Arc-et-Câble: Construction Method

This lecture serves as a complement to the study of the Papeterie Burgo structure, focusing on the cable and roof system. The instructor explains the modeling of the cable, the introduction of additional elements for support, and the behavior of the structure under asymmetric loads. The lecture delves into the concept of self-anchored suspension systems, rare due to the need for specific construction methods. The instructor also discusses the construction process of the roof, highlighting a unique approach involving pylons, central cables, and lateral elements. By analyzing the compression and equilibrium within the structure, the lecture showcases a distinctive construction method that eliminates the need for anchor blocks. The session concludes by emphasizing the structure's design as an arc-and-cable system, providing insights into its construction and functionality.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts (21)

The Art of Structures I - Cables and arcs

L'art des structures propose une découverte du fonctionnement des structures porteuses, telles que les bâtiments, les toitures ou les ponts. Ce cours présente les principes du dimensionnement et les s

The Art of Structures II - Lattice structures, beams and frames

Les structures en treillis, en poutre, en dalles et en cadre sont essentielles pour une grande partie des constructions modernes : immeubles pour l'habitation ou de bureaux, halles et usines, ponts, o

In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information.

Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes).

In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on this page show how higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression (reversible data compression) which does not degrade the data.

Image compression is a type of data compression applied to s, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data. Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics.

A compression artifact (or artefact) is a noticeable distortion of media (including , audio, and video) caused by the application of lossy compression. Lossy data compression involves discarding some of the media's data so that it becomes small enough to be stored within the desired or transmitted (streamed) within the available bandwidth (known as the data rate or bit rate). If the compressor cannot store enough data in the compressed version, the result is a loss of quality, or introduction of artifacts.