• Structural Engineering and Mechanics
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• 제18권1호
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• pp.91-112
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• 2004

Concrete is a composite material and at meso-level, may be assumed to be composed of three phases: aggregate, mortar-matrix and aggregate-matrix interface. It is postulated herein that although non-linear material parameters are generally used to model this composite structure by finite element method, linear elastic fracture mechanics principles can be used for modelling at the meso level, if the properties of all three phases are known. For this reason, a novel meso-mechanical approach for concrete fracture which uses the composite material model with distributed-phase for elastic properties of phases and considers the size effect according to linear elastic fracture mechanics for strength properties of phases is presented in this paper. Consequently, the developed model needs two parameters such as compressive strength and maximum grain size of concrete. The model is applied to three most popular fracture mechanics approaches for concrete namely the two-parameter model, the effective crack model and the size effect model. It is concluded that the developed model well agrees with considered approaches.

• 한국CDE학회논문집
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• 제11권6호
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• pp.393-402
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• 2006

The purpose of this study is to develop mechanisms of nD model-based design by the combination of 2D drawing standards and 3D building models from the current 2D and text-based design. The aim of this study can be archived by defining the 2D model extension definitions for the IFC model development and harmonizing existing 2D standards. The paper examines 1) 3D Representation of Building Element and Building Services element, and 2D Model extension of IFC2X.2, 2) Basic development of additional 2D element that should be added to IFC model, and 3) mapping method between current 2D standard and IFC2.X2. Following this approach, the interoperability problem between 3D model and 2D drawing can be solved and finally an extended data model could be developed.

• Biotechnology and Bioprocess Engineering:BBE
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• 제10권2호
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• pp.142-148
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• 2005

This paper proposes a cell age model for Penicillium chrysogenum fed-batch cultivation to supply a qualitative insight into morphology-associated dynamics. The average ages of the segregated cell populations, such as growing cells, non-growing cells and intact productive cells, were estimated by this model. A combined model was obtained by incorporating the aver-age ages of the cell sub-populations into a known but modified segregated kinetic model from literature. For simulations, no additional effort was needed for parameter identification since the cell age model has no internal parameters. Validation of the combined model was per-formed by 20 charges of industrial-scale penicillin cultivation. Meanwhile, only two charge-dependent parameters were required in the combined model among approximately 20 parameters in total. The model is thus easily transformed into an adaptive model for a further application in on-line state variables prediction and optimal scheduling.

• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.265-273
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• 2016

A water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The three models are validated using Matlab with nonlinear input-output data that was not used during training.

• Journal of electromagnetic engineering and science
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• 제18권2호
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• pp.136-140
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• 2018

We propose an improved semi-empirical scattering model for X-band radar backscattering from rough sea surfaces. This new model has a wider validity range of wind speeds than does the existing semi-empirical sea spectrum (SESS) model. First, we retrieved the small-roughness parameters from the sea surfaces, which were numerically generated using the Pierson-Moskowitz spectrum and measurement datasets for various wind speeds. Then, we computed the backscattering coefficients of the small-roughness surfaces for various wind speeds using the integral equation method model. Finally, the large-roughness characteristics were taken into account by integrating the small-roughness backscattering coefficients multiplying them with the surface slope probability density function for all possible surface slopes. The new model includes a wind speed range below 3.46 m/s, which was not covered by the existing SESS model. The accuracy of the new model was verified with two measurement datasets for various wind speeds from 0.5 m/s to 14 m/s.

• Journal of information and communication convergence engineering
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• 제17권2호
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• pp.128-134
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• 2019

Based on the concept of Industry 4.0, various sensors are attached to facilities and equipment to collect data in real time and diagnose faults using analyzing techniques. Diagnostic technology continuously monitors faults or performance degradation of facilities and equipment in operation and diagnoses abnormal symptoms to ensure safety and availability through maintenance before failure occurs. In this paper, we propose a model to analyze the data and diagnose the state or failure using machine learning. The diagnosis model is based on a support vector machine (SVM)-based diagnosis model and a self-learning one-class SVM-based diagnostic model. In the future, it is expected that this model can be applied to facilities used in the entire industry by applying the actual data to the diagnostic model proposed in this paper, conducting the experiment, and verifying it through the model performance evaluation index.

