检索结果-南通市图书馆

A reweighted damped singular spectrum analysis method for robust seismic noise suppression

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Petroleum Science 2024年第3期21卷 1671-1682页

作者： wei-Lin Huang Yan-Xin Zhou yang Zhou wei-Jie liu Ji-dong Li State Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing2249China SINOPEC Petroleum Exploration and Production Research Institute Beijing102206China SINOPEC Geophysical Research Institute Nanjing211103jiangsuChina

(Multichannel)Singular spectrum analysis is considered as one of the most effective methods for seismic incoherent noise *** utilizes the low-rank feature of seismic signal and regards the noise suppression as a low-rank reconstruction ***,in some cases the seismic geophones receive some erratic disturbances and the amplitudes are dramatically larger than other *** presence of this kind of noise,called erratic noise,makes singular spectrum analysis(SSA)reconstruction unstable and has undesirable effects on the final *** robustify the low-rank reconstruction of seismic data by a reweighted damped SSA(RD-SSA)*** incorporates the damped SSA,an improved version of SSA,into a reweighted *** damping operator is used to weaken the artificial disturbance introduced by the low-rank projection of both erratic and random *** central idea of the RD-SSA method is to iteratively approximate the observed data with the quadratic norm for the first iteration and the Tukeys bisquare norm for the rest *** RD-SSA method can suppress seismic incoherent noise and keep the reconstruction process robust to the erratic *** feasibility of RD-SSA is validated via both synthetic and field data examples.

关键词： Singular spectrum analysis Damping operator Seismic erratic noise Seismic signal processing Robust low-rank reconstruction

Realizing the excellent oxidation resistance of an environmental barrier coating through aluminum surface modification

在线全文

学校读者我要写书评

暂无评论

Journal of Advanced Ceramics 2024年第7期13卷 976-986页

作者： Lin dong Wen-Qi yang Lin Chen Guan-Jun yang Chang-jiu Li State Key Laboratory for Mechanical Behavior of Materials School of Materials Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China Xi’an Aerospace Engine Company Limited in China Aerospace Science and Technology Corporation Xi’an 710065China

The lifetime of Si-based environmental barrier coatings(EBCs)is constrained by thermally grown SiO_(2)oxidelayer(SiO_(2)-TGO),which can cause premature cracking and *** address this issue,a new approach for surfacemodification using aluminum is *** oxidation performance was examined in a 50 vol%H_(2)O-50 vol%O_(2)environment at 1350℃for up to 300 *** results indicate that a dense ytterbium aluminum garnet(YbAG)layer wasformed after modification,decreasing the porosity by 80%.Due to the elimination of fast diffusion channels and the lowoxygen permeability of YbAG,aluminum modification significantly reduced the growth rate of SiO_(2)-TGO by nearly twoorders of ***,its thickness decreased by more than 70%after 300 h of exposure.A diffusioncontrolled oxidation mechanism indicates that the modified dense surface is equivalent to an initial SiO_(2)layer with a specificthickness,causing a shift in the oxidation time and increasing the oxidation *** research provides valuableinsights for designing Si-based EBC with improved lifetimes.

关键词： environmental barrier coating(EBC) oxidation modification diffusion cracking

Intelligent representation method of image flatness for cold rolled strip

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Iron and Steel Research International 2024年第5期31卷 1177-1195页

作者： yang-huan Xu dong-cheng Wang Hong-min liu Bo-wei Duan National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao066004HebeiChina National Key Laboratory of Metal Forming Technology and Heavy Equipment China National Heavy Machinery Research Institute Co.Ltd.Xi’an710018ShaanxiChina State Key Laboratory of Metastable Materials Science and Technology Yanshan UniversityQinhuangdao066004HebeiChina

Real flatness images are the bases for flatness detection based on machine vision of cold rolled *** characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model with deep semantic segmentation networks is *** interference areas in the real flatness image can be eliminated by the SLD model,and valid information can be *** this basis,the concept of image flatness is proposed for the first *** image flatness representation(IFAR)model is established on the basis of an autoencoder with a new *** optimal structure of the bottleneck layer is 16×16×4,and the IFAR model exhibits a good representation ***,interpretability analysis of the representation factors is carried out,and the difference and physical meaning of the representation factors for image flatness with different categories are *** flatness with new defect morphologies(bilateral quarter waves and large middle waves)that are not present in the original dataset are generated by modifying the representation factors of the no wave ***,the SLD and IFAR models are used to detect and represent all the real flatness images on the test *** average processing time for a single image is 11.42 ms,which is suitable for industrial *** research results provide effective methods and ideas for intelligent flatness detection technology based on machine vision.

