Since a considerable portion of our work considers state-of-the-art research we produce a large amount of peer-reviewed papers, conference presentations and project reports. On this page we accumulate all published works and their abstracts. Feel free to get in touch if you have any further questions.
Bridges are a vital, but also extremely vulnerable part of transportation infrastructure. The design and construction of a bridge have a large influence on its longevity although these phases are short compared to its life span. It is therefore essential that at the acceptance the bridge together with the accurate as-built information is delivered to the owner. A bridge owner relies on as-built high-quality information and on information on a bridge condition to initiate interventions that ensure its safety and serviceability. The information on the bridge condition is obtained through regular inspections as well as monitoring activities. During the lifetime of a bridge, these diagnostic activities may generate a huge amount of data that needs to be managed. With changing environmental actions, accurate and usable information from the inspection and monitoring – in conjunction with as-built data – is essential for efficient and timely maintenance planning.
Inspections and maintenance planning require organized, automated, open and intuitive digital processes, which should consider both object data and related condition data. This seamless digital process is supported by existing Bridge Management Systems but can be vastly improved. In particular, most BMS do not support geometric representation which makes data collection during inspections quite tedious. The introduction of BIM in BMS can substantially facilitate the collection of inspection data and accurately localize monitoring data. Moreover, the exact geometry of bridges can enhance maintenance planning by simulation of the structural behaviour of the as-is structure under different environmental actions. BIM’s incorporation would evolve BMS into a fully digital storage system and a platform for data exchange with existing BIM solutions as well as for maintenance planning that include deterioration forecast, optimization and analysis models. The vision includes 3D+ software and hardware independent data exchange between different software technologies during life span and beyond. Open BIM technology for interoperability from the technical, semantic and organizational points is of main interest. The current status of development and challenges that need to be overcome for the successful fulfilment of the presented vision are discussed.
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Die Prognose der Zustandsentwicklung ist eine wesentliche Komponente innerhalb des Erhaltungsmanagements der Straßeninfrastruktur. In Deutschland wird hierfür derzeit ein deterministisches Prognoseverfahren eingesetzt, das mit Hilfe von Verhaltensfunktionen und deren Kalibrierung die Zustandsentwicklung eines Straßenabschnittes prognostiziert. Gleichwohl ist das Zustandsverhalten von Straßen von einer großen Anzahl an Einflussfaktoren geprägt, die eine treffende Prognose erschwert. Die damit verbundenen Unsicherheiten sind mit den bisher eingesetzten deterministischen Prognosemethoden nicht abbildbar. In diesem Beitrag wird eine zweistufige probabilistische Bayes’sche Methodik zur Prognose der Zustandsentwicklung von Fahrbahnen auf der Grundlage des Extended Kalman-Filters (EKF) vorgestellt und deren praktische Anwendung auf Straßenzustandsdaten aufgezeigt. Das entwickelte Modell ist in der Lage, sowohl die Unsicherheiten im zukünftigen Verhalten des Straßenzustands aufgrund von zahlreichen Einflussfaktoren, wie z. B. den Materialeigenschaften und der Verkehrsbelastung, als auch Unsicherheiten aufgrund der Messpräzision der Zustandserfassung abzubilden. Der entwickelte Bayes‘sche Ansatz ist für beliebige Zustandsmerkmale (z. B. Längs- und Querebenheit, Griffigkeit, Risse usw.) anwendbar. Die Methodik wurde in einen webbasierten IT-Prototyp implementiert und anhand von Daten aus Straßennetzen in Deutschland, Österreich und der Schweiz erprobt. Die Prognoseergebnisse zeigen eine hohe Übereinstimmung zu den Daten aus dem Validierungsdatensatz. Neben der Prognose der mittleren Zustandsentwicklungen bietet das Verfahren den wesentlichen Vorteil der Quantifizierung von Unsicherheiten in der objektbezogenen Zustandsprognose. Damit liefert die Methodik einen wichtigen Baustein auf dem Weg zu einem risikobasierten Erhaltungsmanagement.
Eine leistungsfähige und sichere Straßeninfrastruktur ist die Grundvoraussetzung für gesellschaftlichen Fortschritt: Sie ermöglicht Wirtschaftswachstum, Beschäftigung und Wohlstand und stellt damit das Rückgrat einer modernen Gesellschaft dar. Ein wachsamer Infrastrukturbetreiber kann die Szenarien, welche die Sicherheit und Leistungsfähigkeit der Straßeninfrastruktur gefährden könnten, rechtzeitig erkennen und Gegenmaßnahmen zur Abwendung dieser Szenarien planen und einleiten. Die Entscheidungsfindung zu diesen Maßnahmen ist die Hauptaufgabe des Erhaltungsmanagements und ihre Qualität ist von Umfang und Qualität der verfügbaren Daten abhängig ist. Durch den Einsatz von Building Information Modeling (BIM) stehen Daten zur Verfügung, mit welchen die Straßeninfrastruktur realitätstreu während der gesamten Lebensdauer abgebildet wird. Mit dieser Datengrundlage können die in den letzten Jahrzehnten entwickelten da- tenhungrigen Modelle eingesetzt werden, mit welchen das Verhalten der Infrastruktur unter verschiedenen Einwirkungen simuliert werden kann. Diese Simulationen ermöglichen bessere Entscheidungen in Bezug auf die Auswahl von baulichen Maßnahmen und folglich eine effizientere Nutzung der Straßeninfrastruktur. Der Artikel zeigt das Nutzenpotential eines BIM-basierten Erhaltungsmanagements sowie wie die hierfür erforderlichen BIM(odelle) bereitgestellt werden können.
