117 resultados para Numerical Computation
Resumo:
Pós-graduação em Ciência da Computação - IBILCE
Resumo:
Pós-graduação em Física - IFT
Resumo:
Pós-graduação em Engenharia Mecânica - FEG
Resumo:
Bio-molecular computing, 'computations performed by bio-molecules', is already challenging traditional approaches to computation both theoretically and technologically. Often placed within the wider context of ´bio-inspired' or 'natural' or even 'unconventional' computing, the study of natural and artificial molecular computations is adding to our understanding of biology, physical sciences and computer science well beyond the framework of existing design and implementation paradigms. In this introduction, We wish to outline the current scope of the field and assemble some basic arguments that, bio-molecular computation is of central importance to computer science, physical sciences and biology using HOL - Higher Order Logic. HOL is used as the computational tool in our R&D work. DNA was analyzed as a chemical computing engine, in our effort to develop novel formalisms to understand the molecular scale bio-chemical computing behavior using HOL. In our view, our focus is one of the pioneering efforts in this promising domain of nano-bio scale chemical information processing dynamics.
Resumo:
This paper presents numerical modeling of a turbulent natural gas flow through a non-premixed industrial burner of a slab reheating furnace. The furnace is equipped with diffusion side swirl burners capable of utilizing natural gas or coke oven gas alternatively through the same nozzles. The study is focused on one of the burners of the preheating zone. Computational Fluid Dynamics simulation has been used to predict the burner orifice turbulent flow. Flow rate and pressure at burner upstream were validated by experimental measurements. The outcomes of the numerical modeling are analyzed for the different turbulence models in terms of pressure drop, velocity profiles, and orifice discharge coefficient. The standard, RNG, and Realizable k-epsilon models and Reynolds Stress Model (RSM) have been used. The main purpose of the numerical investigation is to determine the turbulence model that more consistently reproduces the experimental results of the flow through an industrial non-premixed burner orifice. The comparisons between simulations indicate that all the models tested satisfactorily and represent the experimental conditions. However, the Realizable k-epsilon model seems to be the most appropriate turbulence model, since it provides results that are quite similar to the RSM and RNG k-epsilon models, requiring only slightly more computational power than the standard k-epsilon model. (C) 2014 Elsevier Ltd. All rights reserved.
Resumo:
A number of studies have demonstrated that simple elastic network models can reproduce experimental B-factors, providing insights into the structure-function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B-factors. Elastic network models are built on the experimental C coordinates, and they only take the pairs of C atoms within a given cutoff distance r(c) into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119-129. (c) 2013 Wiley Periodicals, Inc.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave (GW) astrophysics communities. The purpose of NINJA is to study the ability to detect GWs emitted from merging binary black holes (BBH) and recover their parameters with next-generation GW observatories. We report here on the results of the second NINJA project, NINJA-2, which employs 60 complete BBH hybrid waveforms consisting of a numerical portion modelling the late inspiral, merger, and ringdown stitched to a post-Newtonian portion modelling the early inspiral. In a 'blind injection challenge' similar to that conducted in recent Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo science runs, we added seven hybrid waveforms to two months of data recoloured to predictions of Advanced LIGO (aLIGO) and Advanced Virgo (AdV) sensitivity curves during their first observing runs. The resulting data was analysed by GW detection algorithms and 6 of the waveforms were recovered with false alarm rates smaller than 1 in a thousand years. Parameter-estimation algorithms were run on each of these waveforms to explore the ability to constrain the masses, component angular momenta and sky position of these waveforms. We find that the strong degeneracy between the mass ratio and the BHs' angular momenta will make it difficult to precisely estimate these parameters with aLIGO and AdV. We also perform a large-scale Monte Carlo study to assess the ability to recover each of the 60 hybrid waveforms with early aLIGO and AdV sensitivity curves. Our results predict that early aLIGO and AdV will have a volume-weighted average sensitive distance of 300 Mpc (1 Gpc) for 10M circle dot + 10M circle dot (50M circle dot + 50M circle dot) BBH coalescences. We demonstrate that neglecting the component angular momenta in the waveform models used in matched-filtering will result in a reduction in sensitivity for systems with large component angular momenta. This reduction is estimated to be up to similar to 15% for 50M circle dot + 50M circle dot BBH coalescences with almost maximal angular momenta aligned with the orbit when using early aLIGO and AdV sensitivity curves.
Resumo:
Convergence to a period one fixed point is investigated for both logistic and cubic maps. For the logistic map the relaxation to the fixed point is considered near a transcritical bifurcation while for the cubic map it is near a pitchfork bifurcation. We confirmed that the convergence to the fixed point in both logistic and cubic maps for a region close to the fixed point goes exponentially fast to the fixed point and with a relaxation time described by a power law of exponent -1. At the bifurcation point, the exponent is not universal and depends on the type of the bifurcation as well as on the nonlinearity of the map.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
The FENE-CR model is investigated through a numerical algorithm to simulate the time-dependent moving free surface flow produced by a jet impinging on a flat surface. The objective is to demonstrate that by increasing the extensibility parameter L, the numerical solutions converge to the solutions obtained with the Oldroyd-B model. The governing equations are solved by an established free surface flow solver based on the finite difference and marker-and-cell methods. Numerical predictions of the extensional viscosity obtained with several values of the parameter L are presented. The results show that if the extensibility parameter L is sufficiently large then the extensional viscosities obtained with the FENE-CR model approximate the corresponding Oldroyd-B viscosity. Moreover, the flow from a jet impinging on a flat surface is simulated with various values of the extensibility parameter L and the fluid flow visualizations display convergence to the Oldroyd-B jet flow results.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.
Resumo:
An excitation force that is not influenced by the system state is said to be an ideal energy source. In real situations, a direct and feedback coupling between the excitation source and the system must always exist at a certain level. This manifestation of the law of conservation of energy is known as the Sommerfeld effect. In the case of obtaining a mathematical model for such a system, additional equations are usually necessary to describe the vibration sources with limited power and its coupling with the mechanical system. In this work, a cantilever beam and a non-ideal DC motor fixed to its free end are analyzed. The motor has an unbalanced mass that provides excitation to the system which is proportional to the current applied to the motor. During the coast up operation of the motor, if the drive power is increased slowly, making the excitation frequency pass through the first natural frequency of the beam, the DC motor speed will remain the same until it suddenly jumps to a much higher value (simultaneously its amplitude jumps to a much lower value) upon exceeding a critical input power. It was found that the Sommerfeld effect depends on some system parameters and the motor operational procedures. These parameters are explored to avoid the resonance capture in the Sommerfeld effect. Numerical simulations and experimental tests are used to help gather insight of this dynamic behavior. (C) 2014 Elsevier Ltd. All rights reserved.