2013
DOI: 10.1080/15732479.2013.835327
|View full text |Cite
|
Sign up to set email alerts
|

Monitoring of traffic action local effects in highway bridge deck slabs and the influence of measurement duration on extreme value estimates

Abstract: In recent years, monitoring has offered a viable complement or even alternative to traditional analytical safety verification approaches. However, there still remains a lack of guidance for the use of monitored data in safety verification work. Limited resources often necessitate relatively short time frames for safety verification of problematic bridges. While the duration of monitoring is always an important consideration, it is rarely examined explicitly in terms of its influence on the predicted characteri… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
5
0
1

Year Published

2014
2014
2023
2023

Publication Types

Select...
6
1
1

Relationship

1
7

Authors

Journals

citations
Cited by 14 publications
(6 citation statements)
references
References 25 publications
0
5
0
1
Order By: Relevance
“…The design combination of both loads is computed for ultimate limit state (ULS) and serviceability limit state (SLS) respecting formulations proposed in standards [29]. Considering G to be the value of self-weight of the structure and the wind to be a leading action, design combinations E d can be written as following: (6) SLS:E d = G + (F w ) lead + (ψ 0 F t ) accomp (7) where: ψ 0 are factors for combination value of accompanying variable traffic actions, ψ 0,TS = 0.75 -for the concentrated axle load (LM1, [18]) and ψ 0,UDL = 0.4 -for the uniformly distributed load (LM1, [18]). Considering values of partial factors for the wind (γ w = 1.5) and traffic (γ w = 1.35), Equation (6) and Equation ( 7) take the following form:…”
Section: Design Load Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…The design combination of both loads is computed for ultimate limit state (ULS) and serviceability limit state (SLS) respecting formulations proposed in standards [29]. Considering G to be the value of self-weight of the structure and the wind to be a leading action, design combinations E d can be written as following: (6) SLS:E d = G + (F w ) lead + (ψ 0 F t ) accomp (7) where: ψ 0 are factors for combination value of accompanying variable traffic actions, ψ 0,TS = 0.75 -for the concentrated axle load (LM1, [18]) and ψ 0,UDL = 0.4 -for the uniformly distributed load (LM1, [18]). Considering values of partial factors for the wind (γ w = 1.5) and traffic (γ w = 1.35), Equation (6) and Equation ( 7) take the following form:…”
Section: Design Load Modelmentioning
confidence: 99%
“…Concerning bridges, EVT has been successfully used to envision the forthcoming situation of structures [7,8] based on the long-term monitoring of traffic actions. For the proper use of EVT, usually, only extreme actions (meaning the highest in absolute value) are considered.…”
Section: Introductionmentioning
confidence: 99%
“…Diese Näherungsfunktionen erlauben eine Vorhersage darüber, welche Extremwerte der Zustandsgröße zukünftig auftreten werden [7] und welche Zuverlässigkeit gegen ein Bauwerksversagen sich hieraus ergibt [8]. Wichtig ist hierbei, dass ausreichend lange Messzeiträume für eine solche Untersuchung zur Verfügung stehen müssen [9] und die Langzeitstabilität der Messanlage für den Zeitraum gewährleistet ist [10].…”
Section: Introductionunclassified
“…In development of European standards for traffic actions, such as background works on EN [5], some approaches of the extreme values theory (EVT) are used for forecasting of return levels of actions [6]. EVT has been successfully used to envision the forthcoming situation of bridges [7,8] based on the long-term monitoring of traffic actions. One of the most efficient approaches of EVT to be used in wind engineering [9] is the Peaks Over Threshold (POT) method, that has proven to work well also for precipitation predictions with non-stationary data [10] or for electricity demand estimation with a time-varying threshold [11].…”
Section: Introductionmentioning
confidence: 99%