A cross-section averaged Advection-Dispersion equation (ADE) model was developed to simulate the transport of fertilizer in furrow irrigation. The advection and dispersion processes were solved separately by implementing the method of the characteristics with cubic spline interpolation (and natural boundary condition) and weighted finite difference scheme respectively. A zero-flux boundary condition during advance and an advective gradient at the downstream end of an open furrow were established. Local pseudo-steady state was assumed in order to apply Fischer's longitudinal dispersion equation under non-uniform and unsteady furrow flow conditions. Also, several parameters were used to evaluate the ADE model and fertigation performance.A field tracer experiment in two types of downstream-end furrow and two treatments was conducted and described. Infiltration and roughness parameters were calibrated by implementing a volume balance approach. The calibrated parameters were used as input data to run the surface irrigation model (SRFR). The roughness coefficient was 0.045 for wheel and 0.055 for non-wheel furrow treatment for bare soil. The root mean square error (RMSE) comparing the computed and observed infiltrated volume was in the range of 0.09-0.38 m3. The close match between simulated and observed data indicates an acceptable calibration. Pulses of fertilizer injected at the head end of four furrows each having unique management characteristics were simulated satisfactorily during the entire duration of the irrigation event. The constant value of the longitudinal dispersion coefficient was 1 m2 min-1 and yielded an acceptable space-time evolution of the pulses of tracer injected. Similar results for the dispersion coefficient were obtained with Fischer's equation in non-uniform and unsteady stream flow conditions in the furrow. An evaluation of several fertigation strategies for furrow systems indicated that fertigation by pulses could help reduce leaching and runoff losses in surface irrigation systems.

An initial-value problem consists of an ordinary differential equation subject to an initial condition. The right-hand side of the differential equation can be interpreted as additively split when it is comprised of the sum of two or more contributing factors. For instance, the right-hand sides of initial-value problems derived from advection-diffusion-reaction equations are comprised of the sum of terms emanating from three distinct physical processes: advection, diffusion, and reaction. In some cases, solutions to initial-value problems can be calculated analytically, but when an analytic solution is unknown or nonexistent, methods of numerical integration are used to calculate solutions. The runtime performance of numerical methods is problem dependent; therefore, one must choose an appropriate numerical method to achieve favourable performance, according to characteristics of the problem. Additive methods of numerical integration apply distinct methods to the distinct contributing factors of an additively split problem. Treating the contributing factors with methods that are known to perform well on them individually has the potential to yield an additive method that outperforms single methods applied to the entire (unsplit) problem. Splittings of the right-hand side can be physics-based, i.e., based on physical characteristics of the problem, such as advection, diffusion, or reaction terms. Splittings can also be based on linearization, called Jacobian splitting in this thesis, where the linearized part of the problem is treated with one method and the rest of the problem is treated with another. A comparison of these splitting techniques is performed by applying a set of additive methods to a test suite of problems. Many common non-additive methods are also included to serve as a performance baseline. To perform this numerical study, a problem-solving environment was developed to evaluate permutations of problems, methods, and their associated parameters. The test suite is comprised of several distinct advection-diffusion-reaction equations that have been chosen to represent a wide range of common problem characteristics. When solving split problems in the test suite, it is found that additive Runge–Kutta methods of orders three, four, and five using Jacobian splitting generally outperform those same methods using physics-based splitting. These results provide evidence that Jacobian splitting is an effective approach when solving such initial-value problems in practice.

