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Effect of Atwood number on convergent Richtmyer-Meshkov instability

Acta Mechanica Sinica 2021年第3期37卷 434-446,I0002页

作者： Jinggang Tang fu Zhang Xisheng Luo Zhigang Zhai Department of Modem Mechanics University of Science and Technology of ChinaHefei 230026China Beijing Institute of Space Long March Vehicle Beijing 100076China

Developments of two-dimensional single-mode light/heavy interfaces driven by convergent shock waves are numerically investigated,focusing on the effect of the Atwood number on the Rayleigh-Taylor stabilization,the compressibility and the *** different test gases,including C〇2,Kr,R22,R12 and SF6,are considered with air as the ambient *** is clarified for the first time that the unperturbed interface begins to decelerate when the shock focuses at the convergence center,and the acceleration during the deceleration phase is proportional to the Atwood *** the first reshock,the interface moves outwards with a deceleration until it starts moving *** the initial interface is weakly disturbed,a more obvious amplitude reduction is observed for the case with a larger Atwood number before the reshock,which means that the Rayleigh-Taylor stabilization is *** assess the effect of the Atwood number on the compressibility and the nonlinearity,three models,including a linear incompressible model,a nonlinear incompressible model and a linear compressible model,are adopted to predict the amplitude growth before the *** results show that the nonlinearity is weak,and is almost not influenced by the Atwood number before the *** compressibility,however,greatly changes the amplitude *** the Atwood number increases,the compressibility plays a less significant role in the amplitude growth because a heavier gas is harder to be *** a gas with a larger specific heat ratio is also difficult to be compressed,the specific heat ratio plays a minor role to the compressibility relative to the Atwood *** the reshock,the amplitude grows linearly until the nonlinearity in the cases with large Atwood numbers is strong enough to reduce the amplitude growth rate.

关键词： Atwood number Convergent shock wave Richtmyer-Meshkov instability Rayleigh-Taylor effect Compressibility

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A large-scale clustering and 3D trajectory optimization approach for UAV swarms

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Science China(Information Sciences) 2021年第4期64卷 84-99页

作者： Ting MA Haibo ZHOU Bo QIAN Aiyong fu School of Electronic Science and Engineering Nanjing University

With the significant development of unmanned aerial vehicles(UAVs) technologies, a rapid increase on the use of UAV swarms in a wide range of civilian and emergency applications has been ***, how to efficiently network the large-scale UAVs and implement the swarms applications without infrastructure support in remote areas is challenging. In this paper, we investigate a hierarchal large-scale infrastructure-less UAV swarm scenario, where numerous UAVs surveil and collect data from the ground and a ferry UAV(Ferry UAV) is designated to carry back all their collected data. We can divide UAV swarms into different areas based on their geographic locations due to the wide range of surveillance. To improve data collection efficiency of Ferry UAV, we introduce a single super cluster head(Super-CH) UAV in each area which can be selected by the proposed modified k-means clustering algorithm with low latency. Then,we design an iterative approach to optimize the 3-dimensional(3D) trajectory of Ferry UAV such that its data collection mission completion time is minimized. Numerical results show the efficiency and low-latency of the proposed clustering algorithm, and the proposed 3D optimal trajectory design for large-scale UAV swarms data collection admits better performance than that with fixed altitude.

关键词： large-scale UAV swarms clustering super-CH selection 3D trajectory design

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Ore-forming Fluid Characteristics of the Saishitang Cu-polymetallic Deposit in Qinghai Province,China

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Acta Geologica Sinica(English Edition) 2015年第2期89卷 485-504页

作者： lai Jianqing JU Peijiao MAO Yin AN Jianghua WANG Xiongjun Key Laboratory of Metallogenic Prediction of Nonferrous Metals Ministry of EducationCentral South University School of Geosciences and Info-Physics Central South University

