• Steel and Composite Structures
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• v.32 no.4
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• pp.455-466
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• 2019

Despite the rapid advancement in computing resources, many real-life design and optimization problems in structural engineering involve huge computation costs. To counter such challenges, approximate models are often used as surrogates for the highly accurate but time intensive finite element models. In this paper, surrogates for first-order shear deformation based finite element models are built using a polynomial regression approach. Using statistical techniques like Box-Cox transformation and ANOVA, the effectiveness of the surrogates is enhanced. The accuracy of the surrogate models is evaluated using statistical metrics like $R^2$, $R^2{_{adj}}$, $R^2{_{pred}}$ and $Q^2{_{F3}}$. By combining these surrogates with nature-inspired multi-criteria decision-making algorithms, namely multi-objective genetic algorithm (MOGA) and multi-objective particle swarm optimization (MOPSO), the optimal combination of various design variables to simultaneously maximize fundamental frequency and frequency separation is predicted. It is seen that the proposed approach is simple, effective and good at inexpensively producing a host of optimal solutions.

• Steel and Composite Structures
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• v.29 no.6
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• pp.703-716
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• 2018

Rapid detection of damages in civil engineering structures, in order to assess their possible disorders and as a result produce competent decision making, are crucial to ensure their health and ultimately enhance the level of public safety. In traditional intelligent health monitoring methods, the features are manually extracted depending on prior knowledge and diagnostic expertise. Inspired by the idea of unsupervised feature learning that uses artificial intelligence techniques to learn features from raw data, a two-stage learning method is proposed here for intelligent health monitoring of civil engineering structures. In the first stage, $Nystr{\ddot{o}}m$ method is used for automatic feature extraction from structural vibration signals. In the second stage, Moving Kernel Principal Component Analysis (MKPCA) is employed to classify the health conditions based on the extracted features. In this paper, KPCA has been implemented in a new form as Moving KPCA for effectively segmenting large data and for determining the changes, as data are continuously collected. Numerical results revealed that the proposed health monitoring system has a satisfactory performance for detecting the damage scenarios of a three-story frame aluminum structure. Furthermore, the enhanced version of KPCA methods exhibited a significant improvement in sensitivity, accuracy, and effectiveness over conventional methods.

• Steel and Composite Structures
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• v.38 no.6
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• pp.717-737
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• 2021

A theoretical energy-based model to capture the mechanical response of thick woven composite laminates, which are used in such applications as maritime or aerospace, to high-velocity impact was developed. The dependences of the impact phenomenon on material and geometrical parameters were analysed making use of the Vaschy-Buckingham Theorem to provide a non-dimensional framework. The model was divided in three different stages splitting the physical interpretation of the perforation process: a first where different dissipative mechanisms such as compression or shear plugging were considered, a second where a transference of linear momentum was assumed and a third where only friction took place. The model was validated against experimental data along with a 3D finite element model. The numerical simulations were used to validate some of the new hypotheses assumed in the theoretical model to provide a more accurate explanation of the phenomena taking place during a high-velocity impact.

• Steel and Composite Structures
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• v.42 no.4
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• pp.489-499
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• 2022

This paper proposes a numerical optimization method to design the mesoscale architecture of textile composite for simultaneously enhancing mechanical and thermal properties, which compete with each other making it difficult to design intuitively. The base cell of the periodic warp and fill yarn system is served as the design space, and optimal fibre yarn geometries are found by solving the optimization problem through the proposed method. With the help of homogenization method, analytical formulae for the effective material properties as functions of the geometry parameters of plain-woven textile composites were derived, and they are used to form the inverse homogenization method to establish the design problem. These modules are then put together to form a multiobjective optimization problem, which is formulated in such a way that the optimal design depends on the weight factors predetermined by the user based on the stiffness and thermal terms in the objective function. Numerical examples illustrate that the developed method can achieve reasonable designs in terms of fibre yarn paths and geometries.

• Smart Structures and Systems
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• v.31 no.2
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• pp.141-154
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• 2023

After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.105-113
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• 2023

The study used the whole-life carbon assessment method to conduct a thorough carbon-neutral evaluation of a standard steel structure. To further assess carbon emissions, 11 design-changed models were evaluated, with changes made to the span between beams and columns. The results of the carbon emission assessment showed savings of approximately 13.1% by implementing the stage of the beyond life cycle. Additionally, the evaluation of carbon emissions through design changes revealed a difference of up to 42.2%. These findings confirmed that recycling and structural design changes can significantly reduce carbon emissions by up to 48.6%, making it an effective means of achieving carbon neutrality. It is therefore necessary to apply the stage of beyond life cycle and structural change to reduce carbon emissions.

