Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

Unmixing hyperspectral intimate mixtures

Proceedings of International Conference Conference Volume 7830 Image and Signal Processing for Remote Sensing XVI Lorenzo Bruzzone Toulouse, France | September 20, 2010

Hyperspectral unmixing based on mixtures of Dirichlet components

This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

Outer Trust-Region Method for Constrained Optimization

Given an algorithm A for solving some mathematical problem based on the iterative solution of simpler subproblems, an outer trust-region (OTR) modification of A is the result of adding a trust-region constraint to each subproblem. The trust-region size is adaptively updated according to the behavior of crucial variables. The new subproblems should not be more complex than the original ones, and the convergence properties of the OTR algorithm should be the same as those of Algorithm A. In the present work, the OTR approach is exploited in connection with the ""greediness phenomenon"" of nonlinear programming. Convergence results for an OTR version of an augmented Lagrangian method for nonconvex constrained optimization are proved, and numerical experiments are presented.

Otimização Topológica com Termo-elasticidade Utilizando Elementos Tri3

This work proposes a formulation for optimization of 2D-structure layouts submitted to mechanic and thermal shipments and applied an h-adaptive filter process which conduced to computational low spend and high definition structural layouts. The main goal of the formulation is to minimize the structure mass submitted to an effective state of stress of von Mises, with stability and lateral restriction variants. A criterion of global measurement was used for intents a parametric condition of stress fields. To avoid singularity problems was considerate a release on the stress restriction. On the optimization was used a material approach where the homogenized constructive equation was function of the material relative density. The intermediary density effective properties were represented for a SIMP-type artificial model. The problem was simplified by use of the method of finite elements of Galerkin using triangles with linear Lagrangian basis. On the solution of the optimization problem, was applied the augmented Lagrangian Method, that consists on minimum problem sequence solution with box-type restrictions, resolved by a 2nd orderprojection method which uses the method of the quasi-Newton without memory, during the problem process solution. This process reduces computational expends showing be more effective and solid. The results materialize more refined layouts with accurate topologic and shape of structure definitions. On the other hand formulation of mass minimization with global stress criterion provides to modeling ready structural layouts, with violation of the criterion of homogeneous distributed stress

Um método primal-dual aplicado na resolução do problema de fluxo de potência ótimo

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

Mineral dust mobilisation, transport, and deposition in different climate epochs

Mineral dust is an important component of the Earth's climate system and provides essential nutrientsrnto oceans and rain forests. During atmospheric transport, dust particles directly and indirectly influencernweather and climate. The strength of dust sources and characteristics of the transport, in turn, mightrnbe subject to climatic changes. Earth system models help for a better understanding of these complexrnmechanisms.rnrnThis thesis applies the global climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) for simulationsrnof the mineral dust cycle under different climatic conditions. The prerequisite for suitable modelrnresults is the determination of the model setup reproducing the most realistic dust cycle in the recentrnclimate. Simulations with this setup are used to gain new insights into properties of the transatlanticrndust transport from Africa to the Americas and adaptations of the model's climate forcing factors allowrnfor investigations of the impact of climatic changes on the dust cycle.rnrnIn the first part, the most appropriate model setup is determined through a number of sensitivity experiments.rnIt uses the dust emission parametrisation from Tegen et al. 2002 and a spectral resolutionrnof T85, corresponding to a horizontal grid spacing of about 155 km. Coarser resolutions are not able tornaccurately reproduce emissions from important source regions such as the Bodele Depression in Chad orrnthe Taklamakan Desert in Central Asia. Furthermore, the representation of ageing and wet deposition ofrndust particles in the model requires a basic sulphur chemical mechanism. This setup is recommended forrnfuture simulations with EMAC focusing on mineral dust.rnrnOne major branch of the global dust cycle is the long-range transport from the world's largest dustrnsource, the Sahara, across the Atlantic Ocean. Seasonal variations of the main transport pathways to thernAmazon Basin in boreal winter and to the Caribbean during summer are well known and understood,rnand corroborated in this thesis. Both Eulerian and Lagrangian methods give estimates on the typicalrntransport times from the source regions to the deposition on the order of nine to ten days. Previously, arnhuge proportion of the dust transported across the Atlantic Ocean has been attributed to emissions fromrnthe Bodele Depression. However, the contribution of this hot spot to the total transport is very low inrnthe present results, although the overall emissions from this region are comparable. Both model resultsrnand data sets analysed earlier, such as satellite products, involve uncertainties and this controversy aboutrndust transport from the Bodele Depression calls for future investigations and clarification.rnrnAforementioned characteristics of the transatlantic dust transport just slightly change in simulationsrnrepresenting climatic conditions of the Little Ice Age in the middle of the last millennium with meanrnnear-surface cooling of 0.5 to 1 K. However, intensification of the West African summer monsoon duringrnthe Little Ice Age is associated with higher dust emissions from North African source regions and wetterrnconditions in the Sahel. Furthermore, the Indian Monsoon and dust emissions from the Arabian Peninsula,rnwhich are affected by this circulation, are intensified during the Little Ice Age, whereas the annual globalrndust budget is similar in both climate epochs. Simulated dust emission fluxes are particularly influencedrnby the surface parameters. Modifications of the model do not affect those in this thesis, to be able tornascribe all differences in the results to changed forcing factors, such as greenhouse gas concentrations.rnDue to meagre comparison data sets, the verification of results presented here is problematic. Deeperrnknowledge about the dust cycle during the Little Ice Age can be obtained by future simulations, based onrnthis work, and additionally using improved reconstructions of surface parameters. Better evaluation ofrnsuch simulations would be possible by refining the temporal resolution of reconstructed dust depositionrnfluxes from existing ice and marine sediment cores.