A presente dissertação apresenta uma análise da presença de componentes estocásticas na equação de advecção-difusão, e como estas influenciam a estabilidade da solução. Para tal, a equação de advecção-difusão determinística com fonte contínua idealizada é resolvida através da transformada de Fourier. Adiante, a equação determinística é combinada com componentes estocásticas na velocidade do vento, comprimento de rugosidade e coeficiente de difusão turbulenta vertical. Além disso, é considerada uma permeabilidade parcial nos contornos verticais, de modo que parte do poluente ultrapassa a camada limite atmosférica ou o solo, e outra parte reflete e retorna `a atmosfera. Os resultados obtidos foram validados com os dados do experimento de Hanford. / The present work presents an analysis of the presence of stochastic components in the advection-diffusion equation and how they influence the stability of the solution. For this purpose, the deterministic advection-diffusion equation with idealized continuous source is solved by Fourier transform. Further, the deterministic equation is combined with stochastic components in the wind speed, the roughness and the vertical eddy diffusion coefficient. Moreover, partial permeability is considered in the vertical contours, in the sense that part of the pollutant leaks out of the atmospheric boundary layer or into the soil, and a part is reflected back into the atmosphere. Results were validated with the Hanford experimental data.

O presente trabalho propõe um novo modelo para dispersão de poluentes na atmosfera, tal modelo foi idealizado no trabalho de dissertação da autora e continuou-se seu desenvolvimento nesta pesquisa. O modelo é baseado na solução semi-analítica da equação de advecção-difusão para emissão contínua, com resolução através do método de separação de variáveis e da transformada de Fourier. As condições de contorno são tratadas como infinitas reflexões do poluente no solo e no topo da camada limite atmosférica. Adiante, estas reflexões são utilizadas de modo parcial, na tentativa de considerar fenômenos da dispersão que não podem ser explicitados no modelo determinístico, de forma que os contornos podem ser entendidos como estocásticos, ou seja, pode-se interpretar os contornos como uma amostragem de uma distribuição. Além disso, é realizada uma otimização nos contornos parcialmente reflexivos, com o objetivo de desenvolver uma metodologia de otimização e determinar os valores ótimos para a reflexão parcial. Os resultados obtidos foram, primeiramente, comparados com os experimentos de Copenhagen e Hanford. Posteriormente, comparou-se o modelo com dados de concentração coletados em uma fábrica de celulose, a CMPC Celulose Riograndense. Simulou-se, também, a dispersão de poluentes emitidos por uma usina termelétrica no Brasil, que faz parte do programa de pesquisa e desenvolvimento tecnológico do setor de energia elétrica da Agência Nacional de Energia Elétrica (ANEEL). / The present work proposes a new model for pollutant dispersion in the atmosphere, this model was idealized in the dissertation work of the author and continued its development in this research. The model is based on the semi-analytic solution of the advectiondiffusion equation for continuous emission, with resolution through the method of separation of variables and the Fourier transform. The boundary conditions are treated as infinite reflections of the pollutant in the soil and at the top of the atmospheric boundary layer. These reflections are used in a partial way in the attempt to consider phenomena of dispersion that can not be explained in the deterministic model, so that the boundaries can be understood as stochastic, that is, one can interpret the boundaries as a sampling of a distribution. In addition, an optimization is performed in the partially reflective boundaries, with the purpose of developing an optimization methodology and determining the optimal values for the partial reflection. The results obtained were firstly compared with the experiments of Copenhagen and Hanford. Subsequently, the model was compared with concentration data collected at a cellulose production plant. The dispersion of pollutants emitted by a thermoelectric plant in Brazil was also simulated, which is part of the research and technological development program of the electric energy sector of the National Electric Energy Agency (ANEEL).