Saishitang Cu-polymetallic deposit is located in the southeast section of Late Paleozoic arcfoid in the southeastern margin of Qaidam platform. Accoring to the geological process of the deposit, four mineralization episodes were identified： melt/fluid coexisting period （O）, skarn period （A）, first sulfide period （B） and second sulfide period （C）, and 10 stages were finally subdivided. Three types of inclusions were classified in seven stages, namely crystal bearing inclusions （type I）, aqueous inclusions （type Ⅱ） and pure liquid inclusions （type Ⅲ）. Type I and Ⅱ inclusions were observed in stage O1, having homogenization temperature from 252 to 431℃, and salinities ranging from 24.3% to 48.0%. Type I inclusion was present in stage A1, having homogenization temperature from 506 to 548℃, and salinities ranging from 39.4% to 44.6%. In stage B1, type Ⅱ and Ⅲ inclusions were observed, with homogenization temperature concentrating between 300-400℃, and salinities from 0.4% to 4.3%. Type II inclusions were present in stage B2, with homogenization temperature varying from 403 to 550℃. In stage C1, type I and II inclusion commonly coexisted, and constituted a boiling inclusion group, having homogenization temperatures at 187-463℃, and salinities in a range of 29.4%-46.8% and 2.2%-11.0%. Type II and III inclusions were developed in stage C2, having homogenization temperature at 124-350℃, and salinities ranging between 1.6% and 15.4%. In stage C3, type Ⅱ and Ⅲ inclusions were presented, with a homogenization temperature range of 164-360℃, and salinities varying from 4.0% to 11.0%. The results of micro-thermal analysis show that fluids are characterized by high temperature and high salinity in stage O1 and A1, and experienced slight decrease in temperature and dramatic decrease in salinity in stage B1 and B2. In stage C1, the salinity of fluid increased greatly and a further decrease of temperature and salinity occurred in stage C2 and C3. Fluids boiled in stage C1. With calcul

关键词： fluid inclusions ore-forming fluid Laser Raman Spectroscopy Saishitang Qinghai Province

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Development of an ANN-based building energy model for information-poor buildings using transfer learning

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Building Simulation 2021年第1期14卷 89-101页

作者： Ao Li fu Xiao Cheng Fan Maomao Hu Department of Building Services Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Construction Management and Real Estate College of Civil EngineeringShenzhen UniversityShenzhenChina Oxford e-Research Centre Department of Engineering Science University of OxfordOxfordUK

Accurate building energy prediction is vital to develop optimal control strategies to enhance building energy efficiency and energy *** recent years,the data-driven approach based on machine learning algorithms has been widely adopted for building energy prediction due to the availability of massive data in building automation systems(BASs),which automatically collect and store real-time building operational *** new buildings and most existing buildings without installing advanced BASs,there is a lack of sufficient data to train data-driven predictive *** learning is a promising method to develop accurate and reliable data-driven building energy prediction models with limited training data by taking advantage of the rich data/knowledge obtained from other *** studies focused on the influences of source building datasets,pre-training data volume,and training data volume on the performance of the transfer learning *** present study aims to develop a transfer learning-based ANN model for one-hour ahead building energy prediction to fill this research *** 400 non-residential buildings’data from the open-source Building Genome Project are used to test the proposed *** analysis demonstrates that transfer learning can effectively improve the accuracy of BPNN-based building energy models for information-poor buildings with very limited training *** most influential building features which influence the effectiveness of transfer learning are found to be building usage and *** research outcomes can provide guidance for implementation of transfer learning,especially in selecting appropriate source buildings and datasets for developing accurate building energy prediction models.

关键词： building energy prediction data-driven approach transfer learning neural network information poor buildings

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CO2 hydrogenation to methanol over Cu/CeO2 and Cu/ZrO2 catalysts:Tuning methanol selectivity via metal-support interaction

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Journal of Energy Chemistry 2020年第1期29卷 22-30,I0002页

作者： Weiwei Wang Zhenping Qu Lixin Song Qiang fu Key Laboratory of Industrial Ecology and Environmental Engineering School of Environmental Science and TechnologyDalian University of TechnologyDalian 116024LiaoningChina State Key Lab of Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023LiaoningChina

Copper-based catalysts for CO2 hydrogenation to methanol are supported on ZrO2 and CeO2,*** results at 3.0 MPa and temperatures between 200 and 300°C reveal that Cu catalysts supported on ZrO2 and CeO2 exhibit better activity and selectivity than pure Cu catalyst due to Cu-support(ZrO2 and CeO2)*** the structural characterizations with in-situ diffuse reflectance infrared Fourier transform spectroscopy(in-situ DRIFTS),Cu/CeO2 shows the higher methanol selectivity due to the formation of main carbonates intermediates,which are closely related with the oxygen vacancies over Cu/*** contrast,bicarbonate and carboxyl species are observed on Cu/ZrO2,which originates from the hydroxyl groups presented on catalyst *** in CO2 adsorption intermediates results in the distinct methanol selectivity over the two catalysts.

