Bond Modelling of prestressed concrete during the prestressing force release

This paper presents an analytical model for simulating the bond between steel and concrete, in precast prestressed concrete elements, during the prestressing force release. The model establishes a relationship between bond stress, steel and concrete stress and slip in such concrete structures. This relationship allows us to evaluate the bond stress in the transmission zone, where bond stress is not constant, along the whole prestressing force release process. The model is validated with the results of a series of tests and is extended to evaluate the transmission length. This capability has been checked by comparing the transmission length predicted by the model and one measured experimentally in a series of tests.

Bond modelling of prestressed concrete during the prestressing force release

This paper presents an analytical model for simulating the bond between steel and concrete, in precast prestressed concrete elements, during the prestressing force release. The model establishes a relationship between bond stress, steel and concrete stress and slip in such concrete structures. This relationship allows us to evaluate the bond stress in the transmission zone, where bond stress is not constant, along the whole prestressing force release process. The model is validated with the results of a series of tests, considering different steel indentation depths and concrete covers and is extended to evaluate the transmission length. This capability has been checked by comparing the transmission length predicted by the model and one measured experimentally in two series of tests.

An analytical model for simulating the bond of prestressed concrete during the prestressed force release

A bond analytical model is proposed in this paper. The model is capable of reproducing the bond stress developed between the steel and concrete, in precast prestressed elements, during the entire process of prestressing force release. The bond stress developed in the transmission zone, where the bond stress is not constant, is also obtained. The steel and concrete stresses as well as the slip between both materials can be also estimated by means of the relation established in the model between these parameters and the bond stress. The model is validated with the results of a series of tests, considering different steel indentation depths and concrete covers and it is extended to evaluate the transmission length. This has been checked by comparing the transmission length predicted by the model and one measured experimentally in two series of tests.

An analytical model for simulating the bond of prestressed concrete during the prestressed force release

A bond analytical model is proposed in this paper. The model is capable of reproducing the bond stress developed between the steel and concrete, in precast prestressed elements, during the entire process of prestressing force release. The bond stress developed in the transmission zone, where the bond stress is not constant, is also obtained. The steel and concrete stresses as well as the slip between both materials can be also estimated by means of the relation established in the model between these parameters and the bond stress. The model is validated with the results of a series of tests, considering different steel indentation depths and concrete covers and it is extended to evaluate the transmission length. This has been checked by comparing the transmission length predicted by the model and one measured experimentally in two series of tests.

Use of the energy-release rate in a 2 scale damage analysis of a bonded joint

Stress singularities appear at the extremities of an adhesive bond. They can produce a damage mechanism that we assimilate in this Note to a crack. The energy release rate permits to characterize its evolution. But a very refined mesh would be necessary for a real structure. Using an asymptotic method based on the small thickness of the bond a limit model with a different local behaviour is suggested. It leads to an approximation of the energy release rate

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.