Questões ambientais estão no centro das discussões nas últimas décadas. A poluição atmosférica, causada pela expansão pós-revolução industrial fez surgir a necessidade de aprender a descrever, usando modelos matemáticos, esse fenômeno. Com esse conhecimento pode-se propor soluções que mitiguem a poluição e os danos colaterais causados ao ambiente. A dispersão de poluentes modelada por soluções analíticas, a partir das equações de advecção-difusão oferecem um conhecimento sobre cada componente que constrói a equação, característica inexistente em outras abordagens, como a numérica. Entretanto ela era incapaz de descrever propriedades que se referem à turbulência, as estruturas coerentes, causadas por componentes não-lineares suprimidas por construção das equações governantes do modelo. Este trabalho estudou uma forma de recuperar características associadas à turbulência através de uma componente fundamental em estruturas coerentes, a fase. Essa é incluída no modelo que passa a descrever manifestações da turbulência em processos de dispersão através de flutuações de pequena escala na concentração da solução do modelo sesquilinear, que é determinístico-estocástico. No decorrer do trabalho há um estudo através de variações de parâmetros para compreender os efeitos da fase no modelo. Ele também foi aplicado ao experimento de Copenhagen e a dois cenários reais com a intenção de compreender o modelo frente à variáveis micrometeorológicas assim como aprimorá-lo para simular a dispersão de poluentes oriundos de fontes de forma realística. / Environmental issues have been at the center of discussions in the last few decades. Atmospheric pollution, caused by post-industrial revolution, has increased the necessity to describe, using mathematical models, this phenomenon. With this knowledge is possible to propose solutions mitigating the pollution and collateral damages caused in the environment. The pollutant dispersion modeled by analytical solutions, from advection-diffusion equations, offers a knowledge about each component that constructs the equation, a characteristic that does not exist in other approaches, such as numerical. However it was unable to describe properties that refer to turbulence, coherent structures, caused by nonlinear components suppressed by constructing the model governing equations. This work studied a way to recover characteristics associated with turbulence through a fundamental component in coherent structures, the phase. This is included in the model which describes manifestations of turbulence in the dispersion process through the presence of small-scale concentration fluctuations in the sesquilinear model, which is deterministicstochastic. In the course of this work there is a study through variations of parameters to understand the phase effects in the model. It was also applied to Copenhagen experiment and to two real scenarios with the intention of understanding the model regarding micrometeorological variables as well as improving it to simulate the pollutant dispersion from sources in a realistic way.

We study heat transfer in one dimension with and without convection, also called advection-diffusion. This is done using the Finite Element Method (FEM) to discretise the mathematical model, i.e. the heat equation. The results are compared to analytic Fourier series solutions. Our main result is that the FEM could be used to better model the heat transfer which allow for more accurate models than today's use of steady state models.

A presente dissertação apresenta uma análise da presença de componentes estocásticas na equação de advecção-difusão, e como estas influenciam a estabilidade da solução. Para tal, a equação de advecção-difusão determinística com fonte contínua idealizada é resolvida através da transformada de Fourier. Adiante, a equação determinística é combinada com componentes estocásticas na velocidade do vento, comprimento de rugosidade e coeficiente de difusão turbulenta vertical. Além disso, é considerada uma permeabilidade parcial nos contornos verticais, de modo que parte do poluente ultrapassa a camada limite atmosférica ou o solo, e outra parte reflete e retorna `a atmosfera. Os resultados obtidos foram validados com os dados do experimento de Hanford. / The present work presents an analysis of the presence of stochastic components in the advection-diffusion equation and how they influence the stability of the solution. For this purpose, the deterministic advection-diffusion equation with idealized continuous source is solved by Fourier transform. Further, the deterministic equation is combined with stochastic components in the wind speed, the roughness and the vertical eddy diffusion coefficient. Moreover, partial permeability is considered in the vertical contours, in the sense that part of the pollutant leaks out of the atmospheric boundary layer or into the soil, and a part is reflected back into the atmosphere. Results were validated with the Hanford experimental data.

In this dissertation, we examine an advection diffusion model for insects inhabiting a spatially heterogeneous environment and moving toward a more favorable environment. We first study the effects of adding a term describing drift or advection toward a favorable environment to diffusion models for population dynamics. The diffusion model is a basic linear two-dimensional diffusion equation describing local dispersal of species. The mathematical advection terms are taken to be Fickian and describe directed movement of the population toward the favorable environment. For this model, the landscape is composed of one homogeneous habitat patch embedded in a spatially heterogeneous environment and the boundary of the habitat inhabited by the population acts as a lethal edge. We also derived the mean occupancy time and the boundary flux of the habitat patch. The diffusion rate and advection parameters of the advection diffusion model are estimated based on mean occupancy time and boundary flux. We then introduce two methods for the identification of these coefficients in the model as well as the capture rate. These two new methods have some advantages over other methods of estimating those parameters, including reduced computational cost and ease of use in the field. We further examine the statistical properties of new methods through simulation, and discuss how mean occupancy time and boundary flux could be estimated in field experiments.

