• 제목/요약/키워드: parameters of model

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간략하고 정확한 장방형 각형강관 가새부재 이력거동 예측 위한 해석모델 (Simple and Accurate Analytical Model for Predicting Cyclic Behavior of Rectangular Steel HSS Braces)

  • 한상환;성민수;마동준
    • 한국지진공학회논문집
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    • 제21권3호
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    • pp.145-152
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    • 2017
  • The objective of this study is to propose a simple and accurate analytical model for HSS braces. For this purpose, a physical theory model is adopted. Rectangular hollow section steel (HSS) braces are considered in this study. To accurately simulate the cyclic behavior of braces using the physical theory model, empirical equations calculating constituent parameters are implemented on the analytical model, which were proposed in the companion paper. The constituent parameters are cyclic brace growth, cyclic buckling load, and the incidence of local buckling and fracture. The analytical model proposed in this study was verified by comparing actual and simulated cyclic curves of brace specimens. It is observed that the proposed model accurately simulates the cyclic behavior of the braces throughout whole response range.

Efficient determination of combined hardening parameters for structural steel materials

  • Han, Sang Whan;Hyun, Jungho;Cho, EunSeon;Lee, Kihak
    • Steel and Composite Structures
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    • 제42권5호
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    • pp.657-669
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    • 2022
  • Structural materials can experience large plastic deformation under extreme cyclic loading that is caused by events like earthquakes. To evaluate the seismic safety of a structure, accurate numerical material models should be used. For a steel structure, the cyclic strain hardening behavior of structural steel should be correctly modeled. In this study, a combined hardening model, consisting of one isotropic hardening model and three nonlinear kinematic hardening models, was used. To determine the values of the combined hardening model parameters efficiently and accurately, the improved opposition-based particle swarm optimization (iOPSO) model was adopted. Low-cycle fatigue tests were conducted for three steel grades commonly used in Korea and their modeling parameters were determined using iOPSO, which was first developed in Korea. To avoid expensive and complex low cycle fatigue (LCF) tests for determining the combined hardening model parameter values for structural steel, empirical equations were proposed for each of the combined hardening model parameters based on the LCF test data of 21 steel grades collected from this study. In these equations, only the properties obtained from the monotonic tensile tests are required as input variables.

국면전환 블랙-숄즈 모형에서 정합성을 가진 모수의 추정 (Calibrated Parameters with Consistency for Option Pricing in the Two-state Regime Switching Black-Scholes Model)

  • 한규식
    • 대한산업공학회지
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    • 제36권2호
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    • pp.101-107
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    • 2010
  • Among a variety of asset dynamics models in order to explain the common properties of financial underlying assets, parametric models are meaningful when their parameters are set reliably. There are two main methods from which we can obtain them. They are to use time-series data of an underlying price or the market option prices of the underlying at one time. Based on the Girsanov theorem, in the pure diffusion models, the parameters calibrated from the option prices should be partially equivalent to those from time-series underling prices. We call this phenomenon model consistency. In this paper, we verify that the two-state regime switching Black-Scholes model is superior in the sense of model consistency, comparing with two popular conventional models, the Black-Scholes model and Heston model.

A Bayesian inference for fixed effect panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제23권2호
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    • pp.179-187
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    • 2016
  • The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

A parameter calibration method for PFC simulation: Development and a case study of limestone

  • Xu, Z.H.;Wang, W.Y.;Lin, P.;Xiong, Y.;Liu, Z.Y.;He, S.J.
    • Geomechanics and Engineering
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    • 제22권1호
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    • pp.97-108
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    • 2020
  • The time-consuming and less objectivity are the main problems of conventional micromechanical parameters calibration method of Particle Flow Code simulations. Thus this study aims to address these two limitation of the conventional "trial-and-error" method. A new calibration method for the linear parallel bond model (CM-LPBM) is proposed. First, numerical simulations are conducted based on the results of the uniaxial compression tests on limestone. The macroscopic response of the numerical model agrees well with the results of the uniaxial compression tests. To reduce the number of the independent micromechanical parameters, numerical simulations are then carried out. Based on the results of the orthogonal experiments and the multi-factor variance analysis, main micromechanical parameters affecting the macro parameters of rocks are proposed. The macro-micro parameter functions are ultimately established using multiple linear regression, and the iteration correction formulas of the micromechanical parameters are obtained. To further verify the validity of the proposed method, a case study is carried out. The error between the macro mechanical response and the numerical results is less than 5%. Hence the calibration method, i.e., the CM-LPBM, is reliable for obtaining the micromechanical parameters quickly and accurately, providing reference for the calibration of micromechanical parameters.

Proposal of Parameter Range that Offered Optimal Performance in the Coastal Morphodynamic Model (XBeach) Through GLUE

  • Bae, Hyunwoo;Do, Kideok;Kim, Inho;Chang, Sungyeol
    • 한국해양공학회지
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    • 제36권4호
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    • pp.251-269
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    • 2022
  • The process-based XBeach model has numerous empirical parameters because of insufficient understanding of hydrodynamics and sediment transport on the nearshore; hence, it is necessary to calibrate parameters to apply to various study areas and wave conditions. Therefore, the calibration process of parameters is essential for the improvement of model performance. Generally, the trial-and-error method is widely used; however, this method is passive and limited to various and comprehensive parameter ranges. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) method was used to estimate the optimal range of three parameters (gamma, facua, and gamma2) using morphological field data collected in Maengbang beach during the four typhoons that struck from September to October 2019. The model performance and optimal range of empirical parameters were evaluated using Brier Skill Score (BSS) along with the baseline profiles, sensitivity, and likelihood density analysis of BSS in the GLUE tools. Accordingly, the optimal parameter combinations were derived when facua was less than 0.15 and simulated well the shifting shape, from crescentic sand bar to alongshore uniform sand bars in the surf zone of Maengbang beach after storm impact. However, the erosion and accretion patterns nearby in the surf zone and shoreline remain challenges in the XBeach model.

