The effect of latent heat of fusion on heat transfer in fluidized-bed coating of thin plates

This paper presents a numerical study of fluidized-bed coating on thin plates using an orthogonal collocation technique. Inclusion of the latent heat of fusion term in the boundary conditions of the mathematical model accounts for the fact that some polymer powders used in coating may be partially crystalline. Predictions of coating thickness on flat plates were made with actual polymers used in fluidized-bed coating. Reasonably good agreement between numerical predictions of the coating thickness and experimental coating data of Richart was obtained for steel panels preheated to 316 degreesC. A good agreement was also obtained between numerical predictions and our coating thickness data for nylon-11 and polyethylene powders. Predicted coating thickness for polyethylene powder on flat plates were obtained with values of heat transfer coefficient closer to those obtained from our experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

Rumors and stable-cause attribution in prediction and behavior

Two stock-market simulation experiments investigated the notion that rumors that invoke stable-cause attributions spawn illusory associations and less regressive predictions and behavior. In Study 1, illusory perceptions of association and stable causation (rumors caused price changes on the day after they appeared) existed despite rigorous conditions of nonassociation (price changes were unrelated to rumors). Predictions (recent price trends will continue) and trading behavior (departures from a strong buy-low-sell-high strategy) were both anti-regressive. In Study 2, stability of attribution was manipulated via a computerized tutorial. Participants taught to view price-changes as caused by stable forces predicted less regressively and departed more from buy-low-sell-high trading patterns than those taught to perceive changes as caused by unstable forces. Results inform a social cognitive and decision theoretic understanding of rumor by integrating it with causal attribution, covariation detection, and prediction theory. (C) 2002 Elsevier Science (USA). All rights reserved.

A cognitive complexity metric applied to cognitive development

Two experiments tested predictions from a theory in which processing load depends on relational complexity (RC), the number of variables related in a single decision. Tasks from six domains (transitivity, hierarchical classification, class inclusion, cardinality, relative-clause sentence comprehension, and hypothesis testing) were administered to children aged 3-8 years. Complexity analyses indicated that the domains entailed ternary relations (three variables). Simpler binary-relation (two variables) items were included for each domain. Thus RC was manipulated with other factors tightly controlled. Results indicated that (i) ternary-relation items were more difficult than comparable binary-relation items, (ii) the RC manipulation was sensitive to age-related changes, (iii) ternary relations were processed at a median age of 5 years, (iv) cross-task correlations were positive, with all tasks loading on a single factor (RC), (v) RC factor scores accounted for 80% (88%) of age-related variance in fluid intelligence (compositionality of sets), (vi) binary- and ternary-relation items formed separate complexity classes, and (vii) the RC approach to defining cognitive complexity is applicable to different content domains. (C) 2002 Elsevier Science (USA). All rights reserved.

Genotypic variation in proanthocyanidin status in the Leucaena genus

The proanthocyanidin (PA) status of 116 accessions from the Leucaena genus representing 21 species, 6 subspecies, 3 varieties and 4 interspecific hybrids was evaluated under uniform environmental and experimental conditions at Redland Bay, Queensland, Australia in October 1997. The PA content of lyophilized youngest fully expanded leaves was measured spectrophotometrically by the butanol/HCl assay referenced to L. leucocephala ssp. glabrata standard PA and expressed as L. leucocephala ssp. glabrata PA equivalents (LLPAE). Considerable interspecific variation in PA concentration existed within the genus, ranging from 0-339 g LLPAE/kg dry matter (DM). Taxa including L. confertiflora, L. cuspidata, L. esculenta and L. greggii contained very high (> 180 g LLPAE/kg DM) PA concentrations. Similarly, many agronomically superior accessions from L. diversifolia, L. pallida and L. trichandra contained extremely high (up to 250 g LLPAE/kg DM) PA concentrations, although these taxa exhibited wide intraspecific variation in PA content offering the potential to select accessions with lower (120-160 g LLPAE/kg DM) PA content. Commercial cultivars of L. leucocephala ssp. glabrata, known to produce forage of superior quality, contained low amounts of PA (33-39 g LLPAE/kg DM). Artificial interspecific hybrids had PA contents intermediate to those of both parents, Lesser-known taxa. including L. collinsii, L. lanceolata, L. lempirana, L. macrophylla, L. magnifica, L. multicapitula, L. salvadorensis and L. trichodes, contained undetectable to low (0-36 g LLPAE/kg DM) quantities of PA and have potential as parents to breed interspecific hybrids of low PA status and superior forage quality. Extractable PA was the dominant PA component, accounting for 91% of total PA within the genus. Regression analysis of accession ranks from different experiments compared to these results indicated that genetic regulation of Leucaena spp. PA content was consistent (P < 0.01) under different edapho-climatic environments. The distribution of PA within the Leucaena genus did not concur with the predictions of various evolutionary and phylogenetic plant defence theories.

