950 resultados para 3D numerical modeling


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Dual-phase-lagging (DPL) models constitute a family of non-Fourier models of heat conduction that allow for the presence of time lags in the heat flux and the temperature gradient. These lags may need to be considered when modeling microscale heat transfer, and thus DPL models have found application in the last years in a wide range of theoretical and technical heat transfer problems. Consequently, analytical solutions and methods for computing numerical approximations have been proposed for particular DPL models in different settings. In this work, a compact difference scheme for second order DPL models is developed, providing higher order precision than a previously proposed method. The scheme is shown to be unconditionally stable and convergent, and its accuracy is illustrated with numerical examples.

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This paper proposes the implementation of different non-local Planetary Boundary Layer schemes within the Regional Atmospheric Modeling System (RAMS) model. The two selected PBL parameterizations are the Medium-Range Forecast (MRF) PBL and its updated version, known as the Yonsei University (YSU) PBL. YSU is a first-order scheme that uses non-local eddy diffusivity coefficients to compute turbulent fluxes. It is based on the MRF, and improves it with an explicit treatment of the entrainment. With the aim of evaluating the RAMS results for these PBL parameterizations, a series of numerical simulations have been performed and contrasted with the results obtained using the Mellor and Yamada (MY) scheme, also widely used, and the standard PBL scheme in the RAMS model. The numerical study carried out here is focused on mesoscale circulation events during the summer, as these meteorological situations dominate this season of the year in the Western Mediterranean coast. In addition, the sensitivity of these PBL parameterizations to the initial soil moisture content is also evaluated. The results show a warmer and moister PBL for the YSU scheme compared to both MRF and MY. The model presents as well a tendency to overestimate the observed temperature and to underestimate the observed humidity, considering all PBL schemes and a low initial soil moisture content. In addition, the bias between the model and the observations is significantly reduced moistening the initial soil moisture of the corresponding run. Thus, varying this parameter has a positive effect and improves the simulated results in relation to the observations. However, there is still a significant overestimation of the wind speed over flatter terrain, independently of the PBL scheme and the initial soil moisture used, even though a different degree of accuracy is reproduced by RAMS taking into account the different sensitivity tests.

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Population balances of polymer species in terms 'of discrete transforms with respect to counts of groups lead to tractable first order partial differential equations when ali rate constants are independent of chain length and loop formation is negligible [l]. Average molecular weights in the absence ofgelation are long known to be readily found through integration of an initial value problem. The extension to size distribution prediction is also feasible, but its performance is often lower to the one provided by methods based upon real chain length domain [2]. Moreover, the absence ofagood starting procedure and a higher numerical sensitivity hás decisively impaired its application to non-linear reversibly deactivated polymerizations, namely NMRP [3].

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The ability to view and interact with 3D models has been happening for a long time. However, vision-based 3D modeling has only seen limited success in applications, as it faces many technical challenges. Hand-held mobile devices have changed the way we interact with virtual reality environments. Their high mobility and technical features, such as inertial sensors, cameras and fast processors, are especially attractive for advancing the state of the art in virtual reality systems. Also, their ubiquity and fast Internet connection open a path to distributed and collaborative development. However, such path has not been fully explored in many domains. VR systems for real world engineering contexts are still difficult to use, especially when geographically dispersed engineering teams need to collaboratively visualize and review 3D CAD models. Another challenge is the ability to rendering these environments at the required interactive rates and with high fidelity. In this document it is presented a virtual reality system mobile for visualization, navigation and reviewing large scale 3D CAD models, held under the CEDAR (Collaborative Engineering Design and Review) project. It’s focused on interaction using different navigation modes. The system uses the mobile device's inertial sensors and camera to allow users to navigate through large scale models. IT professionals, architects, civil engineers and oil industry experts were involved in a qualitative assessment of the CEDAR system, in the form of direct user interaction with the prototypes and audio-recorded interviews about the prototypes. The lessons learned are valuable and are presented on this document. Subsequently it was prepared a quantitative study on the different navigation modes to analyze the best mode to use it in a given situation.

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National Highway Traffic Safety Administration, Washington, D.C.

