Solving the cooling flow problem through mechanical AGN feedback

A fundamental gap in the current understanding of collapsed structures in the universe concerns the thermodynamical evolution of the ordinary, baryonic component. Unopposed radiative cooling of plasma would lead to the cooling catastrophe, a massive inflow of condensing gas toward the centre of galaxies, groups and clusters. The last generation of multiwavelength observations has radically changed our view on baryons, suggesting that the heating linked to the active galactic nucleus (AGN) may be the balancing counterpart of cooling. In this Thesis, I investigate the engine of the heating regulated by the central black hole. I argue that the mechanical feedback, based on massive subrelativistic outflows, is the key to solving the cooling flow problem, i.e. dramatically quenching the cooling rates for several billion years without destroying the cool-core structure. Using an upgraded version of the parallel 3D hydrodynamic code FLASH, I show that anisotropic AGN outflows can further reproduce fundamental observed features, such as buoyant bubbles, cocoon shocks, sonic ripples, metals dredge-up, and subsonic turbulence. The latter is an essential ingredient to drive nonlinear thermal instabilities, which cause cold gas condensation, a residual of the quenched cooling flow and, later, fuel for the AGN feedback engine. The self-regulated outflows are systematically tested on the scales of massive clusters, groups and isolated elliptical galaxies: in lighter less bound objects the feedback needs to be gentler and less efficient, in order to avoid drastic overheating. In this Thesis, I describe in depth the complex hydrodynamics, involving the coupling of the feedback energy to that of the surrounding hot medium. Finally, I present the merits and flaws of all the proposed models, with a critical eye toward observational concordance.

Pseudodifferential analysis in Psi*-algebras on transmission spaces, infinite solving ideal chains and K-theory for conformally compact spaces

The present thesis is a contribution to the theory of algebras of pseudodifferential operators on singular settings. In particular, we focus on the $b$-calculus and the calculus on conformally compact spaces in the sense of Mazzeo and Melrose in connection with the notion of spectral invariant transmission operator algebras. We summarize results given by Gramsch et. al. on the construction of $Psi_0$-and $Psi*$-algebras and the corresponding scales of generalized Sobolev spaces using commutators of certain closed operators and derivations. In the case of a manifold with corners $Z$ we construct a $Psi*$-completion $A_b(Z,{}^bOmega^{1/2})$ of the algebra of zero order $b$-pseudodifferential operators $Psi_{b,cl}(Z, {}^bOmega^{1/2})$ in the corresponding $C*$-closure $B(Z,{}^bOmega^{12})hookrightarrow L(L^2(Z,{}^bOmega^{1/2}))$. The construction will also provide that localised to the (smooth) interior of Z the operators in the $A_b(Z, {}^bOmega^{1/2})$ can be represented as ordinary pseudodifferential operators. In connection with the notion of solvable $C*$-algebras - introduced by Dynin - we calculate the length of the $C*$-closure of $Psi_{b,cl}^0(F,{}^bOmega^{1/2},R^{E(F)})$ in $B(F,{}^bOmega^{1/2}),R^{E(F)})$ by localizing $B(Z, {}^bOmega^{1/2})$ along the boundary face $F$ using the (extended) indical familiy $I^B_{FZ}$. Moreover, we discuss how one can localise a certain solving ideal chain of $B(Z, {}^bOmega^{1/2})$ in neighbourhoods $U_p$ of arbitrary points $pin Z$. This localisation process will recover the singular structure of $U_p$; further, the induced length function $l_p$ is shown to be upper semi-continuous. We give construction methods for $Psi*$- and $C*$-algebras admitting only infinite long solving ideal chains. These algebras will first be realized as unconnected direct sums of (solvable) $C*$-algebras and then refined such that the resulting algebras have arcwise connected spaces of one dimensional representations. In addition, we recall the notion of transmission algebras on manifolds with corners $(Z_i)_{iin N}$ following an idea of Ali Mehmeti, Gramsch et. al. Thereby, we connect the underlying $C^infty$-function spaces using point evaluations in the smooth parts of the $Z_i$ and use generalized Laplacians to generate an appropriate scale of Sobolev spaces. Moreover, it is possible to associate generalized (solving) ideal chains to these algebras, such that to every $ninN$ there exists an ideal chain of length $n$ within the algebra. Finally, we discuss the $K$-theory for algebras of pseudodifferential operators on conformally compact manifolds $X$ and give an index theorem for these operators. In addition, we prove that the Dirac-operator associated to the metric of a conformally compact manifold $X$ is not a Fredholm operator.

