• Structural Engineering and Mechanics
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• v.76 no.1
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• pp.1-15
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• 2020

The aim of this paper is to simply present live load factor calculation methodology formulation with the addition of a simple new future load projection procedure to previously proposed two methods. For this purpose, Oregon Weigh-in-Motion (WIM) data were used to calculate live load factors by using WIM data. These factors were calculated with two different approaches and by presenting new simple modifications in these methods. A very simple future load projection method is presented in this paper. Using four different WIM sites with different average daily truck traffic (ADTT) volume, and all year data, live load factors were obtained. The live load factors, were proposed as a function of ADTT. ADTT values of these sites correspond to three different levels which are approximately ADTT= 5,000, ADTT = 1,500 and ADTT ≤ 500 cases. WIM data for a full year were used from each site in the calibration procedure. Load effects were projected into the future for the different span lengths considering five-year evaluation period and seventy-five-years design life. The live load factor for ADTT=5,000, AASHTO HS20 loading case and five-year evaluation period was obtained as 1.8. In the second approach, the methodology established in the Manual for Bridge Evaluation (MBE) was used to calibrate the live load factors. It was obtained that the calculated live load factors were smaller than those in the MBE specifications, and smaller than those used in the initial calibration which did not convert to the gross vehicle weight (GVW) into truck type 3S2 defined by AASHTO equivalents.

• Smart Structures and Systems
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• v.15 no.3
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• pp.683-698
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• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.29-38
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• 2012

The data quality and measurements along consecutive detector stations can vary much even in the same traffic conditions due to variety in detector types, calibration and maintenance effort, field operation periods, minor geometric changes of roads and so on. These faulty situations often create 10% or more of inherent difference in important traffic measurements between two stations even under stable low flow condition. Low detection rates(DR) and high false alarm rates(FAR) therefore sets in among many popular Automatic Incident Detection Algorithms(AIDA). This research is two-folded and aims mainly to develop a new AIDA for uninterrupted flow. For this purpose, a technique which utilizes a Simple Arithmetic Operation(SAO) of traffic variables is introduced. This SAO technique is designed to address the inherent discrepancy of detector data observed successive stations, and to overcome the degradation of AIDA performance. It was found that this new algorithm improves DR as much as 95 percent and above. And mean time to detection(MTTD) is found to be 1 minutes or less. When it comes to FAR, this new approach compared to existing AIDAs reduces FAR up to 31.0 percent. And capability in persistency check of on-going incidents was found excellent as well.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.73-80
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• 2008

ALINEA algorithm, which is one of the best on-ramp metering algorithms, was designed to control the traffic volume from on-ramp in order to maintain the optimal occupancy rate of the detectors installed downstream of the merge area. But, the reliability of occupancy rate estimated from the loop detectors, which are used most commonly in Korea, is relatively lower than other parameters such as speed and volume. Moreover, because occupancy rate depends on the length of loop detectors and site, lots of calibration work is required whenever they are installed in order to estimate the occupancy rate. Therefore, there exists room for improvement of ALINEA algorithm because only occupancy rate having some problems is considered as a control parameter in ALINEA algorithm. Practically it is difficult to measure or perceive the occupancy rate for traffic engineers and drivers. On the other hand, speed can be good alternative which can overcome the defect induced by using occupancy. In this study, occupancy based ALINEA algorithm is converted to speed based ALINEA assuming the linear relationship between density and speed.

• Smart Structures and Systems
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• v.15 no.3
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• pp.665-682
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• 2015

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.211-221
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• 2007

A structural reliability analysis of fatigue truck model for fatigue failure of highway steel bridges was performed by applying the Miner's fatigue damage rule expressed as a function of various random variables affecting fatigue damage. Among the variables, the statistical parameters for equivalent moment, impact factor, and loadometer were obtained by analyzing recently measured domestic traffic data, whereas the parameters on fatigue strength, girder distribution factor, and headway factor of the measured data available in the literature were used. The effects of various fatigue truck models, fatigue life, ADTT, fatigue detail category, loadometer, and gross vehicle weight of fatigue truck on the reliability index of fatigue damage were analyzed. It is expected that the analytical results presented herein can be used as a basic background material in the calibration of both fatigue design truck and fatigue load factor of LRFD specification.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.731-738
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• 2006

Facing congestion, people want to know traffic information about their routes, especially real-time link travel time (LTT). In this paper, as a sequel paper of the previous non-taxi based LTT generating study by Choi et al. (1998), taxi based GPS probes have been tried to produce LTT for urban arterials. Taxis in itself are good deployment mode of GPS probes although it by nature experiences boarding and alighting time noises which should be accounted. A heuristic real-time dynamic outlier filter algorithm for taxi GPS probe has been developed focusing on urban arterials. An actual traffic survey for dynamic link travel times has been conducted using license plate method for the test arterials of Seoul city transportation network. With the algorithm, it is estimated that 70% of outliers have been filtered and the relative error has been improved by 73.7%. The filtering algorithm developed here would be expected to be in use for other spatial sites with some calibration efforts. Some limitations and future research agenda have also been discussed.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.6
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• pp.600-618
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• 2014

The metadata for urban meteorological observation is standardized through comparison with those established at the World Meteorological Organization and the Korea Meteorological Administration to understand the surrounding environment around the sites exactly and maintain the networks and sites efficiently. It categorizes into metadata for an observational network and observational sites. The latter is again divided into the metadata for station general information, local scale information, micro scale information, and visual information in order to explain urban environment in detail. The metadata also contains the static information such as urban structure, surface cover, metabolism, communication, building density, roof type, moisture/heat sources, and traffic as well as the update information on the environment change, maintenance, replacement, and/or calibration of sensors. The standardized metadata for urban meteorological observation is applied to the Weather Information Service Engine (WISE) integrated meteorological sensor network and sites installed at Incheon area. It will be very useful for site manager as well as researchers in fields of urban meteorology, radiation, surface energy balance, anthropogenic heat, turbulence, heat storage, and boundary layer processes.

• Structural Engineering and Mechanics
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• v.59 no.4
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• pp.703-718
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• 2016

Masonry arch bridges present a large segment of Iranian railway bridge stock. The ever increasing trend in traffic requires constant health monitoring of such structures to determine their load carrying capacity and life expectancy. In this respect, the performance of one of the oldest masonry arch bridges of Iranian railway network is assessed through field tests. Having a total of 11 sensors mounted on the bridge, dynamic tests are carried out on the bridge to study the response of bridge to test train, which is consist of two 6-axle locomotives and two 4-axle freight wagons. Finite element model of the bridge is developed and calibrated by comparing experimental and analytical mid-span deflection, and verified by comparing experimental and analytical natural frequencies. Analytical model is then used to assess the possibility of increasing the allowable axle load of the bridge to 25 tons. Fatigue life expectancy of the bridge is also assessed in permissible limit state. Results of F.E. model suggest an adequacy factor of 3.57 for an axle load of 25 tons. Remaining fatigue life of Veresk is also calculated and shown that a 0.2% decrease will be experienced, if the axle load is increased from 20 tons to 25 tons.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.73-83
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• 2013

Among class quantitative tests for the credit rating systems, the credit rating tests for calibration are to test the class homogeneous differences between observed and predicted probabilities. For one time period, binomial test and chi-square test are included, and normal test and extended traffic lights test are also contained for several time peroids. In this work, we consider real data in which there exists correlation among variables, so that these test methods could be applied to the credit rating systems as well as various kinds of the class data such as BWT data and FSI data.