Tratamiento consistente de restricciones e impacto en dinámica de sistemas multicuerpo

Esta tesis está enmarcada en el estudio de diferentes procedimientos numéricos para resolver la dinámica de un sistema multicuerpo sometido a restricciones e impacto, que puede estar compuesto por sólidos rígidos y deformables conectados entre sí por diversos tipos de uniones. Dentro de los métodos numéricos analizados se presta un especial interés a los métodos consistentes, los cuales tienen por objetivo que la energía calculada en cada paso de tiempo, para un sistema mecánico, tenga una evolución coherente con el comportamiento teórico de la energía. En otras palabras, un método consistente mantiene constante la energía total en un problema conservativo, y en presencia de fuerzas disipativas proporciona un decremento positivo de la energía total. En esta línea se desarrolla un algoritmo numérico consistente con la energía total para resolver las ecuaciones de la dinámica de un sistema multicuerpo. Como parte de este algoritmo se formulan energéticamente consistentes las restricciones y el contacto empleando multiplicadores de Lagrange, penalización y Lagrange aumentado. Se propone también un método para el contacto con sólidos rígidos representados mediante superficies implícitas, basado en una restricción regularizada que se adaptada adecuadamente para el cumplimiento exacto de la restricción de contacto y para ser consistente con la conservación de la energía total. En este contexto se estudian dos enfoques: uno para el contacto elástico puro (sin deformación) formulado con penalización y Lagrange aumentado; y otro basado en un modelo constitutivo para el contacto con penetración. En el segundo enfoque se usa un potencial de penalización que, en ausencia de componentes disipativas, restaura la energía almacenada en el contacto y disipa energía de forma consistente con el modelo continuo cuando las componentes de amortiguamiento y fricción son consideradas. This thesis focuses on the study of several numerical procedures used to solve the dynamics of a multibody system subjected to constraints and impact. The system may be composed by rigid and deformable bodies connected by different types of joints. Within this framework, special attention is paid to consistent methods, which preserve the theoretical behavior of the energy at each time step. In other words, a consistent method keeps the total energy constant in a conservative problem, and provides a positive decrease in the total energy when dissipative forces are present. A numerical algorithm has been developed for solving the dynamical equations of multibody systems, which is energetically consistent. Energetic consistency in contacts and constraints is formulated using Lagrange multipliers, penalty and augmented Lagrange methods. A contact methodology is proposed for rigid bodies with a boundary represented by implicit surfaces. The method is based on a suitable regularized constraint formulation, adapted both to fulfill exactly the contact constraint, and to be consistent with the conservation of the total energy. In this context two different approaches are studied: the first applied to pure elastic contact (without deformation), formulated with penalty and augmented Lagrange; and a second one based on a constitutive model for contact with penetration. In this second approach, a penalty potential is used in the constitutive model, that restores the energy stored in the contact when no dissipative effects are present. On the other hand, the energy is dissipated consistently with the continuous model when friction and damping are considered.