As a result of the CEDR Call 2015 (project Interlink) a framework for a European road OTL is available. AMSfree builds on this result and aims for a wider implementation among individual CEDR members. The AMSfree project analyses the architecture of Infrastructure Asset Management Systems (IAMSs) used by National Road Authorities (NRAs), as well as the asset information content in current IAMSs in order to establish detailed technical requirements for linking IAMS and Building Information Models (BIMs) as infrastructure asset databases on a macro and micro level. The analysis is performed on a range of BIM models utilized by designers and contractors, so the level of development (LOD) for the common infrastructure asset BIM can be agreed on. Hereafter the recommendations for handling the insufficient exchange data are established, as well as the rules for semantic transformation. All data from the source systems is transferred to a reference database by using the established transformation rules.
The semantic transformation between different legacy systems is enabled on the basis of the Industry Foundation Classes (IFC) property templates, taking into account the IFC import/export capabilities of various systems. Specifically, a universal mapping approach between different IFC properties of different legacy systems is defined. For this purpose, a corresponding architecture is developed and prototypical implemented. Existing national data formats (e.g. OKSTRA, Interlis2) are linked with the IFC format.
Based on the results, the interoperability proof-of-concept is developed. Afterwards, the requirements are defined to enable the linkage between the data in IAMS and the IFC model. Based on the requirement a prototype is developed and documented.
The ageing of bridge stock in developed countries worldwide and the increasing number of recorded bridge collapses have underlined the need for more sophisticated and comprehensive assessment procedures concerning the safety and serviceability of structures. In many recent failures, construction errors or deficiencies have contributed to the unfortunate outcome either by depleting the safety margin or speeding up the deterioration rate of structures. This research aims to quantify the impact of construction errors on the structural safety of a bridge considering corresponding models available in the literature that probabilistically characterise the occurrence rate and severity of some of these errors. The nominal probability of failure of structures, neglecting construction errors, is typically computed in numerous works in the literature. Therefore, the novelty of this paper lies in the consideration of an additional source of uncertainty (i.e., construction errors) combined with sophisticated numerical methods leading to a more refined estimation of the probability of failure of structures. Accordingly, some benchmark results focussing on error-free and error-included scenarios are established, providing useful information to close the gap between the nominal and the actual probability of failure of a railway bridge.
Bridge Management Systems (BMSs) are sophisticated software tools, widely used for managing bridges. Comprising a centralized database of all relevant information for the entire bridge stock and analytics to forecast bridges’ condition and maintenance cost, BMSs are irreplaceable tools, used by all the National Road Authorities (NRAs) around the world. These powerful tools, although different from one another, all lack adequate visualization of bridges. Recently, numerous researcher proposed using the Building Information Models (BIMs) to address this issue.
This paper presents the geometric approach of introducing BIM to BMS. Rather than trying to thoroughly connect these two robust systems on the object definition level, this approach focuses on geometry. The paper firstly shows how all the inventory information from BMS can be associated with corresponding BIM objects. Afterward, the ways to include the condition assessment data into BIM are proposed. Once the basics of the geometric approach are explained, the example of connecting BIM with BMS is presented. The example is based on KUBA, the Swiss BMS.
Finally, the feasibility, as well as the challenges of the presented approach are analyzed. The analysis focused on two important questions. Firstly, it considered if BIM is capable of making workflow changes in the Infrastructure Asset Management (IAM) the same way it did it in the construction industry. Secondly, it evaluated the BIM capability to describe all the condition assessment information relevant to IAM.
Bridges are a vital, but also extremely vulnerable part of transportation infrastructure. The design and construction of a bridge have a large influence on its longevity although these phases are short compared to its life span. It is therefore essential that, at the acceptance the bridge together with the accurate as-built information is delivered to the owner. A bridge owner relies on an as-built high-quality information and on information on bridge condition to initiate interventions that ensure its safety and serviceability. The information on bridge condition is obtained by regular inspections as well as monitoring activities. During the lifetime of a bridge these diagnostic activities may generate huge amount of data that needs to be managed. With changing environmental actions, accurate and usable information from the inspection and monitoring – in conjunction with as-built data – is essential for efficient and timely maintenance planning. Inspections and maintenance planning require organized, automated, open and intuitive digital processes, which should consider both object data and related condition data. This seamless digital process is supported by existing Bridge Management Systems but can be vastly improved. In particular, most BMS don’t support geometric representation that render data collection during inspections quite tedious. The introduction of BIM in BMS can substantially facilitate the collection of inspection data and accurately localize monitoring data. Moreover, the exact geometry of bridges can enhance maintenance planning by simulation of structural behavior of as-is structure under different environmental actions. BIM’s incorporation would evolve BMS into a fully digital storage system and a platform for data exchange with existing BIM solutions as well as for maintenance planning that include deterioration forecast, optimization and analysis models. The vision includes 3D+ software and hardware independent data exchange between different software technologies during life span and beyond. Open BIM technology for the interoperability from technical, semantic and organizational point is of main interest. Current status of development and challenges that need to be overcome for successful fulfilment of the presented vision are discussed.
Die bestehenden Asset-Managementsysteme werden sowohl als Auskunftssysteme als auch als Basis für die Entscheidungsfindung im Erhaltungsmanagement benutzt. Die Verkehrsinfrastruktur wird dabei meist in einem 2D-GIS visualisiert, auf einer 3D-Geometrie basieren die Asset-Managementsysteme bisher nicht. Erste Pilotprojekte haben deutlich gezeigt, dass das BIM-basierte Asset Management ein großes Nutzenpotenzial hat. Dies beschränkt sich nicht nur auf intuitive Interkationen bei den Datenabfragen, sondern trägt auch zum visuellen und fachlichen Verständnis der Verknüpfung der einzelnen Bestandteile der Verkehrsinfrastruktur und der umfassenden Dokumentation bei, welche dem Betreiber nach dem Neubau oder der Erhaltungsmaßnahme übergeben wird. Zudem können bisherige Unterbrüche in der Informationskette zwischen Bauausführung und Erhaltungsmanagement geschlossen werden. Somit ist eine sehr detaillierte Informationsbasis vorhanden, welche über die Lebensdauer genutzt werden kann. Die Asset-Managementsysteme ihrerseits enthalten gut strukturierte Daten mit adäquater Semantik und Ontologie, welche sich als eine Grundlage für diese Verknüpfung anbieten. Eine Verknüpfung dieser Daten mit den BIM Modellen aus dem Bereich der Bauausführung steigert die Nützlichkeit von bereits vorhandenen Informationssystemen und ermöglicht ein intuitives Asset Management. In diesem Beitrag wird aufgezeigt wie diese Verknüpfung über die gesamte Lebensdauer erfolgen kann.
