Application of genetic algorithms and thermogravimetry to determine the kinetics of polyurethane foam in smoldering combustion

By Guillermo Rein, C. Lautenberger, A. Fernández-Pello, José L. Torero, D. Urban. 2006

277 citations recorded by the source corpus.

Subfields: Environmental Engineering, Polymers and Plastics, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/7c12f40b11a71cb29139d9d8b1c0710471dd2044

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. C. Fernandez-Pello
2. Guillermo Rein
3. C. Lautenberger
4. T. Hull
5. S. Mckenna

In Polymers and Plastics

1. Guillermo Rein
2. C. Fernandez-Pello
3. C. Lautenberger
4. N. Bal
5. K. Li
6. Jie Ji
7. Xinyan Huang
8. C. Fleischmann

In Safety, Risk, Reliability and Quality

1. Guillermo Rein
2. C. Fernandez-Pello
3. C. Lautenberger
4. N. Bal
5. K. Li
6. Jie Ji
7. Xinyan Huang
8. C. Fleischmann

Citations in the corpus

• Hybrid genetic algorithm to find the best model and the globally optimized overall kinetics parameters for thermal decomposition of plastics (2008, background): “The structure of a hybrid genetic algorithm [22–31]”
• On the effect of inverse modelling and compensation effects in computational pyrolysis for fire scenarios (2015, background): “Genetic Algorithm (GA) [10,14] or Shuffled Complex Evolution (SCE) [11]).”
• Pyrolysis of Medium-Density Fiberboard: Optimized Search for Kinetics Scheme and Parameters via a Genetic Algorithm Driven by Kissinger’s Method (2014, methodology): “Since the late 1990s, with the increase of computational capability new optimization techniques including the genetic algorithms (GA) [7,12,21-23], PEAKFIT [24,25] and least-squares method [4,26] have been adopted for the estimation of kinetic parameters.”
• The fire toxicity of polyurethane foams (2016, result): “The results of these experiments and the mechanism of decomposition derived correlated well with work by Rein et al. (2006) and also Garrido and Font (2015).”
• Generalized pyrolysis model for combustible solids (2007, methodology): “Since the simulations presented here require specification of several model input parameters that cannot be directly measured in the laboratory, genetic algorithm optimization [15, 16] is used to estimate the required model parameters from flammability test data and thermogravimetric analysis.”
• The application of a genetic algorithm to estimate material properties for fire modeling from bench-scale fire test data (2006, methodology): “The authors have used a GA to extract detailed decomposition kinetics of polyurethane foam from thermogravimetric experiments [16].”
• Smouldering Combustion Phenomena in Science and Technology (2009, methodology): “This reaction overlaps with the pyrolysis depending on the propagation mode and oxygen availability [20].”