• Journal of Korean Association for Spatial Structures
• /
• v.23 no.4
• /
• pp.81-88
• /
• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• Journal of computational fluids engineering
• /
• v.15 no.2
• /
• pp.28-34
• /
• 2010

Conductive and radiative thermal model configurations of an imager of a geostationary satellite are presented. A two-plane method is introduced for three dimensional conductive coupling which is not able to be treated by thin shell plate thermal modeling technique. Especially the two-plane method is applied to massive matters and PIP(Payload Interface Plate) in the imager model. Some massive matters in the thermal model are modified by adequate correction factors or equivalent thickness in order to obtain the numerical results of thermal modeling to be consistent with the analytic model. More detailed nodal breakdown is specially employed to the object which has the rapid temperature gradient expected by a rule of thumb. This detailed thermal model of the imager is supposed to be used for analyses and test predictions, and be correlated with the thermal vacuum test results before final in-flight predictions.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.12 s.117
• /
• pp.1192-1200
• /
• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature. However, the identification procedure of the four-parameter is very time-consuming one. In this study a new identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured frequency response functions(FRF) coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment step. A numerical example shows that the proposed method is useful in identifying the viscoelastic material parameters of fractional derivative model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.05a
• /
• pp.1235-1242
• /
• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the nonlinear dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature with fewer parameters than conventional spring-dashpot models. However the identification procedure of the four-parameter is very time-consuming one. An efficient identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured FRFs coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment. A numerical example shows that the proposed method is efficient and robust in identifying the viscoelastic material parameters of fractional derivative model.

• Computers and Concrete
• /
• v.21 no.6
• /
• pp.697-703
• /
• 2018

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.

• Computers and Concrete
• /
• v.32 no.4
• /
• pp.399-410
• /
• 2023

This study proposes a novel use of backpropagated Levenberg-Marquardt neural networks based on computational intelligence heuristics to comprehend the examination of hybrid nanoparticles on the flow of dusty liquid via stretched cylinder. A two-phase model is employed in the present work to describe the fluid flow. The use of desulphated nanoparticles of silver and molybdenum suspended in water as base fluid. The mathematical model represented in terms of partial differential equations, Implementing similarity transformationsis model is converted to ordinary differential equations for the analysis . By adjusting the particle mass concentration and curvature parameter, a unique technique is utilized to generate a dataset for the proposed Levenberg-Marquardt neural networks in various nanoparticle circumstances on the flow of dusty liquid via stretched cylinder. The intelligent solver Levenberg-Marquardt neural networks is trained, tested and verified to identify the nanoparticles on the flow of dusty liquid solution for various situations. The Levenberg-Marquardt neural networks approach is applied for the solution of the hybrid nanoparticles on the flow of dusty liquid via stretched cylinder model. It is validated by comparison with the standard solution, regression analysis, histograms, and absolute error analysis. Strong agreement between proposed results and reference solutions as well as accuracy provide an evidence of the framework's validity.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.16 no.1
• /
• pp.3263-3291
• /
• 1974

Experimental work of grain bin was carried out to develop the methods of natural air in-bin drying and storage. The method is considered to be more economical, labour saving, and an effective countermeasure to grain loss. To examine the possibility of farm use of the grain bin and to analyze the related factors concerned with in-bin grain drying and storage, ambient air conditions (especially the change of air temperature and relative humidity) and grain quality during drying and storage periods were investigated. A laboratory model bin was constructed to investigate the effect of different forced air conditions on the drying characteristics of rice. In addition, a grain bin with 2.2m diameter and 1.8m height, considered to be the optimum size for the average Korean farm, was constructed and tested to examine the drying and storing characteristics of rice. The weather data analyzed in this study was the nine-year (from 1964 to 1972) record of air temperature and relative humidity in the Suweon area, and the thirty-year (from 1931 to 1960) record of pentad normal relative humidity and air temperature in the Seoul area. From the results of the weather data analyses, the adequate air delivery hours (which was arbitrary defined as the condition to give less than 75% relative humidity) to dry the rice during October were about nine hours (from approximately 10 A.M. to 7 P.M, ) a day, in which the average air temperature was about 15.9$^{\circ}C$ and average relative humidity was 66%. The occurence of days having three hours of such conditions was 1, 2, and 1-day within the 1st, 2nd add last 10-day periods for the month of October, respectively. Therefore, it may be considered that the weather condition in October was satisfactory for the forced natural air drying. The results of the laboratory model bin test were analyzed to obtain the drying curve and drying rate for different drying stages and grain layers in the bin corresponding to various conditions of forced natural air. A drying experiment with a prototype grain bin showed that an approximate 5 percent grain moisture gradient through a 1.6 meter grain deposit was observed after 80 hours of intermittent drying, giving an over dried zone in the lower grain layers and an extremely high grain moisture zone in the upper layers. This indicates that an effective measure should be taken to reduce this high moisture gradient. In order to investigate the drying characteristics of bulk grain in a layerturning operation a grain bin test was performed. This showed a significant improvement of uniform drying. In this test, approximate 107 hours were required to dry a depth of 1.6 meter of grain from an initial moisture content of 22.2 percent to a moisture content of 16.7 percent using an air delivery rate of 2.8 cubic meter per a minute per every cubic meter of grain. This resulted in a 2 percent moisture gradient from the top to the bottom of the bin. During storage period, till the end of June the average temperature of grain was 2~3$^{\circ}C$ higher than ambient air temperature. But during July when the grain moisture content went up slightly (less than 1 percent), the average temperature of the grain also increased to 3~5$^{\circ}C$ higher than ambient air temperature. It is therefore recommended that for safe grain storage, grain should not be stored in sheet metal bins after mid May. From the above results, in-bin rice drying and storage can be used effectively on Korean farms. It is strongly recommended that the use of grain-bin system should be implemented for farm use to improve farm drying and storage of rice.

