861 resultados para 091307 Numerical Modelling and Mechanical Characterisation
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Video analysis provides an educational, motivating, and cost-effective alternative to traditional course- related activities in physics education. Our paper presents results from video analysis of experiments “Collision of balls” and “Motion of a ball rolled on inclined plane” as examples to illustrate the laws of conservation of impulse and mechanical energy.
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In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.
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As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.
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Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.
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2010 Mathematics Subject Classification: 60J85, 92D25.
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Supply chains comprise of complex processes spanning across multiple trading partners. The various operations involved generate large number of events that need to be integrated in order to enable internal and external traceability. Further, provenance of artifacts and agents involved in the supply chain operations is now a key traceability requirement. In this paper we propose a Semantic web/Linked data powered framework for the event based representation and analysis of supply chain activities governed by the EPCIS specification. We specifically show how a new EPCIS event type called "Transformation Event" can be semantically annotated using EEM - The EPCIS Event Model to generate linked data, that can be exploited for internal event based traceability in supply chains involving transformation of products. For integrating provenance with traceability, we propose a mapping from EEM to PROV-O. We exemplify our approach on an abstraction of the production processes that are part of the wine supply chain.
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The paper analyzes a special corporate banking product, the so called cash-pool, which gained remarkable popularity in the recent years as firms try to centralize and manage their liquidity more efficiently. The novelty of this paper is the formalization of a valuation model which can serve as a basis for a Monte Carlo simulation to assess the most important benefits of the firms arising from the pooling of their cash holdings. The literature emphasizes several benefits of cash-pooling such as interest rate savings, economy of scale and reduced cash-flow volatility. The presented model focuses on the interest rate savings complemented with a new aspect: the reduced counterparty risk toward the bank. The main conclusion of the analysis is that the value of a cash-pool is higher in case of firms with large, diverse and volatile cash-flows having less access to the capital markets especially if the partner bank is risky and offers a high interest spread. It is also shown that cash-pooling is not the privilege of large multinational firms any more as the initial direct costs can be easily regained within a year even in the case of SMEs.
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Transition metals (Ti, Zr, Hf, Mo, W, V, Nb, Ta, Pd, Pt, Cu, Ag, and Au) are essential building units of many materials and have important industrial applications. Therefore, it is important to understand their thermal and physical behavior when they are subjected to extreme conditions of pressure and temperature. This dissertation presents: • An improved experimental technique to use lasers for the measurement of thermal conductivity of materials under conditions of very high pressure (P, up to 50 GPa) and temperature (T up to 2500 K). • An experimental study of the phase relationship and physical properties of selected transition metals, which revealed new and unexpected physical effects of thermal conductivity in Zr, and Hf under high P-T. • New phase diagrams created for Hf, Ti and Zr from experimental data. • P-T dependence of the lattice parameters in α-hafnium. Contrary to prior reports, the α-ω phase transition in hafnium has a negative dT/dP slope. • New data on thermodynamic and physical properties of several transition metals and their respective high P-T phase diagrams. • First complete thermodynamic database for solid phases of 13 common transition metals was created. This database has: All the thermochemical data on these elements in their standard state (mostly available and compiled); All the equations of state (EoS) formulated from pressure-volume-temperature data (measured as a part of this study and from literature); Complete thermodynamic data for selected elements from standard to extreme conditions. The thermodynamic database provided by this study can be used with available thermodynamic software to calculate all thermophysical properties and phase diagrams at high P-T conditions. For readers who do not have access to this software, tabulated values of all thermodynamic and volume data for the 13 metals at high P-T are included in the APPENDIX. In the APPENDIX, a description of several other high-pressure studies of selected oxide systems is also included. Thermophysical properties (Cp, H, S, G) of the high P-T ω-phase of Ti, Zr and Hf were determined during the optimization of the EoS parameters and are presented in this study for the first time. These results should have important implications in understanding hexagonal-close-packed to simple-hexagonal phase transitions in transition metals and other materials.
