Prediction of Fischer–Tropsch Synthesis Kinetic Parameters Using Neural Networks

2014 ◽  
Vol 9 (2) ◽  
pp. 97-103 ◽  
Author(s):  
Fabiano A. N. Fernandes ◽  
Francisco E. Linhares-Junior ◽  
Samuel J. M. Cartaxo
Keyword(s):  
Neural Networks ◽  
Kinetic Parameters ◽  
Kinetic Mechanism ◽  
Product Distribution ◽  
Operating Conditions ◽  
Tropsch Synthesis ◽  
Polymerization Reaction ◽  
Fischer Tropsch ◽  
Specific Product ◽  
Fischer Tropsch Synthesis

Abstract The kinetic mechanism of the Fischer–Tropsch synthesis (FTS) is complex resembling a polymerization reaction. The kinetic rate constants for initiation, propagation and termination steps and the constants for the equilibrium reactions for methylene formation (in situ monomer) need to be estimated. A mathematical model for the FTS allows for simulating several operating conditions and determining the best operating conditions to produce a specific product distribution, so the kinetic parameters must be statistically valid. This work used neural networks (NNs) to estimate the FTS kinetic parameters, instead of using methods based on least squared error. The results show that NNs with three hidden layers were able to output good estimates of the kinetic parameters with less than 5% of deviation.

Effect of CO Conversion on the Product Distribution of a Co/Al2O3 Fischer–Tropsch Synthesis Catalyst Using a Fixed Bed Reactor

2012 ◽  
Vol 142 (11) ◽  
pp. 1382-1387 ◽  
Author(s):  
Dragomir B. Bukur ◽  
Zhendong Pan ◽  
Wenping Ma ◽  
Gary Jacobs ◽  
Burtron H. Davis
Keyword(s):  
Fixed Bed ◽  
Product Distribution ◽  
Tropsch Synthesis ◽  
Fixed Bed Reactor ◽  
Fischer Tropsch ◽  
Fischer Tropsch Synthesis ◽  
Co Conversion

Modeling the Fischer–Tropsch Product Distribution and Model Implementation

2015 ◽  
Vol 10 (3) ◽  
pp. 147-159 ◽  
Author(s):  
Magne Hillestad
Keyword(s):  
Finite Number ◽  
Product Distribution ◽  
Tropsch Synthesis ◽  
Considerable Reduction ◽  
Fischer Tropsch ◽  
Fischer Tropsch Synthesis ◽  
Component Distribution ◽  
Reduction Of Dimensionality

Abstract The main purpose of this paper is to provide a framework to model a consistent product distribution from the Fischer–Tropsch synthesis. We assume the products follow the Anderson–Schulz–Flory distribution and that there is no chain limitation. Deviation from the ASF distribution is taken into account. In order to implement such a model it is necessary to aggregate reactions into a finite number of reactions and to group components into lumps of components. Here, the component distribution within each lump is described by three parameters, and it is shown how these parameters are modeled. The method gives a considerable reduction of dimensionality and it is demonstrated that the component distribution within the lumps can be reconstructed with accuracy.

scholarly journals Dynamically Operated Fischer–Tropsch Synthesis in PtL—Part 2: Coping with Real PV Profiles

2020 ◽  
Vol 4 (2) ◽  
pp. 27 ◽  
Author(s):  
Marcel Loewert ◽  
Michael Riedinger ◽  
Peter Pfeifer
Keyword(s):  
Flow Rate ◽  
Real Data ◽  
Product Distribution ◽  
Pilot Scale ◽  
Primary Energy ◽  
Tropsch Synthesis ◽  
Photovoltaic System ◽  
Fischer Tropsch ◽  
Fischer Tropsch Synthesis ◽  
Relationship Model

Climate change calls for a paradigm shift in the primary energy generation that comes with new challenges to store and transport energy. A decentralization of energy conversion can only be implemented with novel methods in process engineering. In the second part of our work, we took a deeper look into the load flexibility of microstructured Fischer–Tropsch synthesis reactors to elucidate possible limits of dynamic operation. Real data from a 10 kW photovoltaic system is used to calculate a dynamic H2 feed flow, assuming that electrolysis is capable to react on power changes accordingly. The required CO flow for synthesis could either originate from a constantly operated biomass gasification or from a direct air capture that produces CO2; the latter is assumed to be dynamically converted into synthesis gas with additional hydrogen. Thus two cases exist, the input is constantly changing in syngas ratio or flow rate. These input data were used to perform challenging experiments with the pilot scale setup. Both cases were compared. While it appeared that a fluctuating flow rate is tolerable for constant product composition, a coupled temperature-conversion relationship model was developed. It allows keeping the conversion and product distribution constant despite highly dynamic feed flow conditions.

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