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Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research
Country: Germany
129 Projects, page 1 of 26
  • Funder: EC Project Code: 101088555
    Overall Budget: 2,346,040 EURFunder Contribution: 2,346,040 EUR

    I propose to use autonomous underwater ocean glider vehicles with a newly developed airborne deployment system to measure ocean turbulence in extreme storms, such as hurricanes, typhoons, and tropical storms. These will be the first vertically resolved measurements of ocean turbulence in extreme storms, and will lead to a new understanding and improved estimates of the ocean mixing that is responsible for setting upper ocean temperatures - a crucial and poorly constrained feedback on storm intensity. By combining the observations with turbulence-resolving large eddy simulations, performed on high performance computational clusters, a new observationally-constrained model of the ocean-storm mixing feedback will be constructed that fills a much needed gap in the coupling of extreme storms to the ocean. This is crucial since extreme storms are increasing in strength and frequency through climate change, and are leading to record damages and loss of life in coastal communities. Such measurements are only now possible, since my research team has played a major role in pioneering the use of microstructure turbulence measurements from autonomous underwater gliders, particularly in stormy conditions. The final outcomes of the project will consist of (i) an airborne deployment system for the study of extreme events using autonomous vehicles, (ii) the first observations of upper ocean turbulence and mixing in extreme storms, (iii) a sequence of turbulence-resolving numerical simulations that, together with the observations, will identify and quantify processes responsible for setting upper ocean heat fluxes and turbulent structure in extreme storms, and (iv) a new parameterisation for ocean mixing in extreme storms that quanties the ocean-storm feedback, and its implementation in the forecasting model of the European Centre for Medium-range Weather Forecasts (ECMWF).

  • Funder: EC Project Code: 101001567
    Overall Budget: 1,999,590 EURFunder Contribution: 1,999,590 EUR

    The MA.D.AM project addresses the strong need of wire-based additive manufacturing (AM) for customized value-added metallic materials that are not established yet. The project aims at establishing novel scientific knowledge for the fabrication of novel wire materials and AM parts with hitherto not reached properties, based on the application of high-strength Al-Cu-Li alloys, as cutting-edge candidates for AM in aerospace applications. For this purpose, innovative solid-state materials development and AM processes are utilized to obtain alloys beyond the known thermodynamic borders. The solid-state Friction Extrusion process allows generating phases under non-equilibrium conditions, leading to so far unexplored microstructural states, enabling to produce novel high-performance wire material with tailored properties. To avoid microstructural deterioration and preserve or even improve the beneficial properties of the designed wires, the Solid State Layer Deposition process is employed. The overarching objective of MA.D.AM is to establish the real-world process chain paired with numerical approaches, leading to a digital twin to achieve a hitherto unavailable decryption of the composition-process-microstructure-property relationships for solid-state materials development and AM. To achieve this objective, a systematic multidisciplinary approach based on the combination of sophisticated physical modelling concepts, advanced experimental approaches including characterization techniques and machine learning is pursued. The selected modelling approaches along computational thermodynamics, microstructure and process modelling, together with special-designed (in situ) experiments will establish a clear link between process characteristics and evolution mechanisms such as phase formation and recrystallization kinetics. The digital twin will be built via a novel hybrid modelling strategy based on experimental and numerical data developed on the concepts of machine learning.

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  • Funder: EC Project Code: 703566
    Overall Budget: 159,461 EURFunder Contribution: 159,461 EUR

    The MAGPLANT project is intended to provide a major breakthrough towards the fabrication and application of bioresorbable Mg-alloy implants, which have the remarkable potential of accelerating bone healing while transferring the body’s mechanical load from the implant to the regenerating bone, as the Mg-alloy progressively degrades, thereby avoiding multiple surgical interventions. Moreover Mg is highly biocompatible as it is abundantly present in bone tissue and exhibits mechanical properties similar to those of bone. Although there is currently much research on biodegradable Mg implants, the fundamental aspect for achieving success is controlling the corrosion rate of Mg-alloys in biological media. Because the main form of corrosion on Mg is localized corrosion, a thorough study consisting of localized electrochemical measurements must be performed. In the literature the biodegradable Mg is persistently being addressed as suffering from homogeneous corrosion, which is incorrect and does not provide the information on the microscopic processes occurring as the alloy degrades in contact with biofluids and cellular structures. In the scope of MAGPLANT the corrosion of Mg-alloys will be investigated by using modern localized electrochemical techniques. Therefore the underlying Mg-alloy corrosion mechanisms will be understood from the macro to the microscale level, considering the biological environments of interest. This project fits well into the key societal challenges for H2020 and will contribute to improve Europe’s research position on bioresorbable implants. Such perspective is well supported by the excellence and strong dedication of the host institution in the target research field, along with the research experience of the candidate.

  • Funder: EC Project Code: 236154
  • Funder: EC Project Code: 101067769
    Funder Contribution: 173,847 EUR

    Extreme weather events are already affecting urban areas with sometimes severe impacts on people, infrastructure and socio-economic activities. Faced with these effects, which are expected to increase due to climate change, decision-makers need sound climate information on local urban issues in order to better plan the cities of tomorrow. Today, climate change impacts on urban areas are assessed by separate scientific communities, with some methodological limitations for each approach: Regional Climate Models (RCM) provide climate change information at the regional scale, but with a coarse horizontal resolution for cities and without specific surface parameterisation for urban processes; most high-resolution impact studies focusing on urban issues (energy, thermal comfort) do not take into account urban-regional climate interactions and are city and indicator dependent. The CIRCE project aims to develop a more robust and generic methodology for assessing the impacts of climate change on European cities by (1) identifying innovative impact indicators that are relevant for local decision-makers and can be calculated from modelled and available city data and (2) clarifying the best current regional climate modelling configurations for urban impact studies. To this end, the new generation of high-resolution Convective-Permitting Models (CPM) will be used for the first time in a multi-city ensemble approach. Multi-sectoral indicators will be defined based on local climate risks (with a focus on heat waves and extreme precipitation) and urban issues related to various European cities. The ability of climate models to simulate specific extreme climate events and their impacts on cities will be assessed. Then, their future evolution will be analysed by combining the largest set of RCMs and CPMs currently available. The final objective will be to co-develop an urban climate service demonstrator based on these results and to feed into the CORDEX Flagship Pilot Study URB-RCC.

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