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Thermal Decomposition of Vegetative Fuels

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Thermal Decomposition of Vegetative Fuels Thermal Decomposition of Vegetative Fuels Isaac T. Leventon Morgan C. Bruns Some of the data in this presentation has not been through the NIST review process and should be considered experimental and/or draft results. The Wildfire Problem Introduction • Background Increasing number of people moving to 1 Focus of Study areas in or near fire prone wildlands Experimental Vegetative Fuels • TGA Experiments Accurate predictive modeling of MCC Experiments wildland fires can mitigate the risk that Modeling these fires pose Simulations of Wildfire Spread • 8 Conclusions and Future Work Physics based models can better capture the controlling mechanisms of wildland fires, account for: – Variations in fuel species – Effect of fuel management (e.g., thinning) – Variable environmental conditions 2 Interflam 2019 8/23/2019 Physics-based Modeling of Wildfires Introduction • Background Comprehensive models require a large Focus of Study number of input parameters Experimental Vegetative Fuels TGA Experiments • Parameters may be obtained by MCC Experiments – Direct experiment Modeling – Simulations of Wildfire Literature search Spread – Optimization techniques Conclusions and Future Work • Thermal decomposition measurements are not readily available for a variety of common vegetative fuels10 – Fuel properties that are available from such experiments can be subject to large uncertainty10 3 Interflam 2019 8/23/2019 Existing Measurements and Models of Vegetative Fuels Introduction • 11-20 Background Previous mg-scale measurements Focus of Study – Philpot: Plant mineral content vs. pyrolysis behavior (rate, onset temperature, and residue yields) Experimental Vegetative Fuels – Shafizadeh: Composition (cellulose, hemicellulose, TGA Experiments and lignin) impact on thermal properties, MCC Experiments decomposition pathways, species yields Modeling – Sussot: Temperature range of decomposition, heat Simulations of Wildfire of pyrolysis, total energy released Spread Conclusions and Future Work • “Standard Fire Behavior Fuel Models” 6 – Heat content prescribed as 18.6 kJ g-1 for all but one (of 40 available) fuel models • “Fuel Particle Heat Content” [BTU/lb] 4 Interflam 2019 8/23/2019 Focus of Study Introduction • Background Perform thermal analysis experiments on Focus of Study a variety of common vegetative fuels Experimental – Extract thermal decomposition mechanisms + Vegetative Fuels associated kinetics and heats of combustion TGA Experiments MCC Experiments – Store results in freely available database Modeling Simulations of Wildfire Spread • Conduct CFD simulations of wildfire flame Conclusions and Future Work spread using thermal decomposition models determined from experiments • Quantify model sensitivity to measured variations in fuel decomposition behavior 5 Interflam 2019 8/23/2019 Vegetative Fuels Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work • Six species commonly found in Western United States – Bulk sample (stems + leaves) picked from a series of randomly selected plants – Obtained between May and July of 2017 6 Interflam 2019 8/23/2019 Vegetative Fuels Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work Origin Scientific Name Common Name Adenostoma Chamise Fasciculatum Pacific Southwest Arctostaphylos Glauca Bigberry Manzanita Research Station Ceanothus Greggii Desert Ceanothus (California) Ceanothus Chaparral Leucodermis Whitethorn Rocky Mountain Pinus Contorta Lodgepole Pine Research Station Pseudotsuga Menziesii Douglas-Fir (Montana) 7 Interflam 2019 8/23/2019 Thermal Analysis Experiments Introduction • Background Thermogravimetric Analysis (TGA) Focus of Study – Degradation Reaction Mechanism Experimental – Thermal Degradation Kinetics (Ai, Ei) Vegetative Fuels TGA Experiments MCC Experiments • Microscale Combustion Calorimetry (MCC) Modeling – Heats of combustion of gaseous volatiles (ΔHc) Simulations of Wildfire Spread – Char Yields (μchar) Conclusions and Future Work 8 Interflam 2019 8/23/2019 Thermogravimetric Analysis (TGA) • Furnace – Continuously purged with N₂ Sample Furnace – Well-defined