This project will investigate the capabilities of adaptive structures that change their shape and geometry to accommodate operational loading and life extension to support sustainable infrastructure and circular economy.
The implementation of a circular economy poses pressing challenges. Investments and developments in ways to design infrastructure to last longer is central to this issue, as new designs must satisfy mechanical requirements by means of adaptation to changing environmental and operational loading while meeting sustainability and economic criteria. Both the EU, in its action plan for a circular economy, and the UN, put forward ambitious programs to tackle these challenges.
Current structures are designed to support strong loads that might never been experienced within their nominal life-span. This leads to over design and poor material optimisation in order to cope with the effect of environmental and operational loading. Current designs translate to an increment of the energy used in the manufacturing process, which add additional and unnecessary cost and significant negative environmental impact of the structure [1, 2].
The idea of implementing a flexible structural design capable of adapting to varying environmental conditions and loading parameters represents a revolutionary solution for optimising functionality and extending the useful life of such structures [3, 4]. The core objective of this project is to engineer a self-adapting structure that seamlessly adjusts to the prescribed loading conditions. This adaptation is achieved by integrating principles of physics and data-driven measurements to facilitate real-time feedback mechanisms. Consequently, this dynamic response leads to continuous shape and geometry modifications within the structure, ultimately enhancing its capacity to accommodate the specified loading requirements more effectively. . The alteration in geometry and shape initiates a process that effectively mitigates stress concentration and fosters an extension in the structure's lifespan . The project aims to apply these conceptual structures in the renewable energy sector as they are generally exposed to environmental and operational variabilities (e.g. offshore). The adaptive structures will benefit operability by maximising structural capacity during service.
RQ1 - What type of structure could change shape and geometry to adapt to environmental and operational variabilities?
RQ2 - Given a structure topology, what would be the key parameters to monitor as an indicator to trigger change in shape and geometry?
RQ3 - How to include stochastic modelling of the environmental and operational loadings to identify robust and reliable key parameters on the physical structure.
RQ4 - How to estimate the benefits of an adaptive structure against the current ones for maximising structural capacity during service?
RQ5 - What are some robust algorithms that can control and optimise the geometry of the structure to respond to various loads and environmental conditions?
The methodology is designed to address the research questions (RQ) framed above and it will be distributed across 3 years of research and half a year for finalising and writing-up the PhD thesis.
Year 1: M1 - Literature review and development of fundamental principles.
M1.1 Literature review on:
- Mechanics and dynamics of adaptive structures (RQ 1)
- Manufacturing process for adaptive structures (RQ 1)
- Model updating and characterization of adaptive structures (RQ 2 and 3)
- Effects of Environmental and Operational Variability (EOVs) in adaptive structures (RQ 3 and 4)
- Stochastic modelling for long-term performance evaluation (RQ 5)
M1.2 Preliminary modelling of the mechanics and dynamics of a potential adaptive structure
Year 2: M2 – Modelling, evaluation and framework development
M2.1 Evaluation of the models under different environmental and operational loadings to obtain characteristic responses of motion and therefore define the life performance of the adaptive structure.
- Deterministic: all loading and environmental conditions known (RQ 2)
- Probabilistic: loading conditions only known at a limited number of locations and stochastic environmental conditions (RQ 2 and 3)
M2.3 Establishing a framework that utilises both data and underlying physics to optimise the shape and geometry of the structure for varying loads and environmental conditions (RQ 5)
M2.2 Manufacture prototypes of adaptive structures to verify the models built in M1 and framework developed in M2.3. (RQ 1-5)
Year 3: M3 – Identifying and extracting key indicators for geometry and mechanical properties change.
M3.1 Extracting time-variant measurements from the models developed in M1, with and without the optimisation algorithms developed in M2, and the structure prototype manufactured in M2 to verify the optimisation algorithms and extract key indicators of extended structural life by means of shape and geometry change (RQ 4 and 5)
M3.2 Evaluation of the benefits of the proposed adaptive structures in the context of their environmental impact by means of life performance and operability for maximising structural capacity during service.
A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills. Project specific training will be provided on structural dynamics, stochastic modelling, finite element analysis, merging data and fundamental physics principles and structural design & manufacturing with focus on renewable energy applications.
- Structural mechanics and dynamics
- Stochastic modelling and uncertantinty quantification
- Understanding environmenal and operational variavilites and their impact in structures.
- Knowledge on structures for renewable energy
 Senatore, Gennaro, Philippe Duffour, and Pete Winslow. "Exploring the application domain of adaptive structures." Engineering Structures 167 (2018): 608-628.
 Senatore, Gennaro, and Arka P. Reksowardojo. "Force and shape control strategies for minimum energy adaptive structures." Frontiers in Built Environment 6 (2020): 105.
 Utku, Senol. Theory of adaptive structures: incorporating intelligence into engineered products. Routledge, 2018.
 Miura, Koryo, and Hiroshi Furuya. "Adaptive structure concept for future space applications." AIAA journal 26.8 (1988): 995-1002.
 Cross, Elizabeth J., and Timothy J. Rogers. "Physics-derived covariance functions for machine learning in structural dynamics." IFAC-PapersOnLine 54.7 (2021): 168-173.
 Geiger F, Gade J, von Scheven M, Bischoff M. Optimal design of adaptive structures vs. Optimal adaption of structural design. IFAC-PapersOnLine. 2020 Jan 1;53(2):8363-9.
Apply by Thu Jan 04 2024 at 12:00 via the link: Project Description | The University of Edinburgh
The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.
Tuition fees and stipend are available for Home/EU and International students - open to all UK and non-UK students globally