Fatigue design. environment neglect corrosion, wear, extreme events... approximate forces by a parametric desription or a synthetic spectrum

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1 environment neglect corrosion, wear, extreme events... approximate forces by a parametric esription or a synthetic spectrum Uncertain atigue esign material ata CA-tests external forces, time history CADrawing EM MBS local stresses an strains Well controlle Empirical moels fatigue amage Uncertain mech. structure neglect cracks, scratches, inclusions... approximate structure by the nominal rawing Uncertain GMMC(r) aims at reliability moels that take all uncertainty sources into account for safe esigns. In particular we try to quantify possible physical moel errors.

2 The roun robin project Röhake A comparison of fatigue life preiction by computations Thomas Svensson, SP Builing Technology an Mechanics, Gunnar Härkegår, NTNU Purpose: To investigate the uncertainty of fatigue life preictions ue to moel errors Project: Eight organisations performe in total eleven inepenent fatigue strength preictions of a cast component, base on a rawing an some material-, efect- an surface roughness specifications. Result: The coefficient of variation for the eleven resulting strengths was estimate at 26%

3 Organization Participants Scania, Söertälje Volvo CE Wheel Loaers, Eskilstuna, Volvo CE Articulate Haulers, Braås, Siemens, inspång, NTNU, Tronheim, Inspecta, Stockholm, Volvo Aero, Trollhättan an Atlas Copco Rock Drills, Örebro. Three of the participants performe two ifferent calculations each (the S-N approach an the a/n approach). In aition one of the participants performe an internal comparison (CoV: 18%) Project organizer: The boar of UTMIS (The Sweish atigue Network) SP Builing Technology&Mechanics

4 Problem formulation Problem formulation What is the fatigue strength of the given component at two million cycles? The strength is calculate both for the pull an the push loa cases. Metho Each participant is free to choose the metho he regars most appropriate.

5 Result The calculate fatigue strength from eleven inepenent calculations, pull (re), push (black) t = 3.4 kn = 5.8 kn s t s t = 0.9 =1.5 kn kn st t s 0.26

6 The calculation proceure, overview Stress analysis (inite Element Analysis) Meshing (convergence) Loa cases (pull, push) atigue assessment 1: Initiation of a technical crack base on S-N ata or a fatigue limit S-N Data: ata ajustment (multiaxial stress, stress graient, mean stress, size effect, surface conition) atigue limit: Determine the smallest loa cycle that initiates a technical crack in cycles (manually or by means of a postprocessor) atigue assessment 2: atigue crack analysis base on a/n ata a/n ata (ajustment for R 0) Define initial an final crack sizes Determine the smallest loa cycle that propagates a crack from a i to a f in cycles (manually or by means of a post-processor)

7 What are the main causes of the variation? st t s 0.26 atigue properties of the material Only static strength an fatigue limit properties were available from specifications. Other properties must be foun in literature. Defect contents an role Primarily the mean content is specifie, while fatigue is governe from the worst case. Choice of empirical corrections The influence of multiaxial loas, surface roughness, stress graients, mean stress or size are taken into account by nonunique empirical correction factors.

8 What can be one to iminish the variation? st t s 0.26 atigue properties of the material Only static strength an fatigue limit properties were available from specifications. Other properties must be foun in literature. Inhouse fatigue tests Defect contents an role Choice of empirical corrections Primarily the mean content is specifie, while fatigue is governe from the worst case. The influence of multiaxial loas, surface roughness, stress graients, mean stress or size are taken into account by non-unique empirical correction factors. Avance investigations Book-keeping of experience

9 What to o if we can not reuce the variation enough? st t s 0.26 The possible moel error must be taken into account when eciing safety factors. This is at present usually mae quite arbitrarily in inustry. GMMC(r) works with methos that can inclue the moel error by means of its estimate coefficient of variation in a practical reliability measure, a safety inex. This make it possible to compare ifferent sources of scatter an uncertainty in orer to allocate investigation resources in a goo an efficient way.

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