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Acknowledgments The authors would like to thank Shell E&P Rijswijk, for supporting this research. The authors are grateful to Pat Shannon, Catherine Baudon and Dominique Frizon de Lamotte for many discussions on rift processes. We would like to thank Steven Bergman for thorough comments on an early version of the paper, and Chris Morley and an anonymous reviewer for sharing ideas and references for writing a better paper
Field data, numerical simulations and probability analyses to assess lava flow hazards at Mount Etna
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Improving lava flow hazard assessment is one of the most important and challenging fields of volcanology, and has an immediate and practical impact on society. Here, we present a methodology for the quantitative assessment of lava flow hazards based on a combination of field data, numerical simulations and probability analyses. With the extensive data available on historic eruptions of Mt. Etna, going back over 2000 years, it has been possible to construct two hazard maps, one for flank and the other for summit eruptions, allowing a quantitative analysis of the most likely future courses of lava flows. The effective use of hazard maps of Etna may help in minimizing the damage from volcanic eruptions through correct land use in densely urbanized area with a population of almost one million people. Although this study was conducted on Mt. Etna, the approach used is designed to be applicable to other volcanic areas.
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This work introduces joint power amplifier (PA) and I/Q modulator modelling and compensation for LongTerm Evolution (LTE) transmitters using artificial neural networks (ANNs). The proposed solution util-izes a powerful nonlinear autoregressive with exogenous inputs (NARX) ANN architecture, which yieldsnoticeable results for high peak to average power ratio (PAPR) LTE signals. Given the ANNs learning capa-bilities, this one-step solution, which includes the mitigation of both PA nonlinearity and I/Q modulatorimpairments, is both accurate and adaptable
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The deposition of stiff and strong coatings onto porous templates offers a novel strategy for fabricating macroscale materials with controlled architectures at the micro- and nanoscale. Here, layer-by-layer assembly is utilized to fabricate nanocomposite-coated foams with highly customizable properties by depositing polymer–nanoclay coatings onto open-cell foam templates. The compressive mechanical behavior of these materials evolves in a predictable manner that is qualitatively captured by scaling laws for the mechanical properties of cellular materials. The observed and predicted properties span a remarkable range of density-stiffness space, extending from regions of very soft elastomer foams to very stiff, lightweight honeycomb and lattice materials.
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Understanding the impact of extracellular matrix sub-types and mechanical stretch on cardiac fibroblast activity is required to help unravel the pathophysiology of myocardial fibrotic diseases. Therefore, the purpose of this study was to investigate pro-fibrotic responses of primary human cardiac fibroblast cells exposed to different extracellular matrix components, including collagen sub-types I, III, IV, VI and laminin. The impact of mechanical cyclical stretch and treatment with transforming growth factor beta 1 (TGFβ1) on collagen 1, collagen 3 and alpha smooth muscle actin mRNA expression on different matrices was assessed using quantitative real-time PCR. Our results revealed that all of the matrices studied not only affected the expression of pro-fibrotic genes in primary human cardiac fibroblast cells at rest but also affected their response to TGFβ1. In addition, differential cellular responses to mechanical cyclical stretch were observed depending on the type of matrix the cells were adhered to. These findings may give insight into the impact of selective pathological deposition of extracellular matrix proteins within different disease states and how these could impact the fibrotic environment.
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Engineered cocrystals offer an alternative solid drug form with tailored physicochemical properties. Interestingly, although cocrystals provide many new possibilities, they also present new challenges, particularly in regard to their design and large-scale manufacture. Current literature has primarily focused on the preparation and characterization of novel cocrystals typically containing only the drug and coformer, leaving the subsequent formulation less explored. In this paper we propose, for the first time, the use of hot melt extrusion for the mechanochemical synthesis of pharmaceutical cocrystals in the presence of a meltable binder. In this approach, we examine excipients that are amenable to hot melt extrusion, forming a suspension of cocrystal particulates embedded in a pharmaceutical matrix. Using ibuprofen and isonicotinamide as a model cocrystal reagent pair, formulations extruded with a small molecular matrix carrier (xylitol) were examined to be intimate mixtures wherein the newly formed cocrystal particulates were physically suspended in a matrix. With respect to formulations extruded using polymeric carriers (Soluplus and Eudragit EPO, respectively), however, there was no evidence within PXRD patterns of either crystalline ibuprofen or the cocrystal. Importantly, it was established in this study that an appropriate carrier for a cocrystal reagent pair during HME processing should satisfy certain criteria including limited interaction with parent reagents and cocrystal product, processing temperature sufficiently lower than the onset of cocrystal Tm, low melt viscosity, and rapid solidification upon cooling.