Computational modelling of reduction and smelting processes in the primary metals industries

Abstract not available

3D modelling of mango fruit skin blush in the tree canopy

The fruit of certain mango cultivars (e.g., 'Honey Gold') can develop blush on their skin. Skin blush due to red pigmentation is from the accumulation of anthocyanins. Anthocyanin biosynthesis is related to environmental determinants, including light received by the fruit. It has been observed that mango skin blush varies with position in the tree canopy. However, little investigation into this spatial relationship has been conducted. The objective of this preliminary study was to describe a 'Honey Gold' mango tree by capturing its three-dimensional (3D) architecture. A light path tracing model QuasiMC was then used to predict light received by fruit. The use of this 3D model was to better understand the relationship between mango fruit skin blush and fruit position in the canopy. The digitised mango tree mimicked the real tree at a high level of detail. Observations on mango skin blush distribution supported the proposition that sunlight exposure is an absolute requirement for anthocyanin development. No blush development occurred on shaded skin. It was affirmed that 3D mapping could allow for virtual experiments. For example, for virtual canopy thinning (e.g., 'window pruning') to admit more sunlight with a view to improve fruit blush. Improvements to 3D modelling of mango skin blush could focus on increasing accuracy, e.g., measurement of leaf light reflectance and transmission and the inclusion of the effect shading by branches.

Bioeconomic modelling of woody regrowth carbon offset options in productive grazing systems

Agricultural land has been identified as a potential source of greenhouse gas emissions offsets through biosequestration in vegetation and soil. In the extensive grazing land of Australia, landholders may participate in the Australian Government’s Emissions Reduction Fund and create offsets by reducing woody vegetation clearing and allowing native woody plant regrowth to grow. This study used bioeconomic modelling to evaluate the trade-offs between an existing central Queensland grazing operation, which has been using repeated tree clearing to maintain pasture growth, and an alternative carbon and grazing enterprise in which tree clearing is reduced and the additional carbon sequestered in trees is sold. The results showed that ceasing clearing in favour of producing offsets produces a higher net present value over 20 years than the existing cattle enterprise at carbon prices, which are close to current (2015) market levels (~$13 t–1 CO2-e). However, by modifying key variables, relative profitability did change. Sensitivity analysis evaluated key variables, which determine the relative profitability of carbon and cattle. In order of importance these were: the carbon price, the gross margin of cattle production, the severity of the tree–grass relationship, the area of regrowth retained, the age of regrowth at the start of the project, and to a lesser extent the cost of carbon project administration, compliance and monitoring. Based on the analysis, retaining regrowth to generate carbon income may be worthwhile for cattle producers in Australia, but careful consideration needs to be given to the opportunity cost of reduced cattle income.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

Advanced parametrical modelling of 24 GHz radar sensor IC packaging components

This paper deals with the development of an advanced parametrical modelling concept for packaging components of a 24 GHz radar sensor IC used in automotive driver assistance systems. For fast and efficient design of packages for system-in-package modules (SiP), a simplified model for the description of parasitic electromagnetic effects within the package is desirable, as 3-D field computation becomes inefficient due to the high density of conductive elements of the various signal paths in the package. By using lumped element models for the characterization of the conductive components, a fast indication of the design's signal-quality can be gained, but so far does not offer enough flexibility to cover the whole range of geometric arrangements of signal paths in a contemporary package. This work pursues to meet the challenge of developing a flexible and fast package modelling concept by defining parametric lumped-element models for all basic signal path components, e.g. bond wires, vias, strip lines, bumps and balls. © Author(s) 2011. CC Attribution 3.0 License.

Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project.

Background: Post-discharge mortality is a frequent but poorly recognized contributor to child mortality in resource limited countries. The identification of children at high risk for post-discharge mortality is a critically important first step in addressing this problem. Objectives: The objective of this project was to determine the variables most likely to be associated with post-discharge mortality which are to be included in a prediction modelling study. Methods: A two-round modified Delphi process was completed for the review of a priori selected variables and selection of new variables. Variables were evaluated on relevance according to (1) prediction (2) availability (3) cost and (4) time required for measurement. Participants included experts in a variety of relevant fields. Results: During the first round of the modified Delphi process, 23 experts evaluated 17 variables. Forty further variables were suggested and were reviewed during the second round by 12 experts. During the second round 16 additional variables were evaluated. Thirty unique variables were compiled for use in the prediction modelling study. Conclusion: A systematic approach was utilized to generate an optimal list of candidate predictor variables for the incorporation into a study on prediction of pediatric post-discharge mortality in a resource poor setting.

