Oxford University Research on Resilient and Sustainable Infrastructure (RSI)

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1 Oxford University Research on Resilient and Sustainable Infrastructure (RSI) Martin Williams Department of Engineering Science Ben Kidd Environmental Change Institute

2 Engineering research relevant to RSI Energy infrastructure (Byrne, Martin, Houlsby, Willden, Taylor) Tunnelling (Houlsby, Burd) Buried pipeline detection (Burd, Edwards, Stephens) Structural resilience dynamics and extreme loads (Williams, Blakeborough, Taylor) Water and waste treatment (Hankins, Thompson) Robust control of power grid and internet systems (Papachristodoulou) Intelligent transport (Newman, McCulloch)

3 Energy infrastructure Foundations for offshore structures deep water (oil, gas) shallow (wind) Tidal energy devices Subsea pipelines

4 Oil and gas fields in (ultra) deep water Subsea structures:

5 Limit analysis using OxLim Long skirts, d = 2m Upper bound results Contours show velocity magnitude Probes at 10º intervals

6 load reaction frame (blue) Six degree-of-freedom Loading Rig system of six LVDTs (20mm) footing system of six loading actuators Independent measurement frame (white) six dof load cell

7 Offshore pipelines Carry products at high pressure and high temperature Trench + backfill not feasible, so laid directly on seabed Lateral buckling (thermally induced) is inevitable controlled buckle formation encouraged with snake lay, sleepers, buoyancy, large cyclic lateral movements, up to 20D not uncommon pipe forms berms as it ploughs through soft soil

8 Pipeline lateral buckling V H OxLim analyses of (V, H) yield surfaces for numerous geometrical configurations and berm strength ratios Provides basis for lateral pipe-soil interaction model coded for ABAQUS Increasing berm strength

9 Pipeline lateral buckling Heating Cooling

10 Pipeline unburial research

11 Tidal Energy Research Fundamental questions on Tidal Power Generation: Will it work? How much power will it yield? How can we make optimal use of this scarce resource? How can we access lower flow speed resources? Device modelling THAWT Research activities at Oxford: Device modelling: ounderstanding the fundamental fluid mechanics of novel devices oarray interactions: device-device interference effects Basin modelling: array-basin interactional effects. Development of a specific device: the Transverse Horizontal Axis Water Turbine (THAWT) Tidal Energy Research

12 Array interactional effects Fluid mechanics of novel devices Academics: Borthwick, Houlsby & Willden Researchers: 9 DPhil s & 3 PDRA s Funding: ETI, RCUK, TSB, Oxford Martin School Research using a Hierarchy of numerical & analytical modelling techniques Analytic models: olinear Momentum oblade Element Momentum Theory Reduced order computational models: ocfd embedded actuator disk, line & BEM models Resolved CFD models: ocommercial CFD solvers (RANS) ohigh Order Spectral codes (LES) oshallow Water solvers Basin modelling Tidal Energy Research

13 Finite Element Modelling of Tunnel Installation Model of tunnel under Masonry building: Crack patterns: Damage contours:

14 Electromagnetic detection of buried pipes The Problem

15 The Solution

16 Spin-Out Detector Passive tag

17 Structural/earthquake engineering Real-time hybrid testing:

18 Distributed hybrid testing

19 Power grid in 2050 Supply will still need to meet demand Distributed, uncertain generation from renewable sources makes current approach unmanageable Users should help balance supply and demand Demand Supply Network becomes a large, multi-layered, multi-scale feedback control system Design needs to be done carefully to avoid congestion and instabilities.

20 Similarities to internet congestion control Many users, many destinations Aim to distribute available bandwidth while avoiding congestion collapse User keeps sending packets User doesn t know that there is congestion Link is over-utilized Someone needs to tell the user to slow down

21 Intelligent transport Developing vehicles that will navigate and drive themselves using only on-board sensors, no additional infrastructure This has a massive impact on transport - you don t have to drive all the time Sensors scan local environment with mm accuracy (far better than GPS)

22 Using the system for infrastructure maintenance In the future all cars will be implictily monitoring road conditions because that is how they are seeing - everywhere there is a car in use it can tell us something about the world. We don t need any new fixed infrastructure. We can detect kerb deterioration, road surface properties (paint loss) reflectivity, local relief (potholes) and all as a function of weather (find puddles, frost heave, blocked drains). We could continually image 3D structure and appearance of all signs, cats eyes, centrelines, road works. Identify flood risks, skid risks, ice risks.