Yuanping Song

Polytope Sector-Based Synthesis and Analysis of Microstructural Architectures With Tunable Thermal Conductivity and Expansion

The aim of this paper is to (1) introduce an approach, called polytope sector-based synthesis (PSS), for synthesizing 2D or 3D microstructural architectures that exhibit a desired bulk-property directionality (e.g., isotropic, cubic, orthotropic, etc.), and (2) provide general analytical methods that can be used to rapidly optimize the geometric parameters of these architectures such that they achieve a desired combination of bulk thermal conductivity and thermal expansion properties. Although the methods introduced can be applied to general beam-based microstructural architectures, we demonstrate their utility in the context of an architecture that can be tuned to achieve a large range of extreme thermal expansion coefficients—positive, zero, and negative. The material-property-combination region that can be achieved by this architecture is determined within an Ashby-material-property plot of thermal expansion versus thermal conductivity using the analytical methods introduced. These methods are verified using finite-element analysis (FEA) and both 2D and 3D versions of the design have been fabricated using projection microstereolithography.

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

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.

Erratum to “A High-Speed Large-Range Tip-Tilt-Piston Micromirror Array” [Feb 17 196-205]

In the above paper [1] , there was an error in the first footnote regarding author contribution. The corrected author contribution information is as follows: (Jonathan B. Hopkins and Robert M. Panas are co-first authors.)

Optimal Actuation of Dynamically Driven Serial and Hybrid Flexure Systems

In this paper, we introduce the principles necessary to guide designers in determining the optimal number and placement of actuators for driving the stage of a general serial or hybrid flexure system at any desired speed. Although the degrees of freedom (DOFs) of a flexure system are largely determined by the location and orientation of its flexure elements, the system’s stage will tend to displace in unwanted directions (i.e., parasitic errors) while attempting to traverse its intended DOFs if it is not actuated correctly. The problem of correctly placing actuators is difficult because the optimal location changes depending on the speed with which the stage is driven. Moreover the issue of correctly actuating the stage of a serial or hybrid flexure system is substantially more complicated than actuating the stage of a parallel system because serial and hybrid systems possess multiple rigid bodies, which greatly enhance the system’s dynamic complexity, and provide a host of alternative options for actuating the system with its intended DOFs. In this paper we review the principles of static and dynamic actuation space and provide the mathematics necessary to apply these spaces to serial and hybrid systems such that designers can rapidly visualize all the ways actuators can be placed to correctly drive any combination of the system’s rigid body constituents such that the system’s stage achieves the desired DOFs with minimal parasitic error at any speed.Copyright