Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Interoperable tools for an efficient management and effective planning of the electricity grid (INTERPRETER)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: A single, smart European electricity grid
Action type: Research and Innovation actions
Countries involved: Spain,Spain,Spain,Spain,Belgium,Greece,France,Denmark,Portugal
Call: Research on advanced tools and technological development (H2020-LC-SC3-2019-ES-SCC, 2019)
Start date: 2019-10-01
End date: 2022-09-30
Duration (months): 36.0
Total project cost (EUR): 3907872.5
EU funding (EUR): 3907872.5
Participants: 11
Project status: CLOSED

The transition towards a low-carbon economy is significantly transforming the power system from a unidirectional, centralised and fossil-based system towards a bidirectional, distributed and renewable-based one. In this context, DSOs and TSOs are facing more complex grid operations, including challenges like reverse power flows, additional power flows in transmission systems and grid stability issues. Available tools for grid management in this changing environment have often underperformed for several reasons (e.g. unavailability of grid models, data management restrictions, use of conventional approaches to the application algorithms, etc.). INTERPRETER will overcome limitations of existing tools through a modular grid management solution consisting of a set of 10 software applications for an optimal design, planning, operation and maintenance of the electricity grid – with a special focus on the distribution network – that will be offered to grid operators through an open-source interoperable platform. These tools will support DSOs and TSOs to move from a traditional grid management approach to an active system management approach, considering the rapid deployment of distributed energy resources as well as growing environmental concerns. INTERPRETER activities will be conducted by a strong and well-balanced consortium composed by 5 RTOs, 2 DSOs, 1 SW developer company leader in its sector and 1 SME specialised in communication & dissemination. The project includes an ambitious validation phase, in which the solutions will be tested in 3 pilots in Belgium, Denmark and Spain, thus ensuring a high replicability across Europe. Overall, the project aims to achieve an annual economic impact in the project pilots from investment deferrals of 36.6 M€ due to the remuneration of assets and of 28.15 M€ due to the amortisation of the capacity assets, as well as a recovery of 665,576 € from non-technical losses detection and 11,422 € from reduced outage frequency.

Keywords: grid management platform,data based software applications,interoperability,grid models,smart meters,tso cooperation,ancillary services,res integration,lca and lcc,grid planning
Modelling individual farmer behaviours in Coupled Human Natural Systems under changing climate and society (MODFaBe)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-09-01
End date: 2022-08-31
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: CLOSED

Agriculture is one of the sectors most affected by climate change, especially in lower latitude areas, were climate change will result in increased temperature, reduced rainfall, and increased frequency of extreme weather events such as floods and droughts. Water and food nexus, often embedded in seemingly endless ecological, social and political interactions, are context-dependent, socially constructed and technically uncertain. Modelling techniques have been recognized, also in social sciences, as effective computational techniques to simulate social influence processes in human-nature systems from interactions within community of individual agents. The aim of the proposal is to reduce the vulnerability and improve the resilience of multifunctional irrigation systems to climate change scenarios by modelling individual farmer’ behaviour and informing managers and decision-makers about the effectiveness of different types of interventions. Through the combination of qualitative and quantitative methods and evidence-based analysis from social learning process (survey sample, interviews, statistical analyses, behavioural modelling simulations, artificial intelligence), insights are collected on how individual farmer and key stakeholders behave with respect to climate change adaptation in Coupled Human Natural Systems (CHNS), such as hydrosocial systems (e.g. multifunctional irrigation systems). A key question in today climate change adaptation research will be addressed: Can behaviour modelling help farmers to promote actions and anticipate decisions to adapt to climate change and become more sustainable and resilient? The assessment of farmer’ behavioural on climate change adaptation measures will be conducted on the Muzza irrigation district, located southeast of the city of Milan (Northern Italy). Modelling human behaviour can be used as a safe laboratory for policy experimentation, testing the effectiveness of strategies and policy measures on climate change.

