• International Journal of Highway Engineering
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• v.10 no.3
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• pp.199-208
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• 2008

Prediction the performance of pavement provides proper information to an agency on decision-making process; especially evaluating the pavement performance and prioritizing the work plan. To date, there are a number of approaches to predict the future deterioration of pavements. However, there are some limitation to proper prediction of the pavement service life. In this paper, pavement performance model and pavement condition prediction model are developed in order to improve pavement condition prediction method. The prediction model of pavement condition through the regression analysis of real pavement condition is based on the probability distribution of pavement condition, which set to 5%, 15%, 25% and 50%, by condition of the pavement and traffic volume. The pavement prediction model presented from the behavior of individual pavement condition which are set to 5%, 15%, 25% and 50% of probability distribution. The performance of the prediction model is evaluated from analyzing the average, standard deviation of HPCI, and the percentage of HPCI which is lower than 3.0 of comparable section. In this paper, we will suggest the more rational method to determine the future pavement conditions, including the probabilistic duration and deterministic modeling methods regarding the impact of traffic volume, age, and the type of the pavement.

• International Journal of Highway Engineering
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• v.4 no.4 s.14
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• pp.1-12
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• 2002

Pavement Management System has a special purpose that the rehabilitation strategy applied on pavement should be executable in view of technical and economical point after new pavement open to the traffic. To achieve that purpose, a reliable pavement performance prediction model should be embeded in the system. The object of this study is to develop a probabilistic pavement performance prediction model for evaluating asphalt pavements based on the Markov chain concept. In this paper, methodology of the Markov chain modeling principle is explained, and the application of this model to asphalt pavement is described. As the results, transition matrics for predicting asphalt pavement performance are obtained, and also performance life is estimated quantitatively by this system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.599-605
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• 2012

It is important to decide traffic opening time for construction plan of epoxy asphalt pavement. For this purpose, strength prediction model of epoxy asphalt concrete is required. In this study, Marshall stability was measured according to temperature and time for making strength properties equation. Strength prediction model was developed using chemical kinetics considering temperature variation. The traffic opening time of epoxy asphalt pavement on bridge deck has been predicted using the developed model. The prediction and actual traffic opening times were different by 17-days, because weathers of year 2009-2011 used in prediction model were different from weather of year 2012. When the prediction model used the actually measured temperatures of pavement, the difference between real opening time and prediction opening time was two days. The correlation analysis result between measured strength and prediction strength revealed that the $R^2$ using accurate temperature of pavement was 0.95. An improved precise prediction result is to be obtained if the prediction model uses accurate temperature data of pavement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3D
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• pp.223-229
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• 2012

Skid resistance is defined as the friction between pavement surfaces and vehicle tires. Lower skid resistances were observed as the vehicle speeds the water film thicknesses were increased according to the analysis results using computer modeling. The lift force is calculated from the analysis results and depends on vehicle speeds and the water film thickness. A modified IFI(international friction index) skid resistance prediction model was developed to reduce the differences between the IFI resistance prediction model and the actual skid resistance. The correlation analysis results between the IFI prediction model and the actual skid resistance revealed that the $R^2$ using the modified IFI prediction model was 0.64 whereas the $R^2$ using the conventional IFI prediction model was 0.49. This presents the modified prediction model is better than the conventional one. An improved precise prediction model is to be obtained if water film thicknesses are considered in the modified prediction model.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.8 no.2
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• pp.60-72
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• 2002

포장된 복합비타민의 보관수명을 예측하기 위한 수학모델을 수치해석의 방법 중 finite difference method을 이용한 컴퓨터 프로그램을 개발하였다. 이 컴퓨터 프로그램에는 포장재료의 수분확산계수와 용해도를 비롯한 식품의 수분확산계수 등 다양한 인자들을 포함하고 있다. 포장재료를 통과하는 수분의 물질전달은 G.A.B water sorption isotherm을 기본으로 했다. 본 연구에서는 비정상상태에서의 물질전달로 기본 수학모델링을 구하였다. 본 수학모델과 프로그램의 결과는 실험치와 비교하지 않았고 대신 특정한 경우를 가상하여 이에 존재하는 analytical solutions를 실제로 구하여 본 수학모델과 컴퓨터 프로그램의 신뢰도 측정을 하였다.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.34-43
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• 2019

