• Computers and Concrete
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• v.24 no.3
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• pp.271-282
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• 2019

Concrete undergoes a series of thermo-based physio-chemical changes once exposed to elevated temperatures. Such changes adversely alter the composition of concrete and oftentimes lead to fire-induced explosive spalling. Spalling is a multidimensional, complex and most of all sophisticated phenomenon with the potential to cause significant damage to fire-exposed concrete structures. Despite past and recent research efforts, we continue to be short of a systematic methodology that is able of accurately assessing the tendency of concrete to spall under fire conditions. In order to bridge this knowledge gap, this study explores integrating novel artificial intelligence (AI) techniques; namely, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA), together with traditional statistical analysis (multilinear regression (MLR)), to arrive at state-of-the-art procedures to predict occurrence of fire-induced spalling. Through a comprehensive datadriven examination of actual fire tests, this study demonstrates that AI techniques provide attractive tools capable of predicting fire-induced spalling phenomenon with high precision.

• Fisheries and Aquatic Sciences
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• v.13 no.2
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• pp.167-181
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• 2010

To predict changes in the marine environment of the Beolgyo Stream Estuary in Jeonnam Province, South Korea, where cohesive tidal flats cover a broad area and a large bridge is under construction, this study conducted numerical simulations involving tidal flow and cohesive sediment transport. A wetting and drying (WAD) technique for tidal flats from the Princeton Ocean Model (POM) was applied to a large-scale-grid hydrodynamic module capable of evaluating the flow resistance of structures. Derivation of the eddy viscosity coefficient for wakes created by structures was accomplished through the explicit use of shear velocity and Chezy's average velocity. Furthermore, various field observations, including of tide, tidal flow, suspended sediment concentrations, bottom sediments, and water depth, were performed to verify the model and obtain input data for it. In particular, geologic parameters related to the evaluation of settling velocity and critical shear stresses for erosion and deposition were observed, and numerical tests for the representation of suspended sediment concentrations were performed to determine proper values for the empirical coefficients in the sediment transport module. According to the simulation results, the velocity variation was particularly prominent around the piers in the tidal channel. Erosion occurred mainly along the tidal channels near the piers, where bridge structures reduced the flow cross section, creating strong flow. In contrast, in the rear area of the structure, where the flow was relatively weak due to the formation of eddies, deposition and moderated erosion were predicted. In estuaries and coastal waters, changes in the flow environment caused by artificial structures can produce changes in the sedimentary environment, which in turn can affect the local marine ecosystem. The numerical model proposed in this study will enable systematic prediction of changes to flow and sedimentary environments caused by the construction of artificial structures.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.2
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• pp.344-354
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• 2009

Side scan sonar using acoustic wave plays a very important role in the underwater, sea floor, and shallow marine geologic survey. In this study, we have acquired side scan sonar data for the underwater man-made structures, artificial reefs and fishing grounds, installed and distributed in the survey area. We applied digital image processing techniques to side scan sonar data in order to improve and enhance an image quality. We carried out digital image processing with various kinds of filtering in spatial domain and frequency domain. We tested filtering parameters such as kernel size, differential operator, and statistical value. We could easily estimate the conditions, distribution and environment of artificial structures through the interpretation of side scan sonar.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.403-404
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• 2007

Compound eyes in nature present intriguing topics in physiological optics due to their unique optical scheme for imaging. For example, a bee's eye has thousands of integrated photonic units called ommatidia spherically arranged along a curvilinear surface so that each unit points in a different direction. The omni-directionally arranged ommatidium collects incident light with a narrow range of angular acceptance and independently contributes to the capability of wide field-of-view (FOV) detection. Artificial implementation of compound eyes has attracted a great deal of research interest because the wide FOV exhibits a huge potential for medical, industrial, and military applications. So far, imaging with a FOV over $90^{\circ}$ has been achieved only with fisheye lenses which rely on bulky and expensive multiple lenses and require stringent alignment. In this talk, we will discuss about the spherical 3D arrangement of the photonic structures of biologically inspired artificial compound eyes in a small form-factor to have and the functional and anatomical similiarity with natural compound eyes.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.7
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• pp.20-26
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• 2003

The ultra-lightweight high strength polymer concrete could be used for the drain structures under severe condition. In this study, materials used were unsaturated polyester resin, heavy calcium carbonate, artificial lightweight coarse aggregate and perlite. In the test results, the unit weight of the ultra-lightweight high strength polymer concrete was 946 kg f/$\textrm{m}^3$ and the compressive strength was appeared in 34.5 MPa. The compressive strength, splitting tensile strength, flexural strength, acid resistance and weather resistance were shown in excellently than that of the normal cement concrete. The draining trench had 1m length, 0.24 m width, 0.02 m thickness and 0.07 m height. The developed trench could be effectively used at the draining structures.

• Steel and Composite Structures
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• v.15 no.4
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• pp.451-466
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• 2013

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.

• Earthquakes and Structures
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• v.4 no.5
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• pp.509-525
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• 2013

In this paper, learning capabilities of two types of Arterial Neural Networks, namely hierarchical neural networks and Generalized Regression Neural Network were used in a two-stage approach to develop a method for generating spatial varying accelerograms from acceleration response spectra and a distance parameter in which generated accelerogram is desired. Data collected from closely spaced arrays of seismographs in SMART-1 array were used to train neural networks. The generated accelerograms from the proposed method can be used for multiple support excitations analysis of structures that their supports undergo different motions during an earthquake.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.287-291
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• 2003

To delineate the internal structures of alluvial aquifer, high resolution seismic and GPR methods were adopted in Buyeo Gunsu-Ri area. The result of seismic refraction survey shows the water table of the aquifer and the result of seismic reflection reveals the basement and somewhat dominant internal structures of alluvial aquifer. The internal heterogeneity due to variations in channel behavior can be delineated using GPR survey. GPR profiles for the point bar deposits near Buyeo county reveals two different stratigraphic units the lower inclined heterogeneous strata and the upper horizontally stratified strata. According to the increase of demand for water resource using artificial recharge in alluvium, it is believed that the information acquired by high resolution geophysical methods will have an important roles for the effective and sustainable development and usage of groundwater in alluvial aquifer.

• Smart Structures and Systems
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• v.7 no.3
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• pp.185-198
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• 2011

The promise of biomimetic smart structures that can function as sensors and actuators in biomedicine is enormous. Technological development in the field of stimuli-responsive shape memory polymers have opened up a new avenue of applications for polymer-based synthetic actuators. Such synthetic actuators mimic various attributes of living organisms including responsiveness to stimuli, shape memory, selectivity, motility, and organization. This article briefly reviews various stimuli-responsive shape memory polymers and their application as bioactuators. Although the technological advancements have prototyped the potential applications of these smart materials, their widespread commercialization depends on many factors such as sensitivity, versatility, moldability, robustness, and cost.

• Smart Structures and Systems
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• v.7 no.3
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• pp.199-211
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• 2011

Using computational modeling, we design a pair of biomimetic microcapsules that exploit chemical mechanisms to communicate and alter their local environment. As a result, these synthetic objects can undergo autonomous, directed motion. In the simulations, signaling microcapsules release "agonist" particles, while target microcapsules release "antagonist" particles and the permeabilities of both capsule types depend on the local particle concentration in the surrounding solution. Additionally, the released nanoscopic particles can bind to the underlying substrate and thereby create adhesion gradients that propel the microcapsules to move. Hydrodynamic interactions and the feedback mechanism provided by the dissolved particles are both necessary to achieve the cooperative behavior exhibited by these microcapsules. Our model provides a platform for integrating both the spatial and temporal behavior of assemblies of "artificial cells", and allows us to design a rich variety of structures capable of exhibiting complex dynamics. Due to the cell-like attributes of polymeric microcapsules and polymersomes, material systems are available for realizing our predictions.