Keywords: irrigation,farmer,climate change,human nature systems,modelling,behaviour
Development of Maximum Efficiency Phase Contrast Electron Microscopy (DIGIPHASE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Austria
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-07-01
End date: 2017-06-30
Duration (months): 24.0
Total project cost (EUR): 166156.8
EU funding (EUR): 166156.8
Participants: 1
Project status: CLOSED

Electron microscopy is a key technique for imaging and analysis of materials. Although aberration correction has made atomic resolution possible at low accelerating voltages, beam damage remains a critical limitation for many types of materials. The imaging modes currently in use today are inefficient in terms of the number of transmitted electrons detected and the way in which these are used to derive information. Current detectors integrate over details in the angular distribution of scattered intensities, and make use of only a limited range of scattering angles. In the case of scanning transmission electron microscopy (STEM), a wealth of information is contained in the distribution of electron scattering as a function of the illuminating probe position. The proposed work will make use of pixelated detectors to record this four-dimensional data set and develop methods to intelligently utilize the information it contains. This research project has become possible through recent advances in the sensitivity and speed of pixelated detectors, and offers a new path to maximize the information gained per fast electron. Maximum efficiency phase contrast imaging in STEM recovers the full amplitude and phase components of the specimen, with minimum dose, and maximum signal to noise ratio, and maximum contrast that does not require aberrations. In materials science for example it will enable imaging of charge transfer at point defects and interfaces while simultaneous Z-contrast imaging provides interpretability and chemical sensitivity. Similarly, such high sensitivity phase detection will allow the direct imaging of local electric and magnetic fields at the highest possible spatial resolutions, providing many new opportunities for understanding electronic, spintronic and magnetic materials at the heart of today’s technological advances. In biology, maximum efficiency phase contrast imaging may open the door to the ultimate low dose molecular- and bio-imaging.
Financial Intermediation of Long-Term Savings (LIFE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: France
Call: ERC CONSOLIDATOR GRANTS (ERC-2020-COG, 2020)
Start date: 2021-02-01
End date: 2026-01-31
Duration (months): 60.0
Total project cost (EUR): 875000.0
EU funding (EUR): 875000.0
Participants: 1
Project status: SIGNED

Against a backdrop of population aging and secular decline in interest rates, traditional state and occupational pension systems are under stress, forcing households to increasingly rely on their own savings and to bear financial markets risk. Financial intermediaries increasingly take up the role of collecting and investing households’ long-term savings. In the EU, household savings intermediated by life insurers amount to 8 trillion euros or 22% of aggregate household financial wealth. Moreover, life insurers are not pass-through intermediaries: They actively provide households with insurance against market risk through intergenerational risk sharing mechanisms and return guarantees. I will use a combination of unique regulatory data, empirical designs grounded in theory (existing and that I will develop), and careful identification strategies, to understand the role of life insurers in intermediating households’ long-term savings and providing them with insurance against financial markets risk. I will study how savings products embedding such insurance share aggregate risk between households and intermediaries, and between different cohorts of households. I will analyze the impact of these risk sharing arrangements on the supply of capital to the real economy. I will assess the impact of competition between financial intermediaries and the impact of capital constraints on the provision of insurance against aggregate risk and on the build-up of systemic risk in the insurance sector. On the way, I expect to contribute to the policy debates on the financing of retirement and the regulation of financial intermediaries.

Keywords: long tem savings,european life insurers,intergenerational risk sharing
Transfer the real 3D world to interactive creative endeavours in apparel industry (InKreate)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Spain,Israel,Spain,Romania,Slovenia,Netherlands,Portugal,Portugal
Call: Support technology transfer to the creative industries (H2020-ICT-2016-1, 2016)
Start date: 2017-01-01
End date: 2018-06-30
Duration (months): 18.0
Total project cost (EUR): 1177136.25
EU funding (EUR): 948758.63
Participants: 10
Project status: CLOSED

