A Higher order and stable method for the numerical integration of Random Differential Equations

Trabalho apresentado no Congresso Nacional de Matemática Aplicada à Indústria, 18 a 21 de novembro de 2014, Caldas Novas - Goiás

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Simulation of the energy performance of maize production integrated to pig farming

Foi avaliado o desempenho energético da suinocultura integrada à produção de milho em grão em sistema de plantio direto mecanizado. Nesta concepção de integração proposta, os dejetos suínos são utilizados como fertilizantes na produção de milho. O sistema foi delimitado envolvendo as atividades associadas ao manejo dos suínos e de produção do milho (manejo do solo, cultivo e colheita). O período de análise considerado foi de um ano, o que possibilita a produção de três lotes de suínos e duas safras de milho. Para avaliar o desempenho energético, foram criados três indicadores: eficiência energética, eficiência de uso de fontes não renováveis e o custo de energia não renovável para a produção de proteína. As entradas energéticas são compostas pelos insumos e pela infraestrutura, utilizados na criação dos suínos e na produção de milho, e pela radiação solar incidente no agrossistema. Já as saídas são representadas pelos seus produtos (suínos terminados e o milho). Os resultados obtidos nas simulações apontam que a integração melhora o desempenho energético das granjas suinícolas, aumentando a eficiência energética (186%) e a eficiência não renovável (352%), além de reduzir o custo de energia não renovável para a produção de proteína (‑58%).

Simulation of dynamic pinion course using Runge-Kutta's method and impact modeling

Once defined the relationship between the Starter Motor components and their functions, it is possible to develop a mathematical model capable to predict the Starter behavior during operation. One important aspect is the engagement system behavior. The development of a mathematical tool capable of predicting it is a valuable step in order to reduce the design time, cost and engineering efforts. A mathematical model, represented by differential equations, can be developed using physics laws, evaluating force balance and energy flow through the systems degrees of freedom. Another important physical aspect to be considered in this modeling is the impact conditions (particularly on the pinion and ring-gear contact). This work is a report of those equations application on available mathematical software and the resolution of those equations by Runge-Kutta's numerical integration method, in order to build an accessible engineering tool. Copyright © 2011 SAE International.

A NS-2 simulation model for DNP3 protocol over IEEE 802.15.4 wireless protocol toward low cost simulation of Smart Grid applications

Faced with an imminent restructuring of the electric power system, over the past few years many countries have invested in a new paradigm known as Smart Grid. This paradigm targets optimization and automation of electric power network, using advanced information and communication technologies. Among the main communication protocols for Smart Grids we have the DNP3 protocol, which provides secure data transmission with moderate rates. The IEEE 802.15.4 is another communication protocol also widely used in Smart Grid, especially in the so-called Home Area Network (HAN). Thus, many applications of Smart Grid depends on the interaction of these two protocols. This paper proposes modeling, in the traditional network simulator NS-2, the integration of DNP3 protocol and the IEEE 802.15.4 wireless standard for low cost simulations of Smart Grid applications.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Computational simulation of the flow-induced vibration of a circular cylinder subjected to wake interference

In this work, we considered the flow around two circular cylinders of equal diameter placed in tandem with respect to the incident uniform flow. The upstream cylinder was fixed and the downstream cylinder was completely free to move in the cross-stream direction, with no spring or damper attached to it. The centre-to-centre distance between the cylinders was four diameters, and the Reynolds number was varied from 100 to 645. We performed two- and three-dimensional simulations of this flow using a Spectral/hp element method to discretise the flow equations, coupled to a simple Newmark integration routine that solves the equation of the dynamics of the cylinder. The differences of the behaviours observed in the two- and three-dimensional simulations are highlighted and the data is analysed under the light of previously published experimental results obtained for higher Reynolds numbers.

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.

Numerische Integration, angewandt bei der Inferenz in Zustandsraummodellen

In dieser Arbeit werden neuere methodische Entwicklungen aus dem Bereich der Numerischen Integration für die näherungsweise Berechnung von Zustandraummodellen erprobt. Die resultierenden Algorithmen werden bzgl. ihrer Approximationsgüte mit den populären simulationsbasierten Näherungsverfahren verglichen.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Integration of computational models and experimental characterization to study internal frost damage in cementitious materials

