Academic literature on the topic 'Three-layer fine paper'
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Journal articles on the topic "Three-layer fine paper"
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Gong, Quan Cheng, Jian Zhu, Shi Xing Jia, and Jing Wu. "Investigation on Fine Polishing Technique of Silicon Wafer." Advanced Materials Research 60-61 (January 2009): 232–35. http://dx.doi.org/10.4028/www.scientific.net/amr.60-61.232.
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This paper presents a kind of fine polishing technique that adopts three-step polishing procedure and keeping-wafer-wet method. In order to remove the damaged layer created by lapping process or improve surface condition of silicon wafer, polishing process is needed. In this paper, techniques of improving the surface roughness of silicon are studied, three different polishing processes are presented, and optimum condition has been attained. Experiments of Si-Si bonding are also performed, and results show that after polishing ends, keeping surface of wafer wet is necessary to avoid slurry agglomerating.
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Sabudin, Sulastri, Iu Ching Lie, and Eddy Ezwan Mohamad. "Multi-Cutting Passes for a Fine-Cut Wire Electro Discharge Machining of Stainless Steel." Advanced Materials Research 418-420 (December 2011): 1288–93. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.1288.
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Work piece surfaces produced by wire EDM can exhibit surface alterations resulting from rapid heating and quenching during machining. The thermally altered layers have tremendous impacts on mechanical properties of machined product. Multi-cutting passes of brass wire into stainless steel sheet SS304 has been suggested in this paper. Three holes was machined at one cutting passes, two cutting passes and three cutting passes respectively and the effect on surface roughness of machined steel was investigated. Visual micro-structure study has been done to explore the existence of white layer and Heat Affected Zone (HAZ) layer. Based upon experimental result, the surface roughness is decreased with the increment of cutting passes. The white layer only formed at first cutting part and did not appear at two and three cutting passes.
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Szász, Cs. "Three-dimensional artificial organism model developed upon a two-layer coarse-fine-grid network approach." International Review of Applied Sciences and Engineering 8, no. 2 (2017): 127–33. http://dx.doi.org/10.1556/1848.2017.8.2.4.
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In an attempt to devise a model which more closely imitates cellular biology a three-dimensional (3D) artificial organism model developed upon a two-layer coarse-fine-grid network model is proposed in this paper. The strength of this original approach is that it endeavors to capture the complexity of both the cellular networks as well as that of the biological cell itself, by implementing the internal biological phenomena of an organism into a 3D two different network topology hardware layer. In essence, this model not only keeps the full advantages of previously created 2D models that enable the implementation of similar self-replicating or selfrepairing abilities akin to those expressed by its cellular equivalents in nature, but there the inherent need of artificial cell structures to fulfill the entire role of a biological cell in the network is also expressed. Computer-aided simulation results prove that this kind of 3D coarse-fine-grid approach is well feasible physically therefore the model has been implemented into a computing platform made of custom reconfigurable Field Programmable Gate Array (FPGA) processors.
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Yudin, Yu V., A. A. Kuklina, M. V. Maisuradze, and M. S. Karabanalov. "Visualization of the Bainite Fine Structure Using EBSD and Euler Angles." KnE Engineering 1, no. 1 (2019): 11. http://dx.doi.org/10.18502/keg.v1i1.4385.
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The electron backscatter diffraction method (EBSD) is widely used to studycrystallographic orientational relationships of the steel microstructure constituentsincluding bainite. Nevertheless the fine structure of bainite (subunits, plates) is notinvestigated by this method. In this paper we propose a technique for visualizing ofthe structure of a bainitic steel near-surface layer using the values of Euler anglesobtained by EBSD method. A three-dimensional picture of the bainite fine structure ofthe HY-TUF steel obtained by the proposed technique is in
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Buican, George Răzvan, Gheorghe Oancea, Camil Lancea, and Mihai Alin Pop. "Some Considerations Regarding Micro Hardness of Parts Manufactured from 316-L Steel Using SLM Technology." Applied Mechanics and Materials 760 (May 2015): 515–20. http://dx.doi.org/10.4028/www.scientific.net/amm.760.515.