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In maintenance management, the aim is to achieve or maintain a required level of performance of the existing road infrastructure by systematically determining necessary and optimal maintenance measures. Models for the condition development of roadways are an important building block for the estimation of long-term maintenance costs. The aim of the mapFALKE research project was the further development of methods for the formation of condition prediction models using extended calibration procedures for the determination of behaviour-oriented material properties.
The methodology for the development of deterministic and probabilistic models was identical to the procedure for empirical investigations using observations and their influencing factors. The novelty in the field of condition development models is the use of road data available throughout the network on the one hand, which usually includes only the condition data, and on the other hand data from existing or additionally easily collected laboratory results from local material investigations for the calibration of the models of individual road sections. Within the framework of the model development and calibration, data from material investigations were required, which were available through existing laboratory results from past research work in Germany and Switzerland, on which further material investigations could be carried out. In addition, existing research data could be evaluated again for the modelling. In addition, correlations were tested on existing condition data. Different types of models for the development of the condition were identified and a simple model was developed with a step-by-step approach for calibration depending on the data basis. The current data situation in Switzerland does not yet allow a calibration based on the material investigations. The developed approach can nevertheless be used with a limited data basis to generate models of the condition development from the road operator’s own existing road data. The requirements for the input data were defined and the application in different use cases was demonstrated. The calibration includes the use of new information from current survey campaigns. In addition, the use of additional material investigations is shown.
Within the framework of this research project, various insights were gained from the processing and the results obtained, and corresponding conclusions were drawn. These concern the existing data situation and quality of the condition data of the road surface as well as the data on the layer structure and the associated material investigations. Recommendations for practice, standardisation and further research are derived from this.
With increasing heavy traffic, the maintenance needs to ensure safe and reliable utilization in particular on federal highways, but also on state roads will substantially increase in the future. At the same time, these roads in urban areas are already reaching the limits of their capacity. Therefore, the negative impacts of work zones on traffic flow caused by maintenance interventions should be avoided as far as possible. So far, the effects of maintenance-related road work on road users can only be determined with insufficient accuracy. However, this is indispensable to perform a benefit-cost comparison of the different technically possible maintenance measures for roads and road structures as well as the cross-asset decision-making. The present article describes the developed framework for the application of macroscopic traffic simulation in the field of maintenance management. In this way, the influence of maintenance-related work zones on travel times can be estimated and taken into account in decision-making in a macroeconomic approach. Finally, recommendations for practice and further research needs are discussed.
Safety, reliability, and availability of transportation infrastructure are jeopardized by oncoming natural and man-made hazards that may inflict severe consequences to its stakeholders. In order to avoid or mitigate these extreme events with adequate activities and expedite the recovery in a case of failure, risk-based information-driven approaches are applied in asset management. Here, the main challenges for engineers are to be far-sighted in detecting possible threat scenarios that lead to critical failures, and in estimating related consequences over time. Within these tasks, there are numerous uncertainties to consider: hazards’ intensity & frequency and related asset exposure, increased traffic demand and asset deterioration. Evidently, the prudent decision-making must be based on previous experience, involve various engineering expertise, and entail handling with large amounts of data. Thus, decision support tools (DST) are being developed to aid infrastructure managers to extract the diagnostic information from inspections/monitoring and consider diverse types of risks while balancing stakeholders’ demands and optimizing priorities over all infrastructure asset types.
Recently, risk-based approaches are being expanded to include the aspects of early warning of imminent failure(s) and contingency planning for an extreme event. These topics have been investigated within the scope of a European HORIZON2020 project SAFEWAY, which has a goal to develop a robust, resilience-based decision support framework for management of terrestrial transportation infrastructure. The paper presents the features of the web-based DST prototype, which is one of the main outputs of the SAFEWAY project. The DST allows for temporal risk analysis of assets in an infrastructure network for predefined threat scenarios and maintenance strategies. Here, the benefits of possible maintenance activities can be expressed as a discounted risk reduction, which in turn can be understood as resilience improvement. The resilience of an analysed network can be evaluated for contingency plans, both in medium to long-term as well as in short-term. The application of the DST is demonstrated on the pilot case study within the SAFEWAY project – the road and rail networks in the Santarem region in Portugal. The analysed case study comprises risk/resilience evaluation for predefined failure scenarios of bridges and road/track due to a future extreme flooding event.
In order to be able to estimate the financial resources required for the maintenance of the entire federal trunk road network, maintenance demand forecasts are carried out for a period of 15 years. Pavement Management Systems (PMS) are used for the forecast calculation for pavements. The derivation of technically and economically reasonable maintenance measures and times for sections in need of maintenance is essentially based on an analysis of causes of damage. These are described in a so-called defect class model. During the implementation of the last maintenance needs forecast 2016-2030, it became apparent that this model was severely outdated. The existing model variants were then analysed and revised. The examination and further development of the existing model variants showed that even simplified approaches for deriving maintenance measures in a decentralised context lead to plausible and comparable results at the network level.
There are endangering scenarios that don’t announce themselves such as natural hazards, so there is no ample time to prevent failures of road infrastructure by maintenance measures. It should be noted that the consequences of failures depend not only on immediate losses (e.g., life and limb and material loss), but also on unavailability of infrastructure until it is fully available as before a failure. This means that not only by preventative measures but also by judicious planning of recovery measures, the consequence of failure and therefore risk can be reduced. The consideration of recovery time is essential in estimation of resilience. This article gives an overview on theoretical background of resilience approach and discusses the current state of application of the resilience frameworks in practice. The measures, which target specific resilience aspects, are presented within the case studies that are presented in a separate paper.
