A relaxation kinetic model for transport phenomena in a reactive flow

2006 ◽  
Vol 18 (3) ◽  
pp. 037104 ◽  
Author(s):  
Gilberto M. Kremer ◽  
Miriam Pandolfi Bianchi ◽  
Ana Jacinta Soares
Keyword(s):  
Kinetic Model ◽  
Transport Phenomena ◽  
Reactive Flow ◽  
Relaxation Kinetic

scholarly journals Relaxation of ceramic tile stresses generated by fast drying: a kinetic model

2018 ◽  
Author(s):  
J. L. Amorós ◽  
V. Cantavella ◽  
E. Blasco
Keyword(s):  
Mechanical Properties ◽  
Stress Relaxation ◽  
Kinetic Model ◽  
Moisture Content ◽  
Mechanical Strength ◽  
Ceramic Tile ◽  
Drying Process ◽  
Ceramic Tiles ◽  
Relaxation Kinetic ◽  
Dry Conditions

Abstract Unfired tile mechanical properties are very important in the ceramic tile manufacturing process. Inadequate mechanical properties lead to rejects (both in unfired and fired tiles). Unfired tile mechanical strength changes significantly after the tiles exit the industrial dryer. This behaviour can be explained by assuming that the fast-drying process generates stresses in the tile, which subsequently relax. A kinetic model has been derived, based on Maxwell’s viscoelastic elements, which explains the development of dried tile mechanical strength. This increases asymptotically when the dried tiles are stored in dry conditions. However, if tiles adsorb humidity (upon exiting the dryer), tile mechanical strength rises and then decreases. This is the result of two opposing phenomena: stress relaxation raises mechanical strength while the concurrent rise in moisture content lowers mechanical strength. The developed model successfully describes this joint mechanical behaviour. Keywords: ceramic tiles, fast drying, stress relaxation, kinetic model

Optimization of Reduced Kinetic Models for Reactive Flow Simulations

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
P. Gokulakrishnan ◽  
R. Joklik ◽  
D. Viehe ◽  
A. Trettel ◽  
E. Gonzalez-Juez ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Kinetic Model ◽  
Kinetic Models ◽  
Reaction Rate ◽  
Kinetic Mechanism ◽  
Reactive Flow ◽  
Generation Process ◽  
Flow Simulations ◽  
Target Data ◽  
Reduced Kinetic Mechanism

A robust optimization scheme, known as rkmGen, for reaction rate parameter estimation has been developed for the generation of reduced kinetics models of practical interest for reactive flow simulations. It employs a stochastic optimization algorithm known as simulated annealing (SA), and is implemented in C++ and coupled with Cantera, a chemical kinetics software package, to automate the reduced kinetic mechanism generation process. Reaction rate parameters in reduced order models can be estimated by optimizing against target data generated from a detailed model or by experiment. Target data may be of several different kinds: ignition delay time, blow-out time, laminar flame speed, species time-history profiles, and species reactivity profiles. The software allows for simultaneous optimization against multiple target data sets over a wide range of temperatures, pressures, and equivalence ratios. In this paper, a detailed description of the optimization strategy used for the reaction parameter estimation is provided. To illustrate the performance of the software for reduced kinetic mechanism development, a number of test cases for various fuels were used: one-step, three-step, and four-step global reduced kinetic models for ethylene, Jet-A and methane, respectively, and a 50 step semiglobal reduced kinetic model for methane. The 50 step semiglobal reduced kinetic model was implemented in the Star*CCM+ commercial CFD code to simulate Sandia Flame D using laminar flamelet libraries and compared with the experimental data. Simulations were also performed with the GRI3.0 mechanism for comparisons.

Optimization of Reduced Kinetic Models for Reactive Flow Simulations

2013 ◽  
Author(s):  
P. Gokulakrishnan ◽  
R. Joklik ◽  
D. Viehe ◽  
A. Trettel ◽  
E. Gonzalez-Juez ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Kinetic Model ◽  
Kinetic Models ◽  
Reaction Rate ◽  
Reactive Flow ◽  
Generation Process ◽  
Detailed Model ◽  
Flow Simulations ◽  
Wide Range ◽  
Target Data

A robust optimization scheme, known as rkmGen, for reaction rate parameter estimation has been developed for the generation of reduced kinetics models of practical interest for reactive flow simulations. It employs a stochastic optimization algorithm known as Simulated Annealing, and is implemented in C++ and coupled with Cantera, a chemical kinetics software package, to automate the reduced kinetic mechanism generation process. Reaction rate parameters in reduced order models can be estimated by optimizing against target data generated from a detailed model or by experiment. Target data may be of several different kinds: ignition delay time, blow-out time, laminar flame speed, species time-history profiles and species reactivity profiles. The software allows for simultaneous optimization against multiple target data sets over a wide range of temperatures, pressures and equivalence ratios. In this paper, a detailed description of the optimization strategy used for the reaction parameter estimation is provided. To illustrate the performance of the software for reduced kinetic development, a number of test cases for various fuels were used: one-step, three-step and four-step global reduced kinetic models for ethylene, Jet-A and methane, respectively, and a fifty-step semi-global reduced kinetic model for methane. The fifty-step semi-global reduced kinetic model was implemented in the Star*CCM+ commercial CFD code to simulate Sandia Flame D using laminar flamelet libraries and compared with the experimental data. Simulations were also performed with the GRI3.0 mechanism for comparisons.

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