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In this paper is investigated the effect of building parts with different layer sizes using an additive manufacturing technique, from the statistical point of view. The paper is focused on the differences that appear at the stainless steel parts when the building layer is increased, this being done on the SLM 250 HL machine. This machine uses a fiber laser to melt fine powder on a layer-by-layer basis to create three-dimensional metallic parts from CAD files. The samples were constructed using two different layer thicknesses and then reprocess so that a micro hardness test could be employed. The micro hardness’s are compared using statistical methods. Overall, the obtained results indicate that the outcome influences the manufacturing strategy that it is chosen.
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Wani, M. Arif, and Saduf Afzal. "Optimization of deep network models through fine tuning." International Journal of Intelligent Computing and Cybernetics 11, no. 3 (2018): 386–403. http://dx.doi.org/10.1108/ijicc-06-2017-0070.
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Purpose Many strategies have been put forward for training deep network models, however, stacking of several layers of non-linearities typically results in poor propagation of gradients and activations. The purpose of this paper is to explore the use of two steps strategy where initial deep learning model is obtained first by unsupervised learning and then optimizing the initial deep learning model by fine tuning. A number of fine tuning algorithms are explored in this work for optimizing deep learning models. This includes proposing a new algorithm where Backpropagation with adaptive gain algorithm is integrated with Dropout technique and the authors evaluate its performance in the fine tuning of the pretrained deep network. Design/methodology/approach The parameters of deep neural networks are first learnt using greedy layer-wise unsupervised pretraining. The proposed technique is then used to perform supervised fine tuning of the deep neural network model. Extensive experimental study is performed to evaluate the performance of the proposed fine tuning technique on three benchmark data sets: USPS, Gisette and MNIST. The authors have tested the approach on varying size data sets which include randomly chosen training samples of size 20, 50, 70 and 100 percent from the original data set. Findings Through extensive experimental study, it is concluded that the two steps strategy and the proposed fine tuning technique significantly yield promising results in optimization of deep network models. Originality/value This paper proposes employing several algorithms for fine tuning of deep network model. A new approach that integrates adaptive gain Backpropagation (BP) algorithm with Dropout technique is proposed for fine tuning of deep networks. Evaluation and comparison of various algorithms proposed for fine tuning on three benchmark data sets is presented in the paper.
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Dai, Jin Jin, Xiang Min Li, and Zi Fen Li. "Target Identification Method for Single-Ship Air-Defense Based on Kinematics Characteristics." Advanced Materials Research 546-547 (July 2012): 559–64. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.559.
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In this paper, a target identification method is proposed based on kinematics characteristics for single-ship air-defense. After seriously analyzing the characteristics of modern air strike targets, extracting methods of the features of height, velocity, acceleration, detection distance, continuous radial motion etc. is given. Then, three-layer identification structure is established: layer 1 can identify tactical ballistic missile (TBM) and armed helicopter (AH) according to height, velocity; layer 2 can identify anti-radiation missile (ARM) and precision guided bomb (PGB) according to the features of horizontal continuous decelerated motion and continuous radial motion; layer 3 combines Fuzzy set and DS evidence theory to identify anti-ship missile (ASM) and bomb-attacker (BA) according to the features of height and detection distance. Verified by environment of typical targets, this method proposed in this paper has fine effect of identification.
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Stöpel, D., K. H. Drüe, S. Humbla, et al. "Fine-Line Structuring of Microwave Components on LTCC Substrates." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2012, CICMT (2012): 000607–12. http://dx.doi.org/10.4071/cicmt-2012-tha32.
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Low temperature co-fired ceramics (LTCC) are used in a wide range of RF and microwave applications. The ceramic multilayer technology provides a truly three-dimensional circuit technology, hermetical sealing, hybrid integration, and favorable microwave properties at moderate costs. In order to take full advantage of millimeter wave frequencies, resolutions of lines and spaces below the typical, screen printable 50 μm are desired. This paper describes the technological development of a fine-line structuring process based on resinate thin films and electroplating on LTCC. A combination of thin-film technology and thick-film technology leads to a novel resinate technology. This new process replaces the commonly used expensive sputtered layers, usually required for thin-film structuring combined with standard LTCC technology. The initial layer is replaced by a screen-printed metallo-organic paste (resinate paste). Resinate pastes consist of metallo-organic noble metal compounds (e.g. gold and silver), which are dissolved in organic suspensions. The film thickness after firing is typically below 1 μm. This layer can be used to define structures with high precision using photolithography and electroplating followed by an etching process. The etching processes investigated here showed promising resolutions of 25 μm for lines and spaces. But wet-chemical processes can be applied to sintered LTCC surfaces only. Buried fine structures may be achieved with tape-on-substrate (ToS) technology which allows for laminating and subsequent sintering of structured greensheets onto sintered ceramics. The benefits of this technology for microwave applications are obvious, given an improved resolution and parameter spread, and an accordingly reduced variation of the resulting structures.
