About the Project
The ubiquity of uncertainty in computational estimates concerning real-world engineering problems has long been recognized as a topic of considerable importance, gathering the interest from a constantly increasing number of researchers from a vast array of diverse fields worldwide.
Specifically, in the field of structural engineering the predominant approach for determining, with any preselected level of accuracy, the response/reliability statistics and system fragilities is the Monte Carlo simulation (MCS) method. In this setting, MCS-based approaches have found a widespread application for capturing the inherent stochastic nature of natural hazards (e.g. earthquakes, winds, waves etc) and analyzing structures and systems considering complex nonlinear material behavior. It is worth-mentioning that most contemporary aseismic codes incorporate a stochastic/probabilistic framework for the design of structured facilities, rendering the element of the efficient uncertainty treatment prevalent. MCS-based approaches constitute phenomenologically a rational basis for uncertainty quantification, however, these are accompanied by a considerable computational cost that can reach even to prohibitive levels especially for cases of large scale complex systems.
Over the past five decades considerable effort has been devoted in random vibration analysis of dynamic systems of engineering interest. Clearly, persistent nonlinear stochastic structural dynamics problems faced by engineers in their daily practice are amenable to efficient and comprehensive solutions, harnessing the potential of advances in inelastic random vibration theory.
The envisaged developments of the proposed project are oriented towards determining efficient pathways to capture uncertainty and imprecision in computational engineering estimates in a realistic form reflecting the nature of the available information as typically appears in practice.
From a theoretical viewpoint, the proposed project lies in the intersection of structural dynamics, applied mathematics, probability and statistics. On the practical side, the envisioned methods will be liberated by the constraints of traditional approaches, inducing a paradigm shift in the way modern engineering systems and structures are analysed and designed under the presence of uncertainties.
This opportunity is open to all applicants, with a number of awards for Non-UK nationals limited by UKRI to 1. All candidates will be placed into the EPSRC Doctoral Training Partnership Studentship and selection is based on academic merit.
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