关键词： Cold rolled strip Image flatness Location detection Representation learning Bottleneck layer

Rational design of superior catalysts from topological semimetals with nontrivial energy window

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Rare Metals 2024年第5期43卷 1956-1964页

作者： Min Zhao Li-rong Wang wei liu Ming-Hang Li Ying liu Xue-Fang Dai Guo-dong liu Xiao-Ming Zhang Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Materials Science and Engineering ManufacturingHebei University of TechnologyTianjin 300130China

Materials featuring topological energy bands and nontrivial surface states hold significant promise in unlocking unprecedented opportunities for innovating electrocatalytic ***,it remains a challenge to realize superior topological catalysts which can carry both high catalytic activity and excellent catalytic ***,we propose that a family of Ni-based binary materials hosting fantasying topological conjunct-nodalpoint state and a large nontrivial energy window(NEWD)represents an ideal choice for such superior topological catalysts in hydrogen evolution *** presence of conjunct-nodal-points ensures long Fermi arcs on the surface,thereby enabling an extremely high catalytic *** NEWD plays a crucial role in stabilizing the high catalytic activity against external perturbations,such as strain and electron/hole *** roles for conjunctnodal-points and NEWD are substantiated by the observable weakening of catalytic performance during topological phase transitions,which result in the removal of the conjunct-nodal-points,NEWD and their corresponding long Fermi *** work unveils a hidden mechanism and opens a feasible route for developing superior quantum catalysts from novel topology point of view.

关键词： First-principles modeling Topological semimetal Nontrivial surface states Hydrogen evolution reaction

Research on Pulsar Time Steered Atomic Time Algorithm Based on DPLL

在线全文

学校读者我要写书评

暂无评论

Research in Astronomy and Astrophysics 2024年第3期24卷 237-248页

作者： Ze-Hao Zheng yang liu Dan Shen Fan Feng jiu-Long liu Yue-Xin Ma Xiang-wei Zhu School of Electronic and Communication Engineering Sun Yat-sen UniversityShenzhen 518107China School of Aeronautics and Astronautics Sun Yat-sen UniversityShenzhen 518107China School of Systems Science and Engineering Sun Yat-sen UniversityGuangzhou 510275China

In today’s society,there is a wide demand for high-precision and high-stability time service in the fields of electric power,communication,transportation and *** present,the time standard in various countries is mainly based on atomic clocks,but the frequency drift of atomic clocks will affect the long-term stability *** with atomic clocks,millisecond pulsars have better long-term stability and can complement with the excellent short-term stability of atomic *** order to improve the long-term stability of the atomic timescale,and then improve the timing accuracy,this paper proposes an algorithm for steering the atomic clock ensemble(ACE)by ensemble pulsar time(EPT)based on digital phase locked loop(DPLL).First,the ACE and EPT are generated by the ALGOS algorithm,then the ACE is steered by EPT based on DPLL to calibrate the long-term frequency drift of the atomic clock,so that the generated steered atomic time follows both the short-term stability characteristics of ACE and the long-term stability characteristics of EPT,and finally,the steered atomic time is used to calibrate the local cesium *** experimental results show that the long-term stability of atomic time after steering is improved by 2 orders of magnitude compared with that before steering,and the daily drift of a local cesium clock after calibration is less than 9.47 ns in 3 yr,3 orders of magnitude higher than that before calibration on accuracy.

关键词： (stars) pulsars general-time-methods data analysis-instabilities

Impact of Carbon Chain Structures in the Backbone on the Flexibility of Modified Polyarylene Sulfide Resins: Molecular Dynamics Simulations and Mesoscopic Analysis

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Polymer Science 2024年第4期42卷 544-557页

作者： Chi Zhang rong.liu Jing-Yuan liu Wen-wei Jiang Key Laboratory of Fine Chemical Engineering and Functional Materials School of Chemical EngineeringSichuan UniversityChengdu610065China