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Guo, Chang Qing. "Fabrication & Microstructure of TiB2+TiC Duplex Particulates Reinforced Carbon Steel Matrix Surface Composite." Key Engineering Materials 575-576 (September 2013): 198–202. http://dx.doi.org/10.4028/www.scientific.net/kem.575-576.198.
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This paper presents a novel fabrication process that combines SHS with V-EPC (vacuum expandable pattern casting) and microstructural features of TiB2+TiC duplex particulates reinforced surface composite with carbon steel matrix. Macro structural observation shows that the surface composite is dense and there are no obvious defects. Microstructural investigation demonstrates that the composite from surface to core is consisted of three different layers, i.e., the top surface compound layer, the interim transitional layer and the bottom carbon steel matrix. A large amount of fine TiB2 and TiC duplex particles are evenly distributed in the composite matrix, while the concentration are significantly decreased and non-uniform distribution increased for these particles in the interim layer.
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Wu, Ziteng, Chengyun Song, Yunqing Chen, and Lingxuan Li. "A review of recommendation system research based on bipartite graph." MATEC Web of Conferences 336 (2021): 05010. http://dx.doi.org/10.1051/matecconf/202133605010.
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The interaction history between users and items is usually stored and displayed in the form of bipartite graphs. Neural network recommendation based on the user-item bipartite graph has a significant effect on alleviating the long-standing data sparseness and cold start of the recommendation system. The whole paper is based on the bipartite graph. An review of the recommendation system of graphs summarizes the three characteristics of graph neural network processing bipartite graph data in the recommendation field: interchangeability, Multi-hop transportability, and strong interpretability. The biggest contribution of the full paper is that it summarizes the general framework of graph neural network processing bipartite graph recommendation from the models with the best recommendation effect in the past three years: embedding layer, propagation update layer, and prediction layer. Although there are subtle differences between different models, they are all this framework can be applied, and different models can be regarded as variants of this general model, that is, other models are fine-tuned on the basis of this framework. At the end of the paper, the latest research progress is introduced, and the main challenges and research priorities that will be faced in the future are pointed out.
Dissertations / Theses on the topic "Three-layer fine paper"
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Mattison, Mariell. "Influence of hardwood, softwoodand fractionated pulp in a stratifiedthree-layered fine paper : Lövved, barrved och fraktionerad massa ochdess inverkan på ett treskiktat finpapper." Thesis, Högskolan Dalarna, Grafisk teknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:du-2389.
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Four different trials of stratified three-layered fine paper, of sulphate pulp, were performed to investigate if stratified fine fraction or fibres from birch can improve the properties of a paper compared to a reference sheet. All trials had five different scenarios and each scenario was calendered with different linear load. All sheets had a grammage of 80 g/m2.In the first trial, the paper contained birch, pine and filler of calciumcarbonate (marble), and was manufactured with the pilot paper machine XPM and the stratified headbox Formator at RCF (Stora Enso Research Center in Falun). The furnish consisted of 75% birch and 25% pine.The second trial contained coated sheets with paper from trial one as the base paper. The coating slip contained calciumcarbonate and clay and the amount was approximately 10-12 g/m2.The third trial, also with birch and pine but without filler, was performed at STFI (Skogsindustrins Tekniska Forskningsinstitut in Stockholm) with the laboratory scaled paper machine StratEx and the stratified headbox AQ-vanes. The furnish consisted of 75% birch and 25% pine, except for one scenario which contained of 75% pine and 25% birch.The last trial contained fractionated pulp of birch and pine and was performed at STFI. 50% was fine fraction and 50% was coarse fraction.This test does not show any clear benefits of making stratified sheets of birch and pine when it comes to properties such as bending stiffness, tensile index and surface smoothness. The retention can be improved with birch in the surface plies. It is possible that the formation can be improved with birch in the surface plies and pine in the middle ply. It is also possible that fine fraction in the surface plies and coarse fraction in the middle ply can improve both surface smoothness and bending stiffness. The results in this test are shown with confidence intervals which points out the difficulties of analysing sheets manufactured with a pilot paper machine or a laboratory scaled paper machine.
