Characterisation of intumescent coating performance for performance-based design. Yong Zhang Prof. Yong.C. Wang
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1 Characterisation of intumescent coating performance for performance-based design Yong Zhang Prof. Yong.C. Wang 2-4-1
2 Background Standard fire test methods are used to assess intumescent coating. treated as non-reactive materials. thermal properties are considered the same during tests. Different fire exposures lead to different results. Complex chemical reactions and phase transition undergo when heated.
3 Background There is a strong demand for new, performance based assessing method. A model to predict the performance of intumescent coatings under different fire scenarios. Steel temperature-time relationship Effective thermal conductivity. New, practical test methods.
4 Modelling A modelling has been built by my predecessor. final thickness was taken as an input. limit to specific fire conditions.
5 Key Parameters Chemical factors Composition (proportions of reactants) Chemical kinetic (Activation Energy, Pre-exponent factor) Thermal factors Char structure (bubble size) Char size (final thickness) Other factors Steel thickness Heat flux etc Pressure TGA
6 Modelling Effective thermal conductivity (W/m.K) Q λ = d * T Apparent thermal conductivity (W/m.K) d= final expansion thickness Apparent thermal conductivity Steel temperature (C) d= initial thickness Effective thermal conductivity Steel temperature (C)
7 Theory and Assumptions How to predict the final expansion thickness? The key issues: Q1: How does bubble grow? Q2:When does expansion stop? Q3: How much gas contributing to bubble growth? Gas participation: mass loss + trapped gas = total decomposition Q3 Q2 Q1 Initialise Compute gas generated in each layer Calculate gas trapped among bubbles Calculate expansion growth Determine bubble burst and expansion stop N end Y t>limit? Calculate temperature field Determine material properties Calculate volume fractions of gas and polymer
8 Theory and Assumptions Main assumptions Q1: How does bubble grow? Gases trapped in bubble follow ideal gas law PV = nrt i.e. mrt Px = ws Q2:When does expansion stop? Expansion stops when bubble bursts
9 Bubble Theory Consider an individual bubble The forces across the bubble have to be balanced according to the Young-Laplace equation: P = 2σ 4η + R R R Where p is pressure difference, η -viscosity, σ-surface tension, R-bubble size and dr/dt -expand rate. Bubble bursts (so no further expansion) when P > 2σ 4η R + R R From bitsandpieces.us
10 Bubble theory Combining the ideal gas law equation, after some mathematical work expansion force 2rk wps * m dm dt Surface tension resistance = R + R R 8πσ 16πη Viscosity resistance The expansion is mainly due to gas release from chemical reactions and temperature increase The resistances (viscosity &surface tension) are mainly a function of temperature.
11 Bubble theory Barrier force Bubble growth Bubble burst The extract barrier force curve is unknown, we only know the trend It should be safe to say that bubble bursts when the driving force reaches maximum
12 Bubble Theory Answer to Q1&Q2: Bubble grows following the ideal gas law and stops growing when reaching maximum m dm dt Q3: How much gases are trapped? m(dm/dt) m(dm/dt)
13 Results from the past Furnace tests Three fire profiles Structural samples Iso Fire Slow Fire Fasf Fire t (s)
14 Gas trapped ratio (beta) So far, no suitable experimental solution is found beta. beta.6 β=(423/t) n temp /k Different beta curves used for the modelling temp /k Beta relationship: β = T T x 1+. β gas trapped ratio T temperature T temperature start to release gas x initial coating thickness
15 Standard Fire Beam Web ST 2 initial thickness mm -17% Beam Web ST 4 initial thickness mm 2% Experiment Modelling Time Experiment Modelling Time 2 1 Modelling Beam Web ST 1 initial thickness 1.7 mm Time -1% Experiment Column Web ST initial thickness.964 mm Time 2.7% Experiment Modelling
16 Slow Fire Slow Fire 24 web initial thickness.61 mm Web Modelling -1% Time Slow Fire 23 Web initial thickness.834 mm Web Modelling -2% Time Slow fire 24 Flange initial thickness.61 mm 6% Slow Fire 23 Flange initial thickness.834 mm 11% flange Experiment Flange Modelling Time Time
17 Fast Fire 8 Fast Fire 24 Flange initial.69 mm 2% 8 Fast Fire 24 Web initial thicknes.69 mm 1% Flange Modelling Experimental Modelling Time Time 8 Fast fire 23 flange initial thickness.839 mm 14% 3 8 Fast fire 23 web initial thickness.839 mm 12% Flange Modelling Web Modelling Time Time
18 Experiments and results A cone calorimeter is employed for modelling development and improvement. versatile, small scales, quick experiments and cost-effective. provide feedbacks and inputs for the modelling. can also be used for modelling validation. A furnace is also built to validate the model using structural samples. paint steel wool scale cone Camera PC
19 Experiment and results
20 Experiments and results Weight k=1 k=2 k=3 k=4 Weight 8 6 k=1 Modelling Time Component 1* Component 2 Component 3 Fraction (%) E (kj/mol) A (s -1 ) 3 1.8e6 Component 1 Acid source Component 2 Blow agent Component 3 Charring agent
21 Samples Sample ID Steel thickness mm Initial thickness mm Heat Flux kw/m 2 SA1LP.3 SA2LP.37 SB1LP 1.79 SB2LP 1.73 SC1LP 2.4 SC2LP 2.6 SA36LP.68 6 SA46LP.7 SC16LP 2. 6 SC26LP 2.62 SC36LP SC46LP
22 Results 6 sa1lp initial thickness.3 mm 3 kw/m 2 / o C modelling measured measured modelling /mm time /s temp / o C sb1lp initial thickness.8 mm measured modelling modelling measured thickness /mm / o C sc1lp initial thickness. mm modelling measured modelling measured /mm time /t time /t
23 Results sc16lp initial thickness kw/m modelling measured measured modelling sa36lp initial thickness.7mm time sc36lp intial thickness 1.2 mm 4 / o C time /s modelling measured measured modelling /mm time modelling measured measured modelling 3 2 1
24 Results Sample ID Steel thickness Initial thickness Final thickness E R. Modelling E.R. Diff. SA1LP % SA2LP SB1LP % SB2LP SC1LP % SC2LP SA36LP % SA46LP SC16LP % SC26LP SC36LP % SC46LP
25 Summary New assessing method based on this model Inputs for the model TGA tests (Reactant fractions, chemical kinetic, T ) Mean bubble size Cone Tests for a beta relationship the model can be used to predict Steel-temperature relationship Effective thermal conductivity
26 Future works More cone and furnace tests to validate and improve the model. Different affecting parameters More products from the market Leigths Paint Nullifire Fire
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