22 resultados para computational modeling

em Cambridge University Engineering Department Publications Database


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A new scalable Monotonically Integrated Large Eddy Simulation (MILES) method based on the Compact Accurately Boundary-Adjusting high-REsolution Technique (CABARET) has been applied for the simulation of unsteady flow around NACA0012 airfoil at Re = 400,000 and M = 0.058. The flow solution is coupled with the Ffowcs Williams-Hawkings formulation for far-field noise prediction. The computational modeling results are presented for several computational grid resolutions: 8, 16, and 32 million grid cells and compared with the experimental data available.

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Using computational modeling, we investigate the mechanical properties of polymeric materials composed of coiled chains, or "globules", which encompass a folded secondary structure and are cross-linked by labile bonds to form a macroscopic network. In the presence of an applied force, the globules can unfold into linear chains and thereby dissipate energy as the network is deformed; the latter attribute can contribute to the toughness of the material. Our goal is to determine how to tailor the labile intra- and intermolecular bonds within the network to produce material exhibiting both toughness and strength. Herein, we use the lattice spring model (LSM) to simulate the globules and the cross-linked network. We also utilize our modified Hierarchical Bell model (MHBM) to simulate the rupture and reforming of N parallel bonds. By applying a tensile deformation, we demonstrate that the mechanical properties of the system are sensitive to the values of N in and N out, the respective values of N for the intra- and intermolecular bonds. We find that the strength of the material is mainly controlled by the value of N out, with the higher value of N out providing a stronger material. We also find that, if N in is smaller than N out, the globules can unfold under the tensile load before the sample fractures and, in this manner, can increase the ductility of the sample. Our results provide effective strategies for exploiting relatively weak, labile interactions (e.g., hydrogen bonding or the thiol/disulfide exchange reaction) in both the intra- and intermolecular bonds to tailor the macroscopic performance of the materials. © 2011 American Chemical Society.

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Access to robust and information-rich human cardiac tissue models would accelerate drug-based strategies for treating heart disease. Despite significant effort, the generation of high-fidelity adult-like human cardiac tissue analogs remains challenging. We used computational modeling of tissue contraction and assembly mechanics in conjunction with microfabricated constraints to guide the design of aligned and functional 3D human pluripotent stem cell (hPSC)-derived cardiac microtissues that we term cardiac microwires (CMWs). Miniaturization of the platform circumvented the need for tissue vascularization and enabled higher-throughput image-based analysis of CMW drug responsiveness. CMW tissue properties could be tuned using electromechanical stimuli and cell composition. Specifically, controlling self-assembly of 3D tissues in aligned collagen, and pacing with point stimulation electrodes, were found to promote cardiac maturation-associated gene expression and in vivo-like electrical signal propagation. Furthermore, screening a range of hPSC-derived cardiac cell ratios identified that 75% NKX2 Homeobox 5 (NKX2-5)+ cardiomyocytes and 25% Cluster of Differentiation 90 OR (CD90)+ nonmyocytes optimized tissue remodeling dynamics and yielded enhanced structural and functional properties. Finally, we demonstrate the utility of the optimized platform in a tachycardic model of arrhythmogenesis, an aspect of cardiac electrophysiology not previously recapitulated in 3D in vitro hPSC-derived cardiac microtissue models. The design criteria identified with our CMW platform should accelerate the development of predictive in vitro assays of human heart tissue function.

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This tunable holographic sensor offers interrogation and a reporting transducer as well as an analyte-responsive hydrogel, rendering it label-free and reusable. A single 6 ns laser pulse is used to fabricate holographic sensors consisting of silver nanoparticles arranged periodically within a polymer film. The tunability of the sensor is demonstrated through pH sensing of artificial urine and validated through computational modeling. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Excavation works in urban areas require a preliminary risk damage assessment. In historical cities, the prediction of building response to settlements is necessary to reduce the risk of damage of the architectural heritage. The current method used to predict the building damage due to ground deformations is the Limiting Tensile Strain Method (LTSM). This method is based on an uncoupled soil-structure analysis, in which the building is modelled as an elastic beam subject to imposed greenfield settlements and the induced tensile strains are compared with a limit value for the material. This approach neglects many factors which play an important rule in the response of the structure to tunneling induced settlements. In this paper, the possibility to apply a settlement risk assessment derived from the seismic vulnerability approach is considered. The parameters that influence the structural response to settlements can be defined through numerical coupled analyses which take into account the nonlinear behaviour of masonry and the soil-structure interaction.

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Analytical methods provide a global context from which to understand the dynamics of stone spires, but computational and experimental methods are useful to predict more specific behavior of multiple block structures. In this paper, the spire of St. Mary Magdalene church in Waltham-on-the-Wolds, UK, which was damaged in the 2008 Lincolnshire Earthquake, is used as a case study. Both a physical model and a discrete element computational model of the spire were created and used to investigate collapse under constant horizontal acceleration, impulse base motion, and earthquake ground motion. Results indicate that the global behavior compares well with analytical modeling, but local block displacements evident in DEM and experimental results also reduce the stability of the structure. In this context, the observed damage to St. Mary Magdalene church is evaluated and discussed. © 2012 Elsevier Ltd.

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Pronunciation is an important part of speech acquisition, but little attention has been given to the mechanism or mechanisms by which it develops. Speech sound qualities, for example, have just been assumed to develop by simple imitation. In most accounts this is then assumed to be by acoustic matching, with the infant comparing his output to that of his caregiver. There are theoretical and empirical problems with both of these assumptions, and we present a computational model- Elija-that does not learn to pronounce speech sounds this way. Elija starts by exploring the sound making capabilities of his vocal apparatus. Then he uses the natural responses he gets from a caregiver to learn equivalence relations between his vocal actions and his caregiver's speech. We show that Elija progresses from a babbling stage to learning the names of objects. This demonstrates the viability of a non-imitative mechanism in learning to pronounce.

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Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model. © 2011 Elsevier Ltd.

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In the context of collaborative product development, new requirements need to be accommodated for Virtual Prototyping Simulation (VPS), such as distributed processing and the integration of models created using different tools or languages. Existing solutions focus mainly on the implementation of distributed processing, but this paper explores the issues of combining different models (some of which may be proprietary) developed in different software environments. In this paper, we discuss several approaches for developing VPS, and suggest how it can best be integrated into the design process. An approach is developed to improve collaborative work in a VPS development by combining disparate computational models. Specifically, a system framework is proposed to separate the system-level modeling from the computational infrastructure. The implementation of a simple prototype demonstrates that such a paradigm is viable and thus provides a new means for distributed VPS development. © 2009 by ASME.