Characterization and modeling of diffusion process for mass transport through the Tournemire argillites (Aveyron, France)

Argillites are one of the geological formations studied by IRSN for their confining properties for isolation of radioactive wastes. One of the main objectives is the study of water transport through rocks with very low water content and very low hydraulic conductivity by modeling of natural tracer profiles. This paper presents the protocol developed for and applied to the acquisition of data for chloride content in interstitial water of the Toarcian argillites at the Tournemire site (Southern France). This protocol is based on laboratory diffusion experiments and on modeling. Experimental data obtained during the transient and steady-state parts of diffusion experiments enable, respectively, the assessment of the diffusion coefficient and the determination of Cl concentration in pore water. Using this protocol, profiles with depth for both of these data sets have been acquired along the geological sequence. Taking into account the present knowledge of the geological and hydrogeological history of the Tournemire massif, a conceptual model granting the main role for mass transport to diffusion has been proposed. According to this conceptual model, a one-dimensional numerical model was built for simulating the mass transport of chloride through the sedimentary column, over 53 Ma. The good agreement between experimental data and calculated values for both diffusion coefficients and concentrations of chloride confirms that diffusion is likely the main process for mass transport in the massif. This model was also tested with the deuterium content of interstitial water, applying variable concentrations at the aquifer system boundaries for reflecting the thermal dependency of isotopic composition in precipitation. These simulations also reveal the likely important role of heterogeneities, such as fractures, in the variability of tracer concentrations with regards to a simple diffusion profile.     

Design and Implementation of an Agent Home Scheme Strategy for Prefetch-Based DSM Systems

In recent years, cluster computing has been widely investigated and there is no doubt that it can provide a cost-effective computing infrastructure by aggregating computational power, communication, and storage resources. Moreover, it is also considered to be a very attractive platform for low-cost supercomputing. Distributed shared memory (DSM) systems utilize the physical memory of each computing node interconnected in a private network to form a global virtual shared memory. Since this global shared memory is distributed among the computing nodes, accessing the data located in remote computing nodes is an absolute necessity. However, this action will result in significant remote memory access latencies which are major sources of overhead in DSM systems. For these reasons, in order to increase overall system performance and decrease this overhead, a number of strategies have been devised. Prefetching is one such approach which can reduce latencies, although it always increases the workload in the home nodes. In this paper, we propose a scheme named Agent Home Scheme. Its most noticeable feature, when compared to other schemes, is that the agent home distributes the workloads of each computing nodes when sending data. By doing this, we can reduce not only the workload of the home nodes by balancing the workload for each node, but also the waiting time. Experimental results show that the proposed method can obtain about 20% higher performance than the original JIAJIA, about 18% more than History Prefetching Strategy (HPS), and about 10% higher than Effective Prefetch Strategy (EPS).     

The Impact of Speculative Execution on SMT Processors

By executing two or more threads concurrently, Simultaneous MultiThreading (SMT) architectures are able to exploit both Instruction-Level Parallelism (ILP) and Thread-Level Parallelism (TLP) from the increased number of in-flight instructions that are fetched from multiple threads. However, due to incorrect control speculations, a significant number of these in-flight instructions are discarded from the pipelines of SMT processors (which is a direct consequence of these pipelines getting wider and deeper). Although increasing the accuracy of branch predictors may reduce the number of instructions so discarded from the pipelines, the prediction accuracy cannot be easily scaled up since aggressive branch prediction schemes strongly depend on the particular predictability inherently to the application programs. In this paper, we present an efficient thread scheduling mechanism for SMT processors, called SAFE-T (Speculation-Aware Front-End Throttling): it is easy to implement and allows an SMT processor to selectively perform speculative execution of threads according to the confidence level on branch predictions, hence preventing wrong-path instructions from being fetched. SAFE-T provides an average reduction of 57.9% in the number of discarded instructions and improves the instructions per cycle (IPC) performance by 14.7% on average over the ICOUNT policy across the multi-programmed workloads we simulate. This paper is an extended version of the paper, “Speculation Control for Simultaneous Multithreading,” which appeared in the Proceedings of the 18th International Parallel and Distributed Processing Symposium, Santa Fe, New Mexico, April 2004.     

