Estudo e implementação de modelos de gestão de stocks em sistemas ERP para empresas retalhistas

Dissertação de mestrado em Engenharia de Sistemas

Spanning avalanches in the three-dimensional Gaussian random-field Ising model with metastable dynamics: Field dependence and geometrical properties

Spanning avalanches in the 3D Gaussian Random Field Ising Model (3D-GRFIM) with metastable dynamics at T=0 have been studied. Statistical analysis of the field values for which avalanches occur has enabled a Finite-Size Scaling (FSS) study of the avalanche density to be performed. Furthermore, a direct measurement of the geometrical properties of the avalanches has confirmed an earlier hypothesis that several types of spanning avalanches with two different fractal dimensions coexist at the critical point. We finally compare the phase diagram of the 3D-GRFIM with metastable dynamics with the same model in equilibrium at T=0.

Collective dynamic properties in simple crystals: Influence of the structural disorder

Collective dynamic properties in Lennard-Jones crystals are investigated by molecular dynamics simulation. The study is focused on properties such as the dynamic structure factors, the longitudinal and transverse currents and the density of states. The influence on these properties of the structural disorder is analyzed by comparing the results for one-component crystals with those for liquids and supercooled liquids at analogous conditions. The effects of species-disorder on the collective properties of binary crystals are also discussed.

Self-dynamic structure factor of dense liquids: Theory and simulation

The self-intermediate dynamic structure factor Fs(k,t) of liquid lithium near the melting temperature is calculated by molecular dynamics. The results are compared with the predictions of several theoretical approaches, paying special attention to the Lovesey model and the Wahnstrm and Sjgren mode-coupling theory. To this end the results for the Fs(k,t) second memory function predicted by both models are compared with the ones calculated from the simulations.

Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis.

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Methods for assessment of pre-harvest sprouting in wheat cultivars

The objective of this work was to test methods for pre-harvest sprouting assessment in wheat cultivars. Fourteen wheat cultivars were grown in Londrina and Ponta Grossa municipalities, Paraná state, Brazil. They were sampled at 10 and 17 days after physiological maturity and evaluated using the methods of germination by rainfall simulation (in a greenhouse), in-ear grain sprouting, and grains removed from the ears. The in-ear grain sprouting method allowed the differentiation of cultivars, but showed different resistance levels from the available description of cultivars. The sprouting of grain removed from the ears did not allow a reliable distinction of data on germination in any harvest date or location. The method of rainfall simulation is the most suitable for the assessment of cultivars as to pre-harvest sprouting, regardless of the sampling date and evaluated location.

Development of data sheets for statistical evaluation of fatigue data

To enable a mathematically and physically sound execution of the fatigue test and a correct interpretation of its results, statistical evaluation methods are used to assist in the analysis of fatigue testing data. The main objective of this work is to develop step-by-stepinstructions for statistical analysis of the laboratory fatigue data. The scopeof this project is to provide practical cases about answering the several questions raised in the treatment of test data with application of the methods and formulae in the document IIW-XIII-2138-06 (Best Practice Guide on the Statistical Analysis of Fatigue Data). Generally, the questions in the data sheets involve some aspects: estimation of necessary sample size, verification of the statistical equivalence of the collated sets of data, and determination of characteristic curves in different cases. The series of comprehensive examples which are given in this thesis serve as a demonstration of the various statistical methods to develop a sound procedure to create reliable calculation rules for the fatigue analysis.

Flocking behaviour: Agent-based simulation and hierarchical leadership.

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Statistical Analysis of an SEIR Epidemic Model

This thesis was focussed on statistical analysis methods and proposes the use of Bayesian inference to extract information contained in experimental data by estimating Ebola model parameters. The model is a system of differential equations expressing the behavior and dynamics of Ebola. Two sets of data (onset and death data) were both used to estimate parameters, which has not been done by previous researchers in (Chowell, 2004). To be able to use both data, a new version of the model has been built. Model parameters have been estimated and then used to calculate the basic reproduction number and to study the disease-free equilibrium. Estimates of the parameters were useful to determine how well the model fits the data and how good estimates were, in terms of the information they provided about the possible relationship between variables. The solution showed that Ebola model fits the observed onset data at 98.95% and the observed death data at 93.6%. Since Bayesian inference can not be performed analytically, the Markov chain Monte Carlo approach has been used to generate samples from the posterior distribution over parameters. Samples have been used to check the accuracy of the model and other characteristics of the target posteriors.