Questões ambientais estão no centro das discussões nas últimas décadas. A poluição atmosférica, causada pela expansão pós-revolução industrial fez surgir a necessidade de aprender a descrever, usando modelos matemáticos, esse fenômeno. Com esse conhecimento pode-se propor soluções que mitiguem a poluição e os danos colaterais causados ao ambiente. A dispersão de poluentes modelada por soluções analíticas, a partir das equações de advecção-difusão oferecem um conhecimento sobre cada componente que constrói a equação, característica inexistente em outras abordagens, como a numérica. Entretanto ela era incapaz de descrever propriedades que se referem à turbulência, as estruturas coerentes, causadas por componentes não-lineares suprimidas por construção das equações governantes do modelo. Este trabalho estudou uma forma de recuperar características associadas à turbulência através de uma componente fundamental em estruturas coerentes, a fase. Essa é incluída no modelo que passa a descrever manifestações da turbulência em processos de dispersão através de flutuações de pequena escala na concentração da solução do modelo sesquilinear, que é determinístico-estocástico. No decorrer do trabalho há um estudo através de variações de parâmetros para compreender os efeitos da fase no modelo. Ele também foi aplicado ao experimento de Copenhagen e a dois cenários reais com a intenção de compreender o modelo frente à variáveis micrometeorológicas assim como aprimorá-lo para simular a dispersão de poluentes oriundos de fontes de forma realística. / Environmental issues have been at the center of discussions in the last few decades. Atmospheric pollution, caused by post-industrial revolution, has increased the necessity to describe, using mathematical models, this phenomenon. With this knowledge is possible to propose solutions mitigating the pollution and collateral damages caused in the environment. The pollutant dispersion modeled by analytical solutions, from advection-diffusion equations, offers a knowledge about each component that constructs the equation, a characteristic that does not exist in other approaches, such as numerical. However it was unable to describe properties that refer to turbulence, coherent structures, caused by nonlinear components suppressed by constructing the model governing equations. This work studied a way to recover characteristics associated with turbulence through a fundamental component in coherent structures, the phase. This is included in the model which describes manifestations of turbulence in the dispersion process through the presence of small-scale concentration fluctuations in the sesquilinear model, which is deterministicstochastic. In the course of this work there is a study through variations of parameters to understand the phase effects in the model. It was also applied to Copenhagen experiment and to two real scenarios with the intention of understanding the model regarding micrometeorological variables as well as improving it to simulate the pollutant dispersion from sources in a realistic way.

abstract: This thesis considers two problems in the control of robotic swarms. Firstly, it addresses a trajectory planning and task allocation problem for a swarm of resource-constrained robots that cannot localize or communicate with each other and that exhibit stochasticity in their motion and task switching policies. We model the population dynamics of the robotic swarm as a set of advection-diffusion- reaction (ADR) partial differential equations (PDEs). Specifically, we consider a linear parabolic PDE model that is bilinear in the robots' velocity and task-switching rates. These parameters constitute a set of time-dependent control variables that can be optimized and transmitted to the robots prior to their deployment or broadcasted in real time. The planning and allocation problem can then be formulated as a PDE-constrained optimization problem, which we solve using techniques from optimal control. Simulations of a commercial pollination scenario validate the ability of our control approach to drive a robotic swarm to achieve predefined spatial distributions of activity over a closed domain, which may contain obstacles. Secondly, we consider a mapping problem wherein a robotic swarm is deployed over a closed domain and it is necessary to reconstruct the unknown spatial distribution of a feature of interest. The ADR-based primitives result in a coefficient identification problem for the corresponding system of PDEs. To deal with the inherent ill-posedness of the problem, we frame it as an optimization problem. We validate our approach through simulations and show that reconstruction of the spatially-dependent coefficient can be achieved with considerable accuracy using temporal information alone. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2014