Inversion of Fault Geometric Parameters Based on Mixture Density Networks: A Case Study of the 2013 Ms7.0 Lushan Earthquake in China

2021 ◽  
Author(s):  
Lixuan Zhou ◽  
Caijun Xu
Keyword(s):  
Lushan Earthquake ◽  
Geometric Parameters ◽  
Mixture Density

scholarly journals Optimizing the Geometry of Flexure System Topologies Using the Boundary Learning Optimization Tool

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ali Hatamizadeh ◽  
Yuanping Song ◽  
Jonathan B. Hopkins
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Optimization Algorithm ◽  
Geometric Parameters ◽  
Average Error ◽  
Computational Tool ◽  
Model Training ◽  
Constraint Topologies ◽  
Synthesis Approach

We introduce a new computational tool called the Boundary Learning Optimization Tool (BLOT) that identifies the boundaries of the performance capabilities achieved by general flexure system topologies if their geometric parameters are allowed to vary from their smallest allowable feature sizes to their largest geometrically compatible feature sizes for given constituent materials. The boundaries generated by the BLOT fully define the design spaces of flexure systems and allow designers to visually identify which geometric versions of their synthesized topologies best achieve desired combinations of performance capabilities. The BLOT was created as a complementary tool to the freedom and constraint topologies (FACT) synthesis approach in that the BLOT is intended to optimize the geometry of the flexure topologies synthesized using the FACT approach. The BLOT trains artificial neural networks to create models of parameterized flexure topologies using numerically generated performance solutions from different design instantiations of those topologies. These models are then used by an optimization algorithm to plot the desired topology’s performance boundary. The model-training and boundary-plotting processes iterate using additional numerically generated solutions from each updated boundary generated until the final boundary is guaranteed to be accurate within any average error set by the user. A FACT-synthesized flexure topology is optimized using the BLOT as a simple case study.

Post-seismic allocation of medical staff in the Longmen Shan fault area: case study of the Lushan Earthquake

2015 ◽  
Vol 14 (4) ◽  
pp. 289-311 ◽  
Author(s):  
Jiuping Xu ◽  
Huaidong Xie ◽  
Jiuzhou Dai ◽  
Renqiao Rao
Keyword(s):  
Medical Staff ◽  
Lushan Earthquake ◽  
Longmen Shan Fault

scholarly journals Advanced 3D Photogrammetric Surface Reconstruction of Extensive Objects by UAV Camera Image Acquisition

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2815 ◽  
Author(s):  
Michele Calì ◽  
Rita Ambu
Keyword(s):  
Surface Reconstruction ◽  
Large Scale ◽  
Image Acquisition ◽  
Three Dimensional ◽  
Geometric Parameters ◽  
Reconstruction Accuracy ◽  
Camera Image ◽  
Aerial Vehicle ◽  
Euclidean Distances

This paper proposes a replicable methodology to enhance the accuracy of the photogrammetric reconstruction of large-scale objects based on the optimization of the procedures for Unmanned Aerial Vehicle (UAV) camera image acquisition. The relationships between the acquisition grid shapes, the acquisition grid geometric parameters (pitches, image rates, camera framing, flight heights), and the 3D photogrammetric surface reconstruction accuracy were studied. Ground Sampling Distance (GSD), the necessary number of photos to assure the desired overlapping, and the surface reconstruction accuracy were related to grid shapes, image rate, and camera framing at different flight heights. The established relationships allow to choose the best combination of grid shapes and acquisition grid geometric parameters to obtain the desired accuracy for the required GSD. This outcome was assessed by means of a case study related to the ancient arched brick Bridge of the Saracens in Adrano (Sicily, Italy). The reconstruction of the three-dimensional surfaces of this structure, obtained by the efficient Structure-From-Motion (SfM) algorithms of the commercial software Pix4Mapper, supported the study by validating it with experimental data. A comparison between the surface reconstruction with different acquisition grids at different flight heights and the measurements obtained with a 3D terrestrial laser and total station-theodolites allowed to evaluate the accuracy in terms of Euclidean distances.

scholarly journals A self-adjusting stiffness center design for large stroke compliant XY nanomanipulators

2018 ◽  
Vol 9 (1) ◽  
pp. 41-50 ◽  
Author(s):  
Zhiqing Liu ◽  
Zhen Zhang ◽  
Peng Yan
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Geometric Parameters ◽  
Rotational Stiffness ◽  
Element Analysis ◽  
Redundant Constraint ◽  
Alternative Approach ◽  
Motion Stage ◽  
The Moment

Abstract. In the present paper, it is proposed a self-adjusting stiffness center (SASC) design for large stroke XY beam flexure-based mechanisms. An important feature of the SASC lies in it restricts the in-plane parasitic rotation by reducing the moment of force instead of increasing the rotational stiffness widely utilized in the literature. Specifically, it is shown that by leveraging on the varied stiffness of the parallelogram flexure, the stiffness center can be made stationary by appropriately setting the relevant geometric parameters, so that the parasitic rotation can be restricted. Furthermore, it is presented a millimeter stroke XY nanomanipulator with the SASC-based redundant constraint in a case study. Numerous finite element analysis (FEA) results demonstrate that the proposed design is not only capable of achieving 1.5 × 1.5 mm2 working range in a compact desktop size, but significantly reduces the in-plane moment applied to the motion stage. The proposed SASC-based design provides an alternative approach to reduce the parasitic rotation of large stroke XY beam flexure-based mechanisms.

Systematic Sensitivity Analysis of Spatial One-DOF Models of Diarthrodial Joints

2005 ◽  
Author(s):  
R. Di Gregorio ◽  
V. Parenti-Castelli
Keyword(s):  
Geometric Parameters ◽  
Sensitivity Index ◽  
Anatomical Structures ◽  
Passive Motion ◽  
Influence Coefficients ◽  
Diarthrodial Joints ◽  
Equivalent Mechanism

The identification of an equivalent mechanism which may reproduce at best the relative passive motion of the main anatomical structures of a human articulation is a target of great importance in the study of diarthrodial joints. Passive motion, that is the motion of the joint under virtually unloaded condition, is of basic importance for understanding the role of elements like bones, ligaments, etc. The identification is based on measurements performed during in vitro experiments. Passive motion of a number of human diarthrodial joints may be reproduced by equivalent mechanisms. However, the most critical points when devising the equivalent mechanism are represented by the changes of the subject articulation geometry due to age, sex, body constitution, etc. Thus, the equivalent mechanism sensitivity to the variations of the geometric parameters needs a careful investigation. The passive motion of many diarthrodial joints can be modeled by an equivalent mechanism with one degree of freedom (dof). This paper shows how the sensitivity of a one-dof equivalent mechanism with a finite number of geometric parameters can be studied in a systematic way. A sensitivity index together with some coefficients, called influence coefficients, are proposed which enable measuring the sensitivity of a mechanism, thus allowing the comparison of different equivalent mechanisms from the sensitivity viewpoint. Finally, a case study shows the application of the proposed methodology.

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