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June 25, 2019 | Two CEA Tech demonstrators in Novares’ Nova Car 2

cea list novacar 2Novares unveiled its Nova Car 2 demo car to manufacturers on June 25. The car incorporates around fifteen patented innovations, two of which were developed by CEA Tech institutes.

Novares, an automotive supplier that specializes in plastic parts, recently unveiled its latest demo car, Nova Car 2. Designed for automotive-industry stakeholders, the car showcases the latest innovations to make cars more interactive and user-friendly. This most recent incarnation of the demo car packs in fifteen patented innovations, two of which were developed by CEA Tech institutes.

 

 

CEAList bouton rotatif novacar 2
The rotating piezoelectric button with haptic feedback developed by CEA List

The first, developed by List, is a rotating piezoelectric button with haptic feedback integrated into the center console. The reprogrammable button can be used to move from one system to another (radio, air conditioning, etc.), giving the driver relevant and personalized haptic feedback on the system being controlled.

The second, developed by Leti, is found at the core of a door locking and unlocking system on the door handle and rear panel. Based on thin-layer piezoelectric sensors with a purpose-built design, the system is much more sensitive and reliable than what is currently available on the market. This innovation resulted in a CEA spinoff, WORMS, that will be founded by September and that will have exclusive rights to commercialize the technology.

Novares will kick off its Nova Car 2 world tour in July and also plans to pursue its partnership with all three CEA Tech institutes. Leti, Liten, and List are already working on new and innovative proof-of-concept prototypes for Nova Car 3.

 

 

 

 

 

19 juin 2019 | Le programme Accompagnement Smart Industrie pour les PMI

smart industrie 250Dans le cadre de sa stratégie « Smart Industrie », la Région Île-de-France accompagne 300 PMI franciliennes dans leurs projets de transformation. 

Le programme Accompagnement Smart Industrie est l’opportunité pour les PMI d’améliorer leur performance industrielle globale et leur compétitivité en jouant sur les facteurs humains, technologiques, organisationnels et sur les ruptures marché.

Les experts du CEA List, labellisé institut Carnot, accompagnent les PMI dans une démarche pragmatique, adaptée à leurs enjeux, pour agir sur les leviers de compétitivité du référentiel Industrie du Futur. De cette façon, les PMI ont accès à l’ensemble des opportunités d’innovation proposées par le Digital Innovation Hub de DIGIHALL.

Pour plus d'informations : https://www.accompagnement-smart-industrie.com/

 

 

June 17, 2019 | Electromagnetism used to study the mechanical properties of steel

List acier cnd 250Researchers at List, a CEA Tech institute, have developed simulation models and tools that leverage electromagnetism to characterize steel. These models and tools will be integrated into the CIVA platform so that they can be used to develop industrial non-destructive testing processes.

The mechanical properties of steel are closely related to the steel’s microstructure. The same is true of steel’s magnetic behavior. Modifications to the microstructure can affect the material’s mechanical and magnetic properties.

So, studying steel’s electromagnetic behavior can provide indirect insights into its mechanical properties—but only if other factors that cause variations in the magnetic properties of the metals that make up the steel are taken into account.

List, that earned the Carnot seal in 2006, developed a simulation model of an industrial non-destructive testing process that uses macroscopic measurements of steel’s electromagnetic signature. The idea is to take into account the related sources of variability and, especially, the types of probes used and the material’s heterogeneity. The method leverages an original semi-analytical formulation of the problem and non-linear models to rapidly arrive at a robust solution.

These tools will ultimately be integrated into the CIVA platform so that they can be transferred to industrial users. Whether it is to monitor structural health or control quality during manufacturing, inspecting the microstructure of steel is a major challenge in the nuclear, automotive, and other industries.

Read article at http://www.cea-tech.fr/

 

 

June 6, 2019 | Automating toxic chemical identification

CEA List Identification automatisee de toxiques chimiques 250List1, a CEA Tech institute, partnered with the French National Center for Scientific Research (CNRS) to develop an algorithm to automatically identify toxic chemicals and explosives in real time. The research was part of a French government CBRN-E2 counterterrorism program.

The Police Nationale, one of France’s national police forces, turned to List, a CEA Tech institute, to develop a software application to automatically identify toxic chemicals and explosives in real time. The software leverages a support vector machine (SVM), a sophisticated tool used in artificial intelligence techniques just like neural networks.

Unlike neural networks, however, SVMs are optimal classifiers. In other words, they can determine with a high degree of confidence whether or not a chemical compound is present in a mix.

Any toxic compounds present have to be identified one after the other. So, the researchers developed a smart technique to preselect areas of interest in the FT-IR3 spectra of compounds included in a database of threats. These areas of interest are then inspected within the spectrum of an unknown sample. The information provided to the SVM is pre-calculated and simplified using conventional signal analysis methods.

Another original aspect of the software is that the SVM learns from theoretical spectra, eliminating the need for it to learn from huge databases. A tool developed by List can automatically generate, from just a few real spectra, theoretical spectra of chemical mixes from the thousands of molecules.

Blind tests revealed excellent selectivity and sensitivity (to within 4% or 5% for chemical mixtures in powder form). These methods, called Peak Correlation Classification (PCC), were patented by List.


[1] List earned the prestigious Institut Carnot seal in 2006 (Institut Carnot TN@UPSaclay)
[2] Chemical, biological, radioactive, nuclear, and explosives
[3] FT-IR, or Fourier Transform Infrared Spectroscopy

Read article at http://www.cea-tech.fr/

 

 

May 23, 2019 | Medical scans: reducing doses without compromising on diagnostic quality

scan doseo 250List*, a CEA Tech institute, developed a mathematical model to improve medical imaging protocols so that the lowest possible dose of ionizing radiation can be used without negatively affecting the reliability of the diagnosis.

The level of exposure to radiation during medical scans has been on the rise for a number of years, creating increased health risks for patients. Researchers at List, a CEA Tech institute, have developed new indicators to keep the dose of radiation delivered to a patient during a scan to a strict minimum. The first is used to estimate the dose received by the patient as reliably as possible; the second evaluates the quality of the images produced.

The researchers began by developing and validating a model of the scanner at the DOSEO platform so that they could evaluate a breakdown of the distribution of the dose of radiation received by the patient's body during a scan depending on the equipment's characteristics (geometry, movement of the radiation head, etc.). A Monte Carlo method is used to accurately simulate the trajectory and interaction of particles in matter.

Next, a mathematical observer model was used on a torso phantom filled with water and inserts of various shapes and sizes to assess the image quality. A detectability indicator that reflects the capacity to detect or discern a lesion was used for the assessment. The results were compared to an analysis completed by radiologists assisting with the project so that the model could be validated. The model has already been used to correlate an artificial lesion detectability rate with the dose of radiation received by the patient.

Ultimately these advances could provide radiologists with medical imaging methods that successfully limit radiation doses without compromising patient diagnoses.

*List earned the prestigious Institut Carnot seal in 2006 (Institut Carnot TN@UPSaclay).

Read article at http://www.cea-tech.fr/