A New Resonance-Based Method for the Measurement of Nonmagnetic-Conducting-Sheet Thickness

2011 ◽  
Vol 60 (12) ◽  
pp. 3892-3897 ◽  
Author(s):  
K. Suresh ◽  
G. Uma ◽  
M. Umapathy
Keyword(s):  
Sheet Thickness ◽  
Conducting Sheet

DETERMINATION OF LIGHT SHEET THICKNESS IN PIV

1995 ◽  
Vol 2 (3) ◽  
pp. 259-266 ◽  
Author(s):  
Mahmoud F. Maghrebi ◽  
Kiyosi Kawanisi ◽  
Shoitiro Yokosi
Keyword(s):  
Sheet Thickness ◽  
Light Sheet

scholarly journals Effect of Tool Geometry Parameters on the Formability of a Camera Cover in the Deep Drawing Process

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 3993
Author(s):  
Thanh Trung Do ◽  
Pham Son Minh ◽  
Nhan Le
Keyword(s):  
Deep Drawing ◽  
Thickness Distribution ◽  
Metal Flow ◽  
Sheet Thickness ◽  
Side Wall ◽  
Tool Geometry ◽  
Drawing Process ◽  
Nose Radius ◽  
Deep Drawing Process

The formability of the drawn part in the deep drawing process depends not only on the material properties, but also on the equipment used, metal flow control and tool parameters. The most common defects can be the thickening, stretching and splitting. However, the optimization of tools including the die and punch parameters leads to a reduction of the defects and improves the quality of the products. In this paper, the formability of the camera cover by aluminum alloy A1050 in the deep drawing process was examined relating to the tool geometry parameters based on numerical and experimental analyses. The results showed that the thickness was the smallest and the stress was the highest at one of the bottom corners where the biaxial stretching was the predominant mode of deformation. The problems of the thickening at the flange area, the stretching at the side wall and the splitting at the bottom corners could be prevented when the tool parameters were optimized that related to the thickness and stress. It was clear that the optimal thickness distribution of the camera cover was obtained by the design of tools with the best values—with the die edge radius 10 times, the pocket radius on the bottom of the die 5 times, and the punch nose radius 2.5 times the sheet thickness. Additionally, the quality of the camera cover was improved with a maximum thinning of 25% experimentally, and it was within the suggested maximum allowable thickness reduction of 45% for various industrial applications after optimizing the tool geometry parameters in the deep drawing process.

scholarly journals Attention Multi-Scale Network for Automatic Layer Extraction of Ice Radar Topological Sequences

2021 ◽  
Vol 13 (12) ◽  
pp. 2425
Author(s):  
Yiheng Cai ◽  
Dan Liu ◽  
Jin Xie ◽  
Jingxian Yang ◽  
Xiangbin Cui ◽  
...  
Keyword(s):  
Deep Learning ◽  
Global Climate ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Sheet Thickness ◽  
Learning Methods ◽  
Convolutional Network ◽  
Multi Scale ◽  
Ice Surface ◽  
Layer Extraction

Analyzing the surface and bedrock locations in radar imagery enables the computation of ice sheet thickness, which is important for the study of ice sheets, their volume and how they may contribute to global climate change. However, the traditional handcrafted methods cannot quickly provide quantitative, objective and reliable extraction of information from radargrams. Most traditional handcrafted methods, designed to detect ice-surface and ice-bed layers from ice sheet radargrams, require complex human involvement and are difficult to apply to large datasets, while deep learning methods can obtain better results in a generalized way. In this study, an end-to-end multi-scale attention network (MsANet) is proposed to realize the estimation and reconstruction of layers in sequences of ice sheet radar tomographic images. First, we use an improved 3D convolutional network, C3D-M, whose first full connection layer is replaced by a convolution unit to better maintain the spatial relativity of ice layer features, as the backbone. Then, an adjustable multi-scale module uses different scale filters to learn scale information to enhance the feature extraction capabilities of the network. Finally, an attention module extended to 3D space removes a redundant bottleneck unit to better fuse and refine ice layer features. Radar sequential images collected by the Center of Remote Sensing of Ice Sheets in 2014 are used as training and testing data. Compared with state-of-the-art deep learning methods, the MsANet shows a 10% reduction (2.14 pixels) on the measurement of average mean absolute column-wise error for detecting the ice-surface and ice-bottom layers, runs faster and uses approximately 12 million fewer parameters.

