• International Journal of Highway Engineering
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• v.18 no.1
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• pp.1-11
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• 2016

PURPOSES : This study estimated the load effect of a single heavy truck to develop a live load model for the design and assessment of bridges located on an expressway with a limited truck entry weight. METHODS : The statistical estimation methods for the live load effect acting on a bridge by a heavy vehicle are reviewed, and applications using the actual measurement data for trucks traveling on an expressway are presented. The weight estimation of a single vehicle and its effect on a bridge are fundamental elements in the construction of a live load model. Two statistical estimation methods for the application of extrapolation in a probabilistic study and an additional estimation method that adopts the extreme value theory are reviewed. RESULTS : The proposed methods are applied to the traffic data measured on an expressway. All of the estimation methods yield similar results using the data measured when the weight limit has been relatively well observed because of the rigid enforcement of the weight regulation. On the other hand, when the estimations are made using overweight traffic data, the resulting values differ with the estimation method. CONCLUSIONS : The estimation methods based on the extreme distribution theory and the modified procedure presented in this paper can yield reasonable values for the maximum weight of a single truck, which can be applied in both the design and evaluation of a bridge on an expressway.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.189-197
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• 2009

In this study, truck weight data and load effects of single truck on bridges are analyzed for development of new vehicular load model of the reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In this study, truck weight data collected at four locations are used as well as data from four locations in other studies. Truck weight data are collected from WIM or BWIM system, which are known to give reliable data. Typical truck types, dimensions and axle weight distribution are determined. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I and 100 years maximum truck weights are estimated by linear regression on the probability paper. The load effects of trucks having estimated maximum weights are analyzed for span length from 10 m to 200 m.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.228-232
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• 2002

This paper is reporting the whole process of developing a weight measuring scaler of truck and trailer system for static and dynamic condition. The sensors attached on the top of springs each wheels. Acquisition and data processing performs accurate data extraction from noise environment, filtering and estimation. Weight information was highly distorted with noise and perturbation. Hence the perturbation was classified several categories and evaluated for accurate signal extract. The final products supply accurate and easy readable data of load weight for truck. It supplies total weight as well as loading condition of each axle. It is expected that it give the information to the truck operator of proper amount loading and safe condition to drive with it.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.127-133
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• 2022

Many manufacturers applying third party logistics (3PLs) have some challenges to increase their logistics efficiency. This study introduces an effort to estimate the weight of the delivery trucks provided by 3PL providers, which allows the manufacturer to package and load products in trailers in advance to reduce delivery time. The accuracy of the weigh estimation is more important due to the total weight regulation. This study uses not only the data from the company but also many general prediction variables such as weather, oil prices and population of destinations. In addition, operational statistics variables are developed to indicate the availabilities of the trucks in a specific weight category for each 3PL provider. The prediction model using XGBoost regressor and permutation feature importance method provides highly acceptable performance with MAPE of 2.785% and shows the effectiveness of the developed operational statistics variables.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.143-153
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• 2006

In design of bridges, estimation of actions and loadings is very important for the safety and maintenance of bridges. In general, effect of traffic loading on the bridge can be modeled as live load (including impact load) and fatigue load. For estimation of traffic loading, it is important to get reliable and comprehensive truck statistical data such as the traffic and weight information. To get statistical data, Bridge Weigh-In-Motion (BWIM), which measures the truck weights without stopping the traffic, is need to be developed. In this study, BWIM system with various functions is developed first. Then this system is used to get comprehensive truck data. Traffic loadings including fatigue and live loading are formulated from the truck data acquired from the bridges. Objectives of this study are to develop the BWIM system, to apply the system in test bridge in Highway, and to formulate the live and fatigue loading for bridge design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.511-518
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• 2011