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Thesis (Ph.D.)--University of Washington, 2016-06

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Stratum corneum (SC) desorption experiments have yielded higher calculated steady-state fluxes than those obtained by epidermal penetration studies. A possible explanation of this result is a variable diffusion or partition coefficient across the SC. We therefore developed the diffusion model for percutaneous penetration and desorption to study the effects of either a variable diffusion coefficient or variable partition coefficient in the SC over the diffusion path length. Steady-state flux, lag time, and mean desorption time were obtained from Laplace domain solutions. Numerical inversion of the Laplace domain solutions was used for simulations of solute concentration-distance and amount penetrated (desorbed)-time profiles. Diffusion and partition coefficients heterogeneity were examined using six different models. The effect of heterogeneity on predicted flux from desorption studies was compared with that obtained in permeation studies. Partition coefficient heterogeneity had a more profound effect on predicted fluxes than diffusion coefficient heterogeneity. Concentration-distance profiles show even larger dependence on heterogeneity, which is consistent with experimental tape-stripping data reported for clobetasol propionate and other solutes. The clobetasol propionate tape-stripping data were most consistent with the partition coefficient decreasing exponentially for half the SC and then becoming a constant for the remaining SC. (C) 2004 Wiley-Liss, Inc.

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Computer-aided tomography has been used for many years to provide significant information about the internal properties of an object, particularly in the medical fraternity. By reconstructing one-dimensional (ID) X-ray images, 2D cross-sections and 3D renders can provide a wealth of information about an object's internal structure. An extension of the methodology is reported here to enable the characterization of a model agglomerate structure. It is demonstrated that methods based on X-ray microtomography offer considerable potential in the validation and utilization of distinct element method simulations also examined.

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We explore both the rheology and complex flow behavior of monodisperse polymer melts. Adequate quantities of monodisperse polymer were synthesized in order that both the materials rheology and microprocessing behavior could be established. In parallel, we employ a molecular theory for the polymer rheology that is suitable for comparison with experimental rheometric data and numerical simulation for microprocessing flows. The model is capable of matching both shear and extensional data with minimal parameter fitting. Experimental data for the processing behavior of monodisperse polymers are presented for the first time as flow birefringence and pressure difference data obtained using a Multipass Rheometer with an 11:1 constriction entry and exit flow. Matching of experimental processing data was obtained using the constitutive equation with the Lagrangian numerical solver, FLOWSOLVE. The results show the direct coupling between molecular constitutive response and macroscopic processing behavior, and differentiate flow effects that arise separately from orientation and stretch. (c) 2005 The Society of Rheology.

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A critical assessment is presented for the existing fluid flow models used for dense medium cyclones (DMCs) and hydrocyclones. As the present discussion indicates, the understanding of dense medium cyclone flow is still far from the complete. However, its similarity to the hydrocyclone provides a basis for improved understanding of fluid flow in DMCs. The complexity of fluid flow in DMCs is basically due to the existence of medium as well as the dominance of turbulent particle size and density effects on separation. Both the theoretical and experimental analysis is done with respect to two-phase motions and solid phase flow in hydrocyclones or DMCs. A detailed discussion is presented on the empirical, semiempirical, and the numerical models based upon both the vorticity-stream function approach and Navier-Stokes equations in their primitive variables and in cylindrical coordinates available in literature. The existing equations describing turbulence and multiphase flows in cyclone are also critically reviewed.

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Due to complex field/tissue interactions, high-field magnetic resonance (MR) images suffer significant image distortions that result in compromised diagnostic quality. A new method that attempts to remove these distortions is proposed in this paper and is based on the use of transceiver-phased arrays. The proposed system uses, in the examples presented herein, a shielded four-element transceive-phased array head coil and involves performing two separate scans of the same slice with each scan using different excitations during transmission. By optimizing the amplitudes and phases for each scan, antipodal signal profiles can be obtained, and by combining both the images together, the image distortion can be reduced several fold. A combined hybrid method of moments (MoM)/finite element method (FEM) and finite-difference time-domain (FDTD) technique is proposed and used to elucidate the concept of the new method and to accurately evaluate the electromagnetic field (EMF) in a human head model. In addition, the proposed method is used in conjunction with the generalized auto-calibrating partially parallel acquisitions (GRAPPA) reconstruction technique to enable rapid imaging of the two scans. Simulation results reported herein for 11-T (470-MHz) brain imaging applications show that the new method with GRAPPA reconstruction theoretically results in improved image quality and that the proposed combined hybrid MoM/FEM and FDTD technique is. suitable for high-field magnetic resonance imaging (MRI) numerical analysis.

