Bibliometric analysis of the evolution of biochar research trends and scientific production

Clean Technologies and Environmental Policy - Biochar has caught great attention over the last decade, yielding a large number of publications in a broad range of disciplines. This scientometric...     

Single chamber Solid Oxide Fuel Cells selective electrodes: A real chance with brownmillerite-based nanocomposites

In this contribution brownmillerite-based nanocomposite cathode for Single-Chamber Solid Oxide Fuel Cells is developed. These cells can be very attractive especially for small and cheap devices because of the absence of seals. The efficiency of SC-SOFCs is strictly connected to the selectivity of anode and cathode, the bottleneck for this technology. The development of a cathode inert in fuel oxidation is particularly challenging. Our strategy is to start from a catalytically un-active support (CFA = Ca₂FeAl_0.95Mg_0.05O₅) and induce the formation of iron oxide based nanoparticles, expected to activate oxygen. Symmetric (CFA + FeO_x/CGO/CFA + FeO_x) and complete cells (CFA + FeO_x/CGO/Ni-CGO) are studied in air and methane/oxygen 2:1 mixture. The Area Specific Resistance of CFA + FeO_x is less than 1/3 that of CFA. The high selectivity allows to reach an efficiency of 25%; power still needs to be increased but we demonstrated the possibility to develop selective low cost electrodes. The effect of air, methane/oxygen exposure and the heat treatments were carefully investigated.     

Structure, properties, and thermal stability of nanocrystallite Fe-Ti-N soft magnetic films

We deposited Fe-Ti-N magnetic films with a high sputtering power of 7 W/cm/sup 2/. When the composition of the films was in the range of Fe-Ti(3.9 at.%)-N(8.8 at.%) to Fe-Ti(3.3 at.%)-N(13.5 at.%), the films were composed of /spl alpha/' and Ti/sub 2/N precipitates. With the addition of nitrogen, 4/spl pi/M/sub s/ became higher than that of pure iron, reaching a maximum of 23.8 kG. At the same time, H/sub c/ was reduced to a minimum of 1.12 Oe. The best films can meet the needs of the recording head in dual-element giant magnetoresistive/inductive heads, yielding high storage density (10 Gb/in/sup 2/). The incorporation of N in /spl alpha/-Fe brought about the /spl alpha/' phase with its higher saturation magnetization. Ti additions inhibited the equilibrium decomposition /spl alpha/'/spl rarr//spl alpha/+/spl gamma/'. Because H/sub C//sup D//spl prop/D/sup 6/, where D is average grain diameter, grain size control is very important. The nitrogen induces severe distortion of the /spl alpha/' lattice, which can cause the grains to break into pieces and reduce the grain size. High sputtering power also led to the formation of fine grains, with diameter in the order of 14 nm. Probably Ti/sub 2/N is preferentially precipitated on the grain boundary, pinning the grain boundary and stabilizing the grain size during high-temperature heat treatment. The temperature limit for stability of the structure and its associated low coercivity was not less than 520/spl deg/C.     

A Lattice Approach to Image Segmentation

After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded. It is used as an input to a central theorem of the paper (Theorem 8), that identifies segmentation with the connections that are based on connective criteria. Just as connections, the segmentations can then be regrouped by suprema and infima. The generality of the theorem makes it valid for functions from any space to any other one. Two propositions make precise the AND and OR combinations of connective criteria. The soundness of the approach is demonstrated by listing a series of segmentation techniques. One considers first the cases when the segmentation under study does not involve initial seeds. Various modes of regularity are discussed, which all derive from Lipschitz functions. A second category of examples involves the presence of seeds around which the partition of the space is organized. An overall proposition shows that these examples are a matter for the central theorem. Watershed and jump connection based segmentations illustrate this type of situation. The third and last category of examples deals with cases when the segmentation occurs in an indirect space, such as an histogram, and is then projected back on the actual space under study. The relationships between filtering and segmentation are then investigated. A theoretical chapter introduces and studies the two notions of a pulse opening and of a connected operator. The conditions under which a family of pulse openings can yield a connected filter are clarified. The ability of segmentations to generate pyramids, or hierarchies, is analyzed. A distinction is made between weak hierarchies where the partitions increase when going up in the pyramid, and the strong hierarchies where the various levels are structured as semi-groups, and particularly as granulometric semi-groups. The last section is based on one example, and goes back over the controversy about “lattice” versus “functional” optimization. The problem is now tackled via a case of colour segmentation, where the saturation serves as a cursor between luminance and hue. The emphasis is put on the difficulty of grouping the various necessary optimizations into a single one.     

应用API 581对输气站场进行定量风险评价

目前专门针对输气站场的风险评价方法还不多，现有的手段也只是根据国家法律法规得出定性的评价结果，然后按照评价结果对照得出整改方案。为此，对输气站场的定量风险评价工作提出了一套新方法，得到了定量的和更加客观的风险排序，为管道站场的完整性管理工作提供了有力的支持；并以陕京输气管道榆林压气站为例，应用美国石油学会标准API 581（基于风险检测的基本源文件）对站内设施进行了风险评价，计算了站内设备和管线的失效后果、失效概率，得到了定量风险值，进而分析了风险值产生差异的原因。最后，针对我国输气管道风险评估工作提出了看法和建议。     

基于实际井眼轨迹的抽油杆柱API设计方法

目前的抽油杆柱设计方法大都基于设计井眼轨迹或经验公式，因此设计的抽油杆柱与井眼的匹配性并没有达到最优，结果可能影响了抽油杆柱的受力特性和寿命。概述了目前现有的抽油杆柱设计方法，提出了基于实际井眼轨迹的抽油杆柱API设计方法，即考虑到在三维空间中井下粘滞阻力及动载的影响，利用微单元分析方法计算出轴向载荷与轴向应力，然后在此基础上进行杆柱组合设计，并给出了设计流程。以江苏油田永21-3井为例，对几种设计方法的设计结果进行了对比分析，结果表明，江苏油田目前采用的抽油杆柱设计方法包含了人为经验因素，并不是最优的杆柱设计结果，有待进一步改进。     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis.

This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision-based algorithm is used to extract relevant three-dimensional (3-D) features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3-D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3-D information previously extracted, an accurate distance computation is performed.