 So I was following very closely what happened so far. So I think it's a big opportunity to do some lively discussions after the presentation. So it's really an opportunity for you, I think we should very much focus on interactive discussions after the presentation. To introduce today's event, a presentation for more formally introducing the case study portfolio. Let's speak a little more focused about our case studies. When we set up this course lecture, we had to write a memorandum of understanding so that the mechanism of agreement so someone wants to join this course lecture he has to agree on this memorandum of understanding and we as a group of researchers formulated the memorandum of understanding and what we can find here is we need the case studies also for delivering inputs to our theoretical framework. We need the practical applied situations. We need to utilize our computational tools and we need to demonstrate also the applicability of what we have been thinking about. So in this sense the industry innovation base really support what we have in the memorandum of understanding. This is a great tool to work on this. And yes, so in summary basically our case studies, this working group 4 is the important link to our theoretical working groups on the theoretical framework on the structural health monitoring and performance and the methods and tools working group 1-2-3. And also it is the link to our standardization activities. So we have been working on getting the case studies to work and we have been interacting with the working groups and our framework and we have requested case studies and we have collected quite a few and we have also been studying out the identification of typical challenges or difficulties we have been observing in the previous years of the action. So it is nine case studies which are under development. You will hear eight case studies presentations in case all the case studies presenters are here. So you will hear eight case studies today at this workshop and I think one major step we took here for the case studies and our thinking was that this was already the last two presentations. We need to step it out of all models and also of our conventional integrity management procedures and the specifics of our monitoring systems but to address a decision scenario or a decision situation and we have been primarily looking at the design phase and the operation phase of the infrastructure. I think this is the most important phases. We have monitoring phenomena regarding load processes, damage detection, damage mechanisms, material properties. Actually in our framework we can quite extend this. There is quite some ways to go. If we have a more general perspective for instance on the system states and basically on the complete infrastructure system. Our structures include bridges, building some energy production and storage geotechnical structures and various decision scenarios. We are working on a case study classification so that it becomes easy to overview what we are doing for the case studies and what case studies do we have and what is the result. The first point is that we classify the structure and the type, the life cycle phases or the design and operation phase. What performance we are considering is a deterioration or is it the complete performance of a system including the risks and the extreme loadings. Very important or the most important is our decision scenario who is the decision maker. What is the decision point and type? Here the example is a photo structure integrity management, the structure integrity management consisting of very basic repair inspection monitoring, trumpet plant in the commissioning phase or even before in the design phase. The decision point and type is basically in the design or the commissioning phase of a structure. This is where our models are providing the highest benefit because we can predict the performance. This is all I had in the last presentation. We can predict the performance. We can predict the inspection outcomes. We can predict the way to repair and we can also predict what monitoring data we will obtain. When we associate this to costs with each of the branches we have, then we have a pre-post-surrealization analysis so we do a qualification of the expected benefits before we can optimize with our decision parameters. The best way to visualize our models is pre-post-surrealization before any SHM system installation or any action performance. What is the objective? The objective is to maximize the expected benefits or minimize the risks. We are always working with probabilities and the monetary consequences. Very important is the basics of our decision scenario and then the decision variables. This goes in the decision frame to the rectangles. It's the action and action parameters and it's the information requirements, strategies, inspections, monitoring and what parameters do we have and what different strategies we can utilize. These should all be documented very shortly but distinct here in this classification and then it's the results, what is the value of information like I outlined in the last presentation. What are the decision modes? What do we do in practice if our monitoring system provides one indication, so the structure is safe for instance, then what should be done, then maybe the next inspection or the next pre-pair action can be done later. This is about the classification and the way of summarizing and providing an overview of the case studies we are working on. A few words also to some case studies which are under development and which will not be present here. This is for instance the soil structure and the action effects of exaltation and the response of reinforced concrete ratings in case of earthquakes. So this is very important for Iceland, Jonas who is here, who is working on this case study. He has access to a lot of data and this is a perfect ground for doing such case studies but we are working together on a few challenges like the uncertainty, quantification and maybe how to efficiently do a damage detection after such an event. This is a case study for the value of information for seismic emergency management of the highway bridge. Maria Pina and Simona Mirabilia are working on this case study together with Pierre Francesco Giornal and here we already have a decision tree. That's further development of this generic decision tree we have been seeing at the beginning. And one aspect could be considered here is whether visual inspections are more efficient or monitoring. It's more efficient. Here we have a very well developed, already very well developed case study. There are a few publications about the assessment of fatigue details and what value fatigue monitoring can bring for doing the condition assessment. I think the way of further working on this case study is to also have a system perspective. This is very important. We are going with our methodology in the system perspective but the problems we are working in structural health monitoring and structural health monitoring engineers the focus is on the detail on this handle. This is very good but we need to connect this to a system perspective and the system performance. Another example is industrial case study. This is not an infrastructure system but some more solid tank monitoring. It is of reinforced concrete and this is I think an energy saving device for solar power plants. And here the challenge is what is the most efficient monitoring of the concrete strain and reinforcement corrosion. We have also cases where we have an extensive monitoring record. Also the most efficient way of what this is at work we see this as the largest potential of our methodology but I think this is very important. We also need to address these situations and what we can learn from this. So we could look was it efficient to do monitoring so we have a posterior decision analysis or I think this is the better way. Maybe we can look how we can show our predictions our prediction models for the next case like this and also what could be the most efficient decision-assisted with the experience of this case study and then to account or then go for the next case study but we then need to account for that we may have a different ground and a different case study and we have another uncertainty model. So I think the general challenges for our case study is beyond what is written here I think the way of thinking and to have a clear decision scenario I think this is the major step we have been taking this is maybe not our actual challenge anymore but of course and I think this goes also to a very important point it is the level of detail and we already know, all of us know we are working in engineering with very detailed models but the decisions based on the engineering predictions are taken with much similar models and this simple in the sense of detail not necessarily in the sense of the goodness of the models but they can be very very very efficient models but this step is here to work with the right level of detail and if we do, if we model a decision scenario then the level of detail must not be this high it must not necessarily include all our sophisticated models but we need to have a very clear interface to the model outcomes so that we can maybe not do the decision analysis with these sophisticated models but the input for the decision analysis comes from very sophisticated models so to harmonize the level of detail we need reasonable assumptions and simplifications and uncertainty in representation where are our probabilistic models are based on so these are two general challenges then specific it is, we have been often observing this so we have our SfM system and it provides an outcome how is it related to the performance of the system? this is a very important aspect and this is not solved by industry nor infrastructure operators this is the first task of us, of us as researchers to provide the models but the tasks of the engineers and our people who are working within the decision scenario is that there is an alignment of the information we are getting from our monitoring and inspection to the performance we are having or to the decision scenario which decisions should be supported with this information and then of course we have a complexity challenge so spatial time dependence, spatial and time resolution what is the right level of detail, this is what I already addressed we have these 19 case studies we have an approach of how to work on this is supported by our networking tools we are having mainly by workshops but also training schools we had a very successful training school last year in November and all the aspects, also the education was very nice organized by Maria Pinah, Imangeli so in this sense there is a few levels of documentation internally it is a fact sheet then there is publications of the case study we follow the classification scheme we would like to see the decision scenario which structure, what is the objective of the decisions and what are the results, what is the value of information is it worth in this case to implement SHM, the very basic question but what strategy, what location should be monitored and how long and of course the work on our case studies helps in our construction on the level of the theoretical framework on the appropriateness of tools and methods we are having and we learn from case studies in general specific insights but we also learn about bottlenecks so enough for the introduction part I think this was already a lot of information so let's have a break, refresh the mind and then we go into the case studies thank you