In the domain of high-performance engineering polymers, the enhancement of mechanical flexibility in poly(phenylene sulfide) (PPS) resins has long posed a significant challenge. A novel molecular structure, designated as PP-He-IS, wherein imide rings and an aliphatic hexylene chain are covalently incorporated into the PPS backbone to enhance its flexibility, is introduced in this study. Molecular dynamics (MD) simulations are employed to systematically explore the effects of diversifying the backbone chain structures by substituting phenyl units with alkyl chains of varying lengths, referred to as PP-A-IS where “A” signifies the distinct intermediary alkyl chain configurations. Computational analyses reveal a discernable decrement in the glass transition temperature (Tg) and elastic modulus, counterbalanced by an increment in yield strength as the alkyl chain length is extended. Notably, the PP-He-IS variant is shown to exhibit superior yield strength while simultaneously maintaining reduced elastic modulus and Tg values, positioning it as an advantageous candidate for flexible PPS applications. Mesoscopic analyses further indicate that structures such as PP-He-IS, PP-Pe-IS, and PP-Bu-IS manifest remarkable flexibility, attributable to the presence of freely rotatable carbon-carbon single bonds. Experimental validation confirms that a melting temperature of 504 K which is lower than that of conventional PPS, and lower crystallinity are exhibited by PP-He-IS, thereby affording enhanced processability without compromising inherent thermal stability. Novel insights into the strategic modification of PPS for mechanical flexibility are thus furnished by this study, which also accentuates the pivotal role played by molecular dynamics simulations in spearheading high-throughput investigations in polymer material modifications.

关键词： Molecular dynamics simulations Polyarylene Sulfide Main-chain modifications Flexibility Aliphatic hexylene chain

Pt nanodendrites with a PtIr alloy surface structure exhibit excellent stability toward acidic hydrogen evolution reaction

在线全文

学校读者我要写书评

暂无评论

Nano Research 2024年第6期17卷 4844-4849页

作者： Chang liu Zongnan wei Minna Cao rong Cao State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou 350002China University of Chinese Academy of Sciences Beijing 100049China Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou 350108China

The development of effective and stable electrocatalysts for the hydrogen evolution reaction(HER)in acidic electrolytes is a significant *** this work,homogeneous Pt nanodendrites(Pt NDs)with a PtIr shell were successfully synthesized by a two-step wet chemical *** open three-dimensional(3D)dendritic structure exhibited exceptional electrocatalytic characteristics,exposing as many active sites as ***,by alloying Ir with Pt on the surface,catalytic activity was greatly enhanced while ensuring extremely high *** surface-enriched platinum nanodendritic catalysts(Pt@PtIr NDs)outperformed the control samples and the commercial *** acidic HER test,Pt@PtIr NDs had a lower overpotential(22 mV)than Pt NDs(26 mV)and commercial Pt/C(31 mV)at 10 mA/cm^(2),and the activity of Pt@PtIr NDs remained consistent even after undergoing a continuous durability test for at least 168 h,which was much superior to the performance of commercial Pt/C(10 h)under identical test *** study revealed that the application of 3D Pt dendritic metal alloys may offer a chance for the development of enhanced electrocatalysts in acidic HER.

关键词： Pt nanodendrites iridium high stability hydrogen evolution reaction alloy

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Petroleum Science 2024年第4期21卷 2329-2344页

作者： jiu-Qiang yang Nian-Tian Lin Kai Zhang Yan Cui Chao Fu dong Zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

High-sensitivity formaldehyde gas sensor based on Ce-doped urchin-like SnO_(2) nanowires derived from calcination of Sn-MOFs

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Materials Science 2024年第1期18卷 29-43页

作者： wei Xiao wei yang Shantang liu Hubei Key Lab of Novel Reactor&Green Chemical Technology School of Chemistry and Environmental EngineeringWuhan Institute of TechnologyWuhan 430073China Hubei Key Laboratory of Wudang Local Chinese Medicine Research Department of ChemistrySchool of Pharmaceutical SciencesHubei University of MedicineShiyan 442000China

Metal-organic frameworks(MOFs)have attracted widespread attention due to their regular structures,multiple material centers,and various *** are always considered as one kind of ideal templates for developing highly sensitive and selective gas *** this study,the advantages of MOFs with the high specific surface area(71.9891 m^(2)·g^(-1))and uniform morphology were fully utilized,and urchin-like SnO_(2) nanowires were obtained by the hydrothermal method followed by the calcination using Sn-MOFs consisting of the ligand of C_(9)H_(6)O_(6)(H_(3)BTC)and Sn/Ce center ions as sacrificial *** unique urchin-like nanowire structure facilitated gas diffusion and adsorption,resulting in superior gas sensitivity.A series of Ce-doped SnO_(2) nanowires with different doping ratios were synthesized,and their gas sensing properties towards formaldehyde were *** resulted Ce-SnO_(2) was revealed to have high sensitivity(201.2 at 250℃),rapid response(4 s),long-term stability,and good repeatability for formaldehyde sensing,and the gas sensing mechanism of Ce-SnO_(2) exposed to formaldehyde was also systematically discussed.

关键词： Ce-SnO_(2) SnO_(2) gas sensor formaldehyde Sn-MOF