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Efficient and energy-aware software for stochastic analysis on large-scale systems

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  • Full or part time
    Dr Patelli
    Dr Schewe
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

PLEASE APPLY ONLINE TO THE SCHOOL OF ENGINEERING, PROVIDING THE PROJECT TITLE, NAME OF THE PRIMARY SUPERVISOR AND SELECT THE PROGRAMME CODE "EGPR" (PHD - SCHOOL OF ENGINEERING)

This is a project within the multi-disciplinary EPSRC and ESRC Centre for Doctoral Training (CDT) on Quantification and Management of Risk & Uncertainty in Complex Systems & Environments, within the Institute for Risk and Uncertainty. The studentship is granted for 4 years and includes, in the first year, a Master in Decision Making under Risk & Uncertainty. The project includes extensive collaboration with prime industry to build an optimal basis for employability.

Motivations

In the last decades, it has been widely accepted that the response of structural systems cannot be
realistically predicted by computational models that do not consider the uncertainty. Due to inherent variability of loading and structural components properties, environmental conditions, measurement and manufacturing errors, uncertainty affects the behaviour of systems as a whole. So far, only implicit methods have been applied in the engineering practice, for tackling the issues, mainly based on the use of safety factors. Solely recently, thanks to the advances in computational technology (high performance computing), methods that explicitly account for uncertainties have started to be considered increasingly attractive. The project addresses the problem of developing uncertainty based methods for the design and optimization of structural systems. Theoretical investigations are pursued to highlight advantages, similarities and drawbacks of using different mathematical approaches, adopted for the rational description of uncertainties. Uncertainty-based methods mainly aim at enhancing design procedures by combining complementary approaches in an optimization framework. In engineering applications, such methods are invoked to achieve systems’ improvements both in the direction of robustness and reliability. While robust procedures allow maintaining the stability of performances against variations, reliability procedures decrease the chances of systems’ failure against potential critical condition.

Aim and Objectives

The realistic consideration of uncertainties of various nature and scale is a key issue of this
development to ensure a faultless life of engineering structures and systems despite fluctuations and changes of structural and environmental parameters and conditions. At the same time,
consequences of unexpected events have to be minimized, and decision margins for subsequent
design revisions have to be provided. This complexity requires both probabilistic and set-theoretical
approaches to be considered. In this project efficient simulation tools able to process different representation of the uncertainty will be developed. These tools will allow to identify an optimum design for the problem under investigation that is insensitive to the systems input variations. The outcome of the project is expected to contribute significantly to developments towards sustainability in engineering design.

Requirements

The project requires a sound engineering background, good computational and programming skills, curiosity, creativity and a strong interest to work in a multidisciplinary set-up.

Funding Notes

The PhD Studentship (Tuition fees + stipend of £ 13,726 annually over 4 years) is available for Home/EU students. In addition, a budget for use in own responsibility will be provided.

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