Łazienkowski Bridge Fire in Warsaw – Structural Damage and Restoration Method

Zobel, Henryk; Karwowski, W.; Wróbel, Marcin; Mossakowski, P.

doi:10.1515/ace-2015-0104

Cited by 7 publications

(3 citation statements)

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“…On February 20, 2015, the city authorities decided to dismantle the damaged steel structure of the bridge and mount a new one on the surviving pillars. The team from the Warsaw University of Technology, headed by Professor Zobel, conducted a detailed post fire inspection, which included materials tests, verification of the construction geometry and Finite Element Method (FEM) strength analysis [15]. Experts found numerous additional defects, including dilatation damage, failure of the steel structure of the access walkway, damages to the road surface, protective barriers, paint coatings, and utilities.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Thermal Insulation Type and Thickness on the Structure Mechanical Response Under Fire Conditions

2019

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The concept of fire safety covers an extremely vast scope of issues. To ensure an adequate fire safety level, it is necessary to combine research and actions in several fields, such as the mathematical, physical, or numerical modelling of a fire phenomenon. Another problem is to design different types of fire protection, including alarm systems, sprinkler systems, and also roads and evacuation systems, in a manner that ensures maximum safety for the building’s users. A vital issue is the analysis of the static-strength response of the structure under fire conditions. This study, concerned with such analyses, is limited to steel truss structures. In technical approvals, manufacturers of fire-proofing materials do not account for the character of the performance of individual structural members. The components in compression need thicker insulation than those in tension. This phenomenon is related to the fact that under fire conditions, the flexural buckling coefficient in compressed members is abruptly reduced with an increase in temperature. In turn, this increase in temperature leads to a fast reduction in resistance. In addition, members in tension have much higher resistance than those in compression in the basic design situation, i.e., at the instant of t = 0 min. Consequently, even a considerable decrease in the resistance of tension members is not as dangerous as that of compression members. Therefore, due to the nature of the performance of individual elements, fire-proofing insulation of every steel structure should be computationally verified. Additionally, in this paper, the influence of the type of fire insulation on the mechanical response of the structure was investigated. Calculations were carried out for different types of sprayed-on insulation, and also for contour and box insulation panels. The graphs show the behaviour of the elastic modulus, the yield point, and the resistance of the elements in the successive minutes of the fire for the different methods of fire protection used. The best results were obtained for vermiculite and gypsum spray.

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Section: Introductionmentioning

confidence: 99%

Influence of the Thermal Insulation Type and Thickness on the Structure Mechanical Response Under Fire Conditions

2019

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“…An elongated obstacle not only prevents a free placement of targets for merging point clouds from neighbouring stations, but it also makes it necessary to move the scanner away from the object by distances larger than required for the proper field of view of the scanner. This may cause problems with the instrument range and with the accuracy of determining the position of elements over long distances [7,15,18,22].This may also limit the number and quality of data acquired in order to assess the technical condition of objects over an obstacle, such as bridges [5,23] , making the technology unusable.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Merging Point Clouds at the Maximum Range of a Scanner with Limited Possibilities of Target Placement

Lenda

Lewińska

Siwiec

2019

Archives of Civil Engineering

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The research was aimed at analysing the factors that affect the accuracy of merging point clouds when scanning over longer distances. Research takes into account the limited possibilities of target placement occurring while scanning opposite benches of quarries or open-pit mines, embankments from opposite banks of rivers etc. In all these cases, there is an obstacle/void between the scanner and measured object that prevents the optimal location of targets and enlarging scanning distances. The accuracy factors for cloud merging are: the placement of targets relative to the scanner and measured object, the target type and instrument range. Tests demonstrated that for scanning of objects with lower accuracy requirements, over long distances, it is optimal to choose flat targets for registration. For objects with higher accuracy requirements, scanned from shorter distances, it is worth selecting spherical targets. Targets and scanned object should be on the same side of the void.

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“…Two of the fast lanes of the traffic flow were damaged by the fire. Steel girders, piers, and equipment were also severely damaged in the fire [29].…”

Section: Lazienkowski Bridge Poland 2015mentioning

confidence: 99%

Prediction of Bridge Fires Characteristics Using Machine Learning

Mehrpour¹

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Bridges are an essential component of transportation systems for traffic passage across natural or man-made obstacles. Modern urban trends and growing travel patterns have resulted in a rise in the number of bridges on motorways to avoid road conflict. A major fire might cause irreversible structural deterioration or perhaps the bridge's failure. This research studies the critical factors of bridge fire incidents using a comprehensive database containing 171 bridges. Using an Artificial Neural Network (ANN) model, the vulnerability of bridges in fire is estimated, and the extent of damage is determined based on several key factors including bridge proximity to urban, suburban, or rural areas, structural system, construction materials, annual average daily traffic (AADT), ignition source, combustible types, position of the fires, and the fire-caused damage level. The influence of each parameter on the bridge fires damage levels is investigated. Suggesting measures to reduce the risk of damage, damage levels of fire incidents in different bridges for different scenarios is predicted and a comprehensive and accurate model for definition of vulnerability of bridges under fires is proposed. The outcome of this research will help predict the risk of fire in bridges with various characteristics and the level of damage.

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Łazienkowski Bridge Fire in Warsaw – Structural Damage and Restoration Method

Cited by 7 publications

References 0 publications

Influence of the Thermal Insulation Type and Thickness on the Structure Mechanical Response Under Fire Conditions

Influence of the Thermal Insulation Type and Thickness on the Structure Mechanical Response Under Fire Conditions

Accuracy of Merging Point Clouds at the Maximum Range of a Scanner with Limited Possibilities of Target Placement

Prediction of Bridge Fires Characteristics Using Machine Learning

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