关键词： CO_2 hydrogenation Methanol selectivity In-situ DRIFTS CeO_2 ZrO_2

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Regression model for civil aero-engine gas path parameter deviation based on deep domainadaptation with Res-BP neural network

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Chinese Journal of Aeronautics 2021年第1期34卷 79-90页

作者： Xingjie ZHOU Xuyun fu Minghang ZHAO Shisheng ZHONG Department of Mechanical Engineering Harbin Institute of Technology at WeihaiWeihai 264209China

The variations in gas path parameter deviations can fully reflect the healthy state of aeroengine gas path components and units;therefore,airlines usually take them as key parameters for monitoring the aero-engine gas path performance state and conducting fault *** the past,the airlines could not obtain deviations *** present,a data-driven method based on an aero-engine dataset with a large sample size can be utilized to obtain the ***,it is still difficult to utilize aero-engine datasets with small sample sizes to establish regression models for deviations based on deep neural *** obtain monitoring autonomy of each aero-engine model,it is crucial to transfer and reuse the relevant knowledge of deviation modelling learned from different aero-engine *** paper adopts the Residual-Back Propagation Neural Network(Res-BPNN)to deeply extract high-level features and stacks multi-layer Multi-Kernel Maximum Mean Discrepancy(MK-MMD)adaptation layers to map the extracted high-level features to the Reproduce Kernel Hilbert Space(RKHS)for discrepancy *** further reduce the distribution discrepancy of each aero-engine model,the method of maximizing domain-confusion loss based on an adversarial mechanism is introduced to make the features learned from different domains as close as possible,and then the learned features can be *** the above methods,domain-invariant features can be extracted,and the optimal adaptation effect can be ***,the effectiveness of the proposed method is verified by using cruise data from different civil aero-engine models and compared with other transfer learning algorithms.

关键词： Civil aero-engine Deep domain adaptation Domain confusion Neural networks Transfer learning

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Breviscapine alleviates hepatic injury and inhibits PKC-mRNA and its protein expression in brain-dead BA-Ma mini pigs

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Hepatobiliary & Pancreatic Diseases International 2007年第6期6卷 604-609页

作者： Zhang, Shui-Jun Song, Yan Zhai, Wen-Long Shi, Ji-Hua Feng, liu-Shun Zhao, Yong-fu Chen, Shi Zhengzhou Univ Affiliated Hosp 1 Dept Surg Zhengzhou 450052 Peoples R China Huazhong Univ Sci & Technol Tongi Med Coll Tongji Hosp Inst Transplantat Wuhan 430030 Peoples R China

BACKGROUND: Brain-dead donors are the main sources for organ transplantation, but many studies show that brain-death affects the organ's function after transplantation. This study was undertaken to investigate liver injury after brain-death in BA-Ma mini pigs and the protective effects of breviscapine on hepatic function and on PKC-alpha mRNA and its protein expression. METHODS: Fifteen BA-Ma mini pigs were equally divided into 3 groups at random: brain-dead (group B), breviscapine pretreated (group P), and control (group Q. The brain-dead model was established by increasing intracranial pressure in a modified, slow and intermittent way. At 3, 6, 12, 18 and 24 hours after the initial brain-death, the levels of serum AST, ALT, TNF-alpha, IL-1 beta, and IL-6 were determined. The changes in hepatic tissues were assessed, and the expression of PKC-alpha and PKC-alpha mRNA was detected by immunohistochemistry and RTPCR, respectively. RESULTS: The levels of AST and ALT in groups B and P began to increase 12 hours after brain-death, while the values in group P were lower than those in group B (P<0.05). The levels of IL-1 beta, IL-6, and TNF-alpha in groups B and P at 3, 6, 12 and 18 hours were lower than those in group B (P<0.05). At 6, 12 and 24 hours, the expressions of PKC-a mRNA and PKC-a protein in group P were lower than those in group B (P<0.05). The degree of injury to hepatic cells in group P was milder than that in group B. CONCLUSIONS: Breviscapine inhibits the degree of PKC-alpha mRNA transcription and its protein translation, decreases the release of inflammatory factors, and thus alleviates hepatic injury during brain-death.

