Ridge Network in Crumpled Paper

The network formed by ridges in a straightened sheet of crumpled paper is studied using a laser profilometer. Square sheets of paper were crumpled into balls, unfolded and their height profile measured. From these profiles the imposed ridges were extracted as networks. Nodes were defined as intersections between ridges, and links as the various ridges connecting the nodes. Many network and spatial properties have been investigated. The tail of the ridge length distribution was found to follow a power-law whereas the shorter ridges followed a log-normal distribution. The degree distribution was found to have an exponentially decaying tail, and the degree correlation was found to be disassortative. The facets created by the ridges and the Voronoi diagram formed by the nodes have also been investigated.Comment: 8 pages, 10 figure, 2 tables Replaced due to wrong formating of author name

Impact of seasonal weather on forecasting of power quality disturbances in distribution grids

Power supply disruptions, including short-time disturbances, can lead to large direct and indirect financial losses. The ability to predict the risk of these disturbances allows for preventive actions and increases the reliability of the supply. This paper investigates the impact of using seasonal data of combined common weather conditions on the power quality prediction in distribution grids. Our main contribution consists of weatherbased predictive models for three types of events that frequently occur in these grids, as well as an analysis of the influence of two training approaches: with either seasonal or all-year data, on their performance. All developed models score higher than arbitrary guessing; in several instances the improvement is considerable. It is demonstrated that in some cases the models improve when the training data is limited to a subset corresponding to a particular meteorological season. Examining variable importance values and distributions of the models’ data, it is shown that this situation takes place particularly when weather conditions correlated with the occurrence of power grid events vary across seasonsacceptedVersio

Topology of Fracture Networks

We propose a mapping from fracture systems consisting of intersecting fracture sheets in three dimensions to an abstract network consisting of nodes and links. This makes it possible to analyze fracture systems with the methods developed within modern network theory. We test the mapping for two-dimensional geological fracture outcrops and find that the equivalent networks are small-world and dissasortative. By anlayzing the Discrete Fracture Network model, which is used to generate artifical fracture networks, we also find small world networks. However, the networks turn out to be assortative.Comment: 5 pages, 6 figure

Lessons for Data-Driven Modelling from Harmonics in the Norwegian Grid

With the advancing integration of fluctuating renewables, a more dynamic demand-side, and a grid running closer to its operational limits, future power system operators require new tools to anticipate unwanted events. Advances in machine learning and availability of data suggest great potential in using data-driven approaches, but these will only ever be as good as the data they are based on. To lay the ground-work for future data-driven modelling, we establish a baseline state by analysing the statistical distribution of voltage measurements from three sites in the Norwegian power grid (22, 66, and 300 kV). Measurements span four years, are line and phase voltages, are cycle-by-cycle, and include all (even and odd) harmonics up to the 96 order. They are based on four years of historical data from three Elspec Power Quality Analyzers (corresponding to one trillion samples), which we have extracted, processed, and analyzed. We find that: (i) the distribution of harmonics depends on phase and voltage level; (ii) there is little power beyond the 13 harmonic; (iii) there is temporal clumping of extreme values; and (iv) there is seasonality on different time-scales. For machine learning based modelling these findings suggest that: (i) models should be trained in two steps (first with data from all sites, then adapted to site-level); (ii) including harmonics beyond the 13 is unlikely to increase model performance, and that modelling should include features that (iii) encode the state of the grid, as well as (iv) seasonality. View Full-Text Keywords: machine learning; power systems; harmonic distortion; power qualitypublishedVersio

Meeresspiegelschwankungen und ihre geologische Überlieferung im Karbonatsystem

The dependency between carbonate sediment production on a carbonate platform and its relation to sea-level changes is discusses here. The topography of the upper slope plays an important role in determining the way in which sedimentation continues during lowstands in sea level. The mineralogy and composition of sediments produced on the platform can clearly be related to those found in sediments deposited in the adjacent basin. Two examples from the Recent are described: (1) Sanganeb Atoll (Red Sea), and (2) Pedro Bank (caribbean). The applicability of the "highstand shedding" principle is shown for ancient carbonate platforms

Eigenfrequency maximisation by using irregular lattice structures

Lightweight structures are susceptible to vibration due to their reduced mass. However, conventionally used techniques to avoid high vibration amplitudes (such as increasing the mass and/or applying damping mechanisms) are contradictory to the original goal of designing a lightweight structure. An increase of eigenfrequencies above external, exciting frequencies helps to prevent resonance phenomena. Here, we use a combined design and optimisation method to generate irregular lattice structures to investigate their potential of reaching much higher eigenfrequencies than those of regular structures, while retaining low weight and high stiffness. We generate parametric constructions of lattice structures with different degrees of structural irregularities, including regular lattices with constant and functionally graded strut cross-sections, and irregular lattices. Evolutionary strategic optimisation is used to maximise the first eigenfrequency. Geometric restrictions associated with selective laser melting are considered, and three optimised lattice structures are manufactured in selective laser melting using aluminium (AlSi10Mg). Their eigenfrequencies are measured in vibration experiments with a shaking table. Our approach allows the efficient generation of more than 500 lattice structures. The results show that by using irregular lattice structures, the first eigenfrequency is increased by 58% compared to a regular lattice structure of the same mass. The numerically obtained eigenfrequencies coincided well with the experimental results. It is argued that the implementation of higher degrees of structural irregularities allows the development of solutions with even higher first eigenfrequencies. In conclusion, we show that irregular lattice structures have a high potential to manipulate the eigenfrequencies of lightweight structures