Improving creep strength of the fine-grained heat-affected zone of novel 9Cr martensitic heat-resistant steel via modified thermo-mechanical treatment

The infamous type Ⅳ failure within the fine-grained heat-affected zone (FGHAZ) in G115 steel weldments seriously threatens the safe operation of ultra-supercritical (USC) power plants.In this work,the traditional thermo-mechanical treatment was modified via the replacement of hot-rolling with cold rolling,i.e.,normalizing,cold rolling,and tempering (NCT),which was developed to improve the creep strength of the FGHAZ in G115 steel weldments.The NCT treatment effectively promoted the dissolution of preformed M_(23)C_(6)particles and relieved the boundary segregation of C and Cr during welding thermal cycling,which accelerated the dispersed reprecipitation of M_(23)C_(6) particles within the fresh reaustenitized grains during post-weld heat treatment.In addition,the precipitation of Cu-rich phases and MX particles was promoted evidently due to the deformation-induced dislocations.As a result,the interacting actions between precipitates,dislocations,and boundaries during creep were reinforced considerably.Following this strategy,the creep rupture life of the FGHAZ in G115 steel weldments can be prolonged by 18.6%,which can further push the application of G115 steel in USC power plants.

Bedding parallel fractures in fine-grained sedimentary rocks:Recognition,formation mechanisms,and prediction using well log

Core,thin section,conventional and image logs are used to provide insights into distribution of fractures in fine grained sedimentary rocks of Permian Lucaogou Formation in Jimusar Sag.Bedding parallel fractures are common in fine grained sedimentary rocks which are characterized by layered structures.Core and thin section analysis reveal that fractures in Lucaogou Formation include tectonic inclined fracture,bedding parallel fracture,and abnormal high pressure fracture.Bedding parallel fractures are abundant,but only minor amounts of them remain open,and most of them are partly to fully sealed by carbonate minerals(calcite)and bitumen.Bedding parallel fractures result in a rapid decrease in resistivity,and they are recognized on image logs to extend along bedding planes and have discontinuous surfaces due to partly-fully filled resistive carbonate minerals as well as late stage dissolution.A comprehensive interpretation of distribution of bedding parallel fractures is performed with green line,red line,yellow line and blue line representing bedding planes,induced fractures,resistive fractures,and open(bedding and inclined)fractures,respectively.The strike of bedding parallel fractures is coinciding with bedding planes.Bedding parallel fractures are closely associated with the amounts of bedding planes,and high density of bedding planes favor the formation of bedding parallel fractures.Alternating dark and bright layers have the most abundant bedding parallel fractures on the image logs,and the bedding parallel fractures are always associated with low resistivity zones.The results above may help optimize sweet spots in fine grained sedimentary rocks,and improve future fracturing design and optimize well spacing.

Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset,Methodology and Evaluation

Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

Performance Enhancement of XML Parsing Using Regression and Parallelism

The Extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications.With the existing Document Object Model(DOM)based parsing,the performance degrades due to sequential processing and large memory requirements,thereby requiring an efficient XML parser to mitigate these issues.In this paper,we propose a Parallel XML Tree Generator(PXTG)algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework(RXPF)that analyzes and predicts performance through profiling,regression,and code generation for efficient parsing.The PXTG algorithm is based on dividing the XML file into n parts and producing n trees in parallel.The profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including StAX,SAX,DOM,JDOM,and PXTG on different cores by using multiple file sizes.The regression phase produces the prediction model,based on which the final code for efficient parsing of XML files is produced through the code generation phase.The RXPF framework has shown a significant improvement in performance varying from 9.54%to 32.34%over other existing models used for parsing XML files.

Experimental Study on the Effect of Fine-Grained Soil Content on the Freezing Strength of Aeolian Sand-Cement Interface

In cold regions,understanding the freezing strength of the interface between soil and structure is crucial for designing frost-resistant foundations.To investigate how the content of cement powder in aeolian sand affects this strength,we conducted direct shear tests under various conditions such as different fine-grained soil content,normal stress,and initial moisture content of the soil.By analyzing parameters like soil properties,and volume of ice content,and using the Mohr-Coulomb strength theory to define interface strength,we aimed to indirectly measure the cementation strength of the interface.Our findings revealed that as the particle content increased,the interface stress-strain curves became noticeably stiffer.We also observed a positive linear relationship between freezing strength and silt content,while the initial moisture content of the soil did not significantly impact the strengthening effect of fine-grained soil on freezing strength.Moreover,we discovered that as the powder content increased,the force binding the ice to the interface decreased,while the friction angle at the interface increased.However,the cohesion force at the interface remained relatively unchanged.Overall,our analysis suggests that the increase in freezing strength due to fine-grained soil content is primarily due to the heightened friction between aeolian sand and the interface.

