Benjamin Vincent

A MapReduce-based approach for shortest path problem in large-scale networks

The cloud computing allows to use virtually infinite resources, and seems to be a new promising opportunity to solve scientific computing problems. The MapReduce parallel programming model is a new framework favoring the design of algorithms for cloud computing. Such framework favors processing of problems across huge datasets using a large number of heterogeneous computers over the web. In this paper, we are interested in evaluating how the MapReduce framework can create an innovative way for solving operational research problems. We proposed a MapReduce-based approach for the shortest path problem in large-scale real-road networks. Such a problem is the cornerstone of any real-world routing problem including the dial-a-ride problem (DARP), the pickup and delivery problem (PDP) and its dynamic variants. Most of efficient methods dedicated to these routing problems have to use the shortest path algorithms to construct the distance matrix between each pair of nodes and it could be a time-consuming task on a large-scale network due to its size. We focus on the design of an efficient MapReduce-based approach since a classical shortest path algorithm is not suitable to accomplish efficiently such task. Our objective is not to guarantee the optimality but to provide high quality solutions in acceptable computational time. The proposed approach consists in partitioning the original graph into a set of subgraphs, then solving the shortest path on each subgraph in a parallel way to obtain a solution for the original graph. An iterative improvement procedure is introduced to improve the solution. It is benchmarked on a graph modeling French road networks extracted from OpenStreetMap. The results of the experiment show that such approach achieves significant gain of computational time.

HTS Magnets: Opportunities and Issues for SMES

SMES (superconducting magnetic energy storage) devices are an attractive solution for pulsed current sources. However, the specific stored energy is moderate and has to be improved. High temperature superconductor (HTS) materials offer opportunities in terms of current carrying capabilities as well as mechanical strength. We report the optimization of solenoids with regards to mechanical stress and current density constraints. 20 kJ/kg requires current densities above 150 MA/m2 and stresses of about 400 MPa for energies in the range of 5 to 50 MJ. The optimization code makes possible the study of the influence of different parameters such as the maximum allowable magnetic field. A method is proposed to discriminate space of solution. The best configuration is achieved keeping in mind the peculiar properties of HTS tape (which impact protection of SMES), and the specifications of the application. Parallel to these theoretical approaches, we are developing the magnet technology by first realizing small magnets we test under very high fields (up to 18 T) to apply the large mechanical stresses.

HTS Coil Test Facility in a Large Bore 20 T Resistive Magnet at LNCMI

The high temperature superconductor (HTS) coil development, especially in the interest of high field insert coil, requires characterizations of a prototype coil in high magnetic field. Our test probe fits into the bore of Ø 170 mm 20 T dc magnet, and the sample space Ø 130 mm allows test coils with ~Ø 110 mm and 140 mm height. A fast data acquisition method at sampling period of 0.1 ms was developed for coil quench test program, and a working principle of the method is demonstrated for a small test coil. To accommodate high current required in tests such as Ic and hoop stress tests, the new current leads were manufactured with an optimal current measured in the range of 600 ~ 700 A, which was sufficient for the envisaged coil tests. For short duration, the current lead could carry more than 1000 A without any influence of overheating in short sample Ic test. A demonstration of short sample Ic test is also presented.

Quench Propagation in YBCO Pancake: Experimental and Computational Results

High-temperature superconductors are promising materials for future applications such as high field magnets thanks to their ability to carry high current densities. Nevertheless, their protection still remains a key issue mainly due to the slow velocity of quench propagation. To understand the quench behavior of a YBCO coil, a simulation code has been developed using the CASTEM-CEA finite element software. Simulations can be performed considering constant current and magnetic field. Results of those simulations will be displayed and a way for improving the protection by adding a stabilizer will be discussed. Two well instrumented YBCO coils were fabricated in order to obtain experimental data on quench propagation in pancake configuration. Their design and some measurements are reported in this paper along with another experiment on a double pancake made by and tested at CNRS Grenoble. Finally, we compare the numerical and experimental results and discuss the accuracy of our simulations.

Performance Tests of Prototype High-Field HTS Coils in Grenoble

Longitudinal and transverse quench propagation tests were performed at the Laboratoire National des Champs Magnetiques Intenses (LNCMI) high-field test facility on instrumented double pancake coils fabricated by CEA-Saclay using co-wound high-temperature superconductor (HTS) tapes. Energy deposited on an embedded heater initiated a quench and its subsequent propagations. Following the resulting thermomechanical analysis, a conductor design with stacked HTS tapes co-wound with stabilizers was conceived. A ten-turn demonstrator racetrack coil has been fabricated from the stacked HTS conductor with an aim to investigate the operation margin of an HTS coil in a background magnetic field misaligned from the coil axis as expected for the operating condition of an accelerator magnet insert. A test setup with a high current capacity up to 3 kA and angular variability that utilizes a room-temperature 376-mm-bore 10-T resistive magnet at LNCMI in Grenoble has been built. The performances and operation margin of the racetrack coil were investigated.