Book chapters on the topic "Three-layer fine paper"
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Chiu, Dickson K. W., Shing-Chi Cheung, Sven Till, Lalita Narupiyakul, and Patrick C. K. Hung. "Enhancing E-Service Collaboration with Enforcement and Relationship Management." In Electronic Services. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-967-5.ch015.
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In a business-to-business (B2B) e-service environment, cross-organizational collaboration is important for attaining the interoperability of business processes and their proper enactment. The authors find that B2B collaboration can be divided into multiple layers and perspectives, which has not been adequately addressed in the literature. Besides regular e-service process enactment, robust collaboration requires enforcement, while quality collaboration involves relationship management. These problems are challenging, as they require the enactment of business processes and their monitoring in counter parties outside an organization’s boundary. This paper presents a framework for B2B process collaboration with three layers, namely, collaboration requirements layer, business rule layer, and system implementation layer. The collaboration requirements layer specifies the cross-organizational requirements of e-service processes. In the business rule layer, detailed knowledge of these three types of process collaboration requirements is defined as business rules in a unified Event-Condition-Action (ECA) form. In the system implementation layer, event collaboration interfaces are supported by contemporary Enterprise JavaBeans and Web Services. Based on this architecture, a methodology is presented for the engineering of e-service process collaboration from high-level business requirements down to system implementation details. As a result, B2B process collaboration can be seamlessly defined, enacted, and enforced. Conceptual models of various layers are given in the Unified Modeling Language (UML). We illustrate the applicability of our framework with a running example based on a supply-chain process and evaluate our approach from the perspective of three main stakeholders of e-collaboration, namely users, management, and systems developers.
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Mitev, Tihomir. "Where Is the Missing Matter?" In 3D Printing. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1677-4.ch007.
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The additive manufacturing (or the popular 3D printing) is relatively new technology which opens new spaces for entrepreneurial imagination and promises next stage of the industrial revolution. It is creating three dimensional solid objects from a digital file. The printer transforms the file into a material object layer by layer, using different raw materials. Today, the additive manufacturing is successfully used in architecture, medicine and healthcare, light and heavy industries, education, etc. The paper analyses the roles of actors in manufacturing the objects. It starts with the Heideggerian questioning of technology (), searching for the causes of bringing into appearance of the 3D model. According to Heideggerian analysis the technology is represented as an ‘unveiling of the truth'. The paper suggests that the old understanding of matter as a thing-in-itself should be replaced by a new, flexible, fluid, concept of matter, which is more or less manipulable. The matter is no more an occasion for object's taking place. On the other hand, it seems 3D printing technology is reduced to mere means; a simple intermediary, a copier of ideas. From that perspective the paper questioning the problem of action in ANT and search how action and interaction is distributed and how actors constitutes themselves as well as their actor-world.
Conference papers on the topic "Three-layer fine paper"
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Barcellos, William, Nicolas Hiroaki Shitara, Carolina Toledo Ferraz, Raissa Tavares Vieira Queiroga, Jose Hiroki Saito, and Adilson Gonzaga. "Evaluation of Fine Tuning and Feature Extraction methods in Biometric Periocular Recognition." In XV Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/wvc.2019.7626.
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The aim of this paper is to evaluate the performance of Transfer Learning techniques applied in Convolucional Neural Networks for biometric periocular classification. Two aspects of Transfer Learning were evaluated: the technique known as Fine Tuning and the technique known as Feature Extraction. Two CNN architectures were evaluated, the AlexNet and the VGG-16, and two image databases were used. These two databases have different characteristics regarding the method of acquisition, the amount of classes, the class balancing, and the number of elements in each class. Three experiments were conducted to evaluate the performance of the CNNs. In the first experiment we measured the Feature Extraction accuracy, and in the second one we evaluated the Fine Tuning performance. In the third experiment, we used the AlexNet for Fine Tuning in one database, and then, the FC7 layer of this trained CNN was used for Feature Extraction in the other database. We concluded that the data quality (the presence or not of class samples in the training set), class imbalance (different number of elements in each class) and the selection method of the training and testing, directly influence the CNN accuracy. The Feature Extraction method, by being more simple and does not require network training, has lower accuracy than Fine Tuning. Furthermore, Fine Tuning a CNN with periocular's images from one database, doesn't increase the accuracy of this CNN in Feature Extraction mode for another periocular's database. The accuracy is quite similar to that obtained by the original pre-trained network
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Nakahira, Kohta, Hironori Tago, Fumiaki Endo, Ken Suzuki, and Hideo Miura. "Minimization of the Local Residual Stress in 3D Flip Chip Structures by Optimizing the Mechanical Properties of Electroplated Materials and the Alignment Structure of TSVs and Fine Bumps." In ASME 2011 Pacific Rim Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Systems. ASMEDC, 2011. http://dx.doi.org/10.1115/ipack2011-52063.
