University College London 1 Introduction Interdependency of - - PowerPoint PPT Presentation

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University College London 1 Introduction Interdependency of - - PowerPoint PPT Presentation

Jul 10, 2023 45 likes •299 views

Infrastructure interdependency at Operation level Samane Faramehr Taku Fujiyama University College London 1 Introduction Interdependency of Infrastructure Many studies on existing and obvious interdependencies (e.g. electricity power

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Infrastructure interdependency at Operation level Samane Faramehr Taku Fujiyama University College London

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Introduction Interdependency of Infrastructure

  • Many studies on existing and obvious interdependencies

(e.g. electricity power supplies to other infrastructure (rail))

  • Limited knowledge on

– How one system is affected by another through unexpected means – How users embrace challenges and change behaviours, which leads to transformation of society

  • Research needs

– Numerical tools to empower practitioners

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This presentation

  • Evaluation of dependency between urban water supply and

railway: The scenario of track flooding caused by water main burst Samane Faramehr

  • Interdependencies between power supply industry and

Railways Taku Fujiyama

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EVALUATION OF DEPENDENCY BETWEEN URBAN WATER SUPPLY AND RAILWAY: THE SCENARIO OF TRACK FLOODING CAUSED BY WATER MAIN BURST

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Background

  • Infrastructure systems and interdependency
  • Normal state of operation vs disrupted state
  • Risk management strategies
  • Scenario of track flooding (high consequence)

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Scenario and the case study

  • Past incident: Thameslink track flooding (Jan 2015)
  • Thameslink: between Farringdon and Kentish Town
  • Railway track through cuts and tunnel
  • Immature drainage asset inventory (Network Rail)
  • Railway gradient (Network Rail)
  • Adjacent trunk water mains (Thames Water GIS data)

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Methodology

  • Sub-scenario development
  • Numerical simulation
  • Hydraulic calculation
  • Input (parameters)
  • Ballast and local drainage
  • Railway flooding criteria

Railway asset and operation Water main network Quantified results Sub-scenarios / Input Boundary Sub-scenarios / Input

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Results

Rail Height= 0.159 m Flat bottom standard rail (UIC54)

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Flood caused by trunk main burst Criteria of track flooding

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Results

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  • Distance between

the burst and the lowest point

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Results

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  • Age of track ballast

(new vs fouled ballast)

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Application

Railway asset and operation Quantified results Sub-scenarios / Input Boundary Sub-scenarios / Input Water main network City level GIS Water companies Railway industry Interdependency Risk prioritisation

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Background

  • Infrastructure systems and

interdependency

  • Risk management strategies
  • Scenario of track flooding

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Scenario and the case study

  • Past incident: Thameslink track flooding (Jan 2015)
  • Thameslink: between Farringdon and Kentish Town
  • Railway track through cuts and tunnel
  • Immature drainage asset inventory (Network Rail)
  • Railway gradient (Network Rail)
  • Adjacent major water mains (Thames Water GIS data)

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Methodology

  • Sub-scenario development
  • Numerical simulation
  • Hydraulic calculation
  • Input (parameters)
  • Ballast and local drainage
  • Railway flooding criteria

Railway asset and operation Water main network Quantified results Sub-scenarios / Input Boundary Sub-scenarios / Input

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Application

Railway asset and operation Quantified results Sub-scenarios / Input Boundary Sub-scenarios / Input Water main network City level GIS Water companies Railway industry Interdependency Risk prioritisation

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Results

Rail Height= 0.159 m Flat bottom standard rail (UIC54)

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INTERDEPENDENCIES BETWEEN POWER SUPPLY INDUSTRY AND RAILWAYS

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Background

  • Coal/biomass power stations

concentrated in North Lincolnshire with Immingham being the major import port

  • Critical rail section

around Immingham

  • Quantification of risk is

required

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Critical rail infrastructure in Critical Section

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This Project

  • Develop a Data system to

capture and store of Network Rail’s Data feeds (and power station outputs)

  • Data includes
  • Origin (time, day)
  • Destination (time, day)
  • Tonnage
  • Data Analysis to understand

coal/biomass flow to power stations

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Results: Biomass flow

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500000 1000000 1500000 2000000 2500000 3000000 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 50 100 150 200 250 300 350 400 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17

Production at Drax Biomass Plants Number of Biomass trains to Drax

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Results: Coal flow

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20 40 60 80 100 120 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17

Production at Drax Coal Plants Number of Coal trains to Drax

5000000 10000000 15000000 20000000 25000000 30000000 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17

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Where does biomass to Drax come from?

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Immingham Biomass LP (DBS) 64% Liverpool Biomass TML GBF 26% Hull Biomass LP (DBS) 10%

Data: Aug 2017

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Where does coal to Drax come from?

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Data: Aug 2017

Tyne Coal Terminal GBRf 36% Immingham Humber Import Terml 34% Ferrybridge Pwr Stn GBRf 11% North Blyth GBRF 4% Hull Coal Terminal (GBRF) 3% Tunstead Sdgs 3% Greenburn GBRf 2% Hunterston H.L GBRF 2% Rylstone Tilcon (GBRf) 2% Killoch Colliery GBRf 1% Others 2%

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Conclusion

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  • UCL attempts to create numerical tools/discussions on

infrastructure interdependencies

  • Scenario development is key. Comprehensive evidence- or

data-based development of scenario development

  • Scenarios that consider (or focus on) transformation