从功能和认知的视角看Parallelism

从功能解释语言现象是人类认知和交际的普通模式。普通模式的建立是作为对语言进行功能解释的前提 ,也是人类认知世界和传递信息的哲学抽象。我们可以从功能和认知的视角 。

“Parallelism”与“排比”辨异

英语 Parallelism与汉语“排比”长期以来被误为等值术语 ;1。其实 ,两者之间虽有相似之处 ,但明显的区别仍然不可忽视 ,本文拟从四个方面对此加以对比论证。一、英语 Parallelism既是修辞术语 ,又是语法术语 ;而汉语“排比”只是修辞术语。二、英语“平行项”既可以是三个或三个以上 ,也可以是两个 ;而汉语“排比项”只可以是三个或三个以上。三、英语 Parallelism既可以是并列结构 ,也可以是从属结构 ;而汉语“排比”却只能是并列结构。四、较之英语 Parallelism ,汉语“排比”更加讲究形式上的对称。

Parallelism、antithesis与排比、对偶

Parallelism与antithesis是英语中广泛使用的修辞手段。Parallelism常译为平行式平行结构 ,由两个或两个以上结构完全相同或非常类似的句子构成。并且句子或句子之间的联系由于语义上的一致和句法关系的相关得到加强。Antithesis意味相关、相对 ,是把相反的词、短语或从句用平行或对称的结构排列起来 ,以表达相反或相对的意思 ,使两层意思互相对照 ,达到加强语气的目的。Parallelism及antithesis与汉语的排比、对偶有相似之处 。

英语Parallelism修辞格

英语Parallelism译成汉语时分别为“对偶”、“排比”或“排偶” ,因为它在文中起的修辞作用不同 ,有时它相当于对偶的修辞方法 ,有时它又相当排比修辞方法。它的格式除在句法结构上相对外 ,有时也在音律、韵律、语法。

论Parallelism的形式及功能

本文从形式及功能两个方面对英语ｐａｒａｌｌｅｌｉｓｍ进行了较为深入的探讨，并将其定义为：将同一词语并列重复，或将结构相同或相似、语义相关（相同、相似、互补或相反）、语气一致的词、词组、分句、句子或段落并列使用的一种修辞手段，同时指出，Ｐａｒａｌｌｅｌｉｓｍ不仅具有突出语义、增强韵律的功能，而且具有很强的语篇功能。

浅析“Parallelism”在布什就职演说中的运用

在对修辞与演讲关系简要分析的基础上,文章通过对小布什总统连任就职演说辞中排偶的大量运用的分析,揭示修辞在演讲中的巨大作用和排偶的运用给演讲者带来的恢弘气势、清晰的说理与强大的感召力,以增强读者对演说辞的深刻理解。

Parallelism的结构特征及其语义特点

文章从修辞和语法的角度,探讨了Parallelism的定义,并与汉语中的"排比"修辞格进行了比较。与此同时,文章还通过大量的例句,分析了Parallelism的结构特征及其所具有的语义特点。

功能对等理论指导下Parallelism的翻译——以The Road Less Traveled为例

Parallelism在英语中具有修辞和语法双重功能。在英汉翻译对比研究中,学术界关注较多的是它与中文排比的构成差异及修辞功用,对它的语法功能研究较少。实践证明,英汉排比结构的对等转译不仅有助于保留源文本的语言特色和功能,还可以帮助译文读者更好地把握原文结构,明了行文思路。Parallelism的修辞功能和语法功能同等重要,都应引起译界的足够重视。本文在功能对等理论的指导下,以美国作家M·斯科特·派克的心理学著作——The Road Less Traveled中的排比句的翻译为例,探讨如何通过直译法、转译法、分句法、逆序法、增词法和减词法来提高原文读者和译文读者反应的相似性,实现功能对等目的。

Parallelism和排比的话语特征赏析

英语Parallelism和汉语排比是相类似的修辞手段,二者有相同或相似的话语特征,即结构匀称,衔接流畅,层层排叠,使人读后得到强烈的感染,获得韵律美和语势美的感受。拟以散文、诗歌、演说辞为实例,分析语篇结构和话语语势这两种修辞格的话语特征。

Parallelism修辞格探微

Parallelism意为“平行结构”,即将结构相同或相似、意义并重、语气一致的语言成分并行排列的一种修辞手法。它与汉语“排比”颇为相似,但不等同。从平行项数来看,它可以有两项,也可以有三项或三项以上,通常以二项或三项并行最为常见;就构成格式而言,它有单层次格式和多层次格式两种。