Whereas the manufacturing and distribution of apparel has advanced in past years with the application of new CAM and ITC technologies, the design process is still very traditional. Sketching ideas, creating story boards, draping, and developing technical drawings (also known as technical sketches) are just some of the tasks that are still being done either in the old-fashioned way or with the aid of digital tools, most of which are spinoff uses of technologies developed for other industries, and not adapted to the necessities of the creative apparel industry. At the same time, there are emerging technologies that could reduce the timing and the cost of the design process, such as 3D scanners and 3D sketching tools. New low cost 3D scanners have indeed appeared in the market, and could allow a real customization of the clothes design. Moreover, libraries of 3D realistic avatars adapted to the target population of a new clothing collection will be a great improvement for mass production. Theoretically, a designer could sketch the design over the avatar of a customer, or over a realistic avatar that represents a target population. Sketching designs over real 3D bodies allows the visualization of designs in real dimensions, improves communication between the creative team, and reduce misunderstandings in the following steps (e.g. pattern making, manufacturing, etc.). The realistic visualization of the designs has many advantages: 1) Elimination of manual tasks. 2) Improvement of the communication between designers and decision takers (the managers that approve the design for manufacturing). The realistic visualization reduces misunderstandings and failures. 3) Better cost analysis. InKreate expects to improve the apparel design process using low cost 3D scanners and 3D sketching tools.

Keywords: 3d scan,3d sketch,apparel process design,3d anthropometry
Information Theory with Uncertain Laws (ITUL)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Spain,United Kingdom
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-08-01
End date: 2023-07-31
Duration (months): 72.0
Total project cost (EUR): 1888033.0
EU funding (EUR): 1213654.24
Participants: 2
Project status: SIGNED

Shannon's Information Theory paved the way for the information era by providing the mathematical foundations of digital information systems. A key underlying assumption of Shannon's key results is that the probability law that governing system is known, allowing to optimize the codebook and decoder accordingly. There are a number of important situations where perfectly estimating the system law is impossible; in these situations the codebook and decoder must be designed without complete (or no) knowledge of the system law. The vast majority of the Information Theory literature makes strong simplifying assumptions on the model. Theoretical studies that provide a general treatment of information processing with uncertain laws are hence urgently needed. For general systems, standard asymptotic techniques cannot be invoked and new techniques must be sought. A fundamental understanding of the impact of uncertainty in general systems is crucial to harvesting the potential gains in practice. This project is aimed at contributing towards the ambitious goal of providing a unified framework for the study of Information Theory with uncertain laws. A general framework based on hypothesis testing will be developed and code designs and constructions that naturally follow from the hypothesis testing formulation will be derived. This unconventional and challenging treatment of Information Theory will advance the area and will contribute to Information Sciences and Systems disciplines where Information Theory is relevant. A comprehensive study of the fundamental limits and optimal code design with law uncertainty for general models will represent a major step forward in the field, with the potential to provide new tools and techniques to solve open problems in close disciplines. Therefore, the outcomes of this project will not only benefit communications, but also areas such as probability theory, statistics, physics, computer science and economics.

Keywords: information theory,coding theory,digital communications,data compression
Smart Tools for Railway work safEty and performAnce iMprovement (STREAM)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: European rail initiative
Action type: Research and Innovation actions
Partnership: Shift2Rail (Art-187)
Countries involved: Spain,Italy,Italy,Finland,Belgium,France
Call: Advanced tools and equipment: collaborative robots & wearable mobile machines (TD3.8) (H2020-S2RJU-OC-2020, 2020)
Start date: 2020-12-01
End date: 2023-08-31
Duration (months): 33.0
Total project cost (EUR): 2700000.0
EU funding (EUR): 2700000.0
Participants: 8
Project status: SIGNED

The rail industry is facing important challenges as the average age of the workforce keeps growing while less young workers are interested in the physically demanding work required. Smart technologies can help to reduce work demands, avoid incidents and accidents, and support workers during heavy activities. STREAM support LEAN execution of intelligent maintenance process by introducing technologies that cause negligible modification of current working procedures, yet strongly improve operation planning, safety and performance. STREAM will develop two smart technologies employing environment perception and human intention principles enabling prevention and risk mitigation. First, STREAM will develop a control platform (OTA3M) adapted to existing rail excavators, by exploiting sensors, hydraulic actuators and software which will allow excavators to conduct multi-purpose autonomous operations enabling safe worker-machine collaboration. The OTA3M controls the excavator motion autonomously along tracks and introduces the autonomous capacity of manipulating heavy components relying on motion/force controls, obstacle detection and collision avoidance. Second, STREAM will deploy a modular active exoskeleton (MMPE) to reduce the risk of injury by assisting workers in heavy activities. The MMPE is tailored to track workers to reduce the risk of injury at the lumbar area by reducing biomechanical loading for a vast variety of manual handlings. MMPE understands human intention by exploiting human-activity recognition, proprioceptive sensors, and control strategies, and reducing worker’s efforts by applying specific forces, synchronized with the musculoskeletal system. The MMPE design emphasizes ergonomic aspects and PPEs integration to ensure comfort and usability making it suitable for workers. The consortium, assisted by an end-user board, will assess the devices from the perspectives of performance, ethics, and economic rationale to prepare further commercial exploitation

