• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3100-3111
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• 2021

Numerical modeling for the safety-related equipment used in a nuclear power plant (i.e., cabinet facilities) plays an essential role in seismic risk assessment. A full finite element model is often time-consuming for nonlinear time history analysis due to its computational modeling complexity. Thus, this study aims to generate a simplified model that can capture the nonlinear behavior of the electrical cabinet. Accordingly, the distributed plasticity approach was utilized to examine the stiffness-degradation effect caused by the local buckling of the structure. The inherent dynamic characteristics of the numerical model were validated against the experimental test. The outcomes indicate that the proposed model can adequately represent the significant behavior of the structure, and it is preferred in practice to perform the nonlinear analysis of the cabinet. Further investigations were carried out to evaluate the seismic behavior of the cabinet under the influence of the constitutive law of material models. Three available models in OpenSees (i.e., linear, bilinear, and Giuffre-Menegotto-Pinto (GMP) model) were considered to provide an enhanced understating of the seismic responses of the cabinet. It was found that the material nonlinearity, which is the function of its smoothness, is the most effective parameter for the structural analysis of the cabinet. Also, it showed that implementing nonlinear models reduces the seismic response of the cabinet considerably in comparison with the linear model.

• Steel and Composite Structures
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• v.31 no.2
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• pp.173-185
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• 2019

This paper presents experimental and numerical investigations of aluminum tubular members subjected to combined bending and web crippling. A series of tests was performed on square hollow sections (SHS) fabricated by extrusion using 6061-T6 heat-treated aluminum alloy. Different specimen lengths were tested to obtain the interaction relationship between moment and concentrated load. The non-linear finite element models were developed and verified against the experimental results obtained in this study and test data from existing literature for aluminum tubular sections subjected to pure bending, pure web crippling, and combined bending and web crippling. Geometric and material non-linearities were included in the finite element models. The finite element models closely predicted the strengths and failure modes of the tested specimens. Hence, the models were used for an extensive parametric study of cross-section geometries, and the web slenderness values ranged from 6.0 to 86.2. The combined bending and web crippling test results and strengths predicted from the finite element analysis were compared with the design strengths obtained using the current American Specification, Australian/New Zealand Standard and European Code for aluminum structures. The findings suggest that the current specifications are either quite conservative or unconservative for aluminum square hollow sections subjected to combined bending and web crippling. Hence, a bending and web crippling interaction equation for aluminum square hollow section specimens is proposed in this paper.

• International journal of steel structures
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• v.18 no.5
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• pp.1784-1800
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• 2018

Tension-shear loading is a common loading condition in steel structures during the earthquake shaking. To study ductile fracture in structural steel under multiple stress states, experimental investigations on the different fracture mechanisms in Chinese Q235 steel were conducted. Different tension-shear loading conditions achieved by using six groups of inclined notch butterfly configurations covering pure shear, tension-shear and pure tension cases. Numerical simulations were carried out for all the specimens to determine the stress and strain fields within the critical sections. Two tension-shear fracture models were calibrated based on the hybrid experimental-numerical procedure. The equivalent fracture strain obtained from the round bar under tensile loading was used for evaluating these two models. The results indicated that the tension-shear criterion as a function of the shear fracture parameter had better performance in predicting the fracture initiation of structural steel under different loading conditions.

• Clinical and Experimental Vaccine Research
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• v.12 no.4
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• pp.291-297
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• 2023

Enterovirus infections induce infectious diseases in young children, such as hand, foot, and mouth disease which is characterized by highly contagious rashes or blisters around the hands, feet, buttocks, and mouth. This predominantly arises from enterovirus A71 or coxsackievirus A16 infections and in severe cases, they can lead to encephalitis, paralysis, pulmonary edema, or even fatality, representing a global health threat. Due to the absence of effective therapeutic strategies for these infections, various experimental animal models are being investigated for the development of vaccines. During the early stages of research on enterovirus infections, non-human primate infections exhibited symptoms like those in humans, leading to their utilization as model animals. However, due to economic and ethical considerations, their current usage is limited. While enterovirus infections do not readily occur in mice, an infection model with mouse-adapted strain in neonatal mice has been employed. Cellular receptors have been identified in human cells, and genetically modified mice expressing these receptors have been used. Most recently, the utilization of Mongolian gerbil model is actively being considered and should be pursued for further animal model development. So, herein, we provide a summarized overview of the current portfolio of available enterovirus infection models, emphasizing their respective advantages and limitations.

• Computers and Concrete
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• v.10 no.6
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• pp.557-573
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• 2012

This paper discusses the combined application of two different techniques, Neural Networks (NN) and Principal Component Analysis (PCA), for improved prediction of concrete properties. The combination of these approaches allowed the development of six neural networks models for predicting slump and compressive strength of concrete with mineral additives such as blast furnace slag, fly ash and silica fume. The Back-Propagation Multi-Layer Perceptron (BPMLP) with Bayesian regularization was used in all these models. They are produced to implement the complex nonlinear relationship between the inputs and the output of the network. They are also established through the incorporation of a huge experimental database on concrete organized in the form Mix-Property. Thus, the data comprising the concrete mixtures are much correlated to each others. The PCA is proposed for the compression and the elimination of the correlation between these data. After applying the PCA, the uncorrelated data were used to train the six models. The predictive results of these models were compared with the actual experimental trials. The results showed that the elimination of the correlation between the input parameters using PCA improved the predictive generalisation performance models with smaller architectures and dimensionality reduction. This study showed also that using the developed models for numerical investigations on the parameters affecting the properties of concrete is promising.