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Since the thickness of the stacked silicon chips in 3D integration has been thinned to less than 100 μm, the local thermal deformation of the chips has increased drastically because of the decrease of the flexural rigidity of the thinned chips. The clear periodic thermal deformation and thus, the thermal residual stress distribution appears in the stacked chips due to the periodic alignment of metallic bumps, and they deteriorate the reliability of products. In this paper, the dominant structural factors of the local residual stress in a silicon chip are discussed quantitatively based on the results of a three-dimensional finite element analysis and the measurement of the local residual stress in a chip using stress sensor chips. The piezoresistive strain gauges were embedded in the sensor chips. The length of each gauge was 2 μm, and an unit cell consisted of 4 gauges with different crystallographic directions. This alignment of strain gauges enables to measure the tensor component of three-dimensional stress fields separately. Test flip chip substrates were made by silicon chip on which the area-arrayed tin/copper bumps were electroplated. The width of a bump was fixed at 200 μm, and the bump pitch was varied from 400 μm to 1000 μm. The thickness of the copper layer was about 40 μm and that of tin layer was about 10 μm. This tin layer was used for the rigid joint formation by alloying with copper interconnection formed on a stress sensing chip. The measured amplitude of the residual stress increased from about 30 MPa to 250 MPa depending on the combination of materials such as bump, underfill, and interconnections. It was confirmed that both the material constant of underfill and the alignment structure of fine bumps are the dominant factors of the local deformation and stress of a silicon chip mounted on area-arrayed metallic bumps. It was also confirmed experimentally that both the hound’s-tooth alignment between a TSV (Through Silicon Via) and a bump and control of mechanical properties of electroplated copper thin films used for the TSV and bump is indispensable in order to minimize the packaging-induced stress in the three-dimensionally mounted chips. This test chip is very effective for evaluating the packaging-process induced stress in 3D stacked chips quantitatively.
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Schulz, U., K. Fritscher, C. Leyens, and M. Peters. "Influence of Processing on Microstructure and Performance of EB-PVD Thermal Barrier Coatings." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0579.
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The paper addresses the effect of processing parameters on microstructure and lifetime of EB-PVD PYSZ coatings deposited onto NiCoCrAlY-coated Ni-base superalloys. In particular, the formation of a thermally grown oxide layer, an equiaxed zone, and various columnar arrangements of the highly textured PYSZ layers are discussed with respect to processing conditions. Three different microstructures were cyclically tested at 1100°C. The intermediate columnar structure was superior with respect to cyclic life times to a fine and to a coarse columnar structure which was mainly attributed to differences in the elastic properties. The effect of PYSZ microstructure on hot corrosion behavior of the TBC system at 950°C is briefly discussed.
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Zhu, Zihao, Jing Yu, Yujing Wang, Yajing Sun, Yue Hu, and Qi Wu. "Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/153.
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Fact-based Visual Question Answering (FVQA) requires external knowledge beyond the visible content to answer questions about an image. This ability is challenging but indispensable to achieve general VQA. One limitation of existing FVQA solutions is that they jointly embed all kinds of information without fine-grained selection, which introduces unexpected noises for reasoning the final answer. How to capture the question-oriented and information-complementary evidence remains a key challenge to solve the problem. In this paper, we depict an image by a multi-modal heterogeneous graph, which contains multiple layers of information corresponding to the visual, semantic and factual features. On top of the multi-layer graph representations, we propose a modality-aware heterogeneous graph convolutional network to capture evidence from different layers that is most relevant to the given question. Specifically, the intra-modal graph convolution selects evidence from each modality and cross-modal graph convolution aggregates relevant information across different graph layers. By stacking this process multiple times, our model performs iterative reasoning across three modalities and predicts the optimal answer by analyzing all question-oriented evidence. We achieve a new state-of-the-art performance on the FVQA task and demonstrate the effectiveness and interpretability of our model with extensive experiments.
