Impactos de regulações ambientais sobre o transporte de cargas no Brasil: uma análise para o transporte de soja

O aumento da concentração de gases de efeito estufa na atmosfera levou a uma preocupação de como se reduzir as emissões destes gases. Desta preocupação surgiram instrumentos de regulação a fim de reduzir ou controlar os níveis de poluição. Dentro deste contexto, esta pesquisa analisou o setor de transportes de cargas, com ênfase no transporte de soja. No Brasil, o setor de transportes é um dos principais responsáveis pelas emissões de gases de efeito estufa provenientes da queima de combustíveis fósseis. No setor de transportes, as emissões diferem entre os modais, sendo que as ferrovias e hidrovias poluem menos que as rodovias. Desta forma, simulou-se por meio de um modelo de programação linear se a adoção de medidas regulatórias sobre as emissões de CO2 traria uma alteração no uso das ferrovias e hidrovias. Uma das constatações, ao se utilizar o modelo de Minimização de Fluxo de Custo Mínimo para o transporte de soja em 2013, foi que a capacidade de embarque nos terminais ferroviários e hidroviários desempenha um papel fundamental na redução das emissões de CO2. Se não houver capacidade suficiente, a adoção de uma taxa pode não provocar a redução das emissões. No caso do sistema de compra e crédito de carbono, seria necessária a compra de créditos de carbono, numa situação em que a capacidade de embarque nos terminais intermodais seja limitada. Verificou-se, ainda, que melhorias na infraestrutura podem desempenhar um papel mitigador das emissões. Um aumento da capacidade dos terminais ferroviários e hidroviários existentes, bem como o aumento da capacidade dos portos, pode provocar a redução das emissões de CO2. Se os projetos de expansão das ferrovias e hidrovias desenvolvidos por órgãos governamentais saírem do papel, pode-se chegar a uma redução de pouco mais de 50% das emissões de CO2. Consideraram-se ainda quais seriam os efeitos do aumento do uso de biodiesel como combustível e percebeu-se que seria possível obter reduções tanto das emissões quanto do custo de transporte. Efeitos semelhantes foram encontrados quando se simulou um aumento da eficiência energética. Por fim, percebeu-se nesta pesquisa que a adoção de uma taxa não traria tantos benefícios, econômicos e ambientais, quanto a melhoria da infraestrutura logística do país.

Estratégias de comercialização e investimento, com ênfase em energias renováveis, suportadas por modelos de otimização especializados para avaliação estocástica de risco x retorno.

A comercialização de energia elétrica de fontes renováveis, ordinariamente, constitui-se uma atividade em que as operações são estruturadas sob condições de incerteza, por exemplo, em relação ao preço \"spot\" no mercado de curto prazo e a geração de energia dos empreendimentos. Deriva desse fato a busca dos agentes pela formulação de estratégias e utilização de ferramentais para auxiliá-los em suas tomadas de decisão, visando não somente o retorno financeiro, mas também à mitigação dos riscos envolvidos. Análises de investimentos em fontes renováveis compartilham de desafios similares. Na literatura, o estudo da tomada de decisão considerada ótima sob condições de incerteza se dá por meio da aplicação de técnicas de programação estocástica, que viabiliza a modelagem de problemas com variáveis randômicas e a obtenção de soluções racionais, de interesse para o investidor. Esses modelos permitem a incorporação de métricas de risco, como por exemplo, o Conditional Value-at-Risk, a fim de se obter soluções ótimas que ponderem a expectativa de resultado financeiro e o risco associado da operação, onde a aversão ao risco do agente torna-se um condicionante fundamental. O objetivo principal da Tese - sob a ótica dos agentes geradores, consumidores e comercializadores - é: (i) desenvolver e implementar modelos de otimização em programação linear estocástica com métrica CVaR associada, customizados para cada um desses agentes; e (ii) aplicá-los na análise estratégica de operações como forma de apresentar alternativas factíveis à gestão das atividades desses agentes e contribuir com a proposição de um instrumento conceitualmente robusto e amigável ao usuário, para utilização por parte das empresas. Nesse contexto, como antes frisado, dá-se ênfase na análise do risco financeiro dessas operações por meio da aplicação do CVaR e com base na aversão ao risco do agente. Considera-se as fontes renováveis hídrica e eólica como opções de ativos de geração, de forma a estudar o efeito de complementaridade entre fontes distintas e entre sites distintos da mesma fonte, avaliando-se os rebatimentos nas operações.

Optimización (curso 2011-2012)

Material docente de la asignatura «Simulación y Optimización de procesos químicos». Parte de Optimización OPTIMIZACIÓN TEMA 6. Conceptos Básicos 6.1 Introducción. Desarrollo histórico de la optimización de procesos. 6.2 Funciones y regiones cóncavas y convexas. 6.3 Optimización sin restricciones. 6.4 Optimización con restricciones de igualdad y desigualdad. Condiciones de optimalidad de Karush Khun Tucker 6.5 Interpretación de los Multiplicadores de Lagrange. TEMA 7. Programación lineal 7.1 Introducción. Planteamiento del problema en forma canónica y forma estándar. 7.2 Teoremas de la programación lineal 7.3 Resolución gráfica 7.4 Resolución en forma de tabla. El método simplex. 7.5 Variables artificiales. Método de la Gran M y método de las dos fases. 7.6 Conceptos básicos de dualidad. TEMA 8. Programación no lineal 8.1 Repaso de métodos numéricos de optimización sin restricciones 8.2 Optimización con restricciones. Fundamento de los métodos de programación cuadrática sucesiva y de gradiente reducido. TEMA 9. Introducción a la programación lineal y no lineal con variables discretas. 9.1 Conceptos básicos para la resolución de problemas lineales con variables discretas.(MILP, mixed integer linear programming) 9.2 Introducción a la programación no lineal con variables continuas y discretas (MINLP mixed integer non linear programming) 9.3 Modelado de problemas con variables binarias: 9.3.1 Conceptos básicos de álgebra de Boole 9.3.2 Transformación de expresiones lógicas a expresiones algebraicas 9.3.3 Modelado con variables discretas y continuas. Formulación de envolvente convexa y de la gran M.

