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Development of computational fatigue model for benchmarking of existing weld quality systems
KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.).
KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.).
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Many industries are currently making the transition to high strength steel due to advantages relatedto the high strength to weight ratio of high strength steel. The fatigue properties in high strength steelshow a large dependency of the weld quality in structural applications. Recent studies show a weakrelation between quality classifications and fatigue properties in the current international standard forweld quality assurance, ISO 5817. The objective of this project is to develop and assess a method forpredicting fatigue life in welded joints based on measured weld geometry and applied load.Two different materials (S355 and S960) and two different material thicknesses (2mm and 8mm) wereused in this study. Experiments on cruciform joints were conducted to evaluate the fatigueperformance for different types of weld geometries. A computational model based on FEM and linearelastic fracture mechanics was developed and adapted to fit the experimental results usingoptimization and surrogate models.A comparison between the fatigue behavior according to the standards and the fatigue behavior givenby the computational model was thereafter made. The conclusions that can be made are that thegeneral fatigue behavior differs for the different materials for the same variation in geometry, thefatigue performance depends on a combination of geometrical parameters, the developed computationalmodel cannot be used for the 2mm specimens in this particular case, the use of FAT-curves accordingto the weld quality systems is insufficient to describe fatigue properties for welds in thin high strengthsteel, and different geometries within different weld quality classes can give the same fatigue behavior.

Place, publisher, year, edition, pages
2017.
National Category
Applied Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-217520OAI: oai:DiVA.org:kth-217520DiVA, id: diva2:1156678
External cooperation
Scania
Subject / course
Solid Mechanics
Supervisors
Examiners
Available from: 2017-11-14 Created: 2017-11-14 Last updated: 2017-11-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • Other locale
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