Photo: Rolf van Melis

Contract research in the field safety and reliability analysis

Contract research means to us, finding transparent and practical solutions for the problems that our customers or promotional institutes present. Our participation in a wide variety of research projects has led to an extensive list of publications. Some examples can be found on this page.


(EU funded research project) Development of a Decision Support System for Improved Resilience and Sustainable Reconstruction of historic areas to cope with Climate Change and Extreme Events based on Novel Sensors and Advanced Modelling Tools: The HYPERION Approach (Status: ongoing)

HYPERION aims to leverage

  • existing tools and services (e.g., climate/extreme events models, and their impacts, decay models of building materials, Copernicus services, etc.) and
  • novel technologies (terrestrial and satellite imaging for wide-area inspection, advanced machine learning, etc.)
  • to deliver an integrated resilience assessment platform, addressing multi-hazard risk understanding, better preparedness, faster, adapted and efficient response, and sustainable reconstruction of historic areas. HYPERION will take into account the local eco-systems in the CH areas, mapping out their interactions and following a truly integrated/sustainable reconstruction approach (technical, social, institutional, environmental and economic level), by incorporating active communities participation (using the PLUGGY social platform) and by supporting new business models based on the concept of a “load-balancing” economy, (using an algorithm that acts like a “reverse proxy”, distributing client traffic across different companies within the same sector) and offering financial risk-transfer tools (insurance, Catastrophe-CAT-bonds ) that can ensure the immediate funds availability to fuel timely build-back-better efforts.


    Facebook: Hyperion EU Project

    Twitter: @EUHyperion


    (EU funded research project) ROBotic System with Intelligent Vision and Control for Tunnel Structural INSPECTion and Evaluation (Status: retained for negotiations)

    The latest developments in robotics and the associated fields of computer vision and sensors open the floor for automated robotic solutions, exploitable in the near to medium term in the field of inspection of the civil infrastructure in general and transportation tunnel infrastructure in particular. The latter infrastructure is ageing urgently requiring inspection and assessment. Presently, inspection is mostly performed through tunnel wide visual observations by inspectors. This process is slow, labour intensive, expensive, subjective and often requiring lane shutdown during inspection at a time of limited budgets and inspector resources and heightened requirements for safety and maximum tunnel uptime. ROBINSPECT, driven by the tunnel inspection industry, adapts and integrates recent research results in intelligent control in robotics, computer vision tailored with semi-supervised and active continuous learning and sensing, in an innovative, integrated, robotic system that automatically scans the intrados for potential defects on the surface and detects and measures radial deformation in the cross-section, distance between parallel cracks, cracks and open joints that impact tunnel stability, with mm accuracies. This permits, in one pass, both the inspection and structural assessment of tunnels. Intelligent control and robotics tools are interwoven to set an automatic robotic arm manipulation and an autonomous vehicle navigation so as to minimize humans’ interaction. This way, the structural condition and safety of a tunnel is assessed automatically, reliably and speedily. The initial dataset on tunnel defects is provided from case studies (e.g., from London Underground) to be used not only for transfer learning but also for the evaluation of the structural models.


    (EU funded research project) Reconstruction and REcovery Planning: Rapid and Continuously Updated COnstruction Damage, and Related Needs ASSessment (Status: ready for signature)

    RECONASS will provide a monitoring system for constructed facilities that will provide a near real time, reliable, and continuously updated assessment of the structural condition of the monitored facilities after a disaster with enough detail to be useful for early and full recovery planning. The above assessment will be seamlessly integrated with automated, near real-time and continuously updated assessment of physical damage, loss of functionality, direct economic loss and needs of the monitored facilities and will provide the required input for the prioritization of their repair. Such detailed monitoring is only economical for selected facilities that are essential for response and recovery or facilities that have a high value as a target for terrorist attacks. In case of spatially extended events, in order to assess the physical damage in the whole affected area, the detailed assessment of damage in the monitored facilities will be used for the speedy local calibration of satellite and oblique aerial photography dramatically reducing the required time to inform the post disaster/crisis needs assessment process and provide base data for reconstruction efforts. The above will be part of the RECONASS next generation post-crisis needs assessment tool in regards to construction damage and related needs. This tool will enable fusion of external information, allow for future expansion of the system, provide international interoperability between the involved units for reconstruction and recovery planning and support the collaborative work between these actors.


