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July 25, 2019 | Listening to the flows inside pipes to monitor structural health

List canalisations cndA passive non-destructive testing (NDT) method was developed for the inspection of pipes. The sound of the flows inside of the pipes is processed by a purpose-developed tomography algorithm that reconstructs the pipes’ thickness profile.

The active methods used in structural health monitoring (SHM) consist of emitting a wave, and then studying the modifications to the wave when it encounters a defect. Passive methods are different in that they do not require the emission of a wave prior to taking measurements. Researchers at List, a CEA Tech institute, recently developed a method to measure and analyze the waves generated by the flow of a fluid inside a pipe to detect any defects in the pipe.

The solution developed is based on pairs of fiber Bragg grating rings that serve as elastic wave receivers, and offer the advantage of being more robust under extreme conditions (high temperature, radiation, etc.) than the piezoelectric sensors conventionally employed in active SHM methods. The information from the pairs of sensors is processed by a purpose-developed tomography algorithm to reconstruct the pipe-wall thickness profile. The resulting profile can be used to detect, identify, locate, and measure any defects present.

The method was tested and validated on artificial defects and its performance was compared to that of a traditional active method. It was a success! List, that earned the Carnot seal in 2006, is now partnering with French electric utility EDF to investigate how the method can be used in industrial environments. Other applications, such as in aeronautics, are also possible.

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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.

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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.

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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

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