Project acronym A-DATADRIVE-B
Project Advanced Data-Driven Black-box modelling
Researcher (PI) Johan Adelia K Suykens
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Summary
Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Max ERC Funding
2 485 800 €
Duration
Start date: 2012-04-01, End date: 2017-03-31
Project acronym ActiveWindFarms
Project Active Wind Farms: Optimization and Control of Atmospheric Energy Extraction in Gigawatt Wind Farms
Researcher (PI) Johan Meyers
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Starting Grant (StG), PE8, ERC-2012-StG_20111012
Summary With the recognition that wind energy will become an important contributor to the world’s energy portfolio, several wind farms with a capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and weather. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case. For large wind farms, the vertical structure and turbulence physics of the flow in the ABL become crucial ingredients in their design and operation. This introduces a new set of scientific challenges related to the design and control of large wind farms. The major ambition of the present research proposal is to employ optimal control techniques to control the interaction between large wind farms and the ABL, and optimize overall farm-power extraction. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented. The PI possesses a unique combination of expertise and tools enabling these developments: efficient parallel large-eddy simulations of wind farms, multi-scale turbine modeling, and gradient-based optimization in large optimization-parameter spaces using adjoint formulations. To ensure a maximum impact on the wind-engineering field, the project aims at optimal control, experimental wind-tunnel validation, and at including multi-disciplinary aspects, related to structural mechanics, power quality, and controller design.
Summary
With the recognition that wind energy will become an important contributor to the world’s energy portfolio, several wind farms with a capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and weather. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case. For large wind farms, the vertical structure and turbulence physics of the flow in the ABL become crucial ingredients in their design and operation. This introduces a new set of scientific challenges related to the design and control of large wind farms. The major ambition of the present research proposal is to employ optimal control techniques to control the interaction between large wind farms and the ABL, and optimize overall farm-power extraction. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented. The PI possesses a unique combination of expertise and tools enabling these developments: efficient parallel large-eddy simulations of wind farms, multi-scale turbine modeling, and gradient-based optimization in large optimization-parameter spaces using adjoint formulations. To ensure a maximum impact on the wind-engineering field, the project aims at optimal control, experimental wind-tunnel validation, and at including multi-disciplinary aspects, related to structural mechanics, power quality, and controller design.
Max ERC Funding
1 499 241 €
Duration
Start date: 2012-10-01, End date: 2017-09-30
Project acronym AEROSOL
Project Astrochemistry of old stars:direct probing of unique chemical laboratories
Researcher (PI) Leen Katrien Els Decin
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Consolidator Grant (CoG), PE9, ERC-2014-CoG
Summary The gas and dust in the interstellar medium (ISM) drive the chemical evolution of galaxies, the formation of stars and planets, and the synthesis of complex prebiotic molecules. The prime birth places for this interstellar material are the winds of evolved (super)giant stars. These winds are unique chemical laboratories, in which a large variety of gas and dust species radially expand away from the star.
Recent progress on the observations of these winds has been impressive thanks to Herschel and ALMA. The next challenge is to unravel the wealth of chemical information contained in these data. This is an ambitious task since (1) a plethora of physical and chemical processes interact in a complex way, (2) laboratory data to interpret these interactions are lacking, and (3) theoretical tools to analyse the data do not meet current needs.
To boost the knowledge of the physics and chemistry characterizing these winds, I propose a world-leading multi-disciplinary project combining (1) high-quality data, (2) novel theoretical wind models, and (3) targeted laboratory experiments. The aim is to pinpoint the dominant chemical pathways, unravel the transition from gas-phase to dust species, elucidate the role of clumps on the overall wind structure, and study the reciprocal effect between various dynamical and chemical phenomena.
Now is the right time for this ambitious project thanks to the availability of (1) high-quality multi-wavelength data, including ALMA and Herschel data of the PI, (2) supercomputers enabling a homogeneous analysis of the data using sophisticated theoretical wind models, and (3) novel laboratory equipment to measure the gas-phase reaction rates of key species.
This project will have far-reaching impact on (1) the field of evolved stars, (2) the understanding of the chemical lifecycle of the ISM, (3) chemical studies of dynamically more complex systems, such as exoplanets, protostars, supernovae etc., and (4) it will guide new instrument development.
