scholarly journals Microstructure refinement-homogenization and flexural strength improvement of Al2O3 ceramics fabricated by DLP-stereolithography integrated with chemical precipitation coating process

2021 ◽  
Author(s):  
Guanglin Nie ◽  
Yehua Li ◽  
Pengfei Sheng ◽  
Fei Zuo ◽  
Haolin Wu ◽  
...  
Keyword(s):  
Flexural Strength ◽  
Chemical Precipitation ◽  
Heat Sinks ◽  
Coarse Grained ◽  
Homogeneous Layer ◽  
Mechanical Mixing ◽  
Fine Grained ◽  
Novel Approach ◽  
Ceramic Components ◽  
3D Printed

AbstractIn this study, the chemical precipitation coating (CP) process was creatively integrated with DLP-stereolithography based 3D printing for refining and homogenizing the microstructure of 3D printed Al2O3 ceramic. Based on this novel approach, Al2O3 powder was coated with a homogeneous layer of amorphous Y2O3, with the coated Al2O3 powder found to make the microstructure of 3D printed Al2O3 ceramic more uniform and refined, as compared with the conventional mechanical mixing (MM) of Al2O3 and Y2O3 powders. The grain size of Al2O3 in Sample CP is 64.44% and 51.43% lower than those in the monolithic Al2O3 ceramic and Sample MM, respectively. Sample CP has the highest flexural strength of 455.37±32.17 MPa, which is 14.85% and 25.45% higher than those of Samples MM and AL, respectively; also Sample CP has the highest Weibull modulus of 16.88 among the three kinds of samples. Moreover, the fine grained Sample CP has a close thermal conductivity to the coarse grained Sample MM because of the changes in morphology of Y3Al5O12 phase from semi-connected (Sample MM) to isolated (Sample CP). Finally, specially designed fin-type Al2O3 ceramic heat sinks were successfully fabricated via the novel integrated process, which has been proven to be an effective method for fabricating complex-shaped Al2O3 ceramic components with enhanced flexural strength and reliability.

scholarly journals Microstructure refinement - homogenization and flexural strength improvement of Al2O3 ceramics fabricated by DLP-stereolithography integrated with chemical precipitation coating process

2020 ◽  
Author(s):  
Guanglin Nie ◽  
Yehua Li ◽  
Pengfei Sheng ◽  
Fei Zuo ◽  
Haolin Wu ◽  
...  
Keyword(s):  
Flexural Strength ◽  
Chemical Precipitation ◽  
Heat Sinks ◽  
Coarse Grained ◽  
Homogeneous Layer ◽  
Mechanical Mixing ◽  
Fine Grained ◽  
Novel Approach ◽  
Ceramic Components ◽  
3D Printed

Abstract In this study, the chemical precipitation coating (CP) process was creatively integrated with DLP-stereolithography based 3D printing for refining and homogenizing the microstructure of 3D printed Al2O3 ceramic. Based on this novel approach, Al2O3 powder was coated with a homogeneous layer of amorphous Y2O3; with the coated Al2O3 powder found to make the microstructure of 3D printed Al2O3 ceramic more uniform and refined, as compared with the conventional mechanical mixing (MM) of Al2O3 and Y2O3 powders. The grain size of Al2O3 in Sample CP is 64.44% and 51.43% lower than those in the monolithic Al2O3 ceramic (AL) and Sample MM, respectively. Sample CP has the highest flexural strength of 455.37±32.17 MPa, which is 14.85% and 25.45% higher than those of Samples MM and AL, respectively; also Sample CP has the highest Weibull modulus of 16.88 among the three kinds of samples. Moreover, the fine grained Sample CP has a close thermal conductivity to the coarse grained Sample MM because of the changes in morphology of Y3Al5O12 phase from semi-connected (Sample MM) to isolated (Sample CP). Finally, specially designed fin-type Al2O3 ceramic heat sinks were successfully fabricated via the novel integrated process, which has been proven to be an effective method for fabricating complex-shaped Al2O3 ceramic components with enhanced flexural strength and reliability.

