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The current maintenance management for bridges is mainly based on visual inspection and aims at the repair of identified damages. In the project cluster "Smart Bridge" an adaptive system for holistic evaluation in real time is developed. The following pilot studies show significant aspects of the Smart Bridge. Within the research project "Digital Test Area Autobahn" a new constructed prestressed concrete bridge is implemented with instrumented expansion joints and bearings, a "RTMS©" and a sensor network. By using analytical bridge models and evaluation methods the condition and reliability of the bridge as well as the remaining service life is determined. In the pilot study "duraBASt" sensors for the detection of durability and structural safety as well as data analyzing and evaluation procedures are investigated. The aim of this study is the partial implementation of the aspects: data collection, data processing and model development for condition assessment of the bridge.
Road condition acquisition and assessment are the key to guarantee their permanent availability. In order to maintain a country's whole road network, millions of high-resolution images have to be analyzed annually. Currently, this requires cost and time excessive manual labor. We aim to automate this process to a high degree by applying deep neural networks. Such networks need a lot of data to be trained successfully, which are not publicly available at the moment. In this paper, we present the GAPs dataset, which is the first freely available pavement distress dataset of a size, large enough to train high-performing deep neural networks. It provides high quality images, recorded by a standardized process fulfilling German federal regulations, and detailed distress annotations. For the first time, this enables a fair comparison of research in this field. Furthermore, we present a first evaluation of the state of the art in pavement distress detection and an analysis of the effectiveness of state of the art regularization techniques on this dataset.
The case study "Digital Test Area Autobahn" is presented. A new built (September 2016) pre-stressed concrete bridge is equipped with different monitoring systems for the detection of traffic load, climatic influence and the reaction of the bridge. Possibilities for the implementation of a VoI (Value of Information) analyses are presented.
In future, additional and more detailed data are needed about the current conditions of bridges for preventive maintenance management. Monitoring procedures are not merely able to provide key performance indicators for a specific point in time, but also over a period. These KPIs must be selected in such a way as to permit substantiated statements about the present and future condition of bridges. For this reason, greater efforts must be made to define the significant KPIs for the various types of bridges, and show how these figures can be reliably determined. Both the COST Action TU1402, and TU1406 offer important approaches which, properly combined, can deliver substantial added value to the calculation and description of the condition of bridges in the interest of proactive maintenance management.
The Federal Highway Network of Germany represents considerable fixed assets. Construction and maintenance activities not only require a high budget, but also influence the traffic infrastructure and, thus, the economy and society as a whole. The present safety of the network has to be ensured under consideration of environmental aspects. At the same time the network owner has to make sure that the civil works are carried out in the most efficient way. Considering the fact that financial resources are restricted, the costs have to be spent in a way to obtain the greatest possible benefit. This task is supported by the application of a comprehensive Asset Management, which is subdivided into operational and controlling tasks respectively. The paper describes the current management procedures.
Germany's road infrastructure grew over centuries to become the arteries and lifelines of our society. The present safety of the infrastructure has to be ensured under consideration of environmental aspects. At the same time the owner has to make sure that the maintenance activities are carried out in the most efficient way. Considering the fact that financial resources are restricted, maintenance costs have to be spent in a way to obtain the greatest possible benefit. In the case of bridges, which are one of the most important parts of the road infrastructure in Germany, this task is supported by the application of a bridge management system (BMS). The existing German BMS contains assessment and optimization procedures on object and network level and is the basis for advancements to meet future demands. Developments concern life cycle and quality-oriented, holistically optimized procedures. Reasonable infrastructure management will contribute to meeting efficiency and sustainability objectives and to achieving interoperability. Here holistic network infrastructure management methods are required. There is a strong need for management solutions during the whole service life of a structure. The definition of criteria for evaluation of the relevance of failure mechanisms, including acceptance thresholds, requires the availability of relevant data for management procedure. Tools for innovative investigation methods and an effective data management will help in meeting the requirements. Relevant fields of research are improved maintenance strategies to meet future demands concerning heavy goods traffic, application and further development of nondestructive testing methods for efficient and sustainable management structures, and the improvement of analytic management tools to meet future demands.
This document describes the development and state of the art of orthotropic steel bridges in Germany. Following a short historical review of the performance of orthotropic bridge decks over the last decades, the present traffic loads are described and related to the resistance of the existing structures. Based on four different hazard categories, this paper describes different retrofitting methods. Although several promising strengthening techniques are introduced and evaluated, it appears that further research is urgently required in order to improve these techniques.