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September 16, 2020 | A decision-assistance tool for crisis management

expressif 250ExpressIF®, the artificial reasoning platform developed by CEA List, a CEA Tech institute, has been augmented with a spatial data processing module to assist in decision making. The technology is currently being used to manage wildfires, but it also offers potential in other emergency management situations.

Symbolic artificial intelligence algorithms, which simulate complex reasoning and apply it to heterogeneous and uncertain data, can be extremely useful decision-assistance tools in crisis management scenarios. As part of a project backed by the European Regional Development Fund (ERDF) and France's Occitanie regional CLE fund, CEA List, a member of the Carnot Network, partnered with CGX, a company specializing in geographical information systems, to bring the reasoning capabilities of ExpressIF® to wildfire management professionals.

New spatial data processing capabilities were implemented to more effectively assess a potential on-site response and help determine the best course of action. In the first module, the "rules" expressed in structured language (close to natural language) were used not only to model the spatial reasoning to be applied, but also to process both detailed geographic data and weather forecasts to predict the fire's development over time and space. The second module used the temporal reasoning capabilities of ExpressIF® to monitor the temperatures of assets like vehicles and people on the ground, assess the associated risks, and raise alerts in the event of danger.

The human-machine interface (HMI) developed by CEA Tech Occitanie provides a dedicated module for inputting data (locations, events, means, resources, etc.) and displays the results directly on a map in a web app. Further developments to track the rules applied are underway, with the goal of delivering an automated explanation of the results.

The unique spatial and temporal reasoning capabilities of ExpressIF®, combined with its ability to intelligibly process uncertain data, will be extended and applied to other critical scenarios, setting the platform on a course to become a leading AI technology for crisis management.

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August 18, 2020 | Predicting induced radioactivity in medical accelerators

radioact 250CEA-List, a CEA Tech institute, has mapped the parts that present induced radioactivity in medical particle accelerators, information that is vital to dismantling the equipment safely.

Increasing numbers of the particle accelerators used in radiation therapy are reaching the ends of their lifespans, which raises the issue of dismantling the machines and managing radioactive waste. Particle accelerators contain parts with complex geometries, some of which become radioactive due to their activation with accelerated beams and exposure to the secondary particles generated by interaction with radioactive material. The first challenge is knowing exactly which parts are radioactive. The types and amounts of radioactivity must also be determined. ANDRA, France's national radioactive waste management agency, turned to CEA-List for help dealing with this new problem.

CEA-List lab LNHB (Laboratoire National Henri Becquerel) utilized geometric data from the Varian radiotherapy accelerator at the DOSEO platform and leveraged CEA-List's expertise in Monte Carlo simulations to model the functioning of a medical accelerator and its consequences on the parts that make up the machine. The researchers were able to map the induced radioactivity in the different parts and classify them by the type of radiation emitted (beta or gamma rays).

ANDRA will use the data to ensure that radioactive waste produced from the dismantling of medical accelerators is managed properly. This groundbreaking research positions CEA-List as a source the international community can turn to for an accurate and reliable methodology for the management of radioactive waste from medical accelerators.

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August 4, 2020 | Papyrus keeps an eye on digital systems

papyrus 150Of the many cybersecurity tools developed for industrial software users by CEA List, a CEA Tech institute, the open-source Papyrus platform is a key technology. Not only can Papyrus be used to guide the development of software that protects users’ personal data, but it can also model risk analyses.

In a world where digital technology is ubiquitous, the demand for powerful data protection and cybersecurity solutions will only increase. Therefore, the quality of data protection and cybersecurity specifications will become a decisive factor in the development of complex systems. CEA List, a member of the Carnot Network, has leveraged its expertise in model-driven engineering, through its Papyrus software development platform, for several projects.

CEA List researchers have developed a methodology and the associated tools to ensure that personal data protection regulations (GDPR) are factored in from the initial system design phases. The tool developed by CEA List in research for the EU PDP4E project allows legal obligations to be expressed as functional requirements and technical constraints, so that a system architecture can then be built in a way that guarantees that these obligations are met. The next step will be to test the tools on partner companies’ use cases to ensure that they are robust.

