• Geomechanics and Engineering
• /
• v.14 no.5
• /
• pp.467-477
• /
• 2018

Estimation of hydraulic parameters is a critical step during design of foundation dewatering works. When many piles are installed in an aquifer, estimation of the hydraulic conductivity should consider the blocking of groundwater seepage by the piles. Based on field observations during a dewatering project in Shanghai, hydraulic conductivities are back-calculated using a numerical model considering the actual position of each pile. However, it is difficult to apply the aforementioned model directly in field due to requirement to input each pile geometry into the model. To develop a simple numerical model and find the optimal hydraulic conductivity, three scenarios are examined, in which the soil mass containing the piles is considered to be a uniform porous media. In these three scenarios, different sub-regions with different hydraulic conductivities, based on either automatic inverted calculation, or on effective medium theory (EMT), are established. The results indicate that the error, in the case which determines the hydraulic conductivity based on EMT, is less than that determined in the automatic inversion case. With the application of EMT, only the hydraulic conductivity of the soil outside the pit should be inverted. The soil inside the pit with its piles is divided into sub-regions with different hydraulic conductivities, and the hydraulic conductivity is calculated according to the volume ratio of the piles. Thus, the use of EMT in numerical modelling makes it easier to consider the effect of piles installed in an aquifer.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.304-311
• /
• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.34 no.5
• /
• pp.201-209
• /
• 1985

This paper describes a method for the state estimation by a modified fast decoupled estimation method and system decomposition. The state values are gained by using the weighted least square estimation method, fast decoupled estimation method, and modified fast decoupled estimation method. The estimated values of each method were compared about effectiveness of state values, respectively. This paper investigated the effects of impedance of well-condition or ill-condition into lines. The characteristics of state estimation were gained through hierarchical state estimation. Each method was applied to three model power systems, and, the results of test for the proposed method are given.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.5
• /
• pp.860-865
• /
• 2010

When a circuit breaker is opened, a large capacitance around the buses, the circuit breaker and the potential transformer (PT) might cause PT ferroresonance. During PT ferroresonance, the iron core repeats saturation and unsaturation even though the supplied voltage is a rated voltage. This paper describes an analytical analysis of PT ferroresonance in the transient-state. To analyze ferroresonance analytically, the iron core is modelled by a simplified two-segment core model in this paper. Thus, a nonlinear ordinary differential equation (ODE) for the flux linkage is changed into a linear ODE with constant coefficients, which enables an analytical analysis. In this simplified model, each state, which is either saturated or unsaturated state, corresponds to one of the three modes, i.e. overdamping, critical damping and underdamping. The flux linkage and the voltage in each state are obtained analytically by solving the linear ODE with constant coefficients. The proposed transient analysis is effective in the more understanding of ferroresonance and thus can be used to design a ferroresonance prevention or suppression circuit of a PT.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1201-1204
• /
• 2004

This paper suggests a DCS (Distributed Control System) model for steam temperature system of the thermal power plant. The model calculated within sectional range is linear. In order to calculate mathematical models, the system is partitioned into two or three sectors according to its thermal conditions, that is, saturated water/steam and superheating state. It is divided into three sections; water supply, steam generation and steam heating loop. The steam heating loop is called 'superheater' or steam temperature system. Water spray supply is the control input. A first order linear model is extracted. For linear approach, sectional linearization is achieved. Modeling methodology is a decomposition-synthetic technique. Superheater is composed of several tube-blocks. For this block, linear input-output model is to be calculated. Each tiny model has its transfer function. By expanding these block models to total system, synthetic DCS linear models are derived. Control instrument include/exclude models are also considered. The resultant models include thermal combustion conditions, and applicable to practical plant engineering field.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.233-236
• /
• 2008

To analyze the saline intrusion in the place, such as an estuary, the three-dimensional numerical model is developed. In this study, the advection terms of the governing equations are discretized by upwind scheme. By using an explicit scheme for the longitudinal direction and an implicit scheme for the vertical direction, the numerical model is free from the restriction of temporal step size caused by a relatively small grid ratio. The equation of state is used to consider the density, and the scalar transport equation for salinity is employed the third order TVD to scheme to prevent unphysical oscillation near discontinuity. In order to verify saline intrusion, the numerical model is conducted to compare the previous model in the lock exchange. The present model generally show a good agreement with the previous one.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.6
• /
• pp.2893-2907
• /
• 2019

Wireless mobile communication systems in subway tunnels have been widely researched these years, due to increased demand for the communication applications. As a result, an accurate model is essential to effectively evaluate the communication system performance. Thus, a neoteric three-dimensional (3D) geometry-based stochastic model (GBSM) is proposed for the massive multiple-input multiple-output (MIMO) fading channels in tunnel environment. Furthermore, the statistical properties of the channel such as space-time correlation, amplitude and phase probability density are analyzed and compared with those of the traditional two-dimensional (2D) model by numerical simulations. Finally, the ergodic capacity is investigated based on the proposed model. Numerical results show that the proposed model can describe the channel in tunnels more practically.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.461-470
• /
• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Geomechanics and Engineering
• /
• v.38 no.3
• /
• pp.275-284
• /
• 2024

This paper aims to explore the evolution of the pullout behavior of geocell reinforcement insights from three-dimensional numerical studies. Initially, a developed model was validated with the model test results. The horizontal displacement of geocells and infill sand and the passive resistance transmission in the geocell layer were analyzed deeply to explore the evolution of geocell pullout behavior. The results reveal that the pullout behavior of geocell reinforcement is the pattern of progressive deformation. The geocell pockets are gradually mobilized to resist the pullout force. The vertical walls provide passive pressure, which is the main contributor to the pullout force. Hence, even if the frontal displacement (FD) is up to 90m mm, only half of the pockets are mobilized. Furthermore, the parametric studies, orthogonal analysis, and the building of the predicted model were also carried out to quantitative the geocell pullout behavior. The weights of influencing factors were ranked. Ones can calculate the pullout force accurately by inputting the aspect ratio, geocell modulus, embedded length, frontal displacement, and normal stress.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.8
• /
• pp.753-759
• /
• 2011

The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.