Numerical Meta-modelization based study of the propagation of ultrasonic waves in piping system with corroded area
The aim of the ANR project PYRAMID (http://www.agence-nationale-recherche.fr/Projet-ANR-17-CE08-0046) is to develop some technics of detection and quantification of the wall thinning due to flow accelerated corrosion in piping system. In the framework of this project involving French and Japanese laboratories, CEA LIST develops new numerical tools based on finite elements dedicated to the modelling of an ultrasonic guided wave diffracted by the corrosion in an elbow pipe. These solutions support the design of an inspection process based on electromagnetic-acoustic transduction (EMAT). To this end, the ability of CEA LIST to adapt meta-modeling tools of its physical models will be the key asset to allow intensive use of the simulation.
Post-doc: CNN neural network – managing data uncertainty in the learning database.
The aim is to develop algorithms able to take into account the uncertainty in the learning database of neural networks. The project fits into the context of the dynamic state estimation of liquid-liquid extraction and benefits of its knowledge-based simulator as well as industrial data. Indeed, the status of an industrial chemical process is accessible through operating parameters and available monitoring measures. However, the measures being inherently associated with uncertainty, it is necessary to make the data consistent with process knowledge. Therefore, the goal is to find the best data set of operational parameters (input of the knowledge-based simulator) to provide the model to estimate the real process state known through monitoring measures (output of the knowledge-based simulator). A convolutional neural network (CNN) is being developed in another postdoctoral project to solve the inverse problem to find the best input thanks to the measured output. A consistent set of operating parameters is going to be obtained and state of the process is going to be known during the dynamic regime of the liquid-liquid extraction process. This first step is to evaluate the impact of the uncertainty of operational parameters on the outputs of the knowledge-based model. This step will need to connect the knowledge-based model to URANIE, internal platform developed by CEA ISAS. This knowledge must be taken into account in the second part of the project. The uncertainty observed on the outputs should be taken into account in the learning loop to improve the estimation of the operational parameters by the CNN. The impact of these uncertainties on the CNN computed results must be assesed in order to trust the ability of the CNN to estimate the state of the process.
Through this project, we are at the heart of the thematic of digital simulation for the best control of complex systems.
Design of a safe and secure hypervisor in the context of a manycore architecture
The TSUNAMY project aims at thinking the design of future manycore chips in a collaborative hardware/software approach. It will investigate how crypto-processors can be incorporated into such a chip, turning it into a heterogeneous architecture, where scheduling, resource allocation, resource sharing, and resource isolation will be a concern.
The LaSTRE laboratory has designed Anaxagoros, a micro-kernel which ensures good properties in terms of safety and integration of mixed-criticality applications and is therefore well suited to the virtualization of operating systems. Making this virtualization software layer evolve in the context of the TSUNAMY project is the main goal of this post-doctoral proposal.
The first issue to address deals with the scalability of Anaxagoros on a manycore architecture. This system was designed with multicore scalability in mind : to help reach the highest level of parallelism in a lock-free fashion, innovative techniques were proposed to minimize the amount of synchronization points within the system. This is the first step, but scaling to manycore architectures brings new topics such as cache-coherency or non-uniform memory access that require to focus on data locality as well. The second challenge will be to incorporate genuine security features into Anaxagoros, e.g. regarding protection from covert channels, or confidentiality. The third and final challenge that will be addressed through interactions with the partners of the project is to devise techniques that could be implemented directly in hardware in order to ensure that even a breach in what is usually considered as trusted software will not allow an attacker to gain unprivileged data access or let information leak.
Optimal Multi Agent System management of smart heat grid using thermal storage
The aim of this work is a major contribution to a software framework based on coupling of Modelica/Jade environments that will allow to model, to simulate and to optimise the control of smart heat grid through dedicated thermal storage models development: interface specification to control the storages in the grid, simplified models design of heat grid’s most crucial components to be integrated in Agents (production, distribution/storage, consumption) and design of consumption and production forecast models in order to manage anticipation and improve the overall efficiency. The evaluation of performance is based on the test case build in Modelica simulation environment.
Fabrication and characterization of high thermal conductivity SiCf/SiC composites
SiCf/SiC ceramic matrix composites are foreseen candidates for structure materials and claddings in fast neutron reactor of 4th generation. However, their use may be limited because of their too low thermal conductivity in the operating conditions (< 10 W/mK).
SiCf/SiC ceramic matrix composites are now elaborated by chemical vapour infiltration (CVI). In order to improve their thermal conductivity (reduced porosity), it is planned to develop a hybrid elaboration process combining CVI and liquid routes.
The objective of this study is to determine the conditions of elaboration of a SiC matrix by liquid routes and then to characterize the thermo-mechanical behaviour of the hybrid composites, particularly in relation to CVI references.