Near optimal interval observers bundle for uncertain bioreactors

In this paper we design an interval observer for the estimation of unmeasured variables of uncertain bioreactors. The observer is based on a bounded error observer, as proposed in [Lemesle, V., & Gouzé, J.-L. (2005). Hybrid bounded error observers for uncertain bioreactor models. Bioprocess and Biosystems Engineering, 27, 311-318], that makes use of a loose approximation of the bacterial kinetics. We first show how to generate guaranteed upper and lower bounds on the state, provided that known intervals for the initial condition and the uncertainties are available. These so-called framers depend on a tuning gain. They can be run in parallel and the envelope provides the best estimate. An optimality criterion is introduced leading to the definition of an optimal observer. We show that this criterion provides directly a gain set containing the best framers. The method is applied to the estimation of the total biomass of an industrial wastewater treatment plant, demonstrating its efficiency.     

Safe design of high-performance embedded systems in an MDE framework

In this paper, we use the UML MARTE profile to model high-performance embedded systems (HPES) in the GASPARD2 framework. We address the design correctness issue on the UML model by using the formal validation tools associated with synchronous languages, i.e., the SIGALI model checker, etc. This modeling and validation approach benefits from the advantages of UML as a standard, and from the number of validation tools built around synchronous languages. In our context, model transformations act as a bridge between UML and the chosen validation technologies. They are implemented according to a model-driven engineering approach. The modeling and validation are illustrated using the multimedia functionality of a new-generation cellular phone.     

Cytocompatibility of titanium metal injection molding with various anodic oxidation post-treatments

Metal injection molding (MIM) is a near net shape manufacturing method that allows for the production of components of small to moderate size and complex shape. MIM is a cost-effective and flexible manufacturing technique that provides a large innovative potential over existing methods for the industry of implantable devices. Commercially pure titanium (CP-Ti) samples were machined to the same shape as a composite feedstock with titanium and polyoxymethylene, and these metals were injected, debinded and sintered to assess comparative biological properties. Moreover, we treated MIM-Ti parts with BIOCOAT®, BIODIZE® and BIOCER®, three different anodic oxidation techniques that treat titanium using acid, alkaline and anion enriched electrolytes, respectively. Cytocompatibility as well as morphological and chemical features of surfaces was comparatively assessed on each sample, and the results revealed that MIM-Ti compared to CP-Ti demonstrated a specific surface topography with a higher roughness. MIM-Ti and BIOCER® samples significantly enhanced cell proliferation, cell adhesion and cell differentiation compared to CP-Ti. Interestingly, in the anodization post-treatment established in this study, we demonstrated the ability to improve osseointegration through anionic modification treatment. The excellent biological response we observed with MIM parts using the injection molding process represents a promising manufacturing method for the future implantable devices in direct contact with bones.     

Genetic analysis of geraniol metabolism during fermentation

Geraniol produced by grape is the main precursor of terpenols which play a key role in the floral aroma of white wines. We investigated the fate of geraniol during wine fermentation by Saccharomyces cerevisiae. The volatile compounds produced during fermentation of a medium enriched with geraniol were extracted by Stir-bar sorptive extraction and analysed by GC–MS. We were able to detect and quantify geranyl acetate but also citronellyl- and neryl-acetate. The presence of these compounds partly explains the disparition of geraniol. The amounts of terpenyl esters are strain dependant. We demonstrated both by gene overexpression and gene-deletion the involvement of ATF1 enzyme but not ATF2 in the acetylation of terpenols. The affinity of ATF1 enzyme for several terpenols and for isoamyl alcohol was compared. We also demonstrated that OYE2 is the enzyme involved in geraniol to citronellol reduction. Fermenting strain deleted from OYE2 gene produces far less citronellol than wild type strain. Moreover lab strain over-expressing OYE2 allows 87% geraniol to citronellol reduction in bioconversion experiment compared to about 50% conversion with control strain.     

A new identification method of viscoelastic behavior: Application to the generalized Maxwell model

This paper focuses on the generalized Maxwell model (GMM) identification. The formulation of the transfer function of the GMM is defined, as well as its asymptotes. To compare identification methods of the parameters of the GMM, a test transfer function and two quality indicators are defined. Then, three graphical methods are described, the enclosing curve method, the CRONE method and an original one. But the results of graphical methods are not good enough. Thus, two optimization recursive processes are described to improve the results of graphical methods. The first one is based on an unconstrained non-linear optimization algorithm and the second one is original and allows constraining identified parameters. This new process uses the asymptotes of the modulus and the phase of the transfer function of the GMM. The result of the graphical method optimized with the new process is very accurate and fast.