Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

Mountain centered icefields in northern Scandinavia

Mountain centered glaciers have played a major role throughout the last three million years in the Scandinavian mountains. The climatic extremes, like the present warm interglacial or cold glacial maxima, are very short-lived compared to the periods of intermediate climate conditions, characterized by the persistence of mountain based glaciers and ice fields of regional size. These have persisted in the Scandinavian mountains for about 65% of the Quaternary. Mountain based glaciers thus had a profound impact on large-scale geomorphology, which is manifested in large-scale glacial landforms such as fjords, glacial lakes and U-shaped valleys in and close to the mountain range. Through a mapping of glacial landforms in the northern Scandinavian mountain range, in particular a striking set of lateral moraines, this thesis offers new insights into Weichselian stages predating the last glacial maximum. The aerial photograph mapping and field evidence yield evidence that these lateral moraines were overridden by glacier ice subsequent to their formation. The lateral moraines were dated using terrestrial cosmogenic nuclide techniques. Although the terrestrial cosmogenic nuclide signature of the moraines is inconclusive, an early Weichselian age is tentatively suggested through correlations with other landforms and stratigraphical archives in the region. The abundance and coherent spatial pattern of the lateral moraines also allow a spatial reconstruction of this ice field. The ice field was controlled by topography and had nunataks protruding also where it was thickest close to the elevation axis of the Scandinavian mountain range. Outlet glaciers discharged into the Norwegian fjords and major valleys in Sweden. The process by which mountain based glaciers grow into an ice sheet is a matter of debate. In this thesis, a feedback mechanism between debris on the ice surface and ice sheet growth is presented. In essence, the growth of glaciers and ice sheets may be accelerated by an abundance of debris in their ablation areas. This may occur when the debris cover on the glacier surface inhibits ablation, effectively increasing the glaciers mass balance. It is thus possible that a dirty ablation area may cause the glacier to advance further than a clean glacier under similar conditions. An ice free period of significant length allows soil production through weathering, frost shattering, and slope processes. As glaciers advance through this assemblage of sediments, significant amounts of debris end up on the surface due to both mass wastage and subglacial entrainment. Evidence that this chain of events may occur, is given by large expanses of hummocky moraine (local name Veiki moraine) in the northern Swedish lowlands. Because the Veiki moraine has been correlated with the first Weichselian advance following the Eemian, it implies a heavily debris charged ice sheet emanating from the mountain range and terminating in a stagnant fashion in the lowlands.

Test and Evaluation of the FastSLAM Algorithm in a Mobile Robot

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Performance evaluation of a parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes

[EN]A new parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. We provide a detailed analysis of its performance on shared-memory many-core computer architectures. This performance analysis includes the evaluation of execution time, parallel scalability, load balancing, and parallelism bottlenecks. Additionally, we compare the impact of three previously published graph coloring procedures on the performance of our parallel algorithm. We use six benchmark meshes with a wide range of sizes. Using these experimental data sets, we describe the behavior of the parallel algorithm for different data sizes. We demonstrate that this algorithm is highly scalable when it runs on two different high-performance many-core computers with up to 128 processors...

T-spline parameterization of 2D geometries based on the meccano method with a new T-mesh optimization algorithm

[EN]We present a new method, based on the idea of the meccano method and a novel T-mesh optimization procedure, to construct a T-spline parameterization of 2D geometries for the application of isogeometric analysis. The proposed method only demands a boundary representation of the geometry as input data. The algorithm obtains, as a result, high quality parametric transformation between 2D objects and the parametric domain, the unit square. First, we define a parametric mapping between the input boundary of the object and the boundary of the parametric domain. Then, we build a T-mesh adapted to the geometric singularities of the domain in order to preserve the features of the object boundary with a desired tolerance…

Tectonics and kinematics of curved mountain belts: examples from the Andes and the Alps

