Imperial College London

MrFranzRichter

Faculty of EngineeringDepartment of Mechanical Engineering

Research Assistant
 
 
 
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franz.richter11

 
 
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609City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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4 results found

Yuan H, Restuccia F, Richter F, Rein Get al., 2019, A computational model to simulate self-heating ignition across scales, configurations, and coal origins, Fuel, Vol: 236, Pages: 1100-1109, ISSN: 0016-2361

Self-heating of fuel layers can trigger ignition when the temperature of the surroundings is sufficiently high. Self-heating ignition has been a hazard and safety concern in raw materials production, transportation, and storage facilities for centuries. Hot plate and oven-basket experiments are the two most used lab-scale experiments to assess the hazard of self-heating ignition. While extensive experiments have been done to study this phenomenon, modelling of the experiments is substantially lagging behind. A computational model that can accurately simulate self-heating ignition under the two experimental configurations has not been developed yet. In this study, we build such a model by coupling heat transfer, mass transfer, and chemistry using the open-source code Gpyro. Due to the accessibility of large amount of experimental data, coal is chosen as the material for model validation. A literature review of the kinetic parameters for coal samples from different origins reveals that there is a compensation effect between the activation energy and exponential factor. Combining the compensation effect with our model, we simulate 6 different experimental studies covering the two experimental configurations, a wide range of sample sizes (heights ranging from 5 mm to 126 mm), and various coal origins (6 countries). The model accurately predicts critical ignition temperature (Tig) for all 24 experiments with an error below 7 °C. This computational model unifies for the first time the two most used self-heating ignition experiments and provides theoretical insights to understand self-ignition for different fuels under different conditions.

Journal article

Richter F, Atreya A, Kotsovinos P, Rein Get al., 2019, The effect of chemical composition on the charring of wood across scales, Proceedings of the Combustion Institute, Vol: 37, Pages: 4053-4061, ISSN: 1540-7489

Structural softwood (timber) recently gained attention by architects and engineers as a construction material for high-rise buildings. Regulations restrict the height of these buildings due to safety concerns as their fire behaviour is poorly understood. The fire behaviour and loss of loadbearing capacity of timber is controlled by charring, whose chemical kinetics has rarely been studied. Current models of charring assume, without proof, the same reaction scheme and kinetic parameters apply to all wood species, which potentially introduces a large uncertainty. Here, the hypothesis is tested that the kinetics of different wood species insignificantly affects their charring behaviour. The kinetics is modelled by a microscale kinetic model—including pyrolysis and char oxidation reactions—which assumes that the three main components (cellulose, hemicellulose, and lignin) of wood degrade independently. Variation in the kinetics between different wood species is captured by their different chemical compositions within a wood group (softwood or hardwood). Hardwood is included for comparison. A database of over 600 compositions was compiled from literature, and studied across scales using a microscale (mg-samples) and mesoscale (kg-samples) model. All reactions, kinetic parameters, and physical properties were selected from literature. Both models were validated using blind predictions of high-fidelity experiments from literature. Variation in kinetics were found to have a small effect on the predicted mass loss rate at both scales (±1 g/m2-s) and a negligible effect on the predicted temperatures (±16 K) across different depths, heat fluxes, and oxygen concentrations at the mesoscale. These results prove, for the first time, that the variation in kinetics is negligible for predicting charring across scales. A kinetic model of charring derived for one wood species should be valid for all wood species within softwood or hardwood. Modellers should, t

Journal article

richter F, Rein G, 2017, Pyrolysis kinetics and multi-objective inverse modelling of cellulose at the microscale, Fire Safety Journal, Vol: 91, Pages: 191-199, ISSN: 1873-7226

The chemistry of pyrolysis, together with heat transfer, drives ignition and flame spread of biomass materials under many fire conditions, but it is poorly understood. Cellulose is the main component of biomass and is often taken as its surrogate. Its chemistry of pyrolysisis simpler and dominates the pyrolysis of biomass. Many reaction schemes with corresponding kinetic parameters can be found in the literature for the pyrolysis of cellulose, but their appropriatenessfor fire is unknown. This study investigated inverse modelling andthe blind prediction of six reaction schemes of different complexitiesfor isothermal and non-isothermal thermogravimetric experiments. We used multi-objective optimisation to simultaneously and separatelyinverse model the kinetic parameters of each reaction schemeto several experiments. Afterwards we tested these parameters with blind predictions. For the first time, we reveal a set of equally good solutions for the modelling of pyrolysis chemistry of different experiments. This set of solutions is called a Pareto front, and represents a trade-off between predictions of different experiments. It stems from the uncertainty in the experiments and in the modelling. Parameters derived from non-isothermal experiments compared well with the literature, and performed well in blind predictions of both isothermal and non-isothermal experiments. Complexity beyond the Broido-Shafizadeh scheme with seven parameters proved to beunnecessary to predict the mass loss of cellulose; hence, simplereaction schemes are most appropriate for macroscale fire models.Our results show that modellers should use simple reaction schemes to model pyrolysis in macroscale fire models.

Journal article

vermesi I, Didomizio M, richter F, Weckman E, Rein Get al., 2017, Pyrolysis and spontaneous ignition of wood under transientirradiation: experiments and a-priori predictions, Fire Safety Journal, Vol: 91, Pages: 218-225, ISSN: 1873-7226

Wood is a material widely used in the built environment, but its flammability and response to fire are adisadvantage. Therefore, it is essential to have substantial knowledge of the behavior of wood undergoingexternal heating such as in a fire. The majority of studies in the literature use constant irradiation. Althoughthis assumption simplifies both modelling and experimental endeavors, it is important to assess the behaviorof materials under more comprehensive heating scenarios which might challenge the validity of solid-phaseignition criteria developed previously. These criteria are evaluated here for the spontaneous ignition undertransient irradiation by combining experimental measurements and a-priori predictions from a model of heattransfer and pyrolysis. We have applied a two-step transient irradiation in the cone calorimeter in the formof a growth curve followed by a threshold of constant irradiation. We used white spruce samples of size 100x 100 mm thickness of 38 mm measured the temperature at different depths and the mass loss. A one di-mensional model written in the open source code Gpyro is used to predict the pyrolysis behavior. The modelhas a chemical scheme in which the virgin components of wood (hemicellulose, cellulose, lignin) becomeactive, then decompose in two competing reactions: char and gas, and tar. The kinetic parameters, as wellas the thermal properties of the wood and char are taken from the literature, whileρand moisture contentare measured experimentally. A priori predictions of the temperature, made prior to the experiments, showexcellent agreement with the measurements, being within the experimental uncertainty range. The mass lossrate (MLR) predictions are qualitatively similar to the measurements, but there is a large uncertainty in themeasurements. For a-posteriori simulations, certain parameters are changed after having access to the mea-surements to improve the simulations. We found that the heat of reaction

Journal article

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