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Pieringer, Paul, and Wolfgang Sanz. "A Pressure Gradient Sensitive Wall Function for the Prediction of Turbulent Flow in Thermal Turbomachinery." In ASME Turbo Expo 2005: Power for Land, Sea, and Air. ASMEDC, 2005. http://dx.doi.org/10.1115/gt2005-68471.
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The economical design of thermal turbine stages of high efficiency requires very fast CFD tools of high accuracy. Since efficiency is mainly determined by secondary flow, a major focus in CFD is laid on boundary layer treatment. By resolving the boundary layer using a fine grid, usually the best results can be achieved, but at cost of computational time and memory. Wherever resolving the boundary layer is unacceptable, wall functions are used for simulating the flow close to solid walls. This paper describes a novel wall function approach for the prediction of three-dimensional turbulent boundary layer flows. The model is designed especially for the application to thermal turbomachinery in order to properly predict accelerated, decelerated and separated boundary layers at transonic conditions. The model is based on the law-of-the-wall expression by Spalding and also considers the shear-stress distribution perpendicular to the wall surface, which is mainly determined by pressure gradients. To cope with the boundary conditions, this wall function model uses phantom (ghost) cells, that must be located within the boundary layer, so there is a clearance between the first calculation cell and the wall. This allows an improved grid resolution for wall function approaches. To verify the accuracy of the model, results are shown for turbomachinery vane test cases at both steady state and time-resolved flow conditions.
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Hirsch, Ch, S. Kang, and G. Pointel. "A Numerically Supported Investigation of the 3D Flow in Centrifugal Impellers: Part I — The Validation Base." In ASME 1996 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-gt-151.
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The three-dimensional flow in centrifugal impellers is investigated on the basis of a detailed analysis of the results of numerical simulations. In order to gain confidence in this process, an in-depth validation is performed, based on computations of Krain’s centrifugal compressor and of a radial pump impeller, both with vaneless diffusers. Detailed comparisons with available experimental data provide high confidence in the numerical tools and results. The appearance of a high loss ‘wake’ region results from the transport of boundary layer material from the blade surfaces to the shroud region and its location depends on the balance between secondary and tip leakage flows and is not necessarily connected to 3D boundary layer separation. Although the low momentum spots near the shroud can interfere with 3D separated regions, the main outcome of the present analysis is that these are two distinct phenomena. Part I of this paper focuses on the validation base of the numerical approach, based on fine mesh simulations, while Part II presents an analysis of the different contributions to the secondary flows and attempts to estimate their effect on the overall flow pattern.
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Haldeman, Charles W., and Michael G. Dunn. "Heat Transfer Measurements and Predictions for the Vane and Blade of a Rotating High-Pressure Turbine Stage." In ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/gt2003-38726.
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This paper describes heat-transfer measurements and predictions obtained for the vane and blade of a rotating high-pressure turbine stage. The measurements were obtained with the stage operating at design corrected conditions. A previous paper described the aerodynamics and the blade midspan location heat-transfer data and compared these experimental results with predictions. The intent of the current paper is to concentrate on the measurements and predictions for the 20%, 50%, and 80% span locations on the vane, the vane inner and outer endwall, the 20% and 96% span location on the blade, the blade tip (flat tip), and the stationary blade shroud. Heat-transfer data obtained at midspan for three different TBC coated vanes (fine, medium and coarse) are also presented. Boundary-layer heat transfer predictions at the off-midspan locations are compared with the measurements for both the vane and the blade. The results of a STAR-CD 3D prediction are compared with the 20% and 96% span results for the blade surface. Predictions are not available for comparison with the tip and shroud experimental results.
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Pelevic´, Nikola R., and Theo H. van der Meer. "Numerical Modeling of New Heat Exchanger Materials." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22360.
