• Nuclear Engineering and Technology
• /
• v.54 no.6
• /
• pp.2107-2119
• /
• 2022

Accurate remaining useful life (RUL) prediction for critical components of nuclear power equipment is an important way to realize aging management of nuclear power equipment. The electric gate valve is one of the most safety-critical and widely distributed mechanical equipment in nuclear power installations. However, the electric gate valve's extended service in nuclear installations causes aging and degradation induced by crack propagation and leakages. Hence, it is necessary to develop a robust RUL prediction method to evaluate its operating state. Although the particle filter(PF) algorithm and its variants can deal with this nonlinear problem effectively, they suffer from severe particle degeneracy and depletion, which leads to its sub-optimal performance. In this study, we combined the whale algorithm with regularized particle filtering(RPF) to rationalize the particle distribution before resampling, so as to solve the problem of particle degradation, and for valve RUL prediction. The valve's crack propagation is studied using the RPF approach, which takes the Paris Law as a condition function. The crack growth is observed and updated using the root-mean-square (RMS) signal collected from the acoustic emission sensor. At the same time, the proposed method is compared with other optimization algorithms, such as particle swarm optimization algorithm, and verified by the realistic valve aging experimental data. The conclusion shows that the proposed method can effectively predict and analyze the typical valve degradation patterns.

• Journal of the Korea Concrete Institute
• /
• v.23 no.5
• /
• pp.569-579
• /
• 2011

Reinforced concrete walls subjected to cyclic loading show complicated inelastic behaviors varying with aspect ratio, re-bar detail, and loading condition. In the present study, a macro model for nonlinear analysis of reinforced concrete walls was developed. For exact prediction of inelastic flexure-compression and shear behaviors, the macro model of the wall was idealized with longitudinal and diagonal uniaxial elements. The uniaxial elements consist of concrete and re-bars. Simplified cyclic models for concrete and re-bars under uniaxial loading was used. For verification, the proposed model was applied to slender, lowrise, and coupled walls subjected to cyclic loading. The results showed that the proposed method predicted the nonlinear behaviors of the walls with reasonable precision.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.35 no.2
• /
• pp.150-156
• /
• 2015

In this study, the effects of different mix proportions and fire scenarios (exposure temperatures and post-fire-curing periods) on fire-damaged concrete were analyzed using a nonlinear resonance vibration method based on nonlinear acoustics. The hysteretic nonlinearity parameter was obtained, which can sensitively reflect the damage level of fire-damaged concrete. In addition, a splitting tensile strength test was performed on each fire-damaged specimen to evaluate the residual property. Using the results, a prediction model for estimating the residual strength of fire-damaged concrete was proposed on the basis of the correlation between the hysteretic nonlinearity parameter and the ratio of splitting tensile strength.

• Steel and Composite Structures
• /
• v.9 no.2
• /
• pp.131-158
• /
• 2009

This paper presents a modelling technique for the nonlinear analysis of composite steel-concrete beams with partial shear interaction. It extends the applicability of two stiffness elements previously derived by the authors using the direct stiffness method, i.e. the 6DOF and the 8DOF elements, to account for material nonlinearities. The freedoms are the vertical displacement, the rotation and the slip at both ends for the 6DOF stiffness element, as well as the axial displacement at the level of the reference axis for the 8DOF stiffness element. The solution iterative scheme is based on the secant method, with the convergence criteria relying on the ratios of the Euclidean norms of both forces and displacements. The advantage of the approach is that the displacement and force fields of the stiffness elements are extremely rich as they correspond to those required by the analytical solution of the elastic partial interaction problem, thereby producing a robust numerical technique. Experimental results available in the literature are used to validate the finite element proposed in the paper. For this purpose, those reported by Chapman and Balakrishnan (1964), Fabbrocino et al. (1998, 1999) and Ansourian (1981) are utilised; these consist of six simply supported beams with a point load applied at mid-span inducing positive bending moment in the beams, three simply supported beams with a point load applied at mid-span inducing negative bending moment in the beams, and six two-span continuous composite beams respectively. Based on these comparisons, a preferred degree of discretisation suitable for the proposed modelling technique expressed as a function of the ratio between the element length and depth is proposed, as is the number of Gauss stations needed. This allows for accurate prediction of the nonlinear response of composite beams.