• Structural Engineering and Mechanics
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• 제87권6호
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• pp.601-614
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• 2023

In this study, the uniaxial ratcheting effect of Z2CND18.12N austenitic stainless steel at room and elevated temperatures is firstly simulated based on the Ahmadzadeh-Varvani hardening rule (A-V model), which is embedded into the finite element software ABAQUS by writing the user material subroutine UMAT. The results show that the predicted results of A-V model are lower than the experimental data, and the A-V model is difficult to control ratcheting strain rate. In order to improve the predictive ability of the A-V model, the parameter γ2 of the A-V model is modified using the isotropic hardening criterion, and the extended A-V model is proposed. Comparing the predicted results of the above two models with the experimental data, it is shown that the prediction results of the extended A-V model are in good agreement with the experimental data.

• 공학교육연구
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• 제23권6호
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• pp.3-16
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• 2020

This study aims to introduce the ENACT model, which is a systematic teaching-learning model for cultivating social responsibility of science and engineering college students, and to discuss its educational implications. For the development of the ENACT model, we conducted extensive literature reviews on RRI, STEM education, and science and technology studies (STS). In addition, we examined exemplary overseas education programs emphasizing social responsibility of scientists/engineers and citizens. The ENACT model consists of five steps; 1) Engage in SSIs, 2) Navigate SSIs, 3) Anticipate consequences, 4) Conduct scientific and engineering practice, and 5) Take action. This model links Socioscientific Issues (SSI) education with engineering education, dividing the major elements of social responsibility education for scientists and engineers into the dimensions of epistemology and praxis, and reflected them in the model. This effort enables science and engineering college students to pursue more responsible and sustainable development by carrying out the responsible problem-solving process based on an understanding of the nature of science and technology. We plan to implement ENACT model based programs for science and engineering college students and to examine the effects.

• Computers and Concrete
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• 제31권3호
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• pp.253-265
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• 2023

In this research, the gene expression programming (GEP) technique was employed to provide a new model for predicting the maximum loading capacity of concrete-encased steel (CES) columns. This model was developed based on 96 CES column specimens available in the literature. The six main parameters used in the model were the compressive strength of concrete (f_c), yield stress of structural steel (f_ys), yield stress of steel rebar (f_yr), and cross-sectional areas of concrete, structural steel, and steel rebar (A_c, A_s and A_r respectively). The performance of the prediction model for the ultimate load-carrying capacity was investigated using different statistical indicators such as root mean square error (RMSE), correlation coefficient (R), mean absolute error (MAE), and relative square error (RSE), the corresponding values of which for the proposed model were 620.28, 0.99, 411.8, and 0.01, respectively. Here, the predictions of the model and those of available codes including ACI ITG, AS 3600, CSA-A23, EN 1994, JGJ 138, and NZS 3101 were compared for further model assessment. The obtained results showed that the proposed model had the highest correlation with the experimental data and the lowest error. In addition, to see if the developed model matched engineering realities and corresponded to the previously developed models, a parametric study and sensitivity analysis were carried out. The sensitivity analysis results indicated that the concrete cross-sectional area (A_c) has the greatest effect on the model, while parameter (f_yr) has a negligible effect.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.32-41
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• 2017

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering demanding environment platforms locate and complex topsides structure platforms own. Evacuation planning on platforms is usually challenging. The computational tool is a good choice to plan evacuation by emergency simulation. However, the complex structure of platforms and varied evacuation behaviors usually weaken the advantages of computational simulation. Therefore, this study developed a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model simulation environment by integrating matrix model and network model. During agent definition, in addition to basic characteristics, environment sensing and dynamic escape path planning functions are also developed to improve simulation performance. An example OOGP BIM topsides with different emergent scenarios is used to illustrate the developed model. The results showed that the developed model can well simulate evacuation on OOGPs and improve evacuation performance. The developed model was also suggested to be applied to other industries such as the architecture, engineering, and construction industry.