Monte Carlo simulation of x-ray emission by kilovolt electron bombardment

A physical model for the simulation of x-ray emission spectra from samples irradiated with kilovolt electron beams is proposed. Inner shell ionization by electron impact is described by means of total cross sections evaluated from an optical-data model. A double differential cross section is proposed for bremsstrahlung emission, which reproduces the radiative stopping powers derived from the partial wave calculations of Kissel, Quarles and Pratt [At. Data Nucl. Data Tables 28, 381 (1983)]. These ionization and radiative cross sections have been introduced into a general-purpose Monte Carlo code, which performs simulation of coupled electron and photon transport for arbitrary materials. To improve the efficiency of the simulation, interaction forcing, a variance reduction technique, has been applied for both ionizing collisions and radiative events. The reliability of simulated x-ray spectra is analyzed by comparing simulation results with electron probe measurements.

An Engineering Solution for using Coarse Meshes in the Simulation of Delamination with Cohesive Zone Models

This paper presents a methodology to determine the parameters used in the simulation of delamination in composite materials using decohesion finite elements. A closed-form expression is developed to define the stiffness of the cohesive layer. A novel procedure that allows the use of coarser meshes of decohesion elements in large-scale computations is proposed. The procedure ensures that the energy dissipated by the fracture process is correctly computed. It is shown that coarse-meshed models defined using the approach proposed here yield the same results as the models with finer meshes normally used in the simulation of fracture processes

Simulation of Delamination Propagation in Composites Under High-Cycle Fatigue by Means of Cohesive-Zone Models

A damage model for the simulation of delamination propagation under high-cycle fatigue loading is proposed. The basis for the formulation is a cohesive law that links fracture and damage mechanics to establish the evolution of the damage variable in terms of the crack growth rate dA/dN. The damage state is obtained as a function of the loading conditions as well as the experimentally-determined coefficients of the Paris Law crack propagation rates for the material. It is shown that by using the constitutive fatigue damage model in a structural analysis, experimental results can be reproduced without the need of additional model-specific curve-fitting parameters

An Interface Damage Model for the Simulation of Delamination Under Variable-Mode Ratio in Composite Materials

A thermodynamically consistent damage model for the simulation of progressive delamination under variable mode ratio is presented. The model is formulated in the context of the Damage Mechanics. The constitutive equation that results from the definition of the free energy as a function of a damage variable is used to model the initiation and propagation of delamination. A new delamination initiation criterion is developed to assure that the formulation can account for changes in the loading mode in a thermodynamically consistent way. The formulation proposed accounts for crack closure effets avoiding interfacial penetration of two adjacent layers aftercomplete decohesion. The model is implemented in a finite element formulation. The numerical predictions given by the model are compared with experimental results

Simulation model of wind turbine gearbox and lubrication system

As increasing efficiency of a wind turbine gearbox, more power can be transferred from rotor blades to generator and less power is used to cause wear and heating in the gearbox. By using a simulation model, behavior of the gearbox can be studied before creating expensive prototypes. The objective of the thesis is to model a wind turbine gearbox and its lubrication system to study power losses and heat transfer inside the gearbox and to study the simulation methods of the used software. Software used to create the simulation model is Siemens LMS Imagine.Lab AMESim, which can be used to create one-dimensional mechatronic system simulation models from different fields of engineering. When combining components from different libraries it is possible to create a simulation model, which includes mechanical, thermal and hydraulic models of the gearbox. Results for mechanical, thermal, and hydraulic simulations are presented in the thesis. Due to the large scale of the wind turbine gearbox and the amount of power transmitted, power loss calculations from AMESim software are inaccurate and power losses are modelled as constant efficiency for each gear mesh. Starting values for simulation in thermal and hydraulic simulations were chosen from test measurements and from empirical study as compact and complex design of gearbox prevents accurate test measurements. In further studies to increase the accuracy of the simulation model, components used for power loss calculations needs to be modified and values for unknown variables are needed to be solved through accurate test measurements.