The objective of this doctoral research is to investigate the internal frost damage due to crystallization pore pressure in porous cement-based materials by developing computational and experimental characterization tools. As an essential component of the U.S. infrastructure system, the durability of concrete has significant impact on maintenance costs. In cold climates, freeze-thaw damage is a major issue affecting the durability of concrete. The deleterious effects of the freeze-thaw cycle depend on the microscale characteristics of concrete such as the pore sizes and the pore distribution, as well as the environmental conditions. Recent theories attribute internal frost damage of concrete is caused by crystallization pore pressure in the cold environment. The pore structures have significant impact on freeze-thaw durability of cement/concrete samples. The scanning electron microscope (SEM) and transmission X-ray microscopy (TXM) techniques were applied to characterize freeze-thaw damage within pore structure. In the microscale pore system, the crystallization pressures at sub-cooling temperatures were calculated using interface energy balance with thermodynamic analysis. The multi-phase Extended Finite Element Modeling (XFEM) and bilinear Cohesive Zone Modeling (CZM) were developed to simulate the internal frost damage of heterogeneous cement-based material samples. The fracture simulation with these two techniques were validated by comparing the predicted fracture behavior with the captured damage from compact tension (CT) and single-edge notched beam (SEB) bending tests. The study applied the developed computational tools to simulate the internal frost damage caused by ice crystallization with the two dimensional (2-D) SEM and three dimensional (3-D) reconstructed SEM and TXM digital samples. The pore pressure calculated from thermodynamic analysis was input for model simulation. The 2-D and 3-D bilinear CZM predicted the crack initiation and propagation within cement paste microstructure. The favorably predicted crack paths in concrete/cement samples indicate the developed bilinear CZM techniques have the ability to capture crack nucleation and propagation in cement-based material samples with multiphase and associated interface. By comparing the computational prediction with the actual damaged samples, it also indicates that the ice crystallization pressure is the main mechanism for the internal frost damage in cementitious materials.

Curricular Integration of Simulations in Neuroscience - Instructional and Technical Perspectives

In recent years interactive media and tools, like scientific simulations and simulation environments or dynamic data visualizations, became established methods in the neural and cognitive sciences. Hence, university teachers of neural and cognitive sciences are faced with the challenge to integrate these media into the neuroscientific curriculum. Especially simulations and dynamic visualizations offer great opportunities for teachers and learners, since they are both illustrative and explorable. However, simulations bear instructional problems: they are abstract, demand some computer skills and conceptual knowledge about what simulations intend to explain. By following two central questions this article provides an overview on possible approaches to be applied in neuroscience education and opens perspectives for their curricular integration: (i) How can complex scientific media be transformed for educational use in an efficient and (for students on all levels) comprehensible manner and (ii) by what technical infrastructure can this transformation be supported? Exemplified by educational simulations for the neurosciences and their application in courses, answers to these questions are proposed a) by introducing a specific educational simulation approach for the neurosciences b) by introducing an e-learning environment for simulations, and c) by providing examples of curricular integration on different levels which might help academic teachers to integrate newly created or existing interactive educational resources in their courses.

Simulation von Förderprozessen bei Vibrationsförderanlagen

Die erzielbare Fördergeschwindigkeit bei Vibrationsförderern hängt maßgeblich von der Bewegungsfunktion des Förderorganes ab. Für die gezielte Simulation dieser Anlagen mittels der diskreten Elemente Methode (DEM) ist es notwendig die geometrisch vernetzen Förderorgannachbildungen mit praxisrelevanten Bewegungsfunktionen zu beaufschlagen. Der Artikel beschreibt die Einbindung dieser Bewegungsfunktionen in die quellenoffene DEM-Software LIGGGHTS. Während des Simulationsprozesses wird eine Bewegung vernetzter CAD-Modelle durch trigonometrische Reihen ermöglicht.

The IDE geographical simulation model : predicting long-term effects of infrastructure development projects

It is important to be able to predict changes in the location of populations and industries in regions that are in the process of economic integration. The IDE Geographical Simulation Model (IDE-GSM) has been developed with two major objectives: (1) to determine the dynamics of locations of populations and industries in East Asia in the long-term, and (2) to analyze the impact of specific infrastructure projects on the regional economy at sub-national levels. The basic structure of the IDE-GSM is introduced in this article and accompanied with results of test analyses on the effects of the East West Economic Corridor on regions in Continental South East Asia. Results indicate that border costs appear to play a big role in the location choice of populations and industries, often a more important role than physical infrastructures themselves.

Inferring the Effects of Vertical Integration from Entry Games : An Analysis of the Generic Pharmaceutical Industry

This paper introduces a novel method for examining the effects of vertical integration. The basic idea is to estimate the parameters of a vertical entry game. By carefully specifying firms' payoff equations and constructing appropriate tests, it is possible to use estimates on rival profit effects to make inferences about the existence of vertical foreclosure. I estimate the vertical entry model using data from the US generic pharmaceutical industry. The estimates indicate that vertical integration is unlikely to generate anticompetitive foreclosure effects. On the other hand, significant efficiency effects are found to arise from vertical integration. I use the parameter estimates to simulate a policy that bans vertically integrated entry. The simulation results suggest that such a ban is counterproductive; it is likely to reduce entry into smaller markets.