Summary
The gas and dust in the interstellar medium (ISM) drive the chemical evolution of galaxies, the formation of stars and planets, and the synthesis of complex prebiotic molecules. The prime birth places for this interstellar material are the winds of evolved (super)giant stars. These winds are unique chemical laboratories, in which a large variety of gas and dust species radially expand away from the star.
Recent progress on the observations of these winds has been impressive thanks to Herschel and ALMA. The next challenge is to unravel the wealth of chemical information contained in these data. This is an ambitious task since (1) a plethora of physical and chemical processes interact in a complex way, (2) laboratory data to interpret these interactions are lacking, and (3) theoretical tools to analyse the data do not meet current needs.
To boost the knowledge of the physics and chemistry characterizing these winds, I propose a world-leading multi-disciplinary project combining (1) high-quality data, (2) novel theoretical wind models, and (3) targeted laboratory experiments. The aim is to pinpoint the dominant chemical pathways, unravel the transition from gas-phase to dust species, elucidate the role of clumps on the overall wind structure, and study the reciprocal effect between various dynamical and chemical phenomena.
Now is the right time for this ambitious project thanks to the availability of (1) high-quality multi-wavelength data, including ALMA and Herschel data of the PI, (2) supercomputers enabling a homogeneous analysis of the data using sophisticated theoretical wind models, and (3) novel laboratory equipment to measure the gas-phase reaction rates of key species.
This project will have far-reaching impact on (1) the field of evolved stars, (2) the understanding of the chemical lifecycle of the ISM, (3) chemical studies of dynamically more complex systems, such as exoplanets, protostars, supernovae etc., and (4) it will guide new instrument development.
Max ERC Funding
2 605 897 €
Duration
Start date: 2016-01-01, End date: 2020-12-31
Project acronym AEROSPACEPHYS
Project Multiphysics models and simulations for reacting and plasma flows applied to the space exploration program
Researcher (PI) Thierry Edouard Bertrand Magin
Host Institution (HI) INSTITUT VON KARMAN DE DYNAMIQUE DES FLUIDES
Call Details Starting Grant (StG), PE8, ERC-2010-StG_20091028
Summary Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”
Summary
Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”
Max ERC Funding
1 494 892 €
Duration
Start date: 2010-09-01, End date: 2015-08-31
Project acronym ALUFIX
Project Friction stir processing based local damage mitigation and healing in aluminium alloys
Researcher (PI) Aude SIMAR
Host Institution (HI) UNIVERSITE CATHOLIQUE DE LOUVAIN
Call Details Starting Grant (StG), PE8, ERC-2016-STG
Summary ALUFIX proposes an original strategy for the development of aluminium-based materials involving damage mitigation and extrinsic self-healing concepts exploiting the new opportunities of the solid-state friction stir process. Friction stir processing locally extrudes and drags material from the front to the back and around the tool pin. It involves short duration at moderate temperatures (typically 80% of the melting temperature), fast cooling rates and large plastic deformations leading to far out-of-equilibrium microstructures. The idea is that commercial aluminium alloys can be locally improved and healed in regions of stress concentration where damage is likely to occur. Self-healing in metal-based materials is still in its infancy and existing strategies can hardly be extended to applications. Friction stir processing can enhance the damage and fatigue resistance of aluminium alloys by microstructure homogenisation and refinement. In parallel, friction stir processing can be used to integrate secondary phases in an aluminium matrix. In the ALUFIX project, healing phases will thus be integrated in aluminium in addition to refining and homogenising the microstructure. The “local stress management strategy” favours crack closure and crack deviation at the sub-millimetre scale thanks to a controlled residual stress field. The “transient liquid healing agent” strategy involves the in-situ generation of an out-of-equilibrium compositionally graded microstructure at the aluminium/healing agent interface capable of liquid-phase healing after a thermal treatment. Along the road, a variety of new scientific questions concerning the damage mechanisms will have to be addressed.