Curved mountain belts have always fascinated geologists and geophysicists because of their peculiar structural setting and geodynamic mechanisms of formation. The need of studying orogenic bends arises from the numerous questions to which geologists and geophysicists have tried to answer to during the last two decades, such as: what are the mechanisms governing orogenic bends formation? Why do they form? Do they develop in particular geological conditions? And if so, what are the most favorable conditions? What are their relationships with the deformational history of the belt? Why is the shape of arcuate orogens in many parts of the Earth so different? What are the factors controlling the shape of orogenic bends? Paleomagnetism demonstrated to be one of the most effective techniques in order to document the deformation of a curved belt through the determination of vertical axis rotations. In fact, the pattern of rotations within a curved belt can reveal the occurrence of a bending, and its timing. Nevertheless, paleomagnetic data alone are not sufficient to constrain the tectonic evolution of a curved belt. Usually, structural analysis integrates paleomagnetic data, in defining the kinematics of a belt through kinematic indicators on brittle fault planes (i.e., slickensides, mineral fibers growth, SC-structures). My research program has been focused on the study of curved mountain belts through paleomagnetism, in order to define their kinematics, timing, and mechanisms of formation. Structural analysis, performed only in some regions, supported and integrated paleomagnetic data. In particular, three arcuate orogenic systems have been investigated: the Western Alpine Arc (NW Italy), the Bolivian Orocline (Central Andes, NW Argentina), and the Patagonian Orocline (Tierra del Fuego, southern Argentina). The bending of the Western Alpine Arc has been investigated so far using different approaches, though few based on reliable paleomagnetic data. Results from our paleomagnetic study carried out in the Tertiary Piedmont Basin, located on top of Alpine nappes, indicate that the Western Alpine Arc is a primary bend that has been subsequently tightened by further ~50° during Aquitanian-Serravallian times (23-12 Ma). This mid-Miocene oroclinal bending, superimposing onto a pre-existing Eocene nonrotational arc, is the result of a composite geodynamic mechanism, where slab rollback, mantle flows, and rotating thrust emplacement are intimately linked. Relying on our paleomagnetic and structural evidence, the Bolivian Orocline can be considered as a progressive bend, whose formation has been driven by the along-strike gradient of crustal shortening. The documented clockwise rotations up to 45° are compatible with a secondary-bending type mechanism occurring after Eocene-Oligocene times (30-40 Ma), and their nature is probably related to the widespread shearing taking place between zones of differential shortening. Since ~15 Ma ago, the activity of N-S left-lateral strike-slip faults in the Eastern Cordillera at the border with the Altiplano-Puna plateau induced up to ~40° counterclockwise rotations along the fault zone, locally annulling the regional clockwise rotation. We proposed that mid-Miocene strike-slip activity developed in response of a compressive stress (related to body forces) at the plateau margins, caused by the progressive lateral (southward) growth of the Altiplano-Puna plateau, laterally spreading from the overthickened crustal region of the salient apex. The growth of plateaux by lateral spreading seems to be a mechanism common to other major plateaux in the Earth (i.e., Tibetan plateau). Results from the Patagonian Orocline represent the first reliable constraint to the timing of bending in the southern tip of South America. They indicate that the Patagonian Orocline did not undergo any significant rotation since early Eocene times (~50 Ma), implying that it may be considered either a primary bend, or an orocline formed during the late Cretaceous-early Eocene deformation phase. This result has important implications on the opening of the Drake Passage at ~32 Ma, since it is definitely not related to the formation of the Patagonian orocline, but the sole consequence of the Scotia plate spreading. Finally, relying on the results and implications from the study of the Western Alpine Arc, the Bolivian Orocline, and the Patagonian Orocline, general conclusions on curved mountain belt formation have been inferred.

Preliminary studies for the establishment of a tsunami early detection algorithm to be used in the frame of a Tsunami Warning System

This thesis presents and discusses TEDA, an algorithm for the automatic detection in real-time of tsunamis and large amplitude waves on sea level records. TEDA has been developed in the frame of the Tsunami Research Team of the University of Bologna for coastal tide gauges and it has been calibrated and tested for the tide gauge station of Adak Island, in Alaska. A preliminary study to apply TEDA to offshore buoys in the Pacific Ocean is also presented.

Tectonic geomorphology and active strain of the Northern Apennines mountain front

