scholarly journals A Global Optimization Method to Determine the Complex Material Constants of Piezoelectric Bars in the Length Thickness Extensional Mode

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 169
Author(s):  
Xiangming Xiong ◽  
Xiaotian Li

Optimization methods have been used to determine the elastic, piezoelectric, and dielectric constants of piezoelectric materials from admittance or impedance measurements. The optimal material constants minimize the difference between the modeled and measured admittance or impedance spectra. In this paper, a global optimization method is proposed to calculate the optimal material constants of piezoelectric bars in the length thickness extensional mode. The algorithm is applied to a soft PZT and a hard PZT and is shown to be robust.

Author(s):  
Liqun Wang ◽  
Songqing Shan ◽  
G. Gary Wang

The presence of black-box functions in engineering design, which are usually computation-intensive, demands efficient global optimization methods. This work proposes a new global optimization method for black-box functions. The global optimization method is based on a novel mode-pursuing sampling (MPS) method which systematically generates more sample points in the neighborhood of the function mode while statistically covers the entire search space. Quadratic regression is performed to detect the region containing the global optimum. The sampling and detection process iterates until the global optimum is obtained. Through intensive testing, this method is found to be effective, efficient, robust, and applicable to both continuous and discontinuous functions. It supports simultaneous computation and applies to both unconstrained and constrained optimization problems. Because it does not call any existing global optimization tool, it can be used as a standalone global optimization method for inexpensive problems as well. Limitation of the method is also identified and discussed.


2021 ◽  
Vol 8 (1) ◽  
pp. 149-163
Author(s):  
Yu He ◽  
Guo-Dong Zhao ◽  
Song-Hai Zhang

AbstractStable label movement and smooth label trajectory are critical for effective information understanding. Sudden label changes cannot be avoided by whatever forced directed methods due to the unreliability of resultant force or global optimization methods due to the complex trade-off on the different aspects. To solve this problem, we proposed a hybrid optimization method by taking advantages of the merits of both approaches. We first detect the spatial-temporal intersection regions from whole trajectories of the features, and initialize the layout by optimization in decreasing order by the number of the involved features. The label movements between the spatial-temporal intersection regions are determined by force directed methods. To cope with some features with high speed relative to neighbors, we introduced a force from future, called temporal force, so that the labels of related features can elude ahead of time and retain smooth movements. We also proposed a strategy by optimizing the label layout to predict the trajectories of features so that such global optimization method can be applied to streaming data.


2007 ◽  
Vol 48 (3) ◽  
pp. 315-325 ◽  
Author(s):  
J. Ugon ◽  
S. Kouhbor ◽  
M. Mammadov ◽  
A. Rubinov ◽  
A. Kruger

AbstractFacility location problems are one of the most common applications of optimization methods. Continuous formulations are usually more accurate, but often result in complex problems that cannot be solved using traditional optimization methods. This paper examines theuse of a global optimization method—AGOP—for solving location problems where the objective function is discontinuous. This approach is motivated by a real-world application in wireless networks design.


2014 ◽  
Vol 14 (05) ◽  
pp. 1450065 ◽  
Author(s):  
FILIPA JOÃO ◽  
ANTÓNIO VELOSO ◽  
SANDRA AMADO ◽  
PAULO ARMADA-DA-SILVA ◽  
ANA C. MAURÍCIO

The motion of the skeletal estimated from skin attached marker-based motion capture(MOCAP) systems is known to be affected by significant bias caused by anatomical landmarks mislocation but especially by soft tissue artifacts (such as skin deformation and sliding, inertial effects and muscle contraction). As a consequence, the error associated with this bias can propagate to joint kinematics and kinetics data, particularly in small rodents. The purpose of this study was to perform a segmental kinematic analysis of the rat hindlimb during locomotion, using both global optimization as well as segmental optimization methods. Eight rats were evaluated for natural overground walking and motion of the right hindlimb was captured with an optoeletronic system while the animals walked in the track. Three-dimensional (3D) biomechanical analyses were carried out and hip, knee and ankle joint angular displacements and velocities were calculated. Comparison between both methods demonstrated that the magnitude of the kinematic error due to skin movement increases in the segmental optimization when compared with the global optimization method. The kinematic results assessed with the global optimization method matches more closely to the joint angles and ranges of motion calculated from bone-derived kinematics, being the knee and hip joints with more significant differences.


2015 ◽  
Vol 54 (3) ◽  
pp. 605-623 ◽  
Author(s):  
Anthony C. Didlake ◽  
Gerald M. Heymsfield ◽  
Lin Tian ◽  
Stephen R. Guimond

AbstractThe coplane analysis technique for mapping the three-dimensional wind field of precipitating systems is applied to the NASA High-Altitude Wind and Rain Airborne Profiler (HIWRAP). HIWRAP is a dual-frequency Doppler radar system with two downward-pointing and conically scanning beams. The coplane technique interpolates radar measurements onto a natural coordinate frame, directly solves for two wind components, and integrates the mass continuity equation to retrieve the unobserved third wind component. This technique is tested using a model simulation of a hurricane and compared with a global optimization retrieval. The coplane method produced lower errors for the cross-track and vertical wind components, while the global optimization method produced lower errors for the along-track wind component. Cross-track and vertical wind errors were dependent upon the accuracy of the estimated boundary condition winds near the surface and at nadir, which were derived by making certain assumptions about the vertical velocity field. The coplane technique was then applied successfully to HIWRAP observations of Hurricane Ingrid (2013). Unlike the global optimization method, the coplane analysis allows for a transparent connection between the radar observations and specific analysis results. With this ability, small-scale features can be analyzed more adequately and erroneous radar measurements can be identified more easily.


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