Developing A Model Approximation Method and Parameter Estimates for Solid State Reaction Kinetics

The James S. Markiewicz Solar Energy Research Facility was built to research solar chemistry and currently being used to research the change in metal oxides such as iron or magnesium oxide that act as a medium for the production of hydrogen from water. This is significant because hydrogen can be used in vehicles equipped with appropriate fuel cells and due the decreased cost of producing hydrogen with this method. The shrinking core model which governs this process has proved difficult to solve due to the high number of unknown constants and its non-linearity. We detail in this work the implementation of less common heuristics, mainly Particle Swarm Optimization. This technique was used because of its wide unbiased search for the possible constants. The development and method we are using to solve these unknown constants will be shown

Developing A Model Approximation Method and Parameter Estimates for Solid State Reaction Kinetics

The James S. Markiewicz Solar Energy Research Facility was built to research solar chemistry and currently being used to research the change in metal oxides such as iron or magnesium oxide that act as a medium for the production of hydrogen from water. This is significant because hydrogen can be used in vehicles equipped with appropriate fuel cells and due the decreased cost of producing hydrogen with this method. The shrinking core model which governs this process has proved difficult to solve due to the high number of unknown constants and its non-linearity. We detail in this work the implementation of less common heuristics, mainly Particle Swarm Optimization. This technique was used because of its wide unbiased search for the possible constants. The development and method we are using to solve these unknown constants will be shown

ES2008-54098 STUDY OF A QUENCH DEVICE FOR SYNTHESIS AND HYDROLYSIS of Zn NANOPARTICLES: MODELING AND EXPERIMENTS

ABSTRACT The synthesis and hydrolysis of zinc nanoparticles are carried out in a tubular reactor. A key component of the reactor is a coaxial jet quench device. Three co-axial and multi-inlet confined jets mix Zn(g), steam and argon to produce and hydrolyze zinc nanoparticles. The performance of the quench device is assessed with computational fluid dynamic modeling and measurements of hydrogen conversion and particle size and composition. Numerical data elucidate the impact of varying jet flow rates on temperature and velocity distributions within the reactor. Experiments produce hydrogen conversions of 61 to 79 %. Particle deposition on sections of the reactor surface above 650 K favors hydrolysis. Residence time for in-flight particles is less than one second and these particles are partially hydrolyzed

The Sensitivity of Predicted Solar Thermal Reactor Performance to Solid-state Kinetics

A solar thermal rotary kiln reactor designed to continuously decompose Co3O4 to CoO was analyzed numerically using the finite-volume technique. The reactor model calculates the reactor temperature, the extent to which Co3O4 is converted to CoO, and the efficiency with which concentrated solar energy is used to drive the reaction as a function of the feed rate of Co3O4 and the solar power. In this study, we analyzed the sensitivity of the reactor model to the solid state kinetic model selected for the decomposition reaction. Two competing solid state kinetic models from the literature were considered. The first, called the shrinking core model, was developed at Valparaiso University and the second, the Avrami-Erofeyev model, was developed at the Georgia Institute of Technology. The results show that the reactor model is extremely sensitive to the kinetic model selected. For example, at a Co3O4 feed rate of 90 g/min and a solar power level of 4000 W, the reactor model predicts that 100% of the Co3O4 is converted to CoO at an efficiency of 30.0.% when the shrinking core model is selected for the reaction kinetics and that none of the Co3O4 is converted to CoO when the Avami-Erofeyev model is selected. Given the sensitivity of the predicted reactor performance to the reaction kinetic model, future research is needed to determine why the available kinetic models are different and on developing a more robust model suitable for use in reactor modeling efforts

The Sensitivity of Predicted Solar Thermal Reactor Performance to Solid-state Kinetics

A solar thermal rotary kiln reactor designed to continuously decompose Co3O4 to CoO was analyzed numerically using the finite-volume technique. The reactor model calculates the reactor temperature, the extent to which Co3O4 is converted to CoO, and the efficiency with which concentrated solar energy is used to drive the reaction as a function of the feed rate of Co3O4 and the solar power. In this study, we analyzed the sensitivity of the reactor model to the solid state kinetic model selected for the decomposition reaction. Two competing solid state kinetic models from the literature were considered. The first, called the shrinking core model, was developed at Valparaiso University and the second, the Avrami-Erofeyev model, was developed at the Georgia Institute of Technology. The results show that the reactor model is extremely sensitive to the kinetic model selected. For example, at a Co3O4 feed rate of 90 g/min and a solar power level of 4000 W, the reactor model predicts that 100% of the Co3O4 is converted to CoO at an efficiency of 30.0.% when the shrinking core model is selected for the reaction kinetics and that none of the Co3O4 is converted to CoO when the Avami-Erofeyev model is selected. Given the sensitivity of the predicted reactor performance to the reaction kinetic model, future research is needed to determine why the available kinetic models are different and on developing a more robust model suitable for use in reactor modeling efforts

