• Wind and Structures
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• v.33 no.6
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• Wind and Structures
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• v.35 no.5
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• pp.337-351
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• 2022

As central-slotted box decks usually have excellent flutter performance, studies on this type of deck mostly focus on the vortex-induced vibration (VIV) control. Yet with the increasing span lengths, cable-supported bridges may have critical wind speeds of wind-induced static instability lower than that of the flutter. This is especially likely for bridges with a central-slotted box deck. As a result, the overall aerodynamic performance of such a bridge will depend on its wind-induced static stability. Taking a 1400 m-main-span cable-stayed bridge as an example, this study investigates the influence of a series of deck shape parameters on both static and flutter instabilities. Some crucial shape parameters, like the height ratio of wind fairing and the angle of the inner-lower web, show opposite influences on the two kinds of instabilities. The aerodynamic shape optimization conducted for both static and flutter instabilities on the deck based on parameter-sensitivity studies raises the static critical wind speed by about 10%, and the overall critical wind speed by about 8%. Effective VIV countermeasures for this type of bridge deck have also been proposed.

• Geomechanics and Engineering
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• v.35 no.1
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• pp.55-65
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• 2023

Soft clay is widely spread in nature and encountered in geotechnical engineering applications. The creep property of soft clay greatly affects the long-term performance of its upper structures. Therefore, it is vital to establish a reasonable and practical creep constitutive model. In the study, two updated hyperbolic equations based on the volumetric creep and deviatoric creep are respectively proposed. Subsequently, three creep constitutive models based on different creep behavior, i.e., V-model (use volumetric creep equation), D-model (use deviatoric creep equation) and VD-model (use both volumetric and deviatoric creep equations) are developed and compared. From the aspect of prediction accuracy, both V-model and D-model show good agreements with experimental results, while the predictions of the VD-model are smaller than the experimental results. In terms of the parametric sensitivity, D-model and VD-model are lower sensitive to parameter M (the slope of the critical state line) than V-model. Therefore, the D-model which is developed by incorporating the updated deviatoric creep equation is suggested in engineering applications.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.439-459
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• 2023

Numerical analysis has been adopted in nearly all modern scientific and engineering fields due to the rapid and ongoing evolution of computational technology, with the number of grid or mesh points in a given data field also increasing. Some values must be extracted from large data fields to evaluate and supplement numerical analysis results and observational data, thereby highlighting the need for a fast and effective interpolation approach. The quadrilateral irregular network (QIN) proposed in this study is a fast and reliable interpolation method that is capable of sufficiently satisfying these demands. A comparative sensitivity analysis is first performed using known test functions to assess the accuracy and computational requirements of QIN relative to conventional interpolation methods. These same interpolation methods are then employed to produce simple numerical model results for a real-world comparison. Unlike conventional interpolation methods, QIN can obtain reliable results with a guaranteed degree of accuracy since there is no need to determine the optimal parameter values. Furthermore, QIN is a computationally efficient method compared with conventional interpolation methods that require the entire data space to be evaluated during interpolation, even if only a subset of the data space requires interpolation.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.429-434
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• 1996

K-REM［1］, which is under development as a realistic evaluation model of large break LOCA, is applied to the analysis of cold leg guillotine break of Ulchin 3&4. Fuel parameters on which statistical analysis of their effects on the peak cladding temperature (PCT) are made and system parameters on which the concept of limiting value approach (LVA) are applied, are determined from the single parameter sensitivity study. 3 parameters of fuel gap conductance, fuel thermal conductivity and power peaking factor are selected as fuel related ones and 4 parameters of axial power shape, reactor power, decay heat and the gas pressure of safety injection tank (SIT) are selected as plant system related ones. Response surface of PCT is generated from the plant calculation results and on which Monte Carlo sampling is made to get plant application uncertainty which is statistically combined with code uncertainty to produce the 95th percentile PCT. From the break spectrum analysis, blowdown PCT of 1350.23 K and reflood PCT of 1195.56 K are obtained for break discharge coefficients of 0.8 and 0.5, respectively.

• Smart Structures and Systems
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• v.31 no.5
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• pp.437-454
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• 2023

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• Journal of Powder Materials
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• v.30 no.3
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• pp.223-232
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• 2023

Metal additive manufacturing (AM) has transformed conventional manufacturing processes by offering unprecedented opportunities for design innovation, reduced lead times, and cost-effective production. Aluminum alloy, a material used in metal 3D printing, is a representative lightweight structural material known for its high specific strength and corrosion resistance. Consequently, there is an increasing demand for 3D printed aluminum alloy components across industries, including aerospace, transportation, and consumer goods. To meet this demand, research on alloys and process conditions that satisfy the specific requirement of each industry is necessary. However, 3D printing processes exhibit different behaviors of alloy elements owing to rapid thermal dynamics, making it challenging to predict the microstructure and properties. In this study, we gathered published data on the relationship between alloy composition, processing conditions, and properties. Furthermore, we conducted a sensitivity analysis on the effects of the process variables on the density and hardness of aluminum alloys used in additive manufacturing.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.92-99
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• 2023

In this study, shear fracture specimens are designed using finite element analyses for the characterization of ductile fracture criteria of metal sheets. Many recently suggested ductile fracture criteria require experimental fracture data at the shear stress states in the model parameter identification. However, it is challenging to maintain shear stress states in tension-based specimens from the initial yield to the final fracture, and the loading path can be different for the different materials even with the same shear specimen geometries. To account for this issue, two different shear fracture specimens for low ductility/high ductility metal sheets are designed using the sensitivity tests conducted by finite element simulations. Priorly mechanical properties including the Hosford-Coulomb fracture criterion of the aluminum alloy 7075-T6 and DP590 steel sheets are used in the simulations. The results show that shear stress states are well-maintained until the fracture at the fracture initiation points by optimizing the notch geometries of the shear fracture specimens.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.135-135
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• 2022

In this study, we evaluated uncertainties in baseflow separation filter methods focusing on changes in recession constant (𝛼) values, which include Lynie & Holick (LH) algorithm, Chapman algorithm, Eckhardt filter, and EWMA filter. Here, we analyzed daily streamflow data at 14 stations in the Urmia Lake basin, Iran, from 2015 to 2019. The 𝛼 values were computed using three different approaches from calculating the slope of a recession curve by averaging the flow over all seasons, a correlation method, and a mean value of the ratio of Q_t+1 to Q_t. In addition to the 𝛼 values, the BFImax (maximum value of the baseflow index (BFI)) was determined for the Eckhardt filter through the backward filter method. As results, it indicates that the estimated baseflow is dependent upon the selection of filter methods, their parameters, and catchment characteristics at different stations. In particular, the EWMA filter showed the least changes in estimating the baseflow value by changing the 𝛼 value, and the Eckhardt filter and LH algorithm showed the highest sensitivity to this parameter at different stations.