Summary
ALUFIX proposes an original strategy for the development of aluminium-based materials involving damage mitigation and extrinsic self-healing concepts exploiting the new opportunities of the solid-state friction stir process. Friction stir processing locally extrudes and drags material from the front to the back and around the tool pin. It involves short duration at moderate temperatures (typically 80% of the melting temperature), fast cooling rates and large plastic deformations leading to far out-of-equilibrium microstructures. The idea is that commercial aluminium alloys can be locally improved and healed in regions of stress concentration where damage is likely to occur. Self-healing in metal-based materials is still in its infancy and existing strategies can hardly be extended to applications. Friction stir processing can enhance the damage and fatigue resistance of aluminium alloys by microstructure homogenisation and refinement. In parallel, friction stir processing can be used to integrate secondary phases in an aluminium matrix. In the ALUFIX project, healing phases will thus be integrated in aluminium in addition to refining and homogenising the microstructure. The “local stress management strategy” favours crack closure and crack deviation at the sub-millimetre scale thanks to a controlled residual stress field. The “transient liquid healing agent” strategy involves the in-situ generation of an out-of-equilibrium compositionally graded microstructure at the aluminium/healing agent interface capable of liquid-phase healing after a thermal treatment. Along the road, a variety of new scientific questions concerning the damage mechanisms will have to be addressed.
Max ERC Funding
1 497 447 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym ATTO
Project A new concept for ultra-high capacity wireless networks
Researcher (PI) Piet DEMEESTER
Host Institution (HI) UNIVERSITEIT GENT
Call Details Advanced Grant (AdG), PE7, ERC-2015-AdG
Summary The project will address the following key question:
How can we provide fibre-like connectivity to moving objects (robots, humans) with the following characteristics: very high dedicated bitrate of 100 Gb/s per object, very low latency of <10 μs, very high reliability of 99.999%, very high density of more than one object per m2 and this at low power consumption?
Achieving this would be groundbreaking and it requires a completely new and high-risk approach: applying close proximity wireless communications using low interference ultra-small cells (called “ATTO-cells”) integrated in floors and connected to antennas on the (parallel) floor-facing surface of ground moving objects. This makes it possible to obtain very high densities with very good channel conditions. The technological challenges involved are groundbreaking in mobile networking (overall architecture, handover with extremely low latencies), wireless subsystems (60 GHz substrate integrated waveguide-based distributed antenna systems connected to RF transceivers integrated in floors, low crosstalk between ATTO-cells) and optical interconnect subsystems (simple non-blocking optical coherent remote selection of ATTO-cells, transparent low power 100 Gb/s coherent optical / RF transceiver interconnection using analogue equalization and symbol interleaving to support 4x4 MIMO). By providing this unique communication infrastructure in high density settings, the ATTO concept will not only support the highly demanding future 5G services (UHD streaming, cloud computing and storage, augmented and virtual reality, a range of IoT services, etc.), but also even more demanding services, that are challenging our imagination such as mobile robot swarms or brain computer interfaces with PFlops computing capabilities.
This new concept for ultra-high capacity wireless networks will open up many more opportunities in reconfigurable robot factories, intelligent hospitals, flexible offices, dense public spaces, etc.
Summary
The project will address the following key question:
How can we provide fibre-like connectivity to moving objects (robots, humans) with the following characteristics: very high dedicated bitrate of 100 Gb/s per object, very low latency of <10 μs, very high reliability of 99.999%, very high density of more than one object per m2 and this at low power consumption?
Achieving this would be groundbreaking and it requires a completely new and high-risk approach: applying close proximity wireless communications using low interference ultra-small cells (called “ATTO-cells”) integrated in floors and connected to antennas on the (parallel) floor-facing surface of ground moving objects. This makes it possible to obtain very high densities with very good channel conditions. The technological challenges involved are groundbreaking in mobile networking (overall architecture, handover with extremely low latencies), wireless subsystems (60 GHz substrate integrated waveguide-based distributed antenna systems connected to RF transceivers integrated in floors, low crosstalk between ATTO-cells) and optical interconnect subsystems (simple non-blocking optical coherent remote selection of ATTO-cells, transparent low power 100 Gb/s coherent optical / RF transceiver interconnection using analogue equalization and symbol interleaving to support 4x4 MIMO). By providing this unique communication infrastructure in high density settings, the ATTO concept will not only support the highly demanding future 5G services (UHD streaming, cloud computing and storage, augmented and virtual reality, a range of IoT services, etc.), but also even more demanding services, that are challenging our imagination such as mobile robot swarms or brain computer interfaces with PFlops computing capabilities.