scholarly journals Flexural Strength of Ice on Temperate Lakes

1977 ◽  
Vol 19 (81) ◽  
pp. 247-256 ◽  
Author(s):  
Anthony J. Gow
Keyword(s):  
Stress Concentration ◽  
Thermal Degradation ◽  
Flexural Strength ◽  
Coarse Grained ◽  
Cantilever Beams ◽  
Lake Ice ◽  
Simply Supported ◽  
Fine Grained ◽  
Stress Concentration Effect ◽  
Structural Imperfections

AbstractLarge, simply supported beams of temperate lake ice generally yield significantly higher f1exural strengths than the same beams tested in the cantilever mode. Data support the view that a significant stress concentration may exist at the fixed corners of the cantilever beams. Maximum effects are experienced with beams of cold, brittle ice substantially free of structural imperfections; the stress concentration factor may exceed 2.0 in this kind of ice. In ice that has undergone extensive thermal degradation the stress concentration effect may be eliminated entirely. Simply supported beams generally test stronger when the top surface is placed in tension. This behavior is attributed to differences in ice type; the fine-grained, crack-free top layer of snow-ice usually reacting more strongly in tension than the coarse-grained bottom lake ice which is prone to cracking.

Correlation between dislocation, grain boundary and interface of duplex SS in stress corrosion cracking(SCC)

1990 ◽  
Vol 48 (4) ◽  
pp. 928-929
Author(s):  
Wang Zheng-fang ◽  
Z.F. Wang
Keyword(s):  
Stainless Steel ◽  
Thermal Cycle ◽  
Secondary Phase ◽  
Corrosion Cracking ◽  
Coarse Grained ◽  
Test Environment ◽  
Fine Grained ◽  
Evaluation Test ◽  
Welding Thermal Cycle ◽  
Micro Analysis

The main purpose of this study highlights on the evaluation of chloride SCC resistance of the material,duplex stainless steel,OOCr18Ni5Mo3Si2 (18-5Mo) and its welded coarse grained zone(CGZ).18-5Mo is a dual phases (A+F) stainless steel with yield strength:512N/mm2 .The proportion of secondary Phase(A phase) accounts for 30-35% of the total with fine grained and homogeneously distributed A and F phases(Fig.1).After being welded by a specific welding thermal cycle to the material,i.e. Tmax=1350°C and t8/5=20s,microstructure may change from fine grained morphology to coarse grained morphology and from homogeneously distributed of A phase to a concentration of A phase(Fig.2).Meanwhile,the proportion of A phase reduced from 35% to 5-10°o.For this reason it is known as welded coarse grained zone(CGZ).In association with difference of microstructure between base metal and welded CGZ,so chloride SCC resistance also differ from each other.Test procedures:Constant load tensile test(CLTT) were performed for recording Esce-t curve by which corrosion cracking growth can be described, tf,fractured time,can also be recorded by the test which is taken as a electrochemical behavior and mechanical property for SCC resistance evaluation. Test environment:143°C boiling 42%MgCl2 solution is used.Besides, micro analysis were conducted with light microscopy(LM),SEM,TEM,and Auger energy spectrum(AES) so as to reveal the correlation between the data generated by the CLTT results and micro analysis.

A NOVEL APPROACH TO TURBULENT MULTIPHASE FLOW IMAGING: FLOW IN 3D PRINTED KARSTIC CONDUITS

2016 ◽  
Author(s):  
Samuel N. Jacobson ◽  
◽  
Ellen K. Herman ◽  
Dorothy J. Vesper ◽  
Johnathan E. Moore ◽  
...  
Keyword(s):  
Multiphase Flow ◽  
Flow Imaging ◽  
Novel Approach ◽  
3D Printed

scholarly journals A Novel Approach for a Faster Prototyping of Winter Sport Equipment Using Digital Image Correlation and 3D Printing

Proceedings ◽  
2020 ◽  
Vol 49 (1) ◽  
pp. 125
Author(s):  
Martino Colonna ◽  
Benno Zingerle ◽  
Maria Federica Parisi ◽  
Claudio Gioia ◽  
Alessandro Speranzoni ◽  
...  
Keyword(s):  
3D Printing ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Sport Activity ◽  
Image Correlation ◽  
Topological Optimization ◽  
Design Parameters ◽  
Sport Equipment ◽  
Novel Approach ◽  
3D Printed