PIARC Ref.: RR389-023
The EU-funded HORIZON 2020 project SAFEWAY aims to design, validate and implement holistic methods, strategies, tools and technical interventions to increase resilience of terrestrial transport infrastructure in the face of natural and man-made hazards. The basis for the project is establishing a robust decision support framework which can utilize remotely monitored data on hazards, infrastructure condition and traffic, to yield knowledge on the dynamics of relevant risk factors associated with potential asset failure scenarios. The first task of the framework is elaborating a value system regarding network resilience, based on monetized direct and indirect consequences of inadequate asset performance. Here, the quantitative risk assessment is will be used to estimate the expected loss of benefit of infrastructure due to failures for both single mode and for multi-modal transportation. The benefits of possible maintenance strategies can be expressed as discounted risk reduction, which in turn can be understood as maximizing resilience.
The economic and social losses due to increasing bridges collapse over the years have underlined the importance of the development of more robust bridge structural systems when exposed to harmful events, such as natural hazards, human-made hazards and human errors. Natural and human-made hazards are usually explicitly addressed in the numerous works available in the literature, but when it comes to human errors, very few studies can be found. It is worth mentioning that human errors have been identified as one of the main causes of bridges failure. Consequently, the main goal of this paper is the assessment of human errors impact on the robustness and safety of a prestressed reinforced concrete bridge through a probabilistic-based approach. Uncertainties concerning the numerical model, material strength, geometry and loading condition are used as key input parameters for the probabilistic assessment. Considering the structural system performance in its early days (i.e., virgin reliability index) the human error impact in structural safety is measured according to the structural system performance reduction given different errors with different magnitudes. Therefore, the structural system ability to maintain acceptable levels of performance, given such errors, is assessed.
Inspection of bridges has been a standard assessment procedure for decades. Its purpose is to identify and record all defects of the bridge structure. Normally used inspection techniques are rather simple, mainly relying on visual assessment. This dissertation proposes an improvement of concrete bridge inspection in terms of visual data acquisition, damage identification and digital representation of the bridge with identified damages. Instead of depending strictly on the human eye, photogrammetrically obtained 3D point clouds are used to identify and extract concrete damage features. As the most comprehensive substitute for the old-fashioned inspection report, Bridge Information Model (BrIM) is used as an inventory and inspection data repository. An Industry Foundation Classes (IFC) semantic enrichment framework is proposed to inject the extracted and reconstructed damage features into the as-is IFC model. After the general data model for damage description and its IFC representation are established, the method for generating the as-is IFC model of the bridge is proposed. Damage is identified as a deviation of the as-is geometry, represented by the 3D point cloud, from the as-built geometry, represented by BrIM. Geometric and semantic enrichment of the IFC model is achieved by injecting the reconstructed 3D meshes representing damaged regions and corresponding BMS catalogbased damage information. The proposed method uses Constructive Solid Geometry (CSG) Boolean operations to geometrically enrich the IFC geometry elements, which align with corresponding damage regions from the as-is point cloud. Damage information (e.g., type, extent, and severity) is structured so that it complies to the BMS data structure. Finally, the proposed data model, damage identification, feature extraction, and semantic enrichment method are validated in the presented case study.
In 2011 a long-term pavement performance (LTPP) section was established on a part of the Federal Highway BAB A5 in the centre of Hesse. The aim of this project is to build up a high- quality database for research activities within the field of road maintenance. In addition to the six-monthly pavement condition surveys, data on pavement structure and traffic loads as well as on maintenance and rehabilitation activities are documented in high detail. This article gives an overview of the extent and quality of the collected data.
In order to exemplify the potential of the available data of this LTPP-section to answer various research issues, the influence of different factors on changes in road condition is analysed based on the road condition indicator rutting. Within four years, changes in rutting are more effected by the scattering of the measuring method than being true condition changes. In conclusion, statements about changes in rutting are not reliable without any additional information on the age of the pavements. As a conclusion, an outlook on future investigations is given.
Efficient and secure transport infrastructure is the fundamental prerequisite for social progress. It enables economic growth, employment, and prosperity and thus represents the backbone of modern society. Planning, construction, operation, and maintenance of roadways require significant use of both financial and human resources. The Federal Transport Infrastructure Plan 2030 provides for a total volume of about € 270 billion, of which about € 70 billion will be used to maintain the existing road network by 2030 [BMVI 2016].
In Germany, a Pavement Management System (PMS) is used for a purposeful and objective distribution of funds, which estimates the maintenance requirements of federal highways based on the current state of the network and its future development. For this purpose, modern evaluation methods, as well as sound expertise, are needed. Estimates of the temporal status of pavement fortifications represent an essential element within the PMS in order to estimate the section-related maintenance requirements. The results of these previously deterministic calculations provide the basis for the subsequent decision-making process. The inherent uncertainties within this planning and decision- making process are due to various causes, such as data collection, data maintenance, different material behavior, and traffic and climatic boundary conditions. For future risk-based decision-making, suitable methods are required that can quantify possible events and their associated probabilities of occurrence based on scenarios.
An accurate description of road deterioration is one of the most challenging aspects within the scope of Pavement Management Systems (PMS). However, the data quality is often insufficient, as research has shown a high amount of road sections with measured condition improvements based on a simple comparison of two condition monitoring campaigns. The reasons for these improvements are often unknown due to restricted data quality of recorded maintenance works. Concerning an asset of the current state of a road network, this aspect is not that relevant because measurement errors lead to condition improvements as well as to condition deteriorations. However, concerning a longitudinal analysis of road condition, a consequent exclusion of measured condition improvements leads to a systematic violation of type one and type two errors from a statistical point of view: Road sections whose condition truly got worse are excluded due to measured condition improvements. Even though the mentioned problem is already partially known, suitable methods to handle this issue hardly exist.
