Fire Simulations in Civil Engineering

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Contact: Lukas Arnold l.arnold@fz- juelich.de Nb: I had to remove slides containing input from our industrial partners. Sorry. Fire Simulations in Civil Engineering 07.05.2013 Lukas Arnold

Fire Simulations in Civil Engineering Complex buildings do not fit into rigid fire safety regulations Fire safety can be shown by adequate numerical simulations Two approaches for numerical simulations - Zone models - Field models computational fluid dynamics Figures adopted from Yeoh&Yuen (2009) Slide 2

Fire pyrolysis, combustion & radiation Fire simulations are a combination of multiple models: - Turbulent multi-species fluid dynamics - Pyrolysis - Combustion - Radiation & heat transfer - Soot creation and transport CFD regimes - Weakly compressible - High Reynolds numbers (turbulence modelling: mainly LES) Figure adopted from Yeoh&Yuen (2009) Slide 3

FDS fire dynamics simulator Developed by NIST, USA open source, freely available Fortran code with focus on engineering, not computer science Very large user community, only few developers Finite difference, second order, Cartesian grids Includes all major models, easy to use OpenMP parallelization developed and maintained by one person, who just finished his PhD and moved to industry MPI parallelization: see second bullet - No automatic domain decomposition, no load balancing - Pressure solver is problematic (kind of Schwarz method, FFT) Slide 4

Main equations Pressure decomposition Equation of motion Heat flux Energy equation Divergence equation Continuity equation Slide 5

Radiation transport & soot Radiation is crucial in fire simulations - For pyrolysis - For heat trasfer to solid walls - Cooling of hot smoke FDS uses discrete angle radiation model (order of 100 rays) Soot is a major player in radiation transport Simple soot creation (prediscribed) and transport model (additional species) implemented in FDS Slide 6 Figures adopted from Yeoh&Yuen (2009)

Members FZJ FZJ / BUW BUW Slide 7

Fire Simulations Andreas Meunders Fire Safety Engineer (M.Sc.) PhD student at BUW Kevin Drzycimski TechnomathemaWcs PhD student at FZJ Lukas Arnold Physics, ComputaWonal Science senior researcher at FZJ Close cooperation with University Wuppertal: Lectures for Engineers and Computer Simulations in Sciences Joint Master and PhD students Slide 8

Motivation: underground stations Selected fire disasters - Kings Cross, London (1987), fire under stairs in station - Deutsche Oper, Berlin (2000), the only exit blocked by burning train - Daegu, South Korea (2003), arson attack with hundreds fatalities - Berlin (2011), small fire with massive smoke emission In most cases, toxic gases are the major thread in underground fires Daegu, South Korea (2003) Slide 9

Application Scenario: Metro Stations complex and compact geometries no active smoke or fire control no combustion design fires Slide 10

Application Scenario: Metro Station Slide 11

Application scenario: fire in moving trains Evaluation of ventilation systems Creation of design fires In cooperation with Corinna Trettin (BUW) Simulations run on juropa, up to 128 cores Slide 12

New numerics for fire engineering Support for unstructured meshes (not possible with FDS) Adaptive grids for complex building structures Discontinuous Galerkin method with p-adaptivity High scalability (goal >1k MPI processes) Current work based on the deal.ii library FEM FEM inside an FEM element inside an element FEM FVM betweenfvm elements between ele Slide 13 continuous nodal continuous shape functions nodal shape inside functions an element inside an element local low/high local order low/high - non-equidistant order - non-equidistant nodes for high nodes order for(legendre high ord

ORPHEUS Main idea ORPHEUS: Optimierung der Rauchableitung und Personenführung in U-Bahn-Höfen: Experimente und Simulationen Current project proposal with 12 partners from academia and industry Main idea: optimise smoke management in underground stations Three main topics: - Capture current state (real fire experiments, CFD validation) - Smoke management systems (sensors, ventilation, CFD and small scale models) - Emergency management (communication structures, real-time smoke propagation prognosis) Slide 14

Pedestrian Dynamics Scientific Topics - elemental modelling - route finding - position tracking - laboratory experiments Projects - HERMES (BMBF) - BaSiGo (BMBF) Slide 15

Laboratory Experiments Slide 16

Experiments in Complex Geometries Slide 17

Traffic and Granular Flow (TGF) 2013 Scientific areas: Highway and urban vehicular traffic Granular flow and dynamics of granular materials (jamming, force networks, dense and intermittent flows, friction,...) Pedestrian and evacuation dynamics Collective motion in biological systems (swarm dynamics, molecular motors, social insects,...) Complex networks and their dynamics (transportation networks, Internet, epidemics, social networks,...) Intelligent traffic systems (ITS) Slide 18

Summary Fire simulations are complex (to setup and interpret) due to the combination of multiple (complex) physical and chemical processes Current software (i.e. FDS) lacks of state of the art flow solver, adaptive techniques and the (needed) HPC capabilities Slide 19