Angle- and azimuth-domain common-image gathers by reverse time migration for 3D elastic isotropic media

A 2D algorithm for angle-domain common-image gather (CIG) calculation is extended and modified to produce 3D elastic angle and azimuth CIGs. The elastic seismic data are propagated with the elastic particle displacement wave equation, and then the PP-reflected and PS-converted waves are separated by divergence and curl calculations during application of the excitation-time imaging condition. The incident angles and azimuths are calculated using source propagation directions and the reflector normals. The source propagation direction vector is computed as the spatial gradient of the incident 3C P-wavefield. The vector normal to the reflector is calculated using the Hilbert transform. Ordering the migrated images with respect to incident angles for a fixed azimuth bin, or with respect to azimuths for a fixed incident angle bin, creates angle- or azimuth-domain CIGs, respectively. Sorting the azimuth gathers by the incident angle bins causes a shift to a greater depth for too-high migration velocity and to a smaller depth for too-low migration velocity. For the sorted incident angle gathers, the velocity-dependent depth moveout is within the angle gathers and across the azimuth gathers. This method is compared with three other 3D CIG algorithms with respect to the number of calculations and their disk storage and RAM requirements; it is three to six orders of magnitude faster and requires two to three orders of magnitude less disk space. The method is successfully tested with data for a modified part of the SEG/EAGE overthrust model.

A Heuristic Elastic Particle Swarm Optimization Algorithm for Robot Path Planning

Path planning, as the core of navigation control for mobile robots, has become the focus of research in the field of mobile robots. Various path planning algorithms have been recently proposed. In this paper, in view of the advantages and disadvantages of different path planning algorithms, a heuristic elastic particle swarm algorithm is proposed. Using the path planned by the A* algorithm in a large-scale grid for global guidance, the elastic particle swarm optimization algorithm uses a shrinking operation to determine the globally optimal path formed by locally optimal nodes so that the particles can converge to it rapidly. Furthermore, in the iterative process, the diversity of the particles is ensured by a rebound operation. Computer simulation and real experimental results show that the proposed algorithm not only overcomes the shortcomings of the A* algorithm, which cannot yield the shortest path, but also avoids the problem of failure to converge to the globally optimal path, owing to a lack of heuristic information. Additionally, the proposed algorithm maintains the simplicity and high efficiency of both the algorithms.

An ellipsoidal cap model for adhesion of a soft particle on a rigid substrate

Surface energy outside the contact zone, which is not accounted for in the classical Johnson–Kendall–Roberts (JKR) model, can play an essential role in adhesion mechanics of soft particles. An open problem in the adhesion mechanics of soft elastic particles is how to achieve an explicit expression for the surface energy outside the contact zone in terms of the two JKR-type variables ( a, δ), where a is the radius of the contact zone and δ is the relative approach of two bodies. The present work aims to develop an ellipsoidal cap model for the surface energy outside the contact zone of a soft elastic particle on a rigid substrate in terms of the two JKR-type variables ( a, δ). An explicit expression for the surface energy outside the contact zone is derived, and simple asymptotic equations are obtained to determine the two unknowns ( a, δ). The validity and accuracy of the derived expression and asymptotic equations are verified by good agreement with the Young–Dupre equation in the absence of an external applied force, and are also justified by good agreement of the predicted pull-off force with known results available in recent literature.

Elastic particle deformation in rectangular channel flow as a measure of particle stiffness

Experimental deformation of hydrogel soft particles in a confined channel is quantified and can be used to obtain shear modulus.