Summary
The Proof of Concept “Advanced Reduced order modellinG: Online computational web server for complex parametric Systems”
ARGOS wants to fulfil the demand of a Reduced Order Modelling Offline-Online tool, exploitable thanks to the creation of a
computational interface, handling and analysing a parametric problem in a very intuitive way. ARGOS is a computational
web server hosting several web applications, some with a general purpose and some for very specific problems: users can
access directly through the web browser, using their available device, choose the application they need and finally use it to
tackle the problem of interest. Thanks to the web application, users do not have to install any package by themselves on
their machine. Any device having an internet connection can access ARGOS and run a web computing application. The real
time response, due to the model reduction algorithms, combined with the ease of use of ARGOS, matches the industrial
demand of intuitive and immediate tools. Within this black-box framework, the final user is not required to have any specific
and technical knowledge about reduced order modelling. We thus envision that this approach could be adopted also in many
other fields directly related with applied sciences, for example in medicine and environmental studies. ARGOS will have a
vast audience of companies and institutions, proposing a closer integration between design teams and research and
development teams. ARGOS could also be easily connected with emerging technologies related with data assimilation, data
science and analytics, industrial digital twins, machine learning, diagnosis and maintenance tools, etc.
The mathematical core of the web platform ARGOS will rely on the software developed within the ERC CoG
AROMA-CFD project by valorising open source software libraries ITHACA and RBniCS. Different demos will be developed,
for example in bioengineering, structural mechanics, and industrial shape optimisation in fluid dynamics.
ARGOS wants to fulfil the demand of a Reduced Order Modelling Offline-Online tool, exploitable thanks to the creation of a
computational interface, handling and analysing a parametric problem in a very intuitive way. ARGOS is a computational
web server hosting several web applications, some with a general purpose and some for very specific problems: users can
access directly through the web browser, using their available device, choose the application they need and finally use it to
tackle the problem of interest. Thanks to the web application, users do not have to install any package by themselves on
their machine. Any device having an internet connection can access ARGOS and run a web computing application. The real
time response, due to the model reduction algorithms, combined with the ease of use of ARGOS, matches the industrial
demand of intuitive and immediate tools. Within this black-box framework, the final user is not required to have any specific
and technical knowledge about reduced order modelling. We thus envision that this approach could be adopted also in many
other fields directly related with applied sciences, for example in medicine and environmental studies. ARGOS will have a
vast audience of companies and institutions, proposing a closer integration between design teams and research and
development teams. ARGOS could also be easily connected with emerging technologies related with data assimilation, data
science and analytics, industrial digital twins, machine learning, diagnosis and maintenance tools, etc.
The mathematical core of the web platform ARGOS will rely on the software developed within the ERC CoG
AROMA-CFD project by valorising open source software libraries ITHACA and RBniCS. Different demos will be developed,
for example in bioengineering, structural mechanics, and industrial shape optimisation in fluid dynamics.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101069319 |
| Start date: | 01-07-2022 |
| End date: | 31-12-2023 |
| Total budget - Public funding: | - 150 000,00 Euro |
Cordis data
Original description
The Proof of Concept “Advanced Reduced order modellinG: Online computational web server for complex parametric Systems”ARGOS wants to fulfil the demand of a Reduced Order Modelling Offline-Online tool, exploitable thanks to the creation of a
computational interface, handling and analysing a parametric problem in a very intuitive way. ARGOS is a computational
web server hosting several web applications, some with a general purpose and some for very specific problems: users can
access directly through the web browser, using their available device, choose the application they need and finally use it to
tackle the problem of interest. Thanks to the web application, users do not have to install any package by themselves on
their machine. Any device having an internet connection can access ARGOS and run a web computing application. The real
time response, due to the model reduction algorithms, combined with the ease of use of ARGOS, matches the industrial
demand of intuitive and immediate tools. Within this black-box framework, the final user is not required to have any specific
and technical knowledge about reduced order modelling. We thus envision that this approach could be adopted also in many
other fields directly related with applied sciences, for example in medicine and environmental studies. ARGOS will have a
vast audience of companies and institutions, proposing a closer integration between design teams and research and
development teams. ARGOS could also be easily connected with emerging technologies related with data assimilation, data
science and analytics, industrial digital twins, machine learning, diagnosis and maintenance tools, etc.
The mathematical core of the web platform ARGOS will rely on the software developed within the ERC CoG
AROMA-CFD project by valorising open source software libraries ITHACA and RBniCS. Different demos will be developed,
for example in bioengineering, structural mechanics, and industrial shape optimisation in fluid dynamics.
Status
SIGNEDCall topic
ERC-2022-POC1Update Date
09-02-2023
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