Mechanically Reinforced Bi-2212 Strand

Bi-2212 offers a lot of opportunities for very high fields at low temperature. The current density is large under high fields, particularly with recent enhanced results. The Bi-2212 conductor may be a round strand: a very favorable shape to wind and to make high-current Rutherford cables required for protection. There is no satisfying high-current cable with YBCO. One drawback of Bi-2212 is their low mechanical properties. Large fields and current densities indeed induce high mechanical stresses. To improve the mechanical properties of Bi-2212 strands, Nexans has proposed to reinforce it with a metal sheath wrapped around using their process of shaping and welding. The sheath is wrapped around the strand and laser welded, and the whole is drawn to a diameter of 0.9 mm. Several materials for the sheath were studied to determine their resistance to thermal treatment of Bi-2212 and their mechanical properties after treatment. We choose Inconel 601. A method of perforating the sheath has been developed to enable the oxygenation during the heat treatment. A 6 + 1 conductor has also been produced around an Inconel core and inserted in a tube. The 6 + 1 reinforced conductor was then drawn to a diameter of 2.7 mm. The Ic measurements at 4 K show that our mechanical reinforcement does not significantly lower the transport capacities. They therefore validate the method and the heat treatment.

Industrial Optimal Operation Planning with Financial and Ecological Objectives.

As energy transition is fundamental to have a chance to fight climate change, every stakeholder concerned by energy should be able to get a better knowledge of the consequences of these actions. However, it could be very complex to understand energy problematics without being an expert. This article focuses on giving the possibility to an energy intensive consumer of a district to make decisions about its energy planning while taking into account its specific operating constraints. A practical case has been studied in a heat recovery project to help the experiments planning of a research laboratory according to the thermal needs of the district. At first, the energy planning only aims to reduce its electricity consumption bill. In a second time, we consider re-using the thermal power from processes cooling. Then, two energy planning were realised: reducing district CO2 emissions and reducing district supply cost. Finally, trade-offs between these two goals have been studied. The work is based on mixed-integer linear optimization models (MILP) gathered into a Python library to provide a modular decisions tool for energy stakeholders.

Status of the 43-T Hybrid Magnet of LNCMI-Grenoble

Based on a close collaboration between CEA and CNRS, a new hybrid magnet is being built at LNCMI-Grenoble. By combining a resistive insert, which is made of Bitter and polyhelix coils, with a large bore superconducting outsert, an overall continuous magnetic field of at least 43 T will be produced in a 34-mm warm bore aperture. The superconducting coil relies on the novel development of a Nb-Ti/Cu Rutherford cable-on-conduit conductor cooled down to 1.8 K by a bath of superfluid helium at atmospheric pressure and will produce a nominal magnetic field of 8.5 T in a 1.1-m cold bore diameter. After thorough reviews of the hybrid magnet design, which have anticipated possible upgrades of the maximum magnetic field produced, the project has entered in its production phase. The status and the next steps of the project will be reviewed highlighting the remaining technical challenges.

Support Vector machine and Monte Carlo simulation for robust optimization of industrial processes

Goods-producing industries continuously search to improve the quality of final products. The main approach is to identify a correlation between the process settings and the quality of the final product. In this work, a three steps robust approach is presented to improve an industrial process. The first step consists in using a Support Vector machines Regression (SVR) method to build a model of the considered process. It is based on the historic process data defined by an output (a criterion on the product quality) and multiple inputs (various production line settings). Then an optimization step based on an iterative descent method is done on the obtained model to identify interesting settings. Finally the set of settings found is validated by a Monte Carlo simulation approach used to simulate and test settings close to the one found on the optimization step. The proposed regression and optimization methods are compared to existing methods from the literature on a fluidized bed combustion boiler in the context of paper industry. The experiments confirm the efficiency of our approach.

Shortest Path Challenging Problem

The shortest path problem is a well know routing problem which received a considerable amount of attention for several decades. This problem is the cornerstone of any real-world routing problem including the VRP or the Hub Location. The majority of efficient methods dedicated to these problems consist in computing first the matric of shortest path between nodes. Furthermore, there has been a renaissance of interest in the shortest path problem in recent year for use in various transportation engineering applications. This paper relates to the conception of efficient routing algorithms tuned for mobility. More precisely, it is targeted to the field of pedestrian mobility in an urban environment. In a mobile environment, specific constraints as the treatment of wireless network traffic disturbances must be taken into account. The architecture that we tune for the project is based on an active monitoring system, which dynamically required new shortest path calculation using the exposed web service API. The web service is performed when a specific constraint appears or a new part of the path is required. Using of such architecture offers a new approach in spreading operational research algorithms and our contribution stands at the crossroads of optimization research community and the web service community expectations.