Using niche modelling of indicator species to predict the distribution of xerophitic shrub dune communities in South-Western Portugal

Inland sand dune systems are amongst the most threatened habitat types of Europe. Affected by severe conditions, these habitats present distinct community compositions, which makes them excellent for studying possible interactions among their integrating species and the environment. We focus on understanding the distribution and cooccurrence of the species from dune plant assemblages as a key step for the adequate protection of these habitats. Using data from an extensive survey we identified the shrub species that could be considered indicators of the different xerophytic scrub dune communities in South West Portugal. Then, we modelled the responses of these species to the environmental conditions using Ecological Niche Factor Analysis. We present some preliminary results elucidating whether using species distribution models of indicator species at a regional scale is a valid approach to predict the distribution of the different types of communities inhabiting these endangered habitats.

Landscape metrics as indicators of coastal morphology and its use in ecological niche modelling of seagrass species

Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.

Experimentally and coupled CFD/CSD assisted structural and aeroelastic modelling of the Javelin UAV outboard wing section

This study presents the procedure followed to make a prediction of the critical flutter speed for a composite UAV wing. At the beginning of the study, there was no information available on the materials used for the construction of the wing, and the wing internal structure was unknown. Ground vibration tests were performed in order to detect the structure’s natural frequencies and mode shapes. From tests, it was found that the wing possesses a high stiffness, presenting well separated first bending and torsional natural frequencies. Two finite element models were developed and matched to experimental results. It has been necessary to introduce some assumptions, due to the uncertainties regarding the structure. The matching process was based on natural frequencies’ sensitivity with respect to a change in the mechanical properties of the materials. Once experimental results were met, average material properties were also found. Aerodynamic coefficients for the wing were obtained by means of a CFD software. The same analysis was also conducted when the wing is deformed in its first four mode shapes. A first approximation for flutter critical speed was made with the classical V - g technique. Finally, wing’s aeroelastic behavior was simulated using a coupled CFD/CSD method, obtaining a more accurate flutter prediction. The CSD solver is based on the time integration of modal dynamic equations, requiring the extraction of mode shapes from the previously performed finite-element analysis. Results show that flutter onset is not a risk for the UAV, occurring at velocities well beyond its operative range.

Metabolism modelling of the Urban Water System of Oslo using the package UWOT

Oslo, capitale della Norvegia, sta sperimentando un’improvvisa crescita della popolazione e secondo le stime fornite da Statistics Norway si prevede un aumento di 200 000 abitanti entro il 2040. La crescita della popolazione comporterà un rilevante aumento di domanda di acqua e, insieme ad altri fattori quali l’età delle infrastrutture e i cambiamenti climatici, sarà responsabile di una notevole pressione sulle infrastrutture idriche presenti. In risposta alla necessità di tempestivi cambiamenti, il gestore del servizio idrico della città (Oslo VAV) ha deciso di finanziare progetti per migliorare la robustezza delle infrastrutture idriche. Il lavoro di tesi si inserisce all’interno del progetto E3WDM, istituito nel 2005 con lo scopo di definire una gestione più efficiente della risorsa idrica di Oslo. L’obiettivo generale della tesi è la creazione di un modello metabolico attraverso il software UWOT (Makropoulos et al., 2008) con lo scopo di rappresentare i consumi idrici di due tipiche tipologie abitative nella città di Oslo. L’innovazione di questo studio consiste nella definizione e nella modellazione della domanda idrica all’interno delle abitazioni ad un livello di dettaglio molto elevato. Il nuovo approccio fornito da UWOT consente la simulazione di differenti strategie di intervento e la successiva gestione ottimale della risorsa idrica in grado di minimizzare i consumi di acqua, di energia e i costi, compatibilmente con la domanda idrica richiesta. Il lavoro di tesi comprende: -La descrizione del software UWOT, in particolare lo scopo del modello, l’innovativo approccio adottato, la struttura e il procedimento per creare un modello del sistema idrico urbano. -La definizione dei dati richiesti per la simulazione dei consumi idrici all’interno delle abitazioni nella città di Oslo e i metodi utilizzati per raccoglierli -L’applicazione del modello UWOT per la definizione dei trend di consumi idrici e la successiva analisi dei risultati

Modelling of metal recovery from industrial wastewater using a biopolymer sorbent

Comunicação selecionada e Artigo publicado no Livro de Actas do Congresso

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.

