943 resultados para Discreet Element Modelling


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Abstract: The Murray-Darling Basin comprises over 1 million km2; it lies within four states and one territory; and over 12, 800 GL of irrigation water is used to produce over 40% of the nation's gross value of agricultural production. This production is used by a diverse collection of some-times mutually exclusive commodities (e.g. pasture; stone fruit; grapes; cotton and field crops). The supply of water for irrigation is subject to climatic and policy uncertainty. Variable inflows mean that water property rights do not provide a guaranteed supply. With increasing public scrutiny and environmental issues facing irrigators, greater pressure is being placed on this finite resource. The uncertainty of the water supply, water quality (salinity), combined with where water is utilised, while attempting to maximising return for investment makes for an interesting research field. The utilisation and comparison of a GAMS and Excel based modelling approach has been used to ask: where should we allocate water?; amongst what commodities?; and how does this affect both the quantity of water and the quality of water along the Murray-Darling river system?

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Background: Understanding how clinical variables affect stress distribution facilitates optimal prosthesis design and fabrication and may lead to a decrease in mechanical failures as well as improve implant longevity. Purpose: In this study, the many clinical variations present in implant-supported prosthesis were analyzed by 3-D finite element method. Materials and Method: A geometrical model representing the anterior segment of a human mandible treated with 5 implants supporting a framework was created to perform the tests. The variables introduced in the computer model were cantilever length, elastic modulus of cancellous bone, abutment length, implant length, and framework alloy (AgPd or CoCr). The computer was programmed with physical properties of the materials as derived from the literature, and a 100N vertical load was used to simulate the occlusal force. Images with the fringes of stress were obtained and the maximum stress at each site was plotted in graphs for comparison. Results: Stresses clustered at the elements closest to the loading point. Stress increase was found to be proportional to the increase in cantilever length and inversely proportional to the increase in the elastic modulus of cancellous bone. Increasing the abutment length resulted in a decrease of stress on implants and framework. Stress decrease could not be demonstrated with implants longer than 13 mm. A stiffer framework may allow better stress distribution. Conclusion: The relative physical properties of the many materials involved in an implant-supported prosthesis system affect the way stresses are distributed.

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An important feature of some conceptual modelling grammars is the features they provide to allow database designers to show real-world things may or may not possess a particular attribute or relationship. In the entity-relationship model, for example, the fact that a thing may not possess an attribute can be represented by using a special symbol to indicate that the attribute is optional. Similarly, the fact that a thing may or may not be involved in a relationship can be represented by showing the minimum cardinality of the relationship as zero. Whether these practices should be followed, however, is a contentious issue. An alternative approach is to eliminate optional attributes and relationships from conceptual schema diagrams by using subtypes that have only mandatory attributes and relationships. In this paper, we first present a theory that led us to predict that optional attributes and relationships should be used in conceptual schema diagrams only when users of the diagrams require a surface-level understanding of the domain being represented by the diagrams. When users require a deep-level understanding, however, optional attributes and relationships should not be used because they undermine users' abilities to grasp important domain semantics. We describe three experiments which we then undertook to test our predictions. The results of the experiments support our predictions.

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Purpose: The objective of this study was to evaluate the stress on the cortical bone around single body dental implants supporting mandibular complete fixed denture with rigid (Neopronto System-Neodent) or semirigid splinting system (Barra Distal System-Neodent). Methods and Materials: Stress levels on several system components were analyzed through finite element analysis. Focusing on stress concentration at cortical bone around single body dental implants supporting mandibular complete fixed dentures with rigid ( Neopronto System-Neodent) or semirigid splinting system ( Barra Distal System-Neodent), after axial and oblique occlusal loading simulation, applied in the last cantilever element. Results: The results showed that semirigid implant splinting generated lower von Mises stress in the cortical bone under axial loading. Rigid implant splinting generated higher von Mises stress in the cortical bone under oblique loading. Conclusion: It was concluded that the use of a semirigid system for rehabilitation of edentulous mandibles by means of immediate implant-supported fixed complete denture is recommended, because it reduces stress concentration in the cortical bone. As a consequence, bone level is better preserved, and implant survival is improved. Nevertheless, for both situations the cortical bone integrity was protected, because the maximum stress level findings were lower than those pointed in the literature as being harmful. The maximum stress limit for cortical bone (167 MPa) represents the threshold between plastic and elastic state for a given material. Because any force is applied to an object, and there is no deformation, we can conclude that the elastic threshold was not surpassed, keeping its structural integrity. If the force is higher than the plastic threshold, the object will suffer permanent deformation. In cortical bone, this represents the beginning of bone resorption and/or remodeling processes, which, according to our simulated loading, would not occur. ( Implant Dent 2010; 19:39-49)