Desenvolvimento da célula base de microestruturas periódicas de compósitos sob otimização topológica

This thesis develops a new technique for composite microstructures projects by the Topology Optimization process, in order to maximize rigidity, making use of Deformation Energy Method and using a refining scheme h-adaptative to obtain a better defining the topological contours of the microstructure. This is done by distributing materials optimally in a region of pre-established project named as Cell Base. In this paper, the Finite Element Method is used to describe the field and for government equation solution. The mesh is refined iteratively refining so that the Finite Element Mesh is made on all the elements which represent solid materials, and all empty elements containing at least one node in a solid material region. The Finite Element Method chosen for the model is the linear triangular three nodes. As for the resolution of the nonlinear programming problem with constraints we were used Augmented Lagrangian method, and a minimization algorithm based on the direction of the Quasi-Newton type and Armijo-Wolfe conditions assisting in the lowering process. The Cell Base that represents the composite is found from the equivalence between a fictional material and a preescribe material, distributed optimally in the project area. The use of the strain energy method is justified for providing a lower computational cost due to a simpler formulation than traditional homogenization method. The results are presented prescription with change, in displacement with change, in volume restriction and from various initial values of relative densities.

Long-Range Pollution Transport: Trans-Atlantic Mechanisms and Lagrangian Modeling Methods

Over the past several decades, it has become apparent that anthropogenic activities have resulted in the large-scale enhancement of the levels of many trace gases throughout the troposphere. More recently, attention has been given to the transport pathway taken by these emissions as they are dispersed throughout the atmosphere. The transport pathway determines the physical characteristics of emissions plumes and therefore plays an important role in the chemical transformations that can occur downwind of source regions. For example, the production of ozone (O3) is strongly dependent upon the transport its precursors undergo. O3 can initially be formed within air masses while still over polluted source regions. These polluted air masses can experience continued O3 production or O3 destruction downwind, depending on the air mass's chemical and transport characteristics. At present, however, there are a number of uncertainties in the relationships between transport and O3 production in the North Atlantic lower free troposphere. The first phase of the study presented here used measurements made at the Pico Mountain observatory and model simulations to determine transport pathways for US emissions to the observatory. The Pico Mountain observatory was established in the summer of 2001 in order to address the need to understand the relationships between transport and O3 production. Measurements from the observatory were analyzed in conjunction with model simulations from the Lagrangian particle dispersion model (LPDM), FLEX-PART, in order to determine the transport pathway for events observed at the Pico Mountain observatory during July 2003. A total of 16 events were observed, 4 of which were analyzed in detail. The transport time for these 16 events varied from 4.5 to 7 days, while the transport altitudes over the ocean ranged from 2-8 km, but were typically less than 3 km. In three of the case studies, eastward advection and transport in a weak warm conveyor belt (WCB) airflow was responsible for the export of North American emissions into the FT, while transport in the FT was governed by easterly winds driven by the Azores/Bermuda High (ABH) and transient northerly lows. In the fourth case study, North American emissions were lofted to 6-8 km in a WCB before being entrained in the same cyclone's dry airstream and transported down to the observatory. The results of this study show that the lower marine FT may provide an important transport environment where O3 production may continue, in contrast to transport in the marine boundary layer, where O3 destruction is believed to dominate. The second phase of the study presented here focused on improving the analysis methods that are available with LPDMs. While LPDMs are popular and useful for the analysis of atmospheric trace gas measurements, identifying the transport pathway of emissions from their source to a receptor (the Pico Mountain observatory in our case) using the standard gridded model output, particularly during complex meteorological scenarios can be difficult can be difficult or impossible. The transport study in phase 1 was limited to only 1 month out of more than 3 years of available data and included only 4 case studies out of the 16 events specifically due to this confounding factor. The second phase of this study addressed this difficulty by presenting a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (i.e., concentrations) and backward (i.e., residence time) LPDM simulations, greatly simplifying similar analyses. The ability of the method to successfully determine the source-to-receptor pathway, restoring this Lagrangian information that is lost when the data are gridded, is proven by comparing the pathway determined from this method with the particle trajectories from both the forward and backward models. A sample analysis is also presented, demonstrating that this method is more accurate and easier to use than existing methods using standard LPDM products. Finally, we discuss potential future work that would be possible by combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor.

