• Structural Monitoring and Maintenance
• /
• v.9 no.1
• /
• pp.81-105
• /
• 2022

The use of concrete filled steel tube (CFST) column is widely accepted due to its property of high axial load carrying capacity, more ductility and more resistant to earthquake specially using in bridges and high-rise buildings. The initial imperfection (δ) that produces during casting or fixing causes the reduction in load carrying capacity, this is the reason, experimental capacity is always less then theoretical one. In this research, the effect of δ on load carrying capacity and behavior of concrete filled steel tube (CFST) column have been investigated by numerically simulation of large number of models with different δ and other geometric parameters that include length (L), width (B), steel tube thickness (t), f'_c and f_y. Finite element analysis software ANSYS v18 is used to develop model of SCFST column to evaluate strength capacity, buckling and failure pattern of member which is applied during experimental study under cyclic axial loading. After validation of results, 42 models with different parameters are evaluated to develop empirical equation predicting axial load carrying capacity for different value of δ. Results indicate that empirical equation shows the 0 to 9% error for finite element analysis Forty-two models in comparison with ANSYS results, respectively. Empirical equation can be used for predicting the axial capacity of early estimating the axial capacity of SCFT column including 𝛿.

• Journal of Drive and Control
• /
• v.19 no.1
• /
• pp.51-61
• /
• 2022

This paper presents a model-free system based on a framework of a backstepping sliding mode control (BSMC) with a radial basis function neural network (RBFNN) and adaptive mechanism for electro-hydraulic systems (EHSs). First, an EHS mathematical model was dedicatedly derived to understand the system behavior. Based on the system structure, BSMC was employed to satisfy the output performance. Due to the highly nonlinear characteristics and the presence of parametric uncertainties, a model-free approximator based on an RBFNN was developed to compensate for the EHS dynamics, thus addressing the difficulty in the requirement of system information. Adaptive laws based on the actor-critic neural network (ACNN) were implemented to suppress the existing error in the approximation and satisfy system qualification. The stability of the closed-loop system was theoretically proven by the Lyapunov function. To evaluate the effectiveness of the proposed algorithm, proportional-integrated-derivative (PID) and improved PID with ACNN (ACPID), which are considered two complete model-free methods, and adaptive backstepping sliding mode control, considered an ideal model-based method with the same adaptive laws, were used as two benchmark control strategies in a comparative simulation. The simulated results validated the superiority of the proposed algorithm in achieving nearly the same performance as the ideal adaptive BSMC.

• Nuclear Engineering and Technology
• /
• v.55 no.1
• /
• pp.131-143
• /
• 2023

Constitutive equations in a nuclear reactor safety analysis code are mostly empirical correlations developed from experiments, which always accompany uncertainties. The accuracy of the code can be improved by modifying the constitutive equations fitting wider range of data with less uncertainty. Thus, the sensitivity of the code with respect to the constitutive equations is evaluated quantitatively in the paper to understand the room for improvement of the code. A new methodology is proposed which first starts by dividing the thermal hydraulic conditions into multiple sub-regimes using self-organizing map (SOM) clustering method. The sensitivity analysis is then conducted by multiplying an arbitrary set of coefficients to the constitutive equations for each sub-divided thermal-hydraulic regime with SOM to observe how the code accuracy varies. The randomly chosen multiplier coefficient represents the uncertainty of the constitutive equations. Furthermore, the set with the smallest error with the selected experimental data can be obtained and can provide insight which direction should the constitutive equations be modified to improve the code accuracy. The newly proposed method is applied to a steady-state experiment and a transient experiment to illustrate how the method can provide insight to the code developer.

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

• Wind and Structures
• /
• v.36 no.6
• /
• pp.367-377
• /
• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Journal of Drive and Control
• /
• v.20 no.4
• /
• pp.45-53
• /
• 2023

This study optimized the parameters of the helical gear based on the original external meshing helical gear pump, combined with the analysis of the stability and flow of the basic parameters of the equipment; herringbone gears were used to eliminate the axial force generated by the helical gears. An optimized helical gear rotor was built with NX. The error between the simulation and calculation results of pump displacement was 3.95% and the simulation results were valid. Analysis of the outlet pressure and lift changes (maximum change rates of 0.38% and 0.25%), pressure analysis of the XY center plane at different times in the same cycle (no pressure surge or drop), and analysis of the axial force of the primary and driven rotors (axis The axial force is close to 0) were performed. The results showed that the flow pulsation of the external gear pump was slight, the operation was smooth, vibration and friction were reduced, the wear of bearings and other components could be diminished, and the service life of the equipment was extended. The simulation results showed that the external gear pump met the design requirements.

