• Smart Structures and Systems
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• v.4 no.3
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• pp.367-389
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• 2008

Shape Memory Alloys (SMAs) are unique materials with a paramount potential for various applications in bridges. The novelty of this material lies in its ability to undergo large deformations and return to its undeformed shape through stress removal (superelasticity) or heating (shape memory effect). In particular, Ni-Ti alloys have distinct thermomechanical properties including superelasticity, shape memory effect, and hysteretic damping. SMA along with sensing devices can be effectively used to construct smart Reinforced Concrete (RC) bridges that can detect and repair damage, and adapt to changes in the loading conditions. SMA can also be used to retrofit existing deficient bridges. This includes the use of external post-tensioning, dampers, isolators and/or restrainers. This paper critically examines the fundamental characteristics of SMA and available sensing devices emphasizing the factors that control their properties. Existing SMA models are discussed and the application of one of the models to analyze a bridge pier is presented. SMA applications in the construction of smart bridge structures are discussed. Future trends and methods to achieve smart bridges are also proposed.

• Smart Structures and Systems
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• v.13 no.1
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• pp.81-98
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• 2014

This paper presents the elastic buckling of smart lightweight column structures integrated with a pair of surface piezoelectric layers using artificial intelligence. The finite element modeling of Smart lightweight columns is found using $ANSYS^{(R)}$ software. Then, the first buckling load of the structure is calculated using eigenvalue buckling analysis. To determine the accuracy of the present finite element analysis, a compression study is carried out with literature. Later, parametric studies for length variations, width, and thickness of the elastic core and of the piezoelectric outer layers are performed and the associated buckling load data sets for artificial intelligence are gathered. Finally, the application of soft computing-based methods including artificial neural network (ANN), fuzzy inference system (FIS), and adaptive neuro fuzzy inference system (ANFIS) were carried out. A comparative study is then made between the mentioned soft computing methods and the performance of the models is evaluated using statistic measurements. The comparison of the results reveal that, the ANFIS model with Gaussian membership function provides high accuracy on the prediction of the buckling load in smart lightweight columns, providing better predictions compared to other methods. However, the results obtained from the ANN model using the feed-forward algorithm are also accurate and reliable.

• Journal of Korean Association for Spatial Structures
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• v.22 no.2
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• pp.39-46
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• 2022

Recently, machine learning is widely used to solve optimization problems in various engineering fields. In this study, machine learning is applied to development of a control algorithm for a smart control device for reduction of seismic responses. For this purpose, Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm. A single degree of freedom (SDOF) structure with a smart tuned mass damper (TMD) was used as an example structure. A smart TMD system was composed of MR (magnetorheological) damper instead of passive damper. Reward design of reinforcement learning mainly affects the control performance of the smart TMD. Various hyper-parameters were investigated to optimize the control performance of DQN-based control algorithm. Usually, decrease of the time step for numerical simulation is desirable to increase the accuracy of simulation results. However, the numerical simulation results presented that decrease of the time step for reward calculation might decrease the control performance of DQN-based control algorithm. Therefore, a proper time step for reward calculation should be selected in a DQN training process.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.346-349
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• 2005

The present study aims to design electrically and structurally effective antenna structures in order that the structural surface itself could become the antenna. The basic design concept is composite sandwich structure in which microstrip antenna is embedded and this is termed composite smart structure (CSS). The most important outstanding problem is that composite materials of structural function cannot be used without reducing antenna efficiency. Unfortunately, such materials have high electrical loss. This is a significant design problem that needs to be solved in practical applications. Therefore, the effect of composites facesheet on antenna performances is studied in the first stage. Changes in the gain of microstrip antenna due to composites facesheet have been determined. 'Open condition' is defined when gain is maximized and is a significant new concept in the design of high-gain antennas considering bandwidth in practical application. The open condition can be made with any thickness of outer facesheet by controlling its position. In the design of CSS, glass/epoxy composites and Nomex honeycomb were used with exploiting open condition. Experiments, confirm that the gain is improved (over 11 dBi) and the bandwidth is also as wide as specified in our requirements (over 10% at 12.2 GHz). With the open condition, wideband antenna can be integrated with mechanical structures without reducing any electrical performances, as confirmed experimentally here.

• Smart Structures and Systems
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• v.4 no.5
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• pp.667-684
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• 2008

Numerous devices exist for reducing or eliminating seismic damage to structures. These include passive dampers, semi-active dampers, and active control devices. The performance of structural systems with these devices has often been evaluated using numerical simulations. Experiments on structural systems with these devices, particularly at large-scale, are lacking. This paper describes a real-time hybrid testing facility that has been developed at the Lehigh University NEES Equipment Site. The facility enables real-time large-scale experiments to be performed on structural systems with rate-dependent devices, thereby permitting a more complete evaluation of the seismic performance of the devices and their effectiveness in seismic hazard reduction. The hardware and integrated control architecture for hybrid testing developed at the facility are presented. An application involving the use of passive elastomeric dampers in a three story moment resisting frame subjected to earthquake ground motions is presented. The experiment focused on a test structure consisting of the damper and diagonal bracing, which was coupled to a nonlinear analytical model of the remaining part of the structure (i.e., the moment resisting frame). A tracking indictor is used to track the actuator ability to achieve the command displacement during a test, enabling the quality of the test results to be assessed. An extension of the testbed to the real-time hybrid testing of smart structures with semi-active dampers is described.

• Smart Structures and Systems
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• v.7 no.3
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• Steel and Composite Structures
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• v.39 no.1
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• pp.1-20
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• 2021

An exact solution based on refined third-order theory (TOT) has been presented for functionally graded porous curved beams having deep curvature. The displacement field of the refined TOT is derived by imposing the shear free conditions at the outer and inner surfaces of curved beams. The properties of the two phase composite are tailored according the power law rule and the effective properties are computed using Mori-Tanaka homogenization scheme. The equations of motion as well as consistent boundary conditions are derived using the Hamilton's principle. The curved beam stiffness coefficients (A, B, D) are obtained numerically using six-point Gauss integration scheme without compromising the accuracy due to deepness (1 + z/R) terms. The porosity has been modeled assuming symmetric (even) as well as asymmetric (uneven) distributions across the cross section of curved beam. The programming has been performed in MATLAB and is validated with the results available in the literature as well as 2D finite element model developed in ABAQUS. The effect of inclusion of 1 + z/R terms is studied for deflection, stresses and natural frequencies for FG curved beams of different radii of curvature. Results presented in this work will be useful for comparison of future studies.

• 대한방사선방어학회:학술대회논문집
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• 2010.04a
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• pp.98-99
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• 2010

• Steel and Composite Structures
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• v.18 no.5
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• pp.1119-1127
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• 2015

A finite-element model for beams with partially delaminated layers is used to investigate their behavior. In this formulation account is taken of lateral strains and the first-order shear deformation theory is used. Both displacement continuity and force equilibrium conditions are imposed between the regions with and without delamination. Numerical results of the present model are presented and its performance is evaluated for static and dynamic problems.

• Journal of Korean Association for Spatial Structures
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• v.19 no.3
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• pp.4-8
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• 2019