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Heat transfer enhancement of carbon-nano fibers (CNF’s) attached on a wall surface within a micro-channel is investigated in this paper using a three-dimensional numerical method. Carbon-nanofibers, also known as graphite nanofibers, can be grown by catalytic decomposition of certain hydrocarbon at a metal surface such as iron, cobalt, nickel and some of their alloys. Typical sizes of CNF’s vary between 2 and 100 nm, with lengths ranging from 5 to 100 μm. Experimental research has shown that the presence of carbon-nano fibers grown on a surface of a fine metallic structure can enhance heat transfer by 50% [2]. These fibers influence the fluid flow, and enlarge the heat exchanging surface. The enhancement depends very much on the carbon-nano fibers density and on the structure of the carbon-nano fibers itself. This numerical study is giving directions in optimizing this new material. A random generation growth model has been developed to generate a stochastic structure of the CNF layer. Next to this a 3D Lattice Boltzmann model has been developed to simulate the heat transfer in a micro-channel flow with the surface covered with CNF’s. The 3D Lattice Boltzmann model has been verified on microchannel flow with heat transfer. Results of the conjugate heat transfer (including CNF’s at the wall) will be presented. The influence of carbon-nano fibers density and their structure on the heat transfer coefficient through the carbon-nano fibers layer is determined.
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Mishra, Debakanta, Huseyin Boler, Erol Tutumluer, and James P. Hyslip. "Effectiveness of Chemical Grouting and Stone Blowing as Remedial Measures to Mitigate Differential Movement at Railroad Track Transitions." In 2016 Joint Rail Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/jrc2016-5805.
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Railway transitions like bridge approaches experience differential movements related to differences in track system stiffness, track damping characteristics, foundation type, ballast settlement from fouling and/or degradation, as well as fill and subgrade settlement. A recent research study at the University of Illinois has used advanced geotechnical instrumentation to identify and quantify different factors contributing to recurrent differential movement problems at three different bridge approaches along Amtrak’s Northeast Corridor (NEC) near Chester, Pennsylvania. Field instrumentation data have indicated excessive ballast movement to be the primary factor contributing to the “bump” development at these bridge approaches. Among the different remedial measures applied to mitigate the recurrent track geometry issues were: (1) Chemical Grouting, (2) Stone Blowing, and (3) Under-Tie Pads. This paper will discuss the implementation methods using track geometry records and instrumentation data, and highlight the effectiveness of chemical grouting and stone blowing to mitigate the differential movement problem at railroad bridge approaches. According to the trends in the transient ballast deformation data collected under train loading, both remedial measures were effective in significantly reducing excessive ballast deformation, which was the primary mechanism behind the bump development at these locations. Ballast degradation and presence of excessive fine particles in the ballast layer adversely affected the ability of the grout to bond with aggregate particles. A “clean” ballast layer, on the other hand, facilitated adequate bonding between the grout and ballast particles leading to significantly improved long-term track performance.
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Lall, Pradeep, Madhu Kasturi, Haotian Wu, Ed Davis, and Jeff Suhling. "Correlation of Microstructural Evolution With the Dynamic-Mechanical Viscoelastic Properties of Underfill Under Sustained High Temperature Operation." In ASME 2020 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ipack2020-2675.
Full textAbstract:
Abstract Automotive underhood electronics are subjected to high operating temperatures in the neighborhood of 150 to 200°C for prolonged periods in the neighborhood of 10-years. Consumer grade off-the shelf electronics are designed to operate at 55 to 85 °C with a lower use-life of 3 to 5 years. Underfill materials are used to provide supplemental restraint to fine-pitch area array electronics and meet the reliability requirements. In this paper, a number of different underfill materials are subjected to automotive underhood temperatures to study the effect of long time isothermal exposure on microstructure and dynamic-mechanical properties. It has been shown that isothermal aging oxidizes the underfill, which can change the mechanical properties of the material significantly. The oxidation of underfill was studied experimentally by measuring oxidation layer thickness using polarized optical microscope. The effect on the mechanical properties was studied using the dynamic mechanical properties of underfill with DMA (Dynamic Mechanical Analyzer). Two different underfill materials were subjected to three different isothermal exposure, which are below, near and above the glass transition temperature of the underfills. The dynamic mechanical viscoelastic properties like storage modulus, loss modulus, tan delta and their respective glass transition temperatures were investigated. Three point bending mode was used in the DMA with a frequency of 1 Hz operating at 3 °C/min.