Analyse entrée-sortie

Résumé

L'analyse entrée-sortie, ou analyse entrées-sorties, est une modélisation économique utilisant le tableau entrées-sorties (TES) permettant de prévoir l'influence des changements dans un secteur d'activité particulier ou des changements de consommation sur le reste de l'économie. Il donne une représentation cohérente de la production nationale. Le tableau entrées-sorties a été conçu par le français François Quesnay au dans son Tableau économique (1759). L'analyse a ensuite notamment été développée par Wassily Leontief, qui a reçu le prix Nobel d'économie pour ses travaux en 1973. Modèle L’analyse entrée-sortie (ou intrant-extrant) est connue internationalement sous le nom d’analyse input-output. Historiquement, la première application pratique du modèle a été développée par Maurice Potron, jésuite et polytechnicien français, dès 1912. Cependant, ces travaux tombent dans l'oubli. L'idée sera reprise et diffusée avec davantage de succès par Leontief en (1941). Son modèle

Source officielle

https://fr.wikipedia.org/wiki/Analyse_entr%C3%A9e-sortie

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During construction, a large number of resources are consumed; concurrently, a large amount of greenhouse gas is emitted, which contributes to air pollution. There exist close interactions among construction regions. This study examined the main economy-resources-environment indexes associated with China’s construction industry, embodied in international trade based on the Eora database, by using the input-output model. It investigated the linkages of the economy-resources-environment nexus and suggests recommendations accordingly. We found that the total amount of input consumption and output emissions in China’s construction activities increased rapidly, both locally and abroad. China pulled much more emissions from construction-related activities abroad than the latter pulled from China. The overseas regions’ dependence on China’s construction industry gradually increased. Overall, China’s construction activities accelerated the rate of foreign countries’ resource utilization and air pollution more than it did economic profits for some of these countries. The effects on countries differed. China’s construction industry was closely related to the Asian, African, and Latin American undeveloped regions. In regard to the developed regions, cooperation with Australia, the UK, Sweden and Russia was more frequent. There existed a close relationship between all the economy-resources-environment indexes. Based on the findings, protective measures were suggested, including avoiding unnecessary construction activities, optimizing China’s economic and energy use structure, improving the efficient use of resources, strengthening environmental protection both abroad and locally, as well as reducing the export of products with high energy or resources consumption.

2020

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SO2, which is one of key components that can deteriorate the environment, can be relocated by international trade. Based on the EORA, the EDGAR databases and input-output model, this study calculated China's SO2 emissions caused by import and export, and presented a method to exhibit China's export-related SO2 footprint at a high resolution. The results showed that export generated more SO2 emissions than import, and the two both increased rapidly since 1990, but decreased in 2008 and 2010, respectively. Both importand export-related SO2 emissions were concentrated more in undeveloped regions and several developed countries. High percentage of China's export-related SO2 emissions were mainly observed on the secondary industry activities. The percentages for most sectors increased before 2005 and decreased in 2015. Spatially, the export-related emissions decreased obviously from the southeast to the northwest within China. China's export-related SO2 emissions showed an increasing trend overall during 1990-2012. Areas with increasing emission trends were mainly concentrated in areas where the secondary industries were concentrated, such as the North China Plain. Both the increasing and decreasing areas showed highly significant changing trends. The east and south showed intensive distributions of the highly significant changing trends.

ELSEVIER SCI LTD2020

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Determining crack kinematics from imaged crack patterns

Katrin Beyer, Ketson Roberto Maximiano Dos Santos, Bryan German Pantoja Rosero, Amir Rezaie

Determining the relationship between the cause of damage and the subsequent structural behavior of infrastructure systems requires an accurate characterization of the propagation of cracks, which represents the evolution of the damage state. When no information about the cause of damage is available, kinematic approaches can be used to describe the motion of crack contours. Current image-based approaches to derive crack kinematics use digital image correlation (DIC) on a set of sequential images as the crack propagates. However, DIC is invasive in that the structure surfaces must be painted with random speckle patterns, limiting its use primarily to controlled experiments. In this paper, we propose a novel image-based methodology for computing crack opening in Mode I or Mode II. As an input, this method takes a binary image from a semantic segmentation of an image of a crack pattern. This binary image is used to detect the opposite edges along the crack, which are then registered using an optimization algorithm based on the Euclidean transformation model and non-linear least squares. As a final output, this method produces displacement maps in the tangential and normal directions to the crack skeleton. To demonstrate its performance, we validate our methodology first with synthetic crack patterns and then with real crack patterns. Because this methodology for determining crack openings requires only simple data (just a binary crack pattern image), it is straightforward, robust, and adaptable, thus contributing to the development of structural image-based damage assessments. The computational codes and datasets are available to the public for future research and benchmarking on https://github.com/eesd-epfl/crack_kinematics and https://doi.org/10.5281/zenodo.6632071.

ELSEVIER SCI LTD2022

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