Truck weight data are essential for road infrastructure design, maintenance and management. WIM (Weigh-In-Motion) system provides highway planners, researchers and officials with statistical data. Recently high speed WIM data also uses to support a vehicle weight regulation and enforcement activities. This paper aims at developing axle load estimating models with high speed WIM data collected from national highway. We also suggest a method to estimate axle load using simple regression model for WIM system. The model proposed by this paper, resulted in better axle load estimation in all class of vehicle than conventional model. The developed axle load estimating model will used for on-going or re-calibration procedures to ensure an adequate level of WIM system performance. This model can also be used for missing axle load data imputation in the future.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.90-97
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• 2016

Purpose: Majority of bridges and roads in Gangwon Province have been carrying loads associated with heavy materials such as rocks, mining products, and cement. This location-specific live loads have contributed to the present situation of overloading, compared to other provinces in Korea. However, the bridges in Gangwon province are designed by national bridge design specification, without considering the location-specific live load characteristics. Therefore, this study focuses on the real traffic data accumulated on regional weighing station to verify the live load characteristics, including actual live load gross vehicle weight, axle weight axle spacings, and number of trucks. Methods: In order to take into account the location specific live load, a governmental weigh station (38th national highway Miro) have been selected and the passing truck data are processed. Based on the truck survey, trucks are categorized into 3 different shapes, and each shape has been idealized into normal distribution. Then, the resulting survey data are processed to predict the target maximum live load values, including the axle loads and gross vehicle weights in 75 years service life span. Results: The results are compared to the nationally used DB-24 live loads, and the results show that nationally recognized DB-24 live load does not sufficiently represent real traffic in mountaineous region in Gangwon province. Conclusion: The comparison results in the recommendation of location-specific live load that should be taken into account for bridge design and evaluation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2048-2055
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• 2001

This paper develops a computational model for estimating the ride quality of a cabover type large-sized truck in a double wheel bumpy ride test. The computational model is developed using ADAMS. To verify the developed model, an actual vehicle double wheel bumpy ride test is performed. In the test, the vehicle maintains a straight course with a constant velocity such that the front two wheels are passed the bump at the same time. The bump has the height of 60mm, and the width of 550mm. In the test, four velocities are used. They are 10kph, 20kph, 30kph and 40kph. Since the large-sized truck's center of gravity location is high, and its weight is heavy, it is a quite severe test condition to perform the test with more than 30kph velocity. In the test, vertical accelerations on the floor of the cab are measured. The measured accelerations are compared to the simulation results. From the comparison, it is shown that the developed model can predict not only the measured acceleration's tendency but also peak accelerations quite well. In this paper, the validated model is utilized to compare the ride quality between a vehicle with a multi-leaf spring and a vehicle with a tapered leaf spring in the front suspension system in a double bumpy ride test.

• Journal of Korean Society of Steel Construction
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• v.29 no.6
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• pp.467-477
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• 2017

The live load effect of KL-510 of the current Korean bridge design code is examined by comparing with that of the multiple trucks of which the weights are statistically estimated from measured traffic data as well as with those of the related live load models. The truck weight data measured on the expressway before and after overweight enforcement are used to obtain the truck weights following the same procedures in deciding the live load model of the design codes and the results are compared with the load effect of KL-510. KL-510 yields a very uniform loading effect compared with the multiple truck effects when the weights are estimated from the data which contains some of the heavy trucks over the operational weight limit. KL-510 yields consistent results with the live load of AASHTO LRFD and shows less variation than the past load model DB-24 over the span lengths considered in this study. As a result of this research, the actual truck combinations equivalent to the notional KL-510 load model are constructed and it can be applied to the evaluation of the existing bridge and the calibration of the load factor of the permit vehicle.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.3
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• pp.231-236
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• 2009

Recently, The Hydroforming technology has recognized general technique in manufacture industry. Especially automotive industry, It has applied to increase strength, and decrease weight, cost and part number. The rigid axle suspension type is widely used for truck and bus in commercial vehicles due to simplicity. To develop the hydroforming rigid axle, it is necessary to estimate of the characteristics of front suspension from the design process. In this study, the characteristics estimation of the hydroforming rigid axle is preformed using Finite Element Analysis and apply to shape optimization.