The maintenance cost for road pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance preventive maintenance requires the establishment of a strategic plan through accurate prediction of road pavement. Hence, In this study, the deep neural network(DNN) and the recurrent neural network(RNN) were used in order to develop the expressway pavement damage prediction model. A superior model among these two network models was then suggested by comparing and analyzing their performance. In order to solve the RNN's vanishing gradient problem, the LSTM (Long short-term memory) circuits which are a more complicated form of the RNN structure were used. The learning result showed that the RMSE value of the RNN-LSTM model was 0.102 which was lower than the RMSE value of the DNN model, indicating that the performance of the RNN-LSTM model was superior. In addition, high accuracy of the RNN-LSTM model was verified through the comparison between the estimated average road pavement condition and the actually measured road pavement condition of the target section over time.

• International Journal of Highway Engineering
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• v.4 no.1 s.11
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• pp.123-134
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• 2002

Special pavement test sections were selected to develop a distress prediction model on asphalt pavement of National Highway. Experimental design was conducted for the selection of LTPP sections on in-service pavement(new and overlaid pavement) using several variables affecting pavement performance. Preliminary sections that satisfied the design template were chosen from the national highway database, and final selection was fixed through field inspection. The number of monitoring section is 95 including 47 overlaid pavement. A pavement distress data such as crack and rutting were collected for two years. An interim pavement performance analysis was peformed to show feasibility of performance monitoring program. Data related pavement such as traffic, weather, material characteristic and crack etc. should be collected for next project years and distress prediction model will be developed through the statistical analysis.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.22 no.2
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• pp.33-37
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• 2016

One-way degassing valves usually designed for coffee packaging are recently applied to the various food packaging such as fermented health functional food or home meal replacement (HMR) packaging. The optimized degassing pressure by food product is important factor for keeping effective freshness and improving preservation of the food, therefore the development of degassing valves specified with various open pressure is needed. In this study, the mechanical characteristics of the degassing valve with ring type rubber disk were analyzed and a mathematical model was developed to predict the open pressure of the valve. The model was verified with test results derived from several available valves, and it may be useful in designing and developing a new valve.

• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.67-72
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• 2002

Water content of soils within pavement varies seasonally depending on climatic factors such as rainfall, temperature and so on, since a hydraulic gradient due to rainfall causes moisture flow, and a thermal gradient due to temperature change induces not only heat flow but also moisture flow directly and indirectly. Soils within pavement are usually in an unsaturated state, and heat flow and moisture flow have been recognized as coupled processes with complex interactions between them. This paper presents a one-dimensional analysis model by the finite element method for the coupled heat flow and moisture flow in unsaturated soils. The model can be used to predict not only the change of temperature and water content, but also frist heave with time. It will be a meaningful work for the design and maintenance of pavement to predict the change of the temperature and water content and frist heave. The model is tested through comparisons with the results by other models.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.129-141
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• 2006

The vertical soil pressure developed in the granular layer of asphalt pavement system is influenced by various factors, including the wheel load magnitude, the loading speed, and asphalt pavement temperature. This research observed the distribution of vertical soil pressure in pavement supporting layer by investigating measured data from soil pressure gage in the KHC Test Road. The existing specification of subbase and subgrade compaction was also evaluated with measured vertical pressure. The finite element analysis was conducted to verify the accuracy of results with measured data because it can maximize research capacity without significant field test. The test data was collected from A5, A7, A14, and A15 test sections at August, September, and November 2004 and August 2005. Those test sections and test data were selected because they had best quality. The size of influence area was evaluated and the vertical pressure variation was investigated with respect to load level, load speed, and pavement temperature. The lower speed, higher load level, and higher pavement temperature increased the vertical pressure and reduced the area of influence. The finite element result showed the similar trend of vertical pressure variation in comparison with measured data. The specification of compaction quality for subbase and subgrade is higher than the level of vertical pressure measured with truck load so that it should be lurker investigated.