Review and future directions in the modelling and control of continuous drum granulation

Many granulation plants operate well below design capacity, suffering from high recycle rates and even periodic instabilities. This behaviour cannot be fully predicted using the present models. The main objective of the paper is to provide an overview of the current status of model development for granulation processes and suggest future directions for research and development. The end-use of the models is focused on the optimal design and control of granulation plants using the improved predictions of process dynamics. The development of novel models involving mechanistically based structural switching methods is proposed in the paper. A number of guidelines are proposed for the selection of control relevant model structures. (C) 2002 Published by Elsevier Science B.V.

Characterization of micro-mesoporous carbonaceous materials. Calculations of adsorption isotherm of hydrocarbons

In this paper we apply a method recently developed by Do and co-workers(1) for the prediction of adsorption isotherms of pure vapors on carbonaceous materials. The information required for the prediction is the pore size distribution and the BET constant, C, of a corresponding nonporous surface (graphite). The dispersive adsorption force is assumed to be the dominant force in adsorption mechanism. This applies to nonpolar and weakly polar hydrocarbons. We test this predictive model against the adsorption data of benzene, toluene, n-pentane, n-hexane, and ethanol on a commercial activated carbon. It is found that the predictions are excellent for all adsorbates tested with the exception of ethanol where the predicted values are about 10% less than the experimental data, and this is probably attributed to the electrostatic interaction between ethanol molecules and the functional groups on the carbon surfaces.

Adsorption of mixtures containing subcritical fluids on activated carbon

A theoretical analysis of adsorption of mixtures containing subcritical adsorbates into activated carbon is presented as an extension to the theory for pure component developed earlier by Do and coworkers. In this theory, adsorption of mixtures in a pore follows a two-stage process, similar to that for pure component systems. The first stage is the layering of molecules on the surface, with the behavior of the second and higher layers resembling to that of vapor-liquid equilibrium. The second stage is the pore-filling process when the remaining pore width is small enough and the pressure is high enough to promote the pore filling with liquid mixture having the same compositions as those of the outermost molecular layer just prior to pore filling. The Kelvin equation is applied for mixtures, with the vapor pressure term being replaced by the equilibrium pressure at the compositions of the outermost layer of the liquid film. Simulations are detailed to illustrate the effects of various parameters, and the theory is tested with a number of experimental data on mixture. The predictions were very satisfactory.

Analysis of adsorption data of graphitized thermal carbon black with a DFT-lattice gas theory

In this paper we analyzed the adsorption of gases and vapors on graphitised thermal carbon black by using a modified DFT-lattice theory, in which we assume that the behavior of the first layer in the adsorption film is different from those of second and higher layers. The effects of various parameters on the topology of the adsorption isotherm were first investigated, and the model was then applied in the analysis of adsorption data of numerous substances on carbon black. We have found that the first layer in the adsorption film behaves differently from the second and higher layers in such a way that the adsorbate-adsorbate interaction energy in the first layer is less than that of second and higher layers, and the same is observed for the partition function. Furthermore, the adsorbate-adsorbate and adsorbate-adsorbent interaction energies obtained from the fitting are consistently lower than the corresponding values obtained from the viscosity data and calculated from the Lorentz-Berthelot rule, respectively.

D2 dopamine receptor gene polymorphism discriminates two kinds of novelty seeking

Cloninger's psychobiological model of personality as applied to substance misuse has received mixed support. Contrary to the model, recent data suggest that a combination of high novelty seeking (NS) and high harm avoidance (HA) represents a significant risk for the development of severe substance misuse. A genetic polymorphism previously implicated in severe substance dependence, the A1 allele of the D2 dopamine receptor (DRD2) gene, was examined in relation to NS and HA amongst 203 adolescent boys. Specifically, we hypothesized that subjects with the A1 + allele (A1/A1 and A1/A2 genotypes) would report stronger NS and would exhibit a more positive relationship between NS and HA than those with the A1-allele (A2/A2 genotypes). These predictions were supported. The correlation between NS and HA in 81 A1 + allelic boys (r = 0.27, P = 0.02), and that in the 122 A1- allelic boys (r = -0.15, P = 0.09), indicated that this relationship differed according to allelic status (F = 8.52, P < 0:004). Among those with the A1-allele, the present results are consistent with the traditional view that novelty seeking provides positive reinforcement, or the fulfillment of appetitive drives. In contrast, novelty seeking in those with the A1 + allele appears to include a negative reinforcement or self-medicating function. (C) 2002 Elsevier Science Ltd. All rights reserved.

