Reduction Method
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2022 ◽  
Vol 253 ◽  
pp. 113740
Author(s):  
Isabel González-de-León ◽  
Itsaso Arrayago ◽  
Esther Real ◽  
Enrique Mirambell

Geophysics ◽  
2022 ◽  
pp. 1-85
Author(s):  
Peng Lin ◽  
Suping Peng ◽  
Xiaoqin Cui ◽  
Wenfeng Du ◽  
Chuangjian Li

Seismic diffractions encoding subsurface small-scale geologic structures have great potential for high-resolution imaging of subwavelength information. Diffraction separation from the dominant reflected wavefields still plays a vital role because of the weak energy characteristics of the diffractions. Traditional rank-reduction methods based on the low-rank assumption of reflection events have been commonly used for diffraction separation. However, these methods using truncated singular-value decomposition (TSVD) suffer from the problem of reflection-rank selection by singular-value spectrum analysis, especially for complicated seismic data. In addition, the separation problem for the tangent wavefields of reflections and diffractions is challenging. To alleviate these limitations, we propose an effective diffraction separation strategy using an improved optimal rank-reduction method to remove the dependence on the reflection rank and improve the quality of separation results. The improved rank-reduction method adaptively determines the optimal singular values from the input signals by directly solving an optimization problem that minimizes the Frobenius-norm difference between the estimated and exact reflections instead of the TSVD operation. This improved method can effectively overcome the problem of reflection-rank estimation in the global and local rank-reduction methods and adjusts to the diversity and complexity of seismic data. The adaptive data-driven algorithms show good performance in terms of the trade-off between high-quality diffraction separation and reflection suppression for the optimal rank-reduction operation. Applications of the proposed strategy to synthetic and field examples demonstrate the superiority of diffraction separation in detecting and revealing subsurface small-scale geologic discontinuities and inhomogeneities.


Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 132
Author(s):  
Tsung-Chih Lin ◽  
Chien-Wen Sun ◽  
Yu-Chen Lin ◽  
Majid Moradi Zirkohi

In this paper, an intelligent control scheme is proposed to suppress vibrations between the pantograph and the catenary by regulating the contact force to a reference value, thereby achieving stable current collection. In order to reduce the computational cost, an interval Type-2 adaptive fuzzy logic control with the Moradi–Zirhohi–Lin type reduction method is applied to deal with model uncertainties and exterior interference. Based on a simplified pantograph–catenary system model, the comparative simulation results show that variation of the contact force can be attenuated and variation disturbances can be repressed simultaneously. Furthermore, in terms of computational burden, the proposed type reduction method outperforms other type reduction methods.


Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 266
Author(s):  
Won-Sang Jeong ◽  
Yoon-Seong Lee ◽  
Jung-Hyo Lee ◽  
Chang-Hee Lee ◽  
Chung-Yuen Won

This paper proposes a space vector modulation (SVM)-based common-mode (CM) currents reduction method of an H8 inverter for permanent magnet synchronous motor (PMSM) drives. There are power quality issues in the PMSM drive systems, such as current distortions and CM electromagnetic interference (EMI) due to the fast-switching operation of the inverter. These issues are related to CM voltage (CMV) and CM current (CMC). Although several studies have been conducted to reduce the CMV and CMC, some CMV variations and CMCs are still generated in the real implementation. Unlike conventional methods, the proposed method selects the voltage vectors with similar CMV levels and arranges them considering the series-connected switch operation of the H8 inverter in a voltage vector modulation sequence. At a low modulation index (MI), the proposed method completely restricts the CMV variations into six times. At high MI, the proposed method synthesizes the reference voltage vector differently, depending on the position of the reference vector, to reduce both current distortions and CMCs. The validity of the proposed method is verified through simulations and experimental results.


Author(s):  
Zhengtao Guo ◽  
Wuli Chu

It is essential for engineering manufacture and robust design to evaluate the impact of manufacturing variability on the aerodynamics of compressor blades efficiently and accurately. In the paper, a novel quadratic curve approximation method based on the scanning points of blade design profiles was introduced and combined with Karhunen–Loève expansion, a mathematical dimensionality reduction method for modeling manufacturing variability as truncated Normal process was proposed. Subsequently, Sparse Approximation of Moment-based Arbitrary Polynomial Chaos (SAMBA PC) and computational fluid dynamics (CFD) were applied to build a computational framework for stochastic aerodynamic analysis considering manufacturing variability. Finally, the framework was adopted to evaluate the aerodynamic variations of a high subsonic compressor cascade under the design incidence. The results illustrate that the SAMBA PC method is more efficient than the traditional methods such as Monte Carlo simulation (MCS) for stochastic aerodynamic analysis. Through uncertainty quantification, the impact of manufacturing variability on the global aerodynamic performance is primarily reflected in the fluctuation of aerodynamic losses, and the fluctuation of the total losses is mainly contributed by the fluctuation of the separation loss after the suction peak (a negative pressure spike near the leading edge (LE)) and the boundary-layer loss on the suction surface (SS). With sensitivity analysis, the most important geometric modes to aerodynamics can be revealed, which provides a useful reference for manufacturing inspection process and helps reduce computational cost in robust design.


2021 ◽  
Author(s):  
Katarzyna Gas ◽  
Maciej Sawicki

Steadily growing interest in magnetic characterization of organic compounds aiming at therapeutic purposes, or of other irregular-shaped specimens calls for refinements of experimental methodology to satisfy experimental challenges. Encapsulation in capsules remains the method of choice, but its applicability in precise magnetometry is limited. This is particularly true for minute specimens in single mg range since they are outweighed by the capsules and due to large alignment errors. We present here a complete new experimental methodology which permits 30-fold in situ reduction of the signal of capsules. In practical terms it means that the standard 30 mg capsule is seen by the magnetometer as about 1 mg object, effectively opening the window for precise magnetometry of single mg specimens. The method is shown to work down to 1.8 K and in the whole range of the magnetic fields. The method is demonstrated and validated using the reciprocal space option of MPMS-SQUID magnetometers, however it can be easily incorporated in any magnetometer which can accommodate straw sample holders (i.e. the VSM-SQUID). Importantly, the improved sensitivity is accomplished relying only on the standard accessories and data reduction method provided by the SQUID manufacturer, eliminating needs for an elaborate raw data manipulations.


Author(s):  
Jian-guo Wang ◽  
Qiang Zhou ◽  
Zijiang Zhao ◽  
Zihao Yao ◽  
Zhongzhe Wei ◽  
...  

Modulation of the metal-support interaction plays a key role in many important chemical reactions. Here, by adjusting the reduction method of the catalyst and introducing oxygen vacancies in TiO2 to...


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