Groupme: city data and multi-preference activity allocation

Classic group recommender systems focus on providing suggestions for a fixed group of people. Our work tries to give an inside look at design- ing a new recommender system that is capable of making suggestions for a sequence of activities, dividing people in subgroups, in order to boost over- all group satisfaction. However, this idea increases problem complexity in more dimensions and creates great challenge to the algorithm’s performance. To understand the e↵ectiveness, due to the enhanced complexity and pre- cise problem solving, we implemented an experimental system from data collected from a variety of web services concerning the city of Paris. The sys- tem recommends activities to a group of users from two di↵erent approaches: Local Search and Constraint Programming. The general results show that the number of subgroups can significantly influence the Constraint Program- ming Approaches’s computational time and e�cacy. Generally, Local Search can find results much quicker than Constraint Programming. Over a lengthy period of time, Local Search performs better than Constraint Programming, with similar final results.

Computing primal solutions with exact arithmetics in SCIP.

The research for exact solutions of mixed integer problems is an active topic in the scientific community. State-of-the-art MIP solvers exploit a floating- point numerical representation, therefore introducing small approximations. Although such MIP solvers yield reliable results for the majority of problems, there are cases in which a higher accuracy is required. Indeed, it is known that for some applications floating-point solvers provide falsely feasible solutions, i.e. solutions marked as feasible because of approximations that would not pass a check with exact arithmetic and cannot be practically implemented. The framework of the current dissertation is SCIP, a mixed integer programs solver mainly developed at Zuse Institute Berlin. In the same site we considered a new approach for exactly solving MIPs. Specifically, we developed a constraint handler to plug into SCIP, with the aim to analyze the accuracy of provided floating-point solutions and compute exact primal solutions starting from floating-point ones. We conducted a few computational experiments to test the exact primal constraint handler through the adoption of two main settings. Analysis mode allowed to collect statistics about current SCIP solutions' reliability. Our results confirm that floating-point solutions are accurate enough with respect to many instances. However, our analysis highlighted the presence of numerical errors of variable entity. By using the enforce mode, our constraint handler is able to suggest exact solutions starting from the integer part of a floating-point solution. With the latter setting, results show a general improvement of the quality of provided final solutions, without a significant loss of performances.

Solving the logically constrained multiple choice multiple knapsack problem: A real case

In questa tesi viene analizzato un problema di ottimizzazione proposto da alcuni esercizi commerciali che hanno la necessita` di selezionare e disporre i propri ar- ticoli in negozio. Il problema nasce dall’esigenza di massimizzare il profitto com- plessivo atteso dei prodotti in esposizione, trovando per ognuno una locazione sugli scaffali. I prodotti sono suddivisi in dipartimenti, dai quali solo un ele- mento deve essere selezionato ed esposto. In oltre si prevede la possibilita` di esprimere vincoli sulla locazione e compatibilita` dei prodotti. Il problema risul- tante `e una generalizzazione dei gia` noti Multiple-Choice Knapsack Problem e Multiple Knapsack Problem. Dopo una ricerca esaustiva in letteratura si `e ev- into che questo problema non `e ancora stato studiato. Si `e quindi provveduto a formalizzare il problema mediante un modello di programmazione lineare intera. Si propone un algoritmo esatto per la risoluzione del problema basato su column generation e branch and price. Sono stati formulati quattro modelli differenti per la risoluzione del pricing problem su cui si basa il column generation, per individuare quale sia il piu` efficiente. Tre dei quattro modelli proposti hanno performance comparabili, mentre l’ultimo si `e rivelato piu` inefficiente. Dai risul- tati ottenuti si evince che il metodo risolutivo proposto `e adatto a istanze di dimensione medio-bassa.

Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.

The Supportive Role of the Family in Solving Real and Projected Problems of Everyday Life

In this research the supportive role of the family in coping with everyday problems was studied using two large data sets. The results show the importance of the structural aspect of social support. Mapping individual preferences to support referents showed the crucial role of spouse and parents in solving everyday problems. The individual choices of particular support referents could be fairly accurately predicted from knowledge of the composition of the family, in both categorical regression and logit models. The far lower predictability of the criterion variable was shown using a wide range of socioeconomic, social and demographic indicators. Residence in small cities and indicators of extreme occupational strata were particularly predictive of the choice of support referent. The supportive role of the family was also traced in the personal projects of young adults, which were seen as ecological, natural and dynamic middle-level units of analysis of personality. Different aspects of personal projects, including reliance on social support referents, turned out to be highly interrelated. One the one hand, expectations of support were determined by the content of the project, and on the other, expected social support also influences the content of the project. Sivuha sees this as one of the ways others can enter self-structures.

