L. Hadji*, V. Plevris and G. Papazafeiropoulos, “Investigation of the Static Bending Response of FGM Sandwich Plates”, Journal of Applied and Computational Mechanics, 10(1), pp. 26-37, 2024. DOI: 10.22055/jacm.2023.44278.4194

Abstract:
In the present work, a displacement-based high-order shear deformation theory is introduced for the static response of functionally graded plates. The present theory is variationally consistent and strongly similar to the classical plate theory in many aspects. It does not require the shear correction factor, and gives rise to the transverse shear stress variation so that the transverse shear stresses vary parabolically across the thickness to satisfy free surface conditions for the shear stress. By dividing the transverse displacement into the bending and shear parts and making further assumptions, the number of unknowns and equations of motion of the present theory is reduced a and hence makes them simple to use. The material properties of the plate are assumed to be graded in the thickness direction according to a simple power-law distribution in terms of volume fractions of material constituents. The equilibrium equations of a functionally graded plate are given based on the higher order shear deformation theory. The numerical results presented in the paper are demonstrated by comparing the results with solutions derived from other higher-order models found in the literature and the present numerical results of Finite Element Analysis (FEA). In the numerical results, the effects of the grading materials, lay-up scheme and aspect ratio on the normal stress, shear stress and static deflections of the functionally graded sandwich plates are presented and discussed. It can be concluded that the proposed theory is accurate, elegant and simple in solving the problem of the bending behavior of functionally graded plates.

Keywords:
Sandwich Plates, Functionally Graded Materials, Higher-Order Plate Theory, Stress, FEA.

A. de Macêdo Wahrhaftig, V. Plevris, B.A. Mohamad and D.L. Pereira, "Minimum design bending moment for systems of equivalent stiffness", Structures, 57, Article ID 105224 (DOI: 10.1016/j.istruc.2023.105224), 2023.

Abstract:
In this article, the minimum design bending moment of concrete slender columns is studied by assuming a system of equivalent stiffness. For concrete structural parts such as slender columns, their stiffness is dependent on the loading, originated from lumped and distributed masses, and the rheological behavior of the material. The latter alters the concrete’s modulus of elasticity, introducing changes over time. Basically, the desired transformation is from a one-dimensional non-prismatic system to another prismatic one which exhibits an equivalent bending stiffness. As the bending stiffness changes due to the change of the problem’s independent variables, the geometric characteristics of the transformed system reflect the same dependence as the original system. This implies changes in the minimum design moment since it is linked to the dimensions of the equivalent section. To assess the hypothesis proposed, a numerical simulation is conducted over a real structural system using a vertical loading ranging from zero up to the critical buckling force, taking into account the change in the modulus of deformation of concrete and assuming a certain level of cracking of the material. The results obtained showed that the strategy of using a system of equivalent stiffness simplifies the analysis of non-prismatic elements because the problem is reduced to a prismatic element of equivalent properties. Besides that, due to the incorporation of the concrete creep in the problem, the maximum moment obtained in the equivalent system needs to be multiplied by a factor of 2.94 in order to equal the maximum moment occurring in the original system.

Keywords:
Minimum design moment; Equivalent stiffness; Buckling; Rheological behavior; Reinforced concrete column; Rayleigh method.

R. Ehtisham, W. Qayyum, C.V. Camp, V. Plevris*, J. Mir, Q.Z. Khan and A. Ahmad, "Classification of defects in wooden structures using pre-trained models of convolutional neural network", Case Studies in Construction Materials, 19, Article ID e02530 (DOI: 10.1016/j.cscm.2023.e02530), 2023.

Abstract:
Wooden structures, over time, are challenged by different types of defects. Due to mechanical and weathering effects, these defects can occur in the form of cracks, live and dead knots, dampness, and others. Because of the risk of damage or complete failure, treatment of these defects is necessary, but doing so necessitates their proper identification and classification (categorization). Crack identification and categorization must be part of the inspection procedure for engineering structures in the built environment. Convolutional neural networks (CNNs), a sub-type of Deep Learning (DL), can automatically classify the images of wooden structures to identify such defects. In this study, ten pre-trained models of CNN, namely ResNet18, ResNet50, ResNet101, ShuffleNet, GoogLeNet, Inception-V3, MobileNet-V2, Xception, Inception-ResNet-V2, and NASNet-Mobile are evaluated for the tasks of classification and prediction of defects in wooden structures. Each pre-trained CNN model is additionally trained and validated on an image dataset of 9000 images, equally divided into three classes: cracks, knots, and intact (undamaged). A smaller dataset of 300 images is separately used for testing purposes. Statistical parameters such as accuracy, precision, recall, and F1-score are computed for each CNN model. The Inception-V3 model proved to be the best CNN model for classifying defects in wooden structures based on the model’s accuracy, processing time and overall performance.

Keywords:
Wooden defects; Defects Classification; Pre-trained Models; CNN.