scholarly journals Effect of Structural Differences on the Mechanical Properties of 3D Integrated Woven Spacer Sandwich Composites

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4284
Author(s):  
Lvtao Zhu ◽  
Mahfuz Bin Rahman ◽  
Zhenxing Wang
Keyword(s):  
Mechanical Properties ◽  
Composite Materials ◽  
Three Dimensional ◽  
Sheet Thickness ◽  
Physical And Mechanical Properties ◽  
Sandwich Composites ◽  
Computed Tomography Images ◽  
And Performance ◽  
Industrial Textiles ◽  
Load Conditions

Three-dimensional integrated woven spacer sandwich composites have been widely used as industrial textiles for many applications due to their superior physical and mechanical properties. In this research, 3D integrated woven spacer sandwich composites of five different specifications were produced, and the mechanical properties and performance were investigated under different load conditions. XR-CT (X-ray computed tomography) images were employed to visualize the microstructural details and analyze the fracture morphologies of fractured specimens under different load conditions. In addition, the effects of warp and weft direction, face sheet thickness, and core pile height on the mechanical properties and performance of the composite materials were analyzed. This investigation can provide significant guidance to help determine the structure of composite materials and design new products according to the required mechanical properties.

Characterization of the vibration, stability and static responses of graphene-reinforced sandwich plates under mechanical and thermal loadings using the refined shear deformation plate theory

2021 ◽  
pp. 109963622199386
Author(s):  
Hessameddin Yaghoobi ◽  
Farid Taheri
Keyword(s):  
Shear Deformation ◽  
Volume Fraction ◽  
Plate Theory ◽  
Micromechanical Model ◽  
Sheet Thickness ◽  
Analytical Investigation ◽  
Sandwich Plates ◽  
Simply Supported ◽  
Vibration Stability ◽  
Shear Deformation Plate Theory

An analytical investigation was carried out to assess the free vibration, buckling and deformation responses of simply-supported sandwich plates. The plates constructed with graphene-reinforced polymer composite (GRPC) face sheets and are subjected to mechanical and thermal loadings while being simply-supported or resting on different types of elastic foundation. The temperature-dependent material properties of the face sheets are estimated by employing the modified Halpin-Tsai micromechanical model. The governing differential equations of the system are established based on the refined shear deformation plate theory and solved analytically using the Navier method. The validation of the formulation is carried out through comparisons of the calculated natural frequencies, thermal buckling capacities and maximum deflections of the sandwich plates with those evaluated by the available solutions in the literature. Numerical case studies are considered to examine the influences of the core to face sheet thickness ratio, temperature variation, Winkler- and Pasternak-types foundation, as well as the volume fraction of graphene on the response of the plates. It will be explicitly demonstrated that the vibration, stability and deflection responses of the sandwich plates become significantly affected by the aforementioned parameters.

scholarly journals Light attenuation in a semitransparent foam sheet—Thickness measurement for industrial use

1996 ◽  
Vol 24 (4) ◽  
pp. 339-350 ◽  
Author(s):  
Masahiro Ueda ◽  
Sanae Mizuno ◽  
Akio Matsumura ◽  
Fumio Tohjyo
Keyword(s):  
Light Attenuation ◽  
Sheet Thickness ◽  
Thickness Measurement ◽  
Industrial Use

Current sheet thickness of the outer boundary of the magnetosphere as observed by four CLUSTER satellites

2007 ◽  
Vol 45 (3) ◽  
pp. 268-272 ◽  
Author(s):  
E. V. Panov ◽  
S. P. Savin ◽  
J. Büchner ◽  
A. Korth
Keyword(s):  
Current Sheet ◽  
Outer Boundary ◽  
Sheet Thickness

A thin conducting sheet (TCS) model in 3D FDTD : Implementation and validation

2008 ◽  
Author(s):  
Toufic Abboud ◽  
Francois Bereux ◽  
Jean-Loup Lhermitte ◽  
Pierre Benjamin ◽  
Richard Perraud ◽  
...  
Keyword(s):  
Thin Conducting ◽  
Conducting Sheet
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