The optimization of sport equipment parts requires considerable time and high costs due to the high complexity of the development process. For this reason, we have developed a novel approach to decrease the cost and time for the optimization of the design, which consists of producing a first prototype by 3D printing, applying the forces that normally acts during the sport activity using a test bench, and then measuring the local deformations using 3D digital image correlation (DIC). The design parameters are then modified by topological optimization and then DIC is performed again on the new 3D-printed modified part. The DIC analysis of 3D-printed parts has shown a good agreement with that of the injection-molded ones. The deformation measured with DIC are also well correlated with those provided by finite element method (FEM) analysis, and therefore DIC analysis proves to be a powerful tool to validate FEM models.

scholarly journals Explaining Neural Networks Using Attentive Knowledge Distillation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1280
Author(s):  
Hyeonseok Lee ◽  
Sungchan Kim
Keyword(s):  
Neural Networks ◽  
Model Prediction ◽  
Saliency Map ◽  
Model Parameters ◽  
Learning Capability ◽  
Fine Grained ◽  
Network Layers ◽  
Saliency Maps ◽  
Novel Approach ◽  
Knowledge Distillation

Explaining the prediction of deep neural networks makes the networks more understandable and trusted, leading to their use in various mission critical tasks. Recent progress in the learning capability of networks has primarily been due to the enormous number of model parameters, so that it is usually hard to interpret their operations, as opposed to classical white-box models. For this purpose, generating saliency maps is a popular approach to identify the important input features used for the model prediction. Existing explanation methods typically only use the output of the last convolution layer of the model to generate a saliency map, lacking the information included in intermediate layers. Thus, the corresponding explanations are coarse and result in limited accuracy. Although the accuracy can be improved by iteratively developing a saliency map, this is too time-consuming and is thus impractical. To address these problems, we proposed a novel approach to explain the model prediction by developing an attentive surrogate network using the knowledge distillation. The surrogate network aims to generate a fine-grained saliency map corresponding to the model prediction using meaningful regional information presented over all network layers. Experiments demonstrated that the saliency maps are the result of spatially attentive features learned from the distillation. Thus, they are useful for fine-grained classification tasks. Moreover, the proposed method runs at the rate of 24.3 frames per second, which is much faster than the existing methods by orders of magnitude.

scholarly journals Balanced Sparsity for Efficient DNN Inference on GPU

2019 ◽  
Vol 33 ◽  
pp. 5676-5683 ◽  
Author(s):  
Zhuliang Yao ◽  
Shijie Cao ◽  
Wencong Xiao ◽  
Chen Zhang ◽  
Lanshun Nie
Keyword(s):  
Deep Neural Networks ◽  
General Purpose ◽  
Coarse Grained ◽  
Efficient Computation ◽  
Model Accuracy ◽  
Sparse Model ◽  
Model Inference ◽  
Fine Grained ◽  
Practical Inference ◽  
Speed Up

In trained deep neural networks, unstructured pruning can reduce redundant weights to lower storage cost. However, it requires the customization of hardwares to speed up practical inference. Another trend accelerates sparse model inference on general-purpose hardwares by adopting coarse-grained sparsity to prune or regularize consecutive weights for efficient computation. But this method often sacrifices model accuracy. In this paper, we propose a novel fine-grained sparsity approach, Balanced Sparsity, to achieve high model accuracy with commercial hardwares efficiently. Our approach adapts to high parallelism property of GPU, showing incredible potential for sparsity in the widely deployment of deep learning services. Experiment results show that Balanced Sparsity achieves up to 3.1x practical speedup for model inference on GPU, while retains the same high model accuracy as finegrained sparsity.

scholarly journals Submarine lava deltas of the 2018 eruption of Kīlauea volcano

2021 ◽  
Vol 83 (4) ◽  
Author(s):  
S. Adam Soule ◽  
Michael Zoeller ◽  
Carolyn Parcheta
Keyword(s):  
Grain Size ◽  
Pore Pressure ◽  
Mechanistic Model ◽  
Large Fraction ◽  
Volcanic Hazards ◽  
Lava Flows ◽  
Coarse Grained ◽  
Fine Grained ◽  
Fine Grain ◽  
Delta Formation