The Northern Apennines (NA) chain is the expression of the active plate margin between Europe and Adria. Given the low convergence rates and the moderate seismic activity, ambiguities still occur in defining a seismotectonic framework and many different scenarios have been proposed for the mountain front evolution. Differently from older models that indicate the mountain front as an active thrust at the surface, a recently proposed scenario describes the latter as the frontal limb of a long-wavelength fold (> 150 km) formed by a thrust fault tipped around 17 km at depth, and considered as the active subduction boundary. East of Bologna, this frontal limb is remarkably very straight and its surface is riddled with small, but pervasive high- angle normal faults. However, west of Bologna, some recesses are visible along strike of the mountain front: these perturbations seem due to the presence of shorter wavelength (15 to 25 km along strike) structures showing both NE and NW-vergence. The Pleistocene activity of these structures was already suggested, but not quantitative reconstructions are available in literature. This research investigates the tectonic geomorphology of the NA mountain front with the specific aim to quantify active deformations and infer possible deep causes of both short- and long-wavelength structures. This study documents the presence of a network of active extensional faults, in the foothills south and east of Bologna. For these structures, the strain rate has been measured to find a constant throw-to-length relationship and the slip rates have been compared with measured rates of erosion. Fluvial geomorphology and quantitative analysis of the topography document in detail the active tectonics of two growing domal structures (Castelvetro - Vignola foothills and the Ghiardo plateau) embedded in the mountain front west of Bologna. Here, tilting and river incision rates (interpreted as that long-term uplift rates) have been measured respectively at the mountain front and in the Enza and Panaro valleys, using a well defined stratigraphy of Pleistocene to Holocene river terraces and alluvial fan deposits as growth strata, and seismic reflection profiles relationships. The geometry and uplift rates of the anticlines constrain a simple trishear fault propagation folding model that inverts for blind thrust ramp depth, dip, and slip. Topographic swath profiles and the steepness index of river longitudinal profiles that traverse the anti- clines are consistent with stratigraphy, structures, aquifer geometry, and seismic reflection profiles. Available focal mechanisms of earthquakes with magnitude between Mw 4.1 to 5.4, obtained from a dataset of the instrumental seismicity for the last 30 years, evidence a clear vertical separation at around 15 km between shallow extensional and deeper compressional hypocenters along the mountain front and adjacent foothills. In summary, the studied anticlines appear to grow at rates slower than the growing rate of the longer- wavelength structure that defines the mountain front of the NA. The domal structures show evidences of NW-verging deformation and reactivations of older (late Neogene) thrusts. The reconstructed river incision rates together with rates coming from several other rivers along a 250 km wide stretch of the NA mountain front and recently available in the literature, all indicate a general increase from Middle to Late Pleistocene. This suggests focusing of deformation along a deep structure, as confirmed by the deep compressional seismicity. The maximum rate is however not constant along the mountain front, but varies from 0.2 mm/yr in the west to more than 2.2 mm/yr in the eastern sector, suggesting a similar (eastward-increasing) trend of the apenninic subduction.

Aktionenlernen mit Selbstorganisierenden Karten und Reinforcement Learning

Die vorliegende Arbeit beschäftigt sich mit der Entwicklung eines Funktionsapproximators und dessen Verwendung in Verfahren zum Lernen von diskreten und kontinuierlichen Aktionen: 1. Ein allgemeiner Funktionsapproximator – Locally Weighted Interpolating Growing Neural Gas (LWIGNG) – wird auf Basis eines Wachsenden Neuralen Gases (GNG) entwickelt. Die topologische Nachbarschaft in der Neuronenstruktur wird verwendet, um zwischen benachbarten Neuronen zu interpolieren und durch lokale Gewichtung die Approximation zu berechnen. Die Leistungsfähigkeit des Ansatzes, insbesondere in Hinsicht auf sich verändernde Zielfunktionen und sich verändernde Eingabeverteilungen, wird in verschiedenen Experimenten unter Beweis gestellt. 2. Zum Lernen diskreter Aktionen wird das LWIGNG-Verfahren mit Q-Learning zur Q-LWIGNG-Methode verbunden. Dafür muss der zugrunde liegende GNG-Algorithmus abgeändert werden, da die Eingabedaten beim Aktionenlernen eine bestimmte Reihenfolge haben. Q-LWIGNG erzielt sehr gute Ergebnisse beim Stabbalance- und beim Mountain-Car-Problem und gute Ergebnisse beim Acrobot-Problem. 3. Zum Lernen kontinuierlicher Aktionen wird ein REINFORCE-Algorithmus mit LWIGNG zur ReinforceGNG-Methode verbunden. Dabei wird eine Actor-Critic-Architektur eingesetzt, um aus zeitverzögerten Belohnungen zu lernen. LWIGNG approximiert sowohl die Zustands-Wertefunktion als auch die Politik, die in Form von situationsabhängigen Parametern einer Normalverteilung repräsentiert wird. ReinforceGNG wird erfolgreich zum Lernen von Bewegungen für einen simulierten 2-rädrigen Roboter eingesetzt, der einen rollenden Ball unter bestimmten Bedingungen abfangen soll.

A parallel community detection algorithm

Complex networks analysis is a very popular topic in computer science. Unfortunately this networks, extracted from different contexts, are usually very large and the analysis may be very complicated: computation of metrics on these structures could be very complex. Among all metrics we analyse the extraction of subnetworks called communities: they are groups of nodes that probably play the same role within the whole structure. Communities extraction is an interesting operation in many different fields (biology, economics,...). In this work we present a parallel community detection algorithm that can operate on networks with huge number of nodes and edges. After an introduction to graph theory and high performance computing, we will explain our design strategies and our implementation. Then, we will show some performance evaluation made on a distributed memory architectures i.e. the supercomputer IBM-BlueGene/Q "Fermi" at the CINECA supercomputing center, Italy, and we will comment our results.

Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory

This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.