This new concept for ultra-high capacity wireless networks will open up many more opportunities in reconfigurable robot factories, intelligent hospitals, flexible offices, dense public spaces, etc.
Max ERC Funding
2 496 250 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym BOSS-WAVES
Project Back-reaction Of Solar plaSma to WAVES
Researcher (PI) Tom VAN DOORSSELAERE
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Consolidator Grant (CoG), PE9, ERC-2016-COG
Summary "The solar coronal heating problem is a long-standing astrophysical problem. The slow DC (reconnection) heating models are well developed in detailed 3D numerical simulations. The fast AC (wave) heating mechanisms have traditionally been neglected since there were no wave observations.
Since 2007, we know that the solar atmosphere is filled with transverse waves, but still we have no adequate models (except for my own 1D analytical models) for their dissipation and plasma heating by these waves. We urgently need to know the contribution of these waves to the coronal heating problem.
In BOSS-WAVES, I will innovate the AC wave heating models by utilising novel 3D numerical simulations of propagating transverse waves. From previous results in my team, I know that the inclusion of the back-reaction of the solar plasma is crucial in understanding the energy dissipation: the wave heating leads to chromospheric evaporation and plasma mixing (by the Kelvin-Helmholtz instability).
BOSS-WAVES will bring the AC heating models to the same level of state-of-the-art DC heating models.
The high-risk, high-gain goals are (1) to create a coronal loop heated by waves, starting from an "empty" corona, by evaporating chromospheric material, and (2) to pioneer models for whole active regions heated by transverse waves."
Summary
"The solar coronal heating problem is a long-standing astrophysical problem. The slow DC (reconnection) heating models are well developed in detailed 3D numerical simulations. The fast AC (wave) heating mechanisms have traditionally been neglected since there were no wave observations.
Since 2007, we know that the solar atmosphere is filled with transverse waves, but still we have no adequate models (except for my own 1D analytical models) for their dissipation and plasma heating by these waves. We urgently need to know the contribution of these waves to the coronal heating problem.
In BOSS-WAVES, I will innovate the AC wave heating models by utilising novel 3D numerical simulations of propagating transverse waves. From previous results in my team, I know that the inclusion of the back-reaction of the solar plasma is crucial in understanding the energy dissipation: the wave heating leads to chromospheric evaporation and plasma mixing (by the Kelvin-Helmholtz instability).
BOSS-WAVES will bring the AC heating models to the same level of state-of-the-art DC heating models.
The high-risk, high-gain goals are (1) to create a coronal loop heated by waves, starting from an "empty" corona, by evaporating chromospheric material, and (2) to pioneer models for whole active regions heated by transverse waves."
Max ERC Funding
1 991 960 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym BRIDGE
Project Biomimetic process design for tissue regeneration:
from bench to bedside via in silico modelling
Researcher (PI) Liesbet Geris
Host Institution (HI) UNIVERSITE DE LIEGE
Call Details Starting Grant (StG), PE8, ERC-2011-StG_20101014
Summary "Tissue engineering (TE), the interdisciplinary field combining biomedical and engineering sciences in the search for functional man-made organ replacements, has key issues with the quantity and quality of the generated products. Protocols followed in the lab are mainly trial and error based, requiring a huge amount of manual interventions and lacking clear early time-point quality criteria to guide the process. As a result, these processes are very hard to scale up to industrial production levels. BRIDGE aims to fortify the engineering aspects of the TE field by adding a higher level of understanding and control to the manufacturing process (MP) through the use of in silico models. BRIDGE will focus on the bone TE field to provide proof of concept for its in silico approach.
The combination of the applicant's well-received published and ongoing work on a wide range of modelling tools in the bone field combined with the state-of-the-art experimental techniques present in the TE lab of the additional participant allows envisaging following innovation and impact:
1. proof-of-concept of the use of an in silico blue-print for the design and control of a robust modular TE MP;
2. model-derived optimised culture conditions for patient derived cell populations increasing modular robustness of in vitro chondrogenesis/endochondral ossification;
3. in silico identification of a limited set of in vitro biomarkers that is predictive of the in vivo outcome;
4. model-derived optimised culture conditions increasing quantity and quality of the in vivo outcome of the TE MP;
5. incorporation of congenital defects in the in silico MP design, constituting a further validation of BRIDGE’s in silico approach and a necessary step towards personalised medical care.
