• Ocean Systems Engineering
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• v.11 no.1
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• pp.1-16
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• 2021

Experimental and numerical investigations were conducted to study the performance of a surface-fixed horizontal porous wave barrier in regular waves. The characteristics of the reflection and transmission coefficients, energy dissipation, and vertical wave force were examined versus different porosities of the barrier. Numerical simulations based on 3D Reynolds Averaged Navier-Stokes equations with standard low-Re k-ε turbulent closure and volume of fluid approach were accomplished and compared with the experimental results conducted in a 2D wave tank. Experimental measurements and numerical simulations were shown to be in satisfactory agreement. The qualitative wave behavior propagating over a horizontal porous barrier such as wave run-up, wave breaking, air entrapment, jet flow, and vortex generation was reproduced by CFD computation. Through the discrete harmonic decomposition of the vertical wave force on a wave barrier, the nonlinear characteristics were revealed quantitatively. It was concluded that the surface-fixed horizontal barrier is more effective in dissipating wave energy in the short wave period region and more energy conversion was observed from the first harmonic to higher harmonics with the increase of porosity. The present numerical approach will provide a predictive tool for an accurate and efficient design of the surface-fixed horizontal porous wave barrier.

• Structural Monitoring and Maintenance
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• v.9 no.3
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• pp.289-303
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• 2022

In this study, the impact of assigned pixel labels on the accuracy of crack image identification of steel structures is examined by using an atrous separable convolution neural network (ASCNN). Firstly, images containing fatigue cracks collected from steel structures are classified into four datasets by assigning different pixel labels based on image features. Secondly, the DeepLab v3+ algorithm is used to determine optimal parameters of the ASCNN model by maximizing the average mean-intersection-over-union (mIoU) metric of the datasets. Thirdly, the ASCNN model is trained for various image sizes and hyper-parameters, such as the learning rule, learning rate, and epoch. The optimal parameters of the ASCNN model are determined based on the average mIoU metric. Finally, the trained ASCNN model is evaluated by using 10% untrained images. The result shows that the ASCNN model can segment cracks and other objects in the captured images with an average mIoU of 0.716.

• Smart Structures and Systems
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• v.30 no.3
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• pp.245-253
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• 2022

A two-layer beam consisting of an elastoplastic layer and a functional layer made of shape memory alloy (SMA) TiNi is considered. Constitutive relations for SMA are set by a microstructural model capable to calculate strain increment produced by arbitrary increments of stress and temperature. This model exploits the approximation of small strains. The equations to calculate the variations of the strain and the internal variables are based on the experimentally registered temperature kinetics of the martensitic transformations with an account of the crystallographic features of the transformation and the laws of equilibrium thermodynamics. Stress and phase distributions over the beam height are calculated by steps, by solving on each step the boundary-value problem for given increments of the bending moment (or curvature) and the tensile force (or relative elongation). Simplifying Bernoulli's hypotheses are applied. The temperature is considered homogeneous. The first stage of the numerical experiment is modeling of preliminary deformation of the beam by bending or stretching at a temperature corresponding to the martensitic state of the SMA layer. The second stage simulates heating and subsequent cooling across the temperature interval of the martensitic transformation. The curvature variation depends both on the total thickness of the beam and on the ratio of the layer's thicknesses.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.245-257
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• 2022

Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.

• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.179-193
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• 2022

The shear behaviour of reinforced concrete members has been studied over the past decades by various researchers, and it can be simulated by analysing shear panel elements which has been regarded as a basic element of reinforced concrete members subjected to in-plane biaxial stresses. Despite various experimental studies on shear panel element which have been conducted so far, there are still a lot of uncertainties related to what influencing factors govern the shear behaviour and affect failure mechanism in reinforced concrete members. To identify the uncertainties, a finite element analysis can be used, which enables to investigate the impact of specific variables such as the reinforcement ratio, the shear retention factor, and the material characteristics including aggregate interlock, tension stiffening, compressive softening, and shear behaviour at the crack surface. In this study, a non-linear probabilistic analysis was conducted on reinforced concrete panels using a finite element method optimized for reinforced concrete members and advanced sampling techniques so that probabilistic analysis can be performed effectively. Consequently, this study figures out what analysis methodology and input parameters have the most influence on shear behaviour of reinforced concrete panels.