The kinetics of the heterogeneous oxidation of zinc vapor by carbon dioxide

The heterogeneous oxidation of Zn(g) is a promising reaction pathway for the conversion of CO2 into CO in the two-step Zn/ZnO solar thermochemical cycle as it eliminates the solid-state diffusion limitation that plagues the oxidation of Zn(l,s). The rate of the heterogeneous oxidation of Zn(g) is measured gravimetrically in a quartz tubular flow reactor operated at atmospheric pressure for temperatures between 800 and 1150 K, Zn(g) concentrations up to 36 mol%, and CO2 concentrations up to 45 mol%. The surface kinetics are extracted from the global reaction rate using a numerical reacting flow model that accounts for the transport of reacting species in the gas phase. The oxidation of Zn(g) by CO2 is rapid, on the order of 10−8–10−5 mol cm−2 s−1, and the rate is proportional to the product of the Zn(g) and CO2 partial pressures at the reaction surface. The activation energy for the Arrhenius reaction rate parameter is 44±3 kJ mol−1 and the pre-exponential factor is (92±6)×10−3 mol cm−2 s−1 atm−2. As a result of the rapid rate of oxidation of Zn(g), less than 1 s is required to convert more than 85% of Zn to ZnO

A parameter estimation method for stiff ordinary differential equations using particle swarm optimisation

We propose a two-step method for fitting stiff ordinary differential equation (ODE) models to experimental data. The first step avoids integrating stiff ODEs during the unbounded search for initial estimates of model parameters. To avoid integration, a polynomial approximation of experimental data is generated, differentiated and compared directly to the ODE model, obtaining crude but physically plausible estimates for model parameters. Particle swarm optimisation (PSO) is used for the parameter search to overlook combinations of model parameters leading to undefined solutions of the stiff ODE. After initial estimates are determined, the second step numerically solves the ODE. This refines model parameter values through a bounded search. We demonstrate this method by fitting the model parameters (activation energies and pre-exponential factors) of the Arrhenius-based temperature-dependent kinetic coefficients in the shrinking core solid-state chemical kinetics model for the reduction of Cobalt (II, III) Oxide (Co3 role= presentation style= display: inline; line-height: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; font-family: Helvetica Neue , Helvetica, Arial, sans-serif; position: relative; \u3e33O4 role= presentation style= display: inline; line-height: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; font-family: Helvetica Neue , Helvetica, Arial, sans-serif; position: relative; \u3e44) particles to Cobalt (II) Oxide (CoO)

Heterogeneous oxidation of zinc vapor by steam and mixtures of steam and carbon dioxide

The kinetics of the heterogeneous oxidation of zinc vapor by water vapor were measured in a tube flow reactor for temperatures from 800 to 1100 K, zinc vapor partial pressures up to 0.39 atm, and water vapor partial pressures up to 1.0 atm. The results extend the prior data for oxidation of zinc by water vapor from zinc partial pressures on the order of 0.01 atm to higher values appropriate for fuel production via the Zn/ZnO thermochemical cycle. (cont.

A parameter estimation method for stiff ordinary differential equations using particle swarm optimisation.

We propose a two-step method for fitting stiff ordinary differential equation (ODE) models to experimental data. The first step avoids integrating stiff ODEs during the unbounded search for initial estimates of model parameters. To avoid integration, a polynomial approximation of experimental data is generated, differentiated and compared directly to the ODE model, obtaining crude but physically plausible estimates for model parameters. Particle swarm optimisation (PSO) is used for the parameter search to overlook combinations of model parameters leading to undefined solutions of the stiff ODE. After initial estimates are determined, the second step numerically solves the ODE. This refines model parameter values through a bounded search. We demonstrate this method by fitting the model parameters (activation energies and pre-exponential factors) of the Arrhenius-based temperature-dependent kinetic coefficients in the shrinking core solid-state chemical kinetics model for the reduction of Cobalt (II, III) Oxide (Co3 role= presentation style= display: inline; line-height: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; font-family: Helvetica Neue , Helvetica, Arial, sans-serif; position: relative; \u3e33O4 role= presentation style= display: inline; line-height: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; font-family: Helvetica Neue , Helvetica, Arial, sans-serif; position: relative; \u3e44) particles to Cobalt (II) Oxide (CoO)

Heliostat Attitude Control Strategy in the Solar Energy Research Facility of Valparaiso University

In this paper, a continuous tracking strategy for the heliostat in the James S. Markiewicz Concentrated Solar Energy Research Facility at Valparaiso University is developed. A model of the nonlinear dynamics of the heliostat motion is developed and the open-loop control strategy is presented. Asymptotic stability of the heliostat control using the Lyapunov and LaSalle\u27s theorems were proven. Simulations using the nonlinear dynamic model are presented and interpreted to identify the feedback gain that maximizes the time response of the heliostat without introducing oscillations in its motion. Finally, the control strategy is put to the test during summer-time operation. Data are presented that show that the tracking strategy has an RMS tracking error of 0.058 mrad, where the error is defined as the difference between the desired and actual heliostat positions. Images of the the aperture of a high-temperature solar receiver over 8 hours of testing are also presented to qualitatively demonstrate the success of the tracking strategy