temperature program Sample Carrier • Measure – Mass of sample as a function of temperature N2 Purge • Determine – Thermal degradation Water-cooled reaction mechanism Balance – Associated kinetics (Ai, E i) 9 Interflam 2019 Microscale Combustion Calorimetry (MCC) • Pyrolyzer – Continuously purged with N₂ – Well-defined temperature program – Gaseous pyrolyzates flows to Combustor combustion chamber • Combustor Pyrolyzer – Gases react with excess O₂ – HRR measured by oxygen consumption calorimetry • Determine – Heats of Combustion of Gaseous pyrolyzates (ΔHc ) 10 10 Interflam 2019 Milligram-Scale Experiments Introduction • Background Vegetative Fuel Samples Focus of Study – Stored in desiccator, minimum of 48 h – Whole leaf / stem samples < 0.75 mm thick Experimental Vegetative Fuels TGA Experiments • Test Conditions MCC Experiments – Sample mass: 4.5 to 6.5 mg Modeling – Initial isotherm: 20 minutes at 75 °C Simulations of Wildfire – Heating Rate: 10 K min-1 Spread – Max Temp: 700 °C – Conclusions and Future Work Environment: Pure N2 – Crucible Type: Alumina – Replicate tests: TGA (5x), MCC (3x) • Calibration – Temperature (156.6 to 961.8 °C): Within 3 months – TGA baseline, MCC O2 sensor: Daily 11 Interflam 2019 8/23/2019 TGA Experiments Introduction • Background Chamise Stem Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work • Big Berry Leaf 12 Interflam 2019 8/23/2019 TGA Experiments Stems Leaves – Higher peak mass loss rate, – Decomposition occurs over little mass loss above 400 °C a wider temperature range – Typically two distinct mass – Multiple, overlapping loss peaks reactions 13 Interflam 2019 8/23/2019 Thermal Decomposition Mechanisms Introduction • 12,14 Background Assumed degradation mechanism Focus of Study – Parallel, first order, Arrhenius rate reactions d푚 퐸 Experimental = − σ 1 − 휈 푚 퐴 exp 푖 Vegetative Fuels d푡 푖 푖 푖 푖 푅푇 TGA Experiments – 푚 Total sample mass MCC Experiments – 푚푖 Mass of component 푖 Modeling – 푇 Sample temperature Simulations of Wildfire – 푅 Universal gas constant Spread – 퐴푖, 퐸푖 Kinetic parameters describing the reaction Conclusions and Future Work – 훥푚푖 Mass lost as volatiles in reaction step i – 휇푐ℎ푎푟 Char yield 휇푐ℎ푎푟 = 1 − σ푖 훥푚푖 • Kinetic parameters (퐴푖, 퐸푖) and mass loss in each reaction step (훥푚푖) determined using the algorithm developed in previous presentation 26 14 Interflam 2019 8/23/2019 Experimentally-Measured and Model-Predicted TGA Data Introduction • Background Lodgepole Pine Stem Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work • Big Berry Leaf 15 Interflam 2019 8/23/2019 Experimentally-Measured and Model-Predicted TGA Data Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 16 Interflam 2019 8/23/2019 Experimentally-Measured and Model-Predicted TGA Data Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 17 Interflam 2019 8/23/2019 Kinetic Parameters Describing Decomposition of Vegetative Fuels Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 18 Interflam 2019 8/23/2019 MCC Experiments Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 19 Interflam 2019 8/23/2019 MCC Experiments Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 20 Interflam 2019 8/23/2019 MCC Experiments Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 21 Interflam 2019 8/23/2019 MCC Experiments Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 22 Interflam 2019 8/23/2019 Heats of Combustion Introduction Background Douglas-Fir Leaf Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work • Simple analysis of MCC Data: – Heat of complete combustion, ΔHc,total • Reaction-step specific heats of combustion, ΔHc,i – Consider relative peaks of measured HRR/mvol and dm/dt – Use these peak values (measured) + relative fraction of volatiles released by each reaction step at peak (model) 푁푟푥푛푠 푑푚푖 σ푖=1 Δ퐻푐,푖 × ฬ 퐻푅푅/푚푣표푙 푒푥푝 푑푡 푝푒푎푘 푗 = 푑푚 ተ 푁푟푥푛푠 푑푚푖 푑푡 σ푖=1 ฬ 푒푥푝 푑푡 푝푒푎푘 푗 푝푒푎푘 푗 23 Interflam 2019 8/23/2019 Experimentally-Measured and Model-Predicted MCC Data Introduction Background Focus of Study Experimental Vegetative Fuels TGA Experiments MCC Experiments Modeling Simulations of Wildfire Spread Conclusions and Future Work 24 Interflam 2019 8/23/2019 Experimentally-Measured and Model-Predicted MCC
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