Leaf Asymmetry as a Developmental Constraint Imposed by Auxin-Dependent Phyllotactic Patterning

In a majority of species, leaf development is thought to proceed in a bilaterally symmetric fashion without systematic asymmetries. This is despite the left and right sides of an initiating primordium occupying niches that differ in their distance from sinks and sources of auxin. Here, we revisit an existing model of auxin transport sufficient to recreate spiral phyllotactic patterns and find previously overlooked asymmetries between auxin distribution and the centers of leaf primordia. We show that it is the direction of the phyllotactic spiral that determines the side of the leaf these asymmetries fall on. We empirically confirm the presence of an asymmetric auxin response using a DR5 reporter and observe morphological asymmetries in young leaf primordia. Notably, these morphological asymmetries persist in mature leaves, and we observe left-right asymmetries in the superficially bilaterally symmetric leaves of tomato (Solanum lycopersicum) and Arabidopsis thaliana that are consistent with modeled predictions. We further demonstrate that auxin application to a single side of a leaf primordium is sufficient to recapitulate the asymmetries we observe. Our results provide a framework to study a previously overlooked developmental axis and provide insights into the developmental constraints imposed upon leaf morphology by auxin-dependent phyllotactic patterning.

Decomposing intuitive components in a conceptual problem solving task

Research into intuitive problem solving has shown that objective closeness of participants' hypotheses were closer to the accurate solution than their subjective ratings of closeness. After separating conceptually intuitive problem solving from the solutions of rational incremental tasks and of sudden insight tasks, we replicated this finding by using more precise measures in a conceptual problem-solving task. In a second study, we distinguished performance level, processing style, implicit knowledge and subjective feeling of closeness to the solution within the problem-solving task and examined the relationships of these different components with measures of intelligence and personality. Verbal intelligence correlated with performance level in problem solving, but not with processing style and implicit knowledge. Faith in intuition, openness to experience, and conscientiousness correlated with processing style, but not with implicit knowledge. These findings suggest that one needs to decompose processing style and intuitive components in problem solving to make predictions on effects of intelligence and personality measures.

Parallel algorithm for solving integer linear programs

Linear programs, or LPs, are often used in optimization problems, such as improving manufacturing efficiency of maximizing the yield from limited resources. The most common method for solving LPs is the Simplex Method, which will yield a solution, if one exists, but over the real numbers. From a purely numerical standpoint, it will be an optimal solution, but quite often we desire an optimal integer solution. A linear program in which the variables are also constrained to be integers is called an integer linear program or ILP. It is the focus of this report to present a parallel algorithm for solving ILPs. We discuss a serial algorithm using a breadth-first branch-and-bound search to check the feasible solution space, and then extend it into a parallel algorithm using a client-server model. In the parallel mode, the search may not be truly breadth-first, depending on the solution time for each node in the solution tree. Our search takes advantage of pruning, often resulting in super-linear improvements in solution time. Finally, we present results from sample ILPs, describe a few modifications to enhance the algorithm and improve solution time, and offer suggestions for future work.

Exigencies for engaging undergraduates in rhetorical problem solving : insights from engineering managers and A3 report analyses

Undergraduate education has a historical tradition of preparing students to meet the problem-solving challenges they will encounter in work, civic, and personal contexts. This thesis research was conducted to study the role of rhetoric in engineering problem solving and decision making and to pose pedagogical strategies for preparing undergraduate students for workplace problem solving. Exploratory interviews with engineering managers as well as the heuristic analyses of engineering A3 project planning reports suggest that Aristotelian rhetorical principles are critical to the engineer's success: Engineers must ascertain the rhetorical situation surrounding engineering problems; apply and adapt invention heuristics to conduct inquiry; draw from their investigation to find innovative solutions; and influence decision making by navigating workplace decision-making systems and audiences using rhetorically constructed discourse. To prepare undergraduates for workplace problem solving, university educators are challenged to help undergraduates understand the exigence and realize the kairotic potential inherent in rhetorical problem solving. This thesis offers pedagogical strategies that focus on mentoring learning communities in problem-posing experiences that are situated in many disciplinary, work, and civic contexts. Undergraduates build a flexible rhetorical technê for problem solving as they navigate the nuances of relevant problem-solving systems through the lens of rhetorical practice.

DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

Maximum principle preserving high order schemes for convection-dominated diffusion equations

The maximum principle is an important property of solutions to PDE. Correspondingly, it's of great interest for people to design a high order numerical scheme solving PDE with this property maintained. In this thesis, our particular interest is solving convection-dominated diffusion equation. We first review a nonconventional maximum principle preserving(MPP) high order finite volume(FV) WENO scheme, and then propose a new parametrized MPP high order finite difference(FD) WENO framework, which is generalized from the one solving hyperbolic conservation laws. A formal analysis is presented to show that a third order finite difference scheme with this parametrized MPP flux limiters maintains the third order accuracy without extra CFL constraint when the low order monotone flux is chosen appropriately. Numerical tests in both one and two dimensional cases are performed on the simulation of the incompressible Navier-Stokes equations in vorticity stream-function formulation and several other problems to show the effectiveness of the proposed method.