Estimation of noise radiation including airborne noise using the in-situ blocked force approach (Second report, verification of the estimation method by numerical analysis of noise radiation from a cantilever rectangular plate and proposal of an estimation error reduction method)

Highlights A facile method is adopted to obtain cucumber-like lithiophilic composite skeleton. Massive lithiophilic sites in cucumber-like lithiophilic composite skeleton can promote and guide uniform Li depositions. A unique model of stepwise Li deposition and stripping is determined. Abstract The uncontrolled formation of lithium (Li) dendrites and the unnecessary consumption of electrolyte during the Li plating/stripping process have been major obstacles in developing safe and stable Li metal batteries. Herein, we report a cucumber-like lithiophilic composite skeleton (CLCS) fabricated through a facile oxidation-immersion-reduction method. The stepwise Li deposition and stripping, determined using in situ Raman spectra during the galvanostatic Li charging/discharging process, promote the formation of a dendrite-free Li metal anode. Furthermore, numerous pyridinic N, pyrrolic N, and CuxN sites with excellent lithiophilicity work synergistically to distribute Li ions and suppress the formation of Li dendrites. Owing to these advantages, cells based on CLCS exhibit a high Coulombic efficiency of 97.3% for 700 cycles and an improved lifespan of 2000 h for symmetric cells. The full cells assembled with LiFePO4 (LFP), SeS2 cathodes and CLCS@Li anodes demonstrate high capacities of 110.1 mAh g−1 after 600 cycles at 0.2 A g−1 in CLCS@Li|LFP and 491.8 mAh g−1 after 500 cycles at 1 A g−1 in CLCS@Li|SeS2. The unique design of CLCS may accelerate the application of Li metal anodes in commercial Li metal batteries.

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Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

Remote Sensing ◽

10.3390/rs13101865 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1865

Author(s):

Gabriel Calassou ◽

Pierre-Yves Foucher ◽

Jean-François Léon

Keyword(s):

Matched Filter ◽

Estimation Method ◽

Optimal Estimation ◽

Model Parameters ◽

Surface Reflectance ◽

Sequential Method ◽

Modal Radius ◽

Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

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An Error-Reduction Method for Temporal Phase Unwrapping Based on Double Three-Step Phase-Shifting and Least-Squares Fitting

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.6-7.76 ◽

2012 ◽

Vol 6-7 ◽

pp. 76-81

Author(s):

Yong Liu ◽

Ding Fa Huang ◽

Yong Jiang

Keyword(s):

Least Squares ◽

Reduction Method ◽

Intermediate Phase ◽

Error Reduction ◽

Phase Unwrapping ◽

Phase Shifting ◽

Surface Measurement ◽

Acquisition Time ◽

Least Squares Fitting ◽

Temporal Phase

Phase-shifting interferometry on structured light projection is widely used in 3-D surface measurement. An investigation shows that least-squares fitting can significantly decrease random error by incorporating data from the intermediate phase values, but it cannot completely eliminate nonlinear error. This paper proposes an error-reduction method based on double three-step phase-shifting algorithm and least-squares fitting, and applies it on the temporal phase unwrapping algorithm using three-frequency heterodyne principle. Theoretical analyses and experiment results show that this method can greatly save data acquisition time and improve the precision.

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