Conceptual modelling and ontology: Possibilities and pitfalls

Conceptual modelling is an activity undertaken during information systems development work to build a representation of selected semantics about some real-world domain. Ontological theories have been developed to account for the structure and behavior of the real world in general. In this paper, I discuss why ontological theories can be used to inform conceptual modelling research, practice, and pedagogy. I provide examples from my research to illustrate how a particular ontological theory has enabled me to improve my understanding of certain conceptual modelling practices and grammars. I describe, also, how some colleagues and I have used this theory to generate several counter-intuitive, sometimes surprising predictions about widely advocated conceptual modelling practices - predictions that subsequently were supported in empirical research we undertook. Finally, I discuss several possibilities and pitfalls I perceived to be associated with our using ontological theories to underpin research on conceptual modelling.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Morphological shifts in island-dwelling birds: The roles of generalist foraging and niche expansion

Passerine birds living on islands are usually larger than their mainland counterparts, in terms of both body size and bill size. One explanation for this island rule is that shifts in morphology are an adaptation to facilitate ecological niche expansion. In insular passerines, for instance, increased bill size may facilitate generalist foraging because it allows access to a broader range of feeding niches. Here we use morphologically and ecologically divergent races of white-eyes (Zosteropidae) to test three predictions of this explanation: (1) island populations show a wider feeding niche than mainland populations; (2) island-dwelling populations are made up of individual generalists; and (3) within insular populations there is a positive association between size and degree of foraging generalism. Our results provide only partial support for the traditional explanation. In agreement with the core prediction, island populations of white-eye do consistently display a wider feeding niche than comparative mainland populations. However, observations of individually marked birds reveal that island-dwelling individuals are actually more specialized than expected by chance. Additionally, neither large body size nor large bill size are associated with generalist foraging behavior per se. These latter results remained consistent whether we base our tests on natural foraging behavior or on observations at an experimental tree, and whether we use data from single or multiple cohorts. Taken together, our results suggest that generalist foraging and niche expansion are not the full explanation for morphological shifts in island-dwelling white-eyes. Hence, we review briefly five alternative explanations for morphological divergence in insular populations: environmental determination of morphology, reduced predation pressure, physiological optimization, limited dispersal, and intraspecific dominance.

Discrete element modelling of power draw of tumbling mills

The power required to operate large mills is typically 5-10 MW. Hence, optimisation of power consumption will have a significant impact on overall economic performance and environmental impact. Power draw modelling results using the discrete element code PFC3D have been compared with results derived from the widely used empirical Model of Morrell. This is achieved by calculating the power draw for a range of operating conditions for constant mill size and fill factor using two modelling approaches. fThe discrete element modelling results show that, apart from density, selection of the appropriate material damping ratio is critical for the accuracy of modelling of the mill power draw. The relative insensitivity of the power draw to the material stiffness allows selection of moderate stiffness values, which result in acceptable computation time. The results obtained confirm that modelling of the power draw for a vertical slice of the mill, of thickness 20% of the mill length, is a reliable substitute for modelling the full mill. The power draw predictions from PFC3D show good agreement with those obtained using the empirical model. Due to its inherent flexibility, power draw modelling using PFC3D appears to be a viable and attractive alternative to empirical models where necessary code and computer power are available.

Comparison of DEM and experiment for a scale model SAG mill

Predictions of flow patterns in a 600-mm scale model SAG mill made using four classes of discrete element method (DEM) models are compared to experimental photographs. The accuracy of the various models is assessed using quantitative data on shoulder, toe and vortex center positions taken from ensembles of both experimental and simulation results. These detailed comparisons reveal the strengths and weaknesses of the various models for simulating mills and allow the effect of different modelling assumptions to be quantitatively evaluated. In particular, very close agreement is demonstrated between the full 3D model (including the end wall effects) and the experiments. It is also demonstrated that the traditional two-dimensional circular particle DEM model under-predicts the shoulder, toe and vortex center positions and the power draw by around 10 degrees. The effect of particle shape and the dimensionality of the model are also assessed, with particle shape predominantly affecting the shoulder position while the dimensionality of the model affects mainly the toe position. Crown Copyright (C) 2003 Published by Elsevier Science B.V. All rights reserved.

A mechanistic model for carbon dioxide corrosion of mild steel in the presence of protective iron carbonate films - Part 3: Film growth model

A model of iron carbonate (FeCO3) film growth is proposed, which is an extension of the recent mechanistic model of carbon dioxide (CO2) corrosion by Nesic, et al. In the present model, the film growth occurs by precipitation of iron carbonate once saturation is exceeded. The kinetics of precipitation is dependent on temperature and local species concentrations that are calculated by solving the coupled species transport equations. Precipitation tends to build up a layer of FeCO3 on the surface of the steel and reduce the corrosion rate. On the other hand, the corrosion process induces voids under the precipitated film, thus increasing the porosity and leading to a higher corrosion rate. Depending on the environmental parameters such as temperature, pH, CO2 partial pressure, velocity, etc., the balance of the two processes can lead to a variety of outcomes. Very protective films and low corrosion rates are predicted at high pH, temperature, CO2 partial pressure, and Fe2+ ion concentration due to formation of dense protective films as expected. The model has been successfully calibrated against limited experimental data. Parametric testing of the model has been done to gain insight into the effect of various environmental parameters on iron carbonate film formation. The trends shown in the predictions agreed well with the general understanding of the CO2 corrosion process in the presence of iron carbonate films. The present model confirms that the concept of scaling tendency is a good tool for predicting the likelihood of protective iron carbonate film formation.