• Journal of Environmental Policy
• /
• v.13 no.2
• /
• pp.21-38
• /
• 2014

In response to global warming, the effect of the air temperature on water temperature has been noticed. The change in water temperature in river environment results in the change in water quality and ecosystem, especially Dissolved Oxygen (DO) level, and shifts in aquatic biota. Efforts need to be made to predict future water temperature in order to understand the timing of the projected river temperature. To do this, the data collected by the Ministry of Environment and the Korea Meteororlogical Administration has been used to build a nonlinear relationship between air and water temperature. The logistic function that includes four different parameters was selected as a working model and the parameters were optimized using SCE algorithm. Weekly average values were used to remove time scaling effect because the time scale affects maximum and minimum temperature and then river environment. Generally speaking nonlinear logistic model shows better performance in NSC and RMSE and nonlinear logistic function is recommendable to build a relationship between air and water temperature in Korea. The results will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• Journal of Korean Society for Quality Management
• /
• v.50 no.3
• /
• pp.349-371
• /
• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Earthquakes and Structures
• /
• v.25 no.1
• /
• pp.27-41
• /
• 2023

This study focused on nonlinear effective stress site response analysis using two coupled constitutive models, that is, the DM model (Dafalias and Manzari 2004), which incorporated a simple plasticity sand model accounting for fabric change effects, and the PMDY03 model (Khosravifar et al. 2018), that is, a 3D model for earthquake-induced liquefaction triggering and postliquefaction response. A detailed parametric study was conducted to validate the effectiveness of nonlinear site response analysis and porewater pressure (PWP) generation through a true coupled formulation for assessing the initiation of liquefaction at ground level. The coupled models demonstrated accurate prediction of liquefaction triggering, which was in line with established empirical liquefaction triggering relations in published databases. Several limitations were identified in the evaluation of liquefaction using the cyclic stress method, despite its widespread implementation for calculating liquefaction triggering. Variations in shear stiffness, represented by changes in shear wave velocity (Vs1), exerted the most significant influence on site response. The study further indicated that substantial differences in response spectra between nonlinear total stress and nonlinear effective stress analyses primarily occurred when liquefaction was triggered or on the verge of being triggered, as shown by excess PWP ratios approaching unity. These differences diminished when liquefaction occurred towards the later stages of intense shaking. The soil response was predominantly influenced by the higher stiffness values present prior to liquefaction. A key contribution of this study was to validate the criteria used to assess the triggering of level-ground liquefaction using true coupled effective-stress constitutive models, while also confirming the reliability of numerical approximations including the PDMY03 and DM models. These models effectively captured the principal characteristics of liquefaction observed in field tests and laboratory experiments.

• Journal of Korean Academy of Nursing
• /
• v.45 no.2
• /
• pp.280-292
• /
• 2015

Purpose: In this study a system dynamics methodology was used to identify correlation and nonlinear feedback structure among factors affecting unplanned extubation (UE) of ICU patients and to construct and verify a simulation model. Methods: Factors affecting UE were identified through a theoretical background established by reviewing literature and preceding studies and referencing various statistical data. Related variables were decided through verification of content validity by an expert group. A causal loop diagram (CLD) was made based on the variables. Stock & Flow modeling using Vensim PLE Plus Version 6.0b was performed to establish a model for UE. Results: Based on the literature review and expert verification, 18 variables associated with UE were identified and CLD was prepared. From the prepared CLD, a model was developed by converting to the Stock & Flow Diagram. Results of the simulation showed that patient stress, patient in an agitated state, restraint application, patient movability, and individual intensive nursing were variables giving the greatest effect to UE probability. To verify agreement of the UE model with real situations, simulation with 5 cases was performed. Equation check and sensitivity analysis on TIME STEP were executed to validate model integrity. Conclusion: Results show that identification of a proper model enables prediction of UE probability. This prediction allows for adjustment of related factors, and provides basic data do develop nursing interventions to decrease UE.

• Journal of Navigation and Port Research
• /
• v.35 no.1
• /
• pp.83-91
• /
• 2011

The accuracy of forecasting is remarkably important to reduce total cost or to increase customer services, so it has been studied by many researchers. In this paper, the artificial neural network (ANN), one of the most popular nonlinear forecasting methods, is compared with autoregressive integrated moving average(ARIMA) model through performing a prediction of container traffic. It uses a hybrid methodology that combines both the linear ARIAM and the nonlinear ANN model to improve forecasting performance. Also, it compares the methodology with other models in performance for prediction. In designing network structure, this work specially applies the genetic algorithm which is known as the effectively optimal algorithm in the huge and complex sample space. It includes the time delayed neural network (TDNN) as well as multi-layer perceptron (MLP) which is the most popular neural network model. Experimental results indicate that both ANN and Hybrid models outperform ARIMA model.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.42 no.11
• /
• pp.927-936
• /
• 2014

This paper presents development and verification of the progressive failure analysis upon the composite laminates. Strength and stiffness of the fiber-reinforced composite are analyzed by property degradation approach with emphasis on the material nonlinearity and continuum damage mechanics (CDM). Longitudinal and transverse tensile modes derived from Hashin's failure criterion are used to predict the thresholds for damage initiation and growth. The modified Newton-Raphson iterative procedure is implemented for determining nonlinear elastic and viscoelastic constitutive relations. Laminar properties of the composite are obtained by experiments. Prediction on the un-notched tensile (UNT) specimen is performed under the laminate level. Stress-strain curves and strength results are compared with the experimental measurement. It is concluded that the present nonlinear CDM approach is capable of predicting the strength and stiffness more accurately than the corresponding linear CDM one does.