Numerical modelling of braided fibres for reinforced concrete

Fire has been always a major concern for designers of steel and concrete structures. Designing fire-resistant structural elements is not an easy task due to several limitations such as the lack of fire-resistant construction materials. Concrete reinforcement cover and external insulation are the most commonly adopted systems to protect concrete and steel from overheating, while spalling of concrete is minimised by using HPFRC instead of standard concrete. Although these methodologies work very well for low rise concrete structures, this is not the case for high-rise and inaccessible buildings where fire loading is much longer. Fire can permanently damage structures that cost a lot of money. This is unsafe and can lead to loss of life. In this research, the author proposes a new type of main reinforcement for concrete structures which can provide better fire-resistance than steel or FRP re-bars. This consists of continuous braided fibre rope, generally made from fire-resistant materials such as carbon or glass fibre. These fibres have excellent tensile strengths, sometimes in excess of ten times greater than steel. In addition to fire-resistance, these ropes can produce lighter and corrosive resistant structures. Avoiding the use of expensive resin binders, fibres are easily bound together using braiding techniques, ensuring that tensile stress is evenly distributed throughout the reinforcement. In order to consider braided ropes as a form of reinforcement it is first necessary to establish the mechanical performance at room temperature and investigate the pull-out resistance for both unribbed and ribbed ropes. Ribbing of ropes was achieved by braiding the rope over a series of glass beads. Adhesion between the rope and concrete was drastically improved due to ribbing, and further improved by pre-stressing ropes and reducing the slacked fibres. Two types of material have been considered for the ropes: carbon and aramid. An implicit finite element approach is proposed to model braided fibres using Total Lagrangian formulation, based on the theory of small strains and large rotations. Modelling tows and strands as elastic transversely isotropic materials was a good assumption when stiff and brittle fibres such as carbon and glass fibres are considered. The rope-to-concrete and strand-to-strand bond interaction/adhesion was numerically simulated using newly proposed hierarchical higher order interface elements. Elastic and linear damage cohesive models were used effectively to simulate non-penetrative 'free' sliding interaction between strands, and the adhesion between ropes and concrete respectively. Numerical simulation showed similar de-bonding features when compared with experimental pull-out results of braided ribbed rope reinforced concrete.

3D modelling of the transmissivity of granitic rocks surrounding the old Quinta do Bispo mine | Modelação 3D da transmissividade do maciço granítico envolvente à antiga mina da Quinta do Bispo

Apresenta-se uma metodologia para caracterizar a transmissividade dos Granitos Hercínicos e Metasedimentos do Complexo Xisto-Grauváquico do maciço envolvente e subjacente à antiga área mineira de urânio da Quinta do Bispo. Inicia-se com a modelação das litologias e grau de alteração a que se segue a simulação condicional da densidade de fracturação. No final, a densidade de fracturação é convertida num modelo 3D de transmissividade por relação com os resultados dos ensaios de bombagem. The purpose of this work is to present a methodology for characterizing the transmissivity of the Hercynian granites and complex schist–greywacke metasediment rocks surrounding and underlying the old Quinta do Bispo uranium mining site. The methodology encompasses modelling of lithologies and weathering levels, followed by a conditional simulation of fracture density. Fracture density is then converted into a 3D model of transmissivity via a relationship with pumping tests.

Distribution modelling of wild rabbit hunting yields in its original area (S Iberian Peninsula)

In this work we used the information of the Annual Hunting Reports (AHRs) to obtain a high-resolution model of the potential favourableness for wild rabbit harvesting in Andalusia (southern Spain), using environmental and land-use variables as predictors. We analysed 32,134 AHRs from the period 1993/2001 reported by 6049 game estates to estimate the average hunting yields of wild rabbit in each Andalusian municipality (n5771). We modelled the favourableness for obtaining good hunting yields using stepwise logistic regression on a set of climatic, orographical, land use, and vegetation variables. The favourability equation was used to create a downscaled image representing the favourableness of obtaining good hunting yields for the wild rabbit in 161 km squares in Andalusia, using the Idrisi Image Calculator. The variables that affected hunting yields of wild rabbit were altitude, dry wood crops (mainly olive groves, almond groves, and vineyards), temperature, pasture, slope, and annual number of frost days. The 161 km squares with high favourableness values are scattered throughout the territory, which seems to be caused mainly by the effect of vegetation. Finally, we obtained quality categories for the territory by combining the probability values given by logistic regression with those of the environmental favourability function.