, are obtained.

It is noted that the proposed method can reflect the influences of randomness from material level to structural level, and is efficient for stochastic response determination of shear wall structures.

The purpose of this paper is to present a new simplified local remeshing procedure for the study of discrete crack propagation in finite element (FE) mesh. The proposed technique accounts for the generation and propagation of crack‐like failure within an FE‐model. Beside crack propagation, the technique enables the analysis of fragmentation of initially intact continuum. The capability of modelling fragmentation is essential in various structure‐structure interaction analyses such as projectile impact analysis and ice‐structure interaction analysis.

The procedure combines continuum damage mechanics (CDM), fictitious crack approach and a new local remeshing procedure. In the approach a fictitious crack is replaced by a discrete crack by applying delete‐and‐fill local remeshing. The proposed method is independent of mesh topology unlike the traditional discrete crack approach. The procedure is implemented for 3‐D solid elements in commercial finite element software Abaqus/Explicit using Python scripting. The procedure is completely automated, such that crack initiation and propagation analyses do not require user intervention. A relatively simple constitutive model was implemented strictly for demonstrative purposes.

Well known examples were simulated to verify the applicability of the method. The simulations revealed the capabilities of the method and reasonable correspondence with reference results was obtained. Material fragmentation was successfully simulated in ice‐structure interaction analysis.

The procedure for modelling discrete crack propagation and fragmentation of initially intact quasi‐brittle materials based on local remeshing has not been presented previously. The procedure is well suited for simulation of fragmentation and is implemented in a commercial FE‐software.

Focuses on a finite element computational model for the Timoshenko beam which is idealized as an elasto‐plastic‐damage medium governed by Lemaitre’s continuum damage mechanics (CDM) model for ductile fracture. Response under monotonically increasing loading does not show any deviation from elasto‐plastic simulation. However, a marked difference in the residual stress field is noted by virtue of the unloading phase, in which the CDM model allows for stiffness degradation in contrast to classical elasto‐plasticity which requires unloading at the (frozen) initial stiffness of the material.

Simple but also accurate models are needed to predict the failure response of concrete structures. Simplicity involves modelling assumptions while accuracy involves objectivity of both the experimentally identified model parameters and the numerica results. For concrete‐like heterogeneous and brittle materials, the modelling assumptions idealizing the material as a homogeneous continuum with classical linear or non‐linear behaviour, leads to some problems at the identification stage, namely the size effect phenomena. A continuum damage model, representing the non‐linear behaviour due to microcracking, is proposed here for predictive computations of structural responses. A Weibull based theory is used to determine, in a statistical sense, the value of the initial damage threshold. The essential influence of material heterogeneity on the damage evolution, is accounted for with a bi‐scale approach which is based on the idea of the non‐local continuum with local strain. It has already established that the non‐local approaches yield realistic failure predictions and the numerical results are convergent for subsequent mesh refinements. The applications presented here show the ability of the approach to predict the failure response of concrete structures without being obscured by size effect problems.

This paper aims to introduce a multiscale computational method for structural failure analysis with inheriting simulation of moving trans-scale boundary (MTB). This method is motivated from the error in domain bridging caused by cross-scale damage evolution, which is common in structural failure induced by damage accumulation.

Within the method, vulnerable regions with high stress level are described by continuum damage mechanics, while elastic structural theory is sufficient for the rest, dividing the structural model into two scale domains. The two domains are bridged to generate mixed dimensional finite element equation of the whole system. Inheriting simulation is developed to make the computation of MTB sustainable.

Numerical tests of a notched three-point bending beam and a steel frame show that this MTB method can improve efficiency and ensure accuracy while capturing the effect of material damage on deterioration of components and structure.

The proposed MTB method with inheriting simulation is an extension of multiscale simulation to structural failure analysis. Most importantly, it can deal with cross-scale damage evolution and improve computation efficiency significantly.

In certain cases, traction–separation laws do not reflect the behaviour sufficiently so that thin volumetric elements, Internal Thickness Extrapolation formulations, bulk material projections or various other approaches are applied. All of them have disadvantages in the formulation or practical application.

Damage within thin layers is often modelled using at cohesive zone elements (CZE). The constitutive behaviour of cohesive zone elements is usually described by traction–seperation laws (TSLs) that consider the (traction separation) relation in normal opening and tangential shearing direction. Here, the deformation (separation) as well as the reaction (traction) are vectorial quantities.

In this contribution, a CZE is presented that includes damage from membrane modes.

Membrane mode-related damaging effects that can be seen in physical tests that could not be simulated with standard CZEs are well captured by membrane mode–enhanced cohesive zone elements.

The aim of this paper is to present a novel data transfer technique to simulate, by G/XFEM, a cohesive crack propagation coupled with a smeared damage model. The efficiency of this technique is evaluated in terms of processing time, number of Newton–Raphson iterations and accuracy of structural response.

The cohesive crack is represented by the G/XFEM enrichment strategy. The elements crossed by the crack are divided into triangular cells. The smeared crack model is used to describe the material behavior. In the nonlinear solution of the problem, state variables associated with the original numerical integration points need to be transferred to new points created with the triangular subdivision. A nonlocal strategy is tailored to transfer the scalar and tensor variables of the constitutive model. The performance of this technique is numerically evaluated.

When compared with standard Gauss quadrature integration scheme, the proposed strategy may deliver a slightly superior computational efficiency in terms of processing time. The weighting function parameter used in the nonlocal transfer strategy plays an important role. The equilibrium state in the interactive-incremental solution process is not severely penalized and is readily recovered. The advantages of such proposed technique tend to be even more pronounced in more complex and finer meshes.

This work presents a novel data transfer technique based on the ideas of the nonlocal formulation of the state variables and specially tailored to the simulation of cohesive crack propagation in materials governed by the smeared crack constitutive model.

The purpose of this paper is to investigate the fatigue behavior of rubber using dumb‐bell test specimens under uniaxial loading.

The material used is a vulcanized natural rubber with a formulation typical for engine mounts and an international rubber hardness degree of 60. Fatigue tests are conducted under the displacement controlled condition with a sine waveform of 0.1 Hz and the load ratio of zero.

In modeling fatigue damage behavior, a continuum damage model is presented based on the function of the strain range under cyclic loading. The Ogden strain energy potential is used to define the constitutive relation of the natural rubber. A good agreement is obtained between fatigue experimental data and theoretical predictions.

Fatigue analysis and lifetime evaluation are very important in design to ensure the safety and reliability of rubber components. The design of rubber against fatigue failure is an important topic that must be considered for safety during operation.