AbstractHawaiian and other ocean island lava flows that reach the coastline can deposit significant volumes of lava in submarine deltas. The catastrophic collapse of these deltas represents one of the most significant, but least predictable, volcanic hazards at ocean islands. The volume of lava deposited below sea level in delta-forming eruptions and the mechanisms of delta construction and destruction are rarely documented. Here, we report on bathymetric surveys and ROV observations following the Kīlauea 2018 eruption that, along with a comparison to the deltas formed at Pu‘u ‘Ō‘ō over the past decade, provide new insight into delta formation. Bathymetric differencing reveals that the 2018 deltas contain more than half of the total volume of lava erupted. In addition, we find that the 2018 deltas are comprised largely of coarse-grained volcanic breccias and intact lava flows, which contrast with those at Pu‘u ‘Ō‘ō that contain a large fraction of fine-grained hyaloclastite. We attribute this difference to less efficient fragmentation of the 2018 ‘a‘ā flows leading to fragmentation by collapse rather than hydrovolcanic explosion. We suggest a mechanistic model where the characteristic grain size influences the form and stability of the delta with fine grain size deltas (Pu‘u ‘Ō‘ō) experiencing larger landslides with greater run-out supported by increased pore pressure and with coarse grain size deltas (Kīlauea 2018) experiencing smaller landslides that quickly stop as the pore pressure rapidly dissipates. This difference, if validated for other lava deltas, would provide a means to assess potential delta stability in future eruptions.

scholarly journals A cooperative DDoS attack detection scheme based on entropy and ensemble learning in SDN

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Shanshan Yu ◽  
Jicheng Zhang ◽  
Ju Liu ◽  
Xiaoqing Zhang ◽  
Yafeng Li ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Denial Of Service ◽  
Attack Detection ◽  
Coarse Grained ◽  
Communication Overhead ◽  
Detection Scheme ◽  
Fine Grained ◽  
Ddos Attack ◽  
Network Status ◽  
Ddos Attack Detection

AbstractIn order to solve the problem of distributed denial of service (DDoS) attack detection in software-defined network, we proposed a cooperative DDoS attack detection scheme based on entropy and ensemble learning. This method sets up a coarse-grained preliminary detection module based on entropy in the edge switch to monitor the network status in real time and report to the controller if any abnormality is found. Simultaneously, a fine-grained precise attack detection module is designed in the controller, and a ensemble learning-based algorithm is utilized to further identify abnormal traffic accurately. In this framework, the idle computing capability of edge switches is fully utilized with the design idea of edge computing to offload part of the detection task from the control plane to the data plane innovatively. Simulation results of two common DDoS attack methods, ICMP and SYN, show that the system can effectively detect DDoS attacks and greatly reduce the southbound communication overhead and the burden of the controller as well as the detection delay of the attacks.

Rheology of hydrocarbon gels

1950 ◽  
Vol 200 (1061) ◽  
pp. 183-188 ◽  
Keyword(s):  
Mechanical Properties ◽  
Experimental Measurement ◽  
Theoretical Basis ◽  
Continuous Media ◽  
Point Of View ◽  
Coarse Grained ◽  
Testing Instrument ◽  
Fine Grained ◽  
Mineral Oils ◽  
Space And Time

Hydrocarbon gels contain a number of materials, such as rubber, greases, saponified mineral oils, etc., of great interest for various engineering purposes. Specific requirements in mechanical properties have been met by producing gels in appropriately chosen patterns of constituent components of visible, colloidal, molecular and atomic sizes, ranging from coarse-grained aggregates, represented by sponges, foams, emulsions, etc.; to fine-grained and apparently homogeneous ones, represented by optically clear compounds. The engineer who has to deal with the whole range of such materials will adopt a macroscopic point of view, based on an apparent continuity of all the material structures and of the distributions in space and time of the displacements and forces occurring under mechanical actions. It has been possible to determine these distributions in the framework of a comprehensive scheme in which the fundamental principles of the mechanics of continuous media provide the theoretical basis, and a testing instrument of new design, termed Rheogoniometer, the means of experimental measurement (Weissenberg 1931, 1934, 1946, 1947, 1948).

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