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On Uncertainty Quantification for Engineering Applications

Funder: UK Research and InnovationProject code: 2384880
Funded under: EPSRC

On Uncertainty Quantification for Engineering Applications

Description

Emergent engineering techniques, such as 3D printed steel, present potential benefits to both manufacturing and society as a whole. Such techniques represent ways to accomplish feats which are impossible using classical techniques. For example, 3D printed metals are able to create complex geometric features which are impossible to fabricate otherwise. As these technologies are new, there is limited understanding in how the resultant engineering systems behave and as such present challenges which are statistical in nature. Thus, a great deal of impact may be achieved by developing a suitable statistical methodology for these emergent techniques. In this thesis I will be using a number of carefully designed case studies to develop an appropriate uncertainty quantification (UQ) approach for a complex engineering simulation of a 3D printed bridge. The printing was conducted by welding layers of stainless steel into the desired geometry. Many factors are at play in a welding process as the metal is heated and applied to a surface. The heating and cooling of steels have a profound effect on its material properties. In addition to this, welding machines do not produce consistent, regular welds. As such, the geometry and material properties will both vary throughout a given structure. This variation can't be simply quantified as a given model and as such it is appropriate to consider these variations as stochastic processes.

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