Large-area processing and design of functional piezoelectric nanomaterials for flexible sensors and systems
CEA LETI develops innovative highly flexible strain sensors which exploit the piezoelectric properties of self-organized gallium nitride nanowires. The fabrication steps are basically: i) nanowire growth, ii) nanowire assembly, iii) encapsulation, iv) contacting. First demonstrators with small active area (1.5 cm²) have already been achieved using the Langmuir Blodgett (LB) technique for the assembly of nanowires. The present project is concerned with the scaling-up of the assembly process over large surface areas, as well as controlled patterning of nanowire assemblies in 1D and 2D by using an innovative CEA LITEN roll-to-roll technology called Boostream® which has the same functionalities as LB in its basic function.
The aim of the post doc is to develop a new building block for the Boostream® equipment enabling a controlled assembly of wires with a pre-defined design. The candidate will carry out studies to optimize the wire assembly, develop the process of film patterning and fabricate, integrate and characterize GaN nanowire piezoelectric transducers with dimensions of 15x15 cm².
More generally, this post doc will also provide the opportunity to develop a generic knowledge to manipulate micro or nano wires or fibers giving new solutions in various fields such as surface structuration, electronic skin, energy...
Internet of Things applications: Ultra Low power and adaptive analog-to-digital converters in advanced FD-SOI process
The post-doctoral project aims to study Ultra Low Power and Adaptive Analog-to-Digital Converter (ADC) over a wide operating range of microsystem from Internet of Things or sensor networks applications.
The ADC is one of the main blocks into System on Chip (SoC) because of its position between physical signal treatment (Front-End) and digital treatment (Digital Base Band). Its performances in terms of resolution or frequency ranges affect the overall performances of the SoC. A particular consideration will be carrying out on power consumption and some reconfigurability technics will be used to adapt its consumption to the contextual performances required. To reduce as possible the ADC consumption, advanced FDSOI process will be used.
Based on Ultra Low Power constraints, the post-doctorate student will study the literature and will propose, design and experimentally demonstrate a relevant topology to increase the power efficiency and the performances of ADC by using advanced FDSOI process.
Large scale visual recognition
This post-doc deals with detection and recognition of objects in images and video streams, on a large scale. This is a fundamental task that is the subject of active research in the world, including recent challenges in the evaluation campaigns. The "large scale" aspect refer to both large size databases (eg ten million images) and large number of concepts to recognize (eg 100-10000).The work will concern bothimage description and classification.
At the description level, state of the art techniques rely on local descriptors, aggregated according to dictionaries of "visual words" possibly constructed using Fisher kernels. It is nevertheless necessary to recode these signatures effectively in order to manage large databases. Regarding learning of visual concepts or objects, many algorithms use SVM (support vector machines) but other approaches are sometimes considered, such as those based on boosting or logistic regression.
The proposed position involves research and development of efficient algorithms to find visual entities in very large databases. Tracks are considered and should be discussed with the candidate selected based on prior knowledge and technical discussions.
Deployment of distributed consensus protocols on blockchains with Smart Contract
The aim is to implement various distributed consensus protocols on both public and private blockchain platforms supporting Smart Contracts technology. The techniques based on Proof-of-Stake and token management will be analyzed and their level of security will be evaluated in terms of energy consumption and quality of the distribution of the trust in the system. The techniques to verify the transactions of the blockchain Ethereum will be implemented, as well as other algorithms, lighter and that consume less energy, dedicated to "private" blockchains where users are authenticated. The platform Hyperledger will be used to test the various distributed consensus protocols. New algorithms will be proposed and the solutions will be deployed for applications in the field of the Internet of Things.
In situ analytical device based on the LIBS technique for the characterization of hard environment liquid media
The proposed research project aims at developing an in situ analytical device based on the LIBS technique for the characterization of hard environment liquid media such as high temperature melting materials or highly volatile liquid metals used for development of low carbon energy production. The project involves two CEA teams specialized in LIBS instrumentation, analytical developments and high temperature environments.
At high temperature, the molten metals have a high surface reactivity leading to processes of oxidation, slagging … Non-intrusive analysis of this surface by traditional LIBS tools leads to a non-representative results of the molten metal chemical composition. In this project, a new-patented concept based on a mechanical stirring coupled to the LIBS device is developed in order to have a renewable and stable surface of the liquid metal. The aim is to have an on-line representative composition of the metal during the treatment process. The developed demonstrator will be validated for the analysis of impurities (at ppmw ranges) in liquid silicon (T> 1450 °C) during the purification process and the crystallization one for photovoltaic applications. At the end of the project, recommendations for in-situ analysis of liquid sodium (used as cooling fluid in nuclear reactors) will be given.