关键词： breviscapine BA-Ma mini pigs brain-death protein kinase C

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Crystallization and heat transfer of CaO-SiO2-based slag for high-Mn-high-Al steel

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Journal of Iron and Steel Research International 2020年第7期27卷 788-795页

作者： Jie Yang Deng-fu Chen Miao-yong Zhu College of Material Science and Engineering Chongqing UniversityChongqing400044China School of Metallurgy Northeastern UniversityShenyang 110819LiaoningChina

The crystallization and heat transfer of CaO-SiO2-based slag for high-Mn-high-Al steel have been investigated by coupling composition evolution with heat transfer and non-isothermal *** was found that the concentrations of Al2O3 and MnO in the slag were determined by the relative contents of Al and Mn in molten *** temperature of the slag rose with the increase in Al2O3 content first and then fell due to the coupled effects of basicity and Al2O3,and a small amount of MnO cannot change this *** viscosity of slags led to less obvious characterizations of *** crystalline phase analysis suggested that MnO accumulation suppressed the formation of fluorite *** the Al2O3 content increased,the precipitation of cuspidine was replaced by the blocky gehlenite crystals,while the number and the size of nepheline and fluorite crystals both *** to the thickness and the crystallization structure of slags,the heat flux in the slag film first decreased and then increased with higher Al2O3 ***,a new type of CaO-SiO2-based mold slag with high basicity was applied in plant trial,and the change in composition and properties of mold slag was studied.

关键词： High-Mn-high-Al steel Mold slag Al2O3 accumulation Crystallization Heat transfer

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STUDY ON A NEW APPROACH OF CAVITATION EROSION TEST FOR NONMETALLIC MATERIALS

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Journal of Hydrodynamics 1999年第3期11卷 75-82页

作者： liu Zhi ping, Zhang Dong, Jin Tai lai China Institute of Water Resources and Hydropower Reserarch, Beijing 100038, P.R.China (Received Nov.9, 1998)

This paper deals with the reconstruction and innovation of an ordinary magnetostriction apparatus for cavitation erosion tests of non metallic materials. It aims at making testing specimen to be independent of amplitude amplifier rod, thus overcoming the difficulties of fixing tightly the non metallic specimen to the vibrating rod. Such approach makes the exposure area greatly increased and effectively mitigates the effect of non homogeneity of non metallic specimen on the testing results, thus extending the application of magnetostriction apparatus to carry out cavitation erosion tests to larger size of non metallic and non homogeneous materials. It will render a set of new innovative apparatus and recently developed method to conduct fast and simple cavitation erosion test in days to come. Simultaneously, several tests on non metallic materials have been made by means of such new apparatus, yielding satisfactory results and witnessing the availability of new methods.

关键词： cavitation erosion non metallic materials magnetostriction

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An improved de-interleaving algorithm of radar pulses based on SOFM with self-adaptive network topology

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Journal of Systems Engineering and Electronics 2020年第4期31卷 712-721页

作者： JIANG Wen fu Xiongjun CHANG Jiayun QIN Rui School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China

As a core part of the electronic warfare(EW) system,de-interleaving is used to separate interleaved radar signals. As interleaved radar pulses become more complex and denser, intelligent classification of radar signals has become very important. The self-organizing feature map(SOFM) is an excellent artificial neural network, which has huge advantages in intelligent classification of complex data. However, the de-interleaving process based on SOFM is faced with the problems that the initialization of the map size relies on prior information and the network topology cannot be adaptively adjusted. In this paper, an SOFM with self-adaptive network topology(SANT-SOFM) algorithm is proposed to solve the above problems. The SANT-SOFM algorithm first proposes an adaptive proliferation algorithm to adjust the map size, so that the initialization of the map size is no longer dependent on prior information but is gradually adjusted with the input data. Then,structural optimization algorithms are proposed to gradually optimize the topology of the SOFM network in the iterative process,constructing an optimal SANT. Finally, the optimized SOFM network is used for de-interleaving radar signals. Simulation results show that SANT-SOFM could get excellent performance in complex EW environments and the probability of getting the optimal map size is over 95% in the absence of priori information.

关键词： de-interleaving self-organizing feature map(SOFM) self-adaptive network topology(SANT)

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