Gasification reactivity of charcoal with CO2. Part I: Conversion and structural phenomena

The gasification reaction of fir charcoal with CO₂ was studied by isothermal thermogravimetric analysis under kinetic control. The derived reaction rate (r=dX/dt) as a function of the converted carbon mass (X) was compared with random pore model predictions and found to be much higher at elevated conversion levels than predicted by theory. Similar enhanced reaction rate behaviour was evidenced after removing the natural alkali catalyst from the charcoal by acid washing, suggesting that with untreated charcoal the late reaction rate contribution stems from both, catalytic and additional structure effects. Literature attributes the unpredicted late reaction rate behaviour to the disintegration of the porous char particle into small fragments, which, in line with percolation theory predictions, seems to occur only after a critical conversion level has been reached. However, our gasification data reveal a gradual rise in the charcoal reactivity thereafter, suggesting a breaking up (embrittlement) of the solid phase accompanied by the exposure of fresh surface area from fracturing. The original random pore model derivation given by Bhatia and Perlmutter is extended to account also for these peculiarities and the resulting kinetic relation described our reaction rate data well over the entire conversion range.     

Two-manifold cell-decomposition of r-sets.

This paper discusses the relationships studied between manifold solids and r-sets by defining an r-set as a decomposition in two-manifold cells. This decomposition is represented as a graph (Two-manifold Cell Decomposition graph TCD) in which each node corresponds to a 2 manifold component of the regular set, while each arc or hyperarc defines a non-manifold adjacency between components. The TCD model and data structure encoding it were designed in order to be compatible with a traditional boundary architecture.     

Coupled Physical and Numerical Simulation to Optimize Thermo‐mechanical Metal Forming Processes

The numeric simulation of thermo‐mechanical hot forming processes and the modelling of the structure development and the mechanical properties of complex metallic materials serve for both the optimization of forming processes and the increase of process reliability. To meet close process windows, predictions of the formability of the material as function of the process conditions and material history are required as well. Lifetime evaluation of the tools is made possible from coupled computation of workpiece and tool loads. Material and damage models in use must be adapted on the basis of laboratory experiments and advanced analysis methods.     

Controlled experiments to study corrosion effects due to external varying fields in embedded pipelines

We present controlled laboratory tests carried out to study corrosion effects due to induction currents on pipes embedded in environments with electrical resistance lateral discontinuities. Sacrificial anodes were connected to underground pipes, and corrosion rates were estimated by measuring the mass loss in each anode. We considered 1 Hz and 50 Hz inducting fields, and the effects produced on the pipes were compared with cases without an external field. The results indicated an increase in the corrosion rate when the pipe was under the effect of induction currents, particularly where there was a change of electrical resistance in the soil.     

Effects of blending on surface characteristics of copper corrosion products in drinking water distribution systems

Copper scales formed over 6-months during exposure to ground, surface and saline waters were characterized by EDS, XRD and XPS. Scale color and hardness were light red-brown-black/hard for high alkalinity and blue-green/soft for high SO₄ or Cl waters. Cl was present in surface or saline copper scales. The Cu/Cu₂O ratio decreased with time indicating an e transfer copper corrosion mechanism. Cu₂O, CuO, and Cu(OH)₂ dominated the top 0.5-1 A° scale indicating continuous corrosion. Cu₂O oxidation to CuO increased with alkalinity, and depended on time and pH. Total copper release was predicted using a Cu(OH)₂ model.     

The effects of water pollution on the immersion corrosion of mild and low alloy steels

The short-term immersion corrosion of mild and low alloy steels in seawaters is known to be proportional to the concentration of dissolved oxygen (DO) in the bulk water. Longer-term corrosion is a function of the activity of sulphate-reducing bacteria and is influenced by the concentration of nutrients in the bulk water. These influences are examined in more detail for the corrosion of steels in the brackish waters of the River Thames and for several immersion corrosion sites on the Eastern Australian seaboard and in the North Sea. The published data sources were supplemented with plausible assumptions about environmental conditions. New interpretations of the data are provided based on the previously published model for immersion corrosion. For waters with negligible salinity and sulphate levels early corrosion loss was shown to depend on the dissolved oxygen content of the waters, and later corrosion loss was a direct function of nitrogenous nutrient (pollution) levels. This also applies to longer-term corrosion.     

Experimental and theoretical analysis of the operation of a natural gas cogeneration system using a polymer exchange membrane fuel cell

This paper reports experimental and numerical results of an investigation of five identical cogeneration systems using PEM (Polymer Exchange Membrane) fuel cells and running on natural gas. The natural gas is reformed locally to produce hydrogen. The accuracy of numerical results is validated by comparison with experimental data and the system performances are analysed in terms of electrical, thermal and total efficiencies. It appears that the energetic performances are low, particularly at low current. Simple solutions for enhancing the system electrical performances by modifying control laws are proposed.     

Radial density distribution of fractal clusters

The radial density distributions of fractal clusters generated in both DLCA and RLCA conditions by Monte-Carlo off-lattice cluster-cluster aggregation have been investigated. It has been computed by averaging a large number of clusters of same mass to form an average cluster, which is then considered as spherically symmetric. It is found that the radial density distribution, calculated using the mass center of the cluster as the center point, does not follow the fractal scaling, as sometimes assumed in the literature. An empirical model has been proposed to describe the dependence of the radial density distribution on the number of particles in the cluster. The obtained radial density distribution is used to compute permeability profile of the fractal cluster using several literature models, which is then applied to estimate the cluster hydrodynamic radius, R_h, by considering the cluster as a porous permeable object and using the solution of Brinkman equations for the fluid flow inside the cluster. The so obtained R_h values are compared to those in the literature, computed using the Kirkwood-Riseman (KR) theory. It has been found that, among the five permeability models examined, only the model proposed by Davis (Proceedings of the Institution of Mechanical Engineers Part B 1, 185) provides results in good agreement with those obtained using the KR model. Furthermore, it has been verified that the R_h values are insensitive to the model used for the density distribution.     

Inverse Procedural Modelling of Trees

Procedural tree models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such models and their parameters is a difficult task. We propose an inverse modelling approach for stochastic trees that takes polygonal tree models as input and estimates the parameters of a procedural model so that it produces trees similar to the input. Our framework is based on a novel parametric model for tree generation and uses Monte Carlo Markov Chains to find the optimal set of parameters. We demonstrate our approach on a variety of input models obtained from different sources, such as interactive modelling systems, reconstructed scans of real trees and developmental models.