• Geomechanics and Engineering
• /
• v.37 no.2
• /
• pp.97-107
• /
• 2024

The accurate prediction of grouting upward diffusion height is crucial for estimating the bearing capacity of tip-grouted piles. Borehole construction during the installation of bored piles induces soil unloading, resulting in both radial stress loss in the surrounding soil and an impact on grouting fluid diffusion. In this study, a modified model is developed for predicting grout diffusion height. This model incorporates the classical rheological equation of power-law cement grout and the cavity reverse expansion model to account for different degrees of unloading. A series of single-pile tip grouting and static load tests are conducted with varying initial grouting pressures. The test results demonstrate a significant effect of vertical grout diffusion on improving pile lateral friction resistance and bearing capacity. Increasing the grouting pressure leads to an increase in the vertical height of the grout. A comparison between the predicted values using the proposed model and the actual measured results reveals a model error ranging from -12.3% to 8.0%. Parametric analysis shows that grout diffusion height increases with an increase in the degree of unloading, with a more pronounced effect observed at higher grouting pressures. Two case studies are presented to verify the applicability of the proposed model. Field measurements of grout diffusion height correspond to unloading ratios of 0.68 and 0.71, respectively, as predicted by the model. Neglecting the unloading effect would result in a conservative estimate.

• Investigative Magnetic Resonance Imaging
• /
• v.18 no.4
• /
• pp.303-313
• /
• 2014

Purpose : In-vivo conductivity reconstruction using transmit field ($B_1{^+}$) information of MRI was proposed. We assessed the accuracy of conductivity reconstruction in the presence of statistical noise in complex $B_1{^+}$ map and provided a parametric model of the conductivity-to-noise ratio value. Materials and Methods: The $B_1{^+}$ distribution was simulated for a cylindrical phantom model. By adding complex Gaussian noise to the simulated $B_1{^+}$ map, quantitative conductivity estimation error was evaluated. The quantitative evaluation process was repeated over several different parameters such as Larmor frequency, object radius and SNR of $B_1{^+}$ map. A parametric model for the conductivity-to-noise ratio was developed according to these various parameters. Results: According to the simulation results, conductivity estimation is more sensitive to statistical noise in $B_1{^+}$ phase than to noise in $B_1{^+}$ magnitude. The conductivity estimate of the object of interest does not depend on the external object surrounding it. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the $B_1{^+}$ map, Larmor frequency, the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targeted tissue, SNR of $B_1{^+}$ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. Conclusion: Through all these relationships, quantitative conductivity estimation error due to statistical noise in $B_1{^+}$ map is modeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.

• Journal of Korean Society of Steel Construction
• /
• v.14 no.6
• /
• pp.701-710
• /
• 2002

An analysis program using orthotropic plate elements was developed to simplify the analysis of plates stiffened with open ribs and the orthotropic behavior of stiffened plates and the application of this program were evaluated using the sensitivity analysis and the parametric study. The inertial moment ratio, i.e., the ratio of the inertial moment of the rib to that of the plate was defined and the orthotropic behavior of stiffened plates corresponding to the inertial moment ratio was proved by the sensitivity analysis. To evaluate the application of this program, the parametric study for various types of stiffened plates was performed and then the maximum displacement of this study was compared to that of ABAQUS using isoparametric plate elements. The Results of this study agreed well with that of ABAQUS at the particular inertial moment ratio, that is proposed to the limit ratio of the orthotropic plate analysis and the correlative function between the error ratio and the inertial moment ratio was obtained. Therefore, the orthotropic plate analysis of stiffened plates with open ribs could have safe results over the limit ratio and also have good results simply by using the correlative function of this study.

• Environmental and Resource Economics Review
• /
• v.21 no.3
• /
• pp.743-776
• /
• 2012

This study utilizes the meta-analysis for the benefits transfer (MA-BT) approach to measure social costs the 7 target sites in the City and County of Honolulu. The estimated MA models (MA-1 and MA-1) were evaluated in terms of validity and reliability criteria. This study utilized a parametric t-test and a non-parametric sign rank test for checking validity. A transfer error measured by an absolute percentage difference was utilized to check reliability their similarity. The GIS was utilized for data collection in order to measure social costs for each target site. The results clearly demonstrated that social costs were substantially higher thant direct costs and varied market conditions and different methods used. In terms of validity and reliability criteria, MA models were preferred to the mean transfer value approach. MA-BT approach is desirable for measuring social costs for a project designed to measure social costs for these 7 proposed landfill sites with inaccessible data, on short time frames, and with little money. If researchers and planners have enough time and money, they can implement primary research. If not, the meta-analysis for the benefits transfer approach can be much better than no framework. The use of a GIS can help to identify secondary data within a specific radius of each target site.