Abstract The field of structural mechanics deals with the behavior bodies under loads, and a considerable portion education involves introduction theoretical models to describe real-world elements. However, gap between abstract descriptions in classroom versus experience perception deformation can be an obstacle learning. This paper presents preliminary results use mixed reality technology bridge this by enabling real-time simulation elements effective immersive visualization their response....

In this paper, a new kind of activation function using particular combination stop and play operators is proposed used in feedforward neural network to improve its learning capability the identification nonlinear hysteretic material behavior with both stiffness strength degradation. The neuron are referred as deteriorating generalized Prandtl network, respectively. To show generality it trained on several data sets generated by various mathematical models hysteresis without deterioration...

Abstract Intended to be the first course in design for civil engineering undergraduate students, Introduction Structural Design introduces application of mechanics context material-specific approaches both structural components and systems. Research reveals, however, that students struggle with understanding behavior three-dimensional because shortcomings representations used visualization traditional textbook lecture-oriented instruction. This research project aims leverage mobile augmented...

Deep learning-based defect feature recognition from 2D image datasets, has recently been a very active research area and deep Convolutional Neural Networks have brought breakthroughs toward object detection recognition. Due to CNN's outstanding performance, several recent studies applied it for in either routine or post-earthquake infrastructure inspections reported competitive performance potential automating safety assessment. Despite their benefits, the majority of approaches do not...

This paper describes a novel technique for detecting internal or unseen damage in structural steel members by combining measurements from full-field three-dimensional digital image correlation (3D-DIC) with topology optimization framework. Unlike the majority of conventional methods that rely on specialized forms surface-penetrating waves radiation imaging, this work employs optical cameras to measure surface strains and deformations using 3D-DIC followed an approach detect existing damage....

A new method using neural networks for the transformation of results from dam models to prototypes has been proposed and validated through application Koyna Pine-Flat Dams, which have also investigated by other researchers. The network called neurotransformer. common building a suitable experimental model be tested on shaking table is linear dimensional analysis or simply scaling (LS). However, because LS theoretically applicable systems, it generally provides imprecise extreme loading when...

In this paper, a method has been proposed to use artificial neural networks for the modeling of concrete gravity dams with nonlinear hysteretic response under earthquake loading. The main advantage is that it makes possible design an analysis tool specific dam based on data obtained from monitoring said dam; hence, expected could provide more precise results than software presently available. This especially pronounced when be analyzed strong earthquakes where its and hysteretic. modeler...

Hysteretic phenomena have been observed in different branches of engineering sciences. Although each them has its own characteristics, Madelung’s rules are common among most them. Based on rules, we propose a general approach to the simulation both rate-independent and rate-dependent hystereses with either congruent or non-congruent loops. In this approach, static function accommodates properties hystereses. Using learning capability neural networks, an adaptive model for hysteresis is...

Abstract This study explores a super-elastic memory alloy re-centering damper device and investigates its performance in improving the response of steel frame structures subjected to multi-level seismic hazard. The configuration was initially proposed by authors different paper. (SMARD) counts on high-performance shape (SMA) bars for capability employs friction springs augment deformation capacity. First all, this NiTiHfPd SMAs under various conditions illustrates their application into...

Structural health monitoring (SHM) describes a decision-making framework that is fundamentally guided by state change detection of structural systems. This typically relies on the use continuous or semi-continuous measured response to quantify this in system behavior, which often related initiation some form damage. Measurement approaches used for traditional SHM are numerous, but most limited either describing localized global phenomena, making it challenging characterize operational...

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Digital Twins technology is revolutionizing decision-making in scientific research by integrating models and simulations with real-time data. Unlike traditional Structural Health Monitoring methods, which rely on computationally intensive Image Correlation have limitations data integration, this proposes a novel approach using Artificial Intelligence. Specifically, Convolutional Neural Networks are employed to analyze structural behaviors correlating speckle pattern images deformation...

Advances in imaging technologies and techniques have created new opportunities to leverage high-resolution 3D laser scanning as a non-destructive evaluation (NDE) tool for describing surface features of engineered components. These tools are capable resolving sub-millimeter details including flaws defects, thus providing quantitative data about that historically been assessed via subjective visual assessments. This is invaluable our understanding the performance existing structural system...

Internal properties of a sample can be observed by medical imaging tools, such as ultrasound devices, magnetic resonance (MRI) and optical coherence tomography (OCT) which are based on relying changes in material density or chemical composition [1-21]. As preliminary investigation, the feasibility to detect interior defects inferred from discrepancy elasticity modulus distribution three-dimensional heterogeneous using only surface full-field measurements finite element model updating an...