• Transactions of Materials Processing
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• v.12 no.4
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• pp.358-363
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• 2003

Adiabatic shear bands have been observed in the serrated chip during high strain rate metal cutting process of medium carbon steel and titanium alloy The recent microscopic observations have shown that dynamic recrystallization occurs in the narrow adiabatic shear bands. However the conventional flow stress models such as the Zerilli-Armstrong model and the Johnson-Cook model, in general, do not predict the occurrence of dynamic recrystallization (DRX) in the shear bands and the thermal softening effects accompanied by DRX. In the present study, a strain hardening and thermal softening model is proposed to predict the adiabatic shear localized chip formation. The finite element analysis (FEA) with this proposed flow stress model shows that the temperature of the shear band during cutting process rises above 0.5Τ$_{m}$. The simulation shows that temperature rises to initiate dynamic recrystallization, dynamic recrystallization lowers the flow stress, and that adiabatic shear localized band and the serrated chip are formed. FEA is also used to predict and compare chip formations of two flow stress models in orthogonal metal cutting with AISI 1045. The predictions of the FEA agreed well with the experimental measurements.s.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.435-449
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• 2022

Constitutive modeling that could reasonably predict and effectively evaluate the post-peak structural behavior while eliminating the mesh-dependency in numerical simulation remains to be developed for general engineering applications. Based on the previous work, a simple one-dimensional modeling procedure is proposed to predict and evaluate the post-peak response, as characterized by the evolution of localized strain field, of a steel member to monotonically uniaxial tension. The proposed model extends the classic one-dimensional softening with localization model as introduced by (Schreyer and Chen 1986) to account for the localization length, and bifurcation and rupture points. The new findings of this research are as follows. Two types of strain-softening functions (bilinear and nonlinear) are proposed for comparison. The new failure criterion corresponding to the constitutive modeling is formulated based on the engineering strain inside the localization zone at rupture. Furthermore, a new mathematical expression is developed, based on the strain rate inside and outside the localization zone, to describe the displacement field at which bifurcation occurs. The model solutions are compared with the experimental data on four low-carbon cylindrical steel bars of different lengths. For engineering applications, the model solutions are also compared to the experimental data of a cylindrical steel bar system (three steel bars arranged in series). It is shown that the bilinear and nonlinear softening models can predict the energy dissipation in the post-peak regime with an average difference of only 4%.

• Educational Technology International
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• v.15 no.2
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.

• The Plant Pathology Journal
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• v.30 no.2
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• pp.125-135
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• 2014

A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds $10^{15}cells/g$ within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.1
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• pp.1-8
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• 2022

This study proposes a penetration model in soil considering the wake separation and reattachment based on the integrated force law (IFL). Rigid body dynamics, the IFL, and semi-empirical resistance function about soil are utilized to formulate the motion of the hard projectile. The model can predict the trajectory in soil considering the spherical cavity expansion phenomenon under various oblique angles and angles of attack (AOA). The Mohr-Coulomb yield model is utilized as the resistance function of the soil. To confirm the feasibility of the proposed model, a comparative study is conducted with experimental results described in the open literature. From the comparative study, the penetration depth estimated from the proposed model had about 13.4% error compared to that of the experimental results. In general, the finite element method is widely used to predict the trajectory in soil for a projectile. However, it takes considerable time to construct the computational model for the projectile and perform the numerical simulation. The proposed model only needs to the dimension of the projectile and can predict the trajectory of the projectile in a few seconds.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.155-158
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• 1999

This paper discusses the validity of models to predict the compressive strength of concrete subjected to various temperature histories and the shortcomings of existing rate constant model and apparent activation energy concept. Based on the discussion, a modified rate constant model is proposed. The modified rate constant model, in which apparent activation energy is a nonlinear function of curing temperature and age, accurately estimates the development of the experimental compressive strengths by a few researches. Also, the apparent activation energy of concrete cured with high temperature decreases rapidly with age, but that cured with low temperature decreases gradually with age. Finally a generalized model to predict apparent activation energy and compressive strength is proposed, which is based on the regression results.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.456-461
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• 1995

The concept of hyperbolicity breaking is applied to predict the flow regime transition from inverted annular flow (IAF) to agitated inverted annular flow (AIAF). The resultant correlation has the similar form to Takenaka's empirical one. To validate the proposed model, it is applied to predict Takenaka's experimental results using R-113 refrigerant with four different tube diameters of 3, 5, 7 and 10 mm. The proposed model gives accurate predictions for the tube diameters of 7 and 10 min. As the tube diameter decreases, the differences between the predictions and the experimental results increase slightly. The flow regime transition from AIAF to dispersed flow (DF) is described by the drift flux model.

• Journal of Environmental Science International
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• v.4 no.2
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• pp.159-168
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• 1995

To predict reasonably the movement and the concentration of the pollutants in the coastal area. A simulation model should be prepared considering detail topography with land-sea and the urban effects, and the resolution near the source. The explicit method can not be applied due to the instability of the numerical calculation in high horizontal-grid resolution, while the ADI scheme satisfied with the high horizontal grid resolution and can be used in the fine mesh system which shows the detail topography, atmospheric flow The ADI method which studied the high horizontal grid resolution was excellent. The two dimensional model used in the study using ADI method is proved as a reasonable model to predict the wind field in any small scale area including mountainous coastal urban area.

• International Journal of Concrete Structures and Materials
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• v.6 no.4
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• pp.221-230
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• 2012

Cracking of repair material due to restraint of shrinkage could hinder the intended extension of serviceability of repaired concrete structure. The availability of model to predict shrinkage stress under restraint condition will be useful to assess whether repair material with particular deformation properties is resistance to cracking or not. The accuracy in the prediction will depend upon reliability of the model, input parameters, testing methods used to characterize the input parameters, etc. This paper reviews a variety of models to predict shrinkage stress in patch repair system. Effect of creep and composite action to release shrinkage stress in the patch repair system are quantified and discussed. Accuracy of the models is examined by comparing predicted and measured shrinkage stress. Simplified model to estimate shrinkage stress is proposed which requires only shrinkage property of repair material as an input parameter.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.10-19
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• 1996

In order to build a model to predict accidents in a complicated man-machine sytem, human errors and mechanical reliability can be viewed as the most important factors. Such factors are explicitly included in a generic model. Another point to keep in mind is that the model should be constructed so that the data in a type of accident can be utilized to predict other types of accidents. Based on such a generic prediction model, we analyze the effects of system reliability. When we improve the system reliability, in other words, when there are changes in model parameters, the predicted time to next accidents should be modified influencing the effects of system reliability improvements. We apply Bayesian approach and finds the formula to explain how a change on the machine reliability or human error probability influences the time to next accident.