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Grant
Agency: European Commission | Branch: FP7 | Program: CP-IP | Phase: AAT.2013.1-4. | Award Amount: 37.06M | Year: 2013

AFLoNext is a four year EC L2 project with the objective of proving and maturing highly promising flow control technologies for novel aircraft configurations to achieve a quantum leap in improving aircrafts performance and thus reducing the environmental footprint. The project consortium is composed by forty European partners from fifteen countries. The work has been broken down into seven work packages. The AFLoNext concept is based on six Technology Streams: (1) Hybrid Laminar Flow technology applied on fin and wing for friction drag reduction. (2) Flow control technologies applied on outer wing for performance increase. (3) Technologies for local flow separation control applied in wing/pylon junction to improve the performance and loads situation mainly during take-off and landing. (4) Technologies to control the flow conditions on wing trailing edges thereby improving the performance and loads situation in the whole operational domain. (5) Technologies to mitigate airframe noise during landing generated on flap and undercarriage and through mutual interaction. (6) Technologies to mitigate/control vibrations in the undercarriage area during take-off and landing. AFLoNext aims to prove the engineering feasibility of the HLFC technology for drag reduction on fin in flight test and on wing by means of large scale testing as well as for vibrations mitigation technologies for reduced aircraft weight and for noise mitigation technologies. The peculiarity of the AFLoNext proposal in terms of holistic technical approach and efficient use of resources becomes obvious through the joint use of a flight test aircraft as common test platform for the above mentioned technologies. To improve aircraft performance locally applied active flow control technologies on wing and wing/pylon junction are qualified in wind tunnels or by means of lab-type demonstrators.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-1-2014 | Award Amount: 19.05M | Year: 2015

EUDAT2020 brings together a unique consortium of e-infrastructure providers, research infrastructure operators, and researchers from a wide range of scientific disciplines under several of the ESFRI themes, working together to address the new data challenge. In most research communities, there is a growing awareness that the rising tide of data will require new approaches to data management and that data preservation, access and sharing should be supported in a much better way. Data, and a fortiori Big Data, is a cross-cutting issue touching all research infrastructures. EUDAT2020s vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, combining the richness of numerous community-specific data repositories with the permanence and persistence of some of Europes largest scientific data centres. EUDAT2020 builds on the foundations laid by the first EUDAT project, strengthening the links between the CDI and expanding its functionalities and remit. Covering both access and deposit, from informal data sharing to long-term archiving, and addressing identification, discoverability and computability of both long-tail and big data, EUDAT2020s services will address the full lifecycle of research data. One of the main ambitions of EUDAT2020 is to bridge the gap between research infrastructures and e-Infrastructures through an active engagement strategy, using the communities that are in the consortium as EUDAT beacons and integrating others through innovative partnerships. During its three-year funded life, EUDAT2020 will evolve the CDI into a healthy and vibrant data-infrastructure for Europe, and position EUDAT as a sustainable infrastructure within which the future, changing requirements of a wide range of research communities are addressed.


Grant
Agency: European Commission | Branch: H2020 | Program: CSA | Phase: SPACE | Award Amount: 5.00M | Year: 2014

MACC-III is the last of the pre-operational stages in the development of the Copernicus Atmosphere Service. Its overall institutional objective is to function as the bridge between the developmental precursor projects - GEMS, PROMOTE, MACC and MACC-II- and the Atmosphere Service envisaged to form part of Copernicus Operations. MACC-III will provide continuity of the atmospheric services provided by MACC-II. Its continued provision of coherent atmospheric data and information, either directly or via value-adding downstream services, is for the benefit of European citizens and helps meet global needs as a key European contribution to the Global Climate Observing System (GCOS) and the encompassing Global Earth Observation System of Systems (GEOSS). Its services cover in particular: air quality, climate forcing, stratospheric ozone, UV radiation and solar-energy resources. MACC-IIIs services are freely and openly available to users throughout Europe and in the world. MACC-III and its downstream service sector will enable European citizens at home and abroad to benefit from improved warning, advisory and general information services and from improved formulation and implementation of regulatory policy. MACC-III, together with its scientific-user sector, also helps to improve the provision of science-based information for policy-makers and for decision-making at all levels. The most significant economic benefit by far identified in the ESA-sponsored Socio-Economic Benefits Analysis of Copernicus report published in July 2006 was the long-term benefit from international policy on climate change. Long-term benefit from air quality information ranked second among all Copernicus benefits in terms of present value. Immediate benefits can be achieved through efficiency gains in relation to current policies. The estimated benefits substantially outweigh the costs of developing and operating the proposed services.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: SC5-01-2014 | Award Amount: 14.97M | Year: 2015