The aim of the present study is the development and validation of a probabilistic forecasting model, which takes both the uncertainties in the condition state detection and the estimation of the condition state development into account. Based on a comparison of the predicted condition states with the results of the previously used deterministic methods, the applicability of the developed model shall be assessed. The developed method should enable a future risk-based decision-making process within systematic pavement management. This research is based on data from a long-term observation section in Hesse, Germany. In addition to the condition assessment and evaluation (ZEB), which is carried out every four years, semi-annual condition surveys on each driving lane have been carried out on the approx. 76 km long section of BAB A5 for several years. Furthermore, data on traffic loads, structure, and climatic conditions are collected, and all maintenance and rehabilitation treatments are documented in great detail.
The core element of the developed method is a Bayesian approach. The presented model differentiates between the true condition state of a road surface, observations in the form of condition measurements, and an estimated system behavior at discrete points in time. By combining an a priori system behavior with the continuous comparison between expected and noisy measured condition states, the true condition state of an evaluation section is deduced. The method offers the possibility of a probabilistic prognosis of the most likely condition development over time in order to reflect the large variety of possible condition state developments accurately. The developed method is presented by the example of rutting. Since the condition state development of a road surface is subject to a large number of influencing variables, considerable scattering is observed, which makes it challenging to arrive at an appropriate condition state prognosis. In order to reduce the uncertainties in the forecast, additional information is integrated into the model. First of all, potential influencing factors are identified, and the resulting hypotheses are subjected to a statistical test. The analyses are done with the help of a longitudinal structural equation model (SEM), which is gradually extended by the variable traffic loading. At the end of the investigations, the results calculated with the stochastic prediction model are compared to the results of the previously used deterministic prognosis methods.
As a result, the condition data can be improved by estimating the state distribution after 20 years. Compared to the unprocessed condition data, the deviation between true and predicted mean values can be reduced from 1.0 mm (SD = 1.2 mm) to 0.1 mm (SD = 1.5 mm). In addition to improved prognosis, the data can be enhanced significantly to provide the data basis used to estimate transition matrices. After data preparation, only about 5 % of all evaluation sections have a condition state improvement, whereas in the case of non-processed data, approx. 50 % of the data basis must be discarded due to measured condition state improvements. Due to the enlarged data basis, the transition distributions within the matrices can be modeled more precisely. Based on further differentiation of the state changes according to traffic loads and the respective present type of structure, the condition state distributions of all evaluation sections can be predicted with high accuracy. The deviation of the mean value between true and predicted condition state distribution is 0.0 mm. For the associated standard deviation, a value of 2.6 mm is predicted compared to the standard deviation of the true condition state distribution of 3.2 mm. The comparison between the deterministic and the stochastic method shows that the developed model provides comparable prognosis results to the deterministic method used in the current German guidelines RPE-Stra 01.
The developed probabilistic model allows consideration of the current uncertainties in the estimation of the remaining service life as well as in the planning of maintenance works. The comparison of different maintenance strategies based on probability distributions provides the basis for risk-based decision-making. This fact represents the main advantage, in contrast to deterministic prognosis methods. The high variability in the development of road condition indicates that essential factors influencing the temporal behavior of pavements are currently not recorded across the road network. In particular, this includes information on bearing capacity, which is not yet available at the current time throughout the network. This approach will be focussed in the future since the causes of road surface damages can be thoroughly analyzed only by considering the structural behavior of the road section. Furthermore, a fundamental prerequisite is the systematic documentation and maintenance of all collected data. With the help of this essential information, the condition prognosis can finally be refined.
Building Information Modeling (BIM) representations of bridges enriched by inspection data will add tremendous value to future Bridge Management Systems (BMSs). This paper presents an approach for point cloud-based detection of spalling damage, as well as integrating damage components into a BIM via semantic enrichment of an as-built Industry Foundation Classes (IFC) model. An approach for generating the as-built BIM, geometric reconstruction of detected damage point clusters and semantic-enrichment of the corresponding IFC model is presented. Multiview-classification is used and evaluated for the detection of spalling damage features. The semantic enrichment of as-built IFC models is based on injecting classified and reconstructed damage clusters back into the as-built IFC, thus generating an accurate as-is IFC model compliant to the BMS inspection requirements.
By maintaining Uri road infrastructure, the cantonal road agency is ensuring safety, reliability and driving comfort on the roads for passengers and freight transport and thus, contributes to economic and social added value. The canton Uri has one of the first road agencies with an infrastructure division responsible for all road infrastructure objects. This includes inventory, condition inspections, maintenance planning and necessary data management. Uri maintenance and rehabilitation processes for pavements are embedded in a holistic road asset management process supported by an essential IT infrastructure.
One of the key applications is a flexible decision support tool “infFaros Uri” which was customized and developed together with the infrastructure division of canton Uri to meet their needs. infFaros can handle road sections and bridge together allowing synergy effects and corridor planning. It supports various methodologies including probabilistic and deterministic deterioration, cost/benefit and cost/effectiveness decision-making as well as consideration of four-year maintenance and rehabilitation plan and evaluation of its impact. By linking short- and long-term maintenance and rehabilitation planning using existing cantonal transportation data complex questions can be answered and decision making can be efficiently supported by scenario comparisons. infFaros is a modern web-based application. The paper presents both the technical background of the software and use of it to support four-year maintenance and rehabilitation planning within new Uri road asset management process.
The increased need to manage road infrastructure in holistic manner led in the recent years to vivid research in diagnostics and maintenance planning of all types of road infrastructure objects. The practice lags behind this research and with very few exceptions a silo-based approach to maintenance planning is still dominant within the road agencies. The implementation of a holistic
approach in practice is also hampered by the lack of scientifically sound and yet flexible decision support tool that can handle data of varying quality. With the goal to remove this obstacle and based on the long-term research, the development of infFaros started in 2015.
infFaros can handle road sections and road structures (e.g. bridges) together making use of synergy effects and allowing corridor planning. It supports various methodologies including probabilistic and deterministic deterioration, cost/benefit and cost/effectiveness decision-making as well consideration of already scheduled interventions and the evaluation of their impact. infFaros is a modern web-based application. The paper presents both technical background of the software and outlines its software architecture.