    (EU funded research project) Radio Frequency Identification Tags Linked to on Board Micro-Electro-Mechanical Systems in a Wireless, Remote and Intelligent Monitoring and Assessment System for the Maintenance of CONstructed Facilities (MEMSCON) FP7 Contract-No. 036887

    Rapid advances in Radio Frequency Identification (RFID) technology, in Micro-Electro-Mechanical Systems (MEMS), in lower-power wireless networking and in computation give hopes for a new generation of tiny, cheap, networked sensors that can be ‘sprayed’ on civil and building structures to provide detailed, quantitative information on the structure’s physical state while in service. This information can be used to assess the structural condition and aid decision making on rehabilitation so that safety can be attained and material consumption and rehabilitation costs can be reduced. However, these massively distributed sensor networks and the required algorithms and software tools to enable their applications must overcome a set of technological hurdles before they become widely deployable. Current structural monitoring systems employ conventional cables to allow sensors to communicate their measurements to a central processing unit. They have high installation costs and leave wires vulnerable to ambient signal noise corruption which precludes them from becoming widely adopted. Moreover, the size and complexity of large structures require a large number of sensing points to be installed. The relatively large size of sensors currently employed in structural monitoring precludes their deployment in sensor-rich monitoring systems. An additional constraint to the sensor-rich monitoring systems is the relatively high cost of sensors. The above problems can be solved if MEMS-based sensors are integrated with an RFID tag in a single, tiny, cheap package in a low-power, wireless, networking scheme. The most relative properties for structural analysis are movement (acceleration and displacement) and forces. The corresponding sensors that produce these measurements are accelerometers and strain sensors (stresses and forces can be deduced from strain measurements).


    (EU funded research project) Fibre Optics-Based Intelligent MONItoring and Assessment System for Proactive Maintenance and Seismic Disaster Prevention in Reinforced COncrete Tunnel Linings (MONICO)

    To ensure the safety of vulnerable tunnel cross-sections or sections where very high standards of safety are required, fibre optic sensors providing a real-time, wireless and remote deformation sensing capability, need to be integrated with software that will collect and process the signals and assess the structural reliability of the lining.


    (EU funded research project) Integrated High Resolution Imaging Ground Penetrating Radar and Decision Support System for WATER PIPEline Rehabilitation(WATERPIPE)

    Many EU cities are experiencing increasing problems with their water pipeline infrastructure. The cost of replacing these old, worn-out systems, if left to deteriorate beyond repair, is astronomical and clearly beyond the resources of many communities. Replacement, however, is not the only choice as many of these systems can be rehabilitated at 30 to 70 percent of the cost of replacement. Accordingly, resources are now increasingly being allocated to address pipeline rehabilitation management issues. Due to the emphasis on sustainable management, risk-based approaches for the rehabilitation management of the water supply network need to be developed. Rehabilitation decisions should be based, inter alia, on inspection and evaluation of the pipeline conditions. Yet, utilities cannot locate a number of their old pipes and current inspection technologies typically do not provide the needed detailed information on pipeline damage.

    HRA evaluation concept

    RISA GmbH developed for the VGB-Power-Tech e.V. (European industrial union for electricity and heat production) an evaluation concept for human error in technical systems and transformed this concept into the software HRA (Humanly Reliability Analysis). The HRA programme uses the Swain method.

    Structural reliability

    In the following EU financed projects we were able to exhibit our knowledge in the spheres probabilistic, descriptive software, GIS link-up and system and data integration:


    In the SEISLINES project, the structural reliability of underground mains water pipes was tested for different stresses, including earthquakes. This structural reliability data serves as input for a decision support system which, considering the pipeline material, determines the monetary consequences of different maintenance measures (repair, preventive replacement, preventive maintenance).


    The goal of the LEAKING project was to develop innovative procedures for leakage detection in underground water pipes using electromagnetic waves. The (unsure) output of these devices was then linked with the structural reliability data using the Bayes method. This improves the statement of the structural reliability to serve as input for a decision support system which, depending on the findings, cannot only suggest maintenance measures but also a schedule for the next measurement date.


    In the SEWERINSPECT project an integrated decision support system was being developed, for which the main challenge was, how data from CCTVs can be transferred into maintenance operations. The developed computer system stored the evaluations of the digital recordings from the CCTV inspections on a database. This system enadbled the maintenance engineers to access all stored infomation for the examined part of a sewage system. Within the developed project probabilistic models for the evaluation of structural parameters, such as pipe material, pipe wall strength and load parameters, such as seismic influences. In these models the deterioration of the state of a sewage system was also considered, caused for example by corrosive grounds, industrial waste, ground water and/or loss of the surrounding soil.

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