The goal of PRIMAVERA is to deliver novel, advanced and well-evaluated high-resolution global climate models (GCMs), capable of simulating and predicting regional climate with unprecedented fidelity, out to 2050. This capability will deliver innovative climate science and a new generation of advanced Earth System Models. Sector-specific end-users in policy and business will be identified and engaged individually, with iterative feedback, to ensure that new climate information is tailored, actionable and strengthening societal risk management decisions. These goals will be achieved through the development of coupled GCMs from seven groups across Europe, with sufficient resolution to reproduce realistic weather and climate features (~25km mesh size), in addition to enhanced process parameterisation. Thorough assessment will use innovative process-based metrics and the latest observational and reanalysis datasets. Targeted experimental design will reduce inter-model spread and produce robust projections, forming the European contribution to the CMIP6 High-Resolution Model Intercomparison Project, led by PRIMAVERA. It is the first time that high-resolution coupled GCMs will be used under a single experimental protocol. Coordination, and the underlying process-understanding, will significantly increase the robustness of our findings. Our new capabilities will be used to improve understanding of the drivers of variability and change in European climate, including extremes, since such regional changes continue to be characterised by high uncertainty. We will also explore the frontiers of climate modelling and of high performance computing to produce simulations with a reduced reliance on physical parameterisations. These will explicitly resolve key processes such as ocean eddies, and will include new stochastic parameterisations to represent sub-grid scale processes. These frontiers simulations will further our understanding of the robustness of climate projections.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-5-2015 | Award Amount: 5.69M | Year: 2015

The aim of the present proposal is to establish an Energy Oriented Centre of Excellence for computing applications, (EoCoE). EoCoE (pronounce Echo) will use the prodigious potential offered by the ever-growing computing infrastructure to foster and accelerate the European transition to a reliable and low carbon energy supply. To achieve this goal, we believe that the present revolution in hardware technology calls for a similar paradigm change in the way application codes are designed. EoCoE will assist the energy transition via targeted support to four renewable energy pillars: Meteo, Materials, Water and Fusion, each with a heavy reliance on numerical modelling. These four pillars will be anchored within a strong transversal multidisciplinary basis providing high-end expertise in applied mathematics and HPC. EoCoE is structured around a central Franco-German hub coordinating a pan-European network, gathering a total of 8 countries and 23 teams. Its partners are strongly engaged in both the HPC and energy fields; a prerequisite for the long-term sustainability of EoCoE and also ensuring that it is deeply integrated in the overall European strategy for HPC. The primary goal of EoCoE is to create a new, long lasting and sustainable community around computational energy science. At the same time, EoCoE is committed to deliver high-impact results within the first three years. It will resolve current bottlenecks in application codes, leading to new modelling capabilities and scientific advances among the four user communities; it will develop cutting-edge mathematical and numerical methods, and tools to foster the usage of Exascale computing. Dedicated services for laboratories and industries will be established to leverage this expertise and to foster an ecosystem around HPC for energy. EoCoE will give birth to new collaborations and working methods and will encourage widely spread best practices.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: SPIRE-04-2016 | Award Amount: 6.88M | Year: 2016

The objective of the project IMPROOF is to drastically improve the energy efficiency of steam cracking furnaces by at least 20%, in a cost effective way, while simultaneously reducing emissions of greenhouse gasses and NOx per ton ethylene produced by at least 25%. One important way to reduce the energy input in steam cracking furnaces is to reduce coke formation on the reactor wall. The use of either advanced coil materials, combined with 3D reactor designs, improved process control, and more uniform heat transfer will increase run lengths, reducing simultaneously CO2 emissions and the lifetime of the furnaces. Biogas and bio-oil will be used as alternative fuels because they are considered renewable, and hence, decrease net CO2 production. Application of high emissivity coatings on the external surface of the radiant coils will further substantially improve the energy consumption. Less firing is required to reach the same process temperatures in the radiant coils. This will reduce fuel gas consumption and CO2 emissions by 10 to 15%. IMPROOF will demonstrate the advantage of combining all these technological innovations with an anticipated increase of the time on stream with a factor 3. To select the correct technologies for sustainable implementation in complex plant-wide and industrial data-intensive process systems, all the technology will be implanted in real-plant conditions at TRL6 in DOW. The strongly industrial oriented consortium is composed of 7 industrial partners, including 2 SME completed by 2 RTO and 2 university. This partnership shows a clear and strong path to the industrial and economical world with the involvement of all actors of the furnaces business. The financial resources mobilized by the partners represent a total grant of 6 878 401,25 with a global effort of 538 person.month.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: BG-10-2016 | Award Amount: 8.72M | Year: 2016

Arctic climate change increases the need of a growing number of stakeholders for trustworthy weather and climate predictions, both within the Arctic and beyond. APPLICATE will address this challenge and develop enhanced predictive capacity by bringing together scientists from academia, research institutions and operational prediction centres, including experts in weather and climate prediction and forecast dissemination. APPLICATE will develop a comprehensive framework for observationally constraining and assessing weather and climate models using advanced metrics and diagnostics. This framework will be used to establish the performance of existing models and measure the progress made within the project. APPLICATE will make significant model improvements, focusing on aspects that are known to play pivotal roles in both weather and climate prediction, namely: the atmospheric boundary layer including clouds; sea ice; snow; atmosphere-sea ice-ocean coupling; and oceanic transports. In addition to model developments, APPLICATE will enhance predictive capacity by contributing to the design of the future Arctic observing system and through improved forecast initialization techniques. The impact of Arctic climate change on the weather and climate of the Northern Hemisphere through atmospheric and oceanic linkages will be determined by a comprehensive set of novel multi-model numerical experiments using both coupled and uncoupled ocean and atmosphere models. APPLICATE will develop strong user-engagement and dissemination activities, including pro-active engagement of end-users and the exploitation of modern methods for communication and dissemination. Knowledge-transfer will also benefit from the direct engagement of operational prediction centres in APPLICATE. The educational component of APPLICATE will be developed and implemented in collaboration with the Association of Early Career Polar Scientists (APECS).


