An inverse method for the exploration of layered material appearance

The quantification of material appearance is important in product design. In particular, the sparkle impression of metallic paint used mainly for automobiles varies with the observation angle. Although several evaluation methods and multi-angle measurement devices have been proposed for the impression, it is necessary to add more light sources or cameras to the devices to increase the number of evaluation angles. The present study constructed a device that evaluates the multi-angle sparkle impression in one shot and developed a method for quantifying the impression. The device comprises a line spectral camera, light source, and motorized rotation stage. The quantification method is based on spatial frequency characteristics. It was confirmed that the evaluation value obtained from the image recorded by the constructed device correlates closely with a subjective score. Furthermore, the evaluation value is significantly correlated with that obtained using a commercially available evaluation device.

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Factors Influencing the Fatigue Behavior of Ferrous Laminates

Journal of Engineering Materials and Technology ◽

10.1115/1.3225971 ◽

1987 ◽

Vol 109 (3) ◽

pp. 244-251 ◽

Cited By ~ 13

Author(s):

J. Wittenauer ◽

O. D. Sherby

Keyword(s):

Fatigue Crack ◽

Fatigue Life ◽

Carbon Steel ◽

Fatigue Behavior ◽

Layered Material ◽

Factors Influencing ◽

Ultrahigh Carbon Steel ◽

Processing History ◽

Crack Blunting ◽

Similar Processing

Laminates based on ultrahigh carbon steel were prepared and found to exhibit enhanced fatigue life as compared to a monolithic reference material. This result was achieved through the insertion of weak interlaminar regions of copper into the layered material during preparation of the laminates. The presence of these regions allowed for the operation of a delamination mechanism in advance of the propagating fatigue crack. The result was interlaminar separation and associated crack blunting. Stress-life curves show that an increase in life by as much as a factor of four is achieved for these materials when compared to monolithic specimens of similar processing history.

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Solvothermal Preparation of Spherical Bi2O3 Nanoparticles Uniformly Distributed on Ti3C2Tx for Enhanced Capacitive Performance

Nanoscale Advances ◽

10.1039/d1na00443c ◽

2021 ◽

Author(s):

Tao Li ◽

Xuefeng Chang ◽

Lifang Mei ◽

Xiayun Shu ◽

Jidong Ma ◽

...

Keyword(s):

Electrical Conductivity ◽

Chemical Stability ◽

Layered Structure ◽

Layered Material ◽

Two Dimensional ◽

Capacitive Performance ◽

Solvothermal Preparation

Ti3C2Tx is a promising new two-dimensional layered material for supercapacitors with good electrical conductivity and chemical stability. However, Ti3C2Tx has problems such as collapse of the layered structure and low...

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Quantification of thermal energy generation in annular hyperbolic porous-finned heat sinks using inverse optimization

Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering ◽

10.1177/09544089211024387 ◽

2021 ◽

pp. 095440892110243

Author(s):

Sagnik Pal ◽

Ranjan Das

Keyword(s):

Heat Transfer ◽

Surface Temperature ◽

Heat Generation ◽

Thermal Energy ◽

Inverse Method ◽

Golden Section ◽

Energy Generation ◽

Heat Sinks ◽

Search Technique ◽

Golden Section Search

The present paper introduces an accurate numerical procedure to assess the internal thermal energy generation in an annular porous-finned heat sink from the sole assessment of surface temperature profile using the golden section search technique. All possible heat transfer modes and temperature dependence of all thermal parameters are accounted for in the present nonlinear model. At first, the direct problem is numerically solved using the Runge–Kutta method, whereas for predicting the prevailing heat generation within a given generalized fin domain an inverse method is used with the aid of the golden section search technique. After simplifications, the proposed scheme is credibly verified with other methodologies reported in the existing literature. Numerical predictions are performed under different levels of Gaussian noise from which accurate reconstructions are observed for measurement error up to 20%. The sensitivity study deciphers that the surface temperature field in itself is a strong function of the surface porosity, and the same is controlled through a joint trade-off among heat generation and other thermo-geometrical parameters. The present results acquired from the golden section search technique-assisted inverse method are proposed to be suitable for designing effective and robust porous fin heat sinks in order to deliver safe and enhanced heat transfer along with significant weight reduction with respect to the conventionally used systems. The present inverse estimation technique is proposed to be robust as it can be easily tailored to analyse all possible geometries manufactured from any material in a more accurate manner by taking into account all feasible heat transfer modes.

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Phase-to-pattern inverse design paradigm for fast realization of functional metasurfaces via transfer learning

Nature Communications ◽

10.1038/s41467-021-23087-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Ruichao Zhu ◽

Tianshuo Qiu ◽

Jiafu Wang ◽

Sai Sui ◽

Chenglong Hao ◽

...

Keyword(s):

Transfer Learning ◽

Electromagnetic Waves ◽

Inverse Method ◽

Inverse Design ◽

Learning Network ◽

Design Paradigm ◽

Simulation And Experiment ◽

Meta Atom ◽

Trained Network ◽

Input Phase

AbstractMetasurfaces have provided unprecedented freedom for manipulating electromagnetic waves. In metasurface design, massive meta-atoms have to be optimized to produce the desired phase profiles, which is time-consuming and sometimes prohibitive. In this paper, we propose a fast accurate inverse method of designing functional metasurfaces based on transfer learning, which can generate metasurface patterns monolithically from input phase profiles for specific functions. A transfer learning network based on GoogLeNet-Inception-V3 can predict the phases of 28×8 meta-atoms with an accuracy of around 90%. This method is validated via functional metasurface design using the trained network. Metasurface patterns are generated monolithically for achieving two typical functionals, 2D focusing and abnormal reflection. Both simulation and experiment verify the high design accuracy. This method provides an inverse design paradigm for fast functional metasurface design, and can be readily used to establish a meta-atom library with full phase span.

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