Abstract

The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current"br" framework of increased transportation demand by developing and deploying solutions to optimise maintenance"br" interventions planning. INFRALERT develops an ICT platform - the expert-based Infrastructure Management"br" System eIMS - which follows a modular approach including several expert-based toolkits. This paper presents"br" the architecture of the eIMS as well as the functionalities, methodologies and exemplary results of the toolkits"br" for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv)"br" decision support. The applicability and effectiveness of the eIMS and its toolkits will be demonstrated in two"br" real-world pilot scenarios, which are described in the paper: a meshed road network in Portugal under the"br" jurisdiction of Infraestruturas de Portugal (IP) and a freight railway line in Northern Europe managed by"br" Trafikverket.

Abstract

Providing efficient and environmentally friendly multi-modal transport infrastructures is the key to economic"br" growth, competitiveness, and sustainability. Developing technologies and services for an increased availability"br" and accessibility of inland waterways is a way of strengthening this mode of transport as a competitive alternative"br" to road and rail. In Austria viadonau is taking this approach a few steps further, aiming to establish the waterway"br" Danube as a smart transport infrastructure of the future. The paper will provide an overview on recent"br" achievements and ongoing developments allowing for a seamless cyclic process in the field of waterway"br" infrastructure management. With semi-automatic analysis and measure planning, viadonau's Waterway Asset"br" Management System (WAMS) enables the implementation of pro-active maintenance strategies, including an"br" ongoing assessment and optimization of planned maintenance and construction activities. In addition, the"br" developed services compute all actual information which is needed for an efficient management and navigation.

Abstract

This paper presents a new service life database (DUREE database) for building elements, based on international service life data. The database includes 7‘000 service life data, for more than 2‘000 building elements. In addition, the fitting of the data to a lognormal distribution is presented. The study contributes to the increasing demand of probabilistic building LCA and LCC and provides the possibility to define statistical distributions, with a systematic way, for a large number of building elements and different levels of details (LOD), appropriate for BIM-based assessments.