Effect of long-term service on the precipitates in P92 steel

The precipitates in P92 steel after long-term service in an ultra-supercritical unit were investigated by field-emission scanning electron microscopy and transmission electron microscopy and were found to mainly consist of M23 C6 carbides,Laves phase,and MX carbonitrides.No Z-phase was observed.M23 C6 carbides and Laves phase were found not only on prior austenite grain boundaries,martensite lath boundaries,and subgrain boundaries but also in lath interiors,where two types of MX carbonitrides—Nb-rich and V-rich particles—were also observed but the "winged" complexes were hardly found.Each kind of precipitate within the martensite laths exhibited multifarious morphologies,suggesting that a morphological change of precipitates occurred during long-term service.The M23 C6 carbides and Laves phase coarsened substantially,and the latter grew faster than the former.However,MX carbonitrides exhibited a relatively low coarsening rate.The effect of the evolution of the precipitate phases on the creep rupture strength of P92 steel was discussed.

Interfacial microstructure evolution of 12Cr1MoV/TP347H dissimilar steel welded joints during aging

The interfacial microstructure evolution of 12Cr1MoV/TP347H dissimilar steel welded joints with a nickel-based filler metal during aging was studied in detail to elucidate the mechanism of premature failures of this kind of joints.The results showed that not only a band of granular Cr_(23)C_(6)carbides were formed along the fusion boundary in the ferritic steel during aging,but also a large number of granular or plate-like Cr_(23)C_(6)carbides,which have a cube-cube orientation relationship with the matrix,were also precipitated on the weld metal side of the fu-sion boundary,making this zone be etched more easily than the other zone and become a dark etched band.Stacking faults were found in some Cr_(23)C_(6)carbides.In the as-welded state,deformation twins were observed in the weld metal with a fully austenitic structure.The peak micro-hardness was shifted from the ferritic steel side to the weld metal side of the fusion boundary after aging and the peak value increased signific-antly.Based on the experimental results,a mechanism of premature failures of the joints was proposed.

Knowledge extraction from Chinese wiki encyclopedias

The vision of the Semantic Web is to build a 'Web of data' that enables machines to understand the semantics of information on the Web.The Linked Open Data(LOD) project encourages people and organizations to publish various open data sets as Resource Description Framework(RDF) on the Web,which promotes the development of the Semantic Web.Among various LOD datasets,DBpedia has proved a successful structured knowledge base,and has become the central interlinking-hub of the Web of data in English.However,in the Chinese language,there is little linked data published and linked to DBpedia.This hinders the structured knowledge sharing of both Chinese and cross-lingual resources.This paper deals with an approach for building a large-scale Chinese structured knowledge base from Chinese wiki resources,including Hudong and Baidu Baike.The proposed approach first builds an ontology based on the wiki category system and infoboxes,and then extracts instances from wiki articles.Using Hudong as our source,our approach builds an ontology containing 19 542 concepts and 2381 properties.802 593 instances are extracted and described using the concepts and properties in the extracted ontology and 62 679 of them are linked to equivalent instances in DBpedia.As from Baidu Baike,our approach builds an ontology containing 299 concepts,37 object properties,and 5590 data type properties.1 319 703 instances are extracted from Baidu Baike,and 84 343 of them are linked to instances in DBpedia.We provide RDF dumps and SPARQL endpoint to access the established Chinese knowledge bases.The knowledge bases built using our approach can be used not only in Chinese linked data building,but also in many useful applications of large-scale knowledge bases,such as question-answering and semantic search.

RiMOM-IM： A Novel Iterative Framework for Instance Matching

Instance matching, which aims at discovering the correspondences of instances between knowledge bases, is a fundamental issue for the ontological data sharing and integration in Semantic Web. Although considerable instance matching approaches have already been proposed, how to ensure both high accuracy and efficiency is still a big challenge when dealing with large-scale knowledge bases. This paper proposes an iterative framework, RiMOM-IM （RiMOM-Instance Matching）. The key idea behind this framework is to fully utilize the distinctive and available matching information to improve the efficiency and control the error propagation. We participated in the 2013 and 2014 competition of Ontology Alignment Evaluation Initiative （OAEI）, and our system was ranked the first. Furthermore, the experiments on previous OAEI datasets also show that our system performs the best.