• Computers and Concrete
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• v.18 no.1
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• pp.1-16
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• 2016

In this study, an Artificial Neural Network (ANN) and Adaptive Network-based Fuzzy Inference Systems (ANFIS) prediction models for flexural strength of the cement mortars have been developed. For purpose of constructing this models, 12 different mixes with 144 specimens of the 2, 7, 28 and 90 days flexural strength experimental results of cement mortars containing pure Portland cement (PC), blast furnace slag (BFS), waste tire rubber powder (WTRP) and BFS+WTRP used in training and testing for ANN and ANFIS were gathered from the standard cement tests. The data used in the ANN and ANFIS models are arranged in a format of four input parameters that cover the Portland cement, BFS, WTRP and age of samples and an output parameter which is flexural strength of cement mortars. The ANN and ANFIS models have produced notable excellent outputs with higher coefficients of determination of $R^2$, RMS and MAPE. For the testing of dataset, the $R^2$, RMS and MAPE values for the ANN model were 0.9892, 0.1715 and 0.0212, respectively. Furthermore, the $R^2$, RMS and MAPE values for the ANFIS model were 0.9831, 0.1947 and 0.0270, respectively. As a result, in the models, the training and testing results indicated that experimental data can be estimated to a superior close extent by the ANN and ANFIS models.

• Journal of Environmental Science International
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• v.21 no.6
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• pp.695-704
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• 2012

The application of disinfection models on the plasma process was investigated. Nine empirical models were used to find an optimum model. The variation of parameters in model according to the operating conditions (first voltage, second voltage, air flow rate, pH) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Ralstonia Solanacearum which cause wilt in tomato plantation. Optimum disinfection models were chosen among the nine models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), $r^2$ values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum model was shown as Weibull+talil model followed by Log-linear+ Shoulder+Tail model. Two models were applied to the experimental data according to the variation of the operating conditions. In Weibull+talil model, Log10($N_o$), Log10($N_{res}$), ${\delta}$ and p values were examined. And in Log-linear+Shoulder+Tail model, the Log10($N_o$), Log10($N_{res}$), $k_{max}$, Sl values were calculated and examined.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.5
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• pp.15-25
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• 2000

The purpose of this paper is to examine the visual evaluation structure about the formal changes of streetscape by the different moving speed in two alternative control plans for the building height and the setback regulation. The virtual reality system is applied to the experimental tool. Eighty-two experimental models are made in consideration of the height and the setback of the building regulation cased by Midou-suji street in Osaka City, Japan. and ten typical models are selected by pre-experiment. Since the changes of the landscape structure consists of the height and the setback of the building, four the evaluation items are set: grade of continuity, order, openness, preference. As there are eighty-two landscape models which are too many to be applied in this experiment, ten role models are drawn out and used in this experiment. The mean difference test, discriminant analysis, and multiple linear regression methods had been used for the statistical analysis methods. The results of this study are as follows; 1) It is found out the fact of the difference evaluation structure amount experiments models. 2) From the sketch analysis and interview, it is found out difference cognition structure by the moving speed and alternatives. 3) From the discriminant and regression analysis, it is found out that the evaluation value about continuity becomes low by the moving speed change from walking speed to driving speed. We suggest that continuous experiment should be made with a variety of groups and models, and general and universal results should also be come out of the experiments above.

• Steel and Composite Structures
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• v.21 no.4
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• pp.703-753
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• 2016

The ratcheting behavior was studied experimentally for Z2CND18.12N elbow piping under cyclic bending and steady internal pressure. Dozens of cyclic plasticity models for structural ratcheting responses simulations were used in the paper. The four models, namely, Bilinear (BKH), Multilinear (MKIN/KINH), Chaboche (CH3), were already available in the ANSYS finite element package. Advanced cyclic plasticity models, such as, modified Chaboche (CH4), Ohno-Wang, modified Ohno-Wang, Abdel Karim-Ohno and modified Abdel Karim-Ohno, were implemented into ANSYS for simulating the experimental responses. Results from the experimental and simulation studies were presented in order to demonstrate the state of structural ratcheting response simulation by these models. None of the models evaluated perform satisfactorily in simulating circumferential strain ratcheting response. Further, improvement in cyclic plasticity modeling and incorporation of material and structural features, like time-dependent, temperature-dependent, non-proportional, dynamic strain aging, residual stresses and anisotropy of materials in the analysis would be essential for advancement of low-cycle fatigue simulations of structures.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.347-358
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• 2012

Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.