A damage estimation exercise has been carried out using the building stock inventory and population database of the Istanbul Metropolitan Municipality and selected European earthquake loss estimation packages: KOERILOSS, SELENA, ESCENARIS, SIGE, and DBELA. The input ground-motions, common to all models, correspond to a “credible worst case scenario” involving the rupture of the four segments of the Main Marmara Fault closest to Istanbul in a Mw 7.5 earthquake. The aim of the exercise is to assess the applicability of the selected software packages to earthquake loss estimation in the context of rapid post-earthquake response in European urban centers. The results in terms of predicted building damage and social losses are critically compared amongst each other, as well as with the results of previous scenario-based earthquake loss assessments carried out for the study area. The key methodological aspects and data needs for European rapid post-earthquake loss estimation are thus identified.
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A damage estimation exercise has been carried out using the building stock inventory and population database of the Istanbul Metropolitan Municipality and selected European earthquake loss estimation packages: KOERILOSS, SELENA, ESCENARIS, SIGE, and DBELA. The input ground-motions, common to all models, correspond to a “credible worst case scenario” involving the rupture of the four segments of the Main Marmara Fault closest to Istanbul in a Mw 7.5 earthquake. The aim of the exercise is to assess the applicability of the selected software packages to earthquake loss estimation in the context of rapid post-earthquake response in European urban centers. The results in terms of predicted building damage and social losses are critically compared amongst each other, as well as with the results of previous scenario-based earthquake loss assessments carried out for the study area. The key methodological aspects and data needs for European rapid post-earthquake loss estimation are thus identified.
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From a circular standpoint it is interesting to reuse as much as possible construction and demolition waste (CDW) into new building projects. In most cases CDW will not be directly reusable and will need to be processed and stored first. In order to turn this into a successful business case CDW will need to be reused on a large scale. In this paper we present the concept of a centralized and coordinated location in the City of Utrecht where construction and demolition waste is collected, sorted, worked, stored for reuse, or shipped elsewhere for further processing in renewed materials. This has expected advantages for the amount of material reuse, financial advantages for firms and clients, generating employability in the logistics and processing of materials, optimizing the transport and distribution of materials through the city, and thus the reduction of emissions and congestion. In the paper we explore the local facility of a Circular Hub, and the potential effects on circular reuse, and other effects within the City of Utrecht.
The project aim is to improve collusion resistance of real-world content delivery systems. The research will address the following topics: • Dynamic tracing. Improve the Laarhoven et al. dynamic tracing constructions [1,2] [A11,A19]. Modify the tally based decoder [A1,A3] to make use of dynamic side information. • Defense against multi-channel attacks. Colluders can easily spread the usage of their content access keys over multiple channels, thus making tracing more difficult. These attack scenarios have hardly been studied. Our aim is to reach the same level of understanding as in the single-channel case, i.e. to know the location of the saddlepoint and to derive good accusation scores. Preferably we want to tackle multi-channel dynamic tracing. • Watermarking layer. The watermarking layer (how to embed secret information into content) and the coding layer (what symbols to embed) are mostly treated independently. By using soft decoding techniques and exploiting the “nuts and bolts” of the embedding technique as an extra engineering degree of freedom, one should be able to improve collusion resistance. • Machine Learning. Finding a score function against unknown attacks is difficult. For non-binary decisions there exists no optimal procedure like Neyman-Pearson scoring. We want to investigate if machine learning can yield a reliable way to classify users as attacker or innocent. • Attacker cost/benefit analysis. For the various use cases (static versus dynamic, single-channel versus multi-channel) we will devise economic models and use these to determine the range of operational parameters where the attackers have a financial benefit. For the first three topics we have a fairly accurate idea how they can be achieved, based on work done in the CREST project, which was headed by the main applicant. Neural Networks (NNs) have enjoyed great success in recognizing patterns, particularly Convolutional NNs in image recognition. Recurrent NNs ("LSTM networks") are successfully applied in translation tasks. We plan to combine these two approaches, inspired by traditional score functions, to study whether they can lead to improved tracing. An often-overlooked reality is that large-scale piracy runs as a for-profit business. Thus countermeasures need not be perfect, as long as they increase the attack cost enough to make piracy unattractive. In the field of collusion resistance, this cost analysis has never been performed yet; even a simple model will be valuable to understand which countermeasures are effective.
Climate change has impacted our planet ecosystem(s) in many ways. Among other alterations, the predominance of long(er) drought periods became a point of concern for many countries. A good example is The Netherlands, a country known by its channels and abundant surface water, which has listed “drought effect mitigation” among the different topics in the last version of its “Innovation Agenda” (Kennis en Innovatie Agenda, KIA). There are many challenges to tackle in such scenario, one of them is solutions for small/decentralized communities that suffer from dry-up of surface reservoirs and have no groundwater source available. Such sites are normally far from big cities and coastal zones, which impair the supply via distribution networks. In such cases, Atmospheric Water Generation (AWG) technologies are a plausible solution. These systems have relatively small production rates (few m3 per day), but they can still provide enough volume for cities with up to 100k inhabitants. Despite having real scale systems already installed in different locations worldwide, most systems are between TRL 5 and 6. Thus need further development. SunCET proposes an in-situ evaluation of an AWG system (WaterWin) developed by two different Dutch companies (Solaq and Sustainable Eyes) in the Brazilian semi-arid state of Ceará. The cooperation with NHL Stenden will provide the necessary expertise, analytical and technical support to conduct the tests. The state government of Ceará built an infrastructure to support the realization of in-situ tests, as they want to further accelerate technology implementation in the state. Such structure will make it possible to share costs and decrease total investments for the SMEs. Finally, it is also intended to help establishing partnerships between Dutch SMEs and Brazilian end users, i.e. municipalities of the Ceará state and small agriculture companies in the region.