Combined simulation-optimization methodology for the design of environmental conscious absorption systems

This work addresses the optimization of ammonia–water absorption cycles for cooling and refrigeration applications with economic and environmental concerns. Our approach combines the capabilities of process simulation, multi-objective optimization (MOO), cost analysis and life cycle assessment (LCA). The optimization task is posed in mathematical terms as a multi-objective mixed-integer nonlinear program (moMINLP) that seeks to minimize the total annualized cost and environmental impact of the cycle. This moMINLP is solved by an outer-approximation strategy that iterates between primal nonlinear programming (NLP) subproblems with fixed binaries and a tailored mixed-integer linear programming (MILP) model. The capabilities of our approach are illustrated through its application to an ammonia–water absorption cycle used in cooling and refrigeration applications.

Dyakonons in hyperbolic metamaterials

We have analyzed surface-wave propagation that takes place at the boundary between an isotropic medium and a semi-infinite metal-dielectric periodic medium cut normally to the layers. In the range of frequencies where the periodic medium shows hyperbolic space dispersion, hybridization of surface waves (dyakonons) occurs. At low to moderate frequencies, dyakonons enable tighter confinement near the interface in comparison with pure SPPs. On the other hand, a distinct regime governs dispersion of dyakonons at higher frequencies.

Engineered surface waves in hyperbolic metamaterials

We analyzed surface-wave propagation that takes place at the boundary between a semi-infinite dielectric and a multilayered metamaterial, the latter with indefinite permittivity and cut normally to the layers. Known hyperbolization of the dispersion curve is discussed within distinct spectral regimes, including the role of the surrounding material. Hybridization of surface waves enable tighter confinement near the interface in comparison with pure-TM surface-plasmon polaritons. We demonstrate that the effective-medium approach deviates severely in practical implementations. By using the finite-element method, we predict the existence of long-range oblique surface waves.

Oblique surface waves at an interface between a metal–dielectric superlattice and an isotropic dielectric

We investigate the existence and dispersion characteristics of surface waves that propagate at an interface between a metal–dielectric superlattice and an isotropic dielectric. Within the long-wavelength limit, when the effective-medium (EM) approximation is valid, the superlattice behaves like a uniaxial plasmonic crystal with the main optical axes perpendicular to the metal–dielectric interfaces. We demonstrate that if such a semi-infinite plasmonic crystal is cut normally to the layer interfaces and brought into contact with a semi-infinite dielectric, a new type of surface mode can appear. Such modes can propagate obliquely to the optical axes if favorable conditions regarding the thickness of the layers and the dielectric permittivities of the constituent materials are met. We show that losses within the metallic layers can be substantially reduced by making the layers sufficiently thin. At the same time, a dramatic enlargement of the range of angles for oblique propagation of the new surface modes is observed. This can lead, however, to field non-locality and consequently to failure of the EM approximation.

Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes

In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer® with an external NLP solver implemented in Matlab®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Propagation of Dyakonon Wave-Packets at the Boundary of Metallodielectric Lattices

We rigorously analyze the propagation of localized surface waves that takes place at the boundary between a semi-infinite layered metal-dielectric (MD) nanostructure cut normally to the layers and a isotropic medium. It is demonstrated that Dyakonov-like surface waves (also coined dyakonons) with hybrid polarization may propagate in a wide angular range. As a consequence, dyakonon-based wave-packets (DWPs) may feature sub-wavelength beamwidths. Due to the hyperbolic-dispersion regime in plasmonic crystals, supported DWPs are still in the canalization regime. The apparent quadratic beam spreading, however, is driven by dissipation effects in metal.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Isobutane Alkylation Process Synthesis by means of Hybrid Simulation-Multiobjective Optimization

Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the general public. For the resolution of the problem we employed a hybrid simulation- optimization methodology, i.e., the superstructure of the process was developed directly in a chemical process simulator connected to a state of the art optimizer. The model was formulated as a GDP and solved using a logic algorithm that avoids the reformulation as MINLP -Mixed Integer Non Linear Programming-. Our research gave us Pareto curves compounded by three different configurations where the LCA has been assessed by two different parameters: global warming potential and ecoindicator-99.

Quantum spin Hall phase in multilayer graphene

The so-called quantum spin Hall phase is a topologically nontrivial insulating phase that is predicted to appear in graphene and graphenelike systems. In this paper we address the question of whether this topological property persists in multilayered systems. We consider two situations: purely multilayer graphene and heterostructures where graphene is encapsulated by trivial insulators with a strong spin-orbit coupling. We use a four-orbital tight-binding model that includes full atomic spin-orbit coupling and we calculate the Z2 topological invariant of the bulk states as well as the edge states of semi-infinite crystals with armchair termination. For homogeneous multilayers we find that even when the spin-orbit interaction opens a gap for all possible stackings, only those with an odd number of layers host gapless edge states while those with an even number of layers are trivial insulators. For heterostructures where graphene is encapsulated by trivial insulators, it turns out that interlayer coupling is able to induce a topological gap whose size is controlled by the spin-orbit coupling of the encapsulating materials, indicating that the quantum spin Hall phase can be induced by proximity to trivial insulators.

An analog input-output system for the ILLIAC II.

Issued also as thesis, University of Illinois.