In research being conducted for the ModSecAéro project in partnership with the French Directorate General for Armament, CEA List researchers are developing a methodological framework to assess the resistance of embedded aeronautics systems to cyberattacks. The tools, which leverage the Papyrus platform, will be capable of modeling risk analyses utilizing a methodology that is compliant with the industry’s standards. With the tools being developed, critical components and the associated threats will be identified, the possible attacks on these vulnerable elements will be determined, and countermeasures will be implemented. These functions will be integrated into a model that will improve the analysis over time. A partnership between software developer Trialing and CEA List is expected to lead to the commercialization of the tools.

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July 6, 2020 | NDT: Monitoring dangerous pipework for the Fukushima nuclear power plant decommissioning project

CND fukushimaGuided-wave propagation simulation methods are particularly well-suited to the remote monitoring of difficult-to-access pipe elbow joints. This type of simulation will ultimately be integrated into CIVA, the non-destructive testing (NDT) software suite developed by List, a CEA Tech institute.

To decommission the Fukushima nuclear power plant, the water in the reactor must be emptied through a network of pipes designed specifically for this purpose. The pipes will be in contact with a substantial flow of contaminated water, augmenting the risk of corrosion at certain points along the network. Top Japanese researchers (from Tohoku, Gunma, and Kobe Universities) work with List on the PYRAMID project, funded in part by France's national research agency ANR, to develop NDT methods to monitor corrosion remotely.

Right-angled elbow joints are the most likely to suffer from accelerated corrosion. These welded joints are notoriously difficult to inspect due to the combined effects of the corrosion, weld bumps, the "elbow" shape, and the fluid flowing through the pipes. Because of the difficult access, the probes used to monitor the welds cannot be moved once they are in place. The researchers chose electromagnetic acoustic transducers (EMAT), which, because no other substances are required to couple the probe and the pipe, are well-suited to this type of scenario.

The guided waves emitted by the probes and the propagation of the waves through the elbow joints are simulated using 3D finite-element models developed by List. The simulator is coupled with a fast analytical model to predict the waves' behavior in the straight sections of piping located before and after the elbow joint. The resulting hybrid method, called SAFE-FEM, has already been integrated into the CIVA suite. The additional developments completed for Fukushima will ultimately be added to CIVA.

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July 2, 2020 | BA-Healthcare starts production of its CLEAR-M ventilator monitoring system, designed by List

ClearMOn March 13, at the height of the Covid-19 pandemic, CEA Tech institute List initiated the CLEAR project to develop a solution to the shortage of ventilators.

CLEAR (CEA List Emergency Assistance for Respiration) produced results in early April, in the form of the CLEAR-M ventilator monitoring system designed to enhance emergency and transport ventilators. The high-performance, affordable CLEAR-M prototype was tested in the ventilator weaning ward at the Raymond Poincaré Hospital in Garches on Covid-19 patients in recovery but still on ventilators. CLEAR-M was also implemented at the Nord Essonne Hospitals Emergency Department in Orsay.

The performance of the CLEAR-M system was validated, and is garnering growing interest from both manufacturers and hospitals. Based in Rennes, France, BA-Healthcare, a subsidiary of BA-Systèmes, is currently completing the first test manufacturing run of the system, which will equip emergency and transport ventilators so that they can be used to treat Covid-19 patients. “We are proud to be contributing in any way we can to everyone’s efforts to fight Covid-19. Our people are committed to the project, and we are excited to launch full-scale production,” said BA Healthcare General Manager Samuel Pinault.

List has received other expressions of interest from within the Greater Paris hospital network and from multiple manufacturers. CLEAR-M prototypes have been tested at the Raymond Poincaré Hospital in Garches, by Toulouse EMS, and Brest University Medical Center; the early results are encouraging. The system, which will first need to be approved by France’s drug and medical device regulator, could help improve the care given to patients in future epidemics as well as during transport.