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Modelling and simulation studies were carried out at 26 cement clinker grinding circuits including tube mills, air separators and high pressure grinding rolls in 8 plants. The results reported earlier have shown that tube mills can be modelled as several mills in series, and the internal partition in tube mills can be modelled as a screen which must retain coarse particles in the first compartment but not impede the flow of drying air. In this work the modelling has been extended to show that the Tromp curve which describes separator (classifier) performance can be modelled in terms of d(50)(corr), by-pass, the fish hook, and the sharpness of the curve. Also the high pressure grinding rolls model developed at the Julius Kruttschnitt Mineral Research Centre gives satisfactory predictions using a breakage function derived from impact and compressed bed tests. Simulation studies of a full plant incorporating a tube mill, HPGR and separators showed that the models could successfully predict the performance of the another mill working under different conditions. The simulation capability can therefore be used for process optimization and design. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Petrov-Galerkin methods are known to be versatile techniques for the solution of a wide variety of convection-dispersion transport problems, including those involving steep gradients. but have hitherto received little attention by chemical engineers. We illustrate the technique by means of the well-known problem of simultaneous diffusion and adsorption in a spherical sorbent pellet comprised of spherical, non-overlapping microparticles of uniform size and investigate the uptake dynamics. Solutions to adsorption problems exhibit steep gradients when macropore diffusion controls or micropore diffusion controls, and the application of classical numerical methods to such problems can present difficulties. In this paper, a semi-discrete Petrov-Galerkin finite element method for numerically solving adsorption problems with steep gradients in bidisperse solids is presented. The numerical solution was found to match the analytical solution when the adsorption isotherm is linear and the diffusivities are constant. Computed results for the Langmuir isotherm and non-constant diffusivity in microparticle are numerically evaluated for comparison with results of a fitted-mesh collocation method, which was proposed by Liu and Bhatia (Comput. Chem. Engng. 23 (1999) 933-943). The new method is simple, highly efficient, and well-suited to a variety of adsorption and desorption problems involving steep gradients. (C) 2001 Elsevier Science Ltd. All rights reserved.

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The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.

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The c fins gene encodes the receptor for macrophage colony-stimulating factor-1. This gene is expressed selectively in the macrophage cell lineage. Previous studies have implicated sequences in intron 2 that control transcript elongation in tissue-specific and regulated expression of c -fms. Four macrophage-specific deoxyribonuclease I (DNase I)-hypersensitive sites (DHSS) were identified within mouse intron 2. Sequences of these DHSS were found to be highly conserved compared with those in the human gene. A 250-bp region we refer to as the fins intronic regulatory element (FIRE), which is even more highly conserved than the c-fins proximal promoter, contains many consensus binding sites for macrophage-expressed transcription factors including Spl, PU.1, and C/EBP. FIRE was found to act as a macrophage-specific enhancer and as a promoter with an antisense orientation preference in transient transfections. In stable transfections of the macrophage line RAW264, as well as in clones selected for high and low-level c -fms mRNA expression, the presence of intron 2 increased the frequency and level of expression of reporter genes compared with those attained using the promoter alone. Removal of FIRE abolished reporter gene expression, revealing a suppressive activity in the remaining intronic sequences. Hence, FIRE is shown to be a key regulatory element in the fins gene.

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The IWA Anaerobic Digestion Modelling Task Group was established in 1997 at the 8th World Congress on,Anaerobic Digestion (Sendai, Japan) with the goal of developing a generalised anaerobic digestion model. The structured model includes multiple steps describing biochemical as well as physicochemical processes. The biochemical steps include disintegration from homogeneous particulates to carbohydrates, proteins and lipids; extracellular hydrolysis of these particulate substrates to sugars, amino acids, and long chain fatty acids (LCFA), respectively; acidogenesis from sugars and amino acids to volatile fatty acids (VFAs) and hydrogen; acetogenesis of LCFA and VFAs to acetate; and separate methanogenesis steps from acetate and hydrogen/CO2. The physico-chemical equations describe ion association and dissociation, and gas-liquid transfer. Implemented as a differential and algebraic equation (DAE) set, there are 26 dynamic state concentration variables, and 8 implicit algebraic variables per reactor vessel or element. Implemented as differential equations (DE) only, there are 32 dynamic concentration state variables.