Updating finite element model using dynamic perturbation method and regularization algorithm

  • Chen, Hua-Peng;Huang, Tian-Li
    • Smart Structures and Systems
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    • 제10권4_5호
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    • pp.427-442
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    • 2012
  • An effective approach for updating finite element model is presented which can provide reliable estimates for structural updating parameters from identified operational modal data. On the basis of the dynamic perturbation method, an exact relationship between the perturbation of structural parameters such as stiffness change and the modal properties of the tested structure is developed. An iterative solution procedure is then provided to solve for the structural updating parameters that characterise the modifications of structural parameters at element level, giving optimised solutions in the least squares sense without requiring an optimisation method. A regularization algorithm based on the Tikhonov solution incorporating the generalised cross-validation method is employed to reduce the influence of measurement errors in vibration modal data and then to produce stable and reasonable solutions for the structural updating parameters. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is employed to demonstrate the effectiveness and applicability of the proposed model updating technique. The results from the benchmark problem studies show that the proposed technique can successfully adjust the reduced finite element model of the structure using only limited number of frequencies identified from the recorded ambient vibration measurements.

비연성 RC 기둥의 하중-변형 응답 모사를 위한 모델 매개변수 제안 (Development of Model Parameter Prediction Equations for Simulating Load-deformation Response of Non-ductile RC Columns)

  • 이창석;한상환
    • 한국지진공학회논문집
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    • 제23권2호
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    • pp.119-129
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    • 2019
  • Many reinforced concrete (RC) buildings constructed prior to 1980's lack important features guaranteeing ductile response under earthquake excitation. Structural components in such buildings, especially columns, do not satisfy the reinforcement details demanded by current seismic design codes. Columns with deficient reinforcement details may suffer significant damage when subjected to cyclic lateral loads. They can also experience rapid lateral strength degradation induced by shear failure. The objective of this study is to accurately simulate the load-deformation response of RC columns experiencing shear failure. In order to do so, model parameters are calibrated to the load-deformation response of 40 RC column specimens failed in shear. Multivariate stepwise regression analyses are conducted to develop the relationship between the model parameters and physical parameters of RC column specimens. It is shown that the proposed predictive equations successfully estimated the model parameters of RC column specimens with great accuracy. The proposed equations also showed better accuracy than the existing ones.

잉여생산량을 추정하는 모델과 파라미터 추정방법의 비교 (Comparison of models for estimating surplus productions and methods for estimating their parameters)

  • 권유정;장창익;표희동;서영일
    • 수산해양기술연구
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    • 제49권1호
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    • pp.18-28
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    • 2013
  • It was compared the estimated parameters by the surplus production from three different models, i.e., three types (Schaefer, Gulland, and Schnute) of the traditional surplus production models, a stock production model incorporating covariates (ASPIC) model and a maximum entropy (ME) model. We also evaluated the performance of models in the estimation of their parameters. The maximum sustainable yield (MSY) of small yellow croaker (Pseudosciaena polyactis) in Korean waters ranged from 35,061 metric tons (mt) by Gulland model to 44,844mt by ME model, and fishing effort at MSY ($f_{MSY}$) ranged from 262,188hauls by Schnute model to 355,200hauls by ME model. The lowest root mean square error (RMSE) for small yellow croaker was obtained from the Gulland surplus production model, while the highest RMSE was from Schnute model. However, the highest coefficient of determination ($R^2$) was from the ME model, but the ASPIC model yielded the lowest coefficient. On the other hand, the MSY of Kapenta (Limnothrissa miodon) ranged from 16,880 mt by ASPIC model to 25,373mt by ME model, and $f_{MSY}$, from 94,580hauls by ASPIC model to 225,490hauls by Schnute model. In this case, both the lowest root mean square error (RMSE) and the highest coefficient of determination ($R^2$) were obtained from the ME model, which showed relatively better fits of data to the model, indicating that the ME model is statistically more stable and robust than other models. Moreover, the ME model could provide additional ecologically useful parameters such as, biomass at MSY ($B_{MSY}$), carrying capacity of the population (K), catchability coefficient (q) and the intrinsic rate of population growth (r).

Analyzing consolidation data to obtain elastic viscoplastic parameters of clay

  • Le, Thu M.;Fatahi, Behzad;Disfani, Mahdi;Khabbaz, Hadi
    • Geomechanics and Engineering
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    • 제8권4호
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    • pp.559-594
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    • 2015
  • A nonlinear creep function incorporated into the elastic visco-plastic model may describe the long-term soil deformation more accurately. However, by applying the conventional procedure, there are challenges to determine the model parameters due to limitation of suitable data points. This paper presents a numerical solution to obtain several parameters simultaneously for a nonlinear elastic visco-plastic (EVP) model using the available consolidation data. The finite difference scheme using the Crank-Nicolson procedure is applied to solve a set of coupled partial differential equations of the time dependent strain and pore water pressure dissipation. The model parameters are determined by applying the algorithm of trust-region reflective optimisation in conjunction with the finite difference solution. The proposed method utilises all available consolidation data during dissipation of the excess pore water pressure to determine the required model parameters. Moreover, the reference time in the elastic visco-plastic model can readily be adopted as a unit of time; denoting creep is included in the numerical predictions explicitly from the very first time steps. In this paper, the settlement predictions of thick soft clay layers are presented and discussed to evaluate and compare the accuracy and reliability of the proposed method against the graphical procedure to obtain the model parameters. In addition, comparison of the available experimental results to the numerical predictions confirms the accuracy of the numerical procedure.