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: MG-1.2-2015 | Award Amount: 6.83M | Year: 2016

For decades, most of the aviation research activities have been focused on the reduction of noise and NOx and CO2 emissions. However, emissions from aircraft gas turbine engines of non-volatile PM, consisting primarily of soot particles, are of international concern today. Despite the lack of knowledge toward soot formation processes and characterization in terms of mass and size, engine manufacturers have now to deal with both gas and particles emissions. Furthermore, heat transfer understanding, that is also influenced by soot radiation, is an important matter for the improvement of the combustors durability, as the key point when dealing with low-emissions combustor architectures is to adjust the air flow split between the injection system and the combustors walls. The SOPRANO initiative consequently aims at providing new elements of knowledge, analysis and improved design tools, opening the way to: Alternative designs of combustion systems for future aircrafts that will enter into service after 2025 capable of simultaneously reducing gaseous pollutants and particles, Improved liner lifetime assessment methods. Therefore, the SOPRANO project will deliver more accurate experimental and numerical methodologies for predicting the soot emissions in academic or semi-technical combustion systems. This will contribute to enhance the comprehension of soot particles formation and their impact on heat transfer through radiation. In parallel, the durability of cooling liner materials, related to the walls air flow rate, will be addressed by heat transfer measurements and predictions. Finally, the expected contribution of SOPRANO is to apply these developments in order to determine the main promising concepts, in the framework of current low-NOx technologies, able to control the emitted soot particles in terms of mass and size over a large range of operating conditions without compromising combustors liner durability and performance toward NOx emissions.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: MG-1.1-2014 | Award Amount: 3.05M | Year: 2015

The ability to simulate aerodynamic flows using CFD methods has progressed rapidly over the last decades and has given rise to a change in design processes in aeronautics already. But more improvement is necessary to overcome the (still) existing lack in confidence in CFD usage, based on turbulence modelling. The TILDA project will offer methods and approaches combining advanced and efficient high-order numerical schemes (HOMs) with innovative approaches for LES and DNS in order to resolve all relevant flow features on tens of thousands of processors in order to get close to a full LES/DNS solution for 1billion degrees-of-freedom (DOF) not exceeding turn-around times of a few days. The TILDA project will provide both an improved physical knowledge and more accurate predictions of non-linear, unsteady flows near borders of the flight envelope - which will directly contribute to an enhanced reliability. The main highly innovative objectives, targeting at industrial needs read: Advance methods to accelerate HOM for unsteady turbulence simulations on unstructured grids. Advance methods to accelerate LES and future DNS methodology by multilevel, adaptive, fractal and similar approaches on unstructured grids. Use existent large scale HPC networks to enable industrial applications of LES/DNS close(r) to daily practice. Compact high-order methods offer a very high ratio between computational work per DOF combined to a low data dependency stencil, making these methods extremely well adapted for shared-memory parallel processors, and allow for efficient redistribution over an increased number of processors. Provide grid generation methods for HOM on unstructured grids with emphasis on valid curvilinear meshes for complex geometries, and accounting for mesh and solution quality. Provide suitable I/O and interactive co- and post-processing tools for large datasets. Demonstration of multi-disciplinary capabilities of HOM for LES in the area of aero-acoustics.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-5-2015 | Award Amount: 4.95M | Year: 2015

ESiWACE will substantially improve efficiency and productivity of numerical weather and climate simulation on high-performance computing platforms by supporting the end-to-end workflow of global Earth system modelling in HPC environment. This will be obtained by improving and supporting (1) scalability of models, tools and data management on state-of-the-art supercomputer systems (2) Usability of models and tools throughout the European HPC eco-system, and (3) the Exploitability of the huge amount of resulting data. We will develop solutions for cross-cutting HPC challenges particular to the weather and climate domain. This will range from the development of specific software products to the deployment of user facing services for both, computing and storage. ESiWACE leverages two established European networks, namely (1) the European Network for Earth System modelling, representing the European climate modelling community and (2) the world leading European Centre for Medium-Range Weather Forecasts. The governance structure that defines the services to be provided will be driven by the European weather and climate science community. Weather and climate computing have always been one of the key drivers for HPC development, with domain specific scientific and technical requirements that stretch the capability and capacity of existing software and hardware to the limits. By developing solutions for Europe and at European scale, ESiWACE will directly impact on the competitiveness of the European HPC industry by engendering new products, providing opportunities for exploitation beyond the project itself, and by enhancing the skills base of staff in both industry and academia. ESiWACE will be at once thematic, as it focuses on the HPC application domain of climate and weather modeling, transversal, as it covers several aspects of computational science, and challenge-driven, as climate and weather predictability represents a major societal issue.

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