It is widely accepted that safety and serviceability are primary concerns in bridge design. However, for the most of bridges’ service life, these concerns are addressed indirectly by a qualitative measure, defined herein as condition rating, which is based upon observable damages recorded during inspections. Condition rating is at best, only loosely correlated to safety and serviceability. It would
be more reasonable to address safety and serviceability in an inspection process directly, using the information on bridge performance obtained during the design and construction.
To address this issue, the reliability was chosen as a Key Performance Indicators (KPI) for existing bridges and a novel practical solution is proposed. It is based on survey of observation types (visible defects, measurements, etc.) used in Europe, which were examined with regard to their potential impact on reliability regarding safety and serviceability. The impact of these observations on reliability is also dependent on their type, location and intensity/extent as well as on bridge structural systems. The paper presents a methodology to assess reliability, which heavily relies on data from design and construction phase. It also proposes a set of data elaborated in design and/or construction phase that need to enter current bridge data bases to allow a rough reliability assessment of existing bridges.
The main objective of the COST Action TU1406 is to develop a guideline for the establishment of Quality Control plans for roadway bridges. The guideline is based on conclusions of Working groups 1 and 2 of the Action and is further developed with the contributions and findings of members of Working group 3. The paper presents the overview of the developed framework, where gradual damage processes as well as sudden events are being addressed in evaluation of Key Performance Indicators. The proposed framework relies on data from design and construction phase, as well as from results from visual inspections that are used for an assessment of safety and serviceability – the primary concerns of bridge managers. Special attention is aimed at possible Failure modes and related bridge Vulnerable zones. These are, for instance high moment regions, high shear regions and constructions joints, but can also be zones of bridge conceptual weaknesses. Since there are differences in design and materials for various bridge types, the suitability of the framework is tested separately for girder/frame bridges and arch bridges. Due to the specifics of sudden events, the application of the framework is given separately from gradual damage processes. Emphasis is given on flooding and scour as these are the most common culprits of bridge failures. The steps in the implementation of the framework are briefly shown and an illustrative example is presented.
In the last 40 years road organisations have been striving to adapt and upgrade their policies and procedures using the benefits of novel IT technologies. The efforts have been aimed at elaborating and applying innovative methods to collect useful data and to transform them into high-quality information. Furthermore, significant efforts have been put to resourceful approaches to use this information in decision making. The work of Technical Committee D1 “Asset Management” focused on investigating the organisations’ procedures/policies and management systems to identify innovative approaches.
The report is available online here.
It is foreseeable that in not so distant future, Building Information Models (BIM) of both newly built and existing bridges will be available. These models can and will be included into the Bridge Management System (BMS) and will significantly enhance the quantity of useful information in future BMS. Apart from exact semantic and spatial specification, BIM can embed realistic structural system of a bridge as well as the relevant load situations. The evaluation of the reliability or safety/serviceability would be therefore possible quasi, on-the-fly within the future BMS, provided that the observations and results from SHM can be adequately integrated in BIM. In principle, the
inspection results can be directly captured in the BIM using photogrammetry or some other procedure. Cracks, spalling, deformation, and other defects will be a part of a BIM, which in the most cases alter the BIM geometry.
The data stored in future BMS include also other changes that a bridge experience during its life span. This includes strengthening, widening, seismic retrofit and other structural changes. In short fBMS is similar to the 6D BIM or Asset Information Model, which continues to be updated during the whole service life of a bridge.
The paper discusses the BIM requirements of owner and operators and shows where these deviate from design and construction needs. It presents conceptual framework for integration of BIM in BMS developed by the authors in recent years.
The prediction of road behavior is characterized as a variable process defined by several exogenous factors, such as traffic loads or climate, and endogenous factors, for instance planning, type and quality of construction. This paper discusses the procedure of analyzing big data and potential sources of error by using a pure statistical approach. Therefore, explanatory variables such as age of surface layer, traffic loads and structure thickness were analyzed con- cerning their power of influence on rut depths. This investigation was based on a part of the Ba- varian road network. The results confirmed that the age of a road section, structure thickness and traffic load are effective variables to explain the prospective condition of roads. The used methodological approach offers substantial advantages but has drawbacks as well that have to be taken into account and which are also discussed.
The test methods for four scuffing devices had been written up as technical specification PR CEN/TS 12697-50, Resistance to scuffing, which was reviewed by the DRaT project, under CEDR Call 2014: Asset Management and Maintenance. Existing knowledge on scuffing was reviewed and a round robin testing programme was undertaken with four replicate samples of three variations each of three mixture types. A statistical analysis found that results from the different devices could not be accurately correlated, either for specific asphalt mixture types or overall, nor could specific designs of scuffing equipment be identified as be- ing best for identifying the scuffing-resistance of asphalt mixtures. Nevertheless, enhancements to PR CEN/TS 2697-50:2016 were identified that can be made to make a better and more unified document without rejecting any of the designs of scuffing apparatus. A copy of the revised version of the standard was given in the final report.
With the increasing automation in the field of transportation and the increased demands with regard to the quality of road data, the need to enhance spatial reference of road data from axis to lane referencing has become more importance. Strong drivers of this trend are
autonomous driving, traffic navigation, traffic management, traffic modelling and simulation. However, lane-related data is also widely used in the area of road infrastructure.
The aim of this project is to develop an extension of the model for spatial reference of road data, which allows for lane level instead of “just” road level location referencing. This allows a more precise location description of road data, which are primarily lane-related, such as usage, road condition, signaling, turn restrictions, traffic volume and accidents.
