Analyzing Uncertainty in Civil Engineering by Wolfgang Fellin (auth.), a.o. Univ.-Prof. Dipl.-Ing. Dr.

By Wolfgang Fellin (auth.), a.o. Univ.-Prof. Dipl.-Ing. Dr. Wolfgang Fellin, em. Univ.-Prof. Dipl.-Ing. Heimo Lessmann, a.o. Univ.-Prof. Dr. Michael Oberguggenberger, Dipl.-Ing. Robert Vieider (eds.)

This quantity addresses the problem of uncertainty in civil engineering from layout to building. disasters do ensue in perform. Attributing them to a residual method probability or a defective execution of the undertaking doesn't appropriately disguise the variety of explanations. a better scrutiny of the followed layout, the engineering version, the information, the soil-construction-interaction and the version assumptions is needed. frequently, the uncertainties in preliminary and boundary stipulations are considerable. present engineering perform frequently leaves those concerns apart, although new medical instruments were built some time past a long time that permit a rational description of uncertainties of all types, from version uncertainty to facts uncertainty. it's the objective of this quantity to have a severe examine present engineering hazard suggestions as a way to elevate know-how of uncertainty in numerical computations, shortcomings of a strictly probabilistic security proposal, geotechnical versions of failure mechanisms and their implications for development administration, execution, and the juristic query of accountability. furthermore, some of the new techniques for modelling uncertainty are defined. The e-book is as a result of the a collaborate attempt of mathematicians, engineers and development managers who met on a regular basis in a publish graduate seminar on the college of Innsbruck in the past years.

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The relative tan ϕ , lognormal distribution (ν =0) tan ϕ normally distributed 0 16000 16000 N=100000 9600 6400 3200 0 9600 6400 3200 0 200 400 Z = R − S [kN] 0 600 tan ϕ , lognormal distribution (ν >0) 200 400 Z = R − S [kN] 600 16000 N=100000 N=100000 12800 Frequenzy 12800 Frequenzy 0 tan ϕ , triangular distribution 0 16000 9600 6400 3200 0 N=100000 12800 Frequenzy Frequenzy 12800 9600 6400 3200 0 200 400 Z = R − S [kN] 600 0 0 200 400 Z = R − S [kN] 600 Fig. 6. Simulations with various distributions for tan ϕ frequency provides an estimate for the failure probability pf ≈ Hf /N .

8 Fig. 8. 38 difference. Using the Euclidean metric the minimal distance can be found perpendicular to the curve defined by the limit state g = 0, which is lower than the distance obtained by η, see Fig. 8. g. if we plot g in a c–ϕ coordinate system, instead of a c–tan ϕ system. All these underlying conventions make the distance interpretation ambiguous. One has to keep in mind that any safety definition is kind of arbitrary. Therefore values higher than one are no absolute measure of a distance to failure.

The relative tan ϕ , lognormal distribution (ν =0) tan ϕ normally distributed 0 16000 16000 N=100000 9600 6400 3200 0 9600 6400 3200 0 200 400 Z = R − S [kN] 0 600 tan ϕ , lognormal distribution (ν >0) 200 400 Z = R − S [kN] 600 16000 N=100000 N=100000 12800 Frequenzy 12800 Frequenzy 0 tan ϕ , triangular distribution 0 16000 9600 6400 3200 0 N=100000 12800 Frequenzy Frequenzy 12800 9600 6400 3200 0 200 400 Z = R − S [kN] 600 0 0 200 400 Z = R − S [kN] 600 Fig. 6. Simulations with various distributions for tan ϕ frequency provides an estimate for the failure probability pf ≈ Hf /N .

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