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In modern magnetic resonance imaging (MRI), both patients and radiologists are exposed to strong, nonuniform static magnetic fields inside or outside of the scanner, in which the body movement may be able to induce electric currents in tissues which could be possibly harmful. This paper presents theoretical investigations into the spatial distribution of induced E-fields in the human model when moving at various positions around the magnet. The numerical calculations are based on an efficient, quasistatic, finite-difference scheme and an anatomically realistic, full-body, male model. 3D field profiles from an actively-shielded 4 T magnet system are used and the body model projected through the field profile with normalized velocity. The simulation shows that it is possible to induce E-fields/currents near the level of physiological significance under some circumstances and provides insight into the spatial characteristics of the induced fields. The results are easy to extrapolate to very high field strengths for the safety evaluation at a variety of field strengths and motion velocities.

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The developments of models in Earth Sciences, e.g. for earthquake prediction and for the simulation of mantel convection, are fare from being finalized. Therefore there is a need for a modelling environment that allows scientist to implement and test new models in an easy but flexible way. After been verified, the models should be easy to apply within its scope, typically by setting input parameters through a GUI or web services. It should be possible to link certain parameters to external data sources, such as databases and other simulation codes. Moreover, as typically large-scale meshes have to be used to achieve appropriate resolutions, the computational efficiency of the underlying numerical methods is important. Conceptional this leads to a software system with three major layers: the application layer, the mathematical layer, and the numerical algorithm layer. The latter is implemented as a C/C++ library to solve a basic, computational intensive linear problem, such as a linear partial differential equation. The mathematical layer allows the model developer to define his model and to implement high level solution algorithms (e.g. Newton-Raphson scheme, Crank-Nicholson scheme) or choose these algorithms form an algorithm library. The kernels of the model are generic, typically linear, solvers provided through the numerical algorithm layer. Finally, to provide an easy-to-use application environment, a web interface is (semi-automatically) built to edit the XML input file for the modelling code. In the talk, we will discuss the advantages and disadvantages of this concept in more details. We will also present the modelling environment escript which is a prototype implementation toward such a software system in Python (see www.python.org). Key components of escript are the Data class and the PDE class. Objects of the Data class allow generating, holding, accessing, and manipulating data, in such a way that the actual, in the particular context best, representation is transparent to the user. They are also the key to establish connections with external data sources. PDE class objects are describing (linear) partial differential equation objects to be solved by a numerical library. The current implementation of escript has been linked to the finite element code Finley to solve general linear partial differential equations. We will give a few simple examples which will illustrate the usage escript. Moreover, we show the usage of escript together with Finley for the modelling of interacting fault systems and for the simulation of mantel convection.

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The physical implementation of quantum information processing is one of the major challenges of current research. In the last few years, several theoretical proposals and experimental demonstrations on a small number of qubits have been carried out, but a quantum computing architecture that is straightforwardly scalable, universal, and realizable with state-of-the-art technology is still lacking. In particular, a major ultimate objective is the construction of quantum simulators, yielding massively increased computational power in simulating quantum systems. Here we investigate promising routes towards the actual realization of a quantum computer, based on spin systems. The first one employs molecular nanomagnets with a doublet ground state to encode each qubit and exploits the wide chemical tunability of these systems to obtain the proper topology of inter-qubit interactions. Indeed, recent advances in coordination chemistry allow us to arrange these qubits in chains, with tailored interactions mediated by magnetic linkers. These act as switches of the effective qubit-qubit coupling, thus enabling the implementation of one- and two-qubit gates. Molecular qubits can be controlled either by uniform magnetic pulses, either by local electric fields. We introduce here two different schemes for quantum information processing with either global or local control of the inter-qubit interaction and demonstrate the high performance of these platforms by simulating the system time evolution with state-of-the-art parameters. The second architecture we propose is based on a hybrid spin-photon qubit encoding, which exploits the best characteristic of photons, whose mobility is exploited to efficiently establish long-range entanglement, and spin systems, which ensure long coherence times. The setup consists of spin ensembles coherently coupled to single photons within superconducting coplanar waveguide resonators. The tunability of the resonators frequency is exploited as the only manipulation tool to implement a universal set of quantum gates, by bringing the photons into/out of resonance with the spin transition. The time evolution of the system subject to the pulse sequence used to implement complex quantum algorithms has been simulated by numerically integrating the master equation for the system density matrix, thus including the harmful effects of decoherence. Finally a scheme to overcome the leakage of information due to inhomogeneous broadening of the spin ensemble is pointed out. Both the proposed setups are based on state-of-the-art technological achievements. By extensive numerical experiments we show that their performance is remarkably good, even for the implementation of long sequences of gates used to simulate interesting physical models. Therefore, the here examined systems are really promising buildingblocks of future scalable architectures and can be used for proof-of-principle experiments of quantum information processing and quantum simulation.