We believe that the systematic – and unprecedented – integration of (bone) TE and mathematical modelling, as proposed in BRIDGE, is required to come to a rationalized, engineering approach to design and control bone TE MPs."
Summary
"Tissue engineering (TE), the interdisciplinary field combining biomedical and engineering sciences in the search for functional man-made organ replacements, has key issues with the quantity and quality of the generated products. Protocols followed in the lab are mainly trial and error based, requiring a huge amount of manual interventions and lacking clear early time-point quality criteria to guide the process. As a result, these processes are very hard to scale up to industrial production levels. BRIDGE aims to fortify the engineering aspects of the TE field by adding a higher level of understanding and control to the manufacturing process (MP) through the use of in silico models. BRIDGE will focus on the bone TE field to provide proof of concept for its in silico approach.
The combination of the applicant's well-received published and ongoing work on a wide range of modelling tools in the bone field combined with the state-of-the-art experimental techniques present in the TE lab of the additional participant allows envisaging following innovation and impact:
1. proof-of-concept of the use of an in silico blue-print for the design and control of a robust modular TE MP;
2. model-derived optimised culture conditions for patient derived cell populations increasing modular robustness of in vitro chondrogenesis/endochondral ossification;
3. in silico identification of a limited set of in vitro biomarkers that is predictive of the in vivo outcome;
4. model-derived optimised culture conditions increasing quantity and quality of the in vivo outcome of the TE MP;
5. incorporation of congenital defects in the in silico MP design, constituting a further validation of BRIDGE’s in silico approach and a necessary step towards personalised medical care.
We believe that the systematic – and unprecedented – integration of (bone) TE and mathematical modelling, as proposed in BRIDGE, is required to come to a rationalized, engineering approach to design and control bone TE MPs."
Max ERC Funding
1 191 440 €
Duration
Start date: 2011-12-01, End date: 2016-11-30
Project acronym CAPS
Project Capillary suspensions: a novel route for versatile, cost efficient and environmentally friendly material design
Researcher (PI) Erin Crystal Koos
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Starting Grant (StG), PE8, ERC-2013-StG
Summary A wide variety of materials including coatings and adhesives, emerging materials for nanotechnology products, as well as everyday food products are processed or delivered as suspensions. The flow properties of such suspensions must be finely adjusted according to the demands of the respective processing techniques, even for the feel of cosmetics and the perception of food products is highly influenced by their rheological properties. The recently developed capillary suspensions concept has the potential to revolutionize product formulations and material design. When a small amount (less than 1%) of a second immiscible liquid is added to the continuous phase of a suspension, the rheological properties of the mixture are dramatically altered from a fluid-like to a gel-like state or from a weak to a strong gel and the strength can be tuned in a wide range covering orders of magnitude. Capillary suspensions can be used to create smart, tunable fluids, stabilize mixtures that would otherwise phase separate, significantly reduce the amount organic or polymeric additives, and the strong particle network can be used as a precursor for the manufacturing of cost-efficient porous ceramics and foams with unprecedented properties.
This project will investigate the influence of factors determining capillary suspension formation, the strength of these admixtures as a function of these aspects, and how capillary suspensions depend on external forces. Only such a fundamental understanding of the network formation in capillary suspensions on both the micro- and macroscopic scale will allow for the design of sophisticated new materials. The main objectives of this proposal are to quantify and predict the strength of these admixtures and then use this information to design a variety of new materials in very different application areas including, e.g., porous materials, water-based coatings, ultra low fat foods, and conductive films.
Summary
A wide variety of materials including coatings and adhesives, emerging materials for nanotechnology products, as well as everyday food products are processed or delivered as suspensions. The flow properties of such suspensions must be finely adjusted according to the demands of the respective processing techniques, even for the feel of cosmetics and the perception of food products is highly influenced by their rheological properties. The recently developed capillary suspensions concept has the potential to revolutionize product formulations and material design. When a small amount (less than 1%) of a second immiscible liquid is added to the continuous phase of a suspension, the rheological properties of the mixture are dramatically altered from a fluid-like to a gel-like state or from a weak to a strong gel and the strength can be tuned in a wide range covering orders of magnitude. Capillary suspensions can be used to create smart, tunable fluids, stabilize mixtures that would otherwise phase separate, significantly reduce the amount organic or polymeric additives, and the strong particle network can be used as a precursor for the manufacturing of cost-efficient porous ceramics and foams with unprecedented properties.