The Serbian road network includes a large portion of bridges with shallow foundations vulnerable to local scour as tragically demonstrated during the extreme flooding in May 2014. Currently, the bridge management procedures in Serbia and worldwide do not comprehensively account for a risk of bridge failure due to flooding and fail to provide sufficient information for the decision-making. Thus, a novel methodology for quantitative vulnerability assessment is suggested as a tool to identify the most vulnerable bridges in a network. Herein, the essential task is evaluation of the conditional probability of a bridge failure due to local scour in a flooding event of a certain magnitude. To apply this approach on a network level, there is a dire need to establish precise practice-ready guidelines on an optimal set of information to be used and/or collected in situ, which is discussed on an example of the Serbian bridge database. The vulnerability of a bridge to local scour may be used as a comprehensive indicator of a bridge performance in a flooding event. For a network level, the vulnerability maps with respect to flooding of different magnitudes will give road operators crucial information to apply adequate quality control plans to vulnerable bridges.
Following the principles and goals of COST TU1406 action and the results of preceding WG1 and WG2 reports, the WG3 report elaborates the framework to establish quality control plans for road bridges. The qualitative approach is suggested in evaluation of the key performance indicators (KPIs): Reliability, Availability, Safety, Economy and Environment, with a possibility for an upgrade to a full quantitative approach. It is intended to use all relevant information from inventory and inspections, coupled with engineering judgement. The latter is based on the knowledge on possible bridge failure modes and related vulnerable zones i.e. parts/segments of a bridge where damages have the most significant impact on the bridge performance. If this information is available before inspections, the inspection procedures need not to change significantly. The framework is to be applied on non-landmark bridges, and covers girder, frame and arch bridges types. It is envisioned to have two stages – static and dynamic. In general, the first one comprises the preparatory work, inspection tasks and static (i.e. snapshot) assessment of the KPIs. The second stage implies assessment of remaining service life, KPI development over time and finding an optimal maintenance scenario i.e. decision making.
The report can get downloaded here.
Bridge quality, as a measure of its compliance with the performance goals is tracked by the quality control plan. In other words, the quality could be understood as a comparison between performance indicators and performance goals. Reliability is widely recognized as the most important key performance indicator. This paper proposes a new approach to the mentioned comparison that provides valuable information and consequently improve decision-making regarding future course of action.
A current quality control plan is facing certain limitations. Defects are being detected in the inspection and documented in the inspection report. In the most cases, however the essential information for reliability assessment i.e. the extent and location of the defects is not recorded.
The proposed approach uses a Bayesian net for the prior analysis of the bridge. Afterwards, the net is updated after each inspection, allowing a posterior analysis of the bridge reliability. A damage free state of the bridge, so-called “virgin state” is adopted as a baseline, while inspectors are asked to estimate the severity of the defect and consider the vulnerability of the structural system for the locations of defects.
It is widely accepted that safety and serviceability are primary concerns in bridge design. However, for the most of bridges’ service life, these concerns are addressed indirectly by a qualitative measure, defined herein as condition state, which is based upon observable damages recorded during inspections. Condition state is at best, only loosely correlated to safety and serviceability. It would be more reasonable to address safety and serviceability in inspection process directly, using the information on bridge performance obtained during the design and construction. The future Bridge Management Systems (fBMS) should therefore include this information allowing assessment of safety and serviceability based on inspection results. By including Bridge Information Models that are currently being developed and Structural Health Monitoring, the fBMS will become an invaluable decision-support tool not only for maintenance planning but also for issuing special permits, specification of heavy vehicle corridors, risk assessment due to natural hazards, etc.
The state-of-the-art bridge management practice do not adequately account for flooding and related local scour, thus fail to provide crucial information to viably mitigate consequences of bridge failures. The current policies in practice, which are solely based on visual inspections, need to be updated with efficient, preferably quantitative methodologies for a comprehensive and timely screening of vulnerable bridges. The research is aimed at application of key performance indicators which consider relevant data for assessment of vulnerability to local scour. Herein, particularly bridge exposure and bridge resistance are assessed. The latter involves failure modes, an essential ingredient for evaluation of a probability of failure, which is related to the indicator of reliability. The guidelines are necessary for inspection of bridge vulnerable zones i.e. segments that have the key role in resistance to failure. The practical evaluation of the reliability class is presented for RC girder bridges, which support elaboration of adequate quality control plans.
The original objective of the research project was to combine three planning processes for pavements as defined in the VSS standards, to minimize the planning effort for various existing road networks and to optimize the condition assessment. On one hand, it was demonstrated that the combination of these processes, which was originally intended, does not lead to a minimization of the planning effort. On the other hand, since the majority of road owners already follow structured process for condition assessment, there is little room for further optimization. It is therefore that the original objective had to be adapted.
The adapted goal of this project is, based on the current practice, to link the operative maintenance planning on the object level with a strategic approach based on a long-term consideration within the framework of life cycle cost analyses.
This should enable decision-makers to identify the current and future maintenance needs as well as to identify the short-, medium- and long-term consequences of different maintenance strategies and budget provisions.
The present research project was proposed to answer the still open questions about the specific area of application of these reinforcements and the effects on the interlayer bonding between wearing and base courses and between base course and road base layer.
In a first phase of the work, the materials and structures to be investigated were defined. The selection was carried out based on interlayer bonding test results according to Leutner. In addition, the experimental setups were defined in collaboration with the
responsible persons of ASTRA and cantons. In a second phase, laboratory experiments on down-scaled pavement models were carried out using the Model Mobile Load Simulator (MMLS3). Finally, in the last phase, ad-hoc pavements were constructed and loaded with the traffic Mobile Load Simulator (MLS10). In addition, laboratory tests were carried out on cored specimens taken from the laboratory setups and in situ test sections. Further, numerical simulations were performed using the finite element method to model the effect of the position of the reinforcement in a pavement structure.