• Wind and Structures
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• v.34 no.1
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• pp.91-100
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• 2022

Numerical simulations are conducted to investigate the uniform flow (UF) and sinusoidal streamwise flow (SSF) over an oscillating 5:1 rectangular cylinder with harmonic heaving motion at initial angles of attack of α = 0° and 3° using two-dimensional, unsteady Reynolds-averaged Navier-Stokes (URANS) equations. First, the aerodynamic parameters of a stationary 5:1 rectangular cylinder in UF are compared with the previous experimental and numerical data to validate the capability of the computationally efficient two-dimensional URANS simulations. Then, the unsteady flow field and aerodynamic forces of the oscillating 5:1 rectangular cylinder in SSF are analysed and compared with those in UF to explore the effect of SSF on the rectangular cylinder. Results show that the alternative vortex shedding is disturbed by SSF both at α = 0° and 3°, resulting in a considerable decrease in the vortex-induced force, whereas the unsteady lift component induced by cylinder motion remains almost unchanged in the SSF comparing with that in UF. Notably, the strong buffeting forces are observed at α = 3° and the energy associated with unsteady lift is primarily because of the oscillations of SSF. In addition, the components of unsteady lift induced by the coupling effects of SSF and cylinder motion are discussed in detail.

• Geomechanics and Engineering
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• v.28 no.3
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• pp.225-237
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• 2022

Settlement evaluation is important for shallow tunnels in big cities to estimate the settlement that occurs due to the excavation of twin tunnels. The majority of earlier research on analytical solutions, on the other hand, concentrated on calculating the settlement for a single tunnel. This research introduces a procedure to evaluate the settlement induced by the excavation of twin tunnels (two parallel tunnels). In this study, a series of numerical analysis were performed to validate the analytical solution results. Two geological conditions were considered to derive the settlement depending on each case. The analytical and numerical methods were compared, which involved considering many sections and conducting a parametric study; the results have good agreement. Moreover, a comparison of the 3D flat model and 2D (FEM) with the analytical solution shows that in the fill soil, the maximum settlement values were obtained by the analytical solution. In contrast, the values obtained by the analytical solution in the rock is more conservative than those in the fill. Finally, this method was shown to be appropriate for twin tunnels dug side by side by utilizing finite element analysis 3D and 2D (PLAXIS 3D and PLAXIS 2D) to verify the analytical equations. Eventually, it will be possible to use this approach to predict settlement troughs over twin tunnels.

• Computers and Concrete
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• v.29 no.1
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• pp.1-14
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• 2022

Several aspects influence corrosive processes in reinforced concrete (RC) structures such as environmental conditions, structural geometry and mechanical properties. Since these aspects present large randomnesses, probabilistic models allow a more accurate description of the corrosive phenomena. Besides, the definition of limit states in the reliability assessment requires a proper mechanical model. In this context, this study proposes a straightforward methodology for the mechanical-probabilistic modelling of RC structures subjected to reinforcements' corrosion. An improved damage approach is proposed to define the limit states for the probabilistic modelling, considering three main degradation phenomena: concrete cracking, rebar yielding and rebar corrosion caused either by chloride or carbonation mechanisms. The stochastic analysis is evaluated by the Monte Carlo simulation method due to the computational efficiency of the Lumped Damage Model for Corrosion (LDMC). The proposed mechanical-probabilistic methodology is implemented in a computational framework and applied to the analysis of a simply supported RC beam and a 2D RC frame. Curves illustrate the probability of failure evolution over a service life of 50 years. Moreover, the proposed model allows drawing the probability of failure map and then identifying the critical failure path for progressive collapse analysis. Collapse path changes caused by the corrosion phenomena are observed.

• Wind and Structures
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• v.32 no.5
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• pp.439-452
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• 2021

The concept of Performance objective assessment is extended to wind engineering. This approach applies using the Database-Assisted Design technique, relying on the aerodynamic database provided by the National Institute of Standards and Technology (NIST). A structural model of a low-rise building is analyzed to obtain influence coefficients for internal forces and displacements. Combining these coefficients with time histories of pressure coefficients on the envelope produces time histories of load effects on the structure, for example knee and ridge bending moments, and eave lateral drift. The peak values of such effects are represented by an extreme-value Type I Distribution, which allows the estimation of the gust wind speed leading to the mean hourly extreme loading that cause specific performance objective compromises. Firstly a fully correlated wind field over large tributary areas is assumed and then relaxed to utilize the denser pressure tap data available but with considerably more computational effort. The performance objectives are determined in accordance with the limit state load combinations given in the ASCE 7-16 provisions, particularly the Load and Resistance Factor Design (LRFD) method. The procedure is then repeated for several wind directions and different dominant opening scenarios to determine the cases that produce performance objective criteria. Comparisons with two approaches in ASCE 7 are made.