• Journal of Korean Society of Environmental Engineers
• /
• v.27 no.8
• /
• pp.813-821
• /
• 2005

This paper presents a modeling study of thermal dynamics and turbid current in the Obong Lake, Kangreung. The lake formed by the artificial dam in 1983 for agricultural water supply, is currently under consideration of reconstruction in order to expand the volume of reservoir for water supply and flood control in downstream area. The US Army Corps of Engineers' CE-QUAL-W2, a two-dimensional laterally averaged hydrodynamic and water quality model, was applied to the lake after reconstruction as well as the present lake. The model calibration and verification were conducted against surface water levels and temperature of the lake measured during the years of 2001 and 2003. The model results showed a good agreement with fold measurements both in calibration and verification. Utilizing the validated model, an impact of dam reconstruction on vertical temperature and hydrodynamics were predicted. The model results showed that steep temperature gradient between epilimnion and hypolimnion would be formed during summer, along with extension of cold deep water after reconstruction. During winter and spring seasons, however, the vertical temperature profiles was predicted to be quite similar both before and after reconstruction. This results indicated that thermal stratification would become stronger during summer and stay longer after dam reconstruction. From the examination of predicted water movements, it was noticed that the upstream turbid current would infiltrate into the interface between metalimnion and hypolimnion and then suspended solids would slowly settle down to the bottom before reconstruction. After reconstruction, however, it was shown that the upstream turbid current would stay longer in metalimnion with similar density due to strong stratification. The model also predicted that dam reconstruction would make suspended solids near the dam location significantly decrease.

• Structural Engineering and Mechanics
• /
• v.73 no.2
• /
• pp.191-207
• /
• 2020

This study aims at investigating the size-dependent free vibration of porous nanoplates when exposed to hygrothermal environment and rested on Kerr foundation. Based on the modified power-law model, material properties of porous functionally graded (FG) nanoplates are supposed to change continuously along the thickness direction. The generalized nonlocal strain gradient elasticity theory incorporating three scale factors (i.e. lower- and higher-order nonlocal parameters, strain gradient length scale parameter), is employed to expand the assumption of second shear deformation theory (SSDT) for considering the small size effect on plates. The governing equations are obtained based on Hamilton's principle and then the equations are solved using an analytical method. The elastic Kerr foundation, as a highly effected foundation type, is adopted to capture the foundation effects. Three different patterns of porosity (namely, even, uneven and logarithmic-uneven porosities) are also considered to fill some gaps of porosity impact. A comparative study is given by using various structural models to show the effect of material composition, porosity distribution, temperature and moisture differences, size dependency and elastic Kerr foundation on the size-dependent free vibration of porous nanoplates. Results show a significant change in higher-order frequencies due to small scale parameters, which could be due to the size effect mechanisms. Furthermore, Porosities inside of the material properties often present a stiffness softening effect on the vibration frequency of FG nanoplates.

• Atmosphere
• /
• v.27 no.2
• /
• pp.119-131
• /
• 2017

We present and discuss the Tropopause Folding Turbulence Detection (TFTD) algorithm for the Korean Communication, Ocean, Meteorological Satellite (COMS) which is originally developed for the Tropopause Folding Turbulence Product (TFTP) from the Geostationary Operational Environmental Satellite (GOES)-R. The TFTD algorithm assumes that the tropopause folding is linked to the Clear Air Turbulence (CAT), and thereby the tropopause folding areas are detected from the rapid spatial gradients of the upper tropospheric specific humidity. The Layer Averaged Specific Humidity (LASH) is used to represent the upper tropospheric specific humidity calculated using COMS $6.7{\mu}m$ water vapor channel and ERA-interim reanalysis temperature at 300, 400, and 500 hPa. The comparison of LASH with the numerical model specific humidity shows a strong negative correlation of 80% or more. We apply the single threshold, which is determined from sensitivity analysis, for cloud-clearing to overcome strong gradient of LASH at the edge of clouds. The tropopause break lines are detected from the location of strong LASH-gradient using the Canny edge detection based on the image processing technique. The tropopause folding area is defined by expanding the break lines by 2-degree positive gradient direction. The validations of COMS TFTD is performed with Pilot Reports (PIREPs) filtered out Convective Induced Turbulence (CIT) from Dec 2013 to Nov 2014 over the South Korea. The score test shows 0.49 PODy (Probability of Detection 'Yes') and 0.64 PODn (Probability of Detection 'No'). Low POD results from various kinds of CAT reported from PIREPs and the characteristics of high sensitivity in edge detection algorithm.