One of the most important elements in the planning of maintenance interventions, and, therefore, in road structures management systems, is ability to estimate the costs of maintenance interventions. These costs are normally developed using element level and
structure level unit costs.
In order to estimate these costs, unit costs need to be determined from the actual costs of completed interventions. This, however, is difficult as the costs of such interventions are reported per activity performed, e.g. pouring the concrete, and not per element. This is
because construction companies perform activities and are relatively ambivalent to the number of elements upon which they work. The costs using in the planning of maintenance interventions, however, need to be related directly to the elements or to the structure so
that the service level provided by the elements and structures can be appropriately taken into consideration and the optimal times to intervene can be determined.
This discrepancy means that the actual costs of the completed interventions have to be converted to costs related to the elements or the structure. This conversion requires a cost model, i.e. a model containing the rules for the conversion from the costs of activities to the costs of elements and structure.
In this research project, such a cost model was developed. The developed cost model enables the conversion of costs associated to activities as defined in the NPK-activity catalogue from CRB into costs associated to elements and structures. The cost model was
implemented into the software referred to as DIXIS, after the work area in which the example bridge was located. The mapping table implemented in the software, which only has to be developed once, was developed using the descriptions in the NPK activity catalogue. The software proportionally distributes the cost of the activities are to the elements of the structure to have a maintenance intervention based on the extent of work to be done per element as documented by the construction company. An advantage of the method used in the software is that the current bidding and billing practices remain the same.
The term Asset Management originates from the financial world and has also been used since the 1990s in the road and transport sector and is predominantly used in English-speaking countries. Although there is no uniform definition for Asset Management, the majority of users understands it as “a superordinate strategic approach to the optimal longterm use of road infrastructure with optimal use of resources, based on the fundamentals of engineering, economics and business management as well as corporate governance”.
In this initial project various concepts and definitions of Asset Management were analyzed that have been developed or introduced in other countries in order to formulate a definition of Asset Management that is suitable for the context of Switzerland, including system definition, objectives and decision-making processes.
The use of the term “Asset Management” was widely discussed because of the possible confusion due to its association with finance, and it was decided to rename this term (for use in Switzerland) “Integral Infrastructure Management”.
In addition, the gaps in knowledge discovered in the context of the situation analysis were identified as topics for individual projects of a research package to be carried out.
Infrastructure managers works every day according to some kind of Quality Control Plan (QCP) in
order to ensure a desired quality with minimum traffic interruption balancing cost, risks (implicit
or explicit) and performance. These QCPs varies significantly among European countries, which
urges the establishment of a common European guideline. COST TU1406 Working Group 3 has the
aim of providing a detailed explanation of the steps towards the establishment of a QCP. The
approach is generic and evaluates performance values with due attention to: 1) Structure and its
constitutive element incl. background material such as birth certificates, 2) Time-dependent
Performance Indicators (PI) from observations (e.g. spalling) with due reference to the underlying
deterioration processes (e.g. alkali-silica reaction) and 3) Related Key Performance Indicators (KPI)
based on the Dutch risk-driven maintenance concept RAMSSHE€P . This paper outlines QCP’s
for concrete girder and frame bridges.
Due to increasing age and decreasing budgets the need of road work activity will dramatically increase in the next years especially on heavily used sections of the road network. Therefor decision makers will have more and more problems to solve the conflict between road user requirements and maintenance needs. Besides new planning strategies long-term performing materials for repair and rehabilitation interventions in pavement management promise to show one way out of this dilemma. Supplier and manufacturer of asphalt reinforcement interlayers are commending their products for repair and rehabilitation interventions to improve asphalt performance. At the moment decision makers lack long-term experience to proof these assumptions independently. The presented research project intents to close this gap for defined asphalt pavements with reinforcement interlayers. It includes short term and long term analysis of pavement in the field and laboratory. The results show the influence of reinforcement on cracking, stiffness and bearing capacity of pavement. Additionally, criteria for an application of test methods for new asphalt reinforcement products will be developed. This will enable decision makers in pavement management to evaluate independently the use of asphalt reinforcement products and estimate consequences for long-term pavement performance of these pavement repair and rehabilitation intervention types.
There is a broad consensus that the benefits of road infrastructure for the society cannot be over-estimated. Maintaining these benefits on the long run in economically efficient, environmentally friendly and socially reconcilable manner is the fundamental task of road authorities. This means that they are bound to provide de-sired service quality to road users, or in more concrete terms fast, safe, comfortable and affordable travel. From purely users’ perspective only the highest service quality is good enough. However, besides the technical limits to the service quality, there are also economic constraints. The technically achievable service quality may not be the affordable one. The conflict between the users’ and societal desires one side and available financial resources on the other, is supposed to be resolved in a political process. This occurs more often than not in pursue for short-term political gains, resulting in considerable funding volatility. Professional societies can smoothen this volatility by setting performance goals that are both affordable and acceptable to the road users. One would therefore expect that they differ from country to country mirroring their economic strength. In most cases there are defined as stiff limits on the performance indicators. The actual service quality – measured by performance indicators – is considered insufficient if performance indicators do not meet performance goals. These performance indicators can be quantitative such as posted cruising speed, accident rate, vehicle operational costs, availability etc. or qualitative such as condition state.
With regard to bridges, these performance indicators depend on observations obtained by visual examination, non-destructive testing or a permanent monitoring systems. Typically, they are related to bridge components e.g. girders, abutments, cross beams and indicate existing or expected bridge dysfunctionality that result in one or more insufficient performance indicators. The challenge is to define procedures that connect observations, detected visually or using other examination methods with performance indicators. These procedures should cover the whole range of assessment activities from regular visual inspection to in depth investigations. The confidence in obtained results should however mirror the investigation effort. Furthermore, triggering criteria for more elaborate and expensive examination methods should be provided.
The paper suggests a framework that may overcome the above mentioned challenge and derive the performance indicators from observations and other available data such as construction year, structure type, span, geological conditions, etc.
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