Analysis of Meshfree Methods for Lagrangian Fluid-Structure Interaction

In this dissertation a new numerical method for solving Fluid-Structure Interaction (FSI) problems in a Lagrangian framework is developed, where solids of different constitutive laws can suffer very large deformations and fluids are considered to be newtonian and incompressible. For that, we first introduce a meshless discretization based on local maximum-entropy interpolants. This allows to discretize a spatial domain with no need of tessellation, avoiding the mesh limitations. Later, the Stokes flow problem is studied. The Galerkin meshless method based on a max-ent scheme for this problem suffers from instabilities, and therefore stabilization techniques are discussed and analyzed. An unconditionally stable method is finally formulated based on a Douglas-Wang stabilization. Then, a Langrangian expression for fluid mechanics is derived. This allows us to establish a common framework for fluid and solid domains, such that interaction can be naturally accounted. The resulting equations are also in the need of stabilization, what is corrected with an analogous technique as for the Stokes problem. The fully Lagrangian framework for fluid/solid interaction is completed with simple point-to-point and point-to-surface contact algorithms. The method is finally validated, and some numerical examples show the potential scope of applications.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

Early Australian experience with infliximab, a chimeric antibody against tumour necrosis factor-alpha, in the treatment of Crohn's disease: is its efficacy augmented by steroid-sparing immunosuppressive therapy?

Background: Tumour necrosis factor-alpha (TNF-alpha) plays an important role in the pathology of Crohn's disease. Infliximab, a chimeric antibody against TNF-alpha, has been shown in controlled clinical trials to be effective in two-thirds of patients with refractory or fistulating Crohn's disease. The factors that determine a clinical response in some patients but not others are unknown. Aims: To document the early Australian experience with infliximab treatment for Crohn's disease and to identify factors that may determine a beneficial clinical response. Methods: Gastroenterologists known to have used infliximab for Crohn's disease according to a compassionate use protocol were asked to complete a spreadsheet that included demographic information, Crohn's disease site, severity, other medical or surgical treatments and a global clinical assessment of Crohn's disease outcome, judged by participating physicians as complete and sustained (remission for the duration of the study), complete but unsustained (remission at 4 weeks but not for the whole study) or partial clinical improvement (sustained or unsustained). Results: Fifty-seven patients were able to be evaluated, with a median follow-up time of 16.4 (4-70) weeks, including 23 patients with fistulae. There were 21 adverse events, including four serious events. Fifty-one patients (89%) had a positive clinical response for a median duration (range) of 11 (2-70) weeks. Thirty patients (52%) had a remission at 4 weeks, 10 of whom had remission for longer than 12 weeks. Forty-two per cent of fistulae closed. Sustained remission (P = 0.065), remission at 4 weeks (P = 0.033) and a positive clinical response of any sort (P = 0.004) were more likely in patients on immunosuppressive therapy, despite there being more smelters in this group. Conclusion: This review of the first Australian experience with infliximab corroborates the reported speed and efficacy of this treatment for Crohn's disease. The excellent response appears enhanced by the concomitant use of conventional steroid-sparing immunosuppressive therapy.

An augmented Lanczos algorithm for the efficient computation of a dot-product of a function of a large sparse symmetric matrix

The Lanczos algorithm is appreciated in many situations due to its speed. and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.