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Minimum Design Requirements of High-Speed RailwayBridges Using Reliability-Based Design Optimization

Allahvirdizadeh, Reza (author)
KTH,Bro- och stålbyggnad
Karoumi, Raid, 1962- (author)
KTH,Bro- och stålbyggnad
Andersson, Andreas, 1980- (author)
KTH,Bro- och stålbyggnad
 (creator_code:org_t)
English.
  • Other publication (other academic/artistic)
Abstract Subject headings
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  • Constructing high-speed railway networks received a great attention during pastdecade raising new safety concerns on infrastructure (particularly bridges). It ismainly because of possible excessive vibrations due to higher operating speeds.In this regard, deficiency or vague scientific background for some of designmethodologies are shown by former studies; among which is the adopted safetyfactor for running safety. This limit state occurs if the load path from the trainto the bridge is disturbed by dislocating ballast particles because of excessivevertical accelerations of the bridge deck. Hence, the current article is devotedto update the conventional design methodology. For this objective, reliabilitybaseddesign optimization technique is employed to propose minimum allowablemass and stiffness (or maximum permissible fundamental frequency) which assuressatisfying target reliability level. This is achieved by adaptively trainingKriging meta-models to surrogate the computational models. It seems that theproposed method can result in lighter (economical) bridges in comparison tothe conventional design methodology; however, this beneficial aspect vanishesby increasing span length of the bridge.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Infrastrukturteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Infrastructure Engineering (hsv//eng)

Keyword

Reliability-Based Design Optimization
High-Speed Railway Bridges
Bridge Dynamics
Design Methodology
Meta-Modelling
Kriging
Gaussian Process Regression
Adaptive Sampling.

Publication and Content Type

vet (subject category)
ovr (subject category)

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