• Progress in Superconductivity and Cryogenics
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• v.11 no.4
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• pp.8-11
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• 2009

This study introduced wastewater treatment method by High Gradient Magnetic Separation (HGMS). HGMS treatment was high efficient method for various industrial wastewaters. The system is currently research state, but we have surveyed commercialize the technology for industry. In rolling plate process, coolant wastewater was recycled by sedimentation and sand filter system. It needs several large reservoirs and long time to remove suspended solid (SS) like metal fines and iron oxide in hot rolling plate making process. If removing rate of suspended solid in rolling coolant wastewater is improved by using HGMS system, the productivity of working process can be increased and the area of reservoir can be reduced. We manufactured high temperature superconducting HGMS system that had a purpose to treatment of coolant wastewater in rolling plate process. We fabricated the prototypes of magnetic matrix filter consisting of stainless steel 430 mesh, which is a core component in the magnetic separation system, In our basic preliminary experiment using HGMS system, it has been clear that the fine paramagnetic particles in the coolant wastewater obtained from rolling plate process of POSCO can be separated with high efficiency.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.2
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• pp.32-40
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• 1994

In this study by using EMAT(electro magnetic acoustic transducer)the artificial slit is installed on 12B-SUS pipe test piece. By making 4 cycle SH-burst (EMA) incidence to 45 .deg. angle, the signal data of pulse, received from EMAT are translated into digital-signal-processing- method SSP(Split Spectrum Processing) and Deconvolution method. The main conclusions obtained are as follows; (1) the signal data received from EMAT are translated with digital signal proc- essing of SSP-method and Deconvolution-method and this method shows exellent results more than Ultrasonic testing method does; (2) noise can well be removed by SSP with signal data, and resolution and S/N ratio are advanced; (3) when used with Ultrasonic wave general stainless steel has proporties of multiscattering and reflection phenomena, but resolution is progressed by using Deconvolution method;and (4) as addition-averaging-processing mumber is increasing, the resolution and S/N ratio are improved and the satisfactory signal is obtained.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.149-158
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• 2022

Ladle furnace (LF) slag, waste from the steel-making process, was incorporated to improve the compressive strength of soil cement. LF slag was mixed to replace the cement in the soil-cement samples with wt% ratio 20:0, 15:5, and 10:10 of cement and slag, respectively. LF slag in the range of 5, 10, and 20 wt% was also separately added to the 20-wt% cement-treated soil samples. The soil-cement mixed LF slag samples were incubated in a plastic wrapping for 7, 14, and 28 days. The strength of soil cement was highly developed to be higher than the standard acceptable value (0.6 MPa) after incorporating slag into soil cement. The mixing of LF slag resulted in more hydration products for bonding soil particles, and hence improved the strength of soil cement. With the LF slag mixing either a replacement or additive materials in soil cement, the LF slag to cement ratio is considered to be less than 1, while the cement content should be more than 10 wt%. This is to promote a predominant effect of cement hydration by preventing the partially absorbed water on slag particles and keeping sufficient water content for the cement hydration in soil cement.

• Steel and Composite Structures
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• v.50 no.2
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• pp.237-247
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• 2024

Research on interfacial crack formation in orthotropic bi-materials has experienced a notable increase in recent years, driven by growing concerns about structural integrity and reliability. The existence of a crack at the interface of bi-materials has a substantial impact on mechanical strength and can ultimately lead to fracture. The primary objective of this article is to introduce a comprehensive analytical model and establish stress relationships for investigating interfacial crack between two non-identical orthotropic materials with desired crack-fiber angles. In this paper, we present the application of the Interfacial Maximum Tangential Stress (IMTS) criterion, in combination with the Reinforcement Isotropic Solid (RIS) model, to investigate the behavior of interfacial cracks in orthotropic bi-materials under mixed-mode I/II loading conditions. We analytically characterize the stress state at the interfacial crack tip using both Stress Intensity Factors (SIFs) and the T-stress term. Orthotropic materials, due to their anisotropic nature, can exhibit complex crack tip stress fields, making it challenging to predict crack initiation behavior. The secondary objective of this study is to employ the IMTS criterion to predict the crack initiation angle and explore the notable impact of the T-stress term on fracture behavior. Furthermore, we validate the effectiveness of our approach in evaluating Fracture Limit Curves (FLCs) for interfacial cracks in orthotropic bi-materials by comparing our FLCs with relevant experimental data from existing literature.