This project will investigate the influence of factors determining capillary suspension formation, the strength of these admixtures as a function of these aspects, and how capillary suspensions depend on external forces. Only such a fundamental understanding of the network formation in capillary suspensions on both the micro- and macroscopic scale will allow for the design of sophisticated new materials. The main objectives of this proposal are to quantify and predict the strength of these admixtures and then use this information to design a variety of new materials in very different application areas including, e.g., porous materials, water-based coatings, ultra low fat foods, and conductive films.
Max ERC Funding
1 489 618 €
Duration
Start date: 2013-08-01, End date: 2018-07-31
Project acronym Cathedral
Project Post-Snowden Circuits and Design Methods for Security
Researcher (PI) Ingrid VERBAUWHEDE
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Advanced Grant (AdG), PE7, ERC-2015-AdG
Summary Summary: Comprehensive set of circuits and design methods to create next generation electronic circuits with strong built-in trust and security.
Electronics are integrating/invading into the human environment at an amazing speed, called the Internet-of-Things and next the Internet-of-Everything. This creates huge security problems. Distributed (e.g. body) sensors, pick up often very private data, which is sent digitally into the cloud, over wireless and wired links. Protection of this data relies on high-quality cryptographic algorithms and protocols. The nodes need to be cheap and lightweight, making them very vulnerable to eavesdropping and abuse. Moreover, post-Snowden, society realizes that the attack capabilities of intelligence agencies, and probably following soon of organized crime and other hackers, are orders of magnitude stronger than imagined. Thus there is a strong demand to re-establish trust in ICT systems.
In this proposal we focus on the root of trust: the digital hardware. The overall objective is to provide fundamental enabling technologies for secure trustworthy digital circuits which can be applied in a wide range of applications. To master complexity, digital hardware design is traditionally split into different abstraction layers. We revisit these abstraction layers from a security viewpoint: we look at process variations to the benefit of security, standard cell compatible digital design flow with security as design objective, hardware IP blocks for next generation cryptographic algorithms and protocols (e.g. authenticated encryption schemes, post-quantum public key schemes), integration into embedded HW/SW platforms, and methods to provide trust evidence to higher levels of abstraction. To strengthen the security we investigate the links between the layers. Finally an embedded application is selected as design driver, the security evaluation of which will be fed back to the individual layers.
Summary
Summary: Comprehensive set of circuits and design methods to create next generation electronic circuits with strong built-in trust and security.
Electronics are integrating/invading into the human environment at an amazing speed, called the Internet-of-Things and next the Internet-of-Everything. This creates huge security problems. Distributed (e.g. body) sensors, pick up often very private data, which is sent digitally into the cloud, over wireless and wired links. Protection of this data relies on high-quality cryptographic algorithms and protocols. The nodes need to be cheap and lightweight, making them very vulnerable to eavesdropping and abuse. Moreover, post-Snowden, society realizes that the attack capabilities of intelligence agencies, and probably following soon of organized crime and other hackers, are orders of magnitude stronger than imagined. Thus there is a strong demand to re-establish trust in ICT systems.
In this proposal we focus on the root of trust: the digital hardware. The overall objective is to provide fundamental enabling technologies for secure trustworthy digital circuits which can be applied in a wide range of applications. To master complexity, digital hardware design is traditionally split into different abstraction layers. We revisit these abstraction layers from a security viewpoint: we look at process variations to the benefit of security, standard cell compatible digital design flow with security as design objective, hardware IP blocks for next generation cryptographic algorithms and protocols (e.g. authenticated encryption schemes, post-quantum public key schemes), integration into embedded HW/SW platforms, and methods to provide trust evidence to higher levels of abstraction. To strengthen the security we investigate the links between the layers. Finally an embedded application is selected as design driver, the security evaluation of which will be fed back to the individual layers.
Max ERC Funding
2 369 250 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
