Modeling and analysis methodology for aeroelastically tailored chordwise deformable wings

Structural concepts have been created which produce chordwise camber deformation that results in enhanced lift. A wing box can be tailored to utilize each of these with composites. In attempting to optimize the aerodynamic benefits, we have found there are two optimal designs that are of interest. There is a weight optimum which corresponds to the maximum lift per unit structural weight. There is also a lift optimum that corresponds to maximum absolute lift. New structural models, the basic deformation mechanisms that are utilized and typical analytical results are presented. It appears that lift enhancements of sufficient magnitude can be produced to render this type of wing tailoring of practical interest. Experiments and finite element correlations are performed which confirm the validity of the theoretical models utilized

Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids

Real-life control tasks involve matters of various substances---rigid or soft bodies, liquid, gas---each with distinct physical behaviors. This poses challenges to traditional rigid-body physics engines. Particle-based simulators have been developed to model the dynamics of these complex scenes; however, relying on approximation techniques, their simulation often deviates from real-world physics, especially in the long term. In this paper, we propose to learn a particle-based simulator for complex control tasks. Combining learning with particle-based systems brings in two major benefits: first, the learned simulator, just like other particle-based systems, acts widely on objects of different materials; second, the particle-based representation poses strong inductive bias for learning: particles of the same type have the same dynamics within. This enables the model to quickly adapt to new environments of unknown dynamics within a few observations. We demonstrate robots achieving complex manipulation tasks using the learned simulator, such as manipulating fluids and deformable foam, with experiments both in simulation and in the real world. Our study helps lay the foundation for robot learning of dynamic scenes with particle-based representations.Comment: Accepted to ICLR 2019. Project Page: http://dpi.csail.mit.edu Video: https://www.youtube.com/watch?v=FrPpP7aW3L

ShaneAO: wide science spectrum adaptive optics system for the Lick Observatory

A new high-order adaptive optics system is now being commissioned at the Lick Observatory Shane 3-meter telescope in California. This system uses a high return efficiency sodium beacon and a combination of low and high-order deformable mirrors to achieve diffraction-limited imaging over a wide spectrum of infrared science wavelengths covering 0.8 to 2.2 microns. We present the design performance goals and the first on-sky test results. We discuss several innovations that make this system a pathfinder for next generation AO systems. These include a unique woofer-tweeter control that provides full dynamic range correction from tip/tilt to 16 cycles, variable pupil sampling wavefront sensor, new enhanced silver coatings developed at UC Observatories that improve science and LGS throughput, and tight mechanical rigidity that enables a multi-hour diffraction- limited exposure in LGS mode for faint object spectroscopy science.Comment: 11 pages, 10 figures. Presented at SPIE Astronomical Telescopes + Instrumentation conference, paper 9148-7

Simulations of propelling and energy harvesting articulated bodies via vortex particle-mesh methods

The emergence and understanding of new design paradigms that exploit flow induced mechanical instabilities for propulsion or energy harvesting demands robust and accurate flow structure interaction numerical models. In this context, we develop a novel two dimensional algorithm that combines a Vortex Particle-Mesh (VPM) method and a Multi-Body System (MBS) solver for the simulation of passive and actuated structures in fluids. The hydrodynamic forces and torques are recovered through an innovative approach which crucially complements and extends the projection and penalization approach of Coquerelle et al. and Gazzola et al. The resulting method avoids time consuming computation of the stresses at the wall to recover the force distribution on the surface of complex deforming shapes. This feature distinguishes the proposed approach from other VPM formulations. The methodology was verified against a number of benchmark results ranging from the sedimentation of a 2D cylinder to a passive three segmented structure in the wake of a cylinder. We then showcase the capabilities of this method through the study of an energy harvesting structure where the stocking process is modeled by the use of damping elements

Controlling the Error on Target Motion through Real-time Mesh Adaptation: Applications to Deep Brain Stimulation

We present an error-controlled mesh refinement procedure for needle insertion simulation and apply it to the simulation of electrode implantation for deep brain stimulation, including brain shift. Our approach enables to control the error in the computation of the displacement and stress fields around the needle tip and needle shaft by suitably refining the mesh, whilst maintaining a coarser mesh in other parts of the domain. We demonstrate through academic and practical examples that our approach increases the accuracy of the displacement and stress fields around the needle without increasing the computational expense. This enables real-time simulations. The proposed methodology has direct implications to increase the accuracy and control the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anesthesia, or cryotherapy and can be essential to the development of robotic guidance.Comment: 21 pages, 14 figure

Phase-field approaches to structural topology optimization

The mean compliance minimization in structural topology optimization is solved with the help of a phase field approach. Two steepest descent approaches based on L2- and H-1 gradient flow dynamics are discussed. The resulting flows are given by Allen-Cahn and Cahn-Hilliard type dynamics coupled to a linear elasticity system. We finally compare numerical results obtained from the two different approaches