Keywords: autonomous collision avoidance,road rail excavators,hydraulic robot,motion,force control,occupational exoskeleton,back support active exoskeleton,human activity recognition,manual handling
Novel Superfluids in Ultracold Fermionic Mixtures (SuperCoolMix)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Austria,Austria
Call: ERC ADVANCED GRANT (ERC-2020-ADG, 2020)
Start date: 2022-01-01
End date: 2026-12-31
Duration (months): 60.0
Total project cost (EUR): 2367500.0
EU funding (EUR): 1363125.0
Participants: 2
Project status: SIGNED

The intricate mechanisms leading to superfluidity and superconductivity have fascinated researchers for many decades. The pairing of fermionic constituents is at the heart of a rich class of related phenomena in quantum matter. The understanding of unconventional regimes of superfluidity, such as broken-symmetry systems with finite-momentum pairs, poses great challenges for theory and experiment. Our experimental approach is based on a new ultracold model system, which has become available very recently, following a breakthrough in our laboratory. We combine two fermionic isotopes with different masses (Dy-161 and K-40) to create a quantum-degenerate Fermi-Fermi mixture. The system features the key ingredients required for creating novel strongly interacting superfluids: mass imbalance, tunability of interactions, and collisional stability. At present, our Dy-K system represents the only experimentally available Fermi-Fermi mixture that offers this combination of properties. The key point is that, according to theoretical predictions, mass imbalance favors unconventional regimes of superfluidity. In contrast to the widely investigated ultracold fermionic spin mixtures (systems with equal masses), the regions in the phase diagram for unconventional phases are much larger and appear at temperatures that can be realistically achieved in experiments. We will realize strongly interacting Fermi-Fermi superfluids and investigate the various regimes of superfluidity with the ultimate prospect to demonstrate symmetry-broken phases. For this purpose, we will generalize the methods developed for spin mixtures, and we will develop new species-selective optical traps. We will carry out our main research on the Dy-K system, but we will also push the limits of mass-imbalanced systems by extending our studies to a new system with extreme mass ratio (mixture of Dy-161 with Li-6). Our work will lead to a new generation of experiments on ultracold fermions.

Keywords: ultracold superfluids,quantum gas mixtures,strongly interacting fermi gases
Super Variable Vector Combnation for Voltage Optmisation Energy Saving Hub (SuperEh)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Israel
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-06-01
End date: 2016-08-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

SuperEH aims complete and commercialise the SVVC Energy Hub platform that PowerSines has developed during the last years. The Energy saving prototype shows good performance and there are not technical risk in completing the implementation of the project. SVVC is the electrical topology that gathers into a single design several Voltage optimisation techniques. It integrates two patented technologies developed and used by PowerSines: Induced Negative Voltage (INV) and Variable Vector Combination (VVC). The new topology reduces from four transformers into two transformers (3 phase). This architecture is controlled through eight switches commanded from the algorithm running as embedded SW in the uProcesor control board. We integrate all the power and control components into a single box. All the relevant variables of the installation are collected, monitored and controlled remotely. To get full advantage of all the possibilities we are making the Remote EMS: a complete set of SW tools, running on external webservers, allowing the communication with the local Hubs, monitoring and controlling energy, power analytics/decision making for both Administrative and User profiles, etc.) Added value of this combination SVVC Energy Hub + Remote EMS: - Implementation of cost-efficient E-saving solutions. (20%) - Short payback period. 1 to 3 years . - Simple installation, no modification of current electrical infrastructures. - Stabilisation of the system, detection of irregular consumption. - Proprietary automatic energy saving measurement algorithm unique (and patent pending). - Reduction of maintenance costs (40%) and extension of equipment lifetime (30-50%).

Keywords: voltage optimization,super variable vector combination,energy hub,energy management,systems