983 resultados para Hybrid modelling


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The importance of interlaminar stresses has prompted a fresh look at the theory of laminated plates. An important feature in modelling such laminates is the need to provide for continuity of some strains and stresses, while at the same time allowing for the discontinuities in the others. A new modelling possibility is examined in this paper. The procedure allows for discontinuities in the in-plane stresses and transverse strains and continuity in the in-plane strains and transverse stresses. This theory is in the form of a heirarchy of formulations each representing an iterative step. Application of the theory is illustrated by considering the example of an infinite laminated strip subjected to sinusoidal loading.

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An improved encoding scheme is proposed wherein the quantizer step size incorporates both instantaneous and syllabic adaptation. The information needed to carry out this adaptation is extracted at the coder after the D/A conversion of the digital output, so that the coder and the decoder track each other. A 5-bit coder has been designed and built which has a dynamic range of 38 dB with a constant SNR of 30 dB, and the quality of its output signal is found to be comparable to that of other coding schemes

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This thesis developed an advanced computational model to investigate the motion and deformation properties of red blood cells in capillaries. The novel model is based on the meshfree particle methods and is capable of modelling the large deformation of red blood cells moving through blood vessels. The developed model was employed to simulate the deformation behaviour of healthy and malaria infected red blood cells as well as the motion of red blood cells in stenosed capillaries.

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Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

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The project objective is to undertake paddock modelling across the Great Barrier Reef catchments to determine magnitude of sediment and particulate nutrient reductions from agricultural lands to GBR lagoon achieved over 5 years. Discussions, development and design of a plan (including a monitoring, evaluation, reporting and improvement plan) for GRASP paddock modelling will be undertaken to determine changes in water quality as a result of land management practices adopted by pastoralists. Biophysical outputs will be derived from range of land types, starting conditions and grazing management strategies. GRASP derived outputs will then be incorporated into water models to determine sediment and nutrient estimates for the catchments.

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Organic/inorganic hybrid gels have been developed in order to control the three-dimensional structure of photoactive nanofibers and metallic nanoparticles (NPs). These materials are prepared by simultaneous self-assembly of the 2,3-didecyloxyanthracene (DDOA) gelator and of thiol-capped gold nanoparticles (AuNPs). TEM and fluorescence measurements show that alkane-thiol capped AuNPs are homogeneously dispersed and tightly attached to the thermoreversible fibrillar network formed by the organogelator in n-butanol or n-decanol. Rheology and thermal stability measurements reveal moreover that the mechanical and thermal stabilities of the DDOA organogels are not significantly altered and that they remain strong, viscoelastic materials. The hybrid materials display a variable absorbance in the visible range because of the AuNPs, whereas the strong luminescence of the DDOA nanofibers is efficiently quenched by micromolar amounts of AuNPs. Besides, we obtained hybrid aerogels using supercritical CO2. These arc very low-density porous materials showing fibrillar networks oil which fluorinated gold NPs arc dispersed. These hybrid materials are of high interest because of their tunable optical properties and are under investigation for efficient light scattering.

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Investigate the feasibility and utility of a macadamia physiological model.

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Development of 3D functional structural plant models for macadamias and other tropical fruit and nuts.

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Computational Modelling of the Vacuum Drying of Australian Hardwoods.

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Increased climate variability and the need to establish production forests at more marginal sites requires an understanding of the mechanisms of drought death in production species so that predictions of growth and survival are robust and defendable.

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This project aims to use simulatiion modelling to improve our understanding of the genetics and physiology of complex traits with a view to increasing the rate of genetic gain in plant breeding programs.

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Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

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Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.