Vagelis Plevris Web Site

www.vplevris.net

A. Jiménez Rios, S. Ruiz-Capel, V. Plevris and M. Nogal, “Computational Methods Applied to Earthen Historical Structures”, Frontiers in Built Environment, 9:1219108 (DOI: 10.3389/fbuil.2023.1219108), 2023.

Abstract:
Earthen structures have an important representation among the UNESCO World Heritage List sites as well as among the built environment in general. Unfortunately, earthen heritage structures are also numerous within the UNESCO List of World Heritage in Danger whereas other existing common earthen structures are extremely vulnerable to seismic and climate change events. Within the field of heritage conservation, structural analysis contributes to the safety evaluation of the structure, the diagnosis of the causes of damage and decay, and to the validation of interventions. Thus, the need to develop effective and accurate computational methods suitable for the study of both monumental and vernacular earthen structures becomes evident. This paper compiles, summarizes, and highlights the latest developments and implementations of computational methods for the study of such structure typologies. The literature has been explored following the PRISMA-S checklist methodology and a narrative synthesis was used for the presentation of results. Finally, future trends, opportunities, and challenges are discussed.



Keywords:
Adobe, rammed earth, cob, finite element method, discrete element method, limit analysis.

G. Solorzano and V. Plevris, “An Open-Source Framework for Modeling RC Shear Walls Using Deep Neural Networks”, Advances in Civil Engineering, vol. 2023, Article ID 7953869, 17 pages (DOI: 10.1155/2023/7953869), 2023.

Abstract:
Reinforced concrete (RC) shear walls macroscopic models are simplified strategies able to simulate the complex nonlinear behavior of RC shear walls to some extent, but their efficacy and robustness are limited. In contrast, microscopic models are sophisticated finite element method (FEM) models that are far more accurate and reliable. However, their elevated computational cost turns them unfeasible for most practical applications. In this study, a data-driven surrogate model for analyzing RC shear walls is developed using deep neural networks (DNNs). The surrogate model is trained with thousands of FEM simulations to predict the characteristic curve obtained when a static nonlinear pushover analysis is performed. The surrogate model is extensively tested and found to exhibit a high degree of accuracy in its predictions while being extremely faster than the detailed FEM analysis. The complete framework that made this study possible is provided as an open-source project. The project is developed in Python and includes a parametric FEM model of an RC shear wall in OpenSeesPy, the training and validation of the DNN model in TensorFlow, and an application with an interactive graphical user interface to test the methodology and visualize the results.

Keywords:
Shear Wall, Surrogate Model, Deep Neural Network, Pushover Analysis, OpenSees, Open-Source.

 

 

M. Shabani, M. Kioumarsi and V. Plevris, “Performance-based seismic assessment of a historical masonry arch bridge: Effect of pulse-like excitations”, Frontiers of Structural and Civil Engineering (DOI: 10.1007/s11709-023-0972-z), 2023.

Abstract:
Seismic analysis of historical masonry bridges is important for authorities in all countries hosting such cultural heritage assets. The masonry arch bridge investigated in this study was built during the Roman period and is on the island of Rhodes, in Greece. Fifteen seismic records were considered and categorized as far-field, pulse-like near-field, and non-pulse-like near-field. The earthquake excitations were scaled to a target spectrum, and nonlinear time-history analyses were performed in the transverse direction. The performance levels were introduced based on the pushover curve, and the post-earthquake damage state of the bridge was examined. According to the results, pulse-like near-field events are more damaging than non-pulse-like near-field ground motions. Additionally the bridge is more vulnerable to far-field excitations than near-field events. Furthermore, the structure will suffer extensive post-earthquake damage and must be retrofitted.

Keywords:
Masonry arch bridges, seismic behavior, modal properties, pulse-like records, nonlinear time history analysis.

M. Georgioudakis* and V. Plevris, "Response Spectrum Analysis of Multi-Story Shear Buildings Using Machine Learning Techniques", Computation, 11(7), Article ID 11070126, 22 pages (DOI: 10.3390/computation11070126), 2023.

Abstract:
The dynamic analysis of structures is a computationally intensive procedure that must be considered, in order to make accurate seismic performance assessments in civil and structural engineering applications. To avoid these computationally demanding tasks, simplified methods are often used by engineers in practice, to estimate the behavior of complex structures under dynamic loading. This paper presents an assessment of several machine learning (ML) algorithms, with different characteristics, that aim to predict the dynamic analysis response of multi-story buildings. Large datasets of dynamic response analyses results were generated through standard sampling methods and conventional response spectrum modal analysis procedures. In an effort to obtain the best algorithm performance, an extensive hyper-parameter search was elaborated, followed by the corresponding feature importance. The ML model which exhibited the best performance was deployed in a web application, with the aim of providing predictions of the dynamic responses of multi-story buildings, according to their characteristics.



Keywords:
Response spectrum analysis, ensemble algorithms, machine learning, shear building, SHAP explainability.

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.

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