• Coupled systems mechanics
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• v.7 no.2
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• pp.211-232
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• 2018

In this work we present an upscaling technique for multi-scale computations based on a stochastic model calibration technique. We consider a coarse-scale continuum material model described in the framework of generalized standard materials. The model parameters are considered uncertain, and are determined in a Bayesian framework for the given fine scale data in a form of stored energy and dissipation potential. The proposed stochastic upscaling approach is independent w.r.t. the choice of models on coarse and fine scales. Simple numerical examples are shown to demonstrate the ability of the proposed approach to calibrate coarse scale elastic and inelastic material parameters.

• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.559-573
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• 2012

An adaptive modeling and simulation technique is introduced for the effective and reliable fluid-structure interaction analysis using MSC/Dytran for large-scale complex pressurized liquid containment. The proposed method is composed of a series of the global rigid sloshing analysis and the locally detailed fluid-structure analysis. The critical time at which the system exhibits the severe liquid sloshing response is sought through the former analysis, while the fluid-structure interaction in the local region of interest at the critical time is analyzed by the latter analysis. Differing from the global coarse model, the local fine model considers not only the complex geometry and flexibility of structure but the effect of internal pressure. The locally detailed FSI problem is solved in terms of multi-material volume fractions and the flow and pressure fields obtained by the global analysis at the critical time are specified as the initial conditions. An in-house program for mapping the global analysis results onto the fine-scale local FSI model is developed. The validity and effectiveness of the proposed method are verified through an illustrative numerical experiment.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

• Computers and Concrete
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• v.21 no.4
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• pp.463-470
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• 2018

In the present study, soft computing i.e., machine learning techniques and regression models algorithms have earned much importance for the prediction of the various parameters in different fields of science and engineering. This paper depicts that how regression models can be implemented for the prediction of compressive strength of concrete. Three models are taken into consideration for this; they are Gaussian Process for Regression (GPR), Multi Adaptive Regression Spline (MARS) and Minimax Probability Machine Regression (MPMR). Contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate and age in days have been taken as inputs and compressive strength as output for GPR, MARS and MPMR models. A comparatively large set of data including 1030 normalized previously published results which were obtained from experiments were utilized. Here, a comparison is made between the results obtained from all the above mentioned models and the model which provides the best fit is established. The experimental results manifest that proposed models are robust for determination of compressive strength of concrete.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.3
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• pp.141-148
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• 2022

A hybrid turbulence model has developed by combining a sub-grid scale model using dynamic k equation in LES with k-𝜔 SST model of RANS equation. To ascertain potential applicability of the hybrid turbulence model, fully developed turbulent channel flows at Re_𝜏=180 have been simulated of which computational domain has a top wall with coarse cells and a bottom wall with fine cells. The streamwise mean velocity and turbulent intensity profiles showed a good agreement with DNS data when using the hybrid model rather than using a single model in k-𝜔 SST or dynamic k equation models. Computational simulations of turbulent flows around KVLCC2 with a pre-swirl duct have been mainly performed using the hybrid turbulence model. Compared to the results obtained from RANS simulation with k-𝜔 SST model as well as LES with dynamic k equation SGS model, turbulent wakes of the duct in the present simulation using the hybrid turbulence model were very similar to that of LES. Also, the resistances acting on hull, rudder and duct in hybrid turbulence model were similar to those in RANS simulation whereas the viscous forces acting on the hull in LES had a significant error due to coarse cells inappropriate to the sub-grid scale model.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.459-470
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• 2014

During ship design, welding-induced distortions are roughly estimated as a function of the size of the component as well as the welding process and residual stresses are assumed to be locally in the range of the yield stress. Existing welding simulation methods are very complex and time-consuming and therefore not applicable to large structures like ships. Simplified methods for the estimation of welding effects were and still are subject of several research projects, but mostly concerning smaller structures. The main goal of this paper is the application of a multi-layer welding simulation to the block joint of a ship structure. When welding block joints, high constraints occur due to the ship structure which are assumed to result in accordingly high residual stresses. Constraints measured during construction were realized in a test plant for small-scale welding specimens in order to investigate their and other effects on the residual stresses. Associated welding simulations were successfully performed with fine-mesh finite element models. Further analyses showed that a courser mesh was also able to reproduce the welding-induced reaction forces and hence the residual stresses after some calibration. Based on the coarse modeling it was possible to perform the welding simulation at a block joint in order to investigate the influence of the resulting residual stresses on the behavior of the real structure, showing quite interesting stress distributions. Finally it is discussed whether smaller and idealized models of definite areas of the block joint can be used to achieve the same results offering possibilities to consider residual stresses in the design process.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.697-706
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• 2019

A multiphase flow modeling approach equipped with a hybrid turbulence modeling method is applied to compute the gravity currents in a rectangular channel. The present multiphase solver considers the dense fluid, the less-dense ambient fluid and the air above free surface as three phases with separate flow equations for each phase. The turbulent effect is simulated by the IDDES (improved delayed detach eddy simulation), a hybrid RANS/LES, approach which resolves the turbulent flow away from the wall in the LES mode and models the near wall flow in RANS mode on moderately fine computational meshes. The numerical results show that the present model can successfully reproduce the gravity currents in terms of the propagation speed of the current heads and the emergence of large-scale Kelvin-Helmholtz type interfacial billows and their three dimensional break down into smaller turbulent structures, even on the relatively coarse mesh for wall-modeled RANS computation with low-Reynolds number turbulence model. The present solutions reveal that the modeling approach can capture the large-scale three dimensional behaviors of gravity current head accompanied by the lobe-and-cleft instability at affordable computational resources, which is comparable to the LES results obtained on much fine meshes. It demonstrates that the multiphase modeling method using the hybrid turbulence model can be a promising engineering solver for predicting the physical behaviors of gravity currents in natural environmental configurations.

• Ocean Systems Engineering
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• v.6 no.1
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• pp.61-97
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• 2016

This is the second of two papers on the 3D numerical modeling of nearshore hydro- and morphodynamics. In Part I, the focus was on surf and swash zone hydrodynamics in the cross-shore and longshore directions. Here, we consider nearshore processes with an emphasis on the effects of oceanic forcing and beach characteristics on sediment transport in the cross- and longshore directions, as well as on foreshore bathymetry changes. The Delft3D and XBeach models were used with four turbulence closures (viz., ${\kappa}-{\varepsilon}$, ${\kappa}-L$, ATM and H-LES) to solve the 3D Navier-Stokes equations for incompressible flow as well as the beach morphology. The sediment transport module simulates both bed load and suspended load transport of non-cohesive sediments. Twenty sets of numerical experiments combining nine control parameters under a range of bed characteristics and incident wave and tidal conditions were simulated. For each case, the general morphological response in shore-normal and shore-parallel directions was presented. Numerical results showed that the ${\kappa}-{\varepsilon}$ and H-LES closure models yield similar results that are in better agreement with existing morphodynamic observations than the results of the other turbulence models. The simulations showed that wave forcing drives a sediment circulation pattern that results in bar and berm formation. However, together with wave forcing, tides modulate the predicted nearshore sediment dynamics. The combination of tides and wave action has a notable effect on longshore suspended sediment transport fluxes, relative to wave action alone. The model's ability to predict sediment transport under propagation of obliquely incident wave conditions underscores its potential for understanding the evolution of beach morphology at field scale. For example, the results of the model confirmed that the wave characteristics have a considerable effect on the cumulative erosion/deposition, cross-shore distribution of longshore sediment transport and transport rate across and along the beach face. In addition, for the same type of oceanic forcing, the beach morphology exhibits different erosive characteristics depending on grain size (e.g., foreshore profile evolution is erosive or accretive on fine or coarse sand beaches, respectively). Decreasing wave height increases the proportion of onshore to offshore